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Distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE International Conference on

作者： Narasimhayya B E Ravikumar Lanke Department of Computer Science and Engineering Faculty of Engineering and Technology Jain (Deemed-to-be University) Bangalore India

The development of short-range communication protocols has been essential for efficient device discovery. Short-range communication allows two devices to communicate over short distances, typically up to 10 meters, using low-power radio frequencies. This type of communication is used extensively in applications such as Wi-Fi, Bluetooth, and Zigbee. Short-range communication protocols allow devices to discover each other without the need for a central server or intermediary. This is important for applications such as home automation, where it is necessary for various devices to be able to find each other and communicate. In order for efficient device discovery, short-range communication protocols must be reliable and secure. Reliable protocols are necessary to ensure that devices can find each other, while secure protocols are necessary to ensure that only authorized devices can access one another. Protocols such as Bluetooth, Wi-Fi, and Zigbee have been designed to be reliable and secure. The development of short-range communication protocols can be improved by using predictive algorithms. Predictive algorithms allow devices to automatically detect and respond to changes in the network environment. This enables devices to more efficiently discover each other and establish connections.

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Blending Spline Surfaces Over Polygon Mesh and Their Application to Isogeometric Analysis

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SSRN 2023年

作者： Kravetc, Tatiana Department of Computer Science and Computational Engineering Faculty of Engineering Science and Technology UiT The Arctic University of Norway Norway

Finite elements are allowed to be of a shape suitable for the specific problem. This choice defines thereafter the accuracy of the approximated solution. Moreover, flexible element shapes allow for the construction of an arbitrary domain topology. Polygon meshes are a common representation of the domain that cover any choice of the finite element *** an alternative tool for modeling and analysis, blending spline surfaces support representation on polygon grids. The blending splines have a hierarchical structure, which is obtained by generating local surfaces that cover each node support and then blended with a special type of basis functions. This type of splines in their tensor product form is suitable for application to isogeometric analysis problems. A more general representation constructed on polygonal elements can be used on a wider range of domain topology in comparison with tensor product *** this paper we introduce a novel approach to constructing curvilinear polygon meshes in the blending spline representation in application to the isogeometric analysis context. © 2023, The Authors. All rights reserved.

关键词： Blending

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Review of the issues and a thorough investigation of biometric authentication systems 1

Review of the issues and a thorough investigation of biometr...

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1st IEEE International Interdisciplinary Humanitarian Conference for Sustainability, IIHC 2022

作者： Johri, Prashant Arora, Ms. Sonia Galgotias University Department of Computer Applications Uttar Pradesh Greater Noida India Institute of Engineering and Technology Department of Computer Science and Business System Noida Uttar Pradesh Greater Noida India

ISBN: (纸本)9781665456876

A computer system's user authentication process is based on security mechanisms including passwords, keys, ID cards, and pins, among others. Nonetheless, as innovation propels day to day, there is likewise an expansion in the misappropriation and robbery of these safety efforts. By applying biometrics innovation, an individual can be verified in light of 'what his identity is' as opposed to a component vector got from physiological or potentially social qualities of a person, which is the way biometric security systems became. All the arising biometric innovations and the hardships in every innovation have been completely depicted in this paper to help tenderfoots in picking their exploration subject or a particular biometric innovation. Also, future improvements in biometric innovation are thought of. The main factor in determining whether a claim made by the real entity is true is authentication. Biometrics is one approach to increase authentication's sturdiness among other methods. Since the last decade, biometric technology has been widely used and recognised worldwide to verify a person's identity. Additionally, the technology employed solves the drawbacks of the conventional authentication procedure, such as knowledge-based problems with password and token authentication of an individual. The proposed methodology implemented Convolution neural network with brain organization which will be utilized for the preparation of picture tests and a pre prepared organization of brain can be used in CNN which could eliminate handling time. In results the training accuracy is 6.3 and validation accuracy is 5.3. © 2022 IEEE.

关键词： Machine learning

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An Innovation Development of Decentralized Prove Piercing Data Recuperation Using Improved Red in Mobile Grid Computing

An Innovation Development of Decentralized Prove Piercing Da...

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Distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE International Conference on

作者： Karthikeyan S Merin Thomas Department of Computer Science and Engineering Faculty of Engineering and Technology Jain (Deemed-to-be University) Bangalore India

The recent advancements in mobile computing have opened up the possibilities of decentralized data recovery in mobile grid computing. With the help of improved Red (Recovery of Erased Data) technique, data recovery can be done in a decentralized manner. This method is a combination of distributed computing, data replication, and data recovery algorithms which improves the data recovery process. The improved Red technique uses distributed computing to replicate the data and store it in multiple nodes in the grid. This helps to ensure that the data is distributed and available in multiple nodes for recovery. Data recovery is done by the Red algorithm which traverses the grid and identifies the nodes which have the data and then recovers it. The algorithm uses a technique called "greedy search" to identify the nodes which have the data. This helps to reduce the time and cost associated with the recovery process. The improved Red technique also makes use of data replication which helps to improve the data recovery process. The data is replicated and stored in multiple nodes which helps to improve the speed of data recovery. The replication process helps to ensure that the data is always available and can be recovered quickly. The improved Red technique also makes use of distributed computing to improve the scalability of the data recovery process. The distributed computing helps to ensure that the data recovery process can be done efficiently and quickly. The data recovery process can also be done on a large scale which helps to improve the speed of data recovery.

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Comparative Analysis of Edge Detection Algorithms with Particle Swarm Optimization for Enhanced Image Processing

Comparative Analysis of Edge Detection Algorithms with Parti...

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International Conference on ICT For Smart Society (ICISS)

作者： Sri Rahayu Pulung Nurtantio Andono Pujiono Ahmad Zainul Fanani Department of Informatics Engineering Faculty of Computer Science Dian Nuswantoro University Semarang Indonesia Computer Science Department Institut Teknologi Garut Garut Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

Edge detection plays an important role in various fields by identifying object boundaries and supporting advanced image analysis, such as segmentation, recognition, and tracking. Many edge detection algorithms, such as Canny, Laplacian, and Prewitt, have been developed to address issues such as noise sensitivity, computational complexity, and detection accuracy. This research compares the optimized algorithms using Particle Swarm Optimization (PSO). The results of this study show that the optimized algorithm provides better performance based on the evaluation conducted using entropy, Mean Squared Error (MSE), and computation time, and has practical implications. This research also determines the most effective edge detection technique in various image processing scenarios, thus contributing to the optimization of image analysis workflows in real-world contexts.

关键词： Accuracy Laplace equations Image analysis Image edge detection Noise Prediction algorithms Entropy Computational efficiency Particle swarm optimization Optimization

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Nitinol Based heat Engine for Solar Energy Harvesting

Nitinol Based heat Engine for Solar Energy Harvesting

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International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)

作者： Shivam Nitin Satpute Sameer Ajay Sake Pavitra Praveen Sardesai Parth Sandip Sawant Apurv Vaibhav Sarode Varad Gangadharrao Sadegaonkar Marek Iwaniec Ramesh Narina Anita Dombale Nishant S. Kulkarni Mechanical Engineering Department Vishwakarma Institute of Technology Pune India Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science & Technology Krakow Poland

ISBN: (数字)9798350378627

ISBN: (纸本)9798350378634

The most abundantly available renewable energy source on the earth is solar energy. Conventionally, this energy is converted into electric energy with the help of photovoltaic cells. The efficiency of this commercially available technology is around 5-25%. This article deals with the investigation of an innovative energy harvesting system that uses a Shape Memory Alloy (SMA) to utilize solar heat for generating electric power. SMA shows significant deflection when heated and this characteristic is used to develop a SMA based heat engine. This work proposes a heat engine where a SMA wire is used to convert solar radiation to perform mechanical work. Further, the mechanical work is used to drive a rotary electric generator to produce electric energy. The SMA used for this purpose is Nitinol wire, which absorbs heat from the solar radiation and transforms the same initially to mechanical motion, which later is used to produce electric power. Initially, the SMA element is curved in shape, and it shows a significant deflection when it receives the heat from solar radiation. This deflection of the SMA element is used to operate a rotary electric generator to produce electric energy. The theoretical calculations for balance of the energy flow from incident solar radiations to output electric energy is discussed. The developed prototype shows around 4.5% efficiency with an average power of 2.4 mW.

关键词： Heat engines Solar energy Electric generators Voltage Transforms Power systems Wire

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Semantic Search Engine, Thai Traditional Medicine Knowledge Graph Application

Semantic Search Engine, Thai Traditional Medicine Knowledge ...

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13th International Electrical engineering Congress, iEECON 2025

作者： Sakulpakdee, Natthinan Narischat, Nattavee Srisomboon, Kanabadee Lee, Wilaiporn Pipanmekaporn, Luepol Prayote, Akara King Mongkut's University of Technology North Bangkok Faculty of Apply Science Department of Computer and Information Science Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9798331543952

In this paper, a semantic information retrieval framework is presented to improve the precision of search results by concentrating on the context of concepts is presented. Instead of the keyword matching technique, the graph theory is used for leveraging the relationships and meanings of search terms. Information is represented as a knowledge graph for semantic searching performed by the inference engine and results are passed to the NLP technique for interpreting entity, relationship and property to their relevancy query. In the current system, we focused on healthcare system to helping the foundation recommendations of Thai Traditional Medicine. Once Thai Traditional Medicine contains a numerous of words which have the same meaning, the traditional keyword based cannot retrieve all relevant document. In our proposed semantic architecture, the query is performed an context-based understanding for retrieving all relevant document, therefore, it can retrieve the same number of documents for the queries which have the same meaning. © 2025 IEEE.

关键词： Online searching

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Deep Learning Approaches for Precision Agriculture: Weed and Cotton Crop Classification Using YOLO and Faster RCNN

Deep Learning Approaches for Precision Agriculture: Weed and...

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IT and Industrial Technologies (ICIT), International Conference on

作者： Asad Majeed Fatima Faridoon Muhammad Irfan Ahmar Rashid Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and Technology Topi Pakistan Department of Electrical Engineering Sukkur IBA University Sukkur Pakistan

ISBN: (数字)9798331504465

ISBN: (纸本)9798331504472

Weed infestation in cotton fields significantly challenges agricultural productivity by competing for essential nutrients and water resources. This study presents a comprehensive comparative analysis of two deep learning-based object detection models - YOLO and Faster R-CNN - for automated weed detection in cotton fields. We developed and annotated a custom dataset comprising field images captured under various environmental conditions, labelled in both COCO and YOLO formats using Label Studio. Performance evaluation revealed the YOLO model’s superior capabilities, achieving a mAP50 of 0.775, precision scores of 0.859 for cotton and 0.656 for weed detection, and recall rates of 0.849 and 0.543 for cotton and weed respectively on the test dataset. In comparison, Faster R-CNN showed lower performance with AP scores of 0.708 for cotton and 0.269 for weed detection, particularly struggling with objects of varying sizes. The YOLO model maintained consistent performance across both validation and test datasets, with validation metrics showing mAP50 of 0.982 and mAP50-95 of 0.829. These results establish YOLO’s effectiveness as a reliable tool for automated weed detection in cotton fields, offering a practical solution for precision agriculture applications. The developed model demonstrates the potential for integration into automated crop management systems, contributing to more efficient and targeted weed control strategies.

关键词： YOLO Precision agriculture Deep learning Productivity Accuracy Crops Data models Cotton Reliability Water resources

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Defect Detection of Agricultural Commodities using Image Processing and Artificial Neural Networks

Defect Detection of Agricultural Commodities using Image Pro...

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2022 International Seminar on Application for Technology of Information and Communication, iSemantic 2022

作者： Suprijono, Herwin Kartikadarma, Etika Yusianto, Rindra Marimin, Marimin Dian Nuswantoro University Faculty of Engineering Department of Electrical Engineering Semarang53192 Indonesia Dian Nuswantoro University Study Program of Information Technology Faculty of Computer Science Semarang53192 Indonesia Dian Nuswantoro University Faculty of Engineering Department of Industrial Engineering Semarang53192 Indonesia Faculty of Agricultural Engineering and Technology Department of Agro-Industrial Technology West Java Bogor16002 Indonesia

ISBN: (数字)9781665488396

ISBN: (纸本)9781665488396

Production losses of agricultural commodities on agricultural land due to product defects depend on the level of pest and disease attacks. Defects cause the product not to be harvested or rejected by the market. Data from the Ministry of Agriculture of the Republic of Indonesia in 2021 shows the percentage of defective products for this commodity is 5%. This study aims to detect defects in agricultural products using image processing and artificial neural networks. We used the screening threshold method with potato research samples from Dieng, Indonesia. The study results for spot defects showed that from 100 training data, there were five incorrect identification data, so the accuracy of the training process was 95%. At the same time, the hole defect accuracy is better, which is 97%. It shows that defects in agricultural commodities can be detected using this method. For further research, the development of agricultural product sorting can combine sorting techniques with this method. © 2022 IEEE.

关键词： Defects

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Study of Photonic Platforms for On-Chip Refractive Index Sensing

Study of Photonic Platforms for On-Chip Refractive Index Sen...

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Photonics North

作者： Raghi El Shamy Mohamed A. Swillam Xun Li Department of Electrical and Computer Engineering Faculty of Engineering McMaster University Hamilton Canada Department of Physics School of Science and Engineering The American University in Cairo New Cairo Egypt

ISBN: (数字)9798350366365

ISBN: (纸本)9798350366372

Here we present a rigorous study for the different integrated photonic platforms that can be used for on-chip refractive index (RI) sensing. The study includes the widespread silicon photonics platform, the silicon nitride platform and the silica platform. We compare these three platforms according to five parameters that determine the performance and reliability of the RI sensor. Finally, we conclude with the optimum platform for on-chip RI sensing according to the available technology and the aimed application.

关键词： Refractive index Silicon nitride Silicon photonics system-on-chip Sensors Reliability

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