检索结果-内蒙古大学图书馆

8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Yousif, Muneera Mohammed, Musab Ahmed Celik, Mete Hamdoon, Asmaa E. Jassim, Riham Abdullah, Noor M. College of Information Technology Ninevah University Software Department Mosul Iraq College of Education for Humanities Sciences Kirkuk University Kirkuk Iraq Erciyes University Computer Engineering Department Engineering Faculty Kayseri Turkey Water Resources Studies Center for Northern Region Projects Ministry of Water Resources of Iraq Mosul Iraq

ISBN: (纸本)9798350354423

One of the most important methods of predicting the future is through past events and data repeated over time, as time series are those data indexed using time sequentially on data points distributed according to time, and periodic time series analysis is the analysis of a series of recorded measurements of a phenomenon that are repeated more than once during specific times periods. Periodicity detection has an impact on many areas in the world, such as climate, motion, education et cetera. It is important to consider in solving problems, moreover, there are many data sets in the world, the most prominent of which is time series data, and this type of data is constantly increasing. In the study, several data periodicity analysis methods (such as autocorrelation, wavelet transform, DTW, RNN, LSTM) were inspected. © 2024 IEEE.

关键词： Autocorrelation

来源：评论

学校读者我要写书评

暂无评论

PrAIoritize: Automated Early Prediction and Prioritization of Vulnerabilities in Smart Contracts

arXiv

引用

arXiv 2023年

作者： Soud, Majd Liebel, Grischa Hamdaqa, Mohammad Department of Computer Science Reykjavik University Reykjavik Iceland Department of Computer and Software Engineering Polytechnique Montreal Montreal Canada

Context: Smart contracts are prone to numerous security threats due to undisclosed vulnerabilities and code weaknesses. In Ethereum smart contracts, the challenges of timely addressing these code weaknesses highlight the critical need for automated early prediction and prioritization during the code review process. Efficient prioritization is crucial for smart contract security. Objective: Toward this end, our research aims to provide an automated approach, PrAIoritize, for prioritizing and predicting critical code weaknesses in Ethereum smart contracts during the code review process. Method: To do so, we collected smart contract code reviews sourced from Open Source software (OSS) on GitHub and the Common Vulnerabilities and Exposures (CVE) database. Subsequently, we developed PrAIoritize, an innovative automated prioritization approach. PrAIoritize integrates advanced Large Language Models (LLMs) with sophisticated natural language processing (NLP) techniques. PrAIoritize automates code review labeling by employing a domain-specific lexicon of smart contract weaknesses and their impacts. Following this, feature engineering is conducted for code reviews, and a pre-trained DistilBERT model is utilized for priority classification. Finally, the model is trained and evaluated using code reviews of smart contracts. Results: Our evaluation demonstrates significant improvement over state-of-the-art baselines and commonly used pre-trained models (e.g. T5) for similar classification tasks, with 4.82%-27.94% increase in F-measure, precision, and recall. Conclusion: This paper introduces PrAIoritize, an automated approach that effectively prioritizes smart contract code weaknesses during the review process. By leveraging PrAIoritize, practitioners can efficiently prioritize smart contract code weaknesses, addressing critical code weaknesses promptly and reducing the time and effort required for manual triage. © 2023, CC BY-NC-SA.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

The Classic Television Dramas Restoration Based on Super Resolution 4

The Classic Television Dramas Restoration Based on Super Res...

引用

4th International Conference on computer Information Science and Artificial Intelligence, CISAI 2021

作者： Wang, Wanjun DIng, Xintao Liu, Chao Wu, Jinghua Anhui Institute of Information Technology School of Computer and Software Engineering Wuhu China

ISBN: (纸本)9781665406925

Super-resolution is a widely used technology in many applications, such as video repair. Aiming at the insufficiency of the method Fast Super-Resolution Convolutional Neural Networks (FSRCNN), an image super-resolution reconstruction method based on multi-scale syndication network is proposed in this study. Based on multi-scale structures, a feature sampling model is firstly proposed to extract the features of Low-Resolution image (LR);Secondly, the features are enhanced with the help of feature fusion and sub-pixel convolutional layer;Finally, a joint loss function involving MSE loss and PSNR loss is proposed to improve the optimization of the networks training. Comparison experiments are implemented on the sets of Set5, Setl4, and BSD100. The experimental results suggest that the method shows superiority against the state-of- the-art methods. As an application, the proposed method is applied to increase the resolutions of the television dramas "Journey to the West"and "The Dream of Red Mansion". The repair results improved by 4.67dB and 5.37dB respectively. © 2021 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Relation-Algebraic Verification of Borůvka’s Minimum Spanning Tree Algorithm 1

引用

19th International Conference on Relational and Algebraic Methods in computer Science, RAMiCS 2021

作者： Guttmann, Walter Robinson-O’Brien, Nicolas Department of Computer Science and Software Engineering University of Canterbury Christchurch New Zealand

ISBN: (数字)9783030887018

ISBN: (纸本)9783030887001

Previous work introduced a relation-algebraic framework for reasoning about weighted-graph algorithms. We use this framework to prove partial correctness of a sequential version of Borůvka’s minimum spanning tree algorithm. This is the first formal proof of correctness for this algorithm. We also discuss new abstractions that make it easier to reason about weighted graphs. © 2021, Springer Nature Switzerland AG.

关键词： Algebra

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Based Intrusion Detection for IoT Networks

Deep Learning Based Intrusion Detection for IoT Networks

引用

Ubiquitous Computing and Intelligent Information Systems (ICUIS), International Conference on

作者： P. Ananthi K. Nirmaladevi Mothika G Department of Computer Technology-PG Kongu Engineering College Erode Tamilnadu Department of Computer Applications Madanapalle Institute of Technology &Science MSc Software Systems Kongu Engineering College Erode India

ISBN: (数字)9798331529635

ISBN: (纸本)9798331529642

Intrusion detection is crucial for securing IoT networks amid the rapid proliferation of devices, posing significant security challenges. This study offers a unique intrusion detection model for IoT deep learning methods used in networks include Convolutional Neural Networks (CNN), TabNet, and the Transient Search Optimization (TSO) method. The project starts by developing and evaluating distinct intrusion detection components. CNN, specializing in feature extraction, analyzes network traffic for potential intrusions. TabNet, known for interpretability and effectiveness with structured data, captures intricate relationships. The novel TSO algorithm improves the system's ability to detect temporary anomalies. Each component's performance is assessed individually, highlighting unique strengths. TabNet excels in structured IoT data pattern identification, surpassing CNN. The TSO algorithm strengthens temporary anomaly recognition, enhancing IoT network security. An ensemble technique combines CNN and TabNet predictions, reducing false positives and negatives to elevate overall detection accuracy. The ensemble, using both CNN and TabNet, achieves an impressive accuracy rate exceeding 99%, demonstrating significant gains in intrusion detection performance.

关键词： Deep learning Accuracy Intrusion detection Telecommunication traffic Prediction algorithms Ubiquitous computing Convolutional neural networks Internet of Things Transient analysis Optimization

来源：评论

学校读者我要写书评

暂无评论

Towards Compositional Assurance of Large Cyber-Physical Systems 25

Towards Compositional Assurance of Large Cyber-Physical Syst...

引用

Proceedings of the 1st Workshop on Formal Arguments for Cps CerTification

作者： Gabriel A. Moreno Mark H. Klein Shambwaditya Saha Farzaneh Derakhshan Limin Jia Software Engineering Institute Carnegie Mellon University Pittsburgh PA USA Computer Science Illinois Institute of Technology Chicago IL USA Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA

ISBN: (纸本)9798400716072

Assurance of evolving large cyber-physical systems (CPS) is time-consuming, and usually a bottleneck for deploying them with confidence. Several factors contribute to this problem, including the lack of effective reuse of assurance results, the difficulty to integrate multiple analyses for multiple subsystems, and the lack of explicit consideration of the different levels of trust that different analyses provide. In this paper, we present an approach to assure large CPS that aims to overcome these barriers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Dysarthric Speech Recognition using Depthwise Separable Convolutions: Preliminary Study

Dysarthric Speech Recognition using Depthwise Separable Conv...

引用

Conference on Speech Technology and Human-computer Dialogue, SpeD

作者： Seyed Reza Shahamiri Krishnendu Mandal Sudeshna Sarkar Department of Electrical Computer and Software Engineering Faulty of Engineering The University of Auckland Auckland New Zealand Computer Science & Engineering Department Indian Institute of Technology Kharagpur India

As a neurological disability that affects muscles involved in articulation, dysarthria is a speech impairment that leads to reduced speech intelligibility. In severe cases, these individuals could also be handicapped and unable to interact with digital devices. For such individuals, Automatic Speech Recognition (ASR) technologies could be life changing by enabling them to communicate with others as well as computing devices via voice commands. Nonetheless, ASR systems designed to recognize healthy speech have shown very poor performance to transcribe dysarthric speech, signaling the need to design ASR specifically tailored for dysarthria. Dysarthric Speech Recognition (DRS) research has progressed gradually because of the challenges the research community faces such as the scarcity of dysarthric speech that does not allow the researchers to design deeper acoustic models needed to better learn dysarthric speech variations. In this paper we report on our preliminary findings to improve our previous DSR called Speech Vision and study the effects of Separable Convolutional neurons to improve its acoustic model. Speech Vision is a novel Dysarthric Speech Recognition system that learns to recognize the shape of the words uttered by dysarthric speakers instead of recognizing phone sequences and then mapping them to words. Experiments conducted on the utterances provided by all UA-Speech dysarthric speakers indicate the proposed Depthwise separable architecture provided better word recognition accuracies compared to the original Speech Vision’s architecture across all dysarthric speech intelligibility classes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Audio Based Machine Fault Diagnosis using Hybrid Feature Extraction and Ensemble Learning 15

Audio Based Machine Fault Diagnosis using Hybrid Feature Ext...

引用

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

作者： Singhal, Shashvat Goel, Bhavya Agrawal, Kshitij Sethi, Rithwick Sah, Shashi Jain, Rachit Vishwakarma, Dinesh K. Delhi Technological University Department of Computer Science Delhi India Delhi Technological University Department of Mechanical Engineering Delhi India Delhi Technological University Department of Ece Delhi India Delhi Technological University Department of Software Engineering Delhi India Delhi Technological University Department of Information Technology Delhi India

ISBN: (纸本)9798350370249

Over the last decade, proliferation of mechanical machines has surged exponentially, amplifying the challenge of monitoring their operational health due to the inevitability of wear and tear. Consequently, the conventional human centric approach to tracking machine conditions has become impractical. This underscores the demand for an innovative and efficient strategy. This research involves machine generated audio signals to detect and analyze faults or irregularities. Analyzing the acoustic patterns generated during machine operation makes detecting abnormal sounds associated with specific faults possible. This paper examines various techniques and algorithms for achieving this goal and compares them to recommend the most effective method. Initially, Short Time Fourier transform was performed on the preprocessed audio data. Then, various techniques to perform feature extraction on the transformed audio, such as spectral kurtosis, spectral centroid, zero crossing rate, and Mel spectrogram. Subsequently, the aggregate feature vector was input into various algorithms, including XGBoost, Support Vector Classifier, Random Forest Classifier and Ensemble Learning. The MIMII dataset was trained on these models. The evaluation showed that XGBoost Classifier performed the best as compared to the other models, achieving a total accuracy rate of 98 percent upon incorporating features extraction Melspectrogram, Spectral Kurtosis and Spectral Centroid. © 2024 IEEE.

关键词： Audio Classification Ensemble Learning Mel spectogram Random Forest Classifier Short time Fourier transform Spectral Centroid Spectral Kurtosis Support Vector Classifier XGBoost Zero Crossing Rate

来源：评论

学校读者我要写书评

暂无评论

A Survey on Scheduling the Task in Fog Computing Environment

arXiv

引用

arXiv 2023年

作者： Ishaq, Faiza Ashraf, Humaira Jhanjhi, Nz Department of computer and software Engineering International Islamic University Pakistan School of Computer Science SCS Taylors University Malaysia

With the rapid increase in the Internet of Things (IoT), the amount of data produced and *** processed is also increased. Cloud Computing facilitates to handle storage, processing, and analysis of data as needed. However cloud computing devices are located far away from the IoT devices. Fog computing has emerged as a small cloud computing paradigm that is near to the edge devices and handles the task very efficiently. Fog nodes have a small storage capability than the cloud node but it is designed and deployed near to the edge device so that request must be accessed efficiently and executes in time. In this survey paper we have investigated and analysed the main challenges and issues raised in scheduling the task in fog computing environment. To the best of our knowledge there is no comprehensive survey paper on challenges in task scheduling of fog computing paradigm. In this survey paper research is conducted from 2018 to 2021 and most of the paper selection is done from 2020-2021. Moreover this survey paper organizes the task scheduling approaches and technically plans the identified challenges and issues. Based on the identified issues, we have highlighted the future work directions in the field of task scheduling in fog computing environment. © 2023, CC BY.

关键词： Fog computing

来源：评论

学校读者我要写书评

暂无评论

Towards Understanding Third-party Library Dependency in C/C++ Ecosystem 7

Towards Understanding Third-party Library Dependency in C/C+...

引用

37th IEEE/ACM International Conference on Automated software engineering, ASE 2022

作者： Tang, Wei Xu, Zhengzi Liu, Chengwei Wu, Jiahui Yang, Shouguo Li, Yi Luo, Ping Liu, Yang School of Software Tsinghua University Beijing China School of Computer Science and Engineering Nanyang Technological University Singapore Singapore Institute of Information Engineering Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781450396240

Third-party libraries (TPLs) are frequently reused in software to reduce development cost and the time to market. However, external library dependencies may introduce vulnerabilities into host applications. The issue of library dependency has received considerable critical attention. Many package managers, such as Maven, Pip, and NPM, are proposed to manage TPLs. Moreover, a significant amount of effort has been put into studying dependencies in language ecosystems like Java, Python, and JavaScript except C/C++. Due to the lack of a unified package manager for C/C++, existing research has only few understanding of TPL dependencies in the C/C++ ecosystem, especially at large scale. Towards understanding TPL dependencies in the C/C++ ecosystem, we collect existing TPL databases, package management tools, and dependency detection tools, summarize the dependency patterns of C/C++ projects, and construct a comprehensive and precise C/C++ dependency detector. Using our detector, we extract dependencies from a large-scale database containing 24K C/C++ repositories from GitHub. Based on the extracted dependencies, we provide the results and findings of an empirical study, which aims at understanding the characteristics of the TPL dependencies. We further discuss the implications to manage dependency for C/C++ and the future research directions for software engineering researchers and developers in fields of library development, software composition analysis, and C/C++ package manager. © 2022 ACM.

关键词： Ecosystems

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：