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Fakhar Shahzad,GuoYi Xiu,Imran Khan,Muhammad Shahbaz,Muhammad Usman Riaz,Adnan Abbas 서울대학교 교육연구소 2020 Asia Pacific Education Review Vol.21 No.1
In the provision of massive open online courses (MOOCs), cloud computing services enable students to synchronize their study materials anywhere, anytime, and using any device, which can improve learning performance and strengthen the teacher–student relationship via knowledge sharing. This study builds on the technological–organizational–environmental (TOE) framework and aims to identify the influencing factors of cloud computing adoption in educational settings for the provision of MOOCs. Another aim is to determine how intrinsic motivation moderates individual intention. Therefore, our study conceptualized a model that is supported by an empirical analysis of 232 respondents and takes into account the technological, organizational, and environmental impacts on individual attitudes toward adopting cloud computing in education. We evaluate the study hypotheses using structural equation modeling. The results demonstrate significant relationships between the technological and organizational constructs and attitudes toward the use of cloud computing. Meanwhile, competitive pressure from the environment has not been identified in any relationship with individual attitudes in government universities. The results provide new directions for policymakers to consider in the implementation of CC systems for the provision of MOOCs in developing countries. We also discuss potential implications, contributions, and suggestions for future research.
Muhammad Hasnain,Imran Ghani,Muhammad Fermi Pasha,Ishrat Hayat Malik,Shahzad Malik 한국인터넷방송통신학회 2019 International Journal of Internet, Broadcasting an Vol.11 No.2
Research classification of software modules was done to validate the approaches proposed for addressing limitations in existing classification approaches. The objective of this study was to replicate the experiments of a recently published research study and re-evaluate its results. The reason to repeat the experiment(s) and re-evaluate the results was to verify the approach to identify the faulty and non-faulty modules applied in the original study for the prioritization of test cases. As a methodology, weconducted this study to re-evaluate the results of the study. The results showed that binary logistic regression analysis remains helpful for researchers for predictions, as it provides an overall prediction of accuracy in percentage. Our study shows a prediction accuracy of 92.9% for the PureMVC Java open source program, while the original study showed an 82% prediction accuracy for the same Java program classes. It is believed by the authors that future research can refine the criteria used to classify classes of web systemswritten in various programming languages based on the results of this study.
Bilal, Saqib,Khan, Abdul Latif,Shahzad, Raheem,Kim, Yoon-Ha,Imran, Muhammad,Khan, Muhammad Jamil,Al-Harrasi, Ahmed,Kim, Tae Han,Lee, In-Jung Elsevier 2018 Ecotoxicology and environmental safety Vol.164 No.-
<P><B>Abstract</B></P> <P>Chromium Cr(VI) is highly toxic and leads to impaired phenotypic plasticity of economically important crops. The current study assessed an endophytic-bacteria assisted metal bio-remediation strategy to understand stress-alleviating mechanisms in <I>Glycine max</I> L (soybean) plants inoculated with <I>Sphingomonas</I> sp. LK11 under severe Cr(VI) toxicity. The screening analysis showed that high Cr concentrations (5.0 mM) slightly suppressed LK11 growth and metal uptake by LK11 cells, while significantly enhancing indole-3-acetic acid (IAA) production. Endophytic LK11 significantly upregulated its antioxidant system compared to control by enhancing reduced glutathione (GSH), catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) activities to counteract Cr-induced oxidative stress. Cr toxicity induced cell morphological alteration, as shown by SEM-EDX analysis and triggered significant lipid peroxidation. The interaction between LK11 and soybean in Cr-contaminated soil significantly increased plant growth attributes and down-regulated the synthesis of endogenous defense-related phytohormones, salicylic acid and abscisic acid, by 20% and 37%, respectively, and reduced Cr translocation to the roots, shoot, and leaves. Additionally, Cr-induced oxidative stress was significantly reduced in LK11-inoculated soybean, regulating metal responsive reduced GSH and enzymatic antioxidant CAT. Current findings indicate that LK11 may be a suitable candidate for the bioremediation of Cr-contaminated soil and stimulation of host physiological homeostasis.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Endophytic LK11 act as an alternative strategy for alleviating chromium stress from soybean. </LI> <LI> IAA producing capability of LK11 was remarkably upregulated Under chromium stress. </LI> <LI> LK11 assoiciation promoted host plant growth attributes and modulated endogenous hormones and antioxidants. </LI> <LI> LK11 Inoculated soybean displayed reduced accumulation of chromium. </LI> </UL> </P>
EAR: Enhanced Augmented Reality System for Sports Entertainment Applications
( Zahid Mahmood ),( Tauseef Ali ),( Nazeer Muhammad ),( Nargis Bibi ),( Imran Shahzad ),( Shoaib Azmat ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.12
Augmented Reality (AR) overlays virtual information on real world data, such as displaying useful information on videos/images of a scene. This paper presents an Enhanced AR (EAR) system that displays useful statistical players’ information on captured images of a sports game. We focus on the situation where the input image is degraded by strong sunlight. Proposed EAR system consists of an image enhancement technique to improve the accuracy of subsequent player and face detection. The image enhancement is followed by player and face detection, face recognition, and players’ statistics display. First, an algorithm based on multi-scale retinex is proposed for image enhancement. Then, to detect players’ and faces’, we use adaptive boosting and Haar features for feature extraction and classification. The player face recognition algorithm uses boosted linear discriminant analysis to select features and nearest neighbor classifier for classification. The system can be adjusted to work in different types of sports where the input is an image and the desired output is display of information nearby the recognized players. Simulations are carried out on 2096 different images that contain players in diverse conditions. Proposed EAR system demonstrates the great potential of computer vision based approaches to develop AR applications.