Three Macroterrain Landtype Association classification models were developed to stratify and categorize Utah's West Desert. These models approached terrain segmentation using an energy-flow paradigm from erosional to transitional to depositional landscape. One model was developed as a slope-backed deterministic model that used slope-threshold limits to discriminate between Landtype Associations. A second model was developed as a stochastic, training-data driven supervised classification, using comparative t-values to classify the landscape to the most similar landtype class. The third model was a probabilistic algorithm, which classified the landscape to the most probable class based on multiple iterations of the stochastic model. These models were assessed for performance against Macroterrain Landtype Association classifications from three independent geographical datasets. The performance assessment involved calculating model-to-reference agreement, a piecewise assessment of errors for each Macroterrain Landtype Association class, and a measure of the modeI-to-reference performance relative to that performance expected from random chance.

A urbanização acentuada, fenômeno crescente das últimas décadas, tem atingido níveis elevadíssimos e criado enormes desafios para a gestão das cidades, além de trazer uma vasta gama de efeitos nefastos para a qualidade de vida de seus cidadãos. Dados da ONU de 2016, indicam tratar-se de um caminho sem volta, com uma tendência de agravamento nos próximos anos. Para tentar mitigar esta situação, muito se tem discutido em como aumentar o nível de inteligência das cidades e o interesse pelo tema Cidades Inteligentes tem crescido. Apesar disso, ainda não existe consenso sobre um conceito de cidade inteligente. Se há tempos este conceito se baseava exclusivamente no pilar da tecnologia, hoje uma visão mais evoluída e holística incorpora várias outras dimensões. Já a maioria dos modelos de classificação existentes são estrangeiros e não são aderentes à realidade de um país tão diverso e tão desigual quanto o Brasil. No âmbito nacional, existem algumas iniciativas de criação de conceitos e de modelos de classificação, mas, ou são baseados unicamente no componente tecnológico, ou buscam apenas a criação de rankings tradicionais baseados em ponderações arbitrárias de seus formuladores. A dificuldade de adequação do conceito e dos modelos de classificação à realidade brasileira foram os dois motores principais desta tese. O primeiro objetivo foi desenvolver um conceito de cidade inteligente para o contexto brasileiro. O segundo foi propor um modelo multidimensional de classificação, que fugisse aos padrões tradicionais de um ranking e fosse um instrumento efetivo de aprendizagem, benchmarking e de apoio ao planejamento de políticas públicas das cidades. Por meio de um estudo exploratório e descritivo, junto a 3 cidades de portes diferentes do estado de São Paulo, foram desenvolvidas pesquisas de abordagem quantitativa e qualitativa. A primeira utilizou questionários fechados e levantamento de dados em bases de indicadores específicos para o cálculo dos componentes do Índice Brasileiro Multidimensional de Classificação de Cidades Inteligentes - IBMCCI. Este produto final da tese emprega a mesma abordagem orientada ao usuário do U-MULTIRANK, o ranking multidimensional global de universidades da Comunidade Europeia. A versão final do modelo proposto foi disponibilizada para uso dos gestores municipais com a liberdade de seleção das dimensões, dos indicadores e dos municípios equivalentes para análise. A abordagem qualitativa da pesquisa foi conduzida por meio de entrevistas semiestruturadas, junto a 2 especialistas em gestão municipal. Para validar a ferramenta construída utilizou-se a técnica de validação de conteúdo. Chegou-se à conclusão que é necessário ajustar alguns fatores do modelo e adequar a periodicidade de edição do índice para coincidir com o calendário das eleições municipais. Com estas adequações, o IBMCCI demonstrou grande potencial de se tornar uma ferramenta efetiva de apoio para os formuladores de políticas públicas municipais. / The strong urbanization, a phenomenon that has increased in recent decades, has reached a very high level and has created enormous challenges for the management of cities, as well as bringing a wide range of harmful effects to the quality of life of its citizens. UN data of 2016 indicates that this is one-way road, and it\'s forecast to be worse in the coming years. Trying to mitigate this situation, much has been discussed about how to increase the smartness level of the cities and the interest in subject of Smart Cities has grown. Despite this, there is still no consensus on a smart city concept. If for some time this concept was based exclusively on the pillar of technology, today a more evolved and holistic vision would incorporate several other dimensions. Most of the existing classification models are foreign and are not adherent to the reality of a country as diverse and as unequal as Brazil. At the national level, there are some initiatives to create concepts and classification models, but they are based solely on the technological component or they only seek to create traditional rankings based on arbitrary weights of their formulators. The difficulty of adapting the concepts and the classification models to the Brazilian reality were the two main engines of this thesis. The first aim was to develop a concept of Smart cities for the Brazilian context. The second one was to propose a multidimensional classification model, which would escape the traditional standards of a ranking and be an effective tool for learning, benchmarking and supporting the planning of public policies in cities. By means of an exploratory and descriptive study, along with 3 cities of different sizes of the state of São Paulo, research into quantitative and qualitative approaches were developed. The first one used close ended questionnaires and data collection based on specific indicators for the calculation of the components of the Brazilian Multidimensional Smart Cities Classification Index (IBMCCI). This final thesis product employs the same user-oriented approach as U-MULTIRANK, the multidimensional global ranking of European Community universities. The final version of the proposed model was made available for use by municipal managers with the freedom to select dimensions, indicators and equivalent municipalities for analysis. The qualitative approach of the research was conducted through semi-structured interviews, with 2 specialists in municipal management. In order to validate the built tool, the content validity technique was used. It has come to the conclusion that it is necessary to adjust some factors of the model and to adapt the periodicity of edition of the index to coincide with the calendar of the municipal elections. With these adaptations, the IBMCCI has demonstrated great potential to become an effective support tool for municipal public policy makers.

A lack of empirical evidence to understand neighborhood and residential development processes within neighborhoods has challenged urban planners’ ability to influence the course of future land development. The main objectives of this study were to examine neighborhood and residential development patterns and investigate dynamic processes in northwest Harris County, Texas, along the U.S. Highway 290 transportation corridor from 1945 to 2006. Researchers have identified different patterns of land development: leapfrog, contagion and infill development. However, because of the fuzziness in neighborhood and residential development patterns, the nominal classifications of development patterns are limited in their potential to characterize development patterns both on neighborhood and parcel levels; their applications for development processes and its impacts are even more limited. This study presents a quantitative approach for measuring development patterns by characterizing neighborhood development patterns as a function of spatial distance and temporal lapse time from the closest existing neighborhood to new neighborhood(s). The analysis in this study was based on disaggregated parcel data provided by the Harris County Appraisal District (HCAD) real estate and property records. The quantitative measures of neighborhood development patterns and processes within each pattern of neighborhood were derived by aggregating parcel level data into neighborhood level. This study developed the Long-term Trend of Development Model (LTDM) to classify neighborhood and residential development patterns based on spatial distance and temporal lapse time from existing neighborhoods to new neighborhood(s) each year to examine development processes. Regression analysis was used to identify the relationship between neighborhood patterns and residential development processes. This study found that development patterns can be measured quantitatively with spatial and temporal relationships between prior and new development at the neighborhood level. Empirical evidence supported the hypothesis that leapfrog neighborhood development triggers neighborhood development, contagion follows leapfrog neighborhood quickly, and infill follows contagion after a lapsed time. Residential development patterns in each pattern of neighborhood showed discrete development processes. Age of neighborhood can be used to predict development pressures and growth. In this process, physical and social infrastructure is involved, therefore, development process is best observed on the neighborhood level.

The principal aim of this study was to develop a classification model in disability sports. Using disability swimming as an example, methods of participant observation, interview, survey and document analysis were undertaken in three empirical studies to develop and clarify the classification model and three elements in swimming classification- (a) the classification process, (b) classifiers and (c) the classification system. First, the swimming classification process was identified as a social process. Members in the classification process socially interacted. The detailed classification process was described, interpreted and discussed. Several features in the classification process were identified. They included interaction among social actors, routinization, rules in the process, resources used by classifiers, power relations among social actors, allocation of rewards and sanctions in the classification process, and conflicts among social actors. Second, the role of classifiers as an agent of social control in disability swimming was examined. Resources used by medical and technical classifiers in the classification process to maintain their role and social order, and the socialization of classifiers in swimming were specifically explored. In addition, the important characteristics of swimming classifiers were identified in the study. Third, classification outcomes in disability swimming were monitored to evaluate the effectiveness of the classification system. Performance and impairment approaches were used in the study. Data of performances and types of impairment of Paralympic swimmers were analysed. The results revealed that the swimming classification system was generally fair but some classes needed to be fine-tuned. In this study elements of the classification model were clarified by integration of the results of the three empirical studies and the classification literature. It is suggested that researchers may use the concepts of the classification model for further investigationin disability sportc lassificationa nd disability sport committees may apply the model to systematicallye valuatet heir own classification systems, processes and classifiers.

我國自2000年土污法公布施行以來，至今(2012年)已逾12年，但綜觀環保署之國內場址列管情形統計資料可知，目前我國正面臨污染土地整治推動遲緩的問題。整理國內外相關文獻可知污染土地整治有其必要性，其原因在於如果污染土地持續閒置且不整治重新利用，不僅導致污染土地所造成的問題無法解決，另一方面也會使污染土地因整治而帶來的效益無從實現。而污染土地整治遲緩可能來自污染土地市場存在外部性難以內部化的情形，因此如何解決市場失靈之現象為其關鍵所在。 國外解決污染土地市場失靈的作法，主要分為「誘因給予」與「處罰」二大方式。本研究進一步將其概念透過問卷調查與實際訪談之方式，探討我國污染土地地主及承租人於整治污染土地實務上所面臨的困難，及對促進污染土地再利用相關作法之看法。 實證結果顯示，整治污染土地所面臨的最主要困難為整治經費過高、環境顧問公司市場混亂。於促進污染土地整治再利用的作法上，絕大多數地主及承租人偏好誘因給予方式，例如補助整治經費與減免相關稅負；相對地，較不贊成處罰方式，其原因在於增加財務負擔可能提高污染行為人放棄整治的風險，進而阻礙污染土地的整治再利用。此外，公開污染土地相關資訊供污染行為人參考、引進環境保險相關制度等作法，對未來污染土地整治之推行亦有極大助益。 從實證結果進一步歸納可知影響污染土地整治的因素包含「個別因素」與「總體因素」，並將其發展出一套污染土地分類模式。實際應用我國污染土地統計資料於該模式可知，放棄整治此類型的土地占我國污染土地總面積相當低之比例。因此，政府如能有效推動全面性基礎制度的建置，並搭配相關作法，我國在污染土地的整治推行上應能達到不錯之成效。 / It has been over 12 years since the announcement of Soil and Groundwater Act in year 2000 in Taiwan. However, statistics revealed by the Environmental Protection Administration suggests that the progress of remediation of contaminated land is far from satisfactory. A number of studies have pointed out that if contaminated land continues to be idle, not only can contamination not be solved, but also benefits resulting from remediation are lost. The market for contaminated land suffers from the external effects that in turn lead to a slow pace of remediation. Therefore, how to solve the problem of market failure is the key to promotion of reusing contaminated land. There are two major approaches to alleviating the problems of market failure for contaminated land; they are incentives and liabilities, respectively. In this study, we investigate into landowners and tenants of contaminated land through questionnaires and face-to-face interviews. We intend to discover the difficulties they have encountered in practice and also their views in respect of the approaches that might stimulate the reuse of contaminated land. Empirical results show that the primary difficulties on remediation are the excessive costs and dissatisfactory service of environmental consulting firms. Besides, among the alternative approaches that are expected to accelerate remediation, interviewees tend to prefer incentives over liabilities. They argue that if the government imposes liabilities upon landowners and tenants, their possibility of giving up remediation will be raised. Furthermore, supply of more complete information and introduction of environmental insurance are thought to be able to facilitate remediation in the future. Overall, the empirical evidence highlights a number of contributing factors to an effective remediation. To take a step further, we develop a model to classify the contaminated land in terms of their characteristics such as location, land values…etc. Application of this classification model to two cities suggests that contaminated land that needs direct governmental subsidy only accounts for a small proportion of the total contaminated areas. As a result, we urge the government to establish a platform to provide comprehensive and transparent information. This information platform shall be able to significantly improve the progress of remediation of contaminated land largely through the reinstatement of market mechanism.

A urbanização acentuada, fenômeno crescente das últimas décadas, tem atingido níveis elevadíssimos e criado enormes desafios para a gestão das cidades, além de trazer uma vasta gama de efeitos nefastos para a qualidade de vida de seus cidadãos. Dados da ONU de 2016, indicam tratar-se de um caminho sem volta, com uma tendência de agravamento nos próximos anos. Para tentar mitigar esta situação, muito se tem discutido em como aumentar o nível de inteligência das cidades e o interesse pelo tema Cidades Inteligentes tem crescido. Apesar disso, ainda não existe consenso sobre um conceito de cidade inteligente. Se há tempos este conceito se baseava exclusivamente no pilar da tecnologia, hoje uma visão mais evoluída e holística incorpora várias outras dimensões. Já a maioria dos modelos de classificação existentes são estrangeiros e não são aderentes à realidade de um país tão diverso e tão desigual quanto o Brasil. No âmbito nacional, existem algumas iniciativas de criação de conceitos e de modelos de classificação, mas, ou são baseados unicamente no componente tecnológico, ou buscam apenas a criação de rankings tradicionais baseados em ponderações arbitrárias de seus formuladores. A dificuldade de adequação do conceito e dos modelos de classificação à realidade brasileira foram os dois motores principais desta tese. O primeiro objetivo foi desenvolver um conceito de cidade inteligente para o contexto brasileiro. O segundo foi propor um modelo multidimensional de classificação, que fugisse aos padrões tradicionais de um ranking e fosse um instrumento efetivo de aprendizagem, benchmarking e de apoio ao planejamento de políticas públicas das cidades. Por meio de um estudo exploratório e descritivo, junto a 3 cidades de portes diferentes do estado de São Paulo, foram desenvolvidas pesquisas de abordagem quantitativa e qualitativa. A primeira utilizou questionários fechados e levantamento de dados em bases de indicadores específicos para o cálculo dos componentes do Índice Brasileiro Multidimensional de Classificação de Cidades Inteligentes - IBMCCI. Este produto final da tese emprega a mesma abordagem orientada ao usuário do U-MULTIRANK, o ranking multidimensional global de universidades da Comunidade Europeia. A versão final do modelo proposto foi disponibilizada para uso dos gestores municipais com a liberdade de seleção das dimensões, dos indicadores e dos municípios equivalentes para análise. A abordagem qualitativa da pesquisa foi conduzida por meio de entrevistas semiestruturadas, junto a 2 especialistas em gestão municipal. Para validar a ferramenta construída utilizou-se a técnica de validação de conteúdo. Chegou-se à conclusão que é necessário ajustar alguns fatores do modelo e adequar a periodicidade de edição do índice para coincidir com o calendário das eleições municipais. Com estas adequações, o IBMCCI demonstrou grande potencial de se tornar uma ferramenta efetiva de apoio para os formuladores de políticas públicas municipais. / The strong urbanization, a phenomenon that has increased in recent decades, has reached a very high level and has created enormous challenges for the management of cities, as well as bringing a wide range of harmful effects to the quality of life of its citizens. UN data of 2016 indicates that this is one-way road, and it\'s forecast to be worse in the coming years. Trying to mitigate this situation, much has been discussed about how to increase the smartness level of the cities and the interest in subject of Smart Cities has grown. Despite this, there is still no consensus on a smart city concept. If for some time this concept was based exclusively on the pillar of technology, today a more evolved and holistic vision would incorporate several other dimensions. Most of the existing classification models are foreign and are not adherent to the reality of a country as diverse and as unequal as Brazil. At the national level, there are some initiatives to create concepts and classification models, but they are based solely on the technological component or they only seek to create traditional rankings based on arbitrary weights of their formulators. The difficulty of adapting the concepts and the classification models to the Brazilian reality were the two main engines of this thesis. The first aim was to develop a concept of Smart cities for the Brazilian context. The second one was to propose a multidimensional classification model, which would escape the traditional standards of a ranking and be an effective tool for learning, benchmarking and supporting the planning of public policies in cities. By means of an exploratory and descriptive study, along with 3 cities of different sizes of the state of São Paulo, research into quantitative and qualitative approaches were developed. The first one used close ended questionnaires and data collection based on specific indicators for the calculation of the components of the Brazilian Multidimensional Smart Cities Classification Index (IBMCCI). This final thesis product employs the same user-oriented approach as U-MULTIRANK, the multidimensional global ranking of European Community universities. The final version of the proposed model was made available for use by municipal managers with the freedom to select dimensions, indicators and equivalent municipalities for analysis. The qualitative approach of the research was conducted through semi-structured interviews, with 2 specialists in municipal management. In order to validate the built tool, the content validity technique was used. It has come to the conclusion that it is necessary to adjust some factors of the model and to adapt the periodicity of edition of the index to coincide with the calendar of the municipal elections. With these adaptations, the IBMCCI has demonstrated great potential to become an effective support tool for municipal public policy makers.

<p><a>Internal ribosome entry sites (IRES) are segments of the mRNA found in untranslated regions, which can recruit the ribosome and initiate translation independently of the more widely used 5’ cap dependent translation initiation mechanism. IRES play an important role in conditions where has been 5’ cap dependent translation initiation blocked or repressed. They have been found to play important roles in viral infection, cellular apoptosis, and response to other external stimuli. It has been suggested that about 10% of mRNAs, both viral and cellular, can utilize IRES. But due to the limitations of IRES bicistronic assay, which is a gold standard for identifying IRES, relatively few IRES have been definitively described and functionally validated compared to the potential overall population. Viral and cellular IRES may be mechanistically different, but this is difficult to analyze because the mechanistic differences are still not very clearly defined. Identifying additional IRES is an important step towards better understanding IRES mechanisms. Development of a new bioinformatics tool that can accurately predict IRES from sequence would be a significant step forward in identifying IRES-based regulation, and in elucidating IRES mechanism. This dissertation systematically studies the features which can distinguish IRES from nonIRES sequences. Sequence features such as kmer words, and structural features such as predicted MFE of folding, Q_MFE, and sequence/structure triplets are evaluated as possible discriminative features. Those potential features incorporated into an IRES classifier based on XGBboost, a machine learning model, to classify novel sequences as belong to IRES or nonIRES groups. The XGBoost model performs better than previous predictors, with higher accuracy and lower computational time. The number of features in the model has been greatly reduced, compared to previous predictors, by adding global kmer and structural features. The trained XGBoost model has been implemented as the first high-throughput bioinformatics tool for IRES prediction, IRESpy. This website provides a public tool for all IRES researchers and can be used in other genomics applications such as gene annotation and analysis of differential gene expression.</a></p>

Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using 10-fold cross-validation for evaluation. These clustering and classification analyses strongly suggest that the regions surrounding the 3’end of genes contain sufficiently rich regulatory information to discriminate between over- and under-expressed genes; at least in the case of genes implicated in OC.

No description available.

A novel paper using Canada's real traffic accident data to propose a cost-prediction-based decision-making framework incorporating different ethical foundations for AVs. / Autonomous Vehicles (AVs) hold out the promise of being safer than manually driven cars. However, it is impossible to guarantee the hundred percent avoidance of collisions in a real-life environment with unpredictable objects and events. When accidents become unavoidable, the different reactions of AVs and their outcome will have different consequences. Thus, AVs should incorporate the so-called ‘ethical decision-making algorithm’ when facing unavoidable collisions. This paper is introducing a novel cost-prediction-based decision-making framework incorporating two common ethical foundations human drivers use when facing unavoidable dilemma inducing collisions: Ethical Egoism and Utilitarianism. The cost-prediction algorithm consists of Collision Injury Severity Level Prediction (CISLP) and Cost Evaluation. The CISLP model was trained using both Multinominal Logistic Regression (MLR) and a Decision Tree Classifier (DTC). Both algorithms consider the combination of relationships among traffic collision explanatory features. Four different Cost Evaluation metrics were purposed and compared to suit different application needs. The data set used for training and testing the cost prediction algorithm is the 1999-2017 National Collision Data Base (NCDB) which ensures the realistic and reliability of the algorithm. This paper is a novel paper using Canada's real traffic accident data to propose a cost-prediction-based decision-making framework incorporating different ethical foundations for AVs. / Thesis / Master of Applied Science (MASc)