This thesis shows highly encouraging results as the gain of accuracy reached 18.4% when the pairwise comparisons method was used instead of the direct method for comparing random shapes. The thesis describes a heuristic for generating random but nice shapes, called placated shapes. Random, but visually nice shapes, are often needed for cognitive experiments and processes. These shapes are produced by applying the Gaussian blur to randomly generated polygons. Afterwards, the threshold is set to transform pixels to black and white from di erent shades of gray. This transformation produces placated shapes for easier estimation of areas. Randomly generated placated shapes are used to perform the Monte Carlo method to test the accuracy of cognitive processes by using pairwise comparisons. An on-line questionnaire has been implemented and participants were asked to estimate the areas of ve shapes using a provided unit of measure. They were also asked to compare the shapes in pairs. Such Monte Carlo experiment has never been conducted for 2D case. The received results are of considerable importance.

AN ABSTRACT OF THE DISSERTATION OF CANDACE A. DAVIS, for the Doctor of Philosophy Degree in ANTHROPOLOGY, presented on March 31, 2011, at Southern Illinois University at Carbondale. TITLE: BILATERAL ASYMMETRY IN INCISORS: IMPLICATIONS FOR MIOCENE HOMINOID SPECIES DIAGNOSIS MAJOR PROFESSOR: Dr. Robert S. Corruccini The primary purpose of this dissertation is to show how knowledge of variation and asymmetry in incisor antimeric pairs of living great ape genera can be utilized as a "yardstick" for pairwise comparisons of isolated Miocene ape incisors from the two genera Kenyapithecus and Equatorius . The research was designed to help determine whether these fossil teeth could be reliably sorted into one or more than one genera. Both metric and morphological data for each class of incisor were recorded for Kenyapithecus and Equatorius , and resampling was performed to determine the significance of variation (p<.05) for each of 12 traits. Intraindividual antimeric differences in three genera of extant great apes were compared with interspecimen differences between Equatorius and Kenyapithecus. Pairwise comparisons using resampling sorted out which traits showed intraindividual significant variation and which could be used to discriminate between the two fossil genera under consideration. Based on these results, one can cautiously conclude the two fossil species within these genera are not different enough to justify placing them in two different genera.

The problem of testing multiple hypotheses at once is called the problem of multiple testing. We focused on comparing more than two means in one- way analysis of variance, also known as ANOVA. We dealt with the Tukey me- thod, the Hothorn-Bretz-Westfall method, the bootstrap-based methods and also the Bonferroni method and its modification by the Holm method, the last two methods being popular mainly for their simplicity. We focused in detail on the asymptotic behavior of these methods and then compared them using si- mulations in terms of compliance with the prescribed level and in terms of average strength. Bonferroni's method, which is conservative, is known to lose strength compared to other methods. However, its modification of Holm's method, which is also conservative, in some cases by its strength equates to other more complex methods. 1

Pairwise comparison matrices (PCMs) play a key role in multi-criteria decision making, especially in the analytic hierarchy process. It could be necessary for an expert to compare alternatives based on various criteria. However, for a variety of reasons, such as lack of time or insufficient knowledge, it may happen that the expert cannot provide judgments on all pairs of alternatives. In this case, an incomplete pairwise comparison matrix is formed. In the first research part, an optimization algorithm is proposed for the optimal completion of an incomplete PCM. It is intended to numerically minimize a constrained eigenvalue problem, in which the objective function is difficult to write explicitly in terms of variables. Numerical simulations are carried out to examine the performance of the algorithm. The simulation results show that the proposed algorithm is capable of solving the minimization of the constrained eigenvalue problem. In the second part, a comparative analysis of eleven completion methods is studied. The similarity of the eleven completion methods is analyzed on the basis of numerical simulations and hierarchical clustering. Numerical simulations are performed for PCMs of different orders considering various numbers of missing comparisons. The results suggest the existence of a cluster of five extremely similar methods, and a method significantly dissimilar from all the others. In the third part, the filling in patterns (arrangements of known comparisons) of incomplete PCMs based on their graph representation are investigated under given conditions: regularity, diameter and number of vertices, but without prior information. Regular and quasi-regular graphs with minimal diameter are proposed. Finally, the simulation results indicate that the proposed graphs indeed provide better weight vectors than alternative graphs with the same number of comparisons. This research problem’s contributions include a list of (quasi-)regular graphs with diameters of 2 and 3, and vertices from 5 up to 24.

Les données de classement, c.à. d. des listes ordonnées d'objets, apparaissent naturellement dans une grande variété de situations, notamment lorsque les données proviennent d’activités humaines (bulletins de vote d'élections, enquêtes d'opinion, résultats de compétitions) ou dans des applications modernes du traitement de données (moteurs de recherche, systèmes de recommendation). La conception d'algorithmes d'apprentissage automatique, adaptés à ces données, est donc cruciale. Cependant, en raison de l’absence de structure vectorielle de l’espace des classements et de sa cardinalité explosive lorsque le nombre d'objets augmente, la plupart des méthodes classiques issues des statistiques et de l’analyse multivariée ne peuvent être appliquées directement. Par conséquent, la grande majorité de la littérature repose sur des modèles paramétriques. Dans cette thèse, nous proposons une théorie et des méthodes non paramétriques pour traiter les données de classement. Notre analyse repose fortement sur deux astuces principales. La première est l’utilisation poussée de la distance du tau de Kendall, qui décompose les classements en comparaisons par paires. Cela nous permet d'analyser les distributions sur les classements à travers leurs marginales par paires et à travers une hypothèse spécifique appelée transitivité, qui empêche les cycles dans les préférences de se produire. La seconde est l'utilisation des fonctions de représentation adaptées aux données de classements, envoyant ces dernières dans un espace vectoriel. Trois problèmes différents, non supervisés et supervisés, ont été abordés dans ce contexte: l'agrégation de classement, la réduction de dimensionnalité et la prévision de classements avec variables explicatives.La première partie de cette thèse se concentre sur le problème de l'agrégation de classements, dont l'objectif est de résumer un ensemble de données de classement par un classement consensus. Parmi les méthodes existantes pour ce problème, la méthode d'agrégation de Kemeny se démarque. Ses solutions vérifient de nombreuses propriétés souhaitables, mais peuvent être NP-difficiles à calculer. Dans cette thèse, nous avons étudié la complexité de ce problème de deux manières. Premièrement, nous avons proposé une méthode pour borner la distance du tau de Kendall entre tout candidat pour le consensus (généralement le résultat d'une procédure efficace) et un consensus de Kemeny, sur tout ensemble de données. Nous avons ensuite inscrit le problème d'agrégation de classements dans un cadre statistique rigoureux en le reformulant en termes de distributions sur les classements, et en évaluant la capacité de généralisation de consensus de Kemeny empiriques.La deuxième partie de cette théorie est consacrée à des problèmes d'apprentissage automatique, qui se révèlent être étroitement liés à l'agrégation de classement. Le premier est la réduction de la dimensionnalité pour les données de classement, pour lequel nous proposons une approche de transport optimal, pour approximer une distribution sur les classements par une distribution montrant un certain type de parcimonie. Le second est le problème de la prévision des classements avec variables explicatives, pour lesquelles nous avons étudié plusieurs méthodes. Notre première proposition est d’adapter des méthodes constantes par morceaux à ce problème, qui partitionnent l'espace des variables explicatives en régions et assignent à chaque région un label (un consensus). Notre deuxième proposition est une approche de prédiction structurée, reposant sur des fonctions de représentations, aux avantages théoriques et computationnels, pour les données de classements. / Ranking data, i.e., ordered list of items, naturally appears in a wide variety of situations, especially when the data comes from human activities (ballots in political elections, survey answers, competition results) or in modern applications of data processing (search engines, recommendation systems). The design of machine-learning algorithms, tailored for these data, is thus crucial. However, due to the absence of any vectorial structure of the space of rankings, and its explosive cardinality when the number of items increases, most of the classical methods from statistics and multivariate analysis cannot be applied in a direct manner. Hence, a vast majority of the literature rely on parametric models. In this thesis, we propose a non-parametric theory and methods for ranking data. Our analysis heavily relies on two main tricks. The first one is the extensive use of the Kendall’s tau distance, which decomposes rankings into pairwise comparisons. This enables us to analyze distributions over rankings through their pairwise marginals and through a specific assumption called transitivity, which prevents cycles in the preferences from happening. The second one is the extensive use of embeddings tailored to ranking data, mapping rankings to a vector space. Three different problems, unsupervised and supervised, have been addressed in this context: ranking aggregation, dimensionality reduction and predicting rankings with features.The first part of this thesis focuses on the ranking aggregation problem, where the goal is to summarize a dataset of rankings by a consensus ranking. Among the many ways to state this problem stands out the Kemeny aggregation method, whose solutions have been shown to satisfy many desirable properties, but can be NP-hard to compute. In this work, we have investigated the hardness of this problem in two ways. Firstly, we proposed a method to upper bound the Kendall’s tau distance between any consensus candidate (typically the output of a tractable procedure) and a Kemeny consensus, on any dataset. Then, we have casted the ranking aggregation problem in a rigorous statistical framework, reformulating it in terms of ranking distributions, and assessed the generalization ability of empirical Kemeny consensus.The second part of this thesis is dedicated to machine learning problems which are shown to be closely related to ranking aggregation. The first one is dimensionality reduction for ranking data, for which we propose a mass-transportation approach to approximate any distribution on rankings by a distribution exhibiting a specific type of sparsity. The second one is the problem of predicting rankings with features, for which we investigated several methods. Our first proposal is to adapt piecewise constant methods to this problem, partitioning the feature space into regions and locally assigning as final label (a consensus ranking) to each region. Our second proposal is a structured prediction approach, relying on embedding maps for ranking data enjoying theoretical and computational advantages.

Science and technology are constantly transforming our day-to-day living. Science education has become of vital importance to prepare learners for this everchanging world. Unfortunately, science education in South Africa is hampered by under-qualified and inexperienced teachers. Textbooks of good quality can assist teachers and learners and facilitate the development of science teachers. For this reason thorough assessment of textbooks is needed to inform the selection of good textbooks. An investigation revealed that the available textbook evaluation instruments are not suitable for the evaluation of the physical science textbooks in the South African context. An instrument is needed that focusses on science education textbooks and which prescribes the criteria, weights, evaluation procedure and rating scheme that can ensure justifiable, transparent, reliable and valid evaluation results. This study utilised elements from the Analytic Hierarchy Process (AHP) to develop such an instrument and verified the reliability and validity of the instrument’s evaluation results. Development of the Instrument for the Evaluation of Science Education Textbooks started with the formulation of criteria. Characteristics that influence the quality of textbooks were identified from literature, existing evaluation instruments and stakeholders’ concerns. In accordance with the AHP, these characteristics or criteria were divided into categories or branches to give a hierarchical structure. Subject experts verified the content validity of the hierarchy. Expert science teachers compared the importance of different criteria. The data were used to derive weights for the different criteria with the Expert Choice computer application. A rubric was formulated to act as rating-scheme and score sheet. During the textbook evaluation process the ratings were transferred to a spreadsheet that computed the scores for the quality of a textbook as a whole as well as for the different categories. The instrument was tested on small scale, adjusted and then applied on a larger scale. The results of different analysts were compared to verify the reliability of the instrument. Triangulation with the opinions of teachers who have used the textbooks confirmed the validity of the evaluation results obtained with the instrument. Future investigations on the evaluation instrument can include the use of different rating scales and limiting of criteria. / Thesis (M. Ed. (Didactics))

Science and technology are constantly transforming our day-to-day living. Science education has become of vital importance to prepare learners for this everchanging world. Unfortunately, science education in South Africa is hampered by under-qualified and inexperienced teachers. Textbooks of good quality can assist teachers and learners and facilitate the development of science teachers. For this reason thorough assessment of textbooks is needed to inform the selection of good textbooks. An investigation revealed that the available textbook evaluation instruments are not suitable for the evaluation of the physical science textbooks in the South African context. An instrument is needed that focusses on science education textbooks and which prescribes the criteria, weights, evaluation procedure and rating scheme that can ensure justifiable, transparent, reliable and valid evaluation results. This study utilised elements from the Analytic Hierarchy Process (AHP) to develop such an instrument and verified the reliability and validity of the instrument’s evaluation results. Development of the Instrument for the Evaluation of Science Education Textbooks started with the formulation of criteria. Characteristics that influence the quality of textbooks were identified from literature, existing evaluation instruments and stakeholders’ concerns. In accordance with the AHP, these characteristics or criteria were divided into categories or branches to give a hierarchical structure. Subject experts verified the content validity of the hierarchy. Expert science teachers compared the importance of different criteria. The data were used to derive weights for the different criteria with the Expert Choice computer application. A rubric was formulated to act as rating-scheme and score sheet. During the textbook evaluation process the ratings were transferred to a spreadsheet that computed the scores for the quality of a textbook as a whole as well as for the different categories. The instrument was tested on small scale, adjusted and then applied on a larger scale. The results of different analysts were compared to verify the reliability of the instrument. Triangulation with the opinions of teachers who have used the textbooks confirmed the validity of the evaluation results obtained with the instrument. Future investigations on the evaluation instrument can include the use of different rating scales and limiting of criteria. / Thesis (M. Ed. (Didactics))

Submitted by STEFANO PETRINI DE OLIVEIRA null (stefanopetrini@hotmail.com) on 2016-05-06T00:57:17Z No. of bitstreams: 1 Dissertação - Stefano Petrini.pdf: 1880894 bytes, checksum: 90c6382ea8269445954a2790db221707 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-05-09T20:04:22Z (GMT) No. of bitstreams: 1 petrini_s_me_guara.pdf: 1880894 bytes, checksum: 90c6382ea8269445954a2790db221707 (MD5) / Made available in DSpace on 2016-05-09T20:04:22Z (GMT). No. of bitstreams: 1 petrini_s_me_guara.pdf: 1880894 bytes, checksum: 90c6382ea8269445954a2790db221707 (MD5) Previous issue date: 2016-03-15 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Recent research about the identification of factors that contribute to better sharing of knowledge and ways to evaluate this topic highlight the importance of knowledge management for the organization. Exploring opportunities in this scenario, the present study examines the share of the workers' knowledge in the automotive industry by factors related to the Production Organization, Work Organization and Knowledge Management, with attention to the influence of organizational and interpersonal context in the knowledge sharing process. This delimitation of the industrial sector in the light of the production area is justified by this area has dependence of the workers' tacit knowledge. The research uses a qualitative and quantitative approach in survey format and uses a questionnaire with managers (coordinators and supervisors) to assess the importance of leveraging factors of knowledge management in the view of the leadership body. It employed the Incomplete Pairwise Comparison method proposed by Harker (1986) based on the Analytic Hierarchy Process of Saaty (1977). The survey shows an integration between the factors and highlights the importance of systemic and technical conversation among the workers to improve their knowledge sharing, plus the role of communication, training and work instruction in the knowledge conversion processes. This research expands the theme of the conceptual limits knowledge management found in literature and contributes mainly in managerial direction for the qualification and learning new employees in the continuous process of recycling knowledge and mitigation of knowledge waste. Thus, it contributes to the promotion of an enabling environment for the creation and sharing of knowledge by the people of the workers' environment. / Pesquisas recentes relativas a identificação de fatores que contribuem para o melhor compartilhamento do conhecimento e formas de avaliação do tema evidenciam a importância da Gestão do Conhecimento para a organização. Explorando oportunidades neste cenário, a presente pesquisa analisa o compartilhamento do conhecimento operário na indústria automotiva por meio de fatores relativos à Organização da Produção, Organização do Trabalho e a Gestão do Conhecimento, com atenção a influência do contexto organizacional e interpessoal no processo de compartilhamento de conhecimento. Esta delimitação de setor industrial à luz da área de Produção justifica-se por esta área possuir dependência do conhecimento tácito operário. A pesquisa utiliza uma abordagem quali-quantitativa no formato survey e emprega um questionário com gestores (coordenadores e supervisores) para avaliar a importância dos fatores alavancadores da Gestão do Conhecimento na ótica do corpo de liderança. É empregada o método Incomplete Pairwise Comparison, proposta por Harker (1986) baseada no Analytic Hierarchy Process de Saaty (1977). A pesquisa evidencia uma integração entre os fatores e destaca a importância da conversa sistêmica e técnica entre os operários para o melhor compartilhamento de seu conhecimento, além do papel da comunicação, do treinamento e da instrução de trabalho nos processos de conversão do conhecimento. Esta pesquisa expande os limites conceituais do tema Gestão do Conhecimento verificado na pesquisa bibliográfica e contribui, principalmente, no direcionamento gerencial para a qualificação e aprendizado de novos funcionários, no processo contínuo de reciclagem de conhecimento e mitigação do desperdício do conhecimento. Logo, ela contribui à promoção de um contexto favorável à criação e ao compartilhamento do conhecimento pelas pessoas do ambiente operário.

Följande arbete utgör en fallstudie där en hybridanalys bestående av de två analysverktygen SWOT och AHP tillämpats. Syftet med arbetet har varit att identifiera vad den studerade verksamheten bör prioritera för att bli mer effektiv. Med hjälp av SWOT-modellen har styrkor, svagheter, möjligheter och hot kunnat identifieras. SWOT visar dock inte relevansen av de olika faktorerna och därför har modellen kompletterats med hjälp av AHP. Vid tillämpningen av AHP har en numerisk metod införts, vilket gör det möjligt att kvantifiera faktorerna inom SWOT och således kan de relativa viktfaktorerna härledas. Detta skapar ett tillförlitligare underlag för de strategiska beslut som verksamheten bör vidta, jämfört med om SWOT-analysen utförs självständigt. Studien har med signifikans identifierat att byråkratin ligger bakom en del av ineffektiviteten, vilket medför utdragna inköpsprocesser och planeringsprocesser. Studien utvärderar två olika skalor som en del av den numeriska metoden, en linjär och en kvadratisk. Den kvadratiska kräver normalt mer tid, men medför också högre tillförlitlighet. Däremot kan den medföra nackdelar om man inkluderar allokerandet av resurser, såsom tid, pengar eller personal som en tredje dimension inom AHP. Slutligen föreslår denna studie ett upplägg av hybridmodellen där man utnyttjar signifikansmåttet för att undersöka samstämigheten mellan exempelvis två individer kring vad som bör prioriteras. / This thesis presents a case study where a hybrid analysis containing the two frameworks SWOT and AHP has been made. The purpose has been to identify what the studied support business should prioritize in order to be more efficient. Using SWOT, one has been able to identify strengths, weaknesses, opportunities and threats for the function. However, SWOT fails to show their relevance and therefor it has been supplemented with an AHP analysis. When applying AHP, a numerical method has been introduced that makes it possible to quantify the factors. Thus, the relative weight of the factors can be derived. This will create a more reliable basis for the strategic decisions that the support business should implement. The study shows, with significance that the biggest issue of the support function lies in bureaucracy, causing the purchase and planning processes to be inefficient. The study also evaluates two different scales as a part of the numerical method, one linear and one quadratic. The quadratic usually requires more time but provides a more reliable result. However, it can bring some disadvantages if one includes allocations of resources, such as time, money or labor as a third dimension within AHP. Finally, the thesis proposes a way of using the hybrid model and the significance measurement to find out how two people agrees regarding what should be prioritized.

Soil microbial communities are affected extensively by addition of amendments to their environment. Of particular concern is the addition of poultry litter, which contains a substantial C, energy, and nutrient supply, but also antibiotic resistance genes (ARG), antimicrobials, and a multitude of microbial species. This project seeks to primarily assess if there is a change in bacterial community structure in response to poultry litter amendments to pasture land across geographically independent land across northern Georgia. It may be that changes in the relative abundance of bacterial communities also result in alteration in ARGs, and the community resistance to antibiotics (“resistome”) which in turn increases the potential threat of antibiotic resistance genes. While another part of this study will determine changes in integrons and specific ARGs, this project will focus on changes in bacterial communities and the potential functional changes in the community, which in turn have consequences for ARG levels and its horizontal transfer to various members of the soil community. Addition of waste from livestock is a historical method for increasing nutrients needed in the soil for the cultivation of crops, and in turn causes pronounced shifts in soil microbial communities due to the addition of large amounts of carbon, nutrients, foreign microbes, and other material. This study is unique because it utilizes a novel and relatively large landscape-scale to determine if there are discernable and repeatable patterns of bacterial community structure change in response to amendment regardless of exact soil type or source of chicken litter amendment. In the future, these data can also provide insight into the changes in the relative abundance antibiotic related genes associated with community change. / M.S. / Soil is complicated, both in terms of its physical makeup and the organisms that live inside of it. Predicting changes in soil based on the addition of foreign material such as chemicals or biological waste is not an easy process, and whether or not it is even possible to reliably predict those changes is a matter of some dispute. This study is designed to illustrate that such changes can in fact be reliably and consistently predicted even with regard to the addition of complicated materials to the soil. In this study, specifically, the material in question is chicken litter. A mix of the bedding and waste produced by chickens, litter is commonly handled by composting and is added to soil in farms as a fertilizer rich in organic matter. It is possible to point at specific elements of the soil such as the chemistry and bacteria and see how it is changed with the addition of chicken litter, which allows us to determine the nature and extent of the change that chicken litter has on soil. This study is conducted on a larger scale than similar experiments conducted in the past, making it apparent that these relationships exist on a repeated basis. It is the object of this study to pave the way and make it easier for scientists in the future to determine these relationships in other unique contexts.