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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]

Copyright of Railway Construction Technology is the property of Railway Construction Technology 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.)

Due to the continuous introduction of new building technologies, research results, and technical specifications, the design and construction process of buildings has become extremely complex, paying more attention to the sustainable development of the building itself; it not only requires close communication between project participants, but also an in-depth analysis of building performance and structure is required during the design phase. Building Information Modeling (BIM) technology has been widely used in the development of the construction industry in recent years. It can effectively realize the integration of building information, so that all parties involved in the project can work together based on the same platform, which can more effectively improve work efficiency and save resource input, lower construction costs, and ultimately achieve the goal of sustainable development. On the basis of summarizing the previous research results, this paper uses BIM technology to analyze the optimization effect of large-scale construction engineering from the aspects of information model, resource allocation and technology optimization. The analysis results provide reference for subsequent in-depth 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.

Fuyuan County is located in the eastern part of Yunnan Province, with complex terrain and fragile geological environment. In addition, coal mining engineering activities have led to frequent geological disasters, endangering people's lives, property, and production safety. Constructing a scientific and reasonable geological disaster evaluation system is of great significance for the prevention and control of geological disasters. Eight indexes, including elevation, slope, engineering geological group, structure, average annual rainfall, water system, main road and coal mining activity, were selected to evaluate the susceptibility of geological hazard in Fuyuan County based on geographic information system and weighted information model. The results show that coal mining engineering activities and engineering geological formations are key factors affecting the development of geological hazards in Fuyuan County. The area (proportion) of low-prone, lower-prone, medium-prone, higher-prone and high-prone geological hazards in Fuyuan County are 383. 8 km² (19. 54% ), 449. 77 km² (31. 12% ), 759. 67 km² (23. 53% ), 1 004. 99 km² (13. 93% ) and 630. 97 km² (11. 89% ), respectively. The distribution of high-prone areas is consistent with that of coal mining activities, which is a region with concentrated disaster points. Through ROC curve verification, the correct rate is 77. 95 %, indicating that the zoning is reasonable and can provide reference for the prevention and control of geological disasters in Fuyuan County. [ABSTRACT FROM AUTHOR]

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.)

International interoperability of healthcare and research data requires a commitment to standards. To this end, SNOMED CT was evaluated for representing questionnaire items of the European Registry of Stroke Care Quality using a complex annotation protocol. The agreement between validators and annotators was 72.4%. At least 64% of the information could be represented by using SNOMED CT only, including complex post-coordinations. 9% of the information would require an information model, and 14% the addition of new content to SNOMED CT. Next steps will be the creation of an annotation guideline for questionnaires, a specific reference set, and the combination of both with an information model such as HL7 FHIR. [ABSTRACT FROM AUTHOR]

The paper presents the development of a conceptual information model for optimizing land use and crop forecasting in agriculture, implemented using the PHP programming language, Javascript and the MYSQL database management system. The model is designed to solve optimization problems in various fields such as logistics, manufacturing, finance, etc. As part of the work, an information model was developed, which is a set of data, algorithms and software modules designed to solve optimization problems. The model is implemented based on PHP, Javascript, and MYSQL technologies. The model allows you to solve optimization problems of varying complexity using various optimization methods such as linear programming, nonlinear programming, artificial intelligence methods, etc. The model can be applied to solve optimization problems in various fields. In addition, the model allows you to solve optimization problems with a high degree of accuracy and in a short time, and also has a user-friendly interface that allows users to easily and quickly set optimization tasks. The current optimization problems and forecasting problems are not covered in the work. How this will be implemented is not indicated in the resulting information model. The relevance of scientific research – Every year farmers face the task of how to use the land. And they face many factors, including transportation costs, seed quality, cattle grazing and many other options for using the land. But using the simulation model or information system proposed by us, it is important to understand not only the actual use of the land, but also the economic profit. The system will indicate (advise) based on historical data as an expert, what kind of crop to plant so that there is maximum benefit. Agrotechnical indicators, allows you to create more accurate models and forecasts, which contributes to making informed decisions. Such a system allows farmers and agronomists to respond quickly to changing conditions, optimize land use and improve the efficiency of agricultural production in general. An information model has been developed that will make it possible to predict the harvest taking into account data on weather, soil, crops and historical yield data, as well as optimize land use taking into account data on soil type, climate, crop rotation and financial indicators. The developed information model can improve the efficiency and sustainability of agricultural production. The model can be used by agronomists and farmers to make more informed decisions. The model takes into account data on soil type, climate, crop rotation and financial indicators to optimize land use. [ABSTRACT FROM AUTHOR]

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.

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) 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 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]

The power transmission and transformation projects in the western region are facing the threat of frequent seismic activities, landslides and other geological disasters. Evaluation of the landslide susceptibility in power transmission projects has important theoretical and practical significance for the selection of power transmission channels and station sites, landslide monitoring and prevention in western mountainous areas. This paper takes the Erlang Mountain-Zheduo Mountain power transmission as the research area, based on the study of characteristics of landslide, evaluation factors are selected from aspects such as meteorology, hydrology, topography, rock and soil types; a weighted information model was established by using Pearson correlation coefficient method, CRITIC weight method, and independence weight coefficient method. Based on ArcGIS technology and weighted information model, the landslide susceptibility of Erlang Mountain-Zheduo Mountain Power Transmission Project is evaluated. The ROC curves and AUC value were used to verify the effect of weighted information model, and its AUC value is 0.866, indicating that HPIV model has a good prediction effect on landslide disasters. [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.

A six-legged spider robot is a complex object from the point of view of the problem of synthesizing a system for controlling its movement. To synthesize an advanced control system for such a robot, which must solve non-trivial problems of overcoming obstacles, functioning under conditions of external disturbances, etc., we first solve the problem of synthesizing an information model of the object, on the basis of which its control system will subsequently be built. The paper compares two methods for synthesizing the information model of a six-legged spider-robot. In the first method, an information model is automatically synthesized from a CAD model of a spider-robot in a MATLAB-based graphical programming environment Simulink. In the second method, the information model is synthesized in the environment of dynamic modeling of technical systems SimInTech on the basis of a system of differential equations in the Cauchy form. Control loops and external influences are added to the information models synthesized in each of the modeling environments. The study showed that each of the resulting models has both its own individual advantages and disadvantages. They are mainly related to taking into account the mutual influence of various blocks of models on each other. It is shown that, in the end, the two models complement each other and make it possible to obtain an advanced basis for further synthesis of the motion control system. The results obtained in this work make it possible to use information models as a basis for the development of a control system for a physical model of a sixlegged spider-robot, printed on a 3D printer and assembled on the basis of the Arduino hardware platform. [ABSTRACT FROM AUTHOR]

Low-voltage distribution lines lack efficient monitoring. With the massive proliferation of distributed energy resource supply, it is necessary to establish an effective monitoring system for low-voltage distribution lines to ensure the electrical safety and continuity of power supply services. This paper proposes monitoring system for low-voltage distribution lines based on the Internet of things (IoT) technology. An IoT based monitoring system contains a large number of low-voltage monitoring terminals, different manufacturers, and different types of terminal equipment to solve the interconnection problem of information interaction. This paper first analyzes the terminal functional communication requirements based on IEC 61850 standards. Further, the information models required by the electrical volume collection and non-electric quantity collection functions are studied. The information modeling for different types of monitoring terminal equipment is presented and thus provide the configuration suggestions. The monitoring terminal based on the information model developed in this paper is applied in a university campus to realize the monitoring of low-voltage lines and distributed power supply. [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.)

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]

Global environmental pollution has an extremely negative impact on the population of the planet and threatens the future of mankind. One of the main sources of waste and toxic emissions into the atmosphere is the construction sector. It is necessary to find ways to minimize the damage caused to nature. Currently, artificial intelligence technologies are among the most promising ways to improve the environment. Automatic control systems solve a number of problems related to reducing costs and resources, full use of renewable energy sources, improving the safety of energy systems, and many others. The purpose of this article is to determine the functionality of artificial intelligence technologies and ways of their application in green construction. To solve this problem, methods of analysis and synthesis of existing information models were applied. The article discloses automatic control systems in the design, construction, and operation of buildings. These include well-known methods, such as Building Information Model, Machine Learning, Deep Learning, and narrow-profile ones: Response Surface Methodology, Multi-Agent System, Digital Twins, etc. In addition, the study states that when planning and arranging green buildings must adhere to the following principles: high energy efficiency, rational use of natural resources, adaptation to the environment and climate, ensuring comfort and safety for residents. The article presents the standards of green construction existing in the world. This work can serve as a guide when choosing information models and is of practical value in the development of green 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]