检索结果-内蒙古大学图书馆

7th International Conference on Emerging Applications of Information technology, EAIT 2022

作者： Chatterjee, Ayan Prinz, Andreas Pahari, Nibedita Das, Jishnu Riegler, Michael Alexander Department of Information Technology Center for eHealth University of Agder Kristiansand Norway Department of Software Engineering Knowit AS Oslo Norway Department of Library and Information Science University of Calcutta Calcutta India Department of Holistic Systems Simula Research Laboratory Oslo Norway

ISBN: (纸本)9789811951909

The collective effects of sleep loss and sleep disorders are correlated with many adverse health consequences, including increased risk of high blood pressure, obesity, diabetes, depressive state, and cardiovascular symptoms. Research in eHealth can provide methods to enrich personal health care with information and communication technologies (ICTs). An eCoach system may allow people to manage a healthy lifestyle with extended health state monitoring (e.g., sleep) and tailored recommendation generation. Using supervised machine learning (ML) techniques, this study investigated the possibility of classifying sleep stages at night for adults on hourly and daily basis. The daily total sleep minutes and hourly total sleep minutes for defined sleeping period served as input for the classification models. We first used publicly available Fitbit dataset to build the initial classification models. Second, using the transfer learning approach, we re-used the top five best-performing models on a real dataset as collected from the MOX2-5 wearable medical-grade activity device. We found that support vector classifier (SVC) with "linear" kernel outdated other classifiers with a mean accuracy score of 99.92% for hourly sleep classification and a K-nearest neighbor (KNN) outpaced other classifiers with a mean accuracy score of 99.47% for daily sleep classification, for the public Fitbit datasets. Moreover, to determine the practical efficacy of the classifier models, we conceptualized to use the classifier models in an eCoach prototype system to attain tailored sleep goals (e.g., a weekly goal of 49–63 h of sleeping). © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

An Intelligent and Interpretable Intrusion Detection System for Unmanned Aerial Vehicles

An Intelligent and Interpretable Intrusion Detection System ...

引用

IEEE International Conference on Communications (ICC)

作者： Danish Javeed Tianhan Gao Prabhat Kumar Shifa Shoukat Ijaz Ahmad Randhir Kumar Software College Northeastern University Shenyang China Department of Software Engineering School of Engineering Science LUT University Lappeenranta Finland Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong China Department of Computer Science and Engineering SRM University AP AP India

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

The increasing adoption of Unmanned Aerial Ve-hicles (UAV s) in various critical applications necessitates robust security measures to protect these systems from cyber threats. In response, this research introduces an innovative Intrusion Detection System (IDS) specifically tailored for UAV s. The proposed IDS leverages Hierarchical Attention-based Long Short-Term Memory (H-LSTM) networks to effectively model the intricate temporal dependencies in UAV data. This architecture allows for comprehensive surveillance of UAV behavior, capturing both short-term anomalies and long-term deviations from expected patterns. The hierarchical attention mechanism enables the system to focus on salient features within the data, enhancing detection accuracy and robustness. To address the critical need for interpretable AI in cybersecurity, we incorporate Shapley Ad-ditive Explanations (SHAP) into our IDS. SHAP values provide a coherent and intuitive explanation of the IDS's decisions by emphasizing the specific features and their contributions to the intrusion detection process. The performance of the proposed system is rigorously evaluated using the N-BaIoT dataset. Our experiments demonstrate that the H-LSTM-based IDS outper-forms traditional methods, achieving a higher detection rate while minimizing false positives. Moreover, the incorporation of SHAP explanations facilitates rapid incident analysis, allowing security professionals to discern between genuine threats and benign anomalies effectively.

关键词： Industries Federated learning Surveillance Intrusion detection Autonomous aerial vehicles Feature extraction Robustness

来源：评论

学校读者我要写书评

暂无评论

Predicting software Functional Size Using Natural Language Processing: An Exploratory Case Study

Predicting Software Functional Size Using Natural Language P...

引用

Euromicro Conference on software engineering and advanced Applications (SEAA)

作者： Hüseyin Ünlü Samet Tenekeci Can Çiftçi İbrahim Baran Oral Tunahan Atalay Tuna Hacaloğlu Burcu Musaoğlu Onur DemirǶrs Department of Computer Engineering Izmir Institute of Technology Izmir Turkiye Bilgi Grubu Izmir Turkiye Department of Information Systems Engineering Atilim University Ankara Turkiye Department of Software and IT Engineering Ecole de Technologie Superieure Montreal Canada Siskon Software & Automation Izmir Turkiye

ISBN: (数字)9798350380262

ISBN: (纸本)9798350380279

software Size Measurement (SSM) plays an essential role in software project management as it enables the acquisition of software size, which is the primary input for development effort and schedule estimation. However, many small and medium-sized companies cannot perform objective SSM and software Effort Estimation (SEE) due to the lack of resources and an expert workforce. This results in inadequate estimates and projects exceeding the planned time and budget. Therefore, organizations need to perform objective SSM and SEE using minimal resources without an expert workforce. In this research, we conducted an exploratory case study to predict the functional size of software project requirements using state-of-the-art large language models (LLMs). For this aim, we fine-tuned BERT and BERT_SE with a set of user stories and their respective functional size in COSMIC Function Points (CFP). We gathered the user stories included in different project requirement documents. In total size prediction, we achieved 72.8% accuracy with BERT and 74.4% accuracy with BERT_SE. In data movement-based size prediction, we achieved 87.5% average accuracy with BERT and 88.1% average accuracy with BERT_SE. Although we use relatively small datasets in model training, these results are promising and hold significant value as they demonstrate the practical utility of language models in SSM.

关键词： Training Schedules Accuracy Estimation Project management Companies Predictive models Size measurement software Natural language processing

来源：评论

学校读者我要写书评

暂无评论

Predictive Hiring System: Information technology Consultants Soft Skills

Predictive Hiring System: Information Technology Consultants...

引用

International Conference on advanced Intelligent systems for Sustainable Development, AI2SD 2022

作者： Lamjid, Asmaa El Bouchti, Karim Ziti, Soumia Mohamed, Reda Oussama Labrim, Hicham Riadsolh, Anouar Belkacemi, Mourad Intelligence Processing System and Security Mohammed V University in Rabat Rabat Morocco Algorithms Networks Intelligent Systems and Software Engineering Research Faculty of Sciences Mohammed V University in Rabat Rabat Morocco Advanced Systems Engineering Laboratory National School of Applied Sciences Ibn Tofail University Kenitra Morocco Faculty of Sciences Mohammed V University in Rabat Rabat Morocco

ISBN: (纸本)9783031263835

Recruiting candidates who will perform well within any organization has become a challenge in the Human Resources sector. Generally, poor recruitment can negatively reflect the progression and evolution of the organism. Soft skills are personality traits and behaviors wanted by recruiters to provide high performance, and they are the skills that will help candidates succeed in their jobs. This work proposes a new predictive hiring model based on soft skills used in the human resources area for Information technology Consultants. This model helps organizations’ recruiters choose the best candidates and avoid lousy recruitment. The implementation of the proposed model has been running under a machine learning algorithm, the Support Vector Machine algorithm using different functions to choose which one of the implementations is best displayed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

INNSE: Invertible neural network-based DNA image storage with self-correction encoding

引用

Computational and Structural Biotechnology Journal 2025年 27卷 2492-2502页

作者： Zheng, Yanfen Zhang, Xiaokang Sun, Lijun Cao, Ben Wang, Bin Zhang, Qiang Zheng, Pan School of Computer Science and Technology Dalian University of Technology Liaoning Dalian116024 China The Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Liaoning Dalian116622 China Department of Accounting and Information Systems University of Canterbury Upper Riccarton Christchurch8140 New Zealand

DNA storage has become an alternative to silicon-based storage of media. However, when used to store multimodal data such as images, it fails to take full advantage of the characteristics of high correlation and variability present in such data, and currently remains inferior in terms of encoding density and time complexity. It also has the shortcoming of weak performance in terms of error correction methods to address insertion and deletion errors caused by error crosstalk. Therefore, we proposed an invertible neural network-based DNA image storage self-correction encoding method (INNSE) that uses the invertibility of network to perform up-down sampling processing on image and video data, thereby greatly reducing the number of DNA sequences required for data storage. A codebook generator was then designed to encode low-dimensional vectors into DNA sequences that meet various constraints. Finally, a self-correction method was constructed to achieve DNA sequence error correction at the base level without adding any redundant information. Our experimental results showed that, compared to the Yin-Yang algorithm, the encoding density of INNSE was increased by 3×, encoding time complexity was reduced by 95.26%. Under a simulated error rate of 2%, PSNR and SSIM were raised by 80.88% and 63.82%, respectively, proving that INNSE has significant advantages in encoding performance and error correction ability. © 2025

关键词： Network coding

来源：评论

学校读者我要写书评

暂无评论

Automatic Deployment to Kubernetes Cluster by Applying a New Learning Tool and Learning Processes 10

Automatic Deployment to Kubernetes Cluster by Applying a New...

引用

10th Workshop on software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2023

作者： Golis, Tomáš Dakić, Pavle Vranić, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Ilkovičova 2 Bratislava842 16 4 Slovakia Faculty of Informatics and Computing Singidunum University Danijelova 32 Belgrade Serbia

The rapid growth and widespread adoption of containerization technologies, such as Docker, and the increasing popularity of Kubernetes as a container orchestration platform have significantly shaped the landscape of modern software development and deployment. Containers have created a paradigm shift in application packaging, offering a consistent and portable environment across diverse infrastructure setups. Meanwhile, Kubernetes has emerged as the dominant choice for managing containerized applications at scale, providing features such as automated scaling, load balancing, and fault tolerance. However, despite the numerous advantages containers and Kubernetes offer, deploying applications to a Kubernetes cluster often poses challenges due to the steep learning curve and complex configuration requirements. To address these challenges, this paper aims to introduce a comprehensive learning tool that automates and simplifies the deployment process on Kubernetes clusters. © 2023 Copyright for this paper by its authors.

关键词： CI/CD Container orchestration Docker image Kubernetes

来源：评论

学校读者我要写书评

暂无评论

Exploiting Inter-sample and Inter-feature Relations in Dataset Distillation

arXiv

引用

arXiv 2024年

作者： Deng, Wenxiao Li, Wenbin Ding, Tianyu Wang, Lei Zhang, Hongguang Huang, Kuihua Huo, Jing Gao, Yang State Key Laboratory for Novel Software Technology Nanjing University China Microsoft Corporation United States University of Wollongong Australia Systems Engineering Institute AMS China School of Systems Engineering University of Defense Technology China

Dataset distillation has emerged as a promising approach in deep learning, enabling efficient training with small synthetic datasets derived from larger real ones. Particularly, distribution matching-based distillation methods attract attention thanks to its effectiveness and low computational cost. However, these methods face two primary limitations: the dispersed feature distribution within the same class in synthetic datasets, reducing class discrimination, and an exclusive focus on mean feature consistency, lacking precision and comprehensiveness. To address these challenges, we introduce two novel constraints: a class centralization constraint and a covariance matching constraint. The class centralization constraint aims to enhance class discrimination by more closely clustering samples within classes. The covariance matching constraint seeks to achieve more accurate feature distribution matching between real and synthetic datasets through local feature covariance matrices, particularly beneficial when sample sizes are much smaller than the number of features. Experiments demonstrate notable improvements with these constraints, yielding performance boosts of up to 6.6% on CIFAR10, 2.9% on SVHN, 2.5% on CIFAR100, and 2.5% on TinyImageNet, compared to the state-of-the-art relevant methods. In addition, our method maintains robust performance in cross-architecture settings, with a maximum performance drop of 1.7% on four architectures. Code is available at https://***/VincenDen/IID. Copyright © 2024, The Authors. All rights reserved.

关键词： Distillation

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Particle Swarm Optimization based on Q-Learning for Multiobjective Distributed Flow-Shop Scheduling Problem

A Hybrid Particle Swarm Optimization based on Q-Learning for...

引用

2023 International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2023

作者： Li, Chen Zhang, Wenqiang Lin, Lin School of Software Dalian University of Technology Dalian116620 China College of Info. Sci. and Eng. Henan University of Technology Zhengzhou450001 China International School of Info. Sci. and Eng. Dalian University of Technology Dalian China Dalian University of Technology DUT-RU International School of Information Science and Engineering Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province Dalian116620 China Fuzzy Logic Systems Institute lizuka8200067 Japan

ISBN: (纸本)9798350318012

This study addresses the distributed flow-shop scheduling problem (DFSP) and aims to minimize the makespan and the total processing time. Although many intelligent algorithms have been proposed to solve DFSP, the efficiency and quality of these solutions still need further improvement to meet higher production requirements. Therefore, a hybrid particle swarm optimization with enhanced directional search and Q-learning-based variable neighborhood search is proposed. The directional search quickly explores the particle swarm in multiple directions, which enhances the convergence ability in different areas of Pareto front. The Q-learning-based variable neighborhood local search prevents the proposed algorithm from falling into a local optimum. The comparative results and statistical analysis of the experiments demonstrate the superior convergence and distribution performance of the proposed algorithm. © 2023 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

Enhancing Multiscale Simulations with Constitutive Relations-Aware Deep Operator Networks

arXiv

引用

arXiv 2024年

作者： Eivazi, Hamidreza Alikhani, Mahyar Tröger, Jendrik-Alexander Wittek, Stefan Hartmann, Stefan Rausch, Andreas Institute for Software and Systems Engineering Clausthal University of Technology Clausthal-Zellerfeld38678 Germany Institute of Applied Mechanics Clausthal University of Technology Clausthal-Zellerfeld38678 Germany

Multiscale problems are widely observed across diverse domains in physics and engineering. Translating these problems into numerical simulations and solving them using numerical schemes, e.g. the finite element method, is costly due to the demand of solving initial boundary-value problems at multiple scales. On the other hand, multiscale finite element computations are commended for their ability to integrate micro-structural properties into macroscopic computational analyses using homogenization techniques. Recently, neural operator-based surrogate models have shown trustworthy performance for solving a wide range of partial differential equations. In this work, we propose a hybrid method in which we utilize deep operator networks for surrogate modeling of the microscale physics. This allows us to embed the constitutive relations of the microscale into the model architecture and to predict microscale strains and stresses based on the prescribed macroscale strain inputs. Furthermore, numerical homogenization is carried out to obtain the macroscale quantities of interest. We apply the proposed approach to quasi-static problems of solid mechanics. The results demonstrate that our constitutive relations-aware DeepONet can yield accurate solutions even when being confronted with a restricted dataset during model development. Copyright © 2024, The Authors. All rights reserved.

关键词： Finite element method

来源：评论

学校读者我要写书评

暂无评论

Forensic Investigation of Malicious Activities in Digital Environments 4

Forensic Investigation of Malicious Activities in Digital En...

引用

4th IEEE International Conference on Data engineering and Communication systems, ICDECS 2024

作者： Pasumpon Pandian, A. Anakath, A.S. Kannadasan, R. Ravikumar, K. Abdul Kareem, D. Care College of Engineering Department of Computer Science and Engineering Trichy India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India School of Computer Science and Engineering Department of Software Systems Tamil Nadu Vellore India Rrase College of Engineering Padappai Department of Computer Science & Engineering Chennai India Grt Institute of Engineering and Technology Department of Artificial Intelligence and Data Science Tamil Nadu Tiruttani India

ISBN: (纸本)9798350393354

Several digital dangers were investigated. Malware dominated analysis with 45 attacks. We found 30 phishing attacks. 22 data breaches, 15 cyber espionage, 18 identity theft. This indicates the kind and frequency of harassment digital forensic specialists endure. Digital evidence was crucial to the case. 65 pieces of evidence were collected on computers. 42 incidents showed smartphones and tablets' digital investigative potential. There were 55 examples of communication patterns requiring network logs. In 28 and 12, cloud services and removable media provided proof. A wide range of evidence sources stresses the need for extensive collecting. Digital forensics were essential to the inquiry. In 70% of cases, disk imaging software created forensic copies of metadata-and timestamp-containing storage media. Network packet analyzers examined 48 traffic logs and communication patterns. To analyze volatile memory, 35 cases used memory forensics. In 25 cases, malware analysis platforms decrypted malware. In 60 situations, file recovery software recovered lost or hidden files. Digital forensic specialists' diverse arsenal for thorough investigations is shown here. Legal and ethical considerations dominated the study. The law was important, and all inquiries followed norms. A strong chain of custody protects evidence integrity and admissibility. The data privacy rules were respected. Legal evidence is admissible in court. Ethics ensured objective investigations. This underlines digital forensic investigations' legal and ethical foundation. © 2024 IEEE.

关键词： Cybersecurity

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：