• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.551-557
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• 2015

Synchronization methods for shared data need to be selected properly based on characteristics of data and applications. In this paper we suggest a new semantic synchronization method, semanticAppr, for non_transactional data in disconnected mode. Our approach reduces loss of works in cooperative environments by weakening constraint of serializability. In addition it reduces data transfer by sending operation log instead document itself.

• MALSORI
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• no.44
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• pp.115-130
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• 2002

Voice input is often required in many new application environments, but the low rate of speech recognition makes it difficult to extend its application. Previous approaches were to raise the accuracy of the recognition by post-processing of the recognition results, which were all lexical-oriented. We suggest a new semantic-oriented approach in speech recognition error correction. Through experiments using a speech-driven in-vehicle telematics information application, we show the excellent performance of our approach and some advantages it has as a semantic-oriented approach over a pure lexical-oriented approach.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1919-1925
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• 2022

In this paper, we propose an image-to-image translation approach based on the conditional generative adversarial network for semantic segmentation. Semantic segmentation is the task of clustering parts of an image together which belong to the same object class. Unlike the traditional pixel-wise classification approach, the proposed method parses an input RGB image to its corresponding semantic segmentation mask using a pixel regression approach. The proposed method is based on the Pix2Pix image synthesis method. We employ residual connections-based convolutional neural network architectures for both the generator and discriminator architectures, as the residual connections speed up the training process and generate more accurate results. The proposed method has been trained and tested on the NYU-depthV2 dataset and could achieve a good mIOU value (49.5%). We also compare the proposed approach to the current methods in semantic segmentation showing that the proposed method outperforms most of those methods.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.107-116
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• 2012

The applying of semantic technologies that aim to let computers understand and automatically process the meaning of the interlinked data on the Web is spreading. In Semantic Web, understanding and accessing the associations between data that is, the meaning between data as well as accessing to the data itself is important. W3C recommended RDF (Resource Description Framework) as a standard format to represent both Semantic Web data and their associations and also proposed several RDF query languages in order to support query processing for RDF data. However further researches on the query language definition considering the semantic associations and query processing techniques are still required. In this paper, using the suffix array-based indexing scheme previously introduced for RDF query processing, we propose a query processing approach to handle ${\rho}$-path query which is the representative type of semantic associations. To evaluate the query processing performance of the proposed approach, we implemented two different types of query processing approaches and measured the average query processing times. The experiments show that the proposed approach achieved 1.8 to 2.5 and 3.8 to 11 times better performance respectively than others two.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.238-240
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• 2002

If there is an Information Retrieval system which comprehends the semantic content of documents and knows the preference of users. the system can search the information better on the Internet, or improve the IR performance. Therefore we propose the IR model which combines semantic based indexing and fuzzy relevance model. In addition to the statistical approach, we chose the semantic approach in indexing, lexical chains, because we assume it would improve the performance of the index term extraction. Furthermore, we combined the semantic based indexing with the fuzzy model, which finds out the exact relevance of the user preference and index terms. The proposed system works as follows: First, the presented system indexes documents by the efficient index term extraction method using lexical chains. And then, if a user tends to retrieve the information from the indexed document collection, the extended IR model calculates and ranks the relevance of user query. user preference and index terms by some metrics. When we experimented each module, semantic based indexing and extended fuzzy model. it gave noticeable results. The combination of these modules is expected to improve the information retrieval performance.

• Journal of the Ergonomics Society of Korea
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• v.32 no.4
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• pp.371-380
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• 2013

Objective: The aim of this study is to investigate the effects of design parameters of vibrotactile signals on semantic association with transmitted information conveying different meanings. Background: As information communication relying on human visual channel becomes excessive, the utility of vibrotactile signals is being interested as a substitute measure of delivering information. Properly designed hapticons may relieve burden of visual communication by rendering distinct and meaningfully compatible haptic sensations. Method: A typical Kansei engineering approach was adopted in this study. Ten most distinctive hapticons were selected among those having different frequencies and amplitudes. Associations between the hapticons and twenty four pairs of adjectives used to describe the state of automobile in control were gathered from thirty subjects using semantic differential scales. Results: The selected pairs of adjectives were summarized by factor analysis into two semantic dimensions named 'Awareness' and 'Directionality'. The experimental hapticons matched with the semantic dimensions were presented as a haptic emotion map. Conclusion: The results from this study support that frequencies and amplitudes of haptic signals play important roles in arousing different human perceptions regarding the two haptic emotional dimensions. Application: Properly designed hapticons with respect to the contents of transmitted information will increase human operator's situation awareness as well as system performance. The result from this study can be used to develop standardized hapticons for active haptic communication.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.716-730
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• 2017

In this paper, we propose a transliteration approach based on semantic information (i.e., language origin and gender) which are automatically learnt from the person name, aiming to transliterate the person name of Uyghur into Chinese. The proposed approach integrates semantic scores (i.e., performance on language origin and gender detection) with general transliteration model and generates the semantic knowledge-based model which can produce the best candidate transliteration results. In the experiment, we use the datasets which contain the person names of different language origins: Uyghur and Chinese. The results show that the proposed semantic transliteration model substantially outperforms the general transliteration model and greatly improves the mean reciprocal rank (MRR) performance on two datasets, as well as aids in developing more efficient transliteration for named entities.

• Journal of Korea Technology Innovation Society
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• v.8 no.2
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• pp.605-622
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• 2005

Because, next generation web, semantic web consists of documents with semantic information, it enables computer interpret the contents of the documents, so that the information retrieval, interpretation and integration can be automated. The web documents with the semantic information may be made in ontology. In this paper, collaborative approach among the ontology design techniques is more excellent than the other techniques because it design the ontology through continuous evaluations and modification in terms of multiple views. So, we propose the process of designing and implementing the ontology for specific domain, which is Yeomigi tour place. Delphi technique, that is a kind of collaborative approach, is used when the ontology is designed.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.340-356
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• 2024

Bridging traditional experts' disciplinary boundaries is important for nuclear knowledge management systems. However, expert competences are often described in unstructured texts and require substantial human effort to link related competences across disciplines. The purpose of this research is to develop and evaluate a natural language processing approach, based on Latent Semantic Analysis, to enable the automatic linking of related competences across different disciplines and communities of practice. With datasets of unstructured texts as input training data, our results show that the algorithm can readily identify nuclear domain-specific semantic links between words and concepts. We discuss how our results can be utilized to generate a quantitative network of links between competences across disciplines, thus acting as an enabler for identifying and bridging communities of practice, in nuclear and beyond.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1157-1159
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• 1987

A syntactic and semantic approach is used to make type classification based on feature points(whorl, delta, core) and the shape of flow line around feature points. The image is divided into 30 by 30 subregions which are represented in the average direction and 4-tuple direction component. Next the relaxation process with singularity detection and convergency checking is performed. A set of semantic languages is used to describe the major flow line around the extracted feature points. LR(1) parser and feature transfer function are used to recognize the coded flow patterns. The 72 fingerprint impressions is used to test the proposed approach and the rate of the classification is about 93 percentages.