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35th Irish systems and Signals Conference, ISSC 2024

作者： Hassard, Peter Kerr, Dermot School of Computing Engineering and Intelligent Systems Ulster University United Kingdom

ISBN: (纸本)9798350352986

This paper demonstrates how supervised machine learning algorithms can be leveraged to predict match outcomes from 2015/16 football season for matches in the top professional leagues of 5 countries (Spain - La Liga, England - Premier League, Italy - Serie A, Germany - 1. Bundesliga and France - Ligue 1). In the summer of 2023 StatsBomb released this free data;once important features on game play activity are generated and processed. A clear correlation between the match outcome and the location of a team's events on the pitch will be shown, moreover the ability to predict a match outcome based on the team's previous matches, this was done using their mean values for relevant features. For optimal prediction levels, the machine learning models in this paper had their hyperparameters selectively adjusted. © 2024 IEEE.

关键词： Forecasting

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Web Application Vulnerabilities 8

Web Application Vulnerabilities

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8th International Symposium on Computer Science and intelligent Control, ISCSIC 2024

作者： McNally, Stephen Curran, Kevin Ulster University School of Computing Engineering & Intelligent Systems Londonderry United Kingdom

ISBN: (纸本)9798350380286

In the digital age web applications have become a staple of our daily lives due to their convenience and efficiency. It is our main form of communication, transactions and how we access information. With the abilities of web applications, we have become reliant on them for our day-to-day tasks. Although this is not inherently bad, it has become clear that web application security is a paramount tool for online use, particularly among businesses and organisations. Web application security is the practice of protecting websites, applications, and APIs from attacks. This form of security aims to ensure that web applications function smoothly and remain unhindered by cyber vandalism, data theft, and other malicious attacks. This report will explore the top three vulnerabilities highlighted by the most recent OWASP top ten vulnerabilities report, last updated in 2021. These vulnerabilities include broken access control, cryptography failures and injection attacks. Moreover, each section will highlight how these security techniques defend, can be exploited and what measures developers can take to better defend web applications. The paper addresses the future of web application security in the context of emerging technologies such as artificial intelligence (AI) and machine learning. It speculates on how these technologies might be integrated into security strategies to enhance threat detection and response capabilities. The concept of DevSecOps is introduced as an evolutionary approach to integrate security into the development process of web applications, emphasizing the shift towards proactive security practices. In conclusion, the paper highlights the critical nature of web application security in the digital age. It provides a detailed examination of the most pressing vulnerabilities and offers guidance on implementing effective security measures. The aim is to equip developers, security professionals, and organizations with the knowledge and tools necessary to build

关键词： Cyber attacks

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Real-Time Human Pose Estimation as a Cost-Effective Solution for the Teleoporation of a 6-Axis Cobot Arm 22

Real-Time Human Pose Estimation as a Cost-Effective Solution...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Henderson, Benn Coleman, Sonya Kerr, Dermot Quinn, Justin Harrigan, Shane School of Computing Engineering and Intelligent Systems Ulster University Londonderry United Kingdom

ISBN: (纸本)9798331527471

This paper explores the application of BlazePose, a monocular human pose estimation (HPE) model, within a teleoperation framework for a UR5 six-axis robot. Achieving teleoperation with only a single RGB camera and a device without a powerful GPU will improve accessibility and cost effectiveness of teleoperation solutions. This study evaluates the 2D pose estimation capabilities of BlazePose for robotic teleoperation tasks. Given the necessity of manipulating the UR5 in three-dimensional space, we implement a 2D-based controller that translates the teleoperator’s 2D right hand position within a configurable hand workspace to the corresponding position of the robot’s Tool Centre Point (TCP) within the robot’s available workspace along two dimensions. The left hand is then utilised for controlling the robot’s motion along the third dimension and operating the attached OnRobot RG2 gripper during the pick- and-place task. Additionally, we explore an alternative control paradigm utilising the 3D pose estimation of BlazePose for a more intuitive controller. Two experiments are conducted: the pick-and-place task to assess the 2D-based controller in common robotic tasks, and a hold position task. The hold position task aims to assess the amount of excess movement attributable to the HPE model when utilising the 3D-based controller. The results reveal that while the 2D pose estimation capabilities enable effective teleoperation, the utilisation of 3D estimation results in poor translation to robot control and significant excess motion. These findings underscore the importance of accurate depth estimation in 3D HPE models for precise and reliable teleoperation. © 2024 IEEE.

关键词： Remote control

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INTEGRATING UNMANNED AERIAL systems INTO THE intelligent systems engineering CURRICULUM 34th

INTEGRATING UNMANNED AERIAL SYSTEMS INTO THE INTELLIGENT SYS...

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34th Congress of the International Council of the Aeronautical Sciences, ICAS 2024

作者： Dantsker, Or D. Department of Intelligent Systems Engineering Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN United States

This paper presents two hands-on, project-based courses on unmanned aerial systems recently offered by the intelligent systems engineering program at Indiana University. In Fall 2023, ENGR-E399/599 Autonomous Sports was redeveloped to focus on integrated vehicle design and development of lighter-than-air vehicles in a capstone-like, project-based course format. And in Spring 2024, ENGR-E399/599 Unmanned Aerial systems was developed to introduce students to UAS in a lecture-lab-project format where students learned about underlying aircraft concepts, developed a micro-controller-based autopilot, ultimately integrated it into a small fixed-wing unmanned aircraft that was test flown. These courses, geared towards advanced undergraduate and graduate students, allow them to apply their prerequisite knowledge to these hardware-lab heavy courses, enabling experiential learning, i.e. "learn-by-doing". © 2024, International Council of the Aeronautical Sciences. All rights reserved.

关键词： Students

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Cloud-based Learning for Robot Control

Cloud-based Learning for Robot Control

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2023 IEEE International Conference on Industrial Technology, ICIT 2023

作者： Harrigan, Shane Coleman, Sonya Kerr, Dermot Quinn, Justin Lindsay, Leeanne Madden, Kyle School of Computing Engineering and Intelligent Systems Ulster University Derry United Kingdom

ISBN: (纸本)9798350336504

This paper introduces the Virtual Manufacturing Platform (VMP), a cloud-complete educational platform targeting manufacturing industries providing tutorials and sandboxing. The scope of this paper focuses on the robot control architecture of the platform which allows for seamless control of both virtual and physical robots and end-effectors accompanied by supportive educational materials. The platform seeks to de-risk automation investments for small to medium enterprises by offering confirmatory environments and knowledge transfer opportunities. © 2023 IEEE.

关键词： End effectors

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Adaptive Fixed-Time Synchronization of Delayed Memristor-Based Neural Networks with Discontinuous Activations

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Computer Modeling in engineering & Sciences 2023年第1期134卷 221-239页

作者： Tianyuan Jia Xiangyong Chen Xiurong Yao Feng Zhao Jianlong Qiu School of Automation and Electrical Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of ShandongLinyi UniversityLinyi276005China The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and School of AutomationChina University of GeosciencesWuhan430074China

Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this *** continuous and discontinuous activations are considered *** the mixed delays which are closer to reality are taken into the ***,two kinds of control schemes are proposed,including feedback and adaptive control *** on some lemmas,mathematical inequalities and the designed controllers,a few synchronization criteria are ***,the upper bound of settling time(ST)which is independent of the initial values is ***,the feasibility of our theory is attested by simulation examples.

关键词： Memristor-based neural networks fixed-time synchronization mixed delays discontinuous activations adaptive control

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Enhancing Security: Evaluating RFID Card Access Control systems using SHA-256

Enhancing Security: Evaluating RFID Card Access Control Syst...

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2024 International Conference on Innovation and Intelligence for Informatics, computing, and Technologies, 3ICT 2024

作者： Yang, You Zhi Ramly, Athirah Mohd Sharif, Mhd Saeed Department of Computing and Information Systems Sunway University Selangor Malaysia School of Architecture Computing and Engineering UEL London United Kingdom Intelligent Technologies Research Group School of Architecture Computing and Engineering UEL London United Kingdom

ISBN: (纸本)9798331533137

This paper focuses on enhancing the security of a chosen system by implementing multiple layers of protection, including concealing sensitive data on the Liquid Crystal Display (LCD), utilizing hashed Unique Identifiers (UIDs), and deploying biometric dual-factor authentication via fingerprint recognition. The system is considered secure as it prevents unauthorized access attempts, even if the tag appears legitimate. The paper covers various stages, from component procurement to vulnerability assessment, exploitation, and solution development. While this paper significantly improves system security, further investigation remains crucial. Therefore, this paper not only addresses immediate security implementations but also paves the way for ongoing analysis and improvements aimed at defending the system against malicious threats while optimizing its performance. ©2024 IEEE.

关键词： Liquid crystal displays

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AFuNet: an attention-based fusion network to classify texts in a resource-constrained language

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Neural computing and Applications 2025年第9期37卷 6725-6748页

作者： Hossain, Md. Rajib Hoque, Mohammed Moshiul Dewan, M. Ali Akber Hoque, Enamul Siddique, Nazmul Department of Computer Science & Engineering Chittagong University of Engineering & Technology Chittagong4349 Bangladesh School of Computing and Information Systems Faculty of Science and Technology Athabasca University AthabascaABT9S 3A3 Canada School of Information Technology York University TorontoONM3J 1P3 Canada School of Computing Engineering and Intelligent Systems Ulster University Coleraine United Kingdom

In the era of widespread Internet use and extensive social media interaction, the digital realm is accumulating vast amounts of unstructured text data. This unstructured data often contain undesirable information, necessitating time-consuming manual classification efforts. An intelligent text classification system capable of automatically categorizing digitized texts based on semantic meaning is crucial. However, this task is particularly challenging for low-resource languages like Bengali due to a shortage of annotated corpora, issues with out-of-vocabulary words, lack of domain-specific hyperparameter tuning, limited ability to extract generalized text features, and class imbalances within the corpus. AFuNet: an attention-based fusion network to classify texts in a resource-constrained language. AFuNet undergoes a comprehensive four-phase experimental process, including baseline model evaluation and hyperparameter tuning, late fusion and model selection, attention-based early fusion and model identification, and an ablation study with impact analysis. Fine-tuned based on five Bengali text classification corpora, AFuNet achieves impressive accuracies: 96.60 ± 0.2 (BTCC11), 85.37 ± 0.2 (OSBC), 97.35 ± 0.2 (BARD), 93.74 ± 0.2 (IndicNLP), and 96.51 ± 0.2 (ProthomAlo). In comparison with previous state-of-the-art models on these corpora, AFuNet demonstrates significant accuracy improvements ranging from 0.54% to 4.49%, showcasing its effectiveness in advancing text classification capabilities for the Bengali language. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Semantics

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Leveraging Artificial Intelligence to Secure Wireless Network: Exploring Threats, Existing Approaches, and Proposed Mitigation Strategies

Leveraging Artificial Intelligence to Secure Wireless Networ...

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2024 International Conference on Innovation and Intelligence for Informatics, computing, and Technologies, 3ICT 2024

作者： Nan Xin, Alice Lee Ramly, Athirah Mohd Behjati, Mehran Sharif, Mhd Saeed Department of Computing and Information Systems Sunway University Selangor Malaysia School of Architecture Computing and Engineering UEL London United Kingdom Intelligent Technologies Research Group School of Architecture Computing and Engineering UEL London United Kingdom

ISBN: (纸本)9798331533137

The exponential growth of network has introduced new Internet-of-Things (IoT) use cases that has enabling us convenience and comfort. The surge of IoT devices due to the capabilities brought by fifth generation (5G) have given rise to security threats and attacks, particularly malware attacks IoT botnets have been an alarming issue, where smart devices can be manipulated by malicious actors to commence subsequent attacks such as Denial of Service (DoS). Traditional and complex security techniques may not be a viable solution towards these resource-constrained devices with limited processing power. Machine Learning techniques (ML) are the rising trend, and it is often used in Intrusion Detection systems and Network Anomaly Detection. This paper emphasizes on analyzing and comparing various ML models on the IoT-23 dataset. It aims to predict anomalies and conclude the model with optimal performance and least computational time cost that can be used for network anomaly detection systems with real-time data in future works. The ML models used in this paper are Decision Trees (DT), K-nearest neighbours (KNN), Random Forest (RF), Naïve Bayes (NB) and Histogram Gradient Boosting (HGB). DT displayed the best performance with an accuracy score of 73% and F1 score of 0.49 with a time cost of 28.22 seconds. ©2024 IEEE.

关键词： 5G mobile communication systems

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A Hybrid Multi-Objective Teaching Learning-Based Optimization Using Reference Points and R2 Indicator 22

A Hybrid Multi-Objective Teaching Learning-Based Optimizatio...

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6th International Conference on intelligent systems, Metaheuristics and Swarm Intelligence, ISMSI 2022

作者： Tahernezhad-Javazm, Farajollah Rankin, Debbie Coyle, Damien School Of Computing Engineering And Intelligent Systems Ulster University United Kingdom School Of Computing Engineering And Intelligent Systems Ulster University United Kingdom

ISBN: (纸本)9781450396288

Hybrid multi-objective evolutionary algorithms have recently become a hot topic in the domain of metaheuristics. Introducing new algorithms that inherit other algorithms' operators and structures can improve the performance of the algorithm. Here, we proposed a hybrid multi-objective algorithm based on the operators of the genetic algorithm (GA) and teaching learning-based optimization (TLBO) and the structures of reference point-based (from NSGA-III) and R2 indicators methods. The new algorithm (R2-HMTLBO) improves diversity and convergence by using NSGA-III and R2-based TLBO, respectively. Also, to enhance the algorithm performance, an elite archive is proposed. The proposed multi-objective algorithm is evaluated on 19 benchmark test problems and compared to four state-of-the-art algorithms. IGD metric is applied for comparison, and the results reveal that the proposed R2-HMTLBO outperforms MOEA/D, MOMBI-II, and MOEA/IGD-NS significantly in 16/19 tests, 14/19 tests and 13/19 tests, respectively. Furthermore, R2-HMTLBO obtained considerably better results compared to all other algorithms in 4 test problems, although it does not outperform NSGA-III on a number of tests. © 2022 Owner/Author.

关键词： Genetic algorithms

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