This study investigates the influence of silver oxide (Ag2O) concentration on the optical characteristics of phosphate bioactive glasses (PBGs). PBGs have emerged as promising alternatives to conventional silicate glasses in the medical field due to their excellent bioactivity and chemical resistance. Samples with varying Ag2O concentrations (0, 0.25, 0.5, and 0.75g) were sintered at 780°C for 2 hrs in an electric furnace. The samples were subjected to Fourier transfer infrared spectroscopy (FTIR), ultraviolet-visible (UV-Vis) spectroscopy, and photoluminescence (PL) tests to assess their functional groups and optical properties. By analyzing the FTIR spectrum of phosphate bioactive glass containing different amounts of Ag2O, it is

The (NiTsPc) thin films operating by vacuum evaporation technique are high recital and good desirable for number of applications, were dumped on glass substrates at room temperature with (200±20nm) thickness and doped with Al at different percentage (0.01,0.03) besides annealing the sample with 200˚C for 1 hours . The stimuluses of aluminum dopant percentage on characterization of the dropped (Ni Ts Pc) thin films were studied through X-ray diffraction in addition from the attained results, were all the films have polycrystalline in nature, as well the fallouts of XRD aimed at film illustrations polycrystalline, depending on the Al ratio doping, the results, SEM exposed the surface is regularly homogeneous. Utilizing first-ideolog

The structural, optical properties of cupper indium gallium selenite (CuIn1-xGaxSe) have been studied. CuIn1-xGaxSe thin films for x=0.6 have been prepared by thermal evaporation technique, of 2000±20 nm thickness, with rate of deposition 2±0.1 nm/sec, on glass substrate at room temperature. Heat treatment has been carried out in the range (373-773) K for 1 hour. It demonstrated from the XRD method that all the as-deposited and annealed films have polycrystalline structure of multiphase. The optical measurement of the CIGS thin films conformed that they have, direct allowed energy gap equal to 1.7 eV. The values of some important optical parameters of the studied films such as (absorption coefficient, refractive index, extinction coeffici

In this paper a thin films of selenium was prepare on substrates of n-Si by evaporation in a vacuum technique with thickness about 0.5μm. And then an annealing process was done on samples at two temperature (100 and 200) C ° in a vacuum furnace (10^-3 torr).
Some structural, optical and mechanical properties of prepared thin films were measured. Results showed that the prepared film was the crystallization, optical transmittance and micro hardness of the prepared thin films increased significantly after annealing.

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

As an important resource, entanglement light source has been used in developing quantum information technologies, such as quantum key distribution(QKD). There are few experiments implementing entanglement-based deterministic QKD protocols since the security of existing protocols may be compromised in lossy channels. In this work, we report on a loss-tolerant deterministic QKD experiment which follows a modified “Ping-Pong”(PP) protocol. The experiment results demonstrate for the first time that a secure deterministic QKD session can be fulfilled in a channel with an optical loss of 9 dB, based on a telecom-band entangled photon source. This exhibits a conceivable prospect of ultilizing entanglement light source in real-life fiber-based

PC-based controller is an approach to control systems with Real-Time parameters by controlling selected manipulating variable to accomplish the objectives. Shell and tube heat exchanger have been identified as process models that are inherently nonlinear and hard to control due to unavailability of the exact models’ descriptions. PC and analogue input output card will be used as the controller that controls the heat exchanger hot stream to the desired temperature.
The control methodology by using four speed pump as manipulating variable to control the temperature of the hot stream to cool to the desired temperature.
In this work, the dynamics of cross flow shell and tube heat exchanger is modeled from step changes in cold water f

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet