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Electronics
Volume 8
Issue 7
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Electronics, Volume 8, Issue 7 (July 2019) – 100 articles

Cover Story (view full-size image): The vehicular ad hoc network (VANET) is one major aspect of intelligent transportation systems (ITSs). VANETs have been used to improve driver and passenger safety on roads and highways. Therefore, the improvement of road safety consciousness is desired in VANETs. Sporadic message transmission causes overutilization of RSU or CPU as a result of hybrid DoS attacks (HDSAs) encountered in the vulnerable environment of VANET deployment. Most existing methods that have been used do not provide vehicular fog computing (VFC), hybrid optimization algorithms (HOA), or key distribution establishment (KDE). However, these combined methods have the tendency to provide swarm intelligence and enough storage for the trustworthiness computation of safety messages. View this paper.
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10 pages, 1723 KiB  
Article
A Charge-Sharing-Based Two-Phase Charging Scheme for Zero-Crossing-Based Integrator Circuits
by Dong-Jick Min and Jae Hoon Shim
Electronics 2019, 8(7), 821; https://doi.org/10.3390/electronics8070821 - 23 Jul 2019
Cited by 6 | Viewed by 4822
Abstract
As an effort to improve the energy efficiency of switched-capacitor circuits, zero-crossing- based integrators (ZCBI) that consist of zero-crossing detectors and charging circuits have been proposed. To break the trade-off between accuracy and speed, ZCBI typically employs a two-phase charging scheme that relies [...] Read more.
As an effort to improve the energy efficiency of switched-capacitor circuits, zero-crossing- based integrators (ZCBI) that consist of zero-crossing detectors and charging circuits have been proposed. To break the trade-off between accuracy and speed, ZCBI typically employs a two-phase charging scheme that relies on an additional threshold for zero-crossing detection. This paper proposes a simpler realization method of the two-phase charging scheme by means of charge sharing. To demonstrate feasibility of the proposed method, we designed and fabricated a second-order delta-sigma modulator in 180-nm complementary metal–oxide–semiconductor (CMOS) technology. The measurement results show that the modulator exhibits a peak signal-to-noise-and-distortion ratio (SNDR) of 46.3 dB over the bandwidth of 156 kHz with the power consumption of 684 µW. We also designed the same modulator in 65-nm CMOS technology and simulation results imply that the proposed circuit is able to achieve a much better energy efficiency in advanced technology. Full article
(This article belongs to the Section Circuit and Signal Processing)
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<p>Conventional zero-crossing-based switched-capacitor circuit. (<b>a</b>) Schematic diagram. (<b>b</b>) Timing diagram.</p> Full article ">Figure 2
<p>Two-phase charging schemes. (<b>a</b>) Bidirectional. (<b>b</b>) Unidirectional.</p> Full article ">Figure 3
<p>A switched-capacitor circuit using an inverter-based zero-crossing-detectors (ZCD) [<a href="#B16-electronics-08-00821" class="html-bibr">16</a>].</p> Full article ">Figure 4
<p>The inverter-based zero-crossing-based integrators (ZCBI) using a dynamic buffer. (<b>a</b>) Schematic diagram. (<b>b</b>) Timing diagram.</p> Full article ">Figure 5
<p>The ZCBI employing the charge-sharing-based two-phase charging scheme. (<b>a</b>) Schematic diagram. (<b>b</b>) Normal operation. (<b>c</b>) Erroneous operation.</p> Full article ">Figure 6
<p>The structure of the designed second-order <math display="inline"><semantics> <mrow> <mo>Δ</mo> <mo>Σ</mo> </mrow> </semantics></math> modulator.</p> Full article ">Figure 7
<p>Schematic diagram of the modulator.</p> Full article ">Figure 8
<p>Chip micrograph. The core size is 650 µm × 460 µm.</p> Full article ">Figure 9
<p>Distribution of <math display="inline"><semantics> <msub> <mi>V</mi> <mrow> <mi mathvariant="normal">X</mi> <mo>|</mo> <mi>reset</mi> </mrow> </msub> </semantics></math>.</p> Full article ">Figure 10
<p>Test setup.</p> Full article ">Figure 11
<p>Measured results. (<b>a</b>) Power spectral density (# of fast Fourier transform (FFT) bins: 32768). (<b>b</b>) Signal-to-noise ratio (SNR) and signal-to-noise and distortion ratio (SNDR) versus input amplitudes.</p> Full article ">Figure 12
<p>Simulated SNR and SNDR over temperature.</p> Full article ">
15 pages, 7143 KiB  
Article
Evaluation of Direct Torque Control with a Constant-Frequency Torque Regulator under Various Discrete Interleaving Carriers
by Ibrahim Mohd Alsofyani and Kyo-Beum Lee
Electronics 2019, 8(7), 820; https://doi.org/10.3390/electronics8070820 - 23 Jul 2019
Cited by 9 | Viewed by 4398
Abstract
Constant-frequency torque regulator–based direct torque control (CFTR-DTC) provides an attractive and powerful control strategy for induction and permanent-magnet motors. However, this scheme has two major issues: A sector-flux droop at low speed and poor torque dynamic performance. To improve the performance of this [...] Read more.
Constant-frequency torque regulator–based direct torque control (CFTR-DTC) provides an attractive and powerful control strategy for induction and permanent-magnet motors. However, this scheme has two major issues: A sector-flux droop at low speed and poor torque dynamic performance. To improve the performance of this control method, interleaving triangular carriers are used to replace the single carrier in the CFTR controller to increase the duty voltage cycles and reduce the flux droop. However, this method causes an increase in the motor torque ripple. Hence, in this work, different discrete steps when generating the interleaving carriers in CFTR-DTC of an induction machine are compared. The comparison involves the investigation of the torque dynamic performance and torque and stator flux ripples. The effectiveness of the proposed CFTR-DTC with various discrete interleaving-carriers is validated through simulation and experimental results. Full article
(This article belongs to the Section Power Electronics)
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<p>Conventional structure of constant-frequency torque regulator–based direct torque control (CFTR-DTC). PI—proportional-integral regulator; IM—induction motor.</p> Full article ">Figure 2
<p>Conventional structure of CFTR-DTC.</p> Full article ">Figure 3
<p>Typical waveforms for the proposed strategy at low speed.</p> Full article ">Figure 4
<p>Simulation results of low-speed performance for CFTR-DTC with (<b>a</b>) single carrier and (<b>b</b>) interleaving carriers.</p> Full article ">Figure 4 Cont.
<p>Simulation results of low-speed performance for CFTR-DTC with (<b>a</b>) single carrier and (<b>b</b>) interleaving carriers.</p> Full article ">Figure 5
<p>Simulation results of dynamic torque performance for CFTR-DTC with (<b>a</b>) single carrier and (<b>b</b>) interleaving carriers.</p> Full article ">Figure 6
<p>Enlargement of simulation results shown in <a href="#electronics-08-00820-f005" class="html-fig">Figure 5</a> for CFTR-DTC with (<b>a</b>) single carrier and (<b>b</b>) interleaving carriers.</p> Full article ">Figure 7
<p>Simulation results of external load disturbance for the proposed CFTR-DTC with interleaving carriers at 30 rpm.</p> Full article ">Figure 8
<p>Experimental setup. DSP—digital signal processor.</p> Full article ">Figure 9
<p>Discrete implementation of the upper triangular carriers: (<b>a</b>) Interleaving CFTR-3, (<b>b</b>) interleaving CFTR-4, and (<b>c</b>) interleaving CFTR-5.</p> Full article ">Figure 10
<p>Experimental results of low-speed performance for CFTR-DTC with (<b>a</b>) single carrier and (<b>b</b>) interleaving carriers.</p> Full article ">Figure 11
<p>Experimental results of steady-state performance for (<b>a</b>) interleaving CFTR-3, (<b>b</b>) interleaving CFTR-4, and (<b>c</b>) interleaving CFTR-5.</p> Full article ">Figure 12
<p>Experimental results of steady-state performance for (<b>a</b>) conventional CFTR-DTC, (<b>b</b>) interleaving CFTR-3, (<b>c</b>) interleaving CFTR-4, and (<b>d</b>) interleaving CFTR-5.</p> Full article ">Figure 13
<p>Experimental results of external load disturbance for the proposed CFTR-DTC with interleaving carriers at 30 rpm.</p> Full article ">
21 pages, 1168 KiB  
Article
On Performance Analysis of Underlay Cognitive Radio-Aware Hybrid OMA/NOMA Networks with Imperfect CSI
by Dinh-Thuan Do, Anh-Tu Le and Byung Moo Lee
Electronics 2019, 8(7), 819; https://doi.org/10.3390/electronics8070819 - 22 Jul 2019
Cited by 56 | Viewed by 5700
Abstract
This study considers the outage and throughput performance of downlink in the secondary network of cognitive radio assisted non-orthogonal multiple access (NOMA) systems. Both orthogonal multiple access (OMA) mode and NOMA mode are investigated with respect to status of decoding operation of each [...] Read more.
This study considers the outage and throughput performance of downlink in the secondary network of cognitive radio assisted non-orthogonal multiple access (NOMA) systems. Both orthogonal multiple access (OMA) mode and NOMA mode are investigated with respect to status of decoding operation of each user. Depending on the transmit signal-to-noise ratio (SNR) at the primary source and interference constraint from the primary network, the closed-form expressions of the outage probability for two users are obtained and compared in terms of performance. To obtain further insights, an asymptotic analysis of the outage probability in the high SNR regime is presented. Optimal throughput also provides insight in the computation of the power allocation factor. Furthermore, power allocation factor, target rates, and transmit SNR are evaluated to obtain reasonable outage performance. Monte Carlo simulations are conducted to confirm the analytical results. Full article
(This article belongs to the Special Issue Cooperative Communications for Future Wireless Systems)
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<p>System model of cognitive radio(CR) and section scheme of OMA/non-orthogonal multiple access(NOMA).</p> Full article ">Figure 2
<p>Outage probability of <math display="inline"><semantics> <mrow> <mi>O</mi> <msub> <mi>P</mi> <msub> <mi>U</mi> <mn>2</mn> </msub> </msub> </mrow> </semantics></math> vs. SNR with varying <math display="inline"><semantics> <msub> <mi>R</mi> <mn>2</mn> </msub> </semantics></math>.</p> Full article ">Figure 3
<p>Outage probability of two users vs. SNR with a varying level of CSI imperfection <math display="inline"><semantics> <mi>σ</mi> </semantics></math> with <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>R</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>0</mn> <mo>.</mo> <mn>5</mn> <mrow> <mo>(</mo> <mi>B</mi> <mi>P</mi> <mi>C</mi> <mi>U</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p> Full article ">Figure 4
<p>Outage probability of <math display="inline"><semantics> <mrow> <mi>O</mi> <msub> <mi>P</mi> <msub> <mi>U</mi> <mn>2</mn> </msub> </msub> </mrow> </semantics></math> vs. distance <math display="inline"><semantics> <msub> <mi>d</mi> <mn>12</mn> </msub> </semantics></math> with varying <math display="inline"><semantics> <msub> <mover accent="true"> <mi>ρ</mi> <mo>¯</mo> </mover> <mi>S</mi> </msub> </semantics></math> with <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>.</p> Full article ">Figure 5
<p>Outage probability of two users vs. target rates with SNR = 10, 20 dB.</p> Full article ">Figure 6
<p>Throughput of user <math display="inline"><semantics> <msub> <mi>U</mi> <mn>2</mn> </msub> </semantics></math> vs. <math display="inline"><semantics> <mi>α</mi> </semantics></math>.</p> Full article ">Figure 7
<p>Throughput of <math display="inline"><semantics> <msub> <mi>U</mi> <mn>2</mn> </msub> </semantics></math> vs. the target rate <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>R</mi> <mn>2</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 8
<p>Throughput of system vs. the target rate <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>R</mi> <mn>2</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 9
<p>Outage probability of <math display="inline"><semantics> <msub> <mi>U</mi> <mn>1</mn> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>U</mi> <mn>1</mn> </msub> </semantics></math> vs. number of antenna <math display="inline"><semantics> <mrow> <mi>M</mi> <mo>=</mo> <mi>H</mi> </mrow> </semantics></math>.</p> Full article ">
21 pages, 3424 KiB  
Article
Choosing the Best Locomotion Mode in Reconfigurable Rovers
by Carlos Jesús Pérez del Pulgar Mancebo, Pablo Romeo Manrique, Gonzalo Jesús Paz Delgado, José Ricardo Sánchez Ibáñez and Martin Azkarate
Electronics 2019, 8(7), 818; https://doi.org/10.3390/electronics8070818 - 22 Jul 2019
Cited by 3 | Viewed by 5304
Abstract
The use of autonomous rovers for planetary exploration is crucial to traverse long distances and perform new discoveries on other planets. One of the most important issues is related to the interaction between the rover wheel and terrain, which would help to save [...] Read more.
The use of autonomous rovers for planetary exploration is crucial to traverse long distances and perform new discoveries on other planets. One of the most important issues is related to the interaction between the rover wheel and terrain, which would help to save energy and even avoid getting entrapped. The use of reconfigurable rovers with different locomotion modes has demonstrated improvement of traction and energy consumption. Therefore, the objective of this paper is to determine the best locomotion mode during the rover traverse, based on simple parameters, which would be obtained from propioceptive sensors. For this purpose, interaction of different terrains have been modelled and analysed with the ExoTeR, a scale prototype rover of the European ExoMars 2020 mission. This rover is able to perform, among others, the wheel walking locomotion mode, which has been demonstrated to improve traction in different situations. Currently, it is difficult to decide the instant time the rover has to switch from this locomotion mode to another. This paper also proposes a novel method to estimate the slip ratio, useful for deciding the best locomotion mode. Finally, results are obtained from an immersive simulation environment. It shows how each locomotion mode is suitable for different terrains and slopes and the proposed method is able to estimate the slip ratio. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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<p>Diagram of the proposed normal driving model. Positions, forces and torques are depicted in order to illustrate the used notation and implied forces.</p> Full article ">Figure 2
<p>Diagram of the proposed wheel walking mode. It represents both steps, wheel-backward and wheel-forward that are carried out by wheels <math display="inline"><semantics> <mrow> <mi>w</mi> <mn>1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>w</mi> <mn>2</mn> </mrow> </semantics></math>, respectively.</p> Full article ">Figure 3
<p>Distance covered by the wheels during the acceleration step. It is used to estimate the slip ratio.</p> Full article ">Figure 4
<p>Diagram that shows the trajectory of the rover in the XY plane for the acceleration step. As shown, the rover performs a curve, whose turning radius can be estimated as an ICR with a radius <span class="html-italic">R</span>.</p> Full article ">Figure 5
<p>Simulation environment. It shows interactions between the used software. The 3D model of the ExoTeR rover is obtained from SolidWorks and included within Vortex Studio. Matlab &amp; Simulink is used to perform the locomotion modes motion planner, retrieve power consumption and estimate the slip ratio during wheel walking.</p> Full article ">Figure 6
<p>Vortex Studio defined contact points for different terrains. Depending on the Stiffness and Damping parameters, these contact points can be increased or decreased. (<b>a</b>) Terrains 1 and 2; (<b>b</b>) Terrains 3 and 4; (<b>c</b>) Terrains 5 and 6.</p> Full article ">Figure 7
<p>Ideal and real angular velocities of the walking joints and wheels. As shown, the walking joint generates a peak for each step. It is due to the joint controller implemented in Vortex Studio. The wheel is able to follow the velocity reference with a small time delay.</p> Full article ">Figure 8
<p>Rover linear velocity during wheel walking. Peaks on the walking joints causes the same effect over the linear velocity of the rover.</p> Full article ">Figure 9
<p>Average current consumption of wheel walking and normal driving locomotion modes on different terrains. It is always lower in normal driving, however, the difference is decreased as <math display="inline"><semantics> <mi>σ</mi> </semantics></math> and <math display="inline"><semantics> <mi>ρ</mi> </semantics></math> are increased.</p> Full article ">Figure 10
<p>Average speed of wheel walking and normal driving locomotion modes on different terrains. normal driving velocity is higher than wheel walking only for very low <math display="inline"><semantics> <mi>σ</mi> </semantics></math> and <math display="inline"><semantics> <mi>ρ</mi> </semantics></math>.</p> Full article ">Figure 11
<p>Relation between current consumption and speed of both locomotion modes, in function of slope and for different terrains. As shown, normal driving provides lower As/m than wheel walking for terrains 1 to 3. wheel walking shows a better performance in terrains 4 to 6 and slopes lower than 7<math display="inline"><semantics> <msup> <mrow/> <mo>∘</mo> </msup> </semantics></math>.</p> Full article ">Figure 12
<p>Best locomotion mode in function of slope and terrain. This figure shows how normal driving is the best one in most of cases, and wheel walking is suitable for terrains with <math display="inline"><semantics> <mrow> <mi>σ</mi> <mo>≥</mo> <mn>0.47</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ρ</mi> <mo>≥</mo> <mn>0.21</mn> </mrow> </semantics></math>. It is worth mentioning that grey area in the figure represents terrains and slopes that cannot be overcome by the rover due to the terrain parameters and the slope.</p> Full article ">Figure 13
<p>Errors of the slip estimator for different terrains and velocities during the acceleration steps. Analysing terrains 1 to 3, there are high errors for high velocity increments, and low errors for low velocity increments. The contrary happens for terrains 4 to 6. A balance between errors for different parameters arise with velocity x2.</p> Full article ">Figure 14
<p>Representation of the parameters to be optimised, the maximum slip ratio and the rover turning radius due to the velocity increment. Based on it, the chosen velocity increment is x2.</p> Full article ">
20 pages, 791 KiB  
Article
Enabling Non-Linear Energy Harvesting in Power Domain Based Multiple Access in Relaying Networks: Outage and Ergodic Capacity Performance Analysis
by Thanh-Luan Nguyen, Minh-Sang Van Nguyen, Dinh-Thuan Do and Miroslav Voznak
Electronics 2019, 8(7), 817; https://doi.org/10.3390/electronics8070817 - 22 Jul 2019
Cited by 6 | Viewed by 4329
Abstract
The Power Domain-based Multiple Access (PDMA) scheme is considered as one kind of Non-Orthogonal Multiple Access (NOMA) in green communications and can support energy-limited devices by employing wireless power transfer. Such a technique is known as a lifetime-expanding solution for operations in future [...] Read more.
The Power Domain-based Multiple Access (PDMA) scheme is considered as one kind of Non-Orthogonal Multiple Access (NOMA) in green communications and can support energy-limited devices by employing wireless power transfer. Such a technique is known as a lifetime-expanding solution for operations in future access policy, especially in the deployment of power-constrained relays for a three-node dual-hop system. In particular, PDMA and energy harvesting are considered as two communication concepts, which are jointly investigated in this paper. However, the dual-hop relaying network system is a popular model assuming an ideal linear energy harvesting circuit, as in recent works, while the practical system situation motivates us to concentrate on another protocol, namely non-linear energy harvesting. As important results, a closed-form formula of outage probability and ergodic capacity is studied under a practical non-linear energy harvesting model. To explore the optimal system performance in terms of outage probability and ergodic capacity, several main parameters including the energy harvesting coefficients, position allocation of each node, power allocation factors, and transmit signal-to-noise ratio (SNR) are jointly considered. To provide insights into the performance, the approximate expressions for the ergodic capacity are given. By matching analytical and Monte Carlo simulations, the correctness of this framework can be examined. With the observation of the simulation results, the figures also show that the performance of energy harvesting-aware PDMA systems under the proposed model can satisfy the requirements in real PDMA applications. Full article
(This article belongs to the Special Issue Recent Technical Developments in Energy-Efficient 5G Mobile Cells)
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<p>System model of downlink in the Non-linear Energy Harvesting (NEH)-NOMA network.</p> Full article ">Figure 2
<p>Outage probability of User 1 and User 2 versus <math display="inline"><semantics> <msub> <mi>R</mi> <mn>1</mn> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>R</mi> <mn>2</mn> </msub> </semantics></math>.</p> Full article ">Figure 3
<p>Outage probability of User 1 and User 2 versus SNR.</p> Full article ">Figure 4
<p>Outage probability of User 1 and User 2 versus SNR.</p> Full article ">Figure 5
<p>Outage probability of User 1 and User 2 versus distance.</p> Full article ">Figure 6
<p>Ergodic capacity of User 1 and User 2 versus SNR.</p> Full article ">Figure 7
<p>Ergodic capacity of User 1 and User 2 versus distance.</p> Full article ">Figure 8
<p>Ergodic capacity of User 1 and User 2 versus <math display="inline"><semantics> <msub> <mi>p</mi> <mrow> <mi>t</mi> <mi>h</mi> </mrow> </msub> </semantics></math>.</p> Full article ">
15 pages, 2437 KiB  
Article
Optimal Scheduling Strategy of Distribution Network Based on Electric Vehicle Forecasting
by Fenglei Li, Chunxia Dou and Shiyun Xu
Electronics 2019, 8(7), 816; https://doi.org/10.3390/electronics8070816 - 22 Jul 2019
Cited by 15 | Viewed by 4115
Abstract
Based on the Monte Carlo method, this paper simulates, predicts the load, and considers the travel chain of electric vehicles and different charging methods to establish a predictive model. Based on the results of electric vehicle simulation prediction, an optimal scheduling model of [...] Read more.
Based on the Monte Carlo method, this paper simulates, predicts the load, and considers the travel chain of electric vehicles and different charging methods to establish a predictive model. Based on the results of electric vehicle simulation prediction, an optimal scheduling model of the distribution network considering the demand response side load is established. The firefly optimization algorithm is used to solve the optimal scheduling problem. The results show that the prediction model proposed in this paper has a certain reference value for the prediction of an electric vehicle load. The electric vehicle is placed in the optimal scheduling resource of the distribution network, which increases the dimension of the scheduling resources of the network and improves the economics of the distribution network operation. Full article
(This article belongs to the Special Issue Advances in Power Electronics Technologies for Renewable Energy Systems)
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<p>Time and space distribution prediction of the charging load of electric vehicle (EV).</p> Full article ">Figure 2
<p>The travelling chain of a typical day.</p> Full article ">Figure 3
<p>Travel chain diagram.</p> Full article ">Figure 4
<p>Electric vehicle charging load forecasting flow chart.</p> Full article ">Figure 5
<p>Charging load curve for different functional areas.</p> Full article ">Figure 6
<p>Charging load curve for different fast charge ratios.</p> Full article ">Figure 7
<p>Optimized scheduling scheme for accessing EV.</p> Full article ">Figure 8
<p>Optimized scheduling scheme for unconnected EV.</p> Full article ">
13 pages, 942 KiB  
Article
High-Throughput and Low-Latency Digital Baseband Architecture for Energy-Efficient Wireless VR Systems
by Seokha Hwang, Seungsik Moon, Dongyun Kam, Inn-Yeal Oh and Youngjoo Lee
Electronics 2019, 8(7), 815; https://doi.org/10.3390/electronics8070815 - 22 Jul 2019
Cited by 4 | Viewed by 5014
Abstract
This paper presents a novel baseband architecture that supports high-speed wireless VR solutions using 60 GHz RF circuits. Based on the experimental observations by our previous 60 GHz transceiver circuits, the efficient baseband architecture is proposed to enhance the quality of transmission. To [...] Read more.
This paper presents a novel baseband architecture that supports high-speed wireless VR solutions using 60 GHz RF circuits. Based on the experimental observations by our previous 60 GHz transceiver circuits, the efficient baseband architecture is proposed to enhance the quality of transmission. To achieve a zero-latency transmission, we define an (106,920, 95,040) interleaved-BCH error-correction code (ECC), which removes iterative processing steps in the previous LDPC ECC standardized for the near-field wireless communication. Introducing the block-level interleaving, the proposed baseband processing successfully scatters the existing burst errors to the small-sized component codes, and recovers up to 1080 consecutive bit errors in a data frame of 106,920 bits. To support the high-speed wireless VR system, we also design the massive-parallel BCH encoder and decoder, which is tightly connected to the block-level interleaver and de-interleaver. Including the high-speed analog interfaces for the external devices, the proposed baseband architecture is designed in 65 nm CMOS, supporting a data rate of up to 12.8 Gbps. Experimental results show that the proposed wireless VR solution can transfer up to 4 K high-resolution video streams without using time-consuming compression and decompression, successfully achieving a transfer latency of 1 ms. Full article
(This article belongs to the Special Issue VLSI Architecture Design for Digital Signal Processing)
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<p>Processing flow of the proposed wireless VR system.</p> Full article ">Figure 2
<p>Error pattern observed by the previous 60 GHz RF circuit. (<b>a</b>) Error count = 0, Error rate = 0; (<b>b</b>) Error count = 116,656, Error rate = 4.32 × <math display="inline"><semantics> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>5</mn> </mrow> </msup> </semantics></math>.</p> Full article ">Figure 3
<p>Construction of the proposed interleaved BCH codes.</p> Full article ">Figure 4
<p>Proposed interleaving and buffering scheme for seamless data transaction.</p> Full article ">Figure 5
<p>Proposed de-interleaving and buffering scheme for seamless error correction.</p> Full article ">Figure 6
<p>The example of the burst error correcting with proposed interleaving scheme.</p> Full article ">Figure 7
<p>Block diagram of the proposed digital baseband system.</p> Full article ">Figure 8
<p>Block diagram of the proposed one-lane BCH encoder (<b>a</b>) and decoder (<b>b</b>) architecture.</p> Full article ">Figure 9
<p>The die-photo of the prototype baseband processor.</p> Full article ">Figure 10
<p>Error-correcting capabilities of different ECC solutions.</p> Full article ">Figure 11
<p>A FPGA-based testing platform with high-speed interface I/Os.</p> Full article ">
11 pages, 3421 KiB  
Article
A High-Accuracy Ultra-Low-Power Offset-Cancelation On-Off Bandgap Reference for Implantable Medical Electronics
by Jiangtao Xu, Yawei Wang, Minshun Wu, Ruizhi Zhang, Sufen Wei, Guohe Zhang and Cheng-Fu Yang
Electronics 2019, 8(7), 814; https://doi.org/10.3390/electronics8070814 - 21 Jul 2019
Cited by 3 | Viewed by 4610
Abstract
An ultra-low-power and high-accuracy on-off bandgap reference (BGR) is demonstrated in this paper for implantable medical electronics. The proposed BGR shows an average current consumption of 78 nA under 2.8 V supply and an output voltage of 1.17 V with an untrimmed accuracy [...] Read more.
An ultra-low-power and high-accuracy on-off bandgap reference (BGR) is demonstrated in this paper for implantable medical electronics. The proposed BGR shows an average current consumption of 78 nA under 2.8 V supply and an output voltage of 1.17 V with an untrimmed accuracy of 0.69%. The on-off bandgap combined with sample-and-hold switched-RC filter is developed to reduce power consumption and noise. The on-off mechanism allows a relatively higher current in the sample phase to alleviate the process variation of bipolar transistors. To compensate the error caused by operational amplifier offset, the correlated double sampling strategy is adopted in the BGR. The proposed BGR is implemented in 0.35 μm standard CMOS process and occupies a total area of 0.063 mm2. Measurement results show that the circuit works properly in the supply voltage range of 1.8–3.2 V and achieves a line regulation of 0.59 mV/V. When the temperature varies from −20 to 80 °C, an average temperature coefficient of 19.6 ppm/°C is achieved. Full article
(This article belongs to the Section Microelectronics)
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<p>The basic topology of the bipolar junction transistor (BJT)-based bandgap reference (BGR) core circuit.</p> Full article ">Figure 2
<p>Block diagram of the proposed BGR.</p> Full article ">Figure 3
<p>(<b>a</b>) Proposed on-off BGR with chopper mechanism; (<b>b</b>) Control clocks for BGR power cycle and chopper blocks.</p> Full article ">Figure 4
<p>(<b>a</b>) Proposed sampling-capacitor circuit along with switched-RC block; (<b>b</b>) Control clocks for sampling switches.</p> Full article ">Figure 5
<p>Proposed sample-and-hold switched-RC filter circuit and control clock timing.</p> Full article ">Figure 6
<p>The output voltage of the proposed circuit.</p> Full article ">Figure 7
<p>(<b>a</b>) 200 Monte Carlo simulation results. (<b>b</b>) Temperature coefficient simulation at 2.8 V supply.</p> Full article ">Figure 8
<p>Microphotograph of BGR chip.</p> Full article ">Figure 9
<p>Measured results for 30 samples.</p> Full article ">Figure 10
<p>Measured reference voltage versus temperature for 30 samples.</p> Full article ">Figure 11
<p>Measured reference voltage versus the supply voltage.</p> Full article ">Figure 12
<p>Measured power supply rejection ratio (PSRR).</p> Full article ">
19 pages, 9791 KiB  
Article
Design of an Oscillation-Based BIST System for Active Analog Integrated Filters in 0.18 µm CMOS
by Leonid Kladovščikov, Marijan Jurgo and Romualdas Navickas
Electronics 2019, 8(7), 813; https://doi.org/10.3390/electronics8070813 - 20 Jul 2019
Cited by 6 | Viewed by 3793
Abstract
In this paper, an oscillation-based built-in self-test system for active an analog integrated circuit is presented. This built-in self-test system was used to detect catastrophic and parametric faults, introduced during chip manufacturing. As circuits under test (CUT), second-order Sallen-Key, Akerberg-Mossberg and Tow-Thomas biquad [...] Read more.
In this paper, an oscillation-based built-in self-test system for active an analog integrated circuit is presented. This built-in self-test system was used to detect catastrophic and parametric faults, introduced during chip manufacturing. As circuits under test (CUT), second-order Sallen-Key, Akerberg-Mossberg and Tow-Thomas biquad filters were designed. The proposed test hardware detects parametric and catastrophic faults on changeable limits. The influence of both oscillation and test hardware on fault detection limits were investigated and analyzed. The proposed oscillation based self-test system was designed and simulated in 0.18 µm complementary metal-oxide semiconductor (CMOS) technology. Due to the easiness of implementation and configuration for testing of different active analog filters, such self-test systems can be effectively used in modern integrated circuits, made of a large number of devices and circuits, such as the multi-standard transceivers used in the core hardware of software-defined radios. Using the proposed test strategy, the fault tolerance limits for catastrophic faults varied from 96% to 100% for all injected faults in different structures of low pass filters (LPF). The detection range of parametric faults of passive components’ nominal value, depending on the used structure of the filter, did not exceed –0.74% – 0.72% in case of Sallen-Key, –3.31% – 1.00% in case of Akerberg-Mossberg and –2.39% – 1.44% in case of Tow-Thomas LPF. Full article
(This article belongs to the Section Microelectronics)
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<p>Basic diagram of the functional block: (<b>a</b>) during normal operation; (<b>b</b>) converted into an oscillator.</p> Full article ">Figure 2
<p>Circuit diagram of the proposed oscillation-based built-in self-test (OBIST) structure.</p> Full article ">Figure 3
<p>The operation algorithm of the proposed OBIST system.</p> Full article ">Figure 4
<p>Structure of the second-order Sallen-Key low pass filter.</p> Full article ">Figure 5
<p>Structure of the second-order Akerberg-Mossberg low pass filter.</p> Full article ">Figure 6
<p>Structure of the second-order Tow-Thomas low pass filter.</p> Full article ">Figure 7
<p>Schematic of two-stage operational amplifier.</p> Full article ">Figure 8
<p>Schematic of feedback circuit.</p> Full article ">Figure 9
<p>Dependency of the resistance of the transmission gate on the transistors’ size.</p> Full article ">Figure 10
<p>Dependency of the CUT’s oscillation frequency on the size of the transmission gate and inverter: (<b>a</b>) Sallen-Key; (<b>b</b>) Akerberg-Mossberg; (<b>c</b>) Tow-Thomas.</p> Full article ">Figure 10 Cont.
<p>Dependency of the CUT’s oscillation frequency on the size of the transmission gate and inverter: (<b>a</b>) Sallen-Key; (<b>b</b>) Akerberg-Mossberg; (<b>c</b>) Tow-Thomas.</p> Full article ">Figure 11
<p>Variations of the dependency of the maximum CUT oscillation frequency on the size of the feedback inverter, when <span class="html-italic">M</span><sub>TG</sub> = 16: (<b>a</b>) Sallen-Key; (<b>b</b>) Akerberg-Mossberg; (<b>c</b>) Tow-Thomas.</p> Full article ">Figure 11 Cont.
<p>Variations of the dependency of the maximum CUT oscillation frequency on the size of the feedback inverter, when <span class="html-italic">M</span><sub>TG</sub> = 16: (<b>a</b>) Sallen-Key; (<b>b</b>) Akerberg-Mossberg; (<b>c</b>) Tow-Thomas.</p> Full article ">Figure 12
<p>Variations of the dependency of the maximum CUT oscillation frequency on the size of the transmission gate, when <span class="html-italic">M</span><sub>IV</sub> = 28: (<b>a</b>) Sallen-Key; (<b>b</b>) Akerberg-Mossberg; (<b>c</b>) Tow-Thomas.</p> Full article ">Figure 13
<p>Variations of the maximum oscillation frequency for the filter structures when <span class="html-italic">M</span><sub>TG</sub> = 16, <span class="html-italic">M</span><sub>IV</sub> = 28: (<b>a</b>) Sallen-Key; (<b>b</b>) Akerberg-Mossberg; (<b>c</b>) Tow-Thomas.</p> Full article ">Figure 14
<p>Short and open fault models for: (<b>a</b>) Metal–oxide–semiconductor (MOS) transistor; (<b>b</b>) resistor; (<b>c</b>) capacitor.</p> Full article ">Figure 15
<p>Process and mismatch variations of components used in CUT: (<b>a</b>) capacitors; (<b>b</b>) resistors.</p> Full article ">Figure 16
<p>The dependencies of the oscillation frequency of the Sallen-Key filter configured as an oscillator on variations of the passive components.</p> Full article ">
17 pages, 8482 KiB  
Article
Unobtrusive Sleep Monitoring Using Movement Activity by Video Analysis
by Yuan-Kai Wang, Hung-Yu Chen and Jian-Ru Chen
Electronics 2019, 8(7), 812; https://doi.org/10.3390/electronics8070812 - 20 Jul 2019
Cited by 14 | Viewed by 4907
Abstract
Sleep healthcare at home is a new research topic that needs to develop new sensors, hardware and algorithms with the consideration of convenience, portability and accuracy. Monitoring sleep behaviors by visual sensors represents one new unobtrusive approach to facilitating sleep monitoring and benefits [...] Read more.
Sleep healthcare at home is a new research topic that needs to develop new sensors, hardware and algorithms with the consideration of convenience, portability and accuracy. Monitoring sleep behaviors by visual sensors represents one new unobtrusive approach to facilitating sleep monitoring and benefits sleep quality. The challenge of video surveillance for sleep behavior analysis is that we have to tackle bad image illumination issue and large pose variations during sleeping. This paper proposes a robust method for sleep pose analysis with human joints model. The method first tackles the illumination variation issue of infrared videos to improve the image quality and help better feature extraction. Image matching by keypoint features is proposed to detect and track the positions of human joints and build a human model robust to occlusion. Sleep poses are then inferred from joint positions by probabilistic reasoning in order to tolerate occluded joints. Experiments are conducted on the video polysomnography data recorded in sleep laboratory. Sleep pose experiments are given to examine the accuracy of joint detection and tacking, and the accuracy of sleep poses. High accuracy of the experiments demonstrates the validity of the proposed method. Full article
(This article belongs to the Special Issue Sensing and Signal Processing in Smart Healthcare)
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<p>The proposed scheme for sleep pose recognition. (<b>a</b>) An infrared camera is used to acquire the sleep videos and analyze body joint positions. (<b>b</b>) Pajamas with ten near infrared (NIR)-sensitive patches are designed to facilitate the detection of body joints.</p> Full article ">Figure 2
<p>Enhanced NIR images with different Gaussian kernel sizes from 50 to 250. (<b>a</b>) Original image. (<b>b</b>) <span class="html-italic">c</span> = 50. (<b>c</b>) <span class="html-italic">c</span> = 100. (<b>d</b>) <span class="html-italic">c</span> = 150. (<b>e</b>) <span class="html-italic">c</span> = 200. (<b>f</b>) <span class="html-italic">c</span> = 250.</p> Full article ">Figure 3
<p>Keypoint detection and joint detection. (<b>a</b>) Image descriptor of an original lateral-pose image overlaid with keypoints of length and orientation information. Each arrow represents one detected keypoint. (<b>b</b>) A joint detection example for left ankle. It is detected by matching a specific joint marker representing the left ankle with a visual marker in the sleep image.</p> Full article ">Figure 4
<p>An example of reconstructed human model by fully detected joints. (<b>a</b>) A standard model with a standing pose. (<b>b</b>) A sleep image overlaid with the detected/tracked joints found by keypoint match and structured learning. (<b>c</b>) Reconstructed model of the lateral pose.</p> Full article ">Figure 5
<p>Enhancement of NIR images. (<b>a</b>) Original image. (<b>b</b>) Histogram stretching. (<b>c</b>) Histogram equalization. (<b>d</b>) Gamma correction. (<b>e</b>) Single-scale Retinex. (<b>f</b>) The proposed illumination compensation method.</p> Full article ">Figure 6
<p>Effect of image enhancement (IE) for the performance improvement of the error of total sleep time.</p> Full article ">Figure 7
<p>Examples of joint detection results. Each double-red circle represents a detected joint. (<b>a</b>) Lateral pose with ten successful detections. (<b>b</b>) Supine pose with ten successful detections. (<b>c</b>) Supine pose with eight successful detections. The right-knee and right-elbow joints are missed because of great distortion induced by perspective and cloth’s wrinkles.</p> Full article ">Figure 8
<p>Accuracy evaluation. (<b>a</b>) The effect of the threshold of matched keypoint numbers. (<b>b</b>) Average precision of joint localization. (<b>c</b>) Average distance error of joint localization.</p> Full article ">Figure 9
<p>Comparison of six inference algorithms with respect to (<b>a</b>) execution time, and (<b>b</b>) accuracy.</p> Full article ">
18 pages, 3146 KiB  
Article
A Smart Binaural Hearing Aid Architecture Based on a Mobile Computing Platform
by Yingdan Li, Fei Chen, Zhuoyi Sun, Zhaoyang Weng, Xian Tang, Hanjun Jiang and Zhihua Wang
Electronics 2019, 8(7), 811; https://doi.org/10.3390/electronics8070811 - 20 Jul 2019
Cited by 5 | Viewed by 8586
Abstract
This paper presents a new structure for hearing aids. Normally, the power consumption and user experience are contradictory. The proposed hearing aid structure mainly consists of three parts: the earpieces, the mobile computing platform, and the real-time speech-enhancement application. It can run complex [...] Read more.
This paper presents a new structure for hearing aids. Normally, the power consumption and user experience are contradictory. The proposed hearing aid structure mainly consists of three parts: the earpieces, the mobile computing platform, and the real-time speech-enhancement application. It can run complex algorithms without carrying out heavy calculations on the processors in the hearing aid. Thus, the binaural algorithm is utilized without being limited by complexity and power consumption to improve the user experience. Moreover, the speech-enhancement algorithm can be updated much more easily than in traditional built-in digital signal process hearing aids. A good level of user experience is achieved by combining the hearing aid and mobile computing platform with a 400-MHz transceiver; furthermore, the 400-MHz transceiver can reduce path loss around the body. The concept verification process showed that the overall usage of the central processing unit in the smartphone is around 16%, the signal-to-noise ratios show at least a 30% improvement in some environments, and the whole system delay is 8.8 ms. The presented objective and subjective results show significant improvements regarding user experience and usability brought about by the proposed structure. Full article
(This article belongs to the Section Bioelectronics)
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<p>Types of hearing aids [<a href="#B25-electronics-08-00811" class="html-bibr">25</a>] and batteries.</p> Full article ">Figure 2
<p>Basic digital hearing aid [<a href="#B7-electronics-08-00811" class="html-bibr">7</a>].</p> Full article ">Figure 3
<p>Proposed architecture of the HA.</p> Full article ">Figure 4
<p>Block diagram of the wireless transceiver.</p> Full article ">Figure 5
<p>Block diagram of the Digital Acoustic Baseband (DABB).</p> Full article ">Figure 6
<p>Block diagram of the battery/power management unit.</p> Full article ">Figure 7
<p>The three working modes in the battery/power management unit.</p> Full article ">Figure 8
<p>Block diagram of the real-time software.</p> Full article ">Figure 9
<p>Top-level system block diagram of the earpiece.</p> Full article ">Figure 10
<p>Packet definition.</p> Full article ">Figure 11
<p>Proposed diagram of the system data exchange module.</p> Full article ">Figure 12
<p>Signal data exchange control state machine.</p> Full article ">Figure 13
<p>Flow of packet exchange.</p> Full article ">Figure 14
<p>Overview of the verification system.</p> Full article ">Figure 15
<p>Block diagram with system delay analysis.</p> Full article ">Figure 16
<p>The comparison results of the improved SNR in different SNRs under different daily noise scenarios.</p> Full article ">Figure 17
<p>The comparison results of PESQin different SNRs under different daily noise scenarios.</p> Full article ">Figure 18
<p>The comparison results of Short-Time Objective Intelligibility (STOI) in different SNRs under different daily noise scenarios.</p> Full article ">
19 pages, 6706 KiB  
Article
Customized Vibration Generator for State of Health Monitoring of Prosthetic Implants and Pseudo-Bionic Machine–Human Feedbacks
by Ilya Galkin, Maxim Vorobyov, Oskars Gainutdinovs and Peteris Studers
Electronics 2019, 8(7), 810; https://doi.org/10.3390/electronics8070810 - 19 Jul 2019
Cited by 9 | Viewed by 4373
Abstract
Modern industrial, household and other equipment include sophisticated power mechanisms and complicated control solutions that require tighter human–machine–human interactions to form the structures known as cyber–physical–human systems. Their significant parts are human–machine command links and machine–human feedbacks. Such systems are found in medicine, [...] Read more.
Modern industrial, household and other equipment include sophisticated power mechanisms and complicated control solutions that require tighter human–machine–human interactions to form the structures known as cyber–physical–human systems. Their significant parts are human–machine command links and machine–human feedbacks. Such systems are found in medicine, e.g., in orthopedics, where they are important for the operation and functional abilities of orthopedic devices—wheelchair, prosthesis, rehabilitation units, etc. The mentioned feedbacks may be implemented based on the haptic perceptions that requires vibration actuators. In orthopedics, such actuators can be used also for diagnostic purposes. This research brings forward the idea of the use of 3D printing in conjunction with high quality permanent magnets. This allows for the achievement of better efficiency, smaller size, and the developing of actuators individually for particular circumstances. The obtained simulation, experimental data, and data about 3D manufacturing generally confirm the above hypothesis. In particular, the stiffness coefficient of the actuator’s membrane and attached mass, which can be changed easily during 3D printing, affects the frequency of maximal power output. Secondly, the 3D manufacturing process is quick, tunable and rather cheap. Finally, an elaboration of the design of the actuator that allows for the real-time modification of stiffness and mass in a program way is planned for future works. Full article
(This article belongs to the Special Issue Recent Advances in Biometrics and its Applications)
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<p>Use of vibration in orthopedic systems: (<b>a</b>) Human–machine–human interaction; (<b>b</b>) diagnostic system.</p> Full article ">Figure 2
<p>Two different femur X-ray after osteointegration: (<b>a</b>) The residual femur is long, and its osteointegrated stem has a diameter of 19 mm; (<b>b</b>) the residual femur is short, and it osteointegrated stem has a diameter of 12 mm; (<b>c</b>) normal femur for comparison.</p> Full article ">Figure 3
<p>Structure of the proposed vibration generator: (<b>a</b>) Not energized; (<b>b</b>) attracting force; (<b>c</b>) buoyant force; and (<b>d</b>) equivalent scheme with spring.</p> Full article ">Figure 4
<p>Design of vibration actuator: Industrial (<b>a</b>), small (<b>b</b>), and large (<b>c</b>).</p> Full article ">Figure 5
<p>Comparison of measured displacement values for different actuators.</p> Full article ">Figure 6
<p>Simulation velocity values for different actuators.</p> Full article ">Figure 7
<p>Mass influence on industrial actuator measured data.</p> Full article ">Figure 8
<p>Mass influence on industrial actuator simulation data.</p> Full article ">Figure 9
<p>Influence on large actuator measured data.</p> Full article ">Figure 10
<p>Influence on large actuator simulation data.</p> Full article ">Figure 11
<p>Influence on small actuator measured data.</p> Full article ">Figure 12
<p>Influence on small actuator simulation data.</p> Full article ">Figure 13
<p>Comparison of experimentally measured characteristics (frequency response) of the commercially available and proposed actuators absolute values.</p> Full article ">Figure 14
<p>Structure of the proposed adjustable vibration generator: (<b>a</b>) Flexible configuration; (<b>b</b>) average flexibility; and (<b>c</b>) rigid configuration.</p> Full article ">Figure 15
<p>Results of simulation of adjustable vibration generator.</p> Full article ">Figure 16
<p>Results of measurement of adjustable vibration generator.</p> Full article ">Figure 17
<p>Results of measurement of adjustable vibration generator THD (total harmonic distortion).</p> Full article ">
15 pages, 1655 KiB  
Article
Ancillary Service with Grid Connected PV: A Real-Time Hardware-in-the-Loop Approach for Evaluation of Performances
by Yujia Huo and Giambattista Gruosso
Electronics 2019, 8(7), 809; https://doi.org/10.3390/electronics8070809 - 19 Jul 2019
Cited by 10 | Viewed by 3782
Abstract
The integration of photovoltaic (PV) systems with the grid is undoubtedly an issue of great interest both in terms of energy production, but also as a support to the grid as an ancillary service, but to evaluate the performance of the use of [...] Read more.
The integration of photovoltaic (PV) systems with the grid is undoubtedly an issue of great interest both in terms of energy production, but also as a support to the grid as an ancillary service, but to evaluate the performance of the use of PV in an unconventional way, it is necessary to have reference models to be applied to evaluate the characteristics and integration requirements. In this work, an ancillary service provided by a grid-connected PV is shown and a hardware in the loop simulation environment is created to simulate performances and integration issues. Full article
(This article belongs to the Special Issue Grid Connected Photovoltaic Systems)
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<p>The functional scheme of the micro-grid under test.</p> Full article ">Figure 2
<p>Ancillary service implemented in photovoltaic (PV) system.</p> Full article ">Figure 3
<p>Real-time simulation (RTS) model of micro-grid under test.</p> Full article ">Figure 4
<p>Simulation Framework: Controller-hardware-in-the-loop (C-Hil) is performed with dSPACE DS1404 and the real-time simulator is the Typhoon Hil402.</p> Full article ">Figure 5
<p>Digital PLL preliminary (<b>Left</b>) and improved (<b>Right</b>) implementation.</p> Full article ">Figure 6
<p>(<b>a</b>) PQ calculation without phase compensation, (<b>b</b>) PQ calculation with phase compensation.</p> Full article ">Figure 7
<p>Comparison of the currents during the control stage with the ideal “reference current” and the generated one from control.</p> Full article ">Figure 8
<p>Frequency transients under load connection at the 15th s without ancillary service (blue), with the proposed method (red). In (black) the same simulation done using virtual synchronous generator (VSG) tecnique.</p> Full article ">Figure 9
<p>Frequency transients under the load disconnection. In yellow, we show the simulation without regulation. In blue, we show the simulation with regulation in the C-HIL case and in orange, we show the pure real-time simulation. The blue simulation highlights how the presence of the sampling done by the controller introduces numerical instabilities that move away from the ideality of pure simulation. These oscillations must be taken into account in the optimal design phase of the control system.</p> Full article ">Figure 10
<p>Frequency transients: without ancillary service (yellow), with ancillary service verified in real-time simulation (red) and with ancillary service verified in C-HIL simulation (blue).</p> Full article ">Figure 11
<p>Repeatability of the C-HIL simulation: Considering that the C-Hil simulation, includes sampling and delays due to communication between the two devices, we wanted to prove how the repeatability is guaranteed, so we repeated the simulation under the same conditions.</p> Full article ">Figure 12
<p>PV irradiance’s influence on the frequency dynamic. In this figure it is shown the effect of a sudden change of radiation during the frequency regulation phase.</p> Full article ">
18 pages, 8902 KiB  
Article
A Context-Aware Route Finding Algorithm for Self-Driving Tourists Using Ontology
by Maryam Barzegar, Abolghasem Sadeghi-Niaraki, Maryam Shakeri and Soo-Mi Choi
Electronics 2019, 8(7), 808; https://doi.org/10.3390/electronics8070808 - 19 Jul 2019
Cited by 6 | Viewed by 3635
Abstract
This study proposed a context-aware ontology-based route finding algorithm for self-driving tourists. In this algorithm, two ontologies—namely drivers’ experiences and required tourist services—were used according to tourist requirements. Trips were classified into business and touristic. The algorithm was then compared with Google Maps [...] Read more.
This study proposed a context-aware ontology-based route finding algorithm for self-driving tourists. In this algorithm, two ontologies—namely drivers’ experiences and required tourist services—were used according to tourist requirements. Trips were classified into business and touristic. The algorithm was then compared with Google Maps in terms of travel time and travel length for evaluation. The results showed that the proposed algorithm performed similarly to Google Maps in some cases of business trips and better in other cases, with a maximum 10-min travel time difference. In touristic trips, the capabilities of the proposed algorithm were far better than those of Google Maps. Full article
(This article belongs to the Section Computer Science & Engineering)
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<p>Driver’s experience ontology.</p> Full article ">Figure 2
<p>Ontology of required tourist services.</p> Full article ">Figure 3
<p>Context-related information.</p> Full article ">Figure 4
<p>Two cases of the proposed route finding algorithm.</p> Full article ">Figure 5
<p>Business trip algorithm.</p> Full article ">Figure 6
<p>(<b>a</b>) Hierarchical Experimental Network (<b>b</b>) Definition of the rectangle for the main network Ji-Hua et al. (2013).</p> Full article ">Figure 7
<p>Touristic trip algorithm.</p> Full article ">Figure 8
<p>Comparison of travel length for two cases of the proposed method.</p> Full article ">Figure 9
<p>Comparison of travel time for two cases of the proposed method.</p> Full article ">Figure 10
<p>Comparison of two methods at off-peak traffic times.</p> Full article ">Figure 11
<p>Comparison of two methods at peak traffic times.</p> Full article ">Figure 12
<p>Comparison of route length for the proposed algorithm and Google Maps at off-peak traffic times.</p> Full article ">Figure 13
<p>Comparison of travel time for the proposed algorithm and Google Maps at off-peak traffic times.</p> Full article ">Figure 14
<p>Comparison of travel length for the proposed algorithm and Google Maps at peak traffic times.</p> Full article ">Figure 15
<p>Comparison of travel time for the proposed algorithm and Google Maps at peak traffic times.</p> Full article ">Figure 16
<p>The proposed route with two stops on the way.</p> Full article ">
13 pages, 1149 KiB  
Article
FT-GAN: Face Transformation with Key Points Alignment for Pose-Invariant Face Recognition
by Weiwei Zhuang, Liang Chen, Chaoqun Hong, Yuxin Liang and Keshou Wu
Electronics 2019, 8(7), 807; https://doi.org/10.3390/electronics8070807 - 19 Jul 2019
Cited by 9 | Viewed by 7885
Abstract
Face recognition has been comprehensively studied. However, face recognition in the wild still suffers from unconstrained face directions. Frontal face synthesis is a popular solution, but some facial features are missed after synthesis. This paper presents a novel method for pose-invariant face recognition. [...] Read more.
Face recognition has been comprehensively studied. However, face recognition in the wild still suffers from unconstrained face directions. Frontal face synthesis is a popular solution, but some facial features are missed after synthesis. This paper presents a novel method for pose-invariant face recognition. It is based on face transformation with key points alignment based on generative adversarial networks (FT-GAN). In this method, we introduce CycleGAN for pixel transformation to achieve coarse face transformation results, and these results are refined by key point alignment. In this way, frontal face synthesis is modeled as a two-task process. The results of comprehensive experiments show the effectiveness of FT-GAN. Full article
(This article belongs to the Special Issue Multidimensional Digital Signal Processing)
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<p>Flowchart of the proposed framework. Without loss of generality, we use gray images in the example. For each input image, we use CycleGAN to synthesize a frontal face. Besides, facial key points are extracted and used to align the facial landmarks. In this way, the result of CycleGAN is refined and an improved result is computed.</p> Full article ">Figure 2
<p>The face alignment network (FAN) constructed by stacking four hourglass (HG) networks.</p> Full article ">Figure 3
<p>Comparison of frontal face synthesis. From top to bottom, we show the original frontal faces, profiles, the results of complete representations with a generative adversarial network (CR-GAN), the original CycleGAN, and face transformation with key points alignment based on generative adversarial networks (FT-GAN). From left to right, we show the results of different facial angles: <math display="inline"><semantics> <msup> <mn>30</mn> <mo>∘</mo> </msup> </semantics></math>, <math display="inline"><semantics> <msup> <mn>45</mn> <mo>∘</mo> </msup> </semantics></math>, <math display="inline"><semantics> <msup> <mn>60</mn> <mo>∘</mo> </msup> </semantics></math>, <math display="inline"><semantics> <msup> <mn>75</mn> <mo>∘</mo> </msup> </semantics></math>, and <math display="inline"><semantics> <msup> <mn>90</mn> <mo>∘</mo> </msup> </semantics></math>.</p> Full article ">Figure 4
<p>The missing rates in face detection for Multi-Pie. (<b>a</b>) Dlib; (<b>b</b>) MTCNN.</p> Full article ">Figure 5
<p>The missing rates in face detection for the Head Pose Image Database (HPID). (<b>a</b>) Dlib; (<b>b</b>) MTCNN.</p> Full article ">Figure 6
<p>The accuracy of 1:1 face matching for Multi-Pie. (<b>a</b>) Dlib; (<b>b</b>) FaceNet.</p> Full article ">Figure 7
<p>The accuracy of 1:1 face matching for HPID. (<b>a</b>) Dlib; (<b>b</b>) FaceNet.</p> Full article ">Figure 8
<p>The accuracy of 1:<span class="html-italic">N</span> face matching for Multi-Pie. (<b>a</b>) Dlib; (<b>b</b>) FaceNet.</p> Full article ">Figure 9
<p>The accuracy of 1:<span class="html-italic">N</span> face matching for HPID. (<b>a</b>) Dlib; (<b>b</b>) FaceNet.</p> Full article ">Figure 10
<p>The accuracy of 1:<span class="html-italic">N</span> face matching with different key point extraction methods. (<b>a</b>) Dlib; (<b>b</b>) FaceNet.</p> Full article ">
16 pages, 1165 KiB  
Article
Continuous and Stable Cross-Eye Jamming via a Circular Retrodirective Array
by Tianpeng Liu, Xizhang Wei, Zhen Liu and Zhiqiang Guan
Electronics 2019, 8(7), 806; https://doi.org/10.3390/electronics8070806 - 19 Jul 2019
Cited by 4 | Viewed by 3743
Abstract
Cross-eye jamming is an angular deception jamming technique against monopulse radar. Multiple-element retrodirective cross-eye jamming (MRCJ) as an improved method, uses a retrodirective antenna array with multiple antenna elements in a cross-eye jammer and can obtain better jamming performance. However, the practical MRCJ [...] Read more.
Cross-eye jamming is an angular deception jamming technique against monopulse radar. Multiple-element retrodirective cross-eye jamming (MRCJ) as an improved method, uses a retrodirective antenna array with multiple antenna elements in a cross-eye jammer and can obtain better jamming performance. However, the practical MRCJ system employing a linear antenna array becomes ineffective when the threat radar appears in the antenna array’s end-fire direction. To meet multiple threats from different directions and provide continuous jamming, MRCJ employing a circular antenna array (C-MRCJ) is proposed after defining the modulation direction of system parameters. Optimal configuration of C-MRCJ providing stable jamming performance is discussed. The number of the jammer loops is analyzed under considerable jamming performance and moderate hardware cost. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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<p>A retrodirective cross-eye jamming system with two antenna elements.</p> Full article ">Figure 2
<p>The jamming geometry where C-MRCJ deceives a phase-comparison monopulse radar.</p> Full article ">Figure 3
<p>DOA information and modulation direction for C-MRCJ with three jammer loops.</p> Full article ">Figure 4
<p>The flow diagram of signal processing of modified C-MRCJ.</p> Full article ">Figure 5
<p>The process of MD modification for modified C-MRCJ.</p> Full article ">Figure 6
<p>Two different configurations of C-MRCJ with six antenna elements. The platform is denoted by a black square. (<b>a</b>) Configuration 1 where <math display="inline"><semantics> <mrow> <msub> <mi>α</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>α</mi> <mn>3</mn> </msub> <mo>=</mo> <msup> <mn>15</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>α</mi> <mn>2</mn> </msub> <mo>=</mo> <msup> <mn>150</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>. (<b>b</b>) Configuration 2 where <math display="inline"><semantics> <mrow> <msub> <mi>α</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>α</mi> <mn>2</mn> </msub> <mo>=</mo> <msub> <mi>α</mi> <mn>3</mn> </msub> <mo>=</mo> <msup> <mn>60</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>.</p> Full article ">Figure 7
<p>Configuration of L-MRCJ with six antenna elements. The base-lengths of the three jammer loops are <math display="inline"><semantics> <msub> <mi>d</mi> <mi>c</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <mn>4</mn> <msub> <mi>d</mi> <mi>c</mi> </msub> <mo>/</mo> <mn>5</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>3</mn> <msub> <mi>d</mi> <mi>c</mi> </msub> <mo>/</mo> <mn>5</mn> </mrow> </semantics></math>, respectively.</p> Full article ">Figure 8
<p>Monopulse-indicated angles of different jammer array configurations when the radar antennas rotate. The system parameters of TRCJ are <math display="inline"><semantics> <mrow> <mo>−</mo> <mn>0.5</mn> </mrow> </semantics></math> dB and <math display="inline"><semantics> <msup> <mn>180</mn> <mo>∘</mo> </msup> </semantics></math>, and the system parameters of L-MRCJ and C-MRCJ which are <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>a</mi> <mn>3</mn> </msub> <mo>=</mo> <mo>−</mo> <mn>0.5</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mi>ϕ</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>ϕ</mi> <mn>2</mn> </msub> <mo>=</mo> <msub> <mi>ϕ</mi> <mn>3</mn> </msub> <mo>=</mo> <msup> <mn>180</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>.</p> Full article ">Figure 9
<p>Monopulse-indicated angles of L-MRCJ and C-MRCJ when the jammer antennas rotate. (<b>a</b>) The system parameters are <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>a</mi> <mn>2</mn> </msub> <mo>=</mo> <msub> <mi>a</mi> <mn>3</mn> </msub> <mo>=</mo> <mo>−</mo> <mn>0.5</mn> <mspace width="3.33333pt"/> <mi>dB</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ϕ</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>ϕ</mi> <mn>2</mn> </msub> <mo>=</mo> <msub> <mi>ϕ</mi> <mn>3</mn> </msub> <mo>=</mo> <msup> <mn>180</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>. (<b>b</b>) The system parameters are <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>1</mn> </msub> <mo>=</mo> <mo>−</mo> <mn>0.5</mn> <mspace width="3.33333pt"/> <mi>dB</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>2</mn> </msub> <mo>=</mo> <mo>−</mo> <mn>1.5</mn> <mspace width="3.33333pt"/> <mi>dB</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>3</mn> </msub> <mo>=</mo> <mo>−</mo> <mn>2.5</mn> <mspace width="3.33333pt"/> <mi>dB</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ϕ</mi> <mn>1</mn> </msub> <mo>=</mo> <msup> <mn>170</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ϕ</mi> <mn>2</mn> </msub> <mo>=</mo> <msup> <mn>175</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ϕ</mi> <mn>3</mn> </msub> <mo>=</mo> <msup> <mn>180</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>.</p> Full article ">Figure 10
<p>Monopulse-indicated angles of L-MRCJ and modified C-MRCJ when the jammer antennas rotate. (<b>a</b>) The system parameters are <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>a</mi> <mn>2</mn> </msub> <mo>=</mo> <msub> <mi>a</mi> <mn>3</mn> </msub> <mo>=</mo> <mo>−</mo> <mn>0.5</mn> <mspace width="3.33333pt"/> <mi>dB</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ϕ</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>ϕ</mi> <mn>2</mn> </msub> <mo>=</mo> <msub> <mi>ϕ</mi> <mn>3</mn> </msub> <mo>=</mo> <msup> <mn>180</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>. (<b>b</b>) The system parameters are <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>1</mn> </msub> <mo>=</mo> <mo>−</mo> <mn>0.5</mn> <mspace width="3.33333pt"/> <mi>dB</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>2</mn> </msub> <mo>=</mo> <mo>−</mo> <mn>1.5</mn> <mspace width="3.33333pt"/> <mi>dB</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>3</mn> </msub> <mo>=</mo> <mo>−</mo> <mn>2.5</mn> <mspace width="3.33333pt"/> <mi>dB</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ϕ</mi> <mn>1</mn> </msub> <mo>=</mo> <msup> <mn>170</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ϕ</mi> <mn>2</mn> </msub> <mo>=</mo> <msup> <mn>175</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ϕ</mi> <mn>3</mn> </msub> <mo>=</mo> <msup> <mn>180</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>.</p> Full article ">Figure 11
<p>Monopulse-indicated angles for different configurations when the jammer antennas rotate. The system parameters are <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>a</mi> <mn>2</mn> </msub> <mo>=</mo> <msub> <mi>a</mi> <mn>3</mn> </msub> <mo>=</mo> <mo>−</mo> <mn>0.5</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mi>ϕ</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>ϕ</mi> <mn>2</mn> </msub> <mo>=</mo> <msub> <mi>ϕ</mi> <mn>3</mn> </msub> <mo>=</mo> <msup> <mn>180</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>. (<b>a</b>) Symmetrical case. (<b>b</b>) Asymmetrical case.</p> Full article ">Figure 12
<p>The arithmetic mean and variance of monopulse-indicated angle. (<b>a</b>) Arithmetic mean for the symmetrical case. (<b>b</b>) Arithmetic mean for the asymmetrical case. (<b>c</b>) Variance for the symmetrical case. (<b>d</b>) Variance for the asymmetrical case.</p> Full article ">Figure 13
<p>Monopulse-indicated angles of modified C-MRCJ with the optimal configuration for a range of antenna numbers when the jammer antennas rotate. The system parameters are <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>a</mi> <mn>2</mn> </msub> <mo>=</mo> <msub> <mi>a</mi> <mn>3</mn> </msub> <mo>=</mo> <mo>−</mo> <mn>0.5</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mi>ϕ</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>ϕ</mi> <mn>2</mn> </msub> <mo>=</mo> <msub> <mi>ϕ</mi> <mn>3</mn> </msub> <mo>=</mo> <msup> <mn>180</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>.</p> Full article ">Figure 14
<p>The arithmetic mean and variance of monopulse-indicated angle for different jammer antenna numbers. (<b>a</b>) Arithmetic mean. (<b>b</b>) Variance.</p> Full article ">
11 pages, 2762 KiB  
Article
Improvement in SNR by Adaptive Range Gates for RCS Measurements in the THz Region
by Shuang Pang, Yang Zeng, Qi Yang, Bin Deng, Hongqiang Wang and Yuliang Qin
Electronics 2019, 8(7), 805; https://doi.org/10.3390/electronics8070805 - 18 Jul 2019
Cited by 6 | Viewed by 3573
Abstract
One of the major concerns in radar cross-section (RCS) measurements is the isolation of the target echo from unwanted spurious signals. Generally, the method of software range gate is applied to extract useful data. However, this method may not work to expectations, especially [...] Read more.
One of the major concerns in radar cross-section (RCS) measurements is the isolation of the target echo from unwanted spurious signals. Generally, the method of software range gate is applied to extract useful data. However, this method may not work to expectations, especially for targets with a large length-width ratio. This is because the effective target zone is dependent on the aspect angle. The implementation of conventional fixed range gates will introduce an uneven clutter signal that leads to a decline in signal-to-noise ratio. The influence of this uneven clutter signal becomes increasingly severe in the terahertz band, where the wavelength is short and the illumination power is weak. In this work, the concept of adaptive range gates was adopted to extract a target echo of higher accuracy. The dimension of the range gate was determined by the angle-dependent radial projection of the target. In order to evaluate the performance of the proposed method, both experimental measurements and numerical simulations were conducted. Noticeable improvements in the signal-to-noise ratio at certain angles were observed. Full article
(This article belongs to the Special Issue Terahertz Technology and Its Applications)
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<p>Evolution of a typical step-frequency (SF) signal composed of <span class="html-italic">N</span> pulses. (<b>a</b>) The frequency of the pulses increases by step in time; (<b>b</b>) The model of signals generated by the programmable network analyzer (PNA).</p> Full article ">Figure 2
<p>Schematic of the adaptive range gate.</p> Full article ">Figure 3
<p>Comparison of two range gates at different azimuths. (<b>a</b>) Certain angles, (<b>b</b>) 0° to 360°.</p> Full article ">Figure 4
<p>The schematic diagram of the radar system.</p> Full article ">Figure 5
<p>The THz multiplier chains. (<b>a</b>) 220 GHz, (<b>b</b>) 440 GHz.</p> Full article ">Figure 6
<p>The THz radar cross-section (RCS) measurement scene. (<b>a</b>) The measurement system, (<b>b</b>) The cylinder.</p> Full article ">Figure 7
<p>The flowchart of the data extraction procedure to obtain the RCS of the target by the two range gate methods.</p> Full article ">Figure 8
<p>The azimuthal angle configuration of the measurement (<b>a</b>) and the range profiles at 0° and 90° in the time domain and the respective adaptive range gates. (<b>b</b>) 220 GHz, (<b>c</b>) 440 GHz.</p> Full article ">Figure 9
<p>RCS measurement results of a metallic cylinder. (<b>a</b>) 220 GHz, (<b>b</b>) 440 GHz.</p> Full article ">Figure 10
<p>Comparison of RCS difference under two circumstances. (<b>a</b>) The variation of RCS difference with the size of the adaptive range gate, (<b>b</b>) the variation of RCS difference with SNR.</p> Full article ">
11 pages, 8445 KiB  
Article
Prototyping of an All-pMOS-Based Cross-Coupled Voltage Multiplier in Single-Well CMOS Technology for Energy Harvesting Utilizing a Gastric Acid Battery
by Shinya Yoshida, Hiroshi Miyaguchi and Tsutomu Nakamura
Electronics 2019, 8(7), 804; https://doi.org/10.3390/electronics8070804 - 18 Jul 2019
Cited by 4 | Viewed by 3883
Abstract
A gastric acid battery and its charge storage in a capacitor are a simple and safe method to provide a power source to an ingestible device. For that method, the electromotive force of the battery should be boosted for storing a large amount [...] Read more.
A gastric acid battery and its charge storage in a capacitor are a simple and safe method to provide a power source to an ingestible device. For that method, the electromotive force of the battery should be boosted for storing a large amount of energy. In this study, we have proposed an all-p-channel metal-oxide semiconductor (pMOS)-based cross-coupled voltage multiplier (CCVM) utilizing single-well CMOS technology to achieve a voltage boosting higher than from a conventional complementary MOS (CMOS) CCVM. We prototyped a custom integrated circuit (IC) implemented with the above CCVMs and a ring oscillator as a clock source. The characterization experiment demonstrated that our proposed pMOS-based CCVM can boost the input voltage higher because it avoids the body effect problem resulting from an n-channel MOS transistor. This circuit was also demonstrated to significantly reduce the circuit area on the IC, which is advantageous as it reduces the chip size or provides an area for other functional circuits. This simple circuit structure based on mature and low-cost technologies matches well with disposal applications such as an ingestible device. We believe that this pMOS-based CCVM has the potential to become a useful energy harvesting circuit for ingestible devices. Full article
(This article belongs to the Special Issue Energy Efficient Circuit Design Techniques for Low Power Systems)
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<p>Schematic of an ingestible sensor system based on a stored charge as a power source utilizing a gastric acid battery via a voltage-boosting circuit.</p> Full article ">Figure 2
<p>Schematic of (<b>a</b>) a conventional CMOS-based CCVM and (<b>b</b>) an all-p-channel metal-oxide semiconductor (pMOS)-based CCVM.</p> Full article ">Figure 3
<p>Schematic of the (<b>a</b>) all-pMOS-based CCVM and (<b>b</b>) conventional CMOS-based CCVM with four stages. “P: W/L = 20/0.6 × 10” implies that 10 pMOS transistors with a gate width and length of 20 and 0.6 μm, respectively, are connected in parallel. The N-wells of the transistor, which are surrounded by dashed blue lines, are separated.</p> Full article ">Figure 4
<p>Schematic of the generation circuit of two-phase clocks using a ring oscillator circuit.</p> Full article ">Figure 5
<p>Layout schematic of the prototyped custom IC (0.6 μm/5 V CMOS process) for the energy harvesting of the gastric acid power generation.</p> Full article ">Figure 6
<p>Setup schematic of the characterization of the prototyped CCVMs.</p> Full article ">Figure 7
<p>Typical simulation result of the voltage-boosting behavior for each CCVM and dependency on the clock frequency when <span class="html-italic">V</span><sub>gen</sub> is set as 1.3 V. <span class="html-italic">V</span><sub>1</sub> to <span class="html-italic">V</span><sub>4</sub> correspond to the measured voltage of the intermediate or final storage capacitors at each stage, as shown in <a href="#electronics-08-00804-f003" class="html-fig">Figure 3</a>.</p> Full article ">Figure 8
<p>Measurement result of the transition of the boosted voltage at each capacitor in the prototyped circuits.</p> Full article ">Figure 9
<p>Dependence of the reached voltage (<span class="html-italic">V</span><sub>4_40s</sub>) at the fourth stage (<span class="html-italic">V</span><sub>4</sub>) on <span class="html-italic">V</span><sub>gen</sub> (0.85, 1.0, or 1.3 V) and clock frequency (100 Hz, 300 Hz, 1 kHz, 3 kHz, or 10 kHz). <span class="html-italic">V</span><sub>4_40s</sub> is defined as the <span class="html-italic">V</span><sub>4</sub> value at 40 s after the boosting process starts.</p> Full article ">Figure 10
<p>Dependence of the boosting quickness on <span class="html-italic">V</span><sub>gen</sub> and the frequency. The quickness is defined as the required time until 63.2% of <span class="html-italic">V</span><sub>4_40s</sub> is reached.</p> Full article ">Figure 11
<p>Dependency of (<b>a</b>) the frequency and (<b>b</b>) duty ratio of the ring oscillator circuit on the <span class="html-italic">V</span><sub>gen</sub> and <span class="html-italic">RC</span> parameters.</p> Full article ">Figure 12
<p>A pair of Mg–Pt electrodes with diameters of 2 mm as a gastric acid battery for the demonstration of energy harvesting via the CCVMs.</p> Full article ">Figure 13
<p>Voltage-boosting behavior at <span class="html-italic">V</span><sub>1</sub>–<span class="html-italic">V</span><sub>4</sub> for each CCVM in the Mg–Pt gastric acid battery dipped in an artificial gastric acid juice.</p> Full article ">
13 pages, 1194 KiB  
Article
Efficient Implementation of 2D and 3D Sparse Deconvolutional Neural Networks with a Uniform Architecture on FPGAs
by Deguang Wang, Junzhong Shen, Mei Wen and Chunyuan Zhang
Electronics 2019, 8(7), 803; https://doi.org/10.3390/electronics8070803 - 18 Jul 2019
Cited by 11 | Viewed by 3516
Abstract
Three-dimensional (3D) deconvolution is widely used in many computer vision applications. However, most previous works have only focused on accelerating two-dimensional (2D) deconvolutional neural networks (DCNNs) on Field-Programmable Gate Arrays (FPGAs), while the acceleration of 3D DCNNs has not been well studied in [...] Read more.
Three-dimensional (3D) deconvolution is widely used in many computer vision applications. However, most previous works have only focused on accelerating two-dimensional (2D) deconvolutional neural networks (DCNNs) on Field-Programmable Gate Arrays (FPGAs), while the acceleration of 3D DCNNs has not been well studied in depth as they have higher computational complexity and sparsity than 2D DCNNs. In this paper, we focus on the acceleration of both 2D and 3D sparse DCNNs on FPGAs by proposing efficient schemes for mapping 2D and 3D sparse DCNNs on a uniform architecture. Firstly, a pruning method is used to prune unimportant network connections and increase the sparsity of weights. After being pruned, the number of parameters of DCNNs is reduced significantly without accuracy loss. Secondly, the remaining non-zero weights are encoded in coordinate (COO) format, reducing the memory demands of parameters. Finally, to demonstrate the effectiveness of our work, we implement our accelerator design on the Xilinx VC709 evaluation platform for four real-life 2D and 3D DCNNs. After the first two steps, the storage required of DCNNs is reduced up to 3.9×. Results show that the performance of our method on the accelerator outperforms that of the our prior work by 2.5× to 3.6× in latency. Full article
(This article belongs to the Special Issue Convolutional Neural Network Design and Hardware Implementation for Real-Time Vision Applications)
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<p>Sparsity of the input feature maps in deconvolutional layers.</p> Full article ">Figure 2
<p>Three-step pruning pipeline.</p> Full article ">Figure 3
<p>Coordinate (COO) format illustration.</p> Full article ">Figure 4
<p>A real-life 2D DCNN model for image generation.</p> Full article ">Figure 5
<p>Illustration of the process of deconvolutions: (<b>a</b>) 2D deconvolutions; (<b>b</b>) 3D deconvolutions.</p> Full article ">Figure 6
<p>An overview of our proposed architecture.</p> Full article ">Figure 7
<p>Illustration of the 3D input oriented mapping (IOM) method.</p> Full article ">Figure 8
<p>Dataflow of the computation engine.</p> Full article ">Figure 9
<p>Overall sparsity of weights.</p> Full article ">Figure 10
<p>Processing elements (PE) utilization.</p> Full article ">Figure 11
<p>Performance comparison with our prior work [<a href="#B11-electronics-08-00803" class="html-bibr">11</a>].</p> Full article ">Figure 12
<p>Performance as a function of the sparsity of weights.</p> Full article ">
22 pages, 3791 KiB  
Article
A n-out-of-n Sharing Digital Image Scheme by Using Color Palette
by Ching-Nung Yang, Qin-Dong Sun, Yan-Xiao Liu and Ci-Ming Wu
Electronics 2019, 8(7), 802; https://doi.org/10.3390/electronics8070802 - 17 Jul 2019
Viewed by 3006
Abstract
A secret image sharing (SIS) scheme inserts a secret message into shadow images in a way that if shadow images are combined in a specific way, the secret image can be recovered. A 2-out-of-2 sharing digital image scheme (SDIS) adopts a color palette [...] Read more.
A secret image sharing (SIS) scheme inserts a secret message into shadow images in a way that if shadow images are combined in a specific way, the secret image can be recovered. A 2-out-of-2 sharing digital image scheme (SDIS) adopts a color palette to share a digital color secret image into two shadow images, and the secret image can be recovered from two shadow images, while any one shadow image has no information about the secret image. This 2-out-of-2 SDIS may keep the shadow size small because by using a color palette, and thus has advantage of reducing storage. However, the previous works on SDIS are just 2-out-of-2 scheme and have limited functions. In this paper, we take the lead to study a general n-out-of-n SDIS which can be applied on more than two shadow. The proposed SDIS is implemented on the basis of 2-out-of-2 SDIS. Our main contribution has the higher contrast of binary meaningful shadow and the larger region in color shadows revealing cover image when compared with previous 2-out-of-2 SDISs. Meanwhile, our SDIS is resistant to colluder attack. Full article
(This article belongs to the Special Issue Signal Processing and Analysis of Electrical Circuit)
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<p>Blocks of <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mo>,</mo> <mn>2</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS: (<b>a</b>) secret block <span class="html-italic">B</span>, shadow blocks <math display="inline"><semantics> <msup> <mi>B</mi> <mrow> <mo stretchy="false">(</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </msup> </semantics></math> and <math display="inline"><semantics> <msup> <mi>B</mi> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mo stretchy="false">)</mo> </mrow> </msup> </semantics></math> (<b>b</b>) diagrammatical representation of Wei et al.’s <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mo>,</mo> <mn>2</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS with binary meaningful shadows.</p> Full article ">Figure 2
<p>Shadows of the proposed <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mi>n</mi> <mo>,</mo> <mi>n</mi> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS: (<b>a</b>) using Wei et al.’s <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mo>,</mo> <mn>2</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS for <math display="inline"><semantics> <msup> <mi>B</mi> <mrow> <mo stretchy="false">(</mo> <msub> <mi>j</mi> <mn>1</mn> </msub> <mo stretchy="false">)</mo> </mrow> </msup> </semantics></math> and <math display="inline"><semantics> <msup> <mi>B</mi> <mrow> <mo stretchy="false">(</mo> <msub> <mi>j</mi> <mn>2</mn> </msub> <mo stretchy="false">)</mo> </mrow> </msup> </semantics></math> (<b>b</b>) using Yang et al.’s <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mo>,</mo> <mn>2</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS for <math display="inline"><semantics> <msup> <mi>B</mi> <mrow> <mo stretchy="false">(</mo> <msub> <mi>j</mi> <mn>1</mn> </msub> <mo stretchy="false">)</mo> </mrow> </msup> </semantics></math> and <math display="inline"><semantics> <msup> <mi>B</mi> <mrow> <mo stretchy="false">(</mo> <msub> <mi>j</mi> <mn>2</mn> </msub> <mo stretchy="false">)</mo> </mrow> </msup> </semantics></math>.</p> Full article ">Figure 3
<p>Block diagram of the proposed <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mi>n</mi> <mo>,</mo> <mi>n</mi> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS.</p> Full article ">Figure 4
<p>Blocks for sharing true clor image: (<b>a</b>) 25-bit <math display="inline"><semantics> <msub> <mi>B</mi> <mi>T</mi> </msub> </semantics></math> (<b>b</b>) 9-bit <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mi>r</mi> </msub> <mo>,</mo> <msub> <mi>B</mi> <mi>g</mi> </msub> <mo>,</mo> <msub> <mi>B</mi> <mrow> <mi>b</mi> <mi>l</mi> </mrow> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 5
<p>Block patterns: (<b>a</b>) a pixel with a color in <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>C</mi> <mi>I</mi> </mrow> </semantics></math> (<b>b</b>) the corresponding block <math display="inline"><semantics> <msup> <mi>B</mi> <mrow> <mo stretchy="false">(</mo> <mi>i</mi> <mo stretchy="false">)</mo> </mrow> </msup> </semantics></math> in <math display="inline"><semantics> <mrow> <mi>N</mi> <msub> <mi>S</mi> <mi>i</mi> </msub> </mrow> </semantics></math> (<b>c</b>) the corresponding <math display="inline"><semantics> <mrow> <mn>6</mn> <mi>B</mi> <mn>3</mn> <mi>W</mi> </mrow> </semantics></math> block in <math display="inline"><semantics> <mrow> <mi>N</mi> <msub> <mi>S</mi> <mi>i</mi> </msub> </mrow> </semantics></math> (<b>d</b>) the corresponding block in <math display="inline"><semantics> <mrow> <mi>C</mi> <msub> <mi>S</mi> <mi>i</mi> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 6
<p>Block patterns: (<b>a</b>) 9 color pixels with color <math display="inline"><semantics> <mrow> <msub> <mi>C</mi> <mn>1</mn> </msub> <mo>−</mo> <msub> <mi>C</mi> <mn>9</mn> </msub> </mrow> </semantics></math> in <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>C</mi> <msup> <mi>I</mi> <msup> <mrow/> <mo>′</mo> </msup> </msup> </mrow> </semantics></math> (<b>b</b>) the corresponding block <math display="inline"><semantics> <msup> <mi>B</mi> <mrow> <mo stretchy="false">(</mo> <mi>i</mi> <mo stretchy="false">)</mo> </mrow> </msup> </semantics></math> in <math display="inline"><semantics> <mrow> <mi>N</mi> <msub> <mi>S</mi> <mi>i</mi> </msub> </mrow> </semantics></math> (<b>c</b>) the corresponding color block in <math display="inline"><semantics> <mrow> <mi>C</mi> <msubsup> <mi>S</mi> <mrow> <mi>i</mi> </mrow> <msup> <mrow/> <mo>′</mo> </msup> </msubsup> </mrow> </semantics></math>.</p> Full article ">Figure 7
<p>Five color cover images with photos of birds: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>C</mi> <msub> <mi>I</mi> <mn>1</mn> </msub> </mrow> </semantics></math> (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>C</mi> <msub> <mi>I</mi> <mn>2</mn> </msub> </mrow> </semantics></math> (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>C</mi> <msub> <mi>I</mi> <mn>3</mn> </msub> </mrow> </semantics></math> (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>C</mi> <msub> <mi>I</mi> <mn>4</mn> </msub> </mrow> </semantics></math> (<b>e</b>) <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>C</mi> <msub> <mi>I</mi> <mn>5</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 8
<p>Five color cover images with photos of birds: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>C</mi> <msub> <mi>I</mi> <mn>1</mn> </msub> </mrow> </semantics></math> (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>C</mi> <msub> <mi>I</mi> <mn>2</mn> </msub> </mrow> </semantics></math> (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>C</mi> <msub> <mi>I</mi> <mn>3</mn> </msub> </mrow> </semantics></math> (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>C</mi> <msub> <mi>I</mi> <mn>4</mn> </msub> </mrow> </semantics></math> (<b>e</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>C</mi> <msub> <mi>I</mi> <mn>5</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 9
<p>Two secret images: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>S</mi> <msub> <mi>I</mi> <mn>1</mn> </msub> </mrow> </semantics></math>: 256-color Lena (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>S</mi> <msub> <mi>I</mi> <mn>2</mn> </msub> </mrow> </semantics></math>: true color Kaleidoscope.</p> Full article ">Figure 10
<p>Noise-like shadows of the proposed <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mn>3</mn> <mo>,</mo> <mn>3</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>N</mi> <msub> <mi>S</mi> <mn>1</mn> </msub> </mrow> </semantics></math> (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>N</mi> <msub> <mi>S</mi> <mn>2</mn> </msub> </mrow> </semantics></math> (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>N</mi> <msub> <mi>S</mi> <mn>3</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 11
<p>Binary meaningful shadows of the proposed <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mn>3</mn> <mo>,</mo> <mn>3</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>B</mi> <msub> <mi>S</mi> <mn>1</mn> </msub> </mrow> </semantics></math> (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>B</mi> <msub> <mi>S</mi> <mn>2</mn> </msub> </mrow> </semantics></math> (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>B</mi> <msub> <mi>S</mi> <mn>3</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 12
<p>Color meaningful shadows of the proposed <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mn>3</mn> <mo>,</mo> <mn>3</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <msub> <mi>S</mi> <mn>1</mn> </msub> </mrow> </semantics></math> (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <msub> <mi>S</mi> <mn>2</mn> </msub> </mrow> </semantics></math> (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <msub> <mi>S</mi> <mn>3</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 13
<p>Color meaningful shadows of the proposed <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mn>3</mn> <mo>,</mo> <mn>3</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS sharing a true color secret image: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <msub> <mi>S</mi> <mn>1</mn> </msub> </mrow> </semantics></math> (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <msub> <mi>S</mi> <mn>2</mn> </msub> </mrow> </semantics></math> (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <msub> <mi>S</mi> <mn>3</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 14
<p>Binary snd color meaningful shadows of the proposed: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>B</mi> <msub> <mi>S</mi> <mn>1</mn> </msub> <mo>–</mo> <mi>B</mi> <msub> <mi>S</mi> <mn>4</mn> </msub> </mrow> </semantics></math> (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <msub> <mi>S</mi> <mn>1</mn> </msub> <mo>–</mo> <mi>C</mi> <msub> <mi>S</mi> <mn>4</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 15
<p>Binary snd color meaningful shadows of the proposed: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>B</mi> <msub> <mi>S</mi> <mn>1</mn> </msub> <mo>–</mo> <mi>B</mi> <msub> <mi>S</mi> <mn>5</mn> </msub> </mrow> </semantics></math> (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <msub> <mi>S</mi> <mn>1</mn> </msub> <mo>–</mo> <mi>C</mi> <msub> <mi>S</mi> <mn>5</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 16
<p>Color meaningful shadows of <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mn>3</mn> <mo>,</mo> <mn>3</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS by the approach of enhancing visual quality: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <msubsup> <mi>S</mi> <mn>1</mn> <msup> <mrow/> <mo>′</mo> </msup> </msubsup> </mrow> </semantics></math> (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <msubsup> <mi>S</mi> <mn>2</mn> <msup> <mrow/> <mo>′</mo> </msup> </msubsup> </mrow> </semantics></math> (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>C</mi> <msubsup> <mi>S</mi> <mrow> <mn>3</mn> </mrow> <msup> <mrow/> <mo>′</mo> </msup> </msubsup> </mrow> </semantics></math>.</p> Full article ">Figure 17
<p>Color meaningful shadows and enlarged parts of cropped image area for <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mn>3</mn> <mo>,</mo> <mn>3</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS: (<b>a</b>) using the original method (<b>b</b>) using the approach of enhancing visual quality.</p> Full article ">Figure 18
<p>The proposed <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mn>5</mn> <mo>,</mo> <mn>5</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-SDIS using <math display="inline"><semantics> <mrow> <mn>8</mn> <mi>B</mi> <mn>1</mn> <mi>W</mi> </mrow> </semantics></math> block (<b>a</b>) five color meaningful shadows (<b>b</b>) 256-color <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>I</mi> </mrow> </semantics></math> and its corresponding <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>P</mi> </mrow> </semantics></math> (<b>c</b>) the recovered 256-color <math display="inline"><semantics> <mrow> <mi>S</mi> <msup> <mi>I</mi> <mn>1</mn> </msup> </mrow> </semantics></math> and color palette <math display="inline"><semantics> <mrow> <mi>C</mi> <msup> <mi>P</mi> <msup> <mrow/> <mo>′</mo> </msup> </msup> </mrow> </semantics></math> under <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mi>n</mi> <mo>−</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>-colluder attack.</p> Full article ">
25 pages, 6365 KiB  
Article
An Intelligent Air Quality Sensing System for Open-Skin Wound Monitoring
by Hina Sattar, Imran Sarwar Bajwa and Umar Farooq Shafi
Electronics 2019, 8(7), 801; https://doi.org/10.3390/electronics8070801 - 17 Jul 2019
Cited by 6 | Viewed by 5353
Abstract
There are many factors that may have a significant effect on the skin wound healing process. The environment is one of them. Although different previous research woks have highlighted the role of environmental elements such as humidity, temperature, dust, etc., in the process [...] Read more.
There are many factors that may have a significant effect on the skin wound healing process. The environment is one of them. Although different previous research woks have highlighted the role of environmental elements such as humidity, temperature, dust, etc., in the process of skin wound healing, there is no predefined method available to identify the favourable or adverse environment conditions that seriously affect (positively or negatively) the skin wound healing process. In the current research work, an IoT-based approach is used to design an AQSS (Air Quality Sensing System) using sensors for the acquisition of real-time environment data, and the SVM (Support Vector Machine) classifier is applied to classify environments into one of the two categories, i.e., “favourable”, and “unfavourable”. The proposed system is also supported with an Android application to provide an easy-to-use interface. The proposed system provides an easy and simple means for patients to evaluate the environmental parameters and monitor their effects in the process of open skin wound healing. Full article
(This article belongs to the Special Issue Internet of Things (IoT)-Based Wireless Health: Enabling Technologies and Applications)
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<p>(<b>A</b>) Skin open wound abrasion. (<b>B</b>) Skin open wound avulsion. (<b>C</b>) Skin open wound laceration. (<b>D</b>) Skin open wound puncture.</p> Full article ">Figure 2
<p>Environmental classification model.</p> Full article ">Figure 3
<p>Phases of the proposed model. AQSS, Air Quality Sensing System.</p> Full article ">Figure 4
<p>AQSS circuit design.</p> Full article ">Figure 5
<p>Phases of the proposed model.</p> Full article ">Figure 6
<p>Training steps of the proposed SVM.</p> Full article ">Figure 7
<p>Trained SVM.</p> Full article ">Figure 8
<p>Scatter plot between temperature and humidity.</p> Full article ">Figure 9
<p>Scatter plot between air quality and humidity.</p> Full article ">Figure 10
<p>Scatter plot between dust particles and humidity.</p> Full article ">Figure 11
<p>Scatter plot between dust particles and air quality.</p> Full article ">Figure 12
<p>ROC curve.</p> Full article ">Figure 13
<p>Confusion matrix.</p> Full article ">Figure 14
<p>SVM predicted class types.</p> Full article ">Figure 15
<p>SVM classifier prediction evaluation chart.</p> Full article ">Figure A1
<p>Arduino UNO microcontroller.</p> Full article ">Figure A2
<p>DHT11 humidity and temperature sensor.</p> Full article ">Figure A3
<p>Gas sensor.</p> Full article ">Figure A4
<p>Optical dust sensor.</p> Full article ">
21 pages, 5515 KiB  
Article
Effectiveness Assessment of a Nanocrystalline Sleeve Ferrite Core Compared with Ceramic Cores for Reducing Conducted EMI
by Adrian Suarez, Jorge Victoria, Jose Torres, Pedro A. Martinez, Antonio Alcarria, Julio Martos, Raimundo Garcia-Olcina, Jesus Soret, Steffen Muetsch and Alexander Gerfer
Electronics 2019, 8(7), 800; https://doi.org/10.3390/electronics8070800 - 17 Jul 2019
Cited by 13 | Viewed by 6612
Abstract
The interconnection of different electronic devices or systems through cables is becoming more difficult due to the hard restrictions related to electromagnetic compatibility (EMC) in order to comply with requirements. Therefore, the use of EMC components is a good solution to manage the [...] Read more.
The interconnection of different electronic devices or systems through cables is becoming more difficult due to the hard restrictions related to electromagnetic compatibility (EMC) in order to comply with requirements. Therefore, the use of EMC components is a good solution to manage the problems associated with the filtering of electromagnetic interference (EMI) in cables and to pass the compliance test. In this sense, sleeve ferrite cores become a very interesting solution since they can be set around a wire and, hence, they provide an effective solution against EMI without having to redesign the electronic circuit. This contribution is focused on the characterization of the performance of a sleeve ferrite core based on a novel nanocrystalline (NC) novel material for EMI suppression and comparing it to the most conventional ceramic ferrite cores such as MnZn and NiZn. The research highlights the suitability of an NC novel component in terms of its magnetic properties to reduce EMI within the conducted emissions range. This range is generally defined by the International Special Committee on Radio Interference (CISPR) test standards frequency band that covers from 150 kHz up to 30 MHz (108 MHz in the case of CISPR 25). First, this study presents a description of the main parameters that define the behavior of NC and ceramic cores and, secondly, by analyzing the data obtained from experimental procedures, it is possible to directly determine the insertion loss parameter. Hence, this characterization procedure is used to obtain the performance of NC material compared to the conventional sleeve ferrite core compositions employed to filter the interferences in this problematic frequency range. As can be deduced from the results obtained, an NC sleeve ferrite core provides the best performance in terms of EMI filtering within a significant frequency range between 100 kHz and 100 MHz. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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<p>Diagram of common mode (CM) and differential mode (DM) currents passing through a ferrite core.</p> Full article ">Figure 2
<p>Relative Permeability of nanocrystalline (NC) compared with MnZn and NiZn sleeve ferrite cores compositions.</p> Full article ">Figure 3
<p>Complex relative permeability split into real and imaginary components: (<b>a</b>) NC sleeve ferrite core; (<b>b</b>) MnZn sleeve ferrite core; (<b>c</b>) NiZn sleeve ferrite core.</p> Full article ">Figure 3 Cont.
<p>Complex relative permeability split into real and imaginary components: (<b>a</b>) NC sleeve ferrite core; (<b>b</b>) MnZn sleeve ferrite core; (<b>c</b>) NiZn sleeve ferrite core.</p> Full article ">Figure 4
<p>Vector relationship between <math display="inline"><semantics> <mrow> <msub> <mo>µ</mo> <mi>r</mi> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <msup> <mo>µ</mo> <mo>″</mo> </msup> </semantics></math>, and <math display="inline"><semantics> <msup> <mo>µ</mo> <mo>″</mo> </msup> </semantics></math> (<b>left</b>); vector relationship between Z<sub>F</sub>, R and X<sub>L</sub> (2πfL) (<b>right</b>).</p> Full article ">Figure 5
<p>Simplified sleeve ferrite core equivalent circuit.</p> Full article ">Figure 6
<p>Magnitude of the impedance of the AWG26 (American Wire Gauge) wires used to measure the impedance of the sleeve ferrite cores.</p> Full article ">Figure 7
<p>Impedance measurements of the NC, MnZn and NiZn sleeve ferrites winding around them 1 turn: (<b>a</b>) Magnitude impedance of three cable ferrites; (<b>b</b>) NC R and X<sub>L</sub> impedance components; (<b>c</b>) MnZn R and X<sub>L</sub> impedance components; and, (<b>d</b>) NiZn R and X<sub>L</sub> impedance components.</p> Full article ">Figure 8
<p>Impedance measurements of the NC, MnZn and NiZn sleeve ferrites after winding around them by two turns: (<b>a</b>) Magnitude impedance of three cable ferrites; (<b>b</b>) NC R and X<sub>L</sub> impedance components; (<b>c</b>) MnZn R and X<sub>L</sub> impedance components; (<b>d</b>) NiZn R and X<sub>L</sub> impedance components.</p> Full article ">Figure 9
<p>Comparison of the magnitude impedance and angle phase of X<sub>L</sub>/R of the NC sleeve ferrite core compared to MnZn and NiZn by winding around them one and two turns: (<b>a</b>) NC sleeve ferrite core; (<b>b</b>) MnZn sleeve ferrite core; (<b>c</b>) NiZn sleeve ferrite core.</p> Full article ">Figure 10
<p>Diagram of source and load equivalents circuits used to determine the insertion loss parameter of a sleeve ferrite core when it is introduced into a system.</p> Full article ">Figure 11
<p>Experimental measurement setup for characterizing NC and ceramic sleeve ferrite cores in terms of decibels.</p> Full article ">Figure 12
<p>Comparison of the impedance obtained from three different procedures considering one and two turns wound around the sleeve ferrite core: measuring it directly, mathematically from the relative permeability and extracted from the experimental insertion loss. (<b>a</b>) NC sleeve ferrite core; (<b>b</b>) MnZn sleeve ferrite core; and, (<b>c</b>) NiZn sleeve ferrite core.</p> Full article ">Figure 12 Cont.
<p>Comparison of the impedance obtained from three different procedures considering one and two turns wound around the sleeve ferrite core: measuring it directly, mathematically from the relative permeability and extracted from the experimental insertion loss. (<b>a</b>) NC sleeve ferrite core; (<b>b</b>) MnZn sleeve ferrite core; and, (<b>c</b>) NiZn sleeve ferrite core.</p> Full article ">Figure 13
<p>Comparison of the experimental insertion loss determined for NC, MnZn and NiZn sleeve ferrite cores by winding one turn.</p> Full article ">Figure 14
<p>Comparison of the experimental insertion loss determined for NC, MnZn and NiZn sleeve ferrite cores by winding two turns.</p> Full article ">Figure 15
<p>Extrapolation of the measured insertion loss for systems with an impedance of 100 Ω and 10 Ω, considering one turn for NC, MnZn and NiZn sleeve ferrite cores.</p> Full article ">
18 pages, 6177 KiB  
Article
Model-Based Optimization of an LLC-Resonant DC-DC Converter
by Nikolay Hinov, Bogdan Gilev and Tsveti Hranov
Electronics 2019, 8(7), 799; https://doi.org/10.3390/electronics8070799 - 17 Jul 2019
Cited by 6 | Viewed by 3611
Abstract
The study presented in the paper is to guarantee the performance of the LLC DC-DC converter using model-based optimization. The primary scope of the study is to maintain the output parameters regardless of the variation of the values of the circuit elements. In [...] Read more.
The study presented in the paper is to guarantee the performance of the LLC DC-DC converter using model-based optimization. The primary scope of the study is to maintain the output parameters regardless of the variation of the values of the circuit elements. In engineering practice, it is known that any schematic element cannot be reproduced with an absolute accuracy of features. In addition, its main parameters change during operation due to changes in operating temperature, aging, operating modes and so on. Optimization procedures are a tool for finding the most appropriate values for circuit elements, with selected constraints, target functions and operating modes. In electronic converters, these are most often: minimal loss, maximum efficiency, the critical-aperiodic transition process, realization of certain dynamics, appropriate modes of operation and so on. The results obtained show that using the proposed approach produces more robustness to disturbances and tolerances, with improved dynamics and faster transient processes. On the other hand, the value of the circuit elements is smaller, and reliable operation of the protection and automatic regulation systems is achieved. Full article
(This article belongs to the Section Power Electronics)
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<p>LLC DC-DC resonant converter with split capacitor.</p> Full article ">Figure 2
<p>Measurements at five operating regimes, collected with a digital signal oscilloscope.</p> Full article ">Figure 3
<p>Waveforms of conducted simulations with the mathematical model.</p> Full article ">Figure 4
<p>Tolerance analysis of the average output voltage.</p> Full article ">Figure 5
<p>Tolerance analysis of the output voltage ripple.</p> Full article ">Figure 6
<p>Tolerance analysis of the resonant current.</p> Full article ">Figure 7
<p>Tolerance analysis of the maximum capacitor voltage.</p> Full article ">Figure 8
<p>Tolerance analysis of the transient response of the output voltage.</p> Full article ">Figure 9
<p>Tolerance analysis of the transient response of the resonant capacitor voltage.</p> Full article ">Figure 10
<p>Optimization procedures for the output capacitor value.</p> Full article ">Figure 11
<p>Optimization procedures of the resonant tank circuit elements.</p> Full article ">Figure 12
<p>Tolerance analysis of the average output voltage with optimized values.</p> Full article ">Figure 13
<p>Tolerance analysis of the output voltage ripple with optimized values.</p> Full article ">Figure 14
<p>Tolerance analysis of the resonant current with optimized values.</p> Full article ">Figure 15
<p>Tolerance analysis of the resonant capacitor voltage with optimized values.</p> Full article ">Figure 16
<p>Tolerance analysis of the transient response of the output voltage with optimized values.</p> Full article ">Figure 17
<p>Tolerance analysis of the transient response of the resonant capacitor voltage with optimized values.</p> Full article ">Figure 18
<p>Block diagram of the converter model and the embedded Simulink Response Optimization tool.</p> Full article ">Figure 19
<p>Tolerance analysis results with optimization, conducted with Simulink Response Optimization.</p> Full article ">
17 pages, 7370 KiB  
Article
Single-Switch LED Post-Regulator Based on a Modified Class-E Resonant Converter with Voltage Clamp
by Javier Ribas, Pablo J. Quintana, Jesus Cardesin, Antonio J. Calleja and Emilio Lopez-Corominas
Electronics 2019, 8(7), 798; https://doi.org/10.3390/electronics8070798 - 16 Jul 2019
Cited by 4 | Viewed by 3560
Abstract
The strict restrictions imposed both by mandatory regulations and by the recommendations contained in current standards have led to the fact that most commercially available LED ballasts nowadays use two-stage topologies. The first stage is intended to comply with the harmonics standards and [...] Read more.
The strict restrictions imposed both by mandatory regulations and by the recommendations contained in current standards have led to the fact that most commercially available LED ballasts nowadays use two-stage topologies. The first stage is intended to comply with the harmonics standards and the second stage is used to control the LED current and reduce the low frequency ripple. In this work, a new DC–DC resonant converter topology is presented. This topology is derived from a modified Class-E resonant inverter by adding a clamping diode. This diode achieves a double goal: it limits the maximum switch voltage and works as a power recirculating path. This way, the proposed topology behaves as a loss-less impedance placed in series with the LED thus allowing to control the output power. This converter maintains the extremely small switching losses inherent to the Class-E inverter while reducing the voltage stress across the switch. This work presents a simplified design methodology based on the fundamental approach. This methodology was used to design and build a DC–DC post-regulator for a 40 W LED lamp. The results obtained with the laboratory prototype show that this circuit can be used to stabilize and dim the LED current while maintaining very small losses. The measured efficiency was 95.7% at nominal power and above 90% when dimmed down to 25%. Full article
(This article belongs to the Special Issue Latest Developments in LED Drivers)
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Figure 1
<p>Operation of the series current regulator.</p> Full article ">Figure 2
<p>Schematics of the proposed topology.</p> Full article ">Figure 3
<p>Basic waveforms of the proposed series regulator.</p> Full article ">Figure 4
<p>Detail of the operation of the proposed circuit.</p> Full article ">Figure 5
<p>Variation of the angles <span class="html-italic">α</span>, <span class="html-italic">β</span>, <span class="html-italic">asin</span>(<span class="html-italic">q</span>), <span class="html-italic">γ</span> y <span class="html-italic">γ<sub>max</sub></span> as a function of <span class="html-italic">q</span> for different <span class="html-italic">ĸ</span> values: (<b>a</b>) <span class="html-italic">ĸ</span> equal to 1.2; (<b>b</b>) <span class="html-italic">ĸ</span> equal to 1.4; (<b>c</b>) <span class="html-italic">ĸ</span> equal to 1.6; (<b>d</b>) <span class="html-italic">ĸ</span> equal to 1.8; and (<b>e</b>) <span class="html-italic">ĸ</span> equal to 2.0.</p> Full article ">Figure 6
<p>Ratio between the amplitudes of the second harmonic and the fundamental component of <span class="html-italic">i<sub>res</sub></span>.</p> Full article ">Figure 7
<p>Small-signal output power static sensitivity as a function of <span class="html-italic">q</span> for <span class="html-italic">ν</span> equal to 1.5: (<b>a</b>) Against changes in the input voltage; (<b>b</b>) Against changes in the LED voltage; (<b>c</b>) Against changes in the operating frequency.</p> Full article ">Figure 8
<p>Simplified schematics of the control circuit.</p> Full article ">Figure 9
<p>Feedforward control response with <span class="html-italic">V<sub>B</sub></span> and <span class="html-italic">V<sub>LED</sub></span> combined.</p> Full article ">Figure 10
<p>Converter waveforms at nominal operating point.</p> Full article ">Figure 11
<p>Converter waveforms for <span class="html-italic">ĸ</span> = 2, <span class="html-italic">V<sub>B</sub></span> = 138 V and P = 6.1 W.</p> Full article ">Figure 12
<p>Converter measured efficiency <span class="html-italic">η</span> and <span class="html-italic">ĸ</span> value as a function of the output power for three different bus voltages.</p> Full article ">Figure 13
<p>Converter waveforms with a 16 V, 100 Hz ripple in <span class="html-italic">V<sub>B</sub></span> with feedforward control disabled.</p> Full article ">Figure 14
<p>Converter waveforms with a 16 V, 100 Hz ripple in <span class="html-italic">V<sub>B</sub></span> with feedforward control enabled.</p> Full article ">
18 pages, 3542 KiB  
Article
Near-Field Immunity Test Method for Fast Radiated Immunity Test Debugging of Automotive Electronics
by Jawad Yousaf, Doojin Lee, JunHee Han, Hosang Lee, Muhammad Faisal, Jeongeun Kim and Wansoo Nah
Electronics 2019, 8(7), 797; https://doi.org/10.3390/electronics8070797 - 16 Jul 2019
Cited by 2 | Viewed by 4948
Abstract
This study presents a near-field immunity test (NFIT) method for the fast debugging of radiated susceptibility of industrial devices. The proposed approach is based on the development of an NFIT setup which comprises of developed near-field electric and magnetic field probes and device [...] Read more.
This study presents a near-field immunity test (NFIT) method for the fast debugging of radiated susceptibility of industrial devices. The proposed approach is based on the development of an NFIT setup which comprises of developed near-field electric and magnetic field probes and device under test (DUT). The developed small-size and handy near-field testing probes inject the high electric (up to 1000 V/m) and magnetic (up to 2.4 A/m) fields on the DUT in the radar pulse ranges (1.2 to 1.4 GHz and 2.7 to 3.1 GHz) with the lower fed input power (up to 15 W) from the power amplifier in the developed NFIT setup. The proof of concept is validated with the successful near-field immunity debugging of an electric power steering (EPS) device used in the automotive industry with the developed NFIT setup. The radiated susceptibility debugging test results of developed NFIT method and conventional method of ISO 11452-2 test setup turned out to be close to each other for the tested DUT in immunity performance. The proposed procedure has advantages of industry usefulness with fast, handy, and cost-effective radiated immunity debugging of the DUT without the requirement of large antenna, high-power amplifiers, optical DUT connecting harness, and an anechoic chamber as needed in ISO 11452-2 standard setup for the debugging analysis. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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Figure 1
<p>ISO 11452-2 far-field radiated immunity test setup for frequencies above 1 GHz [<a href="#B11-electronics-08-00797" class="html-bibr">11</a>].</p> Full article ">Figure 2
<p>Proposed near-field immunity test (NFIT) setup for fast radiated immunity debugging of DUT.</p> Full article ">Figure 3
<p>Flow chart used for the verification of the proposed NFIT setup.</p> Full article ">Figure 4
<p>Design of proposed E-field probe (L-fed circular patch antenna): (<b>a</b>) Geometry and design parameters; (<b>b</b>) Photograph of the fabricated E-field probe for 1.2–1.4 GHz range (1st E-probe); and (<b>c</b>) Photograph of the fabricated E-field probe for 2.7–3.1 GHz range (2nd E-probe).</p> Full article ">Figure 5
<p>Simulation setup for NFIT method: (<b>a</b>) Schematic design; and (<b>b</b>) HFSS simulation setup with designed E-field probes.</p> Full article ">Figure 6
<p>Simulated E-field distribution with input power of 12 W (<b>a</b>) L-probe antenna for 1.2–1.4 GHz at the center frequency of 1.3 GHz (1st E-probe); and (<b>b</b>) L-probe antenna for 2.7–3.1 GHz at the center frequency of 2.9 GHz (2nd E-probe).</p> Full article ">Figure 7
<p>Simulated E-field intensity on the metal surface at the center cross section of the steel plate with input power of 12 W (<b>a</b>) L-probe antenna for 1.2–1.4 GHz range (1st E-probe); and (<b>b</b>) L-probe antenna for 2.7–3.1 GHz range (2nd E-probe).</p> Full article ">Figure 8
<p>Comparison of the measured and simulated <span class="html-italic">S</span>-parameters: (<b>a</b>) Experiment setup for the <span class="html-italic">S</span>-parameters measurements; (<b>b</b>) <span class="html-italic">S</span>-parameters of L-probe antenna for 1.2–1.4 GHz (1st E-probe); and (<b>c</b>) <span class="html-italic">S</span>-parameters of L-probe antenna for 2.7–3.1GHz (2nd E-probe).</p> Full article ">Figure 9
<p>Designed magnetic field probe: (<b>a</b>) Top view; (<b>b</b>) Bottom view; and (<b>c</b>) 3D view (<math display="inline"><semantics> <msub> <mi>L</mi> <mn>1</mn> </msub> </semantics></math> = 80 mm, <math display="inline"><semantics> <msub> <mi>L</mi> <mn>2</mn> </msub> </semantics></math> = 18 mm, <math display="inline"><semantics> <msub> <mi>L</mi> <mn>3</mn> </msub> </semantics></math> = 12 mm, <math display="inline"><semantics> <msub> <mi>L</mi> <mn>4</mn> </msub> </semantics></math> = 50 mm, <math display="inline"><semantics> <msub> <mi>L</mi> <mn>5</mn> </msub> </semantics></math> = 45 mm, <math display="inline"><semantics> <msub> <mi>W</mi> <mn>1</mn> </msub> </semantics></math> = 80 mm, <math display="inline"><semantics> <msub> <mi>W</mi> <mn>2</mn> </msub> </semantics></math> = 33 mm, <math display="inline"><semantics> <msub> <mi>W</mi> <mn>3</mn> </msub> </semantics></math> = 23 mm, <math display="inline"><semantics> <msub> <mi>W</mi> <mn>4</mn> </msub> </semantics></math> = 15 mm, <math display="inline"><semantics> <msub> <mi>W</mi> <mn>5</mn> </msub> </semantics></math> = 3 mm, <math display="inline"><semantics> <msub> <mi>W</mi> <mn>6</mn> </msub> </semantics></math> = 38 mm, <math display="inline"><semantics> <msub> <mi>W</mi> <mn>7</mn> </msub> </semantics></math> = 37.4 mm, and <span class="html-italic">t</span> = 1.53 mm).</p> Full article ">Figure 10
<p>HFSS simulation setup of magnetic field probe with <span class="html-italic">d</span> = 5 cm.</p> Full article ">Figure 11
<p>Simulated H-field distribution with input power of 15 W (<b>a</b>) H-field probe for 1.2–1.4 GHz at the center frequency of 1.3 GHz, (<b>b</b>) H-field probe for 2.7–3.1 GHz at the center frequency of 2.9 GHz.</p> Full article ">Figure 12
<p>Simulated H-field intensity on the metal surface at the center cross section of the steel plate with input power of 15 W (<b>a</b>) Field levels for 1.2–1.4 GHz range, (<b>b</b>) Field levels for 2.7–3.1 GHz range.</p> Full article ">Figure 13
<p>Fabricated H-field probe and <span class="html-italic">S</span>-parameter results: (<b>a</b>) Photograph of manufactured probe; (<b>b</b>) Picture of measurement setup for the <span class="html-italic">S</span>-parameter measurements of designed H-field probe; and (<b>c</b>) Comparison of simulated and measured <span class="html-italic">S</span>-parameters.</p> Full article ">Figure 14
<p>Steering system of a typical modern era vehicle [<a href="#B34-electronics-08-00797" class="html-bibr">34</a>].</p> Full article ">Figure 15
<p>A typical temperature monitoring IC of EPS.</p> Full article ">Figure 16
<p>NFIT setup for the RI debugging of a specific automotive industry electronic DUT (EPS) (<b>a</b>) Complete laboratory bench test description of the proposed NFIT RI setup; (<b>b</b>) Photograph of the E-field probe and DUT (probe is 50 mm away from DUT); and (<b>c</b>) Photograph of the H-field probe and DUT (probe is 50 mm away from DUT).</p> Full article ">Figure 17
<p>Performed NFIT RI results for a specific automotive industry electronic DUT with E-field probe (see <a href="#electronics-08-00797-f016" class="html-fig">Figure 16</a>b): (<b>a</b>) Induced voltage in PCB with near-field E-probe driven by 12 W input power (error debugging); and (<b>b</b>) Induced voltage in PCB after circuit modification (error rectification) with near-field E-probe is driven by same 12 W input power.</p> Full article ">Figure 18
<p>Performed NFIT RI results for a specific automotive industry electronic DUT with H-field probe (see <a href="#electronics-08-00797-f016" class="html-fig">Figure 16</a>b): (<b>a</b>) Induced voltage in PCB with near-field H-field probe driven by 15 W input power (error debugging); and (<b>b</b>) Induced voltage in PCB after circuit modification (error rectification) with H-field probe driven by same 15 W input power.</p> Full article ">
26 pages, 5540 KiB  
Article
Maximum Transmit Power for UE in an LTE Small Cell Uplink
by Amir Haider and Seung-Hoon Hwang
Electronics 2019, 8(7), 796; https://doi.org/10.3390/electronics8070796 - 16 Jul 2019
Cited by 15 | Viewed by 9810
Abstract
To furnish the network with small cells, it is vital to consider parameters like cell size, interference in the network, and deployment strategies to maximize the network’s performance gains expected from small cells. With a small cell network, it is critical to analyze [...] Read more.
To furnish the network with small cells, it is vital to consider parameters like cell size, interference in the network, and deployment strategies to maximize the network’s performance gains expected from small cells. With a small cell network, it is critical to analyze the impact of the uplink power control parameters on the network’s performance. In particular, the maximum transmit power (Pmax) for user equipment (UE) needs to be revisited for small cells, since it is a major contributor towards interference. In this work, the network performance was evaluated for different Pmax values for the small cell uplink. Various deployment scenarios for furnishing the existing macro layer in LTE networks with small cells were considered. The Pmax limit for a small cell uplink was evaluated for both homogenous small cell and heterogeneous networks (HetNet). The numerical results showed that it would be appropriate to adopt Pmax = 18 dBm in uniformly distributed small cells rather than Pmax = 23 dBm, as in macro environments. The choice of Pmax = 18 dBm was further validated for three HetNet deployment scenarios. A decrease of 0.52 dBm and an increase of 0.03 dBm and 3.29 dBm in the proposed Pmax = 18 dBm were observed for the three HetNet deployments, respectively. Furthermore, we propose that the fractional power control mode can be employed instead of the full compensation mode in small cell uplinks. Full article
(This article belongs to the Special Issue Recent Technical Developments in Energy-Efficient 5G Mobile Cells)
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<p>Fluid model for uniformly distributed cells. Zoomed view shows a uniform UE distribution in each cell.</p> Full article ">Figure 2
<p>HetNet scenario for uniformly distributed small cells within a macro cell.</p> Full article ">Figure 3
<p>HetNet scenario for deployment of small cells near the macro cell eNodeB.</p> Full article ">Figure 4
<p>HetNet scenario for deployment of macro cells near the edge of the macro cell.</p> Full article ">Figure 5
<p>SIR as a function of <span class="html-italic">α</span><sub>macro</sub> in the homogenous macro cell deployment.</p> Full article ">Figure 6
<p>Outage probability as a function of SIR for the UE at the cell edge.</p> Full article ">Figure 7
<p>SIR as a function of <span class="html-italic">α</span><sub>small</sub> in the homogenous small cell deployment.</p> Full article ">Figure 8
<p>Interference comparison as a function of <span class="html-italic">P</span><sub>max</sub> in the uniform macro and small cell deployments.</p> Full article ">Figure 9
<p>SIR as a function of <span class="html-italic">α</span><sub>small</sub> in the homogenous small cell deployment.</p> Full article ">Figure 10
<p>Spectral efficiency for small cells as a function of distance and <span class="html-italic">α</span><sub>small</sub> in homogenous small cell deployment.</p> Full article ">Figure 11
<p>Interference comparison as a function of <span class="html-italic">P</span><sub>max</sub> in the uniform macro cell and HetNet deployments.</p> Full article ">Figure 12
<p>SIR as a function of <span class="html-italic">α</span><sub>small</sub> in the HetNet deployment.</p> Full article ">Figure 13
<p>Spectral efficiency for the small cell as a function of distance and <span class="html-italic">α</span><sub>small</sub> in the HetNet deployment with uniformly distributed small cells.</p> Full article ">Figure 14
<p>Interference comparison as a function of <span class="html-italic">P</span><sub>max</sub> in the uniform macro cell and HetNet deployments.</p> Full article ">Figure 15
<p>SIR as a function of <span class="html-italic">α</span><sub>small</sub> in the HetNet deployment.</p> Full article ">Figure 16
<p>Spectral efficiency for the small cell as a function of distance and <span class="html-italic">α</span><sub>small</sub> in the HetNet deployment with small cells near the macro cell eNodeB.</p> Full article ">Figure 17
<p>Interference comparison as a function of <span class="html-italic">P</span><sub>max</sub> in the uniform macro cell and HetNet deployments.</p> Full article ">Figure 18
<p>SIR as a function of <span class="html-italic">α</span><sub>small</sub> in the HetNet deployment.</p> Full article ">Figure 19
<p>Spectral efficiency for the small cell as a function of distance and <span class="html-italic">α</span><sub>small</sub> in the HetNet deployment with small cells near the macro cell edge.</p> Full article ">
12 pages, 3996 KiB  
Article
A Multi-Inductor H Bridge Fault Current Limiter
by Amir Heidary, Hamid Radmanesh, Ali Moghim, Kamran Ghorbanyan, Kumars Rouzbehi, Eduardo M. G. Rodrigues and Edris Pouresmaeil
Electronics 2019, 8(7), 795; https://doi.org/10.3390/electronics8070795 - 16 Jul 2019
Cited by 16 | Viewed by 4019
Abstract
Current power systems will suffer from increasing pressure as a result of an upsurge in demand and will experience an ever-growing penetration of distributed power generation, which are factors that will contribute to a higher of incidence fault current levels. Fault current limiters [...] Read more.
Current power systems will suffer from increasing pressure as a result of an upsurge in demand and will experience an ever-growing penetration of distributed power generation, which are factors that will contribute to a higher of incidence fault current levels. Fault current limiters (FCLs) are key power electronic devices. They are able to limit the prospective fault current without completely disconnecting in cases in which a fault occurs, for instance, in a power transmission grid. This paper proposes a new type of FCL capable of fault current limiting in two steps. In this way, the FCLs’ power electronic switches experience significantly less stress and their overall performance will significantly increase. The proposed device is essentially a controllable H bridge type fault current limiter (HBFCL) that is comprised of two variable inductances, which operate to reduce current of main switch in the first stage of current limiting. In the next step, the main switch can limit the fault current while it becomes open. Simulation studies are carried out using MATLAB and its prototype setup is built and tested. The comparison of experimental and simulation results indicates that the proposed HBFCL is a promising solution to address protection issues. Full article
(This article belongs to the Special Issue Industrial Applications of Power Electronics)
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<p>Proposed H bridge type fault current limiter (HBFCL) topology.</p> Full article ">Figure 2
<p>HBFCL equivalent circuit. (<b>a</b>) Normal operation mode, (<b>b</b>) fault operation mode in first state, and (<b>c</b>) fault operation mode in second state.</p> Full article ">Figure 3
<p>HBFCL control block diagram.</p> Full article ">Figure 4
<p>System voltage and current without HBFCL effect—the line current during normal and fault conditions.</p> Full article ">Figure 5
<p>System voltage and current without HBFCL effect—the point of common coupling (PCC) voltage during normal and fault conditions.</p> Full article ">Figure 6
<p>(<b>a</b>) Line and SW1 switch currents during normal and fault conditions affected by HBFCL and (<b>b</b>) PCC voltage during normal and fault conditions affected by HBFCL.</p> Full article ">Figure 7
<p>The effect of <span class="html-italic">SW</span><sub>2</sub> and <span class="html-italic">SW</span><sub>3</sub> on the PCC transient recovery voltage and the <span class="html-italic">SW</span><sub>1</sub> transient recovery voltage.</p> Full article ">Figure 8
<p>The line current with and without HBFCL protection.</p> Full article ">Figure 9
<p>The proposed experimental setup.</p> Full article ">Figure 10
<p>(<b>a</b>) Line current during normal and fault condition, (<b>b</b>) PCC voltage during normal and fault condition, and (<b>c</b>) main switch current during normal and fault condition.</p> Full article ">Figure 10 Cont.
<p>(<b>a</b>) Line current during normal and fault condition, (<b>b</b>) PCC voltage during normal and fault condition, and (<b>c</b>) main switch current during normal and fault condition.</p> Full article ">
19 pages, 1211 KiB  
Article
Expressing Personalities of Conversational Agents through Visual and Verbal Feedback
by Seo-young Lee, Gyuho Lee, Soomin Kim and Joonhwan Lee
Electronics 2019, 8(7), 794; https://doi.org/10.3390/electronics8070794 - 16 Jul 2019
Cited by 14 | Viewed by 4470
Abstract
As the uses of conversational agents increase, the affective and social abilities of agents become important with their functional abilities. Agents that lack affective abilities could frustrate users during interaction. This study applied personality to implement the natural feedback of conversational agents referring [...] Read more.
As the uses of conversational agents increase, the affective and social abilities of agents become important with their functional abilities. Agents that lack affective abilities could frustrate users during interaction. This study applied personality to implement the natural feedback of conversational agents referring to the concept of affective computing. Two types of feedback were used to express conversational agents’ personality: (1) visual feedback and (2) verbal cues. For visual feedback, participants (N = 45) watched visual feedback with different colors and motions. For verbal cues, participants (N = 60) heard different conditions of agents’ voices with different scripts. The results indicated that the motions of visual feedback were more significant than colors. Fast motions could express distinct and positive personalities. Different verbal cues were perceived as different personalities. The perceptions of personalities differed according to the vocal gender. This study provided design implications for personality expressions applicable to diverse interfaces. Full article
(This article belongs to the Special Issue Electronics and Dynamic Open Innovation)
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<p>Telepresence robot used in the entire study.</p> Full article ">Figure 2
<p>Visual feedback 1–8 used in the study.</p> Full article ">Figure 3
<p>Partially captured sequence of motions of visual feedback. All visual feedback moved with the same sequence.</p> Full article ">Figure 4
<p>Average mean values of conversational agent’s perceived personalities depending on different levels of motions of visual feedback.</p> Full article ">
15 pages, 2339 KiB  
Article
Embedded Flight Control Based on Adaptive Sliding Mode Strategy for a Quadrotor Micro Air Vehicle
by Herman Castañeda and J.L. Gordillo
Electronics 2019, 8(7), 793; https://doi.org/10.3390/electronics8070793 - 16 Jul 2019
Cited by 15 | Viewed by 4037
Abstract
The design of an embedded flight controller for a quadrotor micro air vehicle, which is subject to uncertainties and perturbations, is addressed. In order to obtain robustness against bounded uncertainties and disturbances, an adaptive sliding mode controller is proposed. The control adaptive gains [...] Read more.
The design of an embedded flight controller for a quadrotor micro air vehicle, which is subject to uncertainties and perturbations, is addressed. In order to obtain robustness against bounded uncertainties and disturbances, an adaptive sliding mode controller is proposed. The control adaptive gains allow using only necessary control to satisfy the task, reducing the chattering effect and at the same time reject external perturbations. Furthermore, a stability analysis of the closed-loop system is given. Finally, simulations and experimental results carried out on a commercial micro air vehicle demonstrate the feasibility and advantages of the proposed flight controller. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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<p>Referential frames’ configuration.</p> Full article ">Figure 2
<p>Regulation. Controllers comparison: adaptive sliding mode control (asmc), feedback linearization (fbl), and proportional integral derivative with gravity compensation control (PID).</p> Full article ">Figure 3
<p>Regulation. Control inputs of the controllers and adaptive gains of the asmc.</p> Full article ">Figure 4
<p>Hovering. Pose of the quadrotor MAV.</p> Full article ">Figure 5
<p>Error, reference versus variable state.</p> Full article ">Figure 6
<p>Hovering. Control inputs of the quadrotor MAV.</p> Full article ">Figure 7
<p>Hovering. Adaptive control gains.</p> Full article ">Figure 8
<p>Hovering. Pose of the quadrotor MAV subject to external perturbations.</p> Full article ">Figure 9
<p>Error. Reference versus variable state under perturbations.</p> Full article ">Figure 10
<p>Hovering. Control inputs of the quadrotor MAV under external perturbations.</p> Full article ">Figure 11
<p>Hovering. Adaptive control gains under external perturbations.</p> Full article ">
7 pages, 2879 KiB  
Article
A Study of the Sulfidation Behavior on Palladium-Coated Copper Wire with a Flash-Gold Layer (PCA) after Wire Bonding
by Kuan-Jen Chen, Fei-Yi Hung and Chia-Yun Chang
Electronics 2019, 8(7), 792; https://doi.org/10.3390/electronics8070792 - 15 Jul 2019
Cited by 6 | Viewed by 4120
Abstract
Palladium-coated copper wire with a flash-gold layer (PCA) is an oxidation-resistant fine wire that simultaneously has the properties of palladium-coated copper wire (PCC) and gold-coated copper wire. This research used an extreme sulfidation test to compare corrosion resistance between the PCC and PCA [...] Read more.
Palladium-coated copper wire with a flash-gold layer (PCA) is an oxidation-resistant fine wire that simultaneously has the properties of palladium-coated copper wire (PCC) and gold-coated copper wire. This research used an extreme sulfidation test to compare corrosion resistance between the PCC and PCA wires. In addition to closely examining the morphology of the wires, the internal matrix after the sulfidation test is also discussed. In doing so, the PCA wire was bonded onto the aluminum pads and the sulfidation test was conducted. Then, we observed its morphology and elemental distribution and found that the flash-gold layer of the PCA wire effectively enhanced resistance to sulfidation corrosion. Because the copper ball had an alloying effect on the ball bonding, it produced different shapes of sulfide after the sulfidation test. The degree of corrosion on the wedge bond was different because of the presence or absence of the coated layer. In contrast, the flash-gold layer of the PCA wire enhanced the bonding force and retained low resistance characteristics after the sulfidation test. Full article
(This article belongs to the Section Microelectronics)
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<p>(<b>a</b>,<b>b</b>) Surface morphologies, cross-section images, and (<b>c</b>,<b>d</b>) depth profile of the PCC and PCA wires after the sulfidation for 4 h.</p> Full article ">Figure 2
<p>Tensile properties of PCA and PCC wires after sulfidation: (<b>a</b>) Maximum load, and (<b>b</b>) elongation.</p> Full article ">Figure 3
<p>Electrical properties of PCC and PCA wires (<b>a</b>) before and (<b>b</b>,<b>c</b>) after sulfidation.</p> Full article ">Figure 4
<p>Morphologies of PCA wire bonding after different sulfidation durations: (<b>a</b>) 20 min and (<b>b</b>) 4 h.</p> Full article ">Figure 5
<p>(<b>a</b>) Fracture load and (<b>b</b>) fracture surface of PCA ball bond wire after sulfidation.</p> Full article ">Figure 6
<p>Electrical properties of the PCA ball bond wire after sulfidation.</p> Full article ">
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