Extending Hybrid CSP with Probability and Stochasticity

Probabilistic and stochastic behavior are omnipresent in computer controlled systems, in particular, so-called safety-critical hybrid systems, because of fundamental properties of nature, uncertain environments, or simplifications to overcome complexity. Tightly intertwining discrete, continuous and stochastic dynamics complicates modelling, analysis and verification of stochastic hybrid systems (SHSs). In the literature, this issue has been extensively investigated, but unfortunately it still remains challenging as no promising general solutions are available yet. In this paper, we give our effort by proposing a general compositional approach for modelling and verification of SHSs. First, we extend Hybrid CSP (HCSP), a very expressive and process algebra-like formal modeling language for hybrid systems, by introducing probability and stochasticity to model SHSs, which is called stochastic HCSP (SHCSP). To this end, ordinary differential equations (ODEs) are generalized by stochastic differential equations (SDEs) and non-deterministic choice is replaced by probabilistic choice. Then, we extend Hybrid Hoare Logic (HHL) to specify and reason about SHCSP processes. We demonstrate our approach by an example from real-world.Comment: The conference version of this paper is accepted by SETTA 201

Data quality issues in electronic health records for large-scale databases

Data Quality (DQ) in Electronic Health Records (EHRs) is one of the core functions that play a decisive role to improve the healthcare service quality. The DQ issues in EHRs are a noticeable trend to improve the introduction of an adaptive framework for interoperability and standards in Large-Scale Databases (LSDB) management systems. Therefore, large data communications are challenging in the traditional approaches to satisfy the needs of the consumers, as data is often not capture directly into the Database Management Systems (DBMS) in a seasonably enough fashion to enable their subsequent uses. In addition, large data plays a vital role in containing plenty of treasures for all the fields in the DBMS. EHRs technology provides portfolio management systems that allow HealthCare Organisations (HCOs) to deliver a higher quality of care to their patients than that which is possible with paper-based records. EHRs are in high demand for HCOs to run their daily services as increasing numbers of huge datasets occur every day. Efficient EHR systems reduce the data redundancy as well as the system application failure and increase the possibility to draw all necessary reports. However, one of the main challenges in developing efficient EHR systems is the inherent difficulty to coherently manage data from diverse heterogeneous sources. It is practically challenging to integrate diverse data into a global schema, which satisfies the need of users. The efficient management of EHR systems using an existing DBMS present challenges because of incompatibility and sometimes inconsistency of data structures. As a result, no common methodological approach is currently in existence to effectively solve every data integration problem. The challenges of the DQ issue raised the need to find an efficient way to integrate large EHRs from diverse heterogeneous sources. To handle and align a large dataset efficiently, the hybrid algorithm method with the logical combination of Fuzzy-Ontology along with a large-scale EHRs analysis platform has shown the results in term of improved accuracy. This study investigated and addressed the raised DQ issues to interventions to overcome these barriers and challenges, including the provision of EHRs as they pertain to DQ and has combined features to search, extract, filter, clean and integrate data to ensure that users can coherently create new consistent data sets. The study researched the design of a hybrid method based on Fuzzy-Ontology with performed mathematical simulations based on the Markov Chain Probability Model. The similarity measurement based on dynamic Hungarian algorithm was followed by the Design Science Research (DSR) methodology, which will increase the quality of service over HCOs in adaptive frameworks

Transactions of 2015 International Conference on Health Information Technology Advancement Vol.3, No. 1

The Third International Conference on Health Information Technology Advancement Kalamazoo, Michigan, October 30-31, 2015 Conference Chair Bernard Han, Ph.D., HIT Pro Department of Business Information Systems Haworth College of Business Western Michigan University Kalamazoo, MI 49008 Transactions Editor Dr. Huei Lee, Professor Department of Computer Information Systems Eastern Michigan University Ypsilanti, MI 48197 Volume 3, No. 1 Hosted by The Center for Health Information Technology Advancement, WM

Innovative communication, effective coordination and knowledge management in UK local authority planning departments

This thesis sets out to examine the scope for integrated knowledge based planning systems. Five planning departments in the South East Midlands of the UK have been investigated through environmental appraisal, conceptual modelling and empirical evidence gathering. The results of analyses suggest a number of configurations, which could provide reformation instruments in the context of technological innovation, social coordination and knowledge management for sustainable development. This research study provided the insights and learning into how to successfully develop and implement an integrated knowledge based planning system. The primary aspiration of this research was to develop a robust pragmatic framework to support an efficient and effective delivery of the planning system in the UK local government towards sustainable development. A mixed research methodology was employed for the research fieldwork. Firstly, an extensive review of literature took place to summarise and synthesise the arguments of the key research propositions contributing to the development of an integrated knowledge based planning system. Secondly, exploratory fieldwork took place as an appropriate methodology in this study, applying the semi-structured interview and questionnaire techniques to gather data from senior level planning officials who were directly involved in the planning system transformation. This study was initiated by examining the previous planning environment in the UK local government and its transformation from its conventional state to a contemporary emergent state. The fieldwork was carried out to identify the key supportive and preventive knowledge factors for both explicit and tacit knowledge domains. As a result, the nature of successful technology based initiatives was determined and solutions to the possible emerging challenges were appraised

Utilizing Distributed Ledger Technology to Integrate Anglophone and Indigenous Pedagogies in the 21st Century – The Case for Hawaii

The emergence of the Fourth Industrial Revolution (Industry 4.0) is rapidly transforming many global industries influenced by the growth and use of artificial intelligence (AI), distributed ledger technology (DLT), ubiquitous cloud and edge computing as well as other emerging digital platform-based systems. Mobile technologies and their use and adoption in education have generated research concerning new approaches for technology-enhanced learning (TEL), including mobile learning (m-learning). The evolution of TEL and recent research on m-learning and ubiquitous learning (u-learning) offer the potential for a new phase of educational delivery marked by a continuity of the learning experience across different learning settings using the mobile device as the mediator. Chan and colleagues use the term “seamless learning” to describe these new affordances. Indigenous peoples have historically experienced both the positive and negative effects of being educated within the Anglophone tradition. American Indian, Alaska Native, and Native Hawaiian students have had the highest high-school dropout rates of any racial or ethnic groups in the United States and are the least represented on college campuses at both the undergraduate and graduate levels. This thesis has selected the Native Hawaiian indigenous culture for in-depth analysis. It examines the epistemological and ontological underpinnings of the Native Hawaiian worldview and the educational history of indigenous Hawaiians in the State of Hawaii, both ancient and modern. In addition, it examines the potential for the synthesis of the Anglophone and Native Hawaiian pedagogical traditions in order to improve educational outcomes for these and other indigenous students attending United States public schools. Since the early 1960s, the education of Native Hawaiians in the State of Hawaii has undergone a gradual systemic transformation that has led to improved outcomes. To that end, the Hawaiian language, cultural values, and the use of traditional pedagogies have blossomed, primarily due to the establishment of indigenous-led Hawaiian culture-based education (CBE) initiatives and scholarship. Moreover, the creation of a growing number of Hawaiian Language Immersion and Public Charter Schools has elevated these CBE pedagogies to a new level of importance within the public education system of Hawaii. While significant challenges to increased progress remain, the innovative use of a cultural strengths-based approach has succeeded in addressing several of the historical barriers hindering Native Hawaiian student motivation and engagement in education. In addition, empirical research conducted in Hawaii has verified a CBE model framework capable of improving indigenous student outcomes within the Anglophone traditions of the United States educational system. This thesis examines the potential for the integration of traditional Anglophone and indigenous pedagogies implemented through mobile seamless learning modalities. It analyses the significant synergies available through the utilization of DLT and Hyperledger applications for the facilitation of seamless learning interactions between providers and seekers of education when structured within a new integrative model. It also examines the unexplored gaps in the research associated with mobile-assisted seamless learning (MSL) and recommends the potential application of the model design to close those gaps, increase the seamlessness of MSL and propel learning opportunities. The model is then situated within both the Anglophone and Native Hawaiian pedagogical traditions in order to illustrate the MSL affordances available for both educators and mobile indigenous learners. Finally, several use cases of the integrative model are provided to demonstrate its flexibility and extendibility in different m-learning and other indigenous and traditional learning environments. While not a comprehensive or complete solution, this integrative model nonetheless has implications for future research as well as potentially broad applications for indigenous communities to collaborate and share their knowledge at a lower cost, and for educators and students worldwide to benefit mutually as the Fourth Industrial Revolution advances

Factors to improve data quality of electronic medical records

Electronic Medical Record (EMR) systems have been identified as having the potential to improve health care and allow the health care sector to reap a number of benefits when implemented successfully. These benefits include enabling quick and easy access to patient files and also reducing the problem of misplaced or lost patient files. Such EMRs allow for patient records to be up to date, provided that health care practitioners capture standard and consistent data in the relevant fields. In Africa, there are only a few countries that have successfully implemented EMR systems due to social and technological challenges. Social factors include lack of computer skilled health workers, lack of adequate training, physician’s resistance to shift from using paper records to electronic records, either due to complex systems or the fear of being replaced by the systems. On the other hand, the technological factors include lack of Information Technology (IT) and clinical resources, lack of internet access, financial barriers to purchase the necessary technological hardware and implementation costs. A few South African health care institutions have implemented EMR systems, however, most of the public health care facilities still make use of a manual system to capture patient information. In the case where public health care facilities do have an EMR system implemented, there are problems with the consistency of the data that is captured. The inconsistency is caused by the different understandings that the health care professionals have regarding the importance of capturing the necessary information that is collected at various points in health care institutions, thus affecting data quality. For the successful implementation and use of EMR systems, everything within the health care organisation should be integrated. In other words, the steering committee and workgroup, the equipment, the product, the processes, the system and the facility design and construction should be incorporated to work together. The common problems identified in literature regarding data quality in EMRs include misspelled words, inconsistent word strings, inaccurate information entered on the record and incompleteness of the record. These problems lead to poor quality information, lack of accessibility of the record, poorly organised notes and inaccurate information about the patient. The South African strategy aims to implement a National Health Insurance (NHI) which will provide citizens with equitable access to health care. For the successful implementation of the NHI strategy, South African health care sectors should address the barriers which were identified and learn from other African countries that have successfully implemented EMR systems and had positive outcomes. Therefore, this study investigates how data quality can be improved on electronic medical records in public health care in South Africa? The qualitative research methodology approach was used for this study. Interviews were conducted with eight health care professionals at Klerksdorp, in the North West province to obtain data regarding the factors they would deem important for the improvement of data quality in EMRs. The Data Quality Framework (DQF) was applied in this study and six dimensions were identified as the factors to improve data quality. These dimensions include completeness, accuracy, consistency, conformity, timeliness, and integrity. From the analysis of the interview responses, it was discovered that there were, in fact, data quality issues experienced at the public health care facilities of South Africa. A need was identified for the use of data quality assessment tools and solutions to address the data quality issues or challenges that health care practitioners are faced with during their daily jobs. Seven barriers were also identified as having an impact on the successful implementation of EMRs at health care institutions. These barriers, together with the data quality issues, influence the successful use of EMRs and should not be overlooked. From these barriers the study developed seven Critical Success Factors which can be used by the National Department of Health to improve the quality of EMRs.Thesis (MCom) -- Faculty of Management and Commerce, 201