According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through the conveyor belt motion. An optimal speed controlling mechanism of the conveyor belt is presented by detecting smartly the parts' number and weights using the vision sensor, where the latter will give sufficient visualization about the system. Then image processing will deliver the important data to ANN, which will optimally decide the best conveyor belt speed. This decided speed will achieve the aim of power saving in belt motion. The proposed controlling system will optimally switch the speed of the conveyor belt system to ON, OFF and idle status in order to minimize the consumption of energy in the conveyor belt. As the conveyor belt is fully loaded it moves at its maximum speed. But if the conveyor is partially loaded, the speed will be adjusted accordingly by the ANN. If no loading existed, the conveyor will be stopped. By this way, a very significant energy amount in addition to cost will be saved. The developed conveyor belt system will modernize industrial manufacturing lines, besides reducing energy consumption and cost and increasing the conveyor belts lifetime
Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak
... Show MoreThis study reports on natural convection heat transfer in a square enclosure of length (L=20 cm) with a saturated porous medium (solid glass beads) having same fluid (air) at lower horizontal layer and free air fill in the rest of the cavity's space. The experimental work has been performed under the effects of heating from bottom by constant heat flux q=150,300,450,600 W/m2 for four porous layers thickness Hp (2.5,5,7.5,1) cm and three heaters length δ(20,14,7) cm. The top enclosure wall was good insulated and the two side walls were symmetrically cooled at constant temperature. Four layers of porous media with small porosity, Rayleigh number range (60.354 - 241.41) and (Da) 3.025x10-8 has been investigated. The obtained data of temperatu
... Show MoreIn diabetes, impaired wound healing and other tissue abnormalities are considered major concerns. Many factorsaffect the time and quality of wound healing. One of the purposes of medical sciences is wound healing in a short time withreduced side effects. The herbal products are more precious in both prophylaxis as well as curative in delayed diabetic woundhealing activity when compared to synthetic drugs.A wide range of evidence has shown that capers plant possesses differentbiological effects, including antioxidant, anticancer and antibacterial effects. Phytochemical analysis shows thatC. spinosahashigh quantities of bioactive constituents, including polyphenolic compounds, which are responsible for its health-promotingeffects. The healing
... Show MoreCompounds of (ZnO)1-x(SnO 2 ) x were prepared with various proportions of tin oxide (SiO 2) (x = 0.0, 0.2, 0.4, 0.6, 0.8, 1.0) by mixing zinc oxide (ZnO) with highpurity tin oxide and then sintering the mixture in an oven at a temperature of 1000 °C for a period of 1 h. The resulting powders were ground and pressed into tablets of 1 cm diameter and 0.5 cm thickness. The properties of (ZnO) 1-x(SnO 2 ) x composites flms were prepared and studied as sensitive to the diferent gases NO2 and H2 S. Thin flms were prepared from (ZnO) 1-x(SnO 2 ) x via pulsed laser deposition method using glass and single crystal silicon for investigation the morphology and gas sensing properties with a thickness of 150 nm. The morphology examinat
... Show MoreThis study explored the feasibility of removing nickel (Ni) and Pb (II) from water solutions using the adsorption technique by cellulose recovered from office paper waste. Metal removal is required to reduce the direct or indirect exposure of industrial waste to the environment, due to its potential for harm to human health and ecosystems. The release criterion is maintained to keep the efficient wastewater treatment of the metals of concern, which are toxic to both humans and other organisms. The cellulose was first prepared from office paper waste. The removal values can be rationalized as follows: Lead removal efficiencies of were obtained upto %95.0632, while the removals of nickel were obtained as 54.3866%. The adsorption proce
... Show MoreObjective: To evaluate the effectiveness of educational program on female students’ knowledge toward premenstrual syndrome.
Methodology: A quasi-experimental design study conducing on (140) student purposely in four secondary schools at Al-sadder city (70) student for study group and (70) for control group. The prevalence of PMS selected through American College of Obstetricians and Gynecologists (ACOG) (2015) criterias to select PMS students before program. The education program were set in four steps, the first step (pre-test) is to assess the knowledge , before the implementation of the program, the second step is implementing the program, following two steps post-test I and II between each test two weeks. Validity is determined