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Forecasting Transmission and Distribution System Flexibility Needs for Severe Weather Condition Resilience and Outage Management
With the increase in the complexity of the topology of transmission and distribution systems, associated with the predictability in the management of the dispatch of prosumers, new techniques for state estimation, and application of metaheuristics are necessary. In the current work a pilot project in Greece that addresses the difficulties of congestion and balancing management that system operators face in the renewable energy sources era, in accordance with the OneNet’s architecture is described. Available resources of grid’s flexibility are identified, and the implementation of an integrated monitoring system based on weather conditions with an energy control and dispatch system in the Greek electricity grid is addressed. The document suggests that flexibility resources will derive through predictions that have been improved and efficient forecasts from increased spatial resolution Numerical Weather Predictions and integration of Artificial Intelligence preventing the power system of entering dangerous topological or operational states.
Journal Article
Active System Management Approach for Flexibility Services to the Greek Transmission and Distribution System
New methods for state estimation are required due to the complexity of the topology of transmission and distribution systems, and the predictability in the management of prosumer dispatch. This paper describes a pilot project in Greece that, in accordance with OneNet’s architecture, addresses the challenges of congestion and balancing management that system operators face due to the high penetration of renewable energy sources. The respective data requirements and the IT/OT environment are described, as well as the interconnections among the various modules and functionalities. Available resources of the grid’s flexibility are identified, and the implementation of an integrated monitoring system based on efficient forecasting of volatile generation and demand is addressed. Congestion management and frequency and voltage control are in the center of interest of the demonstrator where, in close collaboration with system operators, respective network models are being developed.
Journal Article
Using Actors and Use Cases for Software Size Estimation
Software size estimation represents a complex task, which is based on data analysis or on an algorithmic estimation approach. Software size estimation is a nontrivial task, which is important for software project planning and management. In this paper, a new method called Actors and Use Cases Size Estimation is proposed. The new method is based on the number of actors and use cases only. The method is based on stepwise regression and led to a very significant reduction in errors when estimating the size of software systems compared to Use Case Points-based methods. The proposed method is independent of Use Case Points, which allows the elimination of the effect of the inaccurate determination of Use Case Points components, because such components are not used in the proposed method.
Journal Article
Strategizing blockchain adoption in public cultural services: a comprehensive scoping review
PurposeThis paper explores the application of blockchain technology in the public cultural sector, where adoption remains limited despite its potential. The study identifies major use case scenarios and empirical examples of blockchain adoption in public sector cultural services through a scoping literature review.Design/methodology/approachA scoping literature review was conducted to map research and conceptual approaches to blockchain technology in the public cultural sector, focusing on key use cases emerging and empirical examples.FindingsThe review reveals that while blockchain has the potential to enhance public cultural services, its adoption is still in its early stages. Identified use cases include tokenization of cultural assets, digital rights management and decentralized funding models. Empirical examples in the public cultural sector are sparse, and the impact of the technology remains largely theoretical.Research limitations/implicationsThe study is limited by the scarcity of empirical data on blockchain adoption in public cultural services. Future research should focus on in-depth case studies and empirical analyses to understand the practical implications of blockchain in this sector.Practical implicationsPublic sector organizations offering cultural services may use these insights to guide blockchain adoption and implementation decisions.Social implicationsBlockchain adoption in public cultural services has the potential to democratize access, enhance transparency and foster community engagement, contributing to a more inclusive and participatory cultural ecosystem.Originality/valueThis paper contributes to the emerging discourse on blockchain in the public sector, focusing on the often-overlooked cultural services. It highlights the benefits and challenges of blockchain adoption in this sector, providing insights for future research and policy decisions.
Journal Article
A use case driven approach to game modeling
With the increase in market needs, game development teams are facing a high demand of creating new games every year. Although several methodologies and tools were introduced to support the game development life cycle, there is still a lack of evidence that these techniques improve game requirements understandability among development teams. The use of models in requirements engineering is considered a promising approach to support requirements elicitation, negotiation, validation, and management. In the context of game development, game designers argue that models are hard to learn and would restrict their creativity. In this paper, we introduce a novel use case-based game modeling approach that extends the standard UML use case diagram. The proposed technique allows for better representation of game-related requirements and promotes a common understanding of game requirements among game development teams. Our approach is implemented in a tool, called game use case modeling, and its applicability is demonstrated using four well-known games, Super Mario Bros, Tetris, Just Dance, and The Walking Dead. Moreover, in order to assess the perceived understandability, learnability, and usefulness of the proposed approach, we have conducted a survey involving 29 participants from the game development community. Results indicate a very satisfactory agreement regarding the added value of the proposed approach and a willingness of adoption by the game development community.
Journal Article
Use Case Based Blended Teaching of IIoT Cybersecurity in the Industry 4.0 Era
Industry 4.0 and Industrial Internet of Things (IIoT) are paradigms that are driving current industrial revolution by connecting to the Internet industrial machinery, management tools or products so as to control and gather data about them. The problem is that many IIoT/Industry 4.0 devices have been connected to the Internet without considering the implementation of proper security measures, thus existing many examples of misconfigured or weakly protected devices. Securing such systems requires very specific skills, which, unfortunately, are not taught extensively in engineering schools. This article details how Industry 4.0 and IIoT cybersecurity can be learned through practical use cases, making use of a methodology that allows for carrying out audits to students that have no previous experience in IIoT or industrial cybersecurity. The described teaching approach is blended and has been imparted at the University of A Coruña (Spain) during the last years, even during the first semester of 2020, when the university was closed due to the COVID-19 pandemic lockdown. Such an approach is supported by online tools like Shodan, which ease the detection of vulnerable IIoT devices. The feedback results provided by the students show that they consider useful the proposed methodology, which allowed them to find that 13% of the IIoT/Industry 4.0 systems they analyzed could be accessed really easily. In addition, the obtained teaching results indicate that the established course learning outcomes are accomplished. Therefore, this article provides useful guidelines for teaching industrial cybersecurity and thus train the next generation of security researchers and developers.
Journal Article
From Use Case to Use Case Slices: An Automated Approach
A use case has been widely adopted for requirements specification, which can be created on a high abstraction level or a very detailed level. A use case with a very detailed level can be a lot more useful for requirements elicitation, but such a model may become too complex and difficult to understand the whole context. A use case slice is introduced in order to simplify the requirements analysis and ensure the correctness of software incremental development process (e.g., the agile development process). However, a use case is usually divided into multiple use case slices in a manual way. Some errors may occur during this manual process. In this article, the authors present an automated approach for dividing a use case into use case slices. The approach first decomposes a use case into multiple use case stories, and then these stories can be composed into different use case slices according to different requirements. These use case slices cover all the functionality of the original use case. The authors give a decomposition theory and propose the corresponding algorithm. A case study demonstrates these results.
Journal Article
The suburban land question : a global survey
As part of the urbanization process, suburban development involves the conversion of rural land to urban use. When discussing the suburbs, most writers focus on particular countries in the northern hemisphere, implying that patterns and processes elsewhere are fundamentally different. The purpose of The Suburban Land Question is to identify the common elements of suburban development, focusing on issues associated with the scale and pace of rapid urbanization around the world.
Editors Richard Harris and Ute Lehrer and a diverse group of contributors draw on a variety of sources, including official data, planning documents, newspapers, interviews, photographs, and field observations to explore the pattern, process, and planning of suburban land development. Featuring case studies from major world regions, including China, India, Latin America, South Africa, as well as France, Austria, the Netherlands, the United States, and Canada, the volume identifies and discusses the peculiarly transitional character of suburban land. In addition to place and time, The Suburban Land Question addresses the many elements that distinguish land development in urban fringe areas, including economy, social infrastructure, and legality.
eBook
Optimization of use case point through the use of metaheuristic algorithm in estimating software effort
Use Case Points estimation framework relies on the complexity weight parameters to estimate software development projects. However, due to the discontinue parameters, it lead to abrupt weight classification and results in inaccurate estimation. Several research studies have addressed these weaknesses by employing various approaches, including fuzzy logic, regression analysis, and optimization techniques. Nevertheless, the utilization of optimization techniques to determine use case weight parameter values has yet to be extensively explored, with the potential to enhance accuracy further. Motivated by this, the current research delves into various metaheuristic search-based algorithms, such as genetic algorithms, Firefly algorithms, Reptile search algorithms, Particle swarm optimization, and Grey Wolf optimizers. The experimental investigation was carried out using a Silhavy UCP estimation dataset, which contains 71 project data from three software houses and is publicly available. Furthermore, we compared the performance between models based on metaheuristic algorithms. The findings indicate that the performance of the Firefly algorithm outperforms the others based on five accuracy metrics: mean absolute error, mean balance relative error, mean inverted relative error, standardized accuracy, and effect size.
Journal Article