Currently, cloud services have become a novel business model for information services owing to the rapid development of Cloud Computing (CC) technology. Hence, an efficient Smart Contract (SC) creation for cloud data ...
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The amount of information nowadays is rapidly growing. Aside from valuable information, information that is unrelated to a target or is meaningless is also growing. Big data and broader digital technologies are consid...
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The development of Deepfakes has become more prevalent with the rise of Generative Adversarial Networks (GANs). Deepfakes are synthetically created, modified images that have been made to look real;they pose severe so...
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Automated Guided Vehicle(AGV)scheduling problem is an emerging research topic in the recent *** paper studies an integrated scheduling problem comprising task assignment and path planning for *** reduce the transporta...
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Automated Guided Vehicle(AGV)scheduling problem is an emerging research topic in the recent *** paper studies an integrated scheduling problem comprising task assignment and path planning for *** reduce the transportation cost of AGVs,this work also proposes an optimization method consisting of the total running distance,total delay time,and machine loss cost of AGVs.A mathematical model is formulated for the problem at hand,along with an improved Discrete Invasive Weed Optimization algorithm(DIWO).In the proposed DIWO algorithm,an insertion-based local search operator is developed to improve the local search ability of the algorithm.A staggered time departure heuristic is also proposed to reduce the number of AGV collisions in path *** experiments are conducted,and 100 instances from actual factories have proven the effectiveness of the optimization method.
Attackers try to forge or delete personal information access records to hide traces of their attacks. As personal information access records can be used to analyze infringement accidents or as legal evidence in the ev...
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In serverless computing, the service provider takes full responsibility for function management. However, serverless computing has many challenges regarding data security and function scheduling. To address these chal...
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The development of natural language processing has been facilitated by introducing numerous high-quality datasets and cutting-edge methodologies. Downstream NLP tasks, including sentiment analysis, are essential for c...
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This paper presents an approach to improve medical image retrieval, particularly for brain tumors, by addressing the gap between low-level visual and high-level perceived contents in MRI, X-ray, and CT scans. Traditio...
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This paper presents an approach to improve medical image retrieval, particularly for brain tumors, by addressing the gap between low-level visual and high-level perceived contents in MRI, X-ray, and CT scans. Traditional methods based on color, shape, or texture are less effective. The proposed solution uses machine learning to handle high-dimensional image features, reducing computational complexity and mitigating issues caused by artifacts or noise. It employs a genetic algorithm for feature reduction and a hybrid residual UNet(HResUNet) model for Region-of-Interest(ROI) segmentation and classification, with enhanced image preprocessing. The study examines various loss functions, finding that a hybrid loss function yields superior results, and the GA-HResUNet model outperforms the HResUNet. Comparative analysis with state-of-the-art models shows a 4% improvement in retrieval accuracy.
In the field of machine learning, the classification of musical instrument sounds is becoming popular. The aim of this work is to automate the identification and categorization of diverse musical instruments based on ...
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The quick advancement in AI has led to the development of refined large language models (LLM). While LLM is a specific type of generative AI focused on generative text generative AI is a broader category encompassing ...
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