检索结果-内蒙古大学图书馆

28th International Conference on Knowledge Based and Intelligent information and Engineering systems, KES 2024

作者： Wieckowski, Jakub Bialon, Pawel Salabun, Wojciech Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland National Institute of Telecommunications ul. Szachowa 1 Warsaw04-894 Poland

In the area of decision-making, where complexities often exceed experts' analytical capabilities, this study addresses a critical gap by introducing a novel methodology for sensitivity analysis within the Multi-Criteria Decision Analysis (MCDA) problems. Current analytical frameworks struggle to comprehensively consider potential modifications to values within decision matrices, making it challenging to understand their impact in detail. To address this challenge, decision-makers need enhanced tools, and MCDA methods combined with systematic changes in selected elements of the decision matrix stand out as a promising approach. However, existing studies primarily focus on different criteria-weight scenarios, leaving an unexplored gap in the simultaneous modification of multiple values within the decision matrix. This paper integrates sensitivity analysis within the MCDA methods, extending its role in the comprehensive assessment of decision problems. Sensitivity analysis becomes crucial in offering decision-makers a broader perspective, aiding them in navigating the complexities of decision-making in dynamic environments. Recognizing the unexplored potential in sensitivity analysis, the study proposed a novel approach of simultaneous modification of multiple values in a decision matrix, offering an extension of conventional one-at-a-time modifications. As a Proof of Concept (PoC) research work, the study investigated whether the determined approach provides divergent preference scores compared to the traditional single-modification method across ten different MCDA techniques. The results showed that modifying multiple values simultaneously produced different preference scores of alternatives than in the case of a conventional single change, showing that additional insight knowledge could be extracted from this type of sensitivity analysis. © 2024 The Authors.

关键词： Sensitivity analysis

来源：评论

学校读者我要写书评

暂无评论

A Blockchain-driven Architecture for Usage Control in Solid

arXiv

引用

arXiv 2023年

作者： Basile, Davide Di Ciccio, Claudio Goretti, Valerio Kirrane, Sabrina Department of Computer Science Sapienza University of Rome Italy Department of Information Systems and Operations Vienna University of Economics and Business Austria

Decentralization initiatives like Solid and *** enable data owners to control who has access to their data and to stimulate innovation by creating both application and data markets. Once data owners share their data with others, though, it is no longer possible for them to control how their data are used. To address this issue, we propose a usage control architecture to monitor compliance with usage control policies. To this end, our solution relies on blockchain and trusted execution environments. We demonstrate the potential of the architecture by describing the various workflows needed to realize a motivating use case scenario for data markets. Additionally, we discuss the merits of the approach from privacy, security, integrateability, and affordability perspectives. Copyright © 2023, The Authors. All rights reserved.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

A Review and Analysis of Localization Techniques in Underwater Wireless Sensor Networks

引用

computers, Materials & Continua 2023年第6期75卷 5697-5715页

作者： Seema Rani Anju Anupma Sangwan Krishna Kumar Kashif Nisar Tariq Rahim Soomro Ag.Asri Ag.Ibrahim Manoj Gupta Laxmi Chandand Sadiq Ali Khan Department of CSE Guru Jambheshwar University of Science&TechnologyHisar125001India Department of Hydro and Renewable Energy Indian Institute of Technology RoorkeeIndia College of Computer Science and Information Systems Institute of Business ManagementKorangi Creek RoadKarachi75190SindhPakistan Faculty of Computing and Informatics Universiti Malaysia SabahJalan UMSKota Kinabalu88400SabahMalaysia Department of Electronics and Communication Engineering JECRC UniversityJaipurRajasthanIndia Computer Science Department UBIT Karachi UniversityKarachi75270Pakistan

In recent years,there has been a rapid growth in Underwater Wireless Sensor Networks(UWSNs).The focus of research in this area is now on solving the problems associated with large-scale *** of the major issues in such a network is the localization of underwater *** is required for tracking objects and detecting the *** is also considered tagging of data where sensed contents are not found of any use without *** is useless for application until the position of sensed content is *** article’s major goal is to review and analyze underwater node localization to solve the localization issues in *** present paper describes various existing localization schemes and broadly categorizes these schemes as Centralized and Distributed localization schemes ***,a detailed subdivision of these localization schemes is ***,these localization schemes are compared from different *** detailed analysis of these schemes in terms of certain performance metrics has been discussed in this *** the end,the paper addresses several future directions for potential research in improving localization problems of UWSN.

关键词： Underwater wireless sensor networks localization schemes node localization ranging algorithms estimation based prediction based

来源：评论

学校读者我要写书评

暂无评论

Extended Forgery Detection Framework for COVID-19 Medical Data Using Convolutional Neural Network

引用

computers, Materials & Continua 2021年第9期68卷 3773-3787页

作者： Sajid Habib Gill Noor Ahmed Sheikh Samina Rajpar Zain ul Abidin N.Z.Jhanjhi Muneer Ahmad Mirza Abdur Razzaq Sultan S.Alshamrani Yasir Malik Fehmi Jaafar Department of Computer Science Shah Abdul Latif UniversityKhairpur66020SindhPakistan National College of Business Administration&Economics Lahore54000Pakistan School of Computer Science and Engineering SCETaylor’s UniversityMalaysia Department of Information Systems Faculty of Computer Science&Information TechnologyUniversiti MalayaMalaysia Department of Information Technology College of Computer and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Engineering&Computing SciencesNew York Institute of TechnologyVancouverCanada The Computer Research Institute of Montreal QuebecCanada

Medical data tampering has become one of the main challenges in the field of secure-aware medical data *** of normal patients’medical data to present them as COVID-19 patients is an illegitimate action that has been carried out in different ways ***,the integrity of these data can be *** detection is a method of detecting an anomaly in manipulated forged *** appropriate number of features are needed to identify an anomaly as either forged or non-forged data in order to find distortion or tampering in the original *** neural networks(CNNs)have contributed a major breakthrough in this type of *** has been much interest from both the clinicians and the AI community in the possibility of widespread usage of artificial neural networks for quick diagnosis using medical data for early COVID-19 patient *** purpose of this paper is to detect forgery in COVID-19 medical data by using CNN in the error level analysis(ELA)by verifying the noise pattern in the *** proposed improved ELA method is evaluated using a type of data splicing forgery and sigmoid and ReLU phenomenon *** proposed method is verified by manipulating COVID-19 data using different types of forgeries and then applying the proposed CNN model to the data to detect the data *** results show that the accuracy of the proposed CNN model on the test COVID-19 data is approximately 92%.

关键词： Data security data privacy medical-data forgery COVID-19 convolutional neural network machine learning deep learning

来源：评论

学校读者我要写书评

暂无评论

Evolution-Based Performance Prediction of Star Cricketers

引用

computers, Materials & Continua 2021年第10期69卷 1215-1232页

作者： Haseeb Ahmad Shahbaz Ahmad Muhammad Asif Mobashar Rehman Abdullah Alharbi Zahid Ullah Department of Computer Science National Textile UniversityFaisalabadPakistan Faculty of Information and Communication Technology Universiti Tunku Abdul RahmanKampar31900PerakMalaysia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Systems King Abdulaziz UniversityJeddahSaudi Arabia

Cricket databases contain rich and useful information to examine and forecasting patterns and *** paper predicts Star Cricketers(SCs)from batting and bowling domains by employing supervised machine learning *** this aim,each player’s performance evolution is retrieved by using effective features that incorporate the standard performance measures of each player and their *** is performed by applying Bayesianrule,function and decision-tree-based *** evaluations are performed to validate the applicability of the proposed *** particular,the impact of the individual features on the prediction of SCs are ***,the category and model-wise feature evaluations are also conducted.A cross-validation mechanism is applied to validate the performance of our proposed approach which further confirms that the incorporated features are statistically ***,leading SCs are extracted based on their performance evolution scores and their standings are cross-checked with those provided by the International Cricket Council.

关键词： Online social databases cricket star cricketers prediction machine learning

来源：评论

学校读者我要写书评

暂无评论

Application Monitoring Using Libc Call Interception

Application Monitoring Using Libc Call Interception

引用

2nd International Conference on Intelligent Computing, information and Control systems, ICICCS 2020

作者： Thuwal, Harish Vashishtha, Utkarsh Department of Computer Science and Engineering IIT Delhi India Department of Computer Science and Information Systems BITS Pilani India

ISBN: (纸本)9789811584428

Generally available application monitoring solutions comprise basic aggregated metrics. This paper collects such metrics in the form of raw data. We have worked out a very primitive piece written in Golang, which manifests results from HTTP/HTTPS calls from/to the system being monitored. This process can be easily extended and applied to various architectures that use the libc library to make low-level system calls to interact with sockets or, in a more basic sense, files. The experimentation and the proof of concept were carried out on various languages, viz. C, Java, Python, and Golang itself using Docker and some classic open-source compilers. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： C (programming language)

来源：评论

学校读者我要写书评

暂无评论

Predicting Student Dropout: A Machine Learning Approach

Predicting Student Dropout: A Machine Learning Approach

引用

International Conference on Computing and Networking Technology (ICCNT)

作者： Sreedham Deb Mst. Sakira Rezowana Sammy Abdur Nur Tusher Md. Rabbi Salehin Sakib Md. Firoz Hasan Ajharul Islam Aunik Computer Science and Engineering Daffodil International University Dhaka Bangladesh Management Information Systems Begum Rokeya University Rangpur Bangladesh Computer Science Wayne State College Wayne Nebraska United States

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Student dropout is a pervasive problem in the education system, with a significant number of students failing to complete their studies due to various reasons such as academic difficulties, financial issues, personal problems, and more. Dropout not only affects the student’s academic and career prospects but also has significant financial and social costs for educational institutions and society. Identifying at-risk students and providing targeted interventions to prevent dropout has been a longstanding goal of educational researchers and practitioners. In recent years, machine Learning algorithms have emerged as a promising method for predicting student attrition and pinpointing the primary elements that contribute to it. Predicting student attrition and pinpointing the primary elements that contribute to it. This research paper offers an extensive investigation of the application of machine-learning algorithms-in-predicting student attrition. The study is based on dataset of student’s academic and demographic information collected from a major university in the Bangladesh. The dataset comprises information on over 400 students who enrolled in the university between 2015 and 2020, including their academic records, demographic characteristics, and enrollment history. Analyze datasets utilizing a variety of machine learning approaches such as support vector machines, random forests, logistic regression etc. Evaluate the performance of these algorithms using metrics such as accuracy, precision, recall, and F1 score. Our study finds that machine learning algorithms can effectively predict student dropout with high accuracy, precision, and recall. The best-performing algorithm is Random Forest with a precision of 0.78, recall of 0.78, and $F 1$-score of 0.78. Logistic regression and KNN algorithms also perform reasonably well, with a precision of 0.75 and 0.76, respectively.

关键词： Support vector machines Measurement Logistic regression Machine learning algorithms Accuracy Predictive models Nearest neighbor methods Prediction algorithms History Random forests

来源：评论

学校读者我要写书评

暂无评论

Recurrent Optical Spectrum Slicing Receiver for Power Fading Mitigation in Highly Dispersive Links using Programmable Photonics

Recurrent Optical Spectrum Slicing Receiver for Power Fading...

引用

2024 IEEE Photonics Conference, IPC 2024

作者： Sozos, K. Da Ros, F. Yankov, Metodi Deligiannidis, Stavros Sarantoglou, G. Mesaritakis, C. Bogris, A. University of West Attica Department of Informatics and Computer Engineering Aghiou Spiridonos Egaleo Athens12243 Greece Technical University of Denmark Department of Electrical and Photonics Engineering Ørsteds Plads Kgs. LyngbyDK-2800 Denmark University of the Aegean Department of Information and Communication Systems Engineering Palama 2 Karlovassi83200 Greece

We experimentally validate our works in recurrent optical spectrum slicers for dispersion compensation in IM/DD links, exploiting programmable photonics. We equalize 50 km of 64 Gb/s PAM-4 transmission in C-band, with... 详细信息

ISBN: (纸本)9798350361957

关键词： Optical links

来源：评论

学校读者我要写书评

暂无评论

Resume Ranker: AI-Based Skill Analysis and Skill Matching System

Resume Ranker: AI-Based Skill Analysis and Skill Matching Sy...

引用

International Conference on Intelligent Computing in Data Sciences (ICDS)

作者： Nikethani Gangoda Kavindu Piumal Yasantha Chamina Sewwandi Navindu Induvara Samantha Thelijjagoda Nishantha Giguruwa Department of Information Technology Sri Lanka Institute of Information Technology Sri Lanka Department of Computer Systems Engineering Sri Lanka Institute of Information Technology Sri Lanka College of Sustainability and Tourism Ritsumeikan Asia Pacific University Japan

ISBN: (数字)9798350351200

ISBN: (纸本)9798350351217

In response to Japan's imminent labor shortage crisis and its sluggish integration of IT into industry, an innovative AI-Based Skill Analysis and Matching System is proposed. With projections indicating a demand for 7 million foreign workers by 2040, there arises an urgent need for streamlined HR training processes. The system leverages advanced technologies to accelerate candidate selection and job matching, encompassing resume parsing, keyword filtering, skill matching, and improvement. Methodologically, various libraries, modules, and NLP models are integrated for comprehensive data extraction and analysis. Techniques such as tokenization, lemmatization, and cosine similarity-based matching optimize the alignment of candidates with job requirements. Findings demonstrate the system's effectiveness in reducing recruitment time and effort, enabling recruiters to focus on assessing relevant candidates efficiently. Additionally, the system offers tailored skill enhancement recommendations to candidates, facilitating their integration into the Japanese workforce. The significance of this research lies in its contribution to mitigating Japan's labor shortage crisis and advancing HR management practices. By harnessing AI technologies, the system not only addresses immediate labor market needs but also sets the stage for a technology-driven approach to talent acquisition. Overall, this research fosters advancements in HR management, benefiting employers and job seekers within and beyond Japan.

关键词： Industries Training Procurement Social networking (online) Resumes Refining Machine learning Tokenization Research and development Recruitment

来源：评论

学校读者我要写书评

暂无评论

Statistical Delay and Error-Rate Bounded QoS Provisioning for RSMA Based 6G Mobile Wireless Networks in the Non-Asymptotic Regime

Statistical Delay and Error-Rate Bounded QoS Provisioning fo...

引用

IEEE International Conference on Communications (ICC)

作者： Xi Zhang Qixuan Zhu H. Vincent Poor Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA Department of Electrical and Computer Engineering Princeton University Princeton NJ USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

The upcoming 6G mobile wireless networks are expected to support massive ultra-reliable and low-latency communications (mURLLC), which is an emerging service that demands more stringent requirements than the fifth generation (5G) wireless networks on delay and error-rate bounded quality-of-services (QoS) with massive connectivity. Finite blocklength coding (FBC) techniques based short packets communication techniques have been shown to be able to support both the statistical delay and error-rate bounded QoS provisioning. Rate splitting (RS) multiple access schemes have been proposed to address the sum degree-of-freedom loss problem over massive multiple-input and multiple-output channels when massive mobile users request to access the network. However, how to support the statistical delay and error-rate bounded QoS provisioning using FBC among massive mobile users to enable the massive access has not been sufficiently studied. In this paper, we propose to integrate FBC with RS techniques to achieve mURLLC transmissions. First, we define the ∊-effective capacity to measure the performance of statistical delay and error-rate bounded provisioning, and obtain a closed-form ∊-effective capacity under the RS scheme. Then, we maximize the aggregate ∊-effective capacity over all mobile users by deriving an optimal transmit power allocation strategy for the RS scheme. Finally, using numerical analyses, we validate and evaluate our proposed RS schemes to support statistical delay and error-rate bounded QoS provisioning over 6G communication networks in the non-asymptotic regime.

关键词： 6G mobile communication Numerical analysis Error probability Wireless networks Aggregates Measurement uncertainty Quality of service

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：