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32nd Telecommunications Forum, TELFOR 2024

作者： Jeftovic, Milica Vuletic, Pavle Stanisavljevic, Zarko Capgemini Engineering Belgrade Serbia University of Belgrade School of Electrical Engineering Department of Computer Science and Information Technology Belgrade Serbia

ISBN: (纸本)9798350391053

This paper analyses current best practices for using security mechanisms in extract, transform, and load (ETL) tools. The results of the analysis are visually represented in a form of an optimal security model used in these tools at the moment. In order to test the recommended model, it was implemented in a selected open source ETL tool. At the end, advantages and disadvantages of the recommended model are enlisted and directions for further improvement of the model are given. © 2024 IEEE.

关键词： ETL tools Security Mechanisms Security Model

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Navigation On Mobile Computing Devices with A Walking Using Object-Oriented Techniques to Communicate Stick 3

Navigation On Mobile Computing Devices with A Walking Using ...

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3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Ramesh Prabhakaran, R. Guhan, P. Raj, E George Dharma Prakash Karthika, K. Angel Maanu, P. Mizoram University Department of Computer Engineering Mizoram India Panimalar Engineering College Department of Electrical and Electronical Engineering Chennai India Bharathidasan University School of Computer Science and Engineering Trichy India Karpagam College of Engineering Department of Information Technology Coimbatore India Panimalar Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331528201

Moving around in their surroundings is challenging for elderly people and people with visual impairments. The majority of functional sticks in use today are not intelligent and lack an innate ability to recognize obstacles. In an effort to address this issue, mobility and orientation specialists who assist the blind by teaching them to move freely and safely using their remaining senses are brought in. They can navigate around obstacles with the aid of guidance dogs as well. These techniques have drawbacks, such as the dogs' inability to comprehend complicated instructions, the high cost of maintaining these trained dogs, and the need to hire an expert. In light of the aforementioned difficulties, the "Smart walking stick"has become a potential answer. The "Mobile based walking stick"is a useful mobility aid with the capacity to call a relative who can help in the event of an accident, detect obstacles above ground level and pits using ultrasonic sensors, recognize when a collision has occurred, and call the user's mobile phone if it has been misplaced to share the location's GPS for use with GSM connectivity and to share with the user's mention contacts. With some visually disabled people as test subjects, a test case was run, and 95% of the time it was successful. © 2024 IEEE.

关键词： Ultrasonic sensors

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RDP: Ranked Differential Privacy for Facial Feature Protection in Multiscale Sparsified Subspaces

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IEEE Internet of Things Journal 2025年第11期12卷 17333-17348页

作者： Ou, Lu Liao, Shaolin Gao, Shihui Huang, Guandong Qin, Zheng Hunan University School of Journalism and Communication Hunan Changsha410082 China Sun Yat-sen University School of Electronics and Information Technology Guangzhou510275 China Illinois Institute of Technology Department of Electrical and Computer Engineering ChicagoIL60616 United States Purdue University Elmore School of Electrical and Computer Engineering West LafayetteIN47907 United States Hunan University College of Computer Science and Electronic Engineering Hunan Changsha410082 China State Grid Hunan Materials Company Department of Deployment Management Hunan Changsha410118 China

With the widespread sharing of personal face images on the Internet, systems based on face recognition encounter the real threat of being breached by potential adversaries who are able to access individuals’ face images and use them to intrude the systems. In this article, we propose a novel privacy protection method in the sparsified multiscale feature subspaces to protect sensitive facial features, taking care of the influence or weight-ranked subspace coefficients on the privacy budget, named "ranked differential privacy (RDP)." After the multiscale subspaces’ decomposition, the lightweight Laplacian noise is added to the dimension-reduced sparsified subspaces’ coefficients according to the geometric superposition method. Then, we rigorously prove that the RDP satisfies Ε0-differential privacy. After that, the nonlinear Lagrange multiplier method (LM) is formulated for the constraint optimization problem of maximizing the utility of protected face images of high-visualization quality with sanitizing noise, under a given privacy budget Ε0. Then, two methods are proposed to solve the nonlinear Lagrangian multiplier method (LM) problem and obtain the optimal noise scale parameters: 1) the analytical normalization approximation (NA) method with identical average noise scale parameter for real-time online applications and 2) the LM optimization method via gradient descent (LMGD) to obtain the nonlinear solution through iterative updating for more accurate offline applications. Experimental results on two real-world datasets show that our proposed RDP outperforms other state-of-the-art methods: at a privacy budget of Ε0 = 0.2 , the peak signal-to-noise ratio (PSNR) of the optimized RDP is about ~10 dB higher than (10 times as high as) the highest PSNR of all state-of-the-art methods compared. © 2014 IEEE.

关键词： Differential privacy

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Performance Analysis of Multiple HAPS-Based Hybrid FSO/RF Space-Air-Ground Network 16

Performance Analysis of Multiple HAPS-Based Hybrid FSO/RF Sp...

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16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

作者： Singh, Deepshikha Swaminathan, R. Marrapu, Aravind Madhukumar, A.S. Indian Institute of Technology Indore Department of Electrical Engineering India School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9798350383119

Sixth generation (6G) networks are anticipated to support increasingly data-hungry applications by expanding the network capabilities and connectivity. Free space optics (FSO) communication with space-air-ground (SAG) network becomes a potential solution to meet the enormous traffic demands and ubiquitous connectivity requirement in 6G networks. In spite of various advantages offered by FSO communication such as high bandwidth availability, large unlicensed spectrum, better security, etc., the FSO link exhibits a high degree of responsiveness to atmospheric turbulence, attenuation, and pointing errors. Thus to mitigate the severe atmospheric effects, we propose a multiple high-altitude platform station (HAPS)-based SAG network, where HAPS functions as a decode-and-forward (DF) relay node between ground station and satellite. We take into account a hybrid FSO/radio frequency (RF) link for connecting ground station and HAPS nodes and an FSO link between HAPS and satellite. The performance analysis of the proposed SAG network involves evaluating the outage probability and average symbol error rate (SER) considering the presence of pointing errors and assuming Málaga distribution in case of FSO and shadowed k - μ fading distribution in case of RF link. Furthermore, asymptotic analysis is conducted to determine the diversity gain of the proposed system. Numerical results demonstrate that the proposed multiple HAPS-based hybrid FSO/RF SAG network outperforms all other existing HAPS-based SAG network models in the literature. © 2024 IEEE.

关键词： DF relaying free space optics (FSO) high-altitude platform station (HAPS) hybrid FSO/RF performance analysis

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Work in Progress: Emerging from Shadows: Optimal Hidden Actuator Attack to Cyber-Physical Systems 30

Work in Progress: Emerging from Shadows: Optimal Hidden Actu...

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30th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2024

作者： Hamid Miji, Md Kausar Liu, Mengyu Akowuah, Francis E Kong, Fanxin The South Dakota School of Mines and Technology Department of Electrical Engineering and Computer Science Rapid CitySD United States University of Notre Dame Department of Computer Science and Engineering South BendIN United States

ISBN: (纸本)9798350358414

Industries are embracing information technology and constructing more robust machines known as Cyber-Physical Systems(CPS) to automate processes. CPSs are envisioned to be pervasive, coordinating, and integrating computation, sensing, actuation, and physical processes. CPSs have various applications in life-critical scenarios, where their performance and reliability can have direct impacts on human safety and well-being. However, CPSs are vulnerable to malicious attacks, and researchers have developed detectors to identify such attacks in different contexts. Surprisingly, little work has been done to detect attacks on the actuators of CPS. Furthermore, actuators face a high risk of optimal hidden attacks designed by powerful attackers, which can push them into an unsafe state without detection. To the best of our knowledge, no such attacks on actuators have been developed yet. In this paper, we design an optimal hidden attack for actuators and evaluate its effectiveness. First, we develop a mathematical model for actuators and then create a linear program for convex optimization. Second, we solve the optimization problem and simulate the optimal attack. © 2024 IEEE.

关键词： Cyber Physical System

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Design of an RF-CMOS Switched-Capacitor Power Amplifier for NB-IoT RF Transceivers

Design of an RF-CMOS Switched-Capacitor Power Amplifier for ...

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2023 International Young Engineers Forum in electrical and computer engineering, YEF-ECE 2023

作者： Santos, Ana Isabel Pedro Oliveira, Joao NOVA School of Science and Technology Department of Electrical and Computer Engineering Caparica Portugal Centre of Technology and Systems CTS-UNINOVA Department of Electrical and Computer Engineering Caparica Portugal

ISBN: (纸本)9798350300420

The paper presents the implementation of a Switched Capacitor Power Amplifier (SCPA) to be integrated into a Narrowband Internet of Things (NB-IoT) Transceiver. The SCPA is designed to operate at a frequency of 0.9GHz and aiming the maximum output power allowed by the standard of 23dBm. All the blocks within the SCPA were developed using RF components of a standard 130nm CMOS process, with a 1.2V/2.4V supply voltage. Results show that the SCPA is able to produce a maximum output power of 15.61dBm with a maximum Power-Added Efficiency (PAE) of 26.52% and a Total Harmonic Distortion (THD) of 0.68%. The measured HD2 and HD3 are-70.23dBc and-43.41dBc, respectively. Additional Process, Voltage and Temperature (PVT) corners and Monte Carlo simulations indicate the SCPA operates properly when subject to different conditions and mismatches. Besides the SCPA, a 16 QAM modulation stage is designed in VerilogA in order to evaluate the performance of the RF PA when a sequence of symbols is transmitted. © 2023 IEEE.

关键词： Power amplifiers

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Smart Energy Management in Solar-Powered 2BHK Residential Building Based on Forecast-Driven Optimization and EV Scheduling 4

Smart Energy Management in Solar-Powered 2BHK Residential Bu...

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4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Kumar, M. Praveen Raja, S. Charles Dharssini, A.C.Vishnu Keerthi, P. Thiagarajar College of Engineering Department of Eee Madurai India School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia

ISBN: (纸本)9798331529635

The study aims to address a comprehensive energy optimization approach for a 2BHK residential building located in Bodinayakanur, Theni, Tamil Nadu, equipped with a 2 kW solar panel. The study focuses on minimizing energy costs by integrating day-ahead energy forecasting using a Long Short-Term Memory (LSTM) model with rule-based meta-heuristic optimization for load scheduling. Two scenarios are analyzed: the first optimizes the scheduling of household appliances, and the second incorporates an electric vehicle (EV) into the load profile. The optimization strategy shifts secondary loads, such as EV charging and non-essential appliances, to off-peak hours while maximizing solar energy utilization. Efficient management of energy demand and load scheduling results in significant cost savings and enhanced grid stability. The findings demonstrate the practical viability of the energy optimization framework for reducing electricity costs in real-world residential settings, especially in areas with renewable energy integration. © 2024 IEEE.

关键词： Costs

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Image-Based Automatic Energy Meter Reading Using Deep Learning

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computers, Materials & Continua 2023年第1期74卷 203-216页

作者： Muhammad Imran Hafeez Anwar Muhammad Tufail Abdullah Khan Murad Khan Dzati Athiar Ramli Institute of Computer Sciences and Information Technology Faculty of Management and Computer SciencesThe University of AgriculturePeshawarPakistan Department of Electrical and Computer Engineering COMSATS University IslamabadAttock CampusAttock CityPakistan Kuwait College of Science and Technology Kuwait CityKuwait School of Electrical&Electronic Engineering USM Engineering CampusUniversiti Sains MalaysiaPenang14300Malaysia

We propose to perform an image-based framework for electrical energy meter *** aim is to extract the image region that depicts the digits and then recognize them to record the consumed *** the readings of serial numbers and energy meter units,an automatic billing system using the Internet of Things and a graphical user interface is deployable in a real-time ***,such region extraction and character recognition become challenging due to image variations caused by several factors such as partial occlusion due to dust on the meter display,orientation and scale variations caused by camera positioning,and non-uniform illumination caused by *** this end,our work evaluates and compares the stateof-the art deep learning algorithm You Only Look Once(YOLO)along with traditional handcrafted features for text extraction and *** image dataset contains 10,000 images of electrical energymeters and is further expanded by data augmentation such as in-plane rotation and scaling tomake the deep learning algorithms robust to these image *** training and evaluation,the image dataset is annotated to produce the ground truth of all the ***,YOLO achieves superior performance over the traditional handcrafted features with an average recognition rate of 98%for all the *** proves to be robust against the mentioned image variations compared with the traditional handcrafted *** proposed method can be highly instrumental in reducing the time and effort involved in the currentmeter reading,where workers visit door to door,take images ofmeters and manually extract readings from these images.

关键词： Convolutional neural network object localization machine learning

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Using Cohort-Based Analytics to Better Understand Student Progress

Using Cohort-Based Analytics to Better Understand Student Pr...

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2024 ASEE Annual Conference and Exposition

作者： Manasil, Kristi Heileman, Gregory L. Hemaraja, Rohit Sharma, Bhavya Slim, Ahmad Sharifi, Melika Sharifi, Roxana Yusuf, Husain Al The School of Information The University of Arizona United States Department of Electrical & Computer Engineering The University of Arizona United States Department of Computer Science The University of Arizona United States

engineering programs are typically among the most tightly prescribed programs within the academic landscape on any university campus. The strict nature of these programs often results in students taking more credits than stipulated, thereby leaving them struggling to graduate in a timely manner. The ability to identify potential blockers or challenges in an engineering program's curriculum is vital to student success and the promotion of on-time graduation. This paper provides a comprehensive examination of patterns and trends observed by a newly developed cohort tracking analytics platform. This platform provides analyses over a cohort of students which uncovers insights that are not easily identified when only looking at data at the individual student level. The analysis pinpoints courses that many students within the cohort have taken that are not applicable to the degree, along with the reasons why these courses are not applicable. It also identifies trends in courses that must be repeated by a significant portion of the cohort. It examines the courses constituting a program's degree requirements that have yielded both the best and worst grade value outcomes. In addition, an exploration of a cohort's efficiency of credit hour production is provided for both the home institution units and transfer units, which shows where credits are not aligning with degree requirements and therefore not counting towards degree completion. Finally, a comparative analysis of programs within the engineering field is performed as well as a comparison of engineering programs to non-engineering programs. This type of analysis demonstrates the differences in how students in engineering programs make progress towards their degree completion. The statistical analyses furnished by this platform provide administrators with an evidence-based foundation to support programmatic modifications and enhancements. This allows administrators to depart from the past practices of having to rely on a

关键词： Students

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Classification and Source Location Indication of Jamming Attacks Targeting UAVs via Multi-output Multiclass Machine Learning Modeling

Classification and Source Location Indication of Jamming Att...

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Alkhatib, M. McCormick, M. Williams, L. Leon, A. Camerano, L. Shamaileh, K. Al Devabhaktuni, V. Kaabouch, N. Purdue University Northwest Electrical and Computer Engineering Department HammondIN46323 United States Illinois State University Electrical and Computer Engineering Department NormalIL61761 United States University of North Dakota School of Electrical Engineering and Computer Science Grand ForksND58202 United States

ISBN: (纸本)9798350324136

This paper introduces machine learning (ML) as a solution for the detection and range localization of jamming attacks targeting the global positioning system (GPS) technology, with applications to unmanned aerial vehicles (UAVs). Different multi-output multiclass ML models are trained with GPS-specific sample datasets obtained from exhaustive feature extraction and data collection routines that followed a set of realistic experimentations of attack scenarios. The resulting models enable the classification of four attack types (i.e., barrage, single-Tone, successive-pulse, protocol-Aware), the jamming direction, and the distance from the jamming source by yielding a detection rate (DR), misdetection rate (MDR), false alarm rate (FAR), and F-score (FS) of 98.9%, 1.39%, 0.28%, and 0.989, respectively. © 2024 IEEE.

关键词： Global positioning system (GPS) jamming classification jamming localization machine learning (ML) unmanned aerial vehicles (UAVs).

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