Medical interpreter services will be essential for developing and implementing culturally relevant interventions and treatment for limited English proficiency (LEP) populations. This study sought to identify the possible risks or protective factors that may be associated with vicarious traumatization (VT) or vicarious posttraumatic growth among medical interpreters in behavioral health settings. A 2-step cluster analysis was conducted yielding 2 distinct groupings of medical interpreters (Subtype 1, n = 73; Subtype 2, n = 101). The most important predictor determining the 2 subtypes was whether the participant had a personal history of trauma. In addition, there were significant differences between the 2 subtypes among the following variables: Trauma and Attachment Belief Scale T-scores of VT; years as a medical interpreter; years as a behavioral health medical interpreter; level of education as it relates to interpreting; personal history of trauma; personal or family history similar to any of the trauma survivors served in the past year; specific mental health training; sought personal therapy related to exposure to traumatic material from work environment; current relationship status; race; and whether spoken, sign, or both spoken and sign language interpretation was provided. The results of this quantitative study further support the constructivist self-development theory where VT is the result of the accumulated effects of repeated exposure to trauma material in combination with the person of the provider. Understanding these risk and protective factors will continue to support the provision of effective treatment of LEP individuals in behavioral health settings and the ongoing professional development of behavioral health medical interpreters.

We present two Swarm Intelligence based approaches for data clustering. The first algorithm, Fuzzy Ants, presented in this thesis clusters data without the initial knowledge of the number of clusters. It is a two stage algorithm. In the first stage the ants cluster data to initially create raw clusters which are refined using the Fuzzy C Means algorithm. Initially, the ants move the individual objects to form heaps. The centroids of these heaps are redefined by the Fuzzy C Means algorithm. In the second stage the objects obtained from the Fuzzy C Means algorithm are hardened according to the maximum membership criteria to form new heaps. These new heaps are then moved by the ants. The final clusters formed are refined by using the Fuzzy C Means algorithm. Results from experiments with 13 datasets show that the partitions produced are competitive with those from FCM. The second algorithm, Fuzzy ant clustering with centroids, is also a two stage algorithm, it requires an initial knowledge of the number of clusters in the data. In the first stage of the algorithm ants move the cluster centers in feature space. The cluster centers found by the ants are evaluated using a reformulated Fuzzy C Means criterion. In the second stage the best cluster centers found are used as the initial cluster centers for the Fuzzy C Means algorithm. Results on 18 datasets show that the partitions found by FCM using the ant initialization are better than those from randomly initialized FCM. Hard C Means was also used in the second stage and the partitions from the ant algorithm are better than from randomly initialized Hard C Means. The Fuzzy Ants algorithm is a novel method to find the number of clusters in the data and also provides good initializations for the FCM and HCM algorithms. We performed sensitivity analysis on the controlling parameters and found the Fuzzy Ants algorithm to be very sensitive to the Tcreateforheap parameter. The FCM and HCM algorithms, with random initializations can get stuck in a bad extrema, the Fuzzy ant clustering with centroids algorithm successfully avoids these bad extremas.

Traffic signal systems serve as one of the most powerful control tools in improving the efficiency of surface transportation travel. Traffic operations on arterial roads are particularly complex because of traffic interruptions caused by signalized intersections along the corridor. This dissertation research presents a systematic framework of integrated traffic control in an attempt to break down the complexities into several simpler sub-problems such as pattern recognition, environment-mobility relationships and multi-objective optimization for multi-criterial signal timing design. The overall goal of this dissertation is to develop signal timing plans, including a day plan schedule, cycle length parameters, splits and offsets, which are suitable for real traffic conditions with consideration of multi-criterial performance of the surface transportation system. To this end, the specific objectives are to: (1) identify appropriate time-of-day breakpoints and intervals to accommodate traffic pattern variations for day plan schedule of signal timing; (2) explore the relationship between environmental outcomes (e.g., emissions) from emission estimators and mobility measures (e.g., delay and stops) for different types of intersections; (3) optimize signal timing parameters for multi-criteria objectives (e.g., minimizing vehicular delay, number of stops, marginal costs of emissions and total costs), with the comparison of performance metrics for different objectives, at the intersection level; (4) optimize arterial offsets for different objectives at the arterial level and compare the performance metrics of different objectives to recommend suitable objectives for integrated multi-criteria signal timing design in arterial traffic operations. An extensive review of the literature, which covers existing tools, traffic patterns, traffic control with environmental concerns, and related optimization methods, shows that both opportunities and challenges have emerged for multi-criteria traffic signal timing design. These opportunities include large quantities of traffic condition data collected by system detectors or non-intrusive data collection platforms as well as powerful tools for microscopic traffic modeling and instantaneous emission estimation. The challenge is how to effectively deal with these big data, either from field collection or detailed simulation, and provide useful information for decision makers in practice. Methodologically, there's a tradeoff between the accuracy of objective function values and the computational efficiency of simulation and optimization. To address this need, in this dissertation, traffic signal timing design that systematically enables the use of integrated data and models are investigated and analyzed in the four steps/studies. The technology of identifying time-of-day breakpoints in the first study shows a mathematical way to classify dynamic traffic patterns by understanding dynamic traffic features and instabilities at a macroscopic level on arterials. Given the limitations of using built-in emissions modules within current traffic simulation and signal optimization tools, the metamodeling-based approach presented in the second study makes a methodological contribution. The findings of the second study on environment-mobility relationships set up the base for extensive application of two-stage optimization in the third and fourth studies for sustainable traffic operations and management. The comparison of outputs from an advanced estimator with those from the current tool also addresses improving the emissions module for more accurate analysis (e.g., benefit-cost analysis) in practical signal retiming projects. The third study shows that there are tradeoffs between minimizing delay and minimizing marginal costs of emissions. When total cost (including cost of delay, fuel consumption and emissions) is set as a single objective function, that objective clears the way for relatively reliable results for all the aspects. In the fourth study, the improvements in marginal cost of emissions and total cost by dynamic programming procedure are obvious, which indicates the effectiveness of using total link cost as an objective at the corridor level. In summary, this dissertation advocates a sustainable traffic control system by simultaneously considering travel time, fuel consumption and emissions. The outcomes of this integrated multi-criteria signal timing design can be easily implemented by traffic operators in their daily life of retiming signal timing.

高級人力的培育和充分利用, 是政府施政的基本目標,當我們論及高級人 力的運用時,具有大專(含)以上學歷的工作者對目前職業的滿意程度是不 能忽略的一項因素。「職業滿意度」是指就業者在工作情境中所得到的心 理反應狀態而言。滿意程度的高低, 會影響到工作的效率,以至於整個工 作單位的績效。因此, 工作者滿意程度與否,亦為探討人力運用問題時重 要的一環。本文以實際問卷調查資料,就影響職業滿意度的因素對就業者 的職業滿意度作判別分析。傳統上的判別分析方法,都是用來處理連續性 資料, 而本文所要分析的資料都是離散資料 , 即屬質化(qualitative)的 變數。文中介紹一種離散資料的判別分析方法, 及應用在實際資料的分析 結果;另外,本文進而嘗試以一般用於處理連續性資料的常態假設及無母數 統計法來分析離散資料, 所得的判別結果與離散資料 判別法相比較。最 後本文以叢聚分析法, 來討論職業別對職業滿意度的叢聚狀況。

This thesis primarily addresses the problem of automatic measurement of ore textures by image analysis in a way that is relevant to mineral processing. Specifically, it addresses the following major hypotheses: • Automatic logging of drill core by image analysis provides a feasible alternative to manual logging by geologists. • Image analysis can quantify process mineralogy by physically meaningful parameters. • Multi-scale image analysis, over a wide range of size scales, provides potential benefits to process mineralogy that are additional to those available from small-scale analysis alone, and also better retains the information content of manual logging. • Image analysis can provide physically meaningful, ore-texture-related, additive regionalised variables that can be input to geostatistical models and the definition of domains. The central focus of the thesis is the development of an automatic, multi-scale method to identify and measure objects in an image, using a specially-developed skeleton termed the morphological CWT skeleton. This skeleton is a multi-scale extension of the morphological skeleton commonly used in image analysis, and is derived from the continuous wavelet transform (CWT). Objects take the form of hierarchical segments from image segmentation based on the CWT. Only the Mexican hat, also known as the Laplacian-of-Gaussian, wavelet is used, although other wavelet shapes are possible. The natural scale of each object is defined to be the size scale at which its CWT signal (the contrast between the interior and exterior of the object) is strongest. In addition to the natural scale, the analysis automatically records the mineral composition of both the interior and exterior of each object, and shape descriptors of the object. The measurements of natural scale, mineral composition and shape are designed to relate to: • The size to which ore must be broken in order to liberate objects. • Minerals that need to be separated by physical or chemical means once objects have been liberated. • Capability to distinguish qualitatively different ore-texture types that may have different geological origins and for which different processing regimes may provide an economic benefit. Measurements are taken over size scales from three pixels to hundreds of pixels. For the major case study the pixel size is about 50 µm, but the methodology is equally applicable to photomicrographs in which the pixel size is about 4 µm. The methodology for identifying objects in images contributes to the field of scale-space image segmentation, and has advantages in performing the following actions automatically: • Finding optimal size scales in hierarchical image segmentation (natural scale). • Merging segments that are similar and spatially close together (although not necessarily touching), using the structure of the morphological CWT skeleton, thus aiding recognition of complex structures in an image. • Defining the contrast between each segment and its surrounding segments appropriately for the size scale of the segment, in a way that extends well beyond the segment boundary. For process mineralogy this contrast quantifies mineral associations at different size scales. The notion of natural scale defined in this thesis may have applications to other fields of image processing, such as mammography and cell measurements in biological microscopy. The objects identified in images are input to cluster analysis, using a finite mixture model to group the objects into object populations according to their size, composition and shape descriptors. Each image is then characterised by the abundances of different object populations that occur in it. These abundances form additive, regionalised variables that can be input into geostatistical block models. The images are themselves input to higher-level cluster analysis based on a hidden Markov model. A collection of images is divided into different ore texture types, based on differences in the abundances of the textural object populations. The ore texture types help to define geostatistical domains in an ore body. Input images for the methodology take the form of mineral maps, in which a particular mineral has been assigned to each pixel in the image prior to analysis. A method of analysing unmapped, raw colour images of ore is also outlined, as is a new model for fracture of ore. The major case study in the thesis is an analysis of approximately 1000 metres of continuously-imaged drill core from four drill holes in the Ernest Henry iron-oxide-copper-gold ore deposit (Queensland, Australia). Thirty-one texture-related variables are used to summarise the individual half-metres of drill core, and ten major ore texture types are identified. Good agreement is obtained between locations of major changes in ore type found by automatic image analysis, and those identified from manual core logging carried out by geologists. The texture-related variables are found to explain a significant amount of the variation in comminution hardness of ore within the deposit, over and above that explained by changes in abundances of the component minerals. The thesis also contributes new algorithms with wide applicability in image processing: • A fast algorithm for computing the continuous wavelet transform of a signal or image: The new algorithm is simpler in form and several times faster than the best previously-published algorithms. It consists of a single finite impulse response (FIR) filter. • A fast algorithm for computing Euclidean geodesic distance. This algorithm runs in O(1) arithmetic operations per pixel processed, which has not been achieved by any previously published algorithm. Geodesic distance is widely used in image processing, for segmentation and shape characterisation.

<p>This study investigates the realisation of phonological quantity in the dialects of Modern Swedish, based on a corpus containing recordings from 86 locations in Sweden and the Swedishspeaking parts of Finland. The corpus was recorded as part of the national SweDia project.</p><p>The study is explorative in character. Quantity structures in Swedish dialects and their geographical distribution, as described in the dialectological literature, are compared to the results of a data-driven categorisation (cluster analysis). The results reveal an overall good correspondence of the data driven and the traditional categorisation, although with some deviations in the detail.</p><p>The study is divided into two parts. The first part lays the foundation for the data-driven categorisation, which is then described in the second part. First, the phonology and phonetics of quantity in Swedish are described in terms of durational distinctions and vocalic quality differences that typically accompany the durational differences. Preaspiration, which appears to be a normative feature in some dialects, is covered as well. An overview of the historical development of the Swedish quantity system is provided, with special emphasis on a phonological interpretation of quantity changes. Thereafter, dialectological evidence is combined with phonological and typological considerations to develop a categorisation of Swedish dialects.</p><p>The second part explains the methodology of cluster analysis and applies this method to vowel and consonant durations from one contrastive word pair, in order to obtain an alternative dialect categorisation. Analyses of vowel quality and preaspiration are performed in addition to the durational analyses. Hypotheses derived from the cluster analysis are then tested on one additional word pair recorded in 75 locations and on three additional word pairs recorded in four locations.</p><p>The general pattern emerging from the cluster analysis is a categorisation of the dialects into three main types, a Finland-Swedish, a Northern and a Southern type. This categorisation shows a good geographical agreement with the categorisation that is derived from the analysis of the dialectological literature. Therefore, the durational patterns of the three types are interpreted as reflections of three different phonological systems: 4-way systems with vocalic and consonantal quantity, 3-way systems with vocalic quantity and with consonantal quantity only after short vowels, and 2-way systems with complementary quantity. From the historical perspective, the 4-way system constitutes the most conservative and the 2-way system the most recently developed system.</p><p>Finally, it is argued that the historical development is one of the factors behind occasional mismatches between the data-driven and the dialectological categorisation. Data from one of the dialects, which has recently abandoned a 4-way system but has obviously retained the durational properties of the older system, is used as an example to illustrate this historical hypothesis.</p>

This study investigates the realisation of phonological quantity in the dialects of Modern Swedish, based on a corpus containing recordings from 86 locations in Sweden and the Swedishspeaking parts of Finland. The corpus was recorded as part of the national SweDia project. The study is explorative in character. Quantity structures in Swedish dialects and their geographical distribution, as described in the dialectological literature, are compared to the results of a data-driven categorisation (cluster analysis). The results reveal an overall good correspondence of the data driven and the traditional categorisation, although with some deviations in the detail. The study is divided into two parts. The first part lays the foundation for the data-driven categorisation, which is then described in the second part. First, the phonology and phonetics of quantity in Swedish are described in terms of durational distinctions and vocalic quality differences that typically accompany the durational differences. Preaspiration, which appears to be a normative feature in some dialects, is covered as well. An overview of the historical development of the Swedish quantity system is provided, with special emphasis on a phonological interpretation of quantity changes. Thereafter, dialectological evidence is combined with phonological and typological considerations to develop a categorisation of Swedish dialects. The second part explains the methodology of cluster analysis and applies this method to vowel and consonant durations from one contrastive word pair, in order to obtain an alternative dialect categorisation. Analyses of vowel quality and preaspiration are performed in addition to the durational analyses. Hypotheses derived from the cluster analysis are then tested on one additional word pair recorded in 75 locations and on three additional word pairs recorded in four locations. The general pattern emerging from the cluster analysis is a categorisation of the dialects into three main types, a Finland-Swedish, a Northern and a Southern type. This categorisation shows a good geographical agreement with the categorisation that is derived from the analysis of the dialectological literature. Therefore, the durational patterns of the three types are interpreted as reflections of three different phonological systems: 4-way systems with vocalic and consonantal quantity, 3-way systems with vocalic quantity and with consonantal quantity only after short vowels, and 2-way systems with complementary quantity. From the historical perspective, the 4-way system constitutes the most conservative and the 2-way system the most recently developed system. Finally, it is argued that the historical development is one of the factors behind occasional mismatches between the data-driven and the dialectological categorisation. Data from one of the dialects, which has recently abandoned a 4-way system but has obviously retained the durational properties of the older system, is used as an example to illustrate this historical hypothesis.

Daily aerosol samples (PM) were collected at a rural station, which is 5 km away from the Turkish-Bulgarian border between April 2006 and March 2008. Aerosol samples were analyzed for elements by ICPMS, ions by IC and black carbon by aethalometer to provide a multi-species aerosol data set, which can represent aerosol population for Northwestern Turkey and Eastern Europe. Average concentration of SO42-, NO3- and NH4+ was 5.8, 2.9 and 2.0 &mu / g m-3, respectively, while total aerosol mass was 66 &mu / g m-3. Seasonal variation of crustal species had maxima in summer, while most of the anthropogenic species had maxima in winter. Rainfall was found as the only local meteorological parameter affecting aerosols concentrations. The dominant sectors of air masses arriving the Northwestern Turkey were northeast in summer and west-northwest in winter. Air masses were classified into five clusters regarding their wind speed and direction. Most species indicated significant differences between clusters. The influence of forest fires in Ukraine and Russian Federation was identified by cluster analysis using soluble K as tracer. Source apportionment of PM was carried out by EPA PMF model and five sources were resolved. Crustal emissions were found to be the major contributor to PM (41%). The second largest source was distant anthropogenic sources with a contribution of 26%. Traffic was also a remarkable source with 16% contribution. Sea salt and stationary combustion sources accounted for 9% and 8% of PM, respectively. Potential source regions of resolved sources were determined by potential source contribution function (PSCF).

Hurricane Katrina devastated New Orleans, the Gulf Coast and the United States in August of 2005. While an emerging literature base details the consequences and lessons learned from Hurricane Katrina, a critical missing piece for understanding Hurricane Katrina American landfall is a rhetorical perspective. I argue a rhetorical perspective can significantly contribute to a better understanding of Hurricane Katrina’s implications for creating policy, community and identity. As a case study, I employ Kenneth Burke’s cluster analysis to examine the use of the label “Third World” to describe New Orleans, the Gulf Coast and the United States in the mass media coverage of Hurricane Katrina.

Memory impairments are common in individuals with temporal lobe epilepsy (TLE). This is understandable given that temporal lobe brain structures involved in TLE play a central role in encoding memories. It is widely accepted that individuals whose seizure focus is in the left temporal lobe (LTLE) tend to have verbal memory impairments, whereas individuals whose seizure focus is in the right temporal lobe (RTLE) tend to have visuospatial memory impairments. However, evidence of functional subdivisions within the left and right temporal lobes in both the animal and human literature suggest that more specific subtypes of memory impairment may exist in TLE based on differences in seizure foci. The aim of this study was to identify more specific subtypes of memory-impairments in patients with intractable TLE using several measures of memory functioning and cluster analysis. Identification of more specific memory subtypes in TLE could have prognostic significance for patients and contribute to our knowledge about the organization of memory systems of the human brain. Four memory subtypes were identified in this sample: 1) patients with mild to moderate figural memory deficits; 2) patients with moderate to severe figural memory deficits, mild facial recognition deficits, and mild attention/concentration deficits; 3) patients with severe figural memory deficits and mild verbal episodic memory deficits; and 4) patients with no episodic or semantic memory deficits. Unexpectedly, the subtypes found did not exhibit the expected pattern of verbal memory impairments with left temporal lobe damage/dysfunction or visuospatial memory impairments with right temporal lobe damage/dysfunction. However, consistent with the literature, there was a trend towards some clusters with better verbal memory having higher left hippocampal volumes; and a trend towards one cluster with facial recognition deficits having lower anterior temporal lobe volumes. Small sample sizes in this study limited the ability to clearly validate many of the cluster differences, particularly differences in brain volumes. Nevertheless, the results of this study support the hypothesis that subtypes of memory impairment do exist in patients with TLE. With larger sample sizes, it is plausible that additional subtypes may be found, or the characteristics of the subtypes found may become clearer.