A computational model of intonation for yorùbá text-to-speech synthesis:design and analysis

In this paper we present the design and analysis of an intonation model for text-to-speech (TTS) synthesis applications using a combination of Relational Tree (RT) and Fuzzy Logic (FL) technologies. The model is demonstrated using the Standard Yorùbá (SY) language. In the proposed intonation model, phonological information extracted from text is converted into an RT. RT is a sophisticated data structure that represents the peaks and valleys as well as the spatial structure of a waveform symbolically in the form of trees. An initial approximation to the RT, called Skeletal Tree (ST), is first generated algorithmically. The exact numerical values of the peaks and valleys on the ST is then computed using FL. Quantitative analysis of the result gives RMSE of 0.56 and 0.71 for peak and valley respectively. Mean Opinion Scores (MOS) of 9.5 and 6.8, on a scale of 1 - -10, was obtained for intelligibility and naturalness respectively.

Computational model of bladder tissue based on its measured optical properties

Urinary bladder diseases are a common problem throughout the world and often difficult to accurately diagnose. Furthermore, they pose a heavy financial burden on health services. Urinary bladder tissue from male pigs was spectrophotometrically measured and the resulting data used to calculate the absorption, transmission, and reflectance parameters, along with the derived coefficients of scattering and absorption. These were employed to create a "generic" computational bladder model based on optical properties, simulating the propagation of photons through the tissue at different wavelengths. Using the Monte-Carlo method and fluorescence spectra of UV and blue excited wavelength, diagnostically important biomarkers were modeled. Additionally, the multifunctional noninvasive diagnostics system "LAKK-M" was used to gather fluorescence data to further provide essential comparisons. The ultimate goal of the study was to successfully simulate the effects of varying excited radiation wavelengths on bladder tissue to determine the effectiveness of photonics diagnostic devices. With increased accuracy, this model could be used to reliably aid in differentiating healthy and pathological tissues within the bladder and potentially other hollow organs.

Production of Referring Expressions for an Unknown Audience : a Computational Model of Communal Common Ground

The research reported in this article is based on the Ph.D. project of Dr. RK, which was funded by the Scottish Informatics and Computer Science Alliance (SICSA). KvD acknowledges support from the EPSRC under the RefNet grant (EP/J019615/1).

A NATURALISTIC COMPUTATIONAL MODEL OF HUMAN BEHAVIOR IN NAVIGATION AND SEARCH TASKS

Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.

A computational model of hydrogen production by steam reforming of dimethyl ether in a large scale CFB reactor. Part II:parametric analysis

This study presents a computational parametric analysis of DME steam reforming in a large scale Circulating Fluidized Bed (CFB) reactor. The Computational Fluid Dynamic (CFD) model used, which is based on Eulerian-Eulerian dispersed flow, has been developed and validated in Part I of this study [1]. The effect of the reactor inlet configuration, gas residence time, inlet temperature and steam to DME ratio on the overall reactor performance and products have all been investigated. The results have shown that the use of double sided solid feeding system remarkable improvement in the flow uniformity, but with limited effect on the reactions and products. The temperature has been found to play a dominant role in increasing the DME conversion and the hydrogen yield. According to the parametric analysis, it is recommended to run the CFB reactor at around 300 °C inlet temperature, 5.5 steam to DME molar ratio, 4 s gas residence time and 37,104 ml gcat -1 h-1 space velocity. At these conditions, the DME conversion and hydrogen molar concentration in the product gas were both found to be around 80%.

Systems biology of plants : from intraspecific genome variation to computational morphodynamics

Recently, the introduction of second generation sequencing and further advance-ments in confocal microscopy have enabled system-level studies for the functional characterization of genes. The degree of complexity intrinsic to these approaches needs the development of bioinformatics methodologies and computational models for extracting meaningful biological knowledge from the enormous amount of experi¬mental data which is continuously generated. This PhD thesis presents several novel bioinformatics methods and computational models to address specific biological questions in Plant Biology by using the plant Arabidopsis thaliana as a model system. First, a spatio-temporal qualitative analysis of quantitative transcript and protein profiles is applied to show the role of the BREVIS RADIX (BRX) protein in the auxin- cytokinin crosstalk for root meristem growth. Core of this PhD work is the functional characterization of the interplay between the BRX protein and the plant hormone auxin in the root meristem by using a computational model based on experimental evidence. Hyphotesis generated by the modelled to the discovery of a differential endocytosis pattern in the root meristem that splits the auxin transcriptional response via the plasma membrane to nucleus partitioning of BRX. This positional information system creates an auxin transcriptional pattern that deviates from the canonical auxin response and is necessary to sustain the expression of a subset of BRX-dependent auxin-responsive genes to drive root meristem growth. In the second part of this PhD thesis, we characterized the genome-wide impact of large scale deletions on four divergent Arabidopsis natural strains, through the integration of Ultra-High Throughput Sequencing data with data from genomic hybridizations on tiling arrays. Analysis of the identified deletions revealed a considerable portion of protein coding genes affected and supported a history of genomic rearrangements shaped by evolution. In the last part of the thesis, we showed that VIP3 gene in Arabidopsis has an evo-lutionary conserved role in the 3' to 5' mRNA degradation machinery, by applying a novel approach for the analysis of mRNA-Seq data from random-primed mRNA. Altogether, this PhD research contains major advancements in the study of natural genomic variation in plants and in the application of computational morphodynamics models for the functional characterization of biological pathways essential for the plant. - Récemment, l'introduction du séquençage de seconde génération et les avancées dans la microscopie confocale ont permis des études à l'échelle des différents systèmes cellulaires pour la caractérisation fonctionnelle de gènes. Le degrés de complexité intrinsèque à ces approches ont requis le développement de méthodologies bioinformatiques et de modèles mathématiques afin d'extraire de la masse de données expérimentale générée, des information biologiques significatives. Ce doctorat présente à la fois des méthodes bioinformatiques originales et des modèles mathématiques pour répondre à certaines questions spécifiques de Biologie Végétale en utilisant la plante Arabidopsis thaliana comme modèle. Premièrement, une analyse qualitative spatio-temporelle de profiles quantitatifs de transcripts et de protéines est utilisée pour montrer le rôle de la protéine BREVIS RADIX (BRX) dans le dialogue entre l'auxine et les cytokinines, des phytohormones, dans la croissance du méristème racinaire. Le noyau de ce travail de thèse est la caractérisation fonctionnelle de l'interaction entre la protéine BRX et la phytohormone auxine dans le méristème de la racine en utilisant des modèles informatiques basés sur des preuves expérimentales. Les hypothèses produites par le modèle ont mené à la découverte d'un schéma différentiel d'endocytose dans le méristème racinaire qui divise la réponse transcriptionnelle à l'auxine par le partitionnement de BRX de la membrane plasmique au noyau de la cellule. Cette information positionnelle crée une réponse transcriptionnelle à l'auxine qui dévie de la réponse canonique à l'auxine et est nécessaire pour soutenir l'expression d'un sous ensemble de gènes répondant à l'auxine et dépendant de BRX pour conduire la croissance du méristème. Dans la seconde partie de cette thèse de doctorat, nous avons caractérisé l'impact sur l'ensemble du génome des délétions à grande échelle sur quatre souches divergentes naturelles d'Arabidopsis, à travers l'intégration du séquençage à ultra-haut-débit avec l'hybridation génomique sur puces ADN. L'analyse des délétions identifiées a révélé qu'une proportion considérable de gènes codant était affectée, supportant l'idée d'un historique de réarrangement génomique modelé durant l'évolution. Dans la dernière partie de cette thèse, nous avons montré que le gène VÏP3 dans Arabidopsis a conservé un rôle évolutif dans la machinerie de dégradation des ARNm dans le sens 3' à 5', en appliquant une nouvelle approche pour l'analyse des données de séquençage d'ARNm issue de transcripts amplifiés aléatoirement. Dans son ensemble, cette recherche de doctorat contient des avancées majeures dans l'étude des variations génomiques naturelles des plantes et dans l'application de modèles morphodynamiques informatiques pour la caractérisation de réseaux biologiques essentiels à la plante. - Le développement des plantes est écrit dans leurs codes génétiques. Pour comprendre comment les plantes sont capables de s'adapter aux changements environnementaux, il est essentiel d'étudier comment leurs gènes gouvernent leur formation. Plus nous essayons de comprendre le fonctionnement d'une plante, plus nous réalisons la complexité des mécanismes biologiques, à tel point que l'utilisation d'outils et de modèles mathématiques devient indispensable. Dans ce travail, avec l'utilisation de la plante modèle Arabidopsis thalicinci nous avons résolu des problèmes biologiques spécifiques à travers le développement et l'application de méthodes informatiques concrètes. Dans un premier temps, nous avons investigué comment le gène BREVIS RADIX (BRX) régule le développement de la racine en contrôlant la réponse à deux hormones : l'auxine et la cytokinine. Nous avons employé une analyse statistique sur des mesures quantitatives de transcripts et de produits de gènes afin de démontrer que BRX joue un rôle antagonisant dans le dialogue entre ces deux hormones. Lorsque ce-dialogue moléculaire est perturbé, la racine primaire voit sa longueur dramatiquement réduite. Pour comprendre comment BRX répond à l'auxine, nous avons développé un modèle informatique basé sur des résultats expérimentaux. Les simulations successives ont mené à la découverte d'un signal positionnel qui contrôle la réponse de la racine à l'auxine par la régulation du mouvement intracellulaire de BRX. Dans la seconde partie de cette thèse, nous avons analysé le génome entier de quatre souches naturelles d'Arabidopsis et nous avons trouvé qu'une grande partie de leurs gènes étaient manquant par rapport à la souche de référence. Ce résultat indique que l'historique des modifications génomiques conduites par l'évolution détermine une disponibilité différentielle des gènes fonctionnels dans ces plantes. Dans la dernière partie de ce travail, nous avons analysé les données du transcriptome de la plante où le gène VIP3 était non fonctionnel. Ceci nous a permis de découvrir le rôle double de VIP3 dans la régulation de l'initiation de la transcription et dans la dégradation des transcripts. Ce rôle double n'avait jusqu'alors été démontrée que chez l'homme. Ce travail de doctorat supporte le développement et l'application de méthodologies informatiques comme outils inestimables pour résoudre la complexité des problèmes biologiques dans la recherche végétale. L'intégration de la biologie végétale et l'informatique est devenue de plus en plus importante pour l'avancée de nos connaissances sur le fonctionnement et le développement des plantes.

Computational modeling of resting-state activity demonstrates markers of normalcy in children with prenatal or perinatal stroke.

Children who sustain a prenatal or perinatal brain injury in the form of a stroke develop remarkably normal cognitive functions in certain areas, with a particular strength in language skills. A dominant explanation for this is that brain regions from the contralesional hemisphere "take over" their functions, whereas the damaged areas and other ipsilesional regions play much less of a role. However, it is difficult to tease apart whether changes in neural activity after early brain injury are due to damage caused by the lesion or by processes related to postinjury reorganization. We sought to differentiate between these two causes by investigating the functional connectivity (FC) of brain areas during the resting state in human children with early brain injury using a computational model. We simulated a large-scale network consisting of realistic models of local brain areas coupled through anatomical connectivity information of healthy and injured participants. We then compared the resulting simulated FC values of healthy and injured participants with the empirical ones. We found that the empirical connectivity values, especially of the damaged areas, correlated better with simulated values of a healthy brain than those of an injured brain. This result indicates that the structural damage caused by an early brain injury is unlikely to have an adverse and sustained impact on the functional connections, albeit during the resting state, of damaged areas. Therefore, these areas could continue to play a role in the development of near-normal function in certain domains such as language in these children.

Model based analysis of the post-combustion calcium looping process for carbon dioxide capture

This thesis presents a one-dimensional, semi-empirical dynamic model for the simulation and analysis of a calcium looping process for post-combustion CO2 capture. Reduction of greenhouse emissions from fossil fuel power production requires rapid actions including the development of efficient carbon capture and sequestration technologies. The development of new carbon capture technologies can be expedited by using modelling tools. Techno-economical evaluation of new capture processes can be done quickly and cost-effectively with computational models before building expensive pilot plants. Post-combustion calcium looping is a developing carbon capture process which utilizes fluidized bed technology with lime as a sorbent. The main objective of this work was to analyse the technological feasibility of the calcium looping process at different scales with a computational model. A one-dimensional dynamic model was applied to the calcium looping process, simulating the behaviour of the interconnected circulating fluidized bed reactors. The model incorporates fundamental mass and energy balance solvers to semi-empirical models describing solid behaviour in a circulating fluidized bed and chemical reactions occurring in the calcium loop. In addition, fluidized bed combustion, heat transfer and core-wall layer effects were modelled. The calcium looping model framework was successfully applied to a 30 kWth laboratory scale and a pilot scale unit 1.7 MWth and used to design a conceptual 250 MWth industrial scale unit. Valuable information was gathered from the behaviour of a small scale laboratory device. In addition, the interconnected behaviour of pilot plant reactors and the effect of solid fluidization on the thermal and carbon dioxide balances of the system were analysed. The scale-up study provided practical information on the thermal design of an industrial sized unit, selection of particle size and operability in different load scenarios.

Implementation of Quantitative Reaction-based Model Refinement

Building a computational model for complex biological systems is an iterative process. It starts from an abstraction of the process and then incorporates more details regarding the specific biochemical reactions which results in the change of the model fit. Meanwhile, the model’s numerical properties such as its numerical fit and validation should be preserved. However, refitting the model after each refinement iteration is computationally expensive resource-wise. There is an alternative approach which ensures the model fit preservation without the need to refit the model after each refinement iteration. And this approach is known as quantitative model refinement. The aim of this thesis is to develop and implement a tool called ModelRef which does the quantitative model refinement automatically. It is both implemented as a stand-alone Java application and as one of Anduril framework components. ModelRef performs data refinement of a model and generates the results in two different well known formats (SBML and CPS formats). The development of this tool successfully reduces the time and resource needed and the errors generated as well by traditional reiteration of the whole model to perform the fitting procedure.

A Comparative Study of Convective Parameterization Schemes in WRF-NMM Model

Severe local storms, including tornadoes, damaging hail and wind gusts, frequently occur over the eastern and northeastern states of India during the pre-monsoon season (March-May). Forecasting thunderstorms is one of the most difficult tasks in weather prediction, due to their rather small spatial and temporal extension and the inherent non-linearity of their dynamics and physics. In this paper, sensitivity experiments are conducted with the WRF-NMM model to test the impact of convective parameterization schemes on simulating severe thunderstorms that occurred over Kolkata on 20 May 2006 and 21 May 2007 and validated the model results with observation. In addition, a simulation without convective parameterization scheme was performed for each case to determine if the model could simulate the convection explicitly. A statistical analysis based on mean absolute error, root mean square error and correlation coefficient is performed for comparisons between the simulated and observed data with different convective schemes. This study shows that the prediction of thunderstorm affected parameters is sensitive to convective schemes. The Grell-Devenyi cloud ensemble convective scheme is well simulated the thunderstorm activities in terms of time, intensity and the region of occurrence of the events as compared to other convective schemes and also explicit scheme

Parallel implementation and one year experiments with the Danish Eulerian Model

Large scale air pollution models are powerful tools, designed to meet the increasing demand in different environmental studies. The atmosphere is the most dynamic component of the environment, where the pollutants can be moved quickly on far distnce. Therefore the air pollution modeling must be done in a large computational domain. Moreover, all relevant physical, chemical and photochemical processes must be taken into account. In such complex models operator splitting is very often applied in order to achieve sufficient accuracy as well as efficiency of the numerical solution. The Danish Eulerian Model (DEM) is one of the most advanced such models. Its space domain (4800 × 4800 km) covers Europe, most of the Mediterian and neighboring parts of Asia and the Atlantic Ocean. Efficient parallelization is crucial for the performance and practical capabilities of this huge computational model. Different splitting schemes, based on the main processes mentioned above, have been implemented and tested with respect to accuracy and performance in the new version of DEM. Some numerical results of these experiments are presented in this paper.

Closed-loop feedback computation model of dynamical reputation based on the local trust evaluation in business-to-consumer e-commerce

Trust and reputation are important factors that influence the success of both traditional transactions in physical social networks and modern e-commerce in virtual Internet environments. It is difficult to define the concept of trust and quantify it because trust has both subjective and objective characteristics at the same time. A well-reported issue with reputation management system in business-to-consumer (BtoC) e-commerce is the “all good reputation” problem. In order to deal with the confusion, a new computational model of reputation is proposed in this paper. The ratings of each customer are set as basic trust score events. In addition, the time series of massive ratings are aggregated to formulate the sellers’ local temporal trust scores by Beta distribution. A logical model of trust and reputation is established based on the analysis of the dynamical relationship between trust and reputation. As for single goods with repeat transactions, an iterative mathematical model of trust and reputation is established with a closed-loop feedback mechanism. Numerical experiments on repeated transactions recorded over a period of 24 months are performed. The experimental results show that the proposed method plays guiding roles for both theoretical research into trust and reputation and the practical design of reputation systems in BtoC e-commerce.

Agent-based model to rural-urban migration analysis

In this paper, we analyze the rural-urban migration phenomenon as it is usually observed in economies which are in the early stages of industrialization. The analysis is conducted by means of a statistical mechanics approach which builds a computational agent-based model. Agents are placed on a lattice and the connections among them are described via an Ising-like model. Simulations on this computational model show some emergent properties that are common in developing economies, such as a transitional dynamics characterized by continuous growth of urban population, followed by the equalization of expected wages between rural and urban sectors (Harris-Todaro equilibrium condition), urban concentration and increasing of per capita income. (c) 2005 Elsevier B.V. All rights reserved.