In this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample

In the arid to semi-arid lands the extracted hydrological features are essential ones, since their effect on water projects managing, agricultural projects administrating, and animals grazing, so that this research is considered to be vital research because the climate of Qurain AL-Thamad basin is arid climate and basin region inhabited by many tribes who works in agricultural and grazing fields. The illustration of hydrological features using morphometric analyses is optimum since the quantization issue of basin factors, in the past this would be difficult using classical procedures (i.e. using paper topographic maps and planmeter). Recently as in this work modern procedures has been used (i.e. satellite imagery DEM as ancillary image a

 Data Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the need

     This study aims to build a wireless computer network for a large company or university to enhance mobility and allow university users to stay connected at any time or place, which is achieved by applying the Universal Interoperability for Microwave Access (WiMax) technology. WiMax is based on the 802.16 sets of standards and has the most efficient and advanced hardware capabilities to meet the demands of teachers and students to browse the web or download files quickly. OPNET Modeler version 14.5 was used to determine the quality of service parameters of WiMax.

A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un

In the present study rice microsatellite marker (RM 171) was used to evaluate the genetic diversity and determining cultivar identity among ten rice varieties (oryza sativa L.) (Seven local and three commercial varieties). PCR technique was performed using two specific primers. The result showed presence of a band (305bp) DNA sequencing was done to PCR product to detect sequence variation between the ten rice varieties. In order to detect the relationship among all varieties, alignment of RM171 marker sequence was carried out for each variety. Amber and Daawat varieties showed the highest similarity with 98% identity, while the difference (2%) consists of two gaps and two transition mutations (T/C) and (C/T). Furthermore, Amber was align

Due to the lack of vehicle-to-infrastructure (V2I) communication in the existing transportation systems, traffic light detection and recognition is essential for advanced driver assistant systems (ADAS) and road infrastructure surveys. Additionally, autonomous vehicles have the potential to change urban transportation by making it safe, economical, sustainable, congestion-free, and transportable in other ways. Because of their limitations, traditional traffic light detection and recognition algorithms are not able to recognize traffic lights as effectively as deep learning-based techniques, which take a lot of time and effort to develop. The main aim of this research is to propose a traffic light detection and recognition model based on

This study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J