检索结果-内蒙古大学图书馆

2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Budarapu, Aadithya Vikram Gaddam, John Hyde Boyedi, Ramu Muthyala, Thoshan Kumer Kathirisetty, Nikhila Dept. of Information Technology Hyderabad India Dept. of Computer Science and Data Science Hyderabad India

ISBN: (纸本)9798350370188

The maintenance and enhancement of dynamic soil characteristics are the primary focus of soil management in agriculture to increase crop productivity. Higher productivity may result from efficient soil control of resources and corrective micronutrient treatments. Using CNN and 'KNN' algorithms, the 'soil land classification and crop prediction system' application was created. In this study, two datasets are used: one to obtain crop prediction and the other for soil land categorization. The kind of soils are trained using CNN ('VGG- 19') algorithm, and the accuracy of the model is calculated. The trained model is then utilized in the Flask web app to forecast the type of soil. Another data set with nitrogen, phosphorus, potassium, pH, and temperature as features and the class type of crop as a label is used to forecast crop production. These two algorithms are used to create the flask website, which accepts inputs such as soil picture, soil type prediction, and land parameter inputs for crop prediction. © 2024 IEEE.

关键词： Soils

来源：评论

学校读者我要写书评

暂无评论

QoS-Constrained Service Migrations in MEC Using Dynamic Service Prioritisation Algorithm

QoS-Constrained Service Migrations in MEC Using Dynamic Serv...

引用

2024 International Conference on Artificial Intelligence and Emerging technology, Global AI Summit 2024

作者： Velrajan, Saravanan Jeyaprakash, Thangakumar Hindustan Institute of Technology and Science Dept. of Computer Science Chennai India

ISBN: (纸本)9798350379716

The rapid expansion of 5G networks and the increased focus on user experience has resulted in the growth of Multi-access Edge Computing (MEC) at the edge of wireless networks. The indeterministic workloads handled by MEC often lead to overloaded applications. Services migrations are performed in MEC to manage the application performance, potentially minimising the impact on the user's Quality of Experience (QoE). While prior research on application migrations in MEC has primarily focused on subscriber mobility, energy management, and resource optimisation, a gap exists in understanding how these migrations impact application performance in MEC environments with stringent Service Level Agreements (SLAs). This research proposes a new approach for service migrations in MEC based on dynamic service prioritisation. The proposed Dynamic Service Prioritisation Algorithm (DSPA). uses a variable application performance watermark to trigger migrations, enabling MEC infrastructure to dynamically adapt to indeterministic workloads. DSPA selects services for migration by optimally balancing service load and migration time parameters. Through extensive simulations, our study proves that DSPA is best suited for managing the performance of diverse applications hosted in MEC. DSPA exhibited superior performance in minimising SLA violations and mitigating user experience impact during service migrations compared to other contemporary algorithms. © 2024 IEEE.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

Using Game Theory to Prioritize Goals in Requirements Engineering 4

Using Game Theory to Prioritize Goals in Requirements Engine...

引用

4th International Conference on Next Generation Computing Applications, NextComp 2024

作者： Munthali, Isaac Kankuzi, Bennett Malawi University of Science and Technology Dept. of Computer Science & IT Thyolo Malawi

ISBN: (纸本)9798331517403

Prioritizing competing goals among different stakeholders in requirements engineering is usually a daunting task for system architects as each of the stakeholders have their own interests. This study modeled this conflicting environment among stakeholders as a non-cooperative game in game theory with goals modeled as strategies and utility value of each goal as pay-offs in a pay-off matrix. In a user study that employed the NashPy algorithm to deduce the Nash equilibrium of the strategies in a two player game, the tool was able to automatically deduce goals which needed to be prioritized to achieve a win-win situation for two stakeholders. This was also confirmed by stakeholders. The paper has three contributions: modelling goals for stakeholders in requirements engineering as a non-cooperative game in game theory;automatically deducing goals that need prioritization among stakeholders in requirements engineering based on the Nash equilibrium;and performing a user study to validate the deduced prioritized goals. © 2024 IEEE.

关键词： Requirements engineering

来源：评论

学校读者我要写书评

暂无评论

Leveraging ML to Detect Fraudulent Customs Declaration: A Case of Logistic Regression and LightGBM Algorithms 4

Leveraging ML to Detect Fraudulent Customs Declaration: A Ca...

引用

4th International Conference on Next Generation Computing Applications, NextComp 2024

作者： Chilomo, Innocent Kankuzi, Bennett Malawi University of Science and Technology Dept. of Computer Science and IT Thyolo Malawi

ISBN: (纸本)9798331517403

Harmonised System (HS) code fraud, also known as Customs tariff classification fraud, is common in developed and developing countries. It occurs when traders intentionally mis-classify goods during the time of clearance. Classification fraud results in tax revenue loss, restricted and prohibited goods entry, and unfair market competition. Current manual verification techniques to detect classification fraud are time-consuming and error-prone;thus, an effective and precise strategy is required. In this study, we developed and evaluated the performance of Logistic Regression and LightGBM machine learning models in detecting HS Code fraud using a dataset obtained from a government Revenue Authority in a developing country. Results show that the LightGBM model outperformed Logistic Regression. The LightGBM model demonstrated superior accuracy (0.961), precision (0.890), recall (0.901), and F1 score (0.896) as compared to the Logistic Regression model, which had accuracy (0.932), precision (0.772), recall (0.900), and F1 score (0.831). Our contribution is threefold: Firstly, the dataset used is from a developing country, unlike other studies that use datasets from developed countries. Secondly, we worked with Customs import data collected at an 8-digit HS code level, whereas most similar studies typically used HS codes at 2, 4, or 6-digit levels. Lastly, unlike comparable studies, we have compared the performance of Logistic Regression and LightGBM machine learning algorithms. © 2024 IEEE.

关键词： Logistic regression

来源：评论

学校读者我要写书评

暂无评论

Proposal for the Support Method Presentation Model Utilizing Nursing Home Insights 9

Proposal for the Support Method Presentation Model Utilizing...

引用

9th International Conference on Business and Industrial Research, ICBIR 2024

作者： Nakajima, Yoko Yuki, Masamune Ptaszynski, Michal Honma, Hirotoshi Akiba, Tomoyoshi Masui, Fumito Institute of Technology Kushiro Colloege Dept. of Creative Engineering Kushiro Japan School of Regional Innovation and Social Design Engineering of Kitami Institute of Technology Kitami Japan Toyohashi University of Technology Dept. of Computer Science and Technology and Engineering Toyohashi Japan

ISBN: (纸本)9798350383010

One of the significant problems faced by dementia group homes is the high caregiver turnover rate. In particular, there is an urgent need to prevent the turnover of new caregivers and work toward ensuring and improving the quality of care. To address this issue, we are developing a care method support system that utilizes two databases: a personal attributes database and a care case database ([1]-[3]). The personal attributes database extracts personal attributes such as hobbies and previous occupations of residents from care records and care conference minutes. The care case database extracts cases of resident problems, their solutions, and the original text containing them. The care method support system presents candidates for appropriate responses to problems faced by residents based on these databases. In this study, we generated two care suggestion models: Care Suggestion Model: This model applies text similarity to the care case database to suggest candidates for appropriate responses to unregistered problems. Personalized Care Suggestion Model: This model applies clustering to the personal attributes database and generates a care suggestion model that considers personal attributes. We compared the two models and tested the usefulness of the model. © 2024 IEEE.

关键词： Nursing

来源：评论

学校读者我要写书评

暂无评论

Effective Machine Learning Model for Disease Recognition and Categorization of Mango Leaves

Effective Machine Learning Model for Disease Recognition and...

引用

2024 International Conference on Computational Intelligence and Computing Applications, ICCICA 2024

作者： Kumar, Sandeep Gupta, Bhupesh Grover, Richa Chhabra, Mohit Computer Science & Engineering Dept. Ambala Mullana India Panipat Institute Of Engineering & Technology Computer Science & Engineering Dept. India

ISBN: (纸本)9798350306446

Maintaining the health and production of mango farms depends on the early detection of illnesses in mango trees. Despite the vital role agriculture plays, it remains an industry receiving limited attention from the machine-learning community. A noteworthy challenge is the lack of standardized and openly accessible agricultural datasets, impeding researchers from fully leveraging the potential of advanced computational prediction tools. The study focuses on employing deep learning and image processing techniques for diagnosing prevalent mango leaf diseases in India. The goal is to enhance both the quality and quantity of agricultural production by implementing effective disease control measures upon identifying plant diseases. The automation of plant disease detection proves particularly beneficial, reducing the monitoring efforts required by large farms. Rapid identification of leaf diseases is crucial, given that leaves serve as a plant's primary source of nutrition. Notably, none of the seven different mango leaf illnesses that have been observed in India have ever been the subject of earlier research. In this study, we provide a lightweight Resnet50 model that can reliably classify healthy mango leaves and the seven discovered illnesses on mango leaves. The performance of our proposed lightweight Resnet-50 model is evaluated against many pre-trained models, such as Exception, Resnet101, and VGG16. The findings reveal that the lightweight Resnet-50 model achieves the highest testing accuracy, reaching an impressive 95%. This underscores the model's effectiveness in automating the identification of mango leaf diseases, offering a promising solution for improving agricultural practices in India. © 2024 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

A comprehensive step of XAI for Bengali and English text detection and recognition from natural scene images 2

A comprehensive step of XAI for Bengali and English text det...

引用

2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： Dutta, Mithun Das, Utpol Kanti Das, Jugal Krishna Rangamati Science and Technology University Dept. of Computer Science and Engineering Rangamati Bangladesh Jahangirnagar University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350367461

A critical first step in many applications, including augmented reality, document analysis, and scene comprehension, is text detection from images. Even though text identification for the English language has advanced significantly, there are particular difficulties when applying these methods to languages such as Bengali because of variations in script, morphology, and typographic characteristics. This article offers a wonderful method for leveraging the Faster R-CNN framework to identify and categorize text from images that contain Bengali and English sentences. The study utilizes a dataset named "Bengali and English text image dataset (BETID)"that consists of images with text in both Bengali and English scripts, taken from a variety of sources such as books, documents, natural scenes, internet images, and landscapes. Pre-processing methods are used to improve the resilience and generalization of the model, including image scaling, normalization, and augmentation. The Faster R-CNN architecture is tuned and trained to identify text regions in images and categorize Bengali or English text. The performance of the text Classification model is evaluated using evaluation measures such as accuracy on the BETID dataset. The proposed Faster R-CNN model achieved an average of 97.90% accuracy, which is better than other deep learning models. Empirical findings showcase the capacity of transfer learning to alleviate data scarcity concerns and enhance text detection precision for low-resource languages such as Bengali.) © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Highway Traffic Surveillance over UAV Dataset via Blob Detection and Histogram of Gradient 4

Highway Traffic Surveillance over UAV Dataset via Blob Detec...

引用

4th International Conference on Advancements in Computational sciences, ICACS 2023

作者： Qureshi, Asifa Mehmood Butt, Abdul Haleem Jalal, Ahmad Air University Dept. of Creative Technologies Islamabad Pakistan Air University Dept. of Computer Science Islamabad Pakistan

ISBN: (纸本)9781665463775

Systems for traffic monitoring often rely on local platforms. Aerial images provide the flexibility to sense the vehicle location and movements with appropriate resolution over a broader area via mobile platforms. This research study presents a method to monitor traffic flow effectively using aerial images. A novel dataset was used to evaluate the research study. In total 100 images were used, and further each image was divided into a burst of three images. The detection is being done on the first image of each burst whereas the other two images were used for tracking. Vehicle detection mainly depends on blob detection techniques with dynamic thresholding methods. To track vehicles, a shape model is generated for each of the detected vehicles. The model is used for template matching to locate all possible positions of the vehicle. The tracking results are improved by selecting only those matches having the direction and magnitude above a threshold. The accuracy of the detection algorithm in terms of correctness and completeness is 86% and 79% respectively. Through geometric computation, 73.4% of vehicles' shape model was correctly estimated. Further, the estimated shape models were used for tracking which tracked 74.9% of vehicles correctly. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Smart Vehicle Procurement System using Blockchain technology 3

Smart Vehicle Procurement System using Blockchain Technology

引用

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

作者： Kumar, Boddu Manoj Rajeswari, G. Duraipandian, Kavitha David, Shiela Dept. of Computer Science and Engineering with specialization in Blockchain Technology Sathyabama Institute of Science and Technology Tamil Nadu Chennai India Dept. of Computer Science and Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai600119 India

ISBN: (纸本)9798331527549

Blockchain technology has become more widespread in our lives revolutionizing various industries through improved security, transparency, and operational efficiency. Its decentralized ledger system is particularly effective in areas like finance and supply chain management ensuring data integrity and reducing the need for middlemen. This study explores how blockchain technology is used in the process of buying vehicles highlighting its benefits compared to methods. Traditional vehicle purchases involve a network of dealers, banks and regulators leading to inefficiencies, higher costs and potential fraud. The usual process involves steps like financing checking vehicle history and changing ownership. Each requiring extensive paperwork and third-party intervention. In contrast using blockchain for vehicle purchases can simplify things through contracts that automate tasks like verifying history securely transferring ownership instantly settling payments. The unchangeable nature of records ensures that all transaction data remains secure against tampering fostering trust between buyers and sellers. Furthermore, blockchain can cut costs significantly by removing the need for middlemen such, as escrow services and title companies while reducing burdens. The advanced security elements built into technology help reduce the chances of fraudulent actions like altering odometer readings or selling stolen cars. This study showcases a comparison illustrating how blockchain can simplify the process of buying vehicles offering an economical and secure experience. © 2025 IEEE.

关键词： Decentralized finance

来源：评论

学校读者我要写书评

暂无评论

Application of VGIS Digital Twin Platform for Enhanced Oilfield Disaster Management and Environmental Protection

引用

Informatica (Slovenia) 2024年第14期48卷 27-42页

作者： Alabbasi, Awab Aljabery, Maalim A. Bölük, Pınar Sarısaray Faculty of Engineering and Natural Sciences Electrical and Computer Engineering Dept. Bahcesehir University Istanbul34353 Turkey Faculty of Computer Science and Information Technology Computer Science Dept. University of Basrah Basrah61004 Iraq Faculty of Engineering and Natural Sciences Software Engineering Dept. Bahçeşehir University Istanbul34353 Turkey

VGIS (Virtual Geographic Information System) Platform is a unified oilfield operations management platform based on MaaS (Management as a Service) that integrates advanced technologies such as AIoT (Artificial Intelligence & Internet of Things), GIS (Geographic Information System), Digital Twin, and AR (Augmented Reality)/ VR (Virtual Reality). The VGIS platform connects, collects, integrates, analyses, and acts on disparate data sources to provide the oilfield with a centralized view to help make informed decisions fast, bring operational visibility across all assets to improve safety and operational efficiency, reduce costs and improve margins, provide comprehensive analytics and decision support, increase business agility, and reduce management complexity. This is a case study of the application of the VGIS platform Majnoon oilfield, Basrah, Iraq. VGIS digital transformation, production process, and KPIs (Key performance indicators) are highly managed taking oilfield management to a higher level globally, in this study, the objective is to address and resolve the issue of high costs associated with using cloud services by utilising a local Data Center (a large group of networked computer servers typically used by organizations for the remote storage, processing, or distribution of large amounts of data). This approach involves directly uploading 3D maps to ensure faster service on the intranet, eliminating the need to pay for cloud *** aims providing a platform for researching and implementing monitoring and controlling processes in a more convenient and remote manner. The vGIS platform has emerged as a crucial instrument in the realm of disaster response and crisis management. This technology enables responders to rapidly evaluate, analyse, and respond to crucial information in real-time. This research examined the application of vGIS technology in disaster response and analyse the potential advantages and obstacles associated with its utilisation. © 2

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：