Community detection is a valuable tool for studying the function and dynamic structure of most real-world networks. Existing techniques either concentrate on the network's topological structure or node properties ...
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The emergence of the Internet-of-Things is anticipated to create a vast market for what are known as smart edge devices,opening numerous opportunities across countless domains,including personalized healthcare and adv...
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The emergence of the Internet-of-Things is anticipated to create a vast market for what are known as smart edge devices,opening numerous opportunities across countless domains,including personalized healthcare and advanced *** 3D integration,edge devices can achieve unprecedented miniaturization while simultaneously boosting processing power and minimizing energy ***,we demonstrate a back-end-of-line compatible optoelectronic synapse with a transfer learning method on health care applications,including electroencephalogram(EEG)-based seizure prediction,electromyography(EMG)-based gesture recognition,and electrocardiogram(ECG)-based arrhythmia *** experiments on three biomedical datasets,we observe the classification accuracy improvement for the pretrained model with 2.93%on EEG,4.90%on ECG,and 7.92%on EMG,*** optical programming property of the device enables an ultralow power(2.8×10^(-13) J)fine-tuning process and offers solutions for patient-specific issues in edge computing ***,the device exhibits impressive light-sensitive characteristics that enable a range of light-triggered synaptic functions,making it promising for neuromorphic vision *** display the benefits of these intricate synaptic properties,a 5×5 optoelectronic synapse array is developed,effectively simulating human visual perception and memory *** proposed flexible optoelectronic synapse holds immense potential for advancing the fields of neuromorphic physiological signal processing and artificial visual systems in wearable applications.
Distance and size estimation of objects of interests is an inevitable task for many navigation and obstacle avoidance algorithms mainly used in autonomus and robotic systems. Stereo vision systems, inspired by human v...
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This research proposes a quad-mode H-beam metasurface (MTS)-embedded dual-band circularly-polarized (CP) multi-tiered antenna scheme with 5G (n79) and Wi-Fi 6E capabilities. The proposed antenna scheme consists of thr...
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Effective management of electricity consumption (EC) in smart buildings (SBs) is crucial for optimizing operational efficiency, cost savings, and ensuring sustainable resource utilization. Accurate EC prediction enabl...
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This work introduces novel architecture components and training procedures to create augmented neural networks with the ability to process data bidirectionally via an end-to-end approximate inverse. We develop pseudoi...
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The increasing penetration of renewable energy resources with highly fluctuating outputs has placed increasing concern on the accuracy and timeliness of electric power system state estimation(SE).Meanwhile,we note tha...
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The increasing penetration of renewable energy resources with highly fluctuating outputs has placed increasing concern on the accuracy and timeliness of electric power system state estimation(SE).Meanwhile,we note that only a fraction of system states fluctuate at the millisecond level and require to be *** such,refreshing only those states with significant variation would enhance the computational efficiency of SE and make fast-continuous update of states ***,this is difficult to achieve with conventional SE methods,which generally refresh states of the entire system every 4–5 *** this context,we propose a local hybrid linear SE framework using stream processing,in which synchronized measurements received from phasor measurement units(PMUs),and trigger/timingmode measurements received from remote terminal units(RTUs)are used to update the associated local ***,the measurement update process efficiency and timeliness are enhanced by proposing a trigger measurement-based fast dynamic partitioning algorithm for determining the areas of the system with states requiring *** particular,non-iterative hybrid linear formulations with both RTUs and PMUs are employed to solve the local SE *** timeliness,accuracy,and computational efficiency of the proposed method are demonstrated by extensive simulations based on IEEE 118-,300-,and 2383-bus systems.
In this paper,a combined robust fault detection and isolation scheme is studied for satellite system subject to actuator faults,external disturbances,and parametric *** proposed methodology incorporates a residual gen...
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In this paper,a combined robust fault detection and isolation scheme is studied for satellite system subject to actuator faults,external disturbances,and parametric *** proposed methodology incorporates a residual generation module,including a bank of filters,into an intelligent residual evaluation ***,residual filters are designed based on an improved nonlinear differential algebraic approach so that they are not affected by external *** residual evaluation module is developed based on the suggested series and parallel ***,a new ensemble classification scheme defined as blended learning integrates heterogeneous classifiers to enhance the performance.A wide range of simulations is carried out in a high-fidelity satellite simulator subject to the constant and time-varying actuator faults in the presence of disturbances,manoeuvres,uncertainties,and *** obtained results demonstrate the effectiveness of the proposed robust fault detection and isolation method compared to the traditional nonlinear differential algebraic approach.
Due to the complex structure and large size of large-capacity oil-immersed power transformers,it is difficult to predict the winding temperature distribution directly by numerical analysis.A 180 MVA,220 kV oil-immerse...
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Due to the complex structure and large size of large-capacity oil-immersed power transformers,it is difficult to predict the winding temperature distribution directly by numerical analysis.A 180 MVA,220 kV oil-immersed self-cooling power transformer is used as the research *** authors decouple the internal fluid domain of the power transformer into four regions:high voltage windings,medium voltage windings,low voltage windings,and radiators through fluid networks and establish the 3D fluidtemperature field numerical analysis model of the four regions,*** results of the fluid network model are used as the inlet boundary conditions for the 3D fluidtemperature numerical analysis *** turn,the fluid resistance of the fluid network model is corrected according to the results of the 3D fluid-temperature field numerical analysis *** prediction of the temperature distribution of windings is realised by the coupling calculation between the fluid network model and the 3D fluid-temperature field numerical analysis *** on this,the effect of the loading method of the heat source is also investigated using the proposed *** hotspot temperatures of the high-voltage,medium-voltage,and low-voltage windings are 89.43,86.33,and 80.96°C,***,an experimental platform is built to verify the *** maximum relative error between calculated and measured values is 4.42%,which meets the engineering accuracy requirement.
Cloud computing is an emerging field in information technology, enabling users to access a shared pool of computing resources. Despite its potential, cloud technology presents various challenges, with one of the most ...
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