Air quality is closely connected to the well-being of humans, ecosystems, and wildlife, making its continuous monitoring and preservation as a prime importance. Various causes contribute to air pollution, exerting a n...
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This paper presents an integrated Internet of Things based approach to smart surveillance and urban parking management systems, emphasizing robust object detection and precise parking occupancy monitoring. Our solutio...
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Achieving a balance between recommending popular items and long-tail items has consistently posed a challenge in the field of recommendation systems. Traditional recommendation algorithms often exhibit a bias towards ...
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This work presents a novel dual-technique method that uses Drop Attention (DA) for regularization and Attention Entropy Loss (AE) for optimization in the Swin Transformer framework to improve leaf disease classificati...
As wafer circuit width shrinks down to less than ten nanometers in recent years,stringent quality control in the wafer manufacturing process is increasingly *** to the coupling of neighboring cluster tools and coordin...
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As wafer circuit width shrinks down to less than ten nanometers in recent years,stringent quality control in the wafer manufacturing process is increasingly *** to the coupling of neighboring cluster tools and coordination of multiple robots in a multi-cluster tool,wafer production scheduling becomes rather *** a wafer is processed,due to high-temperature chemical reactions in a chamber,the robot should be controlled to take it out of the processing chamber at the right *** order to ensure the uniformity of integrated circuits on wafers,it is highly desirable to make the differences in wafer post-processing time among the individual tools in a multicluster tool as small as *** achieve this goal,for the first time,this work aims to find an optimal schedule for a dual-arm multi-cluster tool to regulate the wafer post-processing *** do so,we propose polynomial-time algorithms to find an optimal schedule,which can achieve the highest throughput,and minimize the total post-processing time of the processing *** propose a linear program model and another algorithm to balance the differences in the post-processing time between any pair of adjacent cluster *** industrial examples are given to illustrate the application and effectiveness of the proposed method.
Semantic segmentation of remote sensing urban scene imagery is a dense prediction task, which has been applied to the land-cover or land-use category. However, the dimension of remote sensing image is huge, which will...
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An individual's unwanted and unpleasant reactions that arise from regular drug use are referred to as adverse drug reactions, or ADRs. Mild side effects to serious, potentially fatal diseases can be caused by thes...
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An individual's unwanted and unpleasant reactions that arise from regular drug use are referred to as adverse drug reactions, or ADRs. Mild side effects to serious, potentially fatal diseases can be caused by these reactions. In order to guarantee the security and effectiveness of pharmacological interventions, it is imperative to track and comprehend ADRs. This paper presents an approach in pharmacovigilance to classify drug reactions caused by different drugs by combining firefly algorithm with different classifiers. The firefly algorithm assigns firefly to each subsets of features and uses the objective function in order to calculate the distance and making cluster of firefly. In the end it gives us the most optimal set of features which we further use in our classification. We also have experimented on three types of classifiers which are: Random Forest, K-Nearest Neighbour, Decision Tree. In the end we have compared the accuracy, Precision, F1 Score of different classifiers and concluded that by using firefly for feature extraction we can increase accuracy, precision and F1-score. We have also compared this Firefly algorithm with Elephant Herding Optimization (EHO) used for feature selection. We dived into the advancements and challenges faced during the prediction of reactions of drugs. There is much scope in this as we can further increase our performance and efficiency by combining multiple classifiers or using different feature extraction techniques. We used a dataset consisting of 1333 entries with 24 features from Kaggle, split into training and testing sets with a 70:30 ratio. The results demonstrate that applying the Firefly Algorithm enhances model performance. Random Forest classifier achieved the highest accuracy of 97.5% with the Firefly Algorithm, compared to 97.2% without it. Similarly, KNN and Decision Tree classifiers also showed improvements in accuracy, with KNN improving from 93.5% to 95.0% and Decision Tree improving from 96.7% to 97.0%. Add
Cloud computing technology is favored by users because of its strong computing power and convenient *** the same time,scheduling performance has an extremely efficient impact on promoting carbon ***,scheduling researc...
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Cloud computing technology is favored by users because of its strong computing power and convenient *** the same time,scheduling performance has an extremely efficient impact on promoting carbon ***,scheduling research in the multi-cloud environment aims to address the challenges brought by business demands to cloud data centers during peak ***,the scheduling problem has promising application prospects under themulti-cloud *** paper points out that the currently studied scheduling problems in the multi-cloud environment mainly include independent task scheduling and workflow task scheduling based on the dependencies between *** paper reviews the concepts,types,objectives,advantages,challenges,and research status of task scheduling in the multi-cloud *** scheduling strategies proposed in the existing related references are analyzed,discussed,and summarized,including research motivation,optimization algorithm,and related ***,the research status of the two kinds of task scheduling is compared,and several future important research directions of multi-cloud task scheduling are proposed.
Knowledge Base Question Answering (KBQA) intends to obtain credible answers to natural language questions based on knowledge bases. Knowledge graphs, also known as graph databases, explicitly present a large amount of...
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Chinese Semantic Error Recognition (CSER) has always been a weak link in Chinese language processing due to the complexity and obscureness of Chinese semantics. Existing research has gradually focused on leveraging pr...
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