Interpreting deep neural networks is of great importance to understand and verify deep models for natural language processing(NLP)***,most existing approaches only focus on improving the performance of models but igno...
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Interpreting deep neural networks is of great importance to understand and verify deep models for natural language processing(NLP)***,most existing approaches only focus on improving the performance of models but ignore their *** this work,we propose a Randomly Wired Graph Neural Network(RWGNN)by using graph to model the structure of Neural Network,which could solve two major problems(word-boundary ambiguity and polysemy)of ***,we develop a pipeline to explain the RWGNNby using Saliency Map and Adversarial *** results demonstrate that our approach can identify meaningful and reasonable interpretations for hidden states of RWGNN.
Automatic speech recognition is one of the technologies that change the game regarding the transcription of spoken language to text. A new methodology combining both feature extraction methods, including the Mel-Frequ...
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Healthcare data is most unorganized and decentralized in many countries, including India. EHR (Electronic Health Record) has increased its acceptability and importance as it assists in medical research and helps backt...
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For achieving Energy-Efficiency in wireless sensor networks(WSNs),different schemes have been proposed which focuses only on reducing the energy consumption.A shortest path determines for the Base Station(BS),but faul...
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For achieving Energy-Efficiency in wireless sensor networks(WSNs),different schemes have been proposed which focuses only on reducing the energy consumption.A shortest path determines for the Base Station(BS),but fault tolerance and energy balancing gives equal importance for improving the network *** saving energy in WSNs,clustering is considered as one of the effective methods for Wireless Sensor *** of the excessive overload,more energy consumed by cluster heads(CHs)in a cluster based WSN to receive and aggregate the information from member sensor nodes and it leads to *** increasing the WSNs’lifetime,the CHs selection has played a key role in energy consumption for sensor *** Energy Efficient Unequal Fault Tolerant Clustering Approach(EEUFTC)is proposed for reducing the energy utilization through the intelligent methods like Particle Swarm Optimization(PSO).In this approach,an optimal Master Cluster Head(MCH)-Master data Aggregator(MDA),selection method is proposed which uses the fitness values and they evaluate based on the PSO for two optimal nodes in each cluster to act as Master Data Aggregator(MDA),and Master Cluster *** data from the cluster members collected by the chosen MCH exclusively and the MDA is used for collected data reception from MCH transmits to the ***,the MCH overhead *** the heavy communication of data,overhead controls using the scheduling of Energy-Efficient Time Division Multiple Access(EE-TDMA).To describe the proposed method superiority based on various performance metrics,simulation and results are compared to the existing methods.
The rampant issue of vehicle theft on a global scale demands more effective security solutions. Traditional methods like keys and alarms have shown limitations in deterring theft. This paper presents a novel approach ...
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Trained Artificial Intelligence (AI) models are challenging to install on edge devices as they are low in memory and computational power. Pruned AI (PAI) models are therefore needed with minimal degradation in perform...
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Every day,more and more data is being produced by the Internet of Things(IoT)*** data differ in amount,diversity,veracity,and *** of latency,various types of data handling in cloud computing are not suitable for many ...
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Every day,more and more data is being produced by the Internet of Things(IoT)*** data differ in amount,diversity,veracity,and *** of latency,various types of data handling in cloud computing are not suitable for many time-sensitive *** users move from one site to another,mobility also adds to the *** placing computing close to IoT devices with mobility support,fog computing addresses these *** efficient Load Balancing Algorithm(LBA)improves user experience and Quality of Service(QoS).Classification of Request(CoR)based Resource Adaptive LBA is suggested in this *** technique clusters fog nodes using an efficient K-means clustering algorithm and then uses a Decision Tree approach to categorize the *** decision-making process for time-sensitive and delay-tolerable requests is facilitated by the classification of *** does the operation based on these *** MobFogSim simulation program is utilized to assess how well the algorithm with mobility features *** outcome demonstrates that the LBA algorithm’s performance enhances the total system performance,which was attained by(90.8%).Using LBA,several metrics may be examined,including Response Time(RT),delay(d),Energy Consumption(EC),and *** the on-demand provisioning of necessary resources to IoT users,our suggested LBA assures effective resource usage.
Federated Learning (FL) provides a valuable framework that allows for the collaborative training of models across distributed networks while maintaining the privacy of the data involved. The concept of secure aggregat...
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Combined effects of asymmetric defect distributions and asymmetric gate work functions (WFs) on the performances of self-aligned dual-gate poly-Si TFTs are investigated. Normally, small grains with plentiful grain bou...
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The event management mechanism matches messages that have been subscribed to and events that have been published. To identify the subscriptions that correspond to the occurrence inside the category, it must first run ...
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