For many years, the construction industry damages have been overlooked such as unreasonable consumption of resources in addition to producing a lot of construction waste but with global awareness growth towards the sustainable development issues, the sustainable construction practices have been adopted, taking into account the environment and human safety. The research aims to propose a management system for construction practices which could be adopted during constructing different types of sustainable buildings besides formulating flowcharts which clarify the required whole phases of sustainable buildings life cycle. The research includes two parts: theoretical part which generally ,handles the sustainability concepts at construction i

Human interaction technology based on motion capture (MoCap) systems is a vital tool for human kinematics analysis, with applications in clinical settings, animations, and video games. We introduce a new method for analyzing and estimating dorsal spine movement using a MoCap system. The captured data by the MoCap system are processed and analyzed to estimate the motion kinematics of three primary regions; the shoulders, spine, and hips. This work contributes a non-invasive and anatomically guided framework that enables region-specific analysis of spinal motion which could be used as a clinical alternative to invasive measurement techniques. The hierarchy of our model consists of five main levels; motion capture system settings, marker data

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Background: The final stage of endodontic therapy is complete obturation of the root canal system to provide as perfect as possible at the cementodentinal junction of the apical foramen. The purpose of this in vitro study was to evaluate the sealing ability of injection molded thermoplasticized gutta percha and lateral condensation techniques with and without the use of sealers. Materials and Methods: Forty freshly extracted adult human maxillary central incisors with complete formed apices were utilized in this study. The teeth were randomly divided into four groups for evaluation of the apical seal. Group (1) lateral condensation gutta percha technique without sealer, (2) lateral condensation gutta percha technique with sealer, (3) Inject

Exposing the dorsal superficial skin of rats to partial-depth burn leads to bacterial and microbes Invasion. Topical treatment is required in most superficial burn cases Moist exposed burn ointment (MEBO) protects wounds from infection and enhances healing without any harmful effects of purified chemicals is caused. The topical using of HA gel in rat models with full and partial thickness surgical wounds shows enhancement in wound repair. In this study, we compared the healing efficacy of topical use of hyaluronic acid gel products with MEBO as standard management in rats that were exposed to a partial-thickness burn. The experiment included twenty-four (24) adult albino rats of male sex with weight (150-220 gm) of 3 months’ age divided i

Four antimony compounds were used in this inves as additives to retard combustion of unsaturated polyester and epoxy resins, namely: 1. Tetraethyl ammonium tribromoethylantimonates (additive I). 2. Tetraethyl ammonium chlorodibromoethylantimonates (additive II). 3. Tetraethyl ammonium trichloroethylantimonates (additive III). 4. Tetraethyl ammonium bromodichloroethylantimonates (additive IV). The effects of these additives on flammability of unsaturated polyester and epoxy resins have been studied by using sheets of the resins with weight percentages of (0.5,1.0,1.5,2.0,2.5&3.0%) of the additives in dimensions of (150 X150X3)mm .Three standard test methods were used to measure the flame retardation which are: (ASTM:D -2863), (ASTM:D-635