• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.189-194
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• 2012

In this paper, we propose a query expansion method based on word graphs using pseudo-relevant and pseudo non-relevant documents to achieve performance improvement in information retrieval. The initially retrieved documents are classified into a core cluster when a document includes core query terms extracted by query term combinations and the degree of query term proximity. Otherwise, documents are classified into a non-core cluster. The documents that belong to a core query cluster can be seen as pseudo-relevant documents, and the documents that belong to a non-core cluster can be seen as pseudo non-relevant documents. Each cluster is represented as a graph which has nodes and edges. Each node represents a term and each edge represents proximity between the term and a query term. The term weight is calculated by subtracting the term weight in the non-core cluster graph from the term weight in the core cluster graph. It means that a term with a high weight in a non-core cluster graph should not be considered as an expanded term. Expansion terms are selected according to the term weights. Experimental results on TREC WT10g test collection show that the proposed method achieves 9.4% improvement over the language model in mean average precision.

• Journal of KIISE
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• v.42 no.3
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• pp.307-319
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• 2015

Current ontology studies use the Hadoop distributed storage framework to perform map-reduce algorithm-based reasoning for scalable ontologies. In this paper, however, we propose a novel approach for scalable Web Ontology Language (OWL) Horst Lite ontology reasoning, based on distributed cluster memories. Rule-based reasoning, which is frequently used for scalable ontologies, iteratively executes triple-format ontology rules, until the inferred data no longer exists. Therefore, when the scalable ontology reasoning is performed on computer hard drives, the ontology reasoner suffers from performance limitations. In order to overcome this drawback, we propose an approach that loads the ontologies into distributed cluster memories, using Spark (a memory-based distributed computing framework), which executes the ontology reasoning. In order to implement an appropriate OWL Horst Lite ontology reasoning system on Spark, our method divides the scalable ontologies into blocks, loads each block into the cluster nodes, and subsequently handles the data in the distributed memories. We used the Lehigh University Benchmark, which is used to evaluate ontology inference and search speed, to experimentally evaluate the methods suggested in this paper, which we applied to LUBM8000 (1.1 billion triples, 155 gigabytes). When compared with WebPIE, a representative mapreduce algorithm-based scalable ontology reasoner, the proposed approach showed a throughput improvement of 320% (62k/s) over WebPIE (19k/s).

• Fashion & Textile Research Journal
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• v.14 no.2
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• pp.193-202
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• 2012

With entering the 21st century, modern people's dark inside and panic are emerging as the talking point on the theater stage. Even in the field of stage costume, the necessity of a research is being demanded through analyzing on psychological anguish and structure of characters. Accordingly, this study aims to allow the stage costume design to be expressed a human being's Doppelg$\ddot{a}$nger Image, which was elicited through analyzing a work of the play titled Le Grand C$\acute{e}$r$\acute{e}$monial by a playwriter Fernando Arrabal, who draws the conflictory and contradictory duplicity, which positions in a human being's deep inside by having chaos as catalyst. A research subject is 'Le Grand C$\acute{e}$r$\acute{e}$monial,' which was staged as the winter performance in commemoration of the 50th anniversary for the foundation of Dept. of Theater, Chung-Ang Univ. in November 2009. Psychology of characters in a play, which varies dimensionally, could be delivered, as nonverbal element called costume, by applying costume design of Cavanoza, Syl, Nice to Doppelg$\ddot{a}$nger Image such as Innocence vs Cruelty, Purity vs Superficiality and Restraint vs Freedom, which were elicited through analyzing characters. Through this study, the costume, which was expressed by visualizing a human being's Doppelg$\ddot{a}$nger Image, could be known to function as important dramatic factor of allowing character's psychology to be understood through costume as well as functioning as visual and sensible language, which is important for communication with the audience. A research on costume design, which reflects a character's complex inside, is expected to be likely continued through in-depth analysis on a playwriter's intention and on the appearing characters at the current point of time when an active research is being performed on stage costume in the wake of this study.

• Science of Emotion and Sensibility
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• v.14 no.3
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• pp.371-384
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• 2011

Three experiments were carried out to examine how LED lighting hues influence to the rating and recognition of affective stimuli. In Experiment 1 and 2, IAPS affective pictures were used and an affective rating(valence and arousal) task and a recognition memory task were conducted under red, green, blue, and white hue LED lightings in Experiment 1 and cyan, magenta, yellow, and white ones in Experiment 2, respectively. In Experiment 3, affective words were used and the same two tasks were conducted under red, green, blue, and white hue LED lightings. According to the results of affective rating tasks, when primary hues(RGB) were used, red LED lighting elicited an excitement at the arousal dimension and green LED lighting evoked pleasantness at the valence one. When secondary hues(CMY) were used, magenta and cyan showed the similar but weaker patterns of responses comparing to red and green. The results of recognition memory task showed that the responses to the picture stimuli presented at green and cyan hue lightings tended to be a bit faster comparing to the stimuli presented at the other conditions but the difference was insignificant. In Experiment 3, however, recognition memory responses to the affective words presented at green hue lighting were faster significantly. These results indicate that warm colors like red and magenta elicit unpleasantness or excitement while cool colors like green and cyan evoke pleasantness or relaxation, and the primary hues provoke more positive or negative affectivity than secondary ones do. Particularly, the result of recognition memory task in Experiment 3 suggests that green hue LED lighting might be advantageous at the memory performance of language stimuli rather than visual ones.

• Korean Journal of Cognitive Science
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• v.27 no.1
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• pp.27-41
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• 2016

Named entity recognition is to classify elements in text into predefined categories and used for various departments which receives natural language inputs. In this paper, we propose a method which can generate named entity training corpus automatically using knowledge bases. We apply two different methods to generate corpus depending on the knowledge bases. One of the methods attaches named entity labels to text data using Wikipedia. The other method crawls data from web and labels named entities to web text data using Freebase. We conduct two experiments to evaluate corpus quality and our proposed method for generating Named entity recognition corpus automatically. We extract sentences randomly from two corpus which called Wikipedia corpus and Web corpus then label them to validate both automatic labeled corpus. We also show the performance of named entity recognizer trained by corpus generated in our proposed method. The result shows that our proposed method adapts well with new corpus which reflects diverse sentence structures and the newest entities.

• Korean Journal of Cognitive Science
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• v.21 no.2
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• pp.309-338
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• 2010

In this paper, we studied the brain-computer interface (BCI). BCIs help severely disabled people to control external devices by analyzing their brain signals evoked from motor imageries. The findings in the field of neurophysiology revealed that the power of $\beta$(14-26 Hz) and $\mu$(8-12 Hz) rhythms decreases or increases in synchrony of the underlying neuronal populations in the sensorymotor cortex when people imagine the movement of their body parts. These are called Event-Related Desynchronization / Synchronization (ERD/ERS), respectively. We implemented a BCI-based mouse interface system which enabled subjects to control a computer mouse cursor into four different directions (e.g., up, down, left, and right) by analyzing brain signal patterns online. Tongue, foot, left-hand, and right-hand motor imageries were utilized to stimulate a human brain. We used a non-invasive EEG which records brain's spontaneous electrical activity over a short period of time by placing electrodes on the scalp. Because of the nature of the EEG signals, i.e., low amplitude and vulnerability to artifacts and noise, it is hard to analyze and classify brain signals measured by EEG directly. In order to overcome these obstacles, we applied statistical machine-learning techniques. We could achieve high performance in the classification of four motor imageries by employing Common Spatial Pattern (CSP) and Linear Discriminant Analysis (LDA) which transformed input EEG signals into a new coordinate system making the variances among different motor imagery signals maximized for easy classification. From the inspection of the topographies of the results, we could also confirm ERD/ERS appeared at different brain areas for different motor imageries showing the correspondence with the anatomical and neurophysiological knowledge.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1468-1474
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• 2010

The establishment of a successful business must be preceded by comprehensive entrepreneurial preparation and research, as well as the development of a truly attractive business idea. Research to-date has tended to be based solely on factors relating to entrepreneurial activity or business performance. Research into the development and evaluation of a business idea has been insufficient. The purpose of this research is to propose a methodology for evaluating the attractiveness of a business idea objectively. This research measures the attractiveness of a business idea by the click through rate (CTR) to a website generated by specific keyword entry into internet search engines. The attractiveness of a business idea can be presented by the formula: number of relevant keyword searches x CTR on search results. As the number of searches for individual keywords is published by the search engines and it is possible to estimate CTRs for specific search results, we can objectively evaluate the attractiveness of a business idea. By analyzing keyword search data and CTRs obtained from search engines over a one month period, 1124 keywords that relate to foreign language education have been identified. A regression formula has also been derived, predicting the click through rate for search results. This research and its findings can be used to raise the success rates of new businesses; proposing objective guidelines for business idea development and evaluation. It is particularly meaningful because it introduces a new methodology to the arena.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1460-1471
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• 2007

A 3-Dimensional engine in a mobile embedded device is divided into a C-based OpenGL/ES and a Java-based JSR184 which interprets and executes a byte code in a real-time. In these two standards, the JSR184 supporting Java objects uses more processor resources than an OpenGL/ES and thus has a constraint when it is used in an embedded device with a limited computing power. On the other hand, 3-Dimensional contents employed in existing personal computer are created by utilizing advantages of Java and secured numerous users in European market, due to the good quality in contents and extensive service in a commercial network, GSM. Because of the reason, a mobile embedded device used in a GSM network needs a JSR184 which can provide an existing Java-based 3-Dimensional contents without extra conversion processes, but the current version of Java-based 3-Dimensional engine has drawbacks in application to commercial products because it requires more computing power than the mobile embedded device. This paper proposes a binding technique with the advantages of Java objects to improve a processing speed of 3-Dimensional contents in limited resources of a mobile embedded device. The technique supports a JSR184 standard interface in the upper layer to utilize 3-Dimensional contents using Java, employs a different code-conversion language, KNI(Kilo Native Interface), in the middle layer to interface between OpenGL/ES and JSR184, and embodies an OpenGL/ES standard in the lower layer. The validity of the binding technique is demonstrated through a simulator and a FPGA embedding an ARM.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.192-197
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• 1999

Programmers who write distributed programs are faced with a dilemma when writing the systems communication code. If the code is written by hand or partly by hand, then the speed of the application may be maximized, but the human effort required to implement and maintain the system is greatly increased. On the other hand, if the code is generated using a CORBA IDL compiler then the programmer effort will be reduced, but the performance of the application may be poor. So we need the optimizing the code generated by CORBA IDL compiler. We introduce the techniques which have been used by typical programming languages into compilation of IDL. We separate the phase of compilation into three phase. The first phase parses interface definition in IDL, manages nested scope and generates AST(Abstract Syntax Tree). The second phase implements the optimization. The third phase generates the code in target language. In this paper, we focus on the first phase. We separate interface definition into interface and message representation from AST. This supports the separate optimization of code in second phase.

• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.253-260
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• 2009

Many algorithms for computer vision and pattern recognition have recently been implemented on GPU (graphic processing unit) for faster computational times. However, the implementation has two problems. First, the programmer should master the fundamentals of the graphics shading languages that require the prior knowledge on computer graphics. Second, in a job that needs much cooperation between CPU and GPU, which is usual in image processing and pattern recognition contrary to the graphic area, CPU should generate raw feature data for GPU processing as much as possible to effectively utilize GPU performance. This paper proposes more quick and efficient implementation of neural networks on both GPU and multi-core CPU. We use CUDA (compute unified device architecture) that can be easily programmed due to its simple C language-like style instead of GPU to solve the first problem. Moreover, OpenMP (Open Multi-Processing) is used to concurrently process multiple data with single instruction on multi-core CPU, which results in effectively utilizing the memories of GPU. In the experiments, we implemented neural networks-based text extraction system using the proposed architecture, and the computational times showed about 15 times faster than implementation on only GPU without OpenMP.