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9th IEEE engineering Education World Conference, EDUNINE 2025

作者： Bogosian, Biayna Vassigh, Shahin Narula, Bhavleen Kaur Corrigan, Seth Perez, Giancarlo Lor, Mohammadreza Akbari Vodinepally, Bhanu Erana, Tisa Islam Alan Finlayson, Mark Chen, Shu-Ching Arizona State University The Design School Tempe AZ United States Florida International University Department of Architecture Miami FL United States University of California School for Inf. and Computer Sci. Irvine CA United States University of Missouri School of Science and Engineering Kansas City MO United States Florida International University School of Computer and Inf. Sci. Miami FL United States

ISBN: (纸本)9798331542788

This paper introduces the Intelligent Learning Platform for Robotics Operations (IL-PRO), a Virtual Reality (VR) system designed to enhance robotics training in the Architecture, engineering, and Construction (AEC) industry. IL-PRO addresses the growing need for effective training methods as the AEC sector adopts robotic automation. The system integrates VR technology with game-assisted learning, combining online multimedia lessons for theory with immersive VR tasks for practical skills. Developed iteratively using Design-Based Research principles, IL-PRO incorporates realistic robot simulations and progressive task complexity. The VR environment, built in Unity, aims to enhance engagement, motor coordination, and spatial awareness in robotics training. While future goals include AI-driven personalized instruction, this work-in-progress focuses on VR curriculum development and implementation. The paper concludes by discussing future directions, including curriculum expansion and cross-institutional adoption, to establish new benchmarks in innovative robotics education for the AEC industry. © 2025 IEEE.

关键词： AEC training artificial intelligence curriculum immersive learning robotics virtual reality

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Work in Progress: VR-based Robotics Training for AEC Industry

Work in Progress: VR-based Robotics Training for AEC Industr...

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IEEE World engineering Education Conference (EDUNINE)

作者： Biayna Bogosian Shahin Vassigh Bhavleen Kaur Narula Seth Corrigan Giancarlo Perez Mohammadreza Akbari Lor Bhanu Vodinepally Tisa Islam Erana Mark Alan Finlayson Shu-Ching Chen The Design School Arizona State University Tempe AZ USA Department of Architecture Florida International University Miami FL USA School for Inf. and Computer Sci. University of California Irvine CA USA School of Science and Engineering University of Missouri Kansas City MO USA School of Computer and Inf. Sci. Florida International University Miami FL USA

ISBN: (数字)9798331542788

ISBN: (纸本)9798331542795

关键词： Training Industries Solid modeling Service robots Robot kinematics Multimedia systems Curriculum development Motor coordination engineering education Immersive learning

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Blind Source Separation: A Performance Review Approach 5

Blind Source Separation: A Performance Review Approach

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5th International Conference on Signal Processing and inf.rmation Security, ICSPIS 2022

作者： Taha, Luay Yassin Abdel-Raheem, Esam Div. of Business Eng. and Inf. Sciences and Tech. AltoonaPA16601 United States University of Windsor Department of Electrical and Computer Engineering WindsorONN9B 3P4 Canada

ISBN: (纸本)9781665492652

Blind source separation (BSS) has been used extensively for the last three decades to extract different sources such as speech, biomedical, and image sources. The quality of extraction is governed by the extraction metrics of the BSS algorithms. The aim of this work is to review the extraction metrics for 27 different algorithms used in some previous works. Results show that the best algorithms in speech extraction is obtained when using independent low-rank matrix analysis (ILRMA) and canonical correlation (CC) based BSS. For image source separation, ZEODS algorithm has shown the highest extraction evaluation score. For fetal electrocardiogram (FEEG) source separation, the null space idempotent transformation matrix (NSITM) and the generalized functional link artificial neural network (GFLANN) show the highest evaluation scores. For electroencephalogram(EEG) signals de-noising and source extraction, the short and long term prediction blind source extraction (SLTP-BSE), B-spline mutual inf.rmation independent component analysis (BMICA), and FASTICA, show the highest evaluation scores. The impact of evaluating the extraction algorithms result in optimum source separation. © 2022 IEEE.

关键词： Blind source separation

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Improved Distance (Sensitivity) Oracles with Subquadratic Space

Improved Distance (Sensitivity) Oracles with Subquadratic Sp...

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Annual IEEE Symposium on Foundations of computer Science

作者： Davide Bilò Shiri Chechik Keerti Choudhary Sarel Cohen Tobias Friedrich Martin Schirneck Dep. of Inf. Eng. CS and Mathematics University of L'Aquila Department of Computer Science Tel Aviv University Dep. of CS and Engineering Indian Institute of Technology Delhi School of Computer Science The Academic College of Tel Aviv-Yaffo Hasso Plattner Institute University of Potsdam Faculty of Computer Science University of Vienna

ISBN: (数字)9798331516741

ISBN: (纸本)9798331516758

A distance oracle (DO) for a graph $G$ is a data structure that, when queried with vertices $s,t$ , returns an estimate $\widehat{d}(s,t)$ of their distance in $G$ . The oracle has stretch $(\alpha, \beta)$ if the estimate satisfies $d(s,t)\leqslant \widehat{d}(s,t)\leqslant \alpha\cdot d(s,t)+\beta$ . An $f-\mathbf{edge}$ fault-tolerant distance sensitivity oracle $(f-\mathbf{DSO})$ additionally receives a set $F$ of up to $f$ edges and estimates the distance in $G-F$ . Our first contribution is the design of new distance oracles with subquadratic space for undirected graphs. We show that introducing a small additive stretch $\beta > 0$ allows one to make the multiplicative stretch $\alpha$ arbitrarily small. This sidesteps a known lower bound of $\alpha\geqslant 3$ (for $\beta=0$ and subquadratic space) [Thorup & Zwick, JACM 2005]. We present a DO for graphs with edge weights in $[0, W]$ that, for any positive integer $\ell$ and any $c\in(0,\ell/2]$ , has stretch $(1+\frac{1}{\ell},2W)$ , space $\widetilde{O}(n^{2-\frac{c}{\ell}})$ , and query time $O(n^{c})$ , generalizing results by Agarwal and Godfrey [SODA 2013] to arbitrarily dense graphs. Our second contribution is a framework that turns an $(\alpha,\beta)- \mathbf{stretch}$ DO for unweighted graphs into an $(\alpha(1+\varepsilon),\beta)-\mathbf{stretch}. f-\mathbf{DSO}$ with sensitivity $f=o(\log(n)/\log\log n)$ retaining sub-quadratic space. This generalizes a result by Bilò, Chechik, Choudhary, Cohen, Friedrich, Krogmann, and Schirneck [TheoretiCS 2024]. Combining the framework with our new DO gives an $f-\mathbf{DSO}$ that, for any $\gamma\in(0, (\ell+1)/2]$ , has stretch $((1+\frac{1}{\ell})(1+\varepsilon), 2)$ , space $n^{2-\frac{\gamma}{(t+1)(f+1)}+o(1)}/\varepsilon^{f+2}$ , and query time $\widetilde{O}(n^{\gamma}/\varepsilon^{2})$ . This is the first $f-\mathbf{DSO}$ with subquadratic space, n

关键词： computer science Fault tolerance Sensitivity Additives Fault tolerant systems Data structures

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Digital forensics for the socio-cyber world (DF-SCW): A novel framework for deepfake multimedia investigation on social media platforms

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Egyptian inf.rmatics Journal 2024年 27卷

作者： Ayub Khan, Abdullah Chen, Yen-Lin Hajjej, Fahima Ahmed Shaikh, Aftab Yang, Jing Soon Ku, Chin Yee Por, Lip Department of Computer Science and Information Technology Benazir Bhutto Shaheed University Lyari Sindh Karachi75660 Pakistan Department of Computer Science Sindh Madressatul Islam University Sindh Karachi74000 Pakistan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei106344 Taiwan Department of Software Engineering College of Computer and Inf. Sci. Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Computer System and Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur50603 Malaysia Department of Computer Science Universiti Tunku Abdul Rahman Kampar31900 Malaysia

Owing to the major development of social media platforms, the usage of technological adaptation increases by means of editing software tools. Posting media in social communication environments has become one of our common daily routines. Before posting, various editing generators are used to manipulate pixel values, such as for enhancing brightness and contrast. Undoubtedly, this software helps bring posting media from ordinary to outstanding. But such a type of editing crosses the line in terms of creating fakes—anything that comes from anywhere and does not retain its originality anyway. It poses a series of issues in the process of multimedia forensics investigation and chain of custody. In order to restrict the attempts at deep faking and make the investigation hierarchy more effective, efficient, and reliable in the socio-cyber space (SCS), this paper presents a novel framework called DF-SCW. A digital forensics-enabled socio-cyber world with artificial intelligence (AI), especially deep neural networks (DNNs), for detecting and analyzing deep fake media investigations on social media platforms. It compares pixels with their neighboring values in the same media (such as images and videos) to identify inf.rmation about the original one. There is a media flag designed to filter out malicious and dangerous attempts, like a powerful leader declaring war. Putting flags on such fakes helps digital investigators resist sharing the posts. In addition, the other prospect of this research is to make the digital forensics ecosystem more appropriate to take qualitative judgments in real-time while media is uploaded on social media platforms. The simulation of the proposed DF-SCW is tested on three different platforms, such as Instagram, Facebook, and Twitter. Through the experiment, the DF-SCW outperformed in terms of detection, identification, and analysis of deepfake media by an increased rate of 3.77%. © 2024

关键词： Social networking (online)

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A Dynamic Series Voltage Regulator for Load Protection in Bipolar DC Power System

A Dynamic Series Voltage Regulator for Load Protection in Bi...

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IEEE Canada Electric Power Conference, EPEC

作者： Ramin Babazadeh-Dizaji Mohammad Hassan Ghaderi Mohsen Ghafouri Mohsen Hamzeh Concordia Ins. for Inf. Systems Eng. Concordia University Montreal Canada Department of Electrical Engineering University of Texas at Dallas Richardson TX USA School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781665463195

The low-voltage DC distribution systems are comprised of various components with a wide range of power ratings. In such systems, compared with unipolar configurations, bipolar structures bring considerable superiority in terms of efficiency, safety, and compatibility. However, the scarcity of protection methods has restricted the expansion of bipolar DC grids. In line with this trend, this paper presents a dynamic series regulator (DSVR) for the protection of sensitive loads in bipolar DC distribution systems. The proposed DSVR injects dynamic voltage for a set of selected sensitive loads to suppress the probable voltage abnormalities in the system. Therefore, it provides desirable satisfaction of voltage quality metrics in bipolar DC power systems. The proposed DSVR is composed of a multi-active bridge converter with one primary and two secondary windings followed by two full-bridge DC-DC converters. To evaluate the feasibility and effectiveness of the proposed concept, various simulations of several case studies are carried out in the PLECS (Plexim) software.

关键词： Regulators Voltage fluctuations Power system dynamics Windings Bridge circuits DC-DC power converters Software

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Blind Source Separation: A Performance Review Approach

Blind Source Separation: A Performance Review Approach

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International Conference on Signal Processing and inf.rmation Security (ICSPIS)

作者： Luay Yassin Taha Esam Abdel-Raheem Div. of Business Eng. and Inf. Sciences and Tech. Altoona Pennsylvania 16601 United States Department of Electrical and Computer Engineering University of Windsor Windsor ON N9B 3P4 Canada

ISBN: (纸本)9781665492669

关键词： Measurement Signal processing algorithms Null space Prediction algorithms Blind source separation Data mining Signal denoising

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TEM Characterization of the Edges of CsPb2Br5 Perovskite Crystals

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Microscopy and Microanalysis 2018年第S1期24卷 1984-1985页

作者： Hector A. Calderon Francisco Robles-Hernandez Yanan Wang Chong Wang Xinghua Su Viktor G. Hadjiev Yizhou Ni Md Kamrul Alam Yan Yao Yu Yang Instituto Politecnico Nacional ESFM Depto. Fisica CDMX Mexico 07338 Inst. of Fund. Frontier Scie. U. of Electronic Science and Technology Sichuan610054 China Dep. of Electrical and Computer Engineering University of Houston Houston Texas77204 USA Inst. of Optoel. Inf. Mat. School of Mat. Sci. and Eng. Yunnan University Kunming 650091 China School of Materials Science and Engineering Chang'an University Xi'an Shaanxi710061 China Texas Center for Superconductivity University of Houston Houston TX77204 USA Department of Mechanical Engineering University of Houston Houston TX77204 USA Department of Physics University of Houston Houston Texas77204 USA Materials Science & Engineering University of Houston Houston Texas77204 USA

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A Big Data Processing Framework for Self-Healing Internet of Things Applications

A Big Data Processing Framework for Self-Healing Internet of...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Bahadir Dundar Merve Astekin Mehmet S. Aktas Computer Engineering Department Yildiz Technical University Esenler-Istanbul Turkey TUBITAK Inf. & Inf. Security Res. Center Gebze-Kocaeli Turkey

ISBN: (纸本)9781509047963

In this study, we introduce a big data processing framework that provides self-healing capability in the Internet of Things domain. We discuss the high-level architecture of this framework and its prototype implementation. To identify faulty conditions, we utilize a complex-event processing technique by applying a rule-based pattern-detection algorithm on the events generated real-time. For events, we use a descriptor metadata of the measurements (such as CPU usage, memory usage, bandwidth usage) taken from Internet of Things devices. To understand the usability and effectiveness of the proposed architecture, we test the prototype implementation for performance and scalability under increasing incoming message rates. The results are promising, because its processing overhead is negligible.

关键词： complex event processing big data internet of things self-healing systems predictive maintenance

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Anomaly detection and monitoring in Internet of Things communication

Anomaly detection and monitoring in Internet of Things commu...

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International Conference on inf.rmation Technology and Electrical engineering (ICITEE)

作者： Deris Stiawan Mohd. Yazid Idris Reza Firsandaya Malik Siti Nurmaini Rahmat Budiarto Department of Computer Engineering Universitas Sriwijaya Dept. Soft Engineering Universiti Teknologi Malaysia College of Computer Science & Inf. Technology Albaha University Saudi Arabia

ISBN: (纸本)9781509041404

The Internet of Things (IoT) presents unique challenges in detecting anomaly and monitoring all connected devices in a network. Moreover, one of the objectives of anonymity in communication is to protect the data traffic of devices. The summary status visualization is indispensable to depict all devices/sensors that are most indicative of a pending failure and a predictive power/energy. Thus, this paper proposes a multi-platform monitoring and anomaly detection system that supports heterogeneous devices. The proposed system addresses the problems of: (i) how to monitor the network to prevent device failures and (ii) how to design a comprehensive feature for the early anomaly detection of IoT communication.

关键词： Heterogeneous Monitoring Detection Anomaly Internet of Things

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