检索结果-内蒙古大学图书馆

2nd International Conference on Advancements in Computing, ICAC 2020

作者： Fernando, K.J.L. Jayalath, W.J.D.L.D.D. Ranasinghe, A.D.R.N. Bandara, P.K.B.P.S. De Silva, Hansi Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9781728184128

3I-LMS is meant to conquer the insurmountable restraints to class/lecture room education. What are insurmountable restraints to physical classroom education and how does 3I-LMS conquer them. Firstly, the lockdown and physical distancing warranted by the spread of Covid-19. In order to overcome the restraints of the pandemic 3I-LMS would be the obvious answer. 3I-LMS, the medium for delivery and reception, is online for both learners and trainers. Secondly, ineffectiveness resulting in frail in pass rates, fast diminishing memory, faulty study techniques are overcome. 3I-LMS makes studying satisfied, gamified, engaged and enjoying. The outcome would be lasting memory, effective study techniques, higher recall rates leading to improved pass rates. Thirdly, inefficiencies such as slow access to relevant lessons, notes, slow answer evaluation, feedback, clarification to routine questions are also resolved by 3I-LMS. 3I-LMS provides for keyword search, relevant subject wise notes, instant answers for routine questions thus contributing to improved efficiencies. Additionally, 3I-LMS has unique and innovative features to assist assignment completion, emanate milestone alerts, monitoring emotions and time utilization. 3I-LMS provides for utmost security. Thus, the solution deploys face recognition and keystroke dynamics to combat impersonation, copying and unauthorized referencing. © 2020 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

ML Techniques for Employee Performance Prediction

ML Techniques for Employee Performance Prediction

引用

Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), International Conference on

作者： Brajesh Kumar Prateek Agrawal Dipesh Uike Melanie Lourens Indira Bhati M. Chandrakumar Peter Department of Computer Science & Engineering Dr. APJ Abdul Kalam Women's Institute of Technology Darbhanga Bihar Gurukula Kangri (Deemed to be University) Dr. Ambedkar Institute of management studies and research Nagpur Maharashtra Faculty of Management Sciences Durban University of Technology South Africa Department of Management MMIM Maharishi Markandeshwar (Deemed to be University) Department of Software Engineering PeriyarManiammai Institute of Science and Technology Thanjavur Tamilnadu

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

When it comes to maximizing the effectiveness of a business and promoting professional growth, employee performance prediction is an extremely important factor. This research article investigates the use of machine learning (ML) approaches to forecast employee performance, with a particular emphasis on the incorporation of different algorithms from different sources to improve accuracy and dependability. Methods that have been used for a long time, such as linear regression and decision trees, are evaluated alongside more recent approaches, such as ensemble methods and deep learning. To refine the prediction models, our research makes use of approaches such as feature selection and dimensionality reduction. These techniques are utilized by utilizing previous performance data, demographic information, and behavioral indicators. It has been demonstrated through the analysis that sophisticated machine learning techniques, in particular ensemble and deep learning models, are superior to traditional methods when it comes to anticipating employee performance. Our findings offer HR departments concrete insights that can be used to adopt data-driven methods for performance management, which will eventually contribute to improved organizational outcomes and increased employee satisfaction. This paper offers opportunities for future development in predictive analytics within the field of human resources and emphasizes the potential of machine learning to alter performance evaluation systems.

关键词： Deep learning Performance evaluation Accuracy Machine learning algorithms Linear regression Predictive models Prediction algorithms Feature extraction Ensemble learning Predictive analytics

来源：评论

学校读者我要写书评

暂无评论

Block Hunter: Federated Learning for Cyber Threat Hunting in Blockchain-based IIoT Networks

arXiv

引用

arXiv 2022年

作者： Yazdinejad, Abbas Dehghantanha, Ali Parizi, Reza M. Hammoudeh, Mohammad Karimipour, Hadis Srivastava, Gautam The Cyber Science Lab University of Guelph Canada The College of Computing and Software Engineering Kennesaw State University GA United States Information & Computer Science Department King Fahd University of Petroleum & Minerals Saudi Arabia The School of Engineering Department of Electrical and Software Engineering The University of Calgary Alberta Canada The Department of Math and Computer Science Brandon University Manitoba Canada The Research Centre for Interneural Computing China Medical University Taichung Taiwan

Nowadays, blockchain-based technologies are being developed in various industries to improve data security. In the context of the Industrial Internet of Things (IIoT), a chain-based network is one of the most notable applications of blockchain technology. IIoT devices have become increasingly prevalent in our digital world, especially in support of developing smart factories. Although blockchain is a powerful tool, it is vulnerable to cyber attacks. Detecting anomalies in blockchain-based IIoT networks in smart factories is crucial in protecting networks and systems from unexpected attacks. In this paper, we use Federated Learning (FL) to build a threat hunting framework called Block Hunter to automatically hunt for attacks in blockchain-based IIoT networks. Block Hunter utilizes a cluster-based architecture for anomaly detection combined with several machine learning models in a federated environment. To the best of our knowledge, Block Hunter is the first federated threat hunting model in IIoT networks that identifies anomalous behavior while preserving privacy. Our results prove the efficiency of the Block Hunter in detecting anomalous activities with high accuracy and minimum required bandwidth. © 2022, CC BY.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

GLIB: Ameliorated English Skills Development with Artificial Intelligence 1

GLIB: Ameliorated English Skills Development with Artificial...

引用

1st IEEE Bangalore Humanitarian Technology Conference, B-HTC 2020

作者： Srikanthan, Praveenkumar Nizar, Roshan Ravikumar, Abishaan Lalitharan, Keerthigan Harshanath, S.M.B. Alosius, Jesuthasan Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9781728187945

In language learning, most of the learners can learn the theory and memorize the sound of a language. However, the ability to speak and learn a language properly requires good practice, experience and good learning strategies. This research is an approach to innovate and improve the language learning strategies along with practices that help to improve the language skills for non-native learners and children who are in the early stage of learning. In this research, the English language will be used to experiment with our solution as the source due to its demand and familiarity in the world. This research is focused on four main skills such as conversation skills, pronunciation skills, listening skills and grammatical skills. This research is done by analyzing the difficulties in each of the skills mentioned above and also discusses and provides details about the solution implemented to improve learning English in an efficient way. The implementation of this research is done by using technologies like natural language processing, machine learning, and deep learning approaches to come up with components to train the learner. The application of this research is delivered by using a cross-platform application called GLIB. The name GLIB is inspired by a library in C language which represents fluency. This mobile application provides facilities to improve all the English language skills mentioned above along with guides, tips, practices, and feedback based on an evaluation to improve the English language. © 2020 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Understanding Neural Network Through Neuron Level

SSRN

引用

SSRN 2023年

作者： Dou, Hui Zhao, Jian Shen, Furao State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing210023 China School of Electronic Science and Engineering Nanjing University Nanjing210023 China School of Artificial Intelligence Nanjing University Nanjing210023 China

Neuron is the basic unit of the neural network. In this paper, we present a method for visualizing the process of neuron learning. The features learned by different neurons can be combined flexibly to analyze the working mechanism of different components of the network. In the medical field, researchers use medical scanners that capture images of the brain to observe the human brain. Similarly, we analyze the neural network by visualizing the feature learned by the neuron. The method is applicable to the neural network composed of artificial neurons without requiring structure changes. Through experiments, we analyze the working mechanism of different network structures and evaluate the network interpretability from different perspectives. © 2023, The Authors. All rights reserved.

关键词： Neurons

来源：评论

学校读者我要写书评

暂无评论

Unveiling the evolution of IoT threats: Trends, tactics, and simulation analysis

引用

computers & Security 2025年

作者： Kok Onn Chee Mengmeng Ge Guangdong Bai Dan Dongseong Kim School of Electrical Engineering and Computer Science The University of Queensland Brisbane QLD Australia Department of Computer Science and Software Engineering University of Canterbury New Zealand

Since the inception of Mirai in 2016, a proliferation of advanced botnets targeting Internet of Things (IoT) devices has occurred, resulting in a notable increase in large-scale cyber attacks against online services. The continual emergence of novel strategies characterises the evolving landscape of IoT botnets. Despite this, a comprehensive understanding of this evolving threat remains elusive, impeding the development of robust defence mechanisms. This paper investigated 55 instances of IoT botnets spanning from 2008 to 2021 to elucidate their evolutionary patterns based on prevalent tactics and techniques. A novel taxonomy of IoT botnets is proposed and formulated with attack tactics, techniques, types, and procedures. We augment our existing simulation framework, IoTSecSim, with enhanced functionalities to simulate novel cyber-attack scenarios incorporating diverse network configurations, evolving attack tactics, and defence strategies. Through comprehensive simulations via the extended IoTSecSim, we assessed the impact of these evolving IoT attack tactics and gauged the efficacy of traditional defence mechanisms using various security metrics.

关键词： Graphical security modelling Internet of things Botnet attacks Simulation Security evaluation Evolving attacks Taxonomy

来源：评论

学校读者我要写书评

暂无评论

SiamIRPN: Siamese Visual Tracking with Improved Region Proposal Networks

SiamIRPN: Siamese Visual Tracking with Improved Region Propo...

引用

Frontiers of Robotics and software engineering (FRSE), International Conference on

作者： Dun Cao Renhua Dai Tianyu Zhao Fayez Alqahtani Amr Tolba R. Simon Sherratt Min Zhu School of Computer and Communications Engineering Changsha University of Science and Technology Changsha Hunan China Key Lab of Broadcast Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Software Engineering Department College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Computer Science Department Community College King Saud University Riyadh Saudi Arabia School of Biomedical Engineering The University of Reading United Kingdom College of Information Science and Technology Zhejiang Shuren University Zhejiang China

Though introducing the Region Proposal Network (RPN) from object detection enabled Siamese trackers’ success, RPN-based trackers still struggle in challenging scenarios. We posit that the reason comes from two major limitations of the introduced RPN, where one is that the external structure of the RPN is simple and straight, the other is that the internal components used in RPN cannot cope with complex scenes. In this paper, we propose an Improved RPN (IRPN) suitable for visual tracking. Externally, we place a Convolutional Block Attention Mechanism (CBAM) to the IRPN, and internally, we adopt the advanced component groups for the IPRN. Using multiple IRPN blocks and deep architecture, we propose a Siamese tracker (SiamIRPN) having a layer-wise structure. Comprehensive experiments and ablation studies on five benchmarks (VOT-2019, OTB100, UAV123, GOT-10k, and NFS) show our proposed SiamIRPN achieves competitive performance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multi-Swarm Genetic Gray Wolf Optimizer with Embedded Autoencoders for High-Dimensional Expensive Problems

SSRN

引用

SSRN 2023年

作者： Zhai, Jiahui Bi, Jing Yuan, Haitao Zhou, Mengchu School of Software Engineering Faculty of Information Technology Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

High-dimensional expensive problems are often encountered in the design and optimization of complex robotic and automated systems and distributed computing systems, and they suffer from a time-consuming fitness evaluation process. It is extremely challenging and difficult to produce promising solutions in high-dimensional search space. This work proposes an evolutionary optimization framework with embedded autoencoders that effectively solve optimization problems with high-dimensional search spaces. Autoencoders provide strong dimension reduction and feature extraction abilities that compress a high-dimensional space to an informative low-dimensional one. Search operations are performed in a low-dimensional space, thereby guiding a whole population to converge to the optimal solution more efficiently. Multiple subpopulations coevolve iteratively in a distributed manner. One subpopulation is embedded by an autoencoder, and the other one is guided by a proposed Multi-swarm Gray wolf optimizer based on Genetic learning (MGG). Thus, the proposed multi-swarm framework is named Autoencoder-based MGG (AMGG). AMGG consists of three proposed strategies that well balance exploration and exploitation abilities, i.e., a Dynamic subgroup Number Strategy for reducing the number of subpopulations, a Subpopulation Reorganization Strategy for sharing useful information about each subpopulation, and a Purposeful Detection Strategy for jumping out of local optima and improving exploration ability. AMGG is compared with several widely used algorithms by using typical benchmark functions and a real-life optimization problem. Extensive experimental results prove that AMGG outperforms its peers in terms of search accuracy and convergence efficiency. © 2023, The Authors. All rights reserved.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Modeling relation path for knowledge graph via dynamic projection 32

Modeling relation path for knowledge graph via dynamic proje...

引用

32nd International Conference on software engineering and Knowledge engineering, SEKE 2020

作者： Zhu, Hongming Jiang, Yizhi Wang, Xiaowen Fan, Hongfei Liu, Qin Du, Bowen School of Software Engineering Tongji University China Department of Computer Science University of Warwick United Kingdom

ISBN: (纸本)1891706500

The application of representation learning in knowledge graphs has been a hot topic in recent years. Using representation learning methods, the semantic information contained in knowledge graphs can be embedded into low-dimensional dense vector spaces to achieve the purpose of efficiently processing knowledge graphs. A large number of research results have proved the advantage of the representation learning model represented by the translation model in processing knowledge graph related tasks. However, most translation models focus on the direct relation between entities and ignore the multi-hop relation between entities in the knowledge graph. In this paper, the relation path between entities in the knowledge graph is modeled. Considering the diversity of entities and relations in the knowledge graph, we embed entities and relations into different semantic spaces, and project the embedding results to the same space dynamically, while maintaining the consistency of the relation path between entities. We use benchmark datasets to evaluate the performance of the proposed model on the task of knowledge completion. The experiment shows that the model proposed in this paper is of great significance to solve the problem of knowledge completion in the knowledge graph. © 2020 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Research on Seedling Grading of Platycladus Orientalis Based on Fuzzy C-Means Clustering Algorithm Improved by Genetic Sparrow Family Search Optimization

SSRN

引用

SSRN 2024年

作者： Liu, Yang Zhou, Juan Wang, Juan Di, Bao Wang, Chao Ren, Zhenhui College of Mechanical and Electrical Engineering Hebei Agricultural University Baoding071001 China Department of Computer Application Engineering Hebei Software Institute Baoding071000 China College of Horticulture Hebei Agricultural University Baoding071001 China College of Information Science and Technology Hebei Agricultural University Baoding071001 China

Platycladus orientalis has high ecological and economic value, but the quality of Platycladus orientalis seedlings varies greatly. The original quality grading standard is relatively simple and the grading boundary is not clear. It is of great significance to use the in-situ Electrical Impedance Spectroscopy (EIS) technique for nondestructive testing of Platycladus orientalis roots and the improved fuzzy C-means clustering algorithm for scientific and accurate grading of Platycladus orientalis seedlings combined with morphological parameters. As a result, five parameters were found reflecting the quality of Platycladus orientalis seedlings, including phase angle at 4000Hz and tangent value at 400kHz, which could reflect the quality of roots. An Fuzzy C-means (FCM) clustering algorithm improved by genetic sparrow family search optimization (GSFS-FCM) was proposed. Through the test of standard functions and typical datasets, it was found that the number of clusters of the algorithm could be determined automatically. Although the running time is increased, the number of iterations is reduced by more than 12%, and the clustering error rate is reduced by more than 8%. Finally, eight months old Platycladus orientalis seedlings were divided into six grades with the GSFS-FCM algorithm. From the present study it can be concluded that among the Platycladus orientalis seedlings root EIS parameters measured by the instrument in situ, phase angle at 4000Hz and tangent value at 400kHz can be used to represent the quality of the roots. GSFS-FCM algorithm can effectively and automatically grading the seedlings of Platycladus orientalis without specifying the number of clusters. The algorithm has fewer iterations and higher accuracy. © 2024, The Authors. All rights reserved.

关键词： Clustering algorithms

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：