In this study, we utilize a recently proposed non-parametric metaheuristic algorithm known as geometric mean optimization (GMO) to adjust the hidden layer input weights and bias of six ANN variants, namely PSNN, SPNN,...
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Cloud is based on the underlying technology of virtualization. Here, the physical servers are divided into multiple virtual servers. Through the technology of virtualization, each virtual server contains virtual machi...
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The highly infectious and mutating COVID-19, known as the novel coronavirus, poses a substantial threat to both human health and the global economy. Detecting COVID-19 early presents a challenge due to its resemblance...
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Numerous neural network(NN)applications are now being deployed to mobile *** applications usually have large amounts of calculation and data while requiring low inference latency,which poses challenges to the computin...
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Numerous neural network(NN)applications are now being deployed to mobile *** applications usually have large amounts of calculation and data while requiring low inference latency,which poses challenges to the computing ability of mobile ***,devices’life and performance depend on ***,in many scenarios,such as industrial production and automotive systems,where the environmental temperatures are usually high,it is important to control devices’temperatures to maintain steady *** this paper,we propose a thermal-aware channel-wise heterogeneous NN inference *** contains two parts,the thermal-aware dynamic frequency(TADF)algorithm and the heterogeneous-processor single-layer workload distribution(HSWD)*** on a mobile device’s architecture characteristics and environmental temperature,TADF can adjust the appropriate running speed of the central processing unit and graphics processing unit,and then the workload of each layer in the NN model is distributed by HSWD in line with each processor’s running speed and the characteristics of the layers as well as heterogeneous *** experimental results,where representative NNs and mobile devices were used,show that the proposed method can considerably improve the speed of the on-device inference by 21%–43%over the traditional inference method.
Pretrained language models (PLMs) have shown remarkable performance on question answering (QA) tasks, but they usually require fine-tuning (FT) that depends on a substantial quantity of QA pairs. Therefore, improving ...
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Purpose-The paper aims to introduce an efficient routing algorithm for wireless sensor networks(WSNs).It proposes an improved evaporation rate water cycle(improved ER-WC)algorithm and outlining the systems performance...
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Purpose-The paper aims to introduce an efficient routing algorithm for wireless sensor networks(WSNs).It proposes an improved evaporation rate water cycle(improved ER-WC)algorithm and outlining the systems performance in improving the energy efficiency of *** proposed technique mainly analyzes the clustering problem of WSNs when huge tasks are ***/methodology/approach-This proposed improved ER-WC algorithm is used for analyzing various factors such as network cluster-head(CH)energy,CH location and CH density in improved *** proposed study will solve the energy efficiency and improve network throughput in ***-This proposed work provides optimal clustering method for Fuzzy C-means(FCM)where efficiency is improved in *** evaluations are conducted to find network lifespan,network throughput,total network residual energy and network *** limitations/implications-The proposed improved ER-WC algorithm has some implications when different energy levels of node are used in *** implications-This research work analyzes the nodes’energy and throughput by selecting correct CHs in intra-cluster *** can possibly analyze the factors such as CH location,network CH energy and CH ***/value-This proposed research work proves to be performing better for improving the network throughput and increases energy efficiency for WSNs.
As one of the most representative recommendation solutions, traditional collaborative filtering (CF) models typically have limitations in dealing with large-scale, sparse data to capture complex relationships between ...
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Background: Investors estimate how a company's stock or financial instrument will perform in the future, which is known as the stock market prediction. Stock markets are one of the many industries that have benefi...
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The COVID-19 pandemic has resulted in a significant increase in the number of pneumonia cases, including those caused by the Coronavirus. To detect COVID pneumonia, RT-PCR is used as the primary detection tool for COV...
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As the power demand in data centers is increasing,the power capacity of the power supply system has become an essential resource to be *** many data centers use power oversubscription to make full use of the power cap...
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As the power demand in data centers is increasing,the power capacity of the power supply system has become an essential resource to be *** many data centers use power oversubscription to make full use of the power capacity,there are unavoidable power supply risks associated with ***,how to improve the data center power capacity utilization while ensuring power supply security has become an important *** solve this problem,we first define it and propose a risk evaluation metric called Weighted Power Supply Risk(WPSRisk).Then,a method,named Hybrid Genetic Algorithm with Ant Colony System(HGAACS),is proposed to improve power capacity utilization and reduce power supply risks by optimizing the server placement in the power supply *** uses historical power data of each server to find a better placement solution by population *** possesses not only the remarkable local search ability of Ant Colony System(ACS),but also enhances the global search capability by incorporating genetic operators from Genetic Algorithm(GA).To verify the performance of HGAACS,we experimentally compare it with five other placement *** experimental results show that HGAACS can perform better than other algorithms in both improving power utilization and reducing the riskof powersupply system.
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