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A Personalized Book Recommender System for Adults Based on Deep Learning and Filtering 15

A Personalized Book Recommender System for Adults Based on D...

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15th international conference on Knowledge Discovery and Information Retrieval, KDIR 2023 as part of the 15th international Joint conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2023

作者： Ng, Yiu-Kai Computer Science Department Brigham Young University TMCB ProvoUT3361 United States

ISBN: (纸本)9789897586712

Reading improves the reader's vocabulary and knowledge of the world. It can open minds to different ideas which may challenge the reader to view things in a different light. Reading books benefits both physical and mental health of the reader, and those benefits can last a lifetime. It begins in early childhood and continue through the senior years. A good book should make the reader curious to learn more, and excited to share with others. For some readers, their reluctance to read is due to competing interests such as sports. For others, it is because reading is difficult and they associate it with frustration and strain. A lack of imagination can turn reading into a rather boring activity. In order to encourage adults to read, we propose an elegant book recommender for adults based on a deep learning and filtering approaches that can infer the content and the quality of books without utilizing the actual content, which are often unavailable due to the copyright constraint. Our book recommender filters books for adult readers simply based on user ratings, which are widely available on social media, for making recommendations. Experimental results have verified the effectiveness of our proposed book recommender system. Copyright © 2023 by SCITEPRESS - science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Recommender systems

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EARIC: Exploiting ADC Registers in IoT and control systems 21st

EARIC: Exploiting ADC Registers in IoT and Control Systems

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21st international conference on Applied Cryptography and Network Security (ACNS)

作者： Chekole, Eyasu Getahun thulasiraman, Rajaram Zhou, Jianying Singapore Univ Technol & Design Singapore Singapore

ISBN: (纸本)9783031411809;9783031411816

An analog-to-digital converter (ADC) is a critical part of most computing systems as it converts analog signals into quantifiable digital values. Since most digital devices operate only on digital values, the ADC acts as an interface between the digital and analog worlds. Hence, ADCs are commonly used in a wide-range of application areas, such as internet of things (IoT), industrial control systems (ICS), cyberphysical systems (CPS), audio/video devices, medical imaging, digital oscilloscopes, and cell phones, among others. For example, programmable logic controllers (PLCs) in ICS/CPS often make control decisions based on digital values that are converted from analog signals by ADCs. Due to its crucial role in various applications, ADCs are often targeted by a wide-range of physical and cyber attacks. Attackers may exploit vulnerabilities that could be found in the software/hardware of ADCs. In this work, we first conduct a deeper study on the ADC conversion logic to scrutinize relevant vulnerabilities that were not well explored by prior works. Hence, we manage to identify exploitable vulnerabilities on certain ADC registers that are used in the ADC conversion process. these vulnerabilities can allow attackers to launch dangerous attacks that can disrupt the behaviour of the targeted system (e.g., an IoT or control system) in a stealthy way. As a proof of concept, we design three such attacks by exploiting the vulnerabilities identified. Finally, we test the attacks on a mini-CPS testbed we designed using IoT devices, analog sensors and actuators. Our experimental results reveal high effectiveness of the proposed attack techniques in misleading PLCs to make incorrect control decisions in CPS. We also analyze the impact of such attacks when launched in realistic CPS testbeds.

关键词： ADC Security ADC Vulnerabilities ADC Attacks CPS Security ICS Security PLC Attacks IoT Security

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

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

引用

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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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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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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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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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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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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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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