• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1781-1791
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• 1996

A number of research issues such as knowledge acquisition, inferencing techniques, and knowledge refinement methodologies have been involved in the development of expert systems. Since each issue is considered very com- plicated, there has been little effort to take all the issues into account collectively at once. However, knowledge acquisition and inferencing are closely reated because the knowledge is extracted by human experts from the inferencing process for solving a specific task or problem. Knowledge refinement is also accomplished by hand-ling problems caused during the inferencing process of the system due to incompleteness and inconsistency of the knowledge base. From this perspecitive, we present a method by which software platform is established in which those issues are integrated in the development of expert systems, especially in the domain where the domain models and concepts are hard to be constructed because of inherent fuzziness of the domain. We apply a machine learning technique,technique, conceptual clustering,to build a knowledge base and rual models by which an efficient inferencing,incermental knp\owledge acquisition and refinment are possible.

• Proceedings of the Materials Research Society of Korea Conference
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• 2003.11a
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• pp.135-135
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• 2003

The fast evolution in the fold of optical communication systems demands powerful optical information treatment. These functions can be performed by integrated optical systems. A key component of such systems is erbium doped waveguide amplifier(EDWA). The intra 4f radiative transition of Er at 1.5 $\mu\textrm{m}$ is particularly interesting because this wavelength is standard in optical telecommunications. The fabrication of waveguide amplifier for integrated optics using sol-gel process has received an increasing attention. Potential advantage of lower cost by less capital equipment and easy processing makes this process an attractive alternatives to conventional technologies like flame hydrolysis deposition, ion exchange and chemical vapor deposition, etc. In addition, sol-gel process has been found to be extremely suitable for the control of composition and refractive index related directly with optical properties. The main drawback of such an amplifier with respect to the EDWA is the need for a much higher Er3+ concentration to compensate for the smaller interaction length. However, the high doping of Er might be resulted in the non-radiative relaxation by clustering of Er ions End co-operative upconversion. In order to solve this problem, we investigate the possibility of avoiding short Er-Er distances by encapsulation of Er3+ ions in hosts such as organic-inorganic hybrid materials. For inorganic-organic hybrid sols, methacryloxypropyltrimethoxysilane (MPTS), zirconyl chloride octahydrate and erbium(III) chloride hexahydrate were used as starting materials, followed by conventional sol-gel process. It was observed by TEM that nano sols having core/shell toplology were formed, depending on the mole ratio of Zr/Er. The surface roughness for the coatings on Si substrate was investigated by AFM as a function of Zr/Er ratio. The local environment and vibrational Properties of Er3+ ions were studied using Near-IR, FT-IR, and UV/Vis spectroscopy. Nano hybrid coatings derived from polymer and Er doped encapsulation Eave the good luminescence at 1.55$\mu\textrm{m}$.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1273-1287
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• 2009

PEGASIS, a chain-based protocol, forms chains from sensor nodes so that each node transmits and receives from a neighbor. In this way, only one node (known as a HEAD) is selected from that chain to transmit to the sink. Although PEGASIS is able to balance the workload among all of the nodes by selecting the HEAD node in turn, a considerable amount of energy may be wasted when nodes which are far away from sink node act as the HEAD. In this study, DERP (Distance-based Energy-efficient Routing Protocol) is proposed to address this problem. DERP is a chain-based protocol that improves the greedy-algorithm in PEGASIS by taking into account the distance from the HEAD to the sink node. The main idea of DERP is to adopt a pre-HEAD (P-HD) to distribute the energy load evenly among sensor nodes. In addition, to scale DERP to a large network, it can be extended to a multi-hop clustering protocol by selecting a "relay node" according to the distance between the P-HD and SINK. Analysis and simulation studies of DERP show that it consumes up to 80% less energy, and has less of a transmission delay compared to PEGASIS.

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.151-157
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• 2014

Recently UAV(unmanned aerial vehicle) is frequently used not only for military purpose but also for civil purpose. UAV automatically navigates following the coordinates input in advance using GPS information. However it is impossible when GPS cannot be received because of jamming or external interference. In order to solve this problem, we propose a real-time segmentation and classification algorithm for the specific regions from UAV image in this paper. We use the super-pixels algorithm using graph-based image segmentation as a pre-processing stage for the feature extraction. We choose the most ideal model by analyzing various color models and mixture color models. Also, we use support vector machine for classification, which is one of the machine learning algorithms and can use small quantity of training data. 18 color and texture feature vectors are extracted from the UAV image, then 3 classes of regions; river, vinyl house, rice filed are classified in real-time through training and prediction processes.

• The KIPS Transactions:PartA
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• v.14A no.7
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• pp.435-442
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• 2007

This paper is concerned with the mesh segmentation problem that can be applied to diverse applications such as texture mapping, simplification, morphing, compression, and shape matching for 3D mesh models. The mesh segmentation is the process of dividing a given mesh into the disjoint set of sub-meshes. We propose a method for segmenting meshes by simultaneously reflecting global and local geometric characteristics of the meshes. First, we extract sharp vertices over mesh vertices by interpreting the curvatures and convexity of a given mesh, which are respectively contained in the local and global geometric characteristics of the mesh. Next, we partition the sharp vertices into the $\kappa$ number of clusters by adopting the $\kappa$-means clustering method [29] based on the Euclidean distances between all pairs of the sharp vertices. Other vertices excluding the sharp vertices are merged into the nearest clusters by Euclidean distances. Also we implement the proposed method and visualize its experimental results on several 3D mesh models.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.577-588
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• 2014

The collection and storage of a large volumes of data are becoming easier; however, the number of variables is sometimes more than the number of samples(objects). We now face the problem of dependency among variables(such as multicollinearity) due to the increased number of variables. We cannot apply various statistical methods without satisfying independency assumption. In order to overcome such a drawback we consider a categorizing (or discretizing) observations. We have a data set of nancial indices from banks in Korea that contain 78 variables from 16 banks. Genetic sequence data is also a good example of a large data and there have been numerous statistical methods to handle it. We discover lots of useful bank information after we transform bank data into categorical data that resembles genetic sequence data and apply bioinformatic techniques.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.101-110
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• 2009

Multi-agent systems are mostly used to integrate the intelligent and distributed approaches to various systems for effective sharing of resources and dynamic system reconfigurations. Object replication is usually used to implement fault tolerance and solve the problem of unexpected failures to the system. This paper presents the intelligent multi-agent distributed platform based on the dynamic object group management and proposes an object search technique based on the proposed filtered k-means (Fk-means). We propose Fk-means for the search mechanism to find alternative objects in the event of object failures and transparently reconnect client to the object. The filtering range of Fk-means value is set only to include relevant objects within the group to perform the search method efficiently. The simulation result shows that the proposed mechanism provides fast and accurate search for the distributed object groups.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.610-617
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• 2003

Similarity matching in video database is of growing importance in many new applications such as video clustering and digital video libraries. In order to provide efficient access to relevant data in large databases, there have been many research efforts in video indexing with diverse spatial and temporal features. however, most of the previous works relied on sequential matching methods or memory-based inverted file techniques, thus making them unsuitable for a large volume of video databases. In order to resolve this problem, this paper proposes an effective and scalable indexing technique using a trie, originally proposed for string matching, as an index structure. For building an index, we convert each frame into a symbol sequence using a window order heuristic and build a disk-resident trie from a set of symbol sequences. For query processing, we perform a depth-first search on the trie and execute a temporal segmentation. To verify the superiority of our approach, we perform several experiments with real and synthetic data sets. The results reveal that our approach consistently outperforms the sequential scan method, and the performance gain is maintained even with a large volume of video databases.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.7
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• pp.75-83
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• 2007

IEC code based decision nile have been widely applied to detect incipient faults in power transformers. However, this method has a drawback to achieve the diagnosis with accuracy without experienced experts. In order to resolve this problem, we propose an artificial diagnosis algorithm to detect faults of power transformers using Self-Organizing Feature Map(SOM). The proposed method has two stages such as model construction and diagnostic procedure. First, faulty model is constructed by feature maps obtained by unsupervised learning for training data. And then, diagnosis is performed by compare feature map with it obtained for test data. Also the proposed method usぉms the possibility and degree of aging as well as the fault occurred in transformer by clustering and distance measure schemes. To demonstrate the validity of proposed method, various experiments are unformed and their results are presented.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.201-204
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• 2003

At a consequence of WWW large popularity, the internet has suffered from various performance problems, such as network congestion and overloaded servers. These days, it is not uncommon to find servers refusing connections because they are overloaded. Web server performance has always been a key issue in the design and operation of on-line systems. With regard to Internet, performance is also critical, because users want fast and easy access to all objects (e.g., documents, graphics, audio, and video) available on the net. To solve this problem, a number of companies are exploring the benefits of having multiple geographically or locally distributed Internet sites. This requires a comprehensive scheme for traffic management, which includes the principle of an optimal load balancing of client requests across multiple clusters of real servers. This paper focuses on the performance analysis of Web server and we apply these results to load balancing in clustering web server. It also discusses the mam steps needed to carry out a WWW performance analysis effort and shows relations between the workload characteristics and system resource usage. Also, we will introduce an optimal load balancing algorithm base on the RTSM (Real-Time Server Monitor) and Fuzzy Inference Engine for the local status of a real server, and the benefits is provided with of the suggested method.