A framework for integrating syntax, semantics and pragmatics for computer-aided professional practice: With application of costing in construction industry

Producing a bill of quantity is a knowledge-based, dynamic and collaborative process, and evolves with variances and current evidence. However, within the context of information system practice in BIM, knowledge of cost estimation has not been represented, nor has it been integrated into the processes based on BIM. This paper intends to establish an innovative means of taking data from the BIM linked to a project, and using it to create the necessary items for a bill of quantity that will enable cost estimation to be undertaken for the project. Our framework is founded upon the belief that three components are necessary to gain a full awareness of the domain which is being computerised; the information type which is to be assessed for compatibility (syntax), the definition for the pricing domain (semantics), and the precise implementation environment for the standards being taken into account (pragmatics). In order to achieve this, a prototype is created that allows a cost item for the bill of quantity to be spontaneously generated, by means of the semantic web ontology and a forward chain algorithm. Within this paper, ‘cost items’ signify the elements included in a bill of quantity, including details of their description, quantity and price. As a means of authenticating the process being developed, the authors of this work effectively implemented it in the production of cost items. In addition, the items created were contrasted with those produced by specialists. For this reason, this innovative framework introduces the possibility of a new means of applying semantic web ontology and forward chain algorithm to construction professional practice resulting in automatic cost estimation. These key outcomes demonstrate that, decoupling the professional practice into three key components of syntax, semantics and pragmatics can provide tangible benefits to domain use

A multi-agent system for pervasive healthcare

Wireless technology based pervasive healthcare has been proposed in many applications such as disease management and accident prevention for cost saving and promoting citizen’s wellbeing. However, the emphasis so far is on the artefacts with limited attentions to guiding the development of an effective and efficient solution for pervasive healthcare. Therefore, this paper aims to propose a framework of multi-agent systems design for pervasive healthcare by adopting the concept of pervasive informatics and using the methods of organisational semiotics. The proposed multi-agent system for pervasive healthcare utilises sensory information to support healthcare professionals for providing appropriate care. The key contributions contain theoretical aspect and practical aspect. In theory, this paper articulates the information interactions between the pervasive healthcare environment and stakeholders by using the methods of organisational semiotics; in practice, the proposed framework improves the healthcare quality by providing appropriate medical attentions when and as needed. In this paper, both systems and functional architecture of the multi-agent system are elaborated with the use of wireless technologies such as RFID and wireless sensor networks. The future study will focus on the implementation of the proposed framework

Dynamical Friction Models for Black-Hole Binary Formation in AGN Disks

Stellar-mass black holes (sBH) embedded in gaseous disks of active galactic nuclei (AGN) can be important sources of detectable gravitational radiation for LIGO/Virgo when they form binaries and coalesce due to orbital decay. In this paper, we study the effect of gas dynamical friction (DF) on the formation of BH binaries in AGN disks using $N$-body simulations. We employ two simplified models of DF, with the force on the BH depending on $\Delta {\bf v}$, the velocity of the sBH relative to the background Keplerian gas. We integrate the motion of two sBH initially on circular orbits around the central supermassive black hole (SMBH), and evaluate the probability of binary formation under various conditions. We find that both models of DF (with different dependence of the frictional coefficient on $|\Delta{\bf v}|$) can foster the formation of binaries when the effective friction timescale $\tau$ satisfies $\Omega_{\rm K}\tau\lesssim 20-30$ (where $\Omega_{\rm K}$ is the Keplerian frequency around the SMBH): prograde binaries are formed when the DF is stronger (smaller $\tau$), while retrograde binaries dominate when the DF is weaker (larger $\tau$). We determine the distribution of both prograde and retrograde binaries as a function of initial orbital separation and the DF strength. Using our models of DF, we show that for a given sBH number density in the AGN disk, the formation rate of sBH binaries increases with decreasing $\tau$ and can reach a moderate value with a sufficiently strong DF.Comment: 17 pages, 13 figures, submitted to Ap

Pragmatic oriented data interoperability for smart healthcare information systems

Smart healthcare is a complex domain for systems integration due to human and technical factors and heterogeneous data sources involved. As a part of smart city, it is such a complex area where clinical functions require smartness of multi-systems collaborations for effective communications among departments, and radiology is one of the areas highly relies on intelligent information integration and communication. Therefore, it faces many challenges regarding integration and its interoperability such as information collision, heterogeneous data sources, policy obstacles, and procedure mismanagement. The purpose of this study is to conduct an analysis of data, semantic, and pragmatic interoperability of systems integration in radiology department, and to develop a pragmatic interoperability framework for guiding the integration. We select an on-going project at a local hospital for undertaking our case study. The project is to achieve data sharing and interoperability among Radiology Information Systems (RIS), Electronic Patient Record (EPR), and Picture Archiving and Communication Systems (PACS). Qualitative data collection and analysis methods are used. The data sources consisted of documentation including publications and internal working papers, one year of non-participant observations and 37 interviews with radiologists, clinicians, directors of IT services, referring clinicians, radiographers, receptionists and secretary. We identified four primary phases of data analysis process for the case study: requirements and barriers identification, integration approach, interoperability measurements, and knowledge foundations. Each phase is discussed and supported by qualitative data. Through the analysis we also develop a pragmatic interoperability framework that summaries the empirical findings and proposes recommendations for guiding the integration in the radiology context

Value co‐creation between foreign firms and indigenous small‐ and medium‐sized enterprises (SMEs) in Kazakhstan's oil and gas industry: the role of information technology spillovers

Study related to the extractive sector still plays a limited role in the mainstream international business (IB) and management literature, with even less focus on ongoing liberalisation and digitalisation in the industry. This paper was motivated by the question of how collaboration between foreign and indigenous oil and gas (O&G) companies can support small and mediumsized indigenous technological development. A three-stage qualitative–interpretive method based on interviews with industry experts has been adopted in order to build three case studies. The main contribution of this paper is the development of a model that explains how different actors can cocreate value in the ecosystem of public–private partnership (PPP) in the O&G industry through digital technologies. This paper proposes what companies and the government could do to increase the competitiveness of the local economy, diversify from O&G into high technological industries, and support industrial development through information and communication technologies (ICT)

Knowledge-based clinical pathway for medical quality improvement

Clinical pathways have been adopted for various diseases in clinical departments for quality improvement as a result of standardization of medical activities in treatment process. Using knowledge-based decision support on the basis of clinical pathways is a promising strategy to improve medical quality effectively. However, the clinical pathway knowledge has not been fully integrated into treatment process and thus cannot provide comprehensive support to the actual work practice. Therefore this paper proposes a knowledgebased clinical pathway management method which contributes to make use of clinical knowledge to support and optimize medical practice. We have developed a knowledgebased clinical pathway management system to demonstrate how the clinical pathway knowledge comprehensively supports the treatment process. The experiences from the use of this system show that the treatment quality can be effectively improved by the extracted and classified clinical pathway knowledge, seamless integration of patient-specific clinical pathway recommendations with medical tasks and the evaluating pathway deviations for optimization

Domain Generalization with Small Data

In this work, we propose to tackle the problem of domain generalization in the context of insufficient samples. Instead of extracting latent feature embeddings based on deterministic models, we propose to learn a domain-invariant representation based on the probabilistic framework by mapping each data point into probabilistic embeddings. Specifically, we first extend empirical maximum mean discrepancy (MMD) to a novel probabilistic MMD that can measure the discrepancy between mixture distributions (i.e., source domains) consisting of a series of latent distributions rather than latent points. Moreover, instead of imposing the contrastive semantic alignment (CSA) loss based on pairs of latent points, a novel probabilistic CSA loss encourages positive probabilistic embedding pairs to be closer while pulling other negative ones apart. Benefiting from the learned representation captured by probabilistic models, our proposed method can marriage the measurement on the distribution over distributions (i.e., the global perspective alignment) and the distribution-based contrastive semantic alignment (i.e., the local perspective alignment). Extensive experimental results on three challenging medical datasets show the effectiveness of our proposed method in the context of insufficient data compared with state-of-the-art methods

e-Leadership through strategic alignment: an empirical study of small- and medium-sized enterprises in the digital age

Small- and medium-sized enterprises (SMEs) play an important role in the European economy. A critical challenge faced by SME leaders, as a consequence of the continuing digital technology revolution, is how to optimally align business strategy with digital technology to fully leverage the potential offered by these technologies in pursuit of longevity and growth. There is a paucity of empirical research examining how e-leadership in SMEs drives successful alignment between business strategy and digital technology fostering longevity and growth. To address this gap, in this paper we develop an empirically derived e-leadership model. Initially we develop a theoretical model of e-leadership drawing on strategic alignment theory. This provides a theoretical foundation on how SMEs can harness digital technology in support of their business strategy enabling sustainable growth. An in-depth empirical study was undertaken interviewing 42 successful European SME leaders to validate, advance and substantiate our theoretically driven model. The outcome of the two stage process – inductive development of a theoretically driven e-leadership model and deductive advancement to develop a complete model through in-depth interviews with successful European SME leaders – is an e-leadership model with specific constructs fostering effective strategic alignment. The resulting diagnostic model enables SME decision makers to exercise effective e-leadership by creating productive alignment between business strategy and digital technology improving longevity and growth prospects

E-Leadership through Strategic Alignment: An Empirical Study of Small- and Medium-sized Enterprises in the Digital Age

Small- and medium-sized enterprises (SMEs) play an important role in the European economy. A critical challenge faced by SME leaders, as a consequence of the continuing digital technology revolution, is how to optimally align business strategy with digital technology to fully leverage the potential offered by these technologies in pursuit of longevity and growth. There is a paucity of empirical research examining how e-leadership in SMEs drives successful alignment between business strategy and digital technology fostering longevity and growth. To address this gap, in this paper we develop an empirically derived e-leadership model. Initially we develop a theoretical model of e-leadership drawing on strategic alignment theory. This provides a theoretical foundation on how SMEs can harness digital technology in support of their business strategy enabling sustainable growth. An in-depth empirical study was undertaken interviewing 42 successful European SME leaders to validate, advance and substantiate our theoretically driven model. The outcome of the two stage process – inductive development of a theoretically driven e-leadership model and deductive advancement to develop a complete model through in-depth interviews with successful European SME leaders – is an e-leadership model with specific constructs fostering effective strategic alignment. The resulting diagnostic model enables SME decision makers to exercise effective e-leadership by creating productive alignment between business strategy and digital technology improving longevity and growth prospects