Motifs template is the input for many bioinformatics systems such codons finding, transcription, transaction, sequential pattern miner, and bioinformatics databases analysis. The size of motifs arranged from one base up to several Mega bases, therefore, the typing errors increase according to the size of motifs. In addition, when the structures motifs are submitted to bioinformatics systems, the specifications of motifs components are required, i.e. the simple motifs, gaps, and the lower bound and upper bound of each gap. The motifs can be of DNA, RNA, or Protein. In this research, a motif parser and visualization module is designed depending on a proposed a context free grammar, CFG, and colors human recognition system. GFC describes the m

Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co

The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen

Reliability analysis methods are used to evaluate the safety of reinforced concrete structures by evaluating the limit state function 𝑔(𝑋𝑖). For implicit limit state function and nonlinear analysis , an advanced reliability analysis methods are needed. Monte Carlo simulation (MCS) can be used in this case however, as the number of input variables increases, the time required for MCS also increases, making it a time consuming method especially for complex problems with implicit performance functions. In such cases, MCS-based FORM (First Order Reliability Method) and Artificial Neural Network-based FORM (ANN FORM) have been proposed as alternatives. However, it is important to note that both MCS-FORM and ANN-FORM can also be time-con

This research aims at studying each of the cold and hot thermal wavelengths affecting
Iraq for a minimum climatic course of 11 years beginning from 1992 till 2002. Three stations
were selected including the parts of Iraq surface: Mosul, Baghdad and Basrah.
The wave days were also connected with the related climatic elements represented by
the wind direction and speeds and the relative humidity. It was shown that Iraq is affected by
the rates of hot thermal wave lengths greatly compared to the rates of cold wavelengths. The
results suggested that the highest rate of hot and cold wavelengths recorded over Basra station
was (3.5) days for the cold and (5) days for the hot. While the lowest rates was at Mosul
station

The Iraqi houses flattening the roof by a concrete panel, and because of the panels on the top directly exposed to the solar radiation become unbearably hot and cold during the summer and winter. The traditional concrete panel components are cement, sand, and aggregate, which have a poor thermal property. The usage of materials with low thermal conductivity with no negative reflects on its mechanical properties gives good improvements to the thermal properties of the concrete panel. The practical part of this work was built on a multi-stage mixing plan. In the first stage the mixing ratio based on the ratios of the sand to cement. The second stage mixing ratios based on replacing the coarse aggregate quantities with the

   In the oil industry, the processing of vacuum residue has an important economic and environmental benefit. This work aims to produce industrial petroleum coke with light fuel fractions (gasoline, kerosene , gas oil) as the main product and de asphalted oil (DAO) as a side production from treatment secondary product matter of vacuum residue. Vacuum residue was produced from the bottom of vacuum distillation unit of the crude oil. Experimentally, the study investigated the effect of the thermal conversion process on (vacuum residue) as a raw material at temperature reaches to 500 °C, pressure 20 atm. and residence time for about 3 hours. The first step of this treatment is constructing a carbon steel batch re

In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.