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

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

Background: Low-level laser therapy (LLLT) has been extensively applied to improve wound healing due to some biostimulatory properties presented by laser arrays apparently able to accelerate the repair of soft tissue injuries. However, the role of proinflammatory interlukines not been studied yet. IL_1 ? represent one of the most important poroinflammatory interlukines that involved in wound healing. The goal of this study was to investigate the effect of 790-805nm diode laser on the expression of IL_1 ? during wound healing in mice. Materials and Methods: Standard-sized wounds (1.5cm) were carried out in the face of 96 white albino mice. Half of them underwent LLLT treatment (360 J/cm 2) at 790-805 nm delivered immediately after wound pro

    The goal of this research to identify the effect of the probing questions in the collection of material literature with students of the Kurdish language department, to achieve the aim of the research, the researcher has chosen a sample from the students of third stage of the Kurdish language Department, Faculty of Education / Ibn Rushd as a field for the application of experiment.The number of sample  reached (71) students divided into two groups represented two divisions of the experimental groups under study to the style of questions sounding by (35) students, and represented the other division of the control group, which studied in the way normal and by (36) students, as rewarded r

Knowledge of the mineralogical composition of a petroleum reservoir's formation is crucial for the petrophysical evaluation of the reservoir. The Mishrif formation, which is prevalent in the Middle East, is renowned for its mineralogical complexity. Multi-mineral inversion, which combines multiple logs and inversions for multiple minerals at once, can make it easier to figure out what minerals are in the Mishrif Formation. This method could help identify minerals better and give more information about the minerals that make up the formation. In this study, an error model is used to find a link between the measurements of the tools and the petrophysical parameters. An error minimization procedure is subsequently applied to determine

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c