检索结果-内蒙古大学图书馆

IEEE Integrated STEM Education Conference (ISEC)

作者： Avimanyou Vatsa Dohyun Lee Benen Sullivan Daniel Hogan Amishi Mittal Elise R. Morton Harald F. Parzer Department of Computer Science Director of Deep Chain (DC) Lab Gildart Haase School of Computer Sciences&Engineering Fairleigh Dickinson University Teaneck NJ Intern in Deep Chain (DC) Lab Fairleigh Dickinson University and a Bergen County Academy (BCA) student Hackensack NJ Department of Biological Sciences Fairleigh Dickinson University NJ

The State of the World’s Birds 2022 report estimated a decline in 30% of the world’s birds since 1970, largely attributed to habitat loss, climate change, and other anthropogenic factors [1, 3]. Chimney swifts are aerial insectivores that forage during the day and commonly roost in large colonies inside hollow vertical human-made structures such as chimneys. Signaled by sunset, large groups of this species, sometimes comprised of thousands of individuals, exhibit an impressive display of coordinated entry into their roosting sites. Despite this striking behavior and close relationship with humans, the factors influencing this collective behavior are poorly understood. To understand how anthropogenic and environmental factors influence the population health of this (and other species), reliable methods for counting individuals are required. The purpose of this study is to develop an automated method to accurately count the number of birds over a given period at the roosting *** understand the behavior of colonially roosting species such as the Chimney swift, we proposed a methodology in which we collect and analyze videos of birds at roosting sites to understand their behaviors. The proposed approach consists of two steps: physically gathering the video with cameras perched at optimal locations [2] and utilizing video segmentation algorithms to count the number of birds at roosting sites over *** final goal of this research is to build useful data for ecologists that can be utilized to fill critical gaps in knowledge. To achieve this, the number of birds counted over time will be analyzed with ambient weather datasets at different geographical locations. Therefore, in this paper, we use four video segmentation algorithms to detect and track the movement of birds, count the number of birds at certain intervals, and then compare the performance of the algorithms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Human Activity Recognition: Fight Detection using Long term Recurrent Convolutional Network (LRCN)

Human Activity Recognition: Fight Detection using Long term ...

引用

Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), International Conference on

作者： Ngrddy Jhnvi S.K. Bhrdwj Ajay Sharma Shamneesh Sharma Ankur Sodhi Saikat Gochhait School of Computer Science and Engineering Lovely Professional University Phagwara Punjab India Delivery and Student Success upGrad Education Private Limited Bangalore Karnataka India Enterprise Businees and Career Services upGrad Education Private Limited Bangalore Karnataka India Symbiosis Institute of Digital and Telecom Management Constituent of Symbiosis International Deemed University Pune India

ISBN: (数字)9798350368710

ISBN: (纸本)9798350368727

Human Activity Recognition for Fight Detection is an important research domain aimed at automatically identifying patterns indicative of physical altercations. Leveraging deep learning models like CNNs and RNNs, this approach extracts features from video frames to recognize fight-related behavioural patterns. The primary objective is to develop a machine learning model capable of autonomously detecting instances of fights in video footage, using techniques such as the Long-term Recurrent Convolutional Network (LRCN). Training involves a comprehensive dataset encompassing examples of both fights and non-fight activities, with model performance evaluated using standard metrics. Each frame undergoes individual analysis by the model to predict the presence of any indications of a fight. The model predicts the action with an accuracy of 98.03% and the movements given as input can be categorized as fights or no fights.

关键词： Training Measurement Industries Predictive models Feature extraction Pattern recognition Convolutional neural networks Object recognition Human activity recognition Standards

来源：评论

学校读者我要写书评

暂无评论

Simplified Framework for Diagnosis Brain Disease Using Functional Connectivity

Simplified Framework for Diagnosis Brain Disease Using Funct...

引用

Communication & Computing (WCONF), World Conference on

作者： T. Swarnalatha B. Supraja Akhila Akula Raaid Alubady K Saikumar Patakottu Prasadareddy Department of CSE PBR Visvodaya Institute Of Technology And Science Kavali Department of CSE GNITC Hyderabad Department of Electronics and Communication Engineering MLR Institute of Technology Hyderabad Telangana India Technical Engineering College Al-Ayen University Thi-Qar Iraq College of Information Networks University of Babylon Babylon Iraq Computer Science Malla Reddy University Malla Reddy University School of Engineering Maisammaguda Dulapally Hyderabad Telangana Dept. of ECE Student MVGR College of Engineering Vijayaram Nagar campus Chintalavalasa Vizianagaram Andhra Pradesh

ISBN: (数字)9798350395327

ISBN: (纸本)9798350395334

Diagnosing brain infections is another region where artificial intelligence and neuroscience research meet. Functional connectivity (FC) examination has turned into the standard method for checking out fMRI information. The quantitative investigation of functional magnetic resonance imaging (fMRI) information might uncover significant variables that assistance in clinical assessment. Then again, the greater part of the review done in the past has zeroed in on placing mind sicknesses into bunches in light of low-request FC characteristics and has disregarded the conceivable significance of high-request utilitarian connections between cerebrum regions. To protect this issue, physicists formulated an unusual MFC a multi-level fusion classification paradigm for recognizing mental disorders. To begin, they built a model using a deep neural network (DNN) to collect and formulate vital fundamental portrayals for the depressed-request and extreme-request FC designs we fashioned. During the preparation of the DNN model, there were both uncontrolled and directed learning steps. During the managed calibrating, model learning was added to make the element portrayal more reduced inside each class and simpler to distinguish from different classes. Then, at that point, to characterize mind illnesses, we consolidated the theoretical staggered FC highlights we had learned and utilized various leveled stacking learning techniques to prepare a troupe classifier. Deliberate tests were finished with two genuine, enormous-scope fMRI datasets. The recommended MFC model worked effectively in ordering information for various preprocessing processes, different mind parcellations, and different cross-approval techniques, which shows that it works and can be utilized in a wide range of circumstances. By and large, this work gives an effective method for consolidating significant low-request and high-request FC examples to make it more straightforward to order mind sicknesses.

关键词： Neuroscience Reviews Mental disorders Stacking Cerebrum Artificial neural networks Functional magnetic resonance imaging Standards Medical diagnostic imaging Diseases

来源：评论

学校读者我要写书评

暂无评论

Improving the Cellular Characteristics of Aluminum Foam for Maximum Sound Absorption Coefficient Using Genetic Algorithm

引用

Sound & Vibration 2021年第2期55卷 117-130页

作者： Mohammad Javad Jafari Mohsen Niknam Sharak Ali Khavanin Touraj Ebadzadeh Mahmood Fazlali Rohollah Fallah Madvari Department of Occupational Health Engineering School of Public Health and SafetyShahid Beheshti University of Medical SciencesTehranIran Mechanical Engineering Department of Mechanical EngineeringUniversity of BirjandBirjandIran Department of Occupational Health Engineering Faculty of Medical SciencesTarbiat Modares UniversityTehranIran Department of Ceramics Materials and Energy Research CenterAlborzIran Department of Data and Computer Science Faculty of Mathematical SciencesShahid Beheshti UniversityTehranIran Student Research Committee Department of Occupational Health EngineeringSchool of Public Health and SafetyShahid Beheshti University of Medical SciencesTehranIran Department of Occupational Health School of Public HealthShahid Sadoughi University of Medical SciencesYazdIran

Fabricating of metal foams with desired morphological parameters including pore size,porosity and pore opening is possible now using sintering ***,if it is possible to determine the morphology of metal foam to absorb sound at a given frequency,and then fabricate it through sintering,it is expected to have optimized metal foams for the best sound *** sound absorption models such as Lu model describe the relationship between morphological parameters and the sound absorption *** this study,the Lu model was used to optimize the morphological parameters of aluminum metal foam for the best sound absorption *** this purpose,the Lu model was numerically solved using written codes in MATLAB *** validating the proposed codes with benchmark data,the genetic algorithm(GA)was applied to optimize the affecting morphological parameters on the sound absorption *** optimization was carried out for the thicknesses of 5 mm to 40 mm at the sound frequency range of 250 Hz–8000 *** optimized parameters ranged from 50%to 95%for porosity,0.1 mm to 4.5 mm for pore size,and 0.07 mm to 0.6 mm for pore opening *** result of this study was applied to fabricate the desired aluminum metal foams for the best sound *** novel approach applied in this study,is expected to be successfully applied in for best sound absorption in desired frequencies.

关键词： Acoustic model Genetic Algorithm(GA) metal foam optimization Sound Absorption Coefficient(SAC)

来源：评论

学校读者我要写书评

暂无评论

An AI-Centred Adaptive Cognitive Network Traffic Modelling & Measurement Technique For EIS

An AI-Centred Adaptive Cognitive Network Traffic Modelling &...

引用

Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： L. Bharathi Nimish H. Vasoya Lavish Kansal Anita Gehlot Bajila Swathi Suyeb Ahmed Khan Department of Electronics and Communication Engineering Ramachandra College of Engineering Eluru Andhra Pradesh Department of Student Startup Children's University Gandhinagar Gujarat Lovely Professional University Phagwara Uttaranchal Institute of Technology Uttaranchal University India School of Computer Science and Artificial Intelligence SR University Warangal Telangana India Baba Kuma Singh Ji Engineering College Hoshiar Nagar Amritsar

The IoT is the foundation of the Enterprise Information System (EIS), which collects a lot of business information. For EIS, timely, accurate data analysis & transfer are crucial. For net management & traffic optimization in EIS, Network infrastructure traffic is crucial. Nevertheless, the needs for fine-grain traffic monitoring are in conflict with the monitoring overheads & precision. Long-standing promises of artificial intelligence (AI) include the ability to recognise the physical attributes of network activity & take appropriate steps in response. In order to decrease network monitoring overheads & increase measurement precision, we present an AI centred between light Adapt Measuring System (ALAMM) for SDN in this study. Initially, we simulate & forecast the network congestion information using AI. We suggest an adaptive strategy to choose the rate of traffic sample centred on the outcomes of traffic forecasting. Next, we instruct switching devices to evaluate the coarse-grain traffic of flow pattern & networks using the measuring primitives. In order to retrieve the Fine grained (FG) assessment & optimise the measured values, the matrices refilling & optimizing approach is finally suggested. Simulated outcomes demonstrate that our method can accurately and efficiently determine network activity.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Intelligent Headlights for Adapting Beam Patterns with Raspberry Pi and Convolutional Neural Networks

Intelligent Headlights for Adapting Beam Patterns with Raspb...

引用

Device Intelligence, Computing and Communication Technologies, (DICCT), International Conference on

作者： P. Maheswari S. Gowriswari S. Balasubramani A. Ramesh Babu Jijith NK S. Murugan Faculty of Management Studies SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Instrumentation and Communication Engineering Sri Sairam Engineering College Chennai Tamil Nadu India Department of Electronics and Communication Engineering R.M.D. Engineering College Chennai Tamil Nadu India School of Computer Applications Vidya Vikas Institute of Engineering and Technology Mysore Karnataka India DXN Holdings BHD and Doctoral Student Symbiosis International (Deemed University) Pune Maharashtra India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798350372847

ISBN: (纸本)9798350372854

This study uses intelligent headlights to improve car safety and economy. The suggested system uses Raspberry Pi and Convolutional Neural Networks (CNNs) to dynamically modify beam patterns to real-time ambient circumstances and context. The Raspberry Pi is a flexible computer platform, and CNNs automatically analyze sensor and video data to modify headlight beam patterns. A trained CNN model recognizes impending vehicles, pedestrians, and road conditions. By analyzing this information, the headlights dynamically optimize the beam pattern to maximize visibility and minimize road user glare. This flexibility improves road safety by optimizing lighting when required, minimizing driver fatigue, and enhancing response times. Raspberry Pi allows for a cost-effective and easy retrofitting of current vehicles with intelligent headlights. The system's scalability and adaptability make it suitable for many automotive applications, helping to construct smart and linked transportation systems. This discovery is a major step towards intelligent and adaptable lighting systems that improve vehicle safety and economy.

关键词： Training Adaptation models Lighting Streaming media Road safety Real-time systems Safety

来源：评论

学校读者我要写书评

暂无评论

DLIDAP: Experimental Evaluation of Drug Prediction System Using Modified Deep Learning Strategy with Intelligent Data Analyzer Principles

DLIDAP: Experimental Evaluation of Drug Prediction System Us...

引用

International Conference on Power, Energy, Control and Transmission Systems (ICPECTS)

作者： Muzeeb Khan Patan Nihar Ranjan Kar Ankita Chakraborty Jayendra Gopal Thatipudi Ramchandra Mahadik Solleti Phani Kumar Department of EEE Sagi Rama Krishnam Raju Engineering College Bhimavaram India School of Pharmacy Centurion University of Technology and Management Odisha India Lecturer Nowgong Polytechnic Assam India Student Department of Computer Science University of North Texas Bharati Vidyapeeth Deemed to be University Pune India Department of CSE Koneru Lakshmaiah Education Foundation Andhra Pradesh India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508852

Sentiment analysis, or the act of deducing an individual's view on a topic from their written expression, is a rapidly developing field within the larger field of natural language processing. Medication sentiment analysis has gained traction in recent years as researchers have discovered that classifying medicines by their efficacy through the evaluation of user reviews can help potential future consumers learn more about and make better judgments about a drug. To improve the precision with which pharmaceuticals may be classified according to their efficacy, the suggested research seeks for the keywords by tokenization and lemmatization. Such labeling can be useful in the fight against disease and the promotion of health and happiness. A drug review dataset was constructed using information from the UCI machine learning repository, subsequently four machine learning methods were implemented for binary categorization and one was utilized for multiclass categorization. The effectiveness of these four classifier algorithms has been examined by analyzing the results they produce. Between each of these techniques (Naive Bayes classifier, Random Forest, and Support Vector Classifier), the multilayer perceptron had been shown to have the greatest effectiveness, with an accuracy of 98%.

关键词： Drugs Sentiment analysis Machine learning algorithms Reviews Process control Prediction algorithms Vectors Tokenization Classification algorithms Random forests

来源：评论

学校读者我要写书评

暂无评论

Utilization of GPS Technology in the Maritime Sector on Motor Sailing Yachts 8

Utilization of GPS Technology in the Maritime Sector on Moto...

引用

8th International Seminar on Ocean and Coastal engineering, Environmental and Natural Disaster Management, ISOCEEN 2020

作者： Quintania, Melani Faturachman, Danny Husain, T. Pasupati, Bayu Taufik, Ahmad Management Department Faculty of Economy Darma Persada University Indonesia Marine Engineering Department Faculty of Marine Technology Darma Persada University Indonesia Information System Department School of Management and Computer Science STMIK Widuri Jakarta Indonesia Student of Doctoral Management YAI Persada University Indonesia

The utilization of technology only aims to be fast, precise, and accurate in each implementation and find a better solution at that time in several sectors. This study aims to identify the use of Global Positioning Technology (GPS) technology to track the position of the motor sailing yachts, specifically with the features used on a device or smart-phone during a trip or expedition. This research uses a type of applied research to solve problems that are faced clearly, and the results can be used as a basis for solving corrective steps. The results found that GPS-Technology on motor sailing yachts in "Pelayaran Rakyat"maritime can receive coordinates point and then send these coordinates to the vessel-tracking systems to determine the position of the motor sailing yachts between users. © Published under licence by IOP Publishing Ltd.

关键词： Yachts

来源：评论

学校读者我要写书评

暂无评论

A protection and assurance version for E-authorities Web Services based totally on Cloudlet computing

A protection and assurance version for E-authorities Web Ser...

引用

Technological Advancements and Innovations (ICTAI), International Conference on

作者： Devang Pratap Singh Subhadra Rajpoot Puneet Singh Student of Computer Science and Engineering Amity School Of Engineering and Technology Greater Noida India Amity School of Engineering and Technology Greater Noida India Faculty of Communications Engineering Military College of Telecommunication engineering Mhow Madhya Pradesh

ISBN: (纸本)9781665420884

In the present scenario, Web Administration and cloud computing are the spine architecture of any e-authorities application due to its interoperable and robust nature. Web benefits that are kept up in Cloud computing bring in easy consideration in examination and industry as far as getting the conveyed Web administrations. Consequently, gaining more trust between the imparted Web administrations which has been continuously getting more accessible for Web administrations shoppers, executives, and Web specialist organizations particularly the e-government administrations. Likewise, the proposed architecture is handling the issues that emerge when Web administration purchasers are speaking with most of the e-legislative Web administrations are furnished through a depended on Cloud-based system that is not bound via any administrative authority. Furthermore, Cloudlet computing is used to quantify the supplier of Web benefits' reliability and compliance to the distributed strategy using input from the Web administration customer.

关键词： Cloud computing Technological innovation Law Computational modeling Organizations computer architecture Service-oriented architecture

来源：评论

学校读者我要写书评

暂无评论

A Detailed Investigation on Various Cyber Security Models and their Comparisons with the Detailed Performance Analysis for the Application of IIOT Systems

A Detailed Investigation on Various Cyber Security Models an...

引用

Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Sumeet Gupta Ramakrishnan Raman Digvijay Singh Durgaprasad Gangodkar Aadesh Ajit Shinde Sumit Chauhan Core Cluster School of Business — SoB University of Petroleum & Energy Studies Dehradun Symbiosis Institute of Business Management Pune & Symbiosis International (Deemed University) Pune Maharashtra India Uttaranchal Institute of Technology Uttaranchal University Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Student Department of Cyber Security Symbiosis Skills and Professional University Pune Maharashtra (Computer Science) Management Education & Research Institute (Affiliated to GGSIP University New Delhi) New Delhi

Data security & Cyber security are sometimes used indiscriminately, however the first emphasizes that the exact point does have the potential to be a victim, whereas the second one addresses the function of the individual in the security process. Nevertheless, because it emphasizes the ethical component of civilization holistically, this debate of cyber security holds significant implications. Different architectures & designs have been proposed to handle the problem of cyber security. Additionally, it covers the ideas behind cyber security, including its organizational structure, human resources, and advice on how to safeguard private data on computers. This essay examines such designs, their shortcomings, as well as the prior methods employed to lessen these dangers. Additionally, the paper makes suggestions for additional study.

关键词：

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：