Slummiparakeista kyläkarnevaaleihin : Kumpulan ja Toukolan imagonmuutos sanomalehdissä 1963-1999

Having to do with residential areas, geographical image research in Finland has concentrated mainly on those areas with a relatively negative image, such as eastern parts of Helsinki. However, Kumpula and Toukola are former working class residential areas whose image nowadays is mainly positive. This research aims at understanding the process through which their image has gradually come to be that way. Theoretical background of the research relies on human geography and it s viewpoints on places, spaces and areas. Areas, in this research, are understood to be founded on discursive processes that form meanings in societies. This approach is useful because it provides a way to research newspapers and to see how they affect the society. In addition I lean on Sirpa Tani s research on place images to study image and it s formation process. Her point of view covers especially well the effect of media on images and their formation. Articles published in Helsingin Sanomat and Ilta-Sanomat between the years 1963 and 1999 form the data of the research. Methodologically I proceeded by using content analysis to see what kind of topics have been dominating the news feed from Kumpula and Toukola. Content analysis was followed by discourse analysis, which allowed me to focus on the ways of speaking about and representing Kumpula and Toukola. Discourse analysis also reveals whose viewpoint is being represented in media when it comes to publishing news from these parts of the city. It is clearly visible from the results of this research that the image of Kumpula and Toukola has gone through a significant change between 1963 and 1999. In the 1960s discussion in newspapers was dominated by the need for more effective city planning. This meant that Kumpula and Toukola were under a demolition threat in order for the city to built more effectively on those areas. At the same time there was discussion about wooden houses that were built in Kumpula and Toukola right after the second World War. Those houses were in a poor condition, it was even said in the newspapers that people were living in slum-like conditions in them. By the 1980s the image of Kumpula and Toukola gradually started to change. At this time gentrification process was affecting the areas and well-educated working force moved to Kumpula and Toukola. Already in the beginning of 1990s the image of the areas was highly positive. Throughout this decade newspapers published news on Kumpula and Toukola that commented favorably on the atmosphere and the feeling of togetherness among the residents. In addition Kumpula village carnivals, that were first held in 1991, brought a lot of positive publicity to the areas. This research has revelead that especially the active participationg of the residents to promote joint causes has positively affected the image of Kumpula and Toukola. Since the 1960s fighting for the preservation of the areas has provided a reason for a stronger feeling of communality and identifying in the community. This feeling of togetherness in a community has carried all the way to the 1990s, when the areas, having been affected by gentrification, could make good use of the positive image in order to promote joint causes. Keywords: Image, reputation, newspapers, discursive practices

Characterization of viral proteins ofOryctes baculovirus and comparison between two geographical isolates

BacilliformOryctes baculovirus particles have been visualized in electron micrographs of midgut sections from virus infectedOryctes rhinoceros beetles. Morphologically the Indian isolate (Oryctes baculovirus, KI) resembled the previously reportedOryctes baculovirus, isolate PV505. The constituent proteins of baculovirus KI have been analysed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and by Western blots using polyclonal antibodies raised against the complete viral particles, as probes. A total of forty eight viral proteins have been identified. Fourteen viral proteins were located on the viral envelope. Among the proteins constituting the nucleocapsid, three were located internally within the capsid. A 23.5 kDa protein was tightly associated with viral DNA in the nucleocapsid core. Two envelope and seven capsid proteins stained positive for glycosylation. Comparison between the viral proteins of KI and PV505 revealed differences in SDS-PAGE profiles and glycosylation patterns. Immunoblotting of KI and PV505 proteins with anti KI antiserum demonstrated antigenic differences between the two viral isolates.

GAP-RBF based NR image quality measurement for JPEG coded images

In this paper, we present a growing and pruning radial basis function based no-reference (NR) image quality model for JPEG-coded images. The quality of the images are estimated without referring to their original images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity factors such as edge amplitude, edge length, background activity and background luminance. Image quality estimation involves computation of functional relationship between HVS features and subjective test scores. Here, the problem of quality estimation is transformed to a function approximation problem and solved using GAP-RBF network. GAP-RBF network uses sequential learning algorithm to approximate the functional relationship. The computational complexity and memory requirement are less in GAP-RBF algorithm compared to other batch learning algorithms. Also, the GAP-RBF algorithm finds a compact image quality model and does not require retraining when the new image samples are presented. Experimental results prove that the GAP-RBF image quality model does emulate the mean opinion score (MOS). The subjective test results of the proposed metric are compared with JPEG no-reference image quality index as well as full-reference structural similarity image quality index and it is observed to outperform both.

Text localization and extraction from complex gray images

We propose two texture-based approaches, one involving Gabor filters and the other employing log-polar wavelets, for separating text from non-text elements in a document image. Both the proposed algorithms compute local energy at some information-rich points, which are marked by Harris' corner detector. The advantage of this approach is that the algorithm calculates the local energy at selected points and not throughout the image, thus saving a lot of computational time. The algorithm has been tested on a large set of scanned text pages and the results have been seen to be better than the results from the existing algorithms. Among the proposed schemes, the Gabor filter based scheme marginally outperforms the wavelet based scheme.

Automatic text block separation in document images

Separation of printed text blocks from the non-text areas, containing signatures, handwritten text, logos and other such symbols, is a necessary first step for an OCR involving printed text recognition. In the present work, we compare the efficacy of some feature-classifier combinations to carry out this separation task. We have selected length-nomalized horizontal projection profile (HPP) as the starting point of such a separation task. This is with the assumption that the printed text blocks contain lines of text which generate HPP's with some regularity. Such an assumption is demonstrated to be valid. Our features are the HPP and its two transformed versions, namely, eigen and Fisher profiles. Four well known classifiers, namely, Nearest neighbor, Linear discriminant function, SVM's and artificial neural networks have been considered and efficiency of the combination of these classifiers with the above features is compared. A sequential floating feature selection technique has been adopted to enhance the efficiency of this separation task. The results give an average accuracy of about 96.

Binarization and localization of text images captured on a mobile phone camera

This paper proposes and compares four methods of binarzing text images captured using a camera mounted on a cell phone. The advantages and disadvantages(image clarity and computational complexity) of each method over the others are demonstrated through binarized results. The images are of VGA or lower resolution.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

Memory-based reasoning approach for pattern recognition of binary images

Template matching is concerned with measuring the similarity between patterns of two objects. This paper proposes a memory-based reasoning approach for pattern recognition of binary images with a large template set. It seems that memory-based reasoning intrinsically requires a large database. Moreover, some binary image recognition problems inherently need large template sets, such as the recognition of Chinese characters which needs thousands of templates. The proposed algorithm is based on the Connection Machine, which is the most massively parallel machine to date, using a multiresolution method to search for the matching template. The approach uses the pyramid data structure for the multiresolution representation of templates and the input image pattern. For a given binary image it scans the template pyramid searching the match. A binary image of N × N pixels can be matched in O(log N) time complexity by our algorithm and is independent of the number of templates. Implementation of the proposed scheme is described in detail.

Quantitation of serological cross-reactivity between two geographical isolates of Oryctes baculovirus by a modified ELISA

An assay was developed for quantitation of the antigenic relationship between viruses, by modification of the indirect ELISA. The principle of this method is to estimate the epitopes not shared between the related viruses, after titration of the antibodies specific to the common epitopes as in a blocking ELISA. In practice, varying concentrations of purified virus are preincubated with a fixed dilution of heterologous or homologous antiserum and the unbound antibodies present in the mixture are back titrated with virus particles bound to microtitre plates. The antigenic relationship is described in terms of differentiation index (DI) and total antigenic reactivity (TAR). This method has been used to quantitate cross-reactivity between two geographically different isolates of Oryctes baculovirus.

Multiple contour extraction from graylevel images using an artificial neural network

For active contour modeling (ACM), we propose a novel self-organizing map (SOM)-based approach, called the batch-SOM (BSOM), that attempts to integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contours from images. We employ feature points, in the form of ail edge-map (as obtained from a standard edge-detection operation), to guide the contour (as in the case of SOM-based ACMs) along with the gradient and intensity variations in a local region to ensure that the contour does not "leak" into the object boundary in case of faulty feature points (weak or broken edges). In contrast with the snake-based ACMs, however, we do not use an explicit energy functional (based on gradient or intensity) for controlling the contour movement. We extend the BSOM to handle extraction of contours of multiple objects, by splitting a single contour into as many subcontours as the objects in the image. The BSOM and its extended version are tested on synthetic binary and gray-level images with both single and multiple objects. We also demonstrate the efficacy of the BSOM on images of objects having both convex and nonconvex boundaries. The results demonstrate the superiority of the BSOM over others. Finally, we analyze the limitations of the BSOM.

Tibetan Written Images : A Study of Imagery in the Writings of Dhondup Gyal

Dhondup Gyal (Don grub rgyal, 1953 - 1985) was a Tibetan writer from Amdo (Qinghai, People's Republic of China). He wrote several prose works, poems, scholarly writings and other works which have been later on collected together into The Collected Works of Dhondup Gyal, in six volumes. He had a remarkable influence on the development of modern Tibetan literature in the 1980s. Examining his works, which are characterized by rich imagery, it is possible to notice a transition from traditional to modern ways of literary expression. Imagery is found in both the poems and prose works of Dhondup Gyal. Nature imagery is especially prominent and his writings contain images of flowers and plants, animals, water, wind and clouds, the heavenly bodies and other environmental elements. Also there are images of parts of the body and material and cultural images. To analyse the images, most of which are metaphors and similes, the use of the cognitive theory of metaphor provides a good framework for making comparisons with images in traditional Tibetan literature and also some images in Chinese, Indian and Western literary works. The analysis shows that the images have both traditional and innovative features. The source domains of images often appear similar to those found in traditional Tibetan literature and are slow to change. However, innovative shifts occur in the way they are mapped on their target domains, which may express new meanings and are usually secular in nature if compared to the religiosity which often characterizes traditional Tibetan literature. Dhondup Gyal's poems are written in a variety of styles, ranging from traditional types of verse compositions and poems in the ornate kāvya-style to modern free verse poetry. The powerful central images of his free verse poems and some other works can be viewed as structurally innovative and have been analysed with the help of the theory of conceptual blending. They are often ambiguous in their meaning, but can be interpreted to express ideas related to creativity, freedom and the need for change and development.

Geographical Distribution Patterns of Amphibians in the Western Ghats, India

The Western Ghats of India are very rich in amphibian species with 117 species of frogs, toads and caecilians. Eighty-nine species are endemic to this biogeographical region. Analysis of ranges and patterns of geographical distribution of amphibians on the Western Ghats suggest that the southern half of the Western Ghats and the low-medium elevation hills are more diverse in species than the northern half and higher hills. This is attributed to the more widespread rainfall and the less variable climatic conditions in the south. About half the species are apparently localized. Of those species with wider ranges, a majority show patchy distribution. Species preferring the moist evergreen forests as habitats tend to have patchy distributions. This appears to be a result of habitat destruction and fragmentation. The overall patterns of species richness and local endemism are rather different from those of the angiosperms and birds. In birds and angiosperms, a significant proportion of endemics are found on the higher hills. On the contrary, endemic amphibian species are found in the lower altitudinal range of 0-1000 m, with a majority between 800 and 1000 m.