An empirical analysis of the factors and measures of Enterprise Architecture Management success

Enterprise Architecture Management (EAM) is discussed in academia and industry as a vehicle to guide IT implementations, alignment, compliance assessment, or technology management. Still, a lack of knowledge prevails about how EAM can be successfully used, and how positive impact can be realized from EAM. To determine these factors, we identify EAM success factors and measures through literature reviews and exploratory interviews and propose a theoretical model that explains key factors and measures of EAM success. We test our model with data collected from a cross-sectional survey of 133 EAM practitioners. The results confirm the existence of an impact of four distinct EAM success factors, ‘EAM product quality’, ‘EAM infrastructure quality’, ‘EAM service delivery quality’, and ‘EAM organizational anchoring’, and two important EAM success measures, ‘intentions to use EAM’ and ‘Organizational and Project Benefits’ in a confirmatory analysis of the model. We found the construct ‘EAM organizational anchoring’ to be a core focal concept that mediated the effect of success factors such as ‘EAM infrastructure quality’ and ‘EAM service quality’ on the success measures. We also found that ‘EAM satisfaction’ was irrelevant to determining or measuring success. We discuss implications for theory and EAM practice.

Bayesian computational methods for spatial analysis of images

This thesis introduces a new way of using prior information in a spatial model and develops scalable algorithms for fitting this model to large imaging datasets. These methods are employed for image-guided radiation therapy and satellite based classification of land use and water quality. This study has utilized a pre-computation step to achieve a hundredfold improvement in the elapsed runtime for model fitting. This makes it much more feasible to apply these models to real-world problems, and enables full Bayesian inference for images with a million or more pixels.

A values analysis of attitudes towards the use of law to prevent obesity: How might these values inform public health law theory and practice?

This thesis asks whether values, like government duty, individual responsibility, community and social justice, influence the way that scholars and research participants think about the use of law to prevent obesity. It explores the way participants speak about values when expressing their support for or against a variety of government regulatory interventions, including taxation, food labelling reforms and advertising restrictions. This research contributes to our understanding of theories of public health law and public health ethics. The qualitative findings also have implications for policy development, in advocating for a variety of government interventions to prevent obesity.

An archival analysis of green information technology: The current state and future directions

This thesis provides a review of 199 papers published on Green IT/IS between 2007−2014, in order to present taxonomy of segments in Green IT/IS publications, where the segments are later used for multiple analyses to facilitate future research and to provide a retrospective analysis of existing knowledge and gaps thereof. This research also attempts to make a unique contribution to our understanding of Green IT/IS, by consolidating papers it observes current patterns of literature through approach analysis and segmentation, as well as allocating studies to the technology, process, or outcome (TPO) stage. Highlighting the necessity of a consolidated approach, these classification systems have been combined into a TPO matrix so that the studies could be arranged according to which stage of the Green IT/IS cycle they were focused on. We believe that these analyses will provide a solid platform from which future Green IT/IS research can be launched.

Statistical, electrical and mathematical analysis of water treed cross-linked polyethylene cable insulation

This work examined a new method of detecting small water filled cracks in underground insulation ('water trees') using data from commecially available non-destructive testing equipment. A testing facility was constructed and a computer simulation of the insulation designed in order to test the proposed ageing factor - the degree of non-linearity. This was a large industry-backed project involving an ARC linkage grant, Ergon Energy and the University of Queensland, as well as the Queensland University of Technology.

Analysis of arm elevation muscle activity through different movement planes and speeds during in-water and dry-land exercise

Objective The objectives of this cross-sectional, analytical inference analysis were to compare shoulder muscle activation at arm elevations of 0° to 90° through different movement planes and speeds during in-water and dry-land exercise and to extrapolate this information to a clinical rehabilitation model. Methods Six muscles of right-handed adult subjects (n = 16; males/females: 50%; age: 26.1 ± 4.5 years) were examined with surface electromyography during arm elevation in water and on dry land. Participants randomly performed 3 elevation movements (flexion, abduction, and scaption) through 0° to 90°. Three movement speeds were used for each movement as determined by a metronome (30°/sec, 45°/sec, and 90°/sec). Dry-land maximal voluntary contraction tests were used to determine movement normalization. Results Muscle activity levels were significantly lower in water compared with dry land at 30°/sec and 45°/sec but significantly higher at 90°/sec. This sequential progressive activation with increased movement speed was proportionally higher on transition from gravity-based on-land activity to water-based isokinetic resistance. The pectoralis major and latissimus dorsi muscles showed higher activity during abduction and scaption. Conclusions These findings on muscle activation suggest protocols in which active flexion is introduced first at low speeds (30°/sec) in water, then at medium speeds (45°/sec) in water or on dry land, and finally at high speeds (90°/sec) on dry land before in water. Abduction requires higher stabilization, necessitating its introduction after flexion, with scaption introduced last. This model of progressive sequential movement ensures that early active motion and then stabilization are appropriately introduced. This should reduce rehabilitation time and improve therapeutic goals without compromising patient safety or introducing inappropriate muscle recruitment or movement speed.

Confirmatory factory analysis of the Neck Disability Index in a general problematic neck population indicates a one-factor model

BACKGROUND CONTEXT: The Neck Disability Index frequently is used to measure outcomes of the neck. The statistical rigor of the Neck Disability Index has been assessed with conflicting outcomes. To date, Confirmatory Factor Analysis of the Neck Disability Index has not been reported for a suitably large population study. Because the Neck Disability Index is not a condition-specific measure of neck function, initial Confirmatory Factor Analysis should consider problematic neck patients as a homogenous group. PURPOSE: We sought to analyze the factor structure of the Neck Disability Index through Confirmatory Factor Analysis in a symptomatic, homogeneous, neck population, with respect to pooled populations and gender subgroups. STUDY DESIGN: This was a secondary analysis of pooled data. PATIENT SAMPLE: A total of 1,278 symptomatic neck patients (67.5% female, median age 41 years), 803 nonspecific and 475 with whiplash-associated disorder. OUTCOME MEASURES: The Neck Disability Index was used to measure outcomes. METHODS: We analyzed pooled baseline data from six independent studies of patients with neck problems who completed Neck Disability Index questionnaires at baseline. The Confirmatory Factor Analysis was considered in three scenarios: the full sample and separate sexes. Models were compared empirically for best fit. RESULTS: Two-factor models have good psychometric properties across both the pooled and sex subgroups. However, according to these analyses, the one-factor solution is preferable from both a statistical perspective and parsimony. The two-factor model was close to significant for the male subgroup (p<.07) where questions separated into constructs of mental function (pain, reading headaches and concentration) and physical function (personal care, lifting, work, driving, sleep, and recreation). CONCLUSIONS: The Neck Disability Index demonstrated a one-factor structure when analyzed by Confirmatory Factor Analysis in a pooled, homogenous sample of neck problem patients. However, a two-factor model did approach significance for male subjects where questions separated into constructs of mental and physical function. Further investigations in different conditions, subgroup and sex-specific populations are warranted.

Electromyography and sonomyography analysis of the tibialis anterior: a cross sectional study

Background Foot dorsiflexion plays an essential role in both controlling balance and human gait. Electromyography (EMG) and sonomyography (SMG) can provide information on several aspects of muscle function. The aim was to establish the relationship between the EMG and SMG variables during isotonic contractions of foot dorsiflexors. Methods Twenty-seven healthy young adults performed the foot dorsiflexion test on a device designed ad hoc. EMG variables were maximum peak and area under the curve. Muscular architecture variables were muscle thickness and pennation angle. Descriptive statistical analysis, inferential analysis and a multivariate linear regression model were carried out. The confidence level was established with a statistically significant p-value of less than 0.05. Results The correlation between EMG variables and SMG variables was r = 0.462 (p < 0.05). The linear regression model to the dependent variable “peak normalized tibialis anterior (TA)” from the independent variables “pennation angle and thickness”, was significant (p = 0.002) with an explained variance of R2 = 0.693 and SEE = 0.16. Conclusions There is a significant relationship and degree of contribution between EMG and SMG variables during isotonic contractions of the TA muscle. Our results suggest that EMG and SMG can be feasible tools for monitoring and assessment of foot dorsiflexors. TA muscle parameterization and assessment is relevant in order to know that increased strength accelerates the recovery of lower limb injuries.

A kinematic analysis of the hand function

Background The evaluation of the hand function is an essential element within the clinical practice. The usual assessments are focus on the ability to perform activities of daily life. The inclusion of instruments to measure kinematic variables provides a new approach to the assessment. Inertial sensors adapted to the hand could be used as a complementary instrument to the traditional assessment. Material: clinimetric assessment (Upper Limb Functional Index, Quick Dash), antrophometric variables (eight and weight), dynamometry (palm preasure) was taken. Functional analysis was made with Acceleglove system for the right hand and computer system. The glove has six acceleration sensor, one on each finger and another one on the reverse palm. Method Analytic, transversal approach. Ten healthy subject made six task on evaluation table (tripod pinch, lateral pinch and tip pinch, extension grip, spherical grip and power grip). Each task was made and measure three times, the second one was analyze for the results section. A Matlab script was created for the analysis of each movement and detection phase based on module vector. Results The module acceleration vector offers useful information of the hand function. The data analysis obtained during the performance of functional gestures allows to identify five different phases within the movement, three static phase and tow dynamic, each module vector was allied to one task. Conclusion Module vector variables could be used for the analysis of the different task made by the hand. Inertial sensor could be use as a complement for the traditional assessment system.

Analysis of the neuromuscular activity during rising from a chair in water and on dry land

PURPOSE: The purpose of the present study was to analyze the neuromuscular responses during the performance of a sit to stand [STS] task in water and on dry land. SCOPE: 10 healthy subjects, five males and five females were recruited for study. Surface electromyography sEMG was used for lower limb and trunk muscles maximal voluntarty contraction [MVC] and during the STS task. RESULTS: Muscle activity was significantly higher on dry land than in water normalized signals by MVC from the quadriceps-vastus medialis [17.3%], the quadriceps - rectus femoris [5.3%], the long head of the biceps femoris [5.5%], the tibialis anterior [13.9%], the gastrocnemius medialis [3.4%], the soleus [6.2%]. However, the muscle activity was higher in water for the rectus abdominis [-26.6%] and the erector spinae [-22.6%]. CONCLUSIONS: This study for the first time describes the neuromuscular responses in healthy subjects during the performance of the STS task in water. The differences in lower limb and trunk muscle activity should be considered when using the STS movement in aquatic rehabilitation.

Stochastic analysis of a radial-inflow turbine in the presence of parametric uncertainties

This paper presents an uncertainty quantification study of the performance analysis of the high pressure ratio single stage radial-inflow turbine used in the Sundstrand Power Systems T-100 Multi-purpose Small Power Unit. A deterministic 3D volume-averaged Computational Fluid Dynamics (CFD) solver is coupled with a non-statistical generalized Polynomial Chaos (gPC) representation based on a pseudo-spectral projection method. One of the advantages of this approach is that it does not require any modification of the CFD code for the propagation of random disturbances in the aerodynamic and geometric fields. The stochastic results highlight the importance of the blade thickness and trailing edge tip radius on the total-to-static efficiency of the turbine compared to the angular velocity and trailing edge tip length. From a theoretical point of view, the use of the gPC representation on an arbitrary grid also allows the investigation of the sensitivity of the blade thickness profiles on the turbine efficiency. The gPC approach is also applied to coupled random parameters. The results show that the most influential coupled random variables are trailing edge tip radius coupled with the angular velocity.

Information-theoretic analysis of brain white matter fiber orientation distribution functions

We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.

Automated 3D mapping & shape analysis of the lateral ventricles via fluid registration of multiple surface-based atlases

We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles, designed for monitoring degenerative disease effects in clinical neuroscience studies and drug trials. First we used a set of parameterized surfaces to represent the ventricles in a manually labeled set of 9 subjects' MRIs (atlases). We fluidly registered each of these atlases and mesh models to a set of MRIs from 12 Alzheimer's disease (AD) patients and 14 matched healthy elderly subjects, and we averaged the resulting meshes for each of these images. Validation experiments on expert segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease-related alterations monotonically improved as the number of atlases, N, was increased from 1 to 9. We then combined the segmentations with a radial mapping approach to localize ventricular shape differences in patients. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases, and we formulated a statistical stopping criterion to determine the optimal value of N. Anterior horn anomalies in Alzheimer's patients were only detected with the multi-atlas segmentation, which clearly outperformed the standard single-atlas approach.

Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship

Modern non-invasive brain imaging technologies, such as diffusion weighted magnetic resonance imaging (DWI), enable the mapping of neural fiber tracts in the white matter, providing a basis to reconstruct a detailed map of brain structural connectivity networks. Brain connectivity networks differ from random networks in their topology, which can be measured using small worldness, modularity, and high-degree nodes (hubs). Still, little is known about how individual differences in structural brain network properties relate to age, sex, or genetic differences. Recently, some groups have reported brain network biomarkers that enable differentiation among individuals, pairs of individuals, and groups of individuals. In addition to studying new topological features, here we provide a unifying general method to investigate topological brain networks and connectivity differences between individuals, pairs of individuals, and groups of individuals at several levels of the data hierarchy, while appropriately controlling false discovery rate (FDR) errors. We apply our new method to a large dataset of high quality brain connectivity networks obtained from High Angular Resolution Diffusion Imaging (HARDI) tractography in 303 young adult twins, siblings, and unrelated people. Our proposed approach can accurately classify brain connectivity networks based on sex (93% accuracy) and kinship (88.5% accuracy). We find statistically significant differences associated with sex and kinship both in the brain connectivity networks and in derived topological metrics, such as the clustering coefficient and the communicability matrix.

Discovery of genes that affect human brain connectivity: A genome-wide analysis of the connectome

Human brain connectivity is disrupted in a wide range of disorders from Alzheimer's disease to autism but little is known about which specific genes affect it. Here we conducted a genome-wide association for connectivity matrices that capture information on the density of fiber connections between 70 brain regions. We scanned a large twin cohort (N=366) with 4-Tesla high angular resolution diffusion imaging (105-gradient HARDI). Using whole brain HARDI tractography, we extracted a relatively sparse 70×70 matrix representing fiber density between all pairs of cortical regions automatically labeled in co-registered anatomical scans. Additive genetic factors accounted for 1-58% of the variance in connectivity between 90 (of 122) tested nodes. We discovered genome-wide significant associations between variants and connectivity. GWAS permutations at various levels of heritability, and split-sample replication, validated our genetic findings. The resulting genes may offer new leads for mechanisms influencing aberrant connectivity and neurodegeneration. © 2012 IEEE.