피부의 움직임을 이용한 초박형, 다변형 압전 발전기

피부 부착형 압전 발전기 , 다변형 구조 , 높은 에너지 변환 효율 , 등각접촉prohibitionⅠ. Introduction 1 1.1. Motivation 1 Ⅱ. Interdigitated electrode with piezoelectric generator 18 2.1. Ferroelectric P(VDF-TrFE) copolymer 2.2. Experiment details 20 2.2.1. Development of interdigitated electrodes 2.2.2. Fabrication of piezoelectric generators 2.2.2.1. Fabricate interdigitated electrodes 2.2.2.2. Formation of P(VDF-TrFE) filMaster 2.2.3. Bending test measurements and characterization 2.3. Results and discussion 27 2.3.1. Output performance of the piezoelectric generator 2.3.2. Optimization of the piezoelectric generator 2.3.2.1. Gap between adjacent electrodes 2.3.2.2. Electrode design 2.3.2.3. Film thickness 2.3.3. Working principle and strain calculation 2.4. Conclusion 41 Ⅲ. Ultrathin multi-deformable piezoelectric generator 42 3.1. Ultrathin piezoelectric generator 3.1.1. Stretchable wavy-ribbons 3.1.2. Conformable energy harvester 3.2. Experimental details 47 3.2.1. Ultrathin PI film substrate 3.2.2. Compression and stretching 3.2.3. Device characterization 3.3. Results and discussion 50 3.3.1. Output performance of the multi-deformable generator 3.3.2. Wavy-ribbon multi-deformation formation 3.3.3. Required energy for deformation 3.4. Conclusion 60MasterdCollectio

Performance Optimization of Object Tracking Algorithms in OpenCV on GPUs

Machine-learning-based computer vision is increasingly versatile and being leveraged by a wide range of smart devices. Due to the limited performance/energy budget of computing units in smart devices, the careful implementation of computer vision algorithms is critical. In this paper, we analyze the performance bottleneck of two well-known computer vision algorithms for object tracking: object detection and optical flow in the Open-source Computer Vision library (OpenCV). Based on our in-depth analysis of their implementation, we found the current implementation fails to utilize Open Computing Language (OpenCL) accelerators (e.g., GPUs). Based on the analysis, we propose several optimization strategies and apply them to the OpenCL implementation of object tracking algorithms. Our evaluation results demonstrate the performance of the object detection is improved by up to 86% and the performance of the optical flow by up to 10%. We believe our optimization strategies can be applied to other computer vision algorithms implemented in OpenCL

Recent Advances on Nanofiber Fabrications: Unconventional State-of-the-Art Spinning Techniques

In this review, we describe recent relevant advances in the fabrication of polymeric nanofibers to address challenges in conventional approaches such as electrospinning, namely low throughput and productivity with low size uniformity, assembly with a regulated structure and even architecture, and location with desired alignments and orientations. The efforts discussed have mainly been devoted to realize novel apparatus designed to resolve individual issues that have arisen, i.e., eliminating ejection tips of spinnerets in a simple electrospinning system by effective control of an applied electric field and by using mechanical force, introducing a uniquely designed spinning apparatus including a solution ejection system and a collection system, and employing particular processes using a ferroelectric material and reactive precursors for atomic layer deposition. The impact of these advances to ultimately attain a fabrication technique to solve all the issues simultaneously is highlighted with regard to manufacturing high-quality nanofibers with high- throughput and eventually, practically implementing the nanofibers in cutting-edge applications on an industrial scale

Performance Optimization of Object Tracking Algorithms in OpenCV on GPUs

Machine-learning-based computer vision is increasingly versatile and being leveraged by a wide range of smart devices. Due to the limited performance/energy budget of computing units in smart devices, the careful implementation of computer vision algorithms is critical. In this paper, we analyze the performance bottleneck of two well-known computer vision algorithms for object tracking: object detection and optical flow in the Open-source Computer Vision library (OpenCV). Based on our in-depth analysis of their implementation, we found the current implementation fails to utilize Open Computing Language (OpenCL) accelerators (e.g., GPUs). Based on the analysis, we propose several optimization strategies and apply them to the OpenCL implementation of object tracking algorithms. Our evaluation results demonstrate the performance of the object detection is improved by up to 86% and the performance of the optical flow by up to 10%. We believe our optimization strategies can be applied to other computer vision algorithms implemented in OpenCL

Improvement of Fog Simulation by the Nudging of Meteorological Tower Data in the WRF and PAFOG Coupled Model

Improvement of fog simulation accuracy was investigated for the fogs that occurred on the south coast of the Korean Peninsula using the WRF (3D) and PAFOG (1D) coupled model. In total, 22 fog cases were simulated and accuracy of the fog simulation was examined based on Critical Success Index, Hit Rate and False Alarm Rate. The performance of the coupled WRF-PAFOG model was better than that of the single WRF model as expected. However, much more significant improvement appeared only when the data from a 300 m meteorological tower was not only used for the initial conditions but also nudged during the simulation. Moreover, a proper prescription of soil moisture was found to be important for accurate fog simulation especially for the fog cases with prior precipitation since efficient moisture supply from the precipitation-soaked soil might have been critical for fog formation. It was also demonstrated that with such optimal coupled model setting, a coastal radiation fog event with prior precipitation could be very realistically simulated: the fog onset and dissipation times matched so well with observation. In detail, radiative cooling at the surface was critical to form a surface inversion layer as the night fell. Then the vapor flux from the precipitation-soaked surface was confined within the inversion layer to form fog. It is suggested that a proper prescription of soil moisture in the model based on observations, if readily available, could be a cost-effective method for improving operational fog forecasting, considering the fact that tall meteorological towers are a rarity in the world

Post-fabrication tuning of origami-inspired mechanical metamaterials based on Tachi-Miura Polyhedron

We investigate the reconfigurability and tunability of the tessellation of Tachi-Miura Polyhedron (TMP), an origami-based cellular structure composed of bellows-like unit cells. Lattice-based three-dimensional mechanical metamaterials have recently received significant scientific interest due to their superior and unique mechanical performance compared to conventional materials. However, it is often challenging to achieve tunability and reconfigurability from these metamaterials, since their geometry and functionality tend to be pre-determined in the design and fabrication stage. Here, we utilize TMP's highly versatile phase-transforming and tessellating capabilities to design reconfigurable metamaterial architecture with tunable mechanical properties. The theoretical analyses and experiments with heat processing discover the wide range of the in-situ tunability of the metamaterial – specifically orders of magnitude change in effective density, Young's modulus, and Poisson's ratio – after its fabrication within the elastic deformation regime. We also witness a rather unique behavior of the inverse correlation between effective density and stiffness. This mechanical platform paves the way to design the metamaterial that can actively adapt to various external environments

Non-fluorinated non-solvating cosolvent enabling superior performance of lithium metal negative electrode battery

The growth of dendrites on lithium metal electrodes is problematic because it causes irreversible capacity loss and safety hazards. Localised high-concentration electrolytes (LHCEs) can form a mechanically stable solid-electrolyte interphase and prevent uneven growth of lithium metal. However, the optimal physicochemical properties of LHCEs have not been clearly determined which limits the choice to fluorinated non-solvating cosolvents (FNSCs). Also, FNSCs in LHCEs raise environmental concerns, are costly, and may cause low cathodic stability owing to their low lowest unoccupied molecular orbital level, leading to unsatisfactory cycle life. Here, we spectroscopically measured the Li+ solvation ability and miscibility of candidate non-fluorinated non-solvating cosolvents (NFNSCs) and identified the suitable physicochemical properties for non-solvating cosolvents. Using our design principle, we proposed NFNSCs that deliver a coulombic efficiency up to 99.0% over 1400 cycles. NMR spectra revealed that the designed NFNSCs were highly stable in electrolytes during extended cycles. In addition, solvation structure analysis by Raman spectroscopy and theoretical calculation of Li+ binding energy suggested that the low ability of these NFNSCs to solvate Li+ originates from the aromatic ring that allows delocalisation of electron pairs on the oxygen atom. Localised high-concentration electrolyte is key to prevent uneven growth of lithium metal by forming a mechanically stable solid-electrolyte interphase. Here, the authors identify the suitable physicochemical properties for non-solvating co-solvents that improve the performance of lithium metal battery.N

A Case for Hardware-Based Demand Paging

© 2020 IEEE.The virtual memory system is pervasive in today's computer systems, and demand paging is the key enabling mechanism for it. At a page miss, the CPU raises an exception, and the page fault handler is responsible for fetching the requested page from the disk. The OS typically performs a context switch to run other threads as traditional disk access is slow. However, with the widespread adoption of high-performance storage devices, such as low-latency solid-state drives (SSDs), the traditional OS-based demand paging is no longer effective because a considerable portion of the demand paging latency is now spent inside the OS kernel. Thus, this paper makes a case for hardware-based demand paging that mostly eliminates OS involvement in page miss handling to provide a near-disk-access-time latency for demand paging. To this end, two architectural extensions are proposed: LBA-augmented page table that moves I/O stack operations to the control plane and Storage Management Unit that enables CPU to directly issue I/O commands without OS intervention in most cases. OS support is also proposed to detach tasks for memory resource management from the critical path. The evaluation results using both a cycle-level simulator and a real x86 machine with an ultra-low latency SSD show that the proposed scheme reduces the demand paging latency by 37.0%, and hence improves the performance of FIO read random benchmark by up to 57.1% and a NoSQL server by up to 27.3% with real-world workloads. As a side effect of eliminating OS intervention, the IPC of the user-level code is also increased by up to 7.0%.N

All-Organic, Solution-Processed, Extremely Conformal, Mechanically Biocompatible, and Breathable Epidermal Electrodes

Conformal integration of an epidermal device with the skin, as well as sweat and air permeability, are crucial to reduce stress on biological tissues. Nanofiber-based porous mesh structures (breathable devices) are commonly utilized to prevent skin problems. Noble metals are normally deposited on nanomesh substrates to form breathable electrodes. However, these are expensive and require high-vacuum processes involving time-consuming multistep procedures. Organic materials are suitable alternatives that can be simply processed in solution. We report a simple, cost-effective, mechanically biocompatible, and breathable organic epidermal electrode for biometric devices. Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) is sprayed on a nanofiber-mesh structure, treated using only heat and water to enhance its biocompatibility and conductivity, and used as the electrode. The treatment is accomplished using an autoclave, simultaneously reducing the electrical resistance and sterilizing the electrode for practical use. This research can lead to affordable and biocompatible epidermal electrodes with improved suitability for various biomedical applications. © 2020 American Chemical Society.FALS

Combined machine learning and biomolecular analysis for stability assessment of anaerobic ammonium oxidation under salt stress

In this study, the stability of the total nitrogen removal efficiency (TNRE) was modeled using an artificial neural network (ANN)-based binary classification model for the anaerobic ammonium oxidation (AMX) process under saline conditions. The TNRE was stabilized to 80.2 +/- 11.4% at the final phase under the salinity of 1.0 +/-& nbsp;0.02%. The results of terminal restriction fragment length polymorphism (T-RFLP) analysis showed the predominance of Candidatus Jettenia genus. Real-time quantitative PCR analysis revealed the average abundance of Ca. Jettenia and Kuenenia spp. increased in 3.2 +/- 5.4 x 108 and 2.0 +/- 2.2 x 105 copies/mL, respectively. The prediction accuracy using operational parameters with data augmentation was 88.2%. However, integration with T-RFLP and real-time qPCR signals improved the prediction accuracy by 97.1%. This study revealed the feasible application of machine learning and biomolecular signals to the stability prediction of the AMX process under increased salinity