Teaching the Right Letter Pronunciation in Reciting the Holy Quran Using Intelligent Tutoring System

An Intelligent Tutoring System (ITS) is a computer system that offers an instant, adapted instruction and customized feedback to students without human teacher interference. Reciting "Tajweed" the Holy Quran in the appropriate way is very important for all Muslims and is obligatory in Islamic devotions such as prayers. In this paper, the researchers introduce an intelligent tutoring system for teaching Reciting "Tajweed". Our "Tajweed" tutoring system is limited to "Tafkhim and Tarqiq in TAJWEED" the Holy Quran, Rewaya: Hafs from ‘Aasem. The system was evaluated by reciting teachers and students, and the results were auspicious

Energy Efficiency Prediction using Artificial Neural Network

Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a dataset for building energy performance. The main factors for input variables are: relative compactness, roof area, overall height, surface area, glazing are a, wall area, glazing area distribution of a building, orientation, and the output variables: heating and cooling loads of the building. The dataset used for training are the data published in the literature for various 768 residential buildings. The model was trained and validated, most important factors affecting heating load and cooling load are identified, and the accuracy for the validation was 99.60%

Effect of Specimen Size and Shape on the Compressive Strength of High Strength Concrete

The influence of specimen size and shape on the measured compressive strength was investigated for different high strength concrete mixes. Over 260 specimens from 30 high strength concrete mixtures were cast and tested. It was found, that on average, the ratio of the compressive strength of 150 x 300 mm cylinders to 150 mm cubes was 0.80; while for 100 x 200 mm cylinders to 150 mm cubes was 0.93. Also, on average, the ratio of the compressive strength of 150 x 300 mm cylinders to 100 x 200 mm cylinders was 0.86

Potato Classification Using Deep Learning

Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of potatoes, which can be classified into a number of categories based on the cooked texture and ingredient functionality. Using a public dataset of 2400 images of potatoes, we trained a deep convolutional neural network to identify 4 types (Red, Red Washed, Sweet, and White).The trained model achieved an accuracy of 99.5% of test set, demonstrating the feasibility of this approach

Design and Synthesis of Oxazoline-Based Scaffolds for Hybrid Lewis Acid/Lewis Base Catalysis of Carbon–Carbon Bond Formation

A new class of hybrid Lewis acid/Lewis base catalysts has been designed and prepared with an initial objective of promoting stereoselective direct aldol reactions. Several scaffolds were synthesized that contain amine moieties capable of enamine catalysis, connected to heterocyclic metal-chelating sections composed of an oxazole–oxazoline or thiazole–oxazoline. Early screening results have identified oxa­zole–oxazoline-based systems capable of promoting a highly diastereo- and enantioselective direct aldol reaction of propionaldehyde with 4-nitrobenzaldehyde, when combined with Lewis acids such as zinc triflate

Handwritten Signature Verification using Deep Learning

Every person has his/her own unique signature that is used mainly for the purposes of personal identification and verification of important documents or legal transactions. There are two kinds of signature verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her signature on a digital tablet or a similar device. Offline signature verification is not efficient and slow for a large number of documents. To overcome the drawbacks of offline signature verification, we have seen a growth in online biometric personal verification such as fingerprints, eye scan etc. In this paper we created CNN model using python for offline signature and after training and validating, the accuracy of testing was 99.70%

The Pulsed Spectra of Two Extraordinary Pulsars

We report on X-ray monitoring of two isolated pulsars within the same RXTE field of view. PSR J1811-1925 in the young supernova remnant G11.2-0.3 has a nearly sinusoidal pulse profile with a hard pulsed spectrum (photon index \~1.2). The pulsar is a highly efficient (~ 1% of spin-down energy) emitter of 2-50 keV pulsed X-rays despite having a fairly typical B ~ 2e12 G magnetic field. PSR J1809-1943/XTE J1810-197 is a newly discovered slow (P=5.54 s), apparently isolated X-ray pulsar which increased in flux by a factor of ~100 in 2003 January. Nine months of monitoring observations have shown a decrease in pulsed flux of ~ 30% without a significant change in its apparently thermal spectrum (kT ~0.7 keV) or pulse profile. During this time, the spin-down torque has fluctuated by a factor of ~ 2. Both the torque and the flux have remained steady for the last 3 months, at levels consistent with a magnetar interpretation.Comment: 3 pages, 4 figures, to appear in the Proceedings of X-ray Timing 2003: Rossi and Beyond, ed. P. Kaaret, F.K. Lamb, & J.H. Swank held in Cambridge, MA, Nov. 3-5, 200

On modelling network coded ARQ-based channels

Network coding (NC) has been an attractive research topic in recent years as a means of offering a throughput improvement, especially in multicast scenarios. The throughput gain is achieved by introducing an algebraic method for combining multiple input streams of packets which are addressing one output port at an intermediate node. We present a practical implementation of network coding in conjunction with error control schemes, namely the Stop-and-Wait (SW) and Selective Repeat (SR) protocols. We propose a modified NC scheme and apply it at an intermediate SW ARQ-based link to reduce ARQ control signals at each transmission. We further extend this work to investigate the usefulness of NC in the Butterfly multicast network which adopts the SR ARQ protocol as an error control scheme. We validate our throughput analysis using a relatively recent discrete-event simulator, SimEvents®. The results show that the proposed scheme offers a throughput advantage of at least 50% over traditional SW ARQ, and that this is particularly noticeable in the presence of high error rates. In the multicast network, however, simulation results show that when compared with the traditional scheme, NC-SR ARQ can achieve a throughput gain of between 2% and 96% in a low bandwidth channel and up to 19% in a high bandwidth channel with errors