Length-weight relationship and condition factor of black carp (Mylopharyngodon spiceus Richardson) in Bangladesh

The length-weight relationship and condition factor of Mylopharyngodon spiceus were determined. The result of the study showed the dependence of weight (W) on the total length (L) in the following form: W= 0.006L(super 3.156) or in the logarithmic form Log W=- 2.1851 + 3.156 Log L. Standard errors of length and weight were 0.674 cm and 3.214 g respectively. The co-efficient correlation "r" was found to be 0.972 which indicated that the relationship between length and body weight of the fish was highly significant. The t-test also indicated that the correlation between length and weight was significant. The range and mean value of condition factor (K) were 0.865 to 1.041 and 0.958 respectively.

Nonparametric Bayesian sparse factor models with application to gene expression modeling

A nonparametric Bayesian extension of Factor Analysis (FA) is proposed where observed data $\mathbf{Y}$ is modeled as a linear superposition, $\mathbf{G}$, of a potentially infinite number of hidden factors, $\mathbf{X}$. The Indian Buffet Process (IBP) is used as a prior on $\mathbf{G}$ to incorporate sparsity and to allow the number of latent features to be inferred. The model's utility for modeling gene expression data is investigated using randomly generated data sets based on a known sparse connectivity matrix for E. Coli, and on three biological data sets of increasing complexity.

Robust control of plants with saturation nonlinearity based on coprime factor representations

We consider the robust control of plants with saturation nonlinearities from an input/output viewpoint. First, we present a parameterization for anti-windup control based on coprime factorizations of the controller. Second, we propose a synthesis method which exploits the freedom to choose a particular coprime factorization.

Real time feature-based facial tracking using Lie algebras

We have developed a novel human facial tracking system that operates in real time at a video frame rate without needing any special hardware. The approach is based on the use of Lie algebra, and uses three-dimensional feature points on the targeted human face. It is assumed that the roughly estimated facial model (relative coordinates of the three-dimensional feature points) is known. First, the initial feature positions of the face are determined using a model fitting technique. Then, the tracking is operated by the following sequence: (1) capture the new video frame and render feature points to the image plane; (2) search for new positions of the feature points on the image plane; (3) get the Euclidean matrix from the moving vector and the three-dimensional information for the points; and (4) rotate and translate the feature points by using the Euclidean matrix, and render the new points on the image plane. The key algorithm of this tracker is to estimate the Euclidean matrix by using a least square technique based on Lie algebra. The resulting tracker performed very well on the task of tracking a human face.

On the use of a decimative spectral estimation method based on eigenanalysis and SVD for formant and bandwidth tracking of speech signals

In this paper, a Decimative Spectral estimation method based on Eigenanalysis and SVD (Singular Value Decomposition) is presented and applied to speech signals in order to estimate Formant/Bandwidth values. The underlying model decomposes a signal into complex damped sinusoids. The algorithm is applied not only on speech samples but on a small amount of the autocorrelation coefficients of a speech frame as well, for finer estimation. Correct estimation of Formant/Bandwidth values depend on the model order thus, the requested number of poles. Overall, experimentation results indicate that the proposed methodology successfully estimates formant trajectories and their respective bandwidths.

Video tracking using dual-treewavelet polar matching and particle filtering

In this paper, we describe a video tracking application using the dual-tree polar matching algorithm. The models are specified in a probabilistic setting, and a particle ilter is used to perform the sequential inference. Computer simulations demonstrate the ability of the algorithm to track a simulated video moving target in an urban environment with complete and partial occlusions. © The Institution of Engineering and Technology.

Nonparametric mixtures of factor analyzers

The mixtures of factor analyzers (MFA) model allows data to be modeled as a mixture of Gaussians with a reduced parametrization. We present the formulation of a nonparametric form of the MFA model, the Dirichlet process MFA (DPMFA). The proposed model can be used for density estimation or clustering of high dimensiona data. We utilize the DPMFA for clustering the action potentials of different neurons from extracellular recordings, a problem known as spike sorting. DPMFA model is compared to Dirichlet process mixtures of Gaussians model (DPGMM) which has a higher computational complexity. We show that DPMFA has similar modeling performance in lower dimensions when compared to DPGMM, and is able to work in higher dimensions. ©2009 IEEE.

Physiological modelling for improved reliability in silhouette-driven gradient-based hand tracking

We present a gradient-based motion capture system that robustly tracks a human hand, based on abstracted visual information - silhouettes. Despite the ambiguity in the visual data and despite the vulnerability of gradient-based methods in the face of such ambiguity, we minimise problems related to misfit by using a model of the hand's physiology, which is entirely non-visual, subject-invariant, and assumed to be known a priori. By modelling seven distinct aspects of the hand's physiology we derive prior densities which are incorporated into the tracking system within a Bayesian framework. We demonstrate how the posterior is formed, and how our formulation leads to the extraction of the maximum a posteriori estimate using a gradient-based search. Our results demonstrate an enormous improvement in tracking precision and reliability, while also achieving near real-time performance. © 2009 IEEE.

Online multiple classifier boosting for object tracking

This paper presents a new online multi-classifier boosting algorithm for learning object appearance models. In many cases the appearance model is multi-modal, which we capture by training and updating multiple strong classifiers. The proposed algorithm jointly learns the classifiers and a soft partitioning of the input space, defining an area of expertise for each classifier. We show how this formulation improves the specificity of the strong classifiers, allowing simultaneous location and pose estimation in a tracking task. The proposed online scheme iteratively adapts the classifiers during tracking. Experiments show that the algorithm successfully learns multi-modal appearance models during a short initial training phase, subsequently updating them for tracking an object under rapid appearance changes. © 2010 IEEE.

3D multi-car tracking based on monocular video

We propose a system that can reliably track multiple cars in congested traffic environments. Our system's key basis is the implementation of a sequential Monte Carlo algorithm, which introduces robustness against problems arising due to the proximity between vehicles. By directly modelling occlusions and collisions between cars we obtain promising results on an urban traffic dataset. Extensions to this initial framework are also suggested. © 2010 IEEE.

ISOLATION AND PROPERTIES OF A BLOOD-COAGULATION FACTOR-X ACTIVATOR FROM THE VENOM OF KING COBRA (OPHIOPHAGUS HANNAH)

A specific blood coagulation factor X activator was purified from the venom of Ophiophagus hannah by gel filtration and two steps of FPLC Mono-Q column ion-exchange chromatography. It showed a single protein band both in sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and alkaline polyacrylamide gel electrophoresis. The mol. wt was estimated to be 62,000 in non-reducing conditions and 64,500 in reducing conditions by SDS-PAGE. The isoelectric point was found to be pH 5.6. The enzyme had weak amidolytic activities toward CBS 65-25, but it showed no activities on S-2266, S-2302, thrombin substrate S-2238, plasmin substrate S-2251 or factor Xa substrate S-2222. It had no arginine esterase activity toward substrate benzoylarginine ethylester (BAEE). The enzyme activated factor X in vitro and the effect was absolutely Ca2+ dependent, with a Hill coefficient of 6.83. It could not activate prothrombin nor had any effect on fibrinogen and thus appeared to act specifically on factor X. The procoagulant activity of the enzyme was almost completely inhibited by serine protease inhibitors like PMSF, TPCK and soybean trypsin inhibitor; partially inhibited by L-cysteine. Metal chelator EDTA did not inhibit its procoagulant activity. These results suggest that the factor X activator from O. hannah venom is a serine protease.

AN ACTIVATOR OF BLOOD-COAGULATION FACTOR-X FROM THE VENOM OF BUNGARUS-FASCIATUS

A specific activator of blood coagulation factor X was purified from the venom of Bungarus fasciatus by gel filtration and by ion-exchange chromatography on a Mono-Q column (FPLC). It consisted of a single polypeptide chain, with a mel. wt of 70,000 in reducing and non-reducing conditions. The enzyme had an amidolytic activity towards the chromogenic substrates S-2266 and S-2302 but it did not hydrolyse S-2238, S2251 or S-2222, which are specific substrates for thrombin, plasmin and factor Xa, respectively. The enzyme activated factor X in vitro and the effect was Ca2+ dependent with a Hill coefficient of 7.9. As with physiological activators, the venom activator cleaves the heavy chain of factor X, producing the activated factor Xa alpha. The purified factor X activator from B. fasciatus venom did not activate prothrombin, nor did it cleave or clot purified fibrinogen. The amidolytic activity and the factor X activation activity of the factor X activator from B. fasciatus venom were readily inhibited by serine protease inhibitors such as diisopropyl fluorophosphate (DFP), phenylmethanesulfonyl fluoride (PMSF), benzamidine and by soybean trypsin inhibitor but not by EDTA. These observations suggest that the factor X activator from B. fasciatus venom is a serine protease. It therefore differs from those of activators obtained from Vipera russelli and Bothrops atrox venoms, which are metalloproteinases.