• Journal of KIISE:Software and Applications
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• v.28 no.12
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• pp.875-884
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• 2001

Although the self organizing map (SOM) is widely utilized in such fields of data visualization and topology preserving mapping, since it should have the topology fixed before trained, it has some shortcomings that it is difficult to apply it to practical problems, and classification capability is quite low despite better clustering performance. To overcome these points this paper proposes the dynamic topology preserving self-organizing map(DTSOM) that dynamically splits the output nodes on the map and trains them, and attempts to improve the classification capability by combining multiple DTSOMs K-Winner method has been applied to combine DTSOMs which produces K outputs with winner node selection method. This produces even better performance than the conventional combining methods such as majority voting weighting, BKS Bayesian, Borda, Condorect and reliability sum. DTSOM remedies the shortcoming of determining the topology in advance, and the classification rate increases significantly by combing multiple maps trained with different features. Experimental results with handwritten digit recognition indicate that the proposed method works out to problems of conventional SOM effectively so to improve the classification rate to 98.1%.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.129-139
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• 2003

The PC cluster architecture is considered as a cost-effective alternative to the existing supercomputers for realizing a high-performance information retrieval (IR) system. To implement an efficient IR system on a PC cluster, it is essential to achieve maximum parallelism by having the data appropriately distributed to the local hard disks of the PCs in such a way that the disk I/O and the subsequent computation are distributed as evenly as possible to all the PCs. If the terms in the inverted index file can be classified to closely related clusters, the parallelism can be maximized by distributing them to the PCs in an interleaved manner. One of the goals of this research is the development of methods for automatically clustering the terms based on the likelihood of the terms' co-occurrence in the same query. Also, in this paper, we propose a method for duplicate distribution of inverted index records among the PCs to achieve fault-tolerance as well as dynamic load balancing. Experiments with a large corpus revealed the efficiency and effectiveness of our method.

• Aerospace Engineering and Technology
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• v.12 no.1
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• pp.87-93
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• 2013

The conceptual design lunar lander demonstrator has been developed to use as a test bed for advanced spacecraft technologies and to test a prototype planetary lander capable of vertical takeoff and landing. Size of the lunar lander demonstrator is the same as that of lunar lander conceptually designed, however, the weight of lunar lander demonstrator is designed in 1/6 scale in consideration of gravity difference between moon and earth. The thruster clustering and virtual flight test were performed in the demonstrator fixed on the ground. The demonstrator ground test has been conducted for two months in the test site for the solid motor combustion of the Goheung Flight Center. The purposes of ground test of demonstrator are to demonstrate and verify essential electronics, propulsion system, control algorithm, embedded software, structure and system operation technologies before developing the flight model lander. This paper is described about the virtual flight test including test configuration, test aims and test facilities

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1733-1748
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• 1997

In this paper, we propose the classification scheme and retrieval mechanism which can apply to many application domains in order to construct the software reuse library. Classification scheme which is the core of the accessibility in the reusability, is defined by the hierarchical structure using the agglomerative clusters. Agglomerative cluster means the group of the reuse component by the functional relationships. Functional relationships are measured by the HACM which is the representation method about software components to calculate the similarities among the classes in the particular domain. And clustering informations are added to the library structure which determines the functionality and accuracy of the retrieval system. And the system stores the classification results such as the index information with the weights, the similarity matrix, the hierarchical structure. Therefore users can retrieve the software component using the query which is the natural language. The thesis is studied to focus on the findability of software components in the reuse library. As a result, the part of the construction process of the reuse library was automated, and we can construct the object-oriented reuse library with the extendibility and relationship about the reuse components. Also the our process is visualized through the browse hierarchy of the retrieval environment, and the retrieval system is integrated to the reuse system CARS 2.1.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.11
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• pp.635-642
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• 2004

The traditional communication protocols such as TCP/IP are not suitable for PC cluster systems because of their high software processing overhead. To eliminate this overhead, industry leaders have defined the Virtual Interface Architecture (VIA). VIA provides two different data transfer mechanisms, a traditional Send/Receive model and the Remote Direct Memory Access (RDMA) model. RDMA is extremely efficient way to reduce software overhead because it can bypass the OS and use the network interface controller (NIC) directly for communication, also bypass the CPU on the remote host. In this paper, we have implemented VIA-based RDMA mechanism in hardware. Compared to the traditional Send/Receive model, the RDMA mechanism improves latency and bandwidth. Our RDMA mechanism can also communicate without using remote CPU cycles. Our experimental results show a minimum latency of 12.5${\mu}\textrm{s}$ and a maximum bandwidth of 95.5MB/s. As a result, our RDMA mechanism allows PC cluster systems to have a high performance communication method.

• Journal of KIISE:Software and Applications
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• v.27 no.1
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• pp.74-83
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• 2000

There is a rapid increase in the use of digital video information in recent years. Especially, user requires the environment which retrieves video from passive access to active access, to be more efficiently. we need to implement video retrieval system including video parsing, clustering, and browsing to satisfy user's requirement. In this paper, we first divide video sequence to shots which are primary unit for automatic indexing, using a hybrid method with mixing histogram method and pixel-based method. After the shot boundaries are detected, corresponding key frames can be extracted. Key frames are very important portion because they help to understand overall contents of video. In this paper, we first analyze camera operation in video and then select different number of key frames depend on shot complexity. At last, we compose panorama images from shots which are containing panning or tilting in order to provide more useful and understandable browsing environment to users.

• Journal of KIISE:Software and Applications
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• v.32 no.9
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• pp.901-911
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• 2005

With the development of e-commerce and the proliferation of easily accessible information, information filtering has become a popular technique to prune large information spaces so that users are directed toward those items that best meet their needs and preferences. While many collaborative filtering systems have succeeded in capturing the similarities among users or items based on ratings to provide good recommendations, there are still some challenges for them to be more efficient, especially the user bias problem, non-transitive association problem and cold start problem. Those three problems impede us to capture more accurate similarities among users or items. In this paper, we provide probabilistic model approaches for UCHM and ICHM which are suggested to solve the addressed problems in hopes of achieving better performance. In this probabilistic model, objects (users or items) are classified into groups and predictions are made for users considering the Gaussian distribution of user ratings. Experiments on a real-word data set illustrate that our proposed approach is comparable with others.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.347-354
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• 2021

As interest in artificial intelligence education for elementary school students has recently increased, it is necessary to analyze the existing elementary information education research from a macroscopic point of view to understand the current situation and to provide implications for subsequent research. This study analyzed Journal of The Korean Association of Information Education for the purpose of looking at the research trend of elementary information education in Korea. For the data of the study, all papers published until 2020 in the first issue of the journal were selected, and 11 research topics were derived by modeling topics. As a result of the study, topic T1, the highest proportion, was analyzed to account for about 38%, and keywords such as education, research, analysis, elementary school, and information were derived according to the order of contribution to topic T1. As a result of regression analysis according to the year of the topic, it was found that the research trend is changing to computing thinking, software education, and artificial intelligence education. The significance of this study is that text data related to elementary information education is objectively clustered.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.75-86
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• 2022

This study aims to solve the problem of class imbalance in numerical data by using a deep learning-based Variational AutoEncoder and to improve the performance of the learning model by augmenting the learning data. We propose 'D-VAE' to artificially increase the number of records for a given table data. The main features of the proposed technique go through discretization and feature selection in the preprocessing process to optimize the data. In the discretization process, K-means are applied and grouped, and then converted into one-hot vectors by one-hot encoding technique. Subsequently, for memory efficiency, sample data are generated with Variational AutoEncoder using only features that help predict with RFECV among feature selection techniques. To verify the performance of the proposed model, we demonstrate its validity by conducting experiments by data augmentation ratio.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.167-172
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• 2023

The P-3C maritime patrol aircraft operated by the Republic of Korea Navy is equipped with various sensor devices (LRUs, line replace units) for tactical data collection. Depending on the characteristics of the sensor device, it operates with various communication protocols such as IEEE 802.3, MIL-STD-1553A/B, and ARINC-429. In addition, the collected tactical data is processed in the tactical station for mission operators, and this tactical station constitutes a clustering network on Gigabit Ethernet and operates in a distributed processing method. For communication with the sensor device, a specific tactical station mounts a peripheral device (eg. ARINC-429 interface card). The problem is that the performance of the entire distributed processing according to the peripheral device control and communication relay of this specific device is degraded, and even the operation stop of the tactical station has a problem of disconnecting the communication with the related sensor device. In this paper, we propose a method to mount a separate gateway to solve this problem, and the validity of the proposed application is demonstrated through the operation result of this gateway.