Radio observations from astronomical sources like supernovae became one the most important sources of information about the physical properties of those objects. However, such radio observations are affected by various types of noise such as those from sky, background, receiver, and the system itself. Therefore, it is essential to eliminate or reduce these undesired noise from the signals in order to ensure accurate measurements and analysis of radio observations. One of the most commonly used methods for reducing the noise is to use a noise calibrator. In this study, the 3-m Baghdad University Radio Telescope (BURT) has been used to observe crab nebula with and without using a calibration unit in order to investigate its impact on the signal. Radio observations of crab nebula have been carried out for different periods in 2022. Several parameters of the telescope have been calculated and analyzed using statistical measurements with and without using the noise calibration unit. Those parameters are receiver gain, system temperature, antenna temperature, and degree per flux unit. The results of this research revealed that the fluctuation sensitivity of BURT improved by about an order of magnitude, when the noise calibration unit is used. The root mean square error and the radiometer equation of the antenna temperature decreased to less than 33% and 10%, respectively in comparison to their initial values. In conclusion, the noise calibration unit plays a crucial role to improve the sensitivity of a radio telescope drastically.
The complexity of multimedia contents is significantly increasing in the current world. This leads to an exigent demand for developing highly effective systems to satisfy human needs. Until today, handwritten signature considered an important means that is used in banks and businesses to evidence identity, so there are many works tried to develop a method for recognition purpose. This paper introduced an efficient technique for offline signature recognition depending on extracting the local feature by utilizing the haar wavelet subbands and energy. Three different sets of features are utilized by partitioning the signature image into non overlapping blocks where different block sizes are used. CEDAR signature database is used as a dataset f
... Show MoreInvestigating the human mobility patterns is a highly interesting field in the 21th century, and it takes vast attention from multi-disciplinary scientists in physics, economic, social, computer, engineering…etc. depending on the concept that relates between human mobility patterns and their communications. Hence, the necessity for a rich repository of data has emerged. Therefore, the most powerful solution is the usage of GSM network data, which gives millions of Call Details Records gained from urban regions. However, the available data still have shortcomings, because it gives only the indication of spatio-temporal data at only the moment of mobile communication activities. In th
In this paper we deal with the problem of ciphering and useful from group isomorphism for construct public key cipher system, Where construction 1-EL- Gamal Algorithm. 2- key- exchange Algorithm
he aim of this study is to get a plant extracts to use it as molluscicides to control the snail vector of Schistosomiasis andfinely control the disease. Laboratory study was performed to compare the molluscicidal activity of leaves and stems extractsof Cucumis melo against Bulinus truncatus snail. The snail B. truncatus was exposed to a serial concentrations of leaves andstems extracts (4000ppm, 5000ppm) in this work. Different effects of the extracts to the snail B. truncatus were recorded.These effects includes death, escaping and imbalance of snail behavior. 96hr-LD50 values of leaves extracts were calculatedfor the doses 4000 and 5000ppm as (76 and 37%) respectively while for stems were (105 and 47%) respectively. We found thatthe snail
... Show MoreThe feature extraction step plays major role for proper object classification and recognition, this step depends mainly on correct object detection in the given scene, the object detection algorithms may result with some noises that affect the final object shape, a novel approach is introduced in this paper for filling the holes in that object for better object detection and for correct feature extraction, this method is based on the hole definition which is the black pixel surrounded by a connected boundary region, and hence trying to find a connected contour region that surrounds the background pixel using roadmap racing algorithm, the method shows a good results in 2D space objects.
Keywords: object filling, object detection, objec
This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.
Image Fusion Using A Convolutional Neural Network