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A Study on Simplification of LCC Estimation Through Correlation Estimation Between Cost Elements for Railway Catenary System

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Transactions of the Korean Institute of electrical Engineers 2024年第5期73卷 900-905页

作者： Jeng, Chang-Mo Lee, Jong-Woo Dept. of railway Electrical Signaling Engineering Seoul National University of Science and Technology Korea Republic of Dept. of railway Electrical Signaling Engineering Seoul National University of Science Korea and Technology Korea Republic of

Life cycle cost (LCC) analysis is crucial for estimating total cost of system constructions across various industries, especially defense, aerospace, railways where products are complex and long-lasting. A significant challenge in LCC modeling lies in the limited availability of reliable life-cycle data, leading to uncertainties in system specifications, estimation methods, and scenario analysis. Despite the existence of historical construction data, inherent uncertainties often restrict their direct use. In projects like catenary system construction for railways, LCC is heavily influenced by project length, with material costs being one of the most deterministic elements compared to other cost factors. This paper proposes a novel cost element coefficients method to facilitate the estimation of total construction costs. Our method leverages historical data and addresses uncertainties, providing a practical tool for LCC analysis in railway projects. Copyright © The Korean Institute of electrical Engineers.

关键词： Life cycle

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A simplified hybrid model for state of charge estimation using 1-D Kalman filter and Coulomb counting 50

A simplified hybrid model for state of charge estimation usi...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Garg, Kritika Sarker, Rahul Ahmad, Aaqib Kaur, Mehakpreet Teja, A.V. Ravi Dept. of Electrical Engineering IIT Ropar Rupnagar India Dept. of Computer Science Engineering PU Patiala India

ISBN: (纸本)9781665464543

This document is a model with an accurate estimation of the battery’s State Of Charge (SOC), which is pivotal for prime performance and optimal lifespan of the rechargeable batteries. Though traditional methods, like Open Circuit Voltage (OCV) and Coulomb Counting (CC), are advantageous, they suffer from several limitations, such as sensitivity to temperature changes, frequent calibration, ageing effects, and measurement inaccuracies. This paper proposes 1-D Kalman Filter (1-D HKF) with an approach that incorporates the OCV and CC results into the state space model for better and more accurate SOC estimation. So, the model is called 1-D HKF or Hybrid Kalman filter that, influenced the long-term stability and estimation accuracy of CC and the accuracy of OCV at specific points to get over the individual limitations. The model trained by 1-D HKF adapts itself and adjusts the gain based on the uncertainties of each measured value to ensure optimal value information. So, We evaluate the performance of the 1-D HKF versus the traditional methods Kalman Filter using examples and exploratory data. The proposed approach illustrates significantly improved accuracy and robustness across various operating conditions, including varying temperatures and discharge rates. © 2024 IEEE.

关键词： State of charge

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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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Post-mastoidectomy Surface Multi-View Synthesis from a Single Microscopy Image

Post-mastoidectomy Surface Multi-View Synthesis from a Singl...

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Medical Imaging 2025: Image-Guided Procedures, Robotic Interventions, and Modeling

作者： Zhang, Yike Noble, Jack H. Dept. of Computer Science Vanderbilt University United States Dept. of Electrical and Computer Engineering Vanderbilt University United States

ISBN: (纸本)9781510685949

Cochlear Implant (CI) procedures involve performing an invasive mastoidectomy to insert an electrode array into the cochlea. In this paper, we introduce a novel pipeline that is capable of generating synthetic multi-view videos from a single CI microscope image. In our approach, we use a patient's pre-operative CT scan to predict the post-mastoidectomy surface using a method designed for this purpose. We manually align the surface with a selected microscope frame to obtain an accurate initial pose of the reconstructed CT mesh relative to the microscope. We then perform UV projection to transfer the colors from the frame to surface textures. Novel views of the textured surface can be used to generate a large dataset of synthetic frames with ground truth poses. We evaluated the quality of synthetic views rendered using Pytorch3D and PyVista. We found both rendering engines lead to similarly high-quality synthetic novel-view frames compared to ground truth with a structural similarity index for both methods averaging ∼0.86. A large dataset of novel views with known poses is critical for ongoing training of a method to automatically estimate microscope pose for 2D to 3D registration with the pre-operative CT to facilitate augmented reality surgery. This dataset will empower various downstream tasks, such as integrating Augmented Reality (AR) in the OR, tracking surgical tools, and supporting other video analysis studies. © 2025 SPIE

关键词： Cochlear implants

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Latency Analysis of In-Vehicle Network for Advanced Driver Assistance System 100

Latency Analysis of In-Vehicle Network for Advanced Driver A...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Park, Hanyoung Cho, Minji Jang, Yongjae Choi, Ji-Woong Dept. of Electrical Engineering & Computer Science Daegu Korea Republic of

ISBN: (纸本)9798331517786

Considering the advancements in autonomous driving technologies, the necessity for an advanced driver assistance system (ADAS) to incorporate a multitude of sensors for enhanced precision has become paramount. Consequently, the increase of sensors correlates directly with the escalation of autonomous driving capabilities. However, this escalation causes a larger volume of data traffic and an increase in the latency within the in-vehicle network (IVN). As the IVN latency increases, the overall latency of ADAS from the sensor to the actuator increases. This increased latency can affect the safety of ADAS. Hence, latency analysis for various sensors is required. In this paper, we struct Ethernet-based zonal architecture considered for future automotive architecture and analyze the factor of end-to-end latency for the safety-related ADAS with multi-type sensors, including IVN latency. © 2024 IEEE.

关键词： Advanced driver assistance systems

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Evaluation of Self- and Weakly-Supervised Training Strategies for Atlas-Based Segmentation of the Epitympanum Surface in CT Images using DABS-MS

Evaluation of Self- and Weakly-Supervised Training Strategie...

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Medical Imaging 2025: Image-Guided Procedures, Robotic Interventions, and Modeling

作者： Mason, Hannah G. Noble, Jack H. Dept. of Computer Science Vanderbilt University United States Dept. of Electrical and Computer Engineering Vanderbilt University United States

ISBN: (纸本)9781510685949

Cochlear implants (CIs) are neural prosthetics used to improve hearing performance in patients with severe-to-profound hearing loss. CIs contain an electrode array that is surgically implanted in the patient's cochlea. The position of the array in the cochlea has been shown to be associated with hearing outcomes. In the traditional surgical approach, the surgeon cannot directly visualize the final position of the array in the cochlea. Thus, due to wide variability in cochlear anatomy, the arrays are often poorly positioned. Our lab has previously proposed an augmented reality surgery system for assisting with CI insertion and improving intra-cochlear positioning. The approach relies on preoperative CT-based planning of the procedure as well as 3D to 2D registration of the plan to the monocular microscope video to facilitate augmented reality overlay. Herein, we hypothesize the epitympanum is an ideal anatomical structure to localize in CT and microscopy to facilitate the 3D to 2D registration. We propose and evaluate an atlas-based method of localizing the epitympanum in 3D CT images as the first step of this registration pipeline. This method builds upon our previously proposed DABS-MS framework, a 3D self-supervised U-Net-based network for accurate atlas-based segmentation. We propose a new tissue-based loss function for further improvement. The weakly supervised method achieved median 95th percentile Hausdorff distances of 0.3786 mm on 15 test cases with ground truth and showed significant improvement when compared to the self-supervised method. These results demonstrate the promise of the method for use in augmented reality-assisted cochlear implantation. © 2025 SPIE

关键词： Cochlear implants

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Cultural Intelligence in AI Ethics: A Systematic Framework for Implementation Across Global Contexts 3

Cultural Intelligence in AI Ethics: A Systematic Framework f...

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3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Kumar, Devesh Kumar, Kamlesh Choudhary, Rahul Kumar Singh, Varnika NIT Hamirpur Dept. of Computer Science & Engineering India NIT Hamirpur Dept. of Electrical Engineering India Panjab University UIET Dept. of Electronics & Communication Engineering Chandigarh India

ISBN: (纸本)9798331523893

This research examines artificial intelligence ethics implementation across diverse cultural contexts through case studies in healthcare, finance, education, and corporate sectors. Using mixed-methods analysis across six cultural regions, the study reveals fundamental variations in approaches to AI ethics, particularly regarding data privacy and human-technology relationships. The integration of Western, Eastern, and African perspectives yields three frameworks: a cultural intelligence model for AI development, an adaptive governance mechanism, and a cross-cultural collaboration approach. Results demonstrate that successful AI implementation requires balancing diverse cultural perspectives with technical innovation through flexible governance structures, providing practical pathways for culturally sensitive AI development. © 2025 IEEE.

关键词： Intelligent computing

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Adversarial Machine Learning Attack on Machine Learning-based Controller for Solar Inverters

Adversarial Machine Learning Attack on Machine Learning-base...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Massa, Joaquin Kim, Kyoung-Tak Kim, Taesic Ahn, BoHyun Venayagamoorthy, Kumar Zeng, Jianwu Texas A&m University-Kingsville Dept. of Electrical Engineering and Computer Science Kingsville United States Soongsil University Dept. of Electrical Engineering Seoul Korea Republic of University of Missour-Columbia Dept. of Electrical Engineering and Computer Science Columbia United States Clemson University Dept. of Electrical and Computer Engineering Clemson United States Minnesota State University Mankato Dept. of Electrical and Computer Engineering and Technology Mankato United States

ISBN: (纸本)9798350376067

Adversarial machine learning (ML) attacks are stealthy attacks designed to mislead the ML model results. This paper explores adversarial ML attacks that generate adversarial noisy input data in an ML-based controller in a solar inverter. Three types of ML models, long short-term memory (LSTM), gated recurrent unit (GRU)), and bidirectional-LSTM (Bi-LSTM), are designed to replace proportional-integral (PI) controller-based vector control for a solar inverter and two white-box adversarial ML attacks (Basic Iterative Method (BIM) attack and Fast Sign-Gradient Method (FGSM)) are applied to the ML controllers. It is observed that the adversary ML attacks designed in stealthy way do not affect the PI controller, while significantly degrading performance of the ML-based controllers. Moreover, the BIM attack is more effective than FGSM and Bi-LSTM-based controller is relatively robust to the attacks compared to peer. © 2024 IEEE.

关键词： Adversarial machine learning

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PhishGuard: A Convolutional Neural Network-Based Model for Detecting Phishing URLs with Explainability Analysis 3

PhishGuard: A Convolutional Neural Network-Based Model for D...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Islam, Md Robiul Islam, Md Mahamodul Afrin, Mst. Suraiya Antara, Anika Tabassum, Nujhat Amin, Al Uttara University Dept. of Computer Science and Engineering Dhaka Bangladesh University of Oslo Dept. of Informatics Oslo Norway Dept. of Building Engineering and Construction Management Khulna Bangladesh BRAC University Dept. of Electrical and Electronics Engineering Dhaka Bangladesh North South University Dept. of Electrical and Computer Engineering Dhaka Bangladesh Dept. of Computer Science American International Dhaka Bangladesh

ISBN: (纸本)9798350372120

Cybersecurity is one of the global issues because of the extensive dependence on cyber systems of individuals, industries, and organizations. Among the cyber attacks, phishing is increasing tremendously and affecting the global economy. Therefore, this phenomenon highlights the vital need for enhancing user awareness and robust support at both individual and organizational levels. Phishing URL identification is the best way to address the problem. Various machine learning and deep learning methods have been proposed to automate the detection of phishing URLs. However, these approaches often need more convincing accuracy and rely on datasets consisting of limited samples. Furthermore, these black-box intelligent models' decision to detect Suspicious URLs needs proper explanation to understand the features affecting the output. To address the issues, we propose a 1 D Convolutional Neural Network (CNN) and trained the model with extensive features and a substantial amount of data. The proposed model outperforms existing works by attaining an accuracy of 99.85 %. Additionally, our explainability analysis highlights certain features that significantly contribute to identifying the phishing URL. © 2024 IEEE.

关键词： Convolutional neural networks

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Enhancing the Kubernetes Platform with a Load-Aware Orchestration Strategy

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SN computer science 2025年第3期6卷 1-15页

作者： Marchese, Angelo Tomarchio, Orazio Dept. of Electrical Electronic and Computer Engineering University of Catania Catania Italy

Microservice architecture is increasingly favored for building large-scale applications designed for deployment in distributed and resource-constrained cloud-to-edge computing environments. As a cloud-native approach, microservices are particularly powerful due to their loosely coupled, independently deployable, and scalable characteristics. These features enable distributed deployment and flexible integration across robust cloud data centers and heterogeneous, often resource-limited, edge nodes. To fully leverage these advantages, there is a need for advanced placement algorithms that can optimize application performance by utilizing the strengths of microservices. In response to these challenges, we propose to extend Kubernetes with a load-aware orchestration strategy, which enhances its capability to deploy microservice applications within shared clusters characterized by dynamic resource usage patterns. Our approach orchestrates applications dynamically, based on real-time resource usage, allowing for continuous adjustment of their placement to match evolving conditions. Evaluation of a prototype system in a testbed environment demonstrates that this approach offers substantial benefits compared to the standard Kubernetes scheduler. © The Author(s) 2025.

关键词： Cloud continuum Container technology Kubernetes descheduler Kubernetes scheduler Microservice architecture

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