In the present work, a density functional theory (DFT) calculation to simulate reduced graphene oxide (rGO) hybrid with zinc oxide (ZnO) nanoparticle's sensitivity to NO2 gas is performed. In comparison with the experiment, DFT calculations give acceptable results to available bond lengths, lattice parameters, X-ray photoelectron spectroscopy (XPS), energy gaps, Gibbs free energy, enthalpy, entropy, etc. to ZnO, rGO, and ZnO/rGO hybrid. ZnO and rGO show n-type and p-type semiconductor behavior, respectively. The formed p-n heterojunction between rGO and ZnO is of the staggering gap type. Results show that rGO increases the sensitivity of ZnO to NO2 gas as they form a hybrid. ZnO/rGO hybrid has a higher number of vacancies that can be used to attract oxygen atoms from NO2 and change the resistivity of the hybrid. The combined reduction of oxygen from NO2 and NO can give a very high value of the Gibbs free energy of reaction that explains the ppb level sensitivity of the ZnO/rGO hybrid. The dissociation of NO2 in the air reduces the sensitivity of the ZnO/rGO hybrid at temperatures higher than 300 ̊C.
The novel was generally distinguished from other literary arts in its connection with the living reality as an imaginative practice that relies on political, economic, social, intellectual and cultural references and as a crucial tool in reading cultural references and dive deep into reality. As every novelist has a vision to embody this reality. As every novelist has a vision to embody this reality. The novel of ("Exceeded border by Hammed Al-Kafa’i) is a considered a fertile field for presenting social issues in their apparent structure and revealing the cultural patterns behind them which lies in its deep structure. The novel here moves its characters in its imaginary world in a way that it becomes more capable of adaptation and crysta
... Show MoreMachine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
... Show MoreIn the current paradigms of information technology, cloud computing is the most essential kind of computer service. It satisfies the need for high-volume customers, flexible computing capabilities for a range of applications like as database archiving and business analytics, and the requirement for extra computer resources to provide a financial value for cloud providers. The purpose of this investigation is to assess the viability of doing data audits remotely inside a cloud computing setting. There includes discussion of the theory behind cloud computing and distributed storage systems, as well as the method of remote data auditing. In this research, it is mentioned to safeguard the data that is outsourced and stored in cloud serv
... Show MoreABSTRACT: BACKGROUND: Trivial number of books, concerning traditional medicine, had mentioned a galactagogual role of Garden cress seeds. Others ignore that. This controversy, in addition to the steroid (family of sex hormones) contents of the seeds, directed us to evaluate the role of this herb in mammogenesis and lactogenesis. METHODS: Twelve parameters were used to assess the effect of Garden cress seeds on the mammary gland of young adult virgin rats. These parameters comprise gross assessment, histological examination (routine/ haematoxylin and eosin stain and special stain/ PAS), enzymatic histochemical study (alkaline phosphatase, acid phosphatase and lipoprotein lipase cytochemical localization), biochemical estimations (hor
... Show MoreOne of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first
... Show MoreThe widespread use of images, especially color images and rapid advancement of computer science, have led to an emphasis on securing these images and defending them against intruders. One of the most popular ways to protect images is to use encryption algorithms that convert data in a way that is not recognized by someone other than the intended user. The Advanced Encryption Standard algorithm (AES) is one of the most protected encryption algorithms. However, due to various types of theoretical and practical assaults, like a statistical attack, differential analysis, and brute force attack, its security is under attack.
In this paper, a modified AES coined as (M-AES) is proposed to improve the efficiency
... Show MoreSpergularia iraqensis sp. nov. is described as a new species from Iraq. This species has been collected from Diyala Province in the central east of Iraq; it is closely related to Spergularia rubra (L.) J. Presl & C. Presl, 1819 and Spergularia bocconei (Scheele) Graebn., 1919.
The distinguishing of the morphological characteristics of the new species alongside the two similar species are discussed with photographs, and an identification key is given for Spergularia iraqensis and other closely related species.
Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.