ICT Policy Outcomes for National Development: The Place of Knowledge Integration and Management in Nigerian Higher Education
Chinyere Onyemaechi Agabi,
Comfort Nkogho Agbor,
Nwachukwu Prince Ololube
Issue:
Volume 4, Issue 5, October 2015
Pages:
104-111
Received:
17 September 2015
Accepted:
24 September 2015
Published:
10 October 2015
Abstract: The prologues of Information Communication Technology (ICT) usage including its integration and diffusion kicked off a new era in educational processes and has fundamentally changed the conventional methods of teaching and learning in higher education institutions (HEIs) around the world, and have transformed contemporary processes of teaching and learning experiences of both lecturers and students. The debates here are made with reference to (1) the contexts of ICT and knowledge integration (2) the challenges of ICT usage and knowledge integration, and (3) ICT policy outcomes and national development. A qualitative research method was adopted; the use of document and observation were indispensable part of the methods for data gathering. The study found that the lofty hopes, keenness and enthusiasm for ICT and knowledge integration and management are obstructed as the nation is faced with inadequacies in essential ICT infrastructures and services such as telecommunication services, electricity, incompetent ICT personnel, inadequate funding, poor economic situation, poverty, high ICT literacy rate and so on. However, there is an ongoing moves and development to ensure effective ICT knowledge integration and management in education resources in Nigeria and Africa higher education institutions. This novel study recommends that higher education should become expansive, positive and proactive actors in ICT knowledge integration and management in teaching, learning and research for academics, non-academics to foster admirable academic environment aimed at meeting national development. This learned debate has implication for education practitioners, curriculum developers and designers, policy makers, planners and the government.
Abstract: The prologues of Information Communication Technology (ICT) usage including its integration and diffusion kicked off a new era in educational processes and has fundamentally changed the conventional methods of teaching and learning in higher education institutions (HEIs) around the world, and have transformed contemporary processes of teaching and ...
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On the Development Robust and Fast Algorithm of Action and Identity Recognition
Khawlah Hussein Alhamzah,
Tianjiang Wang
Issue:
Volume 4, Issue 5, October 2015
Pages:
112-118
Received:
11 July 2015
Accepted:
9 November 2015
Published:
2 December 2015
Abstract: Human action recognition and surveillance applications are playing a key important in the present days and took an increasing interest in modern. Since most previous methods strictly limited to action classification in different scenarios and not take attention to human identity that makes an action at the same time. We present a novel and fast algorithm to recognize action and identity in a single framework. We assumed one person makes one action in a video. To identify and training the owner of the video to the classifier, we proposed the watermark embedded as 2-D wavelet transform as binary image, which is contains identity information in the training video. We used these wavelet coefficients as identity descriptors. To represent feature motion representation, we used motion energy image (MEI) and motion history image (MHI) as temporal template of the human actions and Zernike moments to extract shape features of the action from MEI and MHI. In this research, a set of Zernike moment based feature vectors is proposed for human action recognition, which is capture the global properties of an object rather than the local ones. We have composed two different feature vectors by evaluating the variance values of lower order Zernike moments in the four-dimensional Zernike moment space with encouraging experimental results. It has discriminative information that is suitable for classification, especially on related actions, such as running and jogging, that is most previous researches fail to classify them even human vision HVS. Nearest neighbor classifier is used for action and identity categorization. The result of these experiments suggests that this method has a high recognition rate in both action and identity accuracy on KTH data sets.
Abstract: Human action recognition and surveillance applications are playing a key important in the present days and took an increasing interest in modern. Since most previous methods strictly limited to action classification in different scenarios and not take attention to human identity that makes an action at the same time. We present a novel and fast alg...
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