This research provides a study of the virtual museums features and characteristics and contributes to the recognition of the diversity of visual presentation methods, as the virtual museums give the act of participation and visual communication with programs at an open time, so that it would contribute to reflection, thinking and recording notes, developing the actual and innovative skills through seeing the environments. The study has been divided into two sections the first one is virtual museum techniques. The techniques were studied to reach the public and are used remotely by the services of personal computers or smart phones being virtual libraries that store images and information that was formed and built in a digital way and how the aesthetics of the virtual museum had a profound effect on reception. The second section was the aesthetics of the imaginary space in the virtual museum to study the analysis of the samples, the diversity of presentation methods in virtual museum space. The research ended up with the results and conclusions. The importance of virtual museums which invest that space in the presentation is that they present information in a simple and interesting way in receiving the experiences and the viewer has the freedom to choose the distance in which he sees the work and the ease of touching the different dimensions of objects through the sense of sight. The virtual museums are areas located within the Internet whose purpose is advertising and defining a museum which could have no presence in reality. The use of virtual museums technologies, and accelerated technical progress and developments in the field of communication and technology and the growing interest in knowledge and discovery increased. The research ended up with some recommendations and proposals.
Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte
... Show MoreCapparis spinosa is one of the oldest genera grown in Iraqi land with worldwide traditional medicinal uses beside the culinary uses. These uses were own to the presence of many phytochemical including flavonoids, polyphenols. Among the reported polyphenolic acids are caffeic, chlorogenic and ferulic acids with well-known powerful antioxidant properties. The present work aimed to identify the presence of these polyphenolic acids in Iraqi caper naturally gown in the rural area of middle Iraq following standard chromatographic procedures. Aerial parts of the plant (buds, berries and leaves) were extracted with hydroalcoholic solvent by maceration method. Thin layer chromatographic techniques and HPLC analysis were performed to iden
... Show MoreWith the aim of developing potential antimicrobials, a series of novel Ciprofloxacin methylene isatin derivatives incorporating different aromatic aldehydes were synthesized and characterized by FTIR, 1H NMR, Mass spectroscopy and bases of elemental analysis. In addition, the in vitro antibacterial and antifungal properties were tested against some human pathogenic microorganisms by employing the disc diffusion technique. A majority of compounds were showing activity against several of the microorganisms. The relationship between the functional group variation and the biological activity of the evaluated compounds is discussed. From comparisons of the compounds, 3c was determined to be the most active compound.
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
... Show MoreABSTRACT Background: Diabetes and periodontitis are complicated prolonged disorders through a recognized two-way association. There is elongated-conventional mark that hyperglycaemia in diabetes is affected on immune-inflammatory response and disturb the action of osteoclast and in balance bone turnover, which might rise the person vulnerability to the progress of prolonged periodontitis. Osteocalcin is one of the greatest plentiful matrix proteins originate in bones and produced absolutely there. Small osteocalcin crumbles are noticed in regions of bone remodeling and are in fact degradation products of the bone matrix, that is released outside cells into the Gingival Crevicular Fluid (GCF) and saliva after destruction of periodontal tissu
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