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Ultra-Wideband Pattern Reconfigurable Antenna for Base station Applications 5

Ultra-Wideband Pattern Reconfigurable Antenna for Base stati...

引用

5th IEEE India Council International Subsections Conference, INDISCON 2024

作者： Bhickta, Shalini Jaglan, Naveen Kumar, Amit Jaypee University of Information Technology Dept. of Electronics and Communication Engineering Waknaghat Solan India Jaypee University of Information Technology Dept. of Computer Science & Engineering and Information Technology Waknaghat Solan India

ISBN: (纸本)9798350376753

The proposed work aims at 5G base station antenna communication applications. The Reconfigurable Antenna is built with an idea of parasitic loaded elements in antenna. The proposed design has a zig-zag S-shape structure with a driven Monopole antenna located along the central axis and a parasitic structure enfolding around the monopole. Reconfiguration is accomplished by adjusting the PIN diodes bias voltages. The 2.44-9.46 GHz frequency range i.e., the Ultra-Wide-Band frequency spectrum is used at which this reconfigurable antenna is designed to operate. This paper has three radiation pattern which are obtained by two PIN diodes. Beam-steering capability in the elevation plane is achieved i.e., θ (0°-180°). The outcome shows the design's potential and its wide range concurrent applications for base station antennas. © 2024 IEEE.

关键词： Monopole antennas

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Breakpoint Estimation Using Age-Based SIR Model on COVID -19 Epidemic in Bangladesh 5

Breakpoint Estimation Using Age-Based SIR Model on COVID -19...

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5th International Conference on Sustainable Technologies for Industry 5.0, STI 2023

作者： Roy, Tonushree Masud, Md Abdul Hossain, Mohammad Jamal Samsuzzaman, Md. Hossen, Md. Showrov Jannath, Nahary Pstu Dept of Computer Science and Information Technology Dhaka Bangladesh Pstu Dept of Computer and Communication Engineering Dhaka Bangladesh

ISBN: (纸本)9798350394290

COVID-19 has disrupted the harmonic rhythm of civilized societies worldwide, including Bangladesh. The impact of this all-encompassing pandemic situation has spread across the globe and has also affected Bangladesh. COVID-19 prediction and breakpoint estimation have garnered significant attention for facilitating the recovery of a normal and healthy life. The SIR (Susceptible-Infected-Removed/Recovered) model is a widely-used epidemiological model employed for breakpoint estimation and prediction. Breakpoint estimation represents the point at which the curve reaches its highest peak position. In this study, we propose a variant of the SIR model, specifically an age-based SIR model, to estimate the breakpoint of the COVID-19 pandemic in Bangladesh. Our approach considers the age distribution of the population, recognizing its significant impact on disease spread and mortality rates. We focus on the effectiveness of age-specific contamination and treatment efforts to assess their role in combating the pandemic. To examine the impact of age categories, we compare results across selected groups based on different population factors. The findings indicate that middle-aged people are the most vulnerable group. Consequently, we excluded the less vulnerable groups and estimated the breakpoint using data from the most vulnerable age groups. The results from the age-based SIR model demonstrate a minimization of the gap between the predicted model and actual data points. Thus, the selected age groups exhibit better performance compared to considering all populations. This prediction serves to raise awareness among people, helping them understand the severity of this pandemic. © 2023 IEEE.

关键词： COVID-19

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An Investigation of Deep Neural Network based Techniques for Object Detection and Recognition Task in computer Vision 2

An Investigation of Deep Neural Network based Techniques for...

引用

2nd International Conference on Edge Computing and Applications, ICECAA 2023

作者： Sunil Kumar, Aithal S Mahesh, Kavitha St Joseph Engineering College Dept. of Computer Science and Engineering Mangalore India Nmam Institute of Technology Nitte Dept. of Computer Science and Engineering India Science and Engineering Nagarjuna College of Engineering & Technology Mudugurki Bengaluru India

ISBN: (纸本)9798350347579

Detection of objects and its recognition in visual sequences are the two critical tasks in the computer vision field. Various real-time applications such as autonomous vehicles, face recognition, health-care systems and space exploration requires highly reliable and precise object detection models. Traditional object detection and recognition algorithms are based on hand crafted and are considered to be erroneous, time consuming and expensive leading to the significant reduction of accuracy rate for object detection in large datasets. Recently, large number of promising deep neural networks models have been emerged for facilitating automated and accurate detection of varying scale objects and its precise recognition across various computer vision applications. Several GPU based neural models thereby incorporating context-aware capabilities have shown effective performance, which overcomes the drawbacks of traditional techniques. This research study provides an investigation of several popular deep learning models that exists for accurate object detection in various forms of visual sequences. Varying scale objects are detected frequently available in popular MS COCO and PASCAL datasets and their performance are evaluated utilizing one stage Yolo family and two stage Faster RCNN deep learning object detectors. At the end of the study, several future research directions for object detection task are discussed. © 2023 IEEE.

关键词： Object detection

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FPGA Implementation of Educational RISC- V Processor Suitable for Embedded Applications 3

FPGA Implementation of Educational RISC- V Processor Suitabl...

引用

3rd International Conference on Electrical, computer and Communication engineering, ECCE 2023

作者： Banna Saif, Md. Hasanul Sadad, Nahin Ul Islam Mondal, Md. Nazrul Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798350345360

Learning computer architecture has been a tough task for the learners. Sometimes it is not very effective when an architecture is learnt theoretically. Learning an architecture like RISC-V which has huge industrial interest has an additional benefit. The RISC-V instruction set architecture that is free to use was developed with flexibility and durability in mind. The adaptability of RISC-V enables a wide range of hardware implementations. Interests in Field Programmable Gate Array (FPGA) is growing in recent times due to its feasibility, flexibility and efficiency. In this paper, we implemented an educational processor based on the RISC-V architecture on FPGA with support for interfacing intended for embedded applications. An assembler was also designed and developed which can convert assembly codes into RISC-V standard machine codes that can help the users to operate the CPU easily. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Multiple Disease Prediction Based on User Symptoms using Machine Learning Algorithms 2

Multiple Disease Prediction Based on User Symptoms using Mac...

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2nd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Pentela, Ujwala Meesala, Anjali Nirupama Karingula, Deekshitha Seelamsetti, Nandini Krishna Veerlapalli, Swapna Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350347456

Every day, many individuals encounter different illnesses. The prognosis of a disease is the most pivotal part of treatment. Enormous increase in healthcare and medical data enabled accurate medical data analysis, which aids in early sickness discovery and beforehand patient care. This study focuses on performing research on the enormous medical data by exercising numerous supervised classification algorithms like Decision Tree, Support Vector Machine, K- Nearest Neighbor, Logistic Regression, Naive Bayes and Random Forest to anticipate the most probable disease grounded on the symptoms and also to directly prognosticate the possibility of whether or not the person might be suffering from that particular illness. Based on the symptoms, the model uses the results of the supervised classification algorithms and gives a final validation indicating the disease that the existent might be suffering. On combining the prognostications from all the below classification algorithms, the model returns a more accurate verification when compared to the prognostications made by individual models. This study enhances the swiftness of decision-making and can reduce the rate of false cons. It helps healthcare associations make better decisions about how to proceed with early patient care. It also aids healthcare professionals in developing further effective ways of treating patients. © 2023 IEEE.

关键词： Support vector machines

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A Procedure for Optimization of Placement Products in Large Industrial Areas of a Greek Soft Drinks Company

A Procedure for Optimization of Placement Products in Large ...

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2024 International Conference on Applied Mathematics and computer Science, ICAMCS 2024

作者： Tsakiridis, Sotirios Tsimpiris, Alkiviadis Angeioplastis, Athanasios Papaioannou, Nikolaos Mastorocostas, Paris Papakonstantinou, Apostolos Kamilali, Angeliki Varsamis, Dimitrios International Hellenic University Dept. Computer Informatics and Telecommunications Engineering Serres Greece University of West Attica Dept. Informatics and Computer Engineering Egaleo Greece Cyprus University of Technology Dept Civil Engineering and Geomatics Lemesos Cyprus

ISBN: (纸本)9798350363807

In this paper we present the process of optimal placement of industrial products (pallets) in mapped ware-houses and specifically in a soft drink company in Greece. The optimization criterion is to minimize the cost of moving the lifting machine that places the products in specific positions. The computational method of optimal placement of industrial products receives data from the automatic product count of the mapped warehouse and from the sales predictive model. Therefore, the computational method, having knowledge of the location and number of products in the warehouse and the prediction of sales for each product, places the products produced in an optimal way. Automatic product counting is carried out using an unmanned aerial vehicle (UAV) which developed and applied in soft drink company in Greece. The sales prediction is carried out through a prediction model which developed in a soft drink company in Greece. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Implementing HR Management System with an AI Powered ChatBot 3

Implementing HR Management System with an AI Powered ChatBot

引用

3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Susitra, D. Pratheesh, G. Karthiga, J.D. Dhanalakshmi, K. Shamreen Ahamed, B. Sylvia Grace, J. Dept. of Computer Science and Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai600119 India

ISBN: (纸本)9798331527549

Human Resource (HR) management is one important section that increases the success of an organization to handle some important functions like employee data manipulation, attendance tracking, payroll processing, and performance evaluation. With the management of these processes becoming key to the success of small-scale startups, it poses a very big challenge for many of them to be able to manage these processes efficiently and cost efficient. By contrast, the old era of traditional HR systems was based on database driven architectures that are expensive in terms of operational cost, require storage space and complex infrastructural needs. These limitations often make traditional HR systems impossible for a startup that would prefer lightweight, affordable, and scalable solutions. Startups need robust platforms to streamline HR work streams, but often lack with financial resources for building complex database driven systems. In this paper, an AI powered HR management system is developed to simplify employee management processes for small scale startups. In this system. cache memory is used instead of traditional databases, thereby the operational cost of the system will be reduced for storage and retrieval of employee details. Automated Attendance Management enhanced with Face Recognition technology, Payroll Management, Leave Management, Feedback Submission modules are included. It is integrated with an AI powered chatbot, which facilitates a smooth interaction by the employees with query for information, submit leave requests and pull up all payroll information etc. A user-friendly dashboard for a consolidated view of employee profiles, attendance records, leave approvals, and payroll data can be served over an optimized and time efficient HR workflow. This system addresses the needs of the startups such as flexible usage, cost effective operations and improved resource management. © 2025 IEEE.

关键词： AI powered chatbot for Small-scale startups using cache memory attendance management face recognition HR Management System leave management payroll management

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Mouse Cursor Control Using Dynamic Hand Gesture Recognition

Mouse Cursor Control Using Dynamic Hand Gesture Recognition

引用

2024 IEEE International Conference on Communication, Computing and Signal Processing, IICCCS 2024

作者： Fonseca, Darryll Majumder, Tanmoy Mitra, Banita Das, Arpita Das, Biswajit Bhowmik, Anirban School of Computer Engineering Vellore Institute of Technology Chennai India School of Electronics Engineering Vellore Institute of Technology Chennai India Tripura Institute of Technology Dept. of Electronics and Communication Engineering Agartala India

ISBN: (纸本)9798350390759

Hand gestures are the most common way of interaction among humans in the physical world. Gestures are used in everyday life to interact with objects around us. Hand gesture is becoming the most comfortable alternative technique to replace the conventional mouse. Herein, we report the development of a dynamic hand gesture user interface that tracks and recognizes in real time based on color segmentation and recognition. Operation such as file dragging, right and left clicks and scrolling up and down has been studied. The colors are calibrated in order to make sure that no other similar shades of color from the background interfere during the process. © 2024 IEEE.

关键词： Gesture recognition

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Hybrid Model for Image Forgery Detection In Smart Healthcare

Hybrid Model for Image Forgery Detection In Smart Healthcare

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2023 International Conference on computer, Electronics and Electrical engineering and their Applications, IC2E3 2023

作者： Srilakshmi, V. Purushotham, D. Abhinav, Chinta Godalla, Nikhil Varshith, S.V. Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350338003

Smart Healthcare Systems (SHS) are gradually replacing traditional healthcare systems that involve human intervention. This is due to the advancement of IOT devices and also the introduction of edge computing. SHS provides security, flexibility, and efficiency. A key feature of SHS is to transport images from one place to another in real-time. Due to technological advancements, these images can tamper which is image forgery, this threats security in SHS. To tackle this problem, Image Forgery Detection using Support Vector Machines (SVM) and Extreme Learning Machines (ELM) is proposed in this model. We combine the scores of both SVM and ELM using Bayesian Sum Rule (BSR). The model is utilized to verify if the forgery is done or not. This model can be inbuilt into the SHS. Forgery Detection enhances security and reduces the threat of systems being failed, as images play a key role in the treatment procedure. © 2023 IEEE.

关键词： Support vector machines

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Efficiency Improvement Mechanism Analysis of Sidewall Passivation GaN based Micro-LEDs by Atomic Layer Deposition

Efficiency Improvement Mechanism Analysis of Sidewall Passiv...

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International Symposium, Seminar, and Exhibition, Display Week 2024

作者： Zhanghu, Mengyuan Liu, Yibo Liu, Zhaojun Dept. of Electric and Electronic Engineering Southern University of Science and Technology Shenzhen China Dept. of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

Sidewall passivation using atomic layer deposition (ALD) can efficiently improve external quantum efficiency (EQE). Such treatment increases EQE, a combination of internal quantum efficiency (IQE) and light extraction efficiency (LEE), primarily by curtailing surface recombination according to the ABC model. Determined by the ratio of radiative recombination rate to total recombination rate, the IQE of an LED holds a significant correlation with the diode's ideality factor in the Shockley model. In this paper, we analysis the mechanism of ALD sidewall passivation enhancing device performance in detail from the aspects of electrical performance improvement and optical performance improvement. © 2024, John Wiley and Sons Inc. All rights reserved.

关键词： Gallium nitride

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