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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Jinshun Ou Jiying Ren Wenguang Li Panling Huang Jun Zhou Jiehan Zhou Tao Zhang School of Mechanical Engineering Shandong University Jinan China School of Computer Science and Technology Shandong University of Science and Technology Qingdao China Faculty of Information Technology and Electrical Engineering University of Oulu Oulu Finland Qingdao Hanhe Cable Co. Ltd. Qingdao China

ISBN: (数字)9798350391916

ISBN: (纸本)9798350391923

This paper presents a novel 2D laser data line feature extraction algorithm based on normal vector clustering(2D-LLFE-NVC). The algorithm consists of normal vector calculation, normal normalization based on multi-scale operator normal difference and median filter, and line feature extraction based on normal vector clustering. Unlike existing methods, 2D-LLFE-NVC leverages the continuity of laser point clouds and detects breakpoints using multi-scale operators based on normal differences. The extracted line features are more accurate and correct on a global scale. To validate its performance, we conducted SLAM experiments in a 5000-square-meter indoor environment using both the proposed algorithm and existing methods. By comparing the line feature points extracted by these different approaches with manually annotated line feature points, and demonstrating the superior performance of the proposed method in terms of correctness and completeness.

关键词： Point cloud compression Simultaneous localization and mapping Mechatronics Lasers Clustering algorithms Object segmentation Filtering algorithms Feature extraction Vectors Indoor environment

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Energy Landscape Shaping for Robust Control of Atoms in Optical Lattices

arXiv

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arXiv 2025年

作者： Weidner, C.A. O'Neil, S.P. Jonckheere, E.A. Langbein, F.C. Schirmer, S.G. Quantum Engineering Technology Laboratories H. H. Wills Physics Laboratory Department of Electrical and Electronic Engineering University of Bristol BristolBS8 1FD United Kingdom Department of Electrical Engineering and Computer Science United States Military Academy West PointNY10996 United States Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90007 United States School of Computer Science and Informatics Cardiff University CardiffCF24 4AG United Kingdom Faculty of Science & Engineering Physics Swansea University SwanseaSA2 8PP United Kingdom

Robust quantum control is crucial for realizing practical quantum technologies. Energy landscape shaping offers an alternative to conventional dynamic control, providing theoretically enhanced robustness and simplifying implementation for certain applications. This work demonstrates the feasibility of robust energy landscape control in a practical implementation with ultracold atoms. We leverage a digital mirror device (DMD) to shape optical potentials, creating complex energy landscapes. To achieve a desired objective, such as efficient quantum state transfer, we formulate a novel hybrid optimization approach that effectively handles both continuous (laser power) and discrete (DMD pixel activation) control parameters. This approach combines constrained quasi-Newton methods with surrogate models for efficient exploration of the vast parameter space. Furthermore, we introduce a framework for analyzing the robustness of the resulting control schemes against experimental uncertainties. By modeling uncertainties as structured perturbations, we systematically assess controller performance and identify robust solutions. We apply these techniques to maximize spin transfer in a chain of trapped atoms, achieving high-fidelity control while maintaining robustness. Our findings provide insights into the experimental viability of controlled spin transfer in cold atom systems. More broadly, the presented optimization and robustness analysis methods apply to a wide range of quantum control problems, offering a toolkit for designing and evaluating robust controllers in complex experimental settings. Copyright © 2025, The Authors. All rights reserved.

关键词： Robust control

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Clustering Approach for Modeling Course Difficulty Level in Adaptive Learning

Clustering Approach for Modeling Course Difficulty Level in ...

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IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications

作者： Imamah Umi Laili Yuhana Arif Djunaidy Eric Pardede Mauridhi Hery Purnomo Departement of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Departement of Informatics Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Departement of Information Systems Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Departement of Computer Science and Information Technology La Trobe University Bundoora VIC Australia

ISBN: (数字)9798350322996

ISBN: (纸本)9798350323009

The variations in students’ abilities present challenges in achieving desired learning outcomes. Students exhibit different levels of comprehension regarding the complexity of learning materials. In this study, we aim to model the difficulty levels of learning materials using a clustering approach to offer personalized learning material recommendations within an adaptive learning framework. Data were collected from student scores of Data Structure course obtained between 2020 and 2022 at the University of Trunojoyo Madura. The dataset modeling process adheres to the CRISP-DM Methodology, employing the K-Means clustering method and Euclidean Distance. We employed the Within-Cluster Sum of Squares (WCSS) metric and silhouette score to identify the optimal K-value, which resulted in a value of 5, accompanied by a silhouette score of 0.629. Our analysis pinpointed Stack and Deque as the easiest, while Linked List emerged as the most challenging course material. Accordingly, we will assign a label of 1 to the easiest materials, 2 to those of medium difficulty, and 3 to the most challenging ones. These labels will serve as criteria for recommending suitable learning materials to students based on their knowledge level. We will assess the ratio between the overall knowledge level score and the difficulty level of the material. The ratio value will serve as a reference for determining material recommendations for students. Materials categorized with the highest difficulty levels are exclusively suggested to students demonstrating faster learning abilities with a high value of ratio, and vice versa. This approach is feasible for implementation in adaptive learning.

关键词： Measurement Adaptive learning Adaptation models Computational modeling Clustering methods Virtual environments Euclidean distance

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An Innovative Method for Adjustable Broadband THz to Mid-IR Optical Modulator Using Graphene Gratings Surface Plasmon Fabry-Perot Resonances with Low Insertion Loss, High Speed and Modulation Depth

SSRN

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SSRN 2022年

作者： Jafari, Behnam Gholizadeh, Elnaz Golmohammadi, Saeed Ebadzadeh, Mohammadtaghy Soofi, Hadi Aghili, Sina Faculty of Electrical and Computer Engineering University of Tabriz Tabriz*** Iran School of Electrical Engineering and Computer Science University of Ottawa OttawaONK1N 6N5 Canada

Through numerical modeling, we present an ultrasensitive tunable Terahertz (THz) to Mid-IR modulator composed of single-layer graphene-based gratings combined with a Fabry–Perot (FP) cavity. The perpendicular-polarized incident light on gratings causes the grating edges to act as an electrical dipole, resulting in an FP interferometer of induced plasmonic waves on the graphene surface. The electric field in the cavity is substantially limited by the activation of standing-waves (SWs) graphene surface plasmon polaritons. The multi-mode SWs formation inside the gratings provides an excellent platform for THz to Mid-IR light modulation with promising features. We have demonstrated a modulation depth of 100% in desired frequencies with near zero insertion loss via full-wave electromagnetic simulations at the normal incident in the THz to Mid-IR range. The light reflection and absorption of the proposed structure have a multi-band profile due to the FP behavior. Therefore, it can be easily tuned by electrically directing the chemical potential of graphene. Due to multi resonance-based reflected light, each resonance represents different behavior with different modulation parameters. In other words, not only any desired frequency can be chosen, but also at the constant frequency of interest;by choosing the appropriate mode, the desired linewidth, FWHM, and modulation depth can be easily obtained. Finally, we investigated the device bandwidth. The THz modulator requires a large device area for an average number of gratings, and the device area the 3 dB frequency reaches as high as 1.5 THz, which depicts the high modulation speed in the proposed modulator. The proposed graphene plasmonic grating scheme is a promising candidate for developing the on-chip integrated THz to Mid-IR optical telecommunications. Moreover, the perfect absorption of graphene opens an opportunity to design photodetectors with high responsivity and quantum efficiency, which gives the proposed structur

关键词： Graphene

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Economic indicators evaluation to study the feasibility of a solar agriculture farm: A case study

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Solar Compass 2024年 10卷

作者： Gautam, Shivani Das, D. Bhagwan Saxena, Ajay Kumar Lecturer at Department of Physics and Computer Science Faculty of Science Dayalbagh Educational Institute (Deemed to be University) UP Dayalbagh Agra 282 005 India Professor at Department of Electrical Engineering Faculty of Engineering Dayalbagh Educational Institute (Deemed to be University) UP Dayalbagh Agra 282 005 India Professor Emeritus at Department of Electrical Engineering Faculty of Engineering Dayalbagh Educational Institute (Deemed to be University) UP Dayalbagh Agra 282 005 India

The 209 kWp solar agricultural farm at Dayalbagh Educational Institute's Dairy Campus in Agra, India, is the subject of this economic analysis. This study analyzes economic indicators relevant to agriculture food production, such as gross financial margins, farm profits, and cost-benefit ratios. Other measured variables include NPV (net present value), PB (payback period), and LCOE (levelized cost of electricity) of solar power generation to determine the economic viability of this agrivoltaics (production of solar energy and agriculture on the same land) APV project. Farm profit and gross financial margins both are positive values of 161, 907 INR (Indian Rupees) and 316, 907 INR, respectively. The cost-benefit ratio was *** economic factors of solar energy generation were studied for two systems: surface-mounted or ground-mounted solar systems and an elevated solar system with agriculture production on the same ground (APV or agrivoltaics). Both systems had the same production capacity. Two different hypothetical situations were used for each system. In the first situation (Case Study A), the assumption was that solar power performance would remain constant during operation. In the second situation (Case Study B), the assumption was that annual performance would be reduced by 0.5 %.The results show that APV is better than the surface-mounted system because there is no significant difference between the payback periods of APV and surface-mounted systems;the NPV of APV is greater than the surface-mounted solar system for both the study case A and case B and the LCOE of APV is 55 % less than the LCOE of the surface-mounted solar system. © 2024 The Author(s)

关键词： Agriculture Agrivoltaics Economics Solar

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Drone-assisted adaptive object detection and privacy-preserving surveillance in smart cities using whale-optimized deep reinforcement learning techniques

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Scientific Reports 2025年第1期15卷 1-20页

作者： Abu-Khadrah, Ahmed Al-Qerem, Ahmad Hassan, Mohammad R. Ali, Ali Mohd Jarrah, Muath Department of Electrical Engineering College of Engineering Technology Al-Balqa Applied University Amman Jordan Department of Computer Science Faculty of Information Technology Zarqa University Zarqa 13132 Jordan Communications and Computer Engineering Department Faculty of Engineering Al-Ahliyya Amman University Amman Jordan School of Computing Skyline University College Sharjah United Arab Emirates

Drone/ unmanned aerial vehicles (UAV) surveillance for object/ human detection is familiar in large gatherings in the modern cities era. Artificial intelligence algorithms and computer-aided processing will handle the images extracted from the surveillance videos to reveal the object. This article proposes a novel object detection technique (ODT) that assimilates whale optimization algorithms and deep reinforcement learning. The optimization algorithm detects spreading image features from the origin to the end of x×y pixels. This feature extraction is performed until the complete image pixels are covered to identify their existence in the least position. The forging behaviour of the whales is implied to identify highly overlapping features for object/ human detection/ classification. If the overlapping features increase, the whale’s movement is updated from the last-known highest pixel position. The reinforcement learning recommends that new whale agents validate the low overlapping features, such that the forging whale agent moves towards the large overlapping feature. Therefore, the highest overlapping feature-based pixel differentiation is pursued using forging and searching whales to identify objects through collated pixels. © The Author(s) 2025.

关键词： DRL Feature overlap Object detection Whale optimization

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Applied whispering gallery modes on ZnO nanorods coated glass for humidity sensing application

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Optoelectronics Letters 2021年第5期17卷 298-301页

作者： Mohd Hafiz Jali Hazli Rafis Abdul Rahim Md Ashadi Md Johari Maslinda Mat Sharif Siti Halma Johari Siddharth Thokchom Habibah Mohamed Moh Yasin Sulaiman Wadi Harun Department of Electrical Engineering University of MalayaKuala Lumpur50603Malaysia Faculty of Electrical Engineering Universiti Teknikal Malaysia MelakaMelaka76100Malaysia Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia MelakaMelaka76100Malaysia Faculty of Electrical and Electronic Engineering Technology Universiti Teknikal Malaysia MelakaMelaka76100Malaysia School of Technology Assam Don Bosco UniversityGuwahatiAssam781017India Malaysia-Japan International Institute of Technology Universiti Teknologi MalaysiaKuala Lumpur54100Malaysia Department of Physics Faculty of Science and TechnologyAirlangga UniversitySurabayaIndonesia

In this letter,a humidity sensor is demonstrated by applying a whispering gallery mode(WGM)from a microsphere resonator onto the ZnO nanorods coated glass *** diameter of the microsphere was 234μm and the glass surface was coated with ZnO nanorods using the hydrothermal method at growth duration of 12 h.A significant response to humidity level ranging from 35%RH to 85%RH has been observed with the sensitivity of 0.0142 nm/%*** proposed humidity sensor has successfully employed to enhance interaction between the whispering gallery mode evanescent and surrounds analyte with the assistance of ZnO nanorods coated glass.

关键词： WGM ZnO Applied whispering gallery modes on ZnO nanorods coated glass for humidity sensing application

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Navigating cloud computing security: strategies, risks, and best practices

Navigating cloud computing security: strategies, risks, and ...

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8th IET Smart Cities Symposium (SCS 2024)

作者： Ammar Odeh Qasem S. Abu Al-Haija Tareq Alhajahjeh Raed Mesleh Computer Science Princess Sumaya University For Technology Amman Jordan Department of Cybersecurity Jordan University of Science and Technology Irbid Jordan Tareq Alhajahjeh Faculty of Computing Engineering and Media De Montfort University Leicester UK Electrical Engineering Department German Jordanian University Amman Jordan

ISBN: (数字)9781837243105

This research analyzes cloud computing environments' inherent security and privacy risks. It examines crucial aspects of cloud security, including data encryption, access control mechanisms, identity management, and the implementation of firewalls and intrusion detection systems. The study emphasizes the significance of regular security audits, compliance checks, and the development of robust data backup and disaster recovery plans. Furthermore, it highlights the importance of employee training and awareness in mitigating security threats. The paper delves into the complexities of secure APIs, segmentation, isolation strategies, and the necessity of regular system updates and patching. Additionally, it examines the evolving landscape of cloud security through the lenses of Cloud Security Posture Management (CSPM), the Shared Responsibility Model, and Zero Trust Architecture. This comprehensive approach provides valuable insights into enhancing security measures in cloud computing, thereby safeguarding sensitive data and maintaining user trust in an era where data security is paramount.

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Medical Image Fusion Based on Weighted Least Square Optimization and Deep Learning Algorithm 9

Medical Image Fusion Based on Weighted Least Square Optimiza...

引用

9th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2021

作者： Ghandour, C. El-Shafai, Walid El-Rabaie, S. Menoufia University Faculty of Electronic Engineering Department of Electronics and Electrical Communications Engineering Menouf32952 Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh Saudi Arabia

ISBN: (纸本)9781665482929

Recently, medical image processing has become a hot area of research, especially with the rapid development in technology and instrumentation, and that's because of its effective role in the health sector. So that it becomes a very active research tool. This research introduces an image fusion algorithm that utilizes a deep learning model to produce only one medical fused image that includes all the traits from the medical source images. Firstly, the source images are separated into detailed content and base parts using the Gaussian and rolling guidance filters (RGF). Secondly, by the weighted averaging strategy, the base parts are fused. For the detail content, to quote traits of multi-layer which employ weighted average strategy to produce the fused detail content several candidates, the deep learning network is utilized. The max selection technique is employed to gain the last detailed content as soon as these candidates are gotten. Eventually, by uniting the fused detail and base layers, the fused image will be recreated. The experimental outcomes show that this algorithm can accomplish better results by comparing the other fusion methods in both thematic assessment and visual quality. © 2021 IEEE.

关键词： Learning algorithms

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Program memory optimization for automatically generated tests for AUTOSAR RTE

Program memory optimization for automatically generated test...

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2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021

作者： Vlasicek, Kristijan Vidovic, Ivan Teslic, Nikola Pekez, Nenad Institute RT-RK Osijek Llc for Information Technology Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Osijek Croatia Faculty of Technical Science University of Novi Sad Serbia RT-RK Institute for Computer Based Systems Serbia

ISBN: (纸本)9781665404174

With the technological advancements in the automotive industry, the need for more electronic components has increased as well as for the appropriate software, that is, appropriate drivers. The development of such software is usually based on the AUTOSAR standard, while the required electronics use embedded computer systems. Considering that the embedded computer systems have limited resources, the software needs to be optimized. In this paper, the program memory of the considered software was optimized. The optimization was done using the following methods: introduction of generic functions, extraction of repetitive functions in the header files and dead code elimination. The optimization methods were applied by changing a code fragment written in C programming language. In that way, the program memory optimization method could be applied to all software components (SWCs) using Test Environment Generator (TEG). Afterward, the program code testing was done on a testing board. The results of the testing on board prove the functionality of the optimized program code. The applied methods optimized the memory usage (6.16% reduction) and preserved the functionality of the program code to an appropriate extent. © 2021 IEEE.

关键词： Embedded systems

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