• Proceedings of the Korea Association of Information Systems Conference
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• 2002.11a
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• pp.289-312
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• 2002

This study suggests the Link weight analysis approach to choose input variables and an integrated model to make more accurate bankruptcy prediction model. the Link weight analysis approach is a method to choose input variables to analyze each input node's link weight which is the absolute value of link weight between an input nodes and a hidden layer. There are the weak-linked neurons elimination method, the strong-linked neurons selection method in the link weight analysis approach. The Integrated Model is a combined type adapting Bagging method that uses the average value of the four models, the optimal weak-linked-neurons elimination method, optimal strong-linked neurons selection method, decision-making tree model, and MDA. As a result, the methods suggested in this study - the optimal strong-linked neurons selection method, the optimal weak-linked neurons elimination method, and the integrated model - show much higher accuracy than MDA and decision making tree model. Especially the integrated model shows much higher accuracy than MDA and decision making tree model and shows slightly higher accuracy than the optimal weak-linked neurons elimination method and the optimal strong-linked neurons selection method.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.1
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• pp.119-128
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• 2017

G-induced Loss of Consciousness(G-LOC) can be predicted by measuring Electromyogram(EMG) signals. Existing studies have mainly focused on specific body parts and lacked of consideration with quantitative EMG indices. The purpose of this study is to analyze the indices of EMG signals by human body parts for monitoring G-LOC condition. The data of seven EMG features such as Root Mean Square(RMS), Integrated Absolute Value(IAV), and Mean Absolute Value(MAV) for reflecting muscle contraction and Slope Sign Changes(SSC), Waveform Length (WL), Zero Crossing(ZC), and Median Frequency(MF) for representing muscle contraction and fatigue was retrieved from high G-training on a human centrifuge simulator. A total of 19 trainees out of 47 trainees of the Korean Air Force fell into G-LOC condition during the training in attaching EMG sensor to three body parts(neck, abdomen, calf). IAV, MAV, WL, and ZC under condition after G-LOC were decreased by 17 %, 17 %, 18 %, and 4 % comparing to those under condition before G-LOC respectively. Also, RMS, IAV, MAV, and WL in neck part under condition after G-LOC were higher than those under condition before G-LOC; while, those in abdomen and calf part lower. This study suggest that measurement of IAV and WL by attaching EMG sensor to calf part may be optimal for predicting G-LOC.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.2
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• pp.248-255
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• 2009

Error is the major problem in communication system. Absolute circuit is one of the most important building blocks to implement for the error measurement in communication system as well as in analog circuit design. The main goal of this paper is to design a circuit with high accuracy and minimum error performance. In this paper, a new current mode absolute circuit is implemented to calculate the absolute value of two signals. This new design shows enhanced performance and low distortion over the previous implementation. The proposed circuit is simulated using Hspice and implemented in analog viterbi decoder. It is very suitable for implementing in error calculation for the large scale integrated circuit. Hspice simulation results of previous and new one circuit are reported.

• Journal of The Korea Institute of Healthcare Architecture
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• v.14 no.2
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• pp.15-23
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• 2008

The criterion of 'void space' in this paper is based on the sense of unusual experiences to afford the improvement of the value of cultural life with the sense of Healing. The more chances to spiritual converse with nature and oneself, the higher the value of healing experiences that one has will grow. This analysis has been done on the premises that this is derived from the inner conversation with 'nature' and 'oneself', as well as among 'others'. In other words, while the 'community void' affords programmatic aspect in relations between humans, the 'ecological void', systemic aspect in relations between human and nature, the 'meditation void', the aspect of image in relations between human and human's inside. Jong-soung Kimm and Hyo-sang Seung are Korean architects who have consistently expressed contrastive essential characteristics of the 'void space' in their contemporary works. While the void space of contemporary Korean architectures have shown various external forms, there has been a trace deeply rooted from the absolute and neutral concepts of the masters of Modern architects and 'Madang'of Korean traditional space. The integrated composition in the works of Jong-soung Kimm suggested integrated characters and healing affordances of 'Madang', but it hardly showed the poetic simplicity that could be seen from the image of traditional 'Madang'. On the other hand, the works of Hyo-sang Seung represented the simple and silent image of 'Madang', but showed fragmented characteristics that didn't sufficiently afford the integrated healing functions of 'Madang'.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.19-33
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• 2001

Link weight analysis approach is suggested as a heuristic for selection of input nodes in artificial neural network for bankruptcy prediction. That is to analyze each input node\\\\`s link weight-absolute value of link weight between an input node and a hidden node in a well-trained neural network model. Prediction accuracy of three methods in this approach, -weak-linked-neurons elimination method, strong-linked-neurons selection method and integrated link weight model-is compared with that of decision tree and multivariate discrimination analysis. In result, the methods suggested in this study show higher accuracy than decision tree and multivariate discrimination analysis. Especially an integrated model has much higher accuracy than any individual models.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.82-91
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• 2022

In this paper, time series prediction method of photovoltaic power is introduced using seasonal autoregressive integrated moving average (SARIMA). In order to obtain the best fitting model by a time series method in the absence of an environmental sensor, this research was used data below 50% of cloud cover. Three samples were extracted by time intervals from the raw data. After that, the best fitting models were derived from mean absolute percentage error (MAPE) with the minimum akaike information criterion (AIC) or beysian information criterion (BIC). They are SARIMA (1,0,0)(0,2,2)14, SARIMA (1,0,0)(0,2,2)28, SARIMA (2,0,3)(1,2,2)55. Generally parameter of model derived from BIC was lower than AIC. SARIMA (2,0,3)(1,2,2)55, unlike other models, was drawn by AIC. And the performance of models obtained by SARIMA was compared. MAPE value was affected by the seasonal period of the sample. It is estimated that long seasonal period samples include atmosphere irregularity. Consequently using 1 hour or 30 minutes interval sample is able to be helpful for prediction accuracy improvement.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.57-67
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• 2024

This paper explores the potential of electromyography (EMG) as a means of gesture recognition for user input in gesture-based interaction. EMG utilizes small electrodes within muscles to detect and interpret user movements, presenting a viable input method. To classify user gestures based on EMG data, machine learning techniques are employed, necessitating the preprocessing of raw EMG data to extract relevant features. EMG characteristics can be expressed through formulas such as Integrated EMG (IEMG), Mean Absolute Value (MAV), Simple Square Integral (SSI), Variance (VAR), and Root Mean Square (RMS). Additionally, determining the suitable time for gesture classification is crucial, considering the perceptual, cognitive, and response times required for user input. To address this, segment sizes ranging from a minimum of 100ms to a maximum of 1,000ms are varied, and feature extraction is performed to identify the optimal segment size for gesture classification. Notably, data learning employs overlapped segmentation to reduce the interval between data points, thereby increasing the quantity of training data. Using this approach, the paper employs four machine learning models (KNN, SVC, RF, XGBoost) to train and evaluate the system, achieving accuracy rates exceeding 96% for all models in real-time gesture input scenarios with a maximum segment size of 200ms.

• Research in Community and Public Health Nursing
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• v.7 no.1
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• pp.38-51
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• 1996

There is a increasingly growing emphasis on health promotion, disease prevention and optimum functioning for peaple including the chronically ill and disabled. According as the purpose of the nursing is the promotion of health, the value and belief of heal th within the nursing paradigm need to be defined in every culture. The paradigm components must be explored for meaning given by the aged in their traditional thought and philosophy, The problem addressed by this qualitative study was how the aged recognize value and belief of health, which contribute to the development of Korean nursing theory. Theoretical support for the study was from Leininger's cultural care theory and Korean philosophy and traditional oriented thought. Literature review refers to literature on the aged, health of the aged, and definition and meaning of general health concept. Grounded theory methodology guied the research methodology and analysis to build a substantive theory. The informants were 119 from a variety of social levels and family patterns; traditionally the aged are responsible for the health. The concentrated interviewing period was from may to june, 1995 ; the interviews were done by the researcher with two supporter and most were recorded on audio tape. Result from analysis of base datas follows; The value and belief of health that emerged from the categories and properties were the physical stability, the stability of mind, the stability of mind and body, the smoothness (harmony) of body function, the family concord, and the perfection of self. These values and beliefs of health are affected by the cosmic dual forces thought is based on the Great Absolute, family principle of confucian scholar, and Buddism. Among the values and beliefs of health, family concord is found out Korean culture peculiarities. These values and beliefs are all integrated into the idea of health. The study provided implications for nursing theory research, education, and practice change and development.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.3
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• pp.235-240
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• 1996

Forecasts of monthly landings of walleye pollock, Theragra chalcogramma, in Korea were carried out by the seasonal Autoregressive Integrated Moving Average(ARlMA) model. The Box - Cox transformation on the walleye pollock catch data handles nonstationary variance. The equation of Box - Cox transformation was Y'=($Y^0.31$_ 1)/0.31. The model identification was determined by minimum AIC(Akaike Information Criteria). And the seasonal ARlMA model is presented (1- O.583B)(1- $B^1$)(l- $B^12$)$Z_t$ =(l- O.912B)(1- O.732$B^12$)et where: $Z_t$=value at month t ; $B^p$ is a backward shift operator, that is, $B^p$$Z_t$=$Z_t$-P; and et= error term at month t, which is to forecast 24 months ahead the walleye pollock landings in Korea. Monthly forecasts of the walleye pollock landings for 1993~ 1994, which were compared with the actual landings, had an absolute percentage error(APE) range of 20.2-226.1 %. Thtal observed annual landings in 1993 and 1994 were 16, 61OM/T and 1O, 748M/T respectively, while the model predicted 10, 7 48M/T and 8, 203M/T(APE 37.0% and 23.7%, respectively).

• Smart Media Journal
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• v.11 no.5
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• pp.38-47
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• 2022

Honey is one of the most significant ingredients in conventional food production in different regions of the world. Honey is commonly used as an ingredient in ethnic food. Beekeeping is performed in various locations as part of the local food culture and an occupation related to pollinator production. It is important to conduct beekeeping so that it generates food culture and helps regulate the regional environment in an integrated manner in preserving and improving local food culture. This study analyzes different types of environmental factors of a smart bee farm. The major goal of this study is to determine the best prediction model between the linear regression model (LM) and the support vector regression model (SVR) based on the environmental factors of a smart bee farm. The performance of prediction models is measured by R² value, root mean squared error (RMSE), and mean absolute error (MAE). From all analysis reports, the best prediction model is the support vector regression model (SVR) with a low coefficient of variation, and the R² values for Farm inside temperature, bee box inside temperature, and Farm inside humidity are 0.97, 0.96, and 0.44.