One of the most important factors that influences a stream's hydraulic and ecological health is the streambed's sediment size distribution. This distribution affects streambed stability, sediment transport rates, and flood levels by defining the roughness of the stream channel. Adverse effects on water quality and wildlife can be expected when excessive fine sediments enter a stream. Many chemicals and toxic materials are transported through streams by binding to fine sediments. Increases in fine sediments also seriously impact the survival of fish species present in the stream. Fine sediments fill tiny spaces between larger particles thereby denying fish embryos the necessary fresh water to survive. Reforestation, constructed wetlands, and slope stabilization are a few management practices typically utilized to reduce the amount of sediment entering a stream. To effectively gauge the success of these techniques, the sediment size distribution of the stream must be monitored. Gravel bed streams are typically stratified vertically, in terms of particle size, in three layers, with each layer having its own distinct grain size distribution. The top two layers of the stream bed, the pavement and subpavement, are the most significant in determining the characteristics of the stream. These top two layers are only as thick as the largest particle size contained within each layer. This vertical stratification by particle size makes it difficult to characterize the grain size distribution of the surface layer. The traditional bulk or volume sampling procedure removes a specified volume of material from the stream bed. However, if the bed exhibits vertical stratification, the volume sample will mix different populations, resulting in inaccurate sample results. To obtain accurate results for the pavement size distribution, a surface oriented sampling technique must be employed. The most common types of surface oriented sampling are grid and areal sampling. Due to limitations in the sampling techniques, grid samples typically truncate the sample at the finer grain sizes, while areal samples typically truncate the sample at the coarser grain sizes. When combined with an analysis technique, either frequency-by-number or frequency-by-weight, the sample results can be represented in terms of a cumulative grain size distribution. However, the results of different sampling and analysis procedures can lead to biased results, which are not equivalent to traditional volume sampling results. Different conversions, dependent on both the sampling and analysis technique, are employed to remove the bias from surface sample results. The topic of the present study is to determine the accuracy of sediment samples obtained by the different sampling techniques. Knowing the accuracy of a sample is imperative if the sample results are to be meaningful. Different methods are discussed for placing confidence intervals on grid sample results based on statistical distributions. The binomial distribution and its approximation with the normal distribution have been suggested for these confidence intervals in previous studies. In this study, the use of the multinomial distribution for these confidence intervals is also explored. The multinomial distribution seems to best represent the grid sampling process. Based on analyses of the different distributions, recommendations are made. Additionally, figures are given to estimate the grid sample size necessary to achieve a required accuracy for each distribution. This type of sample size determination figure is extremely useful when preparing for grid sampling in the field. Accuracy and sample size determination for areal and volume samples present difficulties not encountered with grid sampling. The variability in number of particles contained in the sample coupled with the wide range of particle sizes present make direct statistical analysis impossible. Limited studies have been reported on the necessary volume to sample for gravel deposits. The majority of these studies make recommendations based on empirical results that may not be applicable to different size distributions. Even fewer studies have been published that address the issue of areal sample size. However, using grid sample results as a basis, a technique is presented to estimate the necessary sizes for areal and volume samples. These areal and volume sample sizes are designed to match the accuracy of the original grid sample for a specified grain size percentile of interest. Obtaining grid and areal results with the same accuracy can be useful when considering hybrid samples. A hybrid sample represents a combination of grid and areal sample results that give a final grain size distribution curve that is not truncated. Laboratory experiments were performed on synthetic stream beds to test these theories. The synthetic stream beds were created using both glass beads and natural sediments. Reducing sampling errors and obtaining accurate samples in the field are also briefly discussed. Additionally, recommendations are also made for using the most efficient sampling technique to achieve the required accuracy. / Master of Science

個體選擇模式(discrete choice model)廣泛應用於國外的交通運輸及行銷領域，而國內交通運輸領域，也長期以此模式分析個體的運具選擇行為。反觀國內的行銷領域，因較難取得消費者的商品品牌購買紀錄，而鮮少應用個體選擇模式分析消費者的選擇行為。有鑒於此，本研究嘗試以問卷收集消費者對三個洗髮精品牌的選擇行為，以個體選擇模式中的多項邏輯模式(multinomial logit model)、巢狀邏輯模式(nested multinomial logit model)、混合多項邏輯模式(mixed logit model)進行分析，檢驗問卷設計中的促銷活動、消費者特性對選擇行為的影響性。 實證分析的結果發現，洗髮精的原價格及促銷折扣、贈品容量、加量不加價等促銷活動，皆對消費者的選擇行為有顯著的影響力，其中促銷折扣與贈品容量影響的程度較大，是較具有效果的促銷活動。而消費者的性別、年齡、職業及品牌更換的頻率，皆影響洗髮精的選擇行為。此外，消費者若固定選擇自己最常購買的洗髮精，此類型的消費者與其他人的品牌選擇行為，也有顯著的不同。 此外，根據本研究樣本，我們也發現海倫仙度絲與潘婷間的替代、互補性較強。 / Discrete choice model has been demonstrated to be a useful tool for analyzing consumers’ choice behavior data in the area of transportation and marketing research. However, since a complete data set containing consumers’ history of purchase behavior was rarely available to public, the model was less popular in the marketing research area than in the transportation research in Taiwan. Based on limited survey data on consumers’ choice among three different brands of shampoo, we applied multinomial logit model、nested multinomial logit model、mixed logit model in this study to understand promotion program’s effect on consumers’ choice behavior , the result showed that shampoos’ original price、discount、volume of hair conditioner bestowal、more volume with the same price all had significant impacts on consumers’ choice behavior, among them, discount and volume of hair conditioner bestowel influenced more .In addition, consumers’ gender、age、occupation and frequency of changing brands also affected consumers on choosing brands of shampoos. The study also found that a consumer who chose the same brand regularly behaved notably differently.

<p>Commercial and regional brewers are increasingly investing in sustainability equipment that reduces input use, operating costs, and environmental impact. These technologies often require significant upfront costs that can limit market access to microbreweries. One potential solution for these brewers is to market their product as sustainable and charge a premium for their product to offset some of the costs. A stated preference choice experiment of a nationally-representative sample is undertaken to elicit consumer willingness-to-pay (WTP) for sustainability attributes in beer, thus determining whether a market for sustainably-made beer exists. The facets of sustainability, including water reduction, energy reduction, and landfill diversion, are portrayed through eco-labels affixed the front of the primary packaging (aluminum can or glass bottle). Multiple specifications are employed to handle model shortcomings and incorporate discrete heterogeneity. Across all model specifications, <a>consumers show a positive and statistically significant marginal WTP for landfill diversion practices and carbon reduction practices, ranging from $0.40 to $1.37 per six-pack and $0.67 to $1.21 per six-pack, respectively. </a>These results indicate consumers do in fact place value on beer produced using sustainable practices, and the demographics of consumers with the greatest WTP are similar to that of craft beer consumer.</p>

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Made available in DSpace on 2016-03-15T19:30:40Z (GMT). No. of bitstreams: 1 Joao Francisco Morozini.pdf: 739724 bytes, checksum: ef453f4c172739b8e64d4eb3d89a31f9 (MD5) Previous issue date: 2010-11-08 / Fundo Mackenzie de Pesquisa / From the perspective of the firm, divestitures are alternative ways to contract limits, as well as acquisitions, alliances, joint ventures and organic growth are ways to expand them. Although researchers have given considerable attention to the economic motivations that lead to acquisitions, which really takes into account when making decision on the purchase or not (Timing of acquisitions,) is still relatively little studied. Several investigations have dealt with national and international M & A from the perspective of performance analysis and value creation and growth of the firm. Research focuses on issues related to the organic growth strategy, highlighting those reflected in the experiences of Siemens, UPS, The Home Depot, and SYSCO. From this, the objective of this thesis is to highlight the factors that influence the choice of form of investment in the growth of Brazilian industry, namely investment in organic growth or inorganic growth. To answer the research problem proposed in this thesis was used as a research method: the aims, the developed method was descriptive and explanatory, the procedures, the research was documentary, and how to address the problem, was quantitative. The research problem to be answered in this thesis is: There are factors considered crucial to choose between investment in organic growth and inorganic growth in investment as an alternative to business expansion? The survey consists of 93 publicly traded Brazilian companies, analyzed in the period 1995 to 2008, with secondary data obtained from Economática. To test the eight hypotheses of this study used two econometric models of regression: The first panel Binomial Data with static and unbalanced, with cutting data transverse with fixed effect models, random and Pooled. The second was the Multinomial Logit. The tests from this model revealed that the statistically significant exogenous variables that were presented in the order: Fol_Fin (financial slack) and Log_Ven (logarithm of sales) at the 5% significance and positive sign of the coefficient Binomial Panel Data; Log_Ven (logarithm of sales), Fol_Fin (financial slack), with positive sign of the coefficient and the 5% level of significance and Gr_Rent (level of profitability) with negative sign of the coefficient at the 5% significance level. These results in general contribute to elucidate the question as originally proposed, providing empirical evidence of the relationship of some factors that may be decisive for the choice of form of investment in organic growth or inorganic. Therefore, we conclude that there really are factors that determine what decision or direction on how to invest in growth in Brazilian industry. / Da perspectiva da firma, desinvestimentos são maneiras alternativas para contrair limites,assim como aquisições, alianças, joint ventures e crescimento orgânico são maneiras para expandi-las. Embora pesquisadores tenham dado considerável atenção para as motivações econômicas que levam às aquisições, o que realmente se leva em conta no momento da decisão sobre fazer ou não a aquisição (Timing of acquisitions,) ainda é relativamente pouco estudado. Várias pesquisas nacionais e internacionais têm tratado de Fusões e Aquisições sob a perspectiva de análise de desempenho e criação de valor e do crescimento da firma. Pesquisas concentram-se em questões relacionadas com a estratégia para o crescimento orgânico, ressaltando aquelas refletidas nas experiências da Siemens, UPS, The Home Depot, e SYSCO. A partir disso, o objetivo desta tese é evidenciar os fatores que influenciam na escolha da forma de investimento no crescimento das indústrias brasileiras,ou seja, investimento em crescimento orgânico ou em crescimento inorgânico. Para responder o problema de pesquisa proposto nesta tese utilizou-se como método de pesquisa:quanto aos objetivos, o método desenvolvido foi o descritivo e o explicativo; quanto aos procedimentos, a pesquisa foi documental; e quanto à abordagem do problema, foi quantitativa. O problema de pesquisa a ser respondido nesta tese é: Existem fatores considerados determinantes para escolher entre investimento em crescimento orgânico e investimento em crescimento inorgânico como alternativa de expansão das empresas? A população da pesquisa é composta 93 indústrias brasileiras de capital aberto, analisadas no período de 1995 a 2008, com dados secundários, obtidos no Economática. Para testar as oito hipóteses deste estudo utilizaram-se dois modelos econométricos de regressão: O primeiro com Painel Binomial de Dados estático e não balanceado, com dados de corte transversal,com os modelos de efeito fixo, aleatório e Pooled. O segundo foi o Logit Multinomial. Os testes a partir deste modelo revelaram que estatisticamente as variáveis exógenas que apresentaram significância foram pela ordem: Fol_Fin (folga financeira) e Log_Ven (logarítimo das vendas) ao nível de 5% de significância, e sinal do coeficiente positivo no Painel Binomial de Dados; Log_Ven (logarítimo das vendas), Fol_Fin (folga financeira), com sinal do coeficiente positivo e ao nível de 5% de significância e Gr_Rent (grau de rentabilidade) com sinal do coeficiente negativo ao nível de 5% de significância. Os resultados desta pesquisa em termos gerais contribuem para elucidar a questão proposta inicialmente, oferecendo evidências empíricas da relação de alguns fatores que podem ser determinantes para a escolha da forma de investimento em crescimento orgânico ou inorgânico. Portanto, conclui-se que realmente existem fatores que determinam ou direcionam qual decisão sobre a forma de investimento em crescimento nas indústrias brasileiras.

L‟objectif de toute analyse économique sur l‟offre de travail, est en général, de mieux cerner les problématiques liées à l‟emploi permettant de décliner des politiques en direction du marché du travail. Cette thèse n‟échappe pas à cet objectif bien qu‟elle soit orientée vers les femmes. A partir des analyses développées dans cette thèse, nous avons apporté un nouvel éclairage sur les facteurs déterminants qui poussent ou empêchent la femme sénégalaise à intégrer le marché du travail. Les approches théoriques développées, nous ont conduit à considérer la nature des relations conjugales, les différentes perceptions du travail et des obligations familiales correspondants à différents types de comportements féminins d‟offre de travail. Le comportement d‟offre de travail de la femme sénégalaise est ainsi influencé par des caractéristiques individuelles telles que l‟âge, le niveau d‟éducation, et des caractéristiques familiales courantes telles que la présence d‟enfant(s) de moins de 5ans dans le ménage, la présence d‟un conjoint (statut matrimonial), le revenu du conjoint, la taille du ménage, le statut monétaire matérialisé par la pauvreté, le versement de transferts à des descendants ou ascendants.Par le biais de la modélisation logistique dichotomique et multinomiale, nous avons montré que le niveau d‟éducation est positivement corrélé à la participation des femmes sur le marché du travail et constitue de surcroît, un ticket d‟entrée dans le secteur public. Contrairement au statut matrimonial (être mariée), la présence d‟enfants de moins de 5 ans et le revenu du conjoint ne semblent pas être un obstacle à l‟intégration des femmes sur le marché du travail, mais cette présence d‟enfant semble orienter les sénégalaises vers le secteur informel au détriment des autres secteurs (public et privé formel). Ce qui est souvent motivé par les conditions de travail plus flexibles dans ce secteur permettant aux femmes de concilier activités économiques et obligations familiales. Par ailleurs, les femmes appartenant aux ménages pauvres semblent être plus disposer à offrir du travail que celles appartenant aux ménages non pauvres, mais elles ont moins de chances d‟être dans le secteur public, le secteur privé formel et dans une moindre mesure dans les ambassades et ONG que dans l‟informel par rapport à celles qui ne sont pas pauvres. / The objective of any economic analysis of the elabor supply is generally to better understand issues related to employment allowing formulating policies towards the labor market. This thesis is not an exception to this objective although it focuses exclusively on women. From the analysis of the present thesis, we have shed new light on the main factors driving or inhibiting the senegalese woman to enter the labor market. The theoretical approaches developed have led us to consider the nature of marital relationships, the different perceptions of work and family obligations corresponding to different types of female behavior of labor supply. Through a dicotomous and multinomial logit model, we have shown that the behavior of labor supply of senegalese women is influenced by individual characteristics such as the age and education level, and standard family characteristics such as the presence of under 5 years old child/children in the household, the presence of a spouce (marital status), the income of the spouse, the householf size, the monetary status indicated by the poverty, the remittances to descendants or ascendants.

Automatiserad dokumentklassificering är en process eller metod som syftar till att bearbeta ochhantera dokument i digitala former. Många företag strävar efter en textklassificeringsmetodiksom kan lösa olika problem. Ett av dessa problem är att klassificera och organisera ett stort antaldokument baserat på en uppsättning av fördefinierade kategorier.Detta examensarbete syftar till att hjälpa Medius, vilket är ett företag som arbetar med fakturaarbetsflöde, att klassificera dokumenten som behandlas i deras fakturaarbetsflöde till fakturoroch icke-fakturor. Detta har åstadkommits genom att implementera och utvärdera olika klassificeringsmetoder för maskininlärning med avseende på deras noggrannhet och effektivitet för attklassificera finansiella dokument, där endast fakturor är av intresse.I denna avhandling har två dokumentrepresentationsmetoder "Term Frequency Inverse DocumentFrequency (TF-IDF) och Doc2Vec" använts för att representera dokumenten som vektorer. Representationen syftar till att minska komplexiteten i dokumenten och göra de lättare att hantera.Dessutom har tre klassificeringsmetoder använts för att automatisera dokumentklassificeringsprocessen för fakturor. Dessa metoder var Logistic Regression, Multinomial Naïve Bayes och SupportVector Machine.Resultaten från denna avhandling visade att alla klassificeringsmetoder som använde TF-IDF, föratt representera dokumenten som vektorer, gav goda resultat i from av prestanda och noggranhet.Noggrannheten för alla tre klassificeringsmetoderna var över 90%, vilket var kravet för att dennastudie skulle anses vara lyckad. Dessutom verkade Logistic Regression att ha det lättare att klassificera dokumenten jämfört med andra metoder. Ett test på riktiga data "dokument" som flödarin i Medius fakturaarbetsflöde visade att Logistic Regression lyckades att korrekt klassificeranästan 96% av dokumenten.Avslutningsvis, fastställdes Logistic Regression tillsammans med TF-IDF som de övergripandeoch mest lämpliga metoderna att klara av problmet om dokumentklassficering. Dessvärre, kundeDoc2Vec inte ge ett bra resultat p.g.a. datamängden inte var anpassad och tillräcklig för attmetoden skulle fungera bra. / Automated document classification is an essential technique that aims to process and managedocuments in digital forms. Many companies strive for a text classification methodology thatcan solve a plethora of problems. One of these problems is classifying and organizing a massiveamount of documents based on a set of predefined categories.This thesis aims to help Medius, a company that works with invoice workflow, to classify theirdocuments into invoices and non-invoices. This has been accomplished by implementing andevaluating various machine learning classification methods in terms of their accuracy and efficiencyfor the task of financial document classification, where only invoices are of interest. Furthermore,the necessary pre-processing steps for achieving good performance are considered when evaluatingthe mentioned classification methods.In this study, two document representation methods "Term Frequency Inverse Document Frequency (TF-IDF) and Doc2Vec" were used to represent the documents as fixed-length vectors.The representation aims to reduce the complexity of the documents and make them easier tohandle. In addition, three classification methods have been used to automate the document classification process for invoices. These methods were Logistic Regression, Multinomial Naïve Bayesand Support Vector Machine.The results from this thesis indicate that all classification methods used TF-IDF, to represent thedocuments as vectors, give high performance and accuracy. The accuracy of all three classificationmethods is over 90%, which is the prerequisite for the success of this study. Moreover, LogisticRegression appears to cope with this task very easily, since it classifies the documents moreefficiently compared to the other methods. A test of real data flowing into Medius’ invoiceworkflow shows that Logistic Regression is able to correctly classify up to 96% of the data.In conclusion, the Logistic Regression together with TF-IDF is determined to be the overall mostappropriate method out of the other tested methods. In addition, Doc2Vec suffers to providea good result because the data set is not customized and sufficient for the method to workwell.

國人自殺死亡自1997年起已經連續10年進入國人十大死因之列，且其排名及自殺率有逐年上升的趨勢。國防部相當重視自殺防治工作1977年起國軍即設置有「趙老師」負責心理諮商與輔導工作，1994年更推廣設立心輔官制度，其主要目的就是要在部隊中從事心理衛生的防治工作，以避免自殺事件的發生。但從1997至2008年統計數據分析，軍中自我傷害死亡自1997年起逐年上升，至2002年達最高峰，2003年後雖有降低，但各年度因自我傷害死亡仍在20人以上。從數據來看，軍中自我傷害事件並未因國防部大力推動自我傷害防治工作下降。因此，本文的目的在於找出影響官兵自我傷害的原因，提供國防部在自我傷害防治策略上有更為周全的決策考量，以降低國軍官兵自我傷害事件的發生。 / Suicide has been one of the top ten reasons behind the deaths of our countrymen since 1997. In addition, its ranking and suicide rate are both climbing over the years. The Ministry of Defense puts a lot of efforts into suicide prevention. Since 1977, the military has set up ‘Teacher Zhao’ to be in charge of psychological consultations and counseling work. In addition, ‘counseling officers’ system has been set up and its main purpose is to do prevention work about mental health in the military in order to prevent the occurrence of suicides. However, analyzing the statistics from 1997 to 2008, deaths due to self-mutilations in the military are increasing since 1997 and peaked in 2002. Although the number decreases since 2003 but there are still over 20 deaths due to self-mutilations every year. Looking at the statistics, self-mutilations in the military did not decrease even though the Military of Defense pushes for prevention of self-mutilations. Therefore, the purpose of this paper is to find out the reasons affecting self-mutilations, provide the Ministry of Defense a well-rounded decision making mechanism on how to prevent self-mutilations in order to decrease the occurrence of self-mutilations in the military.

Long-distance and intercity travel generally make up a small portion of the total number of trips taken by an individual, while representing a large portion of aggregate distance traveled on the transportation system. While some research exists on intercity travel behavior between large metropolitan centers, this thesis addresses a need for more research on travel behavior between non-metropolitan areas and large metropolitan centers. This research specifically considers travel from home locations in northern New England, going to Boston, New York City, Philadelphia, and Washington, DC. These trips are important for quality of life, multimodal planning, and rural economies. This research identifies and quantifies factors that influence people's mode choice (automobile, intercity bus, passenger rail, or commercial air travel) for these trips. The research uses survey questionnaire data, latent factor analysis, and discrete choice modeling methods. Factors include sociodemographic, built environment, latent attitudes, and trip characteristics. The survey, designed by the University of Vermont Transportation Research Center and the New England Transportation Institute, was conducted by Resource Systems Group, Inc. in 2014, with an initial sample size of 2560. Factor analysis was used to prepare 6 latent attitudinal factors, based on 70 attitudinal responses from the survey statements. The survey data were augmented with built environment variables using geographic information systems (GIS) analysis. A set of multinomial logit models, and a set of nested logit models, were estimated for business and non-business trip mode choice. Results indicate that for this type of travel, factors influencing mode choice for both business and non-business trips include trip distance; land use; personal use of technology; and latent attitudes about auto dependence, preference for automobile, and comfort with personal space and safety on public transportation. Gender is a less significant factor. Age is only significant for non-business trips. The results reinforce the importance and viability of modeling long-distance travel from less populated regions to large metropolitan areas, and the significant roles of trip distance, built environment, personal attitudes, and sociodemographic factors in how people choose to make these trips for different purposes. Future research should continue to improve these types of long-distance mode choice models by incorporating mode specific travel time and cost, developing more specific attitudinal statements to expand latent factor analysis, and further exploring built environment variables. Improving these models will promote better planning, engineering, operations, and infrastructure investment decisions in many regions and communities across the United States which have not yet been well studied, possibly impacting levels of service.

<div>Prediction of player performance is a key component in the construction of baseball team rosters. Traditionally, the problem of predicting seasonal plate appearance outcomes has been approached univariately. That is, focusing on each outcome separately rather than jointly modeling the collection of outcomes. More recently, there has been a greater emphasis on joint modeling, thereby accounting for the correlations between outcomes. However, most of these state of the art prediction models are the proprietary property of teams or industrial sports entities and so little is available in open publications.</div><div><br></div><div>This dissertation introduces a joint modeling approach to predict seasonal plate appearance outcome vectors using a mixed-effects multinomial logistic-normal model. This model accounts for positive and negative correlations between outcomes both across and within player seasons. It is also applied to the important, yet unaddressed, problem of predicting performance for players moving between the Japanese and American major leagues.</div><div><br></div>This work begins by motivating the methodological choices through a comparison of state of the art procedures followed by a detailed description of the modeling and estimation approach that includes model t assessments. We then apply the method to longitudinal multinomial count data of baseball player-seasons for players moving between the Japanese and American major leagues and discuss the results. Extensions of this modeling framework to other similar data structures are also discussed.<br>