• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.108-118
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• 2010

In this paper, we propose Context-based Music Recommendation (COMUS) ontology for modeling user's musical preferences and context and for supporting reasoning about the user's desired emotion and preferences. The COMUS provides an upper Music Ontology that captures concepts about the general properties of music such as title, artists and genre and also provides extensibility for adding domain-specific ontologies, such as Mood and Situation, in a hierarchical manner. The COMUS is music dedicated ontology in OWL constructed by incorporating domain specific classes for music recommendation into the Music Ontology. Using this context ontology, we believe that the use of logical reasoning by checking the consistency of context information, and reasoning over the high-level, implicit context from the low-level, explicit information. As a novelty, our ontology can express detailed and complicated relations among the music, moods and situations, enabling users to find appropriate music for the application. We present some of the experiments we performed as a case-study for music recommendation.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.447-458
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• 2012

We present a method to recognize hand gestures using skeletal joint data obtained from Microsoft's Kinect sensor. We propose a combination feature of multi-angle histograms robust to orientation variations to represent the observation sequence of skeletons. The proposed feature efficiently represents the orientation variations of gestures that can be occurred according to person or environment by combining the multiple angle histograms with various angular-quantization levels. The gesture represented as combination of multi-angle histograms and random decision forest classifier improve the recognition performance. We conduct the experiments in hand gesture dataset obtained from a kinect sensor and show that our method outperforms the other methods by comparing the recognition performance.

• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.556-561
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• 2016

This paper describes implementation of a 13.56 MHz, 5 kW RF high power generator for ISM band applications. This RF generator consists of four LDMOS modules of 1.25kW class-AB push-pull power amplifier with drive amplifier and its outputs are combined by using Wilkinson type transmission-line transformers. Its generator has a high efficiency and output power better than linearity. In order to discharge power transistor heats, we used on water cooled copper plate. Also, these have a composite circuit of combiner and low-pass filter and safety circuit to detector over and reflected power. The RF generator has achieved a efficiency of 79 % at 5.33 kW of saturated power level experimentally.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.1-9
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• 2013

This paper propose a human action recognition method that uses bag-of-features (BoF) based on CS-LBP (center-symmetric local binary pattern) and a spatial pyramid in addition to the random forest classifier. To construct the BoF, an image divided into dense regular grids and extract from each patch. A code word which is a visual vocabulary, is formed by k-means clustering of a random subset of patches. For enhanced action discrimination, local BoF histogram from three subdivided levels of a spatial pyramid is estimated, and a weighted BoF histogram is generated by concatenating the local histograms. For action classification, a random forest, which is an ensemble of decision trees, is built to model the distribution of each action class. The random forest combined with the weighted BoF histogram is successfully applied to Standford Action 40 including various human action images, and its classification performance is better than that of other methods. Furthermore, the proposed method allows action recognition to be performed in near real-time.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1532-1541
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• 1999

In this paper, we built an Object Oriented Framework for Web collaboration system which contains high level analysis information and design knowledge for java applets and applications that enable web clients to communicate and collaborate each other. Components of framework contain design information, source codes and executable codes for reuse. We had defined a development method for domain framework in related works and built a web collaboration system framework following it. We defined subsystem of web collaboration system for the communication and collaboration between web clients. We also BBS, Q&A system, board service system for the communication and collaboration between web clients. We also developed visual tools for framework usability : source code generator, class editor, knowledge supporting tools.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.19-26
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• 2010

This paper proposes a classifier based on rectangular feature to detect face in real time. The goal is to realize a strong detection algorithm which satisfies both efficiency in calculation and detection performance. The proposed algorithm consists of the following three stages: Feature creation, classifier study and real time facial domain detection. Feature creation organizes a feature set with the proposed five rectangular features and calculates the feature values efficiently by using SAT (Summed-Area Tables). Classifier learning creates classifiers hierarchically by using the AdaBoost algorithm. In addition, it gets excellent detection performance by applying important face patterns repeatedly at the next level. Real time facial domain detection finds facial domains rapidly and efficiently through the classifier based on the rectangular feature that was created. Also, the recognition rate was improved by using the domain which detected a face domain as the input image and by using PCA and KNN algorithms and a Class to Class rather than the existing Point to Point technique.

• Journal of Digital Contents Society
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• v.15 no.5
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• pp.603-612
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• 2014

To provide efficient and correct search results, ontology which use the structure of information, is considered as a main mechanism in the semantic web. Therefore, recent research in information retrieval and data construction have emphasized the use of ontologies as a data representation and search mechanism. In this paper, we propose a semantic search method using ontology to improve search ability in web environment. Ontology and knowledge base is used to represent semantic meaning of the data and provide related web documents and facts as results. Also, search result ranking mechanism is proposed. The mechanism use cardinality of the keyword in the contents and structural information of ontology. Experimental results with several query processing indicate that different coefficient value in the expression gives different results in sample ontology system and we propose appropriate values of the coefficient.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.77-88
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• 2017

Recently, with the advent of knowledge based society where information and knowledge make values, patents which are the representative form of intellectual property have become important, and the number of the patents follows growing trends. Thus, it needs to classify the patents depending on the technological topic of the invention appropriately in order to use a vast amount of the patent information effectively. IPC (International Patent Classification) is widely used for this situation. Researches about IPC automatic classification have been studied using data mining and machine learning algorithms to improve current IPC classification task which categorizes patent documents by hand. However, most of the previous researches have focused on applying various existing machine learning methods to the patent documents rather than considering on the characteristics of the data or the structure of patent documents. In this paper, therefore, we propose to use two structural fields, technical field and background, considered as having impacts on the patent classification, where the two field are selected by applying of the characteristics of patent documents and the role of the structural fields. We also construct multi-label classification model to reflect what a patent document could have multiple IPCs. Furthermore, we propose a method to classify patent documents at the IPC subclass level comprised of 630 categories so that we investigate the possibility of applying the IPC multi-label classification model into the real field. The effect of structural fields of patent documents are examined using 564,793 registered patents in Korea, and 87.2% precision is obtained in the case of using title, abstract, claims, technical field and background. From this sequence, we verify that the technical field and background have an important role in improving the precision of IPC multi-label classification in IPC subclass level.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.442-453
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• 2007

A model-based integrated development tool for the development of USN application programs is proposed in this paper. The proposed tool has been implemented as a plug-in for Eclipse platform. The tool consists of Graphical User Interface, Modeler, Configuration Information Generator, Validity Checker, Source Code Generator and Templates Storage. Developers can implement USN applications from models of sensor networks using the tool. The developer can implement USN applications by automatic generation of execution code of each node in the sensor network after he/she designs a model of the sensor network. The configuration information of each node is automatically generated from the validated USN model. Then, the execution code is automatically generated using the configuration information and the predefined templates. Through the tool of this paper, developers can easily implement valid USN applications even if they do not know the details of low-level information. Also, a large number of application programs can be generated at once because application programs are generated from sensor network model instead of models of applications. Accordingly, the development effort of USN applications will be decreased and developers can consistently construct USN applications from USN models using the proposed tool.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2A
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• pp.95-104
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• 2010

In wireless communication system, a variety of retransmission algorithms are used in order to improve the quality of service of users. But the system may be inefficient because retransmission algorithms operate independently with other layers. Also, the quality of service can be degraded due to the unnecessary retransmission of packets. To solve these problems, the study on the cross-layer retransmission schemes have been widely performed. However, in order to apply cross-layer retransmission schemes to wireless communication system, whether the performance of cross-layer retransmission schemes meets QoS requirements of each service class has to be verified. Thus, this paper proposes the mathematical model for analyzing the performance of the cross-layer retransmission schemes and derives both the suitable retransmission scheme and the optimal retransmission parameter on each service class. The proposed mathematical model selects the MCS level based on channel state information and The performance analysis is comparatively easy in case that HARQ, ARQ, and AMC schemes are combined. The proposed mathematical model also enables the analysis of the packet transmission delay. To utilize the analytical model, this paper derives the suitable retransmission scheme and the optimal retransmission parameter for delay sensitive services in WiMAX system. Also, the proposed analytical model can be used to analyze the performance of wireless communication system such as LTE and WLAN.