• Advanced Industrial SCIence
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• v.1 no.1
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• pp.7-15
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• 2022

To adopt the development in the medical scenario IoT developed towards the advancement with the processing of a large amount of medical data defined as an Internet of Medical Things (IoMT). The vast range of collected medical data is stored in the cloud in the structured manner to process the collected healthcare data. However, it is difficult to handle the huge volume of the healthcare data so it is necessary to develop an appropriate scheme for the healthcare structured data. In this paper, a machine learning mode for processing the structured heath care data collected from the IoMT is suggested. To process the vast range of healthcare data, this paper proposed an MTGPLSTM model for the processing of the medical data. The proposed model integrates the linear regression model for the processing of healthcare information. With the developed model outlier model is implemented based on the FinTech model for the evaluation and prediction of the COVID-19 healthcare dataset collected from the IoMT. The proposed MTGPLSTM model comprises of the regression model to predict and evaluate the planning scheme for the prevention of the infection spreading. The developed model performance is evaluated based on the consideration of the different classifiers such as LR, SVR, RFR, LSTM and the proposed MTGPLSTM model and the different size of data as 1GB, 2GB and 3GB is mainly concerned. The comparative analysis expressed that the proposed MTGPLSTM model achieves ~4% reduced MAPE and RMSE value for the worldwide data; in case of china minimal MAPE value of 0.97 is achieved which is ~ 6% minimal than the existing classifier leads.

• The Journal of Korea Robotics Society
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• v.4 no.2
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• pp.147-154
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• 2009

Visions of ubiquitous robotics and ambient intelligence involve distributing information, knowledge, computation over a wide range of servers and data storage devices located all over the world, and integrating tiny microprocessors, actuators, and sensors into everyday objects as well in order to make them smart. In this paper, we introduce our ongoing research effort aimed at realizing ubiquitous robots in an information structured space. For this, a ubiquitous space and ambient intelligent systems for a librarian robot are introduced and the RFID technology based approach for these systems is described.

• Journal of Industrial Technology
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• v.29 no.B
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• pp.17-23
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• 2009

In many cases, clustering algorithms have been used for extracting and discovering useful information from non-linear data. They have made a great effect on performances of the systems dealing with non-linear data. Thus, this paper presents a new approach called hierarchically structured clustering algorithm, and it is applied to the prediction system for non-linear time series data. The proposed hierarchically structured clustering algorithm (called HCKA: Hierarchical Cross-correlation and K-means clustering Algorithms) in which the cross-correlation and k-means clustering algorithm are combined can accept the correlationship of non-linear time series as well as statistical characteristics. First, the optimal differences of data are generated, which can suitably reveal the characteristics of non-linear time series. Second, the generated differences are classified into the upper clusters for their predictors by the cross-correlation clustering algorithm, and then each classified differences are classified again into the lower fuzzy sets by the k-means clustering algorithm. As a result, the proposed method can give an efficient classification and improve the performance. Finally, we demonstrates the effectiveness of the proposed HCKA via typical time series examples.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.99-104
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• 2022

In this paper, to increase the maintenance efficiency of the urban railway train control system and to build a standard data system, we collect as much as possible structured, unstructured, and semi-structured data, and collect data by sensing and monitoring the system status and system status and monitoring. pre-process function data(Identification, purification, integration, transformation) through effective data classification and maintenance activities business classification system was studied. The purpose of this is to define the data matrix model by considering the relationship with the data generated and managed in the O&M stage of the train control system operated by the urban railway together with the WBS model, and to reflect and utilize it in practice.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.297-306
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• 2002

This paper handles the design and implementation of the system for transforming the XML document bated on XML Schema being different in syntax but similar in logic, with using structured differences analysis. In the system, the merge data is generated from the source and destination documents by utilizing data registry and structured differences analysis, and then XML document is generated from the generated merge data. The XML document transformation system is designed that transformation process to the present application system from the different application system gains advantage in the aspect of time, cost, and reliability. The implementation environment of the system is that it is run on IBM compatible PC and it is developed using the software of visual basic 6.0 with the Platform of Windows 2000.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.545-555
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• 2005

본 연구는 학습 부진아 진단 지식을 온톨로지로 표현함으로써 교사와 학생 간에 발생하는 학습 용어의 불일치성을 해소할 수 있으며 진단 과정에 있어 학습 부진아의 정보를 기반으로 한 추론을 기능하도록 한다. 또한 특정한 진단을 보여주는 일반적인 학습부진아 진단시스템과는 달리, 이러한 지식베이스를 이용하여 사용자에게 정확한 개념어(정답어)를 습득하게끔 해주고, 사용자의 인지 체계 속에 내포되어 있는 개념적 지식을 더욱 더 표면적으로 확장해 나갈 수 있는 온톨로지를 구축하는 방안을 제시한다.

• IE interfaces
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• v.6 no.1
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• pp.47-54
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• 1993

Sequential Numbering System(SNS) is one of the production and inventory management system, which is more effective and practical to minor enterprises than Material Requirement Planning (MRP) system or Just-in-Time(JIT) system. The purpose of the paper is the structured analysis of SNS as the first phase of software development. Data Flow Diagram(DFD), Data Dictionary(DD), and Mini-Specs are used to analyze the system through the second level. The result can be exploited to SNS software design and programming.

• Journal of Digital Convergence
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• v.3 no.1
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• pp.183-194
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• 2005

This study is aimed at building up an Ontology to solve the discrepancy of terminologies between teachers and students by showing, through Ontology, the knowledge for diagnosis of underachieving students. Also this study makes it possible to infer the diagnosis based on information of these underachieving students. In addition, while a general Underachieving Students diagnosis system shows special diagnosis, this Ontology system helps users obtain correct concepts through this knowledge based system, and suggest building an Ontology to extend unclear conceptual knowledge to clearer ones.

• Korean Journal of Adult Nursing
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• v.13 no.3
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• pp.476-485
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• 2001

The purpose of this study was to identify the effect of structured information provided on knowledge and self-care behavior. The subjects of this study were both hospitalized patients and outpatients in K university hospital. The instrument use for this study were the knowledge assessment tool and self-care behavior assessment tool by Eom Soon-Ja(1998) and they were modified for liver cirrhosis patients. The data were analyzed by t-test, Chi-square test, Pearson correlation coefficients using SAS program. The results of this study were as follows. The experimental group which had received structured information provided showed greater increased knowledge of liver cirrhosis(P=.001). The experimental group which had received the structured information provided indicated increased self-care performance rate, especially after information about diet(P=.001), activity and bed rest(P=.001), drug therapy and visiting the hospital(P=.001), prevention of a complication and observation(P=.001). In conclusion, structured information provided showed increased in the degree of knowledge and self-care behavior, so information showing is an effective nursing intervention. It is much needed to employ information showing for chronic patients.

• Journal of the Korean Society of Earth Science Education
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• v.5 no.1
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• pp.8-19
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• 2012

The purpose of this study is to: analyze the characteristics on ill-structured problem-solving process; examine the type of memories used in their monitoring. The data were primary collected from observation and secondary the semi-structured in-depth interviews based on analysis of observation results with two students who belong to science school and a guidance. The findings of this study revealed that the ill-structured problems possess multiple representations and the upper level's problem have several sub-problems. And multiple steps simultaneously exist in particular stage of problem-solving process that is not single sequential but complex flow and have high frequency of discussion step. Type of memories used in ill-structured problems include idiosyncratic memories which is related in personal histories such as school performance, problem-related memories, abstract rules and intuition.