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检索条件"任意字段=International Conference on Advances in Data-driven Computing and Intelligent Systems, ADCIS 2022"

共 558 条记录，以下是91-100 订阅

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A Comprehensive Study on data-driven Fake News Detection Methods 6

A Comprehensive Study on Data-Driven Fake News Detection Met...

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6th international conference on intelligent computing and Control systems, ICICCS 2022

作者： Singh, Kavinder Aditi, Aditi Jaiswal, Amar Kumar Shivam, Ananya Delhi Technological University Department of Computer Science and Engineering New Delhi India

ISBN: (纸本)9781665410359

Social Media has become the new hub to obtain news rather than more traditional platforms. The news available on such effortlessly accessible platform has a significant influence on people's lives politically, socially, and psychologically. Fake news spread from this platform is an issue of grave concern. Spreading fake news is easy on social media, which may cause many issues in the society. Thus, Detecting fake news is one of the crucial task. Many algorithms and data- driven methods are available for detection of fake news. This paper presents a comprehensive analysis of different fake news detection algorithms that are based on data-driven approach. Different models are analysed to study their impact, advantages and limitations. Further, this paper contains a discussion of various details related to the multiple datasets available for the task of fake-news detection. © 2022 IEEE.

关键词： Social networking (online)

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A Comparative Study of Recent advances in Big data Analytics in Vehicular Ad Hoc Networks 18

A Comparative Study of Recent Advances in Big Data Analytics...

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18th IEEE international Wireless Communications and Mobile computing conference (IWCMC)

作者： Zaraket, Kawthar Bennis, Ismail Harb, Hassan Jaber, Ali Abouaissa, Abedalhafid Lebanese Univ Doctoral Sch Sci & Technol MERCEL Lab Beirut Lebanon Univ Haute Alsace IRIMAS Mulhouse France

ISBN: (纸本)9781665467490

Big data is becoming a research focus in intelligent Transportation systems (ITS), which can be seen in many projects worldwide. intelligent transportation systems will produce a large amount of data. The produced big data will profoundly impact the design and application of the ITS, which makes them safer, more efficient, and profitable. Studying big data analytics in ITS is a flourishing field. This paper aims to provide a comparative study of some recent works in Big data analytics for Vehicular Ad Hoc Networks. The study includes reviewing some frameworks that conduct big data analytics in ITS while discussing the data source and collection methods, data analytics methods, platforms and big data analytics application categories. The comparison and implementation of five recent works, with a focus on the data collection and application layers, are followed to pick up the best approach based on the Friedman test results.

关键词： intelligent Transportation systems (ITS) Big data Analytics VANET Machine Learning

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AstroFusion: A GAN-Augmented Approach for Exoplanet Detection 4

AstroFusion: A GAN-Augmented Approach for Exoplanet Detectio...

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4th IEEE international conference on Emerging Techniques in Computational Intelligence, ICETCI 2024

作者： Suresh, Aakash Lakshmi, C. Gopirajan, P.V. Dhanasekaran, K. School of Computing Srm Institute of Science and Technology Chengalpattu Chennai TN Kattankulathur603203 India School of Computing Srm Institute of Science and Technology Department of Computational Intelligence Chengalpattu Chennai TN Kattankulathur603203 India School of Computing Srm Institute of Science and Technology Department of Data Science and Business Systems Chengalpattu Chennai TN Kattankulathur603203 India

ISBN: (纸本)9798350387063

Humanity's exploration of the cosmos spans billions of years, prompting contemplation of our position in the universe. This study advocates for proactive communication with potential intelligent species, driven by uncertainty about their existence. The focus is on exploring Generative Adversarial Networks (GANs) to enhance exoplanet detection through data augmentation. Utilizing the extensive Kepler dataset, the study evaluates the accuracy of conventional machine learning techniques: Logistic Regression, Decision Trees, and Random Forests. (RF)-trained on original data. Subsequently, it assesses the effectiveness of models trained solely on GAN-generated synthetic data and compares their performance with that of models trained on original data. Lastly, it merges original and synthetic data to create a composite dataset, evaluating the ML model's accuracy. The results indicate that models trained solely on synthetic data achieve comparable accuracy to those trained on original data. Furthermore, the combined dataset yields improved accuracy-87%, 95%, and 96% in Logistic Regression, Decision Tree, and RF, respectively-highlighting the potential of GAN-based data augmentation in enhancing exoplanet detection. This study advances space exploration by integrating technology with astronomical research, facilitating more precise and reliable exoplanet detection methods. Leveraging GANs for data augmentation promises novel insights and discoveries about the universe. © 2024 IEEE.

关键词： Generative adversarial networks

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Modelling the relationships between local landscape features and habitat suitability of Genji-firefly Luciola cruciata using Random Forests 12

Modelling the relationships between local landscape features...

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Joint 12th international conference on Soft computing and intelligent systems / 23rd international Symposium on Advanced intelligent systems (SCIS and ISIS)

作者： Ogami, Tomoya Fukuda, Shinji Kakudo, Hirofumi Tokyo Univ Agr & Technol Grad Sch Agr Tokyo Japan Tokyo Univ Agr & Technol Div Environm & Agr Engn Tokyo Japan Kagawa Univ Fac Engn & Design Program Architecture Civil & Environm Engn Takamatsu Kagawa Japan

ISBN: (纸本)9781665499248

Genji-firefly has been one of the key symbols of rural environmental conservation. The species lives underwater as larvae, in the soil when they pupate, and emerges on the ground as adults. Because the habitat conditions of larvae and adults differ greatly, the habitat requirement of Genji-firefly must be clarified over a wide range from instream to the surrounding riparian environment. In this study, we developed a habitat suitability model for Genji-firefly by relating the number of individuals to local landscape features surveyed in a small river in an agricultural watershed. For habitat modelling, Random Forests, a well-known highly predictive machine learning method, was used to model species distributions and to extract quantitative information on their ecological characteristics. As a result, a good agreement was found between observed and modelled number of individuals, although some issues still remain for the test data. We were able to extract local landscape features that characterize the habitat suitability of adult firefly. In future, we plan to deepen our habitat suitability assessment by taking into account uncertainties such as noise originated from absent data.

关键词： habitat suitability landuse data-driven model agriculture water management

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Robotic Precision Fitness: Accurate Pose Training for Elderly Rehabilitation 25th

Robotic Precision Fitness: Accurate Pose Training for Elderl...

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25th international conference on intelligent data Engineering and Automated Learning

作者： Rincon, J. A. Marco-Detchart, C. Univ Burgos Dept Digitalizac Escuela Politen Super Ctra Oron 28 Burgos 09200 Spain Univ Politec Valencia UPV Valencian Res Inst Artificial Intelligence VRAIN Camino Vera S-N Valencia 46022 Spain

ISBN: (纸本)9783031777370;9783031777387

This study presents a novel robotic assistant tailored for elderly rehabilitation. The system combines state-of-the-art artificial intelligence, computer vision, and robotics to provide customized exercise routines and instant feedback. The core of the assistant is a Grove AI V2 vision system, driven by a dual-core Arm Cortex-M55 processor and an Arm Ethos-U55 neural network component. A custom-built robotic torso fitted with 12 servo motors supports the demonstration of a wide variety of upper body exercises. A crucial element in the experiments is the use of Restricted Radial Equivalence Functions (RREFs) and Radial Similarity Measures (RSMs) to precisely match human poses with the robot's demonstrations. This method ensures an accurate evaluation of exercise performance, enhancing the efficacy of physical therapy for the elderly. Using edge computing technologies, the system provides real-time monitoring and personalised care while addressing important privacy issues. The assistant is additionally characterized by a small-sized design that includes a 124x64 pixel OLED display, capable of displaying bio-signal monitoring and an animated face to engage users. This research advances AI-assisted elderly care, aiming to increase independence, physical health, and overall quality of life for aging populations while offering support to healthcare systems and caregivers.

关键词： Edge computing Elderly Rehabilitation Pose Estimation Robotic Assistance

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intelligent Refrigerator using Machine Learning and IoT

Intelligent Refrigerator using Machine Learning and IoT

引用

2022 IEEE international conference on advances in computing, Communication and Applied Informatics, ACCAI 2022

作者： Rajeswari, D. Srinivasan, R. Ramamoorthy, S. Pushpalatha, M. School of Computing College of Engineering and Technology Department of Data Science and Business Systems India School of Computing College of Engineering and Technology SRM Institute of Science and Technology Department of Computing Technologies Kattankulathur603203 India

ISBN: (纸本)9781665495295

Machine Learning and Internet of Things (IoT) play a vital role in the current electronics world. Electronic appliances operated by humans are automated and accessed remotely via IoT and 5G networks. Smart Cars, Drone Deliveries, and intelligent Refrigerators are some of IoT and machine learningmajor applications. Potentially, with the aid of computing devices intelligent Refrigerators can be accessed from anywhere and anytime. In intelligent Refrigerators,a single tap on the computing devices predicts the quality of food items kept in the refrigerator. Besides, in order to work smartly, intelligent IoT devices deployed in intelligent refrigerators predict food quality anonymously using machine learningtechniques. This paper uses ensemble machine learning technique with naive bayes, support vector machine and decision tree to classify the considered fruits are spoiled or not. © 2022 IEEE.

关键词： Support vector machines

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Adaptive Control of Machines: A data driven Model Based Design

Adaptive Control of Machines: A Data Driven Model Based Desi...

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2022 international conference on computing, Communication, Security and intelligent systems, IC3SIS 2022

作者： Anand, Aditya Leena, L. NSS College of Engineering Dept of EEE Kerala Palakkad India

ISBN: (数字)9781665468831

ISBN: (纸本)9781665468831

The paper presents the design, development, analysis of data driven model based control system of PMDC motor. data is obtained from the motor using data acquisition techniques. The plant model is designed through supervised machine learning technique. Artificial Neural Network based motor model was developed. The obtained model was used to design a controller. The model along with its underlying neural network and the controller was developed with the help of MATLAB/SIMULINK platform. © 2022 IEEE.

关键词： Controllers

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Model Construction, Problems and Countermeasures of intelligent Logistics Ecosystem driven by Blockchain Technology

Model Construction, Problems and Countermeasures of Intellig...

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international conference on computing, Robotics and System Sciences (ICRSS)

作者： Huang, Xing Guangzhou Sontan Polytech Coll Guangzhou Peoples R China

ISBN: (纸本)9781665464031

In the process of the development of the digital economy increasingly, block chain and the Internet of things, cloud computing, big data analysis, a new generation of digital technologies such as artificial intelligence fusion application drives the intelligent logistics constantly change, build a logistics business system, the logistics system of supply chain and logistics chain system as the core of ecological intelligent logistics system, but due to the block chain technology is still in its infancy, Therefore, there are some problems such as rough technology and imperfect three core systems. Countermeasures and suggestions for the development of intelligent logistics ecological system are put forward.

关键词： Blockchain technology intelligent logistics Logistics ecosystem Countermeasures

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advances in Machine Learning-driven Quality Control within ERP systems: A Comprehensive Survey 11

Advances in Machine Learning-driven Quality Control within E...

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11th IEEE international conference on intelligent computing and Information systems, ICICIS 2023

作者： Qaddoori Aldoori, Shaymaa Ahmed Mabrouk, Mohamed Mahmoud, Abeer M. Cairo Egypt Faculty of Computer and Information Science Computer Science Department Cairo Egypt

ISBN: (纸本)9798350322101

Enterprise Resource Planning (ERP) systems have become essential instruments in contemporary corporate operations, offering significant benefits in process optimization and efficient data management. The assurance of quality and dependability in these intricate systems is of utmost significance given that errors or inconsistencies might yield extensive ramifications. This study highlights the importance of quality control within ERP systems, emphasizing the crucial role of accuracy and integrity in facilitating efficient decision-making processes and optimizing operational efficiency. This analysis explores the increasing importance of upholding ERP quality as firms become increasingly dependent on these systems to traverse intricate business environments. In addition, this study explores the capacity of machine learning to enhance quality control procedures. Machine learning techniques, owing to their ability to examine large datasets and identify subtle patterns, provide a transformative shift away from the traditional rule-based approaches. Machine learning enhances the capacity to anticipate problems, reduce interruptions, and maintain consistent operational performance by employing real-time anomaly detection, predictive modeling, and adaptation to shifting ERP settings. This study explores the complex confluence of technology and business imperatives, highlighting the transformative impact of the collaboration between machine learning and quality control on the evolution of ERP systems. © 2023 IEEE.

关键词： Decision making

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Alignment of Visual Senses and Acoustical Senses based on Emotion Recognitions 12

Alignment of Visual Senses and Acoustical Senses based on Em...

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Joint 12th international conference on Soft computing and intelligent systems / 23rd international Symposium on Advanced intelligent systems (SCIS and ISIS)

作者： Su, Ja-Hwung Liao, Yi-Wen Kao, Ming-Hung Tsai, Yung-Wen Chang, Chih-Jui Wu, Hsiu-Wei Chen, Cheng-Wei Natl Univ Kaohsiung Dept Comp Sci & Informat Engn Kaohsiung Taiwan Natl Kaohsiung Univ Sci & Technol Dept Intelligent Commerce Kaohsiung Taiwan

ISBN: (纸本)9781665499248

Recently, due to the rapid advances on multimedia technology, multimedia data such as pictures and music has heavily invaded our daily life. By the mobile camera, users capture the interested scenes as the preferred pictures, and then browse these pictures in either computers or mobile devices. This incurs an interesting issue that, how to provide the users with a better browsing/listening atmosphere and experience by music. Actually, it can be viewed as the problem for aligning photos with music and also as an exciting research topic for cross-media retrieval. However, very few studies focus their attention on this topic. To aim at this issue, in this paper, we propose a novel cross-media alignment method that bridges visual pictures to harmonic music by visual emotions and acoustical emotions. In this method, the pictures and music are projected onto the emotion space first. Next, the emotion features are fuzzed to be near the human senses. Finally, the effective alignment method for associating pictures with music is performed. The results of subjective and objective evaluations on the real datasets reveal that, our proposed method can successfully provide the users with a rich experience on audiovisual presentations. Also, the proposed alignment algorithm is shown to be effective in terms of Normalized Discounted Cumulative Gain.

关键词： cross-media alignment visual emotion recognition acoustical emotion recognition fuzzy multimedia information retrieval.

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