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Optimal Mitigation of Renewable Energy Curtailment in Greece through Energy Storage 5

Optimal Mitigation of Renewable Energy Curtailment in Greece...

引用

5th IEEE International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2024

作者： Karapidakis, Emmanuel Nikologiannis, Marios Mozakis, Ioannis Katsigiannis, Yiannis Iliadis, Ioannis Hellenic Mediterranean University Dept. of Electrical and Computer Engineering Heraklion Greece

ISBN: (纸本)9798350352863

The limitation of energy curtailment produced through Renewable Energy Sources (RES) is obstructed by technical, economic, and political factors. This reduction has negative financial consequences for renewable energy producers and may lead to higher electricity prices for consumers. To address these challenges, this study aims to explore the potential benefits of hydrogen energy storage as a solution to reduce renewable energy curtailment and improve the economic viability of renewable energy projects participating in the Day-Ahead Market (DAM). Using recent data from the Independent Power Transmission Operator (IPTO) and the Hellenic Energy Exchange (HEnEx), the study implements a metaheuristic optimisation algorithm, the Moth-Flame Optimiser (MFO), to investigate the feasibility of the proposition. The methodology computes a 1.23% return on investment over an eight-month operational period, with minimal monthly participation. By reducing the costs of the purchase and installation of system components, combined with governmental support in the form of incentives, the current obstacles could be removed. © 2024 IEEE.

关键词： Clean energy

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Multi-Layered Approach to IoT Cybersecurity in Smart Cities 3

Multi-Layered Approach to IoT Cybersecurity in Smart Cities

引用

3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Benjamine, Daniel Anto Madhavan, K. Pavithra, S. Dept. of Computer Science and Engineering Chennai Institute of Technology Chennai India

ISBN: (纸本)9798331527549

Internet of Things (IoT) has been rapidly growing over the past years. There have been many cybersecurity challenges faced by IoT-based smart cities in existing work for the energy, health and transportation sectors. These cybersecurity challenges are crucial to remove in the IoT sector to implement a safe and secure IoT based smart city. Vulnerabilities across layers in IoT are analyzed and a multi-layered model of security is proposed to enhance data integrity and communication security by using AI, blockchain and ML. This paper would also present several policy recommendations to stakeholders and IoT developers for building a safe urban IoT ecosystem. © 2025 IEEE.

关键词： Cybersecurity frameworks IoT smart city technologies urban

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Systematic Comparison of Machine Learning for Activity Recognition in Cross-Subject vs. NonCross-Subject Scenarios: A Preliminary Analysis 8

Systematic Comparison of Machine Learning for Activity Recog...

引用

8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024

作者： Pe, Samuele Nicora, Giovanna Guerra, Bruna Maria Vittoria Sozzi, Stefania Parimbelli, Enea University of Pavia Dept. of Electrical Computer and Biomedical Engineering Pavia Italy

ISBN: (纸本)9798350362138

Human Activity Recognition (HAR) is pivotal for automating the detection and classification of human movements. Technological advances in data collection from sensors and cameras is making automatic HAR increasingly available to support robotics-assisted rehabilitation, where the detection of abnormal patterns in movement and gait can aid clinical evaluation of patients with diverse disorders. HAR typically employs Machine Learning (ML) or Deep Learning (DL) techniques to analyze sensor data patterns for various activities. However, the generalizability of ML/DL models remains underexplored, particularly concerning the impact of different training and evaluation settings. Overfitting is a common challenge, especially in medical applications where user-dependent training data hinder generalization. Investigating the performance of ML and DL algorithms after a cross-subject (CS) and a noncross-subject (NCS) division of the dataset into training and test sets is crucial. This study aims to systematically compare various ML and DL algorithms for HAR, evaluating their performance across the CS and NCS settings to discern the impact of inter-subject variability on model generalizability. © 2024 IEEE.

关键词： Contrastive Learning

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Software Code De-Compilation Techniques and Approaches: A Comparative Study 25

Software Code De-Compilation Techniques and Approaches: A Co...

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Fawareh, Hamed Al-Smadi, Yazan Hassan, Mohammad Fawareh, Faid AlNoor Elrashidi, Ali Zarqa University Dept. of Software Engineering Jordan Zarqa University Dept. of Computer Science Jordan Zarqa University Dept. Of Mathmitical Science Jordan University of Business and Technology Dept. of Electrical Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

De-compilation is the process of executable files as input where the de-compilation process tries to get away the source code, or the majority of it, if the file's source code is lost or damaged for whatever cause. De-compilation has many uses such as code recovery, security testing, and errors corrections, however, de-compilation is cautious since it depends on certain approaches and techniques. Nowadays de-compilation done by many automated and semi-automated tools, but the accuracy and the efficiency of it depend on the proposed approaches and techniques to stand in front of reengineering challenges. This paper aims to highlight up-to-date prior contributions in the field where 8 published research papers from May 2020 until May 2023 were collected to investigate the state-of-art. As a result, some of the researchers tend to develop their own tools and others tend to use popular automated with different approaches and techniques where the majority of the researchers focused on C, C++, and JAVA programming languages where 50% were de-compilation on C language. © 2024 IEEE.

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Preserving Pre-trained Representation Space: On Effectiveness of Prefix-tuning for Large Multi-modal Models

Preserving Pre-trained Representation Space: On Effectivenes...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Kim, Donghoon Lee, Gusang Shim, Kyuhong Shim, Byonghyo Dept. of Electrical and Computer Engineering Seoul National University Korea Republic of

ISBN: (纸本)9798891761681

Recently, we have observed that Large Multi-modal Models (LMMs) are revolutionizing the way machines interact with the world, unlocking new possibilities across various multi-modal applications. To adapt LMMs for downstream tasks, parameter-efficient fine-tuning (PEFT) which only trains additional prefix tokens or modules, has gained popularity. Nevertheless, there has been little analysis of how PEFT works in LMMs. In this paper, we delve into the strengths and weaknesses of each tuning strategy, shifting the focus from the efficiency typically associated with these approaches. We first discover that model parameter tuning methods such as LoRA and Adapters distort the feature representation space learned during pre-training and limit the full utilization of pre-trained knowledge. We also demonstrate that prefix-tuning excels at preserving the representation space, despite its lower performance on downstream tasks. These findings suggest a simple two-step PEFT strategy called Prefix-Tuned PEFT (PT-PEFT), which successively performs prefix-tuning and then PEFT (i.e., Adapter, LoRA), combines the benefits of both. Experimental results show that PT-PEFT not only improves performance in image captioning and visual question answering compared to vanilla PEFT methods but also helps preserve the representation space of the four pre-trained models. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Use of a Hybrid Storage System for Frequency Regulation Services from a Photovoltaic Plant: Emulating Synchronous Generator Dynamics 3

Use of a Hybrid Storage System for Frequency Regulation Serv...

引用

3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Papageorgiou, Pavlos G. Oureilidis, Konstantinos O. Christoforidis, Georgios C. University of Western Macedonia Dept. of Electrical & Computer Engineering Kozani Greece

ISBN: (纸本)9798350375923

The gradual decommissioning of grid-forming synchronous generators and the increasing penetration of grid-following renewable energy sources such as photovoltaics (PVs), undermine the reliable operation of the grid. In this sense, even small power imbalances can cause significant frequency deviations. To address such issues, the employment of standalone battery storage systems is usually proposed to alleviate the power imbalances by releasing/absorbing energy when needed. However, a standalone battery suffers from quick lifetime fading and it cannot effectively provide multiple grid services simultaneously. To this end, this study presents a controller for a hybrid storage system that consists of a power-type superconducting magnetic energy storage (SMES) and an energy-type battery. The hybrid storage system is AC-coupled and provides frequency regulation services on behalf of the PV plant without any modification on its inverter. Through proper control, SMES handles the short-term power fluctuations emulating the inertial properties of a synchronous generator, while battery cope with long-term demands imitating the primary frequency response of the generator. Thus, the distinct features of both SMES and battery are effectively exploited, ensuring minimal stress on battery. To evaluate the proposed method during grid frequency events, simulation results are presented. © 2024 IEEE.

关键词： Synchronous generators

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Controller Design for Water Treatment Plants Using Data-Driven Control 50

Controller Design for Water Treatment Plants Using Data-Driv...

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

作者： Furukawa, Masaki Fujimoto, Yasutaka Dept. of Electrical and Computer Engineering Yokohama National University Yokohama Japan

ISBN: (纸本)9781665464543

This study explores methods for improving energy efficiency in wastewater treatment facilities to address the pressure of rising electricity tariffs. As the energy consumption by water treatment facilities accounting for about 50% of the total electricity consumption in wastewater treatment facilities, particular attention is paid to the energy utilization of blowers within water treatment facilities [1], [2]. The aim is to achieve appropriate control of aeration equipment based on the facility’s conditions and environment, without relying on plant models but using data-driven control. This approach addresses the problem of excessive electricity consumption in current scenarios that rely on manual control or simple control loops. By employing VRFT for the PID controller parameter tuning, a successful improvement in the target response performance was achieved. The proposed method achieved an error in the DO response comparable to that of conventional methods and reduced the operating costs of aeration at wastewater treatment plants by about 12%. © 2024 IEEE.

关键词： data-driven control virtual reference feedback tuning wastewater treatment plant

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UAV-Enabled Covert Cross-Technology Communication in Heterogeneous IoT Networks 100

UAV-Enabled Covert Cross-Technology Communication in Heterog...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Xia, Xiaohao Esmat, Haitham H. Lorenzo, Beatriz Goeckel, Dennis University of Massachusetts Amherst Dept. Electrical and Computer Engineering United States

ISBN: (纸本)9798331517786

Heterogeneous Internet of Things (IoT) networks enabled by Unmanned Aerial Vehicles (UAVs) operate in various protocols and spectrum bands (e.g., WiFi, LoRa, Zigbee) to collect and offload data generated from heterogeneous sensors. However, achieving timely and secure communications is challenging due to uncertain data generation, mobility, and location of wardens. This paper presents a collaborative framework that exploits cross-technology communications to achieve covertness constraints. The aim is to minimize the age of covert information (AoCI) and energy consumption by jointly optimizing data scheduling, power allocation, and offloading decisions by collaborating with UAVs. A multi-agent actor-critic algorithm that incorporates federated learning and attention mechanisms (cluster-MAAC-attention) is presented to solve the previous problem. Our simulation results show that our algorithm reduces the worst AoCI by 4 times, and reduces the penalty by 20 times compared to existing schemes. © 2024 IEEE.

关键词： Zigbee

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Using Semeru Cloud Compiler to Enhance Cloud-Native Java Application Performance 34

Using Semeru Cloud Compiler to Enhance Cloud-Native Java App...

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34th Annual International Conference on Collaborative Advances in Software and Computing, CASCON 2024

作者： Liu, Ryan Shinde, Shreya Tahvildari, Ladan Stoodley, Mark Sundaresan, Vijay Pirvu, Marius University of Waterloo Dept. of Electrical and Computer Engineering Canada IBM Canada

ISBN: (纸本)9798331504830

Java-based applications rely on just-in-time (JIT) compilation to convert bytecode into machine code at run-time to improve throughput. However, JIT compilation is achieved at the cost of additional CPU cycles and memory. In the context of modern cloud, where applications have limited computing resources due to containerization, JIT compilation may potentially become a pain-point. The Semeru Cloud Compiler (SCC) is a promising solution that offloads JIT compilation to a remote cloud compiler to reduce the local overhead of JIT compilation in containers. In this paper, we outline novel research directions to further leverage the advantages of remote cloud compilation by extending the SCC to achieve two goals: (i) reduce application start-up time and (ii) improve JIT compilation decision making. To reduce application start-up time, the proposed enhancement is to extract unused or unlikely to be used Java class files from container images. The SCC can still provide the extracted class files to the client JVM if any turn out to be needed. Our preliminary experiments show that this approach can potentially reduce container image sizes by up to 22.1% and start-up times by up to 9.2% for certain applications. To reduce JIT compilation overhead, the proposed enhancement is to perform dynamic analysis of the Java application using the additional resources on the server-side. In turn, the remote JIT compilation can make more informed decisions regarding which methods to compile and optimizations to apply. We are also developing a novel visualization tool designed to help JIT compiler developers identify pain points in current JIT compilation heuristics. Specifically, we have measured that up to 18.9% of JIT compilations for certain applications may be sub-optimal due to later method inlining, and we are investigating how the SCC could help to avoid these potentially wasted compile-time computations by using information learned from other JVM clients. © 2024 IEEE.

关键词： Program compilers

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Dots to Dialogue: Enhancing Accessibility through Braille Image-to-Speech Conversion 3

Dots to Dialogue: Enhancing Accessibility through Braille Im...

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Shwetha, B.S. Sirisha, M. Vachana, U. Kadlimatti, Aditya Manjushree, N.S. Dept. of Computer Science and Engineering Bangalore Institute of Technology Bengaluru India

ISBN: (纸本)9798331527549

Braille script serves as a fundamental medium of communication for individuals with visual impairments. However, its interpretation by non-experts poses a significant challenge, hindering inclusivity in education and daily interactions. This study proposes a system that leverages Convolutional Neural Networks (CNNs) and the Google Text-to-Speech (GTTS) library to translate Braille text into multilingual speech. This research addresses the challenge of Braille literacy among visually impaired individuals by developing a system that translates Braille text into multilingual speech. The proposed solution utilizes advanced CNNs for accurate Braille character recognition and integrates GTTS technology for real-time speech output. The results demonstrate a significant improvement in accessibility and communication for users, with an accuracy rate of 97.28% achieved using the AlexNet model." © 2025 IEEE.

关键词： Convolutional neural networks

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