• Journal of Information Science Theory and Practice
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• v.1 no.1
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• pp.10-26
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• 2013

Domain transfer is a widely recognized problem for machine learning algorithms because models built upon one data domain generally do not perform well in another data domain. This is especially a challenge for tasks such as opinion classification, which often has to deal with insufficient quantities of labeled data. This study investigates the feasibility of self-training in dealing with the domain transfer problem in opinion classification via leveraging labeled data in non-target data domain(s) and unlabeled data in the target-domain. Specifically, self-training is evaluated for effectiveness in sparse data situations and feasibility for domain adaptation in opinion classification. Three types of Web content are tested: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. Findings of this study suggest that, when there are limited labeled data, self-training is a promising approach for opinion classification, although the contributions vary across data domains. Significant improvement was demonstrated for the most challenging data domain-the blogosphere-when a domain transfer-based self-training strategy was implemented.

• English Language & Literature Teaching
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• v.10 no.1
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• pp.1-22
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• 2004

The primary purpose of this study is to investigate the applicability of content and formal schemata for processing the scientific texts which encompass the human knowledge of the physical world. In general, schema theory is based on the culture-oriented background of a text. From this point of view, the problem as to whether both content and formal schemata are applicable to the comprehension of a scientific text deserves a focal attention in terms of information processing modes. The results of empirical study indicate that whereas the universality of general knowledge content about the natural world attenuates the tenets of schema theory, the rhetorical organization of scientific texts encourages the application of the schema-based approach; the reader's familiarity with the structural patterns of a text facilitates his reading comprehension.

• Journal of Power Electronics
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• v.2 no.4
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• pp.240-249
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• 2002

Power electronics Is an emerging technology New applications are added every year as well as the power handling capabilities are steadily increasing. The demands to the education of engineers in this field are also increasing. Basically the content of the curriculum should be more expanded without extra study time. This paper present a teaching approach which makes it possible very fast for the student to get in-deplh skills in this important area which is the problem-oriented and project-based learning. The trend and application of power electronics are illustrated. The necessary skills for power electronic engineers are outlined followed up by a discussion on how problem-oriented and project-based learning are implemented. A complete curriculum at Aalborg University is presented where different power electronics related projects at different study levels are carried out.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3068-3086
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• 2022

Digital Forensics is gaining popularity in adjudication of criminal cases as use of electronic gadgets in committing crime has risen. Traditional approach to collecting digital evidence falls short when the disk is encrypted. Encryption keys are often stored in RAM when computer is running. An approach to acquire forensic data from RAM when the computer is shut down is proposed. The approach requires that the investigator immediately cools the RAM and transplant it into a host computer provisioned with a tool developed based on cold boot concept to acquire the RAM image. Observation of data obtained from the acquired image compared to the data loaded into memory shows the RAM chips exhibit some level of remanence which allows their content to persist after shutdown which is contrary to accepted knowledge that RAM loses its content immediately there is power cut. Results from experimental setups conducted with three different RAM chips labeled System A, B and C showed at a reduced temperature of -25C, the content suffered decay of 2.125% in 240 seconds, 0.975% in 120 seconds and 1.225% in 300 seconds respectively. Whereas at operating temperature of 25℃, there was decay of 82.33% in 60 seconds, 80.31% in 60 seconds and 95.27% in 120 seconds respectively. The content of RAM suffered significant decay within two minutes without power supply at operating temperature while at a reduced temperature less than 5% decay was observed. The findings show data can be recovered for forensic evidence even if the culprit shuts down the computer.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.101-115
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• 2008

Combining collaborative filtering with some other technique is most common in hybrid recommender systems. As many recommended items from collaborative filtering seem to be similar with respect to content, the collaborative-content hybrid system suffers in terms of quality recommendation and recommending new items as well. To alleviate such problem, we have developed a novel method that uses a diversity metric to select the dissimilar items among the recommended items from collaborative filtering, which together with the input when fed into content space let us improve and include new items in the recommendation. We present experimental results on movielens dataset that shows how our approach performs better than simple content-based system and naive hybrid system.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.411-413
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• 2000

본 논문은 MPEG-4 내용 기반 비디오 코딩을 위한 객체 추출기법을 소개한다. MPEG-4 표준화는 비디오 객체에 대한 접근성, 사용자와 객체의 상호작용, 높은 압축률을 위한 비디오 코딩 알고리즘을 요구한다. 비디오 장면에서

• Annual Conference of KIPS
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• 2022.05a
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• pp.594-597
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• 2022

Recommendation systems are a prominent approach for users to make informed automated judgments. In terms of movie recommendation systems, there are two methods used; Collaborative filtering, which is based on user similarities; and Content-based filtering which takes into account specific user's activity. However, there are still issues with these two existing methods, and to address those, a combination of collaborative and content-based filtering is employed to produce a more effective system. In addition, various similarity methodologies are used to identify parallels among users. This paper focuses on a survey of the various tactics and methods to find solutions based on the problems of the current recommendation system.

• Journal of Internet Computing and Services
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• v.18 no.3
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• pp.49-61
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• 2017

Wikipedia infoboxes have emerged as an important structured information source on the web. To compose infobox for an article, considerable amount of manual effort is required from an author. Due to this manual involvement, infobox suffers from inconsistency, data heterogeneity, incompleteness, schema drift etc. Prior works attempted to solve those problems by generating infobox automatically based on the corresponding article text. However, there are many articles in Wikipedia that do not have enough text content to generate infobox. In this paper, we present an automated approach to generate infobox for movie domain of Wikipedia by extracting information from several sources of the web instead of relying on article text only. The proposed methodology has been developed using semantic relations of article content and available semi-structured information of the web. It processes the article text through some classification processes to identify the template from the large pool of template list. Finally, it extracts the information for the corresponding template attributes from web and thus generates infobox. Through a comprehensive experimental evaluation the proposed scheme was demonstrated as an effective and efficient approach to generate Wikipedia infobox.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.405-420
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• 2021

Purpose: This study started with the question of how to use Virtual Reality (VR) contents as a part of the non-face-to-face education tool that has recently attracted attention. Methods: In this paper, the use of VR contents as an educational tool is explained as a process of 'new media access dimension'. The question was explored on why Virtual Reality (or Augmented Reality) contents are not used as educational tools in the educational field. Results: As a result, the lack of 'material access' such as devices and infrastructure affects 'motivational access' approach stage, which is the previous stage. Again, it has a negative effect on literacy, which is 'skill access' approach stage. As it was found that it was not circulating to the level of "motive-material-skill-usage", it was discussed that it was taking a different step from the past adoption process of ICT and smart media. Conclusion: Based on this, it is believed that immersive content will contribute to arousing interest that can be applied and spread in the educational field, and it is also thought that it will be possible to derive academic interest in the educational effect according to the characteristics of immersive content such as VR.

• The KIPS Transactions:PartB
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• v.11B no.5
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• pp.587-596
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• 2004

During recent years, a new framework, which aims to bring a unified and global approach in indexing, browsing and querying various digital multimedia data such as audio, video and image has been developed. This new system partitions each media stream into smaller units based on actual physical events. These physical events within oath media stream can then be effectively indexed for retrieval. In this paper, we present a new approach that exploits audio, image and video features to segment and analyze the audio-visual data. Integration of audio and visual analysis can overcome the weakness of previous approach that was based on the image or video analysis only. We Implement a web-based multi media data retrieval system called XCRAB and report on its experiment result.