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17th IEEE International Conference on Solid-State and Integrated Circuit Technology, ICSICT 2024

作者： Yuan, Tengfei Wang, Pengjun Zhang, Yuejun Ren, Mingze Hu, Shuang Ningbo University Faculty of Electrical Engineering and Computer Science Zhejiang315211 China Wenzhou University Electrical and Electronic Engineering Wenzhou325035 China

ISBN: (纸本)9798350361834

Physical unclonable function (PUF) utilizes the tiny deviations in the chip manufacturing to generate unique identity keys. Traditional PUFs are generally implemented on dedicated circuit structures, which may not be effective in resource-constrained Internet environments. To solve the above problems, this paper proposes a software PUF based on Digital Signal Processor (DSP-PUF). The DSP-PUF uses the timing violation of the internal registers of the chip to generate random response. Primarily, the mechanism of generating abnormal information between timing paths and registers in DSP chip is analyzed. Secondly, the overclocking clock is applied to make the DSP work abnormally, and the unique and unclonable random response is generated according to the dependence of the response on the path delay. Eventually, DSP-28335 is selected as the DSP-PUF carrier, and the DSP-PUF response extraction is completed by computer, oscilloscope, DSP and other equipment. The test results indicate that the 12000 bit responses generated by DSP-PUF has passed the NIST randomness test, and the worst case reliability is 88.01% in the temperature range of 20° C-80 ° C. Moreover, the proposed DSP-PUF does not use additional circuit structure, and does not need to change the existing circuit structure. It is suitable for privacy information encryption in resource constrained Internet of things (IoT). © 2024 IEEE.

关键词： Data privacy

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Promoting Entrepreneurial Mindset and Diversity in Power engineering Class Through Case Studies 53

Promoting Entrepreneurial Mindset and Diversity in Power Eng...

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Al-Olimat, Khalid S. Ohio Northern University Department of Electrical & Computer Engineering and Computer Science AdaOH45810 United States

ISBN: (纸本)9798350336429

Utilizing student-led case studies as an innovative educational tool can effectively introduce real-world practices into the power engineering classroom. By assigning students to draft a story around a case study, they are given ownership and agency to hone their problem-solving, self-directed learning, and team skills. These case studies are grounded in real-world situations, providing students with opportunities to enhance their domain knowledge in power engineering. The use of case studies offers several advantages, including promoting active and engaged learning, encouraging critical thinking and problem-solving, enhancing the relevance and applicability of course content, facilitating teamwork and collaboration, promoting diversity, and encouraging the use of real-world examples and data. The interactive learning strategy of case studies shifts the emphasis from teacher-centered to more student-centered activities, resulting in a more engaging and immersive learning experience. Evaluation of students' perception and attitude toward this teaching method showed that students have better understanding of the course materials and an appreciation of the method for promoting diversity and entrepreneurial mindset. © 2023 IEEE.

关键词： Case studies diversity entrepreneurial mindset student perception and attitudes

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Generative AI Co-Pilot for Rapid Prototyping of IEC 61499 Control Applications 29

Generative AI Co-Pilot for Rapid Prototyping of IEC 61499 Co...

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29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024

作者： Ovsiannikova, Polina Liakh, Tatiana Jhunjhunwala, Pranay Vyatkin, Valeriy Aalto University Department of Electrical Engineering and Automation Espoo Finland Luleå Tekniska Universitet Department of Computer Science Electrical and Space Engineering Sweden

ISBN: (纸本)9798350361230

This work develops a concept of a natural language co-pilot for the creation of IEC 61499 applications to accelerate initial testing and development. The co-pilot addresses the challenge of generating the correct function blocks that can be opened in popular IEC 61499 IDEs. In our case study, we focus on the generation of the centralised controller that operates particular equipment to perform a defined process. In addition, we have developed a scheme for how the co-pilot will be integrated into the FBME IDE as an AI assistant in the next steps. In the discussion, we provide valuable information for future co-pilot developers on the possible problems they might face in this area and how to overcome them. © 2024 IEEE.

关键词： Rapid prototyping

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An Efficient Lane Following Navigation Strategy With Fusion Attention for Autonomous Drones in Urban Areas

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IEEE Transactions on Vehicular Technology 2023年第3期73卷 3094-3105页

作者： Lee, Chao-Yang Khanum, Abida Wang, Neng-Chung Karuparthi, Bala Syam Kumar Yang, Chu-Sing the Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Douliou64002 Taiwan the Computer Science and Communication Engineering National Cheng Kung University Tainan701 Taiwan the Department of Computer Science and Information Engineering National United University Miao-Li36003 Taiwan the Department of Aeronautical Engineering National Formosa University Huwei632 Taiwan the Department of Electrical Engineering National Cheng Kung University Tainan701 Taiwan

—Drones are a vital part of our daily lives because of their flexible flying nature and low operation and maintenance costs. Navigation is the most important aspect in the autonomous drone era. With that being said, recent studies have tackled the greatly challenging task of obtaining the most feasible and safest path. In this work, we focus on safe and reliable unmanned aerial vehicle navigation in densely populated city environments to efficiently follow the lane. We present herein a deep learning method through which a drone can autonomously navigate by following a lane in a dynamic urban environment. This drone perceives the environment by using two cameras facing front and down. A convolutional neural network (CNN) is used to capture the high-level feature representation through the attention and residual mechanism of the drone’s raw visual inputs. The CNN concurrent pipelines used for three raw visual inputs can output high-level features and follow the concurrent feature fusion into the self-head attention mechanism that encapsulates both dynamic and static information to predict yaw and linear velocity. These predictions are modulated into the final control commands to obtain smooth and continuous inputs that are delivered to the drone. The experimental evaluation results show that the proposed method can learn the drone’s navigation strategy for a lane following a guidance system. The high performance of the trained navigation policy is observed in the simulations with different scenarios. In conclusion, our proposed approach outperforms both existing and current state-of-the-art ImageNet models. © 2023 IEEE.

关键词： Cameras

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A Computationally Effective SDP Solution for Target Localization Using DTD and DFS Measurements in Multistatic Systems With Unknown Signal Propagation Speed

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IEEE Sensors Journal 2025年第12期25卷 22264-22278页

作者： Qi, Qinke Li, Youming Wu, Yonghong Guo, Qiang Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China China Research Institute of Radiowave Propagation Qingdao266107 China Harbin Engineering University College of Information and Communication Engineering Harbin150000 China

This paper investigates the moving target localization in multistatic systems for unknown signal propagation speed environments and presents a semi-definite programming (SDP) solution with reduced computational complexity by differential time delay (DTD) and differential frequency shift (DFS) measurements. Existing research on this problem defines numerous auxiliary variables to pseudo-linearize measurement models, proposing high requirement related to the number of transmitters/receivers for effective localization performance of the solution or causing the computationally demanding solution. To address the aforementioned shortcomings, the auxiliary variables introduced when constructing pseudo-linear equations from the measurement models are minimized as much as possible. After that, based on the weighted least squares (WLS) criterion, a constrained WLS formulation of reducing the number of constraints is proposed, as the constraints included are formulated according to the relationships among auxiliary variables. Considering the non-convexity of the formulation, semi-definite relaxation (SDR) is applied to transform the constrained WLS problem into its SDP form for the global optimum. Besides, the mean square error (MSE) and complexity analyses are conducted to validate the performance of the proposed method from two perspectives. Both analyses and simulation results demonstrate that the method has the ability to balance the localization accuracy and computational load. © 2001-2012 IEEE.

关键词： NP-hard

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Integrating cycleGAN and BERT for Chinese text style transfer

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Multimedia Tools and Applications 2024年 1-20页

作者： Chou, Chien-Hsing Chou, Cheng-Hou Hsieh, Yi-Zeng Yang, Tzu-Shien Department of Mathematics and Information Education National Taipei University of Education Taipei Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Electrical and Computer Engineering Tamkang University New Taipei Taiwan

In this study, we integrate the Bidirectional Encoder Representations from Transformers (BERT) model with the Cycle Generative Adversarial Network (CycleGAN) to create a system for Chinese text style transfer. Natural language processing (NLP) involves converting human languages into data interpretable by computers, enabling applications like text classification, chatbots, and dialogue systems. Recent advancements, such as Google's transformer model and the BERT technique, have significantly improved NLP capabilities through self-attention mechanisms and unsupervised pretraining. Text style transfer modifies the style of texts without altering their semantics. Previous methods like StyIns and models based on disentangled representation learning highlight the challenges of retaining text meaning during style transfer. Our system leverages CycleGAN’s unsupervised learning to convert unpaired data between wuxia and fantasy styles while preserving semantics. Using the pretrained BERT model from the Chinese Knowledge and Information Processing (CKIP) Lab, our experimental results demonstrate successful style conversion, maintaining the original meanings of texts. This integration of BERT and CycleGAN shows promise for further advancements in NLP applications. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Semantics

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Assessing LWIR and Visual Sensor Modalities for UAV Detection and Tracking

Assessing LWIR and Visual Sensor Modalities for UAV Detectio...

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2024 Intermountain engineering, Technology and Computing, IETC 2024

作者： Wadsworth, Emma Brinton, Jacob Vannoy, Trevor C. Whitaker, Bradley M. Computer Engineering University of Utah Salt Lake CityUT United States Computer Science Boston University BostonMA United States Montana State University Electrical and Computer Engineering BozemanMT United States Montana State University Electrical and Computer Engineering and Optical Technology Center BozemanMT United States

ISBN: (纸本)9798350373073

The development of unmanned aerial vehicles has led to a proliferation of drones being used for many different tasks. This necessitates systems for preventing collisions and other accidents, as well as malicious activities that could be carried out by drone operators. A vital part of that task is detecting and tracking drones. Different sensors have different strengths and weaknesses, so it is likely that a combination of sensors will be used in future systems. In order to facilitate the design of such systems, the limitations of current sensors and methods should be assessed. Here, the limitations of single-frame LWIR and RGB camera data are analyzed. Deep learning methods are applied to data at different ranges of pixels-on-target. The given results document the relative success of current single-frame detection methods on these drone targets. © 2024 IEEE.

关键词： computer vision

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Optimal design of single-tuned filters for industrial power systems to reduce harmonic distortion using forest algorithm

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Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A 2024年第4期47卷 414-422页

作者： Lin, Shu-Min Chou, Chih-Ju Lu, Chia-Te Hsiao, Ying-Tung Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Computer Science National Taipei University of Education Taipei Taiwan

This paper presents a novel optimization algorithm for designing single-tuned filters in industrial power systems to reduce harmonic distortion. Single-tuned filters are cost-efficient, simple, and easy to maintain. We formulate the filter design as an optimization problem, minimizing costs while incorporating harmonic limits and system constraints. Our solution algorithm simulates tree growth, proliferation, and death based on the forest algorithm to generate optimal solutions. This enables both local and global searches for fast convergence and feasible designs. Unlike traditional approaches, we account for variations in filter components and system parameters caused by factors like manufacturing tolerances, operating temperature, and frequency variations. Our study contributes by designing adaptive filters that match practical systems. We validate our method against previous publications and other techniques like simulated annealing and teaching-learning-based optimization. Simulation results demonstrate the effectiveness of our approach in minimizing costs, satisfying operation constraints, and accounting for component variations in this complex problem. © 2024 The Chinese Institute of Engineers.

关键词： Power quality

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Tackling System Induced Bias in Federated Learning: Stratification and Convergence Analysis 42

Tackling System Induced Bias in Federated Learning: Stratifi...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Tang, Ming Wong, Vincent W. S. Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China The University of British Columbia Department of Electrical and Computer Engineering Vancouver Canada

ISBN: (纸本)9798350334142

In federated learning, clients cooperatively train a global model by training local models over their datasets under the coordination of a central server. However, clients may sometimes be unavailable for training due to their network connections and energy levels. Considering the highly non-independent and identically distributed (non-IID) degree of the clients' datasets, the local models of the available clients being sampled for training may not represent those of all other clients. This is referred as system induced bias. In this work, we quantify the system induced bias due to time-varying client availability. The theoretical result shows that this bias occurs independently of the number of available clients and the number of clients being sampled in each training round. To address system induced bias, we propose a FedSS algorithm by incorporating stratified sampling and prove that the proposed algorithm is unbiased. We quantify the impact of system parameters on the algorithm performance and derive the performance guarantee of our proposed FedSS algorithm. Theoretical and experimental results on CIFAR-10 and MNIST datasets show that our proposed FedSS algorithm outperforms several benchmark algorithms by up to 5.1 times in terms of the algorithm convergence rate. © 2023 IEEE.

关键词： Learning systems

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A Novel Complexity Scoring Model for Non-Functional Requirements in Request for Proposal in Housing Industry Using FURPS Quality and Moscow Priority Model

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International Journal for Housing science and Its Applications 2024年第4期45卷 30-40页

作者： Rashid, Ekbal Mastorakis, Nikos E. Technical University of Sofia Sofia Bulgaria Sector of Electrical Engineering and Computer Science Hellenic Naval Academy Piraeus Greece English Language Faculty of Engineering Technical University of Sofia Sofia Bulgaria

In this research paper we have attempted to elicit Non-Functional Requirements (NFR) which may or not have been explicitly added to the Request for Proposal (RFP) in housing industry but is important for the success of the program. We have used real time RFPs for the elicitation of NFRs. The sales proposal process, also known as response to RFP process, refers to the methodical steps a vendor takes when developing a proposal in response to a buyer’s RFP which will have details of integrating systems, Software platforms, users, business outcomes, limitations, functional requirements, and may be nonfunctional requirements (NFR). There is some work done by researchers on assessing opaqueness of NFRs and traceability of NFR. But there has been no work on a complexity scoring model for NFRs which enables a vendor to respond to an RFP with best price and schedule. The paper proposes a novel complexity scoring model for NFRs in RFP in Housing industry by using FURPS (Functionality, Usability, Reliability, Performance, Supportability) quality attribute model in conjunction with MoSCoW(Must Have, Should Have, Could Have, Won’t Have) priority model by using mathematical formula. The working model is broken down in steps for Sales and pre-Sales teams of the Vendor and is ready for adoption. © 2024 International Association for Housing science. All rights reserved.

关键词： complexity scoring model construction cost FURPS housing linear regression MoSCoW NFR RFP scatter plot

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