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检索条件"任意字段=International Conference on Engineering of Reconfigurable Systems and Algorithms"

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Supervised machine learning for intrusion detection: A survey and performance evaluation

Supervised machine learning for intrusion detection: A surve...

引用

international conference on Innovation and Technological Advances for Sustainability, ITAS 2023

作者： Chkirbene, Zina Hamila, Ridha College of Engineering Qatar University Qatar

ISBN: (纸本)9781032803722

Cloud computing is a cost-effective way to host and deliver services over the internet, but the large volume of data transmitted makes the cloud network a target for malicious attacks. To protect against these threats, various intrusion detection systems (IDSs) have been developed to identify different types of attacks on the network. However, some of these systems are not always efficient due to the level of human involvement they require. Machine learning approaches, which have been widely used in IDSs, have the potential to improve efficiency by building well-trained models for anomaly detection using large datasets with a variety of attack types. In this paper, we examine the current state of research on using machine learning techniques for IDSs and evaluate the suitability of different algorithms using the UNSW dataset. We compare the accuracy rate and classification performance of several algorithms to determine their effectiveness. © 2025 The Author(s).

关键词： Network intrusion

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Sum Rate Maximization in STAR-RIS Assisted Full-Duplex Communication systems

Sum Rate Maximization in STAR-RIS Assisted Full-Duplex Commu...

引用

IEEE international conference on Communications (ICC)

作者： Perera, Pulasthi P. Warnasooriya, Vanodhya G. Kudathanthirige, Dhanushka Suraweera, Himal A. Univ Peradeniya Dept Elect & Elect Engn Kandy Sri Lanka Cornell Coll Dept Phys & Engn Mt Vernon IA 52314 USA

ISBN: (数字)9781538683477

ISBN: (纸本)9781538683477

The sum rate performance of simultaneous transmitting and reflecting reconfigurable intelligent surface (STARRIS) assisted full-duplex (FD) communication systems is investigated. The reflection and transmission coefficients of STARRIS elements are optimized for the energy splitting and mode switching protocols to maximize the weighted sum rate of the system. The underlying optimization problems are non-convex, and hence, the successive convex approximation technique has been employed to develop efficient algorithms to obtain suboptimal solutions. Thereby, the maximum average weighted sum rate and corresponding coefficients at the STAR-RIS subject to predefined threshold rates and unit-modulus constraints are quantified. The performance of the proposed system design is compared with the conventional reflecting/transmitting-only RISs and half-duplex counterparts via simulations where it is observed that STAR-RIS can boost the performance of FD systems.

关键词： Protocols Half-duplex system Full-duplex system Switches Quality of service reconfigurable intelligent surfaces Reflection

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Design & Development of an Automatic Defense System for Warfare Applications 15

Design & Development of an Automatic Defense System for Warf...

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15th international conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Tejas, R. Venkatesh, L. Shivamadu, D.N. Ravishankar, K. Ninawe, Swapnil S. Gunjal, Samyama G.H. Pavithra, G. Manjunath, T.C. Department of Electronics & Communication Engineering Dayananda Sagar College of Engineering Bangalore India Department of Computer Science & Engineering University Visvesvaraya College of Engineering Bangalore University Karnataka Bengaluru India

ISBN: (纸本)9798331300579

This paper presents the design and implementation of an automated defence system interface leveraging Arduino *** an era of evolving security threats, the development of automatic defense systems has become increasingly *** abstract provides a concise overview of automatic defense systems, focusing on their technologies and *** defense systems encompass a wide range of technologies, including sensors, artificial intelligence, robotics, and communication *** systems are designed to detect, analyze, and respond to potential threats in real-time, minimizing human intervention and response *** components of automatic defense systems include sensor arrays for threat detection, data processing algorithms for threat analysis, and autonomous or semi-autonomous response *** core typically involves sensors (radar, lidar), a command-and-control system for threat evaluation, and countermeasures (missiles, lasers, guns).Applications of automatic defense systems span various domains, including military, homeland security, critical infrastructure protection, and public *** systems offer enhanced situational awareness, rapid threat response, and scalability to adapt to evolving security *** technology continues to advance, the integration of emerging technologies such as machine learning, drones, and IoT further enhances the capabilities of automatic defense *** project "Design & Development of an Automatic Defense System for Warfare Applications" focuses on creating a sophisticated, autonomous defense mechanism aimed at enhancing security and operational efficiency in military *** system integrates advanced sensor technologies, real-time data processing, and artificial intelligence to detect, identify, and neutralize potential threats with minimal human *** features include robust target recognition algorithms, adaptive threat response capabilities, and seamless in

关键词： Optical radar

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Hybrid Adaptive Biased Optical OTFS for RIS-assisted OWC systems

Hybrid Adaptive Biased Optical OTFS for RIS-assisted OWC Sys...

引用

2024 Asia Communications and Photonics conference, ACP 2024 and international conference on Information Photonics and Optical Communications, IPOC 2024

作者： Tang, Shuang Pei, Jianhua Liao, Yuxuan Zhang, Xiao-Ping Song, Jian Dong, Yuhan Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Department of Electronic Engineering Tsinghua University Beijing100084 China

ISBN: (纸本)9798350379266

Adaptive biased optical orthogonal time frequency space (ABO-OTFS) faces challenges in achieving optimal spectral efficiency due to the presence of unused Doppler bins within the system. To address this, we propose two novel hybrid ABO-OTFS (HABO-OTFS) technologies for reconfigurable intelligent surface (RIS)-assisted optical wireless communication (OWC) systems. HABO1-OTFS integrates ABO-OTFS with pulse amplitude modulated discrete multitone (PAM-DMT), offering a straightforward implementation that enables the receiver to directly extract data without the need for complex demodulators. On the other hand, HABO2-OTFS combines ABO-OTFS with various hybrid schemes in a layered approach, providing enhanced flexibility and more efficient utilization of spectral resources. Numerical results demonstrate that both HABO1-OTFS and HABO2-OTFS significantly outperform the existing ABO-OTFS in terms of peak-to-average power ratio (PAPR), spectral efficiency, and power efficiency, underscoring their potential for superior performance in RIS-assisted OWC systems. © 2024 IEEE.

关键词： Adaptive optics

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On the Analysis and Application of Bio-Inspired algorithms for Smart Navigation in Mobile Healthcare Robots 6

On the Analysis and Application of Bio-Inspired Algorithms f...

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6th international conference on Electrical, Control and Instrumentation engineering, ICECIE 2024

作者： Dsouza, Karen Jane Sajikumar, Adwaith Muthukumaraswamy, Senthil A. School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore School of Engineering and Physical Science Heriot-Watt University Dubai United Arab Emirates

ISBN: (纸本)9798350380040

In recent years, healthcare robotics has emerged as a promising solution to address the challenges of nurse burnout and shortages, while simultaneously enhancing patient care. Non-contact vitals monitoring has gained significance in reducing the spread of infectious diseases, exemplified by its role during the COVID-19 pandemic. Among various types of healthcare robots, wheeled mobile robots stand out due to their versatility and potential for autonomous navigation. However, achieving efficient and intelligent navigation in dynamic healthcare environments remains a complex problem. This paper examines behavior-based algorithms and evolutionary algorithms, which take inspiration from biological systems and swarm intelligence. Using these algorithms, the aim is to enhance the capabilities of healthcare robots, allowing them to navigate complex environments with ease and efficiency. This study encompasses an evaluation of popular healthcare robots, such as Dr. Spot, a non-contact vitals monitoring robot, and the versatile Temi robot. Through simulations using the Webots platform and the E-puck robot, we compare the performance of behavior-based and evolutionary algorithms. The results conclude the advantages of evolutionary algorithms in static environments. However, their limitations are observed in dynamic settings, where adaptation is crucial. The findings of this research offer guidance for designing and implementing autonomous wheeled mobile robots in real-world healthcare settings, where efficient and safe navigation is vital to ensure quality patient care. © 2024 IEEE.

关键词： Mobile robots

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Nature-Inspired algorithms-Based Beamforming for Advanced Antenna systems 14th

Nature-Inspired Algorithms-Based Beamforming for Advanced An...

引用

14th EAI international conference on Ad Hoc Networks, AdHocNets 2023

作者： Van Luyen, Tong Van Anh, Nguyen Thi Van Cuong, Nguyen Duong, Tran Hai Trang, Le Thi Hanoi University of Industry Hanoi Viet Nam Faculty of Electronic Engineering Hanoi University of Industry Hanoi Viet Nam

ISBN: (纸本)9783031559921

In pursuit of enhancing the signal processing capabilities of antenna arrays for directed signal transmission and reception in spatial contexts, novel methodologies have been developed for advanced antenna systems. Leveraging cutting-edge technologies such as beamforming (BF) and multiple-input and multiple-output (MIMO) within smart antenna systems has emerged as a compelling strategy for elevating the quality of service, capacity, and coverage in mobile information systems. This paper presents a comparison, wherein algorithms inspired by natural processes are applied to amplitude-only controlled beamforming techniques. Subsequently, a comprehensive assessment is undertaken to discern the merits and demerits of the weight control methodologies employed. Specifically, this study delves into the application of bat algorithms, multi-verse optimization, hybrid particle swarm optimization, and gray wolf optimization in various scenarios. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Beamforming

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Anomalous Behavior Detection in ATM using Different Methodologies: A Review 3

Anomalous Behavior Detection in ATM using Different Methodol...

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3rd international conference on Automation, Computing and Renewable systems, ICACRS 2024

作者： Thakre, Harsh Bhushanwar, Kush Patel, Anil Computer Engineering Department PIET Parul University Gujarat Vadodara India

ISBN: (纸本)9798331532420

The necessity for standardized anomaly detection systems in financial transactions is driven by the alarming increase in ATM fraud and criminal activities. Many techniques for detecting anomalous behavior in ATM systems are also summarized and evaluated in this review article. To better secure financial institutions and customers from fraudsters, it is crucial to examine the reasoning behind these systems, particularly in the areas that pertain to improving security. The overarching purpose of this paper is to present a clear and succinct explanation of the cutting-edge machine learning (ML) and deep learning (DL) algorithms that are presently the backbone of ATM anomaly pattern detection, including more contemporary methods like transfer learning. This review delves into the theoretical foundations of these strategies and compares different algorithms, along with the values of performance indicators that show their strengths and drawbacks. Our goal is to show, via an examination of current methods in actual settings, any flaws or problems that may hinder the development of ATM security in the future. Finally, this work can be used by researchers and those interested in bettering ATM systems and associated secure technologies in the future to study the subject and explore anomaly detection technologies as a means of both practical experience and future advancement. © 2024 IEEE.

关键词： Adversarial machine learning

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Towards Precision Oncology: A Study of Machine Learning Models for Breast Cancer Prediction 10

Towards Precision Oncology: A Study of Machine Learning Mode...

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10th international conference on Advanced Computing and Communication systems, ICACCS 2024

作者： Gracious, L.A. Anto Pajila, P.J. Beslin Johncy, G. Anish, T.P. Prasanth, K. Siva Subramanian, R. R.M.K. College of Engineering and Technology Dept of Cse Tiruvallur India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Chennai India St. Xaviers Catholic College of Engineering Dept of Cse Nagercoil India Computer Science and Engineering S.A.Engineering College Chennai India R.M.K. College of Engineering and Technology Dept of Cse Puduvoyal India

ISBN: (纸本)9798350384369

The rapid growth in Breast Cancer (BC) related death is frightening, making it the most prominent cancer type and a cause of death of women worldwide. It is most important to have advancements in predicting and diagnosing cancer for promoting a healthier life. To increase the advancement in treatment and to increase the survivability of patients it is important to achieve a high level of accuracy in cancer prediction. The ML techniques have given a huge contribution in the prediction process and diagnosing BC, gathering noticeable attention in research, and demonstrating the desired result. The ML algorithms like SVM, RF, LR, C4.5, KNN are applied to the BC Wisconsin Diagnostic dataset. After getting the results, performance evaluation and comparisons were conducted among the various classifiers. The aim of the research paper is to find out and diagnose the BC with the help of the applications of ML algorithms, and with the most effective factors like recall, F-measure accuracy, and precision. SVM gave a good performance comparing to the other classifies by achieving the accuracy of 97.2%. The research describes the role of ML in improving the BC prediction and diagnosis, and providing a clear understanding about the effectiveness of different algorithms to improve the health conditions. © 2024 IEEE.

关键词： Lung cancer

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Integrating Machine Learning and Deep Learning Approaches for Accurate Cardiovascular Disease Prediction from Electronic Health Records

Integrating Machine Learning and Deep Learning Approaches fo...

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2025 international conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Natchathirah, V.S. Meera, T. Devi, S. Padma Velammal College of Engineering And Technology Department of Cse Madurai India

ISBN: (纸本)9798331509828

Cardiovascular diseases (CVDs) are a leading cause of death globally, making early prediction and identification of high-risk patients critical for improving treatment outcomes. This study examines the effectiveness of various machine learning and deep learning algorithms in predicting CVD using electronic health records (EHRs). We evaluate the performance of several ensemble methods, including Gradient Boosting, CatBoost, Random Forest, AdaBoost, and LightGBM (LGBM), alongside deep learning architectures such as Long Short-Term Memory (LSTM) and TABNET, utilizing a large EHR dataset. Our results reveal that CatBoost outperforms other ensemble methods, while TABNET achieves the highest accuracy among the deep learning models assessed. Furthermore, we investigate feature importance and the influence of hyperparameter tuning on model performance, providing insights into optimizing predictive capabilities. This research underscores the potential of advanced algorithms in enhancing early detection of CVD and supporting clinical decision-making. © 2025 IEEE.

关键词： Electronic health record

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Implementation of Path Planning Algorithm for AGV in Smart Warehouse 11

Implementation of Path Planning Algorithm for AGV in Smart W...

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11th international conference on Information Technology, Computer and Electrical engineering, ICITACEE 2024

作者： Davin, Arsenius Sofwan, Aghus Setiawan, Iwan Diponegoro University Faculty of Engineering Department of Electrical Engineering Semarang Indonesia

ISBN: (纸本)9798350389289

The inefficiency of traditional warehouse systems can lead to a 20% decrease in revenue and a 30% reduction in storage capacity within five years. Therefore, this study aims to design an AGV (Automated Guided Vehicle) capable of picking up and storing assets in the warehouse. The design focuses on enabling the AGV to choose the most optimal route. To achieve this, the method used in this research involves creating a warehouse map model using graph theory and employing the A∗ and D∗ algorithms for route selection. The heuristic value in both algorithms is calculated using Euclidean distance in addition to AGV turning costs. The findings demonstrate that, within the confines of the developed warehouse model, the D∗ algorithm perform slightly better than A∗ algorithm by approximately 1.02%. These results offer valuable insights into the efficacy of the D∗ algorithm in conjunction with graph theory mapping for warehouse navigation. By revealing the slight performance advantage of D∗ over A∗ in a static warehouse environment, this research contributes valuable insights for Industry 4.0 implementation. These findings can inform the selection of optimal pathfinding algorithms in warehouse automation, ultimately leading to improved efficiency and competitiveness within Indonesia's logistics sector. © 2024 IEEE.

关键词： Motion planning

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