A joint compression-discrimination neural transformation applied to target detection.

Many image recognition algorithms based on data-learning perform dimensionality reduction before the actual learning and classification because the high dimensionality of raw imagery would require enormous training sets to achieve satisfactory performance. A potential problem with this approach is that most dimensionality reduction techniques, such as principal component analysis (PCA), seek to maximize the representation of data variation into a small number of PCA components, without considering interclass discriminability. This paper presents a neural-network-based transformation that simultaneously seeks to provide dimensionality reduction and a high degree of discriminability by combining together the learning mechanism of a neural-network-based PCA and a backpropagation learning algorithm. The joint discrimination-compression algorithm is applied to infrared imagery to detect military vehicles.     

Interactive Selective and Adaptive Clustering for Detection of Microcalcifications in Mammograms

Estevez, L., Kehtarnavaz, N., and Wendt, R. III, Interactive Selective and Adaptive Clustering for Detection of Microcalcifications in Mammograms,Digital Signal Processing6(1996), 224–232.This paper presents a clustering algorithm, called interactive selective and adaptive clustering (Isaac), to assist radiologists in looking for small clusters of microcalcifications in mammograms. Isaac is developed to identify suspicious microcalcification regions which are missed by other classification techniques due to false positive samples in the feature space. It comprises two parts: (i) selective clustering and (ii) interactive adaptation. The first part reduces the number of false positives by identifying the microcalcification subspace or domains in the feature space. The second part allows the radiologist to improve results by interactively identifying additional false positive or true negative samples. Clinical evaluations of mammograms indicate the potential of using this algorithm as an effective tool to bring microcalcification areas to the attention of the radiologist during a routine reading session of mammograms.     

Stearoyl-CoA desaturase activity in adipose tissue and liver of the cardiomyopathic hamster

Stearoyl-CoA desaturase activity and the fatty acid composition of lipids of adipose tissue and liver were determined in 35- and 180-day-old cardiomyopathic hamsters and age-matched normal controls. Enzyme activity was unchanged in the adipose tissue of 35-day-old animals but was significantly depressed in the 180-day-old cardiomyopathic hamsters. In the liver, stearoyl-CoA desaturase activity was significantly lower in the 35-day-old disease animals but was unchanged in the 180-day-old animals. The analysis of the fatty acid composition of the lipids isolated from adipose tissue showed an increase in the relative percentage of saturated fatty acids accompanied by a decrease in the relative percentage of unsaturated fatty acids in both age groups of the cardiomyopathic hamsters. However, linoleic acid content was increased in the diseased animals. Similar changes in fatty acid composition of lipids from the livers of 35-day-old cardiomyopathic hamsters were observed, but no significant differences in the fatty acid composition between 180-day-old cardiomyopathic hamsters and normal controls were observed. The changes in the fatty acid composition appear to be related to the observed changes in desaturase activity. In is concluded that such changes in desaturase activity and fatty acid composition could affect the normal structure and functions of membranes and membrane-related processes.     

Skin cancer detection by spectroscopic oblique-incidence reflectometry: classification and physiological origins

Data obtained from 102 skin lesions in vivo by spectroscopic oblique-incidence reflectometry were analyzed. The participating physicians initially divided the skin lesions into two visually distinguishable groups based on the lesions' melanocytic conditions. Group 1 consisted of the following two cancerous and benign subgroups: (1) basal cell carcinomas and squamous cell carcinomas and (2) benign actinic keratoses, seborrheic keratoses, and warts. Group 2 consisted of (1) dysplastic nevi and (2) benign common nevi. For each group, a bootstrap-based Bayes classifier was designed to separate the benign from the dysplastic or cancerous tissues. A genetic algorithm was then used to obtain the most effective combination of spatiospectral features for each classifier. The classifiers, tested with prospective blind studies, reached statistical accuracies of 100% and 95% for groups 1 and 2, respectively. Properties that related to cell-nuclear size, to the concentration of oxyhemoglobin, and to the concentration of deoxyhemoglobin as well as the derived concentration of total hemoglobin and oxygen saturation were defined to explain the origins of the classification outcomes.     

Handwriting style classification

This paper describes an independent handwriting style classifier that has been designed to select the best recognizer for a given style of writing. For this purpose a definition of handwriting legibility has been defined and a method implemented that can predict this legibility. The technique consists of two phases. In the feature-extraction phase, a set of 36 features is extracted from the image contour. In the classification phase, two nonparametric classification techniques are applied to the extracted features in order to compare their effectiveness in classifying words into legible, illegible, and middle classes. In the first method, a multiple discriminant analysis (MDA) is used to transform the space of extracted features (36 dimensions) into an optimal discriminant space for a nearest mean based classifier. In the second method, a probabilistic neural network (PNN) based on the Bayes strategy and nonparametric estimation of probability density function is used. The experimental results show that the PNN method gives superior classification results when compared with the MDA method. For the legible, illegible, and middle handwriting the method provides 86.5% (legible/illegible), 65.5% (legible/middle), and 90.5% (middle/illegible) correct classification for two classes. For the three-class legibility classification the rate of correct classification is 67.33% using a PNN classifier.Received: 6 September 2002, Accepted: 19 September 2002, Published online: 6 June 2003     

A SOCIOLOGICAL PERSPECTIVE ON THE REORDERING PROBLEM IN MULTIPATH ROUTING

The term multipath routing means using multiple paths concurrently to transport data over network. The main problem of this routing scheme is the difference among the delays of selected paths, which causes reordering of a single flow's packets. In this paper, this problem is analyzed through a sociological perspective. We show that reordering problem is not inherently related to multipath routing, rather caused by the dominant capitalist view of the problem. then, the problem is addressed through a Marxism perspective. We theoretically prove that by this perspective, there exists a routing scheme that minimizes latency and also the requirement of buffering at receiver.     

Channel choice and the digital divide in e-government: the case of Egypt

This paper examines channel choice and the digital divide in Egyptian electronic government or e-government. Citizens have access to a variety of service delivery channels when they initiate contact with their government, ranging from e-government to more traditional channels such as the phone and in-person visits to a government office. This paper examines the extent of use of both contact channels for citizens and the impact of the digital divide on channel use. A public opinion survey of Egyptian citizens was analyzed, and the results showed that there was a digital divide in the use of e-government by citizens. The digital divide also extended to other contact channels such as the phone and when citizens used multiple contact channels for public service delivery. The results of this study imply that for the development of e-government, especially in the context of a developing country such as Egypt, policy-makers need to understand that e-government is one of many channels that citizens can use when they initiate contact with their government. The results of this study should encourage policy-makers to recognize the importance of public service delivery in a multichannel environment. Shirin Madon is the accepting Associate Editor for this article. View all notes     

Determination of the flow stress of five AHSS sheet materials (DP 600, DP 780, DP 780-CR,DP 780-HY and TRIP 780) using the uniaxial tensile and the biaxial Viscous Pressure Bulge (VPB) tests

Room temperature uniaxial tensile and biaxial Viscous Pressure Bulge (VPB) tests were conducted for five Advanced High Strength Steels (AHSS) sheet materials, and the resulting flow stress curves were compared. Strain ratios (R-values) were also determined in the tensile test and used to correct the biaxial flow stress curves for anisotropy. The pressure vs. dome height raw data in the VPB test was extrapolated to the burst pressure to obtain the flow stress curve until fracture. Results of this work show that the flow stress data can be obtained to higher strain values under biaxial state of stress. Moreover, it was observed that some materials behave differently if subjected to different state of stress. These two conclusions, and the fact that the state of stress in actual stamping processes is almost always biaxial, suggest that the bulge test is a more suitable test for obtaining the flow stress of AHSS sheet materials for use as an input to Finite Element (FE) simulation models.