Hasil untuk "Disasters and engineering"

Bambang Istijono, Andriani Andriani, Taufika Ophiyandri et al.

Abstract From December 2023 to May 2025, Mount Marapi’s eruptions deposited volcanic material into 25 rivers, reducing flow capacity. On 11 May 2024, heavy rain triggered a deadly flash flood, damaging infrastructure and irrigation, and causing 60 fatalities. This study proposes a comprehensive approach to managing post-eruption floods through river engineering and irrigation management. And non-structural mitigation. The research methodology involves collecting secondary data from related agencies and primary data through interviews and observations of river conditions and irrigation systems. And the community. The study emphasizes the use of river engineering techniques to develop effective structural flood control measures. It also advocates for a combination of structural and non-structural interventions to stabilize river flows and reduce disaster impacts. Structural interventions such as sediment control using sabo dams and the design of irrigation intakes adapted to Mount Marapi’s specific conditions aim to minimize sediment transport, enhance agricultural irrigation systems, and improve overall regional resilience. Furthermore, the study provides policy-relevant insights to support government decision-making and offers a foundation for strengthening community resilience to volcanic hazards.

Patricia G. F. Matsubara, Tayana Conte

Over twenty years ago, the Software Engineering (SE) research community have been involved with Evidence-Based Software Engineering (EBSE). EBSE aims to inform industrial practice with the best evidence from rigorous research, preferably from systematic literature reviews (SLRs). Since then, SE researchers have conducted many SLRs, perfected their SLR procedures, proposed alternative ways of presenting their results (such as Evidence Briefings), and profusely discussed how to conduct research that impacts practice. Nevertheless, there is still a feeling that SLRs' results are not reaching practitioners. Something is missing. In this vision paper, we introduce Evidence to Decision (EtD) frameworks from the health sciences, which propose gathering experts in panels to assess the existing best evidence about the impact of an intervention in all relevant outcomes and make structured recommendations based on them. The insight we can leverage from EtD frameworks is not their structure per se but all the relevant criteria for making recommendations to practitioners from SLRs. Furthermore, we provide a worked example based on an SE SLR. We also discuss the challenges the SE research and practice community may face when adopting EtD frameworks, highlighting the need for more comprehensive criteria in our recommendations to industry practitioners.

Junwen Zhang, Xu-yang Bai, Zhixiang Song et al.

Sudhakar Geruganti

The Himalayan region, particularly Uttarakhand, faces recurrent ecological disasters due to unregulated construction, tourism-driven urbanization, and climate change. This paper examines engineering interventions—such as slope stabilization, eco-sensitive drainage systems, and geosynthetic reinforcements—to reduce landslide risks. Case studies from the Char Dham project and Kedarnath floods highlight the consequences of poor planning. The study proposes AI-based terrain modeling, debris flow sensors, and bioengineering solutions (vegetated gabions, soil nailing) to enhance resilience. Global comparisons with the Alps and Andes offer scalable strategies for sustainable development in fragile ecosystems Detailed Description: This research examines the intersection of engineering innovation and geological risk assessment to address Uttarakhand’s recurring ecological disasters (landslides, GLOFs, cloudbursts). It critiques unchecked tourism-driven development (e.g., Char Dham Project) and proposes: Engineering solutions: AI-based terrain modeling, vegetated gabions, and debris flow sensors. Geological tools: InSAR for fault monitoring, glacial lake outburst prediction. Policy integration: Lessons from Swiss Alps (avalanche barriers) and Bhutan’s eco-tourism policies.The study bridges civil engineering, geomorphology, and climate science, offering scalable strategies for global mountain ecosystems.

Muneera Bano, Hashini Gunatilake, Rashina Hoda

Large language models (LLMs) have rapidly gained popularity and are being embedded into professional applications due to their capabilities in generating human-like content. However, unquestioned reliance on their outputs and recommendations can be problematic as LLMs can reinforce societal biases and stereotypes. This study investigates how LLMs, specifically OpenAI's GPT-4 and Microsoft Copilot, can reinforce gender and racial stereotypes within the software engineering (SE) profession through both textual and graphical outputs. We used each LLM to generate 300 profiles, consisting of 100 gender-based and 50 gender-neutral profiles, for a recruitment scenario in SE roles. Recommendations were generated for each profile and evaluated against the job requirements for four distinct SE positions. Each LLM was asked to select the top 5 candidates and subsequently the best candidate for each role. Each LLM was also asked to generate images for the top 5 candidates, providing a dataset for analysing potential biases in both text-based selections and visual representations. Our analysis reveals that both models preferred male and Caucasian profiles, particularly for senior roles, and favoured images featuring traits such as lighter skin tones, slimmer body types, and younger appearances. These findings highlight underlying societal biases influence the outputs of LLMs, contributing to narrow, exclusionary stereotypes that can further limit diversity and perpetuate inequities in the SE field. As LLMs are increasingly adopted within SE research and professional practices, awareness of these biases is crucial to prevent the reinforcement of discriminatory norms and to ensure that AI tools are leveraged to promote an inclusive and equitable engineering culture rather than hinder it.

Hayato Ishida, Amal Elsokary, Maria Aslam et al.

Realisation of significant advances in capabilities of sensors, computing, timing, and communication enabled by quantum technologies is dependent on engineering highly complex systems that integrate quantum devices into existing classical infrastructure. A systems engineering approach is considered to address the growing need for quantum-secure telecommunications that overcome the threat to encryption caused by maturing quantum computation. This work explores a range of existing and future quantum communication networks, specifically quantum key distribution network proposals, to model and demonstrate the evolution of quantum key distribution network architectures. Leveraging Orthogonal Variability Modelling and Systems Modelling Language as candidate modelling languages, the study creates traceable artefacts to promote modular architectures that are reusable for future studies. We propose a variability-driven framework for managing fast-evolving network architectures with respect to increasing stakeholder expectations. The result contributes to the systematic development of viable quantum key distribution networks and supports the investigation of similar integration challenges relevant to the broader context of quantum systems engineering.

C. J. Horwell, S. Ravenhall, R. Clarkson et al.

Abstract Volcanic eruptions produce plumes of ash, gas and aerosols that present a risk to aviation at all standard flight levels. Here, we investigate atmospheric dispersal of volcanic emissions, whether and how they infiltrate aircraft, and whether ground-level public health exposure thresholds can be related to the pressurised cabin environment. We then review the limited evidence for physical and mental health, and behavioural impacts, resulting from volcanic emissions entering aircraft. Serious health risks are considered low for healthy individuals, but respiratory irritation is likely for a high exposure scenario to sulfur dioxide (SO2). Asthmatics are particularly sensitive to SO2, with even relatively low, short exposures, potentially resulting in severe respiratory impacts. Negative group behaviours are not expected but individual distress is possible. Communicating this evidence to the aviation industry may result in more informed decision-making on flightpath alterations and triggering of emergency protocols, both before and during volcanic emission encounters.

Ghina Bani Azifah, Teuku Faisal Fathani, Hendy Setiawan

Abstract Background There were more than 700 earthquakes with a magnitude of more than 5.0 over the past 100 years in the Special Region of Yogyakarta, Indonesia. Due to the high intensity of seismic activities, it is essential to perform seismic hazard analysis by considering local site effects. Therefore, this study aimed to analyze the peak ground acceleration (PGA) value based on the earthquake scenario of May 27, 2006, with a magnitude of 6.3, which occurred on the eastern side of the Opak Fault. Methods The study was conducted in the southern part of the Progo River, the Special Region of Yogyakarta, using 31 boreholes and 18 microtremor measurement points. The analysis was carried out using four methods: Kanai (In: Proceeding of Japan Earthquake Engineering Symposium 1–4, 1966) equation using microtremor data, deterministic equations with Ground Motion Prediction Equations Next Generations Attenuation West 2 (GMPE NGA West 2), Kanno et al (Bull Seismol Soc Am 96:879–897, 2006) attenuation equation, and probabilistic method referring to the Indonesian Seismic code. Results Results indicated that the highest value of PGA was obtained using the deterministic GMPE NGA West 2 weighted attenuation equation, which varied from 0.475 to 0.549 g. Meanwhile, Kanno et al (Bull Seismol Soc Am 96:879–897, 2006) attenuation equation resulted in values ranging from 0.266 to 0.394 g. In contrast, PGA values obtained through microtremor measurement resulted in a smaller value, in the range of 0.126–0.214 g. Probabilistic analysis in the study area produces values ranging from 0.373 to 0.450 g. Conclusion The location on the central side of the Progo River shows a lower PGA value than the other sides. PGA values will tend to be higher at locations near the earthquake source. The low PGA value that resulted from microtremor analysis was due to the consideration of local site effects in determining earthquake parameters in the study area. Determining the seismic hazard analysis method in infrastructure planning requires a comprehensive analysis by considering various parameters, such as the planning and design objectives, the location proximity to earthquake sources, historical seismic conditions, and the presence of the local site effects.

Ali Nasiri, Esmaeil Salimi, Morteza Delfan Azari et al.

Flood zoning has extensive applications in flood management and is considered one of the fundamental and critical pieces of information in flood risk management. Flood zoning in urban areas is much more challenging than modeling in floodplain and river areas due to the two-dimensional nature of the flow and, on the other hand, the density of urban features such as buildings, streets, boulevards, and public pathways. In this study, flood zoning for districts 21 and 22 of Tehran was conducted under the current conditions, where the area is almost devoid of surface water collection channels, using a physically-based rainfall-runoff model and two-dimensional hydraulic routing which is the novelty aspect of the article. For this purpose, the HEC-HMS model was used to estimate the runoff from the mountains, and the MIKE model was used to simulate urban rainfall-runoff. According to the modeling results, the areas affected by a 50-year flood event were identified using an integrated modeling approach in districts 21 and 22, covering 8% of these areas. In these areas, the maximum flood depth is 11.8 meters in Vardavard river and the highest speed is 4.5 meters per second at the beginning of Hashemzadeh street (south of Kharrazi highway). The results indicate that in the event of extreme events such as a 50-year rainfall, a significant portion of the highways and main communication arteries of Tehran leading westward would be disrupted, and traffic would be impossible. Moreover, various land uses would fall within the flood zone, and due to the absence of a surface water network, waterlogging conditions throughout districts 21 and 22 of Tehran are predictable. Therefore, the development of a surface water collection network is one of the main priorities for reducing flood risk in these areas.

Jiewen You, Fangxu Yin, Boen Zhang et al.

Compound extremes, specifically concurrent low wind power (wind droughts) and heat waves, threaten ecological stability and renewable energy. However, their dynamics and impacts remain poorly understood. This study introduces compound wind droughts and heat waves (WDHW) indicator to assess their patterns in mainland China from 2000 to 2022. Using observational data and explainable machine learning (XGBoost and SHAP), we analyzed the spatiotemporal distributions, underlying drivers, and ecological implications of WDHW. Results reveal spatial heterogeneity, with high-frequency WDHW (>70 cumulative days) concentrated in northwestern China and a national increase in event frequency within affected regions (0.042 d yr–1). The XGBoost model performed well, with R2 values of 0.88, 0.83, and 0.84 for training, cross-validation, and test datasets, respectively. SHAP analysis highlights maximum temperature (Tmax; SHAP = 0.722) and vapor pressure deficit (VPD; SHAP = 0.698) as primary drivers, with their interaction (SHAP = 0.321) demonstrating how heat and dryness link with 100-m hub-height winds. Ecological analysis shows peak WDHW frequencies in Half Protected ecoregions (28.8 days) and Deserts & Xeric Shrublands biomes (28.75 days), indicating dual vulnerabilities to biodiversity and energy systems. This study advances understanding of concurrent wind droughts and heat waves, providing implications for sustainable ecological and energy adaptation strategies.

Dwinata Aprialdi, Reza Mohammadpour, Afri Fajar et al.

Abstract We study a tropical river in South‐East Sumatra, where land drainage in the coastal zone has resulted in subsidence and increased flooding risks, exacerbated by sea tides. The novelty of this research is in determining the effect of tide on the lowland drainage system for forestry in a coastal tropical region and the impact of river cleaning on flood management. Five monitoring stations were set up along the Lebong Hitam river and its primary channels to observe flow characteristics, water level, and bathymetry. The results show how the tide effects water level in the river and the adjacent drainage area with Eucalyptus plantations. Cleaning of the river had a significant effect on each station and increased the discharge and velocity by more than five times and reduced the water depth by more than 40%. In light of this research, it can be concluded that the cleaning up process improves flood risk management by decreasing the water level and increasing the discharge and velocity at each of the upstream stations. The cleaning did not have a significant effect on downstream sections of the river where sea levels control the water level in the river to a large extent. The work provides an analysis of tidal river and provides recommendations for current and future drainage and water management.

Luisa Pilar Marques Martins, Antonio Carlos Oscar-Júnior

The homeless population in Brazil has shown significant growth in recent years. This fact is perceived in the main capitals of the country, such as the city of Rio de Janeiro. The number of people affected there has reached 13 thousand, thus exposing a structural, social and economic problem that demands attention from the public authorities. The present study aims to analyse and operationalize the concept of vulnerability in its programmatic (or institutional) dimension based on public policies, also considering the exposure to climate risk to which these people are vulnerable, in a non-inclusive city. Fieldwork, interviews, data collection, and literature surveys on the subject were conducted for this purpose. As a result, it was possible to see that the difficulties faced by this population are related to the deprivation of basic rights, starting with a lack of housing, jobs, and access to public policies that fail to meet the demand for urban shelter. This social impoverishment was exacerbated during and after the COVID-19 pandemic that began in 2020.

Huie Chen, Xiang Gao, Qing Wang

Zhonghan Chen

As the frequency and complexity of natural disasters increase, effective monitoring and early warning have become important for the protection of life and property. This paper discusses the role of unmanned aerial vehicle (UAV) remote sensing technology in natural disaster monitoring and early warning. The research in this paper finds that the advantages of UAVs, which carry multiple sensors and are convenient and dexterous, are conducive to natural disaster monitoring. The article then provides examples of UAV applications in different natural disaster scenarios, including monitoring, early warning, post-disaster assessment and ecological restoration in floods, mudslides and earthquakes. In flood monitoring, UAVs equipped with various sensors, such as multi-spectral sensors and infrared thermal imagers, can quickly scan flood-prone areas and transmit data in real time for timely warning and rescue. In mudslide monitoring, drones can collect data such as surface temperature, soil moisture and vegetation health to help identify signs of potential danger. In earthquake monitoring, drones can provide high-resolution images and video to assess earthquake damage and the condition of infrastructure. The future technological innovation and industry development of UAV remote sensing will continue to progress in terms of sensor technology innovation, application of machine learning and artificial intelligence, range extension, and convergence of communication technologies. The significance of this paper is to highlight the importance of UAV remote sensing in natural disaster management and to provide a vision for future research and applications. Drones will continue to play a key role in facilitating the efficiency and accuracy of natural disaster monitoring and early warning to better address potential threats.

Bofan Yu, Huaixue Xing, Jiaxing Yan et al.

Marcus Kessel, Colin Atkinson

The ability of Generative AI (GAI) technology to automatically check, synthesize and modify software engineering artifacts promises to revolutionize all aspects of software engineering. Using GAI for software engineering tasks is consequently one of the most rapidly expanding fields of software engineering research, with over a hundred LLM-based code models having been published since 2021. However, the overwhelming majority of existing code models share a major weakness - they are exclusively trained on the syntactic facet of software, significantly lowering their trustworthiness in tasks dependent on software semantics. To address this problem, a new class of "Morescient" GAI is needed that is "aware" of (i.e., trained on) both the semantic and static facets of software. This, in turn, will require a new generation of software observation platforms capable of generating large quantities of execution observations in a structured and readily analyzable way. In this paper, we present a vision and roadmap for how such "Morescient" GAI models can be engineered, evolved and disseminated according to the principles of open science.

Roberto Casadei, Gianluca Aguzzi, Giorgio Audrito et al.

Today's distributed and pervasive computing addresses large-scale cyber-physical ecosystems, characterised by dense and large networks of devices capable of computation, communication and interaction with the environment and people. While most research focusses on treating these systems as "composites" (i.e., heterogeneous functional complexes), recent developments in fields such as self-organising systems and swarm robotics have opened up a complementary perspective: treating systems as "collectives" (i.e., uniform, collaborative, and self-organising groups of entities). This article explores the motivations, state of the art, and implications of this "collective computing paradigm" in software engineering, discusses its peculiar challenges, and outlines a path for future research, touching on aspects such as macroprogramming, collective intelligence, self-adaptive middleware, learning, synthesis, and experimentation of collective behaviour.

Valerio Terragni, Annie Vella, Partha Roop et al.

A paradigm shift is underway in Software Engineering, with AI systems such as LLMs playing an increasingly important role in boosting software development productivity. This trend is anticipated to persist. In the next years, we expect a growing symbiotic partnership between human software developers and AI. The Software Engineering research community cannot afford to overlook this trend; we must address the key research challenges posed by the integration of AI into the software development process. In this paper, we present our vision of the future of software development in an AI-driven world and explore the key challenges that our research community should address to realize this vision.

Arthur Pilone, Paulo Meirelles, Fabio Kon et al.

A central challenge for ensuring the success of software projects is to assure the convergence of developers' and users' views. While the availability of large amounts of user data from social media, app store reviews, and support channels bears many benefits, it still remains unclear how software development teams can effectively use this data. We present an LLM-powered approach called DeeperMatcher that helps agile teams use crowd-based requirements engineering (CrowdRE) in their issue and task management. We are currently implementing a command-line tool that enables developers to match issues with relevant user reviews. We validated our approach on an existing English dataset from a well-known open-source project. Additionally, to check how well DeeperMatcher works for other languages, we conducted a single-case mechanism experiment alongside developers of a local project that has issues and user feedback in Brazilian Portuguese. Our preliminary analysis indicates that the accuracy of our approach is highly dependent on the text embedding method used. We discuss further refinements needed for reliable crowd-based requirements engineering with multilingual support.

Bo Han, Zhen Ma, Liang-jun Lin et al.

ABSTRACT: China established Xiong'an New Area in Hebei Province in 2017, which is planned to accommodate about 5 million people, aiming to relieve Beijing City of the functions non-essential to its role as China's capital and to expedite the coordinated development of the Beijing-Tianjin-Hebei region. From 2017 to 2021, the China Geological Survey (CGS) took the lead in multi-factor urban geological surveys involving space, resources, environments, and disasters according to the general requirements of “global vision, international standards, distinctive Chinese features, and future-oriented goals” in Xiong'an New Area, identifying the engineering geologic conditions and geologic environmental challenges of this area. The achievements also include a 3D engineering geological structure model for the whole area, along with “one city proper and five clusters”, insights into the ecology and the background endowment of natural resources like land, geothermal resources, groundwater, and wetland of the area before engineering construction, a comprehensive monitoring network of resources and environments in the area, and the “Transparent Xiong'an” geological information platform that is open, shared, dynamically updated, and three-dimensionally visualized. China's geologists and urban geology have played a significant role in the urban planning and construction of Xiong'an New Area, providing whole-process geological solutions for urban planning, construction, operation and management. The future urban construction of Xiong'an New Area will necessitate the theoretical and technical support of earth system science (ESS) from various aspects, and the purpose is to enhance the resilience of the new type of city and to provide support for the green, low-carbon, and sustainable development of this area.