检索结果-内蒙古大学图书馆

Sustainable Technologies for Industry 4.0 (STI), International Conference on

作者： Saiful Azad Amin Salem Saleh Mufti Mahmud M. Shamim Kaiser Md. Saefullah Miah Green University of Bangladesh Dhaka Bangladesh Faculty of Computing College of Computing & Applied Science University Malaysia Pahang Malaysia Nottingham Trent University Nottingham UK Institute of Information Technology Jahangirnagar University Savar Dhaka Bangladesh

ISBN: (纸本)9781665400107

Healthcare 4.0 has revolutionized the delivery of healthcare services during the last years. Facilitated by it, many hospitals have migrated to the paradigm of being smart. Smartization of hospitals has reduced healthcare costs while providing improved and reliable healthcare services. Thanks to the Internet of Healthcare Things (IoHT) based healthcare delivery frameworks, integration of many heterogeneous devices with varying computational capabilities has been possible. However, this introduced a number of security concerns as many secure communication protocols for traditional networks can not be verbatim employed on these frameworks. To ensure security, the threats can largely be tackled by employing a Trust Management Model (TMM) which will critically evaluate the behavior or activity pattern of the nodes and block the untrusted ones. Towards securing these frameworks through an intelligent TMM, this work proposes a machine learning based Behavioral Trust Model (BTM), where an improved Frequent Pattern Growth ${\left(iFP-Growth\right)}$ algorithm is proposed and applied to extract behavioral signatures of various trust classes. Later, these behavioral signatures are utilized in classifying incoming communication requests to either trustworthy and untrustworthy (trust) class using the Naïve Bayes classifier. The proposed model is tested on a benchmark dataset along with other similar existing models, where the proposed BMT outperforms the existing TMMs.

关键词： Protocols Machine learning algorithms Hospitals Machine learning Benchmark testing Classification algorithms Internet

来源：评论

学校读者我要写书评

暂无评论

Multi-Source Fusion-Based Model with Customized Loss Function for Stock Selection

SSRN

引用

SSRN 2022年

作者： Snášel, Václav Velasquez Silva, Juan Domingo Pant, Millie Georgiou, Dimitrios Kong, Lingping Faculty of Electrical Engineering and Computer Science VŠB-TU Ostrava Czech Republic Departament of Industrial Engineering University of Chile Santiago Chile Chile Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Uttarakhand Roorkee247667 India Faculty of Electrical Engineering and Computer Science National Technical University of Athens Greece

Selecting outstanding tech stocks for investment is challenging for any market investor. This challenge comes from the complexity caused by the dynamic and volatile nature of public policies and macroeconomic factors. Moreover, this task appears complex as an investor needs to decide from a diverse set of stocks, where performance ranking can conflict with another for different criteria, e.g., the contradiction between pure returns and risk performance. The paper proposes a novel model for stock evaluation and selection problems based on multi-source data fusion and decision-level fusion by multi-criteria decision-making (MCDM) techniques. The narrow criteria performance of a single source usually restricts a candidate's overall evaluation, especially on stock selection. Therefore, the proposed multi-source acquisition is promising to enhance reliability with reasonable data fusion, Furthermore, proper raw data processing and information integration by data fusion techniques are essential to obtain more accurate and concise data for decision-making support. Most important, the proposed multi-MCDM decision-fusion procedure can enhance the strength of a model to overcome the weakness of a single-performed model. Besides, we propose a customized loss function that improves the accuracy of time-series data prediction and increases the data's credibility. Meanwhile, the experiment shows that the proposed method reduces the prediction log error by 28\% in a best case on the experimental real-situation data and decreases the time-series data matching cost by 20\% between the prediction and observation. Finally, we conducted the real-world stock data selection by the proposed fusion-based model. The proposed model locates five potential preferred stocks, and the results are practical and effective, which are further justified through a detailed ablation study. Meanwhile, the time-series forecasting data got a lower error prediction than the baseline loss. © 2022, The Author

关键词： Data fusion

来源：评论

学校读者我要写书评

暂无评论

Managing Delivery of Safeguarding Substances as a Mitigation Against Outbreaks of Pandemics

引用

Computers, Materials & Continua 2021年第7期68卷 1161-1181页

作者： Said Ali Hassan Khalid Alnowibet Prachi Agrawal Ali Wagdy Mohamed Department of Operations Research and Decision Support Faculty of Computers and Articial IntelligenceCairo UniversityGiza12613Egypt Department of Statistics and Operations Research College of ScienceKing Saud UniversityRiyadhSaudi Arabia Trafc Safety Technologies Chair Vice Deanship of Scientic ResearchKing Saud UniversityRiyadhSaudi Arabia Department of Mathematics and Scientic Computing National Institute of TechnologyHamirpur177005India Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt School of Engineering and Applied Sciences Wireless Intelligent Networks Center(WINC)Nile UniversityGizaEgypt

The optimum delivery of safeguarding substances is a major part of supply chain management and a crucial issue in the mitigation against the outbreak of pandemics.A problem arises for a decision maker who wants to optimally choose a subset of candidate consumers to maximize the distributed quantities of the needed safeguarding substances within a specic time period.A nonlinear binary mathematical programming model for the problem is *** decision variables are binary ones that represent whether to choose a specic consumer,and design constraints are formulated to keep track of the chosen *** better illustrate the problem,objective,and problem constraints,a real application case study is *** case study involves the optimum delivery of safeguarding substances to several hospitals in the Al-Gharbia Governorate in *** hospitals are selected to represent the consumers of safeguarding substances,as they are the rst crucial frontline for mitigation against a pandemic outbreak.A distribution truck is used to distribute the substances from the main store to the hospitals in specied required quantities during a given working *** objective function is formulated in order to maximize the total amount of delivered quantities during the specied time *** case study is solved using a novel Discrete Binary Gaining Sharing Knowledge-based Optimization algorithm(DBGSK),which involves two main stages:discrete binary junior and senior gaining and sharing *** has the ability of nding the solutions of the introduced problem,and the obtained results demonstrate robustness and convergence toward the optimal solutions.

关键词： Safeguarding substances mitigation against pandemic outbreaks supply chain management metaheuristic optimization

来源：评论

学校读者我要写书评

暂无评论

A Study on the Impact of Gender, Employment Status and Academic Discipline on Cyber Hygiene: A Case Study of University of Nigeria, Nsukka

arXiv

引用

arXiv 2023年

作者： Ugwu, Celestine Ezema, Modesta Ome, Uchenna Ofusori, Lizzy Olebera, Comfort Ukwandu, Elochukwu Department of Computer Science University of Nigeria Nsukka Nigeria School of Management Information Technology & Governance University of KwaZulu-Natal Westvillle Campus Durban South Africa Dept. of Computer Science Faculty of Physical Science Imo State University Owerri Nigeria Dept. of Applied and Computing Engineering Cardiff School of Technologies Cardiff Metropolitan University United Kingdom

The COVID-19 pandemic has helped amplify the importance of Cyber Hygiene. As the reliance on the Internet and IT services increased during the pandemic. This in turn has introduced a new wave of criminal activities such as cybercrimes. With the emergent of COVID-19 which lead to increase in cyber-attacks incidents, the pattern and sophistication, there is an urgent need to carry out an exploratory study to find out users’ level of cyber-hygiene knowledge and culture based on gender, employment status and academic discipline. Above this, with many organisations providing for dual mode work pattern or remote and in-person as the pandemic subsides, this study remains very relevant and hence the aim to investigate the cyber-hygiene knowledge and compliance of university students and employees of the University of Nigeria, Nsukka (UNN). In addition, it attempts to verify the relationship between demographics such as gender, employment status and academic discipline on cyber hygiene culture among students and employees. The sample population is made of employees and students of UNN, where the employees are either academic staff or non-academic staff. The sample size consisted of three hundred and sixteen (316) participants, one hundred and eight-seven (187) of whom were females and one hundred and twenty-nine (129) were males. The results offer some useful insight on cyber hygiene practices at the university © 2023, CC BY-NC-SA.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Bootstrapping Simulation in Determining the Prognostic Factors of Lung Cancer Disease by Parametric Survival Analysis

Bootstrapping Simulation in Determining the Prognostic Facto...

引用

computing (ICOCO), IEEE International Conference on

作者： Siti Afiqah Muhamad Jamil Mohd Asrul Affendi Abdullah Nurain Ibrahim Mahayaudin M. Mansor Nor Azura Md Ghani School of Mathematical Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Shah Alam Selangor Malaysia Faculty of Applied Sciences and Technology Universiti Tun Hussein Onn Malaysia Pagoh Campus Johor Malaysia Institute for Big Data Analytics and Artificial Intelligence (IBDAAI) Kompleks Al-Khawarizmi Universiti Teknologi MARA Shah Alam Selangor Malaysia

Big data analytics focuses on getting useful insights, trends and pattern out of complex and large data. Increasing the sample by resampling the data, in biostatistics expertise, can be employed using the bootstrapping techniques. The world of bootstrapping is very large and expanding where it does not only compute the confidence interval but also perform a standard resampling method. Nevertheless, survival analysis study mostly allows the data to be not normally distributed because of the censored observations. Small number of samples also one of the reasons why this study has to perform bootstrapping to overcome the issues of biasness. Bootstrapping method is said to be one of the best methods in handling skewed data. Thus, by considering bootstrapping method, this study aims to find the most significant prognostic factors of lung cancer disease that affect the survival times with the presence of censored observations by using the parametric survival analysis. Therefore, based on 100, 150, 250 and 600 number of sampling sizes, exponential distribution appeared to fit all the assigned sample sizes. Weibull and log-logistic distribution seems to fit the data only for 100 number of samples. Races and two of the interaction terms in the model appeared to be the most significant prognostic factors affecting the survival time of lung cancer.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Disturbance Observer and Tube-based Model Reference Adaptive Control for Active Suspension Systems with Non-ideal Actuators

引用

IFAC-PapersOnLine 2023年第2期56卷 1075-1081页

作者： Yashar Mousavi Amin Zarei Ibrahim Beklan Kucukdemiral Afef Fekih Alireza Alfi Department of Applied Science School of Computing Engineering and Built Environment Glasgow Caledonian University Glasgow G4 0BA UK Department of Electrical and Computer Engineering University of Sistan and Baluchestan Zahedan Iran Electrical and Computer Engineering Department University of Louisiana at Lafayette P.O. Box 43890 Lafayette LA 70504 USA Faculty of Electrical Engineering Shahrood University of Technology Shahrood 36199-95161 Iran

Active suspension systems undertake a vital role in ensuring passengers’ ride comfort and vehicle vibration attenuation. This work proposes a tube-based model reference adaptive control (TMRAC) that identifies a correctional control component at each time instant for performance amplification of active suspension systems with non-ideal actuators. The TMRAC is augmented by a disturbance observer (DO) to compensate for the effects of dead-zone and hysteresis. Closed-loop stability analysis of the developed method is also investigated in the sense of Lyapunov theory. The developed control scheme's feasibility with regard to suspension safety, road handling, and ride comfort is assessed through simulations by using a class C road profile. Comparison results with DO-based conventional MRAC are also conducted. The obtained results demonstrate that the proposed DO-based control strategy provides a superior ride comfort quality and better road disturbance mitigation with less control effort than the conventional method.

关键词： Tube-based model reference adaptive control Disturbance observer Active suspension system Vibration Non-ideal actuator

来源：评论

学校读者我要写书评

暂无评论

Nonfragile Observer-Based Event-Triggered Fuzzy Tracking Control for Fast-Sampling Singularly Perturbed Systems with Dual-Layer Switching Mechanism and Cyber-Attacks

SSRN

引用

SSRN 2023年

作者： Guo, Fang Luo, Mengzhuo Cheng, Jun Katib, Iyad Shi, Kaibo College of Science Guilin University of Technology Guangxi Guilin541004 China Guangxi Colleges and Universities Key Laboratory of Applied Statistics Guilin541004 China College of Mathematics and Statistics Guangxi Normal University Guangxi Guilin541006 China Department of Computer Science Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia School of Information Science and Engineering Chengdu University Sichuan Chengdu610106 China

This paper investigates the problem of nonfragile observer-based tracking control for a class of fuzzy fast-sampling singularly perturbed systems (SPSs) with sensor saturation, which subject to event-triggered scheme and random cyber-attacks. The switching topology of the fast-sampling SPSs is dominated by a dual-layer switching mechanism, in this case, the Markov process in the underlying system is nonhomogeneous and its time-varying transition probabilities (TPs) are governed by a persistent dwell-time switching signal. First, in order to avoid asynchronous phenomenon of premise variable between the fuzzy fast-sampling SPSs and the fuzzy controller under network environments, the non-parallel distributed compensation (non-PDC) technique is applied to improve the design flexibility and reduce the conservativeness of the results. Furthermore, a novel fuzzy tracking control design scheme is proposed, in which integrating the fuzzy nonfragile observer and reference model signal into the synthetic design of the tracking controller can be expected to reduce the tracking error. Second, by constructing a well-designed time-delay and mode-dependent Lyapunov function, some sufficient conditions are derived such that the closed-loop system is mean-square exponential stable and with extended dissipative tracking performance. Finally, the effectiveness and applicability of the proposed control protocol are illustrated by two simulation examples. © 2023, The Authors. All rights reserved.

关键词： Closed loop systems

来源：评论

学校读者我要写书评

暂无评论

Automated Detection of Brain Abnormality using Deep-Learning-Scheme: A Study 7

Automated Detection of Brain Abnormality using Deep-Learning...

引用

7th IEEE International Conference on Bio Signals, Images and Instrumentation, ICBSII 2021

作者： Kadry, Seifedine Nam, Yunyoung Rauf, Hafiz Tayyab Rajinikanth, Venkatesan Lawal, Isah A. Noroff University College Faculty of Applied Computing and Technology Kristiansand Norway Soonchunhyang University Department of Computer Science and Engineering Asan-si Korea Republic of Staffordshire University Centre for Smart Systems Ai and Cybersecurity Stoke-on-Trent United Kingdom St. Joseph's College of Engineering Department of Electronics and Instrumentation Engineering Chennai600119 India

ISBN: (纸本)9781665441261

Brain is the vital organ in human physiology;which is conscientious for sensory signal handling and judgment making. The irregularity in brain severely influence entire decision making procedure and the unrecognized and untreated defect will lead to various harsh conditions. This research aims to implement pre-trained Deep-Learning-Scheme (DLS) to classify the brain MRI slices using a multi-class classifier. In this research, the brain MRI slices with classes;normal, stroke, Low-Grade-Glioma (LGG) and High-Grade-Glioma (HGG) are considered for the experimental study. In this work every test picture is resized into 224x224x3 pixels and these imagery are then considered to validate the performance of DLS, such as VGG16, VGG19 and ResNet50 using different classifiers. The attained classification accuracy of every DLS with classifiers, SoftMax, SVM-RBF and SVM-Cubic are presented and discussed. © 2021 IEEE.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

A Systematic review of Multi-Mode Fiber based on Dimensional Code in Optical-CDMA 3

A Systematic review of Multi-Mode Fiber based on Dimensional...

引用

3rd International Conference on applied and Practical Sciences, ICAPS 2021

作者： Ghazi, Alaan Aljunid, S.A. Idrus, Syed Zulkarnain Syed Rashidi, C.B.M. Al-Dawoodi, Aras Mahmood, Baban A. Fareed, Alaa Zaenal, Mohammed U. Qasim, Nameer Hashim Rafeeq, Ranjdr M. Faculty of Applied and Human Sciences University Malaysia Perlis Malaysia School of Computer and Communication Engineering University Malaysia Perlis Malaysia Computer Science Department College of Computer Science and Information Technology Kirkuk University Kirkuk Iraq Computer Technical Engineering Al-Qalam University College Iraq School of Computing University Utara Malaysia Malaysia

This paper deals with optical code division multiple access (optical-CDMA) and provides a general analysis of multi-mode fiber (MMF). The purpose of this work is to classify the works in the literature that are related to Optical-CDMA based on MMF and to find the limitation of the researches done in this field. Several challenges that occur in the medium such as multiple-access interference (MAI), pulse dispersion (PD) and nonlinearity in optical fibers deteriorate system performances and become a major performance-limiting factor. © Published under licence by IOP Publishing Ltd.

关键词： Multiple access interference

来源：评论

学校读者我要写书评

暂无评论

Data Mining and Text Mining Approach: Query based Information Retrieval using Genetic Algorithm

Data Mining and Text Mining Approach: Query based Informatio...

引用

Image Processing and Capsule Networks (ICIPCN), International Conference on

作者： S. Ananthi R. Venkateswaran G. Vijaya J. Arun R. Sathya Advanced Research Centre for Future Networks and Digital Twin Sri Eshwar College of Engineering Coimbatore India Faculty-Cyber and Information Security College of Computing & Information SciencesUniversity of Technology and Applied Sciences Salalah Oman Dept. of CSE Sri Krishna College of Engineering and Tech Coimbatore India Dept. of ECE Sri Eshwar College of Engineering Coimbatore India Department of IT Kongunadu College of Engg and Tech Namakkal India

ISBN: (数字)9798350367171

ISBN: (纸本)9798350367188

Information Retrieval system facilitates the retrieval efficiency of the user’s requirement from a collection of information resources. In this research work, Genetic Algorithm (GA) with various fitness functions are implemented for retrieving the relevant document for the given textual query. To increase the efficiency of the retrieval system extended keywords are added to the retrieval system using query reformulation method. Furthermore, the selection procedure namely fitness proportionate selection is used to identify the best fit individual among the chosen population. This selection algorithm assumes that, for the chosen population, the fittest individuals have a greater chance of endurance than weaker ones. The performance of the proposed system is evaluated with three different datasets solely consists of 20,322 documents are analyzed using various matching functions and their results are examined.

关键词： Text mining Accuracy Information resources Text recognition Image processing Data preprocessing Information retrieval

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：