Search

The widespread adoption of electric vehicles (EVs) necessitates effective end-of-life management strategies for their battery packs. When pursuing a recycling strategy to recover valuable materials such as nickel, manganese, cobalt, and lithium, the first step in most cases is to dismantle the battery at least down to module level. The state-of-the-art disassembly of EV battery packs relies on domain knowledge and is carried out manually for the most part. The potential hazards inherent in the dismantling process and increasing numbers of end-of-life batteries, coupled with a shortage of skilled workers, call for a safer and more efficient approach to dismantling than is currently the case. However, due to the high variety of end-of-life battery packs that return to recycling companies and their high system complexity, fully automating the disassembly process is not economically feasible. Therefore, the paper introduces an approach to extract and transfer domain knowledge from human experts to an accessible and structured information model. This model is intended to serve as the foundation for the development of disassembly assistance systems capable of aiding human operators during manual disassembly tasks and, in the long term, enabling the automation of critical disassembly steps. Furthermore, a theoretical concept for a disassembly station is proposed that allows a multi-faceted data collection process by providing a human-machine interface and multi-sensory equipment. This process encompasses detailed analysis of battery components, manual disassembly procedures, and expert insights. It aims at integrating, categorizing, and formalizing the collected data into a machine-readable format that captures both the procedural and semantic aspects of battery disassembly and enables the digital representation of the product and process. [ABSTRACT FROM AUTHOR]

The reliability of software interfaces has become increasingly recognized as a crucial factor impacting the quality, manageability, and efficiency of various software systems. Traditional approaches to software reliability assessment often overlook interface-level reliability, focusing primarily on system-level metrics. However, the growing emphasis on user-centered design has amplified the demand for reliable and user-friendly software interfaces. This paper introduces a novel information model for evaluating the reliability of software interface design, which is crucial for enhancing assessment approaches in software engineering. The proposed model integrates usability testing and reliability attributes early in the software development life cycle (SDLC), particularly in the interface design phase, to enhance the system's overall performance and user experience. The paper describes the current state of models and methods used to evaluate software reliability at the interface design level, outlining the problems that the proposed new model aims to solve. It presents the theoretical basis for the model and provides information on its integration into the SDLC. Analytical examples are used to corroborate the proposed model, demonstrating its usefulness in the early project stages and its ability to improve software interface reliability and practicality. The paper also discusses challenges in adoption and suggests areas for future theoretical and empirical research. By developing a more comprehensive perspective on software quality, this work paves the way for practical, reliable, and user-friendly interfaces across various software domains. [ABSTRACT FROM AUTHOR]

The collaboration among autonomous mobile robots (AMRs), including unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and/or unmanned surface vehicles (USVs), significantly enhances their capabilities by enabling them to tackle more complex tasks exceeding those of individual robots. However, to fully exploit this collaboration, a common understanding of exchanged information—referred to as semantic interoperability—is crucial. Achieving semantic interoperability between these robots requires a deep understanding of relevant information and its underlying structure. To address this challenge, this paper presents a platform- and technology-independent information model developed specifically for AMRs. This model aims to facilitate collaboration by structuring information in a way that ensures semantic interoperability. The paper outlines the model's development process, beginning with a structured consolidation of information from pertinent scientific literature, resulting in a foundational framework for representing knowledge and semantics within the domain of AMRs. The practical application of the information model is demonstrated through a use case involving multiple AMRs. Additionally, the paper provides insights into the employed methodology, emphasizing the significance of systematic literature reviews and collaboration with practitioners to refine and validate the model. It also discusses theoretical and practical implications, addressing potential limitations encountered during the research. [ABSTRACT FROM AUTHOR]

In Wire Arc Additive Manufacturing (WAAM), variable layer heights enable the non-parallel or non-planar slicing of parts. In researching variable layer heights, this paper documents printing strategies for a reference geometry whose key features are non-orthogonal growth and unsupported overhangs. The complexity of 3D printing with welding requires parameter optimization to control the deposition of molten material. Thus, 3D printing with welding requires the precise deposition of molten material. Currently, there is no standard solution for the customization of process parameters and intelligent collection of data from sensors. To address this gap in technology, this research develops an Internet of Things (IoT)-enabled, distributed communication protocol to control process parameters, synchronize commands, and integrate device data. To intelligently collect sensor information, this research creates a query-able database during pre-planning and production. This contributes to fundamental research in WAAM by documenting strategies for printing variable layer heights, the customization of control parameters, and the collection of data through a WAAM Information Model (WIM). [ABSTRACT FROM AUTHOR]

The equipment for coal mine fully mechanized working faces comes from different manufacturers, with inconsistent interfaces, different data systems and business logic, resulting in data barriers and slow data exchange between systems. Based on the industrial Internet architecture, an intelligent fully mechanized mining technology architecture including equipment layer, access layer, edge layer, PaaS layer and application layer is proposed. Based on this architecture, coal mine fully mechanized mining equipment is treated as the overall data object, and a method for constructing an information model of coal mine fully mechanized mining equipment is designed. Four key elements and modeling rules, including attributes, methods, events, and alarms are defined to achieve seamless communication between various physical entities and heterogeneous systems. This means defining, describing, and associating information resources of fully mechanized mining equipment, providing a complete and unified data object expression, description, and operation model. A modeling element optimization mechanism based on importance and semantic similarity is proposed to address the problem of excessive attribute elements in the information model of fully mechanized mining equipment. A fully mechanized mining equipment information model for the 81004 working face of No.1 Mine of Huayang New Materials Technology Group Co., Ltd. is established using the above method. The operation status of the electric motors of the fully mechanized mining equipment is evaluated. The results show that based on this model, all electric motors in the working face could be monitored for starting times in a short period of time, multiple motor equipment starting power balance, and the operating efficiency. Analysis results are generated to provide data support for decision-making work.

Purpose: of the article is to develop a model of the value system of Russian youth, which can form the basis for the formation of the orientations of young people necessary for the state, contributing to the sustainable development of the Russian Federation. Methods: the article used both traditional methods of scientifi c analysis and methods of Bayesian intelligent measurement methodology used in conditions of uncertainty, inaccuracy and incompleteness of data characteristic of social and socio-economic systems. Results: in the presented study, the extensible hierarchical information model of the value system of Russian youth has been developed. The methodology for processing questionnaire data has been developed, the results of which are presented on numerical and linguistic scales, which makes it possible to take into account the uncertainty of the information received. According to the results of the survey of university students of 10 subjects of the Russian Federation aged 17 to 30 years, a total of 1816 people obtained the values of factors characterizing the value world of Russian youth, which allowed her to form her portrait. Some value factors of young people of the Tula region are evaluated and analyzed. Conclusions and Relevance: the proposed model and methodology for processing personal data allows us to create the adequate holistic portrait of Russian youth in modern economic conditions. The formation of two groups of young people characterized by unfavorable and favorable value attitudes towards Russian society has been revealed, which in the future may lead to a confl ict of social and economic interests, thereby negatively aff ecting the pace of economic growth and sustainable development of the state. In order to reduce internal tension between youth groups and the formation of values inherent in Russian society, measures at the federal and regional levels are proposed.

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The soil three-dimensional (3D) pore structure information model has become a new hotspot in the research of cross-scale disposal of information such as ecology, engineering, and geology. It can solve problems such as the intelligent evaluation of ecological water–soil–air–plant feedback, intelligent risk control of foundation compression deformation, and multiscale intelligent disaster prediction and prevention. However, the current soil 3D pore structure model primarily draws on the global one-time static generation in simulation software, leading to low reliability, low stability of multiple generations, poor variability, difficulty in real-time transformation, high consumption of computing resources, and long generation time, making it challenging to meet the requirements of the rapid processing of information models. Therefore, this study adopts the 3D Drawing Protocol (WebGL) technology and implements the scaling, rotation, and translation transformation of 3D pore structures based on the principle of dynamic affine transformation. The random generation and distribution of pores are realized using the improved Monte Carlo method, and the loading response efficiency of the system is optimized. The dynamic interactive operation of arbitrary increasing and decreasing of pore model is realized using the ray and plane intersection detection principle. Finally, this information system established a visual correlation between the content and reaction time of water-retaining agents and soil porosity and pore distribution through tests on the impact of water-retaining agents on soil pore changes. The information system achieved the real-time tracking of soil pore changes under the action of water-retaining agents. This research solves the problems of static and low generation efficiency of the soil mesopore structure in traditional models and realizes the real-time characterization and visualization of dynamic changes and the distribution of the soil pore structure under the influence of external conditions, which can provide an intuitive visualization platform for mesogeological structure research.

The evaluation of landslide susceptibility plays a crucial role in preventing the risks associated with landslides and debris flows, providing valuable insights for the effective prevention and mitigation of geological hazards. However, there is limited research on high-altitude areas. Therefore, this study chose the western Tibetan Plateau as the study area, a representative area known for its susceptibility to landslides and high attitudes. In this study, seven factors were identified based on research objectives. Information value (IVM), weight of evidence (WOE), information value logistic regression (IVM-LR), weight of evidence logistic regression (WOE-LR), information value multi-layer perceptron (IVM-MLP) and weight of evidence multi-layer perceptron (WOE-MLP) were selected and compared for landslide susceptibility. The percentage of disaster area included in each risk level, the AUC value and the ROC curve were used to evaluate the accuracy of the results. The ROC curves of the results were close to the upper–left corner and the AUC values exceeded 0.85, an indication that all results were highly accurate. Moreover, the percentage of disaster area included for each risk showed an upward trend regarding susceptibility. The results indicated that the hybrid model exhibited superior performance in assessing landslide susceptibility at high altitudes. Overall, the results showed great significance regarding disaster prevention and mitigation measures of local governments. [ABSTRACT FROM AUTHOR]

This study focuses on landslide susceptibility assessments in Luoping County, where 9 evaluation factors, including engineering rock group, slope, slope aspect, elevation, undulation, curvature, landform type, distance from rivers, and distance from fault, were selected as the research variables. After conducting collinearity diagnosis and correlation analysis, the information value method was applied to calculate the information value for each classification level of the evaluation factors. Quantitative weights for each evaluation factor were determined using the AHP and logistic regression methods, leading to the construction and comparison of three susceptibility evaluation models: information value, and weighted information value, and information-logistic regression coupled model. The results were categorized into four grades -- none, low, medium, and high – using the GIS-based natural breakpoint method, and their accuracy was validated using ROC curves. The results show that the AUC values of the three evaluation models were 0.757, 0.723 and 0.852 respectively, with the information-logistic regression coupled model demonstrating the highest accuracy. Moreover, the model results were in good agreement with the distribution of landslide geological disaster points. The respective areas (classification ratios) for the none, low, medium, and high categories were 771.1 km2 (25.55%), 836.6 km2 (27.73%), 864.36 km2 (28.64%), and 545.94 km2 (18.08%).

Introduction. The significance of road construction both in investment and construction activity and in the national economy in general is characterized. The specificity of investment and construction activity management, including road construction, which has a multi-level project approach in its basis, is noted.Materials and methods. The research methods are a review of information sources, analysis of the project approach and the basics of road construction management, the usage of a systematic approach with the allocation of project management levels, generalization of professional experience in the service of the state customer, comparative analysis of the material with the identification of problems and trends in the development of project management in road construction.Results. The macro level of project management is considered, because, according to the country’s development goals, the development of road construction is included in the system of national projects. The problems of the management of the national projects, including “Safe high-quality roads” and “Comprehensive plan for modernization and expansion of the trunk infrastructure” are identified. The problems of the state customer practice in the sphere of road construction are analyzed and the specifics of the micro-project level of road construction are defined. The express review of the directions of project management improvement in road construction is presented. The measures of project management improvement are proposed at the inter-branch level, which will be effectively reflected at the micro level of specific road construction projects.Conclusions. Based on the results of the analytical review, the key positions of methodological support for effective project management in road construction were identified: optimization of the value chain of investment and construction projects; consolidation of cost, schedule and quality management parameters into the project model; assessment and management of the moment efficiency of the investment and construction project; use of the synergetic effect of system components of project cost management; implementation of adaptive management of investment and construction projects, precedent management, production modelling and controlling system.

With the development of highways, new technologies should be continuously introduced to improve highway traffic safety. Digital twin (DT) has been an emerging field of research in recent years. To develop a digital twin management system, a data model is essential. In the field of highway operational risk management (HORM), however, the development of data models is still in its infancy. Motivated by the concept of linked data, in this paper, we attempt to propose an information model for HORM. The main achievements of this paper include data architecture, identification and classification code methods, data interaction method, and the developed system. Based on data needs analysis, the highway information model architecture for risk management is defined as five layers: basic highway products, traffic sensors and equipment, traffic rules, traffic flow, and weather. Furthermore, according to the concepts of semantic data, these five layers can be classified into three categories: highway product data, topology data, and sensor data. Although the Industry Foundation Classes (IFC) standard and Brick schema were first proposed and applied in the building domain, some of their entities and relationships can also be applied to highways. To this end, we defined some new classes, a specific ontology, and an integrated framework for HORM. Finally, a case study was carried out. Applying such information model to highways has broad potential. It changes the file-based exchange method to the data-based one, which can promote highway data exchange and applications. The proposed information model could be of great significance for HORM.

Copyright of Railway Standard Design is the property of Railway Standard Design Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Railway Standard Design is the property of Railway Standard Design Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Railway Standard Design is the property of Railway Standard Design Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Geological Hazard & Control is the property of China Institute of Geological Environmental Monitoring (CIGEM) Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

When using machine learning models for landslide susceptibility evaluation, the non-landslide sample points are usually selected randomly outside the landslide influence area, leading to a certain error. To improve the accuracy of landslide susceptibility evaluation, this paper couples the self-organizing map (SOM) neural network, information (I) model, and support vector machine (SVM) model, and proposes a SOM-I-SVM model-based method of landslide susceptibility evaluation, comparing with K-means clustering to verify the reliability of this model. The Maojian District of the city of Shiyan is taken as an example, and seven factors of the distance from water system, slope, rainfall, distance from structure, relative height difference, distance from road, stratigraphic lithology are selected by correlation and importance analyses of environmental factors to establish a landslide susceptibility evaluation system. Based on these, the graded information values of each factor are calculated and used as input variables for landslide susceptibility evaluation. The SOM neural network and K-means clustering are used to select non-landslide samples, and the sample data set is substituted into the I-SVM model to predict landslide susceptibility. The prediction accuracies of the four models, SVM, I-SVM, KMeans-I-SVM and SOM-I-SVM, are compared, and the area under the ROC curve (AUC values) are 0.82, 0.88, 0.90 and 0.91, indicating that the SOM-I-SVM model can effectively improve the accuracy of landslide susceptibility prediction.

In Wire Arc Additive Manufacturing (WAAM), variable layer heights enable the non-parallel or non-planar slicing of parts. In researching variable layer heights, this paper documents printing strategies for a reference geometry whose key features are non-orthogonal growth and unsupported overhangs. The complexity of 3D printing with welding requires parameter optimization to control the deposition of molten material. Thus, 3D printing with welding requires the precise deposition of molten material. Currently, there is no standard solution for the customization of process parameters and intelligent collection of data from sensors. To address this gap in technology, this research develops an Internet of Things (IoT)-enabled, distributed communication protocol to control process parameters, synchronize commands, and integrate device data. To intelligently collect sensor information, this research creates a query-able database during pre-planning and production. This contributes to fundamental research in WAAM by documenting strategies for printing variable layer heights, the customization of control parameters, and the collection of data through a WAAM Information Model (WIM).

Today, installation works occupy a significant amount of all construction works. At the same time, the efficiency of construction processes largely depends on the availability of technological equipment, its ergonomics, and dependence on accompanying construction processes. Improvement of mechanized technological equipment in practice allows to optimize the relevant construction process and obtain an economic effect [1]. Increasing the level of mechanization of construction processes is an urgent engineering task that allows improving the technological process on the construction site . It is especially relevant to develop mechanized modules that allow to improve a certain segment of the construction process, in particular to the possibility of using automated control systems. The process of improving mechanized technological equipment, as a rule, is determined by the conducted research aimed at determining the priority directions for improving such equipment and identifying potential markets, partners and competitors.

The digital twin workshop contains a vast quantity of heterogeneous data from multiple sources, such as the historical state of workshop equipment, which is essential for analyzing implicit problems and bottlenecks in manufacturing tasks. Nevertheless, the current unidirectional and irreversible time flow of the digital twin workshop makes it difficult to optimize workshop productivity using historical data. This paper proposes a scene equipment saving and loading method for the digital twin workshop to address this issue. The initial steps involve defining a workshop information model which represents multiple pieces of workshop equipment in the virtual space and the content of the data it covers. This model stores data for each object type on the workshop using distinct data structures; a workshop element data saving and loading method is proposed, which can save the historical scene equipment data of the digital twin workshop and load the saved data into the digital twin software; finally, a case study is conducted to determine the data compatibility, the saving and loading efficiency, and the system's ability to save and load actual workshop scenes. The results demonstrate that this method can efficiently save and load scene equipment data on the workshop, enabling workshop administrators to identify problems and bottlenecks in historical manufacturing tasks and then take steps to increase workshop productivity. [ABSTRACT FROM AUTHOR]

The translational research community, in general, and the Clinical and Translational Science Awards (CTSA) community, in particular, share the vision of repurposing EHRs for research that will improve the quality of clinical practice. Many members of these communities are also aware that electronic health records (EHRs) suffer limitations of data becoming poorly structured, biased, and unusable out of original context. This creates obstacles to the continuity of care, utility, quality improvement, and translational research. Analogous limitations to sharing objective data in other areas of the natural sciences have been successfully overcome by developing and using common ontologies. This White Paper presents the authors' rationale for the use of ontologies with computable semantics for the improvement of clinical data quality and EHR usability formulated for researchers with a stake in clinical and translational science and who are advocates for the use of information technology in medicine but at the same time are concerned by current major shortfalls. This White Paper outlines pitfalls, opportunities, and solutions and recommends increased investment in research and development of ontologies with computable semantics for a new generation of EHRs. [ABSTRACT FROM AUTHOR]

This paper presents a method for generating urban blocks. Urban blocks are the basis from which urban processes are modelled and assessments of the current situation are made. The proposed method allows with the additional land use data, clustering algorithms and computational operations to obtain a more complete representation of urban blocks. The resulting refined blocks are more suitable for modelling and assessing processes of urban environmental change. Huge blocks (most often encountered outside the city) are divided by the cluster of buildings into smaller blocks that are connected to the road network, which allows them to be considered as full-fledged blocks and not only as a group of buildings. [ABSTRACT FROM AUTHOR]

The information value method is widely used in predicting the susceptibility of geological disasters. However, most susceptibility evaluation models assume that the weight of each influencing factor is equal, which is inconsistent with the actual situation. Therefore, this paper studies the optimization effect of weight calculation method on the information value model. Engineering disturbance disasters are developing in the Himalayan alpine valley in southeastern Tibet. First of all, this paper takes this as the research object and builds a database of engineering disturbance disasters in southeast Tibet through long-term on-site investigation. Then, the relationship between the influencing factors such as slope, aspect, relief, elevation, engineering geological rock formation, rainfall, temperature, and seismic peak acceleration and the distribution of engineering disturbance disasters is analyzed. Finally, the principal component analysis method and logistic regression method are employed to calculate the weight coefficients. Moreover, the susceptibility of engineering disturbance disasters is predicted using the information value model (IV-Only), as well as two weighted information value models (PCA-IV and LR-IV). In addition, the accuracy of these three susceptibility evaluation models is assessed based on two evaluation indexes. The results show that: compared with the equal weight method and the principal component analysis method, the logistic regression method has the highest accuracy. According to the weight coefficient, the control factors of engineering disturbance disasters in the Himalayan alpine canyon area are determined to be slope, aspect, rainfall, and elevation. The research results provide a reference method for the optimization of susceptibility evaluation model. [ABSTRACT FROM AUTHOR]

In China, the majority of mountainous regions are characterized by complex topography and a delicate, sensitive geological environment. These areas, which exhibit insufficient infrastructure and widespread irrational human engineering activities, are often susceptible to geological hazards such as slope instability and soil mass movements. These geological hazards pose substantial threats to human lives and property, hindering the progress of mountainous areas. Therefore, conducting research on evaluating the vulnerability of slope rock and soil mass movement geological hazards (hereinafter referred to as geological hazards) is of utmost importance for hazard prevention, emergency management, and economic advancement in these regions. This study focuses on Xuanwei City and selects eight factors for evaluation, including elevation, gradient, slope aspect, normalized vegetation index, stratigraphic lithology, distance from faults, distance from rivers, and distance from roads. These factors are chosen based on a comprehensive analysis of the spatial and temporal distribution of geological hazards and hazard incubation conditions. Two paired models, the deterministic coefficient model + logistic regression model (CF+LR) and the information quantity model + logistic regression model (I+LR), were employed to assess the study area quantitatively. The performance of these models was assessed by employing receiver operating characteristic (ROC) curves and calculating the corresponding area under curve (AUC) values. The results indicate that: (1) The AUC values for the coupled CF+LR and I+LR models are 0.799 and 0.772, respectively. These results indicate that both models provide an objective and reliable assessment of the vulnerability to geological hazards, specifically slope rock and soil mass movements, in the study area. (2) Based on the CF+LR model calculations, the geological hazard susceptibility of Xuanwei City can be categorized into four zones: extremely high susceptibility (6.09%), high susceptibility (31.08%), medium susceptibility (32.26%), and low susceptibility (30.57%). (3) The CF+LR model more accurately represents the evaluation results and offers a strong reference value. [ABSTRACT FROM AUTHOR]

While digitalization is expected to bring benefits in the area of land use planning, it is also redefining planning practices and entire planning cultures. Limited research exists on this digital transformation, and this article aims to narrow this gap through an empirical case study. In Finland, there is an ongoing transition towards information model (IM)-based planning, driven by public government development programs. Its principal focus is to achieve national-level interoperability of plan data. A harmonized IM for local master and detailed plans has recently been developed for use in municipal urban planning in the future. In addition, a national information system (IS) for built environment data is currently being developed. In this article, the perspectives of Finnish urban planners towards the national IM and IM-based planning were examined through a questionnaire. The results indicate that IM-based planning has a strong impact not only on planning outcomes (i.e., land use plans) but also on the planning context (e.g., planning practices and the planners themselves, software and information systems (ISs), and planning law). We argue that the high expectations set for IM-based planning will not be met without paying attention to the viewpoints of planners, planning practices, and the changes to planning culture in a wider sense. In addition to the technological aspects, the focus should also be on the social and contextual elements of planning.

Water conservancy equipment (WCE) has a large amount of information, structural heterogeneity and complex relationship leads to the difficulty of semantic interoperability in smart water conservancy. To overcome this issue, we propose the WCE information interaction dimension theory, modeling process and instancing method. First, we analyze the smart water conservancy ontology and information factor, and propose semantic information interaction dimension structure of water conservancy Ontology. Second, we construct the network information model structure of water conservancy, through the relationship degree, a tree model which can realize semantic expression and interoperability is formed through the dimensionality reduction of the model. Third, the component attribute set hierarchical relationship architecture water conservancy information model is established, which use XML language to describe this model. Moreover, the three types of instancing methods are proposed. Through OPC unified architecture (OPC UA) technology, water conservancy information model can implement semantic interoperability. The experimental show that the proposed method of semantic information modeling and semantic interoperability of WCE is feasible, and obvious advantages of complete semantic interoperability than in the model architecture, semantic structure and technical implementation.

ABSTRACTThis paper develops a pattern that guides manufacturing system designers and engineers in the identification of requirements and solutions throughout the systems engineering lifecycle. The presented design pattern guides decision-making about the requirements and solutions related to the design and operation of manufacturing plants, lines, cells, and workstations. The research presented in this paper builds on a prior version of the Manufacturing System Design Decomposition, Version 9.2 (MSDD 9.2), which established the requirements and solutions for making effective manufacturing system design decisions. By incorporating decision-centric design and model-based systems engineering tools, MSDD 9.2 is expanded to Manufacturing System Design Decomposition, Version 10.0 (MSDD 10.0) which offers innovative design capabilities in being able to capture and relate all applicable manufacturing system design information as a single source of truth. The design pattern seeks to guide the objective evaluation and introduction of new manufacturing systems, technologies, and products for the manufacturing enterprise.

In this paper, taking debris flow in Dongchuan as the research object, nine influence factors are chosen as the selected indices, including the elevation, slope, aspect, relief, curvature, engineering rock group, distance to faults, distance to faults rivers, and land use types, sample data from 144 debris flows in the study area are used to establish the Dongchuan debris flow susceptibility assessment system. Based on the information model and GIS platform, the information vaule of each factor classification is calculated, and the natural discontinuity method is used to divide the debris flow susceptibility into 4 levels: extremely high-prone areas, high-prone areas, medium-prone areas, and low-prone areas in the study area. The results show that the number of debris flow disasters in the extremely high and high-risk areas in the study area accounted for 94.44%, and the AUC value was 0.876, indicating that the selection of evaluation indicators was reasonable, and the information model was suitable for the evaluation of debris flow susceptibility in Dongchuan.

Copyright of Hydrogeology & Engineering Geology / Shuiwendizhi Gongchengdizhi is the property of Hydrogeology & Engineering Geology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Mass customization demands a wide range of product variants being provided by the manufacturer in a short time. To respond to that, companies embrace approaches such as product platforms and modularization. This impacts the product development process (PDP), especially at the design stage. A major concern is the definition of component and system interfaces since these become essential inputs for later stages. Yet, a suitable method to describe the interfaces, represent them, and share them within a product model is still elusive. Since the information enclosed in the interface is multi-faceted, ranging from geometry to function or kinematics, it can be adjusted or enriched in every stage of product development. Then, it is crucial to understand how this information can support product preparation and planning, as well as how it can be reused in product design or redesign. Thus, this work aims to assess the extent to which these factors were considered in the assembly domain. The study started by presenting current practices on representing the interfaces in the product design and continued by exploring how the information on the interfaces can be used for assembly planning. Subsequently, it proposed a way to represent the knowledge enclosed in the interface and concluded by explaining how this knowledge can be exploited by different stakeholders to improve the process planning and the overall assembly system. A case study shows the application of the proposed approach. Overall, the results showed the benefits of a better representation of interfaces in product design, specifically for the assembly domain, aiming to contribute to defining a strategy for knowledge reuse in manufacturing. [ABSTRACT FROM AUTHOR]

The potential of energy saving can be effectively realized by combining its tools with the methods of information modelling of the life cycle of a capital construction object, which determined the problem statement of this study. In this paper, the dependence of peak and average power of heating systems necessary to maintain comfortable temperature in the building on the climatic characteristics of the construction region is determined. For the dome part, the surface of which is realized in the form of a periodic sequence of elementary cells, the dependences of heat losses through the dome part of the building on the characteristics of the cells are calculated. The parameter describing the energy efficiency of space-planning solutions is determined, and its dependences on the geometric and thermophysical properties of enclosing structures are calculated. The total energy efficiency of the space-planning solution for the heating period is calculated. It is proved that energy optimization of the life cycle is possible only on the basis of heat flows through the surface of enclosing structures, linear and point thermally stressed elements (TSE) arising at the boundary of the dome part, the boundaries of the elementary cells filling the dome and on the structural elements of the triangular hemisphere or stratodesic dome. The formulated algorithms for describing all energy flows through the enclosing structures of the building made it possible to build an information model of the energy and economic efficiency of the life cycle of a capital construction object. The constructed vector information model of the energy and economic efficiency of the life cycle of a capital construction object allows solving the following practical tasks: to determine the dependence of energy costs on climatic parameters; to optimize the composition, terms of implementation and sequence of technical measures aimed at increasing the heat-insulating properties of enclosing structures and thermally stressed elements; to determine the profitability of these measures and their payback period.

In this paper,a geological disaster early warning model is constructed based on GIS,and a susceptibility evaluation system is constructed by using GIS spatial information system to obtain seven influencing factors,including slope,topographic relief,slope shape,rock and soil mass type,geological structure,land use type and vegetation coverage rate.The information quantity value of each influencing factor is determined based on the information model method.At the same time,the hidden points of geological disasters in research area are superimposed and the prone zones are divided to provide reference for the prediction and prevention of geological disasters in this area.

The evaluation of landslide susceptibility plays a crucial role in preventing the risks associated with landslides and debris flows, providing valuable insights for the effective prevention and mitigation of geological hazards. However, there is limited research on high-altitude areas. Therefore, this study chose the western Tibetan Plateau as the study area, a representative area known for its susceptibility to landslides and high attitudes. In this study, seven factors were identified based on research objectives. Information value (IVM), weight of evidence (WOE), information value logistic regression (IVM-LR), weight of evidence logistic regression (WOE-LR), information value multi-layer perceptron (IVM-MLP) and weight of evidence multi-layer perceptron (WOE-MLP) were selected and compared for landslide susceptibility. The percentage of disaster area included in each risk level, the AUC value and the ROC curve were used to evaluate the accuracy of the results. The ROC curves of the results were close to the upper–left corner and the AUC values exceeded 0.85, an indication that all results were highly accurate. Moreover, the percentage of disaster area included for each risk showed an upward trend regarding susceptibility. The results indicated that the hybrid model exhibited superior performance in assessing landslide susceptibility at high altitudes. Overall, the results showed great significance regarding disaster prevention and mitigation measures of local governments.

The subject of the article are the problems of transformation on the basis of breakthrough digital technologies of activity on information support of management and use of accounting information in managerial decision-making. The authors in the course of the research analyze the current state of management accounting and prove that only a factor information model is able to ensure the implementation of the functions of the actual management of the object, allowing observation based on operational, technical, accounting, statistical and data integration requirements. On the example of the system of productivity indicators (qualitatively defined quantity), it is demonstrated that it is possible to implement such requirements for this factor as the object, accuracy and specificity of the work; and an example of a system of indicators for fixed assets — harmonies the functions performed for the object. The article also substantiates the conclusion that the solution of the problems of digital transformation of speech can be provided by an information system functioning based on the platform using Big Data and cloud technologies — DaaS interacting with active elements of the Internet community. In the course of the study, in generalization of modern concepts of management of economic systems, directions of development of digital technologies and their implementation in the processes of information management, methods of system and comparative analysis were used.

The current information exchange interface and human-computer interaction interface of secondary equipment operation and maintenance in substation are not unified,which seriously restricts the efficient operation and maintenance of substation. In view of this situation,the research on the efficient operation and maintenance technology of secondary equipment in substation based on power system general service protocol (GSP) is carried out. Firstly,the architecture of integrated operation and maintenance of secondary equipment in substation is designed,and the information modeling method of integrated operation and maintenance of secondary equipment in substation based on substation operation and maintenance configuration language (SOMCL) is proposed. Then,the service interface and information interaction mechanism of integrated operation and maintenance of secondary equipment in substation are designed based on object-oriented technology (OOT),which achieves the goal of plug and play information interaction between operation and maintenance tools and the object to be transported. Finally,the integrated operation and maintenance tool of secondary equipment in substation is developed to realize the standardization and visualization of operation and maintenance of intelligent secondary equipment in substation,and achieves the goal of integrated and efficient operation and maintenance of secondary equipment in substation. The proposed method has been piloted in several new smart substations,which verifies the feasibility of the integrated operation and maintenance technology of secondary equipment in substation.

In order to effectively predict the spatial probability of landslide occurrence at county scale, the quantitative evaluation and comparative study of landslide susceptibility were carried out based on different statistical coupling models in Puge County, Southwest Sichuan. Six evaluation factors including slope, slope direction, elevation, engineering geological rock group, distance from fault and slope structure are selected to construct the evaluation index system. Information model (I), certainty factor model (CF), weight of evidence model (WF) and frequency ratio model (FR) are coupled with logistic regression model (LR) respectively to conduct landslide susceptibility evaluation. The results show that the evaluation results of each coupled model and the zoning of susceptibility are reasonable. The extremely high susceptibility areas with 129.04 −183.43 km2 (accounting for 6.77% −9.62%) are mainly distributed in the slope zones on both sides of Zemu River and Heishui River Valley. The evaluation accuracy decreases from WF-LR model (AUC=0.869), I-LR model (AUC=0.868), CF-LR model (AUC=0.866), to NFR-LR model (AUC=0.858). The research results can provide an important reference for the quantitative evaluation of county landslide susceptibility in mountainous areas of Southwest Sichuan.

In this study, the general algorithm and technology of design in advanced computer-aided design (CAD) software of the CAD-in-the-Cloud type using an information model (IM) was discussed in detail. Applying design systems of this type increases productivity and quality of the development and enables group work on the project. The proposed information model consists of three main components – working with Autodesk Fusion 360 on a computer, working with cloud capabilities, and designers’ collaboration through the cloud. Nevertheless, some IM elements may be missing in a particular design, or there can be options for applying the proposed steps in the design process. Developing customized respiratory protective equipment (face masks) in Autodesk Fusion 360 CAD family was considered as an example of the suggested IM application. Modern design and producing technologies enable the creation of masks according to individual anatomical characteristics of the human face. In this paper, the protective mask was created by applying modern cloud computing technologies using information models. Information models were adapted to the process of protective mask design. The model of a human headform was developed using the 3D scanning method. After applying retopology tools, a basis of the mask frame was created on the surface of a 3D model of a head. Building a solid model and testing the mask fame configuration under mechanical stresses due to facial expression changing was carried out in Autodesk Fusion 360 CAD software. Finally, the cloud module of the generative design was applied to determine the filtering element configuration.

This paper presents an information model for the association of Computer-Aided Engineering (CAE) behavior models and sensor-based simulation data under consideration of UML-association classes and artifacts of model-based testing (MBT). This scientific work extends the concept of the Digital Twin, consisting of a Digital Master and a Digital Shadow, by the entity of a Simulation Data Management in the Digital Twin (SDM-DT). The required information model of the SDM-DT represents the association between simulation data and simulation models and builds the foundation for the model-based management of simulation conditions for aggregating simulation load cases for predictive use cases. The information model is implemented for a 3D printing use case. [ABSTRACT FROM AUTHOR]

Copyright of Railway Standard Design is the property of Railway Standard Design Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fires caused by electrical reasons such as short circuits and leakage in low-voltage distribution network lines account for a relatively large proportion of the high-rise building fires. Building an electrical fire monitoring system for high-rise buildings based on the Internet of Things (IoTs) technology can monitor electrical circuits in real-time and reduce electrical fires. Aiming at the interconnection and intercommunication of the information exchange of the IoT terminals in the electrical fire monitoring system of high-rise buildings, this paper firstly analyzes the functional communication requirements of the electrical fire monitoring system of high-rise buildings, and combined with the requirements of functional communication, the information model required for electrical quantity collection and non-electricity collection functions is studied based on IEC 61850, which is conducive to the fusion and application of low-voltage distribution network monitoring data and existing distribution automation system data. At the same time, the location information logical node is established by supplementing, which realizes the determination of the spatial position of the terminal and the sensor, the location of the fire source can be determined by analyzing and calculating according to the spatial location information and the spatiotemporal sequence of the detection information. Finally, the information modeling of different types of monitoring terminal equipment is carried out and the configuration suggestion based on SCL language is proposed. By realizing the integration of low-voltage terminal unit (LTU) into the system and the configuration of LTU, the standard system of IEC 61850 can be actually operated. A monitoring terminal based on the proposed information model has been developed and applied to a building in Wuhan. [ABSTRACT FROM AUTHOR]

In order to return data from each product life cycle phase into product design, a methodology for data management is necessary. The product data should be managed in the associated Digital Twin in order to gain information along the product life cycle and to use this information in upstream development processes. In this way, central product information, consistent product models and holistic information flows can be implemented. In this paper, the potential of integrating Digital Twin data as product information in early stages is investigated. By defining requirements, an approach for an information management system for the product life cycle with Digital Twins is created. The novelty of the approach lies in the information model in the form of an UML class diagram. For this purpose, system properties, information flows and communication properties are considered. Using an exemplary data set, the concept is implemented as a Digital assistance system and validated using the case study of a 3D printer. Finally, returning production and usage information into product design holds potential for cost and resource savings. [ABSTRACT FROM AUTHOR]

The sustainable development of the furniture industry is experiencing the challenges of energy consumption and waste disposal. Product–service systems (PSSs) have the potential to promote sustainable development and the opportunity to transition to a circular economy (CE). PSSs can bring a series of benefits to sustainable furniture, but there are still some problems to be considered, such as the safe storage and transmission of information and data and the protection of stakeholders' rights and interests. With digitization becoming a major trend, emerging digital technologies such as blockchain (BC) are proving to have the potential to solve related problems. Therefore, this paper aims to integrate the potential roles of BC and PSSs in the lifecycle of sustainable furniture. This paper adopts a mixed quantitative and qualitative research method. Firstly, the potential relationship among furniture, PSSs, and BC was quantitatively analyzed by VOSviewer. Secondly, this paper qualitatively analyzes the lifecycle stages of sustainable furniture, the advantages of PSSs to promote sustainable furniture, and the potential of BC to enhance the PSSs information model (IM) to further promote sustainable furniture to address related challenges. Subsequently, the conceptual BC-enhanced PSSs IM (BC-PSSs) framework was constructed, which contains the high-level and the low-level of structure and process, and then reviewed and refined through pre-interview questionnaires and follow-up interviews by industry experts and scholars. In addition, discussing the contribution of the conceptual BC-PSSs framework in sustainable furniture, and the potential of BC-PSSs in quantifying design value, encouraging designers to contribute value, and exploring the potential role of BC-PSSs in supporting sustainable consumer behavior. It is the first attempt to construct a conceptual BC-enhanced PSSs IM framework for sustainable furniture from the perspective of lifecycle stages, which can serve as a reference for researchers and policymakers in relevant directions to support sustainable development, in particular contributing to the achievement of SDGs 11 (Sustainable Cities and Communities) and SDGs 12 (Responsible Consumption and Production). [ABSTRACT FROM AUTHOR]

The geological hazard assessment was carried out by the evaluation train thought the study area of multiple disaster species coupling , which has a complete range of disasters such as collapse, landslide and debris flow. The evaluate unit of collapse, landslide and other slopes are grids and the debris flow disasters evaluate units are watershed, Based on the information model and analytic hierarchy process, the risk assessment is carried out respectively, then, the comprehensive geological disaster risk evaluation results of the study area were obtained by taking the method of large value. In the study area, the area of extremely high and high risk area of comprehensive geological disaster is obviously larger than that of the evaluation results of single hazard. The extremely high and high risk area is mainly located in the cataclastic rock area with relatively developed collapse and landslide and extremely prone debris flow basin. In view of the risk assessment of geological disasters in high mountains and valleys, the idea of dividing first and combining later can more reasonably reflect the morphological and spatial differences of different disaster types in the process of risk assessment, and obtain more accurate risk assessment results.

The subject of research is the analysis and definition of the information model of devices, the choice of technologies and protocols for data collection and analysis, routing protocols for the Internet of Things (IoT) networks. The purpose of the article is to create an information model of IoT devices, to define technologies and protocols for data transmission and processing and routing in Internet of Things systems. Building an information model of an IoT device includes identifying data sources and their formats, creating a model and data structure, and analyzing them using tools such as: Eclipse Vorto ThingBoard, Ubodots IoT, Node-Red-UI, freeboard.io . An example of a description of a model of microclimate control devices using the Eclipse Vorto toolkit is given. Two main data processing technologies from IoT devices are considered: IBM Watson IoT, Cisco IWF with examples of their application. Radio frequency, infrared, optical and galvanic technologies for interaction between data collection and data transmission devices in IoT networks with examples of their use are discussed. The areas of application of three main IoT network protocols are considered: MQTT (large corporate networks), CoAP (limited networks on the Internet), Bluetooth Low Energy (local networks without the Internet with a small amount of data).Wi-Fi WebSockets, ZigBee, LoRA, Simple RF, XMPP, RFID, NFC can be used as additional protocols for networks. The features of using routing protocols in IoT networks are discussed: RPL (low power consumption), cognitive RPL (for intelligent networks), CARP (for underwater communication networks), E-CARP (for data reuse).

Introduction. The integrated and sustainable development of urban areas within the framework of urban planning is based on the principle of effective use and is embodied in urban planning solutions. Characteristic aspects of appropriate urban planning solutions encompass various technical, technological, social, environmental, economic issues and development peculiarities of urban areas and buildings. Urban planning solutions, developed for areas and buildings in need of an effective management and evaluation system and a comfortable and safe urban environment, are the subject of this research. The purpose of the research is to develop an approach to organizing the development and selection of optimal urban planning solutions towards the development and transformation of areas and buildings.Materials and methods. Due to its complexity, urban planning goes beyond traditional design and construction and needs sound and effective organization and management methods. Within the framework of this approach, organizational models of development, implementation and optimization of urban planning solutions must have the following components: object and subject of control, parameters of regulatory influence, information and technical support. Towards this end, the list of applications of urban planning solutions, their composition and characteristics are presented. Research methods include structural and functional analysis.Results. The authors have discovered that the effective management of urban planning solutions requires an information model of built-up areas that will be updated and upgraded on an ongoing basis. The mathematical description of the process of selecting optimal urban planning solutions is presented.Conclusions. The list of provisions, formulated by the authors, establishes a scientific rationale for the development and implementation of investment programmes and projects focused on the reengineering of areas and buildings, their composition and structure, establishes an effective regime and configuration of flows of regulatory impacts within the framework of urban planning activities, as well as the preconditions (conditions) of organizing the development and selection of optimal urban planning solutions.

Wubao County is located in the northeastern part of the loess plateau in northern Shaanxi, geological disasters are developing in the area, which seriously threatens the life and property safety of local residents. On the basis of fully analyzing the geological disaster survey data in Wubao County, the evaluation indicators such as slope, slope aspect, and surface curvature were selected for the whole county scale, and the risk assessment was carried out based on the 25 m×25 m grid unit based on the information model based on the GIS platform. The evaluation results are divided into: extremely high risk area, high risk area, medium risk area and low risk area, accounting for 0.63%, 12.58%, 24.40% and 62.39% of the total area respectively. According to the scale of key areas, the factors of slope and slope height are selected, and the analytic hierarchy process model is used to carry out risk assessment of slope units divided by hydrological method based on GIS platform, including 19 extremely high-risk slopes, 69 high-risk slopes, 145 medium-risk slopes, 359 low-risk slopes. The same area (area A) under the two scales was selected to conduct variance analysis on the risk assessment results. It shows that at different scales and the same geographical location, the evaluation results of risk level may be inconsistent. At the county-wide scale, various mathematical statistical models with predictive functions should be used, but at the smaller key area scale, due to the insufficient number of samples used for training, it is not appropriate to use mathematical statistical models. Correspondingly, the grid unit based on GIS tools can be used as the evaluation unit at the county scale; the actual slope body can be used as the evaluation unit at the key area scale.

Objectives. The aim of the study is to develop a methodology for assessing the semantics of weakly structured or morphologically complex visual information models. In order to achieve the goal, a criterion for classifying visual models as complex and an algorithm for obtaining a gradient image with several levels of density were introduced. The gradient image is not binary, thus increasing the reliability of finding boundaries or contours. An auxiliary structural visual model was introduced, and a series of images of different densities was used in processing. Next, the concept of a conditional image coordinate system was introduced. This allows for information to be transferred from different visual models to a synthetic resulting visual model.Methods. Using gradient image processing and constructing a new intermediate structural model allows models with different densities to be linked. A system of conditional image coordinates was introduced and a series of models with different densities to obtain a synthetic image was processed.Results. The visual models obtained from satellite images with poor visibility of objects were processed in the Sun– Earth–Moon system. The Sun–Earth system was chosen as the basis. A characteristic of space images is the fact that the bright light of the Sun “clogs” the images of other objects with large phase angles. The use of the contouring technique allows for the visibility of images of low brightness and high brightness to be equalised. The shift of the frequency response after detection of all objects enabled the formation of a clear visual model.Conclusions. In primary visual models, low brightness images were not visible. They appeared when exposure was increased, while high-density objects merged into one. Because of this, it is fundamentally impossible to obtain a high-quality image of all objects, or the complete semantics of a visual model from a single high, medium, or lowdensity image. In order to obtain the complete semantics of the visual model, a series of images need to be processed with the transfer of images to a common synthetic image. The proposed technique allowed for such problems to be resolved. A comparison of the results obtained using the methods of processing a single image proved the reliability and high information content of the method.

In the process of data connection of each system in fully mechanized working face, it is necessary to perform frequent correspondence between the data point table and the semantics, which leads to the surge of system interconnection and data sharing cost of fully mechanized working face. An information model of intelligent fully mechanized working face based on OLE for process control unified architecture(OPC UA) is proposed. According to the physical composition, functional modules and the information flow requirements between modules of intelligent fully mechanized working face, the information model architecture of intelligent fully mechanized working face is proposed by using object-oriented method. On the basis of this architecture, the physical objects and mining process data in fully mechanized working face are digitized and modeled to form a face-level information model. The static attribute set and process attribute set of basic component, monitoring component set and functional component set objects in information model are introduced in detail. The information model of the intelligent fully mechanized working face is instantiated by adopting the combined modeling mode of the OPC UA and the unified modeling language(UML). The UML class diagram is used to assist in the description of the information model structure, and then converted into the OPC UA information model XML description file. The information model structure data and attribute data are mapped to the OPC UA address space model, and the OPC UA server is started. The practical application results show that each system of fully mechanized working face can access the server address space, and successfully obtain the structure of intelligent fully mechanized working face information model and object data semantics, so as to complete the data collection, storage and update quickly. In order to verify the application effect of the information model, based on the OPC UA server, the information management and integrated analysis platform of fully mechanized working face is developed. The field application test show that the monitoring data displayed by the platform is consistent with the actual operation results (the background data are all from the address space information model), thus verifying the feasibility of the information model combined with the OPC UA protocol to realize the information interconnection of fully mechanized working face.