检索结果-内蒙古大学图书馆

Classification and Categorization of COVID-19 Outbreak in Pakistan

computers, Materials & Continua 2021年第10期69卷 1253-1269页

作者： Amber Ayoub Kainaat Mahboob Abdul Rehman Javed Muhammad Rizwan Thippa Reddy Gadekallu Mustufa Haider Abidi Mohammed Alkahtani Department of Computer Science Kinnaird College for WomenLahore54000Pakistan Department of Cyber Security Air UniversityIslamabadPakistan School of Information Technology and Engineering Vellore Institute of TechnologyTamil NaduIndia Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

Coronavirus is a potentially fatal disease that normally occurs in mammals and ***,in humans,the virus spreads through aerial droplets of any type of fluid secreted from the body of an infected *** is a family of viruses that is more lethal than other unpremeditated *** December 2019,a new variant,i.e.,a novel coronavirus(COVID-19)developed in Wuhan province,*** January 23,2020,the number of infected individuals has increased rapidly,affecting the health and economies of many countries,including *** objective of this research is to provide a system to classify and categorize the COVID-19 outbreak in Pakistan based on the data collected every day from different regions of *** research also compares the performance of machine learning classifiers(i.e.,Decision Tree(DT),Naive Bayes(NB),Support Vector Machine,and Logistic Regression)on the COVID-19 dataset collected in *** to the experimental results,DT and NB classifiers outperformed the other *** addition,the classified data is categorized by implementing a Bayesian Regularization Artificial Neural Network(BRANN)*** results demonstrate that the BRANN classifier outperforms state-of-the-art classifiers.

关键词： COVID-19 pandemic neural network BRANN machine learning

来源：评论

学校读者我要写书评

暂无评论

Using Gradient Boosting Algorithms in Predicting Student Academic Performance

Using Gradient Boosting Algorithms in Predicting Student Aca...

引用

Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Esraa Mashagba Faisal Al-Saqqar Atallah Al-Shatnawi Computer Science Department Prince Hussein Bin Abdullah College for Information Technology Al al-Bayt University Mafraq Jordan Information Systems Department Prince Hussein Bin Abdullah College for Information Technology Al al-Bayt University Mafraq Jordan

Educational institutes carried out a huge research to investigate student academic performance and analyses the major factors that may affect student performance. Educational institutes care about how many students will continue their studies successfully and their appreciation. There is a crucial need to investigate and address the main challenges that may affect the student academic performance. In this paper, we propose a new approach to analyses student academic performance using Gradient Boosting algorithms. In particular, the proposed approach implements the XGBoost, CaBoost and LighGBM Gradient Boosting algorithms. The proposed approach consists of two prediction models: the student final status model and student appreciation model. The achieved results show that the CaBoost algorithm gets the best prediction results when it reaches 92.16% for student final status model and 86.89% for student appreciation model. On the other hand, the LightGBM gets the best results in terms of speed.

关键词： Predictive models Prediction algorithms Boosting Security Business

来源：评论

学校读者我要写书评

暂无评论

Strategic Signaling for Utility Control in Audit Games

arXiv

引用

arXiv 2022年

作者： Chen, Jianan Hu, Qin Jiang, Honglu The Department of Computer and Information Science Indiana University Purdue University IndianapolisIN United States The Department of Informatics and Engineering Systems The University of Texas Rio Grande Valley BrownsvilleTX United States

As an effective method to protect the daily access to sensitive data against malicious attacks, the audit mechanism has been widely deployed in various practical fields. In order to examine security vulnerabilities and prevent the leakage of sensitive data in a timely manner, the database logging system usually employs an online signaling scheme to issue an alert when suspicious access is detected. Defenders can audit alerts to reduce potential damage. This interaction process between a defender and an attacker can be modeled as an audit game. In previous studies, it was found that sending real-time signals in the audit game to warn visitors can improve the benefits of the defender. However, the previous approaches usually assume perfect information of the attacker, or simply concentrate on the utility of the defender. In this paper, we introduce a brand-new zero-determinant (ZD) strategy to study the sequential audit game with online signaling, which empowers the defender to unilaterally control the utility of visitors when accessing sensitive data. In addition, an optimization scheme based on the ZD strategy is designed to effectively maximize the utility difference between the defender and the attacker. Extensive simulation results show that our proposed scheme enhances the security management and control capabilities of the defender to better handle different access requests and safeguard the system security in a cost-efficient manner. Copyright © 2022, The Authors. All rights reserved.

关键词： Game theory

来源：评论

学校读者我要写书评

暂无评论

Enhancement of IoT based Flood Detection and Prevention using Arduino UNO with WiFi Module

Enhancement of IoT based Flood Detection and Prevention usin...

引用

International Conference on Advanced Computing and Communication systems (ICACCS)

作者： R. M. Dilip Charaan J. Shobana P. Krishnamoorthy B. Anni Princy R. J. Abinaya K. Murugesan Department of Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Tamil Nadu India Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur Tamil Nadu India Department of Computer Science and Engineering Siddharth Institute of Engineering & Technology Tamil Nadu India Department of Computer and Communication Engineering Panimalar Engineering College Tamil Nadu India Department of Electronics and Communication Engineering Karpagam Academy of Higher Education Tamil Nadu India Department of Electronics and Communication Engineering Loyola Institute of Technology Tamil Nadu India

The overflow of water from a lake or river usually causes flooding. Sometimes, a dam breach might result in the unexpected release of vast quantities of water. Some of the water seeps into the ground, flooding the region. In a station, rivers are involving the riverbanks. Along with a lack of goods and houses, businesses, and offices, street infrastructure floods contain bacteria, sewage from waste sites, and chemical spills, which later cause a number of diseases. The rate of change in river stage in real time, which can assist signal the gravity and immediacy of this hazard, is a crucial piece of information for flood predictions. Understanding the type of storm that produced the moisture, including its duration, strength, and actual extent, is important for determining the possible severity of the flood. In this system, an Arduino Uno is connected to four separate sensors: a humidity sensor, a flow sensor, a float sensor, and an ultrasonic sensor. The float sensor detects when the water is full. With the aid of IOT, these sensor combinations are utilised to predict floods, alert the appropriate authorities, and sound an immediate alarm in adjacent communities to rapidly relay information about potential floods. These sensors provide data via the IOT’s WiFi module. When flooding conditions are detected, the system warns the nearby villages and places and estimates how long it would take for help to reach at a particular location. The technology also determines when it might be considered a flood and gives them a window of time to leave in case it does.

关键词： Dams Storms Sensor systems Real-time systems Sensors Rivers Floods

来源：评论

学校读者我要写书评

暂无评论

A DCNN with Jellyfish Questoptimization Algorithm in Order to Find Fetus Images

A DCNN with Jellyfish Questoptimization Algorithm in Order t...

引用

Computing, Power and Communication Technologies (IC2PCT), IEEE International Conference on

作者： K Aravinda B Manjunatha Balasubramanian Prabhu Kavin E. Gangadevi Balamurugan Balusamy Shilpa Gite New Horizon College of Engineering Ring Road Bellandur Post Bengaluru India Department of Data Science and Business Systems SRM Institute of Science and Technology Kattankulathur Chengalpattu India Department of Computer Science Loyola College Chennai India Shiv Nadar University Delhi-NationalCapital Region (NCR) India AIML department Symbiosis Institute of Technology Pune. Symbiosis International (Deemed University) Pune India

Incomplete closure around the spinal cord is the underlying cause of spina bifida, a birth condition. Multiple methods exist for identifying the presence of spina bifida. Ultrasound can be used to look for spinal axis deformities. However, due to the distortion inherent in prenatal ultrasound pictures, this method requires the expertise of a skilled physician in order to pinpoint the anomaly. Examining ultrasound pictures visually may be a subjective and error-prone process. The diagnosis procedure for spinal deformities may benefit from a computerised support system that can automatically locate the site of the abnormality. An algorithm for determining whether the entire spine in an ultrasound picture is healthy or diseased would be the first step in developing such software. In this study, we combine the power of the Jellyfish Search Optimisation Algorithm (JFSOA) with a deep convolution neural network to better identify SB. Improved classification accuracy is achieved by JFSOA's optimal selection of the SDL model's learning rate. Foetal ultrasound scans taken in the second trimester are widely regarded as a useful screening technique for identifying birth defects. The foetal spine picture from an ultrasound scan taken at the 18th week of pregnancy is used. Preprocessing pipelines, such as contrast improvement, intensity modification, and denoising, are used to improve the quality of ultrasound pictures and eliminate noise. Using this method, the suggested model can reliably recognise pictures of people with spina bifida. The suggested approach accurately identifies and labels ultrasound pictures as normal or defective based on the attributes retrieved

关键词：

来源：评论

学校读者我要写书评

暂无评论

DQPS: An Intelligent Multi-Hop Computation Offloading Scheme for Workflow Applications in Vehicular Edge Computing Networks

引用

IEEE Transactions on Consumer Electronics 2024年

作者： Lin, Bing Chen, Qiaoxin Chen, Xing Jia, Wen-Kang Lu, Yu Xiong, Neal N. Fujian Normal University College of Physics and Energy Fujian Provincial Key Laboratory of Quantum Manipulation and New Energy Materials Fuzhou350117 China Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering Fuzhou350117 China Peking University School of Computer Science 100871 China Xiamen University Department of Informatics and Communication Engineering Xiamen361005 China Fuzhou University College of Computer and Data Science Fuzhou350118 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350118 China Fujian Normal University College of Photonic and Electronic Engineering Fuzhou350117 China Fujian Normal University Concord University College Fuzhou350117 China Sul Ross State University Department of Computer Mathematical and Physical Sciences AlpineTX79830 United States

Vehicular Edge Computing (VEC) is a feasible solution for autonomous driving as it can offload latency-sensitive and computation-intensive tasks from vehicle terminals to roadside units (RSUs) for real-time processing. Due to the high computational resource the workflow applications (i.e., autonomous driving) required, the small vehicle-to-RSUs communication range, and the scarce available resources for each vehicle, it might be difficult to accomplish complex workflow applications through the single-hop offloading paradigm in the Internet of Vehicles (IoV). In this paper, we propose a reinforcement learning (RL) based multi-hop computation offloading scheme for workflow applications to reduce their execution latency in the VEC networks, which considers the data dependency in workflow applications as well as the trust relationship and communication interference among RSUs. Firstly, a preprocessing method is employed to merge the cut-edges in a workflow to reduce the offloading scale of tasks and compress the encoding dimension of offloading solutions. Then, a Deep Q-network algorithm using Phase-optimal State update (DQPS) is proposed to update the offloading policy distribution, in which the deviation of the phase-optimal state from the current state is estimated as the reward of RL to promote the algorithm's convergence to adapt the dynamic VEC networks. Simulation results show that DQPS has the best performance compared to other benchmark schemes. Moreover, the latency of the identical applications can be reduced by 2.5%-25.3% through our offloading scheme with a multi-hop model compared to that with the single-hop paradigm in IoV. © 1975-2011 IEEE.

关键词： Computation offloading

来源：评论

学校读者我要写书评

暂无评论

The Dynamic Movement of Disaster Management systems Based on Vehicle Networks and Applied on the Healthcare System

引用

Applied Bionics and Biomechanics 2021年 2021卷 5710294页

作者： Alazzam, Malik Bader Alassery, Fawaz Faculty of Computer Science and Informatics Amman Arab University Jordan Department of Computer Engineering College of Computers and Information Technology Taif University Taif Saudi Arabia

In order to save human life and assets, the emergency management system (DMS) requires roving rescue teams to respond promptly and effectively. Installation and restoration of appropriate communication infrastructure are important for reducing the effect of disasters and enabling and coordinating information flow among relief teams working in the region. This paper describes a data collection system based on vehicular cloud network services that incorporates the advantages of both architectures of vehicular ad hoc networks (VANETs) with the cloud to establish vehicular cloud networks (VCNs). Vehicles in the current plan perform tasks like monitoring the environment, gathering data, and transmitting data to the control center depending on their positions and instructions. To build a disaster management system, the proposed system uses hybrid wireless networking, which includes both a central system and ad hoc networks. The implementation results show that the suggested system is more dependable and efficient;even light density is improved in terms of reachability with few hops. Furthermore, as compared to the existing system, the suggested system has a lower end-to-end delay and a higher packet delivery ratio. © 2021 Malik Bader Alazzam and Fawaz Alassery.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

QuerySOD: A Small Object Detection Algorithm Based on Sparse Convolutional Network and Query Mechanism

QuerySOD: A Small Object Detection Algorithm Based on Sparse...

引用

IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Zhengcai Cao Junnian Li Jie Niu MengChu Zhou State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China College of Information Science and Technology Beijing University of Chemical Technology Beijing China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Although remarkable advances have been achieved in generic object detection, small object detection (SOD) remains challenging owing to small objects’ information loss and noisy representation caused by their non-uniform distribution. Their limited width and height, scale variations, and redundant computation make SOD hard. To overcome them, this work proposes a new SOD method based on sparse convolutional network (SCNet) and Query Mechanism called QuerySOD. First, an extended feature pyramid network is constructed for extracting feature maps of small objects with more regional details. Then, a Sparse Head is neatly designed by using SCNet for accelerating the interfering speed and obtaining weights of each layer. After that, a Query Mechanism is innovatively introduced for harvesting the benefit of sparse value feature maps from the Sparse Head. QuerySOD is evaluated on public benchmarks including COCO and VisDrone. Finally, we apply it on ‘Jinghai’ unmanned survey vehicles and receive excellent SOD performance from this real-world application.

关键词： Surveys Accuracy Object detection Seaports Lakes Feature extraction Prediction algorithms Convolutional neural networks Security Noise measurement

来源：评论

学校读者我要写书评

暂无评论

Ge2Sb2Se4 Te Phase Change Material Monolithic Platform for Integrated Photonics

Ge2Sb2Se4 Te Phase Change Material Monolithic Platform for I...

引用

Conference on Lasers and Electro-Optics (CLEO)

作者： Niloy Acharjee Hongyi Sun Siddhartha Ghosh Carlos A. Ríos Ocampo Institute for Research in Electronics & Applied Physics University of Maryland College Park MD USA Department of Electrical & Computer Engineering University of Maryland College Park MD USA Department of Materials Science & Engineering University of Maryland College Park MD USA Space Systems - Northrop Grumman 1 Space Park Blvd Redondo Beach CA USA

We demonstrate a monolithic Ge2Sb2Se4Te platform for tunable photonic integrated circuits. We fabricated and measured various on-chip components, including waveguides with preliminary 55.7±3.65 dB/cm propagation ... 详细信息

ISBN: (纸本)9798350369311

关键词： Phase change materials Waveguide components Refractive index Photonic integrated circuits Crystallization Propagation losses System-on-chip Electro-optical waveguides Optimization Photonics

来源：评论

学校读者我要写书评

暂无评论

Fuzzy Attack Tree: Assessing Cyberattack Risk Using Attack Tree and Fuzzy Logic

Fuzzy Attack Tree: Assessing Cyberattack Risk Using Attack T...

引用

International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Nitin Naik Paul Jenkins Paul Grace Dishita Naik Jingping Song Shaligram Prajapat Durgesh Mishra Longzhi Yang Tossapon Boongoen Natthakan Iam-On School of Informatics and Digital Engineering Aston University United Kingdom Cardiff School of Technologies Cardiff Metropolitan University United Kingdom Birmingham City University United Kingdom Software College Northeastern University China International Institute of Professional Studies Devi Ahilya University India School of Computer Science & Information Technology Symbiosis University of Applied Sciences India Department of Computer and Information Sciences Northumbria University United Kingdom Department of Computer Science Aberystwyth University United Kingdom

Organisations and users have been experiencing significant rises in cyberattacks and their severity, which means that they require a greater awareness and understanding of the anatomy of cyberattacks, to prevent and mitigate their effects. In analysing cyberattacks, there are a number of different approaches that may be used to assess their potential risks and effects. However, these are utilised in specific types of cyberattacks and their analysis, which means they cannot be applied in every situation or cyberattack. Moreover, several other factors may influence the decision to use these approaches, such as cost, complexity, skills and adaptability. As a result, continuous research to design and enhance these approaches is undertaken to produce a generic, cost-effective, easy and adaptable approach. This paper presents one such approach to assess the risk of cyberattacks utilising an attack tree and fuzzy logic. An attack tree is a systematic and illustrative method for describing an attack on a system and analysing its taxonomy and other aspects. Subsequently, the probability and risk of each leaf node in the attack tree are calculated using the proposed formulas. Finally, fuzzy logic enables decision making based on imprecise data and heuristics to obtain the overall risk of attack. This proposed approach comprises systematic steps to accomplish an assessment of any cyberattack and its associated risks in an uncomplicated and effective manner, enabling its prevention and mitigation to be determined. The paper illustrates an application of the proposed approach to assess the risk of an information theft attack on an organisation, which can then be utilised to assess the risk of other cyberattacks.

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：