Specification of vertical semantic consistency rules of UML class diagram refinement using logical approach

Unified Modelling Language (UML) is the most popular modelling language use for software design in software development industries with a class diagram being the most frequently use diagram. Despite the popularity of UML, it is being affected by inconsistency problems of its diagrams at the same or different abstraction levels. Inconsistency in UML is mostly caused by existence of various views on the same system and sometimes leads to potentially conflicting system specifications. In general, syntactic consistency can be automatically checked and therefore is supported by current UML Computer-aided Software Engineering (CASE) tools. Semantic consistency problems, unlike syntactic consistency problems, there exists no specific method for specifying semantic consistency rules and constraints. Therefore, this research has specified twenty-four abstraction rules of class‟s relation semantic among any three related classes of a refined class diagram to semantically equivalent relations of two of the classes using a logical approach. This research has also formalized three vertical semantic consistency rules of a class diagram refinement identified by previous researchers using a logical approach and a set of formalized abstraction rules. The results were successfully evaluated using hotel management system and passenger list system case studies and were found to be reliable and efficient

Business Process Management for optimizing clinical processes: A systematic literature review

Business Process Management is a new strategy for process management that is having a major impact today. Mainly, its use is focused on the industrial, services, and business sector. However, in recent years, it has begun to apply for optimizing clinical processes. So far, no studies that evaluate its true impact on the healthcare sector have been found. This systematic review aims to assess the results of the application of Business Process Management methodology on clinical processes, analyzing whether it can become a useful tool to improve the effectiveness and quality of processes. We conducted a systematic literature review using ScienceDirect, Web of Science, Scopus, PubMed, and Springer databases. After the electronic search process in different databases, 18 articles met the pre-established requirements. The findings support the use of Business Process Management as an effective methodology to optimize clinical processes. Business Process Management has proven to be a feasible and useful methodology to design and optimize clinical processes, as well as to automate tasks. However, a more comprehensive follow-up of this methodology, better technological support, and greater involvement of all the clinical staff are factors that play a key role for the development of its true potential.This work was supported by the Ministerio de Economía y Competitividad of the Spanish Government (ref. TIN2014-53067-C3-1-R) and co-financed by FEDER

Improving performance and the reliability of off-site pre-cast concrete production operations using simulation optimisation

The increased use of precast components in building and heavy civil engineering projects has led to the introduction of innovative management and scheduling systems to meet the demand for increased reliability, efficiency and cost reduction. The aim of this study is to develop an innovative crew allocation system that can efficiently allocate crews of workers to labour-intensive repetitive processes. The objective is to improve off-site pre-cast production operations using Multi-Layered Genetic Algorithms. The Multi-Layered concept emerged in response to the modelling requirements of different sets of labour inputs. As part of the techniques used in developing the Crew Allocation “SIM_Crew” System, a process mapping methodology is used to model the processes of precast concrete operations and to provide the framework and input required for simulation. Process simulation is then used to model and imitate all production processes, and Genetic Algorithms are embedded within the simulation model to provide a rapid and intelligent search. A Multi-Layered chromosome is used to store different sets of inputs such as crews working on different shifts and process priorities. A ‘Class Interval’ selection strategy is developed to improve the chance of selecting the most promising chromosomes for further investigation. Multi-Layered Dynamic crossover and mutation operators are developed to increase the randomness of the searching mechanism for solutions in the solution space. The results illustrate that adopting different combinations of crews of workers has a substantial impact on the labour allocation cost and this should lead to increased efficiency and lower production cost. In addition, the results of the simulation show that minimum throughput time, minimum process-waiting time and optimal resource utilisation profiles can be achieved when compared to a real-life case study

Building workforce capacity for complex care coordination: a function analysis of workflow activity

Background The care coordination workforce includes a range of clinicians who manage care for patients with multiple chronic conditions both within and outside a hospital, in the community, or in a patient’s home. These patients require a multi-skilled approach to support complex care and social support needs as they are typically high users of health, community, and social services. In Australia, workforce structures have not kept pace with this new and emerging workforce. The aim of the study was to develop, map, and analyse workforce functions of a care coordination team. Methods Workflow modelling informed the development of an activity log that was used to collect workflow data in 2013 from care coordinators located within the care coordination service offered by a Local Health Network in Australia. The activity log comprised a detailed classification of care coordination functions based on two major categories – direct and indirect care. Direct care functions were grouped into eight domains. A descriptive quantitative investigation design was used for data analysis. The data was analysed using univariate descriptive statistics with results presented in tables and a figure. Results Care coordinators spent more time (70.9%) on direct care than indirect care (29.1%). Domains of direct care that occupied the most time relative to the 38 direct care functions were ‘Assessment’ (14.1%), ‘Documentation’ (13.9%), ‘Travel time’ (6.3%), and ‘Accepting/discussing referral’ (5.7%). ‘Administration’ formed a large component of indirect care functions (14.8%), followed by ‘Travel’ (12.4%). Sub-analyses of direct care by domains revealed that a group of designated ‘core care coordination functions’ contributed to 40.6% of direct care functions. Conclusions The modelling of care coordination functions and the descriptions of workflow activity support local development of care coordination capacity and workforce capability through extensive practice redesigns

ACHIEVING AUTONOMIC SERVICE ORIENTED ARCHITECTURE USING CASE BASED REASONING

Service-Oriented Architecture (SOA) enables composition of large and complex computational units out of the available atomic services. However, implementation of SOA, for its dynamic nature, could bring about challenges in terms of service discovery, service interaction, service composition, robustness, etc. In the near future, SOA will often need to dynamically re-configuring and re-organizing its topologies of interactions between the web services because of some unpredictable events, such as crashes or network problems, which will cause service unavailability. Complexity and dynamism of the current and future global network system require service architecture that is capable of autonomously changing its structure and functionality to meet dynamic changes in the requirements and environment with little human intervention. This then needs to motivate the research described throughout this thesis. In this thesis, the idea of introducing autonomy and adapting case-based reasoning into SOA in order to extend the intelligence and capability of SOA is contributed and elaborated. It is conducted by proposing architecture of an autonomic SOA framework based on case-based reasoning and the architectural considerations of autonomic computing paradigm. It is then followed by developing and analyzing formal models of the proposed architecture using Petri Net. The framework is also tested and analyzed through case studies, simulation, and prototype development. The case studies show feasibility to employing case-based reasoning and autonomic computing into SOA domain and the simulation results show believability that it would increase the intelligence, capability, usability and robustness of SOA. It was shown that SOA can be improved to cope with dynamic environment and services unavailability by incorporating case-based reasoning and autonomic computing paradigm to monitor and analyze events and service requests, then to plan and execute the appropriate actions using the knowledge stored in knowledge database