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Domain generalized person reidentification based on skewness regularity of higher-order statistics
Get PDFPublisher Copyright: © 2024 Elsevier B.V.The goal of domain-generalized person reidentification (DG-ReID) is to train a model in the source domain and apply it directly to unknown target domains for specific pedestrian retrieval. Existing methods rely primarily on low-order statistics (such as the mean, standard deviation, or variance), thereby ensuring the stability of the source domain data distribution for model training. However, such methods underperform when the data follow a non-Gaussian distribution, thereby reducing the generalization ability of the model on unseen target domains. To address this issue, this study proposes an instance normalization-based skewness regularity (INSR) framework that uses high-order statistics (skewness and high-order moments) to measure the skewness and regularity of the data distribution. Such measures allow further learning of the morphological features (skewness degree, trait of data near the mean, etc.) of complex data distributions for DG-ReID. Specifically, the proposed framework first extracts the skewness and third-order moments from the source domains, which provide more features (high-order moments, variance, etc.) to characterize the data distribution. Subsequently, a batch normalization-like operation was implemented to project the data into a new feature space with zero mean and unit variance, enhancing model adaption and accuracy. Extensive experiments were conducted on small-scale (VIPeR, PRID, GRID, and i-LIDS) and large-scale (Market-1501, DukeMTMC-reID, CUHK03, MSMT17) public datasets using two different protocols, demonstrating that the proposed INSR framework significantly outperforms other state-of-the-art counterparts for DG-ReID.Peer reviewe
Vulnerability Assessment of Historic Areas to Heat Waves. The Case Study of Bilbao
No full textPublisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.The impacts of climate change, such as extreme events and progres-sive global warming, threaten the conservation and habitability of urban cultural heritage. Understanding climate risks to heritage must be part of planning and policy decision-making processes to increase the resilience and sustainability of both social and built environmental systems.. However, despite a large body of literature on climate-related hazards, there is a notable knowledge gap regarding a holistic conceptualization of hazards in historic urban areas, especially in the case of heat waves and urban heat island phenomena. The main goal of this study was to analyze and represent the interaction between historic built environment and heat waves via Geographic Information Systems (GIS) data, considering the vulnerability of historic areas both as urban systems and as heritage areas. To frame a holistic approach, socio-economic, cul-tural, governance (services and resources) and physical (gathering tangible characteristics of all infrastructures, elements and buildings) aspects of the system are taken into ac-count. To this end, a multicriteria risk assessment methodology is developed. Key performance indicators, criteria and requirements addressing relevant vulnerable elements of historic urban areas are identified for the development of the methodology. Moreover, as the foundation for the risk assessment, a categorization based on vulnerability to heat waves is proposed for both buildings and urban spaces. Here, this methodology’s results and its application on a GIS-based model in the historic area of Bilbao (Basque Country, Spain) are presented. This work aims to be replicable and to serve as a reference for future holistic assessments of heatwaves risks in historic urban areas worldwide.Acknowledgements. The authors wish to acknowledge funding from the European Commission through the SHELTER project (GA 821282), as well as the support of the SAREN research group (IT1619–22, Basque Government).Peer reviewe
Life cycle and economic assessment of tidal energy farms in early design phases: Application to a second-generation tidal device
Get PDFPublisher Copyright: © 2024 The Author(s)Ocean currents are emerging as key contributors to renewable energy generation. However, technologies for harvesting tidal current energy are still in the early stages of development. In this context, environmental and economic studies on tidal energy converters (TECs) are crucial to further advance tidal technology and facilitate its entry into the market. This article presents a life cycle and economic assessment of a 34.5 MW tidal farm project comprising 23 second-generation tidal devices, each with a rated power of 1.5 MW. The tidal system was simulated using primary data from the full-scale floating platform Atir. The Atir is a pre-commercial tidal device designed with a steel trimaran and a submerged section for TEC installation. An assessment of 18 environmental impact categories was conducted using the ReCiPe 2016 MidPoint method, with process flow systems modelled using SimaPro v9.2.0.1 software. The environmental assessment indicates emissions of 42.11 g CO2eq per kWh, primarily stemming from manufacturing processes that demand substantial amounts of steel. The economic analysis reveals a Levelized Cost of Electricity (LCOE) of 0.125 EUR/kWh, consistent with European Commission projections. Although the platform structure represents a high initial investment, the lower maintenance costs of the Atir device provide long-term savings and, overall, result in a competitive LCOE. The study also introduces a methodological framework for harmonised environmental and economic assessments in tidal energy projects, proving crucial in supporting decision-making processes.Peer reviewe
Reconstruction-Based Anomaly Detection in Wind Turbine Operation Time Series Using Generative Models
No full textPublisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Unsupervised time series anomaly detection is a common tasks in many real world problems, in which the normal/anomaly labels are extremely unbalanced. In this work, we propose to use three generative models (namely, a basic autoencoder, a transformer autoencoder and a diffusion model) for a reconstruction-based anomaly detection pipeline applied to failure detection in wind turbine operation time series. Our experiments show that the transformer autoencoder yields the most accurate reconstructions of the original time series, whereas the diffusion model is not able to obtain good reconstructions. The reconstruction error, which is used as an anomaly score, seems to follow different distributions for the anomalies and for the normal data in 2 of the 3 models, which is confirmed by our quantitative evaluation. The transformer autoencoder is the best performing generative model, achieving a AUC score of 0.98 in the detection of the anomalies. However, the same result is obtained by standard (i.e. non-generative) outlier detection algorithms, exposing that although the anomalies in this problem are sequence anomalies – with a temporal nature –, they can be effectively modeled and detected as point outliers.Peer reviewe
Reviewing experimental studies on sensible thermal energy storage in cementitious composites: report of the RILEM TC 299-TES
Get PDFPublisher Copyright: © The Author(s) 2024.Thermal energy storage (TES) systems have been a subject of growing interest due to their potential to address the challenges of intermittent renewable energy sources. In this context, cementitious materials are emerging as a promising TES media because of their relative low cost, good thermal properties and ease of handling. This article presents a comprehensive review of studies exploring the use of cementitious materials, particularly concrete, as sensible heat storage media at varying scales, ranging from laboratory investigations to prototype evaluations. Starting from the different kinds of energy storage systems and applications where concrete has been used as a storage media, this article reviews the important properties which makes them a suitable material for the purpose. Reported observations are discussed and summarised based on concrete mix composition/design, aggregate/addition type, size gradation, etc., and performance of these materials. Finally, different cement-based prototypes are examined highlighting their strengths and weaknesses, and general conclusions are drawn.Peer reviewe
Phosphorus-containing lignin intermediates as reactive bio-based flame-retardants for polyurethane and acrylic coatings for wood
Get PDFPublisher Copyright: © 2024 The AuthorsWood has limited fire-retardant properties but this can be improved by using coatings with sustainable and cost-effective flame retardants. For this purpose, lignin is a potential candidate due to its highly aromatic structure and low cost. However, its structure should be modified to achieve good fire behaviour. Thus, phosphorus was incorporated into kraft lignin and the compounds obtained were used for the synthesis of two types of wood coatings: Polyurethanes and Polyacrylates. Phosphorus nuclear magnetic resonance was used to characterize the modified lignin, together with elemental analysis. The incorporation of lignin into the polymers was confirmed by infrared spectroscopy and gel content measurements. The effectiveness of the phosphorus-containing lignin intermediates as bio-based flame retardants was measured by thermogravimetric analysis (TGA), pyrolysis combustion flow calorimetry (PCFC) and cone calorimetry. According to the results, phosphorylated lignin increased the residue and decreased the total heat release of the polyurethane and acrylic coatings. In addition, slight improvements in fire resistance were observed in wood panels coated with acrylic, while no changes were observed in wood coated with polyurethane.Peer reviewe
Correlating gas permeability and morphology of bio-based polyether-block-amide copolymer membranes by IR nanospectroscopy
Get PDFPublisher Copyright: © 2024The gas permeability of polymer membranes is determined by their nanoscale morphology, which strongly depends on the membrane fabrication. Here, we demonstrate how the correlation between gas permeability and fabrication-dependent nanoscale morphology of polymer membranes can be elucidated by infrared (IR) nanospectroscopy based on elastic IR scattering at an atomic force microscope tip. Specifically, we fabricated membranes of PEBAX® RNEW – a bio-based polyether-block-amide copolymer – by solvent casting and extrusion, achieving unprecedented CO2 permeability and CO2/N2 selectivity for the solvent-cast membranes. For the extruded membranes, however, we found an about 50 % reduced CO2 permeability, which could not be explained by differential scanning calorimetry and conventional IR spectroscopy. In contrast, IR nanospectroscopy revealed a highly crystalline polyether oxide (PEO) surface layer on the extruded membranes, not observed for the solvent-cast membranes. Annealing of the extruded membranes at 110 °C transformed the crystalline into amorphous PEO layers, as confirmed by IR nanospectroscopy, yielding a gas permeability close to that of the solvent-cast membranes. We thus attribute the dramatic gas reduction of the extruded membranes to their highly crystalline surface layers. Generally, studying polymer morphology by IR nanospectroscopy provides valuable information for better understanding the local gas permeability properties of polymer membranes.Peer reviewe
Standardisation of equitable climate services by supporting a community of practice
Get PDFPublisher Copyright: © 2024 The AuthorsClimate services are essential to support climate-sensitive decision making, enabling adaptation to climate change and variability, and mitigate the sources of anthropogenic climate change, while taking into account the values and contexts of those involved. The unregulated nature of climate services can lead to low market performance and lack of quality assurance. Best practices, guidance, and standards serve as a form of governance, ensuring quality, legitimacy, and relevance of climate services. The Climateurope2 project (www.climateurope2.eu) addresses this gap by engaging and supporting an equitable and diverse community of climate services to provide recommendations for their standardisation. Four components of climate services are identified (the decision context, the ecosystem of actors and co-production processes, the multiple knowledge systems involved, and the delivery and evaluation of these services) to facilitate analysis. This has resulted in the identification of nine key messages summarising the susceptibility for the climate services standardisation. The recommendations are shared with relevant standardisation bodies and actors as well as with climate services stakeholders and providers.Peer reviewe
Dual-media laser system: Nitrogen vacancy diamond and red semiconductor laser
Get PDFPublisher Copyright: © 2024 The Authors.Diamond is a potential host material for laser applications due to its exceptional thermal properties, ultrawide bandgap, and color centers, which promise gain across the visible spectrum. More recently, coherent laser methods offer improved sensitivity for magnetometry. However, diamond fabrication is difficult in comparison to other crystalline matrices, and many optical loss channels are not yet understood. Here, we demonstrate a continuous-wave laser threshold as a function of the pump intensity on nitrogen-vacancy (NV) color centers. To achieve this, we constructed a laser cavity with both an NV diamond medium and an intracavity antireflection-coated diode laser. This dual-medium approach compensates intrinsic losses of the cavity by providing a fixed additional gain below threshold of the diode laser. We observe a continuous-wave laser threshold of the laser system and linewidth narrowing with increasing green pump power on the NV centers. Our results are a major development toward coherent approaches to magnetometry.Peer reviewe
Towards the Self-Healing of Infrastructure as Code Projects Using Constrained LLM Technologies
No full textPublisher Copyright: © 2024 ACM.The generalization of the use of cloud computing and edge computing solutions in industry requires innovative techniques to keep up with the complexity of these scenarios. In particular, the large heterogeneity of the infrastructural devices and the myriad of services offered by the various private and cloud providers represent a challenge. Infrastructure as Code (IaC) technologies have been adopted to reduce the complexity of these scenarios, but even IaC technologies have their drawbacks, as the errors resulting from their use often combine the complexities of the underlying layers and require a high level of expertise. In this regard, the recent upsurge of Large Language Models represents an opportunity as they are able to tackle different problems. In this article, we aspire to shed light on the automated patching of IaC projects with the help of LLMs. We evaluate the suitability of this hypothesis by using a well-known LLM that is able to solve all the scenarios we envisioned and assess the possibility of doing the same with smaller, offline LLMs, which could lead to the use of these technologies in resource-constrained environments, such as edge computing.Peer reviewe