<p> Executive decision-makers cannot always anticipate and fully understand the implications of information technology outsourcing (ITO) decisions for the long-term processes, capabilities, and performance of their organization, especially when considering ITO for cloud-based services. The purpose of this qualitative, holistic single-case study was to explore the decision-making process, particularly the criteria used by executive decision-makers in U.S.-based multinational corporations (MNCs), for identifying and selecting organizational competencies when engaging in ITO for cloud-based services. Participants included 15 executive decision-makers in U.S.-based MNCs who had participated in decision-making for at least one ITO engagement for cloud-based services. Data collected from individual in-depth interviews, a focus group interview, and document review supported nine dominant themes, including identification of organizational competencies; decision model; contingency and business continuity; communication; skills, knowledge, and speed to market; cost; technology and processes; financial models; and culture change. Findings indicate that executive decision-makers are unable to articulate decision-making criteria and to define processes used for identifying and selecting organizational competencies to consider as part of ITO engagements for cloud-based services. They intuitively understand organizational core competencies and recognize that their organizations should not outsource them. Findings further support that the more experience executive decision-makers have with ITO, the more successful the outsourcing engagement will be. Challenges associated with outsourcing are directly proportional to the amount of outsourcing experience an executive decision maker has with ITO, as the initial outsourcing engagement requires new frameworks and processes. Subsequent outsourcing engagements rely on the structure and lessons learned from prior engagements, thereby reducing the negative impact on the outsourcing process. Unexpected findings included differences between female and male participants on the perception of outcomes of their ITO engagements and the need for an updated financial model for ITO for cloud-based services. Future researchers should consider criteria for identifying and selecting organizational competencies to outsource, methods used to anticipate the long-term impact of ITO for cloud-based services, gender-based perception of success or failure of ITO for cloud-based services, and financial model changes when implementing ITO for cloud-based services.</p><p>

Computer aided molecular design (CAMD) is a powerful technique to design molecules or chemical mixtures that fulfil a set of desirable target properties as specified by users. Molecular physical and thermodynamic properties are selected as the target properties to ensure that the designed molecules can achieve the property functionalities. However, the aspects of safety and health are not strongly emphasised as design objectives in many CAMD problems. In order to ensure that the synthesised molecule does not cause much harm and health-related risks to the consumers, it is critical to integrate both safety and health aspects as design factors in the current CAMD approaches. The main focus of this research is to develop a novel chemical product design methodology that integrates the concept of inherent safety and occupational health aspects in a CAMD framework. The generated molecules that are optimised with respect to the target properties must be evaluated in terms of their safety and health performance. The assessment is conducted by safety and health-related parameters/sub-indexes that have significant adverse impact on both aspects. This proposed approach ensures that a product that possesses the desirable properties, and at the same time meets the safety and health criteria, is produced. The next focus of this research is to generate optimal molecules with the desired functionalities and favourable safety and health attributes in a single-stage CAMD framework. Besides target properties, the concept of inherent safety and health is also considered as design objective to ensure that the synthesised molecules are simultaneously optimised with regards to both criteria. Fuzzy optimisation approach is applied to optimise these two principal design criteria in this work. As molecular properties are utilised as the parameters to examine the safety and health features of the molecules, these properties are often estimated through property prediction models. This research also focuses on the management of uncertainty resulted from properties used in the sub-indexes. The quantification of uncertainty helps to revise the safety and health measurement so that it can better reflect the inherent hazard level of the molecules. The fourth focus of this research is to address the limitations present in the current method of molecular hazard quantification. The enhancement is carried out by adopting the ordered weighted averaging (OWA) operator method with the analytic hierarchy process (AHP) approach in the safety and health assessment. Two case studies on solvent design are considered to demonstrate the presented methodologies.

After the oil crisis held in 1973 and 1979, academicians and industry players have noticed the importance and necessity of having alternative and sustainable energy sources in future. Biological wastes, also named as “Biomass” has been cited as one of the significant sustainable energy sources. Biomass poses an ideal and substantial potential to achieve a sustainable system. However, the development of biomass industry is still relatively sluggish due to the lack of confidence of the investor to venture in this relatively new green business. This is most probably attributed to the low-maturation of biomass technologies compared to other conventional technologies, high logistics cost required for biomass transportation and uncertain market penetration barrier for the biomass-derived products. This raises the importance of having a proper biomass management system and a systematic evaluation approach to assess the sustainability performances of the biomass industry. Therefore, the ultimate goal of this thesis is to develop a sustainable multi-biomass supply chain with the aims of optimising all three sustainability dimensions simultaneously. A sustainable multi-biomass supply chain is referred as the integrated value chain of the green products, which derived from various types of biomass, starting from harvesting stage to the final products delivery stage. This thesis discusses in detail on the relevant previous research works toward the introduction of novel evaluation approach to attain different sustainable objectives (i.e., economic, environmental and social) simultaneously. The evaluation approach encompasses various components, including (i) model reduction by using P-graph integrated two-stage optimisation approach; (ii) consideration of vehicle capacity constraint for detailed transportation cost estimation; (iii) integration of various sustainability indexes using various optimisation techniques. On top of that, two novel debottlenecking approaches, one through principal component analysis (PCA) method; while another through P-graph framework, which able to identify and remove barriers that limit the sustainability performance of the biomass supply chain, are proposed. Aside from this, this thesis also aims to reduce the gaps between the researchers and industry players by developing some user-friendly and non-programming-background dependent decision-making tools. Thus, decision-makers are able to understand the insight of their problems easily without requirement of strong mathematical background. A case study in Johor, a southern state in Malaysia, which is endowed with extensive biomass resources, is used to demonstrate the effective of the proposed approaches.

Hui Shui Cheung. / Thesis submitted in: August 2005. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 37-38). / Abstracts in English and Chinese. / Acknowledgement --- p.i / Abstract --- p.ii / 摘要 --- p.iii / Chapter Chapter 1 --- Introduction --- p.1 / Chapter Chapter 2 --- Related Work --- p.4 / Chapter Chapter 3 --- Single-Source Bandwidth Availability --- p.6 / Chapter 3.1 --- Measurement Methodology --- p.6 / Chapter 3.2 --- Measurement Results --- p.7 / Chapter Chapter 4 --- Multi-Souce Bandwidth Availability --- p.9 / Chapter 4.1 --- Correlation Among Senders --- p.9 / Chapter 4.2 --- Aggregate Bandwidth --- p.10 / Chapter 4.3 --- Sensitivity Analysis --- p.11 / Chapter Chapter 5 --- The Measurement System --- p.15 / Chapter 5.1 --- Overview of PlanetLab --- p.15 / Chapter 5.2 --- Measurement Tool --- p.16 / Chapter 5.3 --- Process Control --- p.17 / Chapter Chapter 6 --- Hybrid-Download Streaming --- p.21 / Chapter 6.1 --- Introduction --- p.21 / Chapter 6.2 --- Streaming Algorithm --- p.22 / Chapter 6.3 --- Performance Evaluation --- p.23 / Chapter Chapter 7 --- Playback-Adaptive Streaming --- p.26 / Chapter 7.1 --- Introduction --- p.26 / Chapter 7.2 --- Streaming Algorithm --- p.27 / Chapter 7.3 --- Adaptive Rebuffering Algorithm --- p.30 / Chapter 7.4 --- Performance Evaluation --- p.31 / Chapter Chapter 8 --- Conclusion --- p.36 / Bibliography --- p.37

The United Nations FAO (Food and Agriculture Organization) reports that a large quantity of global food production for human consumption is wasted every year (1.3 billion tons) with losses estimated between 40 and 50 % for all root and tuber crops, fruits and vegetables (FAO Global Initiative on Food Loss and Waste Reduction). Potatoes tubers are one the worldwide staple foods with an annual total production of circa 368 million tons. A major contributor to this loss is potato infection whilst in storage (in the UK circa 5% of the entire UK crop), with the main culprit being a disease of bacterial origin known as ‘soft rot’. This project attempts to address this post-harvest waste of potato tubers in storage through early detection and monitoring of the disease. The proposed approach for this research was to use gas phase biomarkers for the early detection of soft rot (in other words ‘smelling’ the disease). The first part of the project addressed past research on volatile detection and background on other sensing technologies not previously (or marginally) investigated in these studies. The section on past studies includes all the research carried out from the 1970s by Varns and Glyn to date. Most of the studies focused on Gas Chromatography or Gas Chromatography Mass Spectroscopy. The background section that follows addresses other technologies that could also be employed for volatile monitoring, namely Field Asymmetric Ion mobility Spectrometry, Photoionization Detection, Metal Oxide, Electrochemical, and Nondispersive Infrared gas sensors. Initial work focused on evaluating these gas sensing technologies for both symptomatic and pre-symptomatic progression of potato soft rot, under laboratory conditions. After preliminary investigation, the experimental method chosen consisted in assessing the sensors results at two time points, both for symptomatic and pre-symptomatic disease detection. A total of 80 potato samples (40 for each time point) were tested with 25 different gas sensors. To process the data the following techniques were employed: cumulative sensor responses, unsupervised PCA and k-means and machine learning models (LDA, MARS, SVM, random forest and the C5.0 algorithm). Results show that all these techniques yielded a very high discrimination rate between healthy control and diseased tubers (with 80 to 100% accuracy) for a number of sensors. PID, 3 metal oxide and 3 electrochemical, gas sensors were shortlisted for possible later work. The final part of the project focussed on deploying sensors identified in laboratory conditions in a real store. To this end, a bespoke instrument was developed solely for the monitoring of store environments. The instrument comprised the sensors tested in the previous part of this work that could be readily embedded into a research tool for in-situ experimentation (with the addition of few others for completeness). Three electrochemical, six metal oxide, one nondispersive infrared and the PID sensors were included in the unit. The experimental method employed was based on time course varying from few days to two weeks. Two types of experiments were carried out, namely laboratory work and store room monitoring. Time series results for four types of sample types (unwounded controls, wounded controls and two infected sets) show that some of the sensors (ethanol, ammonia, hydrocarbons, overall volatiles and carbon monoxide) deployed on the instrument could discriminate between the various sample batches and detect soft rot from a very early stage and throughout the experimental work. The bespoke instrument was then deployed in a research store setting for testing (at the AHDB Sutton Bridge Crop Storage Research Centre, UK). Four 1 ton wooden crates controls were placed inside a (56 m3) store room (at 95% RH and 15 ± 1 °C) followed after the fourth day by a batch of infected tubers (with a proportion of infected tubers to controls of 1%). Results over a period of circa three weeks show that some of the sensors (ethanol, ammonia and hydrocarbons) could detect soft rot from a very early stage and throughout the experimental work. In conclusion, the research reported here shows that gas analysis technology could be successfully applied for pre-symptomatic detection and monitoring of soft rot in a storage facility with readily available commercial sensors.

Light sources are an important part of physically-based rendering when accurate imagery is required. High-fidelity models of sky illumination are essential when virtual environments are illuminated via the sky as is commonplace in most outdoor scenarios. The complex nature of sky lighting makes it difficult to accurately model real life skies. The current solutions to sky illumination can be analytically based and are computationally expensive for complex models, or based on captured data. Such captured data is impractical to capture and difficult to use due to temporally inconsistencies in the captured content. This thesis enhances the state-of-the-art in sky lighting by addressing these problems via novel sky illumination methods that are accurate, practical and flexible. This thesis presents two novel sky illumination methods where; the first of which focuses on clear sky lighting and the second one deals with illumination from cloudy skies. The first approach compactly and efficiently represents sky illumination from both existing analytic sky models and from captured environment maps. For analytic models, the approach leads to a low, constant runtime cost for evaluating lighting. When applied to environment maps, this approach approximates the captured lighting at a significantly reduced memory cost, and enables smooth transitions of sky lighting to be created from a small set of environment maps captured at discrete times of day. This makes capture and rendering of real world sky illumination a practical proposition. Results demonstrate less than 4% loss of accuracy compared to ground truth data. The straightforward implementation makes it possible to compute skies at sub milliseconds times on modest GPUs. The second approach focuses on modelling of clouds from whole sky HDR images by using classification and optimisation techniques. This method pre-classifies the input image according to the cloud types of the pixels which improves both the duration and accuracy of the optimisation. The classification process itself compares well with similar processes from meteorological science and classifies whole images with 97% accuracy and individual pixels with an 80% accuracy. The method can be applied to any cloud type as soon as the optical properties are known. When combined with artificial sky lighting models consisting of arbitrary sun position to relight the extracted cloud model any day time simulations can be obtained based on the original single capture. Results for this method demonstrate a performance of 90% accuracy for fully digitally generated environment maps constructed from a single captured environment map when compared with the original capture.

Chapter 1 Reviews the synthesis of polyolefin block copolymers, focussing on strategies involving catalytic coordination polymerisation to produce end-functionalised polyolefins followed by the growth of a second block from the reactive end group using living/controlled techniques. The advantages and disadvantages of the various literature methods are discussed. Chapter 2 Discusses the utilisation of the Catalytic Hydride Insertion Polymerisation (CHIP) mechanism for the synthesis of low molecular weight polyethylene macromonomers by manipulating the relative concentrations of dihydrogen and ethylene in the reactions. The application of the mechanism is investigated further with the introduction of two non-styrenic comonomers 5-vinyl-2-norbornene and 5-ethylidene-2-norbornene. Observations made when we studied the effects of comonomer concentration and dihydrogen partial pressure on the products are discussed and some mechanistic insights for the copolymerisation between ethylene and norbornene derivatives in the presence of dihydrogen are proposed. Chapter 3 Focusses on the investigation of the mechanism for the copolymerisation between the PE-i-DIB macromonomer and n-butyl acrylate using a small-scale batch process and a larger scale starved feed semi-batch process. Observations are found to be consistent with a reversible cross-propagation mechanism between PE-i-DIB and the propagating P(n-BA) chain in which the continued availability of monomer is key to the lifetime of the process, as demonstrated by the difference in the evolution of molecular weight in the batch and semi-batch processes. The semi-batch process also provides superior control over the copolymerisation compared to the batch process. Chapter 4 Investigates the versatility of the PE-i-DIB macromonomer in copolymerisations with several other types of polar monomer. Copolymer products with vinyl esters, methacrylates and styrenes are synthesised and the challenges provided by the new monomer types are discussed. The products discussed here and in Chapter 3 are characterised by NMR, GPC, DLS and DSC and the evidence is found to be consistent with the presence of block copolymers. Chapter 5 Describes the testing of some of the block copolymers synthesised in Chapters 3 and 4 for their wax crystal modification properties in one type of diesel fuel. The block copolymers were tested as neat additives and in formulation with commercial nucleators and growth arrestors in the Cold Filter Plugging Point (CFPP) test to assess performance and to indicate mode of action. The mode of action was then investigated further by observing the effect of the additives on the crystallisation events using DSC. The performance in CFPP and the observations in DSC are consistent with the block copolymers generally acting as nucleating agents, though some also display single-shot activity. There is an observable trend in performance with the varying size of the polar block as well as varying the polar block itself. Chapter 6 Details the experimental procedures used to carry out the work in this thesis.

<p> <b>BACKGROUND:</b> The 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act created meaningful use (MU) incentive program to promote the nationwide adoption of certified electronic health record (EHR) systems. Computerized physician order entry (CPOE) system is a part of the EHR system and a cornerstone of the MU incentive program, which helps to reduce prescribing errors and enhance care coordination for treatment between providers. </p><p> <b>OBJECTIVES:</b> The main objective of this study was to investigate trends in the adoption of CPOE system for medication orders and determine factors associated with meeting the meaningful use criteria for health information technology. </p><p> <b>METHODS:</b> A cross-sectional analysis was conducted using 10 years of data from the 2006&ndash;2015 National Ambulatory Medical Care Survey (NAMCS), 10 years of 2006&ndash;2015 data from the National Hospital Ambulatory Medical Care Survey (NHAMCS)&mdash;emergency department (ED) component, the 2016 American Hospital Association (AHA) Annual Survey Database, and the 2016 AHA Annual Survey Information Technology (IT) Supplement. The outcomes of the study included the adoption of CPOE for medication orders, drug-drug interaction alerts (DDI), guideline reminders, electronic prescribing (eRx), health information exchange (HIE), and compliance with the MU criteria. Descriptive statistics were calculated for all study variables. Bivariate analysis using the chi-square test was used to determine if there is a significant relationship between the adoption of CPOE for medication orders and timing (pre-post meaningful use). Chi-square test for trend was used to determine the significance of the change in the adoption of several EHR functionalities between 2006 and 2015. Logistic regression analyses were performed to identify factors that influence the adoption of several EHR functionalities. All analyses were performed using SAS 9.3 at an alpha of 0.05. </p><p> <b>RESULTS:</b> In NAMCS 2006&ndash;2015, the weighted surveyed physicians&rsquo; responses were weighted to represent 325,070 ambulatory based physicians throughout the U.S. The majority (66%) of respondents worked in group practices, and 34% worked as solo practitioners. The overall AHA annual survey sample had 6,239 hospitals. Of these, a total of 3,656 hospitals responded to the AHA IT supplement survey, representing a response rate of 59%. Primary care physicians&rsquo; adoption of CPOE systems for medication orders was significantly higher than specialists (p &lt; 0.0001). The adoption of CPOE for medication orders was higher in the Post-MU incentive payments period (2012&ndash;2015) compared to pre-MU incentive payments period (2006&ndash;2011) in both the ambulatory care and ED settings (p &lt; 0.0001). From 2006 through 2015 there was a statistically significant increase in the percent of ambulatory care practices adopting CPOE medication ordering system with clinical decision support (CDS) tools and eRx in the ambulatory care setting (p-trend &lt; 0.001). In the same period, group practices compared to solo practices were significantly more likely to adopt these EHR functionalities (p &lt; 0.0001). From 2013 to 2015, physician offices that generated > 50% of their revenue from Medicaid in the ambulatory care setting were less likely to adopt EHR systems that meet the MU criteria compared those generate &le; 50% (p &lt; 0.01). </p><p> <b>CONCLUSION:</b> Findings indicate that physician specialty, practice size, and percentage of revenue from Medicaid are significantly associated with the adoption of selected EHR functionalities. The CPOE for medication orders adoption rates significantly increased post-MU incentive payments. No significant association was found between for-profit hospitals and sending electronic notification to the patient&rsquo;s primary care physician upon ED visit. These results may be important to design interventions to improve EHR adoption.</p><p>

<p> The purpose of this study was to examine the factors affecting the use of information from business intelligence systems (BIS) on decision-making culture. The relationship between analytical decision-making culture and BIS success factors was measured by data integration, analytic capabilities, information content quality, information access quality, and use of information in business processes. A quantitative statistical analysis approach was utilized to answer one research question. The construct of critical success factors was measured using a predefined model developed by Popovic, Hackney, Coelho, and Jaklic (2012). Survey responses were collected from 227 participants who were decision makers. The responses to the survey indicated a high degree of data integration, analytical capabilities, information content quality, information access quality, use of information in business processes, and analytical decision-making culture within organizations. Notably, the uploaded data reflected that data integration, analytical capabilities, and information content quality were not significantly related to analytical decision-making culture. However, information access quality and use of information in business processes were significantly and positively related to the analytical decision-making culture. With the exponential growth of business intelligence, managers are facing extreme challenges with rapid analytical decision making. Therefore, this study is not only significant to practitioners and the scholarly literature, but it also provided crucial information on BIS success factors for organizations in the Midwestern state. </p><p>

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