Photonic crystal fiber interferometers are used in many sensing applications. In this work, an in-reflection photonic crystal fiber (PCF) based on Mach-Zehnder (micro-holes collapsing) (MZ) interferometer, which exhibits high sensitivity to different volatile organic compounds (VOCs), without the needing of any permeable material. The interferometer is robust, compact, and consists of a stub photonic crystal fiber of large-mode area, photonic crystal fiber spliced to standard single mode fiber (SMF) (corning-28), this splicing occurs with optimized splice loss 0.19 dB In the splice regions the voids of the holey fiber are completely collapsed, which allows the excitation and recombination of core and cladding modes. The device reflection

The service quality of any information-based system could be evaluated by the high-end user in such a way that the system developer or responsible intently might use these user experiences to improve, develop and benchmark their system. In this paper, questionnaire implemented to rate to what extent the academic admission system as a web site achieves performance. Data were collected from 21 users of the system; all of them are highly educated and have the experience of using the site. Quadrant and gap analysis were implemented to evaluate the weakness and strength of the data. The major data analyses were performed on the data collected in terms of its importance and satisfaction to the users. A number of statistical tools have been uti

E-mail is an efficient and reliable data exchange service. Spams are undesired e-mail messages which are randomly sent in bulk usually for commercial aims. Obfuscated image spamming is one of the new tricks to bypass text-based and Optical Character Recognition (OCR)-based spam filters. Image spam detection based on image visual features has the advantage of efficiency in terms of reducing the computational cost and improving the performance. In this paper, an image spam detection schema is presented. Suitable image processing techniques were used to capture the image features that can differentiate spam images from non-spam ones. Weighted k-nearest neighbor, which is a simple, yet powerful, machine learning algorithm, was used as a clas

In this paper mildly-regular topological space was introduced via the concept of mildly g-open sets. Many properties of mildly - regular space are investigated and the interactions between mildly-regular space and certain types of topological spaces are considered. Also the concept of strong mildly-regular space was introduced and a main theorem on this space was proved.

The study aims to integrate the visually impaired people into the art connoisseur community through producing special print artworks to enable the visually impaired people to use their other senses to feel artworks by using artistic printing techniques through adding some prominent materials to the printing colors or making an impact that visually impaired people can perceive using their other senses. This study also aims to set up art exhibitions that display tangible works that can enable visually impaired people to feel artwork and understand its elements to enable them to feel it through other senses.
The study follows the experimental method, through using artistic printing techniques, which allow printing with prominent textur

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

المستخلص

يعد تقييم اداء العاملين احد اهم الركائز الاساسية التي يتوقف عليها نجاح أي منظمة تسعى بأن تتطور وتتميز بأنشطتها واداءها وبالأخص المنظمات التي لها خصوصية في عملها كالأجهزة الرقابية التي تعتمد في اداء انشطتها ومسؤولياتها على كفاءة مواردها البشرية, ومن هذا المنطلق يهدف هذا البحث الى تصميم انموذج ثلاثي المحاور (المؤهلات والقدرات، الاداء والانجاز، التعاون والالتزام الوظيفي) ثُماني المستويات

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

There are many methods of searching large amount of data to find one particular piece of information. Such as find name of person in record of mobile. Certain methods of organizing data make the search process more efficient the objective of these methods is to find the element with least cost (least time). Binary search algorithm is faster than sequential and other commonly used search algorithms. This research develops binary search algorithm by using new structure called Triple, structure in this structure data are represented as triple. It consists of three locations (1-Top, 2-Left, and 3-Right) Binary search algorithm divide the search interval in half, this process makes the maximum number of comparisons (Average case com

The main objective of e-learning platforms is to offer a high quality instructing, training and educational services. This purpose would never be achieved without taking the students' motivation into consideration. Examining the voice, we can decide the emotional states of the learners after we apply the famous theory of psychologist SDT (Self Determination Theory). This article will investigate certain difficulties and challenges which face e-learner: the problem of leaving their courses and the student's isolation.
Utilizing Gussian blending model (GMM) so as to tackle and to solve the problems of classification, we can determine the learning abnormal status for e-learner. Our framework is going to increase the students’ moti