In this paper, a novel robust blind grayscale image digital watermarking scheme is introduced based on lifting wavelet transform (LWT) in combination with discrete cosine transform (DCT), Hessenberg decomposition, and entropy analysis for copyright protection of multimedia information. At first, the two levels of LWT are applied to the host grayscale image to improve the imperceptibility of the watermarking scheme and then the high-frequency sub-band of the 2-level of LWT is decomposed by DCT. Next, the DCT coefficients are divided into 4× 4 non-overlapping blocks. After that, Hessenberg decomposition performs on each selected block, whereas the first row, first column element of the upper Hessenberg matrix is utilized to hide the watermark. To evaluate the imperceptibility and robustness of the proposed digital watermarking scheme, the peak signal-to-noise ratio (PSNR), and normalized cross-correlation (NC) are utilized to measure the quality and the ability of the proposed watermarking scheme to robust against signal processing operations and geometric attacks. Experimental and analysis results have demonstrated that the proposed scheme is achieved a very good tradeoff between imperceptibility and robustness. The comparison with other scheme have shown that the proposed digital watermarking schemes have a superior performance in terms of imperceptibility and robustness than other

Face recognition is a biometric technique that can be used for a variety of purposes, such as national security, access control, identity fraud, banking, and finding missing children. Faces are highly dynamic and facial features are not always easily extracted, which can lead to discarding textural information like the smoothness of faces, a hairstyle that, might contain strong identity information. In addition, brightness, scale, and facial expressions play a significant role in the face-recognizing process. Therefore, face recognition is considered as a difficult problem. To figure out this problem effective methods using databases techniques are needed. This paper describes face recognition methods and their structure. Based on Wen Yi Zhao and Rama Chellappa work the face recognition methods are divided into three groups: a holistic approach, feature-based approach, and hybrid approach, where Principal Component Analysis PCA, a holistic approach method, is presented as a mathematical technique that can assist the process of face recognition. Also, the paper shows how the PCA is used to extract facial features by removing the principal components of the available multidimensional data.

Face recognition is a biometric technique that can be used for a variety of purposes, such as national security, access control, identity fraud, banking, and finding missing children. Faces are highly dynamic and facial features are not always easily extracted, which can lead to discarding textural information like the smoothness of faces, a hairstyle that, might contain strong identity information. In addition, brightness, scale, and facial expressions play a significant role in the face-recognizing process. Therefore, face recognition is considered as a difficult problem. To figure out this problem effective methods using databases techniques are needed. This paper describes face recognition methods and their structure. Based on Wen Yi Zhao and Rama Chellappa work the face recognition methods are divided into three groups: a holistic approach, feature-based approach, and hybrid approach, where Principal Component Analysis PCA, a holistic approach method, is presented as a mathematical technique that can assist the process of face recognition. Also, the paper shows how the PCA is used to extract facial features by removing the principal components of the available multidimensional data.

In this paper we present an approach to optimistic concurrency control where the write phase occurs before the validation phase (RWV instead of RVW). Our work extends earlier research into real-time databases that utilized virtual execution to lower disk access overheads. Such work demonstrated that virtual execution allowed an increase in transactions completing before deadlines expired and improvements in overall throughput. However, we demonstrate that only with the reversal of the write and validation phases can virtual execution reach its full potential.

Abstract

This study aims to discover the problems that face Libyan university

students when translating Libyan proverbs into English. It also focuses on

the techniques applied by the students in the translation process. To

achieve the goals, the researchers asked the study participants to

translate about ten Libyan proverbs into Arabic. The sample of this study

consisted of twelve second year students specialized in translation from

the English department in the Assabha Faculty of Arts. The results

showed that some students faced problems in transferring the meaning of

Libyan proverbs into the target language (English). This could be

attributed to the different culture between both languages (i.e. Arabic and

English) The results also revealed that the participants used literal

translation method as their primary strategy. Translation tutors and

curriculum designers need to focus on the effective strategies to achieve

the correct translation of Libyan proverbs into English

This paper presents a new high-capacity algorithm for audio watermarking for the purpose of embedding a watermark audio signal into an original audio signal. This algorithm uses DCT (discrete cosine transform) in combination with SVD (singular value decomposition), DWT (discrete wavelet transform), and CZT (chirp ztransform). For the purpose of ensuring high levels of imperceptibility and robustness, a low-frequency sub band of 1-level DWT is selected to embed the watermark, followed by DCT, CZT, and SVD. As a result, the proposed algorithm achieves a high capacity of 352800 bits per second while a good quality audio signal is maintained (having an objective difference grade of more than-0.04). It also provides high imperceptibility (a signal to noise ratio of more than 58 dB) and it is extremely resistant to common audio attacks, including requantizing, resampling, additive white Gaussian noise or AWGN, MP3 compression, and low-pass filtering. The proposed algorithm presents much better compared to the audio watermarking algorithms already existent.

Abstract

Although listening skill plays a significant role in daily communication and

education process in teaching English , listening subject has long been neglected

in second language teaching. This study aims to explore problems, difficulties

and barriers in teaching listening to Libyan students in our case study Alassaba

area, 3rd year secondary science school, Mosab Ben Omer Secondary School

and Omer Ben Alkhtab Secondary school. The participants of our study were 5

teachers. Classroom observation and teacher’s interview are used for data

collection. It is found that all teachers were using grammar translation method

in teaching listening. Most classes were uncomfortable learning atmosphere,

beside the absence of technology which used and facilitate teaching listening.

The findings based on data analysis and discussion may be of a great

significance to find solutions for these problems and improving the way of

teaching listening

Prosopis farcta (Banks & Sol.) J. F. Macbr. has been reported for the first time from Libya. This species is native in Asia. Flowering specimens of Prosopis farcta collected from Sokna Region about 650 Km south-east Tripoli. It is presented with updated nomenclature, taxonomic description, geographical distribution, place of occurrence in Libya, and field colored photographs are also provided. The voucher specimens were deposited in the Herbarium of Botany Department (ULT), University of , Tripoli, Libya.

A novel non-blind audio watermarking algorithm, using chirp z-transform in combination with discrete wavelet transform and singular value decomposition, is presented in this paper. In the proposed method, a watermark audio signal (about 13 seconds in length) is hidden into an original audio signal (about 51 seconds in length) by applying discrete wavelet transform, chirp z-transform, and singular value decomposition. The effectiveness of the proposed algorithm has been tested using signal-to-noise ratio, objective difference grade (ODG), and normalised cross- correlation of watermarked audio signal under various common audio attacks. Experimental results demonstrate that the algorithm has a high capacity (352.8 kbps), without significant perceptual distortion (ODG > -0.29) and provides good robustness against common audio attacks, including: re-sampling, echo addition, MP3 compression, additive white Gaussian noise, re- quantisation, cutting, and low-pass filtering. This algorithm has a high capacity and excellent audio quality compared with other audio watermarking algorithms.