Hasil untuk "Ocean engineering"

J. Yuh

S. Chakrabarti

Krishnan Batri, Lakshmi S, Mahesh T R et al.

Hyperspectral anomaly detection faces fundamental challenges in balancing spatial context, statistical rigor, and interpretability without ground truth supervision. This article presents spatially informed theoretical model (STIM), a novel unsupervised framework that addresses these challenges through a principled two-stage reference computation architecture. STIM systematically aggregates local spectral statistics into globally informed spatial references, enabling the derivation of three complementary features: energy (photometric deviation), entropy (local spectral coherence), and divergence (global statistical rarity). We establish theoretical foundations including noise robustness, Lipschitz continuity, and information-theoretic optimality with convergence guarantees. Comprehensive validation on five Airborne Visible/Infrared Imaging Spectrometer—Next Generation benchmark datasets demonstrates STIM's substantial superiority over traditional statistical and deep learning methods, achieving 14.6× to 585× improvements in mean anomaly scores with a reliability index of 0.933. Feature dynamics analysis confirms multimodal orthogonality and consistent interpretability across diverse hyperspectral environments. STIM enables robust, interpretable, and generalizable anomaly detection for operational hyperspectral imaging without requiring labeled supervision or scene-specific calibration, advancing the state-of-the-art in unsupervised hyperspectral analysis.

Oleksandr Kosenkov, Ehsan Zabardast, Jannik Fischbach et al.

Implementing privacy by design (PbD) according to the General Data Protection Regulation (GDPR) is met with a growing number of requirements engineering (RE) approaches. However, the question of which RE method for PbD fits best the goals of organisations remains a challenge. We report our endeavor to close this gap by synthesizing a goal-centric approach for PbD methods assessment. We used literature review, interviews, and validation with practitioners to achieve the goal of our study. As practitioners do not approach PbD systematically, we suggest that RE methods for PbD should be assessed against organisational goals, rather than process characteristics only. We hope that, when further developed, the goal-centric approach could support the development, selection, and tailoring of RE practices for PbD.

Yang Wang, Shouwei Gao, Wanghuai Xu et al.

Water covers about 70% of the earth's surface and contains tremendous energy that remains untapped. Despite success in harvesting hydrodynamic energy based on heavy‐weight and bulky electromagnetic generators, a great deal of water energies stored in the low‐frequency flow of water such as in the form of raindrops, river/ocean waves, and the tide, remain largely untapped. In spite of diversity in development strategies and working mechanisms, engineering efficient water energy harvesting devices, especially nanogenerators, requires the elegant control of interfacial properties of substrates for rapid liquid mass and momentum transfer and effective electron generation/transfer. In particular, inspired by various special wetting phenomena in nature, the design of superwetting surfaces offers a new dimension to fundamentally mediate the way the liquid, as well as the charge, interact with the substrate. Herein, the latest progress in the development of nanogenerators with three distinctive interface types—solid/liquid, solid/solid, and liquid/liquid interfaces—are summarized and their representative applications, challenges, and future perspectives are highlighted.

Hongda Li, Hongtao Nie, Bin Wang et al.

Intraspecific crossbreeding is one of the effective methods to improve the disease resistance of R. philippinarum, and excellent traits can usually be produced in the hybrid progeny. In this study, we conducted a challenge experiment with V. alginolyticus on the hybrid progeny (D♀ × W♂ (DW) and W♀ × D♂ (WD)) and inbred progeny (D♀ × D♂ (DD) and W♀ × W♂ (WW)) of R. philippinarum Dalian Jinshitan (Liaoning Province) and Weihai moyedao (Shandong Province) populations, and found that the hybrid progeny had heterosis in resistance to V. alginolyticus. To explore the molecular mechanism of this heterosis, we then performed transcriptome sequencing on the hybrid and inbred progeny challenged with V. alginolyticus for 48 h and those that were not stressed. The results showed that 548 and 260 differentially expressed genes were detected in the hybrid progeny DW and WD, respectively, and 399 and 520 differentially expressed genes were detected in the inbred progeny DD and WW, respectively. Among them, the mRNA expression levels of immune genes and inflammatory factors such as Hsp70, TNFSF13, TRAF6, IFI44, IL17 in hybrid progeny were higher than those in inbred progeny, which may be one of the reasons for heterosis. Heterosis-related module (darkturquoise) was identified and the genes of this module were significantly enriched in the phagosome pathway. These results may provide a molecular basis for the superior ability of intraspecific hybrid progeny of R. philippinarum to survive attack by V. alginolyticus than their parents, thereby deepening our understanding of heterosis in R. philippinarum.

Sen Zhao, Ning Li, Fei‐Fei Jin et al.

Abstract The El Niño‐Southern Oscillation (ENSO) influences ocean wave activity across the Pacific, but its effects on island shores are modulated by local weather and selective sheltering of multi‐modal seas. Utilizing 41 years of high‐resolution wave hindcasts, we decipher the season‐ and locality‐dependent connections between ENSO and wave patterns around the Hawaiian Islands. The north and west‐facing shores, exposed to energetic northwest swells during boreal winters, experience the most pronounced ENSO‐related variability, with increased high‐surf activity during El Niño years. While the year‐round trade wind waves exhibit moderate correlation with ENSO, the basin‐wide climate influence is masked by locally accelerated trade winds in channels and around large headlands. The remarkable global‐to‐local pathway through the high‐resolution hindcast enables development of an ENSO‐based semi‐empirical wave model to statistically describe and predict severe wave conditions on vulnerable shores with potential application in coastal risk management and hazard mitigation for Pacific Islands and beyond.

Ya-Sin Yang, Hsin-Fu Yeh, Chia-Chi Huang et al.

Abstract Given the pressures on water resources caused by global climate change and human activities, the assessment and management of groundwater resources in mountainous region have become increasingly important. The central mountainous region of Taiwan, as one of the significant sources of groundwater recharge, plays a critical role in overall water resource management due to its groundwater storage capacity and recharge capability. Addressing the challenges of limited survey and observational data in mountainous groundwater assessments, this study uses the lumped parameter groundwater model AquiMod to analyze long-term groundwater level changes at 23 monitoring stations in mountainous areas of central Taiwan. This study is based on long-term groundwater level monitoring data (2010–2021) analyzing the relationship between groundwater levels and precipitation, and performs model calibration and prediction. The results indicate a strong correlation between groundwater levels in mountainous areas and precipitation. While the model predictions were satisfactory for most monitoring stations, obtaining Nash Sutcliffe efficiency scores of between 0.5 and 0.9 at 14 of the 23 monitoring stations. However, poorer performance at several stations reflects limitations arising from data gaps, complex local geology, and the inability of the lumped model to represent lateral recharge or anthropogenic influences. Model sensitivity analysis further highlights the critical role of unsaturated zone parameters, such as rooting depth, soil storage and upper-layer saturated hydraulic conductivity, in shaping groundwater responses. In summary, the lumped parameter groundwater model has proven practical for evaluating groundwater in Taiwan’s mountainous regions and can serve as a reference for the sustainable management of future water resources.

Hao Wang, Jinnan Jiang, Muhammad Ali et al.

Plumes and pockmarks are formed when shallow gas breaches the seabed and infiltrates into ocean currents, disrupting the original ecological environment and affecting biological habitats and migration behaviors. An independently developed experimental system was employed in this study to investigate the effects of gas source pressure, burial depth, and number of release orifices on plume morphology and pockmark characteristics, aiming to evaluate their impacts on seabed ecological functions. Experimental results show that the maximum fountain height and plume diameter increase no-linearly with the increase in pressure and orifice number but decrease with increasing burial depth. The plume angle is positively correlated with pressure and negatively correlated with burial depth, showing no correlation with orifice number. Pockmark depth, diameter, and volume exhibit similar variation trends, with pressure being the dominant factor. Analysis of variance reveals that pockmark volume is most sensitive to pressure, while diameter has the least influence. Soil strength measurements after gas release demonstrate distinct patterns: strength increases in the pockmark center and external areas due to compaction, whereas it decreases in the waistline and edge regions due to shear failure. These changes may regulate benthic community distribution by altering sediment stability and pore water chemistry. The findings provide experimental insights into how gas release parameters influence submarine geomorphology and sedimentary environments, contributing to risk assessment of marine ecological disturbances associated with shallow gas activities.

Guo Chen, Hao Wang, Qing-wei Zhang et al.

Study region: The Zhifanggou watershed of the Loess Plateau, China. Study focus: Using rainfall simulation experiments coupled with high-throughput sequencing and fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), we revealed the linkages between DOM molecular characteristics and bacterial/fungal communities in runoff from slopes colonized by three typical biocrusts (cyanobacterial, cyanobacterial-moss, and moss crusts), with bare slope as control. New hydrological insights for the region: Biocrust succession significantly increased DOM molecular diversity by 12–24 % compared to bare slope, while maintaining stable microbial diversity. The bacterial communities in runoff were dominated by Proteobacteria and Actinobacteriota (61–79 %), while Ascomycota (60–94 %) prevailed fungal communities. The DOM molecular composition in runoff was closely associated with bacterial and fungal communities and the biocrusts characteristics within runoff plots. The compositional differences of all compound classes or elemental combinations in runoff generally decreased with biocrust succession. Besides, the positive Spearman correlation between bacteria and DOM in runoff predominantly distributed in higher O/C and lower H/C molecular families, while vice versa for the fungi. Meanwhile, bipartite network analysis further demonstrated that both positive and negative interactions were closely associated to molecular characteristics. When the H/C or O/C ratios of DOM molecules were more similar, their correlations with microbial taxa showed greater similarity. Overall, our findings offer insights into DOM-microbe co-transport mechanisms at soil-aquatic interfaces of semiarid ecosystems.

Georgi Markov, Jon G. Hall, Lucia Rapanotti

Many organisational problems are addressed through systemic change and re-engineering of existing Information Systems rather than radical new design. In the face of widespread IT project failure, devising effective ways to tackle this type of change remains an open challenge. This work discusses the motivation, theoretical foundation, characteristics and evaluation of a novel framework - referred to as POE-$Δ$, which is rooted in design and engineering and is aimed at providing systematic support for representing, structuring and exploring change problems of a socio-technical nature, including implementing their solutions when they exist. We generalise an existing framework of greenfield design as problem solving for application to change problems. From a theoretical perspective,POE-$Δ$ is a strict extension to its parent framework, allowing the seamless integration of greenfield and brownfield design to tackle change problems. A Design Science Research methodology was applied over a decade to define and evaluate POE-$Δ$, with significant case study research conducted to evaluate the framework in its application to real-world change problems of varying criticality and complexity. The results show that POE-$Δ$ exhibits desirable characteristics of a design approach to organisational change and can bring tangible benefits when applied in practice as a holistic and systematic approach to change in socio-technical contexts.

Sebastian Baltes, Florian Angermeir, Chetan Arora et al.

Large Language Models (LLMs) are now ubiquitous in software engineering (SE) research and practice, yet their non-determinism, opaque training data, and rapidly evolving models threaten the reproducibility and replicability of empirical studies. We address this challenge through a collaborative effort of 22 researchers, presenting a taxonomy of seven study types that organizes the landscape of LLM involvement in SE research, together with eight guidelines for designing and reporting such studies. Each guideline distinguishes requirements (must) from recommended practices (should) and is contextualized by the study types it applies to. Our guidelines recommend that researchers: (1) declare LLM usage and role; (2) report model versions, configurations, and customizations; (3) document the tool architecture beyond the model; (4) disclose prompts, their development, and interaction logs; (5) validate LLM outputs with humans; (6) include an open LLM as a baseline; (7) use suitable baselines, benchmarks, and metrics; and (8) articulate limitations and mitigations. We complement the guidelines with an applicability matrix mapping guidelines to study types and a reporting checklist for authors and reviewers. We maintain the study types and guidelines online as a living resource for the community to use and shape (llm-guidelines$.$org).

Allysson Allex Araújo, Marcos Kalinowski, Maria Teresa Baldassarre

In recent years, Software Engineering (SE) scholars and practitioners have emphasized the importance of integrating soft skills into SE education. However, teaching and learning soft skills are complex, as they cannot be acquired passively through raw knowledge acquisition. On the other hand, hackathons have attracted increasing attention due to their experiential, collaborative, and intensive nature, which certain tasks could be similar to real-world software development. This paper aims to discuss the idea of hackathons as an educational strategy for shaping SE students' soft skills in practice. Initially, we overview the existing literature on soft skills and hackathons in SE education. Then, we report preliminary empirical evidence from a seven-day hybrid hackathon involving 40 students. We assess how the hackathon experience promoted innovative and creative thinking, collaboration and teamwork, and knowledge application among participants through a structured questionnaire designed to evaluate students' self-awareness. Lastly, our findings and new directions are analyzed through the lens of Self-Determination Theory, which offers a psychological lens to understand human behavior. This paper contributes to academia by advocating the potential of hackathons in SE education and proposing concrete plans for future research within SDT. For industry, our discussion has implications around developing soft skills in future SE professionals, thereby enhancing their employability and readiness in the software market.

Christoph Treude, Marco A. Gerosa

Artificial intelligence (AI), including large language models and generative AI, is emerging as a significant force in software development, offering developers powerful tools that span the entire development lifecycle. Although software engineering research has extensively studied AI tools in software development, the specific types of interactions between developers and these AI-powered tools have only recently begun to receive attention. Understanding and improving these interactions has the potential to enhance productivity, trust, and efficiency in AI-driven workflows. In this paper, we propose a taxonomy of interaction types between developers and AI tools, identifying eleven distinct interaction types, such as auto-complete code suggestions, command-driven actions, and conversational assistance. Building on this taxonomy, we outline a research agenda focused on optimizing AI interactions, improving developer control, and addressing trust and usability challenges in AI-assisted development. By establishing a structured foundation for studying developer-AI interactions, this paper aims to stimulate research on creating more effective, adaptive AI tools for software development.

Jonathan Ullrich, Matthias Koch, Andreas Vogelsang

With the advent of generative LLMs and their advanced code generation capabilities, some people already envision the end of traditional software engineering, as LLMs may be able to produce high-quality code based solely on the requirements a domain expert feeds into the system. The feasibility of this vision can be assessed by understanding how developers currently incorporate requirements when using LLMs for code generation-a topic that remains largely unexplored. We interviewed 18 practitioners from 14 companies to understand how they (re)use information from requirements and other design artifacts to feed LLMs when generating code. Based on our findings, we propose a theory that explains the processes developers employ and the artifacts they rely on. Our theory suggests that requirements, as typically documented, are too abstract for direct input into LLMs. Instead, they must first be manually decomposed into programming tasks, which are then enriched with design decisions and architectural constraints before being used in prompts. Our study highlights that fundamental RE work is still necessary when LLMs are used to generate code. Our theory is important for contextualizing scientific approaches to automating requirements-centric SE tasks.

Maarten Vlaswinkel, Duarte Antunes, Frank Willems

Decarbonization of the transport sector sets increasingly strict demands to maximize thermal efficiency and minimize greenhouse gas emissions of Internal Combustion Engines. This has led to complex engines with a surge in the number of corresponding tunable parameters in actuator set points and control settings. Automated calibration is therefore essential to keep development time and costs at acceptable levels. In this work, an innovative self-learning calibration method is presented based on in-cylinder pressure curve shaping. This method combines Principal Component Decomposition with constrained Bayesian Optimization. To realize maximal thermal engine efficiency, the optimization problem aims at minimizing the difference between the actual in-cylinder pressure curve and an Idealized Thermodynamic Cycle. By continuously updating a Gaussian Process Regression model of the pressure's Principal Components weights using measurements of the actual operating conditions, the mean in-cylinder pressure curve as well as its uncertainty bounds are learned. This information drives the optimization of calibration parameters, which are automatically adapted while dealing with the risks and uncertainties associated with operational safety and combustion stability. This data-driven method does not require prior knowledge of the system. The proposed method is successfully demonstrated in simulation using a Reactivity Controlled Compression Ignition engine model. The difference between the Gross Indicated Efficiency of the optimal solution found and the true optimum is 0.017%. For this complex engine, the optimal solution was found after 64.4s, which is relatively fast compared to conventional calibration methods.

Minyi Xu, Song Wang, Steven L. Zhang et al.

Abstract Wave monitoring is essential for marine engineering construction, development and utilization of ocean resources, maritime safety and early warning of marine disasters. In this paper, a highly-sensitive wave sensor based on liquid-solid interfacing triboelectric nanogenerator is proposed and systematically investigated. The wave sensor is made of a copper electrode covered by a poly-tetra-fluoroethylene film with microstructural surface. The effects of substrate, wave height, frequency, and water salinity on the performance of wave sensor are systematically investigated. It is found that the output voltage increases linearly with wave height with a sensitivity of 23.5 mV/mm for the electrode width of 10 mm, implying that the wave sensor could sense the wave height in the millimeter range. The sensitivity could be further increased by widening the electrode and/or enhancing the surface hydrophobicity. In a water wave tank, the wave sensor is successfully used to monitor wave around a simulated offshore platform in real time. Therefore, the novel wave sensor could provide an alternative to monitor wave for smart marine equipment.

Xuanlie Zhao, D. Ning, Q. Zou et al.

Abstract Ocean wave energy is attractive for its large reserves, exploitability and low emissions. Although many Wave Energy Converter (WEC) concepts have been proposed, high construction cost hinders the engineering application of WECs. Similar challenges arise in the applications of floating breakwaters. The construction cost can be reduced by combining different structures as one integrated system which has the advantage of cost-sharing, space-sharing and multi-functionality. This integrated design approach has stimulated the rapid development of the hybrid system combining floating breakwaters and WECs in recent years. The novel floating breakwater-WEC system is often classified as a wave-energy-utilizing type floating breakwater. The different approaches for integrating floating breakwaters and WECs are summarized in this review. The hydrodynamic performance and power take-off performance of these hybrid floating breakwater-WEC systems are the focus of this review. The insights gained from previous studies of this kind of system and the potential challenges for further developments of this technology are also provided. The cost-sharing and multi-function of the breakwater-WEC system can help facilitate the engineering application of the floating breakwaters and WECs.

Hafiz Ahsan Said, Demian Garcia-Violini, Nicolas Faedo et al.

Optimal control of wave energy converters (WECs), while converting wave energy into a usable form, such as electricity, may <italic>inject</italic> (reactive) power into the system at various points in the wave cycle. Though somewhat counter-intuitive, this action usually results in improved overall energy conversion. However, recent experimental results show that, on occasion, reactive power peaks can be significantly in excess of active power levels, leaving device developers with difficult decision in how to rate the power take-off of the system i.e. whether to cater for these high reactive power peaks, or limit power flow to rated (active) levels. The origins of these excessive power peaks are currently poorly understood, creating significant uncertainty in how to deal with them. In this paper, we show that, using both theoretical results and an illustrative simulation case study, <italic>under matched controller conditions</italic> (impedance-matching optimal condition), for both monochromatic and panchromatic sea-states, that the maximum peak reactive/active power ratio <italic>never exceeds unity</italic>. However, under mismatched WEC/controller conditions, this peak power ratio can exceed unity, bringing unrealistic demands on the power take-off (PTO) rating. The paper examines the various origins of system/controller mismatch, including modelling error, controller synthesis inaccuracies, and non-ideal PTO behaviour, highlighting the consequences of such errors on reactive power flow levels. This important result points to the need for accurate WEC modeling, while also showing the folly of catering for excessive reactive power peaks.

Xin Liu, Xinyang Zou, Yuanshuo Hao et al.

Individual tree crown delineation (ITCD) employing unmanned aerial vehicle light detection and ranging data can directly obtain high-precision tree-level structural information within a block, with this information being the foundation for monitoring and management of the forest, thus reducing time-consuming labor. Despite the fact that numerous ITCD algorithms have been proposed, there has not yet been a robust and comprehensive comparison of these algorithms in plantations. In this article, we evaluated the performance of seven classic ITCD methods under various stand densities and crown classes and analyzed the parameter sensitivity as well as the correlation of segmentation accuracy with optimal parameters and stand metrics. The results demonstrate that the segmentation and crown description accuracy, stability, and adaptability of the algorithm should be comprehensively considered when choosing an algorithm. The forest characteristics impact the accuracy of the algorithms, and the complexity of the forest canopy structure and omission error of suppressed trees are the key factors impacting ITCD accuracy. Furthermore, this study shows that it is feasible to control the parameters of the algorithm through stand measurement. These results will be helpful in guiding the selection of ITCD methods and will provide support for improving the ITCD algorithm in the future.