• Information Systems Review
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• v.4 no.2
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• pp.223-236
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• 2002

In an agent-based system, each agent has its own decision making capability and competes, cooperates, and communicates each other with an agent interface. Virtual manufacturing has characteristics as a typical application area of agent-based system: complex and time-bound decision making and negotiation. The time-boundness influences the choice of decision making models and design of protocols for internal and external negotiation. In this paper, we provide a case study which suggests a time-bound framework for external and internal negotiation between the agents for virtual manufacturing environment. We illustrate decision making model selection strategy and the system architecture of the agent-based system for the complex and time-bound environment.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.1
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• pp.105-111
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• 2003

Wheel for passenger car support the car weight with tires, and they transmit rolling and braking power into the ground. Whittling away at wheel weight is more effective to boost fuel economy than lighting vehicle body structure. A shape of hole in disk is optimized for minimizing the weight of steel wheel. Pro/ENGINEER program is used for formulating the design model, and ANSYS package is selected for analyzing the design model. It has difficulties to interface these commercial software directly. For Combining both programs, response surface methodology is applied to construct approximation functions for maximum stresses and maximum displacements are obtained by full factorial design of five levels. This steel wheel is modeled in 14-inch diameter of rim, and wide parameter of hole in disk is only selected as design variable for reducing the weight of steel whee. PLBA(Pshenichny-Lim-Belegundu-Arora) algorithm, which used the second-order information in the direction finding problem and uses the active set strategy, is used for solving optimization problems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1542-1550
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• 2019

Legacy studies for classifying arrhythmia have been studied to improve the accuracy of classification, Neural Network, Fuzzy, etc. Deep learning is most frequently used for arrhythmia classification using error backpropagation algorithm by solving the limit of hidden layer number, which is a problem of neural network. In order to apply a deep learning model to an ECG signal, it is necessary to select an optimal model and parameters. In this paper, we propose optimal parameter extraction method based on a deep learning. For this purpose, R-wave is detected in the ECG signal from which noise has been removed, QRS and RR interval segment is modelled. And then, the weights were learned by supervised learning method through deep learning and the model was evaluated by the verification data. The detection and classification rate of R wave and PVC is evaluated through MIT-BIH arrhythmia database. The performance results indicate the average of 99.77% in R wave detection and 97.84% in PVC classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1341-1347
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• 2020

Legacy studies for classifying arrhythmia have been studied in order to improve the accuracy of classification, Neural Network, Fuzzy, Machine Learning, etc. In particular, deep learning is most frequently used for arrhythmia classification using error backpropagation algorithm by solving the limit of hidden layer number, which is a problem of neural network. In order to apply a deep learning model to an ECG signal, it is necessary to select an optimal model and parameters. In this paper, we propose parameter extraction based on AR and arrhythmia classification through a deep learning. For this purpose, the R-wave is detected in the ECG signal from which noise has been removed, QRS and RR interval is modelled. And then, the weights were learned by supervised learning method through deep learning and the model was evaluated by the verification data. The classification rate of PVC is evaluated through MIT-BIH arrhythmia database. The achieved scores indicate arrhythmia classification rate of over 97%.

• The Journal of Korean Association of Computer Education
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• v.12 no.2
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• pp.23-31
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• 2009

The new national K-12 Information subject curriculum which will be effective in year 2010 includes algorithm and programming sections. Programming languages in K-12 are more effective the Educational Programming Language (EPL) than general language, because it focuses on developing problem solving ability rather than training a programmer. Therefore, it is necessary to study for suitable EPL in Korean K-12 curriculum. In this study, we studied and analyzed various types of EPLs available and strategies to apply them to the new national curriculum. First of all, we chose 26 educational programming languages and analyzed their characteristics and functions. Also, we investigated associations between key factors of the new Information curriculum and each language and suggested a proper language for their students' level. Finally, we considered possible problems and suitability to Korean K-12 students. The result of this study help us to choose what is the proper EPL and to consider applicability and criteria of EPLs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1653-1659
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• 2015

Operating Systems is a discipline which handles abstract concepts and techniques. However, most of OS courses have been textbook-oriented theoretical classes. Theoretical classes lead to the decline in the understanding of a lecture and hurt their concentration. Many instructors have tried various ways to help students understand lectures and arouse interests. This paper describes the design and implementation of a web-based educational CPU scheduling simulator which enables learners to set up various situations and simulate scheduling processes using a web browser or a smart-phone. After utilizing the implemented simulator for the class, the survey result for 2014's students shows that it is useful as an educational tool which enhances the understanding of a lecture and develops their problem solving skills.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.917-925
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• 2021

This study aims to specify a constructivism-based instructional method using a modular data analysis tool. The value and meaning of a modular data analysis tool have been examined to be applied in the national curriculum for artificial intelligence education and the process of cultivating problem-solving ability based on computational thinking. The modular data analysis tool visually expresses the cognitive thinking process that forms the schema in equilibrating through assimilation and adjustment. Artificial intelligence education has features that embody abstract knowledge and structure the data analysis module through the represented schema as a BlackBox implemented as an algorithm. Therefore, the value of the modular data analysis tool could be examined because it has the advantage of connecting the conceptual and implicit schema.

• Journal of Korea Water Resources Association
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• v.37 no.12
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• pp.1009-1018
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• 2004

A systematic method using an optimal estimation algorithm is presented for simultaneous estimation of diffuse pollution distributed along a stream reach and model parameters for a stream water quality model. It was applied with the QVAL2E model to the South Han River for optimal estimation of kinetic constants and diffuse loads along the river. Initial calibration results for kinetic constants selected from a sensitivity analysis reveal that diffuse source inputs for nitrogen and phosphorus are essential to satisfy the system mass balance. Diffuse loads for total nitrogen and total phosphorus were estimated solving the expanded inverse problem. Comparison of kinetic constants estimated simultaneously with diffuse sources to those estimated without diffuse loads, suggests that diffuse sources must be included in the optimization not only for its own estimation but also for adequate estimation of the model parameters. Application of optimization method to river water quality modeling is discussed in terms of the sensitivity coefficient matrix structure.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.122-126
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• 2019

These-days technology related to IoT (Internet of Thing) is widely used and there are many types of smart system based IoT like smart health, smart building and so on. In smart health system, it is possible to check someone's health by analyzing data from wearable IoT device like smart watch. Smart building system aims to collect data from sensor such as humidity, temperature, human counter like that and control the building for energy efficiency, security, safety and so forth. Furthermore, smart city system can comprise several smart systems like smart building, smart health, smart mobility, smart energy and etc. In this paper, we propose multimedia IoT based intelligent emergency alarm system for smart city. In existing IoT based smart system, it communicates lightweight data like text data. In the past, due to network's limitations lightweight IoT protocol was proposed for communicating data between things but now network technology develops, problem which is to communicate heavy data is solving. The proposed system obtains video from IP cameras/CCTVs, analyses the video by exploiting AI algorithm for detecting emergencies and prevents them which cause damage or death. If emergency is detected, the proposed system sends warning message that emergency may occur to people or agencies. We built prototype of the intelligent emergency alarm system based on MQTT and assured that the system detected dangerous situation and sent alarm messages. From the test results, it is expected that the system can prevent damages of people, nature and save human life from emergency.

• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1133-1148
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• 2012

This paper presents a hierarchical structuring method for the multidimensional type inheritance indices (MD-TIXs) that support the processing of XML queries in XML databases. MD-TIX uses a multidimensional index structure for efficiently supporting ancestor-descendant explorations that involve both nested element and type inheritance hierarchies. However, In the case of a long Xpath, the building and maintenance of MD-TIX are very difficult because of index entry construction problem. So, we propose a type inheritance index hierarchy method for solving this difficulty. We first construct base indices that support direct relationship explorations between adjacent two types on a given Xpath, and then, based on these base indices, we construct hierarchically the derived indices that support indirect relationship explorations between any two types of Xpath until constructing one target index for supporting the full Xpath. And we also present an algorithm that efficiently constructs a partial index hierarchy for supporting given a set of sub-pathes explorations.