Synthesizing Population for Travel Activity Analysis

Population synthesis is a fundamental procedure for individual-based modeling in transportation research. The population synthesis generates anonymized individuals with selected social-demographic variables that have similar statistical distributions as that of the samples from the real population. Previous studies on population synthesis focused on generating general-purpose population by fitting the joint distributions of multiple variables to their sampled distributions. In addition to fitting the joint distributions, this study focuses on generating population for travel activity analysis by considering individuals’ travel activity patterns and associated social, economic, and demographic characteristics. A person’s daily movement is a time-sequence of activities connected by travel behaviors. It can be described as vectors that include important transportation attributes such as travel distance, travel mode, activity type, activity time, and activity sequence. A multidimensional pattern vector method is used in this study to represent an individual’s daily travel activities. This method is based on the combination of time-geography, sequence alignment, and pattern vector. Using the 2001 and 2009 National Household Travel Survey (NHTS), the travel distance and activity sequence of individuals are normalized, compared, and integrated into a dissimilarity matrix. Major travel activity patterns are then examined by cluster analysis. The random forest model is applied to examine the prominent socio-demographic characteristics that correlate to the activity patterns. The prominent socio-demographic characteristics are then used to synthesize population microdata. Since the algorithm complexity of population synthesis grows exponentially with the number of attributes, the methodology used in this study can effectively reduce the computational intensity by focusing on the most important variables for travel activity analysis. This study also addresses another issue in traditional population synthesis algorithms, i.e., the probability distributions at the individual and household levels cannot be fitted simultaneously. In this study, Iterative Proportional Fitting (IPF) algorithm is used to consider the distributions at different scales and to generate synthetic population microdata with the prominent socio-demographic characteristics. The performance of the algorithm that generates synthesized population is evaluated by scatter plot and Normalized Root Mean Square Error (NRMSE) analysis. In addition, the distributions of socio-demographic attributes in the synthesized data are compared with that of variables in the observed sample dataset. The verification result indicates that the new method can produce a better population microdata. This dissertation describes how to generate a synthetic population for Milwaukee County, WI with prominent socio-demographic variables for travel activity analysis. By critically selecting the prominent socio-demographic factors, the computational intensity of population synthesis is reduced. It is also found that, by aggregating the IPF-generated weights of individuals and using them to the household level, the overall goodness-of-fit can be managed at a reasonable level and the distributions of socio-demographic factors at the individual and household levels can be fitted

Evolutionary genomics : statistical and computational methods

This open access book addresses the challenge of analyzing and understanding the evolutionary dynamics of complex biological systems at the genomic level, and elaborates on some promising strategies that would bring us closer to uncovering of the vital relationships between genotype and phenotype. After a few educational primers, the book continues with sections on sequence homology and alignment, phylogenetic methods to study genome evolution, methodologies for evaluating selective pressures on genomic sequences as well as genomic evolution in light of protein domain architecture and transposable elements, population genomics and other omics, and discussions of current bottlenecks in handling and analyzing genomic data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice that lead to the best results. Authoritative and comprehensive, Evolutionary Genomics: Statistical and Computational Methods, Second Edition aims to serve both novices in biology with strong statistics and computational skills, and molecular biologists with a good grasp of standard mathematical concepts, in moving this important field of study forward

Measuring and predicting adaptation in multidimensional activity-travel patterns

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Biology Education Research. Contemporary topics and directions

This volume consists of 29 original papers presented at the 12th Conference of European Researchers in Didactics of Biology (ERIDOB) organized by the University of Zaragoza in collaboration with University de Santiago de Compostela, hosted in July 2018 by the Faculty of Education, University of Zaragoza, Spain. Recognizing the importance and potential of being well-trained in biology, the bi-annual Conference of ERIDOB is now a firmly established and leading forum for European and non-European researchers to discuss and reflect on research in biology education, to find new ways of ensuring continued advances in teaching and learning this discipline. Biology is a field of research in constant growth. Its advances have brought not only enormous benefits to humanity in fields from Human Biology to Ecology, but also great repercussions in our daily lives. This context makes it necessary for biology education to equip young people with the tools and resources needed to become scientifically literate, critical thinkers and social activists. Some of these concerns are highlighted in this book, whose 29 papers have been selected after having passed a double blind review process by at least one member of the ERIDOB Academic Committee together with an experienced reviewer of the ERIDOB academic community. In the introduction of this volume the keynote conference, How to gather and analyse quality evidence about successful biology classrooms, presented by María Pilar Jiménez Aleixandre, methodological issues related to classroom studies are addressed. Special attention is on qualitative research studies and on successful biology teaching and learning with a double goal: 1) debriefing the processes leading to quality research studies; 2) providing teachers with models, rather than focusing on the problems of unsuccessful teaching