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An Effective Implementation and Comparative Analysis of Mobile Robot Path Planning Algorithms

An Effective Implementation and Comparative Analysis of Mobi...

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2024 IEEE international conference on Recent advances in science and engineering Technology, ICRASET 2024

作者： Vigenesh, M. Taneja, Madhur Jayasree, S. Samrat, Bhavuk Padmapriya, G. Kulkarni, Prutha P Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore641021 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of S&h Chennai127 India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India School of Sciences Chemistry and Biochemistry Karnataka Bangalore India Vishwakarma Institute of Technology Entc Pune India

ISBN: (纸本)9798350388602

Among the most pressing and intricate challenges in control and computer engineering today is the navigation of autonomous mobile robots. People are now more motivated than ever to use innovative methods, thanks to the development of cutting-edge computational engineering technology. In order to address complicated engineering challenges in the real world, researchers have mostly looked to natural occurrences and their methods for inspiration. In challenging and dense environments, path planning is the best way of defining a safe route in which a mobile robot can navigate to achieve a certain goal from another location. Mobile robots thus require smart and efficient route planning algorithms for proper navigation and self-execution capabilities. In this study, four well-known algorithms for route planning were investigated: Hybrid DA+CS algorithm: The proposed methods DA, CS and PSO using a non-holonomic mobile robot. To test these methods, a test environment has been created with static impediments which will remain constant throughout the experiment. This is because it is where the intended route of the mobile robot is followed and where the availability of the map acquired for path planning algorithms allows assessing and testing them. A comparative study of the following algorithms has been carried out in an effort to understand the trade off between them based on the conventional performance indicators being used. © 2024 IEEE.

关键词： Robot programming

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A Comparative Analysis of Liver Cancer Detection using Neural Network Algorithm and Correlation Algorithm 2

A Comparative Analysis of Liver Cancer Detection using Neura...

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2nd international conference Computational and Characterization Techniques in engineering and sciences, IC3TES 2024

作者： Srivastava, Deepak Sharma, Vibhor Kumar, Pramod Sharma, Yogesh Kumar Swami Rama Himalayan University Himalayan School of Science & Technology Department of Computer Science & Engineering Dehradun India I.T.S. Engineering College Computer Science & Engineering Greater Noida India

ISBN: (纸本)9798350364699

The fast development of machine learning and AI in recent years has made it a widely used method. Because of its widespread use and effective pattern recognition and classification techniques, big institutions have begun funding research in the healthcare sector to boost the precision with which illnesses may be predicted. However, there are a number of difficulties in applying these methods. A significant barrier is the lack of a sufficient medical picture data set. This paper aims to provide a modest introduction to deep learning in medical image processing, including both the theoretical foundations and practical implementations of this technique. This thesis explores various major advances in computer science that contribute to the widespread appeal of deep learning (DL). This sheds light on the causes behind deep learning's meteoric rise in numerous application fields, including medical image processing. The aim was to deploy new methodologies on existing cancer datasets to see if machine learning and deep learning algorithms might be used for the detection of cancer. The purpose of this study was to classify cancer using many text and picture datasets. Liver BUPA disease database is the dataset that is processed using various machine learning and deep learning models. In this paper, we provide optimization algorithms that outperform the existing strategies in terms of efficiency. © 2024 IEEE.

关键词： Contrastive Learning

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A comprehensive review of recent advances and challenges in artificial intelligence and machine learning 4th

A comprehensive review of recent advances and challenges in ...

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4th international conference on Computational Methods in science and Technology, ICCMST 2024

作者： Singla, Ishdeep Hans, Aarti Smiksha Diya Swami, Harsh Kumar Ranjan, Rahul Computer Science and Engineering Chandigarh University Mohali Gharuan India

ISBN: (纸本)9781032911571

Modern advances in Artificial Intelligence (AI) and Machine Learning (ML) have transformed many businesses and elements of everyday life. Machine learning and deep learning support disease diagnosis, drug development, and patient risk assessment. This study examines how healthcare organizations evaluate enormous data sets using machine learning. This paper examines pros and downsides of current methods and research obstacles. Our goal is to educate healthcare professionals and government organizations on machine learning-based big data analytics in intelligent healthcare. AIML-powered chatbots enable governments educate and serve residents. They assist people get permits, answer questions, and use government services. Assistants help students make appointments, answer inquiries, and offer course material. Lead generation, product recommendations, and marketing efforts using AIML chatbots may boost revenue. AIML helps companies make data-driven decisions, find patterns, and recognize trends using data analysis and predictive analytics. Machine Learning studies how computers learn and improve without programming. Machine learning (ML) is a very captivating technology that has garnered significant interest over the course of technological advancements. As indicated by its nomenclature, this attribute endows the computer with a capacity that enhances its resemblance to human behaviour: the ability to acquire knowledge. © 2025 the Author(s).

关键词： Adversarial machine learning

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IoT-Driven Revolution: Transforming Elderly Healthcare Through Dynamic Heart Health Monitoring and Analysis

IoT-Driven Revolution: Transforming Elderly Healthcare Throu...

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2024 international conference on advances in Computing Research on science engineering and Technology, ACROSET 2024

作者： Mani, Kamlesh Singh, Kamlesh Kumar Litoriya, Ratnesh Amity University Department of Computer Science and Engineering Lucknow India Amity University Department of Electronics and Communication Engineering Lucknow India Medi-Caps University Department of Computer Science and Engineering Indore India

ISBN: (纸本)9798350388800

This research works to analyze the practical implementation of IoT technology in revamping the elderly health care system, with cardio care and heart health monitoring and analysis in mind. The study goes to great lengths not just to depict but also to seek solutions for the increasing problems of an aging population. As a result, new strategies for the provision of healthcare to the elderly are among the priorities. At its core, the research team will exploit Internet of Things (IoT) devices, sensors, and advanced data analytics to come up with a way of dynamic, continuous, and real-time monitoring of heart health. The paper starts by outlining whether changing demographics related to elderly people should be a top priority in healthcare services and, mainly, how much can be crucial in tackling heart health issues. After setting goals, the study will proceed by formulating, testing, and assessing an efficient Internet of Things-based healthcare approach for monitoring the heart health of elderly people. Regarding details of a method that involves picking up IoT gadgets and sensors, data collection procedures and strategies for participant recruitment will be provided. This article is focused on such technologies as architecture, heart disease monitoring, and algorithms for data processing. Findings unveiled some basic facts about the data collected from the elderly, for instance, their cardiac-related research. The implementation of the research findings in practice is mentioned, stressing patient-oriented projects such as personalized care plans and the interventions done at the right time by the Internet of Things-driven healthy lifestyle system. The last paragraph outlines the future directions for the technology-proficient healthcare assistants of tomorrow, including their refinement and mass use, ultimately ending up with the affirmation of the revolutionized elderly care practices of the future brought forth by IoT technologies. Firstly, the study exemplifies

关键词： Electronic health record

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The Role of Modern Machine Intelligence in Decoding Activity Patterns from Visual Data of Various Organisms

The Role of Modern Machine Intelligence in Decoding Activity...

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2023 international conference on Recent advances in science and engineering Technology, ICRASET 2023

作者： Gowrishankar, J. Kumar, Ritesh Srivastava, Dharmesh Kumar Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Maharishi University of Information Technology Maharishi School of Engineering & Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350306927

The integration of modern machine intelligence presents a transformative paradigm in the study of organisms' behaviors through visual data analysis. Leveraging deep learning algorithms like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), this approach automates the extraction of intricate patterns from images and videos, enabling comprehensive insights into diverse organisms. Object detection algorithms further facilitate precise tracking. By surpassing traditional methods, it enhances accuracy and scalability. Ethical considerations guide responsible research. This fusion of technology and ecology fosters a deeper understanding of natural ecosystems, paving the way for sustainable coexistence with the environment and the preservation of biodiversity. © 2023 IEEE.

关键词： Data handling

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Deep Fake Video Detection using Neural Networks 15

Deep Fake Video Detection using Neural Networks

引用

15th international conference on advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Das, Ancy Y. Sinchana, G. Sushmitha, C.S. Venkatesh, L. Yasaswvene Department of Computer Science and Engineering BGS Institute of Technology Adichunchanagiri University Karnataka BG Nagara India

ISBN: (纸本)9798331300579

As of late, the multiplication of free profound learning programming apparatuses has fundamentally worked with the advancement of practical face trades in recordings, bringing about the development of "DeepFake" (DF) recordings with negligible hints of *** AI-generated media, commonly known as DF, can now be generated with relative ease using artificially intelligent ***, despite the simplicity of generating DF using AI tools, detecting such manipulated content remains a significant *** algorithms to identify DF is inherently *** expect to achieve promising results against a comprehensive dataset of fake videos sourced from standard repositories. © Grenze Scientific Society, 2024.

关键词： Adversarial machine learning

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Enhancing Cybersecurity through Genetic Algorithm-Based Phishing Website Detection

Enhancing Cybersecurity through Genetic Algorithm-Based Phis...

引用

2024 IEEE international conference on Signal Processing, Information, Communication and Systems, SPICSCON 2024

作者： Biplob, Md Badiuzzaman Arefin, Mohammad Shamsul Reza, Ahmed Wasif Computer Science and Engineering Department Chittagong University of Engineering and Technology Chattogram Bangladesh Computer Science and Engineering Department East West University Dhaka Bangladesh

ISBN: (纸本)9798331510213

Cybercriminals design false webpages in an attempt to trick people into disclosing private information, such as passwords and credit card numbers. Strong cybersecurity measures are desperately needed, as phishing attacks are becoming more and more sophisticated. To improve cybersecurity, this study investigates the use of genetic algorithms for phishing website detection. We have used three real-world phishing website datasets to implement our work. Additionally, a thorough methodology that includes feature selection, data preprocessing, and the iterative process of the genetic algorithm is employed. This work proposes a hybrid-based method for phishing identification based on the website's URL that combines genetic and machine learning methods. The algorithm's effectiveness is demonstrated by the results, which also show its adaptability, relative advantages over conventional methods, and promising generalizability. By shedding light on the useful applications of genetic algorithms for phishing detection, the study advances the field of cybersecurity. The final model proposed in this work has a 99.99% accuracy rate on the test set. © 2024 IEEE.

关键词： Phishing

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Enhancing Drug Detection Strategies for Post-Rehabilitated Juveniles: A Comprehensive Review and Empirical Study 1

Enhancing Drug Detection Strategies for Post-Rehabilitated J...

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1st IEEE international conference on advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kaushik, Priyanka Gour, Prabha Bir, Lovish Ansari, Lubna Samnata, Rojalini Soundarya, R. Chandigarh University Dept. of Computer Science Engineering Chandigarh India Madhav University Dept. of Humanities and S.Science Pindwara India Chandigarh University Dept. of of Com. Science Engineering Chandigarh India Mangalayatan University Dept. of Computer Eng. and Applications Aligarh India Usha Martin University Dept. of Pharamcy Jharkhand India Dhanalakshmi Srinivasan College Dept. of Biomedical Engineering Coimbatore India

ISBN: (纸本)9798350356816

Drug addiction is a complex problem that will affect individuals of all ages, including juveniles. It is a chronic and often relapsing disease that requires continued care and support to help individuals achieve and maintain long-term recovery. While rehabilitation programs are designed to help individuals overcome addiction, relapse rates remain high, making post-rehabilitation drug detection an important component of continued care. This study aims to investigate the efficacy of various drug detection techniques for juveniles who have completed their rehabilitation. The success of rehabilitation program for young drug addicts depends on the creation of efficient drug detection rules and procedures that can assist avoid relapse and increase program effectiveness overall. The research technique comprises both an empirical investigation of post-rehabilitated juvenile participants and a thorough evaluation of the literature of past studies on drug detection for young people. The results of this study will have a big impact on how well drug detection policies and practises for young people who have completed their rehabilitation are developed. © 2024 IEEE.

关键词： Addiction Drug Post Rehabilitated Rehabilitation

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Advanced Simulation and Design Methodology of Josephson Traveling-Wave Parametric Amplifiers (JTWPA) for Quantum Electronics Applications 4

Advanced Simulation and Design Methodology of Josephson Trav...

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4th international conference on Innovative Research in Applied science, engineering and Technology, IRASET 2024

作者： Oukaira, Aziz Savaria, Yvon Boukadoum, Mounir Lakhssassi, Ahmed Department Of Engineering And Computer Science GatineauQCJ8X 3X7 Canada Polytechnique Montreal Department Of Electrical Engineering MontrealQCH3T 1J4 Canada Department Of Computer Science MontrealQCH3C 3P8 Canada GatineauQCJ8X 3X7 Canada

ISBN: (纸本)9798350309508

This paper examines the use of a quantum electronics Josephson Traveling-Wave Parametric Amplifier (JTWPA). The JTWPA presents distinctive features for amplifying quantum signals through the nonlinear Josephson junction, influenced by quantum effects at microwave energy scales. The study focuses on characterizing this quantum effects-based parametric amplification, offering perspectives in communication and information processing technologies. The results, obtained with the Advanced Design System (ADS) pathWave tool suggest promising applications of JTWPA, paving the way for significant advances in quantum electronics. Notably, the findings indicate that at a fixed frequency of 4 GHz and a constant pump current of 1.85 μA, the transmission efficiency of JTWPA decreases by 32% when exporting the design as layouts using the High-Frequency Structural Simulator (HFSS). Consequently, optimization with ADS emerges as a crucial step to assess transmission and information processing before the physical implementation of the JTWPA design. © 2024 IEEE.

关键词： Parametric amplifiers

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Enhancing Cloud Security Implementing AI-Based Intrusion Detection Systems 1

Enhancing Cloud Security Implementing AI-Based Intrusion Det...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Santharam, Vinoth Thoguluva Yallamelli, Akhil Raj Gaius Altemimi, Mohammed Alaa H. Arunachalam, Mahesh Prabu Rudrank, Shukla Ghule, Gauri Data Analytics Organization-Comcast Chennai India Amazon Web Services Inc Seattle United States Al-Khwarizmi College of Engineering The University of Baghdad Department of Information and Communication Engineering Baghdad Iraq Department of Information Technology and Computer Science AustinTX United States Kalasalingam Academy of Research and Education Deemed to be University Tamilnadu India Department of E and TC Pune India

ISBN: (纸本)9798331518578

The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion detection systems in the cloud may provide challenges. The pre-established IDS design may overburden a cloud segment due to the additional detection overhead. Within the framework of an adaptively designed networked system. We demonstrate how to fully use available resources without placing undue load on any one cloud server using an intrusion detection system (IDS) based on neural networks. To even more successfully detect new threats, the suggested IDS make use of neural network machine learning (ML). © 2025 IEEE.

关键词： Network intrusion

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