Optimization of Resource Usage for Computer-Based Education through Mobile, Speech and Sky Computing Technology

Cloud computing encompasses any subscription-based or pay-per-use service over the Internet. Using a cloud that is owned by a single service provider has its demerit to the customer such as the risk of downtime or breakdown of equipment arising from disaster that can jeopardize the subscribers’ business. Data security and reliability due to over centralization of company’s data poses a high risk for subscribers, hence a call for distributed cloud also known as Sky Computing. When application is distributed across several clouds with varied interest, infrastructure, policy, etc, the issue therefore will be how to determine the most cost effective cloud during access time. The amount of money a student pays in accessing learning content is determined by how much an institution pay as subscription to cloud providers. The objective of this study is to utilize optimization theory to determine the most cost effective cloud for mobile virtual education in Sky Computing environment. This will be achieved by optimizing resource usage for Computer-based Education through Mobile, Speech and Sky Computing Technology. As a proof of concept, we will design and implement a cloud middle ware (CMW) to interface with an eEducation system. Access to the eEducation shall be Mobile, Speech and Web. Through the communication platform, the students can communicate with their teacher at any convenient time, and vice versa at the most reduced cost

Patient-oriented Evidence-based Treatment Decision Support System (TreatQuest®) for Lung Cancer

Involving patients in healthcare decisions makes a significant and enduring difference to healthcare outcomes. One challenge for patients is the lack of evidence-based information and tools to support their decision making. Although patients have access to significant information through internet and other sources, it is not personalized for their specific situation. This dissertation attempts to help patients acquire evidence-based information relevant to their own situation, so they can make a more informed decision in co-operation with their physicians. Lung cancer has been selected as a focus for this study because lung cancer presents very complex decision making situation and is the leading cause of cancer deaths in both men and woman in every ethnic group worldwide. The prototype decision support system for lung cancer is called TreatQuest®. This system allows users to create their own profile, access cases similar to their case, and learn about treatment options. The evidences for the treatment were extracted from public data and knowledge gained from guideline. The effectiveness of patient-oriented evidence-based approach was validated by having a group of patient use the system. TreatQuest® is one of the first system developed to support patient\u27s treatment decision process, which represent the most recent trend in delivery of healthcare services. Results from this study show that such a patient-oriented decision support system provides an effective way to help patient receive more personalized information and make informed treatments. In summary, patient-oriented evidence-based decision support systems such as TreatQuest®, can improve the decision quality for patients. Also, such systems can improve health care decisions that are made with the active participation of fully informed patients. Therefore, patient-oriented evidence-based decision support systems can have significant impact on the healthcare industry

Human-Centered Explainable Artificial Intelligence for Anomaly Detection in Quality Inspection: A Collaborative Approach to Bridge the Gap Between Humans and AI

In the quality inspection industry, the use of Artificial Intelligence (AI) continues to advance to produce safer and faster autonomous systems that can perceive, learn, decide, and act independently. As observed by the researcher interacting with the local energy company over a one-year period, these AI systems’ performance is limited by the machine’s current inability to explain its decisions and actions to human users. Especially in energy companies, eXplainable-AI (XAI) is critical to achieve speed, reliability, and trustworthiness with human inspection workers. Placing humans alongside AI will establish a sense of trust that augments the individual’s capabilities at the workplace. To achieve such an XAI system centered around humans, it is necessary to design and develop more explainable AI models. Incorporating these XAI systems centered around human workers in the inspection industry brings a significant shift in conducting visual inspections. Adding this explainability factor to the AI intelligent inspection systems makes the decision-making process more sustainable and trustworthy by bringing a collaborative approach. Currently, there is a lack of trust between the inspection workers and AI, creating uncertainty among inspection workers about the use of the existing AI models. To address this gap, the purpose of this qualitative research study was to explore and understand the need for human-centered XAI systems to detect anomalies in quality inspection in energy industries

A user-centred evaluation of a mobile phone-based interactive voice response system to support infectious disease surveillance and access to healthcare for sick children in Ghana: users’ experiences, challenges and opportunities for large-scale application. Part of a concept and pilot study for mobile phone-based Electronic Health Information and Surveillance System (eHISS) for Africa

Brinkel J. A user-centred evaluation of a mobile phone-based interactive voice response system to support infectious disease surveillance and access to healthcare for sick children in Ghana: users’ experiences, challenges and opportunities for large-scale application. Part of a concept and pilot study for mobile phone-based Electronic Health Information and Surveillance System (eHISS) for Africa. Bielefeld: Universität Bielefeld; 2020.Digital Health offers tremendous potential to change the face of health systems in all countries. Although the application of digital technologies in the health sector has become central to global health thinking, various implementation barriers still exist. One of the most significant is the process of user acceptance and adoption of new interventions, which still remains a neglected research area in sub-Saharan Africa. The synopsis is a synthesis of the findings of a three-year research study embedded within a larger research consortium that developed and piloted a mobile phone-based Electronic Health Information and Surveillance System for sub-Saharan Africa (eHISS) in Ghana. The system aimed to support sick children to assess the disease severity, to advice appropriate treatment and to collect data on the occurrence of symptom clusters. The thesis evaluated the usability and acceptance among users of the mobile health (mHealth) system (caregivers of children) by soliciting their views on their experiences while using the system. The doctoral thesis followed a human-centred design (HCD) circle and consisted of the following research activities; (i) the assessment of the state of research, (ii) the innovative field test of a prototype of the eHISS system and an assessment of users’ needs to drive the design, (iii) the evaluation of the clinical decision algorithm as backbone of the electronic system and (iv) the evaluation of experiences with the system after a six-month pilot phase of the system. A manuscript was developed from each research activity for publication, thus making a total of four papers that form the empirical basis of this thesis. Results showed that users are generally open to mHealth and interested in new technologies, and comprehensive knowledge on critical factors favouring and disfavouring the integration of the system in the daily life of participants, and suggestions on how the system could be improved has been gained. The thesis thus confirmed and highlighted the key role of user experiences in the design process of new mHealth approaches, and provided insights on how to develop and evaluate mobile health approaches from the user perspective. Based on the results of the user evaluation, two possible directions for the future of eHISS have been developed. We further conclude that programs and initiatives must be guided by robust strategies to overcome existing barriers for implementation. Like all digital health interventions, the presented eHISS system is not a silver bullet and has significant limitations, but taking the requirements discussed in the thesis into consideration we believe that systems developed based on the eHISS experiences in future can make a real impact on health service delivery and disease response

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

A Standardized Electronic Handover Report for Anesthesia Providers

Background: Despite numerous studies and agencies recommending the standardization of handovers to improve the quality and safety of patient care, intraoperative anesthesia handovers have remained unstandardized at many institutions. Objectives: The purposes of this study were to 1) develop the preliminary Anesthesia Handover Report (AHR) and evaluate its accessibility, layout, and content using feedback from an Expert Sampling Group; 2) create the finalized AHR and evaluate the impact it had on the perceived quality of handover among anesthesia providers; and 3) to assess the uptake of the finalized AHR. Methods: This study was implemented at NorthShore University Health System (NSUHS), Evanston, Highland Park and Glenbrook locations. In Phase 1, an Expert Sampling Group of ten experienced anesthesia providers evaluated the preliminary AHR for its accessibility, layout and content using the Expert Sampling Group Questionnaire. In Phase 2, using feedback from this questionnaire, the finalized AHR was created and all 140 anesthesia providers at the three study locations were invited to utilize and evaluate the AHR during intraoperative anesthesia handover, additionally, during Phase 3 the use of the AHR was queried every two weeks for the duration of Phase 2 to assess uptake. Results: Five anesthesia providers completed the Expert Sampling Group Questionnaire in Phase 1. Changes made to the preliminary AHR in response to feedback from the Expert Sampling Group Questionnaire included the removal of redundant information, more appropriate layout of information in the sidebar, the addition of total drug dose given in the medications panel, an additional hyperlink to anesthesia nerve block reports, and corrections to wrong information being pulled into the AHR. During Phase 2, 21 anesthesia providers completed the Anesthesia Handover Survey. The overall mean Likert score for handover conduct was 3.72 with a SD of .475 (minimum 2, maximum 4), this indicated that overall the majority of the respondents perceived that the AHR improved the conduct component of handover. The overall mean Likert score for teamwork was 3.76, with a SD of .432 (minimum 3, maximum 4), which indicated that respondents felt the AHR improved teamwork during handover. Lastly, the mean Likert score for the handover quality was 3.64 with a SD of .611 (minimum 1, maximum 4), this indicated respondents felt the AHR improved overall handover quality. Results of Phase 3 indicated the uptake did not increase as expected over the six-week monitoring window, but rather peaked during week four and quickly dropped off thereafter. The mean number of times the “Anesthesia Handoff” event button was clicked each week was 3.17. Conclusions: Use of the AHR improved the perceived conduct, teamwork, and quality of intraoperative anesthesia handovers. The use of the AHR did not improve over time. Overall, use of the AHR improved the perceived quality of anesthesia handovers. Future studies should be done to determine if use of the AHR would result in the standardization of anesthesia handovers

Sequencing and Comparative Analysis of \u3ci\u3ede novo\u3c/i\u3e Genome Assemblies of \u3ci\u3eStreptomyces aureofaciens\u3c/i\u3e ATCC 10762

Streptomyces aureofaciens is a Gram-positive Actinomycete used for commercial antibiotic production. Although it has been the subject of many biochemical studies, no public genome resource was available prior to this project. To address this need, the genome of S. aureofaciens ATCC 10762 was sequenced using a combination of sequencing platforms (Illumina and 454-shotgun). Multiple de novo assembly methods (SGA, IDBA, Trinity, SOAPdenovo2, MIRA, Velvet and SPAdes) as well as combinations of these methods were assessed to determine which provided the most robust assembly. Combination strategies led to a consistent overestimation of the total genome size. Empirical data from targeted PCR of predicted gap regions provided a robust validation framework for our de novo assemblies. Overall, the best assembly was generated using SPAdes. The total assembly length was 9.47 Mb and the average G+C content was 71.15 %. We annotated this assembly using the NCBI Prokaryotic Genome Annotation Pipeline, revealing 8,073 total genes, including a total of 7,627 protein coding sequences. Additional functional analysis using the KEGG GENES database provided functional predictions for over 1,400 of these sequences whose functions were not initially inferred by NCBI. The information provided from multiple independent assemblies allowed us to close 200 scaffold gaps present in our first hybrid assembly. Comparative genomic and phylogenetic analyses suggested S. aureofaciens ATCC 10762 may be more closely related to the genus Kitasatospora than to neighboring Streptomyces species. Our results highlight the need for, and the value of, multiple assemblies when attempting to produce high quality prokaryotic genome sequences. Advisor: Etsuko Moriyam

Sequencing and Comparative Analysis of \u3ci\u3ede novo\u3c/i\u3e Genome Assemblies of \u3ci\u3eStreptomyces aureofaciens\u3c/i\u3e ATCC 10762

Streptomyces aureofaciens is a Gram-positive Actinomycete used for commercial antibiotic production. Although it has been the subject of many biochemical studies, no public genome resource was available prior to this project. To address this need, the genome of S. aureofaciens ATCC 10762 was sequenced using a combination of sequencing platforms (Illumina and 454-shotgun). Multiple de novo assembly methods (SGA, IDBA, Trinity, SOAPdenovo2, MIRA, Velvet and SPAdes) as well as combinations of these methods were assessed to determine which provided the most robust assembly. Combination strategies led to a consistent overestimation of the total genome size. Empirical data from targeted PCR of predicted gap regions provided a robust validation framework for our de novo assemblies. Overall, the best assembly was generated using SPAdes. The total assembly length was 9.47 Mb and the average G+C content was 71.15 %. We annotated this assembly using the NCBI Prokaryotic Genome Annotation Pipeline, revealing 8,073 total genes, including a total of 7,627 protein coding sequences. Additional functional analysis using the KEGG GENES database provided functional predictions for over 1,400 of these sequences whose functions were not initially inferred by NCBI. The information provided from multiple independent assemblies allowed us to close 200 scaffold gaps present in our first hybrid assembly. Comparative genomic and phylogenetic analyses suggested S. aureofaciens ATCC 10762 may be more closely related to the genus Kitasatospora than to neighboring Streptomyces species. Our results highlight the need for, and the value of, multiple assemblies when attempting to produce high quality prokaryotic genome sequences. Advisor: Etsuko Moriyam