A roundabout is a highway engineering concept meant to calm traffic, increase safety, reduce stop-and-go travel, reduce accidents and congestion, and decrease traffic delays. It is circular and facilitates one-way traffic flow around a central point. The first part of this study evaluated the principles and methods used to compare the capacity methods of roundabouts with different traffic conditions and geometric configurations. These methods include gap acceptance, empirical, and simulation software methods. Previous studies mentioned in this research used various methods and other new models developed by several researchers. However, this paper's main aim is to compare different roundabout capacity models for acceptabl

The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the

Nosocomial infections are one of the most important causes of mortality and morbidity in hospitals. These are major public health problems worldwide, but particularly in developing countries. The purpose of this research was to analyze the frequency of the microorganisms in the specimens taken from the surgical wounds, and to examine antimicrobial susceptibility for some isolates . Wound swabs were examined from June 2010 to January 2011. The isolates were identified by conventional methods, antimicrobial susceptibility testing was performed by Kirby-Bauer disc diffusion method as per NCCLS guidelines.A total of 102 wound swabs were examined 22(21.56%) swabs were sterile and 80(78.43%) were positive for microorganisms. The results showed

Polycaprolactone polymer is widely used in medical applications due to its biocompatibility. Electro spinning was used to create poly (ε- caprolactone) (PCL) nanocomposite fiber mats containing hydroxyapatite (HA) at concentrations ranging from 0.05 to 0.4% wt. The chemical properties of the fabricated bio composite fibers were evaluated using FTIR and morphologically using field-emission scanning-electron microscopy (FESEM), Porosity, contact angle, as well as mechanical testing(Young Modulus and Tensile strength) of the nanofibers were also studied. The FTIR results showed that all the bonds appeared for the pure PCL fiber and the PCL/HA nano fibers. The FESEM nano fiber showed that the fiber diameter increased from 54.13 to 155.79 (n

A cost-effective and efficient detector was created to conduct thorough turbidimetric measurements by reaction of Co (II) ion with calcium ferro cyanide to form bright green particulate, using the method of continuous flow injection analysis, the use of NAG-5SX1-1D-SSP Analyzer in determining cobalt (II) ion in a test for the validity of the new design. The NAG-5SX1-1D-SSP Analyzer is composed of five irradiation sources of white snow leds having the diameter of 10 mm with one solar cell of 55 mm length, 13.5 mm width. Using a selector switch to select the optimum voltage to be used which was 2.7 VDC. Under conditions of optimization, cobalt (II) ion was determined at 0.005–20 mmol. L–1(n = 23) while linearity dynamic range 0.005–7 mm

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra