The aim of this study was to develop an adequate mathematical model for long-term forecasting of technological progress and economic growth in the digital age (2020-2050). In addition, the task was to develop a model ...The aim of this study was to develop an adequate mathematical model for long-term forecasting of technological progress and economic growth in the digital age (2020-2050). In addition, the task was to develop a model for forecast calculations of labor productivity in the symbiosis of “man + intelligent machine”, where an intelligent machine (IM) is understood as a computer or robot equipped with elements of artificial intelligence (AI), as well as in the digital economy as a whole. In the course of the study, it was shown that in order to implement its goals the Schumpeter-Kondratiev innovation and cycle theory on forming long waves (LW) of economic development influenced by a powerful cluster of economic technologies engendered by industrial revolutions is most appropriate for a long-term forecasting of technological progress and economic growth. The Solow neoclassical model of economic growth, synchronized with LW, gives the opportunity to forecast economic dynamics of technologically advanced countries with a greater precision up to 30 years, the time which correlates with the continuation of LW. In the information and digital age, the key role among the main factors of growth (capital, labour and technological progress) is played by the latter. The authors have developed an information model which allows for forecasting technological progress basing on growth rates of endogenous technological information in economics. The main regimes of producing technological information, corresponding to the eras of information and digital economies, are given in the article, as well as the Lagrangians that engender them. The model is verified on the example of the 5<sup>th</sup> information LW for the US economy (1982-2018) and it has had highly accurate approximation for both technological progress and economic growth. A number of new results were obtained using the developed information models for forecasting technological progress. The forecasting trajectory of economic growth of developed countries (on the example of the USA) on the upward stage of the 6<sup>th</sup> LW (2018-2042), engendered by the digital technologies of the 4<sup>th</sup> Industrial Revolution is given. It is also demonstrated that the symbiosis of human and intelligent machine (IM) is the driving force in the digital economy, where man plays the leading role organizing effective and efficient mutual work. Authors suggest a mathematical model for calculating labour productivity in the digital economy, where the symbiosis of “human + IM” is widely used. The calculations carried out with the help of the model show: 1) the symbiosis of “human + IM” from the very beginning lets to realize the possibilities of increasing work performance in the economy with the help of digital technologies;2) the largest labour productivity is achieved in the symbiosis of “human + IM”, where man labour prevails, and the lowest labour productivity is seen where the largest part of the work is performed by IM;3) developed countries may achieve labour productivity of 3% per year by the mid-2020s, which has all the chances to stay up to the 2040s.展开更多
Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automaticall...Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automatically and manually corrected hydrological slope unit division,the Longhua District,Shenzhen City,Guangdong Province,was selected as the study area.A total of 15 influencing factors,namely Fluctuation,slope,slope aspect,curvature,topographic witness index(TWI),stream power index(SPI),topographic roughness index(TRI),annual average rainfall,distance to water system,engineering rock group,distance to fault,land use,normalized difference vegetation index(NDVI),nighttime light,and distance to road,were selected as evaluation indicators.The information volume model(IV)and random points were used to select non-geological disaster units,and then the random forest model(RF)was used to evaluate the susceptibility to geological disasters.The automatic slope unit and the hydrological slope unit were compared and analyzed in the random forest and information volume random forest models.The results show that the area under the curve(AUC)values of the automatic slope unit evaluation results are 0.931 for the IV-RF model and 0.716 for the RF model,which are 0.6%(IV-RF model)and 1.9%(RF model)higher than those for the hydrological slope unit.Based on a comparison of the evaluation methods based on the two types of slope units,the hydrological slope unit evaluation method based on manual correction is highly subjective,is complicated to operate,and has a low evaluation accuracy,whereas the evaluation method based on automatic slope unit division is efficient and accurate,is suitable for large-scale efficient geological disaster evaluation,and can better deal with the problem of geological disaster susceptibility evaluation.展开更多
The issues and challenges involved in controlling the collaborative changes in a Building Information Modeling(BIM) data repository, in a multi-model collaboration environment, are discussed. It is suggested that mana...The issues and challenges involved in controlling the collaborative changes in a Building Information Modeling(BIM) data repository, in a multi-model collaboration environment, are discussed. It is suggested that managing iterative changes in BIMs is a database problem, exacerbated by the long transaction times needed to support collaborative design progression. This is yet to be resolved in the construction industry and better solutions are needed to support the underlying workflows and computing operations for seamless collaboration on BIMs. With this in mind, this paper proposes the use of the structural and semantic characteristics of BIM objects as a mechanism for tracking changes across co-developed solutions. The creation of object signatures, using hash codes derived from their characteristics, provides a potential mechanism for object comparison and effective change recognition and management.展开更多
With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration wi...With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.展开更多
We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpr...We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpreting these parameters is crucial for effectively exploring and developing oil and gas.However,with the increasing complexity of geological conditions in this industry,there is a growing demand for improved accuracy in reservoir parameter prediction,leading to higher costs associated with manual interpretation.The conventional logging interpretation methods rely on empirical relationships between logging data and reservoir parameters,which suffer from low interpretation efficiency,intense subjectivity,and suitability for ideal conditions.The application of artificial intelligence in the interpretation of logging data provides a new solution to the problems existing in traditional methods.It is expected to improve the accuracy and efficiency of the interpretation.If large and high-quality datasets exist,data-driven models can reveal relationships of arbitrary complexity.Nevertheless,constructing sufficiently large logging datasets with reliable labels remains challenging,making it difficult to apply data-driven models effectively in logging data interpretation.Furthermore,data-driven models often act as“black boxes”without explaining their predictions or ensuring compliance with primary physical constraints.This paper proposes a machine learning method with strong physical constraints by integrating mechanism and data-driven models.Prior knowledge of logging data interpretation is embedded into machine learning regarding network structure,loss function,and optimization algorithm.We employ the Physically Informed Auto-Encoder(PIAE)to predict porosity and water saturation,which can be trained without labeled reservoir parameters using self-supervised learning techniques.This approach effectively achieves automated interpretation and facilitates generalization across diverse datasets.展开更多
Green buildings should respect nature and endeavor to mitigate harmful effects to the environment and occupants.This is often interpreted as creating sustain-able sites,consuming less energy and water,reusing material...Green buildings should respect nature and endeavor to mitigate harmful effects to the environment and occupants.This is often interpreted as creating sustain-able sites,consuming less energy and water,reusing materials,and providing excel-lent indoor environmental quality.Environmentally friendly buildings should also consider literally the impact that they have on birds,millions of them.A major factor in bird collisions with buildings is the choice of building materials.These choices are usually made by the architect who may not be aware of the issue or may be looking for guidance from certification programs such as LEED.As a proof of concept for an educational tool,we developed a software-assisted approach to characterize whether a proposed building design would earn a point for the LEED Pilot Credit 55:Avoiding Bird Collisions.Using the visual programming language Dynamo with the common building information modeling software Revit,we automated the assessment of designs.The approach depends on parameters that incorporate assessments of bird threat for façade materials,analyzes building geom-etry relative to materials,and processes user input on building operation to produce the assessment.展开更多
Dear Editor,This letter deals with automatically constructing an OPC UA information model(IM)aimed at enhancing data interoperability among heterogeneous system components within manufacturing automation systems.Empow...Dear Editor,This letter deals with automatically constructing an OPC UA information model(IM)aimed at enhancing data interoperability among heterogeneous system components within manufacturing automation systems.Empowered by the large language model(LLM),we propose a novel multi-agent collaborative framework to streamline the end-to-end OPC UA IM modeling process.Each agent is equipped with meticulously engineered prompt templates,augmenting their capacity to execute specific tasks.We conduct modeling experiments using real textual data to demonstrate the effectiveness of the proposed method,improving modeling efficiency and reducing the labor workload.展开更多
The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D desi...The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D design coordination,its static nature limits its utility in real-time construction management and operational phases.This paper proposes a novel synergistic framework that integrates the static,deep data of BIM with the dynamic,real-time capabilities of digital twin(DT)technology.The framework establishes a closed-loop data flow from design(BIM)to construction(IoT,drones,BIM 360)to operation(DT platform).We detail the technological stack required,including IoT sensors,cloud computing,and AI-driven analytics.The application of this framework is illustrated through a simulated case study of a mega-terminal airport construction project,demonstrating potential reductions in rework by 15%,improvement in labor productivity by 10%,and enhanced predictive maintenance capabilities.This research contributes to the field of construction engineering by providing a practical model for achieving full lifecycle digitalization and intelligent project management.展开更多
More than two decades ago, object-oriented representation of AEC （architecture engineering and construction） projects started to offer the promise of seamless communication of semantic data models between computer-b...More than two decades ago, object-oriented representation of AEC （architecture engineering and construction） projects started to offer the promise of seamless communication of semantic data models between computer-based systems used from the design stage to the operation of the facilities. BIM （building information modelling） emerged and appeared as a means to store all relevant data generated during the life-cycle of the facilities. But this upstream view of the built environment, arising from the design and construction stages, extended to the downstream operations where building and industrial facilities appeared more and more as huge dynamic data producers and concentrators while being operated. This created new challenges leading to what is referred to as ISCs （intelligent and smart constructions）. The current state of the art is that final constructions still contain various and increasingly versatile control and service systems, which are hardly standardised, and not interconnected among themselves. Monitoring, maintenance and services are done by specialised companies, each responsible of different systems, which are relying on customised software and techniques to meet specific user needs and are based on monolithic applications that require manual configuration for specific uses, maintenance and support. We demonstrate in this paper that the early promises of integration across the actors and along the life-time of facilities have gone a long way but will only be delivered through enhanced standardisation of computerized models, representations, services and operations still not yet fully accomplished 25 years after work started.展开更多
Underground pipeline networks constitute a major component of urban infrastructure,and thus,it is imperative to have an efficient mechanism to manage them.This study introduces a secondary development system to effici...Underground pipeline networks constitute a major component of urban infrastructure,and thus,it is imperative to have an efficient mechanism to manage them.This study introduces a secondary development system to efficiently model underground pipeline networks,using the building information modeling(BIM)-based software Revit.The system comprises separate pipe point and tubulation models.Using a Revit application programming interface(API),the spatial position and attribute data of the pipe points are extracted from a pipeline database,and the corresponding tubulation data are extracted from a tubulation database.Using the Family class in Revit API,the cluster in the self-built library of pipe point is inserted into the spatial location and the attribute data is added;in the same way,all pipeline instances in the pipeline system are created.The extension and localization of the model accelerated the modeling speed.The system was then used in a real construction project.The expansion of the model database and rapid modeling made the application of BIM technology in three-dimensional visualization of underground pipeline networks more convenient.Furthermore,it has applications in pipeline engineering construction and management.展开更多
Slope aspect is one of the indispensable internal factors besides lithology, relative elevation and slope degree. In this paper authors use information value model with Geo graphical Information System （GIS） technol...Slope aspect is one of the indispensable internal factors besides lithology, relative elevation and slope degree. In this paper authors use information value model with Geo graphical Information System （GIS） technology to study how slope aspect contributes to landslide growth from Yunyang to Wushan segment in the Three Gorges Reservoir area, and the relationship between aspect and landslide growth is quantified. Through the research on 205 landslides examples, it is found that the slope contributes most whose aspect is towards south,southeast and southwest aspect contribute moderately, and other five aspects contribute little. The research result inosculates preferably with the fact. The result of this paper can provide potent gist to the construction of Three Gorges Reservoir area in future.展开更多
Computer vision-based inspection methods show promise for automating post-earthquake building inspections.These methods survey a building with unmanned aerial vehicles and automatically detect damage in the collected ...Computer vision-based inspection methods show promise for automating post-earthquake building inspections.These methods survey a building with unmanned aerial vehicles and automatically detect damage in the collected images.Nevertheless,assessing the damage′s impact on structural safety requires localizing damage to specific building components with known design and function.This paper proposes a BIM-based automated inspection framework to provide context for visual surveys.A deep learning-based semantic segmentation algorithm is trained to automatically identify damage in images.The BIM automatically associates any identified damage with specific building components.Then,components are classified into damage states consistent with component fragility models for integration with a structural analysis.To demonstrate the framework,methods are developed to photorealistically simulate severe structural damage in a synthetic computer graphics environment.A graphics model of a real building in Urbana,Illinois,is generated to test the framework;the model is integrated with a structural analysis to apply earthquake damage in a physically realistic manner.A simulated UAV survey is flown of the graphics model and the framework is applied.The method achieves high accuracy in assigning damage states to visible structural components.This assignment enables integration with a performance-based earthquake assessment to classify building safety.展开更多
The vehicle routing and scheduling (VRS) problem with multi-objective and multi-constraint is analyzed, considering the complexity of the modern logistics in city economy and daily life based on the system engineering...The vehicle routing and scheduling (VRS) problem with multi-objective and multi-constraint is analyzed, considering the complexity of the modern logistics in city economy and daily life based on the system engineering. The objective and constraint includes loading, the dispatch and arrival time, transportation conditions,total cost,etc. An information model and a mathematical model are built,and a method based on knowledge and biologic immunity is put forward for optimizing and evaluating the programs dimensions in vehicle routing and scheduling with multi-objective and multi-constraints. The proposed model and method are illustrated in a case study concerning a transport network, and the result shows that more optimization solutions can be easily obtained and the method is efficient and feasible. Comparing with the standard GA and the standard GA without time constraint,the computational time of the algorithm is less in this paper. And the probability of gaining optimal solution is bigger and the result is better under the condition of multi-constraint.展开更多
There are heterogeneous problems between the CAD model and the assembly process document.In the planning stage of assembly process,these heterogeneous problems can decrease the efficiency of information interaction.Ba...There are heterogeneous problems between the CAD model and the assembly process document.In the planning stage of assembly process,these heterogeneous problems can decrease the efficiency of information interaction.Based on knowledge graph,this paper proposes an assembly information model(KGAM)to integrate geometric information from CAD model,non-geometric information and semantic information from assembly process document.KGAM describes the integrated assembly process information as a knowledge graph in the form of“entity-relationship-entity”and“entity-attribute-value”,which can improve the efficiency of information interaction.Taking the trial assembly stage of a certain type of aeroengine compressor rotor component as an example,KGAM is used to get its assembly process knowledge graph.The trial data show the query and update rate of assembly attribute information is improved by more than once.And the query and update rate of assembly semantic information is improved by more than twice.In conclusion,KGAM can solve the heterogeneous problems between the CAD model and the assembly process document and improve the information interaction efficiency.展开更多
A hybrid model that is based on the Combination of keywords and concept was put forward. The hybrid model is built on vector space model and probabilistic reasoning network. It not only can exert the advantages of key...A hybrid model that is based on the Combination of keywords and concept was put forward. The hybrid model is built on vector space model and probabilistic reasoning network. It not only can exert the advantages of keywords retrieval and concept retrieval but also can compensate for their shortcomings. Their parameters can be adjusted according to different usage in order to accept the best information retrieval result, and it has been proved by our experiments.展开更多
Yangtze Estuary Tidal Wetlands Geographic Information System (YETWGIS) is a comprehensive software system for environmental management and decision of Yangtze estuary tidal wetlands. Based on MapObjects components tec...Yangtze Estuary Tidal Wetlands Geographic Information System (YETWGIS) is a comprehensive software system for environmental management and decision of Yangtze estuary tidal wetlands. Based on MapObjects components technology, Data Mining technology, mathematical modeling method and Visual Basic language, this software system has many functions such as displaying, editing, querying and searching, spatial statistics and analysis, thematic map compiling, and environmental quality evaluation. This paper firstly outlined the system structure, key techniques, and achieving methods of YETWGIS, and then, described the core modules (the thematic map compiling module and environmental quality evaluation model module) in detail. In addition, based on information entropy model, it thoroughly discussed the methods of environmental quality evaluation and indicators' weight calculation. Finally, by using YETWGIS, this paper analyzed the spatial distribution characteristics of Heavy Metal and Persistent Organic Pollutants (POPs) of the Yangtze estuary tidal wetlands in 2002, and evaluated the environmental quality of the Yangtze estuary tidal wetlands in 2003.展开更多
Information was a frequently used concept in many fields of investigation. However, this concept is still not really understood, when it is referred for instance to consciousness and its informational structure. In th...Information was a frequently used concept in many fields of investigation. However, this concept is still not really understood, when it is referred for instance to consciousness and its informational structure. In this paper it is followed the concept of information from philosophical to physics perspective, showing especially how this concept could be extended to matter in general and to the living in particular, as a result of the intimate interaction between matter and information, the human body appearing as a bipolar informed-matter structure. It is detailed on this way how this concept could be referred to consciousness, and an informational modeling of consciousness as an informational system of the human body is presented. Based on the anatomic architecture of the organism and on the inference of the specific information concepts, it is shown that the informational system of the human body could be described by seven informational subsystems, which are reflected in consciousness as corresponding cognitive centers. These results are able to explain the main properties of consciousness, both the cognitive and extra-cognitive properties of the mind, like that observed during the near-death experiences and other similar phenomena. Moreover, the results of such a modeling are compared with the existing empirical concepts and models on the energetic architecture of the organism, showing their relevance for the understanding of consciousness.展开更多
BACKGROUND As one of the fatal diseases with high incidence,lung cancer has seriously endangered public health and safety.Elderly patients usually have poor self-care and are more likely to show a series of psychologi...BACKGROUND As one of the fatal diseases with high incidence,lung cancer has seriously endangered public health and safety.Elderly patients usually have poor self-care and are more likely to show a series of psychological problems.AIM To investigate the effectiveness of the initial check,information exchange,final accuracy check,reaction(IIFAR)information care model on the mental health status of elderly patients with lung cancer.METHODS This study is a single-centre study.We randomly recruited 60 elderly patients with lung cancer who attended our hospital from January 2021 to January 2022.These elderly patients with lung cancer were randomly divided into two groups,with the control group taking the conventional propaganda and education and the observation group taking the IIFAR information care model based on the conventional care protocol.The differences in psychological distress,anxiety and depression,life quality,fatigue,and the locus of control in psychology were compared between these two groups,and the causes of psychological distress were analyzed.RESULTS After the intervention,Distress Thermometer,Hospital Anxiety and Depression Scale(HADS)for anxiety and the HADS for depression,Revised Piper’s Fatigue Scale,and Chance Health Locus of Control scores were lower in the observation group compared to the pre-intervention period in the same group and were significantly lower in the observation group compared to those of the control group(P<0.05).After the intervention,Quality of Life Questionnaire Core 30(QLQ-C30),Internal Health Locus of Control,and Powerful Others Health Locus of Control scores were significantly higher in the observation and the control groups compared to the pre-intervention period in their same group,and QLQ-C30 scores were significantly higher in the observation group compared to those of the control group(P<0.05).CONCLUSION The IIFAR information care model can help elderly patients with lung cancer by reducing their anxiety and depression,psychological distress,and fatigue,improving their tendencies on the locus of control in psychology,and enhancing their life qualities.展开更多
BACKGROUND Cerebrovascular disease(CVD)poses a serious threat to human health and safety.Thus,developing a reasonable exercise program plays an important role in the long-term recovery and prognosis for patients with ...BACKGROUND Cerebrovascular disease(CVD)poses a serious threat to human health and safety.Thus,developing a reasonable exercise program plays an important role in the long-term recovery and prognosis for patients with CVD.Studies have shown that predictive nursing can improve the quality of care and that the information–knowledge–attitude–practice(IKAP)nursing model has a positive impact on patients who suffered a stroke.Few studies have combined these two nursing models to treat CVD.AIM To explore the effect of the IKAP nursing model combined with predictive nursing on the Fugl–Meyer motor function(FMA)score,Barthel index score,and disease knowledge mastery rate in patients with CVD.METHODS A total of 140 patients with CVD treated at our hospital between December 2019 and September 2021 were randomly divided into two groups,with 70 patients in each.The control group received routine nursing,while the observation group received the IKAP nursing model combined with predictive nursing.Both groups were observed for self-care ability,motor function,and disease knowledge mastery rate after one month of nursing.RESULTS There was no clear difference between the Barthel index and FMA scores of the two groups before nursing(P>0.05);however,their scores increased after nursing.This increase was more apparent in the observation group,and the difference was statistically significant(P<0.05).The rates of disease knowledge mastery,timely medication,appropriate exercise,and reasonable diet were significantly higher in the observation group than in the control group(P<0.05).The satisfaction rate in the observation group(97.14%)was significantly higher than that in the control group(81.43%;P<0.05).CONCLUSION The IKAP nursing model,combined with predictive nursing,is more effective than routine nursing in the care of patients with CVD,and it can significantly improve the Barthel index and FMA scores with better knowledge acquisition,as well as produce high satisfaction in patients.Moreover,they can be widely used in the clinical setting.展开更多
文摘The aim of this study was to develop an adequate mathematical model for long-term forecasting of technological progress and economic growth in the digital age (2020-2050). In addition, the task was to develop a model for forecast calculations of labor productivity in the symbiosis of “man + intelligent machine”, where an intelligent machine (IM) is understood as a computer or robot equipped with elements of artificial intelligence (AI), as well as in the digital economy as a whole. In the course of the study, it was shown that in order to implement its goals the Schumpeter-Kondratiev innovation and cycle theory on forming long waves (LW) of economic development influenced by a powerful cluster of economic technologies engendered by industrial revolutions is most appropriate for a long-term forecasting of technological progress and economic growth. The Solow neoclassical model of economic growth, synchronized with LW, gives the opportunity to forecast economic dynamics of technologically advanced countries with a greater precision up to 30 years, the time which correlates with the continuation of LW. In the information and digital age, the key role among the main factors of growth (capital, labour and technological progress) is played by the latter. The authors have developed an information model which allows for forecasting technological progress basing on growth rates of endogenous technological information in economics. The main regimes of producing technological information, corresponding to the eras of information and digital economies, are given in the article, as well as the Lagrangians that engender them. The model is verified on the example of the 5<sup>th</sup> information LW for the US economy (1982-2018) and it has had highly accurate approximation for both technological progress and economic growth. A number of new results were obtained using the developed information models for forecasting technological progress. The forecasting trajectory of economic growth of developed countries (on the example of the USA) on the upward stage of the 6<sup>th</sup> LW (2018-2042), engendered by the digital technologies of the 4<sup>th</sup> Industrial Revolution is given. It is also demonstrated that the symbiosis of human and intelligent machine (IM) is the driving force in the digital economy, where man plays the leading role organizing effective and efficient mutual work. Authors suggest a mathematical model for calculating labour productivity in the digital economy, where the symbiosis of “human + IM” is widely used. The calculations carried out with the help of the model show: 1) the symbiosis of “human + IM” from the very beginning lets to realize the possibilities of increasing work performance in the economy with the help of digital technologies;2) the largest labour productivity is achieved in the symbiosis of “human + IM”, where man labour prevails, and the lowest labour productivity is seen where the largest part of the work is performed by IM;3) developed countries may achieve labour productivity of 3% per year by the mid-2020s, which has all the chances to stay up to the 2040s.
文摘Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automatically and manually corrected hydrological slope unit division,the Longhua District,Shenzhen City,Guangdong Province,was selected as the study area.A total of 15 influencing factors,namely Fluctuation,slope,slope aspect,curvature,topographic witness index(TWI),stream power index(SPI),topographic roughness index(TRI),annual average rainfall,distance to water system,engineering rock group,distance to fault,land use,normalized difference vegetation index(NDVI),nighttime light,and distance to road,were selected as evaluation indicators.The information volume model(IV)and random points were used to select non-geological disaster units,and then the random forest model(RF)was used to evaluate the susceptibility to geological disasters.The automatic slope unit and the hydrological slope unit were compared and analyzed in the random forest and information volume random forest models.The results show that the area under the curve(AUC)values of the automatic slope unit evaluation results are 0.931 for the IV-RF model and 0.716 for the RF model,which are 0.6%(IV-RF model)and 1.9%(RF model)higher than those for the hydrological slope unit.Based on a comparison of the evaluation methods based on the two types of slope units,the hydrological slope unit evaluation method based on manual correction is highly subjective,is complicated to operate,and has a low evaluation accuracy,whereas the evaluation method based on automatic slope unit division is efficient and accurate,is suitable for large-scale efficient geological disaster evaluation,and can better deal with the problem of geological disaster susceptibility evaluation.
文摘The issues and challenges involved in controlling the collaborative changes in a Building Information Modeling(BIM) data repository, in a multi-model collaboration environment, are discussed. It is suggested that managing iterative changes in BIMs is a database problem, exacerbated by the long transaction times needed to support collaborative design progression. This is yet to be resolved in the construction industry and better solutions are needed to support the underlying workflows and computing operations for seamless collaboration on BIMs. With this in mind, this paper proposes the use of the structural and semantic characteristics of BIM objects as a mechanism for tracking changes across co-developed solutions. The creation of object signatures, using hash codes derived from their characteristics, provides a potential mechanism for object comparison and effective change recognition and management.
基金Under the auspices of National Natural Science Foundation of China(No.42330510)。
文摘With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.
基金supported by National Key Research and Development Program (2019YFA0708301)National Natural Science Foundation of China (51974337)+2 种基金the Strategic Cooperation Projects of CNPC and CUPB (ZLZX2020-03)Science and Technology Innovation Fund of CNPC (2021DQ02-0403)Open Fund of Petroleum Exploration and Development Research Institute of CNPC (2022-KFKT-09)
文摘We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpreting these parameters is crucial for effectively exploring and developing oil and gas.However,with the increasing complexity of geological conditions in this industry,there is a growing demand for improved accuracy in reservoir parameter prediction,leading to higher costs associated with manual interpretation.The conventional logging interpretation methods rely on empirical relationships between logging data and reservoir parameters,which suffer from low interpretation efficiency,intense subjectivity,and suitability for ideal conditions.The application of artificial intelligence in the interpretation of logging data provides a new solution to the problems existing in traditional methods.It is expected to improve the accuracy and efficiency of the interpretation.If large and high-quality datasets exist,data-driven models can reveal relationships of arbitrary complexity.Nevertheless,constructing sufficiently large logging datasets with reliable labels remains challenging,making it difficult to apply data-driven models effectively in logging data interpretation.Furthermore,data-driven models often act as“black boxes”without explaining their predictions or ensuring compliance with primary physical constraints.This paper proposes a machine learning method with strong physical constraints by integrating mechanism and data-driven models.Prior knowledge of logging data interpretation is embedded into machine learning regarding network structure,loss function,and optimization algorithm.We employ the Physically Informed Auto-Encoder(PIAE)to predict porosity and water saturation,which can be trained without labeled reservoir parameters using self-supervised learning techniques.This approach effectively achieves automated interpretation and facilitates generalization across diverse datasets.
文摘Green buildings should respect nature and endeavor to mitigate harmful effects to the environment and occupants.This is often interpreted as creating sustain-able sites,consuming less energy and water,reusing materials,and providing excel-lent indoor environmental quality.Environmentally friendly buildings should also consider literally the impact that they have on birds,millions of them.A major factor in bird collisions with buildings is the choice of building materials.These choices are usually made by the architect who may not be aware of the issue or may be looking for guidance from certification programs such as LEED.As a proof of concept for an educational tool,we developed a software-assisted approach to characterize whether a proposed building design would earn a point for the LEED Pilot Credit 55:Avoiding Bird Collisions.Using the visual programming language Dynamo with the common building information modeling software Revit,we automated the assessment of designs.The approach depends on parameters that incorporate assessments of bird threat for façade materials,analyzes building geom-etry relative to materials,and processes user input on building operation to produce the assessment.
基金supported supported by the Fundamental Research Funds for the Central Universities(226-2024-00004)the National Natural Science Foundation of China(U23 A20326)Key Research and Development Program of Zhejiang Province(2025C01061).
文摘Dear Editor,This letter deals with automatically constructing an OPC UA information model(IM)aimed at enhancing data interoperability among heterogeneous system components within manufacturing automation systems.Empowered by the large language model(LLM),we propose a novel multi-agent collaborative framework to streamline the end-to-end OPC UA IM modeling process.Each agent is equipped with meticulously engineered prompt templates,augmenting their capacity to execute specific tasks.We conduct modeling experiments using real textual data to demonstrate the effectiveness of the proposed method,improving modeling efficiency and reducing the labor workload.
文摘The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D design coordination,its static nature limits its utility in real-time construction management and operational phases.This paper proposes a novel synergistic framework that integrates the static,deep data of BIM with the dynamic,real-time capabilities of digital twin(DT)technology.The framework establishes a closed-loop data flow from design(BIM)to construction(IoT,drones,BIM 360)to operation(DT platform).We detail the technological stack required,including IoT sensors,cloud computing,and AI-driven analytics.The application of this framework is illustrated through a simulated case study of a mega-terminal airport construction project,demonstrating potential reductions in rework by 15%,improvement in labor productivity by 10%,and enhanced predictive maintenance capabilities.This research contributes to the field of construction engineering by providing a practical model for achieving full lifecycle digitalization and intelligent project management.
文摘More than two decades ago, object-oriented representation of AEC （architecture engineering and construction） projects started to offer the promise of seamless communication of semantic data models between computer-based systems used from the design stage to the operation of the facilities. BIM （building information modelling） emerged and appeared as a means to store all relevant data generated during the life-cycle of the facilities. But this upstream view of the built environment, arising from the design and construction stages, extended to the downstream operations where building and industrial facilities appeared more and more as huge dynamic data producers and concentrators while being operated. This created new challenges leading to what is referred to as ISCs （intelligent and smart constructions）. The current state of the art is that final constructions still contain various and increasingly versatile control and service systems, which are hardly standardised, and not interconnected among themselves. Monitoring, maintenance and services are done by specialised companies, each responsible of different systems, which are relying on customised software and techniques to meet specific user needs and are based on monolithic applications that require manual configuration for specific uses, maintenance and support. We demonstrate in this paper that the early promises of integration across the actors and along the life-time of facilities have gone a long way but will only be delivered through enhanced standardisation of computerized models, representations, services and operations still not yet fully accomplished 25 years after work started.
基金supported by a grant(No.14DZ2292800,http://www.greengeo.net/)from“Technology Service Platform of Civil Engineering”of Science and Technology Commission of Shanghai Municipality.
文摘Underground pipeline networks constitute a major component of urban infrastructure,and thus,it is imperative to have an efficient mechanism to manage them.This study introduces a secondary development system to efficiently model underground pipeline networks,using the building information modeling(BIM)-based software Revit.The system comprises separate pipe point and tubulation models.Using a Revit application programming interface(API),the spatial position and attribute data of the pipe points are extracted from a pipeline database,and the corresponding tubulation data are extracted from a tubulation database.Using the Family class in Revit API,the cluster in the self-built library of pipe point is inserted into the spatial location and the attribute data is added;in the same way,all pipeline instances in the pipeline system are created.The extension and localization of the model accelerated the modeling speed.The system was then used in a real construction project.The expansion of the model database and rapid modeling made the application of BIM technology in three-dimensional visualization of underground pipeline networks more convenient.Furthermore,it has applications in pipeline engineering construction and management.
文摘Slope aspect is one of the indispensable internal factors besides lithology, relative elevation and slope degree. In this paper authors use information value model with Geo graphical Information System （GIS） technology to study how slope aspect contributes to landslide growth from Yunyang to Wushan segment in the Three Gorges Reservoir area, and the relationship between aspect and landslide growth is quantified. Through the research on 205 landslides examples, it is found that the slope contributes most whose aspect is towards south,southeast and southwest aspect contribute moderately, and other five aspects contribute little. The research result inosculates preferably with the fact. The result of this paper can provide potent gist to the construction of Three Gorges Reservoir area in future.
基金Financial support for this research was provided in part by the US Army Corps of Engineers through a subaward from the University of California,San Diego,USA。
文摘Computer vision-based inspection methods show promise for automating post-earthquake building inspections.These methods survey a building with unmanned aerial vehicles and automatically detect damage in the collected images.Nevertheless,assessing the damage′s impact on structural safety requires localizing damage to specific building components with known design and function.This paper proposes a BIM-based automated inspection framework to provide context for visual surveys.A deep learning-based semantic segmentation algorithm is trained to automatically identify damage in images.The BIM automatically associates any identified damage with specific building components.Then,components are classified into damage states consistent with component fragility models for integration with a structural analysis.To demonstrate the framework,methods are developed to photorealistically simulate severe structural damage in a synthetic computer graphics environment.A graphics model of a real building in Urbana,Illinois,is generated to test the framework;the model is integrated with a structural analysis to apply earthquake damage in a physically realistic manner.A simulated UAV survey is flown of the graphics model and the framework is applied.The method achieves high accuracy in assigning damage states to visible structural components.This assignment enables integration with a performance-based earthquake assessment to classify building safety.
基金National natural science foundation (No:70371040)
文摘The vehicle routing and scheduling (VRS) problem with multi-objective and multi-constraint is analyzed, considering the complexity of the modern logistics in city economy and daily life based on the system engineering. The objective and constraint includes loading, the dispatch and arrival time, transportation conditions,total cost,etc. An information model and a mathematical model are built,and a method based on knowledge and biologic immunity is put forward for optimizing and evaluating the programs dimensions in vehicle routing and scheduling with multi-objective and multi-constraints. The proposed model and method are illustrated in a case study concerning a transport network, and the result shows that more optimization solutions can be easily obtained and the method is efficient and feasible. Comparing with the standard GA and the standard GA without time constraint,the computational time of the algorithm is less in this paper. And the probability of gaining optimal solution is bigger and the result is better under the condition of multi-constraint.
基金the National Natural Science Foundation of China(No.51805079)。
文摘There are heterogeneous problems between the CAD model and the assembly process document.In the planning stage of assembly process,these heterogeneous problems can decrease the efficiency of information interaction.Based on knowledge graph,this paper proposes an assembly information model(KGAM)to integrate geometric information from CAD model,non-geometric information and semantic information from assembly process document.KGAM describes the integrated assembly process information as a knowledge graph in the form of“entity-relationship-entity”and“entity-attribute-value”,which can improve the efficiency of information interaction.Taking the trial assembly stage of a certain type of aeroengine compressor rotor component as an example,KGAM is used to get its assembly process knowledge graph.The trial data show the query and update rate of assembly attribute information is improved by more than once.And the query and update rate of assembly semantic information is improved by more than twice.In conclusion,KGAM can solve the heterogeneous problems between the CAD model and the assembly process document and improve the information interaction efficiency.
文摘A hybrid model that is based on the Combination of keywords and concept was put forward. The hybrid model is built on vector space model and probabilistic reasoning network. It not only can exert the advantages of keywords retrieval and concept retrieval but also can compensate for their shortcomings. Their parameters can be adjusted according to different usage in order to accept the best information retrieval result, and it has been proved by our experiments.
基金National Natural Science Foundation of China No.40131020 No.40173030 Shanghai Science Committee and Environmental Bureau Program Shanghai Basic Science Research Key Program No.02DJ14029 Foundation for the Excellent You
文摘Yangtze Estuary Tidal Wetlands Geographic Information System (YETWGIS) is a comprehensive software system for environmental management and decision of Yangtze estuary tidal wetlands. Based on MapObjects components technology, Data Mining technology, mathematical modeling method and Visual Basic language, this software system has many functions such as displaying, editing, querying and searching, spatial statistics and analysis, thematic map compiling, and environmental quality evaluation. This paper firstly outlined the system structure, key techniques, and achieving methods of YETWGIS, and then, described the core modules (the thematic map compiling module and environmental quality evaluation model module) in detail. In addition, based on information entropy model, it thoroughly discussed the methods of environmental quality evaluation and indicators' weight calculation. Finally, by using YETWGIS, this paper analyzed the spatial distribution characteristics of Heavy Metal and Persistent Organic Pollutants (POPs) of the Yangtze estuary tidal wetlands in 2002, and evaluated the environmental quality of the Yangtze estuary tidal wetlands in 2003.
文摘Information was a frequently used concept in many fields of investigation. However, this concept is still not really understood, when it is referred for instance to consciousness and its informational structure. In this paper it is followed the concept of information from philosophical to physics perspective, showing especially how this concept could be extended to matter in general and to the living in particular, as a result of the intimate interaction between matter and information, the human body appearing as a bipolar informed-matter structure. It is detailed on this way how this concept could be referred to consciousness, and an informational modeling of consciousness as an informational system of the human body is presented. Based on the anatomic architecture of the organism and on the inference of the specific information concepts, it is shown that the informational system of the human body could be described by seven informational subsystems, which are reflected in consciousness as corresponding cognitive centers. These results are able to explain the main properties of consciousness, both the cognitive and extra-cognitive properties of the mind, like that observed during the near-death experiences and other similar phenomena. Moreover, the results of such a modeling are compared with the existing empirical concepts and models on the energetic architecture of the organism, showing their relevance for the understanding of consciousness.
文摘BACKGROUND As one of the fatal diseases with high incidence,lung cancer has seriously endangered public health and safety.Elderly patients usually have poor self-care and are more likely to show a series of psychological problems.AIM To investigate the effectiveness of the initial check,information exchange,final accuracy check,reaction(IIFAR)information care model on the mental health status of elderly patients with lung cancer.METHODS This study is a single-centre study.We randomly recruited 60 elderly patients with lung cancer who attended our hospital from January 2021 to January 2022.These elderly patients with lung cancer were randomly divided into two groups,with the control group taking the conventional propaganda and education and the observation group taking the IIFAR information care model based on the conventional care protocol.The differences in psychological distress,anxiety and depression,life quality,fatigue,and the locus of control in psychology were compared between these two groups,and the causes of psychological distress were analyzed.RESULTS After the intervention,Distress Thermometer,Hospital Anxiety and Depression Scale(HADS)for anxiety and the HADS for depression,Revised Piper’s Fatigue Scale,and Chance Health Locus of Control scores were lower in the observation group compared to the pre-intervention period in the same group and were significantly lower in the observation group compared to those of the control group(P<0.05).After the intervention,Quality of Life Questionnaire Core 30(QLQ-C30),Internal Health Locus of Control,and Powerful Others Health Locus of Control scores were significantly higher in the observation and the control groups compared to the pre-intervention period in their same group,and QLQ-C30 scores were significantly higher in the observation group compared to those of the control group(P<0.05).CONCLUSION The IIFAR information care model can help elderly patients with lung cancer by reducing their anxiety and depression,psychological distress,and fatigue,improving their tendencies on the locus of control in psychology,and enhancing their life qualities.
基金Supported by Basic scientific research industry of Heilongjiang Provincial undergraduate universities in 2019,No.2019-KYYWF-1213.
文摘BACKGROUND Cerebrovascular disease(CVD)poses a serious threat to human health and safety.Thus,developing a reasonable exercise program plays an important role in the long-term recovery and prognosis for patients with CVD.Studies have shown that predictive nursing can improve the quality of care and that the information–knowledge–attitude–practice(IKAP)nursing model has a positive impact on patients who suffered a stroke.Few studies have combined these two nursing models to treat CVD.AIM To explore the effect of the IKAP nursing model combined with predictive nursing on the Fugl–Meyer motor function(FMA)score,Barthel index score,and disease knowledge mastery rate in patients with CVD.METHODS A total of 140 patients with CVD treated at our hospital between December 2019 and September 2021 were randomly divided into two groups,with 70 patients in each.The control group received routine nursing,while the observation group received the IKAP nursing model combined with predictive nursing.Both groups were observed for self-care ability,motor function,and disease knowledge mastery rate after one month of nursing.RESULTS There was no clear difference between the Barthel index and FMA scores of the two groups before nursing(P>0.05);however,their scores increased after nursing.This increase was more apparent in the observation group,and the difference was statistically significant(P<0.05).The rates of disease knowledge mastery,timely medication,appropriate exercise,and reasonable diet were significantly higher in the observation group than in the control group(P<0.05).The satisfaction rate in the observation group(97.14%)was significantly higher than that in the control group(81.43%;P<0.05).CONCLUSION The IKAP nursing model,combined with predictive nursing,is more effective than routine nursing in the care of patients with CVD,and it can significantly improve the Barthel index and FMA scores with better knowledge acquisition,as well as produce high satisfaction in patients.Moreover,they can be widely used in the clinical setting.
