Psychology is one of the sciences that consciously overlap in terms of mutual influence with art forms in general and cinematic arts in particular. The psychological effect can be extrapolated into the visual image through the characters and their actions, especially the adoption of psychoanalytic ideas and proposals that came by (Freud), The cinema benefited from the concepts of psychology and participated in the process of creativity and the manufacture of events or the actions of characters, such as the concepts of consciousness and subconsciousness to express the psychological dimension of the film events, these data can be counted on the level of nightmares in the cinematic movies.
The methodological framework included the research problem, which is determined by the following question: What is the psychology of nightmares (horror) in the cinematic movie? And then the researcher stated the value of the research, as well as the aims and limits of the research. The theoretical framework included two sections, the first section: the psychology of the dream. As for the second section: the nightmares (horror) in the cinematic movie, and the researcher came up with the indicators of the theoretical framework. As for the research procedures, it includes the research methodology, the research tool, the research community, the unit of analysis and the research sample. Finally, the analysis of the intended sample represented by the movie (The Call of the Beast), and the researcher came out with a set of results from the analysis of the research sample and conclusions
Industrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil
... Show MoreIn 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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