Multi-label image classification is a critical task in computer vision, in which the correlations between labels are typically exploited by modern classifiers for an effective classification. In this study, we propose...
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Aiming to meet the growing demand for observation and analysis in power systems that based on Internet of Things(IoT),machine learning technology has been adopted to deal with the data-intensive power electronics appl...
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Aiming to meet the growing demand for observation and analysis in power systems that based on Internet of Things(IoT),machine learning technology has been adopted to deal with the data-intensive power electronics applications in *** feeding previous power electronic data into the learning model,accurate information is drawn,and the quality of IoT-based power services is ***,the data-intensive electronic applications with machine learning are split into numerous data/control constrained tasks by workflow *** efficient execution of this data-intensive Power Workflow(PW)needs massive computing resources,which are available in the cloud ***,the execution efficiency of PW decreases due to inappropriate sub-task and data *** addition,the power consumption explodes due to massive data *** address these challenges,a PW placement method named PWP is ***,the Non-dominated Sorting Differential Evolution(NSDE)is used to generate placement *** simulation experiments show that PWP achieves the best trade-off among data acquisition time,power consumption,load distribution and privacy preservation,confirming that PWP is effective for the placement problem.
This article presents a protocol for conducting online think-aloud interviews as well as the reflections of the participants and interviewer on this process. The interviewer and participants commenced the interviews i...
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Context:Decentralized autonomous organizations are a new form of smart contract-based *** autonomous organization platforms,which support the creation of such organizations,are becoming increasingly popular,such as Ar...
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Context:Decentralized autonomous organizations are a new form of smart contract-based *** autonomous organization platforms,which support the creation of such organizations,are becoming increasingly popular,such as Aragon and *** the best fitting platform is challenging for organizations,as a significant number of decision criteria,such as popularity,developer availability,governance issues and consistent documentation of such platforms,should be ***,decision-makers at the organizations are not experts in every domain,so they must continuously acquire volatile knowledge regarding such ***:Supporting decision-makers in selecting the right decentralized autonomous organization platforms by designing an effective decision model is the main objective of this *** aim to provide more insight into their selection process and reduce time and effort significantly by designing a decision ***:This study presents a decision model for the decentralized autonomous organization platform selection *** decision model captures knowledge regarding such platforms and concepts *** model is based on an existing theoretical framework that assists software engineers with a set of multi-criteria decision-making problems in software ***:We conducted three industry case studies in the context of three decentralized autonomous organizations to evaluate the effectiveness and efficiency of the decision model in assisting *** case study participants declared that the decision model provides significantly more insight into their selection process and reduces time and ***:We observe in the empirical evidence from the case studies that decision-makers can make more rational,efficient,and effective decisions with the decision ***,the reusable form of the captured knowledge regarding decentralized autonomous organization platforms can be
To achieve effective feedback and proficiency tracking of students in contemporary educational settings, we propose a methodology that integrates the RNN-GRU model and dynamic Bayesian networks for predicting students...
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Reasoning over the Temporal Knowledge Graph (TKG) that predicts facts in the future has received much attention. Most previous works attempt to model temporal dynamics with knowledge graphs and graph convolution netwo...
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The up-to-date and accurate building footprint database plays a significant role in a large variety of applications. Recently, remote sensing images have provided an important data source for building footprint extrac...
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Chemical accident news data encompasses essential information such as news headlines, news content, and news sources, with the context of news content playing a crucial role. To enhance the accuracy of text feature ex...
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Air Quality Index (AQI) is an important indicator for determining good or bad air quality. The accurate and efficient prediction of AQI plays a positive role in promoting the management of air pollution. However, curr...
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In the past few years,social media and online news platforms have played an essential role in distributing news content *** of the authenticity of news has become a major *** the COVID-19 outbreak,misinformation and f...
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In the past few years,social media and online news platforms have played an essential role in distributing news content *** of the authenticity of news has become a major *** the COVID-19 outbreak,misinformation and fake news were major sources of confusion and insecurity among the general *** the first quarter of the year 2020,around 800 people died due to fake news relevant to *** major goal of this research was to discover the best learning model for achieving high accuracy and performance.A novel case study of the Fake News Classification using ELECTRA model,which achieved 85.11%accuracy score,is thus reported in this *** addition to that,a new novel dataset called COVAX-Reality containing COVID-19 vaccine-related news has been *** the COVAX-Reality dataset,the performance of FNEC is compared to several traditional learning models i.e.,Support Vector Machine(SVM),Naive Bayes(NB),Passive Aggressive Classifier(PAC),Long Short-Term Memory(LSTM),Bi-directional LSTM(Bi-LSTM)and Bi-directional Encoder Representations from Transformers(BERT).For the evaluation of FNEC,standard metrics(Precision,Recall,Accuracy,and F1-Score)were utilized.
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