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18th international KES conference on Agents and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2024

18th International KES Conference on Agents and Multi-Agent ...

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18th international KES conference on Agents and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2024

ISBN: (纸本)9789819764686

The proceedings contain 34 papers. The special focus in this conference is on Agents and Multi-Agent Systems: Technologies and Applications. The topics include: Fair Path Generation for Formation Control Combining Ant Colony and Particle Swarm Optimizations;preference Definition in a Multi-agent System Approach for User-Centric Internet of Things smart Environments;AI-Driven Nitrogen Stress Management in Cereal Crops via Drone technology;agent-Based Simulation for Withdrawal of Energy-Inefficient Housing;resource Limitations of Business Process Simulations: Literature Study;data Augmentation for Business Process Alignment: Proof of Concept and Experimental Design;smart Scheduling in Urban Traffic: A Multi-Agent System for Dynamic Vanpooling;analysis of the Impact on Area Prices Using Propensity Score Matching, Considering the Proportions of Photovoltaic and Thermal Power Generation Simultaneously;consideration of Building a Simulator to Evaluate Methods to Maximize the Effectiveness of Advertising to Households;Human-AI-Collaboration SECI Model: The knowledge Management Model of the Experts’ Tacit knowledges with Augmented LLM-Based AI;modeling Agent Awareness After Hierarchical Managerial Training;development of An Application for Extracting Needs Related to Actual Gas Use Using Text Mining;Impact of Intelligent Systems in the Home Office on Employee Satisfaction—Lessons Learned from the COVID-19 Pandemic;agile Methodologies in Software Development: A Study of Effective Management Strategies for Companies in the Digital Era;predictive Analysis of Cyclical Sales Data;EMG Signal Classification Using Machine Learning for Augmentative Assistance in Cerebral Palsy;wellnessWave—Platform for the Digitization of the Romanian Public Medical System;TRIAGE Predictive Model Based on Artificial Neural Networks and Deep Learning;platform for Automated Assessment of Obstetric Ultrasounds, Using Machine Learning;identification of Fonts in Unstructured Environments Through Deep Lea

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30th international Joint conference on Industrial Engineering and Operations Management, IJCIEOM 2024

30th International Joint Conference on Industrial Engineerin...

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30th international Joint conference on Industrial Engineering and Operations Management, IJCIEOM 2024

ISBN: (纸本)9783031807848

The proceedings contain 37 papers. The special focus in this conference is on Industrial Engineering and Operations Management. The topics include: Proposal for an Optimized Model to Analyze Customer Satisfaction—B2B;mechatronic Framework for smart Beehives: Prototyping and Applications Perspective;digital Fashion: The Impact of Service Quality on Customer Satisfaction;computer Vision as a Resource in smart Warehouses: A Systematic Review;port Logistics Emissions Control Using Machine Learning to Coordinate the Truck Flow;Evolution of Logistics Service Providers: A Study of 5 PL;reinforcement Learning and Discrete Event Simulation Applied to Production Scheduling: A Scoping Review;a Simulation Model to Determine Production Shifts for Pallet Packaging;the Enhanced Factory for Extra-Terrestrial Space technology Operations: Conceptualization and Scenarios’ Definition;digital Twins in Asset Prognosis and Health Management: Definitions, Applications, State of the Art, and Future Trends;Benefits of ERP Information Systems in ESG Management Within Organizations;an Assignment Model for High-Cognitive-Workload Maintenance Activities in Industry 5.0;Forecast of Brazilian GDP Growth Through Consumption of Diesel Oil and Electrical Energy;impact of Distribution Configurations on Supply Chain Performance: A System Dynamics Approach;lean Healthcare Management Through Kaizen in a Public Brazilian Hospital;multicriteria Decision Analysis for Natural Risk Management Context: knowledge Mapping and Analysis (2013–2023);assessment of a Project Management Maturity Diagnostic Tool;Utilizing GPT-4 in the Selection of Health-Tech Startups for a Brazilian Acceleration Program: A Validation Study with 168 Startups;Applicability Analysis of the Power BI with the OKR Methodology in the Strategic Planning Enhancement;customer Satisfaction in Tourism Services Center.

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2nd international conference on Next-Generation Computing and Information Systems, ICNGCIS 2023

2nd International Conference on Next-Generation Computing an...

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2nd international conference on Next-Generation Computing and Information Systems, ICNGCIS 2023

ISBN: (纸本)9781032738659

The proceedings contain papers. The special focus in this conference is on . The topics include: Impact of artificial intelligence on high-penetration renewable physical infrastructure;collaborative attacks and defense;building a safe and secure metaverse;distributed-computing based versatile healthcare services framework for diagnostic markers;supervised context-aware Latent Dirichlet allocation-based drug recommendation model;combination kernel support vector machine based digital twin model for prediction of dyslexia in distributed environment;Time series analysis of vegetation change using remote sensing, GIS and FB prophet;advances in smart farming for precision agriculture: Green-IoT and machine learning as a solution;Towards a serverless computing and edge-intelligence architecture for the Personal-Internet-of-Things (PIoT);IOT and developed deep learning based road accident detection system and societal knowledge management;Healthcare CAD model for hierarchical processing of surgical navigation system;applicability of eye tracking technology in virtual keyboard for human-computer interactions;a digital twin framework for smart contract-based DeFi applications in the metaverse: Towards interoperability, service scaleup & resilience;a novel approach to glass identification using ensemble learning for forensics;deep learning-based cognitive digital twin system for wrist pulse diagnostic and classification;Multi-class instance segmentation for the detection of cervical cancer cells using modified mask RCNN;dilated convolution model for lightweight neural network;artificial intelligence based Monte Carlo model for epidemic forecasting for societal aspect;efficient data visualization through novel recurrent neural network-based dimension reduction;An optimized CNN-based model for pneumonia detection;EEG-based emotion recognition: Leveraging CNNs for precision;A seven layer DNN approach for social-media multilevel image-based text classification.

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AI in Educational Assessment, Applications, and Implications: A Survey 18th

AI in Educational Assessment, Applications, and Implications...

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18th international KES conference on Agents and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2024

作者： Ali, Rawan Bahrami, Mohammad Reza Cyberphysical Systems Lab Innopolis University 1 Universitetskaya Str Innopolis420500 Russia Techno park Samarkand International University of Technology 270 Spitamen Ave. Samarkand140100 Uzbekistan

ISBN: (纸本)9789819764686

Artificial intelligence (AI) is being implemented in more and more various fields. In particular, AI applications in the education sector are rising and have received much attention in recent years, not only because it is considered a breakthrough in the transformation way of knowledge but also because of its capability to satisfy a wide range of functions. This paper aims to provide an overview of the integration of AI in educational assessments across various fields such as engineering, medicine, and mathematics. Throughout the study, we highlight AI potential in addressing educational challenges, improving assessment accuracy, and personalizing learning experiences. Based on the findings, AI-driven tools have the potential to substantially contribute to educational assessment methodologies through real-time feedback, predictive analytics, and customized educational plans. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ambient intelligence

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Analyzing Clinical Data for Improved Diagnosis Using AI/ML Algorithms in smart Health Care 5th

Analyzing Clinical Data for Improved Diagnosis Using AI/ML A...

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5th international conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Lakshmisha, S.K. Alam, Intekhab Bhuvana, J. Bhatt, Rahul School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

This study analyzes the capability for using AI/ML algorithms to improve diagnostic accuracy in smart health care. AI/ML strategies have revolutionized clinical analysis by way of offering state-of-the-art and dependable techniques for studying clinical facts. Via using superior techniques such as machine learning, deep gaining knowledge of, reinforcement studying, temporal pattern recognition, and superior decision tree algorithms, AI/ML algorithms provide plenty extra accurate predictions of diseases and conditions from affected person records. Further, AI/ML algorithms can discover relationships between different clinical elements that aren't visible to medical doctors and clinicians. Through the use of AI/ML algorithms, doctors will be able to make greater correct diagnoses and provide higher remedies to patients. The consequences of this take a look at imply that the AI/ML algorithms tested own the ability to enhance prognosis in clever healthcare in phrases of accuracy, precision, do not forget, and cost-effectiveness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

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Detecting Emotional Incongruity of Sarcasm by Commonsense Reasoning 31

Detecting Emotional Incongruity of Sarcasm by Commonsense Re...

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31st international conference on Computational Linguistics, COLING 2025

作者： Qiu, Ziqi Yu, Jianxing Zhang, Yufeng Lai, Hanjiang Rao, Yanghui Su, Qinliang Yin, Jian School of Artificial Intelligence Sun Yat-sen University Zhuhai519082 China School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China Key Laboratory of Sustainable Tourism Smart Assessment Technology Ministry of Culture and Tourism Pazhou Lab Guangzhou510330 China

ISBN: (纸本)9798891761964

This paper focuses on sarcasm detection, which aims to identify whether given statements convey criticism, mockery, or other negative sentiment opposite to the literal meaning. To detect sarcasm, humans often require a comprehensive understanding of the semantics in the statement and even resort to external commonsense to infer the fine-grained incongruity. However, existing methods lack commonsense inferential ability when they face complex real-world scenarios, leading to unsatisfactory performance. To address this problem, we propose a novel framework for sarcasm detection, which conducts incongruity reasoning based on commonsense augmentation, called EICR. Concretely, we first employ retrieval-augmented large language models to supplement the missing but indispensable commonsense background knowledge. To capture complex contextual associations, we construct a dependency graph and obtain the optimized topology via graph refinement. We further introduce an adaptive reasoning skeleton that integrates prior rules to extract sentiment-inconsistent subgraphs explicitly. To eliminate the possible spurious relations between words and labels, we employ adversarial contrastive learning to enhance the robustness of the detector. Experiments conducted on five datasets demonstrate the effectiveness of EICR. © 2025 Association for Computational Linguistics.

关键词： Semantics

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Design of National smart Public Health Emergency Management System 24

Design of National Smart Public Health Emergency Management ...

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5th international conference on Computer Science and Management technology, ICCSMT 2024

作者： Hu, Hongpu Chen, Qingkun Wan, Yanli He, Qile Gao, Xing Qin, Panpan Yao, Jianhong School of Marxism School of Humanities and Social Sciences Institute of Medical Information Chinese Academy of Medical Sciences Peking Union Medical College Beijing China Institute of Medical Information Chinese Academy of Medical Sciences Peking Union Medical College Beijing China Chinese Academy of Medical Sciences Peking Union Medical College Beijing China

ISBN: (纸本)9798400709999

In order to solve the issues/problems existing in the current public health emergency management system in China, such as imperfect cross-sectoral collaborative management model, incomplete emergency response mechanism caused by long-term medical care and prevention fragmentation, difficulty in early screening, discovery, timely warning and continuous dynamic monitoring of major infectious diseases, ineffective information support, and unformed intelligent emergency management model, we integrated emerging information technologies such as big data (BD) and artificial intelligence (AI) into public health emergency management, designed a new intelligent public health emergency management model, and established an early identification and early risk warning model of public health *** knowledge base and model base of infectious disease prevention and control were built, the intelligent pre-hospital emergency treatment and emergency disposal system were studied, the intelligent public health emergency management platform was developed and pilot application was carried out in order to make up for the shortcomings of traditional emergency management work, realize intelligent public health risk identification, disease prevention and control and emergency handling, and improve public health emergency management service capacity. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Electronic health record

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A Proposed Educational Framework for Professional Upskilling in smart Manufacturing: On-Demand Microlearning Units 6

A Proposed Educational Framework for Professional Upskilling...

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6th international conference on Industry 4.0 and smart Manufacturing, ISM 2024

作者： Pinto, Rui Perez, Adrian Lomba Gonçalves, Gil Lampón, Jesús F. Pérez-Moure, Hugo SYSTEC-ARISE Faculty of Engineering University of Porto Rua Dr. Roberto Frias Porto4200-465 Portugal PorriñoE-36475 Spain Faculty of Economics and Business Sciences University of Vigo Campus Universitario As Lagoas Marcosende Vigo36310 Spain

The rapid advancements in smart manufacturing are transforming industries but also highlighting a significant skills gap, particularly in specialized regions such as Northern Portugal and Galicia. Existing training models often fail to adequately marry the depth of specialized skills with the breadth of interdisciplinary knowledge required in modern manufacturing environments. This paper introduces an innovative educational framework designed to comprehensively address this gap by integrating both hard and soft skills training through a flexible, Pi-shaped model of skill acquisition. Developed within the OpenLabs project, this framework leverages customizable, on-demand microlearning units across three critical domains - digitalization, human factors, and sustainability - complemented by interactive webinars and personalized lab sessions. The framework allows participants to tailor their educational journey to fit their specific career goals, enhancing adaptability and competitiveness in the workforce. This paper details the structure and implementation strategy of the framework, evaluates its potential impact on regional workforce development, and discusses challenges and mitigation strategies. By bridging the identified skills gap with a novel approach to professional education, this framework aims to significantly enhance the capabilities of the workforce in Northern Portugal and Galicia, setting a precedent for future training programs in smart manufacturing globally. © 2024 The Authors. Published by Elsevier B.V.

关键词： smart manufacturing

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Factors Affecting Green Cosmetic's Brand Loyalty: The Mediating Effect of Brand Love 6

Factors Affecting Green Cosmetic's Brand Loyalty: The Mediat...

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6th international conference on Industry 4.0 and smart Manufacturing, ISM 2024

作者： Le, Thi Mai Vu, Khanh Huyen Le, Bao Ngoc Ngoc Luu, Thi Minh International School Vietnam National University Hanoi Viet Nam Department of Marketing Posts and Telecommunications Institute of Technology Hanoi Viet Nam

Understanding the core factors necessary for the sustainable competitiveness of a green product is crucial. The objective of this study is to demonstrate the direct and indirect influences of brand experience, brand image, and customer satisfaction on brand love and brand loyalty. We surveyed 205 respondents using purposive sampling as the data collection technique. Data was collected through surveys and analyzed using SPSS and smartPLS software. The findings of the study indicate that brand love has a positive impact on brand loyalty. Furthermore, brand love fully mediates the impacts of brand experience and customer satisfaction on brand loyalty. On the contrary, brand image directly influences brand loyalty without the mediation of brand love, which departs from previous research and hypotheses. This research aims to address the gaps in previous research articles and contribute new knowledge to theory and practices of green cosmetic brands in Vietnam. © 2025 Elsevier B.V.. All rights reserved.

关键词： Brand Experience Brand Image Brand Love Brand Loyalty Customer Satisfaction Green cosmetic

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Revolutionizing Organic Product Supply Chains: Blockchain, RSA-Encrypted NFTs, and IPFS for Ethical and Transparent Supply Chains 20th

Revolutionizing Organic Product Supply Chains: Blockchain, R...

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20th Principle and Practice of Data and knowledge Acquisition Workshop, PKAW 2024, held in conjunction with the 21st Pacific Rim international conference on Artificial Intelligence, PRICAI 2024

作者： Tuan, Trung Phan Hoang Dang, Khoa Tran Pham, Nghiem Thanh Ba, Nam Tran Kim, Ngan Nguyen Thi Minh, Hieu Doan Phu, Loc Van Cao FPT University Can Tho city Viet Nam FPT Polytechnic Can Tho city Viet Nam

ISBN: (纸本)9789819600250

This paper explores the integration of blockchain technology, smart contracts, RSA-Encrypted NFTs, and IPFS to address transparency and ethical sourcing challenges in the supply chains of organic products. Through a detailed examination and testing of the proposed system on various Ethereum Virtual Machine (EVM)-compatible platforms, the study evaluates the system’s effectiveness in enhancing traceability, operational efficiency, and ethical compliance from production to end consumer. Incorporating insights from existing literature, the research underscores the potential of these technologies to fortify supply chain management by providing accurate, secure, and verifiable data. The findings demonstrate that such an integrated approach can significantly elevate the transparency, trustworthiness, and accountability of organic product supply chains, offering a scalable and economically feasible solution to longstanding industry challenges. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： smart contract

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