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5th international conference on Data science, Machine Learning and Applications, ICDSMLA 2023

5th International Conference on Data Science, Machine Learni...

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5th international conference on Data science, Machine Learning and Applications, ICDSMLA 2023

ISBN: (纸本)9789819780426

The proceedings contain 128 papers. The special focus in this conference is on Data science, Machine Learning and Applications. The topics include: Digitization of Monuments – An Impact on the Tourist Experience with Special Reference to Hampi;resume Parser Using Machine Learning;IOT Based Smart Hydroponics System;comparative Study of Machine Learning and Deep Learning Techniques for Cancer Disease Detection;High Thruput Modulation Approaches Used in Next Generation WiF’s Under Multi-impairments Environments with MATLAB Codes;skin Disease Detection;root Vegetable Crop Recommendation System Based on Soil Properties and Environmental Factors;deep Learning Model Development for an automatic Healthcare Edge computing Application;Empathetic Conversations in Mental Health: Fine-Tuning LLMs for Supportive AI Interactions;exploring Block Chain Technology with Applications, and Future Prospects;a Comprehensive Review of Soft computing Enabled Techniques for IoT Security: State-of-the-Art and Challenges Ahead;Performance Analysis of Machine Learning Algorithms on Imbalanced Datasets Using SMOTE Technique;An AI Based Nutrient Tracking and Analysis System;power Saving Mechanism for Street Lights System Using IoT;automatic Login System Using ATTINY85 IC;forecasting Stock Prices: A Comparative Analysis of Machine Learning, Deep Learning, and Statistical Approaches;smart Vision Bot;robots in Logistics: Apprehension of Current Status and Future Trends in Indian Warehouses;smart Healthcare: Enhancing Patient Well-Being with IoT;Detection of B-ALL Using CNN Model and Deep Learning;a Comprehensive Analysis for Advancements and Challenges in Deep Learning Models for Image Processing;a Comprehensive Survey on Enhancing Patient Care Through Deep Learning and IoT-Enabled Healthcare Innovations;attention-Based Image Caption Generation.

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Smart Last-Mile Delivery with IoT-Connected Robot Vehicles 10

Smart Last-Mile Delivery with IoT-Connected Robot Vehicles

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10th international conference on Smart computing and Communication, ICSCC 2024

作者： Sujatha, M. Kovarasan, Rajesh Kambattan Sudha, K. Mishra, Nilamadhab Thiyagarajan, G. Srinivasan, C. Easwari Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Department of Business Administration Tamil Nadu Mannargudi India School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh India Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350363104

This research discusses using IoT technologies with robot vehicles to improve last-mile deliveries. This novel method optimizes the last stage of the distribution chain, which sometimes presents logistical issues. The system examines robot vehicles' last-mile delivery monitoring, data collecting, and communication capabilities via an Internet of Things connection. These trucks collect and communicate traffic, packaging, and environmental data using sensors and communication equipment. Analyzing and processing this data improves route planning, delivery timing, and performance. Through the IoT, autonomous delivery trucks, a centralized control center, and other components of the delivery ecosystem could operate in combination. This collaborative network helps respond to changing situations such as highway congestion and package urgency by rerouting or raising delivery priority. The potential for delivery trucks to improve productivity, intelligence, and focus on the customer in the last mile of a package's journey. The IoT-driven solutions may be highlighted as major results, advantages, and implications for the logistics sector, addressing urbanization, consumer demands, and environmental concerns in modern delivery systems. © 2024 IEEE.

关键词： Trucks

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5th international conference on Data science, Machine Learning and Applications, ICDSMLA 2023

5th International Conference on Data Science, Machine Learni...

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5th international conference on Data science, Machine Learning and Applications, ICDSMLA 2023

ISBN: (纸本)9789819780303

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Incorporating Practical Single Cell and Spatial Transcriptomics Analysis in a Bioinformatics Course 11

Incorporating Practical Single Cell and Spatial Transcriptom...

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11th international conference on electrical, Electronic and computing engineering, IcETRAN 2024

作者： Smiljković, Lazar Mišić, Marko Obradović, Predrag Kovačević, Vladimir School of Electrical Engineering University of Belgrade Belgrade11000 Serbia BGI Genomics BGI Genomics Belgrade11000 Serbia

ISBN: (纸本)9798350386998

Single-cell RNA sequencing (scRNAseq) and spatial transcriptomics have emerged as a powerful tool for unraveling the heterogeneity of cell populations and understanding cellular dynamics at unprecedented resolution. However, analyzing scRNAseq and spatial data poses unique challenges due to their high dimensionality and inherent noise. In this paper, a comprehensive tutorial on incorporating practical single-cell and spatial transcriptomics analysis is presented using Scanpy in a bioinformatics course at the University of Belgrade, School of electrical engineering. Scanpy, a versatile Python toolkit, offers a wide range of functionalities for quality control, dimensionality reduction, clustering, and trajectory inference. Through lectures and hands-on exercises, students learn essential concepts and techniques, including working with annotated data objects, preprocessing scRNAseq data, performing dimensionality reduction using Principal Component Analysis and Uniform Manifold Approximation and Projection, conducting clustering analysis with the Leiden algorithm, and identifying marker genes for cell type annotation. By equipping students with these skills, we aim to empower the next generation of bioinformaticians to explore the complexities of single-cell and spatial transcriptomics data and advance our understanding of cellular biology. © 2024 IEEE.

关键词： Dimensionality reduction

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Exploring the Potential of Convolutional Neural Networks in automatic Diagnosis of Dragon Fruit Diseases from Plant Photographs 7

Exploring the Potential of Convolutional Neural Networks in ...

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7th international conference on Intelligent computing and control Systems, ICICCS 2023

作者： Mehta, Shiva Kukreja, Vinay Bansal, Ankit Kaur, Kushwant Singh, Amandeep Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Chandigarh University Department of Computer Science and Engineering Mohali India Gulzar Group of Institutions Department of Computer Science and Engineering Ludhiana India

ISBN: (纸本)9798350397253

Numerous instances of dragon fruit diseases over the years have caused an estimated 14% annual crop loss globally, affecting untold millions of people. The study of dragon fruit illnesses, or pathology, aims to increase plants' chances of surviving in the presence of pathogenic parasite microbes and poor climatic conditions. Environment-related elements that influence the development of dragon fruit diseases include temperature, pH, humidity, and moisture. Misdiagnosis can result in chemical overuse that costs money, environmental imbalance and pollution, and the establishment of pathogen strains that are resistant to treatment. The process of diagnosing diseases nowadays is time-consuming, expensive, and dependent on human scouting. Compared to the current method, automatic disease segmentation and diagnosis from dragon fruit photos can be somewhat useful. This study uses Convolutional Neural Network (CNN) models, to accurately identify four kinds of apple plant diseases from photographs of apple plant leaves. 'Healthy,' 'scab,' 'rust,' and 'many illnesses' are among the classifications. © 2023 IEEE.

关键词： Fruits

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Portable System for Health Hygiene Monitoring 4

Portable System for Health Hygiene Monitoring

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4th international conference on control, Artificial Intelligence, Robotics and Optimization, ICCAIRO 2023

作者： Ciufudean, Calin Buzduga, Corneliu Stefan cel Mare University Faculty of Electrical Engineering and Computer Science Suceava Romania

ISBN: (纸本)9798350300918

For healthcare IT is essential, as it determines the quality of people's lives, it creates patterns that help organize medical prevention activity conceptually, therefore it determines the quality of medical care, and ultimately it determines monitoring in real time of vital parameters as well as of environmental ones. The present work presents the design of an automatic health monitoring system capable to sanitize periodically the hands of the wearer. The electronic system developed is a portable one fixed on the wrist. Future developments of this automatic system are also discussed. © 2023 IEEE.

关键词： Health care

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Electronic Warfare UAV Combat Effectiveness Evaluation Based on GrC-Elm

Electronic Warfare UAV Combat Effectiveness Evaluation Based...

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2023 IEEE international conference on electrical, Automation and Computer engineering, ICEACE 2023

作者： Ma, Haichao Wang, Peng Li, Chao Wei, Yanming Air Traffic Control and Navigation College Air Force Engineering University Shaanxi Xi'an710051 China PLA Troop 93886 Air Traffic Control and Meteorological Department Xinjiang Urumqi830006 China School of Mechanical Engineering Xijing University Shaanxi Xi'an710123 China

ISBN: (纸本)9798350309614

To increase the combat capability of Electronic Warfare Unmanned Air Vehicle (EWUAV), a combat effectiveness evaluation method is proposed based on Granular computing (GrC) and modified Extreme Learning Machine (ELM). In the method, the combat effectiveness evaluation index system of EWUAV is constructed through statistical analysis, then using the reduction function of GrC key factors are extracted from many indices, finally the model of EWUAV combat effectiveness evaluation is established through ELM optimized by bat algorithm. Simulation results show that the method provides an effective solution for EWUAV combat effectiveness evaluation. © 2023 IEEE.

关键词： Bat algorithm Combat effectiveness evaluation EWUAV Extreme learning machine Granular computing

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Automated Characterization in Cryocon 22C at Wide Temperature Range using LabVIEW 7

Automated Characterization in Cryocon 22C at Wide Temperatur...

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7th international conference on Computer Applications in electrical engineering-Recent Advances, CERA 2023

作者： Bharadwaj, Jyotiska Bogdanović, Lip Marković, Lovro Jorhat India University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9798350305005

This paper presents the development of an algorithm using LabVIEW, a B2912B SMU, and a Model 22C Cryogenic temperature controller for automating the characterization of various semiconductor devices. The algorithm is carried out using LabVIEW. By removing human error and enhancing precision through temperature control, the research aims to streamline the measurement procedure. Users enter the desired temperature values into the LabVIEW program. The Cryocon 22C is then automatically turned on by the algorithm to use a PID control method to stabilize the temperature near the sample. Once the temperature has stabilized, the software performs automatic characterization of the sample, including Gummel plot and Gummel plot negative sweep. To accurately capture the temperature-dependent features of the sample, measurements are performed at various temperatures. The method has the potential to increase productivity in a variety of semiconductor characterization and research applications due to its success in achieving temperature stability and precise measurements. © 2023 IEEE.

关键词： Automation

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Backstepping control for Tracking of Solenoid Valve Actuated Pneumatic Continuum Soft Robots 19

Backstepping Control for Tracking of Solenoid Valve Actuated...

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19th international conference on electrical engineering, computing science and automatic control, CCE 2022

作者： Ayala-Carrillo, Jorge E. Trejo-Ramos, Christian A. Olguin-Diaz, Ernesto Parra-Vega, Vicente CINVESTAV-IPN Robotics and Advanced Manufacturing Department Ramos Arizpe Mexico

ISBN: (数字)9781665455084

ISBN: (纸本)9781665455084

Among the different soft robot types developed, pneumatic continuum soft robots are nowadays the most widely researched type due to their highly compliant behaviour, but their modeling and control remain challenging tasks given its distribute parameters nature and the nonlinearities of its elastomer material. These nonlinearities are aggravated by considering pneumatic actuation dynamics, leading to a highly complex system. While pneumatic actuation dynamics is usually not taken in account for the design of feedback controllers, experiments have shown that they are far from negligible. In this paper, we study a highly coupled nonlinear model that relates the Lagrangian dynamics approach of a continuum soft robot and the pressure dynamics of its embedded pneumatic chambers. Then, a model-based feedback control strategy based on backstepping is proposed for the tracking of a pneumatic continuum soft robot configuration, achieving exponential stability. Finally, simulations are presented and concluding remarks are discussed. © 2022 IEEE.

关键词： Dynamics

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Impact of Parametric Uncertainties on the Steady-State Performances of DFIG-Based WECS 10th

Impact of Parametric Uncertainties on the Steady-State Perfo...

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10th EAI international conference on Advancements of science and Technology, EAI ICAST 2022

作者： Ayenew, Endalew Biru, Getachew Mulatu, Asrat Berhanu, Milkias Electrical Power and Control Engineering School of Electrical Engineering and Computing Adama Science and Technology University Adama Ethiopia School of Electrical and Computer Engineering Addis Ababa Institute of Technology Addis Ababa University Addis Ababa Ethiopia Center of Excellence for Sustainable Energy College of Electrical and Mechanical Engineering Addis Ababa Science and Technology University Addis Ababa Ethiopia

ISBN: (纸本)9783031411724

This chapter presents the study carried out to discover uncertain parameters in a model of a doubly-fed induction generator (DFIG)-based wind energy conversion system (WECS) and to investigate their effects on WECS plant while harvesting energy from wind at varying speeds. This is carried out by analytically formulating the steady-state models of a DFIG-based WECS and computing the parameters of these models at different wind speeds that drive wind turbines at rotor speed from sub-synchronous to super-synchronous. The main uncertain parameters in this system are the mutual reactances between stator and rotor windings, and the reactance of rotor winding. These variations happen due to the varying wind speed. The effect of parametric uncertainties on the steady-state performances of DFIG-based WECS is examined. The results depicted that the steady-state performances of DFIG-based WECS are influenced by uncertain phenomena. Typically a 0.5% change in mutual reactances caused up to 10 kW change in the generator output power. Mainly, it causes instability in the performances of the DFIG-based WECS and slightly reduces overall efficiency at a higher value of the wind speed. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： DFIG-based WECS HAWT Performances of WECS Uncertain parameter

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