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Graph Transformer Hawkes Processes for Causal Structure Learning in Telecom Networks 18th

Graph Transformer Hawkes Processes for Causal Structure Lear...

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18th international conference on Wireless Artificial Intelligent computing systems and applications, WASA 2024

作者： Yin, Shiwei Li, Ying Wang, Jiandong Kong, Yu College of Computer Science and Technology Qingdao University Qingdao266701 China

ISBN: (纸本)9783031714634

the event sequence in telecommunications networks covers important data such as communication records and system alarms, which is crucial for fault detection and network management. However, existing causality discovery algorithms have challenges on casual discovery in telecom networks. To this end, we design the Graph Transformer Hawkes Process (GthP) model to reveal the causal relationships behind event sequences in telecom networks. Our proposed model is contributed to allow the use of transformer's self-attention mechanism with Hawkes process for casual discovery. To begin with, the proposed GthP injects graph structure information into Transformer's self-attention by graph convolution networks to construct a graph transformer block, which effectively captures the long-range casual dependencies between event types. We then combine the graph transformer block with Hawkes process, in which the intensities of multiple event types evolve based on a continuous-time transformer mechanism. the extensive experiments are implemented for measuring the performance of GthP in real-world telecom data. It demonstrates that GthP has an obvious improvement in comparison with the baselines. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Continuous time systems

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Simulink-Based real-time Control of ABB Industrial 6-DOF Manipulators for Advanced Robotic applications

Simulink-Based Real-Time Control of ABB Industrial 6-DOF Man...

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Human-Computer Interaction, Optimization and Robotic applications (HORA), international Congress on

作者： Paolo Righettini Roberto Strada Filippo Cortinovis Jasmine Santinelli Federico Tabaldi Dept. of Engineering and Applied Sciences University of Bergamo Italy

ISBN: (数字)9798331510886

ISBN: (纸本)9798331510893

Industrial robots have long played a key role in advanced manufacturing thanks to their reprogrammability and adaptability to varied production scenarios. However, due to ever growing requests in terms of efficiency, flexibility, and integration with other equipment, the traditional approach to robot programming, based on the definition of predefined motions, appears increasingly strained. Leading manufacturers of industrial robots have accordingly adapted through the introduction of communication interfaces that allow external computing units to control the manipulator finely and at a high frequency. this work proposes in particular an architecture that enables the control of ABB 6-DOF robot arms using Simulink-based computing platforms, with a special focus on the achievement of hard real-time capabilities. the performance achievable by the resulting system is then experimentally evaluated in a sample, non-standard motion task, with satisfactory results. the overall architecture is shown to be especially suitable for research purposes due to its compatibility on the one hand with a powerful simulation environment and on the other with a wide range of further hardware components such as sensors, cameras and DAQ boards, the use of which may integrated with that of the robot. the main goal of enabling future investigation into topics related to advanced robotic is thus achieved.

关键词： Program processors Service robots Robot vision systems Computer architecture Manipulators Industrial robots real-time systems 6-DOF Sensors Robots

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Lightweight Intrusion Detection for IoT systems Using Artificial Neural Networks 19th

Lightweight Intrusion Detection for IoT Systems Using Artifi...

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19th international conference on Security and Privacy in Communication Networks

作者： Saleh, Radhwan A. A. Al-Awami, Louai Ghaleb, Mustafa Abudaqa, Anas A. King Fahd Univ Petr & Minerals KFUPM Dept Comp Engn Dhahran 31261 Saudi Arabia KFUPM Interdisciplinary Res Ctr Intelligent Secure Syst Dhahran 31261 Saudi Arabia

ISBN: (纸本)9783031649530;9783031649547

Internet of things (IoT) systems, due to their vulnerability to a plethora of security attacks, suffer significant detrimental impacts on their reliability. Additionally, the inherent constraints in IoT devices necessitate the incorporation of lightweight security schemes endowed with the capacity to identify intrusions and serve as a robust line of defense. this study presents a lightweight Intrusion Detection System (IDS) that leverages the power of Artificial Neural Network (ANN) while addressing the challenges within IoT systems. the effectiveness of the proposed IDS has been validated through empirical testing by utilizing the ToN IoT Telemetry dataset. the proposed IDS exhibits superior performance compared to other Machine Learning-based IDS solutions identified in the literature, particularly in terms of binary classification where the feature set is continuous. the proposed IDS consistently exceeds expected benchmarks in multi-class classification, with metrics including recall, precision, accuracy, and F-score ranging between 91% and 100%. More importantly, its high accuracy and low time complexity make it an ideal choice for real-time applications, offering a superior alternative to existing AI-based IDS.

关键词： Intrusion Detection System Lightweight Internet of things Machine Learning Artificial Neural Network

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RISC-V Accelerators, Enablement and applications for Automotive and Smart Home in the ISOLDE Project 24th

RISC-V Accelerators, Enablement and Applications for Automot...

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24th international conference on Embedded Computer systems: Architectures, Modeling, and Simulation

作者： Ciobanu, Catalin Bogdan Galmeanu, Honorius Puscasu, Alexandru Gologanu, Mihai Buiu, Octavian Antonescu, Mihai Serbu, Vlad-Gabriel Moise, Vasile-Madalin Axinte, Cristian-Tiberius Popovici, Alexandru-Tudor Uleru, George-Iulian Stan, Andrei Munteanu, Mihai Drimbarean, Alexandru Nemeti, Csaba Rotar, Danut Comma Grosu, Daniel Moisa, Cosmin Ditu, Bogdan Trusca, Petre Cristian Antache, Marius Costinescu, Simona Sachian, Mari-Anais Suciu, George Gheorghe, Cristian Tudor, Cristina Koci, Kejsi Natl Inst Res & Dev Microtechnol IMT Bucharest Romania Transilvania Univ Brasov Brasov Romania Natl Univ Sci & Technol Politeh Bucharest Bucharest Romania Gheorghe Asachi Tech Univ Iasi Iasi Romania FotoNat SRL Brasov Romania Continental Automot Romania Timisoara Romania NXP Semicond Romania Bucharest Romania BEIA Consult Int Bucharest Romania FotoNat Ltd Galway Ireland

ISBN: (纸本)9783031783791;9783031783807

With Artificial Intelligence applications becoming ubiquitous, both industrial and consumer applications require more computing availability. the increasing need for power-constrained Artificial Intelligence computing asks for new and innovative solutions, on both hardware design as well as on software toolchains that leverage them. At the same time, the challenge of EU technological sovereignty encourages an industry trend oriented to developing its own solutions for power efficient High Performance computing (HPC). In this context, as partners in the ISOLDE project started in 2023, we propose the development of new power efficient embedded HPC accelerators, HPC design platforms, as well as High Level Synthesis (HLS) approaches and toolchain technology designs for RISC-V based applications. Specifically, we envisage applications such as Fast Fourier Transform, Number theoretic Transforms, Post Quantum computing and artificial intelligence, as well as designing ONNX targeted toolchains based on the LLVM compiler, open solutions for Neural Networks (NN) accelerators and new OpenMP extensions. Within the ISOLDE framework, the envisaged applications to prove the readiness of these technologies are the Automotive and the Smart Home demonstrators.

关键词： RISC-V HPC Polymorphic Register File PolyMem AI Accelerator HLS AI Compiler ONNX LLVM OpenMP

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Inventory Management using Near Field Communication (NFC)

Inventory Management using Near Field Communication (NFC)

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Mobile computing and Sustainable Informatics (ICMCSI), international conference on

作者： Abhay Chopde Vedant Keche Apoorv Karmalkar Manas Kasodekar Department of E&TC Engineering Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

this research creates an NFC-inclusive website-based inventory management system that enhances tracking and management of stock. Scanning these tags allows users to obtain a specific product description without wasting time searching through the inventory. the solution is designed to enhance accuracy, efficiency, and user-friendliness for the convenience of the business through enhanced real time tracking and management ofinventories.

关键词： Accuracy Databases Near field communication Medical services Manuals Inventory management real-time systems Mobile applications Manufacturing Mobile computing

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From Concept to reality: A Systematic Review of Urban Digital Twin and their applications in Smart Cities 20th

From Concept to Reality: A Systematic Review of Urban Digita...

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20th international conference on computing in Civil and Building Engineering, ICCCBE 2024

作者： Huang, Hao Tsou, Jin Yeu Department of Architecture and Civil Engineering City University of Hong Kong Kowloon Hong Kong

ISBN: (纸本)9783031842078

Metropolises comprise six primary systems that serve distinct domains: governance, environment, mobility, economy, living, and society. these systems work together to create a macrosystem that constitutes a city. In contemporary urban planning, Smart Cities (SCs) have emerged as a means of effectively managing and integrating critical infrastructure, optimizing resource allocation, coordinating maintenance activities, and addressing complex urban challenges while prioritizing security. Over the past few years, cutting-edge technologies like Wireless Sensor Networks, Building Information Modeling, Internet of things (IoT), Virtual reality, Big Data Analytic, Artificial Intelligence (AI), Cloud computing, Blockchain, and Cyber-Physical systems have paved the way for intelligent and groundbreaking solutions in a variety of industries. Built on the knowledge gained from developing SCs and implementing Digital Twins (DTs) in other sectors, the Urban Digital Twin (UDT) has rapidly expanded in just a few years. UDT technology utilizes real-time data, simulation, machine learning, and reasoning to provide valuable assistance in decision-making processes. However, more than informatization and digitalization practices are required to embrace UDT fully. there has yet to be a comprehensive analysis of how to apply these features of DTs to manage SCs better. this review paper analyzed 150 papers that focused on DT-supported SCs. We aim to identify the drivers, challenges, and future directions for applying UDT-supported technologies. We systematically investigated the characteristics and mechanisms of DTs, categorized different technologies based on their application stages, and identified the key challenges, benefits, and open issues. the findings inform stakeholders in urban management to establish a foundation for future design, development, and widespread adoption of UDT. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Resource allocation

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IoT-Based Smart Farming: Benefits, Attacks, and Security Solutions

IoT-Based Smart Farming: Benefits, Attacks, and Security Sol...

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Human-Computer Interaction, Optimization and Robotic applications (HORA), international Congress on

作者： Kadir Ileri Electrical & Electronics Engineering Bandirma Onyedi Eylul University Balikesir Turkey

ISBN: (数字)9798331510886

ISBN: (纸本)9798331510893

the integration of Internet of things (IoT) technology in agriculture has transformed traditional farming into smart farming by enabling precision agriculture through real-time data collection, automation, and intelligent decision-making processes. IoT-based smart farming integrates technologies such as big data analytics, artificial intelligence (AI), and cloud computing to optimize resource usage and enhance productivity. However, the increasing reliance on IoT in agriculture also brings cybersecurity risks. Smart farming systems are vulnerable to various cyberattacks such as data breaches, malware, ransomware, and denial-of-service (DoS) attacks. these attacks can disrupt operations, compromise data integrity, impact food supply chains, and threaten global food security. this paper discusses the benefits of IoT technologies in smart farming and explores the security challenges in IoT-based smart farming by categorizing threats, identifying system vulnerabilities, and evaluating potential security solutions. By addressing these critical security challenges, this study aims to support the development of more resilient and secure smart farming systems.

关键词： Smart agriculture Productivity Precision agriculture Automation Supply chains real-time systems Security Internet of things Artificial intelligence Computer crime

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A Music Recommender System to Identify the Emotional State of a Person Using Machine Learning Algorithms 4

A Music Recommender System to Identify the Emotional State o...

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4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Muruganantham, A. Malarvizhi, C. Divya Vahini, S. Saranya, D. Uthiramoorthy, A. Karnataka Bengaluru India Psg Institute of Advanced Studies Department of Computer Science Coimbatore India Dr.Mahalingam College of Engineering and Technology Department of Computer Applications Tamil Nadu Pollachi India Sri Eshwar College of Engineering Department of Information Technology Coimbatore India Rathinam College of Arts and Science Department of Computer Science India

ISBN: (纸本)9798331523923

In today's digital world, customized recommendation algorithms can improve user experiences in many different areas. Within the sphere of intelligent human-technology interaction, this paper specifically examines a music recommender system driven by machine learning algorithms. It figures out what mood users are in and can provide an appropriate response in real time. the system being propounded in this essay uses advanced technology in facial expression recognition. With the help of a webcam, it aims to accurately detect user emotions, including joy, sadness, and anger. Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) and Support Vector Machines (SVM) have been employed to effectively classify people's mood and recommend an appropriate song. Our extensive tests and examinations show that CNN, RNN, and SVM models are all very good at guessing users' moods - with high precision, recall, F1-score, and accuracy percentages. Furthermore, in-depth analyses like confusion matrixes illuminate how well each model serves as an emotion recognizer. this study's findings are representative of future prospects in affective computing around the globe with major implications for intelligent recommendation systems to which it's important that the models are sensitive. In conclusion, the suggested Music Recommender System is something new for taking a more personal view: We can be as deeply entertained as the web allows us to be - make tailored entertainment paths in the digital era. © 2025 IEEE.

关键词： Convolutional neural networks

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3D Reconstruction of Building Models Based on 2D Floor Plans Using Statistical Analysis 12th

3D Reconstruction of Building Models Based on 2D Floor Plans...

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12th international conference on Frontiers of Intelligent computing: theory and applications, FICTA 2024

作者： Gasiorowski, Pawel Vassilev, Vassil School of Computing and Digital Media Cyber Security Research Center London Metropolitan University 166-220 Holloway Road LondonN7 8DB United Kingdom

ISBN: (纸本)9789819601424

the focus on interior architecture within the real estate sector has intensified, with floor plans serving as the primary method for illustrating spatial layouts, encompassing rooms, doors, and windows. With advancements in image processing, computer vision, and graphics, it is now feasible to reconstruct and visualize building interiors in 3D. this paper concentrates on the approximate reconstruction of a suburban kindergarten in Sofia, Bulgaria, in 3D for future visualization of indoor pollution levels on a basis of data produced by sensors installed on the premises. We use well-established image processing algorithms for extracting features from a 2D floor plan, classify them statistically, and convert them into GeoJSON format for subsequent 3D reconstruction in Unity game engine. By successfully approximating the internal structure of the kindergarten building, our approach demonstrates significant potential. the results suggest avenues for refinement and application in comparable settings, offering advancements in building analysis and environmental monitoring alike. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Floors

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Character Recognition Using Convolutional Neural Networks Based on CUDA

Character Recognition Using Convolutional Neural Networks Ba...

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international Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Set Paing Tun Applied Mathematics and Artificial Intelligence Department National Research University “MPEI” Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

the article explores character recognition using convolutional neural networks (CNNs) optimized with the CUDA platform to enhance computational efficiency. It outlines the CNN architecture, methods for leveraging GPU-based parallel data processing, and presents experimental results derived from the MNIST dataset. the study highlights that implementing CUDA drastically reduces processing time while maintaining a high level of predictive accuracy. the findings emphasize the potential of GPU acceleration in handling intensive computational tasks, making it a promising approach for real-time applications in image recognition and machine learning.

关键词： Deep learning Training Energy consumption Graphics processing units Parallel processing real-time systems Energy efficiency Convolutional neural networks Character recognition Optimization

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