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.

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.

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.

Quality assurance and institutional accreditation in education is becoming of paramount importance. This study aims to assess the impacts of the accreditation process of the National Center for Quality Assurance and Accreditation (NCAAA) on the quality of education in one of private university in Libya. Methods: The research adopts a descriptive study design in University of Tripoli Alahlia (UTA) where an official accreditation process was completed by the NCQAA during 2017-2019. Data were collected using the self-study report that produced by the NCQAA accreditation committee during the accreditation process, and were retrieved in specific data collection sheet by one of the authors. Results: The NCQAA accreditation process that lasted about 4 years brought significant changes in the educational progressions and made the staff members more aware of quality issues in education. Our findings also reported significant improvements in the quality of education in the university. Conclusions: The process of NCQAA accreditation conducted in UTA has been positively improved the quality of education. Data from other institutions would also expressively increase the relevance and rationality of the study.

Watermarking techniques have been considered as one of the best efficacious methods 

to solve the issues of protecting copyright due to the proliferation of digital multimedia 

information on the internet. The digital multimedia information is such as image, 

audio, and video which can today be easily copied, distributed, and modified without 

loss in fidelity. As a result, it is necessary to utilize some kind of copyright protection 

techniques to avoid illegal copying, distribution, and digital copyright modification. 

The digital watermarking techniques have engaged the researchers’ attention as a 

technique for protecting copyright in the digital multimedia information. This 

technique includes a subcategory of information-hiding technologies in which the 

ownership information is hidden into the original multimedia information without 

impacting the original multimedia information quality. Despite the advances in digital 

watermarking techniques, the main objective of many types of research in digital 

watermarking topic is to improve transparency and resistance to attacks and the present 

digital watermarking schemes are not sufficiently stable or strong against various 

attacks. This study aims to develop state-of-the-art digital watermarking techniques 

for different multimedia information through improving the imperceptibility and 

robustness to geometrical attacks and signal processing operations. Four novel robust 

blind digital watermarking schemes are introduced in this thesis for copyright 

protection of multimedia information that have not been previously introduced. The 

first robust blind digital watermarking scheme is applied for colour images utilizing 

discrete wavelet transform in combination with Walsh Hadamard transform and 

Hessenberg decomposition. The second robust blind digital watermarking scheme is 

applied for grayscale images utilizing discrete wavelet transform in combination with 

Walsh Hadamard transform and Hessenberg decomposition. The third robust blind 

digital watermarking scheme is applied for colour videos utilizing discrete wavelet 

transform in combination with Walsh Hadamard transform and Hessenberg 

decomposition. Forth robust blind digital watermarking scheme is applied for audio 

signals utilizing discrete wavelet transform in combination with Walsh Hadamard 

transform and Hessenberg decomposition. Several experiments are performed in order 

to present the effectiveness of the proposed digital watermarking schemes in terms of 

imperceptibility and robustness against attacks related to each scheme. The proposed 

digital watermarking schemes achieve good imperceptibility and robustness against 

geometrical attacks and signal processing operations. The proposed digital 

watermarking schemes have a superior performance in terms of imperceptibility and 

robustness than other reported schemes in the literature.

Keywords: Watermarking, Copyright Protection, Discrete Wavelet Transform, Walsh 

Hadamard Transform, Hessenberg Decomposition.

Understanding diversity is important in our inclusive society to hedge against ignorance and accommodate plural perspectives. Diversity nowadays can be observed in online social spaces. People from different backgrounds (e.g. gender, age, culture, expertise) are interacting every day around online digital objects (e.g. videos, images and web articles) leaving their social content in different format, commonly as textual comments and profiles. The social clouds around digital objects (i.e. user comments, user profiles and other metadata of digital objects) offer rich source of information about the users and their perspectives on different domains. Although, researchers from disparate disciplines have been working on understanding and measuring diversity from different perspectives, little has been done to automatically measure diversity in social clouds. This is the main objective of this research. This research proposes a semantic driven computational model to systematically represent and automatically measure diversity in a social cloud. Definitions from a prominent diversity framework and Semantic Web techniques underpin the proposed model. Diversity is measured based on four diversity indices - variety, balance, coverage and (within and across) disparity with regards to two perspectives – (a) domain, which is captured in user comments and represented by domain ontologies, and (b) user, which is captured in profiles of users who made the comments and represented by a proposed User Diversity Ontology. The proposed model is operationalised resulting in a Semantic Driven Diversity Analytics Tool (SeDDAT), which is responsible for diversity profiling based on the diversity indices. The proposed approach of applying the model is illustrated on social clouds from two social spaces - open (YouTube) and closed (Active Video Watching (AVW-Space)). The open social cloud shows the applicability of the model to generate diversity profiles of a large pool of videos (600) with thousands of users and comments. Closed social clouds of two user groups around same set of videos illustrate transferability and further utility of the model. A list of possible diversity patterns within social clouds is provided, which in turn deepen the understanding of diversity and open doors for further utilities of the diversity profiles. The proposed model is applicable in similar scenarios, such as in the social clouds around MOOCs and news articles.

Age prediction is an active study field that can substantially affect many computer vision problems like object recognition. In this paper, an accurate system with extensive experiments is proposed to provide an efficient and accurate approach for age range prediction of people from their facial images. Histogram Equalization technique is used to reduce the illumination effects on all facial images taken from FG-NET and UTD aging databases, and image resizing is used to unify all image sizes. Moreover, Histogram of Oriented Gradient (HOG) and Local Binary Pattern (LBP) are used to extract the features of these images. Then, Support Vector Machine (SVM) and k-Nearest Neighbor (k-NN) are used for the classification processes. To evaluate the performance of the proposed system, both Leave-One-Out (LOO) and Confusion Matrix (CM) are used. The extensive and intensified experiments improved the age range predicting performance up to 98.6%.

Colour image watermarking has become one of the most important algorithms for copyright protection. The following paper will present an innovative scheme for watermarking blind colour images using the discrete wavelet transform (DWT), fast Walsh Hadamard transform (FWHT) and the Hessenberg decomposition as its basis. First, two-level DWT followed by FWHT are used to decompose the host image’s red channel. Next, the FWHT coefficients are split into 4× 4 non-overlapping blocks. Then, each selected block is decomposed using Hessenberg decomposition, where the first row, first column element of the upper Hessenberg matrix H is quantified to embed the watermark information. Peak signalto-noise ratio, normalized cross-correlation and structural similarity index measure are used to evaluate the feasibility and the robustness. The experimental results have demonstrated that the proposed watermarking scheme is highly invisible with PSNR> 40 dB, for several watermarked colour images, with a capacity of 4096 bits and execution time of 0.7415 s. The proposed watermarking scheme is also highly resistant to both common image processing and geometrical attacks such as filtering, JPEG2000, noise adding, cropping, scaling, blurring and sharpening, and others

Modelling diversity is especially valuable in soft skills learning, where contextual awareness and understanding of different perspectives are crucial. This paper presents an application of a diversity analytics pipeline to generate domain diversity profiles for learners as captured in their comments while watching videos for learning a soft skill. The datasets for analysis were collected from a series of studies on learning presentation skills with Active Video Watching system (AVW-Space). Two user studies (with 37 postgraduates and 140 undergraduates, respectively) were compared. The learners’ diversity and personal profiles are used to further understand and highlight any notable patterns about their domain coverage on presentation skills.

Diversity has been the subject of study in various disciplines from biology to social science and computing. Respecting and utilising the diversity of the population is increasingly important to broadening knowledge. This paper describes a pipeline for diversity profiling of a pool of text in order to understand its coverage of an underpinning domain. The application is illustrated by using a domain ontology on presentation skills in a case study with 38 postgraduates who made comments while learning pitch presentations with the Active Video Watching system (AVW-Space). The outcome shows different patterns of coverage on the domain by the comments in each of the eight videos.