• Proceedings of the KSPS conference
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• 2003.05a
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• pp.93-96
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• 2003

The present study was conducted to investigate the difference of cortical activation in naming the picture in Korean and English. Experimental design was 2(Korean, English) language condition x 4(no distractor, semantic related distractor, semantic unrelated distrator, corresponding distractor) distractor condition. language condition was between subject factor and distractor condition was within subject factor. The result was that Korean naming condition showed less cortical activation than English naming condition. The activation region was reported in each condition.

• Journal of Advanced Navigation Technology
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• v.12 no.5
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• pp.502-508
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• 2008

With the increased use of the internet and the tremendous amount of data it transfers, it is more necessary to summarize documents. We propose a new method using the Non-negative Semantic Variable Matrix (NSVM) and the generic important of semantic features obtained by Non-negative Matrix Factorization (NMF) to extract the sentences for automatic generic summarization. The proposed method use non-negative constraints which is more similar to the human's cognition process. As a result, the proposed method selects more meaningful sentences for summarization than the unsupervised method used the Latent Semantic Analysis (LSA) or clustering methods. The experimental results show that the proposed method archives better performance than other methods.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.23-28
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• 2002

A fundamental problem in building an intelligent agent is that an agent does not understand the meaning of its perception or its action. One reason that an agent cannot understand the world is partially caused by a syntactic approach that converts a semantic feature into a simple string. To solve this problem, Cohen introduces a semantic approach that an agent autonomously learns a meaningful representation of physical schemas, on which some advanced conceptual structures are built, from physically interacting with environment using its own sensors and effectors. However, Cohen does not deal with a meta level of conceptual primitive that makes recognizing a schema possible. We propose that negation is a meta schema that enables an agent to recognize a physical schema. We prove some semantic aspects of negation.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.180-182
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• 2007

The present study was carried out to investigate how two languages are represented and processed for the late Korean-English bilinguals. To this end, we compared the naming times of Korean-English bilinguals on a series of the picture-word interference tasks. The entire experiment is divided into four parts, each of which required participants to name the pictures in Korean or in English with distractor words visually presented either in Korean or English. The distractor words were semantically related or unrelated to the picture. The results showed that, in different language conditions (L1 naming-L2 distractor, L2 naming - L1 distractor), there was only numerical difference between semantic related and unrelated condition. In same language conditions (L1 naming-L1 distractor, L2 naming-L2 distractor), however, significant semantic interference effect occurred. And, the interference effect was stronger in the L1 distractor condition than in the L2 distractor condition. These results suggest that the semantic processing of L1 and L2 for the late bilinguals are independent each other.

• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.37-51
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• 2017

There has been a growing concern on ontology especially in recent knowledge-based industry and defining a field-customized semantic word network is essential for building it. In this paper, a word network for ontology is established with 785 publications of Korean Society of Rural Planning(KSRP), from 1995 to 2017. Semantic relationships between words in the publications were quantitatively measured with the 'normalized pointwise mutual information' based on the information theory. Appearance and co-appearance frequencies of nouns and adjectives in phrases are analyzed based on the assumption that a 'noun phrase' represents a single 'concept'. The word network of KSRP was compared with that of $WordNet^{TM}$, a world-wide thesaurus network, for the verification. It is proved that the KSRP's word network, established in this paper, provides words' semantic relationships based on the common concepts of Korean rural planning research field. With the results, it is expecting that the established word network can present more opportunity for preparation of the fourth industrial revolution to the field of the Korean rural planning.

• Speech Sciences
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• v.13 no.4
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• pp.187-200
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• 2006

The speech synthesis technology is widely used and its application area is also being broadened to an automatic response service, a learning system for handicapped person, etc. However, the sound quality of the speech synthesizer has not yet reached to the satisfactory level of users. To make a synthesized speech, the existing synthesizer generates rhythms only by the interval information such as space and comma or by several punctuation marks such as a question mark and an exclamation mark so that it is not easy to generate natural rhythms of people even though it is based on mass speech database. To make up for the problem, there is a way to select rhythms after processing language from a higher level information. This paper proposes a method for generating tags for controling rhythms by analyzing the meaning of sentence with speech situation information. We use the Systemic Functional Grammar (SFG) [4] which analyzes the meaning of sentence with speech situation information considering the sentence prior to the given one, the situation of a conversation, the relationship among people in the conversation, etc. In this study, we generate Semantic Speech Control Tag (SSCT) by the result of SFG's meaning analysis and the voice wave analysis.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.1-10
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• 2014

In recent years, the research of 3D mapping technique in urban environments obtained by mobile robots equipped with multiple sensors for recognizing the robot's surroundings is being studied actively. However, the map generated by simple integration of multiple sensors data only gives spatial information to robots. To get a semantic knowledge to help an autonomous mobile robot from the map, the robot has to convert low-level map representations to higher-level ones containing semantic knowledge of a scene. Given a 3D point cloud of an urban scene, this research proposes a method to recognize the objects effectively using 3D graph model for autonomous mobile robots. The proposed method is decomposed into three steps: sequential range data acquisition, normal vector estimation and incremental graph-based segmentation. This method guarantees the both real-time performance and accuracy of recognizing the objects in real urban environments. Also, it can provide plentiful data for classifying the objects. To evaluate a performance of proposed method, computation time and recognition rate of objects are analyzed. Experimental results show that the proposed method has efficiently in understanding the semantic knowledge of an urban environment.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.81-89
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• 2011

It is presumable that properly designed earcons given simultaneously with visual information could enhance the situation awareness of operators when they are involving in highly complicate process control activities. In this study, population stereotypes of earcons with respect to process control information were identified using 60 Korean subjects. To do this, 11 most distinctive earcons were selected from various earcons having different pitch, rhythm, and timbre. Associations between the selected earcons and 40 pairs of adjectives used to describe the state of control in process were gathered from 37 subjects using a semantic differential method. Based on the results from multivariate analyses, the 40 pairs of adjectives were aggregated into three distinctive semantic dimensions. The emotional maps of the 11 earcons matched with the semantic dimensions were presented in this study. On the basis of these results, a general guideline was suggested for designing earcons to deliver process control information.

• Journal of Information Technology Services
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• v.8 no.1
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• pp.203-215
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• 2009

This paper illustrates the application of co-occurrence theory to generate lightweight ontologies semi-automatically. The proposed model includes three steps of a (Semi-) Automatic creation of Ontology; (they are conceptually named as) the Syntactic-based Ontology, the Semantic-based Ontology and the Ontology Refinement. Each of these three steps are designed to interactively work together, so as to generate Lightweight Ontologies. The Syntactic-based Ontology step includes generating Association words using co-occurrence in web documents. The Semantic-based Ontology step includes the Alignment large Association words with small Ontology, through the process of semantic relations by contextual terms. Finally, the Ontology Refinement step includes the domain expert to refine the lightweight Ontologies. We also conducted a case study to generate lightweight ontologies in specific domains(news domain). In this paper, we found two directions including (1) employment co-occurrence theory to generate Syntactic-based Ontology automatically and (2) Alignment large Association words with small Ontology to generate lightweight ontologies semi-automatically. So far as the design and the generation of big Ontology is concerned, the proposed research will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.84-97
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• 2012

M2M (Machine-to-Machine) Technology makes it possible to network all kinds of terminal devices and their corresponding enterprise applications. Therefore, several M2M platforms were developed in China in order to collect information from terminal devices dispersed all over the local places through 3G wireless network. However, when enterprise applications try to integrate with M2M platforms, they should be maintained and refactored to adapt the heterogeneous features and properties of M2M platforms. Moreover, syntactical and semantic unification for information sharing among applications and devices are still unsolved because of raw data transmission and the usage of distinguished business vocabularies. In this paper, we propose and develop an M2M Middleware to support agile application integration with M2M platform. This middleware imports the event engine and XML-based syntax to handle the syntactical unification, makes use of Ontology-based semantic mapping to solve the semantic unification and adopts WebService and ETL techniques to sustain multi-pattern interactive approach, in order to agilely make applications integrated with the M2M platform. Now, the M2M Middleware has been applied in the China Telecom M2M platform. The operation results show that applications will cost less time and workload when being integrated with M2M platform.