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Fabric Defects Detection Using YOLOv8 4th

Fabric Defects Detection Using YOLOv8

引用

4th International Conference on Innovations in Computational Intelligence and computer Vision, ICICV 2024

作者： Kapil, Bhavesh Dutta, Kamlesh Computer Science and Engineering Department National Institute of Technology Hamirpur India

ISBN: (纸本)9789819769919

Fabric defect detection poses a significant challenge in the textile industry due to the intricate shapes and diverse range of fabric defects. Numerous approaches have been suggested to address this issue;however, their efficacy in terms of both detection speed and accuracy has been notably limited. This paper introduces an approach for detecting fabric defects using the YOLOv8 model. The methodology involves using the Tinachi dataset, labeling the dataset with LabelImg, applying data augmentation to the dataset, and iteratively training the YOLOv8 network model. The model achieves a mean Average Precision (mAP) of 78.5%, box_loss of 1.6209, a cls_loss of 1.0495, and a dfl_loss of 1.2898. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Textile industry

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Optimized Routing in FANET Using Marine Predators Algorithm 4

Optimized Routing in FANET Using Marine Predators Algorithm

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Minocha, Sachin Singh, Birmohan Kaur, Manpreet Namasudra, Suyel Lorenz, Pascal School of Computer Science Engineering and Technology Bennett University Greater Noida India Sant Longowal Institute of Engineering and Technology Department of Computer Science and Engineering Longowal India Sant Longowal Institute of Engineering and Technology Department of Electrical and Instrumentation Engineering Longowal India National Institute of Technology Agartala Department of Computer Science and Engineering Tripura India University of Haute Alsace Colmar France

ISBN: (纸本)9798350395914

Flying Adhoc Network (FANET) has gained attention due to regressive real-time use of Unmanned Aerial Vehicles (UAVs). Optimized routing in FANETs is more challenging than mobile ad-hoc networks and vehicular ad-hoc networks due to restricted bandwidth and higher mobility of UAVs. Apart from the Mobile Adhoc Network (MANET) routing protocols, nature-inspired techniques-based optimized routing has shown promising routing performance in FANET. This paper proposes a Marine Predators Algorithm (MPA) based optimized routing protocol for FANET. The proposed routing technique selects a better routing path because of the high exploration and exploitation capabilities of MPA. The fitness function based on link stability and energy efficiency helps to select a routing path with better Quality of Service (QoS). The performance of the proposed technique has been analyzed based on packet arrival ratio, end-to-end delay, and throughput, and it is compared to five state-of-the-art techniques by varying the speed and number of the nodes. The simulation results depict that the proposed work is more efficient than the existing state-of-the-art schemes. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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A Systematic Study for Understanding the Security Risks in 5G Core Network 16

A Systematic Study for Understanding the Security Risks in 5...

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16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

作者： Dixit, Unnati Vittal, Shwetha Antony Franklin, A. Indian Institute of Technology Hyderabad Department of Computer Science and Engineering India

ISBN: (纸本)9798350383119

The widespread adoption of 5G networks has revolutionized communication, providing great connectivity and services across various verticals. Specifically, on the 5G Core (5GC) this has been made possible by leveraging network slicing and Network Function Virtualization (NFV) where multiple Network Functions (NFs) are involved to serve different user requests on the control plane and a variety of service traffic on the data plane. However, as 5G networks embrace zero trust and multi-tenant architectures, this rapid technological advancement has also exposed the 5GC to various security risks such as Distributed Denial of Service (DDoS), Man in The Middle (MITM), cross-slice disruptions, and side-channel attacks. In this regard, this paper presents a comprehensive approach to enhance the security of 5GC through a systematic study of dependency graphs, Betweenness Centrality (BC), and attack graphs. Potential attack scenarios are carefully analyzed by modeling the 3GPP-defined 5GC, performing vulnerability assessments, building attack graphs, analyzing them, and presenting the key inferences from the study. © 2024 IEEE.

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Quality-Driven Web Service Selection: Machine Learning Based Approach 11th

Quality-Driven Web Service Selection: Machine Learning Based...

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11th International Symposium on Applied Computing for Software and Smart Systems, ACSS 2024

作者： Kumar, Dewashish Sarkar, Anirban Department of Computer Science and Engineering National Institute of Technology Durgapur Durgapur India

ISBN: (纸本)9789819797615

The task of choosing a suitable web service has become increasingly difficult in today’s landscape due to the growing number of services offering similar functionalities. This paper addresses the critical need for efficient web service selection based on Quality of Service parameters. A minimal set of discrete QoS characteristics were carefully chosen as inputs for several machine learning models targeted at finding and suggesting suitable web services. The performance of these models is systematically evaluated and compared. The machine learning techniques used for this work include a Support Vector Machine, Decision Tree, and Random Forest. Among these, the results show that the proposed Random Forest model consistently outperforms other techniques in terms of accuracy and effectiveness. This study contributes to the advancement of web service selection methodologies by providing insights into the comparative performance of various machine learning approaches, ultimately offering a valuable guide for decision-makers in navigating the intricate landscape of web service options. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Usability Evaluation of Online Food Delivery Applications in Bangladesh: A Comparative Study

Usability Evaluation of Online Food Delivery Applications in...

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2024 IEEE International Women in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2024

作者： Islam Arif, Md. Ariful Kabir, Shahriar Islam, Zohirul Hussain Khan, Md Faruk Islam, Iyolita Islam, Muhammad Nazrul Military Institute of Science and Technology Department of Computer Science and Engineering Dhaka Bangladesh Bangladesh University of Professionals Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798331535476

The online food order and delivery service is becoming a very popular web-based application in Bangladesh. These days, a growing number of individuals are interested in ordering a variety of foods online. In addition, people are looking for quality food that they can purchase whenever and wherever they want. Online food delivery services are required to be intuitive, user-friendly, and accessible to increase their acceptability in Bangladesh. Therefore, the objective of this study is to explore and assess the existing online food delivery apps in Bangladesh and identify the best application from a usability perspective. To attain these objectives, four online food delivery apps (Food Panda, Hungrynaki, Pathao Food, and efood) were evaluated through Heuristic Evaluation, Cognitive Walkthrough, and System Usability Scale (SUS). The study's findings showed that each app has a number of usability issues requiring to be resolved in order to improve acceptance. The results indicated that from heuristic evaluation, Food Panda had the most number of problems and Hungrynaki had the least number of usability issues;from the cognitive walkthrough perspective, Food Panda and eFood was the mostly usable application;and from SUS evaluation score, Food Panda achieved best score from the users. Overall, Food Panda is the best application from the usability perspective. © 2024 IEEE.

关键词： Food ingredients

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Advancing Data Sovereignty in Distributed Environments: An In-Depth Exploration of Data Localization Challenges

Advancing Data Sovereignty in Distributed Environments: An I...

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2024 International Conference on computer, Electronics, Electrical engineering and their Applications, IC2E3 2024

作者： Kancharla, Jaganmohan Reddy Madhu Kumar, S.D. National Institute of Technology Department of Computer Science & Engineering Calicut India

ISBN: (纸本)9798350388534

Data localization in distributed computing has gotten a lot of attention because it has the potential to improve data sovereignty, make sure regulations are followed, and make data easier to access. However, this practice also brings forth a multitude of challenges and threats to cybersecurity, data privacy, and overall information security. In this comprehensive survey paper, we delve into the complex landscape of challenges and threats associated with data localization in distributed computing environments. We explore the intricate interplay between data localization, distributed infrastructure, cybersecurity, and privacy concerns. This paper provides an in-depth analysis of various challenges such as regulatory compliance, data integrity, authentication, and access control, along with potential threats like data breaches, insider attacks, and unauthorized access. Furthermore, we investigate the state-of-the-art security mechanisms, encryption techniques, privacy-preserving methods, and access control strategies that researchers and practitioners have developed to address these challenges. Through this survey, we aim to provide a comprehensive overview of the critical issues surrounding data localization within cloud computing and shed light on the emerging trends and potential solutions that can pave the way for secure and privacy-aware data localization practices. © 2024 IEEE.

关键词： Data integrity

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Smart Lock Security System 2

Smart Lock Security System

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2nd IEEE International Conference on Advances in Information technology, ICAIT 2024

作者： Ravikumar, Pushpa Arpitha, C.N. Hemanth, N.G. Department of Computer Science and Engineering Adichunchanagiri Institute of Technology Chikkamagaluru India

ISBN: (纸本)9798350383867

With the percentage of single-parent households rising quickly, criminal vulnerability is becoming more of a social issue The main issue is often worry over stranger visiting, especially in the case of single female families. This project focuses on the design strategy for an embedded real-time surveillance system based on a Raspberry Pi for the purpose of detecting intruders. Surveillance technology is reinforced to provide vital security for our daily lives, along with related control and alert functions. Our creative integration of cameras and motion detectors into a web application is the foundation of the suggested security system. Remote sensing cameras and motion detectors are managed and operated by Raspberry Pi. The goal of this research is to create a system that can quickly identify outsiders and respond by taking pictures and sending them to a wireless module that is based on the owner. If owner wish to add the other members to home, then he need to save the person photo in database. © 2024 IEEE.

关键词： Remote sensing

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A CNN and HBA Based Approach for Grape Disease Identification 4

A CNN and HBA Based Approach for Grape Disease Identificatio...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Vishnuvarthan, K. Renugadevi, R. Santhi, S. Kit - Kalaignarkarunanidhi Institute of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798331523923

Grapes are among the most extensively cultivated fruit crops globally, with over 10,000 varieties. They serve as a significant economic resource for many nations due to their diverse applications, including wine production, fresh juice consumption, raisin production, and juice manufacturing. However, grape diseases pose a severe threat to the viticulture industry, leading to substantial financial losses and a decline in wine quality. Manual evaluation is the foundation of traditional disease detection techniques, which are error-prone in addition to saving time. This highlights the need for an automated system capable of analyzing plant health, identifying diseases, and addressing undernourishment efficiently and reliably. Accurate disease diagnosis and timely control measures are crucial for mitigating these challenges. Many scholars have studied various algorithms such as CNN, SVM, Neural Networks, Random Forests, etc., yet each has disadvantages. So we have proposed an automated deep learning-based approach that integrates the Honey Badger Algorithm (HBA) with Convolutional Neural Networks (CNN) for the detection of grape diseases. A phenomenal 95% accuracy rate was attained by the prototype after it was trained on a dataset of 10,000 photos. Its performance was evaluated across various grape varieties and environmental conditions, demonstrating its robustness and adaptability. © 2025 IEEE.

关键词： Wine

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Analysing for Impact of Neutral Sentiments for Enhancing Quality of Services 2

Analysing for Impact of Neutral Sentiments for Enhancing Qua...

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2nd IEEE International Conference on IoT, Communication and Automation technology, ICICAT 2024

作者： Ranjan, Roop Singh, Ranjeet Shukla, Roshan Buddha Institute of Technology Department of Computer Science and Engineering Gorakhpur India

ISBN: (纸本)9798350368109

Sentiment analysis (SA) is an intellectual process of extracting a user's views. Social media is gaining prominence in public transit agencies for communication strategies and daily management. In recent years, web documents are identified as an important source of reviewing individual opinions. Researchers using these social networking platforms are producing a high rate of increase in interest in methods for automatically extracting and analysing opinions from web documents such as for weblogs, customer reviews, movies and public services etc. This paper is an attempt to perform an evaluation of public opinion for the Quality of Services of two very popular public transportations in North India. Opinions of public have been collected in form of tweets for a specific time. An approach based on fuzzy logic and machine learning is introduced to solve the tweets extraction that is used for classification. The impact of neutral tweets is discussed. Results show that the performance of road transport is better than the transport through railway services and neutral tweets play a significant role in emotion analysis of the system. © 2024 IEEE.

关键词： Tweets

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Customer Segmentation using Clustering Techniques: Data-Driven Approach to Enhance Marketing Strategy 5

Customer Segmentation using Clustering Techniques: Data-Driv...

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Sakthi Priya, G. Vignesh Saravanan, K. Hemalatha, B. Karthika, R. Kavya Srinidhi, B. Ramco Institute of Technology Department of Computer Science and Engineering Rajapalayam India

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530013

Customer segmentation is a vital strategy for businesses seeking to enhance their marketing efforts and optimize resource allocation. This research focuses on segmenting customers using the Mall Customer Segmentation dataset, which includes demographic and behavioral attributes such as age, gender, annual income, and spending score. The work begins with data preprocessing, involving the handling of missing values, encoding of categorical variables, and scaling of numerical features to prepare the data for analysis. Following preprocessing, exploratory data analysis (EDA) is conducted to visualize feature distributions and relationships, providing insights into the data's structure. The core of the research involves applying various clustering algorithms-K-Means, Hierarchical Clustering, and DBSCAN-to identify distinct customer segments. The optimal number of clusters is determined through methods like the Elbow Method and Silhouette Score. The clusters are then evaluated for quality, and their characteristics are analyzed to understand different customer segments. This segmentation enables businesses to their marketing strategies, enhance customer satisfaction, and make data-driven decisions based on customer behavior insights and demographics. © 2024 IEEE.

关键词： Sales

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