• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.676-684
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• 2003

eLearning can be defined as an approach to teaching and teaming that utilises Internet technologies to communicate and collaborate in an educational context. This includes technology that supplements traditional classroom training with web-based components and learning environments where the educational process is experienced online. The use of hypertext as an educational tool has a very rich history. The advent of the internet and one of its major application, the world wide web (WWW), has given a tremendous boost to the theory and practice of hypermedia systems for educational purposes. However, the web suffers from an inability to satisfy the heterogeneous needs of a large number of users. For example, web-based courses present the same static teaming material to students with widely differing knowledge of the subject. Adaptive hypermedia techniques can be used to improve the adaptability of eLearning. In this paper we report an approach to the design a unified implementation framework suitable for web-based eLearning that accommodates the three main dimensions of hypermedia adaptation: content, navigation, and presentation. The framework externalises the adaptation strategies using XML notation. The separation of the adaptation strategies from the source code of the eLearning software enables a system using the framework to quickly implement a variety of adaptation strategies. This work is a part of our more general ongoing work on the design of a framework for adaptive content delivery. parts of the framework discussed in this paper have been imulemented in a commercial eLearning engine.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.249-268
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• 2014

Relevance feedback is an effective tool to bridge the gap between superficial image contents and medically-relevant sense in content-based medical image retrieval. In this paper, we propose an interactive medical image search framework based on pairwise constraint propagation. The basic idea is to obtain pairwise constraints from user feedback and propagate them to the entire image set to reconstruct the similarity matrix, and then rank medical images on this new manifold. In contrast to most of the algorithms that only concern manifold structure, the proposed method integrates pairwise constraint information in a feedback procedure and resolves the small sample size and the asymmetrical training typically in relevance feedback. We also introduce a long-term feedback strategy for our retrieval tasks. Experiments on two medical image datasets indicate the proposed approach can significantly improve the performance of medical image retrieval. The experiments also indicate that the proposed approach outperforms previous relevance feedback models.

• International Journal of Knowledge Content Development & Technology
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• v.13 no.4
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• pp.81-94
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• 2023

Purpose - The purpose of this study was to investigate data aspects in Library and Information Science curricula at all levels in selected African Universities. Design/methodology/approach - A review of existing literature on data aspects and LIS Curricula. Secondly, the study juxtaposed web-based courses for fourteen LIS schools to establish data aspects incorporated into their curricula. Findings - The study's findings found that although many LIS schools have some form of data aspects in curricula, coverage is still very limited and basic.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2121-2142
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• 2011

In this paper, we propose an e-Learning process control model that aims to graphically describe and automatically generate the manifest of sequencing prerequisites in packaging SCORM's content aggregation models. In specifying the e-Learning activity sequencing, SCORM provides the concept of sequencing prerequisites to be manifested on each e-Learning activity of the corresponding tree-structured content organization model. However, the course developer is required to completely understand the SCORM's complicated sequencing prerequisites and other extensions. So, it is necessary to achieve an efficient way of packaging for the e-Learning content organization models. The e-Learning process control model proposed in this paper ought to be an impeccable solution for this problem. Consequently, this paper aims to realize a new concept of process-driven e-Learning content aggregating approach supporting the e-Learning process control model and to implement its e-Learning process modeling system graphically describing and automatically generating the SCORM's sequencing prerequisites. Eventually, the proposed model becomes a theoretical basis for implementing a SCORM-based e-Learning process management system satisfying the SCORM's sequencing prerequisite specifications. We strongly believe that the e-Learning process control model and its modeling system achieve convenient packaging in SCORM's content organization models and in implementing an e-Learning management system as well.

• ETRI Journal
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• v.36 no.6
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• pp.988-998
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• 2014

For memory-based big data storage, using hybrid memories consisting of both dynamic random-access memory (DRAM) and non-volatile random-access memories (NVRAMs) is a promising approach. DRAM supports low access time but consumes much energy, whereas NVRAMs have high access time but do not need energy to retain data. In this paper, we propose a new data migration method that can dynamically move data pages into the most appropriate memories to exploit their strengths and alleviate their weaknesses. We predict the access frequency values of the data pages and then measure comprehensively the gains and costs of each placement choice based on these predicted values. Next, we compute the potential benefits of all choices for each candidate page to make page migration decisions. Extensive experiments show that our method improves over the existing ones the access response time by as much as a factor of four, with similar rates of energy consumption.

• Journal of Intelligence and Information Systems
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• v.13 no.1
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• pp.1-14
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• 2007

Character images for the background screen of cell phones are one of the fast growing sectors of the mobile content market. However, character image buyers currently experience tremendous difficulties in searching for desired images due to the awkward image search process. Content-based image retrieval (CBIR) widely used for image retrieval could be a good candidate as a solution to this problem, but it needs to overcome the limitation of the mobile Internet environment where an initial query set (IQS) cannot be easily provided as in the PC-based environment. We propose a new approach, IQS-AutoGen, which automatically generates an initial query set for CBIR on the mobile Internet. The approach applies the collaborative filtering (CF), a well-known recommendation technique, to the CBIR process by using users' preference information collected during the relevance feedback process of CBIR. The results of the experiment using a PC-based prototype system show that the proposed approach successfully satisfies the initial query requirement of CBIR in the mobile Internet environment, thereby outperforming the current image search process on the mobile Internet.

• Journal of Information Technology Services
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• v.6 no.1
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• pp.17-30
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• 2007

The rapid development of information and communication technologies has resulted in rapid increase in the qualitative and quantitative information that can be accessed by information technology. Furthermore an enormous amount of information is provided in various formats. However, there are a group of people who are not able to even approach to targeted information due to physical or environmental problems. Visually handicapped users constitute a class of these users. In this paper, a method of developing user interface for web-based education service is described for the visually handicapped users to access information more efficiently. First, this paper analyzed the problems of visually handicapped users to access information targeting representative domestic sites that supply education services. And based on the results of the above analyses, Nest, this paper explains the web-based education service interface implementation method according to types of the content to be delivered. Lastly, the validity of this method is provided by testing a web page based on the implementation method according to the types of content.

• ETRI Journal
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• v.35 no.6
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• pp.1058-1067
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• 2013

An approach for game bot detection in massively multiplayer online role-playing games (MMORPGs) based on the analysis of game playing behavior is proposed. Since MMORPGs are large-scale games, users can play in various ways. This variety in playing behavior makes it hard to detect game bots based on play behaviors. To cope with this problem, the proposed approach observes game playing behaviors of users and groups them by their behavioral similarities. Then, it develops a local bot detection model for each player group. Since the locally optimized models can more accurately detect game bots within each player group, the combination of those models brings about overall improvement. Behavioral features are selected and developed to accurately detect game bots with the low resolution data, considering common aspects of MMORPG playing. Through the experiment with the real data from a game currently in service, it is shown that the proposed local model approach yields more accurate results.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.145-155
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• 2019

The strength or resilience of refugees is a less emphasized area as the discourse in refugee mental health study mainly weighs on pathologizing the effects of refugee experiences. Within the lenses of strength and resilience, this study explored how refugees and asylum seekers, who experienced violence and loss, coped with trauma and hardship in their newly established lives in South Korea. In this study we analyzed survey data collected from 100 participants (55 asylum seekers and 45 refugees) through open-ended questions. We analyzed narratives for both content and form and provided evidence for factors that reflect coping strategies used by participants to overcome their life adversities. The findings gave rise to; (a) character traits like strong religiosity, personal determination, patience to forbear, hopefulness, and peaceful acceptance of current circumstance; (b) relationships, in the sense of meaningful strong bonds within family members and the instinctive personal resourcefulness to utilize support resources within and outside of their communities; (c) learned skills after migraing to korea; (d) knowledge sets in how to get by in korea; (e) personal talents, and (f) extra abilities that gave power to pass socio-economic difficulties. The findings underscore the importance of considering the strength-based approach either in discussing resilience or intervention. Our approach will allow practitioners to acknowledge that refugees and asylum seekers potentially have a unique set of strengths and abilities that they rely on to overcome their immediate and future problems. It will also guide practitioners as they devise their intervention schemes.

• ETRI Journal
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• v.31 no.4
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• pp.419-428
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• 2009

A question answering (QA) system can be built using multiple QA modules that can individually serve as a QA system in and of themselves. This paper proposes a learnable, strategy-driven QA model that aims at enhancing both efficiency and effectiveness. A strategy is learned using a learning-based classification algorithm that determines the sequence of QA modules to be invoked and decides when to stop invoking additional modules. The learned strategy invokes the most suitable QA module for a given question and attempts to verify the answer by consulting other modules until the level of confidence reaches a threshold. In our experiments, our strategy learning approach obtained improvement over a simple routing approach by 10.5% in effectiveness and 27.2% in efficiency.