检索结果-内蒙古大学图书馆

An Intelligent Secure Adversarial Examples Detection Scheme in Heterogeneous Complex Environments

computers, Materials & Continua 2023年第9期76卷 3859-3876页

作者： Weizheng Wang Xiangqi Wang Xianmin Pan Xingxing Gong Jian Liang Pradip Kumar Sharma Osama Alfarraj Wael Said College of Information Science and Engineering HunanWomen’s UniversityChangsha410138China School of Mathematics and Statistics Hunan First Normal UniversityChangsha410138China School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410114China Department of Computing Science University of AberdeenAberdeenAB243FXUK Department of Computer Science Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Computer Science Faculty of Computers and InformaticsZagazig UniversityZagazig44511Egypt

Image-denoising techniques are widely used to defend against Adversarial Examples(AEs).However,denoising alone cannot completely eliminate adversarial *** remaining perturbations tend to amplify as they propagate through deeper layers of the network,leading to ***,image denoising compromises the classification accuracy of original *** address these challenges in AE defense through image denoising,this paper proposes a novel AE detection *** proposed technique combines multiple traditional image-denoising algorithms and Convolutional Neural Network(CNN)network *** used detector model integrates the classification results of different models as the input to the detector and calculates the final output of the detector based on a machine-learning voting *** analyzing the discrepancy between predictions made by the model on original examples and denoised examples,AEs are detected *** technique reduces computational overhead without modifying the model structure or parameters,effectively avoiding the error amplification caused by *** proposed approach demonstrates excellent detection performance against mainstream AE *** results show outstanding detection performance in well-known AE attacks,including Fast Gradient Sign Method(FGSM),Basic Iteration Method(BIM),DeepFool,and Carlini&Wagner(C&W),achieving a 94%success rate in FGSM detection,while only reducing the accuracy of clean examples by 4%.

关键词： Deep neural networks adversarial example image denoising adversarial example detection machine learning adversarial attack

来源：评论

学校读者我要写书评

暂无评论

Navigating online learning challenges and opportunities: Insights from small group of lecturers during pandemic

引用

Procedia computer Science 2024年 234卷 1164-1174页

作者： Ahmad Faza Harry Budi Santoso Panca O. Hadi Putra Universitas Multimeia Nusantara Faculty of Engineering and Informatics Tangerang 15810 Indonesia Universitas Indonesia Faculty of Computer Science Depok 16424 Indonesia

The implementation of e-learning platforms in higher education offers opportunities to enhance education quality and increase access to flexible learning. However, challenges arise, including limited guidance for students, high dropout rates, and obstacles faced by instructors. This qualitative case study explores the challenges and opportunities of online learning from instructors' perspectives. Data was collected through a survey administered to 23 instructors, and thematic analysis was conducted to identify the themes of challenges and opportunities. Findings reveal challenges in interaction, practical session delivery, monitoring, assessment, and identity verification. Institutional support challenges include insufficient training and socialization. Individual Challenges encompass digital skills, health concerns, and fatigue. Technological challenges involve availability, integration, capacity, and network-related issues. Despite these challenges, online learning provides opportunities for time effectiveness, flexibility, personal development, innovative teaching methods, and collaboration with external experts.

关键词： e-learning platforms online learning instructors' perspectives

来源：评论

学校读者我要写书评

暂无评论

Collaborative learning-based inter-dependent task dispatching and co-location in an integrated edge computing system

引用

Digital Communications and Networks 2024年第6期10卷 1837-1850页

作者： Uchechukwu Awada Jiankang Zhang Sheng Chen Shuangzhi Li Shouyi Yang School of Software Henan Institute of Science and TechnologyXinxiang 453003China School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China Department of Computing and Informatics Bournemouth UniversityPoole BH125BBUK School of Electronics and Computer Science University of SouthamptonSouthampton SO171BJUK Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266100China

Recently,several edge deployment types,such as on-premise edge clusters,Unmanned Aerial Vehicles(UAV)-attached edge devices,telecommunication base stations installed with edge clusters,etc.,are being deployed to enable faster response time for latency-sensitive *** fundamental problem is where and how to offload and schedule multi-dependent tasks so as to minimize their collective execution time and to achieve high resource *** approaches randomly dispatch tasks naively to available edge nodes without considering the resource demands of tasks,inter-dependencies of tasks and edge resource *** approaches can result in the longer waiting time for tasks due to insufficient resource availability or dependency support,as well as provider ***,we present Edge Colla,which is based on the integration of edge resources running across multi-edge *** Colla leverages learning techniques to intelligently dispatch multidependent tasks,and a variant bin-packing optimization method to co-locate these tasks firmly on available nodes to optimally utilize *** experiments on real-world datasets from Alibaba on task dependencies show that our approach can achieve optimal performance than the baseline schemes.

关键词： Edge computing Collaborative learning Resource utilization Execution time Edge federation Gang scheduling

来源：评论

学校读者我要写书评

暂无评论

Designing Quantum-Resilient Blockchain Frameworks: Enhancing Transactional Security with Quantum Algorithms in Decentralized Ledgers

引用

International Journal of Advanced computer Science and Applications 2025年第4期16卷 618-628页

作者： Kale, Meenal R. Baker El-Ebiary, Yousef A. Sathiya, L. Burugari, Vijay Kumar Yulduz, Erkiniy Muniyandy, Elangovan Alanazi, Rakan Department of Humanities Yeshwantrao Chavan College of Engineering Hingna Nagpur India Faculty of Informatics and Computing UniSZA University Malaysia Department of CSE Panimalar Engineering College Chennai India Dept of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan Department of Information Technology Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia

Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secure blockchain like Rivest–Shamir–Adleman (RSA), Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm 256-bit (SHA256) are the characteristic of the traditional cryptographic techniques vulnerable to attack by quantum algorithms: Shor’s and Grover’s algorithms: can efficiently break asymmetric encryption and speed up brute force attacks. Because of this vulnerability, there exists a need to develop an advance quantum resilient blockchain framework to protect the decentralized ledgers from the future threats of the quantum. This research proposes Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD) and Quantum Random Number Generation (QRNG) as a formidable architectural integration, to fortify security of blockchain. Classical encryption is replaced with PQC, QKD with secure key exchange by detecting eavesdropping, and QRNG with improving cryptographic randomness to remove the predictable key vulnerability. Only with a small loss of transaction efficiency, we increase transaction encryption accuracy, key exchange security, and resistance to quantum attacks. In this quantum enhanced blockchain design, the idea is to preserve the decentralization, transparency and security and at the same time overcome the future quantum threat. By going through rigorous analysis and comparative evaluation, we demonstrate that the approach saves blockchain networks from the emerging quantum risks to make sure that the decentralized finance, smart contracts and cross chain transactions. © (2025), (Science and Information Organization). All rights reserved.

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Analyzing intuitionistic fuzzy reliability of LNG-fuel gas supply system using simplified Lambda-tau techniques

引用

Computational and Applied Mathematics 2025年第6期44卷 1-28页

作者： Khajuria, Rocky Komal Lee, Seong Yeob Pamucar, Dragan Stevan Simic, Vladimir Department of Mathematics School of Physical Sciences Doon University Uttarakhand Dehradun248001 India Daejeon Korea Republic of Department of Operations Research and Statistics Faculty of Organizational Sciences University of Belgrade Belgrade Serbia College of Engineering Yuan Ze University Taoyuan City Taiwan Faculty of Transport and Traffic Engineering University of Belgrade Belgrade11010 Serbia Department of Computer Science and Engineering College of Informatics Korea University Seoul02841 Korea Republic of

Liquefied natural gas-fuel gas supply system (LNG-FGSS) play a crucial role in the global energy sector, particularly in supplying natural gas (NG). Studying this system is pivotal for tackling energy needs, environmental issues, and energy infrastructure reliability. Thus, the objective of this paper is to introduce some new methodologies for assessing the intuitionistic fuzzy reliability (IFR) of LNG-FGSS that can incorporate the uncertainty by accumulating fuzziness and hesitation factors during the data processing. This paper presents two simplified IFR analysis techniques for repairable systems that include Min-Max operators based simplified intuitionistic fuzzy lambda-tau methodology (MBSIFLTM) and Min-Max operators and the weakest t-norm (Tω) based simplified intuitionistic fuzzy lambda-tau methodology (MWBSIFLTM). In MBSIFLTM, we used Min-Max operators based simplified arithmetic operations for intuitionistic fuzzy set (IFS), Lambda-tau methodology, and fault tree analysis (FTA) for analyzing different reliability indices of the system. Whereas in MWBSIFLTM, various reliability parameters of the system are assessed by using the Min-Max operators along with the weakest t-norm based simplified arithmetic operations of IFS, Lambda-tau methodology, and FTA. Further to analyzed the credibility and precision of the suggested methodologies, an investigation has been carried out for a LNG-FGSS. Both the proposed techniques and four existing methods are employed to assess the IFR of LNG-FGSS. Consequently, to show the flexibility of the proposed models, a sensitivity analysis is also conducted. Moreover, the ranking of the system’s components has been carried out by utilizing the V-index method, aiming to optimize its overall performance. Comparing the outcomes of the suggested techniques with four other established methods leads to the conclusion that the suggested techniques offer simplicity, ease of application, and optimized IFR indices. © The Author(s) under exc

关键词： Fault tree analysis

来源：评论

学校读者我要写书评

暂无评论

Open and Closed Source Models for LLM-Generated Metaheuristics Solving engineering Optimization Problem 28th

Open and Closed Source Models for LLM-Generated Metaheuris...

引用

28th European Conference on Applications of Evolutionary Computation, EvoApplications 2025, held as part of EvoStar 2025

作者： Senkerik, Roman Viktorin, Adam Kadavy, Tomas Kovac, Jozef Janku, Peter Pekar, Libor Guzowski, Hubert Smolka, Maciej Byrski, Aleksander Pluhacek, Michal A.I.Lab Faculty of Applied Informatics Tomas Bata University Zlin Czech Republic Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University Zlin Czech Republic Faculty of Computer Science AGH University of Krakow Krakow Poland Center of Excellence in Artificial Intelligence AGH University of Krakow Krakow Poland

ISBN: (纸本)9783031900648

This paper explores the applicability of generative AI (genAI), specifically Large Language Models (LLMs), for the automatic generation and configuration of metaheuristic algorithms to address a real-world engineering problem: the optimal parameter estimation of time-delay systems in interconnected heating-cooling loops. The study introduces a pioneering workflow and iterative architecture with feedback within the emerging field of genAI-driven optimization for real optimization problems, eliminating the need for manually crafted or modified algorithms. This automated system empowers domain experts in engineering to solve complex optimization problems with minimal knowledge of optimization algorithms, lowering the barrier to entry for sophisticated algorithm use. We demonstrate how LLMs can generate effective optimizers under conditions like connstrained optimization problems where the solution lies near the boundaries of the search space. Four state-of-the-art LLMs (closed and open-sourced) have been selected for experiments. These are GPT-4o, GPT-4o mini, Claude Sonnet 3.5 and Llama 3.1. All studied LLMs generated metaheuristics that outperformed the initialization baseline optimization method (Random Search and CMA-ES). Notably, the Claude Sonnet 3.5 model generated a metaheuristic with the best mean results, almost matching the performance of the tuned state-of-the-art DISH algorithm, as an example of adaptive Differential Evolution. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Time of arrival

来源：评论

学校读者我要写书评

暂无评论

Lightweight YOLOv5-Based Algorithm to Detect Room Nameplates for Autonomous Smart Wheelchair

Lightweight YOLOv5-Based Algorithm to Detect Room Nameplates...

引用

International Joint Conference on computer Science and Software engineering (JCSSE)

作者： Ainandafiq Muhammad Alqadri Fitri Utaminingrum Departement of Informatics Engineering Faculty of Computer Science Brawijaya University Malang Indonesia

ISBN: (数字)9798350381764

ISBN: (纸本)9798350381771

About 10% individuals with visual impairment also use wheelchair, which makes them difficult to ambulate into a room that can only be distinguished by text independently. One thing that could be a solution is to implement a room nameplate recognition system on autonomous smart wheelchairs so that it can ambulate the user to the dedicated room autonomously. We proposed a lightweight YOLOv5-based method to detect room nameplates that is more suitable for embedded devices such as smart wheelchair. We improved YOLOv5 with ghost module and coordinate attention to reduce model complexity while still maintain the detection accuracy. Using room nameplate images data that has been collected by our self, the proposed method has 29 % less parameter with about the same accuracy as the original YOLOv5. With a low complexity of object detection model, our study may be utilized for room nameplate recognition system on smart wheelchair.

关键词： YOLO computer science Accuracy Embedded systems Attention mechanisms Wheelchairs Computational modeling

来源：评论

学校读者我要写书评

暂无评论

Comparison of Q&A Classification Using BiLSTM Based on Closed Domain Knowledge

Comparison of Q&A Classification Using BiLSTM Based on Close...

引用

Electrical Power, Electronics, Communications, Controls and informatics Seminar (EECCIS)

作者： Alifi Lazuardi Gunawan Fitra Abdurrachman Bachtiar Budi Darma Setiawan Informatics Engineering Department Faculty of Computer Science Brawijaya University Malang Indonesia

ISBN: (数字)9798350379914

ISBN: (纸本)9798350379921

The faculty of computer Science, Universitas Brawijaya (Filkom UB) is committed to providing quality services for the users especially internal and external stakeholders, one of which is through the HaloFilkom service. HaloFilkom services have limitations in terms of time. HaloFilkom services are not available 24 hours due to limited working hours. Questions asked by users are not answered directly. This weakness in the HaloFilkom system can be overcome by using a chatbot system. Chatbot is an interactive system that works with natural human language and can work 24 hours. Thus, the current study explores the basic chatbot model by classifying the Q&A in the closed domain knowledge. The dataset in this research is in the form of pairs of questions and answers regarding various topics at the Filkom UB. The knowledge is preprocessed using text preprocessing which includes case folding, tokenization, padding, and tensorization. One of the chatbot models is a generative model. Creating a generative chatbot model can be done using the Seq2Seq model mechanism which consists of an encoder and decoder. The model created consists of four different architectures, namely a model with an LSTM encoder without attention and with attention and a BiLSTM model encoder without attention and with attention. Hyperparameter tuning was conducted to obtain the best hyperparameter combination. The experiment results show the best hyperparameter combination obtained is hidden size 448, drop out rate 0.5, learning rate 0.001, batch size 64, and teacher force 0. The model with the best loss is obtained with a BiLSTM encoder architecture without an attention mechanism with a train loss of 0.120. The model with the highest BLEU Score was obtained by a model with a BiLSTM encoder architecture without an attention mechanism with a BLEU Score of 0.8587 on the training data. Testing using prompt testing obtained an average BLEU Score of 0.3745 on the BiLSTM encoder without an attention mechanism mo

关键词： Attention mechanisms Force Bidirectional long short term memory Training data computer architecture Chatbots Data models Space exploration Tuning Testing

来源：评论

学校读者我要写书评

暂无评论

Facial Palsy Image Classification Using Landmarks Extraction and Extreme Learning Machine

Facial Palsy Image Classification Using Landmarks Extraction...

引用

IEEE EMBS Conference on Biomedical engineering and Sciences (IECBES)

作者： Frisca P. A. Febriyanti Fitra Abdurrachman Bachtiar Agus W. Widodo Informatics Engineering Department Faculty of Computer Science University of Brawijaya Malang Indonesia

ISBN: (数字)9798350383409

ISBN: (纸本)9798350383416

Facial palsy is a condition characterized by facial paralysis, affecting the patient's motor function. Detection is typically done through a clinical expert's direct observation of facial muscles. However, manual examinations are less effective as patients tend to go for health checks when symptoms indicate severe dysfunction. Due to these challenges, a classification system is built as early screening for facial palsy. This research aims to propose the detection of facial palsy using Extreme Learning Machine algorithm. In this research, we use three datasets: CK+, JAFFE, and Youtube Facial Palsy (YFP). The dataset is divided into training and testing data in an 80:20 ratio. Applied preprocessing techniques of landmark facial feature extraction, selection, and Euclidean distance calculation at specific face points. We employ k-fold cross-validation to find the optimal parameter during the training process. We also implemented oversampling and undersampling techniques to handle imbalanced data. The system classifies facial palsy into normal, mild, moderate, and severe dysfunction. The ELM model achieved Accuracy values of 0.9949, Precision of 0.9888, Recall of 0.9887, and F1-score of 0.9888 on balanced data using an oversampling technique. The current research indicates that the implemented techniques can handle imbalanced data, and contribute to better model performance.

关键词： Training Accuracy Video on demand Extreme learning machines Biological system modeling Data models Robustness Data mining Web sites Testing

来源：评论

学校读者我要写书评

暂无评论

Gated Self-supervised Learning for Improving Supervised Learning

Gated Self-supervised Learning for Improving Supervised Lear...

引用

Artificial Intelligence (CAI), IEEE Conference on

作者： Erland Hilman Fuadi Aristo Renaldo Ruslim Putu Wahyu Kusuma Wardhana Novanto Yudistira Departement of Informatics Engineering Faculty of Computer Science Brawijaya University Malang Indonesia

ISBN: (数字)9798350354096

ISBN: (纸本)9798350354102

In past research on self-supervised learning for image classification, the use of rotation as an augmentation has been common. However, relying solely on rotation as a self-supervised transformation can limit the ability of the model to learn rich features from the data. In this paper, we propose a novel approach to self-supervised learning for image classification using several localizable augmentations with the combination of the gating method. Our approach uses flip and shuffle channel augmentations in addition to the rotation, allowing the model to learn rich features from the data. Furthermore, the gated mixture network is used to weigh the effects of each self-supervised learning on the loss function, allowing the model to focus on the most relevant transformations for classification.

关键词： Deep learning Training Accuracy Supervised learning Self-supervised learning Logic gates Data models

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：