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Emerging Systems and Intelligent Computing (ESIC), International Conference on

作者： Chinmayee Senapati Kumar Janardan Patra Satyaprakash Swain Suvendra Kumar Jayasingh Swagatika Senapati Niranjan Kumar Ray Department of Civil Engineering Institute of Technical Education and Research Siksha ‘O’ Anusandhan Deemed to be University Bhubaneswar India Department of Computer Science and Engineering Odisha University of Technology and Research Bhubaneswar India Department of Computer Science and Engineering Institute of Management of Information Technology Cuttack BPUT Odisha India Department of Computer Science and Engineering Institute of Management of Information Technology Cuttack BPUT Odisha School of Computer Engineering KIIT Deemed to be University Bhubaneswar India

Groundwater, a vital resource for various purposes, faces increasing threats to its quality due to factors like overuse, pollution and climate change. In the semi-arid climate of the state of Telangana, India, exacerbated by intensive agricultural practices, groundwater quality is a significant concern. This study presents a machine learning-based approach for predicting and managing groundwater quality in Telangana, utilizing a stacking ensemble method. Our proposed approach combines decision trees (DT) with meta-models such as logistic regression, K-nearest neighbors (K-NN), Bayesian ridge regression (BRR) and random forest (RF). Trained on a comprehensive dataset from the Telangana Open Data portal (2018-2021), the stacking ensemble demonstrates superior performance, achieving an accuracy of 96.07%, surpassing the best individual model (DT) at 92.68%. It not only enhances predictive capabilities but also provides insights into the spatial distribution of groundwater quality, identifying areas vulnerable to contamination. These findings offer valuable information for policymakers, environmental scientists and water resource managers, guiding informed decision-making for sustainable water resource management in Telangana. This research contributes to the ongoing discourse on environmental conservation and the imperative for effective groundwater management.

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Enhanced SNR Based Admission Control Algorithm for Vehicular Ad-Hoc Network 7

Enhanced SNR Based Admission Control Algorithm for Vehicular...

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7th International Conference on Future Networks and Distributed Systems, ICFNDS 2023

作者： Sameen, Aws Zuhair Alwan, Mohammed Hasan Kadhum, Mayssam Saad Hammadi, Yousif I Alsaeedi, Mokhalad Abdulameer Kadhim Aziz, Ahmed Muthanna, Mohammed Saleh Ali Department Of Medical Instrumentation Engineering Techniques College Of Medical Techniques Al-Farahidi University Baghdad10015 Iraq Department Of Communications Engineering College Of Engineering University Of Diyala Baqubah32001 Iraq Bilad Alrafidain University College Diyala32001 Iraq Department Of Computer Science Faculty Of Computer And Artificial Intelligence Benha University Egypt Department Of International Business Management Tashkent State University Of Economics Tashkent Uzbekistan Institute Of Computer Technologies And Information Security Southern Federal University Taganrog344006 Russia

ISBN: (纸本)9798400709036

Vehicular Ad-hoc Network (VANET) becomes a fundamental subcategory of mobile ad-hoc networks that provides vehicles to communicate with each other and with roadside infrastructure smartly. Various VANET performance challenges are considered in terms of Quality of Service (QoS) due to vehicle speed and transmission rates. Different problems cause performance degradation as performance anomaly where high rates of vehicles have to meet the speed of the low rates vehicle while transmitting data. In this paper, a QoS-aware Signal to Noise Ratio (SNR) admission control mechanism (QASAC) is proposed to handle the performance anomaly problem while maintaining the QoS levels for different traffic types. QASAC has been compared against the latest SNR based admission control mechanism. QASAC has enhanced the performance of data delivery up to 23% in terms of data dropping rates for high priority traffic. © 2023 ACM.

关键词： Vehicular ad hoc networks

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Cloud-Based Wireless Network management System Using COPRAS Method

Cloud-Based Wireless Network Management System Using COPRAS ...

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Multi-Agent Systems for Collaborative Intelligence (ICMSCI), International Conference on

作者： Ravindran D Raja S Murugannatham A Stephen Deepak K. Shanthi V. Sivaraj School of Management Kristu Jayanti College Autonomous Bengaluru India School of Management Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Science (PG) Kristu Jayanti College Autonomous Bengaluru India Department of Computer Science Shri Krishnaswamy College for Women Chennai Tamilnadu India Department of Computer Science Karpagam Academy of Higher Education Coimbatore India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

This research discusses the assessment and ranking of cloud-based wireless network solutions in a manufacturing environment and examines ways to deal with the major troubles and improve performance and reliability as well as safety. The research uses the COPRAS method which in turn is applied to evaluate a wide range of criteria including technical specifications, performance metrics, security features or scalability. Two different network solutions are assessed, named Solutions A and B which has superior composite performance according to our method. As opposed to Solution A, Solution B has advanced scalability options, superior performance metrics, strong security features, and improved cost performance. Implementation of Solution B is expected to make it easier for factories to deal with fluctuations in production volume, resulting in gains in efficiency and productivity. The study makes the point that Manufacturing operations must be able to assess the benefits and drawbacks of moving on various network solutions. However, to ensure that the solution adopted by all concerned will remain effective for some time to come, this kind vigilance is necessary. Since listening alone will do no good, there is a need for continuous surveillance and appraisal to ensure the system of Solution B maintains effectiveness in line with industry needs and standards. The study's findings are useful deeper insights into the evaluation and ranking of cloud-based wireless network solutions in the manufacturing industry making a contribution to its network infrastructure and the optimization of the operational process in manufacturing.

关键词： Measurement Productivity Wireless networks Scalability Surveillance Production facilities Manufacturing Safety Security Standards

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Enhancing the Felsenstein Method to Reinvigorate Phylogenetic Starting in the Big Data 6

Enhancing the Felsenstein Method to Reinvigorate Phylogeneti...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Saxena, Ashendra Kumar Vishwkarma, Priyanka Kumar, Sandeep Thangarasu, N. Bhuvaneshwari, K.S. Ashok, Bhandari Mahesh College of Computing Science and Information Technology Teerthankar Magaveer University Uttar Pradesh Moradabad India Invertis University Department of Computer Science & Engineering Uttar Pradesh Bareilly India School of Commerce and Management IIMT University Uttar Pradesh Meerut India Karpagam Academy of Higher Education Department of Computer Science Tamil Nadu Coimbatore India Karpagam College of Engineering Department of Artificial Intelligence and Data Science Tamilnadu Coimbatore India Vishwakarma Institute of Information Technology Maharashtra Pune India

ISBN: (纸本)9798350304480

The present research examines how the Felsenstein approach might be improved in light of huge data and evolutionary inference. The Felsenstein approach, phylogeny starting points, huge data, statistical techniques, and testing hypotheses are among the important ideas and terms covered in the overview. It emphasizes the importance of repeatability in evolutionary inferences as well as the difficulties brought on by rogue genera and bootstrapping proportions. The article suggests a brand-new strategy to increase the accuracy of phylogenetic investigations that makes use of transfer separation and bipartition distance. The abstract's conclusion emphasizes the need of better methods for managing huge datasets and for recognizing instability taxonomic. © 2023 IEEE.

关键词： ABC Between trees Big data Bipartition distance Bootstrap Confidence intervals Felsenstein method Homogenization Hypothesis testing Phylogenetic estimation Phylogenetic starting Reboot method Rogue taxa Statistical approach Taxonomic units Transfer distance

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Optimizing Railway Traffic management Using Fuzzy Logic-Based Decision-Making Systems

Optimizing Railway Traffic Management Using Fuzzy Logic-Base...

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International Conference on Computational and Characterization Techniques in Engineering & sciences (CCTES)

作者： Nalli Vinaya Kumari G S Pradeep Ghantasala Rajesh Sharma R Ananthanagu U Pellakuri Vidyullatha Dileep Kumar Pandiya Department of Computer Science and Engineering Malla Reddy Engineering College for Women JNTUH Hyderabad Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bengaluru India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Guntur Andhra Pradesh India Principl Software Engineer Zoominfo Technologies Boston USA

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

Railway web page traffic manipulate is a complex and dynamic method that includes making real-time picks based mostly on various uncertain and difficult to understand factors, collectively with fluctuating passenger demand, diverse train schedules, and unpredictable weather conditions. Traditional decision-making strategies often battle to cope with the ones uncertainties, foremost to inefficiencies and potential safety risks. This paper proposes the software program of fuzzy properly judgment-based completely decision-making systems to optimize railway web page traffic manipulate. Fuzzy properly judgment, with its potential to model uncertainty and control difficult to understand data, offers a robust framework for boosting decision-making approaches in railway operations. By simulating various conditions and integrating real-time data, the proposed gadget can dynamically regulate train schedules, manipulate delays, and enhance everyday operational efficiency. The paper may present case studies demonstrating the effectiveness of fuzzy properly judgment in dealing with railway web page traffic, reducing delays, and improving passenger satisfaction. The findings advice that incorporating fuzzy properly judgment into railway web page traffic manipulates systems can purpose greater adaptive and resilient railway operations, ultimately contributing to greater steady and additional reliable rail networks.

关键词： Schedules Uncertainty Scalability Decision making Web pages Rail transportation Real-time systems Software Delays Safety

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Various Modulation Types Classification on the Air by Convolutional Neural Network 7

Various Modulation Types Classification on the Air by Convol...

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7th International Conference on Future Networks and Distributed Systems, ICFNDS 2023

作者： Hammadi, Yousif I Alsaeedi, Mokhalad Abdulameer Kadhim Mahmood, Omar Abdulkareem Sameen, Aws Zuhair Muthanna, Mohammed Saleh Ali Aziz, Ahmed Bilad Alrafidain University College Diyala Iraq Department Of Communications Engineering College Of Engineering University Of Diyala Baqubah32001 Iraq Department Of Medical Instrumentation Engineering Techniques College Of Medical Techniques Al-Farahidi University Baghdad Iraq Institute Of Computer Technologies And Information Security Southern Federal University Taganrog344006 Russia Department Of Computer Science Faculty Of Computer And Artificial Intelligence Benha University Egypt Department Of International Business Management Tashkent State University Of Economics Tashkent Uzbekistan

ISBN: (纸本)9798400709036

Deep learning (DL), a relatively recent AI technique, has been successfully applied to the problem of automated modulation categorization (AMC), with promising results. An essential part of developing the spectrum-sensing capabilities needed by software-defined radio is carrying out radio signal classification jobs, which we did in this research by introducing a better deep neural architecture. Different detection techniques were utilized in the literature;however, DL neural networks are recently utilized in this field. Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM) which is one variation of the RNN network, and other techniques are some of the employed DL architectures in the field of AMC. In this paper, Convolutional Neural Network (CNN) model has been built to automatically classify ten-modulation formats correctly. The suggested CNN network is constructed mainly of six-Convolutional layers. The overall number of trainable parameters in the proposed network is 1,757,962. Thus, the network accuracy, which was achieved during the training reached more than 90%. Python programming packages have been used to implement the suggested approach using *** platform, which provides wide-range of facilities. © 2023 ACM.

关键词： Network architecture

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Envisioning Extraterrestrial Construction and the Future Construction Workforce: A Collective Perspective 41

Envisioning Extraterrestrial Construction and the Future Con...

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41st International Symposium on Automation and Robotics in Construction, ISARC 2024

作者： Jafari, Amirhosein Zhu, Yimin Karunatillake, Suniti Qian, Jennifer Jeong, Shinhee Kazemian, Ali Webb, Andrew Bert S. Turner Department of Construction Management Louisiana State University United States Department of Geology & Geophysics Louisiana State University United States Lutrill & Pearl Payne School of Education Louisiana State University United States Department of Counseling Leadership Adult Education and School Psychology Texas State University United States Division of Computer Science and Engineering Louisiana State University United States

ISBN: (纸本)9780645832211

Humanity’s evolution toward an interplanetary species poses a new frontier for the construction industry: extraterrestrial construction. With fast technological advancements in manufacturing and robotics, it is a matter of when, not if, before humans make perpetual habitats on nearby planetary bodies. We envision the emerging frontier of the construction industry as extraterrestrial construction, where the role of workers and their required skills will change dramatically. Due to the extreme and hazardous outer-space conditions, the future of extraterrestrial construction will be technology-intensive, from using onsite machine and robot operations to using cyberphysical systems for managing logistical operations. Accordingly, the role and skillsets of construction workers in future extraterrestrial construction projects will contrast with the current practices on Earth. We aim to present a collective perspective on the nature of future extraterrestrial construction and the hierarchy of the skills required by future workers, as well as emerging technologies that can be used for developing a future-ready workforce. To accomplish this, we convened a national interdisciplinary workshop, engaging diverse stakeholders in the United States, including researchers, educators, and professionals, from academia, industry, and government. This paper summarizes the outcomes of our workshop, structured around three core themes: future work (extraterrestrial construction), future workers (extraterrestrial workforce), and future technology (emerging technologies for workforce training). The detailed exploration within these three themes marks an initial endeavor to chart a course for training in extraterrestrial construction, particularly with NASA’s Moon to Mars Program in mind. © 2024 ISARC. All Rights Reserved.

关键词： Robotics

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Role of Underwater Robots in Ocean Exploration Research 1

Role of Underwater Robots in Ocean Exploration Research

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1st International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022

作者： Poongundran, Mahizharuvi Prasannan, D. Agnes, J. Sandra Das, Saptorshi Anusha, D.J. Amandykova, Dina Sri Meenakshi Government Arts College for Women Department of Computer Science Tamilnadu India Karpagam College of Engineering Tamilnadu Coimbatore India St. Philomena's College Dept of Computer Science Mysuru India KIIT School of Management Kiit Deemed to Be University India Sri Padmavati MahilaVisvavidy Alayam Department of Computer Science & Engineering Tirupati India International Education Corporation Department of Architecture Almaty Kazakhstan

ISBN: (纸本)9781665497107

Underwater robot is pre-programmed technology that has made it possible for ocean researchers to collect a vast range of information regarding unexplored and dangerous parts of oceans. The robot-ocean network can help researchers in attaining new types of information that was impossible to be collected previously. These remotely operated vehicles go deeper into the water for gaining information using Scarlet Knight. It displays deep ocean cases to the researcher through its automated technology. In literature review chapter of this study, role played by marine-robotics, in exploration research, modelling of underwater robot, sensor and GPS systems incorporation in underwater-robot technology for conducting ocean exploration research are discussed. This section has provided conceptual frameworks and theoretical frameworks for supporting the analysis of the impact of underwater robots in ocean-exploration research. In the methodology chapter of this study, the ways data has been collected in this study have been described. Secondary data collection method is chosen for this study in order to collect vast range of existing information regarding the role of robots in underwater research. Further, in the findings and discussion chapter, different variables including exploration of deep sea for research, use of automated technologies and many others have been discussed. Based upon the findings, it has been found that there exists a positive relationship between ocean research and use of underwater robots. This study has provided recommendations for addressing different challenges associated with this technology in exploring the sea in most effective way for adding new insight into research. © 2022 IEEE.

关键词： Model predictive control

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Computing Paradigms in Emerging Vehicular Environments:A Review

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IEEE/CAA Journal of Automatica Sinica 2021年第3期8卷 491-511页

作者： Lion Silva Naercio Magaia Breno Sousa Anna Kobusińska António Casimiro Constandinos X.Mavromoustakis George Mastorakis Victor Hugo C.de Albuquerque Department of Computer Science Faculty of SciencesUniversity of LisbonLisbon 1749-016Portugal Laboratory of Computing Science PoznańUniversity of TechnologyPoznan 60-965Poland Department of Computer Science University of NicosiaNicosia CY-2417Cyprus Department of Management Science and Technology Hellenic Mediterranean UniversityAgios Nikolaos 72100Greece LAPISCO Federal Institute of EducationScience and Technology of CearáFortaleza 60750-740 ARMTEC Tecnologia em Robótica Fortaleza 60150000Brazil

Determining how to structure vehicular network environments can be done in various ***,we highlight vehicle networks’evolution from vehicular ad-hoc networks(VANET)to the internet of vehicles(Io Vs),listing their benefits and *** also highlight the reasons in adopting wireless technologies,in particular,IEEE 802.11 p and 5 G vehicle-toeverything,as well as the use of paradigms able to store and analyze a vast amount of data to produce intelligence and their applications in vehicular *** also correlate the use of each of these paradigms with the desire to meet existing intelligent transportation systems’*** presentation of each paradigm is given from a historical and logical *** particular,vehicular fog computing improves on the deficiences of vehicular cloud computing,so both are not exclusive from the application point of *** also emphasize some security issues that are linked to the characteristics of these paradigms and vehicular networks,showing that they complement each other and share problems and *** these networks still have many opportunities to grow in both concept and application,we finally discuss concepts and technologies that we believe are *** this work,we emphasize the crucial role of these concepts for the well-being of humanity.

关键词： Computing paradigm cloud edge fog internet of vehicle(IoV) vehicular networks

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A Cascaded 2DOF-PID Control Technique for Drug Scheduling of Chemotherapy System 1

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1st International Conference on Machine Intelligence for Research and Innovations, MAiTRI 2023

作者： Panjwani, Bharti Mohan, Vijay Gupta, Himanshu Verma, Om Prakash Shri Madhwa Vadiraja Institute of Technology and Management Karnataka Udupi India Department of Mechatronics Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal576104 India Department of Computer Science ABES Institute of Technology Ghaziabad201009 India Dr. BR Ambedkar NIT Jalandhar Punjab Jalandhar144011 India

ISBN: (数字)9789819981298

ISBN: (纸本)9789819981281

This paper proposes a cascade control approach with a 2DOF-PID controller for finding the optimal drug schedule during chemotherapeutic treatment. The cell-cycle nonspecific model of tumor growth for breast cancer is considered. Drug concentration and toxicity are regulated by individual controllers. The main objective of the controller design is to reduce the tumor size with minimum harm to the patient. The problem of diverse objectives in chemotherapy is solved by using the NSGA-II optimization technique. The response by 2DOF-PID and conventional PID approach are compared for the designed model. In addition, the performance of controllers in dealing with parametric uncertainty is also included in this work. The findings suggest that the proposed 2DOF-PID technique performs better. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Chemotherapy

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