, founded in 1993, is a private university located in Amman, Jordan. It is accredited by the Jordanian Ministry of Higher Education & Scientific Research. As of 2008 there were 8,000 students enrolled in the university of whom 14% are international students from 28 countries. As is the case in all other Jordanian universities, the credit-hour system is used in the university. Wikipedia.
Al-Omoush K.S.,Al-Zaytoonah University of Jordan
Journal of Organizational and End User Computing | Year: 2017
The purpose of this research is to examine the drivers of Web-based B2B systems adoption from an institutional perspective by means of comparison between durable and nondurable goods-producing industries. A questionnaire survey was developed to collect data from manufacturing firms. Structural Equation Modeling using EQS was conducted to analyze the data. Results revealed that the durability characteristic of goods produced plays a moderating role in the impact of institutional pressures on the top management support of Web-based B2B systems adoption. Results also indicated that top management support, and B2B relationship quality have a direct impact on the extent of adoption and use of Web-based B2B systems. The present study contributes to the continuing discussion about why organizations respond differently to institutional pressures and vary in the level of use of Web-based B2B applications. © 2017, IGI Global.
Al-Allaf O.N.A.,Al-Zaytoonah University of Jordan
Journal of Theoretical and Applied Information Technology | Year: 2017
Speech signals are effected by noise generated by various sources of interferences. Removing noise from speech signals can be regarded as an active research area in signal processing. Thus, we need powerful methods in this area. Therefore, Function Fitting (FitNet) Artificial Neural Networks model was used in this paper for enhancing speech signals. Particle Swarm Optimization (PSO) was used during FitNet learning process to optimize the FitNet learning parameters (such as learning rate, momentum variable and network weights) to achieve best results of speech signal enhancement. At the same time, different optimization techniques for optimizing the values of learning parameters were suggested in this work. This is done to improve the performance of FitNet model for signal enhancement. Better results (320 learning steps, PSNR equal 38 and mean square error (MSE) equal 0.0027) from experiments were achieved when adopting PSO with FitNet with swarm size equal 40 and PSO number of iterations equal 100. Good results (312 learning steps, PSNR equal 35.94 and MSE equal 0.00002) were obtained also when adopting the suggested optimization techniques (learning rate equal 0.00003, 5 hidden units in one hidden layer with the using of Levenberg-Marquardt (LM) as learning algorithm) for optimizing the learning parameters. © 2005 – ongoing JATIT & LLS.
Khalaf R.A.,Al-Zaytoonah University of Jordan
Current Topics in Medicinal Chemistry | Year: 2016
Background: Natural products are characterized by their chemical diversity and being a good source of a range of bioactive structures including antidiabetic compounds. Diabetes mellitus (DM) is considered a major worldwide health concern. Rational drug design has been widely accomplished, to discover and optimize innovative leads for different molecular targets of type 2 DM including α-glucosidase, PPARγ, DPP-IV, PTP1B, AR, GSK-3β, 11β-HSD1, GK, etc. Objective: This review illustrates the potential of natural products as a rich source of lead compounds for antidiabetic drug discovery with some examples of computational studies carried out to determine the possible molecular target, structure activity relationship, and further optimization chances. Conclusion: Natural products will remain an attractive source for researchers to explore their therapeutic potential against DM. Guided by the computational studies; systematic lead optimization via structural modifications will speed up the generation of potential new clinical candidates for the treatment of type 2 DM. © 2016 Bentham Science Publishers.
Al-Debei M.M.,University of Jordan |
Al-Lozi E.,Al-Zaytoonah University of Jordan |
Papazafeiropoulou A.,Brunel University
Decision Support Systems | Year: 2013
This study examines the continuance participation intentions and behaviour on Facebook, as a representative of Social Networking Sites (SNSs), from a social and behavioural perspective. The study extends the Theory of Planned Behaviour (TPB) through the inclusion of perceived value construct and utilizes the extended theory to explain users' continuance participation intentions and behaviour on Facebook. Despite the recent massive uptake of Facebook, our review of the related-literature revealed that very few studies tackled such technologies from the context of post-adoption as in this research. Using data from surveys of undergraduate and postgraduate students in Jordan (n = 403), the extended theory was tested using statistical analysis methods. The results show that attitude, subjective norm, perceived behavioural control, and perceived value have significant effect on the continuance participation intention of post-adopters. Further, the results show that continuance participation intention and perceived value have significant effect on continuance participation behaviour. However, the results show that perceived behavioural control has no significant effect on continuance participation behaviour of post-adopters. When comparing the extended theory developed in this study with the standard TPB, it was found that the inclusion of the perceived value construct in the extended theory is fruitful; as such an extension explained an additional 11.6% of the variance in continuance participation intention and 4.5% of the variance in continuance participation behaviour over the standard TPB constructs. Consistent with the research on value-driven post-adoption behaviour, these findings suggest that continuance intentions and behaviour of users of Facebook are likely to be greater when they perceive the behaviour to be associated with significant added-value (i.e. benefits outperform sacrifices). © 2013 Elsevier B.V. All rights reserved.
Sunoqrot S.,Al-Zaytoonah University of Jordan |
Bugno J.,University of Illinois at Chicago |
Lantvit D.,University of Illinois at Chicago |
Burdette J.E.,University of Illinois at Chicago |
Hong S.,University of Illinois at Chicago
Journal of Controlled Release | Year: 2014
Nanoparticle (NP)-based drug delivery platforms have received a great deal of attention over the past two decades for their potential in targeted cancer therapies. Despite the promises, passive targeting approaches utilizing relatively larger NPs (typically 50-200 nmin diameter) allow for passive tumor accumulation, but hinder efficient intratumoral penetration. Conversely, smaller, actively targeted NPs (<20nmin diameter) penetrate well into the tumor mass, but are limited by their rapid systemic elimination. To overcome these limitations, we have designed amulti-scale hybrid NP platformthat loads smaller poly(amidoamine) (PAMAM) dendrimers (∼5 nm in diameter) into larger poly(ethylene glycol)-b-poly(D,L-lactide) (PEG-PLA) NPs (∼70 nm). A biodistribution study in healthy mice revealed that the hybrid NPs circulated longer than free dendrimers and were mostly cleared by macrophages in the liver and spleen, similar to the in vivo behavior of PEG-PLA NPs. When injected intravenously into the BALB/c athymic nude mice bearing folate receptor (FR)-overexpressing KB xenograft, the targeted hybrid NPs encapsulating folate (FA)-targeted dendrimers achieved longer plasma circulation than free dendrimers and higher tumor concentrations than both free dendrimers and the empty PEG-PLA NPs. These results suggest that the hybrid NPs successfully combine the in vivo advantages of dendrimers and polymeric NPs, demonstrating their potential as a new, modular platform for drug delivery. © 2014 Elsevier B.V. All rights reserved.
Burshaid K.I.,University of Jordan |
Hamdan M.A.,Al-Zaytoonah University of Jordan
Energy Conversion and Management | Year: 2013
This work presents an experimental technique for the measurement of the soot formation in pure fuel, biofuel and emulsified fuel, that constitute this fuels was studied in heated shock tube and investigated the possibility of reducing soot production in locally refined diesel, locally produced biofuel and emulsified fuel. This reduction was conducted using certain oxygenated additives (methane, ethane and acetone). It was found that soot concentration is maximum when pure diesel was burned, followed by emulsified fuels and the lease concentration was obtained when biofuel was burned. Further, methanol has the most significant effect on the reduction of soot once added to each fuel, while acetone has the lease effect on soot reduction. The results gave good indication of the effect for oxygenated additives in reduction the soot formation. © 2012 Elsevier Ltd. All rights reserved.
Al-Debei M.M.,University of Jordan |
Al-Lozi E.,Al-Zaytoonah University of Jordan
Computers in Human Behavior | Year: 2014
As mobile devices become more and more pervasive in our everyday life and their capabilities resemble more and more of those of desktop computers with the added advantage of mobility, examining intention for adoption seems relevant to consumers and mobile service providers alike. Existing research shows that despite this evolution on Mobile Data Services (MDS) development and use, the adoption of their full capabilities is yet to be realized. In this study we focus on the value consumers can potentially gain from using these services. We hypothesize that if we can examine the value that can be delivered to consumers through the use of MDS, then we can explain and predict consumers' intentions to use MDS. We also postulate that perceptions of consumers regarding the value that can be captured when using MDS is directly affected by technological, social, and informational influences. However, in this research, perceived value is used as a multidimensional construct that encapsulates utilitarian, hedonic, uniqueness, epistemic, and economic value dimensions. Our results show that utilitarian value is, according to previous studies, an important adoption factor. Additionally, economic value is also important and significant. Nevertheless, it seems that in our context, hedonic, uniqueness, and epistemic value dimensions are not as important for the use of mobile data services as utilitarian and economic value dimensions. The results of this study can be used by mobile service providers to get insights about consumers' needs and preferences in order to offer better and thus more popular services. © 2014 Elsevier Ltd. All rights reserved.
Althunibat A.,Al-Zaytoonah University of Jordan
Computers in Human Behavior | Year: 2015
Abstract M-learning is characterized as a powerful element of learning and education for facilitating the learning experiences. With enhanced and rapid advancements in technologies of ICTs (Information and Communication Technologies) and mobile, numerous innovative services and applications are being developed. Therefore, it becomes significant to investigate the factors influencing the intentions of m-learning to be used among the students of higher education institution. This study examines the "Technology Acceptance Model" (TAM), "Theory of Reasoned Action" (TRA) and "Unified Theory of Acceptance and Use of Technology" (UTAUT). The study is based on a survey being conducted across diverse groups of students, belonging to different communities and universities. The survey questionnaire was utilized for collecting the relevant data from 250 respondents. The results analyzed yields the impact that the proposed model of m-learning is comprehensive to study in the institutions of higher education. © 2015 Elsevier Ltd.
AL-Allaf O.N.A.,Al-Zaytoonah University of Jordan
Journal of Computer Science | Year: 2010
Problem statement: The problem inherent to any digital image is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop algorithms that compress images to lower data rates with better quality. Artificial neural networks are becoming attractive in image processing where high computational performance and parallel architectures are required. Approach: In this research, a three layered Backpropagation Neural Network (BPNN) was designed for building image compression/decompression system. The Backpropagation neural network algorithm (BP) was used for training the designed BPNN. Many techniques were used to speed up and improve this algorithm by using different BPNN architecture and different values of learning rate and momentum variables. Results: Experiments had been achieved, the results obtained, such as Compression Ratio (CR) and peak signal to noise ratio (PSNR) are compared with the performance of BP with different BPNN architecture and different learning parameters. The efficiency of the designed BPNN comes from reducing the chance of error occurring during the compressed image transmission through analog or digital channel. Conclusion: The performance of the designed BPNN image compression system can be increased by modifying the network itself, learning parameters and weights. Practically, we can note that the BPNN has the ability to compress untrained images but not in the same performance of the trained images. © 2010 Science Publications.
Al-Husainy M.A.F.,Al-Zaytoonah University of Jordan
International Journal of Security and its Applications | Year: 2012
Image encryption is one of the most methods of information hiding. A novel secure encryption method for image hiding is presented in this paper. The proposed method provides good confusion and diffusion properties that ensures high security due to mixing the two Boolean operations: XOR and Rotation that are done on the bits of the pixels in the image. This method is implemented by firstly doing a sequential XOR operation on all the bits of pixels in the image, and secondly makes a circular rotate right of these bits. These two operations are repeated many times during the encryption phase. The security and performance of the proposed encryption method have been evaluated by applying it on images and analyze the recorded results using key space analysis, key sensitivity analysis, and statistical analysis. The performance experiments show that the proposed method is promising to use effectively in wide fields of image encryption.