Copper oxide thin films were deposited on glass substrate using Successive Ionic Layer Adsorption and Reaction (SILAR) method at room temperature. The thickness of the thin films was around 0.43?m.Copper oxide thin films were annealed in air at (200, 300 and 400°C for 45min.The film structure properties were characterized by x-ray diffraction (XRD). XRD patterns indicated the presence of polycrystalline CuO. The average grain size is calculated from the X-rays pattern, it is found that the grain size increased with increasing annealing temperature. Optical transmitter microscope (OTM) and atomic force microscope (AFM) was also used. Direct band gap values of 2.2 eV for an annealed sample and (2, 1.5, 1.4) eV at 200, 300,400oC respect

This study investigates the feasibility of a mobile robot navigating and discovering its location in unknown environments, followed by the creation of maps of these navigated environments for future use. First, a real mobile robot named TurtleBot3 Burger was used to achieve the simultaneous localization and mapping (SLAM) technique for a complex environment with 12 obstacles of different sizes based on the Rviz library, which is built on the robot operating system (ROS) booted in Linux. It is possible to control the robot and perform this process remotely by using an Amazon Elastic Compute Cloud (Amazon EC2) instance service. Then, the map to the Amazon Simple Storage Service (Amazon S3) cloud was uploaded. This provides a database

The aim of this essay is to use a single-index model in developing and adjusting Fama-MacBeth.  Penalized smoothing spline regression technique (SIMPLS) foresaw this adjustment.  Two generalized cross-validation techniques, Generalized Cross Validation Grid (GGCV) and Generalized Cross Validation Fast (FGCV), anticipated the regular value of smoothing covered under this technique. Due to the two-steps nature of the Fama-MacBeth model, this estimation generated four estimates: SIMPLS(FGCV) - SIMPLS(FGCV), SIMPLS(FGCV) - SIM PLS(GGCV), SIMPLS(GGCV) - SIMPLS(FGCV), SIM PLS(GGCV) - SIM PLS(GGCV). Three-factor Fama-French model—market risk premium, size factor, value factor, and their implication for excess stock returns and portfolio return

One of the most difficult issues in the history of communication technology is the transmission of secure images. On the internet, photos are used and shared by millions of individuals for both private and business reasons. Utilizing encryption methods to change the original image into an unintelligible or scrambled version is one way to achieve safe image transfer over the network. Cryptographic approaches based on chaotic logistic theory provide several new and promising options for developing secure Image encryption methods. The main aim of this paper is to build a secure system for encrypting gray and color images. The proposed system consists of two stages, the first stage is the encryption process, in which the keys are genera

Intrinsic viscosities have been studied for polyethylene oxide in water which has wide industrial applications. The polyethylene oxide samples had two different structures, the first one was linear and covers a wide range of molecular weight of 1, 3, 10, 20, 35, 99, 370, 1100, 4600, and 8000 kg/mol and the second one was branched and had molecular weights of 0.55 and 40 kg/mol.
Intrinsic viscosities and Huggins constants have been determined for all types and molecular weights mentioned above at 25ºC using a capillary viscometer. The values of Mark-Houwink parameters (K and a) were equal to 0.0068 ml/g and 0.67 respectively, and have not been published for this range of molecular weight in as yet.

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