A new distribution, the Epsilon Skew Gamma (ESΓ ) distribution, which was first introduced by Abdulah [1], is used on a near Gamma data. We first redefine the ESΓ distribution, its properties, and characteristics, and then we estimate its parameters using the maximum likelihood and moment estimators. We finally use these estimators to fit the data with the ESΓ distribution

Increasing Mobile Device on Cloud Technology will dominate the various industries. Cloud has different data storage and data protecting techniques that based on Data User (DU) and industry’s needs. In this paper, an efficient way of managing user data sharing via Mobile Agent (MA) also called Mobile Proxy (MP) is proposed. The role of Mobile Agent Authorize User to collect the data from Cloud like Proxy and supply data to another Client due to this missing of cloud data is not possible. Instead of access data for all clients, the proxy hold required data and share the customer because of this network reliability, Network Bandwidth, User Congestion, Data Security. Also, this proposed scheme have more functionality like Cloud Authen

     Tectonically, the location of the Al-Ma'aniyah depression area is far from active boundary zones, their tectonic features have to reflect the original depositional environments with some horizontal movement due to rearrangement of the basement blocks during different actives orogenic movements. So, the analysis of aeromagnetic data were considered to estimate the thickness and structural pattern of the sedimentary cover sequences for this area. The aeromagnetic data, which are derived from Iraqi GEOSURV to Al-Ma′aniyah region is analyzed and processed for qualitative and quantitative interpretations. The process includes reducing the aeromagnetic data to pole RTP, separation the aeromagnetic data to regional an

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

ABSTRACT

            This study aimed to choose top stocks through technical analysis tools specially the indicator called (ratio of William index), and test the ability of technical analysis tools in building a portfolio of shares efficient in comparison with the market portfolio. These one technical tools were used for building one portfolios in 21 companies on specific preview conditions and choose 10 companies for the period from (March 2015) to (June 2017). Applied results of the research showed that Portfolio yield for companies selected according to the ratio of William index indicator (0.0406) that

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

Data mining is one of the most popular analysis methods in medical research. It involves finding patterns and correlations in previously unknown datasets. Data mining encompasses various areas of biomedical research, including data collection, clinical decision support, illness or safety monitoring, public health, and inquiry research. Health analytics frequently uses computational methods for data mining, such as clustering, classification, and regression. Studies of large numbers of diverse heterogeneous documents, including biological and electronic information, provided extensive material to medical and health studies.

Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

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