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Canadian Conference on electrical and computer engineering (CCECE)

作者： Aman Samson Mogos Xiaodong Liang C. Y. Chung Department of Electrical and Computer Engineering University of Saskatchewan Saskatoon Canada Department of Electrical Engineering The Hong Kong Polytechnic University Hong Kong China

Distribution transformers are the key components in distribution systems to maintain reliability of the system operation and reduce power outages. In this paper, a literature review is conducted on data-driven methods of the distribution transformer health monitoring by classifying the research streams and emphasizing advancements in machine learning, artificial intelligence and hybrid approaches in this area. The significance of data-driven methods is highlighted, demonstrating their ability to overcome traditional analytic limitations by providing real-time monitoring, prediction, and adaptability. As the distribution system continues to expand due to the increasing penetration of distributed energy resources (DERs) and electric vehicles (EVs), data-driven techniques emerge as a dependable and adaptable option for the effective transformer health monitoring.

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An Authentication Model Using Brainwave Panic Region Classifications from Electroencephalography 7th

An Authentication Model Using Brainwave Panic Region Classif...

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7th International Conference on Communication, Device and Networking, ICCDN 2024

作者： Abiodun, Opeyemi Anuoluwa Oyinloye, Oghenerukevwe E. Thompson, Aderonke F. Olowoyo, Paul Imoize, Agbotiname Lucky Sur, Samarendra Nath Computer Science Department The Federal Polytechnic Ekiti State Ado-Ekiti360211 Nigeria Computer Science Department Ekiti State University Ekiti State Ado-Ekiti360211 Nigeria Cyber Security Department Federal University of Technology Ondo State Akure350106 Nigeria Federal Teaching Hospital Ekiti State Ido-Ekiti Nigeria Department of Electrical and Electronics Engineering Faculty of Engineering University of Lagos Akoka Lagos 100213 Nigeria Department of Electronics and Communication Engineering Sikkim Manipal Institute of Technology Sikkim Manipal University Sikkim India

ISBN: (纸本)9789819764648

Biometric authentication scheme has been widely adopted for authentication purpose due to its uniqueness, universality, and distinctiveness. However, research has shown that these schemes are not necessarily more secured, especially with issues of coercion proliferating the cyberspace. Also, available techniques on repudiation of biometric features for authentication have not adequately explored this exciting topic. Integrating emotional state into the authentication scheme helps to mitigate coercion. This paper presents a framework for emotion as a way of biometric authentication scheme. An emotion classification model was developed by training an emotion classifier brainwave signal from eight subjects under normal state and duress using KNN machine learning algorithm. The authentication scheme grants access to users who pass both verification phases. The emotion classification model achieved an accuracy of 93.6% on the full feature set, while the reduced-feature set, as a result of feature selection, produced an improved accuracy of 94.15%. Hence, the emotion classification model can be integrated into existing biometric authentication system for improved security of critical user information. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Biometrics

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Impact of Plug-in Electric Vehicle Charging and Roof-top PVs on Distribution Transformer Health: A Case Study in Saskatoon, Canada

Impact of Plug-in Electric Vehicle Charging and Roof-top PVs...

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Canadian Conference on electrical and computer engineering (CCECE)

As the adoption of plug-in electric vehicles (PEVs) and rooftop photovoltaic (PV) systems continues to rise, understanding their combined impact on the health of distribution transformers becomes increasingly vital to ensure grid stability and longevity. In this paper, such combined impacts are investigated through a case study in Saskatoon, Canada. Using OpenDSS and MATLAB simulation, various PEV penetration levels and PV generation capacities are explored. Transformer heating dues to ambient temperature and loading is considered. The results show that the increased PEV adoption exacerbates the transformer stress, while the PV integration mitigates these effects, especially during summer, which highlights the need to encourage the rooftop PV adoption to balance the PEV charging demand on transformers. This paper offers valuable insights for electric utilities and policymakers to manage the grid infrastructure and promote sustainable energy practices.

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Multimodal Rumor Detection via Multimodal Prompt Learning

Multimodal Rumor Detection via Multimodal Prompt Learning

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International Joint Conference on Neural Networks (IJCNN)

作者： Fan Chen Xiuhong Li Zhe Li Chenyu Zhou Jiabao Sheng School of Computer Science and Technology Xinjiang University Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Department of Electrical Engineering Stanford University Department of Health Technology and Informatics The Hong Kong Polytechnic University Department of Radiation Oncology Stanford University

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Pre-trained vision-language (V-L) models exhibit significant generalization capabilities in detecting rumors. However, their reliance on single-modality prompts—either language or vision—limits their flexibility for dynamic adjustments in both representation spaces during rumor detection. To address these limitations, we propose a multimodal rumor detection framework that uses prompt learning in both the vision and language domains to align their representations better. Inspired by recent advances in efficiently tuning large language models, we introduce a set of trainable parameters in the input space, keeping the model backbone frozen. Additionally, we use distinct prompts at various early stages, which helps progressively model the relationships between features, enhancing comprehensive context learning. Extensive experiments with two real-world multimodal datasets demonstrate our framework’s superior ability to distinguish rumors from facts.

关键词： Accuracy Large language models Neural networks Tuning Context modeling

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Real-Time Simulation of a Resilient Control Center for Inverter-Based Microgrids

arXiv

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arXiv 2024年

作者： Beikbabaei, Milad Mehrizi-Sani, Ali The Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute State University BlacksburgVA24061 United States

The number of installed remote terminal units (RTU) is on the rise, increasing the observability and control of the power system. RTUs enable sending data to and receiving data from a control center in the power system. A distribution grid control center runs distribution management system (DMS) algorithms, where the DMS takes control actions during transients and outages, such as tripping a circuit breaker and disconnecting a controllable load to increase the resiliency of the grid. Relying on communication-based devices makes the control center vulnerable to cyberattacks, and attackers can send falsified data to the control center to cause disturbances or power outages. Previous work has conducted research on developing ways to detect a cyberattack and ways to mitigate the adverse effects of the attack. This work studies false data injection (FDI) attacks on the DMS algorithm of a fully inverter-based microgrid in real time. The fully inverter-based microgrid is simulated using an RTDS, an amplifier, an electronic load, a server, a network switch, and a router. The DMS is integrated into the server codes and exchanges data with RTDS through TCP/IP protocols. Moreover, a recurrent neural network (RNN) algorithm is used to detect and mitigate the cyberattack. The effectiveness of the detection and mitigation algorithm is tested under various scenarios using the real-time testbed. Copyright © 2024, The Authors. All rights reserved.

关键词： Digital storage

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Memory-Based Set Point Modulation for Improved Transient Response of Distributed Energy Resources

arXiv

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arXiv 2024年

作者： Beikbabaei, Milad Alexander, Brady Venkataramanan, Ashwin Mehrizi-Sani, Ali The Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute State University BlacksburgVA24061 United States

As the composition of the power grid evolves to integrate more renewable generation, its reliance on distributed energy resources (DER) is increasing. Existing DERs are often controlled with proportional integral (PI) controllers that, if not properly tuned or if system parameters change, exhibit sluggish performance or large overshoot. The use of set point automatic adjustment with correction-enabled (SPAACE) with a linear predictor improves the transient response of these DERs without the need to access the PI controller parameters. The limitation of the existing SPAACE method is the high sampling rate needed for improved performance, which is not always practical. This paper proposes the addition of a memory term to the SPAACE with a linear predictor. This memory term is the integral of the errors of previous samples, which adds another layer to the prediction to improve the response at lower sampling rates and further reduces the overshoot and settling time compared to the existing SPAACE method. Time-domain simulation studies are performed in PSCAD/EMTDC to show the effectiveness of the proposed controller. Copyright © 2024, The Authors. All rights reserved.

关键词： Transient analysis

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Online estimation of passive elements in a double conversion UPS system with no additional sensors

Online estimation of passive elements in a double conversion...

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2021 Telecoms Conference, ConfTELE 2021

作者： Oliveira, Tiago J.L. Baptista, Tiago M.C. Caseiro, Luis M.A. Mendes, Andre M.S. Perdigao, Marina S. Cruz, Sergio M.A. University of Coimbra Deec Department of Electrical and Computer Engineering Coimbra Portugal Instituto de Telecomunicações Department of Electrical and Computer Engineering Coimbra Portugal Coimbra Polytechnic - Isec Department of Electrical and Computer Engineering Coimbra Portugal

ISBN: (纸本)9781665415880

Uninterruptible Power Supplies (UPS) represent the main technology used to supply a wide range of critical applications in which information, communication and technology (ICT) facilities such as high-tier datacenters are widely included. Beyond power converters, UPS systems require passive elements not only for proper current/voltage filtering but also to create an internal DC bus. Since these elements are typically subjected to a high amount of stress, deviations of their value can occur over time. With these deviations the overall UPS performance typically decreases and if an element reaches its end-of-life, the protection of the critical loads can even be highly compromised. Hence, the estimation of UPS passive elements is of extreme importance. In this paper, two real-time strategies based on the Adaptive Linear Neuron (ADALINE) approach are proposed to estimate the inductance and capacitance of UPS filters as well as DC bus capacitors capacitance. By using the proposed technique, only sensors required for UPS controllers are used with no additional hardware being required. Simulation results are presented to demonstrate the effectiveness of the proposed estimation methods. © 2021 IEEE.

关键词： Uninterruptible power systems

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Evaluating Electric Vehicle Charging Impacts on Distribution Grid Stability and Efficiency Through Adaptive Load Management Strategies

Evaluating Electric Vehicle Charging Impacts on Distribution...

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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Janakiraman, V. Ahmad, Sabbir Revathi, V. Dutt, Amit Rani, K.Pushpa Al-Rubaye, Taqi Mohammed Khattab Bobba, Phaneendra Babu Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India University Polytechnic Jamia Millia Islamia Department of Electronics Engineering F/O Engineering & Tech India New Horizon College of Engineering Department of Applied Sciences Bangalore India Lovely Professional University Phagwara India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India College of Medical Technologies The Islamic University Department of Medical Laboratory Technology Najaf Iraq Griet Department of Eee Telangana Hyderabad India

ISBN: (纸本)9798331527495

The high growth rates of the EV market create complex issues for distribution grids, forcing a detailed examination of grid responses at high rates of EV deployment. This paper seeks to elucidate the effects of EV charging on the distribution grid stability With this, the impact of the pod on voltage fluctuations, line load, and power loss is assessed using the IEEE 37-bus system. Load patterns of EV charging stations are consequently simulated successfully by a number of real and statistically created synthetic data sources, which truly represent averaged fluctuations in load. The study looks at several charging methods of the EV, such as time of use and smart charging, to determine their impact on the grids. Furthermore, the utilization of renewable energy sources for improving the aspects of grid reliability is explored. Regarding performance aspects related to the expansion of widespread EV charging and the efficiency of the applied measures for grid stabilization, the results of this study offer beneficial information. © 2025 IEEE.

关键词： Electric buses

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Employing Parallelization Technique to Reduce Area and Power in a Booth Encoded Algorithm-Based Multiplier

Employing Parallelization Technique to Reduce Area and Power...

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International Conference on Mixed Design of Integrated Circuits and Systems (MIXDES)

作者： Karwan Javanmardi Sobhan Sofimowloodi Amir Attar Abdollah Amini Department of Electrical Engineering Roj Diyar Nano Electro System Technical and Engineering Company Bukan Iran Department of Electrical Engineering Amirkabir University of Technology (Tehran Polytechnic) Tehran Iran Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (数字)9788363578268

ISBN: (纸本)9798350375701

This paper discusses the improvement of the multiplication operation speed in multipliers based on Booth's algorithm. The main goal of Booth's algorithm is to reduce the number of partial products by half, as a result of which, the multiplication operation will be completed sooner. The method proposed in this paper to solve this problem is designing a parallel multiplier using only one Booth Encoder circuit and one adder circuit. With the help of a series of circuits and control signals, these two circuits work in parallel and simultaneously so that the speed of the multiplication operation is not affected much. The production of partial products and their accumulation is being done in parallel. At the same time, the amount of hardware that is directly related to the power consumption is significantly reduced. The presented design is implemented in CMOS technology and 0.18um process. The proposed multiplier produces the correct output after 78nsec, and its operating speed is 12.8 MHz. The average power consumption of this multiplier is approximately 1.09 mW, and the number of transistors required for its construction is 2927.

关键词： Integrated circuits Power demand Production Logic gates CMOS technology Hardware Timing

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Design Optimization of a 3.3 V Bus Converter for Vertical Power Delivery in Next-Generation Processors

Design Optimization of a 3.3 V Bus Converter for Vertical Po...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Yan Liang Pranav Raj Prakash Ahmed Nabih Qiang Li Bradley Department of Electrical and Computer Engineering Virginia Polytechnic and State University Blacksburg USA NVIDIA Corporation Durham USA

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

The advancements in artificial intelligence and machine learning are driving the development of a new generation of ultra-powerful graphical processing units (GPUs). The latest datacenter-grade GPU cards use the two-stage lateral power delivery with a traditional 12V intermediate bus voltage (IBV). The next-generation GPUs are expected to double in power and package size, resulting in less space for higher power delivery. A previous study proposed a two-stage vertical power delivery solution by relocating the 2 nd stage converters with a lower IBV. In this architecture, an unregulated LLC resonant converter (DCX) based 1 st stage intermediate bus converter (IBC) steps down 48V to a low IBV, and the 2 nd stage is a packaged voltage regulator stacked under the GPU minimizing the power delivery network (PDN) length; however, the I 2 R losses at a very low IBV will limit the overall high-power delivery. To ensure the high-power delivery to future GPUs, this paper focuses on the design of a high-efficiency, high-density 1 st stage IBC with an IBV of 3.3V. A high-density LLC DCX based unit-cell design is implemented enabling the high-power delivery symmetrically. By optimizing the winding arrangement, the leakage flux and winding ac resistance of the transformer are minimized. Additionally, the non-ideal current sharing associated with the top-cooled module is mitigated. The elimination of these issues is critical as they lead to the degradation of parallel winding effectiveness and a reduction in efficiency. The proposed improvements are verified by developing an 840W 3.3V bus converter prototype with a peak efficiency of 97.3% and a power density of 2300 W/in.

关键词： Resistance Power system measurements Density measurement Windings Graphics processing units computer architecture Transformers Thermal loading Voltage control Next generation networking

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