[go: up one dir, main page]
Next Issue
Volume 6, July
Previous Issue
Volume 6, May
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.2
3.0
Journals
Micromachines
Volume 6
Issue 6
share announcement

Micromachines, Volume 6, Issue 6 (June 2015) – 10 articles , Pages 660-812

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
2806 KiB  
Article
PDR/INS/WiFi Integration Based on Handheld Devices for Indoor Pedestrian Navigation
by Yuan Zhuang, Haiyu Lan, You Li and Naser El-Sheimy
Micromachines 2015, 6(6), 793-812; https://doi.org/10.3390/mi6060793 - 23 Jun 2015
Cited by 115 | Viewed by 10092
Abstract
Providing an accurate and practical navigation solution anywhere with portable devices, such as smartphones, is still a challenge, especially in environments where global navigation satellite systems (GNSS) signals are not available or are degraded. This paper proposes a new algorithm that integrates inertial [...] Read more.
Providing an accurate and practical navigation solution anywhere with portable devices, such as smartphones, is still a challenge, especially in environments where global navigation satellite systems (GNSS) signals are not available or are degraded. This paper proposes a new algorithm that integrates inertial navigation system (INS) and pedestrian dead reckoning (PDR) to combine the advantages of both mechanizations for micro-electro-mechanical systems (MEMS) sensors in pedestrian navigation applications. In this PDR/INS integration algorithm, a pseudo-velocity-vector, which is composed of the PDR-derived forward speed and zero lateral and vertical speeds from non-holonomic constraints (NHC), works as an update for the INS to limit the velocity errors. To further limit the drift of MEMS inertial sensors, trilateration-based WiFi positions with small variances are also selected as updates for the PDR/INS integrated system. The experiments illustrate that positioning error is decreased by 60%–75% by using the proposed PDR/INS integrated MEMS solution when compared with PDR. The positioning error is further decreased by 15%–55% if the proposed PDR/INS/WiFi integrated solution is implemented. The average accuracy of the proposed PDR/INS/WiFi integration algorithm achieves 4.5 m in indoor environments. Full article
(This article belongs to the Special Issue Next Generation MEMS-Based Navigation—Systems and Applications)
►▼ Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Illustration for the PDR concept.</p> Full article ">Figure 2
<p>Block diagram of the proposed PDR/INS/WiFi integration system.</p> Full article ">Figure 3
<p>Three experimental trajectories in building E (about 120 m × 40 m). (<b>a</b>) Trajectory I; (<b>b</b>) Trajectory II; (<b>c</b>) Trajectory III.</p> Full article ">Figure 4
<p>Trajectories of PDR, PDR/INS integrated MEMS solution, and the reference.</p> Full article ">Figure 5
<p>The solution of the proposed PDR/INS integrated MEMS solution. (<b>a</b>) Velocity; (<b>b</b>) Attitude.</p> Full article ">Figure 6
<p>Results of the step detection and step length estimation. (<b>a</b>) Step detection for the whole trajectory; (<b>b</b>) Zoom-in of some parts of step detection for the trajectory; (<b>c</b>) Result of step length estimation; (<b>d</b>) Result of pseudo-velocity from step length.</p> Full article ">Figure 7
<p>Results of PDR horizontal velocity and azimuth.</p> Full article ">Figure 8
<p>INS navigation solution. (<b>a</b>) Trajectory; (<b>b</b>) Velocity; (<b>c</b>) Attitude.</p> Full article ">Figure 9
<p>Trilateration-based WiFi positioning solution. (<b>a</b>) WiFi trajectory; (<b>b</b>) Variances of WiFi positions.</p> Full article ">Figure 10
<p>Navigation results of PDR, the proposed MEMS solution, and WiFi/MEMS integration (Trajectory I: Pedestrian 1, Smartphone A). (<b>a</b>) Trajectories; (<b>b</b>) Cumulative error percentages.</p> Full article ">Figure 11
<p>Navigation results of PDR, the proposed MEMS solution, and WiFi/MEMS integration (Trajectory II: Pedestrian 2, Smartphone B). (<b>a</b>) Trajectories; (<b>b</b>) Cumulative error percentages.</p> Full article ">Figure 12
<p>WiFi trajectory (Trajectory II).</p> Full article ">Figure 13
<p>Navigation results of PDR, the proposed MEMS solution, and WiFi/MEMS integration (Trajectory III: Pedestrian 3, Smartphone C). (<b>a</b>) Trajectories; (<b>b</b>) Cumulative error percentages.</p> Full article ">Figure 14
<p>WiFi trajectory (Trajectory III).</p> Full article ">
624 KiB  
Editorial
Special Issue: 15 Years of SU8 as MEMS Material
by Arnaud Bertsch and Philippe Renaud
Micromachines 2015, 6(6), 790-792; https://doi.org/10.3390/mi6060790 - 19 Jun 2015
Cited by 22 | Viewed by 5480
Abstract
In 1997, the first paper using SU-8 as a material for microfabrication was published [1], demonstrating the interest of this negative photoresist for the near-UV structuration of thick layers and the manufacturing of high aspect-ratio components.[...] Full article
(This article belongs to the Special Issue 15 Years of SU8 as MEMS Material)
2916 KiB  
Article
Dynamics of Electrowetting Droplet Motion in Digital Microfluidics Systems: From Dynamic Saturation to Device Physics
by Weiwei Cui, Menglun Zhang, Xuexin Duan, Wei Pang, Daihua Zhang and Hao Zhang
Micromachines 2015, 6(6), 778-789; https://doi.org/10.3390/mi6060778 - 19 Jun 2015
Cited by 28 | Viewed by 10312
Abstract
A quantitative description of the dynamics of droplet motion has been a long-standing concern in electrowetting research. Although many static and dynamic models focusing on droplet motion induced by electrowetting-on-dielectric (EWOD) already exist, some dynamic features do not fit these models well, especially [...] Read more.
A quantitative description of the dynamics of droplet motion has been a long-standing concern in electrowetting research. Although many static and dynamic models focusing on droplet motion induced by electrowetting-on-dielectric (EWOD) already exist, some dynamic features do not fit these models well, especially the dynamic saturation phenomenon. In this paper, a dynamic saturation model of droplet motion on the single-plate EWOD device is presented. The phenomenon that droplet velocity is limited by a dynamic saturation effect is precisely predicted. Based on this model, the relationship between droplet motion and device physics is extensively discussed. The static saturation phenomenon is treated with a double-layer capacitance electric model, and it is demonstrated as one critical factor determining the dynamics of droplet motion. This work presents the relationship between dynamics of electrowetting induced droplet motion and device physics including device structure, surface material and interface electronics, which helps to better understand electrowetting induced droplet motions and physics of digital microfluidics systems. Full article
(This article belongs to the Special Issue Droplet Microfluidics: Techniques and Technologies)
►▼ Show Figures

Figure 1

Figure 1
<p>Schematics of (<b>a</b>) surface tensions on the tri-line interface of droplet on an electrowetting-on-dielectric (EWOD) device; (<b>b</b>) the electrowetting principle; (<b>c</b>) driving force derived from integration of the surface tension in contacting line; and (<b>d</b>) static effects on the droplet including the contact angle saturation (CAS) effect and pinning effect. The surface tensions in (<b>c</b>) represent the component in the driving direction. Furthermore, θ<sub><span class="html-italic">S</span></sub> in (<b>d</b>) stands for the saturated contact angle when the applied voltage is large enough.</p> Full article ">Figure 2
<p>Comparison of curves induced by Brochard’s theoretical model (solid line) and the saturation phenomenon found in experiments (dashed one), which indicates that the dynamic saturation effect cannot be predicted by Brochard’s model.</p> Full article ">Figure 3
<p>Comparison between the dynamic saturation model (line) and experiment results in reference [<a href="#B20-micromachines-06-00778" class="html-bibr">20</a>] (plots). The red curve is induced by Equation (1) and its modification, taking the radium variation into account, is represented by the blue curve.</p> Full article ">Figure 4
<p>Calculated droplet velocity as a function of the applied voltage, according to Equation (1). The parameters used in the calculation are summarized in <a href="#app1-micromachines-06-00778" class="html-app">Table S2 in the supplementary information</a>.</p> Full article ">Figure 5
<p>(<b>a</b>) Velocity of droplet motion as a function of the electrowetting number, <span class="html-italic">M</span>; and (<b>b</b>) the electrowetting number varies with the applied voltage.</p> Full article ">Figure 6
<p>Influence of (<b>a</b>) dielectric layer thickness and (<b>b</b>) relative permittivity on the velocity of the droplet according to Equation (1), with the parameters in <a href="#app1-micromachines-06-00778" class="html-app">Table S2</a>, as presented in the <a href="#app1-micromachines-06-00778" class="html-app">supplementary information</a>.</p> Full article ">Figure 7
<p>Effect of a droplet’s initial contact angle on velocity, according to Equation (2). The initial contact angle is determined by the surface property of the EWOD device. The applied voltages, respectively, are 10, 20, 30, 50, 70, and 160 V from bottom to top. For the range from 150° to 165°, the velocity increases more rapidly with the applied voltage; therefore, this range is “the most effective area” to convert electric energy into droplet kinetic energy. When the applied voltage is greater than 160 V, the saturation velocity is independent with the initial contact angle.</p> Full article ">Figure 8
<p>(<b>a</b>) Charges distribution on the liquid–solid interface and (<b>b</b>) the equivalent electric circuit of the triangle line region. <span class="html-italic">C</span><sub>1</sub> is the capacitance of dielectric layer, and <span class="html-italic">C</span><sub>2</sub> is the capacitance of the double layer that is determined by the accumulated charges distribution.</p> Full article ">
1460 KiB  
Article
Effects of Baffle Configuration on Mixing in a T-Shaped Micro-Channel
by Dong Jin Kang
Micromachines 2015, 6(6), 765-777; https://doi.org/10.3390/mi6060765 - 17 Jun 2015
Cited by 21 | Viewed by 6074
Abstract
A numerical study was performed for a T-shaped microchannel to enhance mixing performance through a baffle configuration. The mixing performance was analyzed in terms of the DOM (degree of mixing) and the pressure load between the two inlets and outlet. Four different baffle [...] Read more.
A numerical study was performed for a T-shaped microchannel to enhance mixing performance through a baffle configuration. The mixing performance was analyzed in terms of the DOM (degree of mixing) and the pressure load between the two inlets and outlet. Four different baffle configurations were designed and simulated to determine how they affect the mixing performance of a T-shaped microchannel. Among the four baffle configurations, a cyclic configuration of baffles produced the best results. It exhibited the fastest growth in the DOM along the microchannel. The cyclic configuration means that four baffles are attached to four side walls of the channel in a cyclic order. The mixing improvement occurs in two ways. One is in the baffle region, when the cyclic configuration causes the fluid flow to rotate in the cross section, unlike other configurations. The other improvement is observed in the remaining outlet branch after the baffle region. This improvement is due to twisting and elongation of the boundary between two fluids. The baffle size and the interval between two consecutive baffles are shown to be optimized in terms of the DOM for a given condition. Full article
(This article belongs to the Special Issue Micromixer & Micromixing)
►▼ Show Figures

Figure 1

Figure 1
<p>Schematic diagram of a T-shaped micro-channel.</p> Full article ">Figure 2
<p>Schematic diagrams of four different configurations of repeated baffles. (<b>a</b>) Upper wall attachment. (<b>b</b>) Opposite wall attachment: type 1. (<b>c</b>) Opposite wall attachment: type 2. (<b>d</b>) Cyclic attachment.</p> Full article ">Figure 3
<p>Effects of baffle thickness on the DOM.</p> Full article ">Figure 4
<p>Variation of pressure difference and its relationship with the DOM. (<b>a</b>) Pressure difference <span class="html-italic">vs.</span> number of baffles. (<b>b</b>) DOM <span class="html-italic">vs.</span> number of baffles.</p> Full article ">Figure 5
<p>Comparison of the mass fraction contours of fluid “B” along the central plane. (<b>a</b>) Upper wall attachment. (<b>b</b>) Opposite wall attachment: type 1. (<b>c</b>) Opposite wall attachment: type 2. (<b>d</b>) Cyclic attachment.</p> Full article ">Figure 6
<p>Comparison of the streamline patterns and vorticity distributions around the baffles. (<b>a</b>) Upper wall attachment. (<b>b</b>) Opposite wall attachment: type 1. (<b>c</b>) Opposite wall attachment: type 2. (<b>d</b>) Cyclic attachment.</p> Full article ">Figure 7
<p>Comparison of the DOM evolutions along the outlet branch.</p> Full article ">Figure 8
<p>Development of the DOM distributions throughout the baffle region.</p> Full article ">Figure 9
<p>Comparison of the DOM evolutions for four different numbers of baffles.</p> Full article ">Figure 10
<p>Definition of clearance gap <span class="html-italic">c</span>.</p> Full article ">Figure 11
<p>Effects of the clearance on the DOM relationship with pressure difference.</p> Full article ">Figure 12
<p>Effects of the baffle interval on the DOM relationship with pressure difference.</p> Full article ">Figure 13
<p>Comparison of the mass fraction distribution in the cross section at 50 μm downstream of baffles for four different baffle clearances and intervals. (<b>a</b>) <span class="html-italic">c</span> = 0 μm and <span class="html-italic">d</span> = 100 μm. (<b>b</b>) <span class="html-italic">c</span> = 15 μm and <span class="html-italic">d</span> = 100 μm. (<b>c</b>) <span class="html-italic">c</span> = 25 μm and <span class="html-italic">d</span> = 100 μm. (<b>d</b>) <span class="html-italic">c</span> = 15 μm and <span class="html-italic">d</span> = 75 μm.</p> Full article ">Figure 14
<p>Comparison of DOM evolution along the outlet branch.</p> Full article ">
4107 KiB  
Article
WiFi-Aided Magnetic Matching for Indoor Navigation with Consumer Portable Devices
by You Li, Yuan Zhuang, Haiyu Lan, Peng Zhang, Xiaoji Niu and Naser El-Sheimy
Micromachines 2015, 6(6), 747-764; https://doi.org/10.3390/mi6060747 - 16 Jun 2015
Cited by 66 | Viewed by 8694
Abstract
This paper presents a WiFi-aided magnetic matching (MM) algorithm for indoor pedestrian navigation with consumer portable devices. This algorithm reduces both the mismatching rate (i.e., the rate of matching to an incorrect point that is more than 20 m away from [...] Read more.
This paper presents a WiFi-aided magnetic matching (MM) algorithm for indoor pedestrian navigation with consumer portable devices. This algorithm reduces both the mismatching rate (i.e., the rate of matching to an incorrect point that is more than 20 m away from the true value) and computational load of MM by using WiFi positioning solutions to limit the MM search space. Walking tests with Samsung Galaxy S3 and S4 smartphones in two different indoor environments (i.e., Environment #1 with abundant WiFi APs and significant magnetic features, and Environment #2 with less WiFi and magnetic information) were conducted to evaluate the proposed algorithm. It was found that WiFi fingerprinting accuracy is related to the signal distributions. MM provided results with small fluctuations but had a significant mismatch rate; when aided by WiFi, MM’s robustness was significantly improved. The outcome of this research indicates that WiFi and MM have complementary characteristics as the former is a point-by-point matching approach and the latter is based on profile-matching. Furthermore, performance improvement through integrating WiFi and MM depends on the environment (e.g., the signal distributions of magnetic intensity and WiFi RSS): In Environment #1 tests, WiFi-aided MM and WiFi provided similar results; in Environment #2 tests, the former was approximately 41.6% better. Our results supported that the WiFi-aided MM algorithm provided more reliable solutions than both WiFi and MM in the areas that have poor WiFi signal distribution or indistinctive magnetic-gradient features. Full article
(This article belongs to the Special Issue Next Generation MEMS-Based Navigation—Systems and Applications)
►▼ Show Figures

Figure 1

Figure 1
<p>Algorithm architecture.</p> Full article ">Figure 2
<p>Procedure of training phases for magnetic matching and WiFi fingerprinting.</p> Full article ">Figure 3
<p>Using WiFi positioning results to limit search space for magnetic matching.</p> Full article ">Figure 4
<p>Trajectories used to generate WiFi and magnetic databases (DBs) at the Energy Environment Experiential Learning (EEEL).</p> Full article ">Figure 5
<p>WiFi signal distribution at EEEL.</p> Full article ">Figure 6
<p>Magnetic distribution at EEEL.</p> Full article ">Figure 7
<p>Test trajectory at EEEL (with abundant WiFi and magnetic information).</p> Full article ">Figure 8
<p>Magnetic matching (MM) result at EEEL.</p> Full article ">Figure 9
<p>WiFi fingerprinting result at EEEL.</p> Full article ">Figure 10
<p>WiFi-aided MM result at EEEL.</p> Full article ">Figure 11
<p>MM position errors at EEEL.</p> Full article ">Figure 12
<p>WiFi position errors at EEEL.</p> Full article ">Figure 13
<p>WiFi-aided MM position errors at EEEL.</p> Full article ">Figure 14
<p>WiFi signal distribution at the Engineering building (ENB).</p> Full article ">Figure 15
<p>Magnetic distribution at ENB.</p> Full article ">Figure 16
<p>MM result at ENB.</p> Full article ">Figure 17
<p>WiFi fingerprinting result at ENB.</p> Full article ">Figure 18
<p>WiFi-aided MM result at ENB.</p> Full article ">Figure 19
<p>MM position errors at ENB.</p> Full article ">Figure 20
<p>WiFi position errors at ENB.</p> Full article ">Figure 21
<p>WiFi-aided MM position errors at ENB.</p> Full article ">
6402 KiB  
Review
Towards Improved Airborne Fire Detection Systems Using Beetle Inspired Infrared Detection and Fire Searching Strategies
by Herbert Bousack, Thilo Kahl, Anke Schmitz and Helmut Schmitz
Micromachines 2015, 6(6), 718-746; https://doi.org/10.3390/mi6060718 - 16 Jun 2015
Cited by 16 | Viewed by 11051
Abstract
Every year forest fires cause severe financial losses in many countries of the world. Additionally, lives of humans as well as of countless animals are often lost. Due to global warming, the problem of wildfires is getting out of control; hence, the burning [...] Read more.
Every year forest fires cause severe financial losses in many countries of the world. Additionally, lives of humans as well as of countless animals are often lost. Due to global warming, the problem of wildfires is getting out of control; hence, the burning of thousands of hectares is obviously increasing. Most important, therefore, is the early detection of an emerging fire before its intensity becomes too high. More than ever, a need for early warning systems capable of detecting small fires from distances as large as possible exists. A look to nature shows that pyrophilous “fire beetles” of the genus Melanophila can be regarded as natural airborne fire detection systems because their larvae can only develop in the wood of fire-killed trees. There is evidence that Melanophila beetles can detect large fires from distances of more than 100 km by visual and infrared cues. In a biomimetic approach, a concept has been developed to use the surveying strategy of the “fire beetles” for the reliable detection of a smoke plume of a fire from large distances by means of a basal infrared emission zone. Future infrared sensors necessary for this ability are also inspired by the natural infrared receptors of Melanophila beetles. Full article
(This article belongs to the Special Issue Biomimetic Systems)
►▼ Show Figures

Figure 1

Figure 1
<p>Infrared (IR) organ of <span class="html-italic">Melanophila acuminata</span>. (<b>a</b>) Dome-shaped IR sensilla at the bottom of a pit organ (whole organ shown in the inset). Each sensillum is accompanied by a smaller wax gland (wg) characterized by tiny pores. Bar: 15 µm (Inset 100 µm). (<b>b</b>) Single IR sensillum centrally opened by focused ion beam (FIB). Specimen was air-dried; therefore only the cuticle is preserved. Microcavities (mc) of the intermediate layer and the inner pressure chamber (ipc) can be discerned inside the sphere. exo: exocuticular outer dome. Bar: 5 µm. (<b>c</b>) Schematic drawing of a photomechanic IR sensillum covered by an outer dome of hard exocuticle (exo). The tip of the dendrite (d) is suspended by fine filaments inside the inner pressure chamber (ipc), which communicates with the fluid in the microcavities (mc) of the intermediate layer. Any increase in fluid pressure is transferred onto the dendritic membrane. (ls): lamellated exocuticular shell of the sphere.</p> Full article ">Figure 2
<p>(<b>Left</b>) Model of a radiating fire front represented by a cuboid with the width <span class="html-italic">W</span><sub>F</sub> of the fire front and the flame height <span class="html-italic">L</span><sub>F</sub>. (<b>Right</b>) The heat flux will be calculated in the distance <span class="html-italic">x</span> from the fire front and at a point with height H above ground representing the altitude of the beetle.</p> Full article ">Figure 3
<p>Radiation heat flux probability distribution (flame front 90–110 m) at a fire distance of 50 km.</p> Full article ">Figure 4
<p>Radiation heat flux (flame front 90–110 m) as function of the fire distance.</p> Full article ">Figure 5
<p>Radiation heat flux (flame front 10–30 m) as function of the fire distance.</p> Full article ">Figure 6
<p>Comparison of the sensillum (<b>left</b>) with the model of the sensor (<b>right</b>).</p> Full article ">Figure 7
<p>Maximum central deflection, <span class="html-italic">y</span><sub>max</sub>, at <span class="html-italic">r</span> = 0 of a circular membrane (silicon, 1 µm thickness) as function of factor Ω and irradiation time for a water-filled cavity. IR power density: 10 W/m<sup>2</sup>, diameter and height of the cavity: 0.5 mm.</p> Full article ">Figure 8
<p>Model of the sensillum with nanocanals (<b>left</b>) and Model of the IR sensor (<b>right</b>) with cavity (pressure <span class="html-italic">P<sub>C</sub></span>, volume <span class="html-italic">V<sub>C</sub></span>) and reservoir (pressure <span class="html-italic">P<sub>R</sub></span>, volume <span class="html-italic">V<sub>R</sub></span>). The canal of the compensation leak has a radius <span class="html-italic">R<sub>L</sub></span> and a length <span class="html-italic">L.</span></p> Full article ">Figure 9
<p>Time dependent pressure in the non-adiabatic cavity and the reservoir as a function of the heat loss from the cavity (decreasing value of Θ corresponding to increasing heat loss and Ω = 1000, γ = 3000 (<span class="html-italic">I</span><sub>o</sub> = 10 W/m<sup>2</sup>), τ = 0.001 s for equal size of cavity <span class="html-italic">V<sub>C</sub></span> and reservoir <span class="html-italic">V<sub>R</sub></span>.</p> Full article ">Figure 10
<p>Time-dependent pressure difference between the non-adiabatic cavity and the reservoir as a function of the heat loss from the cavity and Ω = 1000, γ = 3000 (<span class="html-italic">I</span><sub>0</sub> = 10 W/m<sup>2</sup>), τ<span class="html-italic"><sub>C</sub></span> = τ<span class="html-italic"><sub>R</sub></span> = 0.001 s for equal size of cavity <span class="html-italic">V<sub>C</sub></span> and reservoir <span class="html-italic">V<sub>R</sub></span>.</p> Full article ">Figure 11
<p>Maximum central deflection, <span class="html-italic">y</span><sub>max</sub>, of a circular membrane (silicon, 1 µm thickness) as a function of the factor Ω and heat loss time constant Θ for a water-filled cavity. IR power density: 10 W/m<sup>2</sup>, irradiation time: 0.5 s, diameter and height of the cavity: 0.5 mm, Volume reservoir: 100 × volume of cavity.</p> Full article ">Figure 12
<p>Maximum central deflection, <span class="html-italic">y</span><sub>max</sub>, of a circular membrane (silicon, 1 µm thickness) as function of factor Ω and the relation of cavity volume to reservoir volume for a water-filled cavity. IR power density: 10 W/m<sup>2</sup>, irradiation time: 0.5 s, diameter and height of the cavity: 0.5 mm, heat loss time constant Θ: 0.5 s.</p> Full article ">Figure 13
<p>Relative plate deflection at <span class="html-italic">r</span> = 0 as a function of applied pressure difference compared the influence of a membrane stress for a water-filled cavity.</p> Full article ">Figure 14
<p>Comparison of the thermal effusivity, <span class="html-italic">b</span>, for different materials (Polyvinyl fluoride under the trade name Tedlar<sup>®</sup> is a registered trademark of DuPont; Pyrex<sup>®</sup> is a registered trademark of Corning Incorporated).</p> Full article ">Figure 15
<p>Comparison of the relative deflection δ of the membrane for different fluids (isobaric case, Ω &gt;&gt;1, see Equation (9)). For the same cross section of the cavity, the relative deflection is caused by the same amount of energy absorbed in the fluids. The dimensions and the material properties of the according membrane can be calculated with Ω, see Equation (9) for Ω &gt;&gt; 1.</p> Full article ">Figure 16
<p>Temperature distribution along the cavity axis 0.5 s after the onset of irradiation for a water-filled and a CO<sub>2</sub>-filled cavity with an IR power density at the outer window surface of 10 W/m<sup>2</sup>. In the case of gas, a thin IR absorber film is assumed on the inner glass surface where all the IR energy is absorbed.</p> Full article ">Figure 17
<p>Maximum central deflection, <span class="html-italic">y</span><sub>max</sub>, of a circular membrane at <span class="html-italic">t</span> = 0.5 s as function of factor Ω for a water-filled and CO<sub>2</sub>-filled cavity. IR power density of 10 W/m<sup>2</sup>, diameter and height of the cavity: 0.5 mm.</p> Full article ">Figure 18
<p>Temperature distribution along the cavity axis 0.5 s after the onset of irradiation for different liquids with an IR power density at the outer window surface of 10 W/m<sup>2</sup>. For gas an absorption zone at the inner window surface is assumed.</p> Full article ">Figure 19
<p>(<b>A</b>) Image of a large forest fire taken from a helicopter from a distance of 21 km with a WESCAM MX-15 in Western Australia. The image consists of two superimposed pictures: one taken with a high-resolution video camera and one taken with an infrared (IR) camera (white area “IR” showing the hot infrared emission zone of the ongoing fire). Image courtesy of Aerial Intelligence Unit of DEFS (see Acknowledgements). (<b>B</b>) Schematic drawing of three beetlecopter drones hovering over a terrain with a mountain range. From their stationary airborne positions drones identify a fire with on-board digital video and infrared cameras. By sending a set of alerting data to a central earth station the exact position and the current status of the fire can be determined.</p> Full article ">
4745 KiB  
Article
Reciprocal Estimation of Pedestrian Location and Motion State toward a Smartphone Geo-Context Computing Solution
by Jingbin Liu, Lingli Zhu, Yunsheng Wang, Xinlian Liang, Juha Hyyppä, Tianxing Chu, Keqiang Liu and Ruizhi Chen
Micromachines 2015, 6(6), 699-717; https://doi.org/10.3390/mi6060699 - 15 Jun 2015
Cited by 11 | Viewed by 7176
Abstract
The rapid advance in mobile communications has made information and services ubiquitously accessible. Location and context information have become essential for the effectiveness of services in the era of mobility. This paper proposes the concept of geo-context that is defined as an integral [...] Read more.
The rapid advance in mobile communications has made information and services ubiquitously accessible. Location and context information have become essential for the effectiveness of services in the era of mobility. This paper proposes the concept of geo-context that is defined as an integral synthesis of geographical location, human motion state and mobility context. A geo-context computing solution consists of a positioning engine, a motion state recognition engine, and a context inference component. In the geo-context concept, the human motion states and mobility context are associated with the geographical location where they occur. A hybrid geo-context computing solution is implemented that runs on a smartphone, and it utilizes measurements of multiple sensors and signals of opportunity that are available within a smartphone. Pedestrian location and motion states are estimated jointly under the framework of hidden Markov models, and they are used in a reciprocal manner to improve their estimation performance of one another. It is demonstrated that pedestrian location estimation has better accuracy when its motion state is known, and in turn, the performance of motion state recognition can be improved with increasing reliability when the location is given. The geo-context inference is implemented simply with the expert system principle, and more sophisticated approaches will be developed. Full article
(This article belongs to the Special Issue Next Generation MEMS-Based Navigation—Systems and Applications)
►▼ Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Location and motion state sensing using measurements of versatile signals and sensors available from a smartphone.</p> Full article ">Figure 2
<p>The process of motion state recognition from sensor measurements to recognized activities.</p> Full article ">Figure 3
<p>Structure and temporal evolution process of a hidden Markov model system.</p> Full article ">Figure 4
<p>Architecture of a smartphone hybrid indoor positioning solution that combines measurements of multiple sensors and wireless networks and radio signals mapping knowledge database. Five elements of HMM are determined using different types of information inputs and are applied with the grid-based filter to output location results.</p> Full article ">Figure 5
<p>Experimental environment of the positioning and motion state estimation of this study, which is represented by the 3D point cloud and a snapshot of the interior structure of the FGI building.</p> Full article ">Figure 6
<p>Positioning errors in terms of RMSE (<b>a</b>) and maximum errors (<b>b</b>) when the different cases of MDI combinations are applied. The yellow bars (marked as “5” of <span class="html-italic">x</span>-axis) represent the results of the baseline method MLE.</p> Full article ">Figure 7
<p>Motion state recognition performance indicated by the <span class="html-italic">F</span>-measure when area type-specific state transition probability matrix and overall STP matrix are utilized separately.</p> Full article ">Figure 8
<p>Process of the forward chaining method for geo-context inference.</p> Full article ">Figure 9
<p>Flowchart of the geo-context computing solution and related applications.</p> Full article ">
1161 KiB  
Article
Signal Processing Technique for Combining Numerous MEMS Gyroscopes Based on Dynamic Conditional Correlation
by Jieyu Liu, Qiang Shen and Weiwei Qin
Micromachines 2015, 6(6), 684-698; https://doi.org/10.3390/mi6060684 - 12 Jun 2015
Cited by 15 | Viewed by 6890
Abstract
A signal processing technique is presented to improve the angular rate accuracy of Micro-Electro-Mechanical System (MEMS) gyroscope by combining numerous gyroscopes. Based on the conditional correlation between gyroscopes, a dynamic data fusion model is established. Firstly, the gyroscope error model is built through [...] Read more.
A signal processing technique is presented to improve the angular rate accuracy of Micro-Electro-Mechanical System (MEMS) gyroscope by combining numerous gyroscopes. Based on the conditional correlation between gyroscopes, a dynamic data fusion model is established. Firstly, the gyroscope error model is built through Generalized Autoregressive Conditional Heteroskedasticity (GARCH) process to improve overall performance. Then the conditional covariance obtained through dynamic conditional correlation (DCC) estimator is used to describe the correlation quantitatively. Finally, the approach is validated by a prototype of the virtual gyroscope, which consists of six-gyroscope array. The experimental results indicate that the weights of gyroscopes change with the value of error. Also, the accuracy of combined rate signal is improved dramatically compared to individual gyroscope. The results indicate that the approach not only improves the accuracy of the MEMS gyroscope, but also discovers the fault gyroscope and eliminates its influence. Full article
(This article belongs to the Special Issue Next Generation MEMS-Based Navigation—Systems and Applications)
►▼ Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Prototype of the virtual gyroscope.</p> Full article ">Figure 2
<p>Scale factor plot of the individual gyroscopes.</p> Full article ">Figure 3
<p>Outputs of the individual gyroscopes.</p> Full article ">Figure 4
<p>Internal temperature of gyros</p> Full article ">Figure 5
<p><span class="html-italic">H<sub>t</sub></span> estimated.</p> Full article ">Figure 6
<p>Curve of dynamic correlation coefficient.</p> Full article ">Figure 7
<p>Weights of the individual gyroscopes.</p> Full article ">Figure 8
<p>Outputs of virtual gyroscope.</p> Full article ">Figure 9
<p>Allan variance results of the virtual gyro compared to the single gyro.</p> Full article ">
3468 KiB  
Article
Rotational Efficiency of Photo-Driven Archimedes Screws for Micropumps
by Chih-Lang Lin, Yu-Sheng Lin and Patrice L. Baldeck
Micromachines 2015, 6(6), 674-683; https://doi.org/10.3390/mi6060674 - 9 Jun 2015
Cited by 7 | Viewed by 6593
Abstract
In this study, we characterized the rotational efficiency of the photo-driven Archimedes screw. The micron-sized Archimedes screws were fabricated using the two-photon polymerization technique. Free-floating screws trapped by optical tweezers align in the laser irradiation direction and rotate spontaneously. The influences of the [...] Read more.
In this study, we characterized the rotational efficiency of the photo-driven Archimedes screw. The micron-sized Archimedes screws were fabricated using the two-photon polymerization technique. Free-floating screws trapped by optical tweezers align in the laser irradiation direction and rotate spontaneously. The influences of the screw pitch and the number of screw blades have been investigated in our previous studies. In this paper, the blade thickness and the central rod of the screw were further investigated. The experimental results indicate that the blade thickness contributes to rotational stability, but not to rotational speed, and that the central rod stabilizes the rotating screw but is not conducive to rotational speed. Finally, the effect of the numerical aperture (NA) of the optical tweezers was investigated through a demonstration. The NA is inversely proportional to the rotational speed. Full article
(This article belongs to the Special Issue Micropumps: Design, Fabrication and Applications)
►▼ Show Figures

Figure 1

Figure 1
<p>The two-photon polymerization (TPP) fabrication system.</p> Full article ">Figure 2
<p>Geometric description of an Archimedes screw.</p> Full article ">Figure 3
<p>Scanning electron microscope (SEM) figures of polymerized products (Archimedes micro-screws): (<b>a</b>) screws without a central rod; (<b>b</b>) screws with a central rod.</p> Full article ">Figure 4
<p>Diagram of the optical tweezers system.</p> Full article ">Figure 5
<p>Computer Aided Design (CAD) of Archimedes screws without a central rod.</p> Full article ">Figure 6
<p>The evolution of rotational speeds under increasing laser power for micro-crews with different blade thicknesses (<span class="html-italic">t</span> = 0.5 μm, 1.0 μm, 1.3 μm, and 1.6 μm).</p> Full article ">Figure 7
<p>Schematic explanation of the influence of blade thickness: (<b>a</b>) thin-blade screw; (<b>b</b>) thick-blade screw.</p> Full article ">Figure 8
<p>AutoCAD designs of Archimedes screws with central rod.</p> Full article ">Figure 9
<p>The evolution of rotational speeds under increasing laser power for micro-crews with different rod diameters (<span class="html-italic">d</span> = 0.5 μm, 0.7 μm, 0.9 μm, and 1.1 μm).</p> Full article ">Figure 10
<p>Diagram of effective exposure area.</p> Full article ">Figure 11
<p>Rotational efficiency <span class="html-italic">versus</span> effective exposure area.</p> Full article ">Figure 12
<p>Two cases of optical trappings: (<b>a</b>) large numerical aperture (NA); (<b>b</b>) small NA.</p> Full article ">Figure 13
<p>The evolution of rotational speeds under increasing laser power for micro-crews with different NAs (NA = 1.3 μm, 1.27 μm, 1.23 μm, and 1.2 μm).</p> Full article ">Figure 14
<p>Rotational efficiency <span class="html-italic">versus</span> 1/NA.</p> Full article ">
8441 KiB  
Article
On-Chip Method to Measure Mechanical Characteristics of a Single Cell by Using Moiré Fringe
by Hirotaka Sugiura, Shinya Sakuma, Makoto Kaneko and Fumihito Arai
Micromachines 2015, 6(6), 660-673; https://doi.org/10.3390/mi6060660 - 3 Jun 2015
Cited by 35 | Viewed by 8670
Abstract
We propose a method to characterize the mechanical properties of cells using a robot-integrated microfluidic chip (robochip) and microscopy. The microfluidic chip is designed to apply the specified deformations to a single detached cell using an on-chip actuator probe. The reaction force is [...] Read more.
We propose a method to characterize the mechanical properties of cells using a robot-integrated microfluidic chip (robochip) and microscopy. The microfluidic chip is designed to apply the specified deformations to a single detached cell using an on-chip actuator probe. The reaction force is simultaneously measured using an on-chip force sensor composed of a hollow folded beam and probe structure. In order to measure the cellular characteristics in further detail, a sub-pixel level of resolution of probe position is required. Therefore, we utilize the phase detection of moiré fringe. Using this method, the experimental resolution of the probe position reaches 42 nm. This is approximately ten times smaller than the optical wavelength, which is the limit of sharp imaging with a microscope. Calibration of the force sensor is also important in accurately measuring cellular reaction forces. We calibrated the spring constant from the frequency response, by the proposed sensing method of the probe position. As a representative of mechanical characteristics, we measured the elastic modulus of Madin-Darby Cannie Kidney (MDCK) cells. In spite of the rigid spring constant, the resolution and sensitivity were twice that achieved in our previous study. Unique cellular characteristics can be elucidated by the improvements in sensing resolution and accuracy. Full article
(This article belongs to the Collection Lab-on-a-Chip)
►▼ Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Overview of the on-chip measurement system for cellular mechanical characteristics.</p> Full article ">Figure 2
<p>Fabrication of the proposed robochip: (<b>a</b>) fabrication process flow; (<b>b</b>) photograph of the fabricated chip; and (<b>c</b>) SEM image of the fabricated chip.</p> Full article ">Figure 3
<p>Components for the measurement and proposed method to improve the sensing accuracy.</p> Full article ">Figure 4
<p>(<b>a</b>) Schematic image of the phase detection with moiré fringe and (<b>b</b>) the measurement factors related to the improvement of resolution.</p> Full article ">Figure 5
<p>(<b>a</b>) Geometric illustration of the force sensor and (<b>b</b>) established 1-DOF mechanical model.</p> Full article ">Figure 6
<p>Confirmation of experimental performance: (<b>a</b>) image of the system setup; (<b>b</b>) precision of the proposed sensing method; and (<b>c</b>) typical examples of the data used for the calibration method.</p> Full article ">Figure 7
<p>Measurement of cellular mechanical characteristics: (<b>a</b>) Image and cross sectional view of the system setup and (<b>b</b>) microscopic images at typical points of the measurement.</p> Full article ">Figure 8
<p>Experimentally obtained mechanical characteristics of MDCK cells: (<b>a</b>) The difference when repetitive deformation is applied and (<b>b</b>) the characteristics of three samples at first deformation.</p> Full article ">Figure 9
<p>Performance of the proposed measurement method and previous method [<a href="#B12-micromachines-06-00660" class="html-bibr">12</a>].</p> Full article ">
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-10
Previous Issue
Next Issue
Back to TopTop