Multiple eliminations (de-multiple) are one of seismic processing steps to remove their effects and delineate the correct primary refractors. Using normal move out to flatten primaries is the way to eliminate multiples through transforming these data to frequency-wavenumber domain. The flatten primaries are aligned with zero axis of the frequency-wavenumber domain and any other reflection types (multiples and random noise) are distributed elsewhere. Dip-filter is applied to pass the aligned data and reject others will separate primaries from multiple after transforming the data back from frequency-wavenumber domain to time-distance domain. For that, a suggested name for this technique as normal move out- frequency-wavenumber domain

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

Three Seismic Attributes are used to enhance or delineate geologic feature that cannot be detected within seismic resolution limit. These are Instantaneous Amplitude, Instantaneous Phase and Instantaneous Frequency Attributes. These are applied along two defined picked surface horizons within 3D seismic data for an area in southern Iraq. Two geologic features are deduced, the first represents complex channel system at the top of Saadi Formation and the second represents submarine fan within Mishrif Formation. The semblances of these ancient geological features are dramatically enhanced by using flattening technique.

This paper attempts to shed light on the most influential factors in the importance of religious buildings were destroyed because of the recent war due to the control of terrorist gangs of ISIS over the city of Mosul, and to prioritize their reconstruction and their role in reviving the historical center of Mosul.

The research’s problem emerged in the lack of knowledge about the identifying the most influential factors in the importance of religious buildings and utilizing them to prioritize their reconstruction. This study aims to analyze the factors influencing the importance of religious buildings using the Expert Choice software through the Analytic Hierarchy Process (AHP) to reach an analysis of their weights and propose p

Tourism plays an important role in Malaysia’s economic development as it can boost business opportunity in its surrounding economic. By apply data mining on tourism data for predicting the area of business opportunity is a good choice. Data mining is the process that takes data as input and produces outputs knowledge. Due to the population of travelling in Asia country has increased in these few years. Many entrepreneurs start their owns business but there are some problems such as wrongly invest in the business fields and bad services quality which affected their business income. The objective of this paper is to use data mining technology to meet the business needs and customer needs of tourism enterprises and find the most effective

In order to find the relationship between Helicobacter pylori infection and hematological disease are disorders which primarily affect the blood and blood-forming organs. One hundred and three blood samples were taken for people aged (20-68) years for the period from 10/1/2021 to 1/3/2022, divided into three groups. The first group included 44-person H. pylori-infected with symptoms of infection, the second group had 19-person H. pylori-infected but without symptoms, and the third group included 40 people without H. pylori infection. All studied groups were carried out to measure anti-IgG Ab, Vac A and Ferritin by Enzyme Linked Immunosorbent Assay (ELISA) technique. The statistical analysis indicates a non-significant difference in Vac A (p

Merging biometrics with cryptography has become more familiar and a great scientific field was born for researchers. Biometrics adds distinctive property to the security systems, due biometrics is unique and individual features for every person. In this study, a new method is presented for ciphering data based on fingerprint features. This research is done by addressing plaintext message based on positions of extracted minutiae from fingerprint into a generated random text file regardless the size of data. The proposed method can be explained in three scenarios. In the first scenario the message was used inside random text directly at positions of minutiae in the second scenario the message was encrypted with a choosen word before ciphering