Dry gas is considered one of the most environmentally friendly sources of energy. As a result, developing an efficient strategy for storing this gas has become essential. In this work, MOF-199 was synthesized and characterized in order to investigate the MOF-199 in dry gas adsorption using a built-in volumetric system (methane, ethane, and propane from Basrah gas company). The MOF-199 (metal organic framework) was synthesized using the solvothermal method at 373K for 24h, and then it was characterized. The dry gas adsorption on MOF-199 was studied under various conditions (adsorbent dosage, contact time, temperature, and pressure). The isothermal adsorption of the dry gas had been studied on MOF-199 using two types of mo

The x-ray fluorescence (XRF) of Znpc molecule with (flow of Ar) and Znpc molecule with (grow in N2) showed two peaks at (8.5and 9.5 Kv) referring to orbital transition ) K?-shell & K?-shell) respectively. The study of x-ray diffraction (XRD) where it was observed good growth of the crystal structure as a needle by the sublimation technique with a ?-phase of (monoclinic structure ) . Using Bragg equation the value of the interdistance of the crystalline plane (d-value) were calculated. We noticed good similarity with like once in the American Standards for Testing Material (ASTM) .Powder Diffraction File (PDF) Program was used to ensure the information obtained from (ASTM) . The output of (PDF) was compared with celn program, where the val

Organic permeable‐base transistors (OPBTs) show potential for high‐speed, flexible electronics. Scaling laws of OPBTs are discussed and it is shown that OPBT performance can be increased by reducing their effective device area. Comparing the performance of optimized OPBTs with state‐of‐the‐art organic field‐effect transistors (OFETs), it is shown that OPBTs have a higher potential for an increased transit frequency. Not only do OPBTs reach higher transconductance values without the need for sophisticated structuring techniques, but they are also less sensitive to parasitic contact resistances. With the help of a 2D numerical model, the reduced contact resistances of OPBTs are explained by a homogeneous injection of current acros

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi