A real method of predication brake pad wear ,could lead to substantiol economies of time and money. This paper describes how such a procedure has been used and gives the results to establish is reliability by comparing the predicted wear with that which actually occurs in an existing service. The experimental work was carried out on three different commercial samples ,tested under different operation conditions (speed,load,time...etc)using a test ring especially modified for this purpose. Abrasive wear is mainly studied , since it is the type of wear that takes place in such arrangements. Samples wear tested in presences of sand or mud between the mating surfaces under different operational conditions of speed, load and braking time .Mechanical properties of the pad material samples (hardness, young,s modulus and collapse load under pure bending condition )wear established . The thermal conductivity and surface roughness of the pad material wear also found in order to enable comparison between the surface condition before and after testing. Sliding velocity had a small effect on the wear rate but it had great effect on friction coefficient. Wear rate was affected mainly by the surface temperature which causing a reduction friction coefficient and increasing the wear rate. Surface roughness had almost no effect on the wear rate since it was proved experimentally ,that the surface becomes softer during operation .mechanical properties of the pad material had fluctuating effect on wear rate. The existence of solid particles between pad and disc increasing wear rate and friction coefficient while the mud caused a reduction in wear rate of the pad surface since it acts as a lubricant absorbing the surface heat generated during sliding the area of contact between pad and disc. wear rate obtained experimentally agreed fairly well that found from empirically obtained equations.
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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Background The appropriate disposal of medication is a well-recognized issue that has convened growing recognition in several contexts. Insufficient awareness relating to appropriate methods for the disposal of unneeded medicine may result in notable consequences. The current research was conducted among the public in Iraq with the aim of examining their knowledge, attitude, and practices regarding the proper disposal of unused and expired medicines. Methods The present study used an observational cross-sectional design that was community-based. The data were obtained from using an online questionnaire. The study sample included people of diverse genders, regardless of their race or occupational status. The study mandated that all pa
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Tungsten inert gas arc welding–based shaped metal deposition is a novel additive manufacturing technology which can be used for fabricating solid dense parts by melting a cold wire on a substrate in a layer-by-layer manner via continuous DC arc heat. The shaped metal deposition method would be an alternative way to traditional manufacturing methods, especially for complex featured and large-scale solid parts manufacturing, and it is particularly used for aerospace structural components, manufacturing, and repairing of die/molds and middle-sized dense parts. This article presents the designing, constructing, and controlling of an additive manufacturing system using tungsten inert gas plus wire–based shaped metal deposition metho
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The present study aimed to investigate the possible production of Thioflavin T and the effect of NaCl concentrations and growth phases on the growth rate, doubling time and proline of C. saipanensis N. Hanagata (Scenedesmaceae, Shaerophleales). The alga was cultured in BG 11 medium and six NaCl concentrations were used in the experiments during different growth phases. The results have unveiled the presence of Triflavin T in the alga. The study results showed a growth rate decrease at all NaCl concentrations except in control treatment, while the doubling time, was recorded highest value (14 days) at the NaCl concentration of 0.08 M. The highest value of Proline (0.509 mg. Lˉ¹) was recorded at the treatment of 0.08 M of NaCl and recorded
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