No / Midwifery programmes attract a large number of applications with an ever increasing demand for the small number of places available. Higher Education Institutions (HEI) are concerned with attracting students who have the right attributes for a career in midwifery and who are likely to succeed on the programme. Potential students however are concerned with making the right choice of HEI where they will be comfortable spending three years working towards attaining a degree in midwifery. The University of Bradford has sought an innovative approach to the selection of students. The programme is predominantly taught through problem based learning, which enables the development of a range of skills that will benefit them in professional practice. Personal attributes required for this process can be identified at an early stage therefore a system has been introduced whereby prospective students are selected purely through the utilization of the problem based learning process.

A biodata based personnel selection measure was created to improve the retention rate of Catalog Telemarketing Representatives at a major U.S. retail company. Five separate empirical biodata scoring methods were compared to examine their usefulness in predicting retention and reducing adverse impact. The Mean Standardized Criterion Method, the Option Criterion Correlation Method, Horizontal Percentage Method, Vertical Percentage Method, and Weighted Application Blank Method using England's (1971) Assigned Weights were employed. The study showed that when using generalizable biodata items, all methods, except the Weighted Application Blank Method, were similar in their ability to discriminate between low and high retention employees and produced similar low adverse impact effects. The Weighted Application Blank Method did not discriminate between the low and high retention employees.

This study investigated the attitudes of sixty-four adolescents who completed an instrument designed to measure attitudes toward factors which influence mate selection. The hypotheses examined attitudes toward mate selection and gender, socioeconomic status, educational goals, family structure, and preferred age at marriage. The data were analyzed by calculating percentages and mean scores. The analysis of data revealed that adolescents valued personality-oriented characteristics as the most important characteristics desired in a mate; males and females held different values for certain factors; adolescents from various socioeconomic levels held different values for certain factors; adolescents with different educational goals, and adolescents residing in various family structures held similar values for each factor; and adolescents with various preferences for age at marriage held different values for certain factors.

In this thesis new methods are presented to achieve performance enhancement in wireless cooperative networks. In particular, techniques to improve diversity gain, throughput and minimise the transmission delay are described. A buffer-aided amplify-and-forward max-link relay selection scheme for both symmetric and asymmetric channels is introduced. This approach shows that the max-link scheme is most effective over the traditional max-SNR scheme when the source-to-relay and relay-to-destination links are symmetric. The closed form expressions for the outage probability and average packet delay of the proposed scheme under both symmetric and asymmetric channel configurations is derived. The diversity order and the coding gain of the AF max-link scheme is analytically provided. Then a novel relay selection scheme with significantly reduced packet delay is proposed. Both the outage performance and average packet delay of the proposed scheme are analysed. The analysis shows that, besides the diversity and coding gains, the proposed scheme has average packet delay similar to that of a non buffer-aided relay system when the channel SNR is sufficiently high thereby. A novel buffer-aided link selection scheme based on network-coding in a multiple hop relay network is proposed. Compared with existing approaches, the proposed scheme significantly increases the system throughput. This is achieved by applying data buffers at the relays to decrease the outage probability and using network-coding to increase the data rate. The closed-form expressions of both the average throughput and packet delay are derived. The proposed scheme has not only significantly higher throughput than both the traditional and existing buffer-aided max-link scheme, but also smaller average packet delay than the max-link scheme. A decode-and-forward buffer-aided relay selection for the underlay cognitive relay networks in the presence of both primary transmitter and receiver is presented. A novel buffer aided relay selection scheme for the cognitive relay network is proposed, where the best relay is selected with the highest signal-to-interference-ratio among all available source-to-relay and relay-to-destination links while keeping the interference to the primary destination within a certain level. A closed-form expression for the outage probability of the proposed relay selection scheme is obtained. Finally, A novel security buffer-aided decode-and-forward cooperative wireless networks is considered. An eavesdropper which can intercept the data transmission from both the source and relay nodes is considered to threaten the security of transmission. Finite size data buffers are assumed to be available at every relay in order to avoid having to select concurrently the best source-to-relay and relay-to-destination links. A new max-ratio relay selection policy is proposed to optimise the secrecy transmission by considering all the possible source-to-relay and relay-to-destination links and selecting the relay having the link which maximises the signal to eavesdropper channel gain ratio. Two cases are considered in terms of knowledge of the eavesdropper channel strengths: exact and average gains, respectively. Closed-form expressions for the secrecy outage probability for both cases are obtained. The proposed max-ratio relay selection scheme is shown to outperform one based on max-min-ratio relay scheme.

Background: Feature selection, also known as variable selection, is a technique that selects a subset from a large collection of possible predictors to improve the prediction accuracy in regression model. First objective of this project is to investigate in what data structure LASSO outperforms forward stepwise method. The second objective is to develop a feature selection method, Feature Selection by L1 Regularization of Subset of Parameters (LRSP), which selects the model by combining prior knowledge of inclusion of some covariates, if any, and the information collected from the data. Mathematically, LRSP minimizes the residual sum of squares subject to the sum of the absolute value of a subset of the coefficients being less than a constant. In this project, LRSP is compared with LASSO, Forward Selection, and Ordinary Least Squares to investigate their relative performance for different data structures. Results: simulation results indicate that for moderate number of small sized effects, forward selection outperforms LASSO in both prediction accuracy and the performance of variable selection when the variance of model error term is smaller, regardless of the correlations among the covariates; forward selection also works better in the performance of variable selection when the variance of error term is larger, but the correlations among the covariates are smaller. LRSP was shown to be an efficient method to deal with the problems when prior knowledge of inclusion of covariates is available, and it can also be applied to problems with nuisance parameters, such as linear discriminant analysis.

La sélection variétale a pour objectif la génération de variétés toujours plus performantes pour des caractères agronomiques d'intérêt. Pour les caractères quantitatifs, qui sont sous contrôle génétique polygénique, la sélection variétale consiste à réunir progressivement dans les nouvelles variétés des allèles favorables pour un maximum de gènes. Les processus de sélection évoluent, notamment par l'intégration des progrès concernant les connaissances génétiques et outils biotechnologiques. La sélection génomique est une méthode qui peut prédire la valeur génétique d'individus à partir de données génomiques et d'un modèle d'effets génétiques appris sur une population de référence. Nos études ont porté sur la possibilité d'insérer la sélection génomique dans le processus de sélection pour en augmenter l'efficacité. Notre sujet a été appliqué à un programme privé qui vise l'obtention de variétés de soja performantes pour le rendement et le contenu des graines en protéines, pour répondre à un besoin de protéines d'origine végétale. Des études génétiques sur une population de lignées générées lors de cycles de sélection successifs ont mis en évidence une structuration génétique en deux sous-populations qui ne sont pas "hermétiques". Nous avons étudié par échantillonnages de populations de test la précision de prédiction obtenue dans nos deux groupes avec différents modèles de GS : des modèles GBLUP additifs avec différentes populations d'apprentissage, puis des modèles d'architectures génétiques plus complexes. Les précisions de prédiction de nos modèles étaient proches les unes des autres. Cependant, nos résultats suggèrent que le modèle GBLUP le plus adapté pour obtenir des prédictions précises au sein de nos deux groupes est un modèle appris sur une population représentative du groupe à prédire et comprenant une composante additive et une composante épistatique additive x additive. Nous avons mis en place une application de la GS dans un cycle de sélection en cours de réalisation. Nous avons estimé le potentiel des croisements de départ par simulation de descendants virtuels et prédiction génomique de leurs performances, ce qui nous a permis de choisir trois populations biparentales prometteuses à l'intérieur desquelles nous avons effectué une sélection sur la base de prédictions génomiques. Nous avons développé un outil permettant de simuler des schémas de sélection sur plusieurs cycles consécutifs. Il s'agit d'un outil flexible et générique du point de vue de la définition des schémas de sélection. Cet outil permet notamment de comparer le gain génétique obtenu avec deux schémas différents à partir d'une même population de départ et d'un même modèle des effets génétiques et environnementaux agissant sur l'expression phénotypique d'un caractère. Avec cet outil, nous avons étudié la précision d'évaluation et les composantes de la variance de deux modèles GBLUP (avec ou sans modélisation de l'épistasie) après simulation de différentes architectures génétiques. Nous avons également comparé le schéma de sélection classique et différents schémas incluant une utilisation de la GS. Avec une comparaison sur un cycle, nous n'avons pas observé de gain à utiliser des schémas intégrant la GS pour augmenter l'efficacité de sélection de nouvelles variétés, à coût constant. Par contre, nous avons observé un gain à utiliser la GS pour choisir les croisements en début de cycle : la valeur génétique moyenne des lignées produites augmente de cycle en cycle. Concernant les alternatives au schéma de sélection classique du soja, des études plus approfondies seront nécessaires. Elles permettront notamment d'inclure la simulation des étapes de sélection sur le contenu des graines en protéines et d'étudier la question du gain génétique à long terme. / Varietal selection aims at the generation of increasingly more performing varieties for agronomic traits of interest. In the case of quantitative traits, which are under polygenic genetic control, varietal selection consists in gradually joining together in the new varieties favorable alleles for a maximum number of genes. Selection processes are evolving, in particular by integrating advances in genetic knowledge and biotechnological tools. Genomic selection is a method that can predict the genetic value of individuals from genomic data and a model of genetic effects learned on a reference population. Our studies have focused on the possibility of including genomic selection in the selection process to increase its efficiency. Our subject has been applied to a private program aimed at obtaining soybean varieties performing for yield and seed protein content to meet a need for proteins of plant origin. Genetic studies on a population of lines generated during successive breeding cycles have shown genetic structuration in two subpopulations that are not "hermetic". We studied by samplings of test populations the prediction accuracies obtained within our two groups with different GS models: additive GBLUP models with different learning populations, and then models of more complex genetic architectures. The prediction accuracies of our models were close to one another. However, our results suggest that the most suitable GBLUP model for obtaining accurate predictions within our two groups is a model learned on a population representative of the group to be predicted and including an additive component and an additive x additive epistatic component. We have implemented an application of GS in a selection cycle in progress. We evaluated the potential of initial crosses by simulation of virtual descendants and genomic prediction of their performances, which allowed us to select three promising biparental populations within which we made a selection based on genomic predictions. We have developed a tool to simulate selection schemes over several consecutive cycles. It is a flexible and generic tool from the point of view of selection schemes definition. This tool makes it possible, in particular, to compare the genetic gain obtained with two different schemes starting from a same starting population and from a same model of genetic and environmental effects acting on the phenotypic expression of a trait. With this tool, we studied evaluation accuracy and variance components of two GBLUP models (with or without epistasy modeling) after simulation of different genetic architectures. We also compared the classic selection scheme and different schemes including a use of GS. With a comparison on one cycle, we did not observe any gain in using schemes integrating GS to increase efficiency of selection of new varieties, at constant cost. On the other hand, we observed a gain in using GS to choose crosses at the beginning of cycle: mean genetic value of produced lines increases from one cycle to another. Regarding alternatives to the traditional soybean selection scheme, further studies will be required. In particular, they will include simulation of selection stages on seed protein content and study of long-term genetic gain.

Thesis (MPA.) -- University of Limpopo, 2006 / The main objective of the study was to scrutinize the difficulties that confront the recruitment and selection processes at provincial government level, which recruitment processes are required to be in conformity with national and provincial policies. Furthermore, the study will also endeavor to answer questions on problems emanating from the recruitment and selection of public managers since 27 April 1994. The population selected for purposes of this study was that of the management team of the Department of Public Works in the Limpopo Province. The population consisted of 281 management officials. A proportional stratified random sampling design was used for obtaining a sample, with head office and the six district offices forming the different stratas. 14% of managers in all stratas were taken as a sample. The data was collected using questionnaires and interviews, followed by the collection of selected government reports with appropriate data. In the case of interviews, the following three methods were iv used, namely, non-scheduled interviews, non-scheduled structured interviews and scheduled structured interviews. The study revealed that in the Department of Public Works:  There was a sustained or uncontrollable movement of managers hopping in and out of the department. This was exacerbated by the lack of a retention strategy for controlling this problem. As a result, the cream of the department’s most resourceful managers was lost.  The recruitment and selection processes in the department of Public Works were inappropriately guided due to a lack of proper planning. As a direct result thereof, the wrong managers were recruited.  The internal source was preferred over the external source in conducting the recruitment and selection processes. This limited the opportunities of employing the correct managers.  There have been biases in that the recruitment and selection processes were manipulated in order to benefit certain individuals v at the expense of others. This has had a negative impact on the morale of the rest of the staff. In view of the findings of this study, it is recommended that further research on a broader scope is imperative, with the population consisting of the entire management in the Limpopo Provincial Government. The purpose of such research should be to determine the extent to which the recruitment and selection of managers were impacting on service delivery, which is critical to the welfare of the Limpopo society in particular, and the South African society in general.

The automated analysis of patients’ biomedical data can be used to derive diagnostic and prognostic inferences about the observed patients. Many noninvasive techniques for acquiring biomedical samples generate data that are characterized by a large number of distinct attributes (i.e. features) and a small number of observed patients (i.e. samples). Deriving reliable inferences, such as classifying a given patient as either cancerous or non-cancerous, using these biomedical data requires that the ratio r of the number of samples to the number of features be within the range 5 < r < 10. To satisfy this requirement, the original set of features in the biomedical datasets can be reduced to an ‘optimal’ subset of features that most discriminates the observed patients. Feature selection techniques strategically seek the ‘optimal’ subset. In this thesis, I present a new feature selection technique - multilevel feature selection. The technique seeks the ‘optimal’ feature subset in biomedical datasets using a multilevel search algorithm. This algorithm combines a hierarchical search framework with a search method. The framework, which provides the capability to easily adapt the technique to different forms of biomedical datasets, consists of increasingly coarse forms of the original feature set that are strategically and progressively explored by the search method. Tabu search (a search meta-heuristics) is the search method used in the multilevel feature selection technique. I evaluate the performance of the new technique, in terms of the solution quality, using experiments that compare the classification inferences derived from the result of the technique with those derived from the result of other feature selection techniques such as the basic tabu-search-based feature selection, sequential forward selection, and random feature selection. In the experiments, the same biomedical dataset is used and equivalent amount of computational resource is allocated to the evaluated techniques to provide a common basis for comparison. The empirical results show that the multilevel feature selection technique finds ‘optimal’ subsets that enable more accurate and stable classification than those selected using the other feature selection techniques. Also, a similar comparison of the new technique with a genetic algorithm feature selection technique that selects highly discriminatory regions of consecutive features shows that the multilevel technique finds subsets that enable more stable classification. / February 2006

In this thesis we will evaluate the effectiveness of using daily return percentiles and power means as momentum indicators for quantitative portfolio selection. The statistical significance of momentum strategies has been well-established, but in this thesis we will select the portfolio size and holding period based on current (2012) trading costs and capital gains tax laws for an individual in the United States to ensure the viability of using these strategies. We conclude that the harmonic mean of daily returns is a superior momentum indicator for portfolio construction over the 1970-2011 backtest period.

The European Commission has for some time indicated a desire to remove the remaining restrictions on cabotage. Such liberalization is expected to result in significant changes on some domestic road transport markets. The Scandinavian markets are among these and the local hauilers fear that the lower wages of Easter European hauliers will leave them out of business. In this thesis a scenario of full cabotage liberalization is assumed. Representatives from associations with interest within the Scandinavian road transport markets has been approached with a qualitative survey on carrier selection criteria. Respondents are asked to determine the importance of the criteria, as well as the relevance to the competition between Scandinavian and Eastern European hauliers. Finally they are asked to assess whether the advantage of each criterion lies with Scandinavian or Eastern European hauliers. The qualitative orientation of the survey is achieved though justification and follow up questions. Reliability of pickups and deliveries is still regarded the most important criteria. Also competitive prices received a high rating. It is concluded that the significant price difference between Scandinavian and Eastern European hauliers will benefit Eastern European hauliers considerably in the competition for the simple “from A to B” shipments. For more complicated shipments, entailing a higher level of service, communication and supply chain integration, the local hauliers are expected to stand their ground.