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Smart Learning Services Based on Smart Cloud Computing

Svetlana Kim, Su-Mi Song and Yong-Ik Yoon

Department of Multimedia Science, Sookmyung Women’s University, Chungpa-Dong 2-Ga,Yongsan-Gu 140-742, Seoul, Korea

Communication: Smart Learning Services Based on Smart Cloud Computing ; Sensors 2011, 11(8), 7835-7850

Present : 陳政宇Date：2012/06/01

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Abstract

• Context-aware technologies can make e-learning services smarter and more efficient– a service architecture model is needed

• We suggest the elastic four smarts (E4S)– smart pull, smart prospect, smart content, and

smart push• The E4S focuses on meeting the users’ needs– provides personalized and customized learning

services

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Outline

• 1. Introduction• 2. Smart Cloud Computing• 3. The SCC• 4. Implementation• 5. Conclusion

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1. Introduction(1/4)

• Traditionally e-learning were limited• Smart learning – offers personalized contents, easy adaptation ,

convenient communication environment and rich resources

– still not complete

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1. Introduction(2/4)

• For example– not allocate necessary computing resources– difficulty in interfacing and sharing data with other

systems– duplication and low utilization of existing teaching

resources• To resolve this problem– use cloud computing to support resource

management

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1. Introduction(3/4)

• cloud computing environment provides– the necessary foundation– integration of platform and technology– integrates teaching and research resources

distributed over various locations– anywhere at anytime

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1. Introduction(4/4)

• the existing cloud computing technologies are only passively responsive to users’ needs.– propose a smart cloud computing (SCC) model for

smart learning contents through the E4S• SCC can provide – customized contents to each user

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2. Smart Cloud Computing(1/3)

• The SCC for short based on E4S has the capability to – provide a smart learning environment. – encourages learning system standardization and

provides a means for managing it.

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2. Smart Cloud Computing(2/3)

• A traditional e-learning system can – display single content on a single device – or multiple contents on one device.

• The SCC can – deliver s-learning to the users so they can use

multiple devices to render multi learning contents. • The multi learning contents can be played in

different devices separately to form a “virtual class”.

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2. Smart Cloud Computing(3/3)

• For this, the SCC uses context-aware sensing.– Sensing through the location and IP address of

each device. • Each customized learning contents may differ

in modality (i.e., text-based, audio, video, etc.), capability (i.e., bandwidth), and timing (i.e., types of synchronization).

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3. The SCC

• 3.1. Context-Aware Module• 3.2. The Elastic 4S (E4S) System– 3.2.1. Smart Pull– 3.2.2. Smart Prospect– 3.2.3. Smart Content– 3.2.4. Smart Push

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3.1. Context-Aware Module(1/3)

• The context-aware model– must automatically deduce the actual situation

from the user’s behavior.– based on a hybrid situation that consists of the

user situation and the physical situation. – includes static factors and dynamic factors that

describe the hybrid situation.

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3.1. Context-Aware Module(2/3)

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3.1. Context-Aware Module(3/3)

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3.2. The Elastic 4S (E4S) System

• 3.2.1. Smart Pull• 3.2.2. Smart Prospect• 3.2.3. Smart Content• 3.2.4. Smart Push

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3.2.1. Smart Pull(1/3)

• The Smart Pull identifies a right action service in fusion learning DB based on the user action in context model.

• The fusion learning DB consists of various multimedia learning materials such as video, text, PPT and image scattered in different learning DB.

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3.2.1. Smart Pull(2/3)

• For Example– a user action in the context model requests the topic of

“multimedia”– The Smart Pull extracts a related action of “multimedia” in

fusion learning DB

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3.2.1. Smart Pull(3/3)

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3.2.2. Smart Prospect(1/3)

• The Smart Prospect is mainly responsible for describing the contents in ActionNo– time, memory, resolution and supported

application types.• To access the information in ActionNo, the

Smart Prospect uses a Semantic Description using of UVA (Universal Video Adaptation) model that has been developed by Yoon

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3.2.2. Smart Prospect(2/3)

• The UVA model– uses the video content description in MPEG-7 standard

and MPEG-21 multimedia framework. • The Semantic Description – provides the accurate and meaningful information for the

fusion content. – uses XML, ontology and Resource Description Framework

(RDF) that help define fusion content clearly and precisely.– also represents systematic information about the

contents.

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3.2.2. Smart Prospect(3/3)

• The role of the ontology – formally describe the shared meaning of vocabulary used. – describes the basic fusion learning contents of some

domain (e.g., history of science). – includes the relations between these concepts and some

basic properties. • Based on the ontology, all learning content in the

ActionNo are associated each other.– For example, the description of the video content used in

semantic description can be related to the scenes of video.

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represents playback time of the entire video content

represents the playback time of a shot in the video content

indicates supporting types for some application, such as video, image, PPT or text.

specifies memory and resolution information of video content, respectively

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3.2.3. Smart Content (1/3)

• The Smart Content generates the fusion content for the user’s device using the harmony adaptation.

• The harmony adaptation has two steps– Fusion Content Adaptation

• presents the synchronization among the fusion contents in ActionNo.

– Device Synchronization process• performs the process of synchronization between devices.

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3.2.3. Smart Content (2/3)

• The process of synchronization between multiple devices– creates a channel for each device – the fusion contents can be played on multi devices

at the same time– The Device Synchronization uses SyncML

(Synchronization Markup Language) to set the synchronization between devices.

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3.2.3. Smart Content (3/3)

• The SyncML – an international standard language – matching data between different devices and

applications at any network company .• Through the synchronization between devices,

the adapted contents can be used in Smart Push step.

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3.2.4. Smart Push (1/2)

• As for the content delivery, the situation analyzer will be used.

• the situation analyzer– uses the physical situation information to find the

related details of the contents and devices• If the details of a device and contents are the

same, a link can be established

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3.2.4. Smart Push (2/2)

• The Smart Push delivers a complete set of smart contents to the user using terminal’s AP (Access Point) and MAC-Address

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4. Implementation (1/2)

• fusion content generation and synchronization

the progress of the synchronization

shows a synchronization of the video and audio

shows the synchronization with other fusion media

can be played in the preview

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4. Implementation (2/2)

• delivered the synchronized fusion media to two different devices

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5. Conclusions

• In this paper, we have introduced the use of context-awareness for user behavior and a way to deliver the corresponding contents to the users.

• As a future work, the protocols for smart cloud computing and domain specific ontology will be investigated.