Versatile sensors have broad application prospects in human motion detection, health monitoring, wearable electronic devices and flexible electronic skin and other emerging fields. In this work, the enhanced hydrogel ...
Versatile sensors have broad application prospects in human motion detection, health monitoring, wearable electronic devices and flexible electronic skin and other emerging fields. In this work, the enhanced hydrogel was prepared by freezing and thawing process with calcium ion crosslinking. This composite material shows excellent flexibility and elasticity, and after being cut in half, it can automatically heal well in a short time without external force. It shows great potential in flexible and wearable devices.
Elastic fabric is comfortable to wear, and has been a consumer textile due to its good shape retention and wrinkle resistance after washing. This paper briefly introduces the types and performance characteristics of s...
Elastic fabric is comfortable to wear, and has been a consumer textile due to its good shape retention and wrinkle resistance after washing. This paper briefly introduces the types and performance characteristics of several common elastic fibers, and analyzes the relationship between the structure and elasticity of different elastic fibers. Finally, the development trend of elastic fibers is proposed.
The wide spread use of online recruitment services has led to information explosion in the job market. As a result, the recruiters have to seek the intelligent ways for Person-Job Fit, which is the bridge for adapting...
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In order to effectively obtain the signal from sensor, the analogy signal needs to be amplified and then converted into a digital signal for matching to the sensor characteristics. With a supercapacitive electric fiel...
In order to effectively obtain the signal from sensor, the analogy signal needs to be amplified and then converted into a digital signal for matching to the sensor characteristics. With a supercapacitive electric field sensor based on graphene aerogel, the response current signal from the electric field sensor is weak and unstable. Herein, a high gain and low noise preamplifier is developed, and an amplifier circuit with double T-type feedback network is proposed to reduce the Johnson noise for the amplifier. This design can reduce the thermal noise of resistance by using the smaller resistance under the same gain, and it can effectively reduce the interference of peak noise by adding the feedback capacitance, so as to improve the detection accuracy. The simulation results show that under the same gain condition, the Johnson noise can be reduced by 46% and the detection accuracy can be improved by 12% compared with the traditional T-type feedback network.
Multi-atlas segmentation approach is one of the most widely-used image segmentation techniques in biomedical applications. There are two major challenges in this category of methods, i.e., atlas selection and label fu...
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This paper investigates energy-efficient resource allocation for the two-user downlink with strict latency constraints at users. To cope with strict latency constraints, the capacity formula of the finite blocklength ...
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The frequent directions (FD) technique is a deterministic approach for online sketching that has many applications in machine learning. The conventional FD is a heuristic procedure that often outputs rank deficient ma...
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The frequent directions (FD) technique is a deterministic approach for online sketching that has many applications in machine learning. The conventional FD is a heuristic procedure that often outputs rank deficient matrices. To overcome the rank deficiency problem, we propose a new sketching strategy called robust frequent directions (RFD) by introducing a regularization term. RFD can be derived from an optimization problem. It updates the sketch matrix and the regularization term adaptively and jointly. RFD reduces the approximation error of FD without increasing the computational cost. We also apply RFD to online learning and propose an effective hyperparameter-free online Newton algorithm. We derive a regret bound for our online Newton algorithm based on RFD, which guarantees the robustness of the algorithm. The experimental studies demonstrate that the proposed method outperforms state-of-the-art second order online learning algorithms.
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known about the common practice as well as bott...
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Human parsing has been extensively studied recently (Yamaguchi et al. 2012;Xia et al. 2017) due to its wide applications in many important scenarios. Mainstream fashion parsing models (i.e., parsers) focus on parsing ...
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Human parsing has been extensively studied recently (Yamaguchi et al. 2012;Xia et al. 2017) due to its wide applications in many important scenarios. Mainstream fashion parsing models (i.e., parsers) focus on parsing the high-resolution and clean images. However, directly applying the parsers trained on benchmarks of high-quality samples to a particular application scenario in the wild, e.g., a canteen, airport or workplace, often gives non-satisfactory performance due to domain shift. In this paper, we explore a new and challenging cross-domain human parsing problem: Taking the benchmark dataset with extensive pixel-wise labeling as the source domain, how to obtain a satisfactory parser on a new target domain without requiring any additional manual labeling? To this end, we propose a novel and efficient crossdomain human parsing model to bridge the cross-domain differences in terms of visual appearance and environment conditions and fully exploit commonalities across domains. Our proposed model explicitly learns a feature compensation network, which is specialized for mitigating the cross-domain differences. A discriminative feature adversarial network is introduced to supervise the feature compensation to effectively reduces the discrepancy between feature distributions of two domains. Besides, our proposed model also introduces a structured label adversarial network to guide the parsing results of the target domain to follow the high-order relationships of the structured labels shared across domains. The proposed framework is end-to-end trainable, practical and scalable in real applications. Extensive experiments are conducted where LIP dataset is the source domain and 4 different datasets including surveillance videos, movies and runway shows without any annotations, are evaluated as target domains. The results consistently confirm data efficiency and performance advantages of the proposed method for the challenging cross-domain human parsing problem. Copyright
Dear editor,Motivated by Refs.[1–10],we devote to constructing a class of q-variable 1-resilient rotation symmetric functions（RSFs）over the finite field F;={0,1,...,p-1}in this *** this letter,let p and q be differ...
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Dear editor,Motivated by Refs.[1–10],we devote to constructing a class of q-variable 1-resilient rotation symmetric functions（RSFs）over the finite field F;={0,1,...,p-1}in this *** this letter,let p and q be different odd prime numbers.
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