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Hydrogen Energy Storage System:Review on Recent Progress

Energy engineering 2025年第1期122卷 1-39页

作者： MilleniumWong Hadi Nabipour Afrouzi Research Centre for Sustainable Technologies Faculty of EngineeringComputing and ScienceSwinburne University of TechnologyJalan Simpang TigaKuchingSarawak93350Malaysia College of Engineering Faculty of ComputingEngineering and the Built EnvironmentBirmingham City UniversityBirminghamWest MidlandsEnglandB47XGUK

A hydrogen energy storage system(HESS)is one of the many risingmodern green innovations,using excess energy to generate hydrogen and storing it for various *** that,there have been many discussions about commercializing HESS and improving it ***,the design and sizing process can be overwhelming to comprehend with various sources to examine,and understanding optimal design methodologies is crucial to optimize a HESS *** that,this review aims to collect and analyse a wide range of HESS studies to summarise recent *** different collections of studies are studied,one was sourced by the main author for preliminary readings,and another was obtained via *** findings from the Web of Science platform were also examined for amore comprehensive *** findings include the People’sRepublic of China has been active in HESS research,as most works and active organizations originate from this *** has been mainly researched to support power generation and balance load demands,with financial analysis being the common scope of *** is a common tool used for HESS design,modelling,and optimization as it can handle complex *** neural network(ANN)has the potential to be used to model the HESS,but additional review is required as a formof future *** a commercialization perspective,pressurized hydrogen tanks are ideal for hydrogen storage in a HESS,but other methods can be considered after additional research and *** this review,it can be implied that modelling works will be the way forward for HESS research,but extensive collaborations and additional review are ***,this review summarized various takeaways that future research works on HESS can use.

关键词： Hydrogen energy storage system VOSViewer design review sizing

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Optimal Voltage Regulator Coordination via Cuckoo Search Algorithm in Distributed Generation System to Enhance Grid Stability

Optimal Voltage Regulator Coordination via Cuckoo Search Alg...

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2024 IEEE Sustainable Power and Energy Conference, iSPEC 2024

作者： Kamal, Hamid Ali Afrouzi, Hadi Nabipour Jayamani, Elammaran Ektesabi, Mehran Siang, Chua Hong En, Lee Hui Swinburne University of Technology Faculty of Engineering Computing and Science Sarawak Malaysia Swinburne University of Technology Faculty of Engineering Computing and Science Melbourne Australia

ISBN: (纸本)9798350395075

Hybrid power systems need frequent voltage regulation to handle fluctuations in load profile and renewable energy output, ensuring effective voltage management. This increased need for regulation extends the operating time of the tap changer in transformers, accelerating the degradation of the on-load tap changer (OLTC) device, which happens to be the most costly component of the transformer. In this paper, the optimal coordinated operations among distribution static compensator (DSTATCOM), distributed generation (DGs), and OLTC are proposed using the Cuckoo Search algorithm (CSA). The aim is to optimize voltage deviations, OLTC usage, and power losses. The effectiveness of this approach is evaluated across two realistic scenarios using 32 distribution test systems. The simulation outcomes demonstrate how important coordinated management is in ensuring that voltage standards are met at each node while lowering power losses. © 2024 IEEE.

关键词： Distribution transformers

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Robotic Automation System for Indoor Greenhouse Applications 12

Robotic Automation System for Indoor Greenhouse Applications

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12th IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2024

作者： Qi, Josiah Yang Hung, Lai Chean Jo, Hudyjaya Siswoyo Kiat, Justin Sia Wei Ting, Evon Lim Wan Dunn, Michelle Swinburne University of Technology Faculty of Engineering Computing and Science Kuching Malaysia Swinburne University of Technology Faculty of Engineering Computing and Science Melbourne Australia

ISBN: (纸本)9798350340204

As the world advances, the global population is projected to reach an estimated 9 billion by 2050, leading to a higher demand for food. To boost agricultural production without harming the environment, new and sustainable technologies are essential for improving efficiency and output. Precision farming has existed for years, but as its efficiency improves, scalability on large farms has emerged as a significant challenge. This project proposes using a mobile robotic system that can be deployed in existing greenhouses with minor changes and little additional infrastructure to assist current laborers in the agricultural sector. This paper would focus on the development and early onsite testing of the proposed robot in an indoor greenhouse environment. The robot successfully interacted with plants in 105 out of 135 test runs in a laboratory setting giving a success rate of 75.5%. Onsite testing where done with similar configurations to the laboratory settings to identify potential problems in a different environment. © 2024 IEEE.

关键词： Greenhouse Automation Greenhouses Object Detection Precision Agriculture Precision Farming Robotics Visual Control Feedback

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Implementation of Composable Enterprise in an Evolutionary Way Through Holistic Business-IT Delivery of Business Initiatives: Real Industry Use Case 26

Implementation of Composable Enterprise in an Evolutionary W...

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26th International Conference on Enterprise Information Systems, ICEIS 2024

作者： Ivas, Ivka Faculty of Electrical Engineering and Computing University of Zagreb Croatia

ISBN: (纸本)9789897586927

Service composability, introduced by service-oriented architecture (SOA), is a design principle that encourages the design of reusable services that themselves also consist of reusable services. In domain driven design (DDD), which inspired microservice architectures, the scope of composable service design is interpreted as a software solution domain, while the problem domain lies in the detached business world. This results in IT solutions that are often redundant at the enterprise level or tend to be composable only within a specific enterprise IT ecosystem as a result of the design without understanding the business domain or how the new solution fits into the overall delivery and enterprise architecture. On the other hand, it is not uncommon for company's "business", motivated by revenue increase, to push frequent deliveries of business changes, putting pressure on company's IT to implement quick fix solutions that only solve immediate business problems. All this leads to inconsistent and redundant software systems that increase the complexity of the organization and result in higher maintenance costs and less flexibility in implementing future changes. As a solution, this paper proposes Composable Enterprise, a business-IT approach for architecting the enterprise that introduces Business Composability and a holistic understanding of the enterprise. Business Composability is a business-IT-aligned service abstraction that starts with the notion of first applying service composability to business assets (business capabilities) to achieve the scale and pace required to realize business changes. The purpose of this paper is to provide a methodology for implementing Composable Enterprise in large, complex organisations, not as a massive, enterprise-wide rationalization and consolidation initiative, but in an evolutionary way through the joint and holistic business-IT delivery of business initiatives. The application of the proposed methodology is illustrated using a

关键词： Information services

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A Review of Sustainable Farming with Robotics in Indoor Greenhouse Environments 12

A Review of Sustainable Farming with Robotics in Indoor Gree...

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12th IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2024

ISBN: (纸本)9798350340204

Current trend projected the global population to increase to 9 billion by the year 2050 which will increase the demand of food production by around 70%. The agricultural sector also supplies produce to bio-based products such as bioenergy and bioplastics which is also increasing the demand for crops. However, the situation is not as simple as planting more crops, as current agricultural practices are not sustainable. Environmental impact and climate changes could be reduced with the utilization of indoor farming could bring about a more sustainable farming solution. Combined with the utilization of precision farming solutions such as IoT based sensors and robotic systems indoor farming could become the next step in sustainable farming. The implementation of precision farming in indoor farming comes with its problems which may cause a challenge in the development and deployment period. This paper serves as the preliminary research for the development of a robotic system to be deployed at Sarawak's Digital Economy Corporation (SDEC)'s greenhouse. © 2024 IEEE.

关键词： Sustainable agriculture

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Addressing Imbalance in Health Datasets: A New Method NR-Clustering SMOTE and Distance Metric Modification

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Computers, Materials & Continua 2025年第2期82卷 2931-2949页

作者： Hairani Hairani Triyanna Widiyaningtyas Didik Dwi Prasetya Afrig Aminuddin Department of Electrical Engineering and Informatics Faculty of EngineeringUniversitas Negeri MalangMalang65145Indonesia Department of Computer Science Universitas BumigoraMataram83127Indonesia Department of Computer Graphic and Multimedia Faculty of ComputingCollege of Computing and Applied SciencesUniversiti Malaysia Pahang Al-Sultan AbdullahPekan26600Malaysia

An imbalanced dataset often challenges machine learning, particularly classification methods. Underrepresented minority classes can result in biased and inaccurate models. The Synthetic Minority Over-Sampling Technique (SMOTE) was developed to address the problem of imbalanced data. Over time, several weaknesses of the SMOTE method have been identified in generating synthetic minority class data, such as overlapping, noise, and small disjuncts. However, these studies generally focus on only one of SMOTE’s weaknesses: noise or overlapping. Therefore, this study addresses both issues simultaneously by tackling noise and overlapping in SMOTE-generated data. This study proposes a combined approach of filtering, clustering, and distance modification to reduce noise and overlapping produced by SMOTE. Filtering removes minority class data (noise) located in majority class regions, with the k-nn method applied for filtering. The use of Noise Reduction (NR), which removes data that is considered noise before applying SMOTE, has a positive impact in overcoming data imbalance. Clustering establishes decision boundaries by partitioning data into clusters, allowing SMOTE with modified distance metrics to generate minority class data within each cluster. This SMOTE clustering and distance modification approach aims to minimize overlap in synthetic minority data that could introduce noise. The proposed method is called “NR-Clustering SMOTE,” which has several stages in balancing data: (1) filtering by removing minority classes close to majority classes (data noise) using the k-nn method;(2) clustering data using K-means aims to establish decision boundaries by partitioning data into several clusters;(3) applying SMOTE oversampling with Manhattan distance within each cluster. Test results indicate that the proposed NR-Clustering SMOTE method achieves the best performance across all evaluation metrics for classification methods such as Random Forest, SVM, and Naїve Bayes, compared t

关键词： SMOTE modification Clustering-SMOTE manhattan distance

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A survey on deep-learning-based gaze direction regression: searching for the state-of-the-art 5

A survey on deep-learning-based gaze direction regression: s...

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5th Symposium on Pattern Recognition and Applications, SPRA 2024

作者： Šikić, Franko Vršnak, Donik Lončarić, Sven University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (数字)9781510688803

ISBN: (纸本)9781510688797

In this paper, we present a survey of deep learning-based methods for the regression of gaze direction vector from head and eye images. We describe in detail numerous published methods with a focus on the input data, architecture of the model, and loss function used to supervise the model. Additionally, we present a list of datasets that can be used to train and evaluate gaze direction regression methods. Furthermore, we noticed that the results reported in the literature are often not comparable one to another due to differences in the validation or even test subsets used. To address this problem, we re-evaluated several methods on the commonly used in-the-wild Gaze360 dataset using the same validation setup. The experimental results show that the latest methods, although claiming state-of-the-art results, significantly underperform compared with some older methods. Finally, we show that the temporal models outperform the static models under static test conditions. Copyright © 2025 SPIE.

关键词： Support vector regression

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Conspiracy Theory Detection using Transformers with Multi-task and Multilingual Approaches 25

Conspiracy Theory Detection using Transformers with Multi-ta...

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25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024

作者： Zrnić, Leon University of Zagreb Faculty of Electrical Engineering and Computing Croatia

The COVID-19 pandemic sparked a new age of conspiracy theories in society. This has become an issue, especially since these theories are mixed in with reasonable arguments that criticize the measures taken by governments and their effects. A way to help differentiate these two narratives is using natural language processing (NLP) models such as Transformers. These working notes detail a few approaches to classifying conspiracy and critical narratives and the identification of the key narrative elements present in these texts. We employ these models on two datasets which encompass English and Spanish texts on Telegram talking about the COVID-19 pandemic. Our approaches include using pre-trained BERT and RoBERTa models on monolingual datasets, a multilingual approach in which we translate the Spanish texts into English and the use of a multilingual model on non-translated texts, and using a multi-task model architecture in the identification of narrative elements. Our results show that BERT pre-trained on COVID-19 tweets had similar results to RoBERTa in the binary classification task, while in the token classification task RoBERTa worked better. The monolingual English approach yielded better results than the multilingual one which was, however, better than the Spanish models. We conclude that transformer models can have good results in these classification tasks, making them an easy-to-deploy way to differentiate critical narratives from conspiracy theories. © 2024 Copyright for this paper by its authors.

关键词： Natural language processing systems

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Enhancing Programming Education with Open-Source Generative AI Chatbots 47

Enhancing Programming Education with Open-Source Generative ...

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47th ICT and Electronics Convention, MIPRO 2024

作者： Šarčević, Antonia Tomičić, Ivan Merlin, Andrija Horvat, Marko University Of Zagreb Faculty Of Electrical Engineering And Computing Department Of Applied Computing Zagreb Croatia

ISBN: (纸本)9798350382495

This paper describes the development of an Open-Source Generative AI Chatbot, utilizing free Large Language Models (LLM) to enrich the student learning experience for a university course in 'Introduction to Programming'. The article aims to provide a step-by-step guide for selecting, fine-tuning, and evaluating available models. As a first step in choosing the appropriate LLM, which provides the most accurate responses while not requiring excessive computing power, the article will cover a discussion of the advantages and disadvantages of local vs. cloud-available models. After selecting a few promising models, the next stage includes fine-tuning LLMs to answer domain-specific questions using a dataset containing essential rules, guidelines, and explanatory content regarding the subject. The crucial aspect of selecting a model was evaluating answers, and in this context, both human and automatic evaluation techniques will be presented. Finally, it is possible to enhance the model performance and accuracy by incorporating Retrieval-Augmented Generation (RAG) techniques and exploring the influence of various factors, such as different vector databases, model temperatures, maximum token lengths, prompt templates, embeddings, repetition penalties, and chunking sizes. Our results show that chatbots have significant potential to improve academic support and learning efficiency, as well as personalized education in general. © 2024 IEEE.

关键词： Natural language processing systems

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Revolutionizing Software Development: Autonomous Software Evolution 47

Revolutionizing Software Development: Autonomous Software Ev...

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47th ICT and Electronics Convention, MIPRO 2024

作者： Mlinarić, D. Dončević, J. Brčić, M. Botički, I. University Of Zagreb Faculty Of Electrical Engineering And Computing Croatia

ISBN: (纸本)9798350382495

This paper discusses a software development method focused on creating a self-adapting and evolving system using AI and ML techniques. The goal is to reduce the need for manual software updates, offering a solution that continuously adapts to changing requirements. To achieve this goal, an AI-based update model is presented, and a possible system is discussed. Use case example demonstrate the applicability of the update model in real-world scenarios. As a cloud-based solution, this method could ensure scalability and broad applicability across various industry sectors. © 2024 IEEE.

关键词： Software design

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