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10th International Conference on Control, Instrumentation and Automation, ICCIA 2024

作者： Samadani, Mehraneh Moradi, Elahe Gavagsaz-Ghoachani, Roghayeh Islamic Azad University Science and Research Branch Environmental Science and Engineering Department Tehran Iran Shahre Rey Branch Department of Electrical and Computer Engineering Tehran Iran Shahid Beheshti University Faculty of Mechanical and Energy Engineering Renewable Energy Engineering Department Tehran Iran

ISBN: (纸本)9798331509972

This paper explores the impact of temperature on photovoltaic (PV) cell performance, emphasizing the critical role of innovative teaching methods in engineering education. By integrating illustrative representations and analogies, such as the popcorn analogy, complex concepts related to solar energy, and PV cell efficiency are made accessible. The study examines key factors, like the Shockley five-parameter model and the effects of environmental conditions on PV cell efficiency, highlighting how higher temperatures reduce open-circuit voltage (VOC) and overall power output. Using visual aids and storytelling techniques, aims to enhance student understanding and retention of these intricate topics. The findings underscore the importance of educational strategies that foster deeper comprehension and critical thinking, ultimately preparing future engineers to contribute effectively to sustainable energy solutions. This approach not only aids in better grasping the technical aspects but also cultivates a sense of environmental responsibility among students. © 2024 IEEE.

关键词： Cell engineering

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Automated Brain Tumor Detection Using Soft Computing-Based Segmentation Technique 3

Automated Brain Tumor Detection Using Soft Computing-Based S...

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3rd International Conference on Computing and Information Technology, ICCIT 2023

作者： Zubair, Muhammad Umair, Muhammad Owais, Muhammad University of Central Punjab Faculty of Information Technology & Computer Science Lahore Pakistan Khalifa University Kucars C2PS Dept of Electrical Engineering & Computer Science United Arab Emirates

ISBN: (纸本)9798350321487

Development and growth of abnormal cells within the brain results in brain tumor. In this study, a novel segmentation methodology is proposed for the segmentation of tumor. The proposed model consists of two phases. In the first phase, the brain CT image from the medical database is pre-processed to remove artifacts and noise. For Image segmentation, a Hierarchical Self Organizing Map (HSOM) is used that provides promising segmentation results. The conformist Self Organizing Map (SOM), which was used to categorize the picture row by row, is extended by the HSOM. Thus, the HSOM with vector quantization speeds up calculation at this lowest level of the weight vector, where there are more tumor pixels. The proposed automated system is tested on Kaggle (online available) database and achieves an accuracy of 98.94%. © 2023 IEEE.

关键词： Self organizing maps

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Robust Attacks Detection Model for Internet of Flying Things based on Generative Adversarial Network (GAN) and Adversarial Training

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IEEE Internet of Things Journal 2025年第13期12卷 23961-23974页

作者： Gaber, Tarek Ali, Tarek Nicho, Mathew Torky, Mohamed Engineering and Environment University of Salford School of Science Manchester United Kingdom Suez Canal University Faculty of Computers and Informatics Ismailia Egypt Manchester Metropolitan University Department of Computing and Mathematics Manchester United Kingdom Rabdan Academy Research and Innovation Centre Abu Dhabi United Arab Emirates University of Queensland School of Electrical Engineering and Computer Science Australia Egyptian Russian University-Badr City Faculty of Artificial Intelligence Cairo Egypt

The Internet of Flying Things (IoFT) holds significant promise in fields like disaster management and surveillance. However, it is increasingly vulnerable to cyberattacks that can compromise the confidentiality, integrity, and availability (CIA) of sensitive data. Despite the growing interest in proposing Intrusion Detection Systems (IDSs) for IoFT networks, current literature faces key limitations, particularly the shortage of publicly available IoFT datasets with diverse attacks, and the fact that existing IDSs lack robustness against sophisticated adversarial machine learning attacks. This paper is the first study to address these limitations by proposing a more resilient and accurate IDS tailored for IoFT networks (RIDS-IoFT). We introduce a novel IDS that leverages Generative Adversarial Networks (GANs) to generate a hybrid dataset that combines real IoFT traffic data with GAN-generated adversarial attacks, addressing the dataset diversity issue. Additionally, we introduce an innovative adversarial training method to enhance the system’s defense against evolving threats, such as Fast Gradient Sign Method (FGSM), Basic Iterative Method (BIM), and Carlini & Wagner (C&W) attacks. The proposed RIDS-IoFT was evaluated using four machine learning models, Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), and Logistic Regression (LR), on two datasets: ECU-IoFT and CICIDS2018. The IDS’s performance was assessed based on its ability to detect both traditional and adversarial attacks. The results show that the Random Forest model achieved the highest detection accuracy, up to 96.5%, demonstrating superior performance across both real and hybrid datasets. The proposed RIDS-IoFT not only enhances detection accuracy but also strengthens resilience against adversarial threats, making it suitable for resource-constrained IoFT environments. In conclusion, this study presents a comprehensive approach to securing IoFT networks by combining real and synthetic d

关键词： Generative adversarial networks

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A Highly-Accurate Robot Calibration Method with Line Constraint 20

A Highly-Accurate Robot Calibration Method with Line Constra...

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20th IEEE International Conference on Networking, Sensing and Control, ICNSC 2023

作者： Chen, Tinghui Li, Shuai Luo, Xin Chongqing University of Posts and Telecommunications School of Computer Science and Technology Chongqing China Faculty of Information Technology and Electrical Engineering Oulu Finland Southwest University College of Computer and Information Science Chongqing China

ISBN: (纸本)9798350369502

For the application of industrial robots, positioning accuracy is a significant indicator of their performance. Aiming at the issues of low positioning accuracy, the calibration techniques are employed to obtain the real kinematic parameters for effectively enhancing its accuracy. However, in practical scenarios, for the restriction of the robot workspace, the samples collected during the robot calibration process cannot cover the entire space of the entire space, resulting in an impact on data integrity. To address the above issues, we develop a calibrator integrating the MCS method (measurement configurations selection) and LM algorithm (Levenberg-Marquardt) with a spatial line constraint (LMLC), which contains three-fold: a) selecting a set of most representative measurement configurations according to the observability index for enhancing the stability of calibration results;b) develop an LM algorithm with line constraint to solve the problem of spatial restriction of robot sampling;c) presenting a robot calibrator that combines MCS and LMLC for efficiently improving the robot calibration accuracy. Experiments illustrate that the MCS-LMLC calibrator outperforms state-of-the-art calibrators on an industrial robot's calibration accuracy and computational efficiency. © 2023 IEEE.

关键词： Industrial robots

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Dynamic S-Box Generation Using Novel Chaotic Map with Nonlinearity Tweaking

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computers, Materials & Continua 2023年第5期75卷 3011-3026页

作者： Amjad Hussain Zahid Muhammad Junaid Arshad Musheer Ahmad Naglaa F.Soliman Walid El-Shafai School of Systems and Technology University of Management and TechnologyLahore54700Pakistan Department of Computer Science University of Engineering and TechnologyLahore54700Pakistan Department of Computer Engineering Jamia Millia IslamiaNew Delhi110025India Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

A substitution box(S-Box)is a crucial component of contemporary cryptosystems that provide data protection in block *** the moment,chaotic maps are being created and extensively used to generate these SBoxes as a chaotic map assists in providing disorder and resistance to combat cryptanalytical *** this paper,the construction of a dynamic S-Box using a cipher key is proposed using a novel chaotic map and an innovative tweaking *** projected chaotic map and the proposed tweak approach are presented for the first time and the use of parameters in their workingmakes both of these dynamic in *** tweak approach employs cubic polynomials while permuting the values of an initial S-Box to enhance its cryptographic *** of the parameters are provided using the cipher key and a small variation in values of these parameters results in a completely different unique *** analysis and exploration confirmed that the projected chaoticmap exhibits a significant amount of chaotic *** security assessment in terms of bijectivity,nonlinearity,bits independence,strict avalanche,linear approximation probability,and differential probability criteria are utilized to critically investigate the effectiveness of the proposed S-Box against several *** proposed S-Box’s cryptographic performance is comparable to those of recently projected S-Boxes for its adaption in real-world security *** comparative scrutiny pacifies the genuine potential of the proposed S-Box in terms of its applicability for data security.

关键词： Substitution-box chaotic map data security tweaking

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Extending the Common Greenhouse Ontology with Incident Reporting from Autonomous Systems

Extending the Common Greenhouse Ontology with Incident Repor...

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2024 Joint Ontology Workshops - Episode X: The Tukker Zomer of Ontology, and Satellite Events, JOWO 2024

作者： Eichhorn, Tim Chalan, Ghusen van Roozendaal, Simon Reil, Jens van Ee, Tim Moreira, João Rebelo Sales, Tiago Prince Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands TNO Netherlands Organization for Applied Scientific Research Netherlands Semantics Cybersecurity and Services University of Twente Netherlands

This paper presents the development of an extension to the Common Greenhouse Ontology (CGO) to enhance greenhouse automation, specifically focusing on incident reporting from autonomous systems. This research addresses the evolving landscape of technology in greenhouse operations and the need to support semantic interoperability among various components within a greenhouse ecosystem. By extending the CGO to accommodate robot-based autonomous systems, such as autonomous systems to combat diseases in crops and horticultural indoor positioning systems, this study aims to improve data transfer, understanding, and communication in smart horticulture projects. By designing the CGO extension based on practical implementations within the smart horticulture initiative of TNO and Hortivation, we demonstrate the effectiveness of the extended CGO for autonomous systems in enabling collaboration and standardised communication. The paper concludes by discussing the significance of the ontology extension in driving innovation and efficiency in greenhouse automation, while also highlighting areas for future exploration and refinement. © 2024 Copyright for this paper by its authors.

关键词： Ontology

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Novel Algorithm for Mobile Robot Path Planning in Constrained Environment

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computers, Materials & Continua 2022年第5期71卷 2697-2719页

作者： Aisha Muhammad Mohammed A.H.Ali Sherzod Turaev Ibrahim Haruna Shanono Fadhl Hujainah Mohd Nashrul Mohd Zubir Muhammad Khairi Faiz Erma Rahayu Mohd Faizal Rawad Abdulghafor Faculty of Manufacturing Engineering Universiti Malaysia Pahang(UMP)Pekan26600Malaysia Department of Mechanical Engineering Faculty of EngineeringUniversity of Malaya50603Kuala LumpurMalaysia Department of Computer Science and Software Engineering College of Information TechnologyUnited Arab Emirates UniversityAl AinUnited Arab Emirates Faculty of Electrical and Electronics Engineering Universiti Malaysia Pahang(UMP)Pekan26600Malaysia Department of Mechatronics Engineering Faculty of TechnologyBayero UniversityKano(BUK)700241Nigeria Computer Science and Engineering Department Chalmers and University of Gothenburg41296GothenburgSweden Department of Artificial Intelligence Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia Department of Computer Science Faculty of Information and Communication TechnologyInternational Islamic University Malaysia53100Kuala LumpurMalaysia

This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobilerobot path planning problem in a two-dimensional map with the presence ofconstraints. This approach gives the possibility to find the path for a wheelmobile robot considering some constraints during the robot movement inboth known and unknown environments. The feasible path is determinedbetween the start and goal positions by generating wave of points in alldirection towards the goal point with adhering to constraints. In simulation,the proposed method has been tested in several working environments withdifferent degrees of complexity. The results demonstrated that the proposedmethod is able to generate efficiently an optimal collision-free path. Moreover,the performance of the proposed method was compared with the A-star andlaser simulator (LS) algorithms in terms of path length, computational timeand path smoothness. The results revealed that the proposed method hasshortest path length, less computational time and the best smooth path. Asan average, GLS is faster than A∗ and LS by 7.8 and 5.5 times, respectivelyand presents a path shorter than A∗ and LS by 1.2 and 1.5 times. In orderto verify the performance of the developed method in dealing with constraints, an experimental study was carried out using a Wheeled Mobile Robot(WMR) platform in labs and roads. The experimental work investigates acomplete autonomous WMR path planning in the lab and road environmentsusing a live video streaming. Local maps were built using data from a live video streaming with real-time image processing to detect segments of theanalogous-road in lab or real-road environments. The study shows that theproposed method is able to generate shortest path and best smooth trajectoryfrom start to goal points in comparison with laser simulator.

关键词： Path planning generalized laser simulator wheeled mobile robot global path panning local path planning

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Machine learning assisted snort and zeek in detecting DDoS attacks in software-defined networking

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International Journal of Information Technology (Singapore) 2024年第3期16卷 1627-1643页

作者： AbdulRaheem, Muyideen Oladipo, Idowu Dauda Imoize, Agbotiname Lucky Awotunde, Joseph Bamidele Lee, Cheng-Chi Balogun, Ghaniyyat Bolanle Adeoti, Joshua Oluwatobi Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Ilorin 240003 Nigeria Department of Electrical and Electronics Engineering Faculty of Engineering University of Lagos Akoka Lagos 100213 Nigeria Department of Electrical Engineering and Information Technology Institute of Digital Communication Ruhr University Bochum 44801 Germany Research and Development Center for Physical Education Health and Information Technology Department of Library and Information Science Fu Jen Catholic University New Taipei City 24205 Taiwan Department of Computer Science and Information Engineering Asia University Taichung City 41354 Taiwan

A new network architecture called the Software-Defined Network (SDN) gives next-generation networks a more flexible and efficiently controlled network architecture. Using the programmable central controller design, network supervisors may easily supervise and manage the entire infrastructure. However, due to its centralized structure, SDN has been a target of various attack vectors. The most successful attack method against the SDN among these has been Distributed Denial of Service (DDoS). Therefore, this study proposes a snort and Zeek enabled with machine learning (ML) based model to classify the benign traffic from DDoS attack traffic. This study main contribution is the discovery of new features for DDoS attack detection, which made it difficult to distinguish authorized traffic from attack traffic when spread across so many points of origin. Using the ML-based enabled RYU controller with SNORT and ZEEK created fewer false positives and a smaller variety of true positives per attack than the existing methods. The processing time of ML-based enabled with SNORT and ZEEK on the real-time testbed is better contrasted to the existing methods. Using the open resource technologies offered a far better understanding of cyber safety and its benefits from the readily available programs to construct a solid network keeping an eye on the traffic. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Cybersecurity Distributed denial of service Intrusion detection systems Snort Software-defined networks Virtual machine Zeek

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Efficient multimodal cancelable biometric system based on steganography and cryptography

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Iran Journal of computer science 2023年第2期6卷 109-121页

作者： Salama, Gerges M. El-Gazar, Safaa Nassar, Rana M. El-Shafai, Walid Khalaf, Ashraf A. M. El-Banby, Ghada M. Hamed, Hesham F. A. El-Samie, Fathi E. Abd Department of Electrical Engineering Faculty of Engineering Minia University Minia 61111 Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Security Engineering Laboratory Department of Computer Science Prince Sultan University Riyadh 11586 Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electrical Engineering Faculty of Engineering Egyptian-Russian University Cairo Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh 84428 Saudi Arabia

Due to the development of hacking programs, it has become easy to penetrate systems. Hence, there is a need for strong security mechanisms. The use of traditional passwords has become insufficient to secure systems. Biometric authentication is now widely used for security applications, and it has proven to be superior compared to traditional authentication methods. However, two issues need to be considered in biometric systems. The first is not to keep biometric data in its original form in the database. If biometric traits are hacked, they will no longer be of use. Biometric data should be kept in cancelable forms for reuse. The second issue is the reliance on a single biometric, which limits the verification accuracy. This can be solved by using a multimodal biometric system. Using steganography and cryptography, this paper introduces a cancelable multimodal biometric system. As voiceprints, facial images, and fingerprint images are used. In this paper, the verification is performed through the Mel frequency cepstral coefficients (MFCCs) of the voiceprints. Steganography is used as a tool to secure features extracted from voiceprints by embedding them into the facial image using block-based singular value decomposition (BSVD). Double random phase encoding (DRPE) is utilized as an encryption algorithm to generate the final cancelable templates. To increase the level of system security, fingerprint images are used as random phase masks (RPMs). Verification is performed by estimating the correlation between registered and test MFCCs. The correlation value is then compared with a threshold value, which is calculated using the distribution curves for the genuine and imposter correlations. Equal error rate (EER) values close to zero and an area under the receiver operator characteristic curve (AROC) that is close to one are obtained from the simulation results, demonstrating the outstanding performance of the suggested system. The proposed system achieves good performan

关键词： BSVD Cancelable biometrics DRPE MFCCs

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Performance Comparison of dSPACE and MCU MPC Implementation in PV Power Optimizer

Performance Comparison of dSPACE and MCU MPC Implementation ...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Metry, Morcos Guler, Naki Rohouma, Wesam Balog, Robert S. Texas A&m University Department of Electrical and Computer Engineering Doha Qatar Gazi University Department of Electrical-Electronic Engineering Technology Faculty Ankara Turkey University of Doha for Science and Technology Department of Electrical Engineering Doha Qatar Texas A&m University Department of Electrical and Computer Engineering College StationTX United States

ISBN: (纸本)9798350316445

Finite control set model predictive control (MPC) can be computationally intensive especially when scaled up for more complicated converters since each state variable in the system is evaluated for all possible switching configurations. Multi-objective optimization of the cost function adds to the complexity of MPC. Much of the MPC literature in power electronics relies on expensive rapid prototyping (RP) platforms (RPP) such as dSPACE and OPAL RT. This paper aims to bridge the gap between expensive RPP and low-cost MCUs by exploring the feasibility of rapid prototyping (RP) on the low-cost F28379D launchpad. This paper is aimed toward the practitioner or researcher who desires to reduce to practice the MPC methods developed on a RPP to a lower-cost embedded controller. The suitability of a low-cost Texas Instrument (TI) launchpad to perform the same rapid-prototyping functions needed for MPC regulator development in a full-featured, high-end RPP is discussed. Experimental results using the dSPACE 1006 and the F28379D Launchpad showing steady-state performance and dynamic response are illustrated and compared. Comparative results show the F28379D launchpad and dSPACE 1006 offer similar performance markers. © 2023 IEEE.

关键词： Low-cost controller Model Predictive Control Power Electronics rapid prototyping platforms

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