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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Akhila, Pujala Priyadarshini, R. Banerjee, Shalini Thomas, Beryl Abey School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai India

ISBN: (纸本)9798350305708

The World Health Organization (WHO) reported in 2021 that more over 700, 000 people had committed suicide. Suicide can be stopped, but most efforts have so far been ineffective. However, the application of machine learning presents fresh chances to improve prediction accuracy and advance the cause of suicide prevention. This study uses data-driven methodologies to analyze and predict suicide, and presents the same in this report. Machine learning algorithms and PySpark programs are used to analyze a dataset of demographic, socioeconomic, and psychological characteristics related to suicide instances from a Kaggle dataset comprising of 237519 rows and 7 columns. The study creates prediction models like linear regression, decision tree, decision tree regressor and bagging regressor. The results support efforts to prevent suicide by assisting in the prioritization of resources and focused interventions. © 2023 IEEE.

关键词： bagging decision tree linear regression prediction models pyspark suicide analysis

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Low-Cost Smart Plant Irrigation Control System Using Temperature and Distance Sensors 5th

Low-Cost Smart Plant Irrigation Control System Using Tempera...

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5th International Conference on Soft Computing and Signal Processing, ICSCSP 2022

作者： Malla, Jyotsna Jayashree, J. Vijayashree, J. School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9789811986680

This study revolves around the idea of proposing a smart and low-cost automated irrigation control system. This system attempts to effectively provide an end-to-end solution to irrigation problems by using economical and easily accessible components. Farmers using traditional irrigation systems primarily suffer from the lack of automation tools and the mechanisms to deal with environmental problems. This paper aims to solve the limitations of traditional irrigation systems using commonly used components in a cost-efficient manner. A synergy between temperature and distance sensors is used to manage the motor and hence automate the plant irrigation system. The system is equipped with an actuator (piezo) to shut down the motor and alert the farmer in case of reduced water supply in order to prevent problems arising from depleted underground water levels. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Liquid crystal displays

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Digital Twin Implementation of Autonomous Planning Arc Welding Robot System

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Complex System Modeling and Simulation 2023年第3期3卷 236-251页

作者： Xuewu Wang Yi Hua Jin Gao Zongjie Lin Rui Yu School of Information Science and Engineering East China University of Science and TechnologyShanghai 200237China Institute for Sustainable Manufacturing and also with the Department of Electrical and Computer EngineeringUniversity of KentuckyLexingtonKY 40506USA

Industrial robots are currently applied for ship sub-assembly welding to replace welding workers because of the intelligent production and cost *** order to improve the efficiency of the robot system,a digital twin system of welding path planning for the arc welding robot in ship sub-assembly welding is proposed in this manuscript to achieve autonomous planning and generation of the welding ***,a five-dimensional digital twin model of the dual arc welding robot system is ***,the system kinematics analysis and calibration are studied for communication realization between the virtual and the actual ***,a topology consisting of three bounding volume hierarchies(BVH)trees is proposed to construct digital twin virtual entities in this *** on this topology,algorithms for welding seam extraction and collision detection are ***,the genetic algorithm and the RRT-Connect algorithm combined with region partitioning(RRT-Connect-RP)are applied for the welding sequence global planning and local jump path planning,*** digital twin system and its path planning application are tested in the actual application *** results show that the system can not only simulate the actual welding operation of the arc welding robot but also realize path planning and real-time control of the robot.

关键词： arc welding robot digital twin topology path planning

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Taxonomy for Classification of Cloud Service (Paas) Interoperability 1

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World Conference on Information Systems for Business Management, ISBM 2022

作者： Adhoni, Zameer Ahmed Dayanand Lal, N. Department of Computer Science and Engineering Gitam School of Technology Gitam University Bangalore India

ISBN: (数字)9789811974472

ISBN: (纸本)9789811974465

The decreasing cost of hardware has opened the doors to the development of various concepts like big data and huge storage spaces. The development of the cloud is one major development in this string of developments. The economic and other important contract features like the locking time gave rise to the usage of multi-clouds by various companies for the same or similar applications. The extended form of this scenario leads to operation on data on different clouds giving rise to interoperability. The Infrastructure as a service, Platform as a service, and Software as a service in the cloud force us to define taxonomy based on various views. Each view addresses its own customized problem. There is a need to generalize the taxonomy of interoperability. This paper presents a taxonomy for the classification of the cloud for Platform as a Service. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Interoperability

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Simulation of Social Media-Driven Bubble Formation in Financial Markets using an Agent-Based Model with Hierarchical Influence Network 36

Simulation of Social Media-Driven Bubble Formation in Financ...

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36th European Modeling and Simulation Symposium, EMSS 2024, Held at the 21st International Multidisciplinary Modeling and Simulation Multiconference, I3M 2024

作者： Bohorquez, Gonzalo Cartlidge, John School of Computer Science University of Bristol Bristol United Kingdom School of Engineering Mathematics and Technology University of Bristol Bristol United Kingdom

ISBN: (纸本)9791281988026

We propose that a tree-like hierarchical structure represents a simple and effective way to model the emergent behaviour of financial markets, especially markets where there exists a pronounced intersection between social media influences and investor behaviour. To explore this hypothesis, we introduce an agent-based model of financial markets, where trading agents are embedded in a hierarchical network of communities, and communities influence the strategies and opinions of traders. Empirical analysis of the model shows that its behaviour conforms to several stylized facts observed in real financial markets;and the model is able to realistically simulate the effects that social media-driven phenomena, such as echo chambers and pump-and-dump schemes, have on financial markets. © 2024 The Authors.

关键词： Marketplaces

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Carbon materials:The burgeoning promise in electronics

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International Journal of Minerals,Metallurgy and Materials 2022年第3期29卷 404-423页

作者： Yuting Zheng Junjun Wei Jinlong Liu Liangxian Chen Kang An Xiaotong Zhang Haitao Ye Xiaoping Ouyang Chengming Li Institute for Advanced Materials and Technology(IAMT State Key Laboratory for Advanced Metals and MaterialUniversity of Science and Technology BeijingBeijing 100083China Shunde Graduate School University of Science and Technology BeijingFoshan 528399China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China School of Engineering University of LeicesterLeicester LE17RHUnited Kingdom School of Materials Science and Engineering Xiangtan UniversityXiangtan 411105China

Current electronic technology based on silicon is approaching its physical and scientific limits. Carbon-based devices have numer- ous advantages for next generation electronics (e.g., fast speed, low power consumption and simple process), that when combined with the unique nature of the versatile allotropes of carbon elements, are creating an electronics revolution. Carbon electronics are greatly advancing with new preparations and sophisticated designs. In this perspective, representatives with various dimensions, e.g., carbon nanotubes, graphene, bulk diamond, and their extraordinary performance, are reviewed. The associated state-of-the-art devices and composite hybrid all-carbon structures are also emphasized to reveal their potential in the electronics field. Advances in commercial production have improved the cost effi-ciency, material quality, and device design, accelerating the promise of carbon materials.

关键词： carbon materials nanotube graphene diamond electronic devices

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Agriculture Farming Evolution: Federated Learning CNNs in Combatting Watermelon Leaf Diseases

Agriculture Farming Evolution: Federated Learning CNNs in Co...

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2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Suryavanshi, Ankita Mehta, Shiva Gupta, Amit Aeri, Manisha Jain, Vishal Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Computer Science and Engineering Graphic Era Hill University Uttarakhand Dehradun India Graphic Era Deemed to Be University Computer Science and Engineering Uttarakhand Dehradun India Sharda University Computer Science and Engineering Sharda School of Engineering and Technology U.P. Greater Noida India

ISBN: (纸本)9798350361537

This research paper proposes a unique method using the benefits of federated learning and convolutional neural networks to find watermelon leaf diseases. In particular, the study concentrates on five unique categories of watermelon leaf diseases presented as a distributed dataset across the five clients to reflect FL's decentralisation. The core mechanism lies in the seamless local data training with federated averaging that transforms locally learned insights into an upgraded global model. In the proposed experimental setting, each client (si-1 to si-5) learned a local CNN model using their data of different disease manifestations. Each local model was thoroughly evaluated using precision, recall, F1-score support, and accuracy metrics. Of note, the performance results showed high accuracy on all the clients, with mean accuracy scores between 0.96 and 0.97, indicating how very effective this model was in various data settings. The study additionally explores the analysis of federated averaging, which includes macro, micro, and weighted aggregates to capture collective learning through local models. The mean values of the clients' si-1 to si-5 were 91.70%, 93.48%, and so on. The weighted averages maintained a significant correlation with the macro averages, which varied between 90.70% and 93.47%, confirming that classes were generally balanced in datasets. Similarly, the macro average overall efficiency for all cases was at per cent. In summary, this study highlights the prospects of federated learning with CNNs for revolutionising plant disease detection and classification by embracing decentralised, heterogeneous agricultural environments. © 2024 IEEE.

关键词： Macroinvertebrates

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Robust and Low-Computational Cost Eye Tracking System Using a Generic Webcam 14

Robust and Low-Computational Cost Eye Tracking System Using ...

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14th International Conference on Information and Communication Systems, ICICS 2023

作者： Ajlouni, Mo'ataz A. Al-Bashir, Areen K. Al-Shrida, Wa'ed Al Ajlouni, AIMotasem Bellah Jordan University of Science and Technology Department Biomedical Engineering Irbid Jordan School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9798350307870

Eye-tracking is a process for measuring eye movement and gaze location. It's considered a standard approach for inspecting the visual attention allocation. In this paper, a new eye-tracking approach was tested and evaluated principally for the first time. The detected gaze location values were used to control the mouse cursor in real time on a computer device. A generic web camera was placed on the eyeglasses frame and aimed at the eye;no Infrared light source was used to illuminate the eye. Every captured video frame of the eye is transformed to a grey level, then the contrast is enhanced using histogram equalization. Finally, the image of the eye is identically divided into four groups. The eye gaze position in the horizontal direction is detected by calculating the difference between the left and right groups of pixels. Similarly, the eye gaze in the vertical direction is detected by calculating the difference between lower and upper groups of pixels. The results show high accuracy, low computational cost, and confirmed perfect linearity. Moreover, it is a non-invasive method, and easy to calibrate. © 2023 IEEE.

关键词： Eye tracking

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A dual fuzzy with hybrid deep learning architecture based on CNN with hybrid metaheuristic algorithm for effective segmentation and classification

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International Journal of Information technology (Singapore) 2023年第1期15卷 531-543页

作者： Nagoor, Shafeen Jinny, S. Vinila Department of Computer Science Noorul Islam Centre for Higher Education Thuckalay Kumaracoil India School of Computer Science and Engineering Vellore Institute of Technology Vellore India

Tuberculosis (TB) is becoming a deadly disease that causes tremendous death throughout the world. Early diagnosis of TB is a crucial task that helps to prevent the disease from severity. Therefore, several types of research are being held worldwide for providing a highly effective automatic diagnosing system. Hence, the proposed model has emerged where segmentation, feature extraction, and classification are the three significant parts. In segmentation, Fuzzy Kapur’s Entropy-based Multi-Level Segmentation with Quantum Bat Optimization Algorithm (QBO_KMLBS) is utilized. Secondly, a Deep Inception with Fuzzy based Support Vector Machine with Sine Cosine Optimization algorithm i.e., named SCHHO-IVFSVM is utilized for feature extraction and classification. In this work, the fuzzy logic has been applied to both the segmentation and classification stages in order to improve the performance model of the TB diagnosis. The implementation is done in the MATLAB 2020 platform and the performance is evaluated in terms of performance matrices with four different categories such as single, overlapped, single and overlapped, and overall. These categorizations are evaluated with different datasets and techniques. Finally, the proposed method has shown 96.89% accuracy for the conventional sputum smear microscopy database (CSM_DS) dataset. © 2022, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Fuzzy InceptionV4 Kapur’s entropy Multilevel segmentation Quantum bat optimization Support vector machine

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Merging the Strengths of GPT-4 and DeepLab for Semantic Text Understanding in Digital Textbooks

Merging the Strengths of GPT-4 and DeepLab for Semantic Text...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Anusha, B. Borah, Asha Rani Mishra, Gaurav Thethi, H Pal Al-Allak, Mustafa Abdulhussein Vidhya, B. Veda Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India New Horizon College Of Engineering Department Of Computer Science Engineering Bangalore India Amity School Of Engineering And Technology Amity University Greater Noida India Lovely Professional University Phagwara India College Of Medical Technology The Islamic University Najaf Iraq Mlr Institute Of Technology Department Of Computer Science And Engineering Telangana Hyderabad India

ISBN: (纸本)9798350366846

Gathering all the necessary data is the major objective of this study so that a comprehensive picture can be painted of how new technologies might improve students' understanding of semantic content in digital textbooks. The recommendations for this approach make use of TIFA, CEG, and ACA, or the Adaptive Complexity Adjustment. This approach combines the best features of various algorithms. TIFA makes these learning aids easy to completely comprehend by combining written and visual material. Answering students' queries and providing answers that make sense in the context is CEG's responsibility. To make learning more tailored to everyone, ACA changes the difficulty of the content depending on performance metrics. Conversely, when students ask CEG questions, it finds answers. We compare the proposed method, Semantix Blend, to two more popular approaches, Textbook Classic and Trad Edu. Interpreting text, evaluating visual information, ensuring consistency in context, enabling customisation, making content more accessible, enhancing learning results, and many more advantages are all possible with Semantix Blend. The study's findings will contribute to the improvement of digital textbooks, leading to improved instruction for students in the long term. © 2024 IEEE.

关键词： Semantics

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