检索结果-内蒙古大学图书馆

4th International Conference on Embedded and Distributed systems, EDiS 2024

作者： Khiat, Salim Ould Ali, Yasmine Polytechnic National School of Oran Computer Systems Engineering Department Oran31000 Algeria Polytechnic National School of Oran Computer Systems Engineering Department Oran31000 Algeria

ISBN: (数字)9798331519872

ISBN: (纸本)9798331519872

Decision tree algorithms are very useful approaches in data mining. Indeed, the C4.5 algorithm is a popular data classifier for machine learning. Nowadays there is a wide range of Big Data frameworks such as Hadoop and Apache spark. In this article, we present a comparative study of different implementations of the C4.5 algorithm in a Big Data environment. Then a new approach is proposed for the implementation of the parallel version of the C4.5 algorithm (PC4.5) based on the Apache Spark framework. Experimental results show the superiority of the proposed PC4.5 algorithm over its sequential version and the version on the Hadoop platform. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

A sentiment analysis of the Ukraine-Russia War tweets using knowledge graph convolutional networks

引用

International Journal of Information Technology (Singapore) 2025年 1-18页

作者： Menaouer, Brahami Fairouz, Safa Meriem, Mohammed Boulekbachi Mohammed, Sabri Nada, Matta LABAB Laboratory Computer Systems Engineering Department National Polytechnic School of Oran Oran Algeria Computer Systems Engineering Department National Polytechnic School of Oran Oran Algeria TechCICO Laboratory University of Technology of Troyes Troyes France

Nowadays, social networks play a critical role in online social discourse, particularly during major events such as elections, health crises, and wars. Furthermore, individuals have spent significant time on social networks that consume news and express their opinions and viewpoints on various topics, namely, the Russia-Ukraine War. The Ukraine-Russia War is one of the most complicated and unfortunate events of this decade, with many aspects to be considered to have an informed opinion. For this reason, sentiment analysis research can be useful in analyzing sentiments or opinions about the Ukraine-Russia war, such as Twitter (X) posts. In this study, we propose a new deep learning-based sentiment classification model called "Knowledge Graph Convolutional Networks" that predicts and analyzes sentiments concerning the Russia-Ukraine war. There were 500,000 tweets collected in total, however only 410,428 were left for sentiment analysis after cleaning, lemmatization stemming, and deleting duplicate tweets. Results show that "war", "people", "world", "putin", "energy", "gas", "weapon", and "peace" were some of the most frequently occurring words in the tweets. The main aim of this work is to develop a robust system that provides an understanding of public sentiment towards the Russia-Ukraine war on the X platform. Experimental results demonstrate that it is possible to obtain more accurate sentiment classification results by the proposed method. They also have managerial, economic, and research implications. © Bharati Vidyapeeth's institute of computer Applications and Management 2024.

关键词： Classification Decision support systems Graph Convolutional Networks (GCN) Knowledge graph Knowledge management Opinion mining Twitter sentiment analysis Ukraine-Russia War

来源：评论

学校读者我要写书评

暂无评论

Supervised learning techniques for blood product prediction in patients with hematologic diseases: a multi-centre study in Western Algeria

引用

International Journal of Information Technology (Singapore) 2024年 1-12页

作者： Ykhlef, Amel Labri, Nedjla Selma Brahami, Menaouer LABAB Laboratory Computer Systems Engineering Department National Polytechnic School of Oran Oran Algeria

Blood transfusion is a medical procedure that involves transfusing blood or one of its components from one or more donors into a patient. Digital technology and machine learning have played a crucial role in the blood field and have provided real prospects for the production and distribution of blood products. In this study, we propose supervised machine learning techniques for the multi-label classification of blood products in patients with hematologic diseases. We used three multi-label approaches from the problem transformation category to create a decision support system for blood products label power set (LP), binary relevance (BR), and classifier chain (CC). Multi-label classification using the problem transformation approach is a flexible approach. In this study, we used data from different hospitals in hematology departments and blood transfusion centers to explore the application of contemporary supervised learning algorithms to blood product prediction. The experiment was performed by calculating the Hamming loss and accuracy to facilitate the classification of blood products. As a result, the prediction model achieved an area under the ROC curve of 99.80%, a Hamming loss of 0.30, and an accuracy of 98.8%. The proposed model has been developed to provide accurate and fast results that can save patients’ lives. © Bharati Vidyapeeth's institute of computer Applications and Management 2024.

关键词： Blood product Blood transfusion Hematological diseases Knowledge management Machine learning Multi-label classification Problem transformation methods

来源：评论

学校读者我要写书评

暂无评论

Waterfall: Gozalandia. Distributed protocol with fast finality and proven safety and liveness

IET Blockchain

引用

IET Blockchain 2023年第4期3卷 182-193页

作者： Grybniak, Sergii Leonchyk, Yevhen Mazurok, Igor Nashyvan, Oleksandr Shanin, Ruslan Odessa National Polytechnic University Institute of Computer Systems Institute of Computer Systems Odesa Ukraine Odessa I.I. Mechnikov National University Faculty of Mathematics Physics and Information Technologies Odesa Ukraine

A consensus protocol is a crucial mechanism of distributed networks by which nodes can coordinate their actions and the current state of data. This article describes a BlockDAG consensus algorithm based on the Proof of Stake approach. The protocol provides network participants with cross-voting for the order of blocks, which, in the case of a fair vote, guarantees a quick consensus. Under conditions of dishonest behavior, cross-voting ensures that violations will be quickly detected. In addition, the protocol assumes the existence of a Coordinating network containing information about the approved ordering, which qualitatively increases security and also serves to improve network synchronization. © 2023 The Authors. IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Generalized Two-Point Visual Control Model of Human Steering for Accurate State Estimation1

引用

ASME Letters in Dynamic systems and Control 2025年第1期5卷 011004页

作者： Mai, Rene E. Sears, Katherine Roessling, Grace Julius, Agung Mishra, Sandipan Department of Mechanical Aerospace and Nuclear Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Department of Cognitive Science Rensselaer Polytechnic Institute TroyNY12180 United States Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States

We derive and validate a generalization of the two-point visual control model, an accepted cognitive science model for human steering behavior. The generalized model is needed as current steering models are either insufficiently accurate or too complex for online state estimation. We demonstrate that the generalized model replicates specific human steering behavior with high precision (85% reduction in modeling error) and integrate this model into a human-as-advisor framework where human steering inputs are used for state estimation. As a benchmark study, we use this framework to decipher ambiguous lane markings represented by biased lateral position measurements. We demonstrate that, with the generalized model, the state estimator can accurately estimate the true vehicle state, providing lateral state estimates with under 0.15 m error across participants. However, without the generalized model, the estimator cannot accurately estimate the vehicle's lateral state. © 2024 by ASME.

关键词： Man machine systems

来源：评论

学校读者我要写书评

暂无评论

IMPROVEMENT OF THE ACO ALGORITHM FOR INTELLIGENT TASK SCHEDULING IN CLOUD systems

引用

Scalable Computing 2025年第2期26卷 531-539页

作者： DJEBBAR, ESMA INSAF BELALEM, GHALEM Department of Computer Science Systems Engineering National Polytechnic School of Oran-Maurie Audin Oran Algeria Department of Computer Science University of Oran1-Ahmed Ben Bella Algeria

Cloud computing involves accessing and using computing resources, such as servers, storage, and software applications, over the Internet, enabling scalable access on demand. Cloud computing systems are becoming an essential platform for scientific applications. They enable task scheduling and IT resource allocation. When these resources are not enough to meet demand, planning techniques are necessary. We propose to apply an improved ACO algorithm for intelligent task scheduling and appropriate resource allocation in a cloud environment. This work proposes a modified version of the ACO algorithm that can quickly converge to the best solution to further optimize the total response time, the average response time and the total execution cost. The algorithm suggested based on artificial intelligence application of enhanced ACO is compared with the classical ACO algorithm using Cloudsim simulator. The results obtained after the experiments and simulation are very encouraging to adopt this technique. © (2025), (West University of Timisoara). All rights reserved.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

METHOD OF DETECTION OF INTRUSIONS BASED ON STACKING META-ALGORITHM 5

METHOD OF DETECTION OF INTRUSIONS BASED ON STACKING META-ALG...

引用

5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Gavrylenko, Svitlana Zozulia, Vladislav Khatsko, Nataliia Department of Computer Engineering and Programming National Technical University "Kharkiv Polytechnic Institute" Kharkiv Ukraine Department Information Systems and Technologies National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine

ISBN: (纸本)9798350384499

An analysis of modern computer network intrusion detection systems was carried out. The application of machine and deep learning methods for classification problems has been investigated. The UNSW-NB15 dataset, developed at the Australian Cyber Security Center's (ACCS) Cyber Range Laboratory, contains data on normal network operations and synthetic intrusions. Data pre-processing was performed, including class balancing using the SMOTEENN method and selection of informative features using the Recursive Feature Elimination method. The possibility of using the stacking meta-algorithm to detect intrusions into computer networks has been investigated. A new algorithm for generating packets of raw data is proposed, which generates two sets of training data: one for training basic models, the other for a meta-model. A study of the effectiveness of using Random Forest, ANN, K Nearest Neighbor methods and Support Vector Machine and Random Forest as a decision-making meta-model was conducted. The use of the stacking meta-algorithm with the proposed algorithm for forming packets of output data, as well as basic models and a meta-model, led to a significant improvement in the quality of the model. It was found that, on average, recall and f1 score increased by 55.6% and 37.4%, respectively, compared to raw data and other models. ©2024 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

Insider Attack Prevention:LAPUP—Lightweight Authentication Protocol Using PUF

引用

Journal of Communications and Information Networks 2024年第2期9卷 192-206页

作者： Siranjeevi Rajamanickam Satyanarayana Vollala N.Ramasubramanian Department of Computer Engineering Government Polytechnic CollegeTiruchirappalli 620022India Department of Computer Science and Engineering Dr.Shyama Prasad Mukherjee International Institute of Information Technology-Naya RaipurChhattisgarh 493661India Department of Computer Science and Engineering National Institute of TechnologyTiruchirappalli 620015India

The incredible progress in technologies has drastically increased the usage of Web *** share their credentials like userid and password or use their smart cards to get authenticated by the application *** cards are handy to use,but they are susceptible to stolen smart card attacks and few other notable security *** prefer to use Web applications that guarantee for security against several security attacks,especially insider attacks,which is *** of several existing schemes prove the security pitfalls of the protocols from preventing security attacks,specifically insider *** paper introduces LAPUP:a novel lightweight authentication protocol using physically unclonable function(PUF)to prevent security attacks,principally insider *** PUFs are used to generate the security keys,challenge-response pair(CRP)and hardware signature for designing the *** transmitted messages are shared as hash values and encrypted by the keys generated by *** messages are devoid of all possible attacks executed by any attacker,including insider *** is also free from stolen verifier attacks,as the databases are secured by using the hardware signature generated by *** analysis of the protocol exhibits the strength of LAPUP in preventing insider attacks and its resistance against several other security *** evaluation results of the communication and computation costs of LAPUP clearly shows that it achieves better performance than existing protocols,despite providing enhanced security.

关键词： physically unclonable function(PUF) insiderattacks authenticationkeymanagementserver(AKMS) security

来源：评论

学校读者我要写书评

暂无评论

A Robust Phaseless Imaging Approach Using Reverse Kullback Leibler Divergence and Wirtinger Flow

A Robust Phaseless Imaging Approach Using Reverse Kullback L...

引用

2024 IEEE Conference on Computational Imaging Using Synthetic Apertures, CISA 2024

作者： Choudhury, Nazia Afroz Yonel, Bariscan Yazici, Birsen Rensselaer Polytechnic Institute Electrical Computer and Systems Engineering TroyNY United States

ISBN: (纸本)9798350308648

Phaseless imaging is a prominent field of study in many imaging modalities. In practical applications, the phaseless measurements usually contain noise and outliers, limiting the reconstruction algorithms' performance. In this paper, we study the reverse Kullback-Leibler divergence (RKLD) as a robust objective function for mitigating the effects of corrupted measurements. We optimize RKLD using the state-of-the-art Wirtinger Flow (WF) algorithm for image reconstruction. Then, we numerically demonstrate the performance of RKLD using simulated coded diffraction measurements and a real optical dataset. Additionally, we compare RKLD's performance with other well-known loss functions used by the WF framework, namely, £2-intensity, Poisson, and £2-magnitude. Our simulation results demonstrate that RKLD-based optimization provides higher quality reconstructed images than the other loss functions in the presence of noise and outliers. © 2024 IEEE.

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

ContextAug:model-domain failing test augmentation with contextual information

引用

Frontiers of computer Science 2024年第2期18卷 43-60页

作者： Zhuo ZHANG Jianxin XUE Deheng YANG Xiaoguang MAO School of Information Technology and Engineering Guangzhou College of CommerceGuangzhou 511363China School of Computer and Information Engineering Institute for Artificial IntelligenceShanghai Polytechnic UniversityShanghai 201209China College of Computer National University of Defense TechnologyChangsha 410073China

In the process of software development,the ability to localize faults is crucial for improving the efficiency of *** speaking,detecting and repairing errant behavior at an early stage of the development cycle considerably reduces costs and development *** have tried to utilize various methods to locate the faulty ***,failing test cases usually account for a small portion of the test suite,which inevitably leads to the class-imbalance phenomenon and hampers the effectiveness of fault ***,in this work,we propose a new fault localization approach named *** obtaining dynamic execution through test cases,ContextAug traces these executions to build an information model;subsequently,it constructs a failure context with propagation dependencies to intersect with new model-domain failing test samples synthesized by the minimum variability of the minority feature *** contrast to traditional test generation directly from the input domain,ContextAug seeks a new perspective to synthesize failing test samples from the model domain,which is much easier to augment test *** conducting empirical research on real large-sized programs with 13 state-of-the-art fault localization approaches,ContextAug could significantly improve fault localization effectiveness with up to 54.53%.Thus,ContextAug is verified as able to improve fault localization effectiveness.

关键词： context fault localization test cases

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：