The study entitled (Anthropometric Treatments of the Study Seat Units Used in Elementary stages) highlighted the relations between the sizes of dimensions of the study seats and the different anthropometric sizes of the students. The study problem is manifested in the following question: what are the anthropometric treatments used in the design of the study seats in the elementary stages? The research aims at finding design treatments for the anthropometric variables of the study seats used in the elementary stages, because the study seats have to do with preserving students health and safety through providing an ideal seating mechanism compatible with the anthropometric variables which enhances comfort, safety and focus in the most important educational institution, in which the students spend half of their time, i.e. the school. The descriptive approach has been adopted in the analysis of the samples which represented (3. 33 %) of the research community. The results have shown that the design processes of the formal formations for the study seat units are (100%) incompatible with the anthropometric dimensions in the seat bench body (depth of the seat) in the samples (1-2) which resulted in discomfort and weakness in performance. The lack of backrests in study seat units led to poor functional effectiveness, and they lack safety and security for the students in the three samples with (100%). The study came up with important conclusions that the designer's prior knowledge of the anthropometric measures of the student contributes to activating the performance side( the functional and the formal) in order to achieve the integration feature for the student and the study seat units.
In this study, several ionanofluids (INFs) were prepared in order to study their efficiency as a cooling medium at 25 °C. The two-step technique is used to prepare ionanofluid (INF) by dispersing multi-walled carbon nanotubes (MWCNTs) in two concentrations 0.5 and 1 wt% in ionic liquid (IL). Two types of ionic liquids (ILs) were used: hydrophilic represented by 1-ethyl-3-methylimidazolium tetrafluoroborate [EMIM][BF4] and hydrophobic represented by 1-hexyl-3-methylimidazolium hexafluorophosphate [HMIM][PF6]. The thermophysical properties of the prepared INFs including thermal conductivity (TC), density and viscosity were measured experimental
We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure
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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