- Research Article
1
- 10.1016/j.ymssp.2026.113868
Preliminary results of a fiber optic scour sensor (FOSS) for bridges
- Feb 01, 2026
- Mechanical Systems and Signal Processing
- Kristopher Campbell + 6 more +6
Publications from 2021 to 2026
Showing 10 of 37 papers
Preliminary results of a fiber optic scour sensor (FOSS) for bridges
Data Interoperability Using Smart Data Models and NGSI-LD for the Norwegian Agrifood Sector
The growing adoption of digital technologies in agriculture has led to a proliferation of heterogeneous data from sources such as drones, robotic platforms, and IoT sensors.However, the lack of interoperability across these data streams poses major challenges for integration into decision support systems.This paper presents an approach to harmonising such data using NGSI-LD and Smart Data Models, developed within the Norwegian research project SMARAGD.We demonstrate how domain-specific semantic models and linked data principles can be applied to standardise and enrich geospatial and temporal metadata across three key agritech domains: aerial imagery, robotic sensing, and environmental monitoring.The resulting information assets are integrated into a shared, FIWAREcompatible data space, enabling cross-platform visualisation, querying, and reuse.This work contributes to the development of an open, standards-based digital infrastructure for interoperable, data-driven agriculture in Norway and beyond.
Read moreResilience Engineering in Financial Systems: Strategies for Ensuring Uptime During Volatility
Financial institutions suffer volatility, regulatory scrutiny, cyber risks, and complex technical linkages. System outages and operational failures can influence market stability, customer trust, and regulatory compliance in this setting. For proactive financial system design that can predict, withstand, and recover from interruptions with little service deterioration, resilience engineering is essential. This article examines financial system resilience engineering strategies in detail. It covers redundancy, observability, adaptive capacity, microservices, multi-region deployments, service meshes, Site Reliability Engineering (SRE), chaotic testing, and real-time monitoring. It also examines worldwide regulatory frameworks like the UK FCA recommendations, EU DORA regulation, and US FFIEC standards, highlighting regulatory alignment in operational resilience. JPMorgan Chase's resilience architecture is examined in detail, along with AI-driven observability, Zero Trust architectures, edge computing, and blockchain-based settlements. This research integrates technical, operational, and compliance methods to help financial institutions maintain uptime and service continuity in a dynamic digital economy.
Read moreNavigating epistemological shifts: management of skills development in the construction 4.0 era
Construction skills are being transformed by Construction 4.0, which integrates digital technologies to improve productivity. Previous research has predominantly explored technical advancements without epistemological consideration of skills and performance, leaving a paradigmatic gap in understanding the underlying knowledge guiding the management of skills development research. This study aims to bridge the epistemological positions and methodological approaches driving skills development research in Construction 4.0, drawing on a systematic review from 2019 to 2023. The analysis reveals a paradigm shift towards a diverse and integrative epistemological landscape, characterized by increasing adoption of interpretivism and pragmatism alongside traditional positivist perspectives. Specifically, the findings highlight the emergence of pragmatism as the dominant stance, accounting for 42% of research approaches, indicating a move towards practical, solution-oriented research balancing objective analysis with subjective insights. Additionally, there is a notable increase in the use of mixed methods, reflecting a trend towards methodological pluralism that values complementary insights from both qualitative and quantitative data. This study underscores the need for adaptive research frameworks to navigate the epistemological challenges of digital transformation in construction, paving the way for future research that is both theoretically robust and practically relevant.
Read moreA comprehensive approach for assessing the causes of low productivity in the construction sector: a systematic categorization and ranking using Pareto and Fuzzy analysis
Implementing a comprehensive and globally adaptable assessment approach for causes of low construction productivity has proven to be a contemporary challenge. This prevails since the factors influencing the construction industry vary significantly by geographic region and operational characteristics. Hence, substantial research on this topic has restricted its scope to a particular location without a comprehensive global categorization. Furthermore, much of this research has neglected the influence of subjectivity in the stakeholder response evaluations. To address these shortcomings, this study provides a unique assessment of the construction context initiated by a systematic review of 130 studies published worldwide over the previous 32 years. The 915 unique factors from this systematic review were then categorized into regional and productivity dimensions through Pareto and Frequency analysis techniques. The regional categorization encompassed nine distinct regions spanning the world, while the productivity component encompassed a set of 14 distinctive benchmarks that characterize productivity in the construction industry. These sorted factors were then adapted in the Sri Lankan context as a pilot study through a cross-sectional survey including 117 stakeholders. The following Fuzzy analysis allowed the mitigation of the ambiguity of these survey responses while ranking the factors based on a calculated importance index while also considering the interdependence of the introduced benchmarks. Ultimately, the employed assessment approach for identifying and ranking factors contributing to low construction productivity in this study is proposed as globally adaptable with its successful incorporation of subjective evaluation.
Read moreResidential long-span timber floor typologies: a comprehensive performance assessment and opportunities for value adding to plantation hardwood
ABSTRACT High-performance engineered wood products (EWPs) and composite mass timber products (CMTPs) are being employed more frequently in residential projects with increasing interest in more sustainable systems that achieve long-spans. The relative performance of these systems is not readily apparent, with individual manufacturers offering proprietary products assembled from specific timber resources. In addition, the suitability of producing these long-span systems using plantation hardwoods is currently unknown. This research investigated the comparative performance of four typical EWPs and CMTPs; 1. solid slab, 2. thin-walled cassette, 3. T-sections, and 4. slab on beam. Key performance metrics of depth, mass, stiffness, vibration response, fire performance and global warming potential were assessed. The mechanical performance of two high-strength plantation hardwood varieties (Eucalyptus nitens and Eucalyptus globulus) were determined experimentally and subsequently used to re-calculate performance criteria for the previously assessed typologies. Substantial improvements over the typical softwood varieties were identified, particularly in structural efficiency, global warming potential and fire performance. This highlights the potential for value adding to plantation hardwoods by using them in high-performance long-span engineered floor products.
Read moreA framework for low-carbon mix design of recycled aggregate concrete with supplementary cementitious materials using machine learning and optimization algorithms
This study presents a framework for designing low-carbon and cost-effective mixtures of recycled aggregate concrete (RAC) with supplementary cementitious materials by integrating machine learning and grey wolf optimizer algorithms. The concrete mix design process considers key performance parameters such as compressive strength, chloride ion penetration resistance, and carbonation resistance. A dataset comprising 5306 data samples from 154 scientific resources is collected from the literature to train the machine learning models. Four different techniques, namely random forest, extreme gradient boosting (XGBoost), light gradient boosting (LightBoost), and category boosting (CatBoost) are employed to model the compressive strength, chloride ion penetration, and carbonation resistances of RAC. The best-performing models are then utilized to optimize the RAC mix design by minimizing the cost and reducing the carbon footprint. The results indicate that the CatBoost model demonstrates better predictive performance for the compressive strength and carbonation resistance, while the XGBoost and LightBoost models perform better in estimating chloride ion penetration resistance. Furthermore, the adoption of low-carbon mix design principles leads to a reduction in carbon footprint by 5.0% to 31.5% compared to cost-effective mix design for different compressive strength targets, with varying permeability levels. The framework provides a promising approach for designing environmentally friendly RAC mixtures while considering economic and durability factors.
Read moreWie ontbindt zijn duivels?
R&D Reflection and debate initiates academically inspired discussions on issues that are on the current policy agenda.
Read moreList of figures
This book presents new theories and international empirical evidence on the state of work and employment around the world. Changes in production systems, economic conditions and regulatory conditions are posing new questions about the growing use by employers of precarious forms of work, the contradictory approaches of governments towards employment and social policy, and the ability of trade unions to improve the distribution of decent employment conditions. Designed as a tribute to the highly influential contributions of Jill Rubery, the book proposes a 'new labour market segmentation approach' for the investigation of issues of job quality, employment inequalities, and precarious work. This approach is distinctive in seeking to place the changing international patterns and experiences of labour market inequalities in the wider context of shifting gender relations, regulatory regimes and production structures.
Read moreRelationship Between Psychiatric-Service Consumers' and Providers' Goal Concordance and Consumers' Personal Goal Attainment.
This study tested concordance between consumers' and providers' reports of personal goal setting and its relationship to self-reported goal attainment. Data are from the Israeli Psychiatric Rehabilitation Patient Reported Outcome Measurement project. Consumers (N=2,885) and the providers who were most knowledgeable about their care indicated two domains from a list of ten in which consumers had set goals during the previous year. Consumers reported on goal attainment in each domain. A total of 2,345 consumers (82%) reported a personal goal. Overall, consumer-provider concordance reached 54%. Concordance was greatest in the employment (76%), housing (71%), and intimate relationship (52%) domains and lowest in family relationships (23%) and finances (15%). For most domains, concordance was less than 50%. On average, 75% of consumers reported having achieved their goals. Consumer-provider concordance was associated with goal attainment (p<.001). These findings emphasize the importance of agreed-upon goals and call for conceptualizing goal setting as an interpersonal process central to recovery.
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