This paper studies the effects of stiffeners on shear lag in steel box girders with stiffened flanges. A three-dimensional linear finite element analysis using STAAD.Pro V8i program has been employed to evaluate and determine the actual top flange stress distribution and effective width in steel box girders. The steel plates of the flanges and webs have been modeled by four-node isoparametric shell elements, while the stiffeners have been modeled as beam elements. Different numbers (4, 8, and 15) for the steel stiffeners have been used in this study to establish their effects on the shear lag and longitudinal stresses in the flange. Using stiffeners reduced the magnitude of the top flange longitudinal stresses about 40%, but did

Praise be to God, Lord of the worlds, and the best of prayers, and the completion of the blessing of our master Muhammad Al-Hadi Al-Amin, his family and companions, the righteous and those who followed his path and guided him to the day of judgment.
And after:
It is God's human honor that he has legalized marriage and made optimal goals and intentions for her:
1 establish a safe and reassuring life between the husband and his wife based on the tranquility and love and compassion is achieved through satisfying the instincts of the road project from the verse:  and that He created for you mates from among yourselves to find repose in them and put between you affection and mercy in this are Signs for those who reflect  ()

Porous silicon (P-Si) has been produced in this work by photoelectrochemical (PEC) etching process. The irradiation has been achieved using diode laser of (2 W) power and 810 nm wavelength. The influence of various irradiation times on the properties of P-Si material such as P-Si layer thickness, surface aspect, pore diameter and the thickness of walls between pores as well as porosity and etching rate was investigated by depending on the scanning electron micrograph (SEM) technique and gravimetric measurements.

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre

Global warming has had considerable effects on vital ecosystems, which has also been caused by increased temperatures and CO₂ that follow changes in different abiotic factors, which poses threats to mangrove forests environment. This research was conducted to examine the physiological and morphological characteristics of the Rhizophora apiculata mangrove regarding higher air temperature for the variety of tree species that respond to climate change. Seedlings were cultivated for three months in regulated growth chambers with three varying temperatures of 38°C, 21°C under CO₂ at 450 ppm, and ambient CO₂ concentration i.e., 450 ± 20 ppm under average temperature at 28°C as the control condition