Search Results (2,860)

Speech-driven lip synchronization is a crucial technology for generating realistic facial animations, with broad application prospects in virtual reality, education, training, and other fields. However, existing methods still face challenges in generating high-fidelity facial animations, particularly in addressing lip jitter and facial motion instability issues in continuous frame sequences. This study presents VividWav2Lip, an improved speech-driven lip synchronization model. Our model incorporates three key innovations: a cross-attention mechanism for enhanced audio-visual feature fusion, an optimized network structure with Squeeze-and-Excitation (SE) residual blocks, and the integration of the CodeFormer facial restoration network for post-processing. Extensive experiments were conducted on a diverse dataset comprising multiple languages and facial types. Quantitative evaluations demonstrate that VividWav2Lip outperforms the baseline Wav2Lip model by 5% in lip sync accuracy and image generation quality, with even more significant improvements over other mainstream methods. In subjective assessments, 85% of participants perceived VividWav2Lip-generated animations as more realistic compared to those produced by existing techniques. Additional experiments reveal our model’s robust cross-lingual performance, maintaining consistent quality even for languages not included in the training set. This study not only advances the theoretical foundations of audio-driven lip synchronization but also offers a practical solution for high-fidelity, multilingual dynamic face generation, with potential applications spanning virtual assistants, video dubbing, and personalized content creation. Full article

Advanced video codecs such as High Efficiency Video Coding/H.265 (HEVC) and Versatile Video Coding/H.266 (VVC) are vital for streaming high-quality online video content, as they compress and transmit data efficiently. However, these codecs can occasionally degrade video quality by adding undesirable artifacts such as blockiness, blurriness, and ringing, which can detract from the viewer’s experience. To ensure a seamless and engaging video experience, it is essential to remove these artifacts, which improves viewer comfort and engagement. In this paper, we propose a deep feature fusion based convolutional neural network (CNN) architecture (VVC-PPFF) for post-processing approach to further enhance the performance of VVC. The proposed network, VVC-PPFF, harnesses the power of CNNs to enhance decoded frames, significantly improving the coding efficiency of the state-of-the-art VVC video coding standard. By combining deep features from early and later convolution layers, the network learns to extract both low-level and high-level features, resulting in more generalized outputs that adapt to different quantization parameter (QP) values. The proposed VVC-PPFF network achieves outstanding performance, with Bjøntegaard Delta Rate (BD-Rate) improvements of 5.81% and 6.98% for luma components in random access (RA) and low-delay (LD) configurations, respectively, while also boosting peak signal-to-noise ratio (PSNR). Full article

In cloud-based Distributed Acoustic Sensing (DAS) sensor data management, we are confronted with two primary challenges. First, the development of efficient storage mechanisms capable of handling the enormous volume of data generated by these sensors poses a challenge. To solve this issue, we propose a method to address the issue of handling the large amount of data involved in DAS by designing and implementing a pipeline system to efficiently send the big data to DynamoDB in order to fully use the low latency of the DynamoDB data storage system for a benchmark DAS scheme for performing continuous monitoring over a 100 km range at a meter-scale spatial resolution. We employ the DynamoDB functionality of Amazon Web Services (AWS), which allows highly expandable storage capacity with latency of access of a few tens of milliseconds. The different stages of DAS data handling are performed in a pipeline, and the scheme is optimized for high overall throughput with reduced latency suitable for concurrent, real-time event extraction as well as the minimal storage of raw and intermediate data. In addition, the scalability of the DynamoDB-based data storage scheme is evaluated for linear and nonlinear variations of number of batches of access and a wide range of data sample sizes corresponding to sensing ranges of 1–110 km. The results show latencies of 40 ms per batch of access with low standard deviations of a few milliseconds, and latency per sample decreases for increasing the sample size, paving the way toward the development of scalable, cloud-based data storage services integrating additional post-processing for more precise feature extraction. The technique greatly simplifies DAS data handling in key application areas requiring continuous, large-scale measurement schemes. In addition, the processing of raw traces in a long-distance DAS for real-time monitoring requires the careful design of computational resources to guarantee requisite dynamic performance. Now, we will focus on the design of a system for the performance evaluation of cloud computing systems for diverse computations on DAS data. This system is aimed at unveiling valuable insights into performance metrics and operational efficiencies of computations on the data in the cloud, which will provide a deeper understanding of the system’s performance, identify potential bottlenecks, and suggest areas for improvement. To achieve this, we employ the CloudSim framework. The analysis reveals that the virtual machine (VM) performance decreases significantly the processing time with more capable VMs, influenced by Processing Elements (PEs) and Million Instructions Per Second (MIPS). The results also reflect that, although a larger number of computations is required as the fiber length increases, with the subsequent increase in processing time, the overall speed of computation is still suitable for continuous real-time monitoring. We also see that VMs with lower performance in terms of processing speed and number of CPUs have more inconsistent processing times compared to those with higher performance, while not incurring significantly higher prices. Additionally, the impact of VM parameters on computation time is explored, highlighting the importance of resource optimization in the DAS system design for efficient performance. The study also observes a notable trend in processing time, showing a significant decrease for every additional 50,000 columns processed as the length of the fiber increases. This finding underscores the efficiency gains achieved with larger computational loads, indicating improved system performance and capacity utilization as the DAS system processes more extensive datasets. Full article

Rapid technological advancements in recent years have opened the door to innovative solutions in the field of telecommunications and wireless systems; thus, new materials and manufacturing methods have been explored to satisfy this demand. This paper aims to explore the application of low-cost, commercially available 3D-printed ceramic/polymer composite filaments to design dielectric resonators (DRs) and check their suitability for use in high-frequency applications. Three-dimensional printing was used to fabricate the three-dimensional dielectric resonant prototypes. The filaments were characterized in terms of their thermal and mechanical properties and quality of printability. Additionally, the filaments’ dielectric properties were analyzed, and the prototypes were designed and simulated for a target frequency of ~2.45 GHz. Afterward, the DRs were successfully manufactured using the 3D printing technique, and no post-processing techniques were used in this study. A simple and efficient feeding method was used to finalize the devices, while the printed DRs’ reflection coefficient (S₁₁) was measured. Results on prototype size, manufacture ease, printability, cost per volume, and bandwidth (BW) were used to evaluate the materials’ suitability for high-frequency applications. This research presents an easy and low-cost manufacturing process for DRs, opening a wide range of new applications and revolutionizing the manufacturing of 3D-printed high-frequency devices. Full article

This study investigates the operational characteristics of the Rotating Detonation Engine (RDE), with a focus on fuel injector design. Inspired by the similarity between the fuel injection structure of RDE and the Jet in Supersonic Crossflow (JISC) of a scramjet, experimental research on fuel injectors with jet penetration was conducted. Five injectors were designed, each with a fixed fuel injection area or injection hole diameter. Experiments determined practical injection areas, and an empirical correlation was used to calculate jet penetration heights. Under conditions of a total mass flow rate of 105 ± 5 g/s and an equivalence ratio of 1.05 ± 0.1, combustion modes were analyzed. Initial detonation occurrence was assessed through pressure history, with a detailed analysis via image post-processing. The results indicated that the injector D4N15, with the highest jet penetration height, exhibited deflagration, while D4N23 showed chaotic propagation. The injector D2N60 demonstrated relatively unstable behavior in sustained detonation cases. Thrust comparisons revealed that D4N30, with wider hole spacing and higher jet penetration height, exhibited approximately 12.5% higher specific impulse compared to D1N240. These outcomes confirm the significant impact of jet penetration height and hole spacing on detonation propagation and engine performance. Full article

Perovskite as an emerging semiconductor luminescent material has attracted widespread attention due to its simple preparation, high luminescence quantum yield, high color purity, tunable spectrum, and ability to cover the entire visible light band. However, due to the influence of water or other highly polar solvents, oxygen, temperature, and radiation, perovskite nanocrystals will aggregate or collapse in the lattice, eventually leading to luminescence quenching. This study starts from the postprocessing of perovskite, uses methyl methacrylate as the monomer and TPO as the photoinitiator, and encapsulates the perovskite powder prepared by the hot injection method through ultraviolet light initiation. A method is proposed to improve the luminescence and crystal structure stability of perovskite. By eliminating the influence of environmental factors on perovskite nanocrystals through the dense structure formed by organic polymers, the resistance of perovskite to strong polar solvents such as water will be greatly improved, and it has great potential in the protection of perovskite. Finally, by changing the proportion of halogen elements in the perovskite resin to change the color of the luminescent resin, a fluorescent coating emitting light in all visible light bands is prepared. Fluorescent coatings are widely used in life and industry fields such as plastics, sol, and paper. Full article

Directed energy deposition (DED-LB-p) is used for the production of large components due to the high deposition rates. The large number of process parameters and printing strategies makes it difficult to optimize this process to achieve the optimal properties. Intensive post-processing is still the main obstacle to the widespread use of this process. In this work, the influence of different printing strategies and process parameters on the microstructural and tensile mechanical performance at room temperature is investigated. The porosity is measured in both printing directions. The grain orientation and size are analyzed by EBSD. A very low porosity of less than 0.4% is found in all the printed samples. The samples printed with the optimized offset printing strategy show a significant improvement in tensile strength of 1000 MPa without heat treatment compared to the other processing routes. Full article

Cardiovascular diseases (CVD) remain the leading cause of mortality among older adults. Early detection is critical as the prognosis for advanced-stage CVD is often poor. Consequently, non-invasive diagnostic tools that can assess hemodynamic function, particularly of the aorta, are essential. Computational fluid dynamics (CFD) has emerged as a promising method for simulating cardiovascular dynamics efficiently and cost-effectively, using increasingly accessible computational resources. This study developed a CFD model to assess the aorta geometry using tetrahedral and polyhedral meshes. A healthy aorta was modeled with mesh sizes ranging from 0.2 to 1 mm. Key hemodynamic parameters, including blood pressure waveform, pressure difference, wall shear stress (WSS), and associated wall parameters like relative residence time (RRT), oscillatory shear index (OSI), and endothelial cell activation potential (ECAP) were evaluated. The performance of the CFD simulations, focusing on accuracy and processing time, was assessed to determine clinical viability. The CFD model demonstrated clinically acceptable results, achieving over 95% accuracy while reducing simulation time by up to 54%. The entire simulation process, from image construction to the post-processing of results, was completed in under 120 min. Both mesh types (tetrahedral and polyhedral) provided reliable outputs for hemodynamic analysis. This study provides a novel demonstration of the impact of mesh type in obtaining accurate hemodynamic data, quickly and efficiently, using CFD simulations for non-invasive aortic assessments. The method is particularly beneficial for routine check-ups, offering improved diagnostics for populations with limited healthcare access or higher cardiovascular disease risk. Full article

This study examines the wettability behaviour of 304 stainless steel (304SS) and Ti-6Al-4V (Ti64) surfaces after sequential nanosecond (ns) and picosecond (ps) laser texturing; in particular, how the multi-scale surface structures created influence the lifecycle of surface hydrophobicity. The effect of different post-process treatments is also examined. Surfaces were analysed using Scanning Electron Microscopy (SEM), a white light interferometer optical profiler, and Energy Dispersive X-ray (EDX) spectroscopy. Wettability was assessed through sessile drop contact angle (CA) measurements, conducted at regular intervals over periods of up to 12 months, while EDX scans monitored elemental chemical changes. The results show that sequential (ns + ps) laser processing produced multi-scale surface texture with laser-induced periodic surface structures (LIPSS). Compared to the ns laser case, the (ns + ps) laser processed surfaces transitioned more rapidly to a hydrophobic state and maintained this property for much longer, especially when the single post-process treatment was ultrasonic cleaning. Some interesting features in CA development over these extended timescales are revealed. For 304SS, hydrophobicity was reached in 1–2 days, with the CA then remaining in the range of 120 to 140° for up to 180 days; whereas the ns laser-processed surfaces took longer to reach hydrophobicity and only maintained the condition for up to 30 days. Similar results were found for the case of Ti64. The findings show that such multi-scale structured metal surfaces can offer relatively stable hydrophobic properties, the lifetime of which can be extended significantly through the appropriate selection of laser process parameters and post-process treatment. The addition of LIPSS appears to help extend the longevity of the hydrophobic property. In seeking to identify other factors influencing wettability, from our EDX results, we observed a significant and steady rate of increase in the carbon content at the surface over the study period. Full article

Mycelium-bound composites (MBCs) represent a promising advancement in bio-based building materials, offering sustainable alternatives for engineering and construction applications. This review provides a comprehensive overview of the current research landscape, production methodologies, and standardization ideas related to MBCs. A basic search on Scopus revealed over 250 publications on MBCs between 2020 and 2024, with more than 30% focusing on engineering and materials science. Key studies have investigated the physical and mechanical properties of MBCs, optimizing parameters such as substrate type, fungal species, incubation time, and post-processing to enhance material performance. Standardizing the inspection of MBC properties is crucial for ensuring quality and reliability. Various testing standards, including those from the American Society for Testing and Materials (ASTM), the International Organization for Standardization (ISO), the Japanese Industrial Standard (JIS), European Standards (EN), Deutsches Institut für Normung (DIN), and the Thai Industrial Standards Institute (TIS), are utilized to evaluate density, water absorption, compression strength, tensile strength, insulation, and other critical properties. This review highlights the distinction between lab-scale and apply-scale testing methodologies, emphasizing the need for comprehensive evaluation protocols. Additionally, the production process of MBCs involves critical steps like substrate preparation, fungal species selection, and mycelium growth, necessitating the implementation of good manufacturing practices (GMPs) to ensure consistency and quality. The internal and external structures of MBCs significantly influence their performance, necessitating standardized inspection methods using advanced techniques such as scanning electron microscopy (SEM), X-ray computed tomography (CT) scanning, and surface profilometry. By establishing robust inspection protocols and production standards, the industry can enhance the reliability and adoption of MBCs, contributing to innovations in materials science and promoting environmental sustainability. This review underscores the importance of interdisciplinary collaboration, advanced characterization tools, and regulatory frameworks to address challenges and advance the field of MBCs. Full article

As the fatigue properties of as-built components of additively manufactured (AM) metals are considerably weaker than those of wrought metals because of their rougher surface, post-processing is necessary to improve the fatigue properties. To demonstrate the improvement in the fatigue properties of AM metals via post-processing methods, the fabrication of AlSi10Mg, i.e., PBF–LS/AlSi10Mg, through powder bed fusion (PBF) using laser sintering (LS) and its treatment via submerged laser peening (SLP), using a fiber laser and/or a Nd/YAG laser, was evaluated via plane bending fatigue tests. In SLP, laser ablation (LA) is generated by a pulsed laser and a bubble is generated after LA, which behaves like a cavitation bubble that is referred to as “laser cavitation (LC)”. In this paper, LA-dominated SLP is referred to as “laser treatment (LT)”, while LC collapse-dominated SLP is referred to as “laser cavitation peening (LCP)”, as the impact of LC collapse is used for peening. It was revealed that SLP using a fiber laser corresponded with LT rather than LCP. It was demonstrated that the fatigue strength at N = 10⁷ was 85 MPa for LCP and 103 MPa for the combined process of blasting (B) + LT + LCP, whereas the fatigue strength of the as-built specimen was 54 MPa. Full article

Atrial wall thickness (AWT) is a significant factor in understanding the pathological physiological substrate of atrial fibrillation, with a potentially substantial impact on the outcomes of catheter ablation procedures. Precise measurements of the AWT may provide valuable insights for categorising patients with AF and planning targeted interventions. Objectives: The purpose of this study was to evaluate the characteristics of the left atrium (LA) using non-invasive multidetector computed tomography (MDCT) scans and subsequent three-dimensional (3D) image post-processing using novel software designed to calculate atrial thickness dimensions and mass. Methods: We retrospectively analysed 128 consecutive patients (33.6% females; mean age 55.6 ± 11.2 years) referred for AF ablation (37 with persistent AF and 91 with paroxysmal AF) who underwent preprocedural MDCT. The images were post-processed and analysed using the ADAS software (Galgo Medical), automatically calculating the LA volume and regional wall thickness. In addition, the software employed a regional semi-automatic LA parcellation feature that divided the atrial wall into 12 segments, generating atrial wall thickness (AWT) maps per segment for each patient. Results: This study demonstrated considerable variability in the average thickness of LA walls, with the anterior segments being the thickest across the cohort. Distinct sex-specific differences were observed, with males exhibiting greater anterior and septal wall thickness than females. No significant associations were identified between the average AWT and body mass index, LA volume, or sphericity. Survival analysis conducted over 24 months revealed a meaningful relationship between mean anterior wall thickness and recurrence-free survival, with increased thickness associated with a lower likelihood of AF-free survival. No such relationship was observed for the indexed LA volume. Conclusions: The variability in AWT and its association with recurrence-free survival following AF ablation suggest that AWT should be considered when stratifying patients for AF management and ablation strategies. These findings underscore the need for personalised treatment approaches and further research on the interplay of the structural properties of the left atrium as factors that can serve as important prognostic markers in AF treatment. Full article

The availability of raw Global Navigation Satellites System (GNSS) measurements in Android smartphones fosters advancements in high-precision positioning for mass-market devices. However, challenges like inconsistent pseudo-range and carrier phase observations, limited dual-frequency data integrity, and unidentified hardware biases on the receiver side prevent the ambiguity resolution of smartphone GNSS. Consequently, relying solely on GNSS for high-precision positioning may result in frequent cycle slips in complex conditions such as deep urban canyons, underpasses, forests, and indoor areas due to non-line-of-sight (NLOS) and multipath conditions. Inertial/GNSS fusion is the traditional common solution to tackle these challenges because of their complementary capabilities. For pedestrians and smartphones with low-cost inertial sensors, the usual architecture is Pedestrian Dead Reckoning (PDR)+ GNSS. In addition to this, different GNSS processing techniques like Precise Point Positioning (PPP) and Real-Time Kinematic (RTK) have also been integrated with INS. However, integration with PDR has been limited and only with Kalman Filter (KF) and its variants being the main fusion techniques. Recently, Factor Graph Optimization (FGO) has started to be used as a fusion technique due to its superior accuracy. To the best of our knowledge, on the one hand, no work has tested the fusion of GNSS Post-Processed Kinematics (PPK) and PDR on smartphones. And, on the other hand, the works that have evaluated the fusion of GNSS and PDR employing FGO have always performed it using the GNSS Single-Point Positioning (SPP) technique. Therefore, this work aims to combine the use of the GNSS PPK technique and the FGO fusion technique to evaluate the improvement in accuracy that can be obtained on a smartphone compared with the usual GNSS SPP and KF fusion strategies. We improved the Google Pixel 4 smartphone GNSS using Post-Processed Kinematics (PPK) with the open-source RTKLIB 2.4.3 software, then fused it with PDR via KF and FGO for comparison in offline mode. Our findings indicate that FGO-based PDR+GNSS–PPK improves accuracy by 22.5% compared with FGO-based PDR+GNSS–SPP, which shows smartphones obtain high-precision positioning with the implementation of GNSS–PPK via FGO. Full article

The paper explains how nano exposure is assessed in the construction field and focuses on the production of fire-resistant insulation panels with nanoclay. Utilizing the commercial ANSYS CFX^® software, a preliminary theoretical simulation was conducted on nano exposure in the workplace, which revealed that particle dispersion is primarily driven by diffusion. Panel post-processing through drilling results in the highest inhalation exposure, followed by mixing and grinding activities. Compared to a state of ‘no activity’, each activity resulted in an exposure increase by a factor of min. 1000. An overall assessment suggests that the use of nanoparticles in construction materials may not significantly heighten workers’ exposure to nanopowders when considering particle concentration alone as opposed to using traditional micro-scale materials. However, the issue persists when it comes to blending powders or performing finishing tasks on panels, with concentration levels being significantly higher for drilling, grinding, and mixing powders at 2.4 times above the standard reference value (40,000 particles/cm³); this is unacceptable, even for brief durations. Examination of dermal contact with gloves and masks worn by workers revealed no nanoparticle penetration. Safety measures were proposed for workers based on decision trees to enhance their safety. Ten categories of protection strategies have been devised to combat the impact of nanoparticles, which are tailored to specific technical situations, but they must be modified for various types of nanoparticles despite potential shared health implications. Full article

In this paper, we investigate and propose the application of an unsupervised machine learning clustering method to characterize the spatial and temporal distribution of ionospheric plasma irregularities over the Western African equatorial region. The ordinary Kriging algorithm was used to interpolate the rate of change of the total electron content (TEC) index (ROTI) over gridded 0.5° by 0.5° latitude and longitude regional maps in order to simulate the level of ionospheric plasma irregularities in a quasi-real-time scenario. K-means was used to obtain a spatial mean index through an optimal stratification of regional post-processed ROTI maps. The results obtained could be adapted by appropriate K-means algorithms to a real-time scenario, as has been performed for other applications. This method could allow us to monitor plasma irregularities in real time over the African region and, therefore, lead to the possibility of mitigating their effects on satellite-based location systems in the said region. Full article