Reading English as a foreign language: The interplay of abilities and strategies

This paper investigates the preferred order of reading strategies at three ability levels by L1 Arabic learners of English in an EFL setting. Then it explores whether there was a relationship between ability level and strategy use. Ninety-two EFL college students enrolled in a reading comprehension class participated in this study. They took a TOEFL reading section to determine their reading abilities/levels, and then they completed a biographical and the Survey of Reading Strategies (SORS) questionnaires. Then, statistical analyses were conducted. The results showed that each ability level reported strategy use differently in terms of order and intensity. There was also a statistical significance in strategy use between the high ability and the low ability levels. The low ability level participants reported higher use of the global reading strategies than the high ability group. However, no statistical significance of association was found between reading ability and strategy us

Control Of Packed U-cell Multilevel Five-phase Voltage Source Inverter

A seven level five-phase voltage source inverter with packed U-cell topology is presented in this paper. This is called Packed U-cell because each unit of the inverter is of shape U. Fig. 1 presents a five-phase seven-level inverter power circuit configuration using Packed U-cell. Depending upon the number of capacitors in the investigated topology different level of voltages can be achieved. In the presented topology two capacitors have been used to obtain seven levels (Vdc, 2Vdc/3, Vdc/3, 0, - Vdc/3, -2Vdc/3, -Vdc ). The Voltage across second capacitor (C) must be maintained at one-third of the voltage of the dc link.qscienc

Optical character recognition on heterogeneous SoC for HD automatic number plate recognition system

Automatic number plate recognition (ANPR) systems are becoming vital for safety and security purposes. Typical ANPR systems are based on three stages: number plate localization (NPL), character segmentation (CS), and optical character recognition (OCR). Recently, high definition (HD) cameras have been used to improve their recognition rates. In this paper, four algorithms are proposed for the OCR stage of a real-time HD ANPR system. The proposed algorithms are based on feature extraction (vector crossing, zoning, combined zoning, and vector crossing) and template matching techniques. All proposed algorithms have been implemented using MATLAB as a proof of concept and the best one has been selected for hardware implementation using a heterogeneous system on chip (SoC) platform. The selected platform is the Xilinx Zynq-7000 All Programmable SoC, which consists of an ARM processor and programmable logic. Obtained hardware implementation results have shown that the proposed system can recognize one character in 0.63 ms, with an accuracy of 99.5% while utilizing around 6% of the programmable logic resources. In addition, the use of the heterogenous SoC consumes 36 W which is equivalent to saving around 80% of the energy consumed by the PC used in this work, whereas it is smaller in size by 95%

GC-MS Analysis of Adulterants in Captagon Tablet

In secret laboratories various synthetic or semi-synthetic amphetamine-type stimulants (ATS) are produced and processed. Stimulants of the form of amphetamine (ATS) are the second most common illegal drugs used worldwide, following cannabis. ATS production has increased worldwide, particularly from the Middle East. Fenethylline (CaptagonTM), a derivative of amphetamine, is commonly marketed as a street drug. Objective: this research aimed at applying gas chromatography / mass spectrometry (GC / MS) for fenethylline profiling of confiscated samples from the Saudi market. Methodology: The study of GC / MS was conducted on a general-purpose column (30 mm 0.25 mm i.d) filled with 0.25 mm cross bond, 5% diphenyl dimethyl polysiloxane (Rtx-5MS). The mass was worked in the process of impacting the electron. Results and discussion: Analyzed samples showed positive results for amphetamine in concentrations ranging from 0.07 to 43.02 percent of the substance in 60 percent of the samples. Caffeine was also present in 60 per cent of the samples at levels between 0.61 and 60.31 per cent. In the MS of the other active compounds were recorded in different proportions. Lastly, the presence of other substances in fenethylline samples may contribute to intoxication

OCR based feature extraction and template matching algorithms for Qatari number plate

There are several algorithms and methods that could be applied to perform the character recognition stage of an automatic number plate recognition system; however, the constraints of having a high recognition rate and real-time processing should be taken into consideration. In this paper four algorithms applied to Qatari number plates are presented and compared. The proposed algorithms are based on feature extraction (vector crossing, zoning, combined zoning and vector crossing) and template matching techniques. All four proposed algorithms have been implemented and tested using MATLAB. A total of 2790 Qatari binary character images were used to test the algorithms. Template matching based algorithm showed the highest recognition rate of 99.5% with an average time of 1.95 ms per character

HD Qatari ANPR system

Recently, Automatic Number Plate Recognition (ANPR) systems have become widely used in safety, security, and commercial aspects. The whole ANPR system is based on three main stages: Number Plate Localization (NPL), Character Segmentation (CS), and Optical Character Recognition (OCR). In recent years, to provide better recognition rate, High Definition (HD) cameras have started to be used. However, most known techniques for standard definition are not suitable for real-time HD image processing due to the computationally intensive cost of localizing the number plate. In this paper, algorithms to implement the three main stages of a high definition ANPR system for Qatari number plates are presented. The algorithms have been tested using MATLAB and two databases as a proof of concept. Implementation results have shown that the system is able to process one HD image in 61 ms, with an accuracy of 98.0% in NPL, 99.75% per character in CS, and 99.5% in OCR. 2016 IEEE.Scopu

Optical character recognition on heterogeneous SoC for HD automatic number plate recognition system

Automatic number plate recognition (ANPR) systems are becoming vital for safety and security purposes. Typical ANPR systems are based on three stages: number plate localization (NPL), character segmentation (CS), and optical character recognition (OCR). Recently, high definition (HD) cameras have been used to improve their recognition rates. In this paper, four algorithms are proposed for the OCR stage of a real-time HD ANPR system. The proposed algorithms are based on feature extraction (vector crossing, zoning, combined zoning, and vector crossing) and template matching techniques. All proposed algorithms have been implemented using MATLAB as a proof of concept and the best one has been selected for hardware implementation using a heterogeneous system on chip (SoC) platform. The selected platform is the Xilinx Zynq-7000 All Programmable SoC, which consists of an ARM processor and programmable logic. Obtained hardware implementation results have shown that the proposed system can recognize one character in 0.63 ms, with an accuracy of 99.5% while utilizing around 6% of the programmable logic resources. In addition, the use of the heterogenous SoC consumes 36 W which is equivalent to saving around 80% of the energy consumed by the PC used in this work, whereas it is smaller in size by 95%.Other Information Published in: EURASIP Journal on Image and Video Processing License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1186/s13640-018-0298-2</p

HD number plate localization and character segmentation on the Zynq heterogeneous SoC

Automatic number plate recognition (ANPR) systems have become widely used in safety, security, and commercial aspects. A typical ANPR system consists of three main stages: number plate localization (NPL), character segmentation (CS), and optical character recognition (OCR). In recent years, to provide a better recognition rate, high-definition (HD) cameras have started to be used. However, most known techniques for standard definition (SD) are not suitable for real-time HD image processing due to the computationally intensive cost of processing several-folds more of image pixels, particularly in the NPL stage. In this paper, algorithms suitable for hardware implementation for NPL and CS stages of an HD ANPR system are presented. Software implementation of the algorithms was carried on as a proof of concept, followed by hardware implementation on a heterogeneous system-on-chip (SoC) device that contains an ARM processor and a field-programmable gate array (FPGA). Heterogeneous implementation of these stages has shown that this HD NPL algorithm can localize a number plate in 16.17 ms, with a success rate of 98.0%. The CS algorithm can then segment the detected plate in 0.59 ms, with a success rate of 99.05%. Both stages utilize only 21% of the available on-chip configurable logic blocks