Zooplankton population in the river tigris: Effects of samarra impoundment

The influences of the Samarra impoundment on the ecology of the downstream sector of the river Tigris are investigated. Zooplankton were collected monthly from July 1987 to July 1988. It was found that zooplankton were most abundant during high river discharges in March. During the month of low river discharge, September, the zooplankton population was greatly reduced immediately below the barrage and remained so to the last downstream station. Several factors seem to explain such differences. The high discharge from the impoundment was found to be the dominating factor and may flush the small backwaters in which zooplankton were abundant, thus increasing the population in the river. Zooplankton species vary in their ability to sustain populations in the river, variations which are due mainly to species-specific characteristics.     

A multimedia interactive conferencing application for personalworkstations

The multimedia interactive conferencing application (MICA), a personal-workstation application for multipoint visual teleconferencing, is described. MICA allows people at two or more locations to share visual material such as documents, photographs, and computer screens in a highly interactive way. It supports the distribution, storage, retrieval, and high-quality display of visuals, real-time interaction by pointing and annotation, and meeting services facilities. The context of multimedia teleconferencing and computer-supported cooperative work is established, relating earlier research to the design of MICA. The services MICA offers are outlined. The handling, compression, and display of multiple media, and the design of a suitable user interface for MICA are discussed     

Contributing authors

Contributing authors     

KAFD Arabic font database

Font recognition is useful for improving optical text recognition systems’ accuracy and time, and to restore the documents’ original formats. This paper addresses a need for Arabic font recognition research by introducing an Arabic font recognition database consisting of 40 fonts, 10 sizes (ranging from 8 to 24 points) and 4 styles (viz. normal, bold, italic, and bold–italic). The database is split into three sets (viz. training, validation, and testing). The database is freely available to researchers.¹ Moreover, we introduce a baseline font recognition system for benchmarking purposes, and report identification rates on our KAFD database and the Arabic Printed Text Image (APTI) database with 20 and 10 fonts, respectively. The best recognition rates are achieved using log-Gabor filters.     

KHATT: An open Arabic offline handwritten text database

A comprehensive Arabic handwritten text database is an essential resource for Arabic handwritten text recognition research. This is especially true due to the lack of such database for Arabic handwritten text. In this paper, we report our comprehensive Arabic offline Handwritten Text database (KHATT) consisting of 1000 handwritten forms written by 1000 distinct writers from different countries. The forms were scanned at 200, 300, and 600 dpi resolutions. The database contains 2000 randomly selected paragraphs from 46 sources, 2000 minimal text paragraph covering all the shapes of Arabic characters, and optionally written paragraphs on open subjects. The 2000 random text paragraphs consist of 9327 lines. The database forms were randomly divided into 70%, 15%, and 15% sets for training, testing, and verification, respectively. This enables researchers to use the database and compare their results. A formal verification procedure is implemented to align the handwritten text with its ground truth at the form, paragraph and line levels. The verified ground truth database contains meta-data describing the written text at the page, paragraph, and line levels in text and XML formats. Tools to extract paragraphs from pages and segment paragraphs into lines are developed. In addition we are presenting our experimental results on the database using two classifiers, viz. Hidden Markov Models (HMM) and our novel syntactic classifier.     

QUANTITATIVE MEASUREMENT OF CHROMIUM'S ABILITY TO PROMOTE ADHESION

Using atomic force spectroscopy, we investigated the adhesion-promoting ability of chromium. An intermediate layer of chromium can overcome the low adhesion between metal films and silicon dioxide. For the first time, we quantitatively studied this experimentally well known fact. We compared the adhesion between chromium and different substrates such as gold, silver, mica, and silicon dioxide and, beyond that, the adhesion between silicon dioxide and the same substrates. To avoid additional effects due to water, we chose ethanol as a nonpolar solvent. Taking the interfacial energies of the surfaces with the liquid into account eliminates the direct influence of the fluid medium on the adhesion of the solid material. The results we obtained corroborate the experimental fact of higher adhesion of chromium with the chosen substrates, as well as substantiate the value of chromium as an adhesion promoter. The adhesion of chromium-coated probes on gold, silicon dioxide, and mica is higher than the adhesion of silicon dioxide probes on the same substrates.     

Successful electroconvulsive therapy of Cotard syndrome with bitemporal hypoperfusion

A case study is presented to illustrate a rare condition described by Cotard as "délire de négation". The central symptom is a nihilistic delusion with denial of one's own existence of oneself and that of the external world. In the present case, the syndrome became manifest as an escalation of a recurrent depressive disorder late in life. After initial resistance to therapy, the syndrome was successfully treated with electroconvulsive therapy. For the first time, we report the regional cerebral blood flow measured by 99mTc-HMPAO-SPECT before and after therapy. Before treatment, significant bitemporal hypoperfusion relative to the cerebellum was found, which was no longer demonstrable on remission.     

Recognition of Arabic (Indian) bank check digits using log-gabor filters

In this paper we present a technique for the automatic recognition of Arabic (Indian) bank check digits based on features extracted by using the Log Gabor filters. The digits are classified by using the K-Nearest Neighbor (K-NN), Hidden Markov Models (HMM) and Support Vector Machines (SVM) classifiers. An extensive experimentation is conducted on the CENPARMI data, a database consisting of 7390 samples of Arabic (Indian) digits for training and 3035 samples for testing extracted from real bank checks. The data is normalized to a height of 64 pixels, maintaining the aspect ratio. Log Gabor filters with several scales and orientations are used. In addition, the filtered images are segmented into different region sizes for feature extraction. Recognition rates of 98.95%, 98.75%, 98.62%, 97.21% and 94.43% are achieved with SVM, 1-NN, 3-NN, HMM and NM classifiers, respectively. These results significantly outperform published work using the same database. The misclassified digits are evaluated subjectively and results indicate that human subjects misclassified 1/3 of these digits. The experimental results, including the subjective evaluation of misclassified digits, indicate the effectiveness of the selected Log Gabor filters parameters, the implemented image segmentation technique, and extracted features for practical recognition of Arabic (Indian) digits.