检索结果-内蒙古大学图书馆

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Neravetla, Anuteja Reddy Nomula, Varun Kumar Mohammed, Abdul Sajid Dhanasekaran, S. University of the Cumberlands Department of Information Technology KY United States Georgia Institue of Technology Department of Analytics/Industrial & Systems Engineering United States University of the Cumberlands Dept of School of Computer and Information Sciences KY United States Sri Eshwar College of engineering Department of Electronics and Communication engineering Coimbatore641202 India

ISBN: (纸本)9798350370249

Clever healthcare has turned out to be an increasingly more crucial assignment inside the area of healthcare due to its capability to decorate affected person care transport. Using AI-driven diagnostic decision guide systems is one way to permit more green, correct, and regular healthcare decisions. The structures use records from clinical information to growth predictive fashions that may be used to help the analysis of numerous illnesses. With an AI-driven choice guide device, healthcare carriers can successfully select capability diagnoses based on an affected person's medical information and other elements. The system also can offer hints for treatment plans primarily based on the analysis. AI-pushed structures can also provide actual-time remarks to clinicians, assisting them in improving accuracy and decreasing scientific mistakes. Via the use of AI-pushed preference help systems, healthcare carriers can optimize healthcare shipping, major to better affected person results. © 2024 IEEE.

关键词： Assignment Capability Healthcare Increasingly Primarily

来源：评论

学校读者我要写书评

暂无评论

Adaptive Deep Learning Model to Enhance Smart Greenhouse Agriculture

引用

computers, Materials & Continua 2023年第11期77卷 2545-2564页

作者： Medhat A.Tawfeek Nacim Yanes Leila Jamel Ghadah Aldehim Mahmood A.Mahmood Department of Computer Science College of Computer and Information SciencesJouf UniversityP.O.Box 72314SkakaSaudi Arabia Department of Computer Science Faculty of Computers and InformationMenoufia UniversityP.O.Box 6121890MenoufiaEgypt Department of Software Engineering College of Computer and Information SciencesJouf UniversityP.O.Box 72314SkakaSaudi Arabia RIADI Laboratory La Manouba UniversityP.O.Box2010ManoubaTunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems and Technology Faculty of Graduate Studies and ResearchCairo UniversityP.O.Box 3753450GizaEgypt

The trend towards smart greenhouses stems from various factors,including a lack of agricultural land area owing to population concentration and housing construction on agricultural land,as well as water *** study proposes building a full farming adaptation model that depends on current sensor readings and available datasets from different agricultural research *** proposed model uses a one-dimensional convolutional neural network(CNN)deep learning model to control the growth of strategic crops,including cucumber,pepper,tomato,and *** proposed model uses the Internet of Things(IoT)to collect data on agricultural operations and then uses this data to control and monitor these operations in real *** helps to ensure that crops are getting the right amount of fertilizer,water,light,and temperature,which can lead to improved yields and a reduced risk of crop *** dataset is based on data collected from expert farmers,the photovoltaic construction process,agricultural engineers,and research *** experimental results showed that the precision,recall,F1-measures,and accuracy of the one-dimensional CNN for the tested dataset were approximately 97.3%,98.2%,97.25%,and 97.56%,*** new smart greenhouse automation system was also evaluated on four crops with a high turnover *** system has been found to be highly effective in terms of crop productivity,temperature management and water conservation.

关键词： Greenhouse wireless sensor network deep learning Internet of Things strategic crops monitoring smart irrigation

来源：评论

学校读者我要写书评

暂无评论

SecureChainAI: Integrating Blockchain and Artificial Intelligence for Enhanced Security in IoT Environments 5

SecureChainAI: Integrating Blockchain and Artificial Intelli...

引用

5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Thamaraiselvi, K. Pushpalatha, A. Chidambarathanu, K. Wankhede, Jaishri P. Alagumuthukrishnan, S. Sarveshwaran, Velliangiri New Horizon College of Engineering Department of Information Science and Engineering Bangalore India Karpagam College of Engineering Department of Computer Science and Design Coimbatore India R.M.K. Engineering College Department of Computer Science and Business Systems Kavaraipettai India Cmr Institute of Technology Department of Computer Science and Engineering Hyderabad India Srm Institute of Science and Technology Department of Computational Intelligence Kattankulathur India

ISBN: (纸本)9798331504403

Internet of Things (IoT) systems develop with paramount importance for security in view of the increased deployment of IoT devices over critical sectors like healthcare, industry automation, and smart cities. The risk exposure of such systems is extremely high to potent cyber threats, including those that may result in data integrity and privacy issues and operational unreliability. Security in IoT systems has thus emerged through heterogeneous integration with blockchain and artificial intelligence models. This blockchain technology provides a decentralized, immutable ledger for secure data transactions. AI models, especially those designed by anomaly detection and prediction algorithms, can identify and mitigate cyber threats. In this paper, the authors propose the SecureChainAI model that synergistically integrates artificial intelligence algorithms with blockchain to safeguard IoT environments. The two core building blocks that will make this proposed model real are CaSNet and the EchoChain algorithm. The CaSNet model integrates LSTM, RNN, and GRU techniques with novelty detection for proficient attack prediction and detection using their peculiar capabilities in sequential data handling and the identification of novel attack patterns. The EchoChain algorithm puts blockchain technology into the IoT infrastructure to provide security in communication and integrity of the values. This makes the architecture lightweight, shifting computational loads to the collector node, and hence suitable for IoT devices with low computational resources. Evaluations of the performance necessary to detect different classes of cyberattacks using SecureChainAI have improved on the detection accuracy, precision, recall, f1-score, and reduced error rates. © 2024 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

Smart-Fragile Authentication Scheme for Robust Detecting of Tampering Attacks on English Text

引用

computers, Materials & Continua 2022年第5期71卷 2497-2513页

作者： Mohammad Alamgeer Fahd N.Al-Wesabi Huda G.Iskandar Imran Khan Nadhem Nemri Mohammad Medani Mohammed Abdullah Al-Hagery Ali Mohammed Al-Sharafi Department of Information Systems King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaMalaysia Department of Electrical Engineering University of Engineering and Technology PeshawarPakistan Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyUniversity of BishaKSA

Content authentication,integrity verification,and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication *** this paper,a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking(SFASCDW)is proposed for content authentication and tampering detection of English text.A first-level order of alphanumeric mechanism,based on hidden Markov model,is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed *** researcher uses the first-level order and alphanumeric mechanism of Markov model as a soft computing technique to analyze English ***,he extracts the features of the interrelationship among the contexts of the text,utilizes the extracted features as watermark information,and validates it later with the studied English text to detect any *** has been implemented using PHP with VS code *** robustness,effectiveness,and applicability of SFASCDW are proved with experiments involving four datasets of various lengths in random locations using the three common attacks,namely insertion,reorder,and *** SFASCDW was found to be effective and could be applicable in detecting any possible tampering.

关键词： Watermarking soft computing text analysis hidden Markov model content authentication

来源：评论

学校读者我要写书评

暂无评论

Leveraging Deep Learning in Implementing Efficient Healthcare Processes 15

Leveraging Deep Learning in Implementing Efficient Healthcar...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Nomula, Varun Kumar Mohammed, Abdul Sajid Neravetla, Anuteja Reddy Dhanasekaran, S. Department of Analytics/Industrial & Systems Engineering Georgia Institue of Technology United States Dept of School of Computer and Information Sciences University of the Cumberlands Kentucky United States Department of Information Technology University of the Cumberlands Kentucky United States Department of Electronics and Communication engineering Sri Eshwar College of engineering Coimbatore641202 India

ISBN: (纸本)9798350370249

deep learning is a quick-developing subfield of machine studying. It has made big improvements in diverse areas consisting of computer imagination and prescient, natural language processing, and self-reliant driving. Recently, it has additionally been used to improve healthcare strategies, and this has caused greater efficient and price-effective remedies for conditions and diseases. For instance, deep getting to know has been efficiently used to classify medical photographs, together with X-rays and CAT scans, and hit upon diseases. It can also be used to expect affected person results and examine large datasets of scientific statistics and different clinical statistics. In addition, deep learning is being used to improve the accuracy and speed of diagnosis, prevent medical events, and recommend remedies. It has additionally been used to broaden personalized medicinal drug models by gaining knowledge of affected persons' clinical records and other health-related statistics. Deep getting to know can, as a result, be used to enhance and automate healthcare strategies, main to higher care, and step forward affected person outcomes. ©2024 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Average Performance Analysis of Multi-Class Classification Based on Error-Correcting Output Codes

Average Performance Analysis of Multi-Class Classification B...

引用

2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Kobayashi, Manabu Kumoi, Gendo Yagi, Hideki Hirasawa, Shigeichi Center for Data Science Waseda University Tokyo Japan Nagaoka University of Technology Department of Information and Management Systems Engineering Niigata Japan University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan

ISBN: (纸本)9781665410205

In machine learning, one of the methods to solve multiclass classification problems is a framework called Error-Correcting Output Codes (ECOC), which constructs a multiclass classifier by combining a lot of binary classifiers. ECOC assigns binary codewords to each category, and the multiclass classification performance varies depending on the code. In this study, we treat each element of the codeword as a random variable and evaluate the average performance of ECOC. As a result, for M class classification if the number of binary classifiers is O(M), then the average error probability of various codes approaches that of MAP estimation. We show that the important points are the ratio between the number of binary classifiers and M and the difference between the maximum posterior probability and the second highest posterior probability for the categories. © 2024 IEEE.

关键词： Coding errors

来源：评论

学校读者我要写书评

暂无评论

Performance Assessment of Multi-Controller in Software Defined Network 4

Performance Assessment of Multi-Controller in Software Defin...

引用

4th IEEE International Conference on Computing, Communication, and Intelligent systems, ICCCIS 2023

作者： Jaiswal, Ankita Patra, Sudhansu Shekhar Dash, Bibhuti Bhusan Barik, Lalbihari Pandey, Trilok Nath Mishra, Manoj Ranjan School of Computer Engineering KIlT Deemed to Be University Bhubaneswar India King Abdulaziz University Faculty of Computing and Information Technology in Rabigh Department of Information Systems Saudi Arabia School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350306118

In a network design, the control plane and the data plane are separated by the architectural concept of software defined networking (SDN). A centralised controller that serves as the only point of control for the whole network is introduced by the SDN architecture. The controller serves as a logically centralized entity in charge of communicating the appropriate rules to a switch's flow table. Using a single controller to handle a lot of flows becomes insufficient. A lot of large-scale networks have employed multi-controller SDN to meet their objectives. In this research, we use a multi-controller infinite buffer waiting queue model to analyze the system performance metrics. Both numerical and simulated assessments are used to illustrate the proposed model. © 2023 IEEE.

关键词： Controllers

来源：评论

学校读者我要写书评

暂无评论

Using an Evolutionary Algorithm Such as Genetic Algorithm (Ga) to Optimize Linear Equations 5

Using an Evolutionary Algorithm Such as Genetic Algorithm (G...

引用

5th International Conference on Neural Networks and Neurotechnologies, NeuroNT 2024

作者： Wdaa, Abdul Sttar Ismail Al-Barzinji, Shokhan M. Tarish, Hiba A. College of Education for Pure Science University of Anbar Ramadi Iraq College of Computer Science and Information Technology University of Anbar Department of Computer Networks Systems Ramadi Iraq University of Technology Civil Engineering Departments Baghdad Iraq

ISBN: (纸本)9798350363739

An Evolutionary algorithm is a subset of evolutionary computations. Cloning, mutation, recombination, and selection are some of the methods used by the evolutionary algorithm that were inspired by biological evolution. The problem that was addressed in this study is how to find the coefficient values of the variables in linear equations that contain a set of variables, it must equal the right side. After reviewing previous research looking for optimization, genetic algorithm, which will use in this paper, so how are going to use this strategy to solve our problems? Select the best chromosomes from this population. Perform random chromosomal hybridization. Then, within the genes of our chromosomes, produce random mutations. Will send these chromosomes for selection again. The best chromosomes among them are selected again. It crosses and turns again, and the process is repeated until a certain number of generations have passed or find the best option. After applying the genetic algorithm through the Matlab program to the linear equation, which contains six variables, for example, the results were very excellent, as the parameter values were found in a very short time and with high accuracy, completely matching the right side of the equation. © 2024 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Leveraging Instruction-based Learning for Effective UAV Traffic Management in Dynamic Environment

Leveraging Instruction-based Learning for Effective UAV Traf...

引用

2025 International Conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Ramya, R.S. Daniel, Keren Lois Rajkumar, S. Madhavan, Sruthi S. Akshya, J. Choudhry, Mani Deepak Sri Ramakrishna Engineering College Department of Computer Science and Engineering Coimbatore India KGiSL Institute of Technology Department of Computer Science and Business Systems Coimbatore India Sona College of Technology Department of Information Technology Salem India Nehru Institute of Engineering and Technology Department of Artificial Intelligence and Data Science Coimbatore India Srm Institute of Science and Technology Department of Computational Intelligence Chennai India Srm Institute of Science and Technology Department of Computing Technologies Chennai India

ISBN: (纸本)9798331509828

With the popularization of UAVs (Unmanned Aerial Vehicles) in surveillance, delivery services, environmental monitoring, and increasingly other operational aspects, besides the need to take off and land, efficient traffic management becomes integral for assuring and securing further development and exploitation. Most of the existing traffic management systems for UAVs depend on traditional rule-based algorithms or simpler machine learning techniques, such as DQN or PPO. However, these systems also have enormous challenges: dynamic environments, high-density traffic, and robust decision-making over unpredictable weather and network conditions. In addition, the above traditional models usually experience difficulties in balancing exploration and exploitation, leading to suboptimal routing and enlarged collision risks in complicated urban airspaces. These challenges have driven us to develop a new proposal: a UA V traffic management framework based on Double Deep Q-Network (DDQN) combined with Instruction-Based Learning. In this approach, advanced learning for DDQN optimizes processes at decision-making points for UAVs. The model proposed herein, along with comprehensive simulations and quantitative analyses, demonstrated higher performance in terms of leadership and cumulative rewards while keeping lower training loss compared to the classical algorithms such as DQN, A3C, and PPO. At the same time, the DDQN model presented a better success rate (95%), as also reflected in the balanced precision-recall curve showing an area under the curve of 0.90, over others in the on-point prediction of UAVstate and safety margin of collision. Our experimental results demonstrate that the proposed DDQN-based framework significantly enhances UA V traffic management by optimizing energy consumption in complex airspaces and reducing the risk of collision. © 2025 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Investigating the Determinants of Compliance Intention in Behavior Change Support systems 29

Investigating the Determinants of Compliance Intention in Be...

引用

29th Annual Americas Conference on information systems: Diving into Uncharted Waters, AMCIS 2023

作者： Ekpezu, Akon Obu Oinas-Kukkonen, Harri Wiafe, Isaac Faculty of Information Technology and Electrical Engineering Oulu Advanced Research on Service and Information Systems University of Oulu Finland Department of Computer Science University of Ghana Ghana

ISBN: (纸本)9781713893592

The effectiveness of behavior change support systems (BCSS) in promoting health and well-being is unflinching. However, its long-term effectiveness is hindered by non-compliance. Research in BCSS that focuses on compliance is scarce, particularly the determinants of compliance intention are not well established. To address this gap, this study investigated the determinants of compliance intention in BCSS by extending the persuasive system design model to include competence, effectiveness, enjoyment, and persuasiveness. By surveying a sample of prospective BCSS users (N=234), partial least squares structural equation modeling was used to evaluate the proposed model. The findings suggest that the prospective users’ perceptions of primary task support and dialogue support, as well as social support and credibility support significantly influenced their perceptions of self-competence and system effectiveness respectively. These perceptions influenced enjoyment, then persuasiveness, and finally compliance intention. Future studies will validate these findings on the compliance behavior of BCSS. © 2023 29th Annual Americas Conference on information systems, AMCIS 2023. All rights reserved.

关键词： Behavior Change Support systems Compliance Intention Persuasive systems Design Persuasive technology Physical Activity

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：