检索结果-内蒙古大学图书馆

4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023

作者： Pandey, Ankur Chaturvedi, Ankur Gupta, Manish Mannepalli, Praveen Kumar Kumar, Santosh Chhabra, Gunjan Manipal University School of Computer Science and Engineering Jaipur India Galgotia University Greater Department of Computer Applications Noida India Gla University Department of Electronics and Communication Engineering Mathura India India Era University Department of Computer Science Lucknow India Graphic Era Hill University Deptt. of Cse Dehradun India

ISBN: (纸本)9798350300093

Face detection methods have usually been used mostly for faces that aren't covered up (non-masked faces). These include nose, lips, ears, chin, and eyes. Faces must be concealed by masks in various locations, including labs, hospitals, crime scenes, and areas with high levels of pollution. The global spread of coronavirus known as COVID-19 has disastrous effects on community wellbeing. This study aims to apply a model too complicated data, namely, image and real-time video image tasks for personal face identification with and without a mask. The healthcare industry is in a hazardous state. Numerous preventative measures, including the use of masks, are being set in place to restrict the spread of this sickness;WHO (World Health organization) highly encourages the use of a mask. This extremely large number of COVID-19 samples provides valuable information regarding the pandemic's progression, as well as a possible way to encircle it to prevent future transfers. To prevent the transmission of the virus, several preventative measures have been implemented, including the use of masks. using a face mask that prevents droplet transfer discharged into the atmosphere, on either hand, may help avoid the outbreak. As a solution, the purpose of this function will be to form an FMD (Face Mask Detection) model which can be used as part of an embedded imaging system. It is expected to enhance the detection rate and achieve an accuracy of more than 99%. © 2023 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

High-dimensional nonlinear variable separation solutions and novel wave excitations for the(4+1)-dimensional Boiti-Leon-Manna-Pempinelli equation

引用

Communications in Theoretical Physics 2024年第11期76卷 1-11页

作者： Zu-feng Liang Xiao-yan Tang Wei Ding Department of Physics Hangzhou Normal UniversityHangzhou 310036China School of Mathematical Sciences Key Laboratory of Mathematics and Engineering Applications(Ministry of Education)&Shanghai Key Laboratory of PMMPEast China Normal UniversityShanghai 200241China School of Computer Science and Technology Shanghai Normal UniversityShanghai 200234China

Considering the importance of higher-dimensional equations that are widely applied to real nonlinear problems,many(4+1)-dimensional integrable systems have been established by uplifting the dimensions of their corresponding lower-dimensional integrable ***,an integrable(4+1)-dimensional extension of the Boiti-Leon-Manna-Pempinelli(4DBLMP)equation has been proposed,which can also be considered as an extension of the famous Korteweg-de Vries equation that is applicable in fluids,plasma physics and so *** is shown that new higher-dimensional variable separation solutions with several arbitrary lowerdimensional functions can also be obtained using the multilinear variable separation approach for the 4DBLMP *** addition,by taking advantage of the explicit expressions of the new solutions,versatile(4+1)-dimensional nonlinear wave excitations can be *** an illustration,periodic breathing lumps,multi-dromion-ring-type instantons,and hybrid waves on a doubly periodic wave background are discovered to reveal abundant nonlinear structures and dynamics in higher dimensions.

关键词： (4+1)-dimensional Boiti-Leon-Manna-Pempinelli equation variable separation solution periodic breathing lumps multi-dromion-ring-type instanton hybrid waves on a doubly periodic wave background

来源：评论

学校读者我要写书评

暂无评论

Optimizing Regulatory Compliance in Supply Chains with Blockchain and Gaussian Process Regression 2

Optimizing Regulatory Compliance in Supply Chains with Block...

引用

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

作者： Tulasiram, D. Jebaseeli, S. Kanmani Adnan, Myasar M. Madhavi, Arelli Varshney, Neeraj Nandhini, T.J. CMR College of Engineering & Technology Department of CSE India New Prince Shri Bhavani College of Engineering and Technology Department of IT Tamil Nadu Chennai600073 India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq GRIET Bachupally Department of AI&ML Telangana Hyderabad India GLA University Department of Computer Engineering & Applications Mathura India Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350368109

Increased regulation of the supply chain is another important issue of concern to industries in distinct countries as they struggle to implement the regulation in a network setting. This paper aims to explore ways to improve regulatory compliance through the application of the blockchain and machine learning model, namely Gaussian process regression. Blockchain is an accurate and permanent record-keeping system that can be applied to track the flow of items and associated activities in the supply chain. Compliance can also be enforced, and through smart contracts, analyses of various parameters such as obligations can be monitored and adjusted automatically through GPR which involves the analysis of data from systems that use blockchain to model compliance risks and predict compliance issues. Thus, using the above-mentioned technologies, a company can prevent compliance failures, meet the necessary standards and set up a constant process of improvement in the supply chain area. This research specifically defines the theoretical foundations, application, and advantages of blockchain and GPR in enhancing the compliance of supply chains with the regulations in this work. In this approach, case-study and use of examples show how this approach works in handling compliance issues in several industries. © 2024 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

A Framework for the prediction of Diabtetes Mellitus using Hyper-Parameter tuned XGBoost Classifier 13

A Framework for the prediction of Diabtetes Mellitus using H...

引用

13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022

作者： Gayathri, R. Pati, Peeta Basa Singh, Tripty Nair, Rekha R Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Computer Science and Engineering Bangalore India Dayananda Sagar University School of Engineering Department of Computer Applications Bangalore India

ISBN: (数字)9781665452625

ISBN: (纸本)9781665452625

Diabetes Mellitus is caused by the increase of blood glucose level in the body. It is likely to be the most common disease for the human community which is about 8.8% of the entire population. It is important to identify this disease in the initial stages of the development to reduce the risk factor of further heart diseases and other vital problems. Machine Learning is the one of the recent developments which is very helpful in clinical care guidelines. The PIMA Indian Diabetes dataset is used to predict Type-2 Diabetes Mellitus based on certain clinical diagnostic measurements for females. In this paper, we proposed a framework for prediction of Diabetes Mellitus using Optimised Gradient Descent Boosting Classifier. The performance metrices such as Accuracy, Sensitivity, Specificity and F1 scores are chosen. These experiments are conducted for PIMA Indian Diabetes Dataset and the proposed classifier yields 94.5 %, 92.4 %, 96 % and 92 % for the values in Accuracy, Sensitivity, specificity and F1 score and also compared with other classifier's like K-NN, QDA, SVM and etc. © 2022 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Multidimensional binary layered model for census prediction using machine learning techniques

引用

Asian Journal of Civil engineering 2024年第6期25卷 4877-4891页

作者： El-Salhi, Subhieh Albqowr, Hala Mahmoud Saleh Igried, Bashar Awwad, Sari Dittakan, Kwankamon Department of Computer Information System The Hashemite University Zarqa 13133 Jordan Surveying and Geomatics Engineering Department Al-Balqa Applied University Al-Salt 19117 Jordan Department of Computer Science and Its Applications The Hashemite University Zarqa 13133 Jordan College of Computing Prince of Songkla University Phuket 83120 Thailand

The development of the resource allocation process is based on essential factors, such as population size, which can be considered one of the most critical ones. Estimating the population size for a particular region, especially in developing countries, indicates the government’s authority to invest and utilize the resources efficiently. As a result, forecasting population size is one of the most essential requirements that guide the entire development process and, as a result, affects human well-being. This paper presents a novel technique for census seven prediction of a specific region of interest in the context of satellite images. The Multidimensional Binary Layered Model (MDBL) is a representation technique founded on identifying a given region of interest in terms of the geographical nature of the local surrounding regions. The MDBL is then employed to generate an "effective" classifier using different machine learning techniques such as the Convolutional Neural Network (CNN), k-nearest Neighbor (k-NN), and Support Vector Machine (SVM). The Black Widow Optimization (BWO) method has been used to maximize performance and provide the best machine learning model. In order to produce the best prediction model, this optimization method ensures the models are tuned with the most appropriate hyperparameters. To this end, Al-Karak City, in Jordan, has been used as a case study to evaluate the proposed model. The evaluation of the classifiers has been reported in terms of the accuracy and the Area Under Curve (AUC) measurements. The CNN achieved the “best” overall AUC result of 88%, indicating the significant impact of using the proposed MDBL to generate an accurate, effective classifier. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Binary layered model Black widow optimization (BWO) Census prediction Classification CNN Machine learning

来源：评论

学校读者我要写书评

暂无评论

Integrating Random Forest and Support Vector Regression Models for Optimized Energy Consumption Evaluation in Cloud Computing Data Centers 3

Integrating Random Forest and Support Vector Regression Mode...

引用

3rd International Conference on Technological Advancements in Computational sciences, ICTACS 2023

作者： Shaik, Nazeer Kumar, B. Vinoth Bhati, Anita Kumar, Sandeep Singh, Jagendra Sahu, Dinesh Prasad SRIT-Autonomous Department of Computer Science Engineering Anantapur India Ksr Institute for Engineering and Technology Dept. of Electronics and Communication Engineering Tiruchengode India Jecrc University Department of Computer Applications Jaipur India Raj Kumar Goel Institute of Technology Department of Information Technology Ghaziabad India School of Computer Science Engineering and Technology Bennett University Greater Noida India

ISBN: (纸本)9798350342338

This study proposes a novel approach for energy consumption evaluation in cloud computing data centers. The immense energy consumption of these data centers presents significant environmental and economic challenges. Traditional evaluation methods often fail to provide accurate estimations due to the complex dynamics of cloud computing environments. The research introduces an integrated model, combining Random Forest Regression and Support Vector Regression, along with a Gradient Boosting Regressor for iterative training of regression parameters. We measure the model's performance using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), replacing traditional relative deviation measures. The proposed approach aims to provide more accurate and efficient energy consumption evaluations, offering potential benefits in energy management, operational costs reduction, and minimizing environmental impact. © 2023 IEEE.

关键词： Cloud Computing Energy Consumption Evaluation Gradient Boosting Regressor Random Forest Regression Support Vector Regression

来源：评论

学校读者我要写书评

暂无评论

A Review on Collision Avoidance Application in Automotive Ad Hoc Networks Employing a Novel Source-Based Ant Colony Optimization Routing Protocol Using a Cross-Layer Approach

A Review on Collision Avoidance Application in Automotive Ad...

引用

2023 International Conference on Circuit Power and Computing Technologies, ICCPCT 2023

作者： Lekshmi, V. Pramila, R Suji Symon, Tibbie Pon Noorul Islam Centre for Higher Education Department of Computer Applications Tamil Nadu Thackalay India Mar Baselios Institute of Technology and Science Department of Computer Science and Engineering Kerala India Noorul Islam Centre for Higher Education Department of Electrical and Electronics Engineering Tamil Nadu Thackalay India

ISBN: (纸本)9798350333244

The term 'Vehicle Ad hoc Network' (VANET) refers to a system in which a collection of non-stationary or stationary vehicles share a wireless connection. Until recently, VANETs were primarily used to improve the safety and convenience of driving. Both the AntHocNet method and the Ant based Routing Algorithm (ARA) rely on ACO. It is a combinational method that combines proactive route maintenance with a reactive setup process for route finding. Its objective is to preserve information about current routes and identify new ones. The term 'Ant Colony Optimization' (ACO) refers to a population-based mathematical heuristic that's capable of providing approximate solutions to difficult optimization problems. The aim of ACO is to solve an optimization problem by sending out a colony of virtual ants to find an optimal solution. Ant colony optimization is a probabilistic technique for finding optimum paths. In this paper a detailed literature review for VANET for collision avoidance application based on Ant colony optimization is surveyed. © 2023 IEEE.

关键词： Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

Deep Neural Network Deception Using A Single Pixel Assault 6

Deep Neural Network Deception Using A Single Pixel Assault

引用

6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Singh, Digvijay Yadav, Annu Arora, Rishabh Ravivarman, G. Vijay, S. Arul Antran Sharma, Y.K. School of Engineering and Computer Dev Bhoomi Uttarakhand University Uttarakhand India School of Computer Science and Applications IIMT University Meerut India K. R. Mangalam University Department of Civil Engineering Gurugram India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore India Karpagam College of Engineering Department of Computer Science Engineering Coimbatore India Computer Engineering Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798350304480

Previous studies have shown that Deep Neural Networks'(DNN's) outputs is not consistent and very susceptible to inputs vectors perturbations of any size, and as a result, a number of techniques have been developed for creating effective perturbations on the connections. In this research, we offer a novel divergent transformation method for visually computing very small adversarial perturbations (few-pixel attacks). It works with a wider range of DNN different classifiers and calls for far less adverse data. The findings indicate that, on average, 73.8percent of total of the test photos can be modified to create hostile images by changing just one pixel. Additionally, it is well recognized that analyzing the DNN resilience problem can provide crucial hints for comprehending the geometric characteristics of the DNN decision. a high-dimensional inputs area map. In contrast to earlier research, the outcomes of performing few-pixel attack give quantifiable data and analyses to the geometric knowledge, Genetic algorithm (GA) © 2023 IEEE.

关键词： DNN geometric hostile images Pixel

来源：评论

学校读者我要写书评

暂无评论

A CNN-Based Framework for Detection and Recognition of Objects Using Transfer Learning: A Case Study on Flower Recognition 1

A CNN-Based Framework for Detection and Recognition of Objec...

引用

2023 1st DMIHER International Conference on Artificial Intelligence in Education and Industry 4.0, IDICAIEI 2023

作者： Tiwari, Shivam Sharma, Vikrant Rathore, Yogesh Singh Gandhi, Parul Srivastava, Durgesh Sharda University Department of Computer Science & Engineering Greater Noida India Graphic Era Hill University Computer Science and Engineering Dehradun India Sharda University Computer Science and Application UP Greater Noida India Manav Rachna International Institute of Research and Studies Department of Computer Applications Haryana Faridabad India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India

ISBN: (纸本)9798350338423

The vast variety of floral species present on Earth poses a considerable challenge in memorizing their individual names. Acquiring knowledge about specific flower types inhabiting diverse environments like forests, mountains, and dense regions becomes crucial for their recognition and differentiation. Consequently, the development of a technique for accurately determining flower categories becomes imperative. The task of distinguishing and categorizing a particular blossom amidst the extensive array of floral species presents a formidable task. Hence, the automation of flower species identification has been a subject of extensive research interest. This research domain is characterized by the utilization of features extracted from floral images in conjunction with specialized algorithms aimed at classifying flower species. A prominent aspect of these endeavors is the employment of three widely recognized flower image datasets. The present study constitutes a comprehensive survey of various methodologies proposed by diverse researchers with the objective of accomplishing precise identification of flower species. © 2023 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

A Way to Design Fog Computing Model for 5G Network using Vanet 4

A Way to Design Fog Computing Model for 5G Network using Van...

引用

4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Maruthamuthu, R. Patel, Neeraj Yawanikha, T. Jayasree, S. Alsalami, Zaid Subbarao, S.P.V. Madanapalle Institute of Technology & Science Computer Applications Andhrapradesh Madanapalle India Ies Institute of Technology and Management Ies University Computer Science & Engineering Department M.P Bhopal India Prince Shri Venkateshwara Padmavathy Engineering College India Karpagam Institute of Technology Department of Information Technology Coimbatore641105 India The Islamic University of Babylon College of Technical Engineering Department of Computers Techniques Engineering Babylon Iraq Sreenidhi Institute of Science and Technology Department of Electronics and Communication Engineering Hyderabad India

ISBN: (纸本)9798350360165

Intelligent cities rely heavily on smart automobiles, providing portable computing as well as communication capabilities via a wireless link. By Mobile spontaneous groups, computer fog acts as a middleman between automobiles and the web, giving them access to storing, retrieving and abilities to network. With VANET, which stands processing the request to the vehicle takes fewer minutes since it is a latency-sensitive tech. The most well-known problems with fogged and VANETs are congestion and delays. In this study, we created a priority-based fogged approach to intelligent metro automobile journeys, which lowers fog compute time and postpone, to address such issues. 5G localised Multi-Access edge information workstations was also used to enhance the computer fog infrastructures in meeting timely and The caliber of Level standards, which has greatly reduced the latency and wait. In lieu of the study conducted utilizing simply a web-based design, we achieved a 20% reduction in data time. Additionally, we achieved a 35% reduction in CPU usage as compared to the use of a public cloud platform. © 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

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：