检索结果-内蒙古大学图书馆

2nd international Conference on Edge Computing and Applications, iCECAA 2023

作者： Gandhi, Mohd. Asif Karimli Maharram, Vusal Raja, G. sellapaandi, s.P. Rathor, Ketan singh, Kamlesh Anjuman-I-Islam's Kalsekar Technical Campus Department of Mechanical Engineering Maharashtra Panvel India Strategic Development Center Western Caspian University Azerbaijan Strategic Development Center Azerbaijan State University of Economics Azerbaijan Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram India Psna College of Engineering and Technology Department of Ece Tamilnadu Dindigul India Pmo Gyan Sys Inc Maharashtra India Graphic Era Hill University Department of Computer Science and Engineering Dehradun Campus Dehradun India

ISBN: (纸本)9798350347579

intelligent robots, intelligent mobiles, intelligent stores, and so on are just a few of the areas where computer-aided ergonomics is being put to use. Convenience stores (CVs) are adapting to a new era of competition by offering a wider variety of products and services than ever before, such as daily fresh meals, a cafe, ticketing, and a grocery. therefore, it is becoming increasingly difficult to estimate daily sales of' fresh commodities due to the impact of both internal and external factors. in the long run, a trustworthy sales-forecasting system is going to be critical for enhancing corporate plans and gaining an edge over the competition. in today's internet age, data production has reached unprecedented levels, well beyond what any single human being can comprehend. this has led to the development of a plethora of machine learning methods. in this proposed approach various machine learning methods are explored for predicting store's sales and evaluate them to find the one that works best for the specific scenario. training times are reduced and data quality is enhanced with the help of Normalization in the proposed approach. K-Means is a popular feature selection clustering algorithm. Fuzzy Pruning Ls-sVM is used in the suggested method for training the model. the proposed model has superior performance on sVM and CNN. © 2023 iEEE.

关键词： support vector machines

来源：评论

学校读者我要写书评

暂无评论

A technique Based on Ensemble Machine Learning for the Analysis of Electronic Nose signals 3

A Technique Based on Ensemble Machine Learning for The Analy...

引用

3rd international Conference on Advance Computing and innovative technologies in engineering, iCACitE 2023

作者： taneja, Amit Rajamani, santhosh Kumar shekhawat, Deepika Chanti, Yerrolla Joshi, Kapil Garg, Ashish Chandigarh University AIT-CSE India MAEER MIT Pune's MIMER Medical College and Dr BSTR Hospital TalegaonDabhade Department of E.N.T Maharashtra Pune India Manipal University Department of Computer Science & Engineering Rajasthan Jaipur India SR University School of Computer Science and Artificial Intelligent Telangana Warangal India Uttaranchal University Uttaranchal Institute of Technology India Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350399264

Numerous applications have been documented for electronic nose (e-nose) devices, which are valued for their speed, affordability, and lack of invasiveness. the e-nose scheme is a useful instrument for analyzing volatile chemicals as a distinct 'fingerprint,' especially in the meat industry. the pattern identification algorithm's capacity to decode e-nose signals is crucial to the e-nose system's effectiveness in a wide variety of uses. However, positive results using ensemble approaches have been reported in a number of data types. in this study, an ensemble learning strategy is proposed for e-nose signal analysis, particularly for evaluating beef quality. Not only are learning algorithms and sensor array optimization using ensemble approaches. Ensemble FsA is created by combining three filter-based feature selection algorithms (FsAs) - reliefF, chi-square, and Gini index - for sensor array optimization. When using a single FsA on a collection of homogenous e-nose data for beef quality monitoring, it is common for the results to be inconsistent or unexpected. in addition, multi-class regression and categorization problems are handled by using ensemble learning techniques. We use bagging and boosting algorithms, shown here by Random Forest (RF) and Adaboost. Both a support vector machine (sVM) and a decision tree are used as independent learners, and their results are compared to those of the ensemble. Experiments show that our ensemble method is effective and generalizable for e-nose signal processing. Optimized sensor combination using filter-based FsA consistently outperforms previous methods in both classification and regression. Additionally, despite using a reduced sensor complement, Adaboost as a boosting algorithm yields the highest quality prediction. © 2023 iEEE.

关键词： support vector machines

来源：评论

学校读者我要写书评

暂无评论

Detection of Driver Drowsiness Using Adaptive Eye Characteristic Ratio for Enhanced Road safety

引用

iEEE Access 2025年 13卷 84313-84328页

作者： Lamba, Puneet singh Jain, Rimjhim Khan, shakir Alanazi, sultan M. Jain, Achin Zamani, Abu taha Panwar, Arvind Abdallah, Alsadig Mohammed Adam University of Delhi S. G. T. B. Khalsa College Department of Computer Science New Delhi110007 India University of North Carolina at Charlotte CharlotteNC28223 United States College of Computer and Information Sciences Information Technology Department Riyadh11432 Saudi Arabia Northern Border University Faculty of Science Department of Computer Science Arar73213 Saudi Arabia Bharati Vidyapeeth’s College of Engineering Department of Information Technology New Delhi110063 India Galgotias University School of Computer Science and Engineering Uttar Pradesh Greater Noida203201 India

Every year, countless people lose their lives in serious car accidents, and drowsy driving is a major cause. However, because the earliest indications of exhaustion can be identified before a dangerous scenario develops, the detection and signaling of driver drowsiness are ongoing research topics. this study presents a real-time detection system designed to detect driver’s sleep and deliver timely warnings. the mechanism employs an eye monitoring system that uses eye feature points to detect whether a driver’s eye is tired and delivers an alert if the driver is drowsy. the proposed work recognizes the driver’s face by collecting facial landmarks and gives warning to the driver to avoid crashes by performing adaptive thresholding and drowsiness diagnoses based on Eye Characteristic Ratio. the empirical results show that using random forest classifier, decision tree classifier, KNN classifier, and multinomial classifier, the proposed model achieved 90.48%, 89.44%, 88.63%, and 84.32% accuracy, respectively. © 2013 iEEE.

关键词： Highway accidents

来源：评论

学校读者我要写书评

暂无评论

Enhancing iot-Based smart Farming security with a Hybrid GRU intrusion Detection system

Enhancing IoT-Based Smart Farming Security with a Hybrid GRU...

引用

interdisciplinary Approaches in technology and Management for social innovation (i.t.si), iEEE Conference on

作者： sivakumar Nagarajan s. Vijay s. Karthi RVs Praveen Ramesh Vijaya Babu K Burri Naresh Technical Architect I & I Software Inc Bethlehem USA Department of Data Science Sacred Heart College (Autonomous) Tamilnadu India Department of Computer Science and Engineering V.S.B. Engineering College Karur Tamilnadu India Director Digital Engineering & Assurance LTIMindtree Limited Hyderabad Telangana India SRKR Engineering College Bhimavaram Andhra Pradesh India Department of CSE - Cyber Security CVR College of Engineering Hyderabad Telangana India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

the growing use of iot devices in smart agriculture makes the industry vulnerable to several cyber risks. this study introduces an innovative hybrid intrusion Detection system (iDs) utilising Gated Recurrent Units (GRUs) to improve the security of iot-enabled smart agriculture. compared to current LstM and CNN-based intrusion detection systems, the proposed model effectively incorporates sequential data dependencies, hence minimising false positives and enhancing detection accuracy. Experimental findings indicate that the suggested model surpasses conventional techniques, with an accuracy of 97.5%, an F1 score of 0.96, and a recall of 0.97. these developments create a strong, efficient, and scalable solution for safeguarding iot-based agricultural systems from cyber-attacks.

关键词： smart agriculture technological innovation Accuracy Computational modeling scalability intrusion detection internet of things Object recognition Protection Long short term memory

来源：评论

学校读者我要写书评

暂无评论

Cloud-Based Returns Management solutions in Logistics Using K-Nearest Neighbors Approach

Cloud-Based Returns Management Solutions in Logistics Using ...

引用

intelligent Cyber Physical systems and internet of things (iCoiCi), international Conference on

作者： t. G. Arul Flora J. Gnana Jeslin subramani Roychoudri Kuppan Vijayalakshmi Geetha Ponnaian s. Velmurugan Department of Electronics and Communication Engineering KCG College of Technology Chennai Tamil Nadu India Department of Computer Science and Engineering RMK College of Engineering and Technology Chennai Tamil Nadu India Department of Computer Science and Engineering Usha Rama College of Engineering and Technology Vijayawada Andhra Pradesh India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tami Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Electronics and Communication Engineering T.J.S. Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798331540661

ISBN: (纸本)9798331540678

Efficiently handling returns is one of the specific issues for the e-commerce logistics providers. Using the K-Nearest Neighbors (KNN) method, this research proposes a cloud-based returns management system that may improve the efficiency of managing return procedures. traditional methods of returns management often include human intervention in the form of sorting and decision-making, which may result in unnecessary delays and higher expenses. this technology automates decision-making based on similarity criteria between returned products and current inventory, streamlining the returns process. the proposed method effectively assigns returned items to the most appropriate disposition, whether it restocks, refurbishing, or disposal, by using the scalability and computing capacity of cloud infrastructure. Cloud computing also allows for real-time data processing, which speeds up decision-making and makes operations more agile in general. the system may improve e-commerce logistics returns management via a case study and simulation analysis, demonstrating its efficacy and efficiency. it helps move the needle on how e-commerce operations use cloud computing and machine learning, which in turn enhances competitiveness and consumer happiness in the ever-changing online marketplace.

关键词： Cloud computing Machine learning algorithms Accuracy supply chain management Decision making Nearest neighbor methods Electronic commerce tuning Logistics sorting

来源：评论

学校读者我要写书评

暂无评论

two-stage Deep Learning - Youtube Video Recommendation Process

Two-Stage Deep Learning - YouTube Video Recommendation Proce...

引用

New Frontiers in Communication, Automation, Management and security (iCCAMs), international Conference on

作者： Cheepu Balakrishna D. sharada Mani A Basi Reddy P. Chandrakanth R.senthamil selvan Department of Computer Science and Engineering Saispurthi Institute Of Technology Sathupally Mandal India Department of Computer Science and Engineering QIS college of Engineering and Technology Ongole India Department of Computer Science and Engineering School of Computing Mohan Babu University Tirupati India Department of Computer Science and Engineering N.B.K.R.I.S.T Vidyanagar Kota India Department of Electronics and Communication Engineering Annamacharya Institute of Technology and Sciences Tirupati India

ISBN: (数字)9798350317060

ISBN: (纸本)9798350317077

Youtube is one of the most widely used and technically advanced commercial systems of recommendations. it provides an overview of the system and highlights the remarkable gains in efficiency made possible by deep learning. this research uses the traditional “two-stage” framework for separating and retrieving information. First, a profound model for generating candidates ought to be described, and then a model for ranking candidates ought to be outlined, and both of these should be done in that order. the order in which these two tasks ought to be completed is important. in addition, it offers instruction that can be put into practice as well as valuable insights that have been gleaned from the process of developing, iterating, and managing a large-scale recommendation system that has a significant impact on the experience of the user.

关键词： Deep learning training Video on demand Artificial neural networks Watches Web sites security

来源：评论

学校读者我要写书评

暂无评论

smart Grid Using Power internet of things Architecture 5

Smart Grid Using Power Internet of Things Architecture

引用

5th international Conference on Contemporary Computing and informatics, iC3i 2022

作者： Moorthy, C.Balakrishna sai thrinath, B.V. Palanivel, Manikannan Pavani, K. Kumar, Pankaj Kumar Jha, Manikesh University of Technology and Applied Sciences Engineering Department Salalah Oman Mohan Babu University Sree Vidyanikethan Engineering College Department of EEE Tirupati India A.K.T Memoria College of Engineering and Teachnology Kallakurichi India Aditya Engineering College Dept of ECE Surampalem India Institute Graphic Era Deemed to Be University Department Computer Science and Engineerin Dehradun India St.Martin's Engineering College Kompally Secunderabad India

ISBN: (纸本)9798350398267

the internet of things (iot) is an innovation that has acquired far reaching acknowledgment and is utilized to associate typical items to the internet to give usability and different functionalities. then again, the savvy Grid (sG) is characterized as the power grid incorporated with an enormous organization of data and correspondences innovation (iCt). the sG is the blend of billions of brilliant articles, like shrewd machines and savvy meters, among different kinds of brilliant items, like actuators and sensors. this article is a theoretical of a shrewd grid innovation that was applied to an environmentally friendly power source and depended on the internet of things. the ongoing system of modernizing how power is circulated includes various parts, one of the most significant of which is the brilliant grid, which incorporates computerized innovation and information the board techniques. sun based energy is being considered as a potential sustainable power source;subsequently a photovoltaic cell will be used. this framework is comprised of various huge subsystems, the most significant of which are power age and capacity, power observing and charging, and power control and the board through the usage of iot. © 2022 iEEE.

关键词： internet of things

来源：评论

学校读者我要写书评

暂无评论

integrating Dominant and Binocular Vision in Eye-Hand Coordination: A systematic Review

Integrating Dominant and Binocular Vision in Eye-Hand Coordi...

引用

international Conference on ent Computing and Control systems (iCiCCs)

作者： Reeva Kansagara Diya Doshi Misa Fumakiya Janvi Gevariya Milind shah Dweepna Garg Department of Computer Engineering Devang Patel Institute of Advance Technology & Research (DEPSTAR) Faculty of Technology & Engineering (FTE) Charotar University of Science & Technology (CHARUSAT) Changa India Department of Computer Engineering Sardar Vallabhbhai Patel Institute of Technology (S.V.I.T) Vasad Gujarat India

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

Assessing eye-hand coordination is crucial for understanding and improving the synchronization between visual perception and manual actions. Various studies highlight the significance of this coordination in a wide range of activities. Eye-hand coordination plays a critical role in tasks such as accurately drawing patterns, catching objects, bouncing a ball, playing video games, maneuvering through mazes, and operating a computer mouse. this review thorough into the concept of eye-hand coordination, its practical applications, the connection between neck issues and coordination, and the effectiveness of exercises aimed at enhancing these skills. the review ultimately emphasizes the critical role of eye-hand coordination in performing tasks that require precision, advocating for specialized assessments and improvement techniques.

关键词： Hands Visualization Video games Manuals Motors Control systems Neck synchronization Visual perception systematic literature review

来源：评论

学校读者我要写书评

暂无评论

Assessment of deep neural network for prediction of chronic kidney disease

Assessment of deep neural network for prediction of chronic ...

引用

international Conference on Computing and Networking technology (iCCNt)

作者： Neetu Gupta Hemant Kumar Gupta s. Vaishali Bobbala sreedevi Department of Computer Science & Engineering Manipal University Jaipur Rajasthan India Department of Electronics & Communication Engineering Arya College of Engineering & I.T. Jaipur Rajasthan India Department of Electronics & Communication Engineering Vaagdevi College of Engineering Warangal Telangana India

this study uses deep learning techniques to detect chronic kidney disease at earlier stage to aid in its prevention. Disorders that affect the kidney's natural function are referred to as kidney diseases. this research recommends using a perceptron classifier with multiple layers classifier that is based on deep neural networks to identify CKD in patients. in order to diagnose chronic kidney disease, a database of 400 individuals with 25 attributes was employed. For the tests, the means of the respective attributes were used to replace each missing value in the original data set. the deep neural network's optimal parameters were then produced by fine-tuning the parameters and running several trials. in this research, A deep neural network is designed and developed. the performance of proposed model is compared with various cutting-edge machine learning techniques. Experiments show that the proposed model performs with 99.85% testing accuracy in classification tasks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Approach for integrating Neo4j in a Dual-Model Database system

An Approach for Integrating Neo4j in a Dual-Model Database S...

引用

Emerging trends in engineering and Medical sciences (iCEtEMs), international Conference on

作者： Harsha Vyawahare sarika Khandelwal Prasanna Palsodkar seema Rathod sheetal Dhande Pradnya Vikhar Prachi Palsodkar Computer Science & Engg. Sipna C.O.E.T. Amravati India Computer Science & Engg. G H Raisoni College of Engineering Nagpur India Department of Electronics Engg. Yeshwantrao Chavan College of Engineering Nagpur India Computer Engg. KCES'S COEM Jalgaon India

ISBN: (数字)9798331529352

ISBN: (纸本)9798331529390

Relational (sQL) databases dominate structured data management, while NosQL databases handle unstructured data. Cloud computing and big data environments are increasing data volumes day by day. Graph databases are gaining popularity for managing complex relationships, especially in social networks. traditional databases struggle with interconnected data, leading to the development of hybrid sQL/Graph databases. this paper proposes a new hybrid database design based on data structuredness, showing improved performance over traditional sQL databases in certain scenarios.

关键词： Bridges Cloud computing Databases social networking (online) NosQL databases Relational databases Big Data Market research Data models

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：