检索结果-内蒙古大学图书馆

4th IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Anoop, S. Adwaith, A. Aswin, A. Raja, S.K. Tejasvin, V. Nayan, M.K. Nithin, P.M. Amrita Vishwa Vidyapeetham Department of Electrical and Electronics Engineering Amritapuri India Amrita Vishwa Vidyapeetham Department of Electronics and Communication Engineering Amritapuri India Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Amritapuri India Amrita Vishwa Vidyapeetham Amrita School For Sustainable Futures Amritapuri India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518981

Participatory Rural Appraisal (PRA) is a key methodology in the socially inclusive development of Indian rural communities. Even though there are various organizations and government agencies involved in the 'real' implementation of PRA for identifying the root causes and solutions of poverty, health issues, societal imbalance, and so on, the actual participation of the beneficiaries in the process is still a question mark. In this paper, we try to analyse the effect of actual participation of the people from the local community in the application of some PRA tools to do surveys and identify the root cause of the economic backwardness, and societal imbalance in a rural village in the state of Maharashtra, India. Most of the similar projects are done by management or social science students/researchers/scientists. In this paper, the analysis is done and presented from an engineer's perspective. This project is part of the Live-in-Labs® project of Amrita Vishwa Vidyapeetham to encourage students to live and interact with society and to learn and solve the community's problems. In this paper, we try to explain the various levels of complexities faced during the study, with an emphasis on both failed and succeeded steps. We believe this paper supports practitioners and policymakers who are working towards improving the methodologies and approaches involved in PRA to ensure an inclusive and holistic community integrated development in rural India. © 2024 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Innovative Exploration Techniques: Utilizing IoT-Enabled Robots for Safe and Efficient Underground Tunnel Investigation

Innovative Exploration Techniques: Utilizing IoT-Enabled Rob...

引用

International Conference on Interdisciplinary Approaches in Civil engineering for Sustainable Development, IACESD 2023

作者： Shravan, N. Manoj Kumar, M. Chakravarthi, Bharatesh Bhargavi, C. Department of Computer Science and Engineering Jyothy Institute of Technology Bangalore India School of Computing and Augmented Intelligence Arizona State University S Mill Avenue TempeAZ United States Department of Civil Engineering Jyothy Institute of Technology Bangalore India

ISBN: (纸本)9789819996094

The use of IoT-enabled robots in the investigation and maintenance of underground tunnels has gained significant attention in recent years. These robots, equipped with sensors and cameras, offer numerous advantages, including improved safety, increased efficiency, and cost reduction. This research explores the benefits of employing IoT-enabled robots for tunnel analysis and maintenance, while addressing the challenges associated with their implementation. The study focuses on the use of LIDAR technology for perception, mapping, and navigation of the robots in unstructured underground environments. The autonomous navigation system encompasses perception, map building, location calculation, planning, control, and obstacle avoidance. The research highlights the importance of autonomous systems in assisting humans in various domains and reviews past and present research using various sensors and software. The proposed work presents a comprehensive approach that combines hardware, software, and experimental methodologies to investigate the utilization of IoT-enabled robots for safe and efficient tunnel operations. The research includes the development of customized software applications, integration of advanced sensor technologies, communication infrastructure, and experimental setups to simulate underground tunnel environments. Data collection, analysis, evaluation, and validation are conducted to assess the performance and effectiveness of the IoT-enabled robots (Yan et al. in Int J Distrib Sens Netw 15(5), 2019 [1]). Additionally, the integration of IoT-enabled robots in civil engineering applications is discussed, including construction site monitoring, automated inspection and maintenance, smart infrastructure monitoring, autonomous construction and excavation, hazardous environment exploration, geotechnical monitoring, and disaster response and recovery (Valente et al. in 2020 Global IoT summit (GIoTS). IEEE, pp 1–6, 2020 [2]). The results demonstrate the visualiza

关键词： Cost reduction

来源：评论

学校读者我要写书评

暂无评论

Combined Effect of Concept Drift and Class Imbalance on Model Performance During Stream Classification

引用

computers, Materials & Continua 2023年第4期75卷 1827-1845页

作者： Abdul Sattar Palli Jafreezal Jaafar Manzoor Ahmed Hashmani Heitor Murilo Gomes Aeshah Alsughayyir Abdul Rehman Gilal Department of Computer and Information Sciences Universiti Teknologi PETRONAS(UTP)Seri Iskandar32610Malaysia Centre for Research in Data Science UTPPerak32610Malaysia High Performance Cloud Computing Centre(HPC3) UTPPerak32610Malaysia School of Engineering and Computer Science Victoria University of WellingtonWellington6012New Zealand AI Institute University of Waikato WellingtonHamilton3240New Zealand Anti-Narcotics Force Ministry of Narcotics ControlIslamabad46000Pakistan College of Computer Science and Engineering Taibah UniversityMadinah42353Saudi Arabia

Every application in a smart city environment like the smart grid,health monitoring, security, and surveillance generates non-stationary datastreams. Due to such nature, the statistical properties of data changes overtime, leading to class imbalance and concept drift issues. Both these issuescause model performance degradation. Most of the current work has beenfocused on developing an ensemble strategy by training a new classifier on thelatest data to resolve the issue. These techniques suffer while training the newclassifier if the data is imbalanced. Also, the class imbalance ratio may changegreatly from one input stream to another, making the problem more *** existing solutions proposed for addressing the combined issue of classimbalance and concept drift are lacking in understating of correlation of oneproblem with the other. This work studies the association between conceptdrift and class imbalance ratio and then demonstrates how changes in classimbalance ratio along with concept drift affect the classifier’s *** analyzed the effect of both the issues on minority and majority classesindividually. To do this, we conducted experiments on benchmark datasetsusing state-of-the-art classifiers especially designed for data stream ***, recall, F1 score, and geometric mean were used to measure theperformance. Our findings show that when both class imbalance and conceptdrift problems occur together the performance can decrease up to 15%. Ourresults also show that the increase in the imbalance ratio can cause a 10% to15% decrease in the precision scores of both minority and majority *** study findings may help in designing intelligent and adaptive solutionsthat can cope with the challenges of non-stationary data streams like conceptdrift and class imbalance.

关键词： Classification data streams class imbalance concept drift class imbalance ratio

来源：评论

学校读者我要写书评

暂无评论

Accidental Face Recognition and Detection Using Machine Learning 1

Accidental Face Recognition and Detection Using Machine Lear...

引用

1st International Conference in Advanced Innovation on Smart City, ICAISC 2023

作者： Sharma, Ashish Agrawal, Piyansh Krishan Sharma, Bhisham Dhaou, Imed Ben GLA University Department of Computer Engineering & Applications UP Mathura India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Dar Al-Hekma University Hekma School of Engineering Computing and Informatics Department of Computer Science Jeddah Saudi Arabia

ISBN: (纸本)9781665472753

The data collected from all the States and Union Territories has been compiled in the Publication, according to the ministry of road transport and roads transport research wing. The total number of accident-related deaths in 2018 was 1,51,417, which is a 2.3 percent increase over 2017. Around 85% of accident-related deaths occur in the 18-60 age range, which is the most productive. Road traffic fatalities not only inflict the relatives of the victims considerable emotional suffering, but they also cost the nation a lot of money. In this data maximum hazard happens due to delayed response of family and friends as they are unknown of the situation of the sight of the accident. Also, several cases remain unreported. Our objective is to reduce this number to make our nation strong and prosper. In this current research we are committed to creating a social network where road accidents can be reported quickly to family and friends, so the delayed response can be reduced. The practice of associating a person with a picture has become increasingly common thanks to the media. However, it is less resistant to retinal and fingerprint scanning. The face detection and recognition module created for the current research is described in this paper. Face detection will be performed using Haar-Cascades, while face identification will be performed using Eigenfaces, Fisher faces, and local binary pattern histograms. © 2023 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

XRL-SHAP-Cache:an explainable reinforcement learning approach for intelligent edge service caching in content delivery networks

引用

science China(Information sciences) 2024年第7期67卷 46-71页

作者： Xiaolong XU Fan WU Muhammad BILAL Xiaoyu XIA Wanchun DOU Lina YAO Weiyi ZHONG School of Software Nanjing University of Information Science and Technology School of Computing and Communications Lancaster University School of Computing Technologies Royal Melbourne Institute of Technology State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering University of New South Wales Data 61 Commonwealth Scientific and Industrial Research Organization School of Computer Science Qufu Normal University

Content delivery networks(CDNs) play a pivotal role in the modern internet infrastructure by enabling efficient content delivery across diverse geographical regions. As an essential component of CDNs, the edge caching scheme directly influences the user experience by determining the caching and eviction of content on edge servers. With the emergence of 5G technology, traditional caching schemes have faced challenges in adapting to increasingly complex and dynamic network environments. Consequently, deep reinforcement learning(DRL) offers a promising solution for intelligent zero-touch network governance. However, the blackbox nature of DRL models poses challenges in understanding and making trusting decisions. In this paper,we propose an explainable reinforcement learning(XRL)-based intelligent edge service caching approach,namely XRL-SHAP-Cache, which combines DRL with an explainable artificial intelligence(XAI) technique for cache management in CDNs. Instead of focusing solely on achieving performance gains, this study introduces a novel paradigm for providing interpretable caching strategies, thereby establishing a foundation for future transparent and trustworthy edge caching solutions. Specifically, a multi-level cache scheduling framework for CDNs was formulated theoretically, with the D3QN-based caching scheme serving as the targeted interpretable model. Subsequently, by integrating Deep-SHAP into our framework, the contribution of each state input feature to the agent's Q-value output was calculated, thereby providing valuable insights into the decision-making process. The proposed XRL-SHAP-Cache approach was evaluated through extensive experiments to demonstrate the behavior of the scheduling agent in the face of different environmental *** results demonstrate its strong explainability under various real-life scenarios while maintaining superior performance compared to traditional caching schemes in terms of cache hit ratio, quality of service(QoS),a

关键词： deep reinforcement learning (DRL) explainable artificial intelligence (XAI) multi-level cache content delivery network (CDN) D3QN algorithm Deep-SHAP

来源：评论

学校读者我要写书评

暂无评论

An Advanced Deep Learning Approach Combining Image Analysis for Precise Retinal Disease Detection 1

An Advanced Deep Learning Approach Combining Image Analysis ...

引用

1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Kumar, Ankit Singh, Kamred Udham Singh, Teekam Kumar, Gaurav Pandey, Saroj Kumar Dwivedi, Pushpendra Dhar Gla University Department of Computer Engineering & Apllications UP Mathura India School of Computing Graphic Era Hill University Dehradun India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Raipur India

ISBN: (纸本)9798350330915

The purpose of this research is to showcase a unique hybrid image-centric deep learning system that was developed for the purpose of accurately identifying and diagnosing retinal diseases. Our method overcomes the limits that are connected with conventional imaging and computational analytics, specifically with regard to the accuracy of diagnostics and the level of processing speed. Our technique incorporates optimised models for retinal pictures in a seamless manner by combining the capabilities of convolutional neural networks (CNNs) with the flexibility of transfer learning. These models are then supplemented by advanced feature extraction algorithms. This new development makes it easier to accurately recognise small visual differences in retinal pictures, which are often missed by traditional approaches. Our study, which is based on a large dataset that includes a wide range of retinal anomalies, guarantees not only the correctness of our solution but also its flexibility to a variety of different situations. By demonstrating considerable gains in diagnostic accuracy, sensitivity, and specificity, as well as a notable decrease in the amount of manual feature engineering efforts, rigorous testing speeds up the diagnostic process without sacrificing its dependability. In addition to its use in retinal diagnosis, this model shows the potential of combining deep learning with conventional image analysis. It suggests that this combination might have a transformational influence on digital healthcare, with applications that could be extended to greater issues in medical imaging. In the rapidly developing field of digital healthcare, our results shed light on a potentially fruitful avenue. This avenue involves the use of advanced machine learning methods for the purpose of improving medical diagnosis. © 2023 IEEE.

关键词： Accuracy CNN Data Optimization Deep Learning Feature Extraction Hybrid Image Ophthalmological Retinal Disease SVM

来源：评论

学校读者我要写书评

暂无评论

Knapsack Encryption with Elliptic Curve Cryptography Based Secured Wireless Network 2

Knapsack Encryption with Elliptic Curve Cryptography Based S...

引用

2nd International Conference on Edge computing and Applications, ICECAA 2023

作者： Arun, V. Kuppusamy, P.G. Naveen, G. Santhuja, P. School of Computing Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computing Technologies Tamil Nadu Kattankulathur India Department of Electronics and Communication Engineering Andhra Pradesh Puttur India Jagannath Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chengalpattu India B v Raju Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798350347579

This research study discusses about the prospective future research areas while presenting the state-of-the-art in wireless network cryptography. Elliptic Curve Cryptography (ECC) offers a safe way for interacting nodes to exchange keys. In order to implement ECC, the message is first converted into an affine point on the Elliptic Curve (EC), and then the knapsack method is applied to the ECC-encrypted message across the finite field. This approach presents Knapsack Encryption with ECC Algorithm (KECC) for improving data security in wireless networks. The data is encrypted by using the knapsack algorithm and the ECC algorithm. The necessary encrypted data is forwarded to the receiver via in-between nodes. As a result, it avoids the man-in-the-middle attack. Experimental results prove that the KECC strategy increases the forward ratio. In addition, it reduces the key generation, encryption, as well as decryption computational time. © 2023 IEEE.

关键词： Wireless networks

来源：评论

学校读者我要写书评

暂无评论

High-performance and Multi-functional Control of Transformerless Single-phase Smart Inverter for Grid-connected PV System

引用

Journal of Modern Power Systems and Clean Energy 2021年第6期9卷 1386-1394页

作者： Kamran Zeb Saif Ul Islam Waqar Uddin Imran Khan Muhammad Ishfaq Tiago Davi Curi Busarello H.J.Kim Department of Electrical Engineering Pusan National University School of Electrical Engineering and Computer Science National University of Sciences and Technology Department of Control Automation and Computing EngineeringFederal University of Santa Catarina Blumenau

Highly reliable and flexible control is required for distributed generation(DG) to efficiently connect to the *** inverters play a key role in the control and integration of DG into the power grid and provide advanced functionalities. In this paper, an energy-based single-phase voltage-source smart inverter(SPV-SSI) of 5 k VA is designed and analyzed in detail. SPV-SSI is capable of supplying the power to local load and the utility load up to the rated capacity of the inverter, injecting the power into the grid, storing the energy in lead-acid battery bank, controlling the voltage at the point of common coupling(PCC) during voltage sags or faults, and making decisions on real-time pricing information obtained from the utility grid through advanced metering. The complete design of smart inverter in dq frame, bi-directional DC-DC buck-boost converter, IEEE standard 1547 based islanding and recloser, and static synchronous compensator(STATCOM) functionalities is presented in this paper. Moreover, adaptive controllers, i. e., fuzzy proportional-integral(F-PI) controller and fuzzy-sliding mode controller(F-SMC) are designed. The performances of F-PI controller and F-SMC are superior, stable, and robust compared with those of conventionally tuned PI controllers for voltage control loop(islanded mode) and current control loop(grid-connected mode).

关键词： Distributed generation(DG) inverter convert-er fuzzy-sliding mode controller(F-SMC) fuzzy proportionalintegral(F-PI)controller

来源：评论

学校读者我要写书评

暂无评论

Mask Detection for Life Protection 26

Mask Detection for Life Protection

引用

26th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2022

作者： Vignesh, H. Suresh, J. Lalithamani, N. Department of Computer Science and Engineering Amrita School of Computing Coimbatore Amrita Vishwa Vidyapeetham Coimbatore641112 India

ISBN: (纸本)9781950492664

"Health is Wealth" such a wealth of people is being affected and they are put to death on deathbeds in millions by a newly discovered virus called n-CoV (Corona virus). Covid is so-called mysterious because people affected by this disease are asymptotic. This infectious disease is mostly transmitted through droplets when an infected person coughs or sneezes. One of the main precautions that everyone must follow is wearing a mask. Some people wear masks improperly whenever they visit crowded places where there are high chances of this disease being spread. We have designed a real-time face mask detector that aims at detecting masks worn by people to reduce the transmission of this virus and make people wear masks in crowded areas. We can install this system at the entrance of places where there is more number of crowds. The detector follows Convolutional Neural Network (CNN), a part of Deep-Learning used to analyse visual imagery. It takes an input image, assigns importance (learnable weights and biases) to various aspects/objects of the image, and differentiates one from the other. Cascade Classifier detects the frontal face. Results have shown the detector classifies people with and without masks at an accuracy of 96.97%. © 2022 *** rights reserved.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

COVID-19 Vaccination Progress and Projections Across African Continents 1

COVID-19 Vaccination Progress and Projections Across African...

引用

1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Pandey, Saroj Kumar Singh, Kamred Udham Kumar, Gaurav Singh, Teekam Rathore, Yogesh Kumar Kumar, Ankit Gla University Department of Computer Engineering & Apllications UP Mathura India School of Computing Graphic Era Hill University Dehradun India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Raipur India

ISBN: (纸本)9798350330915

The world's largest immunization programmer of COVID-19 is under ongoing leading to a decline in COVID-19 cases and fatalities amongst the population. There are concerns growing that the poorest nation may be missed out, to the very end of a long queue for the resources. This paper explains the current progress of COVID-19 vaccinations in each continent. Time series analysis is performed on the daily vaccination data taken from 'Our World in Data' for 209 countries. Neural network auto regression (NNAR) model is used for continent-wise projection of vaccination rate for the next 365 days that determines when all of the population in each continent will be immunized. Empirical evaluation helped us to understand the unequal access and distribution of vaccines in African countries. © 2023 IEEE.

关键词： Africa COVID-19 Vaccine NNAR Time Series Analysis

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：