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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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Development of a Mobile Monitoring Application for a Message Queuing Telemetry Transport (MQTT)-Based Struvite Fertilizer Production System 10

Development of a Mobile Monitoring Application for a Message...

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10th International HCI and UX Conference in Indonesia, CHIuXiD 2024

作者： Maulana, Ilham Fitria, Maya Faizah, Cut Nurul Adharani, Daffa Hirta Jinan, Sarah Nada Dawood, Rahmad Universitas Syiah Kuala Department of Electrical and Computer Engineering Banda Aceh23111 Indonesia Universitas Syiah Kuala Interactive Intelligent Systems Reseach Group Department of Electrical and Computer Engineering Banda Aceh23111 Indonesia

ISBN: (纸本)9798350380439

Struvite fertilizer, characterized by its slow-release qualities, is comprised of magnesium, ammonium, and phosphate and is vital for plant growth. The Integrated Laboratory Unit of Universitas Syiah Kuala (USK) has developed a prototype for struvite fertilizer production equipment, but the production process requires manual monitoring. This project seeks to create an MQTT (Message Queuing Telemetry Transport)-based mobile application for the real-time monitoring and control of struvite fertilizer production equipment. The application employs the MQTT communication protocol, known for its quick data transmission and minimal bandwidth requirements. This application incorporates sensors on the production machine, which includes a reactor, filter, and dryer, and employs an Amazon Web Service's (AWS) IoT Core as the MQTT broker. Findings from the application's evaluation indicate that the mobile application can efficiently monitor and control several machine components. Data transmission to MQTT topics was successful, facilitating seamless communication. Functional and integration testing demonstrated that the system operates effectively. Usability testing outcomes yielded an average score of 77.75 with a system usability scale (SUS) approach, signifying that the application possesses a satisfactory degree of usability classified within the 'Grade B' category. © 2024 IEEE.

关键词： Telemetering systems

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Answer Code Validation Program with Test Data Generation for Code Writing Problem in Java Programming Learning Assistant System

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engineering Letters 2024年第5期32卷 981-994页

作者： Wai, Khaing Hsu Funabiki, Nobuo Aung, Soe Thandar Lu, Xiqin Jing, Yanhui Kyaw, Htoo Htoo Sandi Kao, Wen-Chung Department of Information and Communication Systems Okayama University Okayama Japan Department of Computer and Information Science Tokyo University of Agriculture and Technology Tokyo Japan Department of Electrical Engineering National Taiwan Normal University Taipei Taiwan

In order to support the learning of novice students in Java programming, the web-based Java Programming Learning Assistant System (JPLAS) has been developed. JPLAS offers several types of exercise problems to foster code reading and writing skills at different levels. In JPLAS, the code writing problem (CWP) asks a student to write a source code that will pass the test code given in the assignment where the correctness is verified by running them on JUnit. In this paper, to reduce the teacher’s workload during the marking process, we present the answer code validation program that verifies all the source codes from a large number of students for each assignment and reports the number of passing tests for each source code in the CSV file. Besides, to test a source code with various input data, we implement the test data generation algorithm that identifies the data type, generates new data, and replaces it for each test data in the test code. Furthermore, to verify the correctness of the implemented procedures in the source code, we introduce the intermediate state testing in the test code. For evaluations, we applied the proposal to source codes and test codes in a Java programming course in Okayama university, Japan, and confirmed the validity and effectiveness. © 2024, International Association of Engineers. All rights reserved.

关键词： Students

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Evolutionary Paths to Systematically Unlocking the Frequency-Selective Potential of 3D Meta-Atoms 6

Evolutionary Paths to Systematically Unlocking the Frequency...

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6th Australian Microwave Symposium, AMS 2025

作者： Lv, Xiaojing Luo, Zhen Tyo, J. Scott Yang, Yang University of Technology School of Electrical and Data Engineering Sydney Australia University of Technology School of Mechanical and Mechatronic Engineering Sydney Australia Monash University Department of Electrical and Computer Systems Engineering Australia

ISBN: (纸本)9798350379969

This paper highlights the benefits of advanced multi-material 3D printing technology in enhancing the electromagnetic performance of metasurfaces. By systematically evolving geometric structures, the proposed bandpass filtering meta-Atom outperforms existing designs in key metrics, including bandwidth, out-of-band suppression, in-band insertion loss, and transition band steepness, underscoring the significant potential of 3D unit cells. Through the integration of qualitative approach and semi-Analytical design algorithm, the geometric topology is fully optimized without imposing substantial computational demands. © 2025 IEEE.

关键词： Wiener filtering

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Nonlinear Optimal Regulation of SIR Epidemic Model via Finite-Horizon SDRE 26

Nonlinear Optimal Regulation of SIR Epidemic Model via Finit...

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26th International Conference on computer and Information Technology, ICCIT 2023

作者： Paul, Sudipta Islam, Samiul Naidu, Desineni Subbaram Abu Hanif Pramanik, Md. Rensselaer Polytechnic Institute Department of Electrical Computer & Systems Engineering New York United States Rajshahi University of Engineering & Technology Department of Electrical & Computer Engineering Bangladesh University of Minnesota Duluth Department of Electrical Engineering United States

ISBN: (纸本)9798350359015

A Susceptible-Infectious-Recovered (SIR) model is a popular and fundamental epidemiological model often used to assess the efficacy of disease prevention and control measures. SIR disease model, with the implementation of various optimal control methods, is investigated to determine the optimal ways to lessen the effects of an infectious disease. In this research work, a non-linear, closed-loop, finite-horizon, optimal regulation with state-dependent Riccati equation (FH-SDRE) is implemented in an epidemic model called SIR model with vaccination to minimize the infected and susceptible population. Given the nonlinear dynamics of the SIR epidemic model, initially, this method converts the nonlinear equations into a state-dependent coefficient (SDC) matrix, which holds the nonlinearities of the dynamical system. After that, SDRE is solved at every small time instant over a specified finite time period. The core idea here is to utilize an approximate analytical approach that transforms the differential Riccati equation (DRE) into a differential Lyapunov equation (DLE) during every time period. Then, the real-time solution of the DLE at each of these time steps will result in the control law required to achieve the desired system performance. The effectiveness of the FH-SDRE regulation for the SIR model is demonstrated by minimizing the infected and susceptible population within a desired 30-day time period. © 2023 IEEE.

关键词： finite-horizon regulation SIR epidemic model state-dependent Riccati equation

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Next Generation Memristor Reservoir Computing 3

Next Generation Memristor Reservoir Computing

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3rd IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2024

作者： Nikiruy, K. Ivanov, T. Ziegler, M. Rossetti, D. Corinto, F. Ascoli, A. Tetzlaff, R. Demirkol, A.S. Schmitt, N. Micro-and Nanoelectronic Systems Tu Ilmenau Department of Electrical Engineering and Information Technology Ilmenau Germany Turin Italy Institute of Circuits and Systems Tu Dresden Faculty of Electrical and Computer Engineering Dresden Germany

ISBN: (纸本)9798350378009

The nonlinear transformation used in reservoir computing can be effectively replaced by nonlinear vector autoregression (NVAR) for data prediction. In such a method, also known as next generation reservoir computing (NGRC), the input signal consists of a linear part, including several previous data points, and their nonlinear combinations. Here we show that the application of this method to a network with memristive weights (memristors) can be used to predict signals, depending on the nature of the nonlinear functions and the number of memristors. The network allows an accurate prediction of chaotic time series of Mackey-Glass and Duffing oscillators. © 2024 IEEE.

关键词： Memristors

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iLIAC: An approach of identifying dissimilar groups on unstructured numerical image dataset using improved agglomerative clustering technique

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Multimedia Tools and Applications 2024年第39期83卷 86359-86381页

作者： S, Sreedhar Kumar Ahmed, Syed Thouheed Fathima, Afifa Salsabil Mathivanan, Sandeep Kumar Jayagopal, Prabhu Saif, Abdu Gupta, Sachin Kumar Sinha, Garima Department of Computer Science and Engineering School of Engineering and Technology CMR University Karnataka Bengaluru India Department of Electrical Engineering Indian Institute of Technology Hyderabad Telangana Kandi India School of Computer Science and Engineering REVA University Bangalore India School of Computer Science and Engineering Galgotias University Uttar Pradesh Greater Noida203201 India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Communication and Computer Engineering Faculty of Engineering and IT Taiz University Taiz Yemen Katra India Department of Computer Science Engineering Jain University Bangalore India

Unstructured Numerical Image Dataset Separation (UNIDS) method employing an enhanced unsupervised clustering technique. The objective is to delineate an optimal number of distinct groups within the input grayscale (G-S) image content, utilizing the improved limited iteration agglomerative clustering (iLIAC) clustering technique for the separation and enhancement of picture elements. The UNIDS method is structured into two primary stages: partitioning and validation. In the partitioning stage, the UNIDS method identifies an appropriate number of discrete clusters within the grayscale image using the iLIAC technique, eliminating the need for predetermined procedures. Subsequently, the method evaluates the similarity and deviation among data elements within the same group in the resultant image dataset. Additionally, it assesses the proximity and inters severance among clusters in the outcome of the image dataset through the partitioning process. Empirical results indicate that the UNIDS system excels in the spontaneous identification of an optimal number of discrete clusters within the input G-S image. The system demonstrates superior thickness, reduced deviation among data elements within the same cluster, increased inter-separation, and diminished inter-closeness between cluster elements. Furthermore, empirical analysis establishes the superior performance of the UNIDS approach compared to existing clustering techniques. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Iterative methods

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A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 3765-3779页

作者： Renkhoff, Justus Feng, Ke Meier-Doernberg, Marc Velasquez, Alvaro Song, Houbing Herbert Department of Information Systems BaltimoreMD21250 United States Embry-Riddle Aeronautical University Department of Electrical Engineering and Computer Science Daytona BeachFL32114 United States University of Colorado Department of Computer Science BoulderCO80309 United States

Neurosymbolic artificial intelligence (AI) is an emerging branch of AI that combines the strengths of symbolic AI and subsymbolic AI. Symbolic AI is based on the idea that intelligence can be represented using semantically meaningful symbolic rules and representations, while deep learning (DL), or sometimes called subsymbolic AI, is based on the idea that intelligence emerges from the collective behavior of artificial neurons that are connected to each other. A major drawback of DL is that it acts as a 'black box,' meaning that predictions are difficult to explain, making the testing & evaluation (T&E) and validation & verification (V&V) processes of a system that uses subsymbolic AI a challenge. Since neurosymbolic AI combines the advantages of both symbolic and subsymbolic AI, this survey explores how neurosymbolic applications can ease the V&V process. This survey considers two taxonomies of neurosymbolic AI, evaluates them, and analyzes which algorithms are commonly used as the symbolic and subsymbolic components in current applications. Additionally, an overview of current techniques for the T&E and V&V processes of these components is provided. Furthermore, it is investigated how the symbolic part is used for T&E and V&V purposes in current neurosymbolic applications. Our research shows that neurosymbolic AI has great potential to ease the T&E and V&V processes of subsymbolic AI by leveraging the possibilities of symbolic AI. Additionally, the applicability of current T&E and V&V methods to neurosymbolic AI is assessed, and how different neurosymbolic architectures can impact these methods is explored. It is found that current T&E and V&V techniques are partly sufficient to test, evaluate, verify, or validate the symbolic and subsymbolic part of neurosymbolic applications independently, while some of them use approaches where current T&E and V&V methods are not applicable by default, and adjustments or even new approaches are needed. Our research shows that th

关键词： Neural networks

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A Deep Learning Approach for Detecting Diabetic Retinopathy

A Deep Learning Approach for Detecting Diabetic Retinopathy

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2024 International Conference on computer and Applications, ICCA 2024

作者： Nabil, Mohamed Hossam Hassan Hammam, Laila Bastawrous, Hany Ayad Ebrahim, Gamal A. The British University in Egypt Electrical Engineering Department Cairo Egypt Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft Netherlands Ain Shams University Faculty of Engineering Computer and Systems Engineerig Department Cairo Egypt

ISBN: (纸本)9798350367560

The World Health Organization (WHO) reports that diabetic retinopathy affects one-third of diabetics, regardless of their stage of the disease. Several research efforts are focused on its automated detection and diagnosis. Identifying diabetic retinopathy is crucial due to the damage that occurs to the blood vessels of the eye retina, leading to vision blur or even complete blindness. Thus, an annual checkup is needed for people with diabetes. Moreover, uncontrolled sugar levels for diabetes patients could worsen the current stage of diabetic retinopathy. Consequently, automated detection can greatly contribute to the treatment of disease. This can be carried out through several algorithms, including deep learning models and support vector machines, in addition to transfer learning. This contribution proposes a new approach for diabetic retinopathy automated detection based on convolutional neural network (CNN) models. The proposed model provides both binary and multi-class detection. Both scenarios have shown promising results, where the training accuracies of both the binary classification and the multi-class are 92% and 94%, respectively. © 2024 IEEE.

关键词： Convolutional neural networks

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Grid-Forming Inverters for Enhancing Stability and Resilience in Distribution Networks under Transients and Restoration

Grid-Forming Inverters for Enhancing Stability and Resilienc...

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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Selim, Alaa Zhao, Junbo Seo, Gab-Su Ding, Fei Cui, Bai University of Connecticut Department of Electrical and Computer Engineering United States National Renewable Energy Laboratory Power Systems Engineering Center GoldenCO80401 United States Iowa State University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798350313604

The increasing integration of distributed energy resources in distribution networks has significantly reduced system inertia, posing challenges to grid stability during transient events, such as Cold Load Pickup (CLPU). This paper proposes the implementation of grid-forming inverters (GFMs) to enhance the stability of low-inertia distribution systems. The paper also investigates the performance of the GFM-based approach in maintaining voltage profiles along the distribution feeder, especially during CLPU scenarios without synchronous machines. A comparison is made between the GFM-based system and the conventional synchronous machine setup. The synchronous machine is chosen as a reference point for evaluating the effectiveness of the GFM-based approach. The GFM-based system's performance is assessed under various challenging scenarios, including short-circuit faults, islanding, and a combination of these through extensive simulations. The results demonstrate the potential of GFMs to stabilize a distribution system and outperform the traditional rigid synchronous machine during transient events. © 2024 IEEE.

关键词： Electric power distribution

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