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This study hybridizes the background error covariance (BEC) of the hourly atmospheric three-dimensional variational data assimilation (3DVar) in Local Analysis (LA) operated at Japan Meteorological Agency using the flow-dependent BEC derived from the singular vector-based Mesoscale Ensemble Prediction System (MEPS) and the static BEC. The impact of introducing the hybrid BEC into the 3DVar is examined, along with its sensitivities to various factors like the ensemble size that is augmented by using lagged ensemble forecasts, the weight given to the ensemble-based component of BEC, the localization scales, and the use (or not) of the cross-variable correlation. This hybrid 3DVar system can be operated with small additional computational cost because it has no coupling with another ensemble data assimilation system. In sensitivity experiments, this hybrid 3DVar is shown to yield smaller forecast root mean square errors than the pure 3DVar, especially for surface variables. Moreover, the hybrid 3DVar shows a better equitable threat score for strong precipitation. These improvements were greater in the experiments with larger ensemble sizes that were increased by using lagged ensemble forecasts because of the reduced sampling errors in the ensemble-based BEC. These results were sensitive to the weight given to the ensemble-based BEC and the horizontal localization scale, whose optimal values were found to be approximately 0.5 and 100 km, respectively. The longer vertical correlation scale and the cross-variable correlation were also found important to create dynamically-balanced analysis, which is especially true for heavy rain cases. [ABSTRACT FROM AUTHOR]

The research conducted was aimed at developing a comprehensive method to evaluate the technical performance of an operator-centered Operation. The study was conducted under different water supply shortage conditions. The NekooAbad irrigation District was selected for simulation purposes using the Integral-Delay model to simulate flow distribution in the canals. The boundary conditions were based on historical statistics of surface water supply at the source. Seven scenarios were created, ranging from normal to severe water shortage. The technical assessment was based on two aspects: temporal analysis of the daily average water distribution adequacy in 13 main and 149 secondary off-takes. The second aspect included spatial analysis of the distribution of the mentioned index throughout the district. The study classified water distribution adequacy under each scenario. The results showed a pattern of reduced water distribution adequacy from the source to the downstream in all 13 secondary and the main canal. The daily average of the surface water distribution adequacy index ranged from over 10% in the normal scenario to less than 40% in the water scarcity scenarios. The percentage changes ranged from -95% to 64%, 90% to 56%, 89% to 54%, 89% to 50%, 86% to 49%, 86% to 46%, and 33% to 77%. The study also revealed a clear pattern of the operational system's inefficiency in the adequate distribution of surface water under water scarcity scenarios. Furthermore, it identified the vulnerable areas of the district through spatial regionalization maps of water distribution adequacy. [ABSTRACT FROM AUTHOR]

Geographical indication (GI) represents the specific good quality and reputation of the regional characteristics of agricultural products, which is a positive approach for stabilising the export of agricultural products, realising high quality and high prices for agricultural products and rural revitalisation. Based on the China-EU Geographical Indications Agreement, this paper discusses the differences between China and the European Union (EU) in terms of GI protection from three aspects: the institutional framework, the operational system, and the operational status of GIs. The purpose of the study is to identify the differences between China and the EU in the protection of GIs, China's shortcomings, and gaps, and to propose policy recommendations for China to protect GI products better, exploit the economic impact of GIs and enhance the competitiveness of China's exports.

The need for Sharia insurance products in the Muslim community continues to significantly increase. Sharia insurance offers sustainability in overcoming the risk of economic loss based on the principles of Islamic law. In addition, Sharia insurance can be a sustainable solution in providing risk management funds. This study aimed to analyze the development and sustainability of Islamic insurance as an alternative form of risk management, as well as its sustainability in the future. The general review is still in the form of the products offered and operational system models in the Sharia insurance industry. The systematic literature review method was used to obtain a visualization and general description of Islamic insurance, employing 774 data articles from 2010 to 2022. From the results of the analysis, it was found that research discussing Islamic insurance has demonstrated significant developments every year. Mitigating risks by offering the principles of Islamic law represents added value for the Islamic insurance industry. In addition, five models of Sharia insurance systems have been introduced and used; namely, the Mudharabah model, the modified Mudharabah model, the Wakalah model, the hybrid model, and the Waqf model. However, the products offered in Sharia insurance are not too numerous and are still focused on individual risk. Based on these results, Sharia insurance will undergo development in the future in terms of both the products offered and risk management. Of course, it can also lead to a transition to the development of sustainable Sharia insurance. [ABSTRACT FROM AUTHOR]

Sea ice information has traditionally been associated with Manual Ice Charts, however the demand for accurate forecasts is increasing. This study presents an improved operational forecast system for the Arctic sea ice focusing on the Greenlandic waters. In addition, we present different observational sea ice products and conduct inter-comparisons. First, a re-analysis forced by ERA5 from 2000 to 2021 is evaluated to ensure that the forecast system is stable over time and to provide statistics for the users. The output is similar to the initial conditions for a forecast. Secondly, the sea ice forecast system is tested and evaluated based on two re-forecasts forced by the high resolution ECMWF-HRES forecast for the period from January 2019 to September 2021. Both the re-analysis and the re-forecasts include assimilation of sea surface temperatures and sea ice concentrations. We validate the re-analysis and the re-forecast systems for sea ice concentration against different remotely sensed observational products by computing the Integrated Ice Edge Error metric at the initial conditions of each system. The results reveal that the re-analysis and the re-forecast perform well. However, the summertime retreat of sea ice near the western Greenlandic coast seems to be delayed a few days compared with the observations. Importantly, part of the bias associated with the model representation of the sea ice edge is associated with the observational errors due to limitations in the passive microwave product in summertime and also near the coast. An inter-comparison of the observational sea ice products suggests that the model performance could be improved by assimilation of sea ice concentrations derived from a newly-developed automated sea ice product. In addition, analysis of persistence shows that the re-forecast has better skill than the persistence forecast for the vast majority of the time.

Combining optical and synthetic aperture radar (SAR) data for crop mapping has become a crucial way to improve classification accuracy, especially in cloudy and rainy areas. However, the acquisition of optical images is significantly unstable due to the influence of cloudy and rainy weather, which seriously restricts the application of this method in practice. To solve this problem, this study proposed an optical-SAR imagery-based rice mapping method which has the advantages of less dependence on optical images, easy operation and high classification accuracy. To account for the trait of sparse availability of optical images, this method only needs one clear sky optical image in the rice growth period and combined it with multi-temporal SAR images to achieve a high accuracy rice mapping result. Meanwhile, this paper also proposed a comprehensively multi-scale segmentation parameter optimization algorithm, which considers the area consistency, shape error and location difference between the segmented object and reference object, and adopts an orthogonal experiment approach. Based on the optical image, the boundaries of the parcel objects can be segmented, which were subsequently used to perform the object-oriented classification. The results show that the overall accuracy of the proposed method in Yangzhou City is 94.64%. Moreover, according to a random pick test, it is encouraging that the proposed method has strong robustness in response to the instability of the acquisition time of SAR images. A relatively high overall accuracy of 90.09% suggested that the proposed method can provide a reliable rice mapping result in cloudy and rainy areas. [ABSTRACT FROM AUTHOR]

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This paper aims to demonstrate the research-to-application and operational use of numerical hydrologic and hydraulic modeling to (a) quantify potential flash flood risks in small urban communities with high spatial resolution; (b) assess the effectiveness of possible flood mitigation measures appropriate for such communities; and (c) construct an effective operational urban flash flood warning system. The analysis is exemplified through case studies pertaining to a small community with dense housing and steep terrain in Tegucigalpa, Honduras, through numerical simulations with a customized self-contained hydrologic and hydraulic modeling software. Issues associated with limited data and the corresponding modeling are discussed. In order to simulate the extreme scenarios, 24-h design storms with return periods from 1 to 100 years with distinctive temporal and spatial distributions were constructed using both daily and hourly precipitation for each month of the rainy season (May–October). Four flood mitigation plans were examined based on natural channel revegetation and the installation of gabion dams with detention basins. Due to limitations arising from the housing layout and budgets, a feasible plan to implement both measures in selected regions, instead of all regions, is recommended as one of the top candidates from a cost-to-performance ratio perspective. Numerical modeling, customized for the conditions of the case study, is proven to be an effective and robust tool to evaluate urban flood risks and to assess the performance of mitigation measures. The transition from hydrologic and hydraulic modeling to an effective urban flash warning operational system is demonstrated by the regional Urban Flash Flood Warning System (UFFWS) implemented in Istanbul, Turkey. With quality-controlled remotely sensed precipitation observations and forecast data, the system generates forcing in the hydrologic and hydraulic modeling network to generate both historical and forecast flow to assist forecasters in evaluating urban flash flood risks. [ABSTRACT FROM AUTHOR]

Comprehensive resilience management schemes are vital to urban risk governance and sustainable development. In this study, we decompose the urban physical system into the built environment subsystem (BES), information subsystem (IS), and metabolic flow subsystem (MFS), then construct a microscopic mechanism model of the urban system to quantify urban resilience, characterize the dynamics of urban resilience, and analyze the effect of network topology on urban resilience with the complex network method. The results provide several points: (1) There is a tipping point of the system, which crashes at 104.74% times the observed shock intensity in the case of Typhoon Morakot, taking the model parameters unchanged; (2) The topology of resource allocation network has a significant effect on urban resilience; (3) The externality of subsystem varies with the losses caused by negative shocks; and (4) The effects of network topology are contingent on the levels of urban resilience; therefore, for emergency management, city managers need to select resource allocation strategies based on urban resilience, by balancing the functional levels of operational and defensive parts. This study proposes a set of integrated management solutions based on resource deployment relationships among subsystems that can help urban systems better cope with shocks and increase resilience. • A new, multi-dimensional approach to urban resilience assessment was developed. • The topology of resource allocation network was validated as effective for urban resilience. • BES provides an important foundation and plays a stable role in the construction of urban resilience. • Resource allocation should adjust with resilience changes during shock periods. • A cross-system emergency management solution was constructed to cope with shocks. [ABSTRACT FROM AUTHOR]

The regional data assimilation system at the Japan Meteorological Agency uses a variational data assimilation system based on the non-hydrostatic model ASUCA (named ASUCA-Var). This paper reviews the configurations and current status of ASUCA-Var. To consider the consistency of analysis and prognostic variables, the control variables of ASUCA-Var include soil variables and basic atmospheric variables. The background-errors based on the control variables are calculated every 3 h for land and sea grid points to better reflect the representative error covariance structure, considering daily variations and differences in structure on land and sea. Although the cost function is designed to be a perfect quadratic form, the basic field update method in the optimization process allows the nonlinearity of the observation operator and numerical weather prediction model to be incorporated into the solution of optimization problem in the incremental four-dimensional variational (4D-Var) method. The outer/inner models used in the incremental 4D-Var method are based on ASUCA, with suitable configurations according to each resolution and applied linearization. Observation operators are implemented for various kinds of observations used, with unified interfaces encapsulating external simulators. Variational quality control and variational bias correction are also introduced for advanced observation handling within the variational system. Parallelization is introduced to enhance computational efficiency, including adjoint calculations. To assess the impact of assimilated observations, degrees of freedom for signal are also available. Additionally, as a system for operational use, ASUCA-Var is designed for sustainable development. The meso-scale analysis and local analysis workflows are presented as operational implementations of ASUCA-Var. ASUCA-Var enhances forecasting in a wide range of validation indices. The major future improvements of ASUCA-Var include the introduction of the flow-dependent background-error and extension of the control variable to hydrometeors, which are expected to enhance the prediction accuracy of the operational regional model. [ABSTRACT FROM AUTHOR]

In the framework of the increasing competition and the danger of the pandemic global crises, it becomes necessary to boost the operational systems in the pharmaceutical industry, improve the activity related to resource processing, in order to ensure the stability of the organizations. The operational systems of pharmaceutical companies are changing every decade, together with changes in production management, focusing primarily on productivity and economies of scale, economy quality, production flexibility on the scheduling of production, customer, and then - to the economy of speed, innovation, and knowledge, skills and cooperation. One of the most important features of the operational systems is the operational strategy and its flexibility and adaptability because in the real business environment there are frequent changes in economic models, financial architecture, and production technologies. Therefore the operational strategy must take into account the current state of productive potential and the level and type of uncertainty, propose changes that will lead to the formation of future productive potential that will maintain or increase the level of competitiveness of the enterprise.

Combining optical and synthetic aperture radar (SAR) data for crop mapping has become a crucial way to improve classification accuracy, especially in cloudy and rainy areas. However, the acquisition of optical images is significantly unstable due to the influence of cloudy and rainy weather, which seriously restricts the application of this method in practice. To solve this problem, this study proposed an optical-SAR imagery-based rice mapping method which has the advantages of less dependence on optical images, easy operation and high classification accuracy. To account for the trait of sparse availability of optical images, this method only needs one clear sky optical image in the rice growth period and combined it with multi-temporal SAR images to achieve a high accuracy rice mapping result. Meanwhile, this paper also proposed a comprehensively multi-scale segmentation parameter optimization algorithm, which considers the area consistency, shape error and location difference between the segmented object and reference object, and adopts an orthogonal experiment approach. Based on the optical image, the boundaries of the parcel objects can be segmented, which were subsequently used to perform the object-oriented classification. The results show that the overall accuracy of the proposed method in Yangzhou City is 94.64%. Moreover, according to a random pick test, it is encouraging that the proposed method has strong robustness in response to the instability of the acquisition time of SAR images. A relatively high overall accuracy of 90.09% suggested that the proposed method can provide a reliable rice mapping result in cloudy and rainy areas.

This paper aims to demonstrate the research-to-application and operational use of numerical hydrologic and hydraulic modeling to (a) quantify potential flash flood risks in small urban communities with high spatial resolution; (b) assess the effectiveness of possible flood mitigation measures appropriate for such communities; and (c) construct an effective operational urban flash flood warning system. The analysis is exemplified through case studies pertaining to a small community with dense housing and steep terrain in Tegucigalpa, Honduras, through numerical simulations with a customized self-contained hydrologic and hydraulic modeling software. Issues associated with limited data and the corresponding modeling are discussed. In order to simulate the extreme scenarios, 24-h design storms with return periods from 1 to 100 years with distinctive temporal and spatial distributions were constructed using both daily and hourly precipitation for each month of the rainy season (May–October). Four flood mitigation plans were examined based on natural channel revegetation and the installation of gabion dams with detention basins. Due to limitations arising from the housing layout and budgets, a feasible plan to implement both measures in selected regions, instead of all regions, is recommended as one of the top candidates from a cost-to-performance ratio perspective. Numerical modeling, customized for the conditions of the case study, is proven to be an effective and robust tool to evaluate urban flood risks and to assess the performance of mitigation measures. The transition from hydrologic and hydraulic modeling to an effective urban flash warning operational system is demonstrated by the regional Urban Flash Flood Warning System (UFFWS) implemented in Istanbul, Turkey. With quality-controlled remotely sensed precipitation observations and forecast data, the system generates forcing in the hydrologic and hydraulic modeling network to generate both historical and forecast flow to assist forecasters in evaluating urban flash flood risks.

This study presents the drinking water supply system quality analysis in the context of the presence and distribution of eukaryotic assemblage, specifically the presence of algae in 10 specific sites (water treatment plants and fountains) from the Danube Delta. The analysis comes with a new approach based on stakeholders involvement and understanding of the new emerging problems generated by the presence of algae in the water supply system. In order to upgrade the water quality it is needed an improvement on the management of the water supply systems, with direct connection to the management of presence of algae or the occurrences of algal toxins in drinking water sources. Taking into consideration that Romania have no regulation dealing with the occurrence or the presence of algae or algal toxins in recreational or drinking water sources, it is important for all the stakeholders (local communities, local authorities, regional and national authorities etc.) to be informed about the the possibility of their occurrence in drinking or recreational waters, by creating a virtual space where they have access to the researches in this area.

In the framework of the increasing competition and the danger of the pandemic global crises, it becomes necessary to boost the operational systems in the pharmaceutical industry, improve the activity related to resource processing, in order to ensure the stability of the organizations. The operational systems of pharmaceutical companies are changing every decade, together with changes in production management, focusing primarily on productivity and economies of scale, economy quality, production flexibility on the scheduling of production, customer, and then - to the economy of speed, innovation, and knowledge, skills and cooperation. One of the most important features of the operational systems is the operational strategy and its flexibility and adaptability because in the real business environment there are frequent changes in economic models, financial architecture, and production technologies. Therefore the operational strategy must take into account the current state of productive potential and the level and type of uncertainty, propose changes that will lead to the formation of future productive potential that will maintain or increase the level of competitiveness of the enterprise. [ABSTRACT FROM AUTHOR]

The operational Australian Bluelink ocean forecast system is used to transform physical oceanographic observations into coherent analyses and predictions. These analyses and predictions form the basis for information services about the marine environment and its ecosystem, and can provide boundary data for weather predictions. Bluelink information services are available to marine industries (e.g. commercial fishing, aquaculture, shipping, oil and gas, renewable energy), government agencies (e.g. search and rescue, defence, coastal management, environmental protection), and other stakeholders (e.g. recreation, water sports, artisanal and sport fishing) who depend on timely and accurate information about the marine environment. This review highlights the last 15 years of Bluelink achievements delivering mesoscale (eddy-resolving) to sub-mesoscale and short- to medium-range (days to weeks) ocean forecasts and reanalyses. Key achievements include the development of a global ocean forecasting and reanalysis system, a relocatable ocean-atmosphere model and a littoral zone analysis and forecasting capability. Beyond the traditional short-term forecasting of physical ocean properties (temperature, salinity, surface height, currents, waves), marine activities such as water quality and habitat management as well as climate monitoring increasingly rely on operational oceanographic data and products. These are areas of active research of the Bluelink team in collaboration with national and international partners. [ABSTRACT FROM AUTHOR]

• Presented an unique HSR typology based on operational characteristics more independently of infrastructure models. • HSR operational system introduces a strongly differentiate connectivity between HSR European countries. • Not only economic attributes generate strong connection by international services; also cultural ones. • Infrastructural HSR spatial pattern is still designed for national services in Europe. [ABSTRACT FROM AUTHOR]

The three-wheeler, a Sri Lankan form of paratransit, is a popular and important mode of transport in Sri Lankan cities due to largely insufficient public transport systems. However, knowledge of the three-wheeler industry including the role of drivers' groups and the effect of these groups' social capital related factors on the driver's life satisfaction is scarcely available. Thus, the objectives of this study are to clarify the actual condition of the industry and to identify the social capital related factors that affect drivers' life satisfaction in three cities in Sri Lanka. To this end, extensive interviews were conducted and revealed that national and local governments do not control the numbers or management of three-wheeler drivers and vehicles, but they do receive rent for using public road space for parking. In order to determine the effect of social capital factors, including working conditions and societal trust levels, on three-wheeler drivers' life satisfaction, we developed an ordered logit model based on questionnaire surveys in three target cities. In addition, the differences among the cities examined regarding provincial policies for three-wheelers, the percentage of drivers who have other jobs, and relationships between drivers' societies were revealed. As a result of the analysis, we identified differences between drivers based in the three cities regarding the social capital and work-related variables that have the greatest impact on their life satisfaction. In particular, we found that drivers based in the city of Kandy emphasized general social capital variables over work conditions and salary, but the opposite was obtained for the cities of Colombo and Moratuwa.

The paper presents a new method of design and construction aimed at developing a system that helps to prevent accidents involving demolition robot operators. The method is based on a study of user needs and was developed in accordance with Design Thinking methodology. This study provides a theoretical review of designing processes and methodologies, including conceptual design, and explores the implementation of the proposed method in the designing process for a Human–Machine Interface (HMI) accident prevention system. An in-depth study of user needs combined with an analysis of the operational system, both of which followed the stages in the proposed method, as well as with experimental tests on a small remote control demolition robot, inspired the development of an operator-controlled HMI system. The theoretical review concerns non-haptic feedback devices, which can be implemented in the demolition robot remote control or in operator safety equipment. Experimental research helped to determine the data necessary to develop an HMI system that continuously uses information from sensors installed on the machine. The paper also addresses issues related to the implementation of the HMI interface in order to avoid failures resulting from robot misuse and to protect the operator from any hazards caused by potential accidents. This paper emphasizes the importance of the connection between man and machine to overcome the lack of direct information flow in the case of mechanical operation. [ABSTRACT FROM AUTHOR]

In this work the derived occurrence probability of solar energetic particle (SEP) events (i.e. proton events measured at Earth’s position) and their peak fluxes and total fluences depending on coronal mass ejection (CME) parameters, i.e. linear speed (V) and the angular width (AW) are presented. A new SEP catalogue with associated CME data from 1997 to 2013 is utilized. It is found that the SEP probability strongly depends on the CME speed and the angular width as follows: The highest association (72.70%) is obtained for the full halo CMEs with V ≥ 1500 km s−1 and the lowest association (0.7%) is found for the non halo CMEs with 400 km s−1 ≤ V ≤ 1000 km s−1. The SEP occurrence probabilities are different as much as 26 times according to the CME speed (V), comparing fast versus slow CMEs and 44 times according to the AW, comparing halo to non halo CMEs. Furthermore, linear regressions of the proton peak flux and integral fluence at several integral energy channels (E > 10 MeV, E > 30 MeV, E > 60 MeV, E > 100 MeV) were obtained. Our results, were used to build a module of an operational forecasting tool (i.e. FORecasting Solar Particle Events and Flares – FORSPEF, http://tromos.space.noa.gr/forspef/). This module performs nowcasting (short term forecasting) of SEP events using near real-time CME identifications obtained from CACTus (http://sidc.oma.be/cactus/). The outputs offered by the operational module of the tool to the end user (textural, pictorial, archived data) are presented. Finally, the validation of the system, in terms of archived data is described, in terms of categorical scores (Probability of Detection – POD and a False Alarm Rate – FAR).

Noxious atmospheric releases may originate from both accidents and malicious activities. They are a major concern for public authorities or first responders who may wish to have the most accurate situational awareness. Nonetheless, it is difficult to reliably and accurately model the flow, transport, and dispersion processes in large complex built-up environments in a limited amount of time and resources compatible with operational needs. The parallel version of Micro-SWIFT-SPRAY (PMSS) is an attempt to propose a physically sound and fast response modelling system applicable to complicated industrial or urban sites in case of a hazardous release. This paper presents and justifies the choice of the diagnostic flow and Lagrangian dispersion models in PMSS. Then, it documents in detail the development of the parallel algorithms used to reduce the computational time of the models. Finally, the paper emphasizes the preliminary model validation and parallel performances of PMSS based on data from both wind tunnel (Evaluation of Model Uncertainty) and in-field reduced-scale (Mock Urban Setting Test) and real-scale (Oklahoma City) experimental campaigns. [ABSTRACT FROM AUTHOR]

• DHI-GHM provides valuable hydrological information for data scarce areas. • DHI-GHM allows for hourly simulations, as often as new forecasts are available. • Physical based parameter estimation gives informed start for calibration activities. • DHI-GHM produces comparable results in world's main basins to other GHMs. • DHI-GHM is an operational system ideal to support decision-making. An operational global hydrological model (DHI-GHM) has been developed that provides historical, real-time, 10-day and seasonal forecast simulations at the global scale. DHI-GHM is comprised of a distributed gridded rainfall-runoff model with a spatial resolution of 0.1° and an agile kinematic routing model that moves water between model grid cells and sub-catchments and in the river system. Model output includes gridded hydrological variables, such as soil moisture content and different runoff components, and discharge at more than 1 million river points globally. DHI-GHM uses a novel parameterization scheme, where global data products of land surface physical characteristics are used to establish relations with model parameters, and thus DHI-GHM does not rely on local discharge data for model calibration. Multiple forcing datasets were tested, and the combination of ERA5 precipitation and Priestley-Taylor potential evaporation yielded the overall best results with a median KGE of 0.51 and average water balance error of 0.78% based on data from 1667 discharge stations worldwide. The model results and the operational system are particularly relevant for organizations with national, regional, or global scope who need information on large areas at once and for data scarce areas or projects without resources for local scale models. [ABSTRACT FROM AUTHOR]

Reliable and rapid real-time prediction of likely oil transport paths is critical for decision-making from emergency response managers and timely clean-up after a spill. As high-resolution hydrodynamic models are slow, operational oil spill systems generally rely on relatively coarse-grid models to provide quick estimates of the near-future surface-water velocities and oil transport paths. However, the coarse grid resolution introduces model structural errors, which have been called “geometric uncertainty”. Presently, emergency response managers do not have readily-available methods for estimating how geometric uncertainty might affect predictions. This research develops new methods to quantify geometric uncertainty using fine- and coarse-grid models within a lagoonal estuary along the coast of the northern Gulf of Mexico. Using measures of geometric uncertainty, we propose and test a new data-driven uncertainty model along with a multi-model integration approach to quantify this uncertainty in an operational context. The data-driven uncertainty model is developed from a machine learning algorithm that provides a priori assessment of the prediction’s confidence degree. The multi-model integration generates ensemble predictions through comparison with limited fine-grid predictions. The two approaches provide explicit information on the expected scale of modeling errors induced by geometric uncertainty in a manner suitable for operational modeling.

The paper presents a new method of design and construction aimed at developing a system that helps to prevent accidents involving demolition robot operators. The method is based on a study of user needs and was developed in accordance with Design Thinking methodology. This study provides a theoretical review of designing processes and methodologies, including conceptual design, and explores the implementation of the proposed method in the designing process for a Human–Machine Interface (HMI) accident prevention system. An in-depth study of user needs combined with an analysis of the operational system, both of which followed the stages in the proposed method, as well as with experimental tests on a small remote control demolition robot, inspired the development of an operator-controlled HMI system. The theoretical review concerns non-haptic feedback devices, which can be implemented in the demolition robot remote control or in operator safety equipment. Experimental research helped to determine the data necessary to develop an HMI system that continuously uses information from sensors installed on the machine. The paper also addresses issues related to the implementation of the HMI interface in order to avoid failures resulting from robot misuse and to protect the operator from any hazards caused by potential accidents. This paper emphasizes the importance of the connection between man and machine to overcome the lack of direct information flow in the case of mechanical operation.

This work assesses the performance of an operational wave system in the Mediterranean Sea by comparing computed data with measurements collected at different water depths. Nearshore data measurements were collected through a field experiment carried out at Poetto beach (Southern Sardinia, Italy) during spring 2017. In addition to coastal observations, we use intermediate and deep water wave data measured by two buoys: one situated North-West of Corsica and the other in the Gulf of Lion. The operational wave system runs once a day to predict the wave evolution up to five days in advance. We use a multi-grid approach in which a large grid extends over the entire Mediterranean basin and a fine grid covers the coastal seas surrounding the islands of Sardinia and Corsica. The comparison with measurements shows that the operational wave system is able to satisfactorily reproduce the wave evolution in deep and intermediate waters where the relative error of the significant wave height is 17%. The error exceeding 25% in coastal waters suggests that the use of a finer grid and the coupling with an atmospheric model able to catch local effects is advisable to accurately address nearshore wave processes driven by coastal wind forcing.