Zernike Moments has been popularly used in many shape-based image retrieval studies due to its powerful shape representation. However its strength and weaknesses have not been clearly highlighted in the previous studies. Thus, its powerful shape representation could not be fully utilized. In this paper, a method to fully capture the shape representation properties of Zernike Moments is implemented and tested on a single object for binary and grey level images. The proposed method works by determining the boundary of the shape object and then resizing the object shape to the boundary of the image. Three case studies were made. Case 1 is the Zernike Moments implementation on the original shape object image. In Case 2, the centroid of the s

In this paper, a hybrid image compression technique is introduced that integrates discrete wavelet transform (DWT) and linear polynomial coding. In addition, the proposed technique improved the midtread quantizer scheme once by utilizing the block based and the selected factor value. The compression system performance showed the superiority in quality and compression ratio compared to traditional polynomial coding techniques.

The aim of this research was to analyze the financial reporting requirements of segmental information that stipulated by the Iraqi accounting rules, investigating the extent of it compliance with the requirements of the International Financial Reporting Standard No.8 (IFRS 8) and the Statement of Financial Standards No.131 (SFAS 131). Also the research aimed to identify the segmental disclosure practices in listed corporations on Iraq Stock Exchange (ISX), basing on a hypotheses said that “the insufficient  of Iraqi financial reporting requirements of segmental information affect<

  This paper deals  the prediction of the process of  random spatial data of two properties, the first is called  Primary variables  and the second is called secondary  variables ,   the method  that were used in the  prediction process for this type  of data is technique Co-kriging  , the method is usually used when the number of primary variables  meant to predict for one of its elements is measured in a particular location a few (because of the cost or difficulty of obtaining them) compare with secondary variable which is the number of elements  are available and  highly correlated with primary variables, as was the&nbs

the researchers pointed that the poet relied on several means in the form of poetic images, including analogy, and the metaphor with its various elements, The chromatic component has also been used in the formation of its poetic image,and resorted to the correspondence of the senses and the symbol of two types:Self-code, public code : And we find a variety of symbolic stems from different sources, from these symbols, what is religious, including what is historical and what is legendary, and such symbols, which resorted to the rare places of his poems confined to the myths contained in the Bible, His use of the general symbols was ineffective in the poetic picture, relying on the metaphor and metaphor.

The aim of the research is to use the data content analysis technique (DEA) in evaluating the efficiency of the performance of the eight branches of the General Tax Authority, located in Baghdad, represented by Karrada, Karkh parties, Karkh Center, Dora, Bayaa, Kadhimiya, New Baghdad, Rusafa according to the determination of the inputs represented by the number of non-accountable taxpayers and according to the categories professions and commercial business, deduction, transfer of property ownership, real estate and tenders, In addition to determining the outputs according to the checklist that contains nine dimensions to assess the efficiency of the performance of the investigated branches by investing their available resources T

This study deals with the processing  of field seismic data for a seismic line located within the administrative boundaries of Najaf and Muthanna governorates in southern Iraq (7Gn 21) with a length of 54 km. The study was conducted within the Processing Department of the Oil Exploration Company using the Omega  system, which contains a large number of programs that deal with processing, through the use of these programs applied  predictive deconvolution  of both( gap) and (spike). The final section was produced for both types. The gap predictive deconvolution  gave improvement in the shallow reflectors while in deep reflectors it did not give a good improvement, thus giving a good continuity of the reflectors at

This research aims to study the structural analysis of the 2D reflection seismic data for the Judaida subsurface structure located in Kirkuk province, northern Iraq. It is located 60 Km southwest of Kirkuk oil field, and 35 Km southwest of Jambur oil field, the Daquq River passes through the study area. The reflectors in the seismic section were picked and identified by using the synthetic seismograms generated from the logs data of the Jd-1 well. Three main seismic reflectors, Fatha, Jeribe, and the Euphrates were chosen. These mentioned sedimentary formations were deposited during the Middle Miocene, Lower Miocene, and Early-Mid Miocene respectively. Time and depth maps were drawn for these three reflectors by processing average data f

     In-situ measurements of ultraviolet (UV) and solar irradiance is very sparse in Nigeria because of cost; it is  estimated using meteorological parameters. In this work, a low-cost UV and pyranometer device, using locally sourced materials, was developed. The instrument consists of a UV sensor (ML8511), a photodiode (BPW34) housed in a carefully sealed vacuumed glass bulb, the UV and solar irradiance sensor amplifiers, a 16-bit analog-to-digital converter (ADS1115), Arduino mega 2560, liquid crystal display (LCD) and microSD card for data logging. The designed amplifier has an offset voltage of 0.8676 mV. The sensitivity of the irradiance device is 86.819 Wm^-2/mV with a correcting factor of 27.77 Wm^-2 and a

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.