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检索条件"任意字段=7th IASTED International Conference on Advances in Computer Science and Technology"

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Bus Route Tracking System 7th

Bus Route Tracking System

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data science, ICCIDS 2024

作者： Rubesh Muthuvel, R. Nithish Sankar, B. Kasirajan, P. Dheenathayalan, S. Department of Computer Science and Engineering National Engineering College Kovilpatti India

ISBN: (纸本)9783031699856

this research paper explores the challenges faced by daily bus commuters and presents a transformative live route monitoring system designed to address these issues. the project focuses on local buses and utilizes a user-friendly web application integrated with Google Maps. Key features include personalized notifications, precise real-time tracking, and historical performance data for efficient journey planning. the integration of crowd-sourced insights and multimodal functionality enriches user decision-making, while emergency communication, multilingual support, and energy-efficient tracking contribute to an enhanced overall experience. the project also includes a community engagement platform to encourage collaboration and feedback. Accessibility features and offline functionality ensure inclusivity and convenience, while strategic partnerships with local transport authorities bolster system accuracy. © IFIP international Federation for Information Processing 2024

关键词： Decision making

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From Routine to Automation: How RPA advances Administrative Practices in Swedish Universities 13th

From Routine to Automation: How RPA Advances Administrative ...

引用

13th international conference on Electronic Government and the Information Systems Perspective (EGOVIS)

作者： Guner, Evrim Oya Han, Shengnan Juell-Skielse, Gustaf Stockholm Univ S-16425 Kista Sweden Univ Boras S-50190 Boras Sweden

ISBN: (纸本)9783031682100;9783031682117

this study investigates the impact of Robotic Process Automation (RPA) on the development of routine capabilities and practice changes within public organizations. Drawing on the theoretical lens of technology as routine capability, we conducted case studies at two Swedish public universities. Our findings reveal that the implementation of RPA, conceptualized as a routine capability, fostered the emergence of automation practices within these institutions despite their differing implementation experiences. We identified practice changes across four key dimensions: design, execution, diffusion, and shift. this paper contributes to the existing body of knowledge on RPA by offering detailed empirical insights into how it has advanced practices, induced organizational changes, and identified challenges that require further exploration. this research offers practical implications for public organizations managing RPA-triggered organizational transformations towards automation.

关键词： Robotic Process Automation technology as Routine Capability Automation Practice Case Studies Swedish Public Universities

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technology Enabled Self-directed Learning: A Review and Framework 1

引用

Proceedings of the 7th international conference on advances in Computing and Data sciences, ICACDS 2023

作者： Sharma, Sarika Tyagi, Vipin Vaidya, Anagha Atur Centre Model Colony Pune411016 India Jaypee University of Engineering and Technology Raghogarh MP Guna473226 India

ISBN: (数字)9783031379406

ISBN: (纸本)9783031379390

the use of technology to support self-directed in education sector has been on the rise in recent years. Higher educational institutions have utilized technology to enhance teaching and learning in various ways. Advancements in technology have made laptops, tablets, and smartphones more accessible and replaced personal computers as the primary technology in classrooms, giving teachers more options for supporting their students. Researchers have also explored how technology can be used to accommodate the diverse needs of learners and promote autonomous, self-directed learning. With the outbreak of COVID-19, online classes became more prevalent, highlighting the need to further investigate technology-enabled self-directed learning. this paper reviews the existing literature on the topic and presents it in a framework. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Learning algorithms

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Machine Learning Powered Nutritional Guidance System Using Personalized Nutritional and Digital Health Record 7th

Machine Learning Powered Nutritional Guidance System Using P...

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data science, ICCIDS 2024

作者： Shevanie Shupreeya, P. Suseendra, M. Shanthini, S. Computer Science and Engineering St.Joseph’s College of Engineering Semmencheri Tamilnadu Chennai600119 India

ISBN: (纸本)9783031699856

the combination of digital health records and nutritional data has opened up a new world of substantiated salutary recommendations in the data-driven healthcare period of the moment. the objective of this design is to develop a state-of-the-art system that provides substantiated salutary suggestions to people according to their specific health biographies. this revolutionary system will enable druggies to make informed food choices that are in line with their individual health objects, salutary preferences, and constraints by integrating rich nutritive data with full electronic health records along with nearby location to get it. By exercising sophisticated recommendation algorithms and a flexible feedback medium, the system will constantly acclimate itself in trouble to enhance stoner health results. Icing data sequestration and security is of utmost significance, and the design will misbehave with all applicable regulations and norms. © IFIP international Federation for Information Processing 2024.

关键词： Electronic health record

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Anticipating Future College Admission Cutoffs: An Innovative Predictive Model Incorporating Student Reviews and Historical Admissions Cutoff Data Using Machine Learning 7th

Anticipating Future College Admission Cutoffs: An Innovative...

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data science, ICCIDS 2024

作者： Girish, Chikkam Umesh, Tata Karthik, N. Vani, V. Department of Computer Science and Engineering National Institute of Technology Puducherry Karaikal609 609 India

ISBN: (纸本)9783031699818

In this era of ever-increasing competition for the higher education opportunities, the capability to predict future college admission cutoff ranks plays an important role in shaping the educational journeys of prospective students. this work presents an innovative predictive model aimed at assisting students in making well-informed decisions when it comes to college selection. the proposed framework harnesses the power of key elements: student-personal reviews and historical admission cutoff, National Institutional Ranking Framework (NIRF) factors. this predictive model combines the student reviews, with the insights of admission cutoff ranks and NIRF scores. this work showcases a comprehensive approach that not only anticipates future admission cutoffs but also empowers students to make enlightened enrolment choices. this study explores the intricate interplay between student feedback and historical trends, providing a comprehensive perspective on the evolving landscape of college admissions. © IFIP international Federation for Information Processing 2024.

关键词： Adversarial machine learning

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Offensive Language Detection on Telugu Language 7th

Offensive Language Detection on Telugu Language

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data science, ICCIDS 2024

作者： Kalyan, Kakollu Pavan Naveen, Valiveti Vani, V. Karthik, N. Department of Computer Science and Engineering National Institute of Technology Puducherry Karaikal India

ISBN: (纸本)9783031699818

In the present world a lot of data is generated via twitter, Instagram, WhatsApp etc. in different languages. It is important and necessary task to detect the offensive language among those data to create healthy and good environment among people. And it is even highly challenging task to identify offensive language in low resource languages due to less availability of the classified datasets. this paper aims to detecting of offensive language on a low resource language Telugu. To identify solution for this problem different types of ML models and DL models are used. Based on accuracy of the different models we are going to choose a model. To split the data and train the data and to test the data we have been using stratified k fold cross validation which is an efficient way to split the data and to increase model’s ability to perform better. From basis of this experiments, we can have a model to detect offensive language in Telugu and it must be considered as a small step for future models to work on it. © IFIP international Federation for Information Processing 2024.

关键词： Deep learning

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Unveiling the Complexities of the Human Body: Advanced Computational Anatomy for Precision Medicine 24

Unveiling the Complexities of the Human Body: Advanced Compu...

引用

7th international conference on Digital Medicine and Image Processing, DMIP 2024

作者： Lakshmi Parvathi, A. Lavanya, V. Muthamizh Selvam, M. Venu Gopal, I. Raihana Parveen, R. Vijayarajan, V. Department of CSE QIS College of Engineering and Technology Andhra Pradesh Ongole India Department of AIMLDS QIS College of Engineering and Technology Andhra Pradesh Ongole India Department of ECE QIS College of Engineering and Technology Andhra Pradesh Ongole India School Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9798400709586

Concept of the Study: the human body is an intricate matrix, and solving health problems through modern medicine requires us to lay out the insides of this matrix in full force from within. Computational Anatomy (CA) is a rapidly growing field that uses novel computational tools and techniques to model detailed anatomical structures. Despite enormous medical imaging and image analysis advances, their use in clinical routines still has numerous limitations. Research Gap: While technology in medicine has advanced substantially, the clinical application of computational anatomy still needs to be improved regarding these methodologies for incorporating it into precision medicine practice. Objective: In this study, we provide evidence that computational anatomy, with high-resolution imaging, machine-learning, and biomechanical simulations, can improve diagnostic accuracy, individualized treatments, and patient outcomes through them. Methods: We use cutting-edge computational and machine learning methods to understand anatomical variabilities, predict clinical output measures, and stratify treatment planning. Such processes allow one to perform more detailed evaluations on their subjects with structure-per-level identity, helping to individualize them in clinical decision-making. Results: this implies that diagnostics considering individual anatomical variations could be more accurate with computational anatomy. these results could also pave the way toward personalized therapy, leading to a paradigm shift in clinical practice. Conclusion: the present study fills the unmet need by presenting a complete framework to include computational anatomy in clinical practice. these findings suggest that computational anatomy can revolutionize medicine, giving rise to even more precise and economical health care and leading to better patient outcomes. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Medical imaging

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SVM-Based Skin Cancer Diagnosis for Malignant and Benign Tumor Distinction 7th

SVM-Based Skin Cancer Diagnosis for Malignant and Benign Tum...

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data science, ICCIDS 2024

作者： Tanusha, G. Ashwini, K. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (纸本)9783031699818

In this exploration, we have successfully developed an SVM model that can enhance the process of skin cancer diagnosis. By utilizing advanced techniques in image analysis such as SVM, we have extracted unique features from dermatoscopic images of skin cancer, enabling us to detect distinctive dermoscopy patterns that indicate benign or malignant cancer tumors. the work aims to distinguish between benign and malignant growths, and we improved the accuracy of our diagnostic approach by using a support vector classifier and its capabilities. the work comprises the combination of dermoscopic image classification, machine learning, and, medical imaging, which together form a diversified diagnostic tool from various fields. After conducting attentive testing on different datasets to ensure the performance of our SVM model and the ease of use, satisfied outcomes occurred. the objective is to create a model i.e., a diagnostic tool to distinguish dermoscopic images and improve the early detection technology in skin cancer diagnosis to improve skin health of patients and raise awareness among the precautions to be taken. © IFIP international Federation for Information Processing 2024.

关键词： Diseases

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Optimizing Resource Allocation in Agriculture through IoT and AI 7

Optimizing Resource Allocation in Agriculture through IoT an...

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7th international conference on Electronics, Communication and Aerospace technology, ICECA 2023

作者： Rahman, Mirzanur Chippy, T. Dankan Gowda, V. Prasad, K.D.V. Sethi, Harpal Singh Vishnu Prasanth, P. Gauhati University Department of Information Technology Assam Guwahati India Mahaguru Institute of Technology Department of Computer Science and Engineering Kayamkulam Kattachira India BMS Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India Pune India Uttar Pradesh Prayagraj India Sree Sainath Nagar Tirupati517102 India

ISBN: (纸本)9798350340600

Irrigation, fertilisation, and crop rotation has gained paramount importance in the agricultural industry. Technological advances motivate farmers to achieve optimum crop yields. Maximising crop yield via the deployment of cutting-edge agricultural technology is the recent research trend. Increased yields can be achieved by considering various parameters including soil temperature, soil pH, and water availability. this research work proposes the an IoT-based Precision Agriculture system called 'ACRIS: Agriculture Cultivation Recommender and Smart Irrigation System' to provide helpful suggestions to farmers interested in increasing the crop yields by using the Internet of things technology. the suggested method works well in monitoring the agricultural crops. the proposed system is also capable of determining future irrigation planning requirements. Soil conditions like moisture, temperature, and humidity are used as predictors. these experimental results show that the smart irrigation may increase the crop output while decreasing water usage. © 2023 IEEE.

关键词： Moisture

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Effects of Quality Factor and Satisfaction on the Acceptance of Online Learning (Adoption Learning technology) 7

Effects of Quality Factor and Satisfaction on The Acceptance...

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7th international conference on Information technology, InCIT 2023

作者： Prasetya, Fx Hendra Widiantoro, Albertus Dwiyoga Harnadi, Bernardinus Soegijapranata Catholic University Department of Information System Faculty Computer Science Semarang Indonesia

ISBN: (纸本)9798350358698

In recent years, fundamental changes have occurred in the approach to education caused by advances in information and communication technology. Adoption of online learning technology is gaining increasing global attention for a number of reasons. this study aims to explore the complex dynamics between the quality attributes of online learning (System Quality and Service Quality), user Satisfaction (Satisfaction), and Continuance Intention to use (CI) and also pay attention to the factors of Effort Expectancy (EE), Performance Expectancy (PE), Social Influence (SI), Facilitating Condition (FC) and Self Efficacy (SE). the research methodology used in this study began with conducting a literature study on the correlation of the relationship between quality factors and user satisfaction in e-learning in acceptance of technology in e-learning, then a survey was carried out on e-learning users, especially students, then the data was processed statistically using PLS to find a correlation between quality factors and satisfaction in using e-learning. In this study conducted on 318 respondents. the results obtained in this study are that there is a correlation between SQ→Sat, SrQ→ Sat, SQ→EE, EE→PE, Sat →CI, PE→ CI, FC→ EE, SE→EE, FC→PE, SI→PE according to the hypothesis that was compiled based on a study of the literature. © 2023 IEEE.

关键词： E-learning

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