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Previous studies on the susceptibility assessment of regional landslides mainly focused on comparing and improving the results of different evaluation models, while neglected the preservation of information on selected disaster-causing factors and the issue of how to unify factor dimensions. To explore the correlation and dimensionality of disaster causing-factors and their impact on susceptibility assessment, this study selected 12 factors such as elevation, slope, aspect, and terrain undulation, and used new factors extracted from principal component analysis in susceptibility assessment in the northern Jingyuan County. Data standardization, landslide density, and information quantity substitution methods were used to unify the dimensionality of disaster-causing factors. The landslide susceptibility zoning map was drawn based on the GIS platform in the study area. The accuracy of the susceptibility assessment of each mode was evaluated by the receiver operating characteristic curve. The results show that among the information model, the logistic regression model, and the perceptron model, the accuracy of the model evaluation obtained by the factors processed by principal component analysis is the highest. Using the information value substitution method to unify the dimensions of factors can further improve the accuracy of the evaluation of the logistic regression model and the perceptron model. The perceptron model has the highest accuracy (AUC=0.936 7), which is superior to the information model (AUC=0.917 3) and the logistic regression model (AUC=0.927 2). This is an ideal model for the landslide susceptibility assessment in the study area and should be given priority. The results can provide the basic theoretical information for disaster prevention and mitigation in similar areas.

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The article provides an overview of using machine learning models to predict financial indicators, aiming to enhance decision-making for balanced stock portfolios. The study highlights the relevance of this approach due to the dynamic nature of financial markets, where traditional methods fall short. Machine learning techniques like linear regression, decision trees, random forests, and automatic learning platforms, combined with deep learning, are powerful tools for predicting market trends and strategic moves. The research addresses the need for accurate forecasting methods, which is critical for investors and analysts. It evaluates the performance of various machine learning models in market uncertainty, focusing on their ability to capture financial data dependencies. Metrics such as RMSE are used to assess model accuracy. Combining deep learning with machine learning techniques improves prediction capabilities. Ensemble methods, which merge multiple models, particularly enhance accuracy. The study identifies future directions, including refining and integrating models into financial institutions’ practices. The study underscores the potential of AI models to transform financial analytics, leading to better decision-making and more balanced, profitable stock portfolios. Implementing these models in financial institutions can significantly improve their ability to navigate market uncertainties and seize opportunities. [ABSTRACT FROM AUTHOR]

This paper discusses the merit of using a no-model approach (no common product models or ontologies, etc.) for managing information in the AEC. It proposes an option for such an approach through the generation and analysis of semantic and social networks of communication between project stakeholders. The proposed approach advocates for a bottomup discovery of knowledge constructs from stakeholder communication. Knowledge constructs are mini two-mode networks containing, on the one hand, clusters of concepts that appear frequently in the semantic networks of stakeholder communication; and, on the other hand, the social networks of stakeholders discussing these concepts. Using common models (such as IFC) has several limitations, including inflexibility to recognize and accommodate project contexts (which vary constantly), inability to timely capture the emergence of knowledge, and the scope creep problem (the ever-existing need to add more concepts to the common model from within and outside ACE domain). The no-model approach presented here is meant to complement and not replace the established model-based approach. This approach is built on the belief in the ontological agency of project stakeholders: knowledge is a social phenomenon that emerges through interactions between people. It advocates a shift from a top-down format where experts or standards clearinghouses tell (force) practitioners what should be true about their project. In every project, stakeholders customize (the structure of) established knowledge and adopt elements from emerging knowledge to address project-specific needs. They use the more superior intelligence (the human one) to innovate a 'model of what they know' to guide the management of the project in a manner specific to its context. By studying projects' communication, we tell (inform) project stakeholders what knowledge constructs can be found in their communication. Unlike generic/static models, the resulting knowledge constructs are by default sensitive to project conditions. We should re-design our information management systems to be able to recognize and adaptively use the constructs established by project teams to facilitate their sharing of data (along with the established scheme, such as IFC). Relatedly used constructs can be nominated as AEC-wide prototype constructs, representing what we know about a typical project. At the initiation of a new project, these can be the starting scheme used by information and communication systems. As the project evolves and the project's own constructs are generated, the project-specific constructs should guide the flow of information. Contrasting project constructs against prototypes should inform the stakeholders of not only what is factual about their view/model of knowledge, but also how unique are they (from generic/base knowledge). This approach to no-model thinking is advantageous for several reasons. First, addressing the model rigidity problem. Because of the increasing complexity of projects, no single/standardized model can capture all contexts. Second, the increasing need for handling project unstructured data. The proposed approach helps formalize knowledge constructs from such data using network science. Third, recognizing and tracking the evolutionary nature of knowledge. Fourth, supporting innovation: instead of forcing knowers (people) to comply with a static model of reality, the new approach encourages them to imagine new possible futures/worlds--after all, the true essence of digital twinning is to virtualize futures not just to digitize the present. [ABSTRACT FROM AUTHOR]

Digital Health Twins (DHTs) hold immense potential to revolutionize healthcare by providing personalized virtual models of individual patients and their health conditions. This position paper discusses about the needs to overcoming the challenges in standardization and information models for data integration, collection, and visualization for realizing the full potential with digital twin technology. By addressing these challenges, digital health twins can enable better decision-making, enhance patient care, and contribute to the advancement of personalized healthcare solutions. [ABSTRACT FROM AUTHOR]

Background: Unambiguous sharing of data requires information models and terminology in combination, but there is a lack of knowledge as to how they should be combined, leading to impaired interoperability.Objectives: To facilitate creation of guidelines for SNOMED CT terminology binding we have performed a literature review to find existing recommendations and expose knowledge gaps. The primary audience is practitioners and researchers working with terminology binding.Methods: PubMed, Scopus, and Web of Science were searched for papers containing "terminology binding," "subset," "map," "information model" or "implement" and the term "SNOMED."Results: The search yielded 616 unique papers published from 2004 to 2020, from which 55 papers were selected and analyzed inductively. Topics described in the papers include problems related to input material, SNOMED CT, information models, and lack of appropriate tools as well as recommendations regarding competence.Conclusion: Recommendations are given for practitioners and researchers. Many of the stated problems can be solved by better co-operation between domain experts and informaticians and better knowledge of SNOMED CT. Settings where these competences either work together or where staff with knowledge of both act as brokers are well equipped for terminology binding. Tooling is not thoroughly researched and might be a possible way to facilitate terminology binding. [ABSTRACT FROM AUTHOR]

Social media encapsulates one of the most prominent human information behaviours that has rapidly evolved to create a new data-driven paradigm that uses data-intensive digital environments to communicate, collaborate, express opinions and support decisions. This has established social media as a unique information asset for value co-creation as it empowers individuals to actively express opinions and sentiment on all facets of interactions with an external entity. Despite recent research on the theoretical underpinnings of social media in open service innovation, practical demonstrations of actionable insights are limited, mainly due to the voluminous and unstructured nature of social media data. We address this limitation by presenting an evidence-based study that uses machine learning algorithms to generate actionable insights of strategic value from this data-driven paradigm. These outcomes provide fresh perspectives and new thinking that advances social media as an emergent information asset for end-to-end open innovation and incremental value co-creation.

The wide-spread use of Common Data Models and information models in biomedical informatics encourages assumptions that those models could provide the entirety of what is needed for knowledge representation purposes. Based on the lack of computable semantics in frequently used Common Data Models, there appears to be a gap between knowledge representation requirements and these models. In this use-case oriented approach, we explore how a system-theoretic, architecture-centric, ontology-based methodology can help to better understand this gap. We show how using the Generic Component Model helps to analyze the data management system in a way that allows accounting for data management procedures inside the system and knowledge representation of the real world at the same time. [ABSTRACT FROM AUTHOR]

The FAIR Principles are a set of recommendations that aim to underpin knowledge discovery and integration by making the research outcomes Findable, Accessible, Interoperable and Reusable. These guidelines encourage the accurate recording and exchange of data, coupled with contextual information about their creation, expressed in domain-specific standards and machine-readable formats. This paper analyses the potential support to FAIRness of the openEHR specifications and reference implementation, by theoretically assessing their compliance with each of the 15 FAIR principles. Our study highlights how the openEHR approach, thanks to its computable semantics-oriented design, is inherently FAIR-enabling and is a promising implementation strategy for creating FAIR-compliant Clinical Data Repositories (CDRs). [ABSTRACT FROM AUTHOR]

Purpose: The rapid implementation of electronic health records (EHRs) resulted in a lack of data standardization and created considerable difficulty for secondary use of EHR documentation data within and between organizations. While EHRs contain documentation data (input), nurses and healthcare organizations rarely have useable documentation data (output). The purpose of this article is to describe a method of standardizing EHR flowsheet documentation data using information models (IMs) to support exchange, quality improvement, and big data research. As an exemplar, EHR flowsheet metadata (input) from multiple organizations was used to validate a fall prevention IM. Design: A consensus‐based, qualitative, descriptive approach was used to identify a minimum set of essential fall prevention data concepts documented by staff nurses in acute care. The goal was to increase generalizable and comparable nurse‐sensitive data on the prevention of falls across organizations for big data research. Methods: The research team conducted a retrospective, observational study using an iterative, consensus‐based approach to map, analyze, and evaluate nursing flowsheet metadata contributed by eight health systems. The team used FloMap software to aggregate flowsheet data across organizations for mapping and comparison of data to a reference IM. The FloMap analysis was refined with input from staff nurse subject matter experts, review of published evidence, current documentation standards, Magnet Recognition nursing standards, and informal fall prevention nursing use cases. Findings: Flowsheet metadata analyzed from the EHR systems represented 6.6 million patients, 27 million encounters, and 683 million observations. Compared to the original reference IM, five new IM classes were added, concepts were reduced by 14 (from 57 to 43), and 157 value set items were added. The final fall prevention IM incorporated 11 condition or age‐specific fall risk screening tools and a fall event details class with 14 concepts. Conclusion: The iterative, consensus‐based refinement and validation of the fall prevention IM from actual EHR fall prevention flowsheet documentation contributes to the ability to semantically exchange and compare fall prevention data across multiple health systems and organizations. This method and approach provides a process for standardizing flowsheet data as coded data for information exchange and use in big data research. Clinical Relevance: Opportunities exist to work with EHR vendors and the Office of the National Coordinator for Health Information Technology to implement standardized IMs within EHRs to expand interoperability of nurse‐sensitive data. [ABSTRACT FROM AUTHOR]

The article deals with the application of the system approach for constructing informationalgorithmic support for the pharmaceutical development of solid dosage forms. Information modeling of the life cycle of pharmaceutical drug development has been carried out starting from the stage of studying the active pharmaceutical substance and ending with the utilization of the drug. These models are built in the IDEF0 nomination. A generalized block diagram is presented that reflects, in its most general form, the iterative process of developing a ready-made dosage form as applied to the further transfer of technology. The basis of the system approach is QbD - "Quality planned in the development". To implement the QbD principle on the basis of the system approach, systemic set-theoretic models of information support of pharmaceutical development in the nomenclature of Melentiev have been constructed. A model for controlling the pressing process is also provided, which takes into account all the technological stages in the development of a solid dosage form. Functional models in the IDEF0 nomenclature of the technological process are constructed from the preparation of premises, personnel and components of the dosage form to the stage of packing and packaging of the finished dosage form. The construction of an informational intellectual control system for pharmaceutical development has been considered in detail with particular attention paid to the construction of a database of medicinal and auxiliary substances using the example of solid dosage forms. In Melentiev's bracket notation, the database of auxiliary substances necessary for the design of a solid dosage form is filled. The "Entity-relationship" model and the relational model for the database of medicinal and auxiliary substances have been constructe

The information explosion the world has witnessed in the last two decades has forced businesses to adopt a data-driven culture for them to be competitive. These data-driven businesses have access to countless sources of information, and face the challenge of making sense of overwhelming amounts of data in a efficient and reliable manner, which implies the execution of read-intensive operations. In the context of this challenge, a framework for the dynamic read-optimization of large dimensional datasets has been designed, and on top of it a workload-driven mechanism for automatic materialized view selection and creation has been developed. This paper presents an extensive description of this mechanism, along with a proof-of-concept implementation of it and its corresponding performance evaluation. Results show that the proposed mechanism is able to derive a limited but comprehensive set of views leading to a drop in query latency ranging from 80% to 99.99% at the expense of 13% of the disk space used by the base dataset. This way, the devised mechanism enables speeding up query execution by building materialized views that match the actual demand of query workloads. [ABSTRACT FROM AUTHOR]

The value of data models in general and information models in specific has been evaluated by many scientific papers. UML as one modelling notation has documented its value as a foundation for precise specifications. Analyzing implementation guides for data exchange, they rarely include or are based on information models but simple data sets, if at all, as simple technical representation thereof. This paper wants to argue in favor of information models as a basis for creating interoperability specifications using a quite simple example and to include - or at least reference - them when providing implementation guides. The reader is invited to transfer this example to even more complex scenarios. [ABSTRACT FROM AUTHOR]

Featured Application: HBIM models generation for managing heritage information, oriented to preventive conservation of assets of cultural interest. This paper discusses the generation of Historic Building Information Models (HBIM) for the management of heritage information aimed at the preventive conservation of assets of cultural interest, through its experimentation in a specific case study: the façade of the Renaissance quadrant of the Cathedral of Seville. Two methodological aspects are presented: On the one hand, the process of modeling the solid entities that compose the digital model of the object of study, based on the semi-automatic estimation of the generating surfaces of the main faces; on the other hand, a methodological proposal for the modeling of information on the surface of the model. A series of images and data tables are shown as a result of the application of these methods. These represent the process of introducing information related to the current conservation status documentation and recording the treatments included in the preventive conservation works recently developed by a specialized company. The implementation of the digital model in the exposed work validates it as a solvency option, provided from the infographic medium, when facing the need to contain, manage and visualize all the information generated in preventive conservation actions on heritage architecture, facilitating, in turn, cross-cutting relationships between the different analysis that result in a deeper knowledge of this type of building. [ABSTRACT FROM AUTHOR]

There are many factors affecting review duration after a paper has been submitted to a journal. Developing a time-to-acceptance model of each journal for the whole time span from submission to acceptance can help researchers when they are selecting journals to publish research results, as well as help editors when they are optimizing workflow and strategy. Using ISI-indexed journals in the profession of library and information science as an example, this study aims to explore the possible patterns of time-to-acceptance for refereed articles. Based on the theories of maximum likelihood estimation, this article models probability distributions for the retrieved data through the R package fitdistrplus. The Kolmogorov-Smirnov test is further used to determine if the distribution for each journal can be accepted.

One form of activity in cyberspace is the information battle. One of the proposed definitions will define it as a negative co–operation in the sphere of information acquisition, information distortion and information defense, where each side of the action is subordinated to the antagonistic side of the other. It leads to the achievement of political objectives and is aimed at overthrowing the systems of the state responsible for the state of its security. It is important that this condition is at a high, or at least acceptable, level. To ensure this level, it is important to define cybersecurity fighting models that are adequate for the threats and to determine their impact on the level of national security risk in cyberspace. Literature on the subject contains many models of cyberwarfare information that have been shaped in recent years. However, there is no assessment of the adequacy of these models for the risks and risks associated with national security threats. It should be noted that information security itself, as part of national security, is variable. New threats are emerging and, at a very high rate and with high activity in cyberspace, they are capable of destabilising the security of key state administration bodies, military facilities and other important state– run infrastructures. It should be emphasised that existing cyberspace fighting information models are not universal and cannot be used for any type of threat to national security. They need to find, organise and evaluate those that would be the most appropriate not only for national security threats but also for geopolitical determinants. Assumptions for the research and its results are a noticeable increase in the number of cyberattacks, some of which are important from the point of view of national security – the military system and critical infrastructure elements of the state. The following subject of the research was adopted in the article – models of information fight, related to threats to national security coming from / to cyberspace. The purpose of scientific research is to define models of information combat and to determine the suitability and evaluation of these models for the purpose of evaluating the risks of national security threats. Identifying the subject and objectives of the research led to a general research question: What appropriate models of information fight in cyberspace can be defined and used for the risks of national security threats? The research method applied theoretical methods (analysis, synthesis, generalisation, abstraction, inference, analogy and comparison) as well as the empirical method of dialogue and the method of participant observation.

The role of information technologies as interindustry direction of science is presented. The hypothesis of possibility of their uniform information description on the basis of the law on substance circulation in the nature and dialectic interrelation of objects of agricultural production is formulated: earth, plants, animals, machines, environment and society. The interrelation of these resources and its optimality (rationality) is possible on the basis of use of information technologies that in many respects defines efficiency of agrarian production. These postulates unite using a paradigm of information support of technological processes of agricultural production. It is represented by set of objective information (devices, measuring computer systems, information and measuring systems, bases and knowledge data) and subjective one, used at creation of devices, information, expert, and artificial intelligence systems. The authors worked out blocks of information models, calculated and justificated size of the converted word and the size of data stream of the universal block. Their technique of creation of «virtual laboratory» of engine 4Ch10.5/12 (D-144) research with use of the device of data collection of NI PCI-6251 is presented. A special software application is developed to realize interpolating of data of 4-factorial experiment at research of an internal combustion engine.

This paper discusses the generation of Historic Building Information Models (HBIM) for the management of heritage information aimed at the preventive conservation of assets of cultural interest, through its experimentation in a specific case study: the façade of the Renaissance quadrant of the Cathedral of Seville. Two methodological aspects are presented: On the one hand, the process of modeling the solid entities that compose the digital model of the object of study, based on the semi-automatic estimation of the generating surfaces of the main faces; on the other hand, a methodological proposal for the modeling of information on the surface of the model. A series of images and data tables are shown as a result of the application of these methods. These represent the process of introducing information related to the current conservation status documentation and recording the treatments included in the preventive conservation works recently developed by a specialized company. The implementation of the digital model in the exposed work validates it as a solvency option, provided from the infographic medium, when facing the need to contain, manage and visualize all the information generated in preventive conservation actions on heritage architecture, facilitating, in turn, cross-cutting relationships between the different analysis that result in a deeper knowledge of this type of building.

This study aims to improve the interoperability between the application domains of Building Information Modelling (BIM) and Geographic Information Systems (GIS) by linking and harmonizing core information concepts. Many studies have investigated the integration of application schemas and data instances according to the BIM model IFC and the GIS model CityGML. This study investigates integration between core abstract concepts from IFC and ISO/TC 211 standards for GIS—independent of specific application schemas. A pattern was developed for conversion from IFC EXPRESS schemas to Unified Modelling Language (UML) models according to ISO/TC 211 standards. Core concepts from the two application domains were linked in the UML model, and conversions to implementation schemas for the Geography Markup Language (GML) and EXPRESS were tested. The results showed that the IFC model could be described as an ISO/TC 211 compliant UML model and that abstract concepts from ISO/TC 211 standards could be linked to core IFC concepts. Implementation schemas for BIM and GIS formats could be derived from the UML model, enabling implementation in applications from both domains without conversion of concepts. Future work should include refined linking and harmonization of core abstract concepts from the two application domains.

Disassembly, a process of separating the end of life (EOL) product into discrete components for re-utilizing their associated residual values, is an important enabler for the sustainable manufacturing. This work focuses on the modeling of the disassembly planning related information and develops a disassembly information model (DIM) based on an extensive investigation of various informational aspects in the domain of disassembly planning. The developed DIM, which represents an appropriate systematization and classification of the products, processes, uncertainties, and degradations related information, follows a layered modeling methodology in which DIM is subdivided into layers with the intent to separate general knowledge into different levels of abstractions and reach a balance between information reusability and information usability. Two prototype disassembly planning related applications have been incorporated to validate the usability and reusability of the developed DIM. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) offers significant opportunities for product innovation in many fields provided that designers are able to recognize the potential values of AM in a given product development process. However, this may be challenging for design teams without substantial experience with the technology. Design inspiration based on past successful applications of AM may facilitate application of AM even in relatively inexperienced teams. While designs for additive manufacturing (DFAM) methods have experimented with reuse of past knowledge, they may not be sufficient to fully realize AM's innovative potential. In many instances, relevant knowledge may be hard to find, lack context, or simply unavailable. This design information is also typically divorced from the underlying logic of a products' business case. In this paper, we present a knowledge based method for AM design ideation as well as the development of a suite of modular, highly formal ontologies to capture information about innovative uses of AM. This underlying information model, the innovative capabilities of additive manufacturing (ICAM) ontology, aims to facilitate innovative use of AM by connecting a repository of a business and technical knowledge relating to past AM products with a collection of knowledge bases detailing the capabilities of various AM processes and machines. Two case studies are used to explore how this linked knowledge can be queried in the context of a new design problem to identify highly relevant examples of existing products that leveraged AM capabilities to solve similar design problems. [ABSTRACT FROM AUTHOR]

The class of problems of indirect control and diagnostics of complex continuous nonlinear dynamic objects of different physical nature is considered. These tasks relate to the class of problems of inductive modeling, the essence of which is the transition from empirical information to a mathematical model in order to obtain new knowledge and decision making in conditions of material incompleteness and apriline uncertainty of information. The purpose of the work is to solve the problem of ensuring the universality of the diagnostic procedure by developing a generalized model of diagnostic procedure based on the organization of interaction between subsystems of automated diagnostic systems, taking into account the influence of the external environment, the choice of optimal modes of functioning for the creation of effective instrumental means of diagnosing objects of different nature in conditions of incomplete a priori information. The mathematical model of the diagnosing process in the form of a finite automaton, which realizes some mapping of the plural of words of the input alphabet into the set of words of the original alphabet, is proposed. In order to construct a universal diagnostic procedure for complex objects of diagnosing different physical nature, the key stages of the transformation of diagnostic information (constructing a classifier) and the stages of verification of the obtained models at each level have been determined. The V-model of the procedure for diagnosing complex objects of diagnostics of different physical nature under a priori uncertainty conditions is proposed. To construct the algorithm of the functioning of automated diagnostic systems, the generalized essence of the diagnostic process, on the basis of which the algorithm of diagnosing nonlinear dynamic objects of different physical nature under the conditions of incomplete apriline information is allocated. [ABSTRACT FROM AUTHOR]

Contemporary industrial systems are challenged by fast-growing requirements for agile and effective reactivity to rapidly changing market demands. To achieve this set of requirements, new technologies and paradigms like Internet-of-Things (IoT), Big Data Analytics, Internet-of-Services (IoS), and service-oriented architecture (SOA) are being introduced into the industrial environments. These advances result in the confluence of two dissimilar, but complementary domains: the physical operational technologies (OT) and the cyber information technologies (IT) domains. Convergence of these two domains in a cross-layer fashion implies a new set of two major requirements of components and systems: 1) structural connectivity and 2) functional interoperability. However, the wide variety and heterogeneity of industrial systems—especially in the factory floor—entails integration complexity, which is in contrast with the mentioned requirements. In this paper, we focus on how legacy industrial systems can migrate in a cost-effective manner to the new paradigm of integrated IT–OT levels. We propose an interoperability layer requiring no changes on the legacy device that maps field device data into an ISA95-based information model. The performance of our contributed open-source implementation is evaluated in several deployment configurations. [ABSTRACT FROM PUBLISHER]

Information exchange and sharing become a necessity for digital factory but they have been more challenging as the industry is computerized more. This is mainly because the capabilities of computerized systems have grown significantly in a very rapid pace in their own information structure, and they require to retrieve various data from different computer systems. ISO 10303-STEP has been developed to provide a neutral format for exchanging product data. However, implementation of STEP has several issues, including the following two: (1) the complete STEP file should be processed even for querying a small set of data, and (2) information required for realizing any functional activity (e.g., any analysis on any part of a product) is not explicitly identified. Hence, in this study, functionality-based conformance classes (FCCs) are developed to organize the current conformance classes (CCs) (which are the classes required to be implemented fully in order to be conformant to any particular STEP standard) for supporting different functional activities. Following the concept of data exchange specification (DEX)/template, several templates that are repeatedly used small information groups are introduced in order to create manageable sets of data constructs. In this study, the FCCs for 1D tolerance analysis are developed by enriching the available STEP information models with GD&T. The use of extended STEP models is illustrated with a case study. [ABSTRACT FROM AUTHOR]

The manufacturing industry is evolving and starting to use three-dimensional (3D) models as the central knowledge artifact for product data and product definition, or what is known as model-based definition (MBD). The model-based enterprise (MBE) uses MBD as a way to transition away from using traditional paper-based drawings and documentation. As MBD grows in popularity, it is imperative to understand what information is needed in the transition from drawings to models so that the models represent all the relevant information needed for processes to continue efficiently. Finding this information can help to define what data are common amongst different models in different stages of the lifecycle, which could help to establish a common information model. The common information model is a source that contains common information from domain specific elements amongst different aspects of the lifecycle. To help establish this common information model, information about how models are used in the industry within different workflows needs to be understood. To retrieve this information, a survey mechanism was administered to industry professionals from various sectors. Based on the results of the survey a common information model could not be established. However, the results gave great insight that will help in further investigation of the common information model. [ABSTRACT FROM AUTHOR]

Information approach possibilities to model different groups of operational excellence measures interrelations for investment projects has been demonstrated. This model is a tool to understand how production possibilities frontier (PPF) for real estate business is formed and to suggest a most promising paths for its innovation development.

In this article, key points are discussed concerning knowledge representation for clinical decision support systems in the domain of physical medicine and rehabilitation. Information models, classifications and terminologies, such as the “virtual medical record” (vMR), the “international classification of functioning, disability and health” (ICF), the “international classification of diseases” (ICD) and the “systematized nomenclature of medicine—clinical terms” (SNOMED CT), are used for knowledge integration and reasoning. A system is described that supports the measuring of functioning status, diversity, prognosis and similarity between patients in the post-acute stage, thus helping health professionals’ prescription of recommendations.

This article is based on the findings of a study on access and use of poultry management information in rural Tanzania. It highlights the connection between the information system, rural farmers and information providers; and how those linkages can impact information access, usage and farmers' satisfaction. The study findings suggest that rural information dissemination in Tanzania is planned without consulting the rural farmers, resulting in limited access and underutilisation of information. Based on the study findings and drawing on the information systems success model and quadratic usage framework, a model fo r agricultural information dissemination in the context of rural Tanzania is proposed. The proposed model addresses the need to understand the target community before embarking on information dissemination. It places more emphasis on understanding farmers' community, rather than focusing on the information per se. [ABSTRACT FROM AUTHOR]

Despite the popularity of the subject, one surprising aspect of building automation (BA) is the scarcity of authoritative literature references regarding the topic. This situation hampers communication between developers and contributes to the well-known problem of heterogeneity where there is difficulty in integrating solutions from different manufacturers with each other. This article systematizes fundamental concepts and requirements of BA systems, defining each aspect based upon established literature standards. Using these aspects as guidelines, the main BA technology specifications available are then reviewed with respect to their coverage of features. We then proceed by showing that none of the analyzed specifications are able to totally cover the expected standard functionality span of BA. Finally, we conclude that none of the existing approaches are able to fully overcome the problem of heterogeneity by satisfactorily addressing all the aspects of BA endorsed by the standards. [ABSTRACT FROM AUTHOR]

This work is looking to methodological aspects of process modelling. The point of view is more from Process System Engineering (PSE) in order to develop formal and generic techniques for process modelling, and to use representation formalisms matched to computer based modelling environments. A metamodelling approach based on phenomena is presented and discussed. The framework is easy to understand, easy to implement from computational point of view, and can be used as departure point in developing a new generation of modelling languages: languages based on phenomena. The phenomena based metamodelling approach makes the modelling process more efficient for collaboration in heterogeneous modelling environments composed from different and difficult actors: modellers, users and computers.

There are various scenarios in which someone might want to remotely access the data of agricultural machinery. In this article, we concentrate on telematics applications, where the manager of a vehicle fleet has an interest in seeing both what the vehicles are doing and where they are in real time. In this article the feasibility of using OPC Unified Architecture (OPC UA) technology to transfer ISO 11783 related process data between a mobile agricultural vehicle and the Internet is studied. A device containing an ISO 11783 Data Logger, an OPC UA server and a mobile network connection was designed and installed in a vehicle. A capability for downloading and interpreting a ISO 11783 Data Dictionary Object Pool (DDOP) was designed for the OPC UA server application in order to link the ISO 11783 and OPC UA standards together. The system was evaluated by transferring a few process data variables over a 3G connection from a tractor and a connected seed drill. The latency and bandwidth usage of communication were measured and found feasible for telematics. In addition to this, the approach for converting a DDOP to an OPC UA information model was observed to be functional. [ABSTRACT FROM AUTHOR]