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检索条件"任意字段=19th International Conference on Control Systems and Computer Science"

共 42959 条记录，以下是4811-4820 订阅

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Multi-reference Adaptive Gain FXLMS Algorithm for Active Noise control 8

Multi-reference Adaptive Gain FXLMS Algorithm for Active Noi...

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8th international conference on computer and Communication systems, ICCCS 2023

作者： Wu, Quanjiang Wen, Pengwei Chai, Xuzhao Yang, Hui Chen, Jiaxin Zhang, Limin School of Electric and Information Zhong Yuan University of Technology Zhengzhou China

ISBN: (纸本)9781665456128

Multi-reference least mean square algorithm (MR-FXLMS) has been performed more efficiently than the traditional Least mean square algorithm (FXLMS). In this paper, a multi-reference adaptive gain (MRAG-FXLMS) algorithm which is designed to enhance the performance of the multi-reference FXLMS algorithm. the proposed method is derived by combining a novel multi-reference structure and adaptive gain. the adaptive gain is obtained by using the gradient descent method. To evaluate the effectiveness of the proposed algorithm, a computational complexity analysis is conducted. According to the simulation results, it can be concluded that the proposed MRAG-FXLMS algorithm achieves excellent performance in convergence rate and steady-state error compared with the conventional FXLMS algorithm and MR-FXLMS algorithm. © 2023 IEEE.

关键词： Active noise control

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37th international conference on Industrial, Engineering and Other Applications of Applied Intelligent systems, IEA/AIE 2024

37th International Conference on Industrial, Engineering and...

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37th international conference on Industrial, Engineering and Other Applications of Applied Intelligent systems, IEA/AIE 2024

ISBN: (纸本)9789819746767

the proceedings contain 41 papers. the special focus in this conference is on Industrial, Engineering and Other Applications of Applied Intelligent systems. the topics include: A Sparse Binary Data Clustering Method for Transaction Data;improving Noise Robustness of Automatic Speech Recognition Based on a Parallel Adapter Model with Near-Identity Initialization;reconsidering Stochastic Policy Gradient Methods for Traffic Signal control;Hybrid Additive Manufacturing: A Convergence of Physical, Digital, and Social Realms Driven by Generative AI;towards Eco-Friendly Multi-compartment Transportation: A New Bi-objective Iterated Local Search Framework;simulation Optimization of Operating Room Schedules for Elective Surgeries;learning Causality Under Uncertainty for Egocentric Action Anticipation;time Heals Unfairness: Efficient Dynamic Routing at an Autonomous Society;Parallel Implementation of a Convolutional Neural Network on an MPSoC;deep Residual Networks for Pigmented Skin Lesions Diagnosis;weightless Neural Networks Based on Multi-valued Probabilistic Logic for Node for the Handwritten Digit Classification;formal Verification of Neural Networks: A "Step Zero" Approach for Vehicle Detection;PPG-Based Heart Rate Estimation Using Unsupervised Domain Adaptation;a Novel Multi-task Single-Step Traffic Congestion Forecasting Framework for Large-Scale Road Networks;towards Addressing an Open Problem in Coupled Matrix Tensor Factorization for Satellite Imagery Data Using Human-in-Loop;representation and Generation of Music: Incorporating Composers’ Perspectives into Deep Learning Models;evaluation Techniques for Long Short-Term Memory Models: Overfitting Analysis and Handling Missing Values;Live Product Line Engineering Using Density-Based Clustering of CAD Models;fog-Based Ransomware Detection for Internet of Medical things Using Lighweight Machine Learning Algorithms;verifying Autoencoders for Anomaly Detection in Predictive Maintenance;a computer Vision Based Approach fo

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Exploring the Development of Flexible Network Subsystems in Communications Software Design 15

Exploring the Development of Flexible Network Subsystems in ...

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15th international conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Mamatha, G.N. Pandeya, Megha Saraswat, Bhawna School of Engineering and Technology Department of Electronics and Communication Engineering Karnataka Bangalore India Maharishi University of Information Technology Maharishi School of Engineering & Technology Uttar Pradesh India Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India

ISBN: (纸本)9798350370249

the development of cutting-edge telecommunications systems more and more call for the implementation of community subsystems which might be bendy and can unexpectedly reply to modifications in user visitors. Such flexibility requires the layout of a structure able to scaling to distinctive gadget demands while nevertheless being capable of maintain excessive overall performance, reliability, and availability. this paper gives a systematic exploration of the strategies, gear, and ideas important in designing a bendy community subsystem for telecommunications software. We speak the necessities and challenges of developing network structures, and have a look at the feasibility of employing current trendy protocols which includes SIP, SDP, and RTP as a part of a usual structure. Furthermore, we speak the advantages and downsides of using software program-defined networking (SDN) as a part of a flexible community subsystem, along with issues for deploying it. Updates to present community control structures to assist dynamic reconfiguration are explored, in addition to an assessment of in-house and 1/3-celebration answers for integration into a bendy community subsystem. Sooner or later, key layout issues for deploying and managing a flexible community subsystem are discussed and summarized. © 2024 IEEE.

关键词： Downsides Implementation Necessities Networking Nevertheless Telecommunications

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Password Authentication for Older People: Problems, Behaviours and Strategies 11

Password Authentication for Older People: Problems, Behaviou...

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11th international conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2025

作者： Merdenyan, Burak Petrie, Helen Department of Computer Science University of York Heslington East York United Kingdom

ISBN: (纸本)9789897587436

Many aspects of life are now conducted online, and many services requiring a secure account, usually password protected. Creating and tracking many online accounts and passwords is difficult for everyone. For older people it may be particularly problematic but vitally important as online accounts now give access to many healthcare, financial and support services. this study used an online questionnaire to investigate the behaviours, problems, and strategies in relation creating and using password-protected online accounts with a sample of 75 older UK participants (aged 65 to 89) and compare them with a similar sample of young UK participants (aged 18 to 30). the results were surprising, with unexpected differences between the groups, but many similarities. For example, older participants had no difficulties creating passwords of the right length, whereas young participants had difficulties in that task. Older participants had many more complex strategies for creating and remembering passwords, while young participants relied more on re-using old passwords with small changes which then probably caused difficulties remembering them. these results suggest we need to rethink the approach to better supporting older people in password creation and use, taking a more universal design approach, supporting all users with a range of options. Copyright © 2025 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Engineering education

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Building Lightweight Semantic Search Engines

Building Lightweight Semantic Search Engines

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IEEE international conference on e-science and Grid Computing

作者： Michael Rovatsos Rosa Filgueira School of Informatics The University of Edinburgh Edinburgh United Kingdom School of Computer Science University of St Andrews St Andrews United Kingdom

Despite significant advances in methods for processing large volumes of structured and unstructured data, surprisingly little attention has been devoted to developing general practical methodologies that leverage state-of-the-art technologies to build domain-specific semantic search engines tailored to use cases where they could provide substantial benefits. this paper presents a methodology for developing these kinds of systems in a lightweight, modular, and flexible way with a particular focus on providing powerful search tools in domains where non-expert users encounter challenges in exploring the data repository at hand. Using an academic expertise finder tool as a case study, we demonstrate how this methodology allows us to leverage powerful off-the-shelf technology to enable the rapid, low-cost development of semantic search engines, while also affording developers with the necessary flexibility to embed user-centric design in their development in order to maximise uptake and application value.

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17th international conference on the Simulation of Adaptive Behavior, SAB 2024

17th International Conference on the Simulation of Adaptive ...

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17th international conference on the Simulation of Adaptive Behavior, SAB 2024

ISBN: (纸本)9783031715327

the proceedings contain 26 papers. the special focus in this conference is on Simulation of Adaptive Behavior. the topics include: Vector-Based Navigation Inspired by Directional Place Cells;a Behavior-Based Model of Foraging Nectarivorous Echolocating Bats;benefit of Varying Navigation Strategies in Robot Teams;no-brainer: Morphological Computation Driven Adaptive Behavior in Soft Robots;cuttleBot: Emulating Cuttlefish Behavior and Intelligence in a Novel Robot Design;the Emergence of a Complex Representation of Touch through Interaction with a Robot;analyzing Multi-robot Leader-Follower Formations in Obstacle-Laden Environments;spatio-Temporal Dynamics of Social Contagion in Bio-inspired Interaction Networks;behavioural Contagion in Human and Artificial Multi-agent systems: A Computational Modeling Approach;transient Milling Dynamics in Collective Motion with Visual Occlusions;extended Swarming with Embodied Neural Computation for Human control over Swarms;bio-Inspired Agent-Based Model for Collective Shepherding;DaNCES: A Framework for Data-inspired Agent-Based Models of Collective Escape;the Role of Energy Constraints on the Evolution of Predictive Behavior;influence of the Costs of Acquisition of Private and Social Information on Animal Dispersal;integrated Information in Genetically Evolved Braitenberg Vehicles;neural Chaotic Dynamics for Adaptive Exploration control of an Autonomous Flying Robot;non-instructed Motor Skill Learning in Monkeys: Insights from Deep Reinforcement Learning Models;memory-Feedback controllers for Lifelong Sensorimotor Learning in Humanoid Robots;extracting Principles of Exploration Strategies with a Complex Ecological Task;the Cost of Behavioral Flexibility: Reversal Learning Driven by a Spiking Neural Network;"Value" Emerges from Imperfect Memory;the Role of theory of Mind in Finding Predator-Prey Nash Equilibria;nonverbal Immediacy Analysis in Education: A Multimodal Computational Model.

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Dissecting Digital Dangers: A MITRE-Aligned Analysis of Two Prominent Malware Instances 15

Dissecting Digital Dangers: A MITRE-Aligned Analysis of Two ...

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15th international conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Rao, Subhiksha Suresh Mishra, Sahil Rajesh, M. Savant, Richa Vivek Sreevidya, B. Department of Computer Science & Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (纸本)9798350370249

the increasing complexity of malware requires a more thorough comprehension of how they operate. Using the MITRE ATT&CK framework, this project delves into the TrickBot and AsyncRAT malwares, offering a thorough examination of their tactics, techniques, and procedures (TTPs) across the cyber kill chain. this study uncovers trends in how these malicious software gain entry, carry out tasks, remain active, and extract information from a network by correlating TTPs with ATT&CK methods. Key analyses indicate that TrickBot utilizes elevated entropy values to avoid being detected, incorporates modular structures to enhance its capabilities, and utilizes spear-phishing and network spreading to achieve broad infection. AsyncRAT is found to employ sophisticated anti-analysis methods, reflective code loading, and achieves persistence by altering the system registry while avoiding sandbox environments. Additionally, it establishes command and control (C2) connections to maintain long-term access over compromised systems. the observations uncovered in this research emphasize the importance of having strong cybersecurity policies and comprehensive threat intelligence to combat changing threats effectively. Understanding the complex behaviours and evasion methods of these malwares is crucial for creating specific defences and improving security overall. ©2024 IEEE.

关键词： Phishing

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Synthesizing Point Cloud Data Set for Historical Dome systems 19th

Synthesizing Point Cloud Data Set for Historical Dome System...

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19th international conference on computer-Aided Architectural Design (CAAD) - Design Imperatives - the Future is Now

作者： Gunes, Mustafa Cem Mertan, Alican Sahin, Yusuf H. Unal, Gozde Ozkar, Mine Istanbul Tech Univ Architectural Design Comp Grad Program TR-34437 Istanbul Turkey Istanbul Tech Univ Fac Comp & Informat Engn Comp Engn TR-34469 Istanbul Turkey Istanbul Tech Univ Dept Architecture TR-34437 Istanbul Turkey

ISBN: (纸本)9789811912801;9789811912795

this paper offers a workflow for generating synthetic point cloud data sets to be used in deep learning algorithms in tasks of modeling historical architectural elements. Documentation of cultural heritage is a time-consuming process that requires high precision. Computational and semi-automatic tools enhance conventional methods to shorten the duration of the documentation phase and increase the accuracy of the output. Photogrammetry and laser scanning are how geometrical data is acquired and delivered as a point cloud with position, color, and optionally normal vector information. Segmenting architectural elements based on our interpretations of this data is possible using deep neural networks but is limited when, despite the millions of points from one building, the data is insufficient in terms of variance and quantity. To overcome this limitation, we propose a semi-automatic synthetic data set generation using parametric definitions of historic architectural elements. We create a synthetic dataset, namely the Historical Dome Dataset (HDD), consisting of nearly 1000 dome systems with four semantic classes. We quantitatively and qualitatively analyze the usefulness of the HDD by training a number of modern neural networks on it. Our method of synthesizing point clouds can quickly be adapted into similar cultural heritage projects to prepare relevant data to accurately train deep neural networks and process the collected cultural heritage data.

关键词： Cultural heritage Synthetic data set Point clouds Deep learning Training data

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Intelligent Network Architecture for Home Automation and Efficient Solution for Appliance control in Smart Grid 4

Intelligent Network Architecture for Home Automation and Eff...

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4th international conference on Electrical, computer and Telecommunication Engineering, ICECTE 2022

作者： Al Mamun, Abdullah Jewel, Mehedi Hasan Paul, Parag Kumar Rahin, Saima Ahmed Bangladesh Army International University of Science and Technology Department of Electrical and Electronic Engineering Cumilla Bangladesh United International University Department of Computer Science and Engineering Dhaka Bangladesh United International University Department of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350320541

the field of 'Internet of things' (IoT) technology is exploding because of the quick advancements in automation technologies, embedded systems, and networking. It has become an integral part of Home Automation which is the combination of sensor networks, cloud computing, monitoring, and control. this paper discusses networking and provides two distinct methods for managing network-connected appliances as well as two different strategies for controlling the connected appliances and devices resulting in the enhancement of the system's robustness and overall stability. LoRa and 2.4GHz Wi-Fi technology have been used for the networking architecture of the appliances. Direct load control and phase angle-based voltage control methods are designed and developed for controlling the connected appliances. the distinct wireless technologies increase the stability of data transmission while ensuring minimum power consumption. AC voltage control methodology followed in this research also improves the robustness of the control systems. A mobile application platform is also developed and presented in this paper which is used to monitor and control the appliances, also known as sensor nodes. © 2022 IEEE.

关键词： Internet of things

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Citrus Leaf Disease Prediction: Deep Feature Fusion Perspective 5th

Citrus Leaf Disease Prediction: Deep Feature Fusion Perspect...

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5th international conference on Deep Learning, Artificial Intelligence and Robotics, ICDLAIR 2023

作者： Palei, Shantilata Lenka, Rakesh Kumar Behera, Santi Kumari Sethy, Prabira Kumar Nanda, Sandeep Barik, Rabindra Kumar Computer Science and Engineering International Institute of Information Technology Bhubaneswar Odisha Bhubaneswar751003 India Computer Science and Engineering Veer Surendra Sai University of Technology Odisha Sambalpur768018 India Electronics Sambalpur University Odisha Sambalpur768019 India Computer Science and Engineering Sanskriti University Uttar Pradesh Mathura281401 India School of Computer Applications Kalinga Institute of Industrial Technology Odisha Bhubaneswar751024 India

ISBN: (纸本)9783031609343

Citrus disease is a major problem of economic and productive loss in agriculture worldwide. Crops are affected by uneven climatic conditions, which leads to lower agricultural yields. this will affect the world’s agricultural economy. this paper proposes an image recognition method based on machine learning (ML) and deep learning (DL) feature fusion techniques for citrus leaf disease prediction. the three most popular CNN models were considered. the CNN models were AlexNet, vgg16, and vgg19. the features of these CNN models were extracted and fed into the support vector machine (SVM) to classify citrus leaf diseases. these classification models were evaluated in terms of performance metrics calculation. Subsequently, the multilayer feature fusion technique was adapted to the best-performing CNN models. Here, vgg16 performed the best among AlexNet, vgg16, and vgg19. then, the different combinations of feature fusion of vgg16 are adapted. these fused features were fed into the SVM for citrus leaf disease classification. the feature fusion of ‘fc6 plus fc7’ of vgg16 with SVM yielded the best results;that is, the maximum values of accuracy, sensitivity, specificity, precision, FPR, F1 score, MCC, and Kappa coefficient were 97%, 97%, 98.09%, 97.06%, 1.58%, 95.34%, 84.4%, and 86.79% respectively. this method is very much helpful to the farmer as well as to the customers. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Citrus fruits

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