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Using Ontologies for the Development of the University Educational Ecosystem 22

Using Ontologies for the Development of the University Educa...

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22nd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2021

作者： Pustovalova, Natalya Avdeenko, Tatiana Pustovalova, Alexandra Novosibirsk State Technical University Dept. Automation and Computer Engineering Novosibirsk Russia Novosibirsk State Technical University Dept. Applied Mathematics and Computer Science Novosibirsk Russia

ISBN: (纸本)9781665414982

The paper considers the possibility of improving the educational ecosystem by using ontologies in the architecture of the university electronic information environment. Various types of actors of the modern educational ecosystem, interacting within the educational process with educational resources, are presented;their needs that are relevant for its development shortly are analyzed. This paper describes a general approach to using ontology as an element of the IT architecture of a university. Formalizing objects of the educational process in the form of ontology (OWL, RDF models) allows creating various applications for its intellectual support, ensuring the uniformity of architectural solutions and further evolutionary development of the university information environment based on the IEEE LOM and TinCanAPI standards. © 2021 IEEE.

关键词： Ontology

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Collaborative Intrusion Detection System for Intermittent 10 Vs Using Federated Learning and Deep Swarm Particle Optimization

Collaborative Intrusion Detection System for Intermittent 10...

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International Conference on Data science and Advanced Analytics (DSAA)

作者： Farhan Ullah Gautam Srivastava Leonardo Mostarda Diletta Cacciagrano Division of Computer Science University of Camerino Camerino Italy Dept. of Math and Computer Science Brandon University Brandon MB Canada Department of Mathematics and Computer Science University of Perugia Perugia Italy School of Software Northwestern Polytechnical University Xian China

ISBN: (数字)9798350364941

ISBN: (纸本)9798350364958

Intelligent vehicles have significantly influenced the advancement of Intelligent Transportation Systems (ITS). Smart city consumers increasingly depend on vehicular cloud services, highlighting the need for a stronger Internet of Vehicles (IoV s) architecture. Moreover, smart cities deliver high-performance cloud services using multiple technologies, increasing concerns about communication security across entities exchanging indi-vidual requester data. An intelligent privacy-preserving Intrusion Detection System (IDS) is needed to secure IoV data. This work presents a Federated Learning (FL) approach for intermittent IoVs that uses Deep Swarm Particle Optimisation (DSPO) to choose features optimally while protecting user privacy. This approach enables remote IoVs to access shared data securely, ensuring operational confidentiality and privacy. By integrating DPSO with FL, it enhances data analysis and model training for IoV s, optimizing deep learning models for efficient feature selection in secured distributed environments. This cooperative technique not only protects data privacy but also fosters collaboration among IoV devices. We evaluate the proposed method using two standard datasets, namely CICloV2024 and CICEVSE2024. Despite the intermittent nature of IoVs and imbalanced datasets, our approach gives the highest performance.

关键词： Training Cloud computing Analytical models Privacy Smart cities Intrusion detection Feature extraction Data models Security Optimization

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Work in Progress: First Experiences with a Flipped Online Statistics Classroom for Engineering Students

Work in Progress: First Experiences with a Flipped Online St...

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2021 International e-Engineering Education Services Conference, e-Engineering 2021

作者： Andersson, Christina Kroisandt, Gerald Frankfurt University of Applied Sciences Dept. of Computer Science and Engineering Germany Htwsaar School of Engineering Germany

ISBN: (纸本)9781728134703

Unmotivated students, acting as passive consumers, wanting to pass the exam with the least possible effort, is a common problem in basic statistics courses in undergraduate engineering education. Our course in statistics for industrial engineering students is also affected by this passivity problem. One additional issue in this course is that it is part of the study program Industrial Engineering Online, i.e. the tuition of the course takes place online, which can even more strengthen the passivity problem. Therefore, we decided to introduce active learning components in the teaching framework of the course. This paper describes the challenges and opportunities we encountered, when we flipped the online classroom in order to encourage the students to become more active learners and at the same time, hopefully, feel more motivated to take the basic statistics course. © 2021 IEEE.

关键词： Statistics

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Pose-free visual servoing from 3D measurements

Pose-free visual servoing from 3D measurements

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European Control Conference (ECC)

作者： Adrian Burlacu Radu L. Rosca Andrei I. Iancu Enric Cervera Dept. of Automatic Control and Applied Informatics Gheorghe Asachi Technical University of Iasi Romania Dept. of Computer Science and Engineering Jaume I University Spain

In this paper, a novel approach to visual servo control robotic systems is proposed. It is focused on developing a solution using 3D point features without recovering the rigid object’s pose. Pose-free motion is achieved using motion parameterization techniques based on dual numbers and dual vectors. Considering an imposed velocity field over the motion of the 3D point features ensemble, this work proposes a close-form solution to a visual servoing problem. The solution provides stable motion control while preserving the image features in the field of view. However, when some point features leave the field of view, their contribution to the control law is dropped without losing stability. The proposed solution is easy to tune and implement. Various scenarios are used in simulations and real experiments to show how the proposed solution overcomes classic servoing problems.

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Optimal Local Parameters For Hermite Type Cubic Splines

Optimal Local Parameters For Hermite Type Cubic Splines

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International Conference on Engineering of Modern Electric Systems (EMES)

作者： Alexandru Mihai Bica Eugen Laslo Cristian G. Crainic Dept. of Math. and Computer Science University of Oradea Oradea Romania Dept. of Forestry and Forest Eng. University of Oradea Oradea Romania

The local derivatives of Hermite type cubic splines are optimally determined on each subinterval of a given mesh through a set of five classical interpolation procedures in order to minimize a certain objective function. We construct an iterative method that selects on each subinterval, the adequate algorithm for providing the local derivatives which minimize the objective function such that the values of the local derivatives computed at the previous subinterval are preserved in order to keep the smoothness of the spline. The admissible set of classical interpolation procedures consists of the natural cubic spline, the Catmull-Rom cubic spline, the Akima's cubic spline, and the cubic splines with minimal derivative oscillation and those with minimal deviation by the data polygon. A numerical experiment is presented in order to illustrate the performances of the algorithm.

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Evaluation and Comparison of Facial Recognition Technology in Drawn Portraits

Evaluation and Comparison of Facial Recognition Technology i...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Cheng Chang Yong-Yi Fanjiang Chi-Huang Hung Jung-Hua Chen Kiem-Trinh Phung Van-Duc Trieu Graduate Institute of Applied Science and Engineering Fu Jen Catholic University New Taipei City Taiwan Dept. of Computer Science and Information Engineering Graduate Institute of Applied Science and Engineering Fu Jen Catholic University New Taipei City Taiwan Dept. of Information Technology Graduate Institute of Applied Science and Engineering Fu Jen Catholic University Lee-Ming Institute of Technology New Taipei Taiwan Dept. of Computer Science and Information Engineering Fu Jen Catholic University New Taipei City Taiwan Dept. Electronical Engineering Lee-Ming Institute of Technology New Taipei City Taiwan

ISBN: (数字)9798350355079

ISBN: (纸本)9798350355086

Numerous studies have proposed various methods and applications for facial recognition. In camera-equipped environments, these methods can easily identify real faces. However, recognizing faces on printed or Portrait Drawing becomes more complex. In other words, real faces are three-dimensional, and while algorithms can sample feature values, identifying portrait drawing face on paper is relatively more challenging. This study evaluates and compares the effectiveness of various facial recognition techniques on paper-based images, including Haar-cascade, MTCNN, and Dlib 68 feature points.

关键词： Accuracy Image recognition Face recognition Image augmentation Face detection Faces Standards Consumer electronics

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Contextual decision-making with knapsacks beyond the worst case 24

Contextual decision-making with knapsacks beyond the worst c...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Zhaohua Chen Rui Ai Mingwei Yang Yuqi Pan Chang Wang Xiaotie Deng School of Computer Science Peking University Haidian Beijing China IDSS & LIDS Massachusetts Institute of Technology Cambridge MA Dept. of Management Science and Engineering Stanford University Stanford CA School of Engineering and Applied Sciences Harvard University Cambridge MA Dept. of Computer Science Northwestern University Evanston IL School of Computer Science Institute for Artificial Intelligence Peking University Haidian Beijing China

ISBN: (纸本)9798331314385

We study the framework of a dynamic decision-making scenario with resource constraints. In this framework, an agent, whose target is to maximize the total reward under the initial inventory, selects an action in each round upon observing a random request, leading to a reward and resource consumptions that are further associated with an unknown random external factor. While previous research has already established an Õ(√T) worst-case regret for this problem, this work offers two results that go beyond the worst-case perspective: one for the worst-case gap between benchmarks and another for logarithmic regret rates. We first show that an Ω(√T) distance between the commonly used fluid benchmark and the online optimum is unavoidable when the former has a degenerate optimal solution. On the algorithmic side, we merge the re-solving heuristic with distribution estimation skills and propose an algorithm that achieves an Õ(1) regret as long as the fluid LP has a unique and non-degenerate solution. Furthermore, we prove that our algorithm maintains a near-optimal Õ(√T) regret even in the worst cases and extend these results to the setting where the request and external factor are continuous. Regarding information structure, our regret results are obtained under two feedback models, respectively, where the algorithm accesses the external factor at the end of each round and at the end of a round only when a non-null action is executed.

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OCI Runtime Comparison and Analysis Study 5

OCI Runtime Comparison and Analysis Study

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5th IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2022

作者： Jeon, Sung Hwan Shim, Simon Chung, Haejin Nah, Yunmook Dept. of Data Science Graduate School Dankook University Yongin-si Korea Republic of Dept. of Computer Engineering San Jose State University San Jose United States Cha Mirisa College Duksung Women's University Seoul Korea Republic of Dept. of Applied Computer Eng. Dankook University Yongin-si Korea Republic of

ISBN: (数字)9781665471206

ISBN: (纸本)9781665471206

Containers are one of the technologies required for cloud services. Because containers use resources directly on the host, they are lighter and faster than traditional virtual machines. However, it has the disadvantage of poor security and isolation. To solve this problem, security-oriented runtimes such as Kata, gVisor, and Firecracker have emerged. Each runtime is created differently, so performance and resource usage are different. In this study, performance and evaluation of each lowlevel runtime are conducted. © 2022 IEEE.

关键词： Containers

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Two-Area Power System with Automatic Generation Control Utilizing PID Control, FOPID, Particle Swarm Optimization, and Genetic Algorithms 4

Two-Area Power System with Automatic Generation Control Util...

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4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Sati, Madan Mohan Kumar, Dinesh Singh, Akhilesh Raparthi, Mohan Alghayadh, Faisal Yousef Soni, Mukesh Graphic Era Hill University Deptt. of Mathematics Bhimtal263136 India Srm Institute of Science and Technology Dept. of Computer Science and Engg. UP Ghaziabad201204 India Uttarakhand Technical University Campus Institute Deptt. of Electrical Engg. Pithoragarh India Alphabet Life Science Software Engineer DallasTX75063 United States Almaarefa Univ Riyadh College of Applied Sci Computer Science and It Department Saudi Arabia Dr. D. Y. Patil Vidyapeeth School of Science and Technology Pune India

ISBN: (纸本)9798350343670

This study aims to present a feasible LFC (Load Frequency Control) model that integrates physical security limitations, namely GRC, GDB, and TD. The presence of this characteristic guarantees that the design is not only accurate but also capable of being materialized in a physical form. It is suggested that the traditional PI controller be replaced with a PID controller in order to handle the issues that are posed by large-scale power systems that are interconnected. Developing extremely efficient soft computing approaches that are capable of producing the necessary results for both individual and extensive power systems while taking into consideration flaws in modeling is the goal of this endeavor. It is important to get the frequency deviation to zero while still following the rules set by real issues and different working conditions. In order to maintain the electrical flow between the inter-area tie lines that are located within the various control zones at the schedule values that have been specified. In order to achieve optimal levels of performance in both steady state and transient conditions. The purpose of this is to obtain valuable multiple solutions with the intention of future planning and design. It is important to simplify the robust load frequency control design problem by changing it into a low-order proportional integral derivative (PID) control synthesis problem in order to address the practical benefits. This approach is commonly employed in real-world power systems applications. © 2024 IEEE.

关键词： and TD (Transmission Delay ANN BBBC FOPID GDB (Generation Demand Balance) GRC (Generation Rate Constraint) Load Frequency Control (LFC) PID PSO

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The YOLOv8 Edge: Harnessing Custom Datasets for Superior Real-Time Detection 18

The YOLOv8 Edge: Harnessing Custom Datasets for Superior Rea...

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18th IEEE International Conference on Emerging Technologies, ICET 2023

作者： Ahmed, Tafreed Maaz, Ahmad Mahmood, Danyaal Abideen, Zain Ul Arshad, Usama Ali, Raja Hashim BCMaterials Basque Center for Materials Applications & Nanostructure Basque Country Leioa Spain Gik Institute of Engg. Sciences & Technology Faculty of Computer Science & Engineering Topi Pakistan University of Europe for Applied Sciences Dept. of Technology & Software Engineering Berlin Germany

ISBN: (纸本)9798350328172

YOLO has become a central real-time object detection system for robotics, driverless cars, and video monitoring applications. Developing a custom object detection solution that can detect specific objects in real-time video streams has the potential to revolutionize various fields and has been the subject of extensive research. Although there have been advances in object detection, there is still a gap in the research for real-time detection of custom objects with high accuracy and speed. This research addresses this gap by training a YOLOv8 detector on a custom dataset of objects and evaluating its performance on real-time video streams which is by far the latest model and thus is faster and more accurate. Our experimental results demonstrate that our custom-trained YOLOv8 detector achieves high accuracy and real-time performance on a custom dataset of objects. The detector achieved an overall mAP50 of 0.864 and a mAP50-95 of 0.758, with individual class results ranging from 0.47 to 0.995. These findings show that custom training data and YOLOv8 are effective in real-time object detection, which has practical applications in various fields. The significance of the results and our contribution lies in demonstrating the effectiveness of custom training data for improving object detection accuracy and speed using YOLO, which has implications for a wide range of real-world applications. © 2023 IEEE.

关键词： Object detection

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