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31st IEEE International Conference on Electronics, Electrical engineering and Computing, INTERCON 2024

作者： Chaparro-Cruz, Israel N. Santana-Carbajal, Oliver I. Osco-Mamani, Erbert F. Universidad Nacional Jorge Basadre Grohmann Department of Computer Science and Systems Engineering Tacna Peru

ISBN: (纸本)9798350378344

Peru is South America's largest producer and ex-porter of oregano (Origanum vulgare L.), with the Tacna region being the most significant contributor, cultivating 2,499 hectares and producing 11,946 tons, accounting for 65% of the national production. To mitigate the impact of oregano diseases, which lead to substantial crop losses and negatively affect the economy, it is crucial to develop and upgrade technologies for disease management. Accurate classification of oregano diseases can prevent quality deterioration and yield reductions. However, the availability of data and the use of advanced technologies in oregano cultivation are still in their early stages. This study addresses these shortcomings by developing and publishing a novel public dataset for the classification of the most common oregano diseases-Alternaria, Powdery Mildew (Oidium), and Mosaic-using crops from Susapaya - Tarata in Tacna, Peru. To classify oregano diseases, we conducted a comprehensive comparative study, applying Transfer Learning and Fine-Tuning techniques to evaluate the performance of VGG16, MobileNet, MobileNetV2, and NasNetLarge architectures with modifications in the classifier. The experiments revealed that: (i) Fine-Tuning improved validation set accuracy by 4.47% compared to Transfer Learning, (ii) the VGG16 architecture achieved the highest accuracy at 0.993921, (iii) MobileNet and MobileNetV2 models performed similarly, (iv) the NASNetLarge model showed poor performance when only Transfer Learning was applied, and (v) there was a strong significant relationship (R2= 0.84) between the number of parameters and size (in MB) with the performance of the architectures on our dataset. We ensure the reproducibility of the results by making the novel dataset and the best model publicly available on GitHub. © 2024 IEEE.

关键词： Convolutional neural networks

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Monitoring energy losses of a residential building through thermographic assessments 17

Monitoring energy losses of a residential building through t...

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17th International Conference on Development and Application systems, DAS 2024

作者： Eugen, Iavorschi Laurențiu, Milici Dan Faculty of Electrical Engineering and Computer Science Department of Electrical Engineering "Stefan cel Mare" University of Suceava Suceava Romania

ISBN: (纸本)9798350349290

One of the significant opportunities for reducing energy waste and carbon emissions is the renovation, modernization, and rehabilitation of existing buildings. Replacing the windows of existing residential buildings with new energy-efficient ones is an easy way to upgrade an existing home into a nearly zero-energy building, NZEB (nearly zero-energy building). There is a wide variety of methods to discover the thermal weak points of a building, and the continuous innovation of construction materials provides solutions to maximize energy savings and minimize heat transfer to the exterior. This document presents a methodology for visualizing and recording the temperature distribution on the investigated surface of the building envelope to identify and locate vulnerable points where heat losses to the exterior are substantial. The objective was to highlight the need for upgrading the insulation system and replacing the existing windows of the analyzed building based on a multi-objective approach to maximize the building's energy performance and increase thermal comfort indoors. Using a Fluke Ti300+ Thermal Camera, energy losses were visualized through thermographic assessments, which could provide an adequate picture for accurately assessing the building's condition before renovation, to evaluate the need for partial renovation. For the case study, a residential building with one floor and mansard roof located in a region with hot summers and cold winters in Romania was chosen. The results showed that there are several options for significantly reducing the building's energy consumption. Thus, multiple energy efficiency solutions were proposed for the building to reduce heat losses. ©2024 IEEE.

关键词： Heat transfer

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Personal mark density-based high-performance Optical Mark Recognition (OMR) system using K-means clustering algorithm

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Multimedia Tools and Applications 2024年 1-33页

作者： Sancar, Yasin Yavuz, Ugur Karabey Aksakalli, Isil Information Processing Department Open Education Faculty Ataturk University Erzurum25040 Turkey Department of Management Information Systems Ataturk University Erzurum25040 Turkey Department of Computer Engineering Engineering and Architecture Faculty Erzurum Technical University Erzurum25040 Turkey

To evaluate multiple choice question tests, optical forms are commonly used for large-scale exams and these forms are read by the OMR (Optical Mark Recognition) scanners. However, OMR scanners often misinterpret marks that have not been fully erased, which can lead to incorrect readings. To overcome that shortcoming and reduce the time and labor lost in the assessment process, we developed a novel system based on the density of each individual’s markings, providing a more personalized and accurate approach. Instead of reading according to a specific optical form template, a dynamic and flexible structure was generated where users can create own templates and obtain the model that reads according to that template. We also optimized certain aspects of the system for efficiency, such as image memory transfer and QR code reading. These optimizations significantly increase the performance of the OMR scanners. One of the key issues addressed is inaccurate reading of OMR scanners when a student doesn’t fully erase their markings or when markings are faint. After the scanning process, the proposed approach uses a K-means clustering algorithm to classify different density markings. This technique identifies each student’s personal marking density, enabling a more accurate interpretation of their responses. According to the experimental results, we performed 97.7% improvement compared to the misread optics scanned by the conventional OMR devices. In tests performed on 265.816 optical forms, we obtained an accuracy rate of 99.98% and a reading time of 0.12 seconds per optical form. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： K-means clustering

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Intelligent Aquila Optimization Algorithm-Based Node Localization Scheme for Wireless Sensor Networks

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computers, Materials & Continua 2023年第1期74卷 141-152页

作者： Nidhi Agarwal M.Gokilavani S.Nagarajan S.Saranya Hadeel Alsolai Sami Dhahbi Amira Sayed Abdelaziz Department of Information Technology KIET Group of InstitutionsDelhi201206India Department of Computer Science and Engineering Indira Gandhi Delhi Technical University for WomenNew DelhiDelhi110006India Department of Computer Science and Engineering KL UniversityVaddeswaramAndhra Pradesh522502India Department of Electronics&Communication Engineering Saveetha Engineering CollegeChennai602105India Department of Computer Science and Engineering K.Ramakrishnan College of EngineeringTiruchirapalli621112India Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial *** nodes in WSN are placed arbitrarily in the target field,node localization(NL)becomes essential where the positioning of the nodes can be determined by the aid of anchor *** goal of any NL scheme is to improve the localization accuracy and reduce the localization error *** this motivation,this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme(IAOAB-NLS)for *** presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the *** addition,the IAOAB-NLS model is stimulated by the behaviour of *** IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the *** guaranteeing the proficient NL process of the IAOAB-NLS model,widespread experimentation takes place to assure the betterment of the IAOAB-NLS *** resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.

关键词： Aquila optimizer node localization WSN intelligent models unknown nodes anchor nodes

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Arabic Topic Classification Corpus of the Nakba Short Stories 1

Arabic Topic Classification Corpus of the Nakba Short Storie...

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1st International Workshop on Nakba Narratives as Language Resources, Nakba-NLP 2025

作者： Hamed, Osama Zaidkilani, Nadeem Department of Computer Systems Engineering Palestine Technical University-Kadoorie Palestine Department of Computer Engineering and Security Mathematics University Rovira i Virgili Spain Department of Engineering and Technology Al-Zaytona University of Science and Technology Palestine

ISBN: (纸本)9798891762169

In this paper, we enrich Arabic Natural Language Processing (NLP) resources by introducing the "Nakba Topic Classification Corpus (NTCC)," a novel annotated Arabic corpus derived from narratives about the Nakba. The NTCC comprises approximately 470 sentences extracted from eight short stories and captures the thematic depth of the Nakba narratives, providing insights into both historical and personal dimensions. The corpus was annotated in a two-step process. One third of the dataset was manually annotated, achieving an IAA of 87% (later resolved to 100%), while the rest was annotated using a rule-based system based on thematic patterns. This approach ensures consistency and reproducibility, enhancing the corpus’s reliability for NLP research. The NTCC contributes to the preservation of the Palestinian cultural heritage while addressing key challenges in Arabic NLP, such as data scarcity and linguistic complexity. By like topic modeling and classification tasks, the NTCC offers a valuable resource for advancing Arabic NLP research and fostering a deeper understanding of the Nakba narratives. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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CART - Web-Based Institutional Placement Management System Using NLP 10

CART - Web-Based Institutional Placement Management System U...

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10th International Conference on Advanced Computing and Communication systems, ICACCS 2024

作者： Priyanka, G. Amritha, P. Gokul Sundar, U. Sanjai, M.B. Vasanth, R. Sri Eshwar College of Engineering and Technology Department of Computer Science and Business Systems Coimbatore India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384369

The 'CART (Career at Right Time)', a pupil/ company information system, is a web- grounded programmed. The design is grounded on the' Placement Cell' that's presently employed in the University for storing and reacquiring information from scholars and companies who are registered in the placement cell. The Placement Cell maintains a large pupil database in which all pupil information, including particular records and academic performance in terms of marks and grades, is stored, as well as company information, similar as the company's capsule, sphere they work in, job descriptions, reclamation process, and so on. This data is recaptured by the software and shown when demanded by the users. © 2024 IEEE.

关键词： Electric grounding

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Xtractor: A Two-Step Tweet Extractor for Sentiment Analysis 5

Xtractor: A Two-Step Tweet Extractor for Sentiment Analysis

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5th International Conference on Advancements in Computational sciences, ICACS 2024

作者： Alvi, Muhammad Bux Mahoto, Naeem Ahmed Unar, Mukhtiar Ali Shaikh, Muhammad Akram The Islamia University of Bahawalpur Computer Systems Engineering Bahawalpur Pakistan Mehran Uet Software Engineering Department Jamshoro Pakistan Mehran Uet Computer Systems Engineering Department Jamshoro Pakistan Pastic Pakistan Science Foundation Islamabad Pakistan

ISBN: (纸本)9798350394764

Twitter (now X) has been gaining popularity with each passing day since its inception in 2006. People have been using Twitter as an instant repository to collect data and gain insight into folks' minds on trending issues. Although Twitter allows access to its data through streaming and rest APIs, extracting the required data is difficult. The data (tweet) returned by Twitter is in json format, having at least 26 fields. Each field is bundled in the dictionary form data structure. tweet metadata such as tweet 'likes' and 'retweets' increase the volume and complexity of a tweet, making data extraction in a cleaner format more difficult. This work aims to develop an effective two-step tweet extractor (Xtractor: an online-offline keyword-based Twitter data extractor). In the first step, Xtractor collects publicly available topical tweets using keywords, hashtags, or their list on the fly, parses all the tweet fields, and filters them to retain potential field contents without additional payload. The second step of the Xtractor evicts partially matching tweets using the regular expression method to acquire the targeted domain-specific tweets. Using the proposed two-step Twitter data extraction method, datasets concerning the people of Pakistan have been collected, which can be leveraged to get insight for decision-making, specially in the context of sentiment analysis. We found this method efficient, capacitive, and productive. © 2024 IEEE.

关键词： Python

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Advanced dairy cow monitoring: enhanced detection with precision 3D tracking

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Multimedia Tools and Applications 2025年第18期84卷 19117-19146页

作者： Wang, Ranran Li, Yingxiu Yue, Peng Yuan, Chunhong Tian, Fuyang Lu, Xin College of Mechanical and Electronic Engineering Shandong Agricultural University Shandong Tai’an271018 China Department of Computer Science Faculty of Engineering University of Sheffield SheffieldS1 4DP United Kingdom Faculty of Agriculture Iwate University Iwate Morioka020-8550 Japan Faculty of Science and Engineering Iwate University Iwate Morioka020-8550 Japan

Ensuring the welfare of dairy cows requires precise monitoring of their daily exercise to evaluate their physical health. This necessitates innovative methods beyond traditional motion sensors. We present a novel method that integrates an enhanced YOLOv5s object detection model with the DeepSORT multi-object tracking algorithm to meticulously track dairy cow movements, providing holistic information about their health. Our research started with the establishment of a dedicated dataset tailored for cow detection. We then segmented the detection scope to focus on specific regions of interest. Within the modified YOLOv5s model, we replaced the standard CSPDarknet53 backbone with DenseNet to achieve deep separable convolution and feature reorganization modules, leading to reduced parameters, augmented feature expression, and better information flow. In particular, the SPD-Conv module was incorporated to retain intricate details, essential for detecting smaller and low-resolution targets. The transition from Generalized Intersection over Union (GIoU) Loss to Complete Intersection over Union (CIoU) loss improved detection accuracy and sped up model convergence. Our clustering approach, based on the elbow rule, optimized K-means clustering, enhancing speed and precision. For multi-object tracking, the DeepSORT model was tailored to cater to varying cow sizes, and we chose an algorithm to associate appearance information. We converted pixel data into real-world distances, providing exact 3D cow movement metrics. Experimental validation confirmed the efficacy of our approach. Our enhanced model surpassed the original YOLOv5s in performance by 11.1% for accuracy (97.4%), 9.6% for recall (97.8%), and 11.0% for average accuracy (98.2%). The comprehensive accuracy stood at 92.1% for our model. In conclusion, our innovative methodology offers a non-invasive means to monitor dairy cow exercise, paving the way for advanced health assessment techniques in the dairy sector. © The Aut

关键词： K-means clustering

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Skill Mastery Solutions: Your Path to Excellence 10

Skill Mastery Solutions: Your Path to Excellence

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10th International Conference on Advanced Computing and Communication systems, ICACCS 2024

作者： Saranya, E. Ajay, K. Hardika, S. Jayasudha, C. Kishore, R.E. Sri Eshwar College of Engineering and Technology Department of Computer Science and Business Systems Coimbatore India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384369

'Skillstorm' is an innovative and competitive website that harnesses the power of cutting-edge technologies to create a safe and engaging online environment. Developed primarily using Python and Flask, Skillstorm integrates machine learning algorithms to combat cyberbullying, ensuring a positive user experience. This project leverages HashMaps for efficient data management and employs a dynamic front-end interface built with HTML, CSS, and JavaScript. The backend of Skillstorm is powered by Python and Flask, providing a robust and scalable foundation for handling user data, interactions, and website functionality. Skillstorm utilizes machine learning techniques to automatically detect and mitigate instances of cyberbullying and harassment. This proactive approach ensures a safe and welcoming environment for all users. HashMaps are employed for efficient data storage and retrieval, optimizing the performance of the website and enhancing user experience. 'Skillstorm' represents a forward-thinking and comprehensive project that combines Python, Flask, machine learning, HashMaps, HTML, CSS, and JavaScript to create a competitive website that prioritizes user safety and positive interactions in an increasingly digital world. Powered by cutting-edge Python frameworks, we have created a dynamic and immersive experience that will ignite your passion, inspire excellence, and propel you to new heights of achievement. At SkillStorm, we believe that true talent knows no borders. © 2024 IEEE.

关键词： Python

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Assessing the Effects of Blackhole Attacks on MANET Reliability and Security

Assessing the Effects of Blackhole Attacks on MANET Reliabil...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Fadhil, Saif Aamer Najim, Ali Hamza Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Baghdad10011 Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

Mobile Ad Hoc Networks (MANETs) are characterized by some important attributes, including infrastructure, mobile, and dynamic nature, which makes them have vast applications in different areas of computer networks. The black hole attack falls among the strongly criticized security threats within the framework of the MANETs. This deceptive behavior captures data packets from a source destined for the malicious node and then declines them when they are received. This paper comprehensively reviews prior studies done to analyze and mitigate black hole attacks in MANETs. Besides this, we will conduct a comparative analysis of the research above projects. The present paper extends prior work by actually performing the black hole assault simulations in a MANETs environment. This is done with the aid of the NS2 simulator and the Ad Hoc On-Demands Distance Vector (AODV) routing protocol. In this study, the black hole attack is analyzed and the consequences of the attack are assessed in terms of the system performance and security. We analyze crucial parameters like end-to-end latency, PDR, packet drop, and throughput to evaluate the consequences of this assault. From our results derived from the analysis of our simulations, we aim to present substantial points to do with the impacts of blackhole attacks on MANETs. In this way, our goal is to participate in the perpetually evolving efforts aimed at enhancing the security and reliability of such dynamic networks. © 2024 IEEE.

关键词： Mobile ad hoc networks

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