• Journal of KIISE:Databases
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• v.31 no.3
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• pp.205-218
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• 2004

As the development of database technology for managing spatiotemporal data, new types of spatiotemporal application services that need the spatiotemporal knowledge discovery from the large volume of spatiotemporal data are emerging. In this paper, a new 3-layered discovery framework for the development of spatiotemporal knowledge discovery techniques is proposed. The framework supports the foundation model in order not only to define spatiotemporal knowledge discovery problem but also to represent the definition of spatiotemporal knowledge and their relationships. Also the components of spatiotemporal knowledge discovery system and its implementation model are proposed. The discovery framework proposed in this paper satisfies the requirement of the development of new types of spatiotemporal knowledge discovery techniques. The proposed framework can support the representation model of each element and relationships between objects of the spatiotemporal data set, information and knowledge. Hence in designing of the new types of knowledge discovery such as spatiotemporal moving pattern, the proposed framework can not only formalize but also simplify the discovery problems.

• Archives of Plastic Surgery
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• v.34 no.4
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• pp.471-477
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• 2007

Purpose: Hydrofluoric acid(HF) is one of the most dangerous mineral acids with dissociated fluoride ions. As hydrofluoric acid is present in various household products(such as rust removers), a large population of industrials is at the risk of HF exposure. It is a very strong organic acid, used widely in glass etching, metal washing, and in the semiconductor industry. Even when using adequate safety measures, lack of care on the user's part results in chemical burn by HF. Symptoms caused by HF-induced chemical burns shows delayed manifestations resulting in a loss of proper treatment opportunities. We therefore reviewed 20 cases of HF-induced chemical burns and treatment principle. Methods: The objects of this study were 19 male patients and 1 female treated from March 2004 to March 2006. There were 19 cases of injury on digits and 1 on the wrist area. There were 15 cases of immediate treatment after sustaining HF-induced burns, and 5 cases of delayed treatment. As a principle, in the emergency treatment, partial or complete removal of the nail along with copious washing with normal saline was done, depending on the degree of HF invasion of the distal digital extremities. Results: The 15 cases who came to the hospital immediately after the injury were healed completely without sequelae, and those who delayed their treatment needed secondary surgical measures, due to the severity of inflammation and necrosis of the digital tissues. Conclusion: As the industrial sector develops, the use of HF is increasing more and more, leading to increase in incidences of HF-induced chemical burns. When treating chemical burns caused by HF, washing by copious amounts of normal saline, along with early removal of the nails, rather than calcium gluconate, seems to be a available method for preserving the shape and function of the digits and the nail. The education of patients regarding this subject should be empathized accordingly.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.5
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• pp.523-530
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• 2010

Recently more gravity data is being obtained due to the increased demands from the fields of geodesy, geophysics, and military. In general, the observed gravity values are corrected for the effect of tide, instrument drift, and instrument height to generate the absolute gravity values at a point. Until yet, the models for tide and drift corrections and those procedures are not determined in Korea which led to the inconsistent data processing for different data sets. Therefore, in this study, the models for tide and drift are analyzed to select the appropriate models. Based on the analysis, it was found that there is not much difference between Longman and Tamura tide models for celestial objects. Earth tide, however, should be considered in tide correction procedure. In drift corrections, the difference between the model considering only the common points and that considering all points appears significantly large up to 0.04mGal. In this case, the model with all points should be used as it the correct one according to the adjustment theory and it generates estimates with better precision.

• Journal of KIISE
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• v.42 no.8
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• pp.1031-1038
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• 2015

The recent emergence of smart phones, wearable devices, and even the IoT concept made it possible for various objects to interact one another anytime and anywhere. Among many of such smart services, a smart home service typically requires a large number of sensors to recognize the residents' activities. For this reason, the ideas on activity recognition using the data obtained from those sensors are actively discussed and studied these days. Furthermore, plenty of sensors are installed in order to recognize activities and analyze their patterns via data mining techniques. However, if many of these sensors should be installed for IoT smart home service, it raises the issue of cost and energy consumption. In this paper, we proposed a new method for reducing the number of sensors for activity recognition in a smart environment, which utilizes the principal component analysis and clustering techniques, and also show the effect of improvement in terms of the activity recognition by the proposed method.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.9
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• pp.469-478
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• 2001

It is difficult to test a distributed system because of the task of controlling concurrent events,. Existing works do not propose the test sequence generation algorithm in a formal way and the amount of message is large due to synchronization. In this paper, we propose a formal test sequence generation algorithm using logical clock to control concurrent events. It can solve the control-observation problem and makes the test results reproducible. It also provides a generic solution such that the algorithm can be used for any possible communication paradigm. In distributed test, the number of channels among the testers increases non-linearly with the number of distributed objects. We propose a new remote test architecture for solving this problem. SDL Tool is used to verify the correctness of the proposed algorithm and it is applied to the message exchange for the establishment of Q.2971 point-to-multipoint call/connection as a case study.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.487-492
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• 2017

Clustering is a technique which is used to measure similarities between data in big data analysis and data mining field. Among various clustering methods, k-Modes algorithm is representatively used for categorical data. To increase the performance of iterative-centric tasks such as k-Modes, a distributed and concurrent framework Spark has been received great attention recently because it overcomes the limitation of Hadoop. Spark provides an environment that can process large amount of data in main memory using the concept of abstract objects called RDD. Spark provides Mllib, a dedicated library for machine learning, but Mllib only includes k-means that can process only continuous data, so there is a limitation that categorical data processing is impossible. In this paper, we design RDD for k-Modes algorithm for categorical data clustering in spark environment and implement an algorithm that can operate effectively. Experiments show that the proposed algorithm increases linearly in the spark environment.

• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.613-620
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• 2009

It is necessary to develop a system of judging whether or not the parts are defective easily at low cost, especially in a small scale factory which manufactures a large variety of products in small amounts. To develop such system, we require to recognize objects using human's cognitive ability under various circumstances. Human's high intelligence originates mostly from neocortex of human brain. The HTM theory, which is proposed by Jeff Hopkins, is one of the recent researches to model the operation principle of neocortex. In this paper we developed PRESM (Parts image REcognition System for small scale Manufacturing industry) system based on the HTM theory to judge badness of manufactured products. As a result of application to the real field of workplace environments we identified the superiority of our recognition system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1442-1449
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• 2007

Shadows are important elements for realistic rendering of the 3D scene. We cannot recognize the distance of objects in the 3D scene without shadows. Two methods, image-based medthods and object-based methods, are largely used for the rendering of shadows. Object based methods can generate accurate shadow boundaries. However, it cannot be used to generate the realtime shadows because the time complexity defends on the complexity of the 3D scene. Image based methods which are techniques to generate shadows are widely used because of fast calculation time. However, this algorithm has aliasing problems. PCF is a method to solve the aliasing problem. Using PCF technique, antialiased shadow boundaries can be generated. However, PCF with large filter size requires more time to calculate antialiased shadow boundaries. This paper proposes an improved PCF technique which generates antialiased shadow boundaries similar to that of PCF. Compared with PCF, this technique can generate antialiased shadows in less time.

• Journal of the Korean Solar Energy Society
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• v.38 no.3
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• pp.21-28
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• 2018

The objects of PV (Photovoltaic) monitoring system is to reduce the loss of system and operation and maintenance costs. In case of PV plants with configured of centralized inverter type, only 1 PV module might be caused a large loss in the PV plant. For this reason, the monitoring technology of PV module-level that find out the location of the fault module and reduce the system losses is interested. In this paper, a fault diagnosis algorithm are proposed using thermal and electrical characteristics of PV modules under failure. In addition, the monitoring system applied with proposed algorithm was constructed. The wireless sensor using LoRa chip was designed to be able to connect with IoT device in the future. The characteristics of PV module by shading is not failure but it is treated as a temporary failure. In the monitoring system, it is possible to diagnose whether or not failure of bypass diode inside the junction box. The fault diagnosis algorithm are developed on considering a situation such as communication error of wireless sensor and empirical performance evaluation are currently conducting.