Employing a Multilevel Secure Approach in CRM Systems

This research shows how Multilevel Secure (MLS) data models can be used in a Customer Relationship Management (CRM) context. MLS models were originally developed as database models for the management of information in environments characterized by a strict hierarchy of security levels, such as military institutions and government security agencies. Improvements in evolving database technologies have made MLS data modeling practical as well as theoretically appealing. This paper illustrates how an MLS model can be used as a part of the technology for coordinating business-customer interactions with the objective of building long-term customer loyalty. Several examples are used to show how organizing a database management system based on MLS principles can be used to help businesses provide consistent and appropriate content to various customers and partners. Improvements in flexibility and cost of applications, as well as opportunities for new CRM strategies, are discussed as potential benefits of integrating MLS and CRM technology

Acting in Time: Transport Nurses optimising critically ill patients for transfer to a regional ECMO centre. A Grounded Theory Study

Regionalisation and centralisation of Intensive Care Units, coupled with demographic changes, have resulted in an increased demand for inter-hospital transport. The Conventional ventilatory support vs Extracorporeal membrane oxygenation for Severe Adult Respiratory Failure Trial (CESAR), validated the use of ECMO in the UK for critically ill adults. The H1N1 Influenza A epidemic in 2009, led to four more adult ECMO centres being designated, and more recently the World Health Organisation (WHO, 2020), recommended ECMO for eligible patients in the COVID-19 pandemic. A critical incident occurred while I was undertaking the transport of a critically ill adult, which led to the unplanned use of mobile ECMO, still in its infancy. Seeking answers to the questions raised from this incident a research proposal was formed in order to investigate what could be learnt from the actions of transport nurses in promoting stability and preventing deterioration of patient acuity during the transport process. A grounded theory approach was used to try and understand the processes and strategies that experienced transport nurses used in optimising their patients’ stability and generate a substantive theory in explaining their timely actions. Under a pragmatic paradigm, this grounded theory study utilised the methods of Retrospective Medical Records Review and Interviews. Quantitative random sampling of 50 patients retrieved to a regional ECMO centre, allowed the collection of vital physiological variables staged over three time points. Data analysis showed that two out of the eight variables demonstrated a statistical significance in deterioration. Qualitative unstructured interviews from six transport nurses revealed a variety of activities, proactive and reactive, cognitive and physical, with overwhelming attention to time constraints, employed to benefit the patient. An explanatory theory was identified. Acting in Time encapsulated extant theory from the Secure Base Model (SBM) in fostering studies, and the Actor-Network Theory (ANT), from sociological literature. Acting in Time made overt the core virtues, practices, and skills of the transport nurse in aiming to reduce the risks associated will transport of the critically ill adult while striving to maintain patient stability. The study identified a growing need for centralisation, coordination, standardisation, audit, education and training for all those involved in transporting critically ill patients to a regional ECMO centre. It recommends that dedicated regional transport centres should be implemented for the transport of the adult critical care patient. A centralised database should be created for the import of data from the regional transport teams. Education for all nurses, not just transport nurses, needs to be available to deliver high quality care at any point of patient retrieval. A curriculum for transport education for nurses is outlined. This research reinforces and adds to the Intensive Care Society and Faculty of Intensive Care Medicine (ICS & FICM, 2019), and standards of education for nurses enhanced

Strong and Provably Secure Database Access Control

Existing SQL access control mechanisms are extremely limited. Attackers can leak information and escalate their privileges using advanced database features such as views, triggers, and integrity constraints. This is not merely a problem of vendors lagging behind the state-of-the-art. The theoretical foundations for database security lack adequate security definitions and a realistic attacker model, both of which are needed to evaluate the security of modern databases. We address these issues and present a provably secure access control mechanism that prevents attacks that defeat popular SQL database systems.Comment: A short version of this paper has been published in the proceedings of the 1st IEEE European Symposium on Security and Privacy (EuroS&P 2016

Enhancing Critical Thinking in Clinical Laboratory Students: A Multimodal Model

The purpose of this study was to improve critical thinking skills in clinical laboratory technologists through the development, implementation, and assessment of a multimodal model targeting critical thinking skills. Clinical laboratory technologists influence patient care through the testing of laboratory samples. Employers of these entry level professionals identified a need for improved critical thinking skills. This quasi-experimental study aimed to design a multimodal critical thinking model, implement the model into the clinical laboratory educational curriculum, and assesses this skill set for students in a pre-test / post-test format. The model was delivered and assessed for 47 clinical laboratory students at the University of Texas M.D. Anderson Cancer Center’s School of Health Professions. Based on numerical results for the Health Science Reasoning Test (HSRT), no significant difference in critical thinking skills was observed for clinical laboratory students before and after the integration of the multimodal model targeting this skill set into the curriculum. For the purpose of this study, critical thinking was defined as the ability to effectively evaluate and interpret data, apply existing knowledge to solve problems in new situations, demonstrate creativity and resourcefulness in learning, and problem solving, and effectively and persuasively communicate findings. Further analysis of the results indicated that junior and community college students were more likely to improve their HSRT scores after completion of the multimodal model than 4-year university and bachelor level students. Findings also suggest a positive relationship between GPA and improved HSRT scores. The amount of time as student spent on each assessment was directly related to success, and an inverse relationship was observed for usage of the model reference material. Further studies are needed to ensure model validity and generalizability of findings. Additionally, HSRT categorical results indicate the need for model modifications to better target the areas of deduction and inference. The online, asynchronous format may benefit from the addition of mandated discussion boards, and requiring assessment and evaluation completion may reduce the effects of lack of effort due to cognitive fatigue observed for this study

Digital Literacy Adoption with Academic Technology: Namely Digital Information Literacy to Enhance Student Learning Outcomes

This study explores Arts & Science faculty and librarians’ attitude of learning theory and perceptions of digital literacy (DL) and how digital information literacy (DIL) might improve and enhance student learning outcomes. Digital literacy (DL), information literacy (IL), and digital information literacy (DIL) consists of interaction with academic technology (AT) programs and tools. The objectives are: the rise of IL within the parameters of DL and discuss the birth of DIL, examine the modes of adoption and explore the levels of inclusion for faculty and librarians’ concepts of DL with DIL instruction with AT, define the IL phenomenon, and how IL affects faculty and librarian pedagogy. The study reveals the tension and distinction between DL and IL. Key research questions are: What are Arts & Science faculties’ digital literacy (DL) epistemology? What is the librarian’s/ library digital literacy (DL) epistemology perspectives, and what are Arts & Science faculties’ concept of DIL

Application of Hierarchical Temporal Memory to Anomaly Detection of Vital Signs for Ambient Assisted Living

This thesis presents the development of a framework for anomaly detection of vital signs for an Ambient Assisted Living (AAL) health monitoring scenario. It is driven by spatiotemporal reasoning of vital signs that Cortical Learning Algorithms (CLA) based on Hierarchal Temporal Memory (HTM) theory undertakes in an AAL health monitoring scenario to detect anomalous data points preceding cardiac arrest. This thesis begins with a literature review on the existing Ambient intelligence (AmI) paradigm, AAL technologies and anomaly detection algorithms used in a health monitoring scenario. The research revealed the significance of the temporal and spatial reasoning in the vital signs monitoring as the spatiotemporal patterns of vital signs provide a basis to detect irregularities in the health status of elderly people. The HTM theory is yet to be adequately deployed in an AAL health monitoring scenario. Hence HTM theory, network and core operations of the CLA are explored. Despite the fact that standard implementation of the HTM theory comprises of a single-level hierarchy, multiple vital signs, specifically the correlation between them is not sufficiently considered. This insufficiency is of particular significance considering that vital signs are correlated in time and space, which are used in the health monitoring applications for diagnosis and prognosis tasks. This research proposes a novel framework consisting of multi-level HTM networks. The lower level consists of four models allocated to the four vital signs, Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), Heart Rate (HR) and peripheral capillary oxygen saturation (SpO2) in order to learn the spatiotemporal patterns of each vital sign. Additionally, a higher level is introduced to learn spatiotemporal patterns of the anomalous data point detected from the four vital signs. The proposed hierarchical organisation improves the model’s performance by using the semantically improved representation of the sensed data because patterns learned at each level of the hierarchy are reused when combined in novel ways at higher levels. To investigate and evaluate the performance of the proposed framework, several data selection techniques are studied, and accordingly, a total record of 247 elderly patients is extracted from the MIMIC-III clinical database. The performance of the proposed framework is evaluated and compared against several state-of-the-art anomaly detection algorithms using both online and traditional metrics. The proposed framework achieved 83% NAB score which outperforms the HTM and k-NN algorithms by 15%, the HBOS and INFLO SVD by 16% and the k-NN PCA by 21% while the SVM scored 34%. The results prove that multiple HTM networks can achieve better performance when dealing with multi-dimensional data, i.e. data collected from more than one source/sensor