Hasil untuk "River, lake, and water-supply engineering (General)"

Lili Chen, Winn Wing-Yiu Chow, Stella Peng et al.

PURPOSE OR GOAL: This study investigates how GenAI can be integrated with a criterion-referenced grading framework to improve the efficiency and quality of grading for mathematical assessments in engineering. It specifically explores the challenges demonstrators face with manual, model solution-based grading and how a GenAI-supported system can be designed to reliably identify student errors, provide high-quality feedback, and support human graders. The research also examines human graders' perceptions of the effectiveness of this GenAI-assisted approach. ACTUAL OR ANTICIPATED OUTCOMES: The study found that GenAI achieved an overall grading accuracy of 92.5%, comparable to two experienced human graders. The two researchers, who also served as subject demonstrators, perceived the GenAI as a helpful second reviewer that improved accuracy by catching small errors and provided more complete feedback than they could manually. A central outcome was the significant enhancement of formative feedback. However, they noted the GenAI tool is not yet reliable enough for autonomous use, especially with unconventional solutions. CONCLUSIONS/RECOMMENDATIONS/SUMMARY: This study demonstrates that GenAI, when paired with a structured, criterion-referenced framework using binary questions, can grade engineering mathematical assessments with an accuracy comparable to human experts. Its primary contribution is a novel methodological approach that embeds the generation of high-quality, scalable formative feedback directly into the assessment workflow. Future work should investigate student perceptions of GenAI grading and feedback.

付瑶瑶

为实现QE300 桥机（额定起重量300 t）安装100%验收合格率，解决大型桥机安装工序复杂、精度要求高及管控漏洞等问题，构建全周期质量管控体系。先明确螺栓扭矩、轨距误差等核心验收标准，组建专业团队并建立质量追溯与责任追究制度；安装前完成设备材料超声波探伤检测、现场地基静载试验及人员专项培训；安装中严控基础标高偏差、主梁水平度偏差及电气接地电阻；安装后实施三级验收，并开展空载、负载及125%超载调试。该管控模式成功达成100%验收合格率，有效规避隐患，保障桥机安全稳定运行。

Roberto Verdecchia, Justus Bogner

From its first adoption in the late 80s, qualitative research has slowly but steadily made a name for itself in what was, and perhaps still is, the predominantly quantitative software engineering (SE) research landscape. As part of our regular column on empirical software engineering (ACM SIGSOFT SEN-ESE), we reflect on the state of qualitative SE research with a focus group of experts. Among other things, we discuss why qualitative SE research is important, how it evolved over time, common impediments faced while practicing it today, and what the future of qualitative SE research might look like. Joining the conversation are Rashina Hoda (Monash University, Australia), Carolyn Seaman (University of Maryland, United States), and Klaas Stol (University College Cork, Ireland). The content of this paper is a faithful account of our conversation from October 25, 2025, which we moderated and edited for our column.

Dipin Khati, Yijin Liu, David N. Palacio et al.

Applications of Large Language Models (LLMs) are rapidly growing in industry and academia for various software engineering (SE) tasks. As these models become more integral to critical processes, ensuring their reliability and trustworthiness becomes essential. Consequently, the concept of trust in these systems is becoming increasingly critical. Well-calibrated trust is important, as excessive trust can lead to security vulnerabilities, and risks, while insufficient trust can hinder innovation. However, the landscape of trust-related concepts in LLMs in SE is relatively unclear, with concepts such as trust, distrust, and trustworthiness lacking clear conceptualizations in the SE community. To bring clarity to the current research status and identify opportunities for future work, we conducted a comprehensive review of $88$ papers: a systematic literature review of $18$ papers focused on LLMs in SE, complemented by an analysis of 70 papers from broader trust literature. Additionally, we conducted a survey study with 25 domain experts to gain insights into practitioners' understanding of trust and identify gaps between existing literature and developers' perceptions. The result of our analysis serves as a roadmap that covers trust-related concepts in LLMs in SE and highlights areas for future exploration.

Zhimin Zhao

Foundation models (FMs), particularly large language models (LLMs), have shown significant promise in various software engineering (SE) tasks, including code generation, debugging, and requirement refinement. Despite these advances, existing evaluation frameworks are insufficient for assessing model performance in iterative, context-rich workflows characteristic of SE activities. To address this limitation, we introduce \emph{SWE-Arena}, an interactive platform designed to evaluate FMs in SE tasks. SWE-Arena provides a transparent, open-source leaderboard, supports multi-round conversational workflows, and enables end-to-end model comparisons. The platform introduces novel metrics, including \emph{model consistency score} that measures the consistency of model outputs through self-play matches, and \emph{conversation efficiency index} that evaluates model performance while accounting for the number of interaction rounds required to reach conclusions. Moreover, SWE-Arena incorporates a new feature called \emph{RepoChat}, which automatically injects repository-related context (e.g., issues, commits, pull requests) into the conversation, further aligning evaluations with real-world development processes. This paper outlines the design and capabilities of SWE-Arena, emphasizing its potential to advance the evaluation and practical application of FMs in software engineering.

Anatolie Povestca

This article presents the results of research on unpublished archival documents and those housed in the National Museum of History of Moldova, introduced for the first time into the scientific circuit or addressed by our predecessors in a different context, referencing the life and work of our esteemed compatriot: metric certificates, personal files, correspondence regarding the construction of the engineering system, topographic sketches, photographs, and other important materials. Pavel Shchusev was a renowned bridge construction engineer and a well-known professor at higher education institutions in Moscow. His scientific work, engineering endeavors, and private life are less recognized today. Throughout his lengthy professional career spanning over 50 years, he participated as an engineer in the design, construction, and expert evaluation of over 100 infrastructure projects within the geographical area of the USSR, edited more than 80 studies and specialized articles, and published his monumental work dedicated to bridge construction. He wrote memoirs dedicated to Alexei Shchusev and was an associated member of the Academy of Architecture of the USSR. Pavel Shchusev contributed to the development of the Plan for the Organization and Reconstruction of the city of Chișinău and served as a consultant in the field of engineering for the water supply of the capital from the Dniester River through the dams at Dubăsari and Ghidighici, as well as the accumulation lake in Valea Morilor. He is the author of the unrealized project of the central bridge over the Bîc River.

Diana Robinson, Christian Cabrera, Andrew D. Gordon et al.

What if end users could own the software development lifecycle from conception to deployment using only requirements expressed in language, images, video or audio? We explore this idea, building on the capabilities that generative Artificial Intelligence brings to software generation and maintenance techniques. How could designing software in this way better serve end users? What are the implications of this process for the future of end-user software engineering and the software development lifecycle? We discuss the research needed to bridge the gap between where we are today and these imagined systems of the future.

Ya Peng, Dhritiraj Sengupta, Yuanqiang Duan et al.

Aquaculture plays a crucial role in the global food security and nutrition supply, where China accounts for the largest market share. Although there are some studies that focus on large-scale extraction of coastal aquaculture ponds from satellite images, they have often variable accuracies and encounter misclassification due to the similar geometric characteristics of various vivid water bodies. This paper proposes an efficient and novel method that integrates the spatial characteristics and three biophysical parameters (Chlorophyll-a, Trophic State Index, and Floating Algae Index) to map coastal aquaculture ponds at a national scale. These parameters are derived from bio-optical models based on the Google Earth Engine (GEE) cloud computing platform and time series of high-resolution Sentinel-2 images. Our proposed method effectively addresses the misclassification issue between the aquaculture ponds and rivers, lakes, reservoirs, and salt pans and achieves an overall accuracy of 91 % and a Kappa coefficient of 0.83 in the Chinese coastal zone. Our results indicate that the total area of Chinese coastal aquaculture ponds was 1,039,214 ha in 2019, mainly distributed in the Shandong and Guangdong provinces. The highest aquaculture intensity occurs within the 1 km coastal buffer zone, accounting for 22.4 % of the total area. Furthermore, more than half of the Chinese coastal aquaculture ponds are concentrated in the 0-5 km buffer zone. Our method is of general applicability and thus is suitable for large-scale aquaculture ponds mapping projects. Moreover, the biophysical parameters we employ can be considered as new indicators for the classification of various water bodies even with different aquaculture species.

David Lloyd Owen

Abstract Smart water enables utilities, regulators, and customers to make more timely and informed decisions about how they use and regard their water resources. It has been developed to assist demand management by influencing customer behavior and reducing network leakage, lowering energy consumption, and avoiding deploying assets that are not actually needed. Smart water has seen an evolution toward monitoring wastewater applications. Challenges include the need for common operating standards and more cohesive national policy frameworks. As a result, smart water adoption occurs on a utility‐by‐utility basis.

Elizabeth Bjarnason, Mirko Morandini, Markus Borg et al.

The RET (Requirements Engineering and Testing) workshop series provides a meeting point for researchers and practitioners from the two separate fields of Requirements Engineering (RE) and Testing. The goal is to improve the connection and alignment of these two areas through an exchange of ideas, challenges, practices, experiences and results. The long term aim is to build a community and a body of knowledge within the intersection of RE and Testing, i.e. RET. The 2nd workshop was held in co-location with ICSE 2015 in Florence, Italy. The workshop continued in the same interactive vein as the 1st one and included a keynote, paper presentations with ample time for discussions, and a group exercise. For true impact and relevance this cross-cutting area requires contribution from both RE and Testing, and from both researchers and practitioners. A range of papers were presented from short experience papers to full research papers that cover connections between the two fields. One of the main outputs of the 2nd workshop was a categorization of the presented workshop papers according to an initial definition of the area of RET which identifies the aspects RE, Testing and coordination effect.

Nour Alhammad, Alex Bogatu, Norman W Paton

A data lake is a repository of data with potential for future analysis. However, both discovering what data is in a data lake and exploring related data sets can take significant effort, as a data lake can contain an intimidating amount of heterogeneous data. In this paper, we propose the use of schema inference to support the interpretation of the data in the data lake. If a data lake is to support a schema-on-read paradigm, understanding the existing schema of relevant portions of the data lake seems like a prerequisite. In this paper, we make use of approximate indexes that can be used for data discovery to inform the inference of a schema for a data lake, consisting of entity types and the relationships between them. The specific approach identifies candidate entity types by clustering similar data sets from the data lake, and then relationships between data sets in different clusters are used to inform the identification of relationships between the entity types. The approach is evaluated using real-world data repositories, to identify where the proposal is effective, and to inform the identification of areas for further work.

Sarah Spiekermann, Till Winkler

Digital ethics is being discussed worldwide as a necessity to create more reliable IT systems. This discussion, fueled by the fear of uncontrollable artificial intelligence (AI) has moved many institutions and scientists to demand a value-based system engineering. This article presents how organizations can build responsible and ethically founded systems with the 'Value-based Engineering' (VBE) approach that was standardized in the IEEE 7000TM standard. VBE is a transparent, clearly-structured, step-by-step methodology combining innovation management, risk management, system and software engineering in one process framework. It embeds a robust value ontology and terminology. It has been tested in various case studies. This article introduces readers to the most important steps and contributions of the approach.

Christoph Treude

Recommender systems are a valuable tool for software engineers. For example, they can provide developers with a ranked list of files likely to contain a bug, or multiple auto-complete suggestions for a given method stub. However, the way these recommender systems interact with developers is often rudimentary -- a long list of recommendations only ranked by the model's confidence. In this vision paper, we lay out our research agenda for re-imagining how recommender systems for software engineering communicate their insights to developers. When issuing recommendations, our aim is to recommend diverse rather than redundant solutions and present them in ways that highlight their differences. We also want to allow for seamless and interactive navigation of suggestions while striving for holistic end-to-end evaluations. By doing so, we believe that recommender systems can play an even more important role in helping developers write better software.

Sherlock A. Licorish, Christoph Treude, John Grundy et al.

Six months ago an important call was made for researchers globally to provide insights into the way Software Engineering is done in their region. Heeding this call we hereby outline the position Software Engineering in Australasia (New Zealand and Australia). This article first considers the software development methods practices and tools that are popular in the Australasian software engineering community. We then briefly review the particular strengths of software engineering researchers in Australasia. Finally we make an open call for collaborators by reflecting on our current position and identifying future opportunities

M. Pulido‐Velazquez, A. Tilmant

The management of water resources systems involves influencing and improving the interaction among three subsystems: natural (biophysical), economic, and legal-institutional frameworks. In this sense, hydroeconomic models have the advantage of analyzing water management problems through models that explicitly represent these interactions. The combination of economic, engineering, and environmental aspects of management provides better-informed results for decision making in the complex environment in which water management operates. Hydroeconomic models (HEMs) are spatially distributed management models of a river basin or system in which both water supply and demands are economically and hydrologically characterized. This definition is sometimes relaxed to refer in general to water resources management models that include the economic component. In HEMs, the management and allocation of water is either driven by the economic value of water or economically assessed, which contributes to policy analysis and reveals opportunities for better economic management. The traditional view of water demand as a fixed requirement to be satisfied is modified by a view of demand that adapts to the changes in the scarcity of water. The integration of economics in HEMs allows the identification of the best combination of water supply and demand management options within a consistent framework. As water scarcity increases worldwide, water managers will increasingly turn to tools that reveal solutions to increase efficiency in water use, fostering improved economic development through better-informed policy choices.

Kabir Ibrahim, Salman Tariq, Beenish Bakhtawar et al.

This study reviews the state-of-the-art application of fiber optics in water distribution networks for leak detection and localization. The use of fiber optics in the oil and gas sector has been well established; however, its potential in water pipelines is not evident owing to limited research. This study, therefore, presents the research developments of fiber optics in water leak detection and localization using the mixed methodology approach by integrating bibliometric and systematic analyses. A scientometric analysis is carried out to analyze the science maps of (1) journal sources, (2) contributing countries, and (3) co-occurrence of influential keywords. The systematic analysis evaluates the use of eight types of fiber optics, such as accelerometer-based fiber optics and hydrophone-based fiber optics, in water leak detection and localization. The review reveals five important directions for future research such as real network-based studies and the development of hybrid techniques. HIGHLIGHTS The study presents the state-of-the-art review of fiber optics application in water leak detection and localization.; Contributing sources, influential countries, and links between keywords in this domain are discussed using scientometric analysis.; Implementation of major fiber-optic classes including fiber Bragg grating and Raman distributed sensors are discussed.; Limitations and future research directions are given.;

Asril Zevri

This study aims to analyze the requirement for the storage capacity of Danau Asam Reservoir as one of the solutions in increasing the availability of water to meet the needs of raw water due to population growth and climate change which is quite extreme. The study was conducted in the Danau Asam Reservoir with source of water from two watersheds that flow into the reservoir, namely the Lopo River Basin with a catchment area of 11.81 Km2 and Kamat Bay with a catchment area of 12.42 Km2 in Kotawaringin Lama District in the West Kotawaringin Regency. The method used is a quantitative approach based on a simulation of the water balance between the inflow and outflow. The inflow parameter is calculated based on 90% probability reliable discharge using the FJ Mock method in two watersheds and the outflow parameter is based on the raw water demand discharge which is calculated based on the population growth rate. The result of the research indicate that the capacity of the Danau Asam Reservoir is 391,842.72 m3 to meet the raw water needs in Kotawaringin Lama District with a population of 35397 people.

Danyllo Valente da Silva, Bruno Pedraça de Souza, Taisa Guidini Gonçalves et al.

Contemporary software systems (CSS), such as the internet of things (IoT) based software systems, incorporate new concerns and characteristics inherent to the network, software, hardware, context awareness, interoperability, and others, compared to conventional software systems. In this sense, requirements engineering (RE) plays a fundamental role in ensuring these software systems' correct development looking for the business and end-user needs. Several software technologies supporting RE are available in the literature, but many do not cover all CSS specificities, notably those based on IoT. This research article presents RETIoT (Requirements Engineering Technology for the Internet of Things based software systems), aiming to provide methodological, technical, and tooling support to produce IoT software system requirements document. It is composed of an IoT scenario description technique, a checklist to verify IoT scenarios, construction processes, and templates for IoT software systems. A feasibility study was carried out in IoT system projects to observe its templates and identify improvement opportunities. The results indicate the feasibility of RETIoT templates' when used to capture IoT characteristics. However, further experimental studies represent research opportunities, strengthen confidence in its elements (construction process, techniques, and templates), and capture end-user perception.

David Bermbach, Abhishek Chandra, Chandra Krintz et al.

Ever since the commercial offerings of the Cloud started appearing in 2006, the landscape of cloud computing has been undergoing remarkable changes with the emergence of many different types of service offerings, developer productivity enhancement tools, and new application classes as well as the manifestation of cloud functionality closer to the user at the edge. The notion of utility computing, however, has remained constant throughout its evolution, which means that cloud users always seek to save costs of leasing cloud resources while maximizing their use. On the other hand, cloud providers try to maximize their profits while assuring service-level objectives of the cloud-hosted applications and keeping operational costs low. All these outcomes require systematic and sound cloud engineering principles. The aim of this paper is to highlight the importance of cloud engineering, survey the landscape of best practices in cloud engineering and its evolution, discuss many of the existing cloud engineering advances, and identify both the inherent technical challenges and research opportunities for the future of cloud computing in general and cloud engineering in particular.

Ramses Sala

Research and development in computer technology and computational methods have resulted in a wide variety of valuable tools for Computer-Aided Engineering (CAE) and Industrial Engineering. However, despite the exponential increase in computational capabilities and Artificial Intelligence (AI) methods, many of the visionary perspectives on cybernetic automation of design, engineering, and development have not been successfully pursued or realized yet. While contemporary research trends and movements such as Industry 4.0 primarily target progress by connected automation in manufacturing and production, the objective of this paper is to survey progress and formulate perspectives targeted on the automation and autonomization of engineering development processes. Based on an interdisciplinary mini-review, this work identifies open challenges, synergies, and research opportunities towards the realization of resource-efficient cooperative engineering and development systems. In order to go beyond conventional human-centered, tool-based CAE approaches and realize Computational Intelligence Driven Development processes, it is suggested to extend the framework of Computational Rationality to challenges in design, engineering and development.