Expert Systems最新文献_第10页

RETRACTION: Supply Chain Risk Management of Badminton Supplies Company Using Decision Tree Model Assisted by Fuzzy Comprehensive Evaluation

IF 3 4区计算机科学

Expert Systems Pub Date : 2024-11-07 DOI: 10.1111/exsy.13780

引用次数: 0

Developing a digital therapeutic for obesity management through 3D human body reconstruction

IF 3 4区计算机科学

Expert Systems Pub Date : 2024-11-07 DOI: 10.1111/exsy.13678

Hyunsook Lee, Sekyoung Youm

{"title":"Developing a digital therapeutic for obesity management through 3D human body reconstruction","authors":"Hyunsook Lee, Sekyoung Youm","doi":"10.1111/exsy.13678","DOIUrl":"https://doi.org/10.1111/exsy.13678","url":null,"abstract":"This study introduced a groundbreaking approach to address the pressing public health challenges of obesity management and its associated health implications. By establishing a clear link between obesity and various health issues, this study underscores the critical need for effective interventions. Our team developed a pioneering digital therapeutic tool through the application of advanced 3D artificial intelligence technologies. This innovative solution offers a dynamic visual representation of weight loss and health enhancement journeys for individuals with obesity. By providing a platform for users to monitor their progress in real time, digital therapeutics (DTx) foster deeper engagement and strengthen motivation towards health goals. The experimental results showed that the digital therapeutic received high scores in terms of usability, effectiveness, predictiveness and personalization, user satisfaction, and continuous usage and adherence. These findings suggest that DTx can be a valuable tool for the management and treatment of obesity. The effectiveness of this digital approach was thoroughly assessed from multiple dimensions, showing its significant potential and effectiveness in obesity management. These findings advocate ongoing research in this area, projecting that the continuous evolution of DTx will have a profound positive impact on both personal and public health outcomes.","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.13678","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RETRACTION: Auxiliary Cognition System-Based Management Strategy Optimization of Supply Chain of New Energy in Oil–Gas Enterprises

IF 3 4区计算机科学

Expert Systems Pub Date : 2024-11-07 DOI: 10.1111/exsy.13775

引用次数: 0

RETRACTION: The Genetic Algorithm and BP Neural Network in Financial Supply Chain Management Under Information Sharing

IF 3 4区计算机科学

Expert Systems Pub Date : 2024-11-07 DOI: 10.1111/exsy.13779

引用次数: 0

RETRACTION: The Design for Supply Chain Management of Intelligent Logistics System Using Cloud Computing and the Internet of Things

IF 3 4区计算机科学

Expert Systems Pub Date : 2024-11-07 DOI: 10.1111/exsy.13778

{"title":"RETRACTION: The Design for Supply Chain Management of Intelligent Logistics System Using Cloud Computing and the Internet of Things","authors":"","doi":"10.1111/exsy.13778","DOIUrl":"https://doi.org/10.1111/exsy.13778","url":null,"abstract":"\u0000 \u0000 Retraction: H. Wang, Y. Yin, and X. Wang, “ The Design for Supply Chain Management of Intelligent Logistics System Using Cloud Computing and the Internet of Things,” Expert Systems 41, no. 5 (2024): e13271. https://doi.org/10.1111/exsy.13271.\u0000 The above article, published online on 02 March 2023, in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor-in-Chief, David Camacho; and John Wiley & Sons Ltd. The article was submitted as part of a guest-edited special issue. Following publication, it has come to the attention of the journal that this article was accepted solely on the basis of a compromised peer review process. In addition, the authors did not provide a statement regarding individual consent for the images used in Figure 13, which violates the journal's and the publisher's guidelines. The editors have therefore decided to retract the article. The authors did not respond to the notice of retraction.","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.13778","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Few-Shot Contrastive Learning-Based Multi-Round Dialogue Intent Classification Method

IF 3 4区计算机科学

Expert Systems Pub Date : 2024-11-06 DOI: 10.1111/exsy.13771

Feng Wei, Xu Zhang

{"title":"Few-Shot Contrastive Learning-Based Multi-Round Dialogue Intent Classification Method","authors":"Feng Wei, Xu Zhang","doi":"10.1111/exsy.13771","DOIUrl":"https://doi.org/10.1111/exsy.13771","url":null,"abstract":"<div>\u0000 \u0000 Traditional text classification models face challenges in handling long texts and understanding topic transitions in dialogue scenarios, leading to suboptimal performance in automatic speech recognition (ASR)-based multi-round dialogue intent classification. In this article, we propose a few-shot contrastive learning-based multi-round dialogue intent classification method. First, the ASR texts are partitioned, and role-based features are extracted using a Transformer encoder. Second, refined sample pairs are forward-propagated, adversarial samples are generated by perturbing word embedding matrices and contrastive loss is applied to positive sample pairs. Then, positive sample pairs are input into a multi-round reasoning module to learn semantic clues from the entire scenario through multiple dialogues, obtain reasoning features, input them into a classifier to obtain classification results, and calculate multi-task loss. Finally, a prototype update module (PUM) is introduced to rectify the biased prototypes by using gated recurrent unit (GRU) to update the prototypes stored in the memory bank and few-shot learning (FSL) task. Experimental evaluations demonstrate that the proposed method outperforms state-of-the-art methods on two public datasets (DailyDialog and CM) and a private real-world dataset.\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Objective Federated Averaging Algorithm

IF 3 4区计算机科学

Expert Systems Pub Date : 2024-11-06 DOI: 10.1111/exsy.13761

Daoqu Geng, Shouzheng Wang, Yihang Zhang

{"title":"Multi-Objective Federated Averaging Algorithm","authors":"Daoqu Geng, Shouzheng Wang, Yihang Zhang","doi":"10.1111/exsy.13761","DOIUrl":"https://doi.org/10.1111/exsy.13761","url":null,"abstract":"<div>\u0000 \u0000 The recent global trend is the convergence of information and communications technology (ICT). By applying ICT in various fields such as the humanities, new types of products and services are created, and new values that help people's lives can be created. AI can be selected as a representative technology in such convergence ICT. However, applying AI technology to actual production requires ensuring data security. Federated learning (FL) can achieve secure sharing of data, where all parties participate in model training locally and upload it to the server for aggregation. The data never leaves the parties involved, thus solving the problems of data privacy and data silos. However, FL faces issues such as high communication cost, imbalanced performance distribution among participants, and low privacy protection. To achieve a balance between model accuracy, communication cost, fairness, and privacy, this paper proposes a multi-objective optimization-based FL algorithm (M-FedAvg). The multi-objective optimization problem of maximising the accuracy of the global model, minimising the communication cost, minimising the variance of the accuracy, and minimising the privacy budget is solved by NSGA-III. The experimental results show that the algorithm proposed can effectively reduce the communication cost of FL and achieve privacy protection for participants without affecting the accuracy of the global model.\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RETRACTION: Challenges and Vulnerability Evaluation of Smart Cities in IoT Device Based on Cybersecurity Mechanism

IF 3 4区计算机科学

Expert Systems Pub Date : 2024-11-04 DOI: 10.1111/exsy.13774

引用次数: 0

Benchmarking Anomaly Detection Methods: Insights From the UCR Time Series Anomaly Archive

IF 3 4区计算机科学

Expert Systems Pub Date : 2024-10-31 DOI: 10.1111/exsy.13767

Francisco J. Baldán, Diego García-Gil

{"title":"Benchmarking Anomaly Detection Methods: Insights From the UCR Time Series Anomaly Archive","authors":"Francisco J. Baldán, Diego García-Gil","doi":"10.1111/exsy.13767","DOIUrl":"https://doi.org/10.1111/exsy.13767","url":null,"abstract":"Anomaly detection, vital for identifying deviations from normative data patterns, is particularly crucial in sensor-driven real-world applications, which predominantly involve temporal data in the form of time series. Traditional evaluation of anomaly detection methods has relied on public benchmark datasets. Yet, recent revelations have uncovered inherent flaws and inadequacies in these datasets, casting doubt on the perceived progress in the field. To address this challenge, the UCR Time Series Anomaly Archive has been recently proposed—a meticulously curated database comprising 250 time series—designed to provide a robust and error-free benchmark for anomaly detection research. This paper comprehensively evaluates state-of-the-art anomaly detection techniques using the UCR Time Series Anomaly Archive. Our findings demonstrate the efficacy of current methods in accurately detecting anomalies across an important portion of datasets without additional optimization, underscoring the archive's utility as a foundational baseline for future research and development in anomaly detection methodologies.","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.13767","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TOPS: A Framework for Trusted Opinion Analysis of Product Reviews Using Hybrid Deep Learning Based D2CL Filter

IF 3 4区计算机科学

Expert Systems Pub Date : 2024-10-29 DOI: 10.1111/exsy.13765

T. K. Balaji, Annushree Bablani, S. R. Sreeja, Hemant Misra

{"title":"TOPS: A Framework for Trusted Opinion Analysis of Product Reviews Using Hybrid Deep Learning Based D2CL Filter","authors":"T. K. Balaji, Annushree Bablani, S. R. Sreeja, Hemant Misra","doi":"10.1111/exsy.13765","DOIUrl":"https://doi.org/10.1111/exsy.13765","url":null,"abstract":"<div>\u0000 \u0000 The rapid growth of online product reviews has made it increasingly challenging for consumers to make informed purchase decisions. However, the abundance of reviews, including fake or augmented and sarcastic reviews, poses a challenge for consumers. To address this challenge, this paper introduces the TOPS (Trusted Opinion analysis of Product reviewS) framework, a novel approach that leverages a hybrid deep learning-based D2CL (Dual Deep leaning based cleaning) filter to enhance the reliability of online reviews. The proposed methodology employs the D2CL filter to identify and eliminate fake and sarcastic reviews, ensuring that the consolidated sentiment analysis provides users with trustworthy opinions. The framework is equipped with the R-mGRU, a hybrid deep learning model specifically designed to tackle the nuances of product reviews. This model has demonstrated impressive accuracy rates, achieving 89%, 91%, and 94% for fake, sarcasm, and sentiment analysis tasks, respectively. The TOPS framework makes a significant contribution to improving the overall quality and authenticity of product reviews, empowering consumers with more reliable information for informed decision-making in online shopping scenarios.\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0