This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera images and later distinguished vehicles are assigned to the looking at route segment so instantaneous and current velocities are calculated. All data were effectively processed and visualized using both MATLAB and Python programming language and its libraries.
Objective: Aimed to asses the role of PT estimation in early diagnosis and predicting the extent and the outcome of head injury with ICerH and/ or Contusion
Method :PT was measured by Digiclot 818
Group –1: One hundred consecutive head injured patients admitted at Neurosurgical and Al Ramadi teaching hospitals were initially estimated for prothrombin time and subsequently scanned
Group-2 : Two hundred twenty five consecutive non scanned head injured patients admitted to Neurosurgical and Al Ramadi teaching hospitals were estimated with prothrombin time at the time of insult and subsequently for the next two weeks Al – Kindy Col Med J 2012; Vol. 8 No. 1 P: 54
Clinical and neurological evaluation (GCS) score in addition to
Recently, Malaysia has been recognized as one of the most popular destinations for Foreign Direct Investment (FDI) in Southeast Asia. But how do these FDI inflows affect Malaysia economy? This paper aims to identify the role of FDI inflows in Malaysia economic growth through a proposed endogenous growth model. Annual data covers from 1975 to 2010. Unit root test and Johansen Co-integration test are adopted to respectively verify the time series data is stable and the linear combination of the variables is stationary. Hierarchical Multiple Regressions (HMR) Analysis is then conducted to find out the momentum of the Malaysia economic growth including FDI inflows. The results show that the FDI inflows together with the human capital deve
... Show MoreA Tonido cloud server provides a private cloud storage solution and synchronizes customers and employees with the required cloud services over the enterprise. Generally, access to any cloud services by users is via the Internet connection, which can face some problems, and then users may encounter in accessing these services due to a weak Internet connection or heavy load sometimes especially with live video streaming applications overcloud. In this work, flexible and inexpensive proposed accessing methods are submitted and implemented concerning real-time applications that enable users to access cloud services locally and regionally. Practically, to simulate our network connection, we proposed to use the Raspberry-pi3 m
... Show MoreThe compressive residual stresses generated by shot peening, is increased in a direct proportional way with shot peening time (SPT). For each metal, there is an optimum shot peening time (O.S.T) which gives the optimum fatigue life. This paper experimentally studied to optimize shot peening time of aluminium alloy 6061-T651 as well as using of and analysis of variance (ANOVA).
Two types of fatigue test specimens’ configuration were used, one without notch (smooth) and the other with a notch radius (1,25mm), each type was shot peened at different time. The (O.S.T) was experimentally estimated to be 8 minutes reaching the surface stresses at maximum peak of -184.94 MPa.
A response surface methodology (RSM) is presen
... Show MoreThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreThere is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardn
Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate
... Show MoreSamples prepared by using carbon black as a filler material and phenolic resin as a binder. The samples were pressed in a (3) cm diameter cylindrical die to (250)MPa and treated thermally within temperature range of (600-1000)oC for two and three hours. Physical properties tests were performed, like density, porosity, and X-ray tests. Moreover vicker microhardness and electric resistivity tests were done. From the results, it can be concluded that density was increased while porosity was decreased gradually with increasing temperature and treating time. In microhardness test, it found that more temperature and treating time cause more hardness. Finally the resistivity was decreased in steps with temperature and treating time. It can be c
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