The purpose of this study is to quantify the load generated on the buttocks during wheelchair operation in order to clarify the cause of pressure injuries on the buttocks of wheelchair users. In the case of repeated m...
The purpose of this study is to quantify the load generated on the buttocks during wheelchair operation in order to clarify the cause of pressure injuries on the buttocks of wheelchair users. In the case of repeated measurements, pressure injuries may occur by conducting experiments with people with actual disabilities. In this study, we proposed a method of dynamic simulation using a humanoid model in order to carry out buttock load safely due to exercise. In addition, the load on the buttocks is quantified by reproducing a simulated cushion that reproduces the actual physical properties on the simulator. When we conducted an evaluation experiment of the developed simulation to quantify the buttock load, we confirmed the validity of this simulator in the front-back direction. On the other hand, the correlation with the actual data is low in the left-right direction, and it is considered necessary to improve the humanoid model in order to improve the accuracy.
A balanced microstrip filtering phase shifter using 2 three-end folded coupled lines and 3 transmission lines is proposed. With such structure, multiple differential-mode (DM) transmission zeros (TZs) or common-mode (...
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Antibiotics have garnered growing attention as pharmaceuticals ubiquitously present in human society. Within the soil environment, antibiotics exhibit a propensity for high environmental persistence, thereby posing a ...
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Pt modified CoNiCrAl medium-entropy alloys (MEAs) with dual-phase were designed and optimized with novel long-term oxidation resistance life at 1100 °C. MEAs have a lower oxidation rate, and water vapour accelera...
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Sodium(Na)metal batteries with a high volumetric energy density that can be operated at high rates are highly ***,an uneven Na-ion migration in bulk Na anodes leads to localized deposition/dissolution of sodium during...
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Sodium(Na)metal batteries with a high volumetric energy density that can be operated at high rates are highly ***,an uneven Na-ion migration in bulk Na anodes leads to localized deposition/dissolution of sodium during high-rate plating/stripping behaviors,followed by severe dendrite growth and loose ***,we engineer the Na hybrid anode with sodiophilic Na_(3)Bi-penetration to develop the abundant phase-boundary ionic transport *** to intrinsic Na,the reduced adsorption energy and ion-diffusion barrier on Na_(3)Bi ensure even Na^(+)nucleation and rapid Na^(+)migration within the hybrid electrode,leading to uniform deposition and dissolution at high current ***,the bismuthide enables compact Na deposition within the sodiophilic framework during cycling,thus favoring a high volumetric ***,the obtained anode was endowed with a high current density(up to 5 mA∙cm^(−2)),high areal capacity(up to 5 mA∙h∙cm^(−2)),and long-term cycling stability(up to 2800 h at 2 mA∙cm^(−2)).
We present a microscopic simulation of particles with time-dependent spins,where different interaction and density are *** has been observed for the attractive spin-spin interaction,while antiferromagnetism and parama...
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We present a microscopic simulation of particles with time-dependent spins,where different interaction and density are *** has been observed for the attractive spin-spin interaction,while antiferromagnetism and paramagnetism have been observed in different density region for the repulsive spin-spin *** method developed here should be extended to include spin-color interaction into“color molecular dynamics”.
Sequential Recommender Systems (SRS), leveraging the temporal information from users' behaviors, have noticeably improved user experience against traditional systems. However, these behaviors often follow long-tai...
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ISBN:
(数字)9781665410205
ISBN:
(纸本)9781665410212
Sequential Recommender Systems (SRS), leveraging the temporal information from users' behaviors, have noticeably improved user experience against traditional systems. However, these behaviors often follow long-tail distribution, making the systems biased towards popular items (i.e., popularity bias). Moreover, popularity bias would amplify the neglect of long-tail recommendations, thereby sharpening the long-tail problem. Previous researches usually address these challenges independently, focusing on reducing the over-recommendation of popular items or enhancing the representation quality of tail items. Indeed, it is possible to incorporate their merits to achieve the best of both worlds. Thus, we propose a novel and unified framework, named Collaborative Solution to Long tailed problem and Popularity bias (CSLP), to tackle both the long-tail problem and popularity bias simultaneously. To achieve this, we first introduce a representation enhancement module featuring dual generators to enhance user and item representations, particularly for those in the tail. On the other hand, a debiasing module incorporating an Inverse Propensity Score (IPS) with a clipping strategy is introduced to further alleviate the popularity bias. Specifically, this clipping strategy demonstrates a clear decrease in the original IPS method's variance, effectively improving the recommendation for stability and accuracy. Experiments on three widely-used datasets show CSLP's effectiveness in solving both issues. CSLP surpasses all baselines (traditional, popularity bias, and long-tail problem) in overall performance, significantly enhancing recommendation accuracy for both tail users and items, and achieving a more balanced ratio of recommendations between popular and tail items. Code is available at https://***/Echohuangyan/CSLP.
The von Neumann bottleneck and memory wall have posed fundamental limitations in latency and energy consumption of modern computers based on von Neumann architecture. In-memory computing represents a radical shift in ...
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The von Neumann bottleneck and memory wall have posed fundamental limitations in latency and energy consumption of modern computers based on von Neumann architecture. In-memory computing represents a radical shift in the computer architecture that can address such problems by merging computing functions within the memory itself. In this article, we review the emerging nonvolatile memory devices,such as resistance-based and charge-based memory devices, that are explored for in-memory computing applications. We will provide an overview of the materials, mechanisms, and integration of these devices,and discuss the optimizations at the device and array levels that are required to better support in-memory computing. Recent progress in the application of in-memory computing in artificial neural networks, spiking neural networks, digital logic in memory as well as hardware security will also be discussed. Finally, we will discuss the remaining challenges in this field and potential pathways to address them.
Moving objects’ trajectory data is becoming increasingly available with the omnipresent GPS-equipped devices, e.g., smart phones, smart watches, etc. Identification of similar trajectories is a fundamental requiremen...
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ISBN:
(数字)9798350369199
ISBN:
(纸本)9798350369205
Moving objects’ trajectory data is becoming increasingly available with the omnipresent GPS-equipped devices, e.g., smart phones, smart watches, etc. Identification of similar trajectories is a fundamental requirement of many real-world applications, for instance, car pooling, road planning, epidemic contact tracing. There exist a number of studies focusing on trajectory similarity search, where given a query trajectory, similar trajectories are searched from a trajectory store. GPS devices generate trajectories as a continuous data stream, highlighting the critical need for real-time and continuous trajectory similarity search. Thus, given a trajectories stream ($S_{\Gamma}$) and a trajectory store (R), we propose a distributed, continuous and real-time similarity search between $S_{\Gamma}$ and R. The proposed method employs an index-based strategy to facilitate effective similarity search, with the added capability of execution in distributed environments to ensure scalable processing. A comprehensive empirical study is provided to demonstrate the efficiency and pruning capability of the proposed approach.
Voltage-induced dynamic switching in magnetic tunnel junctions (MTJs) is a writing technique for voltage-controlled magnetoresistive random access memory (VCMRAM), which is expected to be an ultimate nonvolatile memor...
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Voltage-induced dynamic switching in magnetic tunnel junctions (MTJs) is a writing technique for voltage-controlled magnetoresistive random access memory (VCMRAM), which is expected to be an ultimate nonvolatile memory with ultralow power consumption. In conventional dynamic switching, the width of subnanosecond write voltage pulses must be precisely controlled to achieve a sufficiently low write-error rate (WER). This very narrow tolerance of pulse width is the biggest technical difficulty in developing VCMRAM. Heavily damped precessional switching is a writing scheme for VCMRAM with a substantially high tolerance of pulse width, although the minimum WER has been much higher than that of conventional dynamic switching with an optimum pulse width. In this study, we theoretically investigate the effect of MTJ shape and the direction of the applied magnetic field on the WER of heavily damped precessional switching. The results show that the WER in elliptical-cylinder MTJs can be several orders of magnitude smaller than that in usual circular-cylinder MTJs when the external magnetic field is applied parallel to the minor axis of the ellipse. The reduction in the WER is due to the fact that the demagnetization field narrows the component of the magnetization distribution perpendicular to the plane direction immediately before the voltage is applied.
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