Clustering web documents using hierarchical representation with multi-granularity

Web document cluster analysis plays an important role in information retrieval by organizing large amounts of documents into a small number of meaningful clusters. Traditional web document clustering is based on the Vector Space Model (VSM), which takes into account only two-level (document and term) knowledge granularity but ignores the bridging paragraph granularity. However, this two-level granularity may lead to unsatisfactory clustering results with “false correlation”. In order to deal with the problem, a Hierarchical Representation Model with Multi-granularity (HRMM), which consists of five-layer representation of data and a twophase clustering process is proposed based on granular computing and article structure theory. To deal with the zero-valued similarity problemresulted from the sparse term-paragraphmatrix, an ontology based strategy and a tolerance-rough-set based strategy are introduced into HRMM. By using granular computing, structural knowledge hidden in documents can be more efficiently and effectively captured in HRMM and thus web document clusters with higher quality can be generated. Extensive experiments show that HRMM, HRMM with tolerancerough-set strategy, and HRMM with ontology all outperform VSM and a representative non VSM-based algorithm, WFP, significantly in terms of the F-Score.

Mathematical Model and Simulation of a Pneumatic Apparatus for In-Drilling Alignment of an Inertial Navigation Unit during Horizontal Well Drilling

Conventional methods in horizontal drilling processes incorporate magnetic surveying techniques for determining the position and orientation of the bottom-hole assembly (BHA). Such means result in an increased weight of the drilling assembly, higher cost due to the use of non-magnetic collars necessary for the shielding of the magnetometers, and significant errors in the position of the drilling bit. A fiber-optic gyroscope (FOG) based inertial navigation system (INS) has been proposed as an alternative to magnetometer -based downhole surveying. The utilizing of a tactical-grade FOG based surveying system in the harsh downhole environment has been shown to be theoretically feasible, yielding a significant BHA position error reduction (less than 100m over a 2-h experiment). To limit the growing errors of the INS, an in-drilling alignment (IDA) method for the INS has been proposed. This article aims at describing a simple, pneumatics-based design of the IDA apparatus and its implementation downhole. A mathematical model of the setup is developed and tested with Bloodshed Dev-C++. The simulations demonstrate a simple, low cost and feasible IDA apparatus.

The Conception of Creation of Integrated Development Environment for Computer Training Systems

The various questions of creation of integrated development environment for computer training systems are considered in the given paper. The information technologies that can be used for creation of the integrated development environment are described. The different didactic aspects of realization of such systems are analyzed. The ways to improve the efficiency and quality of learning process with computer training systems for distance education are pointed.

Application of Regularized Discriminant Analysis

2000 Mathematics Subject Classification: 62H30, 62P99

A spatiotemporal Data Envelopment Analysis (S-T DEA) approach:the need to assess evolving units

One of the major challenges in measuring efficiency in terms of resources and outcomes is the assessment of the evolution of units over time. Although Data Envelopment Analysis (DEA) has been applied for time series datasets, DEA models, by construction, form the reference set for inefficient units (lambda values) based on their distance from the efficient frontier, that is, in a spatial manner. However, when dealing with temporal datasets, the proximity in time between units should also be taken into account, since it reflects the structural resemblance among time periods of a unit that evolves. In this paper, we propose a two-stage spatiotemporal DEA approach, which captures both the spatial and temporal dimension through a multi-objective programming model. In the first stage, DEA is solved iteratively extracting for each unit only previous DMUs as peers in its reference set. In the second stage, the lambda values derived from the first stage are fed to a Multiobjective Mixed Integer Linear Programming model, which filters peers in the reference set based on weights assigned to the spatial and temporal dimension. The approach is demonstrated on a real-world example drawn from software development.

Text analytics of social media: Sentiment analysis, event detection and summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. ^ Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. ^ In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data. ^

Text Analytics of Social Media: Sentiment Analysis, Event Detection and Summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data.

Comparison of earthquake-related consequences through loss analysis of different braced frame structural systems

Il presente elaborato di tesi tratta la valutazione di differenti sistemi di controventatura, sia dal punto di vista di risposta ad un evento sismico che in termini di perdite economiche legate al danneggiamento delle varie componenti. Tra di esse è presentata anche una nuova tipologia strutturale, ideata per ridurre il comportamento “soft-story” e “weak-story”, tipico delle strutture controventate convenzionali. In questo caso, è integrata alla struttura una trave reticolare metallica, che funge da supporto verticale ed è progettata per rimanere in campo elastico. Tale sostegno garantisce una distribuzione più uniforme degli sforzi lungo l’intera altezza della struttura, anziché concentrarli in un unico piano. La ricerca tratta lo studio della fattibilità economica di questa nuova tecnologia, rispetto alle precedenti soluzioni di controventatura adottate, confrontando le perdite economiche delle diverse soluzioni, applicate ad un unico prototipo di edificio collocato a Berkeley, CA. L’analisi sismica tiene in considerazione di tre diversi livelli di intensità, riferiti a un periodo di ritorno di 50 anni, corrispondente alla vita dell’edificio: questi sono caratterizzati dalla probabilità di ricorrenza, rispettivamente del 2%, 10% e 50% ogni 50 anni. L’ambito di ricerca presentato è estremamente innovativo e di primario interesse per lo sviluppo di uno studio sulla resilienza, che può essere adattato anche in un modello di urbanizzazione futura.

Designing an adaptive salutogenic care environment

Humans are profoundly affected by the surroundings which they inhabit. Environmental psychologists have produced numerous credible theories describing optimal human environments, based on the concept of congruence or “fit” (1, 2). Lack of person/environment fit can lead to stress-related illness and lack of psychosocial well-being (3). Conversely, appropriately designed environments can promote wellness (4) or “salutogenesis” (5). Increasingly, research in the area of Evidence-Based Design, largely concentrated in the area of healthcare architecture, has tended to bear out these theories (6). Patients and long-term care residents, because of injury, illness or physical/ cognitive impairment, are less likely to be able to intervene to modify their immediate environment, unless this is designed specifically to facilitate their particular needs. In the context of care settings, detailed design of personal space therefore takes on enormous significance. MyRoom conceptualises a personalisable room, utilising sensoring and networked computing to enable the environment to respond directly and continuously to the occupant. Bio-signals collected and relayed to the system will actuate application(s) intended to positively influence user well-being. Drawing on the evidence base in relation to therapeutic design interventions (7), real-time changes in ambient lighting, colour, image, etc. respond continuously to the user’s physiological state, optimising congruence. Based on research evidence, consideration is also given to development of an application which uses natural images (8). It is envisaged that actuation will require machine-learning based on interpretation of data gathered by sensors; sensoring arrangements may vary depending on context and end-user. Such interventions aim to reduce inappropriate stress/ provide stimulation, supporting both instrumental and cognitive tasks.

The Effects of Brominated Flame Retardants on Thyroid Hormone Homeostasis in Human Placenta Tissues and Cell Culture

Polybrominated diphenyl ethers (PBDEs) are a class of brominated flame retardants (BFRs) that have been heavily used in consumer products such as furniture foams, plastics, and textiles since the mid-1970’s. BFRs are added to products in order to meet state flammability standards intended to increase indoor safety in the event of a fire. The three commercial PBDE mixtures, Penta-, Octa-, and DecaBDE, have all been banned in the United States, however, limited use of DecaBDE is still permitted. PBDEs were phased out of production and added to the Stockholm Convention due to concerns over their environmental persistence and toxicity. Human exposure to PBDEs occurs primarily through the inadvertent ingestion of contaminated house dust, as well as though dietary sources. Despite the phase-out and discontinued use of PBDEs, human exposure to this class of chemicals is likely to continue for decades due to the continued use of treated products and existing environmental reservoirs of PBDEs. Extensive research over the years has shown that PBDEs disrupt thyroid hormone (TH) levels and neurodevelopmental endpoints in rodent and fish models. Additionally, there is growing epidemiological evidence linking PBDE exposure in humans to altered TH homeostasis and neurodevelopmental impairments in children. Due to the importance of THs throughout gestation, there is a great need to understand the effects of BFRs on the developing fetus. Specifically, the placenta plays a critical role in the transport, metabolism, and delivery of THs to the fetal compartment during pregnancy and is a likely target for BFR bioaccumulation and endocrine disruption. The central hypothesis of this dissertation research is that BFRs disrupt the activity of TH sulfotransferase (SULT) enzymes, thereby altering TH concentrations in the placenta.

In the first aim of this dissertation research, the concentrations of PBDEs and 2,4,6-TBP were measured in a cohort of 102 placenta tissue samples from an ongoing pregnancy cohort in Durham, NC. Methods were developed for the extraction and analysis of the BFR analytes. It was found that 2,4,6-TBP was significantly correlated with all PBDE analytes, indicating that 2,4,6-TBP may share common product applications with PBDEs or that 2,4,6-TBP is a metabolite of PBDE compounds. Additionally, this was the first study to measure 2,4,6-TBP in human placenta tissues.

In the second aim of this dissertation research, the placenta tissue concentrations of THs, as well as the endogenous activity of deiodinase (DI) and TH SULT enzymes were quantified using the same cohort of 102 placenta tissue samples. Enzyme activity was detected in all samples and this was the first study to measure TH DI and SULT activity in human placenta tissues. Enzyme activities and TH concentrations were compared with BFR concentrations measured in Aim 1. There were few statistically significant associations observed for the combined data, however, upon stratifying the data set based on infant sex, additional significant associations were observed. For example, among males, those with the highest concentrations of BDE-99 in placenta had T3 levels 0.80 times those with the lowest concentration of BDE-99 (95% confidence interval (CI): 0.59, 1.07). Whereas females with the highest concentrations of BDE-99 in placenta had T3 levels 1.50 times those with the lowest concentration of BDE-99 (95% CI: 1.10, 2.04). Additionally, all BFR analyte concentrations were higher in the placenta of males versus females and they were significantly higher for 2,4,6-TBP and BDE-209. 3,3’-T2 SULT activity was significantly higher in female placenta tissues, while type 3 DI activity was significantly higher in male placenta tissues. This research is the first to show sex-specific differences in the bioaccumulation of BFRs in human placenta tissue, as well as differences in TH concentrations and endogenous DI and SULT activity. The underlying mechanisms of these observed sex differences warrant further investigation.

In the third aim of this dissertation research, the effects of BFRs were examined in a human choriocarcinoma placenta cell line, BeWo. Michaelis-Menten parameters and inhibition curves were calculated for 2,4,6-TBP, 3-OH BDE-47, and 6-OH BDE-47. 2,4,6-TBP was shown to be the most potent inhibitor of 3,3’-T2 SULT activity with a calculated IC50 value of 11.6 nM. It was also shown that 2,4,6-TBP and 3-OH BDE-47 exhibit mixed inhibition of 3,3’-T2 sulfation in BeWo cell homogenates. Next, a series of cell culture exposure experiments were performed using 1, 6, 12, and 24 hour exposure durations. Once again, 2,4,6-TBP was shown to be the most potent inhibitor of basal 3,3’-T2 SULT activity by significantly decreasing activity at the high and medium dose (1 M and 0.5 M, respectively) at all measured time points. Interestingly, BDE-99 was also shown to inhibit basal 3,3’-T2 SULT activity in BeWo cells following the 24 hour exposure, despite exhibiting no inhibitory effects in the BeWo cell homogenate experiments. This indicates that BDE-99 must act through a pathway other than direct enzyme inhibition. Following exposures, the TH concentrations in the cell culture growth media and mRNA expression of TH-related genes were also examined. There was no observed effect of BFR treatment on these endpoints. Future work should focus on determining the downstream biological effects of TH SULT disruption in placental cells, as well as the underlying mechanisms of action responsible for reductions in basal TH SULT activity following BFR exposure.

This was one of the first studies to measure BFRs in a cohort of placenta tissue samples from the United States and the first study to measure THs, DI activity, and SULT activity in human placenta tissues. This research provides a novel contribution to our growing understanding of the effects of BFRs on TH homeostasis within the human placenta, and provides further evidence for sex-specific differences within this important organ. Future research should continue to investigate the effects of environmental contaminants on TH homeostasis within the placenta, as this represents the most critical and vulnerable stage of human development.

Linking Parametric CAD with Adjoint Surface Sensitivities

The goal of this work is to present an efficient CAD-based adjoint process chain for calculating parametric sensitivities (derivatives of the objective function with respect to the CAD parameters) in timescales acceptable for industrial design processes. The idea is based on linking parametric design velocities (geometric sensitivities computed from the CAD model) with adjoint surface sensitivities. A CAD-based design velocity computation method has been implemented based on distances between discrete representations of perturbed geometries. This approach differs from other methods due to the fact that it works with existing commercial CAD packages (unlike most analytical approaches) and it can cope with the changes in CAD model topology and face labeling. Use of the proposed method allows computation of parametric sensitivities using adjoint data at a computational cost which scales with the number of objective functions being considered, while it is essentially independent of the number of design variables. The gradient computation is demonstrated on test cases for a Nozzle Guide Vane (NGV) model and a Turbine Rotor Blade model. The results are validated against finite difference values and good agreement is shown. This gradient information can be passed to an optimization algorithm, which will use it to update the CAD model parameters.

Aerodynamic optimization using Adjoint methods and parametric CAD models

This paper describes an implementation of a method capable of integrating parametric, feature based, CAD models based on commercial software (CATIA) with the SU2 software framework. To exploit the adjoint based methods for aerodynamic optimisation within the SU2, a formulation to obtain geometric sensitivities directly from the commercial CAD parameterisation is introduced, enabling the calculation of gradients with respect to CAD based design variables. To assess the accuracy and efficiency of the alternative approach, two aerodynamic optimisation problems are investigated: an inviscid, 3D, problem with multiple constraints, and a 2D high-lift aerofoil, viscous problem without any constraints. Initial results show the new parameterisation obtaining reliable optimums, with similar levels of performance of the software native parameterisations. In the final paper, details of computing CAD sensitivities will be provided, including accuracy as well as linking geometric sensitivities to aerodynamic objective functions and constraints; the impact in the robustness of the overall method will be assessed and alternative parameterisations will be included.

Simulation als Methode zur Konzipierung vernetzter, getakteter Montagesysteme für variantenreiche Produkte

Die Montage von Produkten in getakteten Fließstraßen als Alternative zu ortsfesten Varianten führt in der Regel zur Verbesserung der logistischen Zielerfüllung. Das volle Potential dieser Organisationsart wird jedoch weitgehend nur für standardisierte Produkte mit hohen Stückzahlen erschlossen. Hindernisse zur Produktion variantenreicher Großerzeugnisse mit volatilen Arbeitsinhalten in einer Fließstraße bestehen vor allem in der Beherrschung der Komplexität in Bezug auf dazu erforderliche flexible Arbeitszeitmodelle, optimierte Produktreihenfolgen sowie operative Taktzeitvariationen. Sollen mehrere Fließstraßen mit differenzierten Produktionsparametern gekoppelt werden, steigt der Anspruch noch einmal erheblich. Bei der Konzipierung und Erprobung geeigneter Organisationsmodelle auf Basis diverser Produktionsszenarien kann auf den Einsatz der Simulationstechnik nicht verzichtet werden.

Representing Variability in Software Architecture

Software Architecture is a high level description of a software intensive system that enables architects to have a better intellectual control over the complete system. It is also used as a communication vehicle among the various system stakeholders. Variability in software-intensive systems is the ability of a software artefact (e.g., a system, subsystem, or component) to be extended, customised, or configured for deployment in a specific context. Although variability in software architecture is recognised as a challenge in multiple domains, there has been no formal consensus on how variability should be captured or represented. In this research, we addressed the problem of representing variability in software architecture through a three phase approach. First, we examined existing literature using the Systematic Literature Review (SLR) methodology, which helped us identify the gaps and challenges within the current body of knowledge. Equipped with the findings from the SLR, a set of design principles have been formulated that are used to introduce variability management capabilities to an existing Architecture Description Language (ADL). The chosen ADL was developed within our research group (ALI) and to which we have had complete access. Finally, we evaluated the new version of the ADL produced using two distinct case studies: one from the Information Systems domain, an Asset Management System (AMS); and another from the embedded systems domain, a Wheel Brake System (WBS). This thesis presents the main findings from the three phases of the research work, including a comprehensive study of the state-of-the-art; the complete specification of an ADL that is focused on managing variability; and the lessons learnt from the evaluation work of two distinct real-life case studies.