The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

The current research variables have received increasing attention in the recent period because they are one of the important issues affecting the future of organizations, as a result of the speed of environmental variables that have greatly affected organizations and for the purpose of explaining the relationships and links between research variables, as this research presents a test "the type and direction of the relationship between strategic foresight capabilities As an independent variable and green creativity "as a respondent variable. A set of questions has arisen about the basic research problem, including what is the nature and level of interest in the research variables (strategic foresight capabilities an

Abstract

The study presents a mathematical model with a disaggregating approach to the problem of production planning of a fida Company; which belongs to the ministry of Industry. The study considers disaggregating the entire production into 3 productive families of (hydraulic cylinders, Aldblatt (dampers), connections hydraulics with each holds similar characteristics in terms of the installation cost, production time and stock cost. The Consequences are an ultimate use of the available production capacity as well as meeting the requirements of these families at a minimal cost using linear programming. Moreover, the study considers developing a Master production schedule that drives detailed material and production requi

Background: To evaluate the effect of antierosive agents (10% Nano-Hydroxyapatite (NHA), 10% Casein Phophopeptide-Amorphous Calcium Phosphate (CPP-ACP), and combination of 10% NHA and 10% CPP-ACP) on loss of minerals from enamel surface of permanent teeth treated with antierosive agents when exposed to an acidic beverage and investigate the morphological changes of treated enamel surface after demineralization with cola based beverage under Scanning Electron Microscope (SEM). Materials and Methods: Sixty maxillary first premolars were randomly divided into four groups, 15 teeth for each group. Group I treated with 10% NHA, Group II treated with 10% CPP-ACP, Group III treated with 10% NHA and 10% CPP-ACP, and Group IV did not treat with any

Esterification reaction is most important reaction in biodiesel production. In this study, oleic acid was used as a suggested feedstock to study and simulate production of biodiesel. Batch esterification of oleic acid was carried out at operating conditions; temperature from 40 to 70 °C, ethanol to oleic acid molar ratio from 1/1 to 6/1, H2SO4 as the catalyst 1 and 5% wt of oleic acid, reaction time up to 180 min. The optimum conditions for the esterification reaction were molar ratio of ethanol/oleic acid 6/1, 5%wt H2SO4 relative to oleic acid, 70 °C, 90 min and conversion of oleic 0.92. The activation energy for the suggested model was 26625 J/mole for forward reaction and 42189 J/mole for equilibrium constant. The obtained results s

In this study, a proposed process for the utilization of hydrogen sulphide separated with other gases from omani natural gas for the production of sulphuric acid by wet sulphuric acid process (WSA) was studied. The processwas simulated at an acid gas feed flow of   5000 m³/hr using Aspen ONE- V7.1-HYSYS software. A sensitivity analysis was conducted to determine the optimum conditions for the operation of plant. This included primarily the threepacked bed reactors connected in series for the production of sulphur trioxidewhich represented the bottleneck of the process. The optimum feed temperature  and catalyst bed volume for each reactor were estimated and then used in the simulation of the whole process for tw

Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of  groups based on a linear combination of a set of relevant variables know discriminant function. In this research  discriminant analysis used to analysis data from repeated measurements design. We  will  deal  with the problem of  discrimination  and  classification in the case of  two  groups by assuming the Compound Symmetry covariance structure  under  the  assumption  of  normality for  univariate  repeated measures data.

Soil wetted pattern from a subsurface drip plays great importance in the design of subsurface drip irrigation (SDI) system for delivering the required water directly to the roots of the plant. An equation to estimate the dimensions of the wetted area in soil are taking into account water uptake by roots is simulated numerically using HYDRUS (2D/3D) software. In this paper, three soil textures namely loamy sand, sandy loam, and loam soil were used with three different types of crops tomato, pepper, and cucumber, respectively, and different values of drip discharge, drip depth, and initial soil moisture content were proposed. The soil wetting patterns were obtained at every thirty minutes for a total time of irrigation equ