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A Study on Verification of Sewage Treatment Expert Operating Experience Using RNN

Transactions of the Korean Institute of electrical Engineers 2025年第4期74卷 691-699页

作者： Nahm, Eui-Seok Dept. of AI Computer Engineering Far East University Korea Republic of

In this paper, we proposed a data quality and diversity guarantee plan and a method to verify the expert operation experience using RNN and a data quality and diversity guarantee plan to 1) solve the two problems of the sewage treatment expert driving experience and 2) the limitation of situation recognition and judgment. As a solution to the lack of data quality and diversity, not all data are used, but a method of filtering and using only the part that is the basis for determining the expert's experience was proposed. In addition, RNN was used to solve the problem of the limitation of situation recognition and judgment. The reason why RNN is used among various neural networks is that RNN is a neural network architecture for deep learning that predicts time series or sequential data, and sewage treatment data is also time series or sequential data. According to the proposed technique, a RNN model with a reliability of more than 8% was implemented, and the effectiveness of the proposed technique was verified by applying two experiences and one incorrect experience of actual operation experts of the target sewage treatment plant. As a result of the verification, both the actual driving expert's experiences 1 and 2 were verified as valid, and for incorrect experiences, there were 3,442 data that matched the expert's experience and 4,444 data that did not match, so the proposed method can verify the expert's experience. © The Korean Institute of electrical Engineers.

关键词： Sewage treatment plants

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Self-supervised Mamba-based Mastoidectomy Shape Prediction for Cochlear Implant Surgery

Self-supervised Mamba-based Mastoidectomy Shape Prediction f...

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Medical Imaging 2025: Image Processing

作者： Zhang, Yike Davalos, Eduardo Su, Dingjie Lou, Ange Noble, Jack H. Dept. of Computer Science Vanderbilt University United States Dept. of Electrical and Computer Engineering Vanderbilt University United States

ISBN: (纸本)9781510685901

Cochlear Implant (CI) procedures require the insertion of an electrode array into the cochlea within the inner ear. To achieve this, mastoidectomy, a surgical procedure involving the removal of part of the mastoid region of the temporal bone using a high-speed drill provides safe access to the cochlea through the middle and inner ear. In this paper, we propose a novel Mamba-based method to synthesize the mastoidectomy volume using only preoperative Computed Tomography (CT) scans, where the mastoid remains intact. Our approach introduces a self-supervised learning framework designed to predict the mastoidectomy shape and reconstruct a 3D post-mastoidectomy surface directly from preoperative CT scans. This reconstruction aligns with intraoperative microscope views, enabling various downstream surgical applications. For training, we leverage postoperative CT scans to bypass manual data cleaning and labeling, even when the region removed during mastoidectomy is affected by challenges such as metal artifacts, low signal-to-noise ratio, or electrode wiring. Our method achieves a mean Dice score of 0.70 in estimating mastoidectomy regions, demonstrating its effectiveness for accurate and efficient surgical preoperative planning. © 2025 SPIE.

关键词： Cochlear implants

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Optimizing relay node placement and routing in WBANs using free search krill herd and harmony search algorithm

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Multimedia Tools and Applications 2025年第10期84卷 7257-7295页

作者： Patra, Sushree Chinmayee Samal, Tusharkanta Kabat, Manas Ranjan Mishra, Manas Ranjan Barik, Ram Chandra Dept. of Computer Sc. & Engineering Veer Surendra Sai University of Technology Odisha Sambalpur India Dept. of Computer Sc. & Engineering DRIEMS University Odisha Cuttack India Dept. of Computer Sc. & Engineering C.V. Raman Global University Odisha Bhubaneswar India

Wireless Body Area Network (WBAN) plays an important role in healthcare applications like in medical, non-medical and psychological sector for remote monitoring of health conditions of patients. Since the biosensors in WBAN are energy constrained in nature, the architecture of energy efficient and cost sensitive WBAN has attracted the researchers during the last decade. In this paper, a mathematical model for optimization of relay node placement in WBAN using Free Search Krill Herd (FSKH) algorithm because of its diversified phases of searching has been proposed. Furthermore, a routing protocol for energy efficient and reliable for data transmission over WBAN by using Harmony Search (HS) algorithm has been designed. The proposed algorithm has less 11.02%, 6.8% energy consumption in standing position, 5.6% and 11.02% in siting position and 12.5% and 18.75% siting on chair than its counterparts EAWD and Modified EAWD. Throughput has increased significantly by approximately 4–5 times as compare to iM-SIMPLE and *** proposed methodology has also shown greater improvement as its first node is completely exhausted after 28,545 rounds of data transmission while its existing counterpart’s iM-SIMPLE and Co-LAEEBA first node dies at 5100 rounds and 6800 rounds of transmission respectively. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Wireless local area networks (WLAN)

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Design and Optimization of an IR-Based Automation System with Telegram Bot Integration for Remote Device Control 4

Design and Optimization of an IR-Based Automation System wit...

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4th International Conference on Robotics, electrical and Signal Processing Techniques, ICREST 2025

作者： Adnan Sharar Oyon, Md. Shihab Himel, Abid Hasan Mredul, Khaliduzzaman Ahmed, Abir Ali, M Tanseer Hossainl, Chowdhury Akram Rahman, Md. Abdur Dept. of Electrical and Electronic Engineering Dhaka Bangladesh Dhaka Bangladesh Dept. of Computer Engineering Dhaka Bangladesh

ISBN: (纸本)9798331530938

Automation is advancing rapidly, with infrared (IR) communication being a key method for controlling electronic devices. Despite this, challenges remain in optimizing IR controllers for consistent performance across varying angles and task loads. A 3D design and a robust algorithm have been developed to enhance the system's accuracy, while security is ensured by matching a unique TOKEN with the Telegram bot for each session. Error rates were analyzed across different angles, with specific zones determined based on performance. Minimal error rates defined the working zone, while higher rates indicated critical and invalid zones. Error rates increased as the transmitter moved further from the optimal angles, such as a 0-6 % error rate when operating within a 0° - 5° range. Reaction time was calculated across multiple tasks, showing an average of 5 seconds per command. Mismatch rates, observed during higher task loads, rose sharply when handling many tasks. For instance, the mismatch rate was 0 % for 12 tasks but 20 % when executing 20 tasks. Performance evaluations demonstrated optimal IR signal strength for reliable control within a distance of 10 to 15 inches, with diminishing effectiveness beyond 20 inches. These findings provide a foundation for developing more reliable and efficient IR control systems for practical applications. © 2025 IEEE.

关键词： Bot (Internet)

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Weather-Dependent Fast Power Flow in Distribution Systems: A Meteorological-Data-Aided Method

Weather-Dependent Fast Power Flow in Distribution Systems: A...

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2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Zhang, Yuanshuo Zhang, Ying Wang, Lei Zhou, Anping Oklahoma State University Dept. Electrical and Computer Engineering Stillwater United States Southern Methodist University Dept. Electrical and Computer Engineering Dallas United States

ISBN: (纸本)9798331541125

The weather-dependent variability of line impedance can substantially impair the accuracy of traditional power flow calculations in electric grids, especially under varying and extreme weather conditions. Recently, significant advancements have been made in weather-dependent power flow (WDPF) algorithms to address this issue in transmission systems. However, determining line parameters in three-phase unbalanced distribution grids remains time-consuming due to the nonlinear and analytically intractable nature of heat-balance functions. To achieve fast and high-fidelity calculations, this paper proposes a novel data-aided WDPF algorithm leveraging readily available weather information to calibrate line parameters in real time. The method enhances the classic backward-forward sweep approach for unbalanced distribution grids by incorporating real-time updates of line parameters based on the thermal model of line conductors during the iterative power flow process. Additionally, well-trained neural networks are employed to expedite power flow calculations by solving line temperature variables. Case studies on two unbalanced IEEE feeders demonstrate that the proposed algorithm surpasses state-of-the-art WDPF algorithms in computational efficiency and accuracy under diverse weather conditions. © 2025 IEEE.

关键词： DC distribution systems

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One-bit DOA Estimation with Array Imperfections: A Learning-based Approach 5

One-bit DOA Estimation with Array Imperfections: A Learning-...

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5th National and the 1st International Conference on Applied Research in electrical engineering, AREE 2025

作者： Azhdari, Yasin Farhang, Mahmoud Shiraz University Dept. of Electrical and Computer Engineering Shiraz Iran

ISBN: (纸本)9798350377170

Low-power and low-complexity Direction-of-Arrival (DOA) estimation is a critical challenge in various signal processing applications. This paper presents a data-driven approach using a neural network framework designed for single-snapshot, one-bit quantized measurements, enabling significant hardware simplification. We explore a Fully Connected (FC) Neural Network architecture (which is identical to a 1D convolutional architecture in the single-snapshot case) trained end-to-end on raw quantized data. The performance of this learned approach is rigorously compared against the well-established MUltiple SIgnal Classification (MUSIC) and Complex-valued Binary Iterative Hard Thresholding (CBIHT) algorithms. Our findings reveal that the proposed neural network achieves superior estimation performance compared to these, especially under low SNR values and in the presence of realistic array imperfections. We observe significant performance gains even without explicitly training the network on data with such imperfections, highlighting the generalization capabilities of the proposed method. © 2025 IEEE.

关键词： Signal to noise ratio

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Quantum Network Routing with Heterogeneous Nodes 17

Quantum Network Routing with Heterogeneous Nodes

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Pandey, Anoop Kumar Tamma, Bheemarjuna Reddy Rao, M.V. Panduranga IIT Hyderabad Dept. of Computer Science and Engineering India

ISBN: (纸本)9798331531195

Deciding a route for the transfer of quantum information (namely, qubits) on a quantum network is a significant problem that is being studied extensively. In this work, we investigate the problem of routing on a quantum network of heterogeneous nodes both with and without fidelity and timing *** propose a Path Request Packet (PRP) based routing scheme for dynamically selecting a path that maximizes the overall probability of transmission success while maintaining fidelity above a threshold and adhering to time constraints. While the proposed scheme can perform suboptimally under fidelity and timing constraints, we discuss a straightforward proof of optimality in the absence of these constraints. Simulations on random graphs demonstrate that the PRP-based scheme performs better, both in terms of reliability and fidelity, than a non-trivial baseline routing algorithm. © 2025 IEEE.

关键词： Quantum electronics

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A New Three-phase Multi-mode AC/DC LLC Converter with Output-controlled Active Rectifier (with V2G and G2V functions) For Fast DC Charging Application 14

A New Three-phase Multi-mode AC/DC LLC Converter with Output...

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14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Xia, Xiaoyi Lam, John York University Dept. of Electrical Engineering and Computer Science Toronto Canada

ISBN: (纸本)9798331516116

This paper proposes a new three-phase multi-mode AC/DC LLC resonant converter with an output-controlled active rectifier for electric vehicle (EV) fast DC charging applications. In the proposed approach, two low-frequency bidirectional switches at the primary side in each phase of the converter allow vehicle-to-grid (V2G, i.e. DC/AC mode) and grid-to-vehicle (G2V, i.e. AC/DC mode) modes. When the proposed converter operates in AC/DC mode, each phase consists of an integrated bridgeless boost power factor corrector and an LLC resonant converter at the primary side. Output voltage regulation is managed by switches on the high frequency transformer's secondary side output rectifier in each phase, with soft-switching operation achieved in all the switches. When the proposed three-phase converter operates in DC/AC mode, each phase consists of a half-bridge DC/DC resonant converter cascaded with a half-bridge grid-side inverter. The operation of the proposed converter is explained in this paper. Results from a 20kW, 480VLLrms/350Vdc, 130kHz design, and a hardware test on a 130kHz, 250V-output proof-of-concept prototype are presented to validate the functionality of the proposed converter. © 2025 IEEE.

关键词： Zero voltage switching

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Quantum-Enhanced Machine Learning for Precision Breast Cancer Diagnosis 17

Quantum-Enhanced Machine Learning for Precision Breast Cance...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Banerjee, Agniva Indian Institute of Science Education and Research Bhopal Dept. Electrical Engineering and Computer Science Bhopal India

ISBN: (纸本)9798331531195

Cancer is the leading cause of premature mortality. Globally, the prevalence of cancer is on the rise, and early-stage diagnosis is crucial for cancer recovery and survival. However, the presence of circulating tumor cells (CTCs) and heterogeneity within the tumor makes it hard to track how cancer changes over time and how resistance to treatment develops. Unfortunately, the cancer diagnosis precision remains inadequate, endangering precious human lives and necessitating costly procedures for accurate treatment. Machine learning (ML) has proven capable of discovering meaningful information and making predictions, particularly with large datasets. Moreover, quantum computers (QCs) inherently possess superposition and parallel computation, features not found in classical computing. Researchers have demonstrated that quantum neural networks (QNNs) achieve a significantly better effective dimension than classical NNs. In this context, this study investigates the application of classical and quantum machine learning (QML) algorithms to classify breast cancer images. Region-based segmentation is used to identify regions of interest and image processing algorithms are performed on segmented breast cancer images to extract meaningful features (e.g., perimeter, area, compactness). An user interface (UI) based software is created to swiftly distinguish benign and malignant instances during image analysis. Although QNNs perform poorly than the classical NNs, there is still a long way to go in developing feature maps and techniques for better performance. In contrast, the classical NNs have gone a long way with well-established algorithms and packages available to us. This research shows that with further development, QML has the potential to enhance cancer diagnosis accuracy and speed, ultimately improving early detection and treatment outcomes. © 2025 IEEE.

关键词： Diseases

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STUDY OVER THE HARMONIC EFFECTS IN electrical DISTRIBUTION NETWORKS

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: electrical engineering and computer science 2025年第1期87卷 259-272页

作者： Ioana, Gabriel Cazacu, Emil Petrescu, Lucian Stănculescu, Marilena Dept. of Electrical Engineering National University of Science and Technology Politehnica Bucharest Romania

This paper analyses the implementation of modern remedial measures to current, and voltage distortion problems generated by power nonlinear industrial loads. For these types of heavily polluted consumers, traditional solutions such as passive or hybrid filters are not suited. Consequently, the active harmonic filters (AHF) are the only pieces of equipment to be considered. Their proper selection is attained only after performing an adequate power quality audit of the main electric parameters at the main low voltage switchboards. The paper presents an AHF-based solution for nonlinear industrial load which reduces the current and voltage harmonics. The solution is validated by harmonics measurements before and after AHF installation. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Active filters

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