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The purpose of this paper is to introduce a new method of ontology‐based digital product data exchange. The digital product data are enriched with virtual prototype (VP) model information and the designed exchange process is discussed. Additionally, an algorithm enabling the ontology‐based data exchange method among missile guide systems is proposed and analyzed.

Semantic sevice‐oriented architecture (SSOA) is an innovative integration architecture for digital product information integration and process integration. In digital product ontology layer of SSOA, a new method of ontology‐based product data exchange is proposed. Compared with traditional information exchange, the method adds the VP's information to general digital products' information. The VP's information is described by building VP static structure ontology and dynamic behavior ontology. The exchange process of the novel method is discussed in detail. Finally, an example illustrating the data exchange among missile guide systems is given and the merits of the proposed method is analyzed.

Simulation information, especially VP information, is not always well defined and taken into account by product data exchange systems such as product data management or product lifecycle management. A formal description of VP information is often required in efficient and effective product data exchange. The goal is to define VP structure and behavior ontologies to enable ontology‐based digital product data exchange.

Using VP information including structure information and behavior information, the paper provides a new method of digital product data exchange.

Facilitating the information exchange and interoperability between stakeholders during the life-cycle of an asset can be one of the fundamental necessities for developing an enhanced information exchange framework. Such a framework can also improve the successful accomplishment of building projects. This paper aims to use Semantic Web technologies for facilitating information exchange within existing building projects.

In real-world building projects, the construction industry’s information supply chain may initiate from near scratch when new building projects are started resulting in diverse data structures represented in unstructured data sources, like Excel spreadsheets and documents. Large-scale data generated throughout a building's life-cycle requires exchanging and processing during an asset's Operation and Maintenance (O&M) phase. Building information modelling (BIM) processes and related technologies can address some of the challenges and limitations of information exchange and interoperability within new building projects. However, the use of BIM in existing and retrofit assets has been hampered by the challenges surrounding the limitations of existing technologies.

The aim of this paper is twofold. Firstly, it briefly outlines the framework previously developed for generating semantically enriched 3D retrofit models. Secondly, a framework is proposed focussing on facilitating the information exchange and interoperability for existing buildings. Semantic Web technologies and standards, such as Web Ontology Language and existing AEC domain ontologies are used to enhance and improve the proposed framework.

The proposed framework is evaluated by implementing an example application and the Resource Description Framework data produced by the previously developed framework. The proposed approach makes a valuable contribution to the asset/facilities management (AM/FM) domain. It should be of interest to various FM practices for existing assets, such as the building information/knowledge management for design, construction and O&M stages of an asset’s life-cycle.

The purpose of this study is to address challenges in the current information exchange process between building information modelling (BIM) and facilities management (FM) systems and to propose a workable solution. This study’s objective is to identify the information exchange requirements and to develop methods for seamless information flow between building information models and FM systems.

Data collection and analysis was based on an extensive literature review of similar studies followed by a questionnaire survey with a total of 112 participants and 2 focus groups with a total of 12 participants to validate the conceptual framework. The outputs of the survey analysis formed the background of the proposed framework to streamline information exchange process between building information models and FM systems.

The study findings form a foundation for enabling the integration of various data sources including building information models. Such integrated platforms will enable automated information exchange between the various data sources and FM systems. The study also provides key information requirements sources to complement the existing construction operations building information exchange information and to support standardization for information exchange process.

The contribution of this study is the identification of information exchange requirements and sources to enable seamless information flow between BIM and FM systems. The study findings will also lay the basis for research studies using the developed framework context to enable the identification of specific data outputs for FM systems inputs.

Suggests that a number of assumptions in the past have been made about how business process improvement, re‐engineering and organizational learning should take place in organizations. Points out that, although a number of these assumptions have been framed on theoretical models, few have been based on the empirical analysis of the nature of actual business processes. Tries to fill this gap with an analysis of data, information and knowledge exchanges in 22 business processes from three organizations. Points to a number of characteristics that appear to be contradictory to some current organizational practices, and that can be helpful to inform future developments in the fields of business process improvement, re‐engineering and organizational learning. Two relevant characteristics are a much higher proportion of data over material exchanges in business processes, and a higher proportion of knowledge exchanges in improvement over core and support processes.

Formats for the exchange of bibliographic data use the ISO 2709 record structure which started out as the structure for the Library of Congress MARC format. The UNISIST Reference Manual was an early international exchange format developed by ICSU‐AB and Unesco and included cataloguing rules suitable for use by A & I Services. The national libraries developed UNIMARC under IFLA auspices as their exchange format since the national formats were not totally compatible. Unesco, concerned about the lack of compatibility between the major international exchange formats, sponsored a symposium, resulting from which a Common Communication Format was developed and ISO began work on a data element directory. International formats also exist for nuclear and agricultural information as well as for serials data. Other formats exist which are used internationally and have different structural characteristics. The International MARC Network Study Steering Committee has taken an interest in the exchange of bibliographic data and has organized a test of UNIMARC and supervised a UNIMARC Handbook to clarify the format. International exchange formats tend to acquire accompanying cataloguing rules: indeed they will only be really effective if there are internationally accepted cataloguing rules and authority files.

To explain an October 16, 2018 US Securities and Exchange Commission order that unanimously upheld a SIFMA challenge to fee increases for “depth-of-book” market data filed by Nasdaq and NYSE Arca and the SEC’s simultaneous remanding of over 400 market data fee and other filings back to the exchanges for consideration under the standards set out in the order.

Explains the criteria for fee increases under the Exchange Act, the SEC’s historic routine approval of exchanges’ proposed fee increases, the SEC’s challenge to two recent market data filings, and the SEC’s remanding of 400 additional market data fee filings challenged by SIFMA to the exchanges and the National Market System (NMS) for reconsideration. Analyzes and discusses the SEC’s order.

The SECs’ SIFMA order appears to raise the bar significantly for what exchanges must show to justify fee increases.More broadly, all five SEC Commissioners (of both parties) appear to be rethinking the role of for-profit exchanges in the regulatory structure.These orders have the potential to rewrite the regulation of market data, other exchange fees, and potentially the relationship between the exchanges and other market participants, for the entire securities industry.

Practical guidance from experienced securities lawyers.

This study constructs time series model, artificial neural networks (ANNs) and statistical topologies to examine the volatility and forecast foreign exchange rates. The Mauritian forex market has been utilized as a case study, and daily data for nominal spot rate (during a time period of five years spanning from 2014 to 2018) for EUR/MUR, GBP/MUR, CAD/MUR and AUD/MUR have been applied for the predictions.

Autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH) models are used as a basis for time series modelling for the analysis, along with the non-linear autoregressive network with exogenous inputs (NARX) neural network backpropagation algorithm utilizing different training functions, namely, Levenberg–Marquardt (LM), Bayesian regularization and scaled conjugate gradient (SCG) algorithms. The study also features a hybrid kernel principal component analysis (KPCA) using the support vector regression (SVR) algorithm as an additional statistical tool to conduct financial market forecasting modelling. Mean squared error (MSE) and root mean square error (RMSE) are employed as indicators for the performance of the models.

The results demonstrated that the GARCH model performed better in terms of volatility clustering and prediction compared to the ARIMA model. On the other hand, the NARX model indicated that LM and Bayesian regularization training algorithms are the most appropriate method of forecasting the different currency exchange rates as the MSE and RMSE seemed to be the lowest error compared to the other training functions. Meanwhile, the results reported that NARX and KPCA–SVR topologies outperformed the linear time series models due to the theory based on the structural risk minimization principle. Finally, the comparison between the NARX model and KPCA–SVR illustrated that the NARX model outperformed the statistical prediction model. Overall, the study deduced that the NARX topology achieves better prediction performance results compared to time series and statistical parameters.

The foreign exchange market is considered to be instable owing to uncertainties in the economic environment of any country and thus, accurate forecasting of foreign exchange rates is crucial for any foreign exchange activity. The study has an important economic implication as it will help researchers, investors, traders, speculators and financial analysts, users of financial news in banking and financial institutions, money changers, non-banking financial companies and stock exchange institutions in Mauritius to take investment decisions in terms of international portfolios. Moreover, currency rates instability might raise transaction costs and diminish the returns in terms of international trade. Exchange rate volatility raises the need to implement a highly organized risk management measures so as to disclose future trend and movement of the foreign currencies which could act as an essential guidance for foreign exchange participants. By this way, they will be more alert before conducting any forex transactions including hedging, asset pricing or any speculation activity, take corrective actions, thus preventing them from making any potential losses in the future and gain more profit.

This is one of the first studies applying artificial intelligence (AI) while making use of time series modelling, the NARX neural network backpropagation algorithm and hybrid KPCA–SVR to predict forex using multiple currencies in the foreign exchange market in Mauritius.

The purpose of this study is to outline the problems associated with asset information management using the Construction Operations Building Information Exchange (COBie) standard and to analyse the causes of industry failure to successfully adopt the standard. Based on this analysis, the paper will propose a process model, namely, Lifecycle Exchange of Asset Data (LEAD) to manage asset dataflow between all building stakeholders from design to construction and ultimately to the facility management team. This model aims to help the construction supply chain to produce complete and high-quality asset data that supports the operation phase of the built environment.

A review of relevant studies provided a theoretical background for this study. The authors then collected and analysed COBie data from five live construction projects using building information modelling (BIM) projects from different design and construction companies. The process model is based on an industry placement within Bouygues UK construction company, which was a Tier 1 building contractor in London in the period from December 2016 to December 2018. The researcher used an inductive approach observing current practises in two construction projects to produce “LEAD” model. Then a focus group was conducted with industry experts to discuss and refine the process model.

Analysis of literature and data collected in the course of this study revealed that although COBie is a BIM Level 2 standard in the UK, there is currently a low success rate in producing complete and accurate COBie data in the UK construction industry. This low rate is because of COBie’s rigid data syntax/structure, complexity and ambiguity of its data exchange process, which suggests that COBie may not be the future of the industry. Based on these findings, the study proposed a process model, namely, “LEAD,” to improve COBie output and also to be used with project-specific information requirements.

To the best of the authors’ knowledge, this paper is one of the first to focus solely on asset data exchange process using COBie standard and highlights the problems the industry faces in this remit. The study is based on industry placement for two years, so the analysis is based on actual and current industry problems. Current industry practices also informed the “LEAD” model, and the model provides a step-by-step guidance in producing and exchanging BIM asset data in all stages of the building lifecycle.

This paper provides a detailed analysis of the most common problems associated with COBie as an asset data exchange standard. Understanding these problems is of high value for industry practitioners to avoid them in projects. The paper also proposed a novel process model that can be used either to improve COBie quality or can be used with any project-specific data requirements.

This report aims to present the state of play of semantic interoperability problems in social security data exchanges.

The subject is presented as an open issue and taking into account the circumstances of the exchanges. Electronic exchanges in European Union social security are used as a case study.

Semantic level of these exchanges seems to be the weakness and the use of controlled vocabularies is proposed as possible solution. The creation and maintenance of metadata sets are finally considered as a compromise solution.

The article proposes a solution for the current semantic problems in electronic exchanges of social security information. The solution could be useful for social security institutions all over the world.

This paper aims to apply blockchains (BCs) for trade clearing and settlement in a realistic clearinghouse. The purpose is to demonstrate the feasibility and scalability of this approach.

The study uses account BCs and trading BCs as building blocks for trade clearing and settlement. Careful design is made to ensure that this approach is feasible and scalable.

A design has been proposed that can process hundreds of thousands of trades for a clearinghouse and it addresses performance, privacy and scalability of realistic trade clearing and settlement. The design has been implemented and experimented in a clearinghouse for over two months and processes over 3B real transactions from an exchange. The first month was to experiment with the system with historical data, the second month was to experiment with real-time data during market trading hours. The system performed as designed and intended.

This is the first large research paper that applied BCs for clearing in the world. The authors applied the system to a clearinghouse and processed over 3 billion transactions, equivalent to 13 years of London Stock Exchange transaction volume, demonstrating that BCs can handle a large number of transactions.

The design can be duplicated to many clearinghouses in the world, and this also paves the way BCs can be used in large financial institutions.

An implication is that other trading firms, clearinghouses and banks can apply the same technology for trade clearing, ushering the way BCs can be used in institutions. As clearing is a core function in business transactions, this has significant implications. The design can be discussed and improved in various communities.

As this is the first application of BCs to large clearinghouses that uses unique BC designs. This has significant value. Many studies have been performed but few have been reported in the scientific community. The system has been implemented, experimented and demonstrated in public for months.