Hasil untuk "Harbors and coast protective works. Coastal engineering. Lighthouses"

Eduard Enoiu, Jean Malm, Gregory Gay

We explore the concept of folklore within software engineering, drawing from folklore studies to define and characterize narratives, myths, rituals, humor, and informal knowledge that circulate within software development communities. Using a literature review and thematic analysis, we curated exemplar folklore items (e.g., beliefs about where defects occur, the 10x developer legend, and technical debt). We analyzed their narrative form, symbolic meaning, occupational relevance, and links to knowledge areas in software engineering. To ground these concepts in practice, we conducted semi-structured interviews with 12 industrial practitioners in Sweden to explore how such narratives are recognized or transmitted within their daily work and how they affect it. Synthesizing these results, we propose a working definition of software engineering folklore as informally transmitted, traditional, and emergent narratives and heuristics enacted within occupational folk groups that shape identity, values, and collective knowledge. We argue that making the concept of software engineering folklore explicit provides a foundation for subsequent ethnography and folklore studies and for reflective practice that can preserve context-effective heuristics while challenging unhelpful folklore.

Ya Zhou, Lei Huang, Liangwen Huang et al.

Global-scale changes in precipitation and temperature lead to regional variations in the hydrologic cycle. Understanding the impacts of climate change on discharge and sediment processes is crucial for effective watershed management, especially in alpine regions. A hydrologic modeling framework was established for the Yarlung Tsangpo River (YTR) watershed, the largest and longest river system on the Tibetan Plateau, which integrates the Soil and Water Assessment Tool (SWAT) with global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The results highlight the importance of temperature in influencing hydrological elements during snowmelt periods in the northeastern and western parts of the YTR basin and precipitation across the entire basin during rainy periods. Compared with discharge, sediment flux has been more sensitive to climate change over the past four decades. The annual mean discharge at the downstream station is projected to decrease by −3.60% ± 2.68% in the near-term period (2025–2035) but increases by 4.18% ± 3.30% in the mid-term period (2040–2050) relative to the baseline value of 2000–2014. Moreover, the annual mean sediment flux is expected to change by −1.06% ± 2.98% in the near-term period and by 8.30% ± 3.65% in the mid-term period. These results will enhance adaptive management and policy-making for alpine regions.

Yuan He, Zihao Fan, Wei Zhao et al.

Vegetation litter is effective in mitigating surface soil erosion caused by rainfall and runoff. Studying the runoff, sediment yield, and hydrodynamic characteristics of the soil covered by vegetation litter cover is crucial to understanding how vegetation litter cover affects soil erosion. To assess the impacts of different types of vegetation litter on soil erosion in the Taiyi Mountain area of northern China, Quercus acutissima Carruth. (QAC), Pinus densiflora Siebold & Zucc. (PDS), Vitex negundo var. heterophylla Rehd. (VNH), and Themeda japonica Willd. (TJW) litter covered soil were the research subjects, and no-litter covered soil was used as a control check (CK). The process of erosion of soil covered by different vegetation litter under different rainfall intensities (50, 75, and 100 mm/h) with 60 min of rainfall was studied. It was found that compared with CK, the runoff and sediment yield rates of litter-covered soil decreased by 18.95%–44.15% and 21.42%–60.16%, respectively. In terms of the effect on reducing the runoff and sediment yield rate, the performance is QAC > PDS > VNH > TJW. Under varying rainfall intensities, the patterns of runoff and sediment yield fluctuate as rainfall duration increases. Likewise, with the increase in rainfall intensity, the runoff yield rate and sediment yield rate also show an increasing trend. The runoff yield rate was increased by 3.21 and 1.49 times under 100 mm/h compared with 50 and 75 mm/h, respectively. Additionally, there were 16.56 and 1.44 times, respectively, and increases in the sediment yield rate. Hydrodynamically, litter cover increases the Darcy-Weisbach friction coefficient by 1.49–11.15 times, increases the shear stress threshold for initiating soil erosion by about 6.67%–38.01%. This further led to a reduction in the runoff flow velocity and stream power, by approximately 14.87%–67.26% and 7.38%–61.54%, respectively, thereby reducing the degree of soil erosion. The current research demonstrates that the characteristics of soil erosion and sediment yield under vegetation litter cover can be more accurately described by the stream power among the hydrodynamic parameters.

Eranga K. Galappaththi, Brandy Ayesu-Danso, Sithuni M. Jayasekara et al.

Despite coastal regions’ importance and vulnerability to climate change, Ghana’s coasts remain underexplored through social-ecological systems (SES) approaches, with limited attention to Indigenous and local communities’ adaptive responses to contemporary challenges. We conducted a study with the aims of (1) identifying the changes in coastal SES as perceived by the Akplabanya community and (2) examining the Akplabanya community’s human adaptation responses to those changes. During two months of fieldwork in Akplabanya, we used four data collection methods: participant observation, semi-structured interviews, key informant interviews, and focus group discussions. We found social-ecological changes related to five themes: (i) coastal climate change (sea-level rise), (ii) resource change (changes in land use), (iii) agrobiodiversity loss (changes in livestock), (iv) pollution (unsustainable practices) and (v) population change (increasing population). As adaptation responses to these changes, the community adaptive responses we found were (a) place (sense of place), (b) agency (emergence of food markets), (c) Indigenous and local knowledge (weakening of Indigenous knowledge), (d) collective action (collective solutions), (e) institutions (partnerships) and (f) learning (awareness). Our study highlights the urgent need for targeted research in regions like Ghana to guide and improve adaptation policy interventions for scientists, policymakers and researchers.

Tim Aebersold, Soheyl Massoudi, Mark D. Fuge

Engineering complex systems (aircraft, buildings, vehicles) requires accounting for geometric and performance couplings across subsystems. As generative models proliferate for specialized domains (wings, structures, engines), a key research gap is how to coordinate frozen, pre-trained submodels to generate full-system designs that are feasible, diverse, and high-performing. We introduce Generative Latent Unification of Expertise-Informed Engineering Models (GLUE), which orchestrates pre-trained, frozen subsystem generators while enforcing system-level feasibility, optimality, and diversity. We propose and benchmark (i) data-driven GLUE models trained on pre-generated system-level designs and (ii) a data-free GLUE model trained online on a differentiable geometry layer. On a UAV design problem with five coupling constraints, we find that data-driven approaches yield diverse, high-performing designs but require large datasets to satisfy constraints reliably. The data-free approach is competitive with Bayesian optimization and gradient-based optimization in performance and feasibility while training a full generative model in only 10 min on a RTX 4090 GPU, requiring more than two orders of magnitude fewer geometry evaluations and FLOPs than the data-driven method. Ablations focused on data-free training show that subsystem output continuity affects coordination, and equality constraints can trigger mode collapse unless mitigated. By integrating unmodified, domain-informed submodels into a modular generative workflow, this work provides a viable path for scaling generative design to complex, real-world engineering systems.

Paris Avgeriou, Nauman bin Ali, Marcos Kalinowski et al.

Increasingly, courses on Empirical Software Engineering research methods are being offered in higher education institutes across the world, mostly at the M.Sc. and Ph.D. levels. While the need for such courses is evident and in line with modern software engineering curricula, educators designing and implementing such courses have so far been reinventing the wheel; every course is designed from scratch with little to no reuse of ideas or content across the community. Due to the nature of the topic, it is rather difficult to get it right the first time when defining the learning objectives, selecting the material, compiling a reader, and, more importantly, designing relevant and appropriate practical work. This leads to substantial effort (through numerous iterations) and poses risks to the course quality. This chapter attempts to support educators in the first and most crucial step in their course design: creating the syllabus. It does so by consolidating the collective experience of the authors as well as of members of the Empirical Software Engineering community; the latter was mined through two working sessions and an online survey. Specifically, it offers a list of the fundamental building blocks for a syllabus, namely course aims, course topics, and practical assignments. The course topics are also linked to the subsequent chapters of this book, so that readers can dig deeper into those chapters and get support on teaching specific research methods or cross-cutting topics. Finally, we guide educators on how to take these building blocks as a starting point and consider a number of relevant aspects to design a syllabus to meet the needs of their own program, students, and curriculum.

Martin Obaidi, Marc Herrmann, Elisa Schmid et al.

Sentiment analysis is an essential technique for investigating the emotional climate within developer teams, contributing to both team productivity and project success. Existing sentiment analysis tools in software engineering primarily rely on English or non-German gold-standard datasets. To address this gap, our work introduces a German dataset of 5,949 unique developer statements, extracted from the German developer forum Android-Hilfe.de. Each statement was annotated with one of six basic emotions, based on the emotion model by Shaver et al., by four German-speaking computer science students. Evaluation of the annotation process showed high interrater agreement and reliability. These results indicate that the dataset is sufficiently valid and robust to support sentiment analysis in the German-speaking software engineering community. Evaluation with existing German sentiment analysis tools confirms the lack of domain-specific solutions for software engineering. We also discuss approaches to optimize annotation and present further use cases for the dataset.

Timo Kehrer, Robert Haines, Guido Juckeland et al.

Anecdotal evidence suggests that Research Software Engineers (RSEs) and Software Engineering Researchers (SERs) often use different terminologies for similar concepts, creating communication challenges. To better understand these divergences, we have started investigating how SE fundamentals from the SER community are interpreted within the RSE community, identifying aligned concepts, knowledge gaps, and areas for potential adaptation. Our preliminary findings reveal opportunities for mutual learning and collaboration, and our systematic methodology for terminology mapping provides a foundation for a crowd-sourced extension and validation in the future.

Filipe R. Cogo, Gustavo A. Oliva, Ahmed E. Hassan

The rapid advancement of AI-assisted software engineering has brought transformative potential to the field of software engineering, but existing tools and paradigms remain limited by cognitive overload, inefficient tool integration, and the narrow capabilities of AI copilots. In response, we propose Compiler.next, a novel search-based compiler designed to enable the seamless evolution of AI-native software systems as part of the emerging Software Engineering 3.0 era. Unlike traditional static compilers, Compiler.next takes human-written intents and automatically generates working software by searching for an optimal solution. This process involves dynamic optimization of cognitive architectures and their constituents (e.g., prompts, foundation model configurations, and system parameters) while finding the optimal trade-off between several objectives, such as accuracy, cost, and latency. This paper outlines the architecture of Compiler.next and positions it as a cornerstone in democratizing software development by lowering the technical barrier for non-experts, enabling scalable, adaptable, and reliable AI-powered software. We present a roadmap to address the core challenges in intent compilation, including developing quality programming constructs, effective search heuristics, reproducibility, and interoperability between compilers. Our vision lays the groundwork for fully automated, search-driven software development, fostering faster innovation and more efficient AI-driven systems.

Roberto Verdecchia, Justus Bogner

While mastered by some, good scientific writing practices within Empirical Software Engineering (ESE) research appear to be seldom discussed and documented. Despite this, these practices are implicit or even explicit evaluation criteria of typical software engineering conferences and journals. In this pragmatic, educational-first document, we want to provide guidance to those who may feel overwhelmed or confused by writing ESE papers, but also those more experienced who still might find an opinionated collection of writing advice useful. The primary audience we had in mind for this paper were our own BSc, MSc, and PhD students, but also students of others. Our documented advice therefore reflects a subjective and personal vision of writing ESE papers. By no means do we claim to be fully objective, generalizable, or representative of the whole discipline. With that being said, writing papers in this way has worked pretty well for us so far. We hope that this guide can at least partially do the same for others.

Polina Lemenkova

Mapping coastal regions is important for environmental assessment and for monitoring spatio-temporal changes. Although traditional cartographic methods using a geographic information system (GIS) are applicable in image classification, machine learning (ML) methods present more advantageous solutions for pattern-finding tasks such as the automated detection of landscape patches in heterogeneous landscapes. This study aimed to discriminate landscape patterns along the eastern coasts of Mozambique using the ML modules of a Geographic Resources Analysis Support System (GRASS) GIS. The random forest (RF) algorithm of the module ‘r.learn.train’ was used to map the coastal landscapes of the eastern shoreline of the Bight of Sofala, using remote sensing (RS) data at multiple temporal scales. The dataset included Landsat 8-9 OLI/TIRS imagery collected in the dry period during 2015, 2018, and 2023, which enabled the evaluation of temporal dynamics. The supervised classification of RS rasters was supported by the Scikit-Learn ML package of Python embedded in the GRASS GIS. The Bight of Sofala is characterized by diverse marine ecosystems dominated by swamp wetlands and mangrove forests located in the mixed saline–fresh waters along the eastern coast of Mozambique. This paper demonstrates the advantages of using ML for RS data classification in the environmental monitoring of coastal areas. The integration of Earth Observation data, processed using a decision tree classifier by ML methods and land cover characteristics enabled the detection of recent changes in the coastal ecosystem of Mozambique, East Africa.

Cheikh Ibrahima Youm, Adama Gueye, Elena García-Villalba et al.

Estuary sedimentary sequences have been the focus of several papers in the last decades; however, the majority these papers were centered in mesotidal and macrotidal estuaries of the middle latitudes. This present paper studies, from a sedimentological point of view, the infilling of a microtidal, wave-dominated tropical estuary, where wide tidal flats, mangroves and sabkhas are developed. Somone Lagoon is a Senegalese protected environment, very rich from an ecological point of view and with a definitive touristic vocation. For this work, 14 piston cores were studied. Additionally, the grain size, calcium carbonate and organic matter contents of 61 sediment samples vertically distributed in these cores were analyzed. The distribution of facies and the vertical sequences of sediments show the influence of the tropical seasonal fluctuations of fluvial sediment supply and evaporation processes. A high degree of bioturbation and an elevated organic content can be interpreted as the result of a high capacity of retention of the organic material into the estuary influenced by the weak tidal currents typical of a microtidal regime. These processes, acting since the last Holocene invasion of sea level, caused an advanced state of infilling of this estuarine system where both flood tidal deltas and bay head deltas prograde above the fine facies of the central domain of the estuary.

Randall W. Parkinson

This investigation evaluated two fundamental assumptions of wetland inundation models designed to emulate landscape evolution and resiliency under conditions of sea level rise: that they can (1) migrate landward at the same rate as the transgressing shoreline and (2) immediately replace the plant community into which they are onlapping. Rates of wetland (e.g., marsh, mangrove) migration were culled from 11 study areas located in five regions of focus: Delaware Bay, Chesapeake Bay, Pamlico Sound, South Florida, and Northwest Florida. The average rate of marsh migration (n = 14) was 3.7 m yr⁻¹. The average rate of South Florida mangrove migration (n = 4) was 38.0 m yr⁻¹. The average rate of upland forest retreat (n = 4) was 3.4 m yr⁻¹. Theoretical rates of shoreline transgression were calculated using site-specific landscape slope and scenario-based NOAA sea level rise elevations in 2050. Rates of shoreline transgression over the marsh landscape averaged 94 m yr⁻¹. The average rate of shoreline transgression in the mangrove-dominated areas of South Florida was 153.2 m yr⁻¹. The calculated rates of shoreline transgression were much faster than the observed horizontal marsh migration, and by 2050, the offset or gap between them averaged 2700 m and ranged between 292 and 5531 m. In South Florida, the gap average was 3516 m and ranged between 2766 m and 4563 m. At sites where both horizontal marsh migration and forest retreat rates were available, the distance or gap between them in 2050 averaged 47 m. Therefore, the results of this study are inconsistent with the two fundamental assumptions of many wetland inundation models and suggest that they may overestimate their resilience under conditions of 21st century accelerating sea level rise.

Kathleen L. McInnes, Robert J. Nicholls, Roderik van de Wal et al.

We synthesize sea-level science developments, priorities and practitioner needs at the end of the 10-year World Climate Research Program Grand Challenge ’Regional Sea-Level Change and Coastal Impacts’. Sea-level science and associated climate services have progressed but are unevenly distributed. There remains deep uncertainty concerning high-end and long-term sea-level projections due to indeterminate emissions, the ice sheet response and other climate tipping points. These are priorities for sea-level science. At the same time practitioners need climate services that provide localized information including median and curated high-end sea-level projections for long-term planning, together with information to address near-term pressures, including extreme sea level-related hazards and land subsidence, which can greatly exceed current rates of climate-induced sea-level rise in some populous coastal settlements. To maximise the impact of scientific knowledge, ongoing co-production between science and practitioner communities is essential. Here we report on recent progress and ways forward for the next decade.

Johan Cederbladh, Antonio Cicchetti

In this paper we discuss the growing need for system behaviour to be validated and verified (V&V'ed) early in model-based systems engineering. Several aspects push companies towards integration of techniques, methods, and processes that promote specific and general V&V activities earlier to support more effective decision-making. As a result, there are incentives to introduce new technologies to remain competitive with the recently drastic changes in system complexity and heterogeneity. Performing V&V early on in development is a means of reducing risk for later error detection while moving key activities earlier in a process. We present a summary of the literature on early V&V and position existing challenges regarding potential solutions and future investigations. In particular, we reason that the software engineering community can act as a source for inspiration as many emerging technologies in the software domain are showing promise in the wider systems domain, and there already exist well formed methods for early V&V of software behaviour in the software modelling community. We conclude the paper with a road-map for future research and development for both researchers and practitioners to further develop the concepts discussed in the paper.

Oleksandr Kosenkov, Michael Unterkalmsteiner, Jannik Fischbach et al.

Context: Regulatory acts are a challenging source when eliciting, interpreting, and analyzing requirements. Requirements engineers often need to involve legal experts who, however, may often not be available. This raises the need for approaches to regulatory Requirements Engineering (RE) covering and integrating both legal and engineering perspectives. Problem: Regulatory RE approaches need to capture and reflect both the elementary concepts and relationships from a legal perspective and their seamless transition to concepts used to specify software requirements. No existing approach considers explicating and managing legal domain knowledge and engineering-legal coordination. Method: We conducted focus group sessions with legal researchers to identify the core challenges to establishing a regulatory RE approach. Based on our findings, we developed a candidate solution and conducted a first conceptual validation to assess its feasibility. Results: We introduce the first version of our Artifact Model for Regulatory Requirements Engineering (AM4RRE) and its conceptual foundation. It provides a blueprint for applying legal (modelling) concepts and well-established RE concepts. Our initial results suggest that artifact-centric RE can be applied to managing legal domain knowledge and engineering-legal coordination. Conclusions: The focus groups that served as a basis for building our model and the results from the expert validation both strengthen our confidence that we already provide a valuable basis for systematically integrating legal concepts into RE. This overcomes contemporary challenges to regulatory RE and serves as a basis for exposure to critical discussions in the community before continuing with the development of tool-supported extensions and large-scale empirical evaluations in practice.

Michael Kampouridis, Nikolaos Vastardis, George Rayment

Lighthouses play a crucial role in ensuring maritime safety by signaling hazardous areas such as dangerous coastlines, shoals, reefs, and rocks, along with aiding harbor entries and aerial navigation. This is achieved through the use of photoresistor sensors that activate or deactivate based on the time of day. However, a significant issue is the potential malfunction of these sensors, leading to the gradual misalignment of the light's operational timing. This paper introduces an innovative machine learning-based approach for automatically detecting such malfunctions. We evaluate four distinct algorithms: decision trees, random forest, extreme gradient boosting, and multi-layer perceptron. Our findings indicate that the multi-layer perceptron is the most effective, capable of detecting timing discrepancies as small as 10-15 minutes. This accuracy makes it a highly efficient tool for automating the detection of faults in lighthouse light sensors.

Ibrahima Pouye, Dieudonné Pessièzoum Adjoussi, Jacques André Ndione et al.

Among the impacts of climate change in West Africa, coastal erosion is the most threatening disaster apart from floods and the increase in temperatures. The southern coast of the Dakar region, as part of the most threatened coastal zones in West Africa, records the most current coastal damages in Dakar due to its coastline dynamics and low-lying area. This paper investigates the influences of the topography and slope of the beach on shoreline dynamics using remote sensing, cartographic tools and statistical methods such as linear regression. It also states the important role of geomorphologic structures in shoreline dynamics. It was conducted in three littoral cells (Mbao, Bargny and Toubab Dialaw) along the southern coast of Dakar. It helps to understand better the role that topography, slope and geomorphology play in coastal dynamics. The Modified Normalized Difference Water Index (MNDWI) was employed to delineate the coastlines before computing the dynamic rate of the coastline using Digital Shoreline Analysis System (DSAS) software. After that, the topography and slope were determined using a digital elevation model (DEM). Then, the correlation between the coastline dynamic, topography and slope was analyzed using the coefficient of correlation and linear regression model. In the Mbao and Bargny littoral cells where the geomorphology is mostly dominated by soils little or not evolved in situ, there is a significant relationship between the coast line dynamic, topography and slope with a coefficient of correlation of about 0.63 and 0.87, respectively. The relationship is not significant in Toubab Dialaw, where the topography and slope are high, and the geomorphology is mainly characterized by a category of sandstone, with a coefficient of 0.15. We conclude that topography, slope and geomorphology play an important role in the shoreline dynamics in the study area.

Xénia Philippenko, Gonéri Le Cozannet

The latest IPCC report estimates that approximately 1 billion people will be at risk from coastal hazards in the near term due to coastal population increase, sea-level rise and other coastal changes. This will occur in a world that is changing rapidly due to climate change, ecosystem decline, human development and the projected transformations of the economy to meet the objectives of the Paris Agreement. In this context, social sciences provide a pivotal perspective to coastal adaptation, for example, while assessing barriers and opportunities across scales, from local to global. This scoping review explores how social sciences support coastal adaptation. We show that Political Sciences, Economics, Sociology and Geography are already supporting coastal adaptation. Yet, scientific fields such as legal sciences, psychology, history and archaeology as well as anthropology and ethnography are less developed in the context of coastal adaptation to sea-level rise. New research avenues could also integrate education, media and communication research and aim at truly interdisciplinary studies linking different branches of social sciences with coastal science and climate services. This effort could help moving from a coastal adaptation often focused on coastal engineering protection to a broader vision of coastal resilient development, also addressing the challenges of mitigation, sustainable development and coastal ecosystem decline.

Thibault Laigre, Yann Balouin, Deborah Villarroel-Lamb et al.

This study investigates the shoreline dynamics of a Caribbean reef-lined beach by utilizing a long-term satellite dataset spanning 75 years and a short-term, high-frequency dataset captured by a fixed camera over 3 years. An array of statistical methods, including ARIMA models, are employed to examine the impact of storms and potential cyclical influences on the shoreline dynamics. The findings indicate that significant storm events trigger a substantial retreat of the vegetation limit, followed by a slow recovery. Given the current frequency of such major events, complete recovery may take several decades, resulting in a minor influence of cyclones on the long-term erosion trend, which remains moderate. The short-term shoreline evolution is primarily driven by the annual cyclicity of the still water level, which generates an annual oscillation—an insight not previously reported. In the context of climate change, alterations to sea-level rise and cyclone frequency could disrupt the observed dynamic equilibrium at different timescales. Such changes could result in an alteration of existing cyclicities, disturbance of recovery periods, increased long-term shoreline retreat rates, and potentially affect overall coastal resilience over time.