Dynamic load-balancing for parallel adaptive unstructured meshes

A parallel method for dynamic partitioning of unstructured meshes is described. The method employs a new iterative optimisation technique which both balances the workload and attempts to minimise the interprocessor communications overhead. Experiments on a series of adaptively refined meshes indicate that the algorithm provides partitions of an equivalent or higher quality to static partitioners (which do not reuse the existing partition) and much more quickly. Perhaps more importantly, the algorithm results in only a small fraction of the amount of data migration compared to the static partitioners.

Parallel dynamic graph-partitioning for unstructured meshes

A parallel method for the dynamic partitioning of unstructured meshes is described. The method introduces a new iterative optimisation technique known as relative gain optimisation which both balances the workload and attempts to minimise the interprocessor communications overhead. Experiments on a series of adaptively refined meshes indicate that the algorithm provides partitions of an equivalent or higher quality to static partitioners (which do not reuse the existing partition) and much more rapidly. Perhaps more importantly, the algorithm results in only a small fraction of the amount of data migration compared to the static partitioners.

Contextual text mining

With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the author(s) of a biomedical publication, or implicit, such as the positive or negative sentiment that an author had when she wrote a product review; there may also be complex context such as the social network of the authors. Many applications require analysis of topic patterns over different contexts. For instance, analysis of search logs in the context of the user can reveal how we can improve the quality of a search engine by optimizing the search results according to particular users; analysis of customer reviews in the context of positive and negative sentiments can help the user summarize public opinions about a product; analysis of blogs or scientific publications in the context of a social network can facilitate discovery of more meaningful topical communities. Since context information significantly affects the choices of topics and language made by authors, in general, it is very important to incorporate it into analyzing and mining text data. In general, modeling the context in text, discovering contextual patterns of language units and topics from text, a general task which we refer to as Contextual Text Mining, has widespread applications in text mining. In this thesis, we provide a novel and systematic study of contextual text mining, which is a new paradigm of text mining treating context information as the ``first-class citizen.'' We formally define the problem of contextual text mining and its basic tasks, and propose a general framework for contextual text mining based on generative modeling of text. This conceptual framework provides general guidance on text mining problems with context information and can be instantiated into many real tasks, including the general problem of contextual topic analysis. We formally present a functional framework for contextual topic analysis, with a general contextual topic model and its various versions, which can effectively solve the text mining problems in a lot of real world applications. We further introduce general components of contextual topic analysis, by adding priors to contextual topic models to incorporate prior knowledge, regularizing contextual topic models with dependency structure of context, and postprocessing contextual patterns to extract refined patterns. The refinements on the general contextual topic model naturally lead to a variety of probabilistic models which incorporate different types of context and various assumptions and constraints. These special versions of the contextual topic model are proved effective in a variety of real applications involving topics and explicit contexts, implicit contexts, and complex contexts. We then introduce a postprocessing procedure for contextual patterns, by generating meaningful labels for multinomial context models. This method provides a general way to interpret text mining results for real users. By applying contextual text mining in the ``context'' of other text information management tasks, including ad hoc text retrieval and web search, we further prove the effectiveness of contextual text mining techniques in a quantitative way with large scale datasets. The framework of contextual text mining not only unifies many explorations of text analysis with context information, but also opens up many new possibilities for future research directions in text mining.

On the temperature dependence of the rate coefficient of formation of C2+ from C + CH+

[EN] We carry out quasi-classical trajectory caculations for theC + CH+ → C2+ + H reaction on an ad hoc computed high-level ab initio potential energy surface. Thermal rate coefficients at the temperatures of relevance in cold interstellar clouds are derived and compared with the assumed, temperature-independent estimates publicly available in kinetic databases KIDA and UDfA. For a temperature of 10 K the database value overestimates by a factor of two the one obtained by us (thus improperly enhancing the destruction route of CH+ in astrochemical kinetic models) which is seen to double in the temperature range 5–300 K with a sharp increase in the first 50 K. The computed values are fitted via the popular Arrhenius–Kooij formula and best-fitting parameters α = 1:32 X 10-9 cm3s-1, β = 0:10 and γ = 2:19 K to be included in the online mentioned databases are provided. Further investigation shows that the temperature dependence of the thermal rate coefficient better conforms to the recently proposed so-called ‘deformed Arrhenius’ law by Aquilanti and Mundim.

Sistemas de gerenciamento de bibliotecas: riscos decorrentes do processo de migração de dados

This work aims to analyze risks related to information technology (IT) in procedures related to data migration. This is done considering ALEPH, Integrated Libray System (ILS) that migrated data to the Library Module present in the software called Sistema Integrado de Gestão de Atividades Acadêmicas (SIGAA) at the Zila Mamede Central Library at the Federal University of Rio Grande do Norte (UFRN) in Natal/Brazil. The methodological procedure used was of a qualitative exploratory research with the realization of case study at the referred library in order to better understand this phenomenon. Data collection was able once there was use of a semi-structured interview that was applied with (11) subjects that are employed at the library as well as in the Technology Superintendence at UFRN. In order to examine data Content analysis as well as thematic review process was performed. After data migration the results of the interview were then linked to both analysis units and their system register with category correspondence. The main risks detected were: data destruction; data loss; data bank communication failure; user response delay; data inconsistency and duplicity. These elements point out implication and generate disorders that affect external and internal system users and lead to stress, work duplicity and hassles. Thus, some measures were taken related to risk management such as adequate planning, central management support, and pilot test simulations. For the advantages it has reduced of: risk, occurrence of problems and possible unforeseen costs, and allows achieving organizational objectives, among other. It is inferred therefore that the risks present in data bank conversion in libraries exist and some are predictable, however, it is seen that librarians do not know or ignore and are not very worried in the identification risks in data bank conversion, their acknowledge would minimize or even extinguish them. Another important aspect to consider is the existence of few empirical research that deal specifically with this subject and thus presenting the new of new approaches in order to promote better understanding of the matter in the corporate environment of the information units

Boreal forest fire impacts on lower troposphere carbon monoxide and ozone levels at the regional to hemispheric scales

Tropospheric ozone (O3) and carbon monoxide (CO) pollution in the Northern Hemisphere is commonly thought to be of anthropogenic origin. While this is true in most cases, copious quantities of pollutants are emitted by fires in boreal regions, and the impact of these fires on CO has been shown to significantly exceed the impact of urban and industrial sources during large fire years. The impact of boreal fires on ozone is still poorly quantified, and large uncertainties exist in the estimates of the fire-released nitrogen oxides (NO x ), a critical factor in ozone production. As boreal fire activity is predicted to increase in the future due to its strong dependence on weather conditions, it is necessary to understand how these fires affect atmospheric composition. To determine the scale of boreal fire impacts on ozone and its precursors, this work combined statistical analysis of ground-based measurements downwind of fires, satellite data analysis, transport modeling and the results of chemical model simulations. The first part of this work focused on determining boreal fire impact on ozone levels downwind of fires, using analysis of observations in several-days-old fire plumes intercepted at the Pico Mountain station (Azores). The results of this study revealed that fires significantly increase midlatitude summertime ozone background during high fire years, implying that predicted future increases in boreal wildfires may affect ozone levels over large regions in the Northern Hemisphere. To improve current estimates of NOx emissions from boreal fires, we further analyzed ΔNOy /ΔCO enhancement ratios in the observed fire plumes together with transport modeling of fire emission estimates. The results of this analysis revealed the presence of a considerable seasonal trend in the fire NOx /CO emission ratio due to the late-summer changes in burning properties. This finding implies that the constant NOx /CO emission ratio currently used in atmospheric modeling is unrealistic, and is likely to introduce a significant bias in the estimated ozone production. Finally, satellite observations were used to determine the impact of fires on atmospheric burdens of nitrogen dioxide (NO2 ) and formaldehyde (HCHO) in the North American boreal region. This analysis demonstrated that fires dominated the HCHO burden over the fires and in plumes up to two days old. This finding provides insights into the magnitude of secondary HCHO production and further enhances scientific understanding of the atmospheric impacts of boreal fires.

El legado de los flujos migratorios hacia la península de Crimea entre 1860 – 1991 en la crisis política de 2014

La presente investigación propone un análisis sobre la crisis política de Crimea en 2014 a partir del influjo que las migraciones desde Rusia han tenido en la historia reciente. Así, a partir de la evaluación de algunos de los momentos de inmigración más representativos en los últimos dos siglos (1860, 1928 y 1991) se vincula el proceso de construcción de la identidad de los inmigrantes -transversal en diferentes periodos históricos en Crimea- con el desarrollo de los eventos de 2014. Lo anterior permite identificar un cierto legado de la migración hacia Crimea en el desarrollo de la crisis, cuyo resultado principal ha sido la anexión de facto de Crimea a Rusia. Ésta no habría sido posible sin el particular ánimo de afinidad con la idea de Rusia –o Russianness- de la mayoría de los habitantes de la península, cuya presencia en la región se explica en parte, a través de los procesos migratorios antes descritos.

Lives apart? Experiences of transnational motherhood by Georgian labour migrants to Italy and their children

International labour migration processes of the last decades saw increasing numbers of solo female migrants employed in the developed countries. Many of these women were mothers who left their children in the sending countries and thus gave rise to a controversial phenomenon of transnational motherhood. The present thesis is based on the first empirical study of intergenerational narratives of mothers, Georgian labour migrants to Italy, and their children, left behind in Georgia. Mothers’ international labour migration is a challenge to the traditional ideology of motherhood. Although unconsciously migrant mothers often adhere to “alternative”, “rational”, future-oriented model(s) of parenting, they continue to live their experiences in the framework of traditional understandings of motherhood, which appears to be unequipped to “frame” transnational motherhood as, from its point of view, mothers’ choice to leave their children is reprehensible, yet transnational mothers’ physical absence is not an equivalent of “leaving” their children. Informants’ narratives strongly suggest that long periods of physical separation did not jeopardize bonds between mothers and children in transnational families. While informants’ selection bias is probable, the mother-child bond was not “broken” and the very essence of motherhood remained intact. Many forms of mothers’ and children’s online co-presence were documented during the interviews. Interviews also prove that the Internet cannot be considered a solution to the problem of family separation, experienced painfully by both mothers and children: it may reduce the pain caused by separation, but cannot be a substitute for mothers’ physical absence from their families. Despite the pain caused by separation, mothers’ emigration appeared to be the right decision made for the good of the family. Interviewed mothers almost univocally reported readiness to “keep going on”, and continue working in emigration to help their children until physically able to do so, because, as they put it, “motherhood never ends”.

The Assessment of Multiple Processes Underlying the Attentional Blink: A Fixed - links Modeling Approach based on Behavioral and Electrophysiological Data

When observers are presented with two visual targets appearing in the same position in close temporal proximity, a marked reduction in detection performance of the second target has often been reported, the so-called attentional blink phenomenon. Several studies found a similar decrement of P300 amplitudes during the attentional blink period as observed with detection performances of the second target. However, whether the parallel courses of second target performances and corresponding P300 amplitudes resulted from the same underlying mechanisms remained unclear. The aim of our study was therefore to investigate whether the mechanisms underlying the AB can be assessed by fixed-links modeling and whether this kind of assessment would reveal the same or at least related processes in the behavioral and electrophysiological data. On both levels of observation three highly similar processes could be identified: an increasing, a decreasing and a u-shaped trend. Corresponding processes from the behavioral and electrophysiological data were substantially correlated, with the two u-shaped trends showing the strongest association with each other. Our results provide evidence for the assumption that the same mechanisms underlie attentional blink task performance at the electrophysiological and behavioral levels as assessed by fixed-links models.

Scavenging processes of atmospheric particulate matter: a numerical modeling of case studies

Below cloud scavenging processes have been investigated considering a numerical simulation, local atmospheric conditions and particulate matter (PM) concentrations, at different sites in Germany. The below cloud scavenging model has been coupled with bulk particulate matter counter TSI (Trust Portacounter dataset, consisting of the variability prediction of the particulate air concentrations during chosen rain events. The TSI samples and meteorological parameters were obtained during three winter Campaigns: at Deuselbach, March 1994, consisting in three different events; Sylt, April 1994 and; Freiburg, March 1995. The results show a good agreement between modeled and observed air concentrations, emphasizing the quality of the conceptual model used in the below cloud scavenging numerical modeling. The results between modeled and observed data have also presented high square Pearson coefficient correlations over 0.7 and significant, except the Freiburg Campaign event. The differences between numerical simulations and observed dataset are explained by the wind direction changes and, perhaps, the absence of advection mass terms inside the modeling. These results validate previous works based on the same conceptual model.

Agile modeling data warehouse development

Most of the traditional software and database development approaches tend to be serial, not evolutionary and certainly not agile, especially on data-oriented aspects. Most of the more commonly used methodologies are strict, meaning they’re composed by several stages each with very specific associated tasks. A clear example is the Rational Unified Process (RUP), divided into Business Modeling, Requirements, Analysis & Design, Implementation, Testing and Deployment. But what happens when the needs of a well design and structured plan, meet the reality of a small starting company that aims to build an entire user experience solution. Here resource control and time productivity is vital, requirements are in constant change, and so is the product itself. In order to succeed in this environment a highly collaborative and evolutionary development approach is mandatory. The implications of constant changing requirements imply an iterative development process. Project focus is on Data Warehouse development and business modeling. This area is usually a tricky one. Business knowledge is part of the enterprise, how they work, their goals, what is relevant for analyses are internal business processes. Throughout this document it will be explained why Agile Modeling development was chosen. How an iterative and evolutionary methodology, allowed for reasonable planning and documentation while permitting development flexibility, from idea to product. More importantly how it was applied on the development of a Retail Focused Data Warehouse. A productized Data Warehouse built on the knowledge of not one but several client needs. One that aims not just to store usual business areas but create an innovative sets of business metrics by joining them with store environment analysis, converting Business Intelligence into Actionable Business Intelligence.

Quantifying rates of landscape evolution and tectonic processes by thermochronology and numerical modeling of crustal heat transport using PECUBE

PECUBE is a three-dimensional thermal-kinematic code capable of solving the heat production-diffusion-advection equation under a temporally varying surface boundary condition. It was initially developed to assess the effects of time-varying surface topography (relief) on low-temperature thermochronological datasets. Thermochronometric ages are predicted by tracking the time-temperature histories of rock-particles ending up at the surface and by combining these with various age-prediction models. In the decade since its inception, the PECUBE code has been under continuous development as its use became wider and addressed different tectonic-geomorphic problems. This paper describes several major recent improvements in the code, including its integration with an inverse-modeling package based on the Neighborhood Algorithm, the incorporation of fault-controlled kinematics, several different ways to address topographic and drainage change through time, the ability to predict subsurface (tunnel or borehole) data, prediction of detrital thermochronology data and a method to compare these with observations, and the coupling with landscape-evolution (or surface-process) models. Each new development is described together with one or several applications, so that the reader and potential user can clearly assess and make use of the capabilities of PECUBE. We end with describing some developments that are currently underway or should take place in the foreseeable future. (C) 2012 Elsevier B.V. All rights reserved.

GeoKernels: Modeling of Spatial Data on GeoManifolds

This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental data modeling on natural manifolds, such as complex topographies of the mountainous regions, where environmental processes are highly influenced by the relief. These relations, possibly regionalized and nonlinear, can be modeled from data with machine learning using the digital elevation models in semi-supervised kernel methods. The range of the tools and methodological issues discussed in the study includes feature selection and semisupervised Support Vector algorithms. The real case study devoted to data-driven modeling of meteorological fields illustrates the discussed approach.

Statistical analysis of survey-based event history data with application to modeling of unemployment duration

Longitudinal surveys are increasingly used to collect event history data on person-specific processes such as transitions between labour market states. Surveybased event history data pose a number of challenges for statistical analysis. These challenges include survey errors due to sampling, non-response, attrition and measurement. This study deals with non-response, attrition and measurement errors in event history data and the bias caused by them in event history analysis. The study also discusses some choices faced by a researcher using longitudinal survey data for event history analysis and demonstrates their effects. These choices include, whether a design-based or a model-based approach is taken, which subset of data to use and, if a design-based approach is taken, which weights to use. The study takes advantage of the possibility to use combined longitudinal survey register data. The Finnish subset of European Community Household Panel (FI ECHP) survey for waves 1–5 were linked at person-level with longitudinal register data. Unemployment spells were used as study variables of interest. Lastly, a simulation study was conducted in order to assess the statistical properties of the Inverse Probability of Censoring Weighting (IPCW) method in a survey data context. The study shows how combined longitudinal survey register data can be used to analyse and compare the non-response and attrition processes, test the missingness mechanism type and estimate the size of bias due to non-response and attrition. In our empirical analysis, initial non-response turned out to be a more important source of bias than attrition. Reported unemployment spells were subject to seam effects, omissions, and, to a lesser extent, overreporting. The use of proxy interviews tended to cause spell omissions. An often-ignored phenomenon classification error in reported spell outcomes, was also found in the data. Neither the Missing At Random (MAR) assumption about non-response and attrition mechanisms, nor the classical assumptions about measurement errors, turned out to be valid. Both measurement errors in spell durations and spell outcomes were found to cause bias in estimates from event history models. Low measurement accuracy affected the estimates of baseline hazard most. The design-based estimates based on data from respondents to all waves of interest and weighted by the last wave weights displayed the largest bias. Using all the available data, including the spells by attriters until the time of attrition, helped to reduce attrition bias. Lastly, the simulation study showed that the IPCW correction to design weights reduces bias due to dependent censoring in design-based Kaplan-Meier and Cox proportional hazard model estimators. The study discusses implications of the results for survey organisations collecting event history data, researchers using surveys for event history analysis, and researchers who develop methods to correct for non-sampling biases in event history data.

Modeling Adsorption Processes of Poly-p-phenylenevinylene Precursor and Sodium Acid Dodecylbenzenesulfonate onto Layer-by-Layer Films Using a Langmuir-type Metastable Equilibrium Model

The adsorption kinetics curves of poly(xylylidene tetrahydrothiophenium chloride) (PTHT), a poly-p-phenylenevinylene (PPV) precursor, and the sodium salt of dodecylbenzene sulfonic acid (DBS), onto (PTHT/DBS)(n) layer-by-layer (LBL) films were characterized by means of UV-vis spectroscopy. The amount of PTHT/DBS and PTHT adsorbed on each layer was shown to be practically independent of adsorption time. A Langmuir-type metastable equilibrium model was used to adjust the adsorption isotherms data and to estimate adsorption/desorption coefficients ratios, k = k(ads)/k(des), values of 2 x 10(5) and 4 x 10(6) for PTHT and PTHT/DBS layers, respectively. The desorption coefficient has been estimated, using literature values for poly(o-methoxyaniline) desorption coefficient, as was found to be in the range of 10(-9) to 10(-6) s(-1), indicating that quasi equilibrium is rapidly attained.