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

作者： Navadharani, N. Mouthami, K. Devipriya, R. Anandamurugan, S. Kpr Institute of Engineering and Technology Dept. of Computer Science Engineering Coimbatore India Kongu Engineering College Dept. of Information Technology Erode India

ISBN: (纸本)9798350384369

Plant diseases pose significant challenges to the agricultural sector, leading to decreased crop production and financial losses. Mango, being a popular fruit worldwide, is susceptible to various leaf diseases. Traditional diagnosis of these disorders requires labor-intensive and time-consuming manual picture interpretation. To address this issue, deep learning models have been utilized to enhance the precision and effectiveness of identifying leaf illness in mango crops. In this study, ResNet50, ResNext50, Convnet, and Conventv2 deep learning models were compared to find the most successful approach. The results demonstrated that the Conventv2 model achieved the highest accuracy of 98.21%. The major aim of the research work is improvising sustainable agricultural practices by leveraging advanced technology for accurate plant disease classification. The findings have implications for improving mango crop management and ensuring a more sustainable and efficient agricultural industry. © 2024 IEEE.

关键词： Fruits

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Version Controlling of User Content in Learning Management Systems for Supporting the Teaching/Learning Process 8

Version Controlling of User Content in Learning Management S...

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8th International Conference on information technology Research, ICITR 2023

作者： Firdhous, Mohamed Fazil Mohamed Elbreiki, Walid Wijesiriwardana, Chaman University of Moratuwa Dept. of Information Technology Moratuwa Sri Lanka College of Computer Technology Dept. of Computer Science Benghazi Libya

ISBN: (纸本)9798350359503

E-Learning or online learning has become an integral part of the educational system all over the world in recent times. The importance of online learning is really felt by almost everybody in the recent COVID19 pandemic as no physical activity could be conducted that required people to meet or gather at a specific place. Learning or Content Management Systems play an important role in any online learning system as most of the teaching and learning activities occur in a disconnected or asynchronous form. One of the main features of any learning management systems is collection and distribution of learning/teaching materials as well as other documents. In this paper, the authors present the results of an in dept. study carried out on the need for version controlling of user uploaded documents to the learning management systems. Also, presented is a document validation technique with a pilot implementation that can effectively compare and cross validate two uploaded files. © 2023 IEEE.

关键词： E-learning

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Study of Digital Image Compression Techniques and Framework for Suitability Selection based on Similarity Measuring Metrics 15

Study of Digital Image Compression Techniques and Framework ...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Mishra, Joynath Kumar, Vipin New Delhi India Dept. of Computer Science and Information Technology Mahatma Gandhi Central University Bihar Motihari India

ISBN: (纸本)9798350370249

In recent years, capturing and transmitting color images through the network to convey visual information in a short time has become a crucial task. Choosing the appropriate compression technique is a challenging endeavor due to technological advancements with inccrement of the memory usage. Various lossless and lossy image compression techniques have been developed over the years. However, the studies pertains to a lack of extensive assessment across various compression algorithms and metrics, necessitating a practical comparative analysis of existing methodologies for color image optimization in graphical representation and storage. Hence, a comprehensive comparative study is conducted on six types of lossless compression techniques (Huffman, RLE, LZW encoding, JPEG2KLeGall53, PNG, WebP) and six types of lossy compression techniques (JPEG-DCT, SVD, K-means, JPEG2K-CDF97, PNG, WebP), evaluating their performance based on input parameters for compresion such as quality factor, selection of singular values, and number of clusters. The outputs are analzed followed by the extracted parameters such as compression ratio (CR), time, RMSE, PSNR, SSIM, FSIM, and bpp to determine the best case of compression. Furthermore, a weighted Friedman ranking test is conducted to determine the most effective compression technique. It is concluded that JPEG2K-CDF97 is optimal for lossy compression, while WebP is considerable for lossless compression. © 2024 IEEE.

关键词： Image compression

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Factors on the UTAUT2 to Identify the Influence on the Usage Behavior of AI-Based Air Quality 3

Factors on the UTAUT2 to Identify the Influence on the Usage...

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3rd International Conference on Creative Communication and Innovative technology, ICCIT 2024

作者： Aini, Qurotul Hartomo, Kristoko Dwi Dwi Purnomo, Hindriyanto Wahab, Abdul Rahardja, Untung Satya Wacana Christian University Dept. of Computer Science and Technology Salatiga Indonesia Satya Wacana Christian University Dept. of Information Technology Salatiga Indonesia International Islamic University Malaysia Dept. of Information and Computer Technology Kuala Lumpur Malaysia University of Raharja Master of Information Technology Tangerang Indonesia

ISBN: (纸本)9798350367492

This study investigates the effect of AI-based air quality detection apps on user behavior in Indonesia, ranked 26th globally for air pollution. Utilizing an online survey with 287 participants, focusing on 156 active users, and employing Partial Least Squares Structural Equation Modeling (PLS-SEM), the research assesses user satisfaction in environmental monitoring using the Unified Theory of Acceptance and Use of technology 2 (UTAUT2). This model examines 9 key variables: Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Price Value (PV), Hedonic Motivation (HM), Habit (HT), Behavioral Intention (BI), Usage Behavior (UB), Considered Risk (CR), and Considered Trust (CT). Key findings emphasize the crucial roles of PE and BI in determining user's usage intentions and behaviors. These insights are vital for enhancing air quality monitoring technologies for developers and policymakers. The study also identifies areas for future research, such as exploring external and demographic influences, to further understand user behavior and satisfaction with AI-based environmental tools. Overall, it highlights the importance of user-centric approaches in technological development for improving environmental health outcomes. © 2024 IEEE.

关键词： Environmental monitoring

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5G the Missing Piece in Digital Transformation of the Construction Sector 28

5G the Missing Piece in Digital Transformation of the Constr...

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28th International computer science and Engineering Conference, ICSEC 2024

作者： Chnaidini, Shaik Khan, M. Jebran Ullah, Fasee Khan, Arafat Ahmad Prashar, Deepak Gulf American University Dept. of Civil Engineering Fujairah United Arab Emirates Sarhad University of Science and Information Technology Dept of Computing and Information Technology Peshawar Pakistan Uinversiti Teknology Petronas Dept. of Computer and Information Sciences Seri Iskandar Malaysia Khonkaen University Dept. of Computer Science Khon Kaen Thailand Lovely Professional University Dept. of Computer Science and Engineering Punjab India

ISBN: (纸本)9798350366860

The 5th generation of wireless technology with a continuum leap rushing towards the future in the world of communication has a puzzle that enables the autonomous machine to work in site making a louder voice that shows the era where even if we cannot be fully robotic, we can make the machines do the work by sitting on a faraway control room. Making ways clear to see the work done miles away on construction sites the 5th generation has not only brought the people close through communication but also made them work collegiately with a clearer view front. The paper discusses 5G and the other related technologies that are emerging all over the world and how it is needed specifically in the construction industry. In the present paper, we tried to shed light on the acceptance and implementation of 5G technology in the construction sector. It is seen that the construction sector in India is lagging behind when it comes to implementation and availability of required support and resources for the 5G implementation. © 2024 IEEE.

关键词： Construction industry

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Relating Muscle Activity and Mouse Sensitivity in FPS Game Players Using Surface EMG Signals 5

Relating Muscle Activity and Mouse Sensitivity in FPS Game P...

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5th International Conference on Biomedical Engineering, IBIOMED 2024

作者： Prajapati, Vaibhav Turlapaty, Anish C. Sarma, Himangshu Ghorai, Mrinmoy Indian Institute of Information Technology Dept. of Electronics and Communication Engineering Sri City India Indian Institute of Information Technology Dept. of Computer Science and Engineering Sri City India

ISBN: (纸本)9798350389265

In the domain of first-person shooter (FPS) gaming, mouse sensitivity is crucial for performance. This paper presents an analysis showing the correlation between specific muscle activity and mouse movement. We analyzed mouse movements from twelve subjects with varying sensitivity levels. A new dataset electromyography analysis of human activity database 8 (EMAHA-DB8), is introduced which involved four mouse designs and two game modes: Medium (normal movement) and Hard (aggressive movement). Sensitivity settings were standardized using effective dots per inch (eDPI), calculated as Mouse DPI multiplied by in-game sensitivity. Hand muscle activity was measured using five Noraxon Ultium wireless surface electromyography (sEMG) sensors with Ag/AgCl electrodes. Various regression models, including Random Forest, Support Vector Regressor, K-Nearest Neighbors Regressor, MLP Regressor, and Gradient Boost Regressor, were used to predict eDPI from muscle movement patterns. Sequential feature selection identified the top ten features, highlighting the most significant muscles for predicting sensitivity. The results demonstrate that the Extensor Carpi Radialis (ECR) is the most active muscle, followed by the Extensor Digitorum (ED), while playing the chosen FPS game. These findings give insights for ergonomic and personalized equipment design to enhance gaming experience and performance. © 2024 IEEE.

关键词： Decision trees

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An Advance Boosting Approach for Multiclass Dry Bean Classification

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Journal of Engineering science and technology Review 2023年第2期16卷 107-115页

作者： Nayak, Janmenjoy Dash, Pandit Byomokesha Naik, Bighnaraj Dept. of Computer Science Maharaja Sriram Chandra Bhanja Deo University Odisha Baripada757003 India Dept. of Information Technology Aditya Institute of Technology and Management AP Tekkali532201 India Dept. of Computer Application Veer Surendra Sai University of Technology Burla768018 India

Dry beans, which are produced in large quantities, have the highest level of genetic diversity. The quality of seeds has a significant impact on crop yield. The importance of seed classification to both marketing and production can be shown by realizing that sustainable agricultural systems depend on these principles. This research is primarily aimed at providing a means to generate uniform seed varieties, as seed is not certified as a single variety. To achieve consistent seed classification, we have proposed Extreme Gradient Boosting ensembles using the Synthetic Minority Over-Sampling Methodology (SMOTE) to differentiate seven distinct registered types of dry beans with similar characteristics. There were a total of 13,611 grains from seven different varieties of dry beans sampled for the classification model. Classification algorithms based on machine learning like Decision Tree (DT), Support Vector Machine (SVM), Multilayer Perceptron (MLP), Adaptive Boosting classifier, Bagging Classifier, and Extreme Gradient Boosting ensembles using the Synthetic Minority Over-Sampling Methodology (SMOTE) were developed and compared. Overall correct classification rates for SVM, MLP, DT, Adaboost, Bagging, and Extreme Gradient Boost classifiers were 94.44%, 94.48%, 96.53%, 96.35%, 96.89%, and 97.32%, respectively. Extreme Gradient Boosting ensembles using the SMOTE classification model have the best accuracy. The results of this study satisfy the producers' and customers' demand for uniform bean varieties. © 2023 School of science, IHU. All rights reserved.

关键词： Adaptive boosting

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A Novel Deep Ensemble Learning Approach to Predict Eye Diseases from OCT Images 5

A Novel Deep Ensemble Learning Approach to Predict Eye Disea...

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

作者： Uddin, Nazim Mia, Md Sajib Uddin, Mohammed Nasir Mahmud, Prince Chandpur Science and Technology University Dept. of Information and Communication Technology Bangladesh Sylhet Engineering College Dept. of Computer Science and Engineering Bangladesh Jagannath University Dept. of Computer Science and Engineering Bangladesh Chandpur Science and Technology University Dept. of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350394290

As the world advances in technology, the classification of eye diseases is thought to have clinical applications since it evaluates and analyzes the results. Optometrists research and diagnose age-related eye problems such as Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), and Drusen using optical coherence tomography (OCT) of the human eye. Because their symptoms are similar, identifying these diseases is challenging and requires hours of expert analysis. The requirements for eye illness classification should be straightforward in nature, structure, and evaluation. Deep Learning Convolutional Neural Network Classification can create a hierarchical representation of images to differentiate between normal and diseased eye patterns for diagnostic purposes. Therefore, this paper aims to implement and define deep learning to classify and identify eye diseases. Using a four-class classification problem, this work investigates the automatic detection of Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), Drusen, and Normal in Optical Coherence Tomography (OCT) pictures. Multi-transfer learning architecture was used in the suggested deep learning Ensemble classification model. The most incredible accuracy of our proposed Ensemble model for multi- class classification was 83%. © 2023 IEEE.

关键词： Optical tomography

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Autoencoder for 3D Palm Print Identification 5

Autoencoder for 3D Palm Print Identification

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5th International Conference on information technology, Applied Mathematics and Statistics, ICITAMS 2023

作者： Naji, Noora Hadi Al-Juboori, Ali Mohsin University Of Al-Qadisiyah College Of Computer Science And Information Technology Dept. Of Computer Science Diwaniyah Iraq

ISBN: (纸本)9798350335118

The issue of personal identification is growing due to how crucial it is to get over the constraints of the existing methods. The current methods have numerous drawbacks, such as the possibility of password forgetfulness and broken or stolen access cards. The significance of bioinformatics-related identification systems resulted from this. This study devised a new approach for recognizing people from images of their palmprints. The scanning equipment uses contactless 3D imaging to collect the input images. The proposed approach is based on Autoencoder. And the obtained results are promising. With 8 minutes of training, the model gave 98% accuracy for the testing dataset. The results are compared with the accuracy and training time of transfer learning-based models. © 2023 IEEE.

关键词： Deep learning

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Utilizing AI-powered Drones for Efficient Flood Rescue Operations 3

Utilizing AI-powered Drones for Efficient Flood Rescue Opera...

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3rd International Conference on Automation, Computing and Renewable Systems, ICACRS 2024

作者： Kumar, M. Jaswanth Bitra, Dhanush Titus, Rohan Jazz, Dill Kiliroor, Cinu C. Dept. of Electronics and Communication Indian Institute of Information Technology Kottayam Kerala Kottayam India Dept. of Computer Science Indian Institute of Information Technology Kottayam Kerala Kottayam India

ISBN: (纸本)9798331532420

In times of severe earthquakes and floods, rapid and effective aid is crucial. Traditional methods often face challenges due to accessibility issues and the vast scale of *** proposed Autonomous Aerial Humanitarian Assistance and Disaster Relief (A2-HADR) System aims to transform disaster response through the use of drone technology. The proposed solution addresses the obstacles in rescue operations by employing drones equipped with Artificial Intelligence (AI) to provide immediate support. The advanced system utilizes state-of-the-art computer Vision technology to autonomously detect people and obstacles from heights of 50-100 meters at various angles and deliver essential supplies like food, clothing, and rescue gear to those in need. We have executed and assessed a range of advanced object detection algorithms, such as YOLOv8, YOLOv9, and Detectron2. After thorough evaluation, Detectron2 emerged as the most effective model among those tested, showcasing exceptional accuracy and resilience. © 2024 IEEE.

关键词： Drones

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