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4th International Conference on Signal Processing and Communication, ICSPC 2023

作者： Virani, Jash Daredi, Nikita Bhanushali, Aayush Shukla, Madhu Shah, Pooja Marwadi University Computer Engineering Big-Data Analytics Department Gujarat Rajkot India Marwadi University Computer Engineering Artificial Intelligence Department Gujarat Rajkot India Pandit Deendayal Energy University Cse Department Gujarat Gandhinagar India

ISBN: (纸本)9798350300772

The rise in mental health problems among people and the need for effective solutions for mental health have led to a lot of research in the machine learning domain for its applications in mental healthcare Many people's lives have been affected by the exponential rise in mental health and depression, and various factors must be revised. Different situations can have an impact on one's mental stability. So, taking the factors in mind like gender, age, insomnia, loneliness, depression level, aggressiveness, stress level etc. we are going to analyze the most affecting factors for poor mental health. Nowadays mostly people are facing some kind of mental health problems but very few people are giving attention to their mental health. So, our main purpose is to analyze the factors and find those factors which are responsible for a person's poor mental health. Those factors are also anonymous by the person itself and They don't even know that they have weak mental health. For that we have taken the initiative to analyze and point out the main causes for poor mental health by circulating a google form Which has questions regarding regular lifestyle and from that we have collected data of different types of persons who are from different professions like students, employees, professors etc. After collecting the data, we had done preprocessing on that data and then we applied machine learning algorithms for classification and prediction. By applying machine learning algorithms, we found different types of outputs and by taking those outputs we can say which are more affecting factors on a person's mental health and we can suggest how people should improve their mental health and what type of things they should avoid for their good mental health. © 2023 IEEE.

关键词： Machine learning

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Cash Flow Forecasting Based on Wavelet Transform and Neural Networks 8

Cash Flow Forecasting Based on Wavelet Transform and Neural ...

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8th International Conference on computer Science and engineering, UBMK 2023

作者： Soylen, Zumra Mammadova, Farida Fasounaki, Mandana Ozmen, Ayse Irem Ince, Gokhan Istanbul Technical University Department of Computer Engineering İstanbul Turkey Mdp Group R&d Department İstanbul Turkey Istanbul Technical University Department of Computer Engineering & Ai and Data Science Application and Research Center İstanbul Turkey

ISBN: (纸本)9798350340815

Cash flow forecasting is a critical task for businesses and financial institutions to ensure effective financial planning and decision-making. However, limited data availability poses a significant challenge when developing accurate and robust cash flow prediction models. In this paper, we investigate the performance of various forecasting methods and propose an approach based on wavelet transform for improving the forecasting accuracy. We demonstrate the effectiveness of the proposed approach with the best combination of wavelet functions and methods for forecasting future values in a univariate time series. We investigate the impact of wavelet transform on forecasting techniques based on open-source datasets. Our methodology includes data collection, preprocessing, feature engineering, model selection, and experimentation using different performance evaluation metrics. © 2023 IEEE.

关键词： Forecasting

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Type 2 Diabetes Mellitus Prediction with Gut Microbes Using Machine Learning Through Shotgun Metagenomic Sequencing 1

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World Conference on Information Systems for Business Management, ISBM 2023

作者： Sharma, Akhilesh Kumar Bhardwaj, Sachit Srivastava, Devesh Kumar Srivastava, Prateek Department of Data Science and Engineering Manipal University Jaipur Rajasthan Jaipur India Department of Information Technology Manipal University Jaipur Rajasthan Jaipur India Department of Computer Science and Engineering Graphic Era Hill University Uttrakhand Dehradun India

ISBN: (数字)9789819983490

ISBN: (纸本)9789819983483

Type 2 diabetes mellitus (T2DM) has become a worldwide epidemic as a result of insulin resistance and insufficient insulin production. New research points to dysbiosis in the gut microbiota as a major contributor to type 2 diabetes. Dysbiosis is an imbalance in gut microbes, metabolic activity, or distribution. Gut microbiome dysbiosis alters intestinal barrier functioning and host metabolic and signaling pathways, which contribute to insulin resistance. This study aims to develop machine learning algorithms capable of predicting type 2 diabetes by utilizing features obtained from shotgun metagenomic sequencing of the gut microbiome. The taxonomic and functional characteristics of the gut microbiota are determined by subjecting them to shotgun metagenomic sequencing. We use metrics such as the area under the receiver operating characteristic curve (ROC-AUC), precision, recall, and F1-score to evaluate the models’ effectiveness. In conclusion, the results of this work show that T2DM may be predicted from gut microbial profiles using shotgun metagenomic sequencing in conjunction with machine learning algorithms. SVM with RBF kernel performed the best with 0.8939 ROC-AUC, followed by random forests with 0.8934 ROC-AUC. These findings lay the groundwork for additional investigations into the impact of gut microbiota on the onset of type 2 diabetes and the creation of methods for detecting it without invasive measures. Exploring possible therapeutic approaches targeting the gut microbiota for T2DM control and validating these models in larger and more varied populations require more investigation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Insulin

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MOCBOA:Multi-Objective Chef-Based Optimization Algorithm Using Hybrid Dominance Relations for Solving engineering Design Problems

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computer Modeling in engineering & Sciences 2025年第4期143卷 967-1008页

作者： Nour Elhouda Chalabi Abdelouahab Attia Abdulaziz S.Almazyad Ali Wagdy Mohamed Frank Werner Pradeep Jangir Mohammad Shokouhifar Computer Science Department University of M’silaIchebiliaM’sila28000Algeria Computer ScienceDepartment Mohamed El Bachir El IbrahimiUniversity of Bordj BouArreridjBordj BouArreridj34000Algeria Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan Faculty of Mathematics Otto-von-Guericke UniversityMagdeburg39016Germany University Centre for Research and Development Chandigarh UniversityMohali140413India Department of Electrical and Computer Engineering Shahid Beheshti UniversityTehran14399Iran DTU AI and Data Science Hub(DAIDASH) Duy Tan UniversityDa Nang550000Vietnam

Multi-objective optimization is critical for problem-solving in engineering,economics,and *** study introduces the Multi-Objective Chef-Based Optimization Algorithm(MOCBOA),an upgraded version of the Chef-Based Optimization Algorithm(CBOA)that addresses distinct *** approach is unique in systematically examining four dominance relations—Pareto,Epsilon,Cone-epsilon,and Strengthened dominance—to evaluate their influence on sustaining solution variety and driving convergence toward the Pareto *** comparison investigation,which was conducted on fifty test problems from the CEC 2021 benchmark and applied to areas such as chemical engineering,mechanical design,and power systems,reveals that the dominance approach used has a considerable impact on the key optimization measures such as the hypervolume *** paper provides a solid foundation for determining themost effective dominance approach and significant insights for both theoretical research and practical applications in multi-objective optimization.

关键词： Multi-objective optimization chef-based optimization algorithm(CBOA) pareto dominance epsilon dominance cone-epsilon dominance strengthened dominance

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Face Mask Detection Using Support Vector Machine

Face Mask Detection Using Support Vector Machine

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Divya Priya, D. Subbulakshmi, R. Purushotham, P. Kiran, Ajmeera Arulananth, T.S. Kavya, S.P. MLR Institute of Technology Department of Computer Science and Engineering Hyderabad India Karpagam Institute of Technology Department of Computer Science and Engineering Coimbatore India MLR Institute of Technology Department of Electroncis and Communication Engineering Hyderabad India KPR Institute of Engineering and Technology Department of Artificial Intelligence and Data Science Coimbatore India

ISBN: (纸本)9798350348217

According to a report published by the World Health Organization (WHO), the only two primary ways in which the COVID-19 virus can be spread are through breathing contaminated air and through direct physical contact. Wearing a mask is one of the bare minimum preventative measures that can be taken against the transmission of certain viral infections, including COVID-19. Therefore, it is much more important to wear a mask properly in very crowded areas such as public parks, supermarkets, and shopping malls. This is because the risk of spreading an infectious disease is significantly higher in these settings. Face Mask Detection is a technique that we developed so that we could avoid problems like these. It can determine whether or not a person is wearing a mask on their face. There have only been a handful of scant studies done on face mask detection. © 2023 IEEE.

关键词： SARS

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LTL Model Checking for Verification of Electronic Medical Record (EMR) Design 8th

LTL Model Checking for Verification of Electronic Medical R...

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8th International Conference on Mathematics: Pure, Applied and Computation, ICoMPAC 2023

作者： Taryana, Acep Adzkiya, Dieky Mufid, Muhammad Syifa’ul Mukhlash, Imam Abate, Alessandro Department of Mathematics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Electrical Engineering Engineering Faculty Universitas Jenderal Soedirman Purwokerto Indonesia Department of Computer Science University of Oxford Oxford United Kingdom

ISBN: (纸本)9789819721351

This paper presents an in-depth investigation into the verification of a software design model, focusing on the context of Electronic Medical Record (EMR) systems. Verification plays a critical role in ensuring the correctness and reliability of such systems, making it a topic of paramount importance. In this study, we undertake the task of remodeling the EMR requirements using a finite transition system to facilitate rigorous analysis and verification. Additionally, we express the formal specification through Linear Temporal Logic (LTL), leveraging its expressive power and ability to capture temporal properties accurately. To assess the validity of the design model, we employ the widely recognized SPIN model checker, a tool known for its effectiveness in detecting errors and inconsistencies in software systems. Our analysis reveals several critical findings. Specifically, the model checker successfully identifies paths within the design model that fail to satisfy the specified LTL formula, shedding light on potential areas of concern. Moreover, the generation of a comprehensive counterexample provides valuable insights for further analysis and improvement of the software design. Overall, this research highlights the significance of verification techniques in software design and emphasizes the applicability of the finite transition system and LTL in this context. The findings underscore the importance of thorough verification and the potential benefits of employing tools like SPIN to enhance the reliability and robustness of EMR systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Software design

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VeRB: Revolutionizing Vehicle Registration with Blockchain for Enhanced Security and Efficiency in RTO Processes 3

VeRB: Revolutionizing Vehicle Registration with Blockchain f...

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Ramalingam, Gautham Praveen Pandian, Deepika Rajan, Deepak Syed Ammal Engineering College Department of Computer Science and Business Systems Tamilnadu Ramanathapuram India Syed Ammal Engineering College Department of Artificial Intelligence and Data Science Tamilnadu Ramanathapuram India Syed Ammal Engineering College Tamilnadu Ramanathapuram India

ISBN: (纸本)9798350354348

The Vehicle-RTO-BlockChain (VeRB) system presents a pioneering solution to modernize the vehicle registration and re-registration process within Regional Transport Offices (RTOs) in India. Our work focuses on implementing blockchain technology to address challenges related to data security, administrative efficiency, and transparency in managing vehicle registration records. The VeRB system encompasses a user-friendly registration portal integrated with robust data verification modules and a permissioned blockchain infrastructure tailored to our specific needs. Through dynamic updating mechanisms and secure historical data storage, our system ensures the accuracy, integrity, and accessibility of registration records while mitigating risks associated with fraud and duplication. This abstract provides an overview of our research, highlighting the key components, benefits, and implications of the VeRB system in revolutionizing automotive registration practices and fostering safer, more streamlined transportation systems tailored to our organizational goals. © 2024 IEEE.

关键词： Blockchain

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Research on Metaverse Security and Forensics

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computers, Materials & Continua 2023年第10期77卷 799-825页

作者： Guangjun Liang Jianfang Xin Qun Wang Xueli Ni Xiangmin Guo Pu Chen Department of Computer Information and Cyber Security Jiangsu Police InstituteNanjingChina Engineering Research Center of Electronic Data Forensics Analysis NanjingChina Key Laboratory of Digital Forensics Department of Public Security of Jiangsu ProvinceNanjingChina School of Intelligent Engineering Nanjing Institute of Railway TechnologyNanjingChina

As a subversive concept,the metaverse has recently attracted widespread attention around the world and has set off a wave of enthusiasm in academic,industrial,and investment ***,while the metaverse brings unprecedented opportunities for transformation to human society,it also contains related *** is a digital living space with information infrastructure,interoperability system,content production system,and value settlement system as the underlying structure in which the inner core is to connect real residents through applications and *** social incentives and governance rules,the metaverse reflects the digital migration of human *** article will conduct an in-depth analysis of the metaverse from the perspective of electronic data ***,from the perspective of Internet development,the background and development process of the metaverse is *** systematically elaborating on the concept and connotation of the metaverse,this paper summarizes the different views of current practitioners,experts,and scholars on the ***,from the perspective of metaverse security,the social risk and crime risks of the metaverse are *** the importance of metaverse forensics is ***,from the perspective of blockchain,smart wearable devices,and virtual reality devices,the objects and characteristics of metaverse forensics have been studied in *** smart wearable devices as an example,this paper gives the relevant experimental process of smart bracelet ***,many challenges faced by metaverse forensics are summarized by us which provide readers with some exploratory guidance.

关键词： Metaverse forensics blockchain smart wear virtual reality

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Autonomous Robot Navigation in Unknown Terrains using Generative Adversarial Networks 4

Autonomous Robot Navigation in Unknown Terrains using Genera...

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4th International Conference on Soft Computing for Security Applications, ICSCSA 2024

作者： Chitra, P. Sridar, K. Govindan, Sudha Britto Raj, S. Akshya, J. Choudhry, Mani Deepak Sundarrajan, M. St Joseph's Institute of Technology Department of Artificial Intelligence and Data Science Chennai India Veerammal Engineering College Department of Computer Science and Engineering Dindigul India Sona College of Technology Department of Computer Science and Engineering Salem India RRASE College of Engineering Department of Computer Science and Engineering Chennai India SRM Institute of Science and Technology Department of Computational Intelligence Chennai India SRM Institute of Science and Technology Department of Computing Technologies Chennai India SRM Institute of Science and Technology Department of Networking and Communications Chennai India

ISBN: (纸本)9798331515720

Autonomous Robot Navigation in unknown and dynamic environments is considered one of the grand challenges in robotics. These motions that guide it span from rescue operations to planetary exploration. Classical methods for path planning, including A*, Dijkstra, and RRT, were unable to balance the efficiency and adaptability of motion planning over complex terrain. This may have a powerful solution using Generative Adversarial Networks (GANs) with advanced machine learning techniques to improve the ability of robotic navigation. This study proposes a GAN-based approach for designing an effective self-adaptive path planning and obstacle avoidance system for autonomous robots. Despite performing well in structured environments, traditional techniques normally fail in analysing the unstructured terrains with real-time adjustments and dynamic changes due to the high computational costs and lack of flexibility involved. In this regard, the proposed GAN-based system resolves these issues by rating navigation paths concerning safety and efficiency. Quantitative analysis demonstrates that within a forest, desert, urban, or off-road environment, the computational times by using the developed strategy turn out to be 0.12 seconds, 0.10 seconds, 0.14 seconds, and 0.13 seconds, respectively, behaving much lower than what can be achieved with other algorithms. This approach proves much superior in terms of computational efficiency path smoothness and adaptability under different environmental conditions in applications related to autonomous robot navigation systems. © 2024 IEEE.

关键词： Generative adversarial networks

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Optimization of Path Planning for Automated Vehicles Using SLAM Algorithm 1st

Optimization of Path Planning for Automated Vehicles Using S...

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1st International Conference on data engineering and Machine Intelligence, ICDEMI 2023

作者： Prinslin, L. Selvi, R. Revathi, B. Yuvabharathi, E. Sharmila, L. Department of Computer Science and Engineering Agni College of Technology Chennai India Department of Artificial Intelligence and Data Science Dhanalakshmi College of Engineering Chennai India Department of Information Technology Jeppiaar Institute of Technology Chennai India Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9789819776153

SLAM (simultaneous localization and mapping) is a technique for automated vehicles that enables simultaneous map building and vehicle localization. The vehicle is able to map out uncharted terrain owing to SLAM algorithms. Engineers use the map information to carry out tasks such as path planning and obstacle avoidance. An autonomous machine needs the ability to plan the motion of a high-level command. For example, if a task is given to explore a particular area, the bot has to plan accordingly to complete the required task. To achieve this level of accomplishment, the path works on an algorithm that solves SLAM and path planning problems. The machine is designed in such a way that it will work as a grass cutter will complete the task in the given frame. The grass-cutting machine creates its own path in the frame and detects obstacle coming in the path. In this way, the SLAM robot is utilized in the application of agricultural field. In the current work, we have designed a 3-D model of a SLAM robot and its various components like the LIDAR Camera, Jetson Nano, Lithium-Ion Battery, Motor, and Body design machine. This model is capable of performing grass-cutting operations using a cutting blade and collection of waste in a sack attached to the machine. This machine works on automation based on path planning algorithms using ROS, this eliminates human interference. Various kinds of research papers were reviewed to compare different kinds of mechanisms and various components were analyzed for the final model *** check and verify that the author names are correctly recognized and presented in the correct sequence order, which is [given name, middle name/initial, family name] for the author(s). In addition, please verify that the name(s) and respective affiliation(s) shown on the metadata page are valid and make any necessary amendments if ***, have edited the affiliation of the last author. © The Author(s), under exclusive license to Springer Nat

关键词： SLAM robotics

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