This study presents the design and application of a cascaded voltage-mode (VM) first-order all-pass filter (APF) integrated circuit (IC) based on a positive differential current conveyor (DDCC+). The proposed single- ...
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The use of computing systems is expected to significantly increase with the rapid proliferation of high-speed computing networks, and their use in modern internet integrated power systems. The increased adoption of co...
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Graphene oxide(GO)is a 2D coating material used to improve fiber optics sensors’response to relative *** resonators(MBRs)have garnered more attention as sensing media *** MBR with a 190μm diameter was coated with **...
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Graphene oxide(GO)is a 2D coating material used to improve fiber optics sensors’response to relative *** resonators(MBRs)have garnered more attention as sensing media *** MBR with a 190μm diameter was coated with ***,tapered fiber light coupling was used to investigate the relative humidity sensing performance in the range of 35—70%RH at 25℃.The MBR showed a higher Q factor before and after GO *** sensitivity of 0.115 dB/%RH was recorded with the 190μm GO-coated MBR sample compared to a sensitivity of 0.022 dB/%RH for the uncoated MBR *** results show that the MBR can be used in fiber optic sensing applications for environmental sensing.
Reliable and accurate short-term forecasting of residential load plays an important role in DSM. However, the high uncertainty inherent in single-user loads makes them difficult to forecast accurately. Various traditi...
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In the last decade, the water and electricity industry has experienced significant investments in smart grid technologies. Within a smart grid framework, information and energy engage in bidirectional transmission, op...
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The proposed research aims to simplify the process of maintaining and monitoring aquariums. Automated operations like temperature, light, and water level monitoring can be performed using the Arduino NANO. The three p...
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Gradient compression is a promising approach to alleviating the communication bottleneck in data parallel deep neural network (DNN) training by significantly reducing the data volume of gradients for synchronization. ...
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Gradient compression is a promising approach to alleviating the communication bottleneck in data parallel deep neural network (DNN) training by significantly reducing the data volume of gradients for synchronization. While gradient compression is being actively adopted by the industry (e.g., Facebook and AWS), our study reveals that there are two critical but often overlooked challenges: 1) inefficient coordination between compression and communication during gradient synchronization incurs substantial overheads, and 2) developing, optimizing, and integrating gradient compression algorithms into DNN systems imposes heavy burdens on DNN practitioners, and ad-hoc compression implementations often yield surprisingly poor system performance. In this paper, we propose a compression-aware gradient synchronization architecture, CaSync, which relies on flexible composition of basic computing and communication primitives. It is general and compatible with any gradient compression algorithms and gradient synchronization strategies and enables high-performance computation-communication pipelining. We further introduce a gradient compression toolkit, CompLL, to enable efficient development and automated integration of on-GPU compression algorithms into DNN systems with little programming burden. Lastly, we build a compression-aware DNN training framework HiPress with CaSync and CompLL. HiPress is open-sourced and runs on mainstream DNN systems such as MXNet, TensorFlow, and PyTorch. Evaluation via a 16-node cluster with 128 NVIDIA V100 GPUs and a 100 Gbps network shows that HiPress improves the training speed over current compression-enabled systems (e.g., BytePS-onebit, Ring-DGC and PyTorch-PowerSGD) by 9.8%-69.5% across six popular DNN models. IEEE
False data injection attack(FDIA)is an attack that affects the stability of grid cyber-physical system(GCPS)by evading the detecting mechanism of bad *** FDIA detection methods usually employ complex neural networkmod...
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False data injection attack(FDIA)is an attack that affects the stability of grid cyber-physical system(GCPS)by evading the detecting mechanism of bad *** FDIA detection methods usually employ complex neural networkmodels to detect FDIA ***,they overlook the fact that FDIA attack samples at public-private network edges are extremely sparse,making it difficult for neural network models to obtain sufficient samples to construct a robust detection *** address this problem,this paper designs an efficient sample generative adversarial model of FDIA attack in public-private network edge,which can effectively bypass the detectionmodel to threaten the power grid system.A generative adversarial network(GAN)framework is first constructed by combining residual networks(ResNet)with fully connected networks(FCN).Then,a sparse adversarial learning model is built by integrating the time-aligned data and normal data,which is used to learn the distribution characteristics between normal data and attack data through iterative ***,we introduce a Gaussian hybrid distributionmatrix by aggregating the network structure of attack data characteristics and normal data characteristics,which can connect and calculate FDIA data with normal ***,efficient FDIA attack samples can be sequentially generated through interactive adversarial *** simulation experiments are conducted with IEEE 14-bus and IEEE 118-bus system data,and the results demonstrate that the generated attack samples of the proposed model can present superior performance compared to state-of-the-art models in terms of attack strength,robustness,and covert capability.
As long as a computer system is connected to the Internet, it is susceptible to attack as a victim. In computer networks, it becomes important to manage the network based on parameters such as network size and network...
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In this work, initially a rectangular microstrip patch antenna measuring (94.8 × 110 × 10) μm3 with a polyamide substrate has been analyzed and developed. The antenna has a bandwidth of 170 GHz (1.98 - 2.15...
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