A model based factorization approach for dense 3D recovery from monocular video

Feature track matrix factorization based methods have been attractive solutions to the Structure-front-motion (Sfnl) problem. Group motion of the feature points is analyzed to get the 3D information. It is well known that the factorization formulations give rise to rank deficient system of equations. Even when enough constraints exist, the extracted models are sparse due the unavailability of pixel level tracks. Pixel level tracking of 3D surfaces is a difficult problem, particularly when the surface has very little texture as in a human face. Only sparsely located feature points can be tracked and tracking error arc inevitable along rotating lose texture surfaces. However, the 3D models of an object class lie in a subspace of the set of all possible 3D models. We propose a novel solution to the Structure-from-motion problem which utilizes the high-resolution 3D obtained from range scanner to compute a basis for this desired subspace. Adding subspace constraints during factorization also facilitates removal of tracking noise which causes distortions outside the subspace. We demonstrate the effectiveness of our formulation by extracting dense 3D structure of a human face and comparing it with a well known Structure-front-motion algorithm due to Brand.

Site characterization model using least-square support vector machine and relevance vector machine based on corrected SPT data (N-c)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N,), N values have been corrected (Ne) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three-dimensional site characterization model, the function N-c=N-c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N, value, is to be approximated in which N, value at any half-space point in Bangalore can be determined. The first algorithm uses least-square support vector machine (LSSVM), which is related to aridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel-based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright (C) 2009 John Wiley & Sons,Ltd.

A finite population model of mlecular evolution: theory and computation

This article is concerned with the evolution of haploid organisms that reproduce asexually. In a seminal piece of work, Eigen and coauthors proposed the quasispecies model in an attempt to understand such an evolutionary process. Their work has impacted antiviral treatment and vaccine design strategies. Yet, predictions of the quasispecies model are at best viewed as a guideline, primarily because it assumes an infinite population size, whereas realistic population sizes can be quite small. In this paper we consider a population genetics-based model aimed at understanding the evolution of such organisms with finite population sizes and present a rigorous study of the convergence and computational issues that arise therein. Our first result is structural and shows that, at any time during the evolution, as the population size tends to infinity, the distribution of genomes predicted by our model converges to that predicted by the quasispecies model. This justifies the continued use of the quasispecies model to derive guidelines for intervention. While the stationary state in the quasispecies model is readily obtained, due to the explosion of the state space in our model, exact computations are prohibitive. Our second set of results are computational in nature and address this issue. We derive conditions on the parameters of evolution under which our stochastic model mixes rapidly. Further, for a class of widely used fitness landscapes we give a fast deterministic algorithm which computes the stationary distribution of our model. These computational tools are expected to serve as a framework for the modeling of strategies for the deployment of mutagenic drugs.

Population dynamics of Penaeus indicus at Sofala Bank, Mozambique: a preliminary study

Length-based methods are used to estimate growth and mortalities of Penaeus indicus at Sofala Bank in Mozambique. This Penaeid shrimp is one of the most important species in the fishery as it constitutes 45% of the catches and has a great influence in their trend. First estimates of growth parameters for this species in Mozambique are presented and a comparison of the derived mortalities with the previous estimates is made.

Silhouette-based object phenotype recognition using 3D shape priors

This paper tackles the novel challenging problem of 3D object phenotype recognition from a single 2D silhouette. To bridge the large pose (articulation or deformation) and camera viewpoint changes between the gallery images and query image, we propose a novel probabilistic inference algorithm based on 3D shape priors. Our approach combines both generative and discriminative learning. We use latent probabilistic generative models to capture 3D shape and pose variations from a set of 3D mesh models. Based on these 3D shape priors, we generate a large number of projections for different phenotype classes, poses, and camera viewpoints, and implement Random Forests to efficiently solve the shape and pose inference problems. By model selection in terms of the silhouette coherency between the query and the projections of 3D shapes synthesized using the galleries, we achieve the phenotype recognition result as well as a fast approximate 3D reconstruction of the query. To verify the efficacy of the proposed approach, we present new datasets which contain over 500 images of various human and shark phenotypes and motions. The experimental results clearly show the benefits of using the 3D priors in the proposed method over previous 2D-based methods. © 2011 IEEE.

Feature Selection based on Rough Sets and Particle Swarm Optimization

X. Wang, J. Yang, X. Teng, W. Xia, and R. Jensen. Feature Selection based on Rough Sets and Particle Swarm Optimization. Pattern Recognition Letters, vol. 28, no. 4, pp. 459-471, 2007.

Tolerance-based and Fuzzy-Rough Feature Selection.

R. Jensen and Q. Shen, 'Tolerance-based and Fuzzy-Rough Feature Selection,' Proceedings of the 16th International Conference on Fuzzy Systems (FUZZ-IEEE'07), pp. 877-882, 2007.

Finding Rough Set Reducts with SAT.

R. Jensen, Q. Shen and A. Tuson, 'Finding Rough Set Reducts with SAT,' Proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, LNAI 3641, pp. 194-203, 2005.

Silica bonded stationary phases: Innovative functionalization methods and novel chromatographic separations based on molecular recognition

The research work included in this thesis examines the synthesis, characterization and chromatographic evaluation of novel bonded silica stationary phases. Innovative methods of preparation of silica hydride intermediates and octadecylsilica using a “green chemistry” approach eliminate the use of toxic organic solvents and exploit the solvating power and enhanced diffusivity of supercritical carbon dioxide to produce phases with a surface coverage of bonded ligands which is comparable to, or exceeds, that achieved using traditional organic solvent-based methods. A new stationary phase is also discussed which displays chromatographic selectivity based on molecular recognition. Chapter 1 introduces the chemistry of silica stationary phases, the retention mechanisms and theories on which reversed-phase liquid chromatography and hydrophilic interaction chromatograpy are based, the art and science of achieving a well packed liquid chromatography column, the properties of supercritical carbon dioxide and molecular recognition chemistry. Chapter 2 compares the properties of silica hydride materials prepared using supercritical carbon dioxide as the reaction medium with those synthesized in an organic solvent. A higher coverage of hydride groups on the silica surface is seen when a monofunctional silane is reacted in supercritical carbon dioxide while trifunctional silanes result in a phase which exhibits different properties depending on the reaction medium used. The differing chromatographic behaviour of these silica hydride materials prepared using supercritical carbon dioxide and using organic solvent are explored in chapter 3. Chapter 4 focusses on the preparation of octadecylsilica using mono-, di- and trifunctional alkoxysilanes in supercritical carbon dioxide and in anhydrous toluene. The surface coverage of octadecyl groups, as calculated using thermogravimetric analysis and elemental analysis, is highest when a trifunctional alkoxysilane is reacted with silica in supercritical carbon dioxide. A novel silica stationary phase is discussed in chapter 5 which displays selectivity for analytes based on their hydrogen bonding capabilities. The phase is also highly selective for barbituric acid and may have a future application in the solid phase extraction of barbiturates from biological samples.

Prediction of the formation and stabilities of energetic salts and ionic liquids based on ab initio electronic structure calculations

A computational approach to predict the thermodynamics for forming a variety of imidazolium-based salts and ionic liquids from typical starting materials is described. The gas-phase proton and methyl cation acidities of several protonating and methylating agents, as well as the proton and methyl cation affinities of many important methyl-, nitro-, and cyano- substituted imidazoles, have been calculated reliably by using the computationally feasible DFT (B3LYP) and MP2 (extrapolated to the complete basis set limit) methods. These accurately calculated proton and methyl cation affinities of neutrals and anions are used in conjunction with an empirical approach based on molecular volumes to estimate the lattice enthalpies and entropies of ionic liquids, organic solids, and organic liquids. These quantities were used to construct a thermodynamic cycle for salt formation to reliably predict the ability to synthesize a variety of salts including ones with potentially high energetic densities. An adjustment of the gas phase thermodynamic cycle to account for solid- and liquid-phase chemistries provides the best overall assessment of salt formation and stability. This has been applied to imidazoles (the cation to be formed) with alkyl, nitro, and cyano substituents. The proton and methyl cation donors studied were as follows: HCl, HBr, HI, (HO)(2)SO2, HSO3CF3 (TfOH), and HSO3(C6H4)CH3 (TsOH); CH3Cl, CH3Br, CH3I, (CH3O)(2)SO2, CH3SO3CF3 (TfOCH3) and CH3SO3(C6H4)CH3 (TsOCH3). As substitution of the cation with electron-withdrawing groups increases, the triflate reagents appear to be the best overall choice as protonating and methylating agents. Even stronger alkylating agents should be considered to enhance the chances of synthetic success. When using the enthalpies of reaction for the gas-phase reactants (eq 6) to form a salt, a cutoff value of - 13 kcal mol(-1) or lower (more negative) should be used as the minimum value for predicting whether a salt can be synthesized.

A bargaining set for monotonic simple games based on external and internal stability

A new bargaining set based on notions of both internal and external stability is developed in the context of endogenous coalition formation. It allows to make an explicit distinction between within-group and outside-group deviation options. This type of distinction is not present in current bargaining sets. For the class of monotonic proper simple games, the outcomes in the bargaining set are characterized. Furthermore, it is shown that the bargaining set of any homogeneous weighted majority game contains an outcome for which the underlying coalition structure consists of a minimal winning coalition and its complement.

‘Emergent reconstruction’ in grounded theory: learning from team-based interview research

Constructivist grounded theory (CGT) methods render an interpretive portrayal, a construction of reality, strengthened when the process of construction is acknowledged. An Irish team study uses CGT to explore intergenerational solidarity at individual, familial and societal levels, and their interface. The study data comprise interviews with 100 people from diverse socio-economic and
age groups. The article contributes insights on applying CGT in team-based interview research on a topic with such breadth of scope. This contrasts with the more usual focused inquiry with a defined population. Adapting the method’s guidelines to the specific inquiry involved challenges in: framing the topic conceptually; situating research participants in contrasting social contexts to
provide interpretive depth; and generating interview data with which to construct theory. We argue that interrogating the very premise of the inquiry allowed for emergent reconstruction, a goal at the heart of the method.

Characterisation of the frequent exacerbator phenotype in COPD patients in a large UK primary care population

BACKGROUND: The 'frequent exacerbator' is recognised as an important phenotype in COPD. Current understanding about this phenotype comes from prospective longitudinal clinical trials in secondary/tertiary care with little information reported in primary care populations.

AIMS: To characterize the frequent-exacerbator phenotype and identify associated risk factors in a large UK primary care COPD population.

METHODS: Using a large database of primary care patients from 80 UK general practices, patients were categorised using GOLD 2014 criteria into high and low risk groups based on exacerbation history. A multivariate logistic regression model was used to investigate covariates associated with the frequent-exacerbator phenotype and risk of experiencing a severe exacerbation (leading to hospitalisation).

RESULTS: Of the total study population (n = 9219), 2612 (28%) fulfilled the criteria for high risk frequent-exacerbators. Independent risk factors (adjusted odds ratio [95% CI]) for ≥2 exacerbations were: most severely impaired modified Medical Research Council (mMRC) dyspnoea score (mMRC grade 4: 4.37 [2.64-7.23]), lower FEV1 percent predicted (FEV1 <30%: 2.42 [1.61-3.65]), co-morbid cardiovascular disease (1.42 [1.19-1.68]), depression (1.56 [1.22-1.99]) or osteoporosis (1.54 [1.19-2.01]), and female gender (1.20 [1.01-1.43]). Older patients (≥75 years), those with most severe lung impairment (FEV1 <30%), those with highest mMRC score and those with co-morbid osteoporosis were identified as most at risk of experiencing exacerbations requiring hospitalisation.

CONCLUSIONS: Although COPD exacerbations occur across all grades of disease severity, female patients with high dyspnoea scores, more severely impaired lung function and co-morbidities are at greatest risk. Elderly patients, with severely impaired lung function, high mMRC scores and osteoporosis are associated with experience of severe exacerbations requiring hospitalisation.

Thermolabile methylenetetrahydrofolate reductase (C677T):frequency in the Irish population

BACKGROUND: The genetic variation which underlies the thermolability and low enzyme activity of 5,10-methylenetetrahydrofolate reductase (MTHFR; C677T) has been extensively studied in many populations, including the Irish population.

AIM: To describe the examination of the C677T substitution in two new control samples drawn from the Irish population.

METHODS: A collection of 487 serum samples was obtained through the blood transfusion services of both the Republic of Ireland and Northern Ireland and a further 115 samples from volunteers.

RESULTS: In both samples, the frequency of the thermolabile/low enzyme activity allele (T) was higher than that previously reported for the Irish population.

CONCLUSION: This finding thus supports the need for a greater use of internal control/family-based association studies, as opposed to the classic case control study design, when assessing the contribution of the MTHFR T allele to disease processes.

Crianças com défices no controlo motor: contributo para a elaboração do core set da Classificação Internacional de Funcionalidade, Incapacidade e Saúde (CIF)

A CIF é um sistema de classificação adotado pela OMS, que serve de referência universal para descrever, avaliar e medir saúde e incapacidade, a nível individual e ao nível da população. Contudo, apesar do interesse internacional gerado em torno da CIF, esta é considerada uma classificação complexa e extensa, fato que despoletou a criação de core sets – listas de itens da CIF especificamente selecionados pela sua relevância na descrição e qualificação de uma determinada condição de saúde – como resposta a esta problemática. Até à data, foram desenvolvidos core sets para várias patologias comuns. Contudo, apesar do controlo motor ser uma área de investigação muito reconhecida nos últimos 20 anos, ainda não possui um core set próprio. Assim, o objetivo deste estudo é contribuir para o desenvolvimento de um core set, com base na CIF-CJ, dirigido para uma descrição abrangente das competências inerentes a crianças, dos 6 aos 18 anos de idade, com défices no controlo motor. Deste modo, recorreu-se a uma revisão da literatura sobre a temática em estudo, de modo a reunir informação para a construção de uma proposta a core set, posteriormente sujeita ao escrutínio de peritos, através do recurso ao método de Delphi. Após várias rondas, foi alcançado um consenso acerca da lista final de códigos CIF que constituem o core set final.