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1
Liu, Xi. "Some new developments for quantile regression." Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/16204.
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Quantile regression (QR) (Koenker and Bassett, 1978), as a comprehensive extension to standard mean regression, has been steadily promoted from both theoretical and applied aspects. Bayesian quantile regression (BQR), which deals with unknown parameter estimation and model uncertainty, is a newly proposed tool of QR. This thesis aims to make some novel contributions to the following three issues related to QR. First, whereas QR for continuous responses has received much attention in literatures, QR for discrete responses has received far less attention. Second, conventional QR methods often show that QR curves crossing lead to invalid distributions for the response. In particular, given a set of covariates, it may turn out, for example, that the predicted 95th percentile of the response is smaller than the 90th percentile for some values of the covariates. Third, mean-based clustering methods are widely developed, but need improvements to deal with clustering extreme-type, heavy tailed-type or outliers problems. This thesis focuses on methods developed over these three challenges: modelling quantile regression with discrete responses, ensuring non-crossing quantile curves for any given sample and modelling tails for collinear data with outliers. The main contributions are listed as below: * The first challenge is studied in Chapter 2, in which a general method for Bayesian inference of regression models beyond the mean with discrete responses is developed. In particular, this method is developed for both Bayesian quantile regression and Bayesian expectile regression. This method provides a direct Bayesian approach to these regression models with a simple and intuitive interpretation of the regression results. The posterior distribution under this approach is shown to not only be coherent to the response variable, irrespective of its true distribution, but also proper in relation to improper priors for unknown model parameters. * Chapter 3 investigates a new kernel-weighted likelihood smoothing quantile regression method. The likelihood is based on a normal scale-mixture representation of an asymmetric Laplace distribution (ALD). This approach benefits of the same good design adaptation just as the local quantile regression (Spokoiny et al., 2014) does and ensures non-crossing quantile curves for any given sample. * In Chapter 4, we introduce an asymmetric Laplace distribution to model the response variable using profile regression, a Bayesian non-parametric model for clustering responses and covariates simultaneously. This development allows us to model more accurately for clusters which are asymmetric and predict more accurately for extreme values of the response variable and/or outliers. In addition to the three major aforementioned challenges, this thesis also addresses other important issues such as smoothing extreme quantile curves and avoiding insensitive to heteroscedastic errors as well as outliers in the response variable. The performances of all the three developments are evaluated via both simulation studies and real data analysis.
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Zhu, Meidong. "Development and regression of the human hyaloid system." Thesis, Sydney Medical School, 1998. http://hdl.handle.net/2123/14472.
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Woolmore, Ashley. "Regression periods in infancy and maternal post-natal depression." Thesis, Open University, 1998. http://oro.open.ac.uk/54154/.
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van de Rijt-Plooij & Plooij (1992) have found periods of 'regressive behaviour' (Regression Periods), which accompany developmental transitions in infancy. In fullterm normal infants these periods occur at specific ages. The present study had two central aims. Firstly, to see if the Plooijs' finding of Regression Periods at 12, 17 and 26 weeks postpartum could be replicated. Secondly, to investigate the relationship between the length of Regression Periods for a control group of participants and a group of participants at heightened risk of developing insecure mother-infant attachment: mothers presenting with symptoms of post-natal depression. Forty-five mother-infant dyads participated in this prospective, longitudinal study. After seeing mothers at home, they were interviewed weekly, for approximately 15 weeks, about specific infant behaviours and their reactions to their infant. Following two types of manipulation of the data, Regression Periods for control group participants were detected at weeks 12, 16,20 and 24, whereas for participants in the post-natal depression group, Regression Periods were detected at weeks 14, 17 and 25, supporting the Plooijs' findings. Regression Periods were longer in the post-natal depression group. Depressed mothers were also less flexible in their mothering style, measured on the Facilitators & Regulators questionnaire. Based on the findings of this study, the development of insecure attachment is discussed. A clinical implication of this work is that information about Regression Periods could be made available to new-mothers, using Regression Period knowledge to focus on the prevention of insecure attachment.
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Fréchette, Luc A. "Development of urban traffic models using a Bayesian regression approach." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq22112.pdf.
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Ranganai, Edmore. "Aspects of model development using regression quantiles and elemental regressions." Thesis, Stellenbosch : Stellenbosch University, 2007. http://hdl.handle.net/10019.1/18668.
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Dissertation (PhD)--University of Stellenbosch, 2007.<br>ENGLISH ABSTRACT: It is well known that ordinary least squares (OLS) procedures are sensitive to deviations from
the classical Gaussian assumptions (outliers) as well as data aberrations in the design space.
The two major data aberrations in the design space are collinearity and high leverage.
Leverage points can also induce or hide collinearity in the design space. Such leverage points
are referred to as collinearity influential points. As a consequence, over the years, many
diagnostic tools to detect these anomalies as well as alternative procedures to counter them
were developed. To counter deviations from the classical Gaussian assumptions many robust
procedures have been proposed. One such class of procedures is the Koenker and Bassett
(1978) Regressions Quantiles (RQs), which are natural extensions of order statistics, to the
linear model. RQs can be found as solutions to linear programming problems (LPs). The basic
optimal solutions to these LPs (which are RQs) correspond to elemental subset (ES)
regressions, which consist of subsets of minimum size to estimate the necessary parameters of
the model.
On the one hand, some ESs correspond to RQs. On the other hand, in the literature it is shown
that many OLS statistics (estimators) are related to ES regression statistics (estimators).
Therefore there is an inherent relationship amongst the three sets of procedures. The
relationship between the ES procedure and the RQ one, has been noted almost “casually” in
the literature while the latter has been fairly widely explored. Using these existing
relationships between the ES procedure and the OLS one as well as new ones, collinearity,
leverage and outlier problems in the RQ scenario were investigated. Also, a lasso procedure
was proposed as variable selection technique in the RQ scenario and some tentative results
were given for it. These results are promising.
Single case diagnostics were considered as well as their relationships to multiple case ones. In
particular, multiple cases of the minimum size to estimate the necessary parameters of the
model, were considered, corresponding to a RQ (ES). In this way regression diagnostics were
developed for both ESs and RQs. The main problems that affect RQs adversely are
collinearity and leverage due to the nature of the computational procedures and the fact that
RQs’ influence functions are unbounded in the design space but bounded in the response
variable. As a consequence of this, RQs have a high affinity for leverage points and a high
exclusion rate of outliers. The influential picture exhibited in the presence of both leverage points and outliers is the net result of these two antagonistic forces. Although RQs are
bounded in the response variable (and therefore fairly robust to outliers), outlier diagnostics
were also considered in order to have a more holistic picture.
The investigations used comprised analytic means as well as simulation. Furthermore,
applications were made to artificial computer generated data sets as well as standard data sets
from the literature. These revealed that the ES based statistics can be used to address
problems arising in the RQ scenario to some degree of success. However, due to the
interdependence between the different aspects, viz. the one between leverage and collinearity
and the one between leverage and outliers, “solutions” are often dependent on the particular
situation. In spite of this complexity, the research did produce some fairly general guidelines
that can be fruitfully used in practice.<br>AFRIKAANSE OPSOMMING: Dit is bekend dat die gewone kleinste kwadraat (KK) prosedures sensitief is vir afwykings
vanaf die klassieke Gaussiese aannames (uitskieters) asook vir data afwykings in die
ontwerpruimte. Twee tipes afwykings van belang in laasgenoemde geval, is kollinearitiet en
punte met hoë hefboom waarde. Laasgenoemde punte kan ook kollineariteit induseer of
versteek in die ontwerp. Na sodanige punte word verwys as kollinêre hefboom punte. Oor die
jare is baie diagnostiese hulpmiddels ontwikkel om hierdie afwykings te identifiseer en om
alternatiewe prosedures daarteen te ontwikkel. Om afwykings vanaf die Gaussiese aanname
teen te werk, is heelwat robuuste prosedures ontwikkel. Een sodanige klas van prosedures is
die Koenker en Bassett (1978) Regressie Kwantiele (RKe), wat natuurlike uitbreidings is van
rangorde statistieke na die lineêre model. RKe kan bepaal word as oplossings van lineêre
programmeringsprobleme (LPs). Die basiese optimale oplossings van hierdie LPs (wat RKe
is) kom ooreen met die elementale deelversameling (ED) regressies, wat bestaan uit
deelversamelings van minimum grootte waarmee die parameters van die model beraam kan
word.
Enersyds geld dat sekere EDs ooreenkom met RKe. Andersyds, uit die literatuur is dit bekend
dat baie KK statistieke (beramers) verwant is aan ED regressie statistieke (beramers). Dit
impliseer dat daar dus ‘n inherente verwantskap is tussen die drie klasse van prosedures. Die
verwantskap tussen die ED en die ooreenkomstige RK prosedures is redelik “terloops” van
melding gemaak in die literatuur, terwyl laasgenoemde prosedures redelik breedvoerig
ondersoek is. Deur gebruik te maak van bestaande verwantskappe tussen ED en KK
prosedures, sowel as nuwes wat ontwikkel is, is kollineariteit, punte met hoë hefboom
waardes en uitskieter probleme in die RK omgewing ondersoek. Voorts is ‘n lasso prosedure
as veranderlike seleksie tegniek voorgestel in die RK situasie en is enkele tentatiewe resultate
daarvoor gegee. Hierdie resultate blyk belowend te wees, veral ook vir verdere navorsing.
Enkel geval diagnostiese tegnieke is beskou sowel as hul verwantskap met meervoudige geval
tegnieke. In die besonder is veral meervoudige gevalle beskou wat van minimum grootte is
om die parameters van die model te kan beraam, en wat ooreenkom met ‘n RK (ED). Met
sodanige benadering is regressie diagnostiese tegnieke ontwikkel vir beide EDs en RKe. Die
belangrikste probleme wat RKe negatief beinvloed, is kollineariteit en punte met hoë
hefboom waardes agv die aard van die berekeningsprosedures en die feit dat RKe se invloedfunksies begrensd is in die ruimte van die afhanklike veranderlike, maar onbegrensd is
in die ontwerpruimte. Gevolglik het RKe ‘n hoë affiniteit vir punte met hoë hefboom waardes
en poog gewoonlik om uitskieters uit te sluit. Die finale uitset wat verkry word wanneer beide
punte met hoë hefboom waardes en uitskieters voorkom, is dan die netto resultaat van hierdie
twee teenstrydige pogings. Alhoewel RKe begrensd is in die onafhanklike veranderlike (en
dus redelik robuust is tov uitskieters), is uitskieter diagnostiese tegnieke ook beskou om ‘n
meer holistiese beeld te verkry.
Die ondersoek het analitiese sowel as simulasie tegnieke gebruik. Voorts is ook gebruik
gemaak van kunsmatige datastelle en standard datastelle uit die literatuur. Hierdie ondersoeke
het getoon dat die ED gebaseerde statistieke met ‘n redelike mate van sukses gebruik kan
word om probleme in die RK omgewing aan te spreek. Dit is egter belangrik om daarop te let
dat as gevolg van die interafhanklikheid tussen kollineariteit en punte met hoë hefboom
waardes asook dié tussen punte met hoë hefboom waardes en uitskieters, “oplossings”
dikwels afhanklik is van die bepaalde situasie. Ten spyte van hierdie kompleksiteit, is op
grond van die navorsing wat gedoen is, tog redelike algemene riglyne verkry wat nuttig in die
praktyk gebruik kan word.
6
Frechette, Luc A. Carleton University Dissertation Engineering Civil and Environmental. "Development of urban traffic models using a Bayesian regression approach." Ottawa, 1996.
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7
Fridgeirsdottir, Gudrun A. "The development of a multiple linear regression model for aiding formulation development of solid dispersions." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/52176/.
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As poor solubility continues to be problem for new chemical entities (NCEs) in medicines development the use and interest in solid dispersions as a formulation-based solution has grown. Solid dispersions, where a drug is typically dispersed in a molecular state within an amorphous water-soluble polymer, present a good strategy to significantly enhance the effective drug solubility and hence bioavailability of drugs. The main drawback of this formulation strategy is the inherent instability of the amorphous form. With the right choice of polymer and manufacturing method, sufficient stability can be accomplished. However, finding the right combination of carrier and manufacturing method can be challenging, being labour, time and material costly. Therefore, a knowledge based support tool based upon a statistically significant data set to help with the formulation process would be of great value in the pharmaceutical industry. Here, 60 solid dispersion formulations were produced using ten, poorly soluble, chemically diverse APIs, three commonly used polymers and two manufacturing methods (spray drying and hot-melt extrusion). A long term stability study, up to one year, was performed on all formulations at accelerated conditions. Samples were regularly checked for the onset of crystallisation during the period, using mainly, polarised light microscopy. The stability data showed a large variance in stability between, methods, polymers and APIs. No obvious trends could be observed. Using statistical modelling, the experimental data in combination with calculated and predicted physicochemical properties of the APIs, several multiple linear regression (MLR) models were built. These had a good adjusted R2 and most showed good predictability in leave-one-out cross validations. Additionally, a validation on half of the models (eg. those based on spray-drying models) using an external dataset showed excellent predictability, with the correct ranking of formulations and accurate prediction of stability. In conclusion, this work has provided important insight into the complex correlations between the physical stability of amorphous solid dispersions and factors such as manufacturing method, carrier and properties of the API. Due to the expansive number of formulations studied here, which is far greater than previously published in the literature in a single study, more general conclusions can be drawn about these correlations than has previously been possible. This thesis has shown the potential of using well-founded statistical models in the formulation development of solid dispersion and given more insight into the complexity of these systems and how stability of these is dependent on multiple factors.
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Saadat, Huzaifa. "Design and development of an automated regression test suite for UEFI." Master's thesis, Universitätsbibliothek Chemnitz, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-159277.
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Unified Extensible Firmware Interface (UEFI) is an industry standard for implementing the basic firmware in the computers. This standard replaces BIOS. A huge amount of C code has been written for the implementation of UEFI. Yet there has been a very little focus on testing UEFI code. The thesis shows how the industry can perform a meaningful testing of UEFI. Spanning the test coverage with the help of test tools over all UEFI phases is a key objective. Moreover, techniques such as Test Driven Development and source code analysis are explained in terms of UEFI to make sure the bugs are minimized in the first place. The results show that the usage of test and analysis tools point to a large number of issues. Some of these issues can be fixed at a very early stage in the Software Development Life Cycle. For this reason the developers and testers should be convinced that they need to focus on testing UEFI from a software perspective.
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Ding, Eric J. (Eric Jaw-Torng). "Using ADL for regression test development in a distributed object environment." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/41381.
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Bergman, Linnea. "Progress or Regression? How Poverty and Development are Portrayed in Advertising." Thesis, Malmö högskola, Fakulteten för kultur och samhälle (KS), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-22316.
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The aim of this paper is to show how organizations portray the developing world and development support in advertisements and how it relates to the criticism existing against development support. What messages are sent to the reader? Do the advertisements contradict the existing criticism against development support or do they reinforce stereotypes and prejudices?Four organizations are analyzed: the Red Cross; Save the Children; PLAN Sweden; and We Effect. The main focus is on their campaigns and outreaching work connected to these campaigns. The analysis is based on a qualitative discourse analysis of the material complemented by a semiotic approach.The developing world is presented as old-fashioned and out obsolete. The problems existing there are simplified and insufficient solutions are offered. Children are commonly occurring and often presented as the main receivers of the support even though the support is available for all ages. Women are over-represented, while men are rarely occurring. However, men are indirect portrayed as the perpetrators and thus the notion of men is present, presenting them as dangerous and irresponsible. The women on the other hand are associated with traditional work e.g. cleaning and sewing as well as caring about the family. Despite that the organizations work all over the world the pictures mainly show black women and children. Overall the developing world is depicted as dependent on others to reach positive development. Difference is accentuated, which could increase prejudices and stereotypes. It is mainly rural environment that is portrayed, which could be seen as depicting the development world as old-fashion and timeless. Positive images of Sweden are used while negative images of other places creating a huge gap between the readers and the people and places presented.
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Hall, Kimberlee K., and Phillip R. Scheuerman. "Development of Multiple Regression Models to Predict Sources of Fecal Pollution." Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etsu-works/2880.
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This study assessed the usefulness of multivariate statistical tools to characterize watershed dynamics and prioritize streams for remediation. Three multiple regression models were developed using water quality data collected from Sinking Creek in the Watauga River watershed in Northeast Tennessee. Model 1 included all water quality parameters, model 2 included parameters identified by stepwise regression, and model 3 was developed using canonical discriminant analysis. Models were evaluated in seven creeks to determine if they correctly classified land use and level of fecal pollution. At the watershed level, the models were statistically significant (p < 0.001) but with low r2 values (Model 1 r2 = 0.02, Model 2 r2 = 0.01, Model 3 r2 = 0.35). Model 3 correctly classified land use in five of seven creeks. These results suggest this approach can be used to set priorities and identify pollution sources, but may be limited when applied across entire watersheds.
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Azizi, Maral. "Application of Adaptive Techniques in Regression Testing for Modern Software Development." Thesis, University of North Texas, 2019. https://digital.library.unt.edu/ark:/67531/metadc1538762/.
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In this dissertation we investigate the applicability of different adaptive techniques to improve the effectiveness and efficiency of the regression testing. Initially, we introduce the concept of regression testing. We then perform a literature review of current practices and state-of-the-art regression testing techniques. Finally, we advance the regression testing techniques by performing four empirical studies in which we use different types of information (e.g. user session, source code, code commit, etc.) to investigate the effectiveness of each software metric on fault detection capability for different software environments. In our first empirical study, we show the effectiveness of applying user session information for test case prioritization. In our next study, we apply learning from the previous study, and implement a collaborative filtering recommender system for test case prioritization, which uses user sessions and change history information as input parameter, and return the risk score associated with each component. Results of this study show that our recommender system improves the effectiveness of test prioritization; the performance of our approach was particularly noteworthy when we were under time constraints. We then investigate the merits of multi-objective testing over single objective techniques with a graph-based testing framework. Results of this study indicate that the use of the graph-based technique reduces the algorithm execution time considerably, while being just as effective as the greedy algorithms in terms of fault detection rate. Finally, we apply the knowledge from the previous studies and implement a query answering framework for regression test selection. This framework is built based on a graph database and uses fault history information and test diversity in attempt to select the most effective set of test cases in term of fault detection capability. Our empirical evaluation of this study with four open source programs shows that our approach can be effective and efficient by selecting a far smaller subset of tests compared to the existing techniques.
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Binks, Paul John. "Development of regression analysis based hydrodynamic equations for conceptual semi-submersible design." Thesis, University of Newcastle Upon Tyne, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262923.
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Came, Paul James. "The roles of Ikk2 and Socs genes in mammary development and regression." Thesis, University of Cambridge, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615168.
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Guo, Jing. "DEVELOPMENTS IN NONPARAMETRIC REGRESSION METHODS WITH APPLICATION TO RAMAN SPECTROSCOPY ANALYSIS." UKnowledge, 2015. http://uknowledge.uky.edu/epb_etds/6.
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Raman spectroscopy has been successfully employed in the classification of breast pathologies involving basis spectra for chemical constituents of breast tissue and resulted in high sensitivity (94%) and specificity (96%) (Haka et al, 2005). Motivated by recent developments in nonparametric regression, in this work, we adapt stacking, boosting, and dynamic ensemble learning into a nonparametric regression framework with application to Raman spectroscopy analysis for breast cancer diagnosis. In Chapter 2, we apply compound estimation (Charnigo and Srinivasan, 2011) in Raman spectra analysis to classify normal, benign, and malignant breast tissue. We explore both the spectra profiles and their derivatives to differentiate different types of breast tissue. In Chapters 3-5 of this dissertation, we develop a novel paradigm for incorporating ensemble learning classification methodology into a nonparametric regression framework. Specifically, in Chapter 3 we set up modified stacking framework and combine different classifiers together to make better predictions in nonparametric regression settings. In Chapter 4 we develop a method by incorporating a modified AdaBoost algorithm in nonparametric regression settings to improve classification accuracy. In Chapter 5 we propose a dynamic ensemble integration based on multiple meta-learning strategies for nonparametric regression based classification. In Chapter 6, we revisit the Raman spectroscopy data in Chapter 2, and make improvements based on the developments of the methods from Chapter 3 to Chapter 4. Finally we summarize the major findings and contributions of this work as well as identify opportunities for future research and their public health implications.
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de, Miguel Ramos Carlos. "Assessment Based on Indicators of the Sustainable Development Goals in Spain : A Data Science Approach." Thesis, KTH, Maskinkonstruktion (Inst.), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-276705.
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The global sustainable development has been marked by the United Nations plans for more than two decades. These plans have been adopted by most of the developed and developing countries to achieve the 2030 Agenda, currently formed by the 17 Sustainable Development Goals. Governments and policy-makers cannot make conscious decisions regarding sustainability progress without knowledge about how well the country is performing this path. This study assessed the evolution of each SDG in Spain through their indicators and whether correlation and dependency between the stated targets exist. Goals 1, 2, 6, 8 and 11 were the less evolved, those which were undergoing a slower process or a negative evolution over the years. The correlation analysis delivered a quick guide of relationships amidst targets to help the appropriate ministries to make prompt decisions knowing which fields will be affected largely. Goal 3 (Good health and well-being) was strongly linked with indicators from Goal 4 (Quality education) and also Goal 6 (Clean water and sanitation). Furthermore, indicators from Goal 7 (Affordable and clean energy) shared a high correlation with the ones from Goal 12 (Responsible consumption and production) and Goal 15 (Life on land). All together obtained 60% share of positive interactions and almost 80% of significant interplays between the targets. Correlation does not imply causality, so multiple linear regression analysis set true numerical relationships and revealed how to enhance certain targets by leveraging others. Less developed indicator was taken as dependent variables and the final independent ones were defined using shrinkage methods. The procedure to reach these expressions could be used to establish the dependency between other relevant indicators and getting the assessment of the performance of this country afterwards.<br>Den globala hållbara utvecklingen har präglats av FN:s planer i mer än två decennier. Dessa planer har antagits av de flesta av de utvecklade länderna och utvecklingsländerna för att uppnå agenda 2030, som för närvarande bildas av de 17 globala målen för hållbar utveckling (SDG). Regeringar och beslutsfattare kan inte fatta medvetna beslut om hållbarhetsframsteg utan kunskap om hur väl landet presterar denna väg. Denna studie undersökte utvecklingen av varje SDG i Spanien genom deras indikatorer och huruvida korrelation och beroende finns mellan de angivna målen. Mål 1, 2, 6, 8 och 11 var de mindre utvecklade. De genomgick en långsammare process eller hade negativ utveckling under åren. Korrelationsanalysen levererade en snabb guide över relationer förhållandet bland mål för att hjälpa de berörda ministerierna att fatta snabba beslut om att veta vilka områden som i hög grad kommer att påverkas. Mål 3 (God hälsa och välbefinnande) var starkt kopplat till indikatorer från mål 4 (Kvalitetsutbildning) och även mål 6 (Rent vatten och sanitet). Dessutom hade indikatorer från mål 7 (prisvärd och ren energi) en hög korrelation med indikatorer från mål 12 (Ansvarsfull konsumtion och produktion) och mål 15 (Liv på land). Tillsammans erhöll 60% positiva interaktioner och nästan 80% betydande samspel mellan målen. Korrelation innebär inte orsakssamband, så flera linjära regressionsanalyser satte riktiga numeriska förhållanden och avslöjade hur man kan förbättra vissa mål genom att utnyttja andra. Mindre utvecklade indikatorer togs som beroende variabler och de slutliga oberoende variablerna definierades med krympningsmetoder. Tillvägagångssättet för att nå dessa uttryck kan användas för att fastställa beroendet mellan andra relevanta indikatorer och få en utvärdering av landets resultat.
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Whitten, Tyson. "Defining and Measuring Persistent Offending." Thesis, Griffith University, 2018. http://hdl.handle.net/10072/378078.
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BACKGROUND
Persistent offending has been a topic of interest in the criminal justice literature for some time. Despite its popularity, the concept remains without a consistent or agreed upon definition. For example, persistent offending has been variably defined as offending before and during adulthood (e.g., Bergman & Andershed, 2009), frequent offending (e.g., McGloin & Stickle, 2011), or an early age of first offence (e.g. Hay & Forrest, 2009). In turn, inconsistent methods have been used to operationalise and identify persistent offenders, such as offending before and after the age of 21 (Farrington, Ttofi, & Coid, 2009), the five percent most frequent offenders (Piquero & Lawton, 2002), and multiple offences committed before the age of 14 (Hagell & Newburn, 1994). The definitional inconsistency surrounding the concept of persistent offending poses a significant threat to the generalisability of research, accuracy of theory, and efficacy of policy and interventions. Although previous authors have highlighted their concerns regarding the methodological inconsistencies pertaining to research on persistent offending (Hagell & Newburn, 1994; Piquero, 2009), these concerns seem to have fallen on deaf ears.
AIMS
This dissertation argues that the use of inconsistent definitions and operationalisations of persistent offending are contributing to the inconsistent findings and competing explanations on the phenomenon. Therefore, more conceptual discussions and empirical observations drawing attention to the ramifications of this issue, as well as methods for rectifying the problem, are needed. Through a series of published and unpublished papers, this dissertation attempts to meet this need by: (1) Highlighting the prevalence of inconsistent definitions, operationalisations, and measures of persistent offending in the literature, and the consequent need for consistency; (2) Empirically demonstrating the flaws associated with these inconsistencies, and; (3) Proposing how to best define, operationalise, and measure persistent offending. The underlying position of this dissertation is that conceptually, persistent offending is best defined and measured by the duration of the criminal career. The arguments and empirical findings in this dissertation support this premise.
DATA AND ANALYSES
This dissertation uses data from the Cambridge Study in Delinquent Development (CSDD). The CSDD is a longitudinal, population-based study that, to date, has observed the development of offending behaviours in 411 South London males from the age of eight to 56. Boys were interviewed in school at ages eight, ten, and 14 years. Conviction data was recorded annually from the age of 10 to 56. All offences leading to a conviction, excluding minor offences such as traffic infractions and public intoxication, were included in the analyses. The vast majority of men (91 percent) were at risk of conviction at 56 years of age. Chi-square, multiple, and logistic regression analyses were used to examine the association between childhood risk factors and conviction frequency, criminal career duration, and different offending pathways. Descriptive statistics and odds ratios were conducted in order to examine the overlap in the number of offenders identified by different operationalisations of persistent offending. Finally, Pearson’s and partial correlation were used to examine the relationship between criminal career duration, conviction frequency, and age of first conviction.
RESULTS
Five key findings are reported in this dissertation. First, reviews of the published literature indicated that many of competing empirical findings can be attributed to the use of different definitions and operationalisations of persistent offending. Second, competing measures of persistent offending (i.e., criminal career duration and conviction frequency) are associated with different types and numbers of childhood risk factors. Indeed, not only did offenders with the longest criminal careers have fewer childhood risk factors than offenders with the most convictions, but the childhood risk factors associated with these offenders did not differ to those experienced by one-time offenders. Third, depending on the key measure used, different operationalisations of persistent offending generally identify vastly different offenders as persistent. Fourth, when controlling for offence frequency, onset age is not associated with criminal career duration. Finally, persistent offenders identified by the duration of the criminal career tend to have the longest criminal careers, a more normative age of onset, and vary in their conviction rates.
CONCLUSION
The collective results of this dissertation support the idea that persistent offending should logically and consistently be defined and measured by the duration of the criminal career. More so, it is proposed that persistent offending should be defined as a criminal career that exceeds the average duration for a criminal career in a population or offender based sample. Nonetheless, a fundamental limitation of proposing a specific definition of persistent offending is that, due to the concepts ambiguity, there are no clear right answers. It may therefore be some time before there is accord on how to define and identify this phenomenon. Nevertheless, it is hoped that, if nothing else, the arguments and findings in this dissertation will spur more scholarly discussions, and help pave the way towards establishing a consistently used definition of persistent offending.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Crim & Crim Justice<br>Arts, Education and Law<br>Full Text
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Sherber, Michael Steven. "Development of a regression-based off-line predictive controller for thermal storage optimization." Thesis, Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/19070.
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Ercisli, Safak. "Development of Enhanced Pavement Deterioration Curves." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/56599.
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Modeling pavement deterioration and predicting the pavement performance is crucial for optimum pavement network management. Currently only a few models exist that incorporate the structural capacity of the pavements into deterioration modeling. This thesis develops pavement deterioration models that take into account, along with the age of the pavement, the pavement structural condition expressed in terms of the Modified Structural Index (MSI). The research found MSI to be a significant input parameter that affects the rate of deterioration of a pavement section by using the Akaike Information Criterion (AIC). The AIC method suggests that a model that includes the MSI is at least 10^21 times more likely to be closer to the true model than a model that does not include the MSI. The developed models display the average deterioration of pavement sections for specific ages and MSI values.
Virginia Department of Transportation (VDOT) annually collects pavement condition data on road sections with various lengths. Due to the nature of data collection practices, many biased measurements or influential outliers exist in this data. Upon the investigation of data quality and characteristics, the models were built based on filtered and cleansed data. Following the regression models, an empirical Bayesian approach was employed to reduce the variance between observed and predicted conditions and to deliver a more accurate prediction model.<br>Master of Science
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Kuhudzai, Anesu G. "Expenditure analysis and planning in a changed economy: a case study approach of Gweru City Council, Zimbabwe." Thesis, University of Fort Hare, 2014. http://hdl.handle.net/10353/d1019780.
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The purpose of this study is to analyse Gweru City Council`s spending pattern and behaviour and to determine if this spending pattern is directed towards poverty reduction and economic development or not. Furthermore, to fit a log-differenced regression model to a historical financial dataset obtained from Gweru City Council Finance Department for the time period July 2009 to September 2012. Regression techniques were used to determine how Gweru City Council`s total income (dependent variable) is affected by its expenditure (independent variables). Econometric modeling techniques were employed for the evaluation of estimate tests, conducted to determine the reliability of the estimated model. The study concludes by providing some recommendations for possible financial plans which could be adopted by Gweru City Council and other local authorities in Zimbabwe for the well-being of Zimbabweans and economic development.
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Andersson, Skog Nils. "Bats in Urban Sweden : A multiple regression analysis of bats’ relationship to urbanization." Thesis, Södertörns högskola, Miljövetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-45771.
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Human development continues to use up more physical space in the natural world, threatening the natural habitats of many organisms. To combat the loss of biodiversity science needs to explore what landscape features are important for different organisms so that we can incorporate these into the modern environment. As bats play an important role in many ecosystems and can reflect changes through trophic levels, analyzing their preferred habitats can help planners improve biological diversity of the urban habitat. Using acoustically identified bat sightings from Artportalen.se for the years 2017-2018, this paper studied the habitats of bats in Sweden. Through multiple regression analysis we examine the response in abundance and/or diversity of bats to physical and socio-cultural attributes of the urban habitat. We examined a total of 10160 bats from 18 species in 418 land cover locales and 306 demographical statistical areas with varying degrees of urbanization. Our results indicate that bat abundance and diversity decrease significantly with higher urbanization while deciduous forests are the most important land cover type for all bats. The results also indicate that wealthier areas have less abundance and diversity even when factoring in population density. Species specific analysis suggested that bat species who are better adapted at foraging in open vegetated landscapes and over water were less susceptible to the negative impacts of the urban habitat. We conclude that diverse habitats with a mixture of open vegetated areas, watercourses and broadleaf forests are the most important land features for a diverse bat fauna along with high connectivity via tree cover and linear landscape elements. If urban planning could incorporate these features into the urban habitat, some of the negative impacts of urbanization could be prevented.
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Hood, Andrew 1976. "The doctrine of command responsibility and the International Criminal Court : development, regression or compromise?" Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=31163.
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When should a commander be held responsible for the crimes of those under his control? Must a commander have known, or is it enough that he should have known, that his subordinates had committed or were about to commit a crime before we impose criminal responsibility on him for failing to prevent or punish those crimes? In attempting to answer these questions, the very foundations of criminal responsibility are set out and form the normative framework within which our examination of the command responsibility doctrine is undertaken. The historical evolution and modern-day application of the command responsibility doctrine are also set out and draws upon two themes; whether there is any justification for the distinction between the responsibility of military and civilian commanders and which mens rea standard should be adopted for the doctrine of command responsibility.
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Sarac, Ferdi. "Development of unsupervised feature selection methods for high dimensional biomedical data in regression domain." Thesis, Northumbria University, 2017. http://nrl.northumbria.ac.uk/36260/.
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In line with technological developments, there is almost no limit to collect data of high dimension in various fields including bioinformatics. In most cases, these high dimensional datasets contain many irrelevant or noisy features which need to be filtered out to find a small but biologically meaningful set of attributes. Although there have been various attempts to select predictive feature sets from high dimensional data in classification and clustering, there have only been limited attempts to do this for regression problems. Since supervised feature selection methods tend to identify noisy features in addition to discriminative variables, unsupervised feature selection methods (USFSMs) are generally regarded as more unbiased approaches. The aim of this thesis is, therefore, to provide (i) a comprehensive overview of feature selection methods for regression problems where feature selection methods are shown along with their types, references, sources, and code repositories (ii) a taxonomy of feature selection methods for regression problems to assist researchers to select appropriate feature selection methods for their research (iii) a deep learning based unsupervised feature selection framework, DFSFR (iv) a K-means based unsupervised feature selection method, KBFS. To the best of our knowledge, DFSFR is the first deep learning based method to be designed particularly for regression tasks. In addition, a hybrid USFSM, DKBFS, is proposed which combines KBFS and DFSFR to select discriminative features from very high dimensional data. The proposed frameworks are compared with the state-of-the-art USFSMs, including Multi Cluster Feature Selection (MCFS), Embedded Unsupervised Feature Selection (EUFS), Infinite Feature Selection (InFS), Spectral Regression Feature Selection (SPFS), Laplacian Score Feature Selection (LapFS), and Term Variance Feature Selection (TV) along with the entire feature sets as well as the methods used in previous studies. To evaluate the effectiveness of proposed methods, four different case studies are considered: (i) a low dimensional RV144 vaccine dataset; (ii) three different high dimensional peptide binding affinity datasets; (iii) a very high dimensional GSE44763 dataset; (iv) a very high dimensional GSE40279 dataset. Experimental results from these data sets are used to validate the effectiveness of the proposed methods. Compared to state-of-the-art feature selection methods, the proposed methods achieve improvements in prediction accuracy of as much as 9% for the RV144 Vaccine dataset, 75% for the peptide binding affinity datasets, 3% for the GSE44763 dataset, and 55% for the GSE40279 dataset.
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McAteer, Martina. "Effects of dietary fat and cholesterol on lipoprotein metabolism and on the development of atherosclerosis in the hamster." Thesis, University of Nottingham, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.342049.
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Tong, Fan. "Capacity demand and climate in Ekerö : Development of tool to predict capacity demand underuncertainty of climate effects." Thesis, KTH, Elektroteknisk teori och konstruktion, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-152522.
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The load forecasting has become an important role in the operation of power system, and several models by using different techniques have been applied to solve these problems. In the literature, the linear regression models are considered as a traditional approach to predict power consumption, and more recently, the artificial neural network (ANN) models have received more attention for a great number of successful and practical applications. This report introduces both linear regression and ANN models to predict the power consumption for Fortum in Ekerö. The characteristics of power consumption of different kinds of consumers are analyzed, together with the effects of weather parameters to power consumption. Further, based on the gained information, the numerical models of load forecasting are built and tested by the historical data. The predictions of power consumption are focus on three cases separately: total power consumption in one year, daily peak power consumption during winter and hourly power consumption. The processes of development of the models will be described, such as the choice of the variables, the transformations of the variables, the structure of the models and the training cases of ANN model. In addition, two linear regression models will be built according to the number of input variables. They are simple linear regression with one input variable and multiple linear regression with several input variables. Comparison between the linear regression and ANN models will be carried out. In the end, it finds out that the linear regression obtains better results for all the cases in Ekerö. Especially, the simple linear regression outperforms in prediction of total power consumption in one year, and the multiple linear regression is better in prediction of daily peak load during the winter.
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Mahalia, Nooshin Ahangar. "Micropolitans in Georgia." Thesis, Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-06302006-112103/.
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Elin, Hörnfeldt. "Designing a visual regression testing tool : Decrease fear-driven development and enhance the quality assurance." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-138398.
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Testing a software is important to maintain the quality of the application. There are many ways of testing functionality of an application but not so many for testing the interface. When reusing CSS is a common approach, one change in the CSS can cause many visual changes on the interface. Not testing these changes, visual errors might occur which can decrease the quality of the application. Also, not knowing where the change is affecting, fear-driven development, i.e. the developers feels fear when changing code, can arise for the developers. In this thesis, a pre-study was made to investigate if any current feardriven development existed among developers. Then a visual regression testing tool was created, using a rapid prototyping process, to help the developers testing the interface during the evolving process of the application. The tool’s primary purpose is to show images of the visual changes that have occurred for the developers and as a result, the fear-driven development can decrease for the developers and the quality can be improved. The tool was implemented using AngularJS, NodeJS and ResembleJS and was tested on UI developers. The developers got a case where they had made CSS changes and then wanted to see how the changes affected the site they were working on. All of the developers felt, often or sometimes, fear when changing code. After using the tool, their feelings of fear-driven development was decreased and they all saw the tool as helpful when finding visual errors that might occur when CSS or web components are changed.
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Niklasson, Mats. "Sensorimotor Therapy: Assessing Quantitative and Qualitative Expressions of Physiological and Psychological Development in Children." Licentiate thesis, Karlstads universitet, Institutionen för sociala och psykologiska studier, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-26869.
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The first purpose of this thesis was to examine whether sensorimotor therapy utilizing the training program ”Retraining for Balance” might be an appropriate technique for sensorimotor proficiency. The second purpose was to gain increased understanding of the effects of sensorimotor therapy on the physical and psychological development of children and youth. A third purpose was to put sensorimotor therapy in a wider perspective through a somewhat novel extension of the theoretical framework. Two naturalistic studies were conducted. Paper I was quantitative and comprised 232 children (181 boys and 51 girls) divided into three groups (1) a younger group (7 years or younger, n=65), (2) a middle group (8 to 10 years old, n=91) and, (3) an older group (11 years old or older, n=76). The participants presented attentional and motor difficulties before starting therapy. The treatment period was in average close to 3 years. Results indicated significant improvements concerning sensorimotor skills in all age groups. Paper II was a qualitative study, which included the records of 8 children (7 boys and 1 girl) randomly selected from the cohort of 232 children. The analysis used the EPP-method and yielded 3 overarching themes, which together formed “the kinesthetic-vestibular developmental model”. The model illustrated how Introductions of sensorimotor exercises pushed the therapy process forward due to periods of Regression and Transformation. The results were generalized to the remaining 224 children in the cohort by comparing each participant’s records with “the kinesthetic-vestibular developmental model”. The tentative conclusion was that sensorimotor therapy according to the method “Retraining for Balance” might constitute a complement to treatment of ADHD, DCD and LD but controlled studies are necessary before more decisive conclusions can be drawn.<br>Baksidestext This thesis had three purposes. (1) to examine whether sensorimotor therapy (SMT) using the training program ”Retraining for Balance” might be a proper technique for sensorimotor proficiency. (2) to gain increased understanding of the effects of SMT on physical and psychological development and, (3) to put SMT in a wider perspective by an extension of the theoretical framework. Two naturalistic studies were conducted. Paper I, which was quantitative, comprised 232 children who presented attentional and motor difficulties. The cohort was divided into three groups depending on age and results after therapy indicated improvements in all groups. Paper II, a qualitative study, selected records of 8 children from the cohort. Analysis yielded 3 overarching themes, which together formed “the kinesthetic-vestibular developmental model” illustrating how Introductions of exercises pushed the process forward due to Regressions and Transformations. The results were generalized to the remaining 224 children. The tentative conclusion of this thesis was that SMT might constitute a complement to treatment of ADHD, DCD and LD but controlled studies are necessary before decisive conclusions can be drawn.
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Davis, David B. "Predictive Modeling of Sulfur Flower Buckwheat (Erigonum umbellatum Torrey) Using Non-Parametric Multiplicative Regression Analysis." Diss., CLICK HERE for online access, 2009. http://contentdm.lib.byu.edu/ETD/image/etd3224.pdf.
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Wright, C. R. F. "The biophysical properties of plantar callus and the relationship between pressure and callus development and regression." Thesis, University of Salford, 2015. http://usir.salford.ac.uk/36946/.
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Plantar calluses are common skin lesions which often require professional treatment by podiatrists. They commonly present under prominent areas such as the metatarsal heads and can cause significant discomfort during ambulation. Furthermore, they are one of the known risk factors for ulceration in individuals with systemic conditions such as diabetes mellitus. Anecdotal evidence suggests that mechanical factors contribute to calluses and there are numerous studies linking callus to increased peak plantar pressure. However, whether callus is a result of increased pressure or vice versa remains unclear. Skin on other areas of the body has been shown to respond to external loading forces, but no research has specifically investigated the relationship between callus and pressure. A critical review of the literature explored the methods used for skin profiling through biophysical skin measurement. Skin hydration, distensibility and topography were revealed to be useful measurement parameters to characterise plantar skin and for this study, three devices were chosen for testing these parameters. However, as these devices have not received much attention for testing plantar callus in previous research, the first study investigated their repeatability on normal and callused plantar skin. These devices were shown to provide adequate measures of skin properties so they were then used in a larger scale study investigating the biophysical characteristics of normal and callused plantar skin. It was found that callused skin was less hydrated, less distensible, and rougher in texture than normal plantar skin. Work was then undertaken to develop a device that could apply loads to plantar skin in a safe manner so that the skin’s response to external loading could be assessed. A subsequent pilot study was conducted to assess whether normal plantar skin in individuals prone to callus would display callus-like skin changes as a result of increased vertical pressure applied by the skin loading device over a minimum period of six weeks. After the skin loading period, no effect could be observed in normal plantar skin properties. The reasons for this are explored in depth. A study was then undertaken in order to assess the effect of plantar pressure reduction in callused skin over a period of 12 weeks. Pressure reduction was achieved by using customised insoles worn by the study participants. No change in callused skin properties was observed and the reasons for this are explored in depth. These studies provide a strong starting point in understanding the link between pressure and callus and provide a foundation for further research.
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Boccalini, Gabriele. "An optical sensor for online hematocrit measurement: characterization and fitting algorithm development." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/6932/.
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Lo scopo del presente lavoro di tesi riguarda la caratterizzazione di un sensore ottico per la lettura di ematocrito e lo sviluppo dell’algoritmo di calibrazione del dispositivo. In altre parole, utilizzando dati ottenuti da una sessione di calibrazione opportunamente pianificata, l’algoritmo sviluppato ha lo scopo di restituire la curva di interpolazione dei dati che caratterizza il trasduttore.
I passi principali del lavoro di tesi svolto sono sintetizzati nei punti seguenti:
1) Pianificazione della sessione di calibrazione necessaria per la raccolta dati e conseguente costruzione di un modello black box.
Output: dato proveniente dal sensore ottico (lettura espressa in mV)
Input: valore di ematocrito espresso in punti percentuali ( questa grandezza rappresenta il valore vero di volume ematico ed è stata ottenuta con un dispositivo di centrifugazione sanguigna)
2) Sviluppo dell’algoritmo
L’algoritmo sviluppato e utilizzato offline ha lo scopo di restituire la curva di regressione dei dati.
Macroscopicamente, il codice possiamo distinguerlo in due parti principali:
1- Acquisizione dei dati provenienti da sensore e stato di funzionamento della pompa bifasica
2- Normalizzazione dei dati ottenuti rispetto al valore di riferimento del sensore e implementazione dell’algoritmo di regressione.
Lo step di normalizzazione dei dati è uno strumento statistico fondamentale per poter mettere a confronto grandezze non uniformi tra loro.
Studi presenti, dimostrano inoltre un mutazione morfologica del globulo rosso in risposta a sollecitazioni meccaniche.
Un ulteriore aspetto trattato nel presente lavoro, riguarda la velocità del flusso sanguigno determinato dalla pompa e come tale grandezza sia in grado di influenzare la lettura di ematocrito.
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Shrestha, Shivesh. "Development of structural condition thresholds for TSD measurements." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78039.
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This thesis presents (a) results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The results showed consistent error standard deviation in the TSD measurements and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT’s Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher.
In order to develop deflection thresholds, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation.<br>Master of Science<br>This thesis presents (a) some of the results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD: which is the variation in repeated TSD measurements on the same section of the road, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The pavement structural number is an abstract number expressing the structural strength of the pavement. The results showed that the TSD measurements were repeatable and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher.
In order to develop deflection thresholds to categorize pavements in different condition: good, fair and poor, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation.
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Chang, Chih-Yao. "Resident Attitudes toward Community Development Alternatives." DigitalCommons@USU, 2010. https://digitalcommons.usu.edu/etd/622.
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Utilizing survey data collected in four communities in the State of Utah, this study examined the extent to which rural resident perceptions and attitudes toward local community circumstances influence their own expectations and attitudes subjectively toward future community development alternatives. Understanding perceptions of community and community development, as well as the patterns of localized community development, is crucial and needs to consider residents' opinions and attitudes toward unique rural economic, environmental, and social conditions in order to help preserve the unique characteristics of the way of life while continuing economic improvement and social betterment in rural areas. Three conceptual frameworks of development (economic, environmental, and social) are applied in this study to explore the relationship between local residents' general attitudes toward the current conditions in their community and their attitudes toward development alternatives. I examine how these three development frameworks guide rural scholars to understand whether the pattern of community development is consistent across the region or localized from community to community. Four different types of rural communities were selected in a Utah-wide community survey in the summer of 2008. These communities are facing four different change patterns: an increasing senior community, an energy-development community, a recreational community, and a constant community that has remained stable over the last five decades. Each type of community has its unique economy, lifestyle, culture, and environment, in which local residents have developed a way of life in response to these changes in social and economic structures. Research findings indicate that the local residents' self-perceptions of community economic situation are not significant indictors to support the arguments of the economic development framework. However, indexes of environmental and social development frameworks are found to have strong associations with locals' environmental and social development alternatives. Also, different types of rural community show different demands for community development strategies, implying that a single development framework would not be sufficient to explain the complex of local residents' perceptions and attitudes toward community development unless the researchers integrate other perspectives into the model.
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Wiese, Linda. "Economic development in ex-Yugoslavia : -Some good advices on the way." Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-130872.
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This thesis will determine the factors that have affected the economy in the countries from ex-Yugoslavia. A couple of regression analyses will test the correlation between GDP Growth or GDP per Capita and twelve independent variables. The analyses tell us that high import ratio, low inflation and not being in an intrastate war are associated with high GDP Growth, where high political rights, being a member of the European Union or having a status as a Candidate Country are associated with high GDP per Capita. The explanation for the different result might be the catch up effect.
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Mann, David. "Determining Optimal Locations for New Wind Energy Development in Iowa." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/theses/683.
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The purpose of this research is to generate the most accurate model possible for predicting locations most suitable for new wind energy development using a case study of Iowa. With the United States poised for significant growth in electricity generation from wind and other renewable resources, this research can help developers, transmission planners, landowners, as well as academics in predicting optimal locations for development. Iowa currently has the second greatest installed wind energy capacity and highest percentage of energy generated from wind of all the states, and has excellent resources and central location for a high level of continued development. This research employs a variety of methods including traditional constraint mapping techniques, logistic regression, and a hybrid of both approaches in attempting to produce the best predictive model possible. The best performing logistic regression model with 11 variables correctly predicts 90.1% of overall observations. A variety of output maps are produced and analyzed, and many suggestions for future research in this area are presented.
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Kizilkaya, Zafer. "An analysis of the effect of commissioning sources on retention and promotion of U.S. Army Officers /." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Jun%5FKizilkaya.pdf.
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Thesis (M.S. in Operations Research)--Naval Postgraduate School, June 2004.<br>Thesis advisor(s): Samuel E. Buttrey, Daniel R. Dolk. Includes bibliographical references (p. 69-70). Also available online.
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Bello, Ghalib. "Application and Extension of Weighted Quantile Sum Regression for the Development of a Clinical Risk Prediction Tool." VCU Scholars Compass, 2014. http://scholarscompass.vcu.edu/etd/608.
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In clinical settings, the diagnosis of medical conditions is often aided by measurement of various serum biomarkers through the use of laboratory tests. These biomarkers provide information about different aspects of a patient’s health and the overall function of different organs. In this dissertation, we develop and validate a weighted composite index that aggregates the information from a variety of health biomarkers covering multiple organ systems. The index can be used for predicting all-cause mortality and could also be used as a holistic measure of overall physiological health status. We refer to it as the Health Status Metric (HSM). Validation analysis shows that the HSM is predictive of long-term mortality risk and exhibits a robust association with concurrent chronic conditions, recent hospital utilization, and self-rated health. We develop the HSM using Weighted Quantile Sum (WQS) regression (Gennings et al., 2013; Carrico, 2013), a novel penalized regression technique that imposes nonnegativity and unit-sum constraints on the coefficients used to weight index components. In this dissertation, we develop a number of extensions to the WQS regression technique and apply them to the construction of the HSM. We introduce a new guided approach for the standardization of index components which accounts for potential nonlinear relationships with the outcome of interest. An extended version of the WQS that accommodates interaction effects among index components is also developed and implemented. In addition, we demonstrate that ensemble learning methods borrowed from the field of machine learning can be used to improve the predictive power of the WQS index. Specifically, we show that the use of techniques such as weighted bagging, the random subspace method and stacked generalization in conjunction with the WQS model can produce an index with substantially enhanced predictive accuracy. Finally, practical applications of the HSM are explored. A comparative study is performed to evaluate the feasibility and effectiveness of a number of ‘real-time’ imputation strategies in potential software applications for computing the HSM. In addition, the efficacy of the HSM as a predictor of hospital readmission is assessed in a cohort of emergency department patients.
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Di, Credico Gioia. "Some developments in semiparametric and cross-classified multilevel models." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3424946.
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Our work has developed from a real epidemiological problem. The carcinogenic effect of cigarette smoking on head and neck cancer has been extensively studied in the literature highlighting a non linear dose-response relationship. Recently, the use of linear regression splines, within semiparametric models framework, has allowed an improvement in the evaluation of the association between smoking habits and head and neck cancer. Our work focuses on the development of a methodology able to improve several aspects of the estimation of the aforementioned relationship. In particular, the approximation of the spline function, represented by truncated linear basis, has been refined by addressing the problem of estimating two key quantities for the definition of a spline function: the number and position of the knots. The proposed methodology uses a Bayesian approach. We then focused on developing a streamlined methodology applicable to generalised linear models for cross-classified data. In particular, the steps necessary to calculate the covariance matrix are optimised with respect to one of the two random effects, allowing a computational gain both in terms of time and memory usage. The proposed algorithms are applied in the context of the inferential variational methods in detail to the mean field variational Bayes.<br>Il nostro lavoro si è sviluppato a partire da un problema epidemiologico reale. L’effetto carcinogenico del fumo di sigaretta sui tumori testa-collo è stato ampiamente studiato in letteratura evidenziando una relazione dose-risposta non lineare. Recentemente, l’utilizzo di spline lineari di regressione nell’ambito di modelli semiparametrici, ha permesso un miglioramento nella valutazione dell’associazione tra fumo e tumori testa-collo. Il nostro lavoro si concentra sullo sviluppo di una metodologia capace di migliorare la stima della suddetta relazione sotto diversi aspetti. In particolare, l'approssimazione della funzione spline, rappresentata attraverso basi lineari troncate, è stata affinata affrontando il problema di stima di due quantità chiave per sua la definizione: il numero e la posizione dei nodi. La metodologia proposta si serve di un approccio Bayesiano. Successivamente ci siamo concentrati sullo sviluppo di una metodologia streamline applicabile a modelli lineari generalizzati per dati con struttura cross-classified. In particolare, gli step necessari al calcolo della matrice di covarianza vengono ottimizzati rispetto ad uno dei due effetti random permettendo un guadagno computazionale sia in termini di tempo che di utilizzo della memoria. Gli algoritmi proposti vengono applicati nell’ambito dei metodi variazionali inferenziali nel dettaglio al mean field variational Bayes.
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Bogdanov, Daniil. "The development and analysis of a computationally efficient data driven suit jacket fit recommendation system." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-222341.
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In this master thesis work we design and analyze a data driven suit jacket fit recommendation system which aim to guide shoppers in the process of assessing garment fit over the web. The system is divided into two stages. In the first stage we analyze labelled customer data, train supervised learning models as to be able to predict optimal suit jacket dimensions of unseen shoppers and determine appropriate models for each suit jacket dimension. In stage two the recommendation system uses the results from stage one and sorts a garment collection from best fit to least fit. The sorted collection is what the fit recommendation system is to return. In this thesis work we propose a particular design of stage two that aim to reduce the complexity of the system but at a cost of reduced quality of the results. The trade-offs are identified and weighed against each other. The results in stage one show that simple supervised learning models with linear regression functions suffice when the independent and dependent variables align at particular landmarks on the body. If style preferences are also to be incorporated into the supervised learning models, non-linear regression functions should be considered as to account for increased complexity. The results in stage two show that the complexity of the recommendation system can be made independent from the complexity of how fit is assessed. And as technology is enabling for more advanced ways of assessing garment fit, such as 3D body scanning techniques, the proposed design of reducing the complexity of the recommendation system enables for highly complex techniques to be utilized without affecting the responsiveness of the system in run-time.<br>I detta masterexamensarbete designar och analyserar vi ett datadrivet rekommendationssystem för kavajer med mål att vägleda nät-handlare i deras process i att bedöma passform över internet. Systemet är uppdelat i två steg. I det första steget analyserar vi märkt data och tränar modeller i att lära sig att framställa prognoser av optimala kavajmått för shoppare som inte systemet har tidigare exponeras för. I steg två tar rekommendationssystemet resultatet ifrån steg ett och sorterar plaggkollektionen från bästa till sämsta passform. Den sorterade kollektionen är vad systemet är tänkt att retunera. I detta arbete föreslåar vi en specifik utformning gällande steg två med mål att reducera komplexiteten av systemet men till en kostnad i noggrannhet vad det gäller resultat. För- och nackdelar identifieras och vägs mot varandra. Resultatet i steg två visar att enkla modeller med linjära regressionsfunktioner räcker när de obereoende och beroende variabler sammanfaller på specifika punkter på kroppen. Om stil-preferenser också vill inkorpereras i dessa modeller bör icke-linjära regressionsfunktioner betraktas för att redogöra för den ökade komplexitet som medföljer. Resultaten i steg två visar att komplexiteten av rekommendationssystemet kan göras obereoende av komplexiteten för hur passform bedöms. Och då teknologin möjliggör för allt mer avancerade sätt att bedöma passform, såsom 3D-scannings tekniker, kan mer komplexa tekniker utnyttjas utan att påverka responstiden för systemet under körtid.
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Zambonin, Giuliano. "Development of Machine Learning-based technologies for major appliances: soft sensing for drying technology applications." Doctoral thesis, Università degli studi di Padova, 2019. http://hdl.handle.net/11577/3425771.
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In this thesis, Machine Learning techniques for the improvements in the performance of household major appliances are described. In particular, the focus is on drying technologies and domestic dryers are the machines of interest selected as case studies. Statistical models called Soft Sensors have been developed to provide estimates of quantities that are costly/time-consuming to measure in our applications using data that were available for other purposes.
The work has been developed as industrially driven research activity in collaborations with Electrolux Italia S.p.a. R&D department located in Porcia, Pordenone, Italy. During the thesis, practical aspects of the implementation of the proposed approaches in a real industrial environment as well as topics related to collaborations between industry and academies are specified.
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Williams, Robert C. "The Development of Mathematical Models for Preliminary Prediction of Highway Construction Duration." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/29483.
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Knowledge of construction duration is pertinent to a number of project planning functions prior to detailed design development. Funding, financing, and resource allocation decisions take place early in project design development and are significantly influenced by the construction duration. Currently, there is not an understanding of the project factors having a statistically significant relationship with highway construction duration. Other industry sectors have successfully used statistical regression analysis to identify and model the project parameters related to construction duration. While the need is seen for such work in highway construction, there are very few studies which attempt to identify duration-influential parameters and their relationship with the highway construction duration.
This research identifies the project factors, known early in design development, which influence highway construction duration. The factors identified are specific to their respective project types and are those factors which demonstrate a statistically-significant relationship with construction duration. This work also quantifies the relationship between the duration-influential factors and highway construction duration. The quantity, magnitude, and sign of the factor coefficient yields evidence regarding the importance of the project factor to highway construction duration. Finally, the research incorporates the duration-influential project factors and their relationship with highway construction duration into mathematical models which assist in the prediction of construction duration. Full and condensed models are presented for Full-Depth Section and Highway Improvement project types. This research uses statistical regression analysis to identify, quantify, and model these early-known, duration-influential project factors.
The results of this research contribute to the body of knowledge of the sponsoring organization (Virginia Department of Transportation), the highway construction industry, and the general construction industry at large.<br>Ph. D.
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Schultz, Sheila R. "Socioemotional Development of Low-Income Children in the Public School Intervention Program." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/27338.
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The current study used data gathered as part of the Head Start/Public School Transition Project (Virginia Site), and included only data on the children who were part of Cohort II (i.e., enrolled in kindergarten in 1993). This database was examined to determine how select child and family characteristics uniquely contributed to parents' and teachers' ratings of the children's social skills and problem behaviors. A series of exploratory factor analyses (EFA), using principal components extraction and varimax rotation, were conducted to identify from the available database underlying constructs associated with the children's development of social skills and problem behaviors. Results of the EFA were used to construct predictor and dependent variables. Separate univariate models were established at four time points and hierarchical multiple regression was used to examine the unique contributions of the various predictors of parent and teacher ratings of children's social skills and problem behaviors. Of the demographic variables examined, the unique contribution of Hispanic ethnicity to parents' ratings of the children's social skills and problem behaviors was significant at all time points. Other predictors that were significant and uniquely contributed the most to parents' ratings of the children's social skills included the family's routine (beginning of kindergarten), parenting style (end of kindergarten), and attitudes about the neighborhood (end of first grade). Parents' attitudes about the behavior of children in the school was a significant predictor of parents' ratings of the children's problem behaviors. None of the predictors contributed significantly to the teacher's ratings of the children's social skills or problem behaviors.<br>Ph. D.
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Crescenzi, Marika. "Exploring the dimorphism during fibrosis development and regression in a murine model of toxin-induced chronic liver injury." Doctoral thesis, Università degli studi di Padova, 2019. http://hdl.handle.net/11577/3422834.
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Liver fibrosis represents a crucial biological process, being the final common pathway of chronic or iterative liver damage. It is consequent to repeated wounds which are known to heal not in a timely manner. The contribution of gender-biased hepatic responses to liver injury represents a lively research topic to be investigated. With this PhD research the crosstalk between fibrosis, the drivers and targets of matrix remodelling and the hepatic immune microenvironment was ascertained and characterized. A murine model of chronic hepatic damage established by repeated administrations of the toxin CCl4 was developed and the injured liver was analysed in a timeframe of 12 weeks, including in addition also a period of washout of 8 weeks which allowed the liver to self-heal. Fibrosis, HSCs activation, analysis of matrix remodelling players in the liver along with immune infiltrating cellular components and circulating sexual hormones and cytokines were deeply investigated. An impaired capability for injured females to resorb excessive hepatic ECM during the self-healing was demonstrated, associated both with a decrease in estradiol concentrations and a delayed MMP9 activity in the onset of chronic hepatic damage. The characterization of the fibrotic milieu demonstrated an imbalance in the axis MMP-TIMP associated with a more inflammatory prone immune profile in female mice. The differences in the immune profile between injured males and females were also confirmed by analysing an array of circulating cytokines. The investigations in liver single cell suspensions of the immune cellular components present accordingly to different stages of severity of the disease, unveiled a residual population of Kupffer cells in females and a restorative macrophages component in males, after the self-healing, which could be responsible for the gender-biased effective fibrosis resolution. Further investigations are needed to ascertain if an angiocrine altered signalling is also part of this imbalance, considering data obtained on VEGFA mRNAs and protein modulations. Moreover, the possibility to translate into other models of hepatic injury data evidenced by this PhD thesis and, above all, to study in humans the biological processes below the liver dimorphism in fibrosis dynamics represents a mandatory condition to augment the knowledge in this lively field of research.
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Ferrari, L. "FAS/FASL PATHWAY IS IMPAIRED IN CHORDOMA AND IS INVOLVED IN ZEBRAFISH (DANIO RERIO) NOTOCHORD DEVELOPMENT AND REGRESSION." Doctoral thesis, Università degli Studi di Milano, 2013. http://hdl.handle.net/2434/221053.
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Abstract
Chordoma is a rare malignant tumor characterized by chemoresistance and unforeseeable prognosis, originating from notochord remnants that do not disappear during development. The apoptotic mechanisms are fundamental for notochord cells development and regression, but little is known about the role of specific apoptotic pathways. At this purpose we investigated the possible implication of Fas/Fasl apoptotic pathway in chordoma tumorigenesis. FASL expression was absent, while both FAS anti- and pro-apoptotic isoforms were detected in most chordomas analyzed and in U-CH1 cells. These findings, besides the prevalent expression of inactive Caspases 8 and 3, suggest that Fas/Fasl pathway is impaired in this tumor. The enhancement of apoptosis in U-CH1 cells by treatment with soluble Fasl indicates that Fas/Fasl pathway can be activated in chordoma, suggesting Fas/Fasl as potential pharmacological targets. We also hypothesized that Fas/Fasl pathway dysregulation may have a role in chordoma onset. To unravel this issue we investigated the function of fas and fasl homologs in the zebrafish notochord development. We found that these genes were specifically expressed in notochord cells. Morpholino mediated knock-down of fas and fasl resulted in abnormal phenotypes mainly showing curved tail and altered motility. Notochord multi-cell-layer jumps instead of the typical “stack-of-coins” organization, larger vacuolated cells, defects in the peri-notochordal sheath structure and in vertebral mineralization have been detected in most morphants. In addition, we observed the persistent expression of ntla and col2a1a, the zebrafish homologs of the human T gene and COL2A1, which were found to be specifically upregulated in chordoma. In conclusion, our findings indicate that Fas/Fasl pathway activity can be enhanced in chordoma. Moreover, we demonstrated for the first time the involvement of fas and fasl in notochord development, differentiation and regression in zebrafish suggesting the implication of this pathway in chordoma onset.
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Ham, Roger, University of Western Sydney, and School of Economics and Finance. "The urban residential economic model : theoretical and empirical developments." THESIS_XXX_EFI_HAM_R.xml, 1999. http://handle.uws.edu.au:8081/1959.7/447.
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The aim of thesis is to analyse the economic model of urban residential location through the application of duality methods. Whilst some dual methods have been used in urban economic modelling in the past this paper proposes alternative dual approaches which appear to be novel, but are complimentary to existing approaches to the urban model. As part of the application of dual techniques the paper proposes a method of application which is general enough to be applied to all Von Thunen type models and tests this proposition on the fundamental agrarian model of Von Thunen. As part of the dual analysis of the urban residential model the conditions for the traditional lot size hypothesis are examined in the light of conditional demand functions stemming from the dual analysis. The work also empirically tests the traditional residential lot size hypothesis for various Australian cities. The empirical method adopted involves estimation of density gradients utilising competing non-nested flexible form models and discrimination between these alternative models utilising semi-parametric non-nested tests based on an artificial regression model. Two of the three competing models have not been used in this context before, one of them being completely novel. Moreover, the artificial regression model has not been previously used in this context, requiring some modification to deal with the problem of competing models with dependent variable transformation.<br>Doctor of Philosophy (PhD)
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Hall, Kimberlee K., and Phillip R. Scheuerman. "Development of Multiple Regression Models to Predict Sources of Fecal Pollution in the Watauga River Watershed in Northeast Tennessee." Digital Commons @ East Tennessee State University, 2013. https://dc.etsu.edu/etsu-works/2954.
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Vadlamani, Tripura. "Development of a Multidimensional Scale of Ergonomic Factors Related to Employee Retention." Ohio University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1283456798.
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Fullmer, Susanna. "Determining Predictors of Peer Relations: A Study on Youth inEthiopia, India, Peru, and Vietnam." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/9084.
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Across the world countries are currently striving to eliminate poverty, improve the quality of education, optimize well-being, among other areas of improvement. In an effort to help such improvements, a group called Young Lives ran a longitudinal study on youth in Ethiopia, India, Peru, and Vietnam that studied the many facets of poverty. The purpose of this study is to utilize the Young Lives dataset to determine how countries can more readily improve social-emotional skills by looking at important experiences in adolescents' lives. Specifically, this study examines what factors increase a child's ability to socialize with peers, which is shown to be linked to higher academic success as well as a fuller development into adulthood. In order to measure the ability to socialize with peers, Young Lives used the relationships with Peers Scale (RPS). I examined, through implementing structural equation modeling techniques, what factors significantly predict RPS scores, as well as which time point the factors are most predictive. I also inspected the psychometric properties of the RPS on the Young Lives' population and observed measurement invariance across time and country in order to ensure this scale is a valid measure. Steps to improve relationships with peers can be taken by encouraging higher intrinsic locus of control, providing equal educational opportunities, improving safety conditions, providing nutritional education, and eliminating competition for resources.
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Ubisse, Amosse Francisco. "A formative evaluation of LPC’s Montessori Preschool Programme." Master's thesis, Faculty of Commerce, 2019. http://hdl.handle.net/11427/31303.
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Research shows that early childhood interventions with fidelity to Montessori model generate learner’s outcomes that outperform the traditional model. The evidence is confirmed in developed and in developing countries. This formative evaluation reports the results of a Montessori model in implementation in township of Mfuleni, located in Cape Town, South Africa. Providing insights into the functioning of the programme, the evaluation confirms that the roll out of the Montessori model is still underway which may explain the reason of the learners not outperforming the comparison group.
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Fullmer, Susanna. "Determining Predictors of Peer Relations: A Study on Youth in Ethiopia, India, Peru, and Vietnam." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/9084.
Full textAbstract:
Across the world countries are currently striving to eliminate poverty, improve the quality of education, optimize well-being, among other areas of improvement. In an effort to help such improvements, a group called Young Lives ran a longitudinal study on youth in Ethiopia, India, Peru, and Vietnam that studied the many facets of poverty. The purpose of this study is to utilize the Young Lives dataset to determine how countries can more readily improve social-emotional skills by looking at important experiences in adolescents' lives. Specifically, this study examines what factors increase a child's ability to socialize with peers, which is shown to be linked to higher academic success as well as a fuller development into adulthood. In order to measure the ability to socialize with peers, Young Lives used the relationships with Peers Scale (RPS). I examined, through implementing structural equation modeling techniques, what factors significantly predict RPS scores, as well as which time point the factors are most predictive. I also inspected the psychometric properties of the RPS on the Young Lives' population and observed measurement invariance across time and country in order to ensure this scale is a valid measure. Steps to improve relationships with peers can be taken by encouraging higher intrinsic locus of control, providing equal educational opportunities, improving safety conditions, providing nutritional education, and eliminating competition for resources.