Interwell tracers help us understand flow patterns within the reservoir and in getting reliable information of the reservoir continuity. Thus, one can obtain different information about the reservoir barriers, fractures and productivity from the amount of tracer produced at each tracer. The main objective of this study is an attempt to model interwell connectivity by analytically calculating missing tracer data in oil fields for the next step of the calculation of swept volume. The feasibility of using analytical solutions to estimate early data and check differences was carried out. In general; all of these applications refer to the applicability and relative ease of using tracers in oil field. The idea is to determine if it is possible to get a good estimate of the swept pore volumes at an early time before the tracer flood is finished since it often takes a long time to capture the complete tracer tail and there is great value in being able to get an early estimate of the results Results indicate that the extrapolation of tracer tail and using the residence time distribution method give accurate sweep volume predictions without the need to wait for long times to get the full tracer profile. / text

The purpose of this dissertation is to explore whether rehabilitation counselor/consumer racial similarity is related to rehabilitation services provided and employment outcomes achieved. This research contributes additional information to the research base on how to educate and train practicing vocational rehabilitation counselors to support culturally and linguistically diverse (CLD) consumers more effectively. Information regarding racial dyads may help to articulate whether CLD counselors are more effective with CLD consumers. Utilizing the RSA-911 data file submitted by California for fiscal year 2006 as well as 189 Multicultural Counseling Inventory (MCI) surveys collected on practicing vocational rehabilitation counselors, ANOVA, MANOVA, ANCOVA and chi-square analysis were used to measure relationships among counselor and consumer dyads that were either similar or dissimilar in ethnicity and case service variables and outcome variables. Additional analysis focused on the influence of high versus low cultural competency of rehabilitation counselors and the same consumer case service and outcome variables. Study results revealed statistically significant differences on MCI total scores between counselor ethnic groups, with Hispanic counselors demonstrating the highest mean scores overall on the MCI. In addition, significant differences existed between counselor ethnic groups on MCI total scores, as well as all four subscale scores. Chi-square was used to investigate the effect of counselor ethnicity and cultural competency scores on the case service variables of job search, rehabilitation technology, maintenance and college training, as well as outcome variables of competitive employment. MANOVA and ANCOVA were used for the continuous outcome variables of cost of services, wages at closure and weekly earnings at closure. Significant chi-square results were found for some of the service and outcome variables for both the matched counselor/consumer dyads and the counselor competency score groups. More significant findings existed in the ANCOVA analysis for cultural competency scores than for matched ethnicity groups. Implications of the findings and suggestions for future research are discussed. / text

Peptide identification is an essential step in protein identification, and Peptide Spectrum Match (PSM) data set is huge, which is a time consuming process to work on a single machine. In a typical run of the peptide identification method, PSMs are positioned by a cross correlation, a statistical score, or a likelihood that the match between the trial and hypothetical is correct and unique. This process takes a long time to execute, and there is a demand for an increase in performance to handle large peptide data sets. Development of distributed frameworks are needed to reduce the processing time, but this comes at the price of complexity in developing and executing them. In distributed computing, the program may divide into multiple parts to be executed. The work in this thesis describes the implementation of Apache Hadoop framework for large-scale peptide identification using C-Ranker. The Apache Hadoop data processing software is immersed in a complex environment composed of massive machine clusters, large data sets, and several processing jobs. The framework uses Apache Hadoop Distributed File System (HDFS) and Apache Mapreduce to store and process the peptide data respectively.The proposed framework uses a peptide processing algorithm named CRanker which takes peptide data as an input and identifies the correct PSMs. The framework has two steps: Execute the C-Ranker algorithm on Hadoop cluster and compare the correct PSMs data generated via Hadoop approach with the normal execution approach of C-Ranker. The goal of this framework is to process large peptide datasets using Apache Hadoop distributed approach.

Mokslinėje – metodinėje literatūroje, krepšinio tema, didžiausias dėmesys skiriamas technikos ir taktikos veiksmų mokymui ir tobulinimui, krepšininkų žaidimo svarbiausiose varžybose analizei (Stonkus, 1985, 2002). Tačiau neanalizuojama įvairi�� techninio - taktinio rengimo priemonių valdymas ir efektyvumas, metodų reikšmingumas žaidėjų intelekto ir jo gebėjimų, bei žaidimo kokybei. Taip pat mokslinėje literatūroje beveik neanalizuojamas ryšys tarp intelekto gebėjimų, koeficiento ir varžybinės veiklos rodiklių. Tyrimo uždaviniai: 1. Apibrėžti varžybinę veiklą, įtakojančių pedagoginių, psichologinių ir socialinių veiksnių teorines prielaidas. 2. Nustatyti krepšininkių intelekto koeficientą ir intelekto gebėjimus (loginį mąstymą, dėmesio koncentraciją). 3. Išanalizuoti krepšininkių ugdymo proceso poveikį jų intelektiniams gebėjimams ir varžybinės veiklos veiksmingumui. 4. Nustatyti intelekto gebėjimų, koeficiento ir varžybinės veiklos efektyvumo sąsają. Tyrimo išvados: Varžybinės veiklos efektyvumą lemia šie pedagoginiai veiksniai: ugdymas, ugdymo rezultatai, trenerio pedagoginis meistriškumas; psichologiniai veiksniai: krepšininkių poreikiai, mąstymas, interesai, intelektas ir jo gebėjimai, charakteris, temperamentas, valia, motyvai, įsitikinimai, nuostatos, vertybinės orientacijos, psichinė įtampa dėl atsakomybės varžybose, komandos psichologinis klimatas; socialiniai veiksniai: sportininkių socialinė, ekonominė bei kultūrinė šeimos padėtis, bendra ekonominė situacija... [toliau žr. visą tekstą] / In the scientific –methodical literature, basketball theme, dedicate the most attention of technical and tactics operation teaching and development, basketball players in the central march analysis (Stonkus, 14985, 2002). But not analyzing different technical – tactical training device controlling and effectiveness, methods importance, player mentality and their ability, and game quality. Also in the scientific literature almost not analyzing relation between mental ability, coefficient and marches activity indexes. Analysis task: 1. To describe game activity, pedagogical influence, theoretical suggestions of psychological and social factors. 2. To determine basketball player’s intellectual coefficient and intellectual ability (logical mind, attention strength). 3. To traverse influence of basketball player’s education process in their intellectuals abilities and game effectiveness. 4. To determine intellectual ability, coefficient and effectiveness link of the game activities. Conclusions: Effectiveness of the game activities determining these pedagogical factors: education, education results, trainer pedagogical skills; psychological factors: basketball player needs, thinking, interests, intellect and its abilities, character, temperament, will, motives, beliefs, attitudes, values orientations, physical intensity about responsibility in the marches, psychological team climate; social factors: sportswoman’s social, economical and cultural family status, general... [to full text]

I propose that CEO employment history is an observable characteristic that reveals the CEO’s unobservable risk-taking preferences. I hypothesize that CEOs that change employers more frequently (mobile CEOs) have a propensity to bear risk and implement riskier firm policies. Using a sample of S&P 1500 CEOs, I find that firms are more likely to hire mobile CEOs when the firm’s prior risk is high, firm-specific human capital is less important, the prior CEO turnover is forced, the prior CEO has a shorter tenure and the board is smaller and has fewer insiders. Mobile CEOs increase financial leverage, invest more in advertising and less in capital expenditures, and increase firm-specific risk. Mobile CEOs invest more (less) in R&D in homogenous (heterogeneous) industries where firm-specific knowledge is less (more) important in making investment decisions. Shareholders react positively to appointments of CEOs who change employers more frequently. I find no difference in long-run accounting performance for CEOs with different employment histories. Firms’ annual stock returns and sales growth are higher for CEOs who change employers more frequently. The cost of debt increases after the firm appoints a mobile CEO. These findings suggest that lower CEO risk aversion and the potential risk-shifting from shareholders to bondholders are sources of shareholder value increases. In sum, my findings provide evidence that CEO employment history is an observable characteristic that reveals the risk-taking preference of the CEO.

Functional magnetic resonance imaging (fMRI) is a relatively new tool that has been used to examine patterns of neural activation within those with traumatic brain injuries (TBI). A review of relevant literature is presented, including alterations in activity within the frontal and parietal regions that are thought to be compensatory in nature. In addition, possible explanations for discrepancies within this research are discussed. The current study expands upon previous work by incorporating a delayed-match-to-sample (DMS) task within an event-related paradigm and neuropsychological testing to compare 12 individuals with a history of TBI to 12 control participants with orthopedic injuries (OI). Participants in the TBI group were high functioning and in the chronic stage of recovery. Neuropsychological testing revealed statistically significant group differences in measures of working memory, processing speed, memory, and executive functioning. However, groups were comparable in accuracy on the DMS task. Percent signal changes in fMRI data revealed statistically significantly increased activation within the right dorsolateral prefrontal cortex (BA 46) for the TBI group compared to controls. Additional alterations in activation were found between groups within the inferior temporal (BA 37) and parietal (BA 7) regions. Regression analyses showed no relationship between neuropsychological testing and percent signal change within BA 46, but predictive relationships between testing and BA 37 and BA 7. Logistic regression analyses suggest that fMRI data did not add any incremental predictive value beyond neuropsychological testing alone when attempting to predict group (TBI vs. OI) membership.

The high frequency (HF) band lies within 2-30 MHz of the electromagnetic spectrum. For decades, the HF band has been recognized as the primary means of long-range wireless communications. When satellite communication first emerged in 1960s, HF technology was considered to be obsolete. However, with its enduring qualities, HF communication survived through this competition and positioned itself as a powerful complementary and/or alternative technology to satellite communications. HF systems have been traditionally associated with low-rate data transmission. With the shift from analog to digital in voice communication, and increasing demands for high-rate data transmission (e.g., e-mail, Internet, FTP), HF communication has been going through a renaissance. Innovative techniques are required to push the capacity limits of the HF band. In this dissertation, we consider cooperative communication as an enabling technology to meet the challenging expectations of future generation HF communication systems. Cooperative communication exploits the broadcast nature of wireless transmission and relies on the cooperation of users relaying the information to one another. We address the design, analysis, and optimization of cooperative HF communication systems considering both multi-carrier and single-carrier architectures. As the multi-carrier HF system, we consider the combination of the orthogonal frequency division multiplexing (OFDM) with the bit interleaved coded modulation (BICM) as the underlying physical layer platform. It is assumed that cooperating nodes may use different HF propagation mechanisms, such as near-vertical-incidence sky wave (NVIS) and surface wave, to relay their received signals to the destination in different environmental scenarios. Diversity gain analysis, optimum relay selection strategy and power allocation between the source and relays are investigated for the proposed cooperative HF system. For single-carrier HF systems, we first derive a matched-filer-bound (MFB) on the error rate performance of the non-regenerative cooperative systems. The results from the MFB analysis are also used for relay selection and power allocation in the multi-relay cooperative systems. To overcome the intersymbol interference impairment induced by frequency-selectivity of the HF channel, equalization is inevitable at the destination in a single-carrier system. In this work, we investigate the minimum-mean-square-error (MMSE) based linear/decision-feedback frequency domain equalizers (FDEs). Both symbol-spaced and fractionally-spaced implementations of the proposed FDEs are considered and their performance is compared under different channel conditions and sampling phase errors at the relay and destination nodes.

The representation and manipulation of visual content in a computer vision system requires a suitable abstraction of raw visual content such as pixels in an image. In this thesis, we study region-based feature representations and in particular, hierarchical segmentations because they do make no assumptions about region granularity. Hierarchical segmentations create a large feature space that increases the cost of subsequent processing in computer vision systems. We introduce a segment filter to reduce the feature space of hierarchical segmentations by identifying unique regions in the images. The filter uses appearance-based properties of the regions and the structure of the segmentation for the selection of a small set of descriptive regions. The filter works in two phases: selection with a criteria based on relative region size and a sorting based on a variational criteria. The filter is applicable to any hierarchical segmentation algorithm, in particular to bottom-up and region growing approaches. We evaluate the filter's performance against an extensive set of ground-truth regions from a dataset containing image sequences with scenes of different complexity. We demonstrate a novel region-to-region image matching approach as a possible application of our segment filter. A reduced segmentation tree is reconstructed based on the set of regions provided by the filtering. The reduction of the feature space by the segment filter simplifies our region-to-region matching approach. The correspondences between regions from two different images is established by a similarity measure. We use a modified mutual information measurement to compute the similarity of regions. The identified region correspondences are refined using the reduced segmentation tree. Our region-to-region matching approach is evaluated with an extensive set of ground-truth correspondences. This evaluation shows the large potential of both, our filtering and our matching approach.

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Mémoire M.A. (Gestion des P.M.O.)-- Université du Québec à Chicoutimi, 1984. / Document électronique également accessible en format PDF. CaQCU