• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.125-130
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• 1998

One of the most urgent problems facing 21 century might seem to be a preparation for an advanced education against an information society and have relation to a new information supporting system in teaching as well as leaning. Nevertheless, our educational circumstances have a lot of problems because an effective information supporting contents for teaching and leaning is insufficient. Especially, we've never been making every effort to develope educational contents providing students with a type of information and knowledge database even though the education which come into use internet has been raising a social issue. Therefore, we propose a model of learning contents for supporting www based distance learning system.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.132-140
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• 2020

It is very important to use appropriate nutrition water for crop growth in hydroponic farming facilities. However, in many cases, the supply of nutrition water is not designed with a precise plan, but is performed in a conventional manner. We proposes a forecasting technique for nutrition water requirements based on a data analysis for optimal strawberry production. To do this, the proposed forecasting technique uses linear regression for correlating strawberry production, soil condition, and environmental parameters with nutrition water demand for the actual two-stage strawberry production soil. Also, it includes predicting the optimal amount of nutrition water requires according to the heterogeneous cultivation environment and variety by comparing the amount of nutrition water needed for the growth and production of different kinds of strawberries. We suggested study uses two types of section beds that are compared to find out the best section bed production of strawberry growth. The dataset includes 233 samples collected from a real strawberry greenhouse, and the four predicted variables consist of the total amounts of nutrition water, average temperature, humidity, and CO₂ in the greenhouse.

• ETRI Journal
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• v.34 no.5
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• pp.743-752
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• 2012

Semantic interpretation of the relationship between noun compound (NC) elements has been a challenging issue due to the lack of contextual information, the unbounded number of combinations, and the absence of a universally accepted system for the categorization. The current models require a huge corpus of data to extract contextual information, which limits their usage in many situations. In this paper, a new semantic relations interpreter for NCs based on novel lightweight binary features is proposed. Some of the binary features used are novel. In addition, the interpreter uses a new feature selection method. By developing these new features and techniques, the proposed method removes the need for any huge corpuses. Implementing this method using a modular and plugin-based framework, and by training it using the largest and the most current fine-grained data set, shows that the accuracy is better than that of previously reported upon methods that utilize large corpuses. This improvement in accuracy and the provision of superior efficiency is achieved not only by improving the old features with such techniques as semantic scattering and sense collocation, but also by using various novel features and classifier max entropy. That the accuracy of the max entropy classifier is higher compared to that of other classifiers, such as a support vector machine, a Na$\ddot{i}$ve Bayes, and a decision tree, is also shown.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.11
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• pp.25-29
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• 1991

In the field of prosthesis arm control, tile pattern classification of the EMG signal is a required basis process and also the estimation of force from col looted EMG data is another necessary duty. But unfortunately, what we've got is not real force but an EMG signal which contains the information of force. This is the reason why he estimate the force from the EMG data. In this paper, when we handle the EMG signal to estimate the force, spatial prewhitening process is applied from which the spatial correlation between the channels are removed. And after the orthogonal transformation, which is used in the force estimation process the transformed signal is inputed into the probabilistic model for pattern classification. To verify the different results of the multiple channels, SNR(signal to noire ratio) function is introduced.

• Nuclear Engineering and Technology
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• v.45 no.1
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• pp.21-28
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• 2013

The flow and heat transfer characteristics of the ex-vessel core melt (corium) were investigated using a commercial CFD code along with the experimental data on the spreading of corium available in the literature (VULCANO VE-U7 test). In the numerical simulation of the unsteady two-phase flow, the volume-of-fluid model was applied for the spreading and interfacial surface formation of corium with the surrounding air. The effects of the key parameters were evaluated for the corium spreading, including the radiation, decay heat, temperature-dependent viscosity and initial temperature of corium. The results showed a reasonable trend of corium progression influenced by the changes in the radiation, decay heat, temperature-dependent viscosity and initial temperature of corium. The modeling of the viscosity appropriate for corium and the radiative heat transfer was critical, since the front progression and temperature profiles were strongly dependent on the models. Further development is required for the code to consider the formation of crust on the surfaces of corium and the interaction with the substrate.

• Journal of the Korean Institute of Telematics and Electronics
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• v.10 no.1
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• pp.9-17
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• 1973

This paper dealt with composition of current stable negatil'e resistance circuit based on Beam resistance of the tube SAMUEL SEBLY suggested. Beam resistance which is decreased by input current increment on definite region of current, accompanied generation of equivalent e. m. f on model circuit. With equivalent e. m. f there appeared increased current on circuit but decrease of terminal voltage. Bloc constructed by above concept induced transistorized circuit which have NPN and a PNP Transistor. Circuit operation predicted and calculated values of negative resistance are coincident with experimental results. A Circuit proposed on this paper sllowed good linearity on Ve-Ji characteristics.

• Journal of Navigation and Port Research
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• v.31 no.4
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• pp.281-287
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• 2007

Human factors have been considered the primary reason of marine accidents. Especially, the collision between vessels is mostly mused by human behavior. However, there have not been many researches to clarify the reason of marine accidents mused by human factors quantitatively. In order to understand human factors and to enhance safe navigation systematically, using a full mission ship-handling simulator, we've investigated the characteristics of avoiding behavior taken by mariners. Further in order to apply the characteristics more widely and effectively, it's necessary to formulate the standard behavior for ship-handling in the condition of collision avoidance. Is this study, therefore, we intended to propose the concept to model the mariner's standard behavior on the handling of collision avoidance as the first step. As a result, we confirmed the contents of information processing in ship-handling that mariner's generally taking to avoid collision.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.585-588
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• 2019

Predictions of Energy Consumption for Industries gain an important place in energy management and control system, as there are dynamic and seasonal changes in the demand and supply of energy. This paper presents and discusses the predictive models for energy consumption of the steel industry. Data used includes lagging and leading current reactive power, lagging and leading current power factor, carbon dioxide (tCO2) emission and load type. In the test set, four statistical models are trained and evaluated: (a) Linear regression (LR), (b) Support Vector Machine with radial kernel (SVM RBF), (c) Gradient Boosting Machine (GBM), (d) random forest (RF). Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used to measure the prediction efficiency of regression designs. When using all the predictors, the best model RF can provide RMSE value 7.33 in the test set.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.97-115
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• 2023

In South Korea, chronic kidney disease(CKD) impacts around 4.6 million adults, leading to a high reliance on hemodialysis. For effective dialysis, vascular access is crucial, with decisions about vascular surgeries often made during dialysis sessions. Anticipating these needs could improve dialysis quality and patient comfort. This study investigates the use of Artificial Intelligence(AI) to predict the timing of surgeries for dialysis vessels, an area not extensively researched. We've developed an AI algorithm using predictive maintenance methods, transitioning from machine learning to a more advanced deep learning approach with Long Short-Term Memory(LSTM) models. The algorithm processes variables such as venous pressure, blood flow, and patient age, demonstrating high effectiveness with metrics exceeding 0.91. By shortening the data collection intervals, a more refined model can be obtained. Implementing this AI in clinical practice could notably enhance patient experience and the quality of medical services in dialysis, marking a significant advancement in the treatment of CKD.

• Journal of Periodontal and Implant Science
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• v.47 no.5
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• pp.292-311
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• 2017

Purpose: Beyond the limited scope of non-specific polyclonal regulatory T cell (Treg)-based immunotherapy, which depends largely on serendipity, the present study explored a target Treg subset appropriate for the delivery of a novel epitope spreader Pep19 antigen as part of a sophisticated form of immunotherapy with defined antigen specificity that induces immune tolerance. Methods: Human polyclonal $CD4^+CD25^+CD127^{lo-}$ Tregs (127-Tregs) and $na\ddot{i}ve$ $CD4^+CD25^+CD45RA^+$ Tregs (45RA-Tregs) were isolated and were stimulated with target peptide 19 (Pep19)-pulsed dendritic cells in a tolerogenic milieu followed by ex vivo expansion. Low-dose interleukin-2 (IL-2) and rapamycin were added to selectively exclude the outgrowth of contaminating effector T cells (Teffs). The following parameters were investigated in the expanded antigen-specific Tregs: the distinct expression of the immunosuppressive Treg marker Foxp3, epigenetic stability (demethylation in the Treg-specific demethylated region), the suppression of Teffs, expression of the homing receptors CD62L/CCR7, and CD95L-mediated apoptosis. The expanded Tregs were adoptively transferred into an $NOD/scid/IL-2R{\gamma}^{-/-}$ mouse model of collagen-induced arthritis. Results: Epitope-spreader Pep19 targeting by 45RA-Tregs led to an outstanding in vitro suppressive T cell fate characterized by robust ex vivo expansion, the salient expression of Foxp3, high epigenetic stability, enhanced T cell suppression, modest expression of CD62L/CCR7, and higher resistance to CD95L-mediated apoptosis. After adoptive transfer, the distinct fate of these T cells demonstrated a potent in vivo immunotherapeutic capability, as indicated by the complete elimination of footpad swelling, prolonged survival, minimal histopathological changes, and preferential localization of $CD4^+CD25^+$ Tregs at the articular joints in a mechanistic and orchestrated way. Conclusions: We propose human $na\ddot{i}ve$ $CD4^+CD25^+CD45RA^+$ Tregs and the epitope spreader Pep19 as cellular and molecular targets for a novel antigen-specific Treg-based vaccination against collagen-induced arthritis.