The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

Affective and evaluative descriptors of pain in the McGill Pain Questionnaire: reduction and reorganization

Recent reports indicate that several descriptors of pain sensations in the McGill Pain Questionnaire (MPQ) are difficult to classify within MPQ sensory subcategories because of incomprehension, underuse, or ambiguity of usage. Adopting the same methodology of recent studies, the present investigation focused on the affective and evaluative subcategories of the MPQ. A decision rule revealed that only 6 of 18 words met criteria for the affective category and 5 of 11 words met criteria for the evaluative category, thus warranting a reduced list of words in these categories. This reduction, however, led to negligible loss of information transmitted. Despite notable changes in classification, the intensity ratings of the retained words correlated very highly with those originally reported for the MPQ. In conclusion, although the intensity ratings of MPQ affective and evaluative descriptors need no revision, selective reduction and reorganization of these descriptors can enhance the efficiency of this approach to pain assessment. [copy ] 2001 by the American Pain Society

Influence of particle morphology on nanostructural feature and conducting property in Sm-doped CeO2 sintered body

Doped ceria (CeO2,) compounds are fluorite type oxides, which show oxide ionic conductivity higher than yttria stabilized zirconia (YSZ), in oxidizing atmospheres. As a consequence of this, considerable interest has been shown in application of these materials for 'low (500-650 degreesC)' or 'intermediate (650-800 degreesC)' temperature operation, solid oxide fuel cells (SOFCs). In this study, the authors prepared two kinds of nanosize Sm-doped CeO2 particles with different morphologies: one type was round and the other was elongated. Processing these powders with different morphology produced dense materials with very different ionic conducting properties and different nanoscale microstructures. Since both particles are very fine and well dispersed, sintered bodies with high density (relative density >95% of theoretical) could be prepared using both types of powder particles. The electrical conductivity of sintered bodies prepared from these powders with different starting morphologies was very different. Materials prepared from particles having a round shape were much higher than those produced using powders with an elongated morphology. Measured activation energies of the corresponding sintered samples showed a similar trend; round particles (60 kJ/mol), elongated particles (74 kJ/mol). While X-ray diffraction (XRD) profiles of these sintered materials were identical, diffuse scatter was observed in the back.-round of selected area electron diffraction pattern recorded from both sintered bodies. This indicated an underlying structure that appeared to have been influenced by the processing technology. Detailed observation using high-resolution transmission electron microscopy (HR-TEM) revealed that the size of microdomain with ordering of cations in the sintered body made from round shape particles was much smaller than that of the sintered body made from elongated particles. Accordingly, it is concluded that the morphology of doped CeO2 powders strongly influenced the microdomain size and electrolytic properties in the doped CeO2 sintered body. (C) 2004 Elsevier B.V. All rights reserved.

Widespread sensory hypersensitivity is a feature of chronic whiplash-associated disorder but not chronic idiopathic neck pain

Objectives: To investigate sensory changes present in patients with chronic whiplash-associated disorders and chronic idiopathic neck pain using a variety of quantitative sensory tests to better understand the pain processing mechanisms underlying persistent symptoms. Methods: A case control study was used with 29 subjects with chronic whiplash-associated disorders, 20 subjects with chronic idiopathic neck pain, and 20 pain-free volunteers. Pressure pain thresholds were measured over the articular pillars of C2-C3, C5-C6, the median, radial, and ulnar nerve trunks in the arm and over a remote site, the muscle belly of tibialis anterior. Heat pain thresholds, cold pain thresholds, and von Frey hair sensibility were measured over the cervical spine, tibialis anterior, and deltoid insertion. Anxiety was measured with the Short-Form of the Spielberger State Anxiety Inventory. Results: Pressure pain thresholds were decreased over cervical spine sites in both subject groups when compared with controls (P < 0.05). In the chronic whiplash-associated disorders group, pressure pain thresholds were also decreased over the tibialis anterior, median, and radial nerve trunks (P < 0.001). Heat pain thresholds were decreased and cold pain thresholds increased at all sites (P < 0.03). No differences in heat pain thresholds or cold pain thresholds were evident in the idiopathic neck pain group at any site compared with the control group (P > 0.27). No abnormalities in von Frey hair sensibility were evident in either neck pain group (P > 0.28). Discussion: Both chronic whiplash-associated disorders and idiopathic neck pain groups were characterized by mechanical hyperalgesia over the cervical spine. Whiplash subjects showed additional widespread hypersensitivity to mechanical pressure and thermal stimuli, which was independent of state anxiety and may represent changes in central pain processing mechanisms. This may have implications for future treatment approaches.

Normalized Gaussian Networks with Mixed Feature Data

With mixed feature data, problems are induced in modeling the gating network of normalized Gaussian (NG) networks as the assumption of multivariate Gaussian becomes invalid. In this paper, we propose an independence model to handle mixed feature data within the framework of NG networks. The method is illustrated using a real example of breast cancer data.

Developmental Pathways in Microcerotermes turneri (Termitidae: Termitinae): Biometric Descriptors of Worker Caste and Instar

The foraging process of location and exploitation of food in complex termite societies is in part reliant upon unequal division of specific tasks amongst its members (polyethism). To conduct studies assessing the role of individuals in foraging activities it is necessary to have descriptors of worker caste and instar. Here we provide biometric descriptors of specific caste and instar for worker caste and instars of Microcerotermes turneri (Froggatt) (Termitidae: Termitinae) for the worker castes (male and female) for the identification of individuals in laboratory assays applicable across multiple nests. The use of head width for determining sex of workers was successful across multiple nests. The length of the first three flagellum segments of the antenna and tibia three could be used to determine worker instar.

A fuzzy approach to texture segmentation

The texture segmentation techniques are diversified by the existence of several approaches. In this paper, we propose fuzzy features for the segmentation of texture image. For this purpose, a membership function is constructed to represent the effect of the neighboring pixels on the current pixel in a window. Using these membership function values, we find a feature by weighted average method for the current pixel. This is repeated for all pixels in the window treating each time one pixel as the current pixel. Using these fuzzy based features, we derive three descriptors such as maximum, entropy, and energy for each window. To segment the texture image, the modified mountain clustering that is unsupervised and fuzzy c-means clustering have been used. The performance of the proposed features is compared with that of fractal features.