Radon is the air contaminant radioactive gas which people exposed to, is a reason for lung damages and lung cancer. The areas that are subject to high radon levels are found by radon concentration measurement. The radon activity concentration, annual effective dose, and potential alpha energy concentration (PAEC), were measured in houses of Ainkawa region using CR-39 solid state nuclear track detectors SSNTDs with the sealed-can technique. In the present paper the estimated values for radon activity concentration are in the range 55.99-112.8 Bq/m³ with 84.30 Bq/m³ as a mean value, the range of annual effective dose are 1.411-2.872 mSv/y, with mean value 2.124 mSv/y, and the potential alpha energy c

Radon concentrations are measured for water samples collected from twenty wells which were drilled in Hashimiya area in addition to twelve samples of surface water using Alpha Gaurd. 140 samples, 7 for each well, were collected represent wet season in continuous pumping and 20 samples, one for each well, were collected represent dry season. Concentration of radon in groundwater is many times of its concentration in surface water. The minimum concentration in groundwater is about (7) Bq/L and (5) Bq/L while the maximum concentration is about (31) Bq/L and (19) Bq/L in wet season and dry season respectively. The range of radon concentrations in river water is between (1.06) Bq/L and (1.21) Bq/L. This study has indicated that there is a flo

In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

This paper presents a hierarchical two-stage outdoor scene classification method using multi-classes of Support Vector Machine (SVM). In this proposed method, the gist feature of all the images in the database is extracted first to obtain the feature vectors. The image of database is classified into eight outdoor scenes classes, four manmade scenes and four natural scenes. Second, a hierarchical classification is applied, where the first stage classifies all manmade scene classes against all natural scene classes, while the second stage of a hierarchical classification classifies the outputs of first stage into either one of the four manmade scene classes or natural scene classes. Binary SVM and multi-classes SVMs are employed in the fir

Feature extraction provide a quick process for extracting object from remote sensing data (images) saving time to urban planner or GIS user from digitizing hundreds of time by hand. In the present work manual, rule based, and classification methods have been applied. And using an object- based approach to classify imagery. From the result, we obtained that each method is suitable for extraction depending on the properties of the object, for example, manual method is convenient for object, which is clear, and have sufficient area, also choosing scale and merge level have significant effect on the classification process and the accuracy of object extraction. Also from the results the rule-based method is more suitable method for extracting

Median filter is adopted to match the noise statistics of the degradation seeking good quality smoothing images. Two methods are suggested in this paper(Pentagonal-Hexagonal mask and Scan Window Mask), the study involved modified median filter for improving noise suppression, the modification is considered toward more reliable results. Modification median filter (Pentagonal-Hexagonal mask) was found gave better results (qualitatively and quantitatively ) than classical median filters and another suggested method (Scan Window Mask), but this will be on the account of the time required. But sometimes when the noise is line type the cross 3x3 filter preferred to another one Pentagonal-Hexagonal with few variation. Scan Window Mask gave bett