Many practical experiments on mixtures (where the components sum to one) include additional lower or upper bounds on components, or on linear combinations of them. Usually theory cannot be used to obtain a good design, and algorithmic methods are necessary. Some of the available methods are discussed. Their performance is evaluated on some examples, and the form of the optimal design is investi...

This paper presents the experiments made to automatically identify emotion in an emotional speech database for Basque. Three different classifiers have been built: one using spectral features and GMM, other with prosodic features and SVM and the last one with prosodic features and GMM. 86 prosodic features were calculated and then an algorithm to select the most relevant ones was applied. The f...

The region-based coding of the volume data is proposed in the present paper. Since the volume data is the three dimensional one, the visualization method is needed to display it. The region segmentation is indispensable to visualize the desired portions only. In the proposed method, the region segmentation result is utilized to code the volume data; the contours and the colors of the regions ar...

While a significant body of work has been done on grasping objects, there is little prior work on placing and arranging objects in the environment. In this work, we consider placing multiple objects in complex placing areas, where neither the object nor the placing area may have been seen by the robot before. Specifically, the placements should not only be stable, but should also follow human u...

Computer experiments often have inputs that are proportions/fractions of components in a mixture. In these mixture computer experiments, it can be of interest to perform robust and tolerance design on the mixture proportions since the proportions are subjected to noise variations. Traditionally, manufacturing of mixture products is controlled via interval tolerances for mixture amounts. In this...

A major issue in clustering uncertain objects is related to the poor efficiency of existing algorithms, which is mainly due to expensive computation of the distance between uncertain objects. This paper discusses how we addressed this issue through an original formulation of the problem of clustering uncertain objects based on the minimization of the variance of the mixture models that represen...

Science education aims at developing students’ knowledge of scientific concepts and principles. However, students differ in their prior knowledge and cognitive skills and thus follow different learning pathways. We examined whether and how experimentation skills predict elementary students’ pathways of conceptual knowledge development in science education. First to sixth grade students (N = 127...

Nonnative speech recognition is becoming more and more important as many speech applications are deployed world wide. Meanwhile, due to the large population of nonnative speakers, speaker adaptation remains the most practical way for providing high performance speech services. Subspace Gaussian Mixture Model (SGMM) has recently been shown to yield superior performance on various native speech r...

In developing speech recognition based services for any task domain, it is necessary to account for the support of an increasing number of languages over the life of the service. This paper considers a small vocabulary speech recognition task in multiple Indian languages. To configure a multi-lingual system in this task domain, an experimental study is presented using data from two linguistical...

augmented downhill simplex method (adsm) is introduced here, that is a heuristic combination of downhill simplex method (dsm) with random search algorithm. in fact, dsm is an interpretable nonlinear local optimization method. however, it is a local exploitation algorithm; so, it can be trapped in a local minimum. in contrast, random search is a global exploration, but less efficient. here, rand...