• Journal of the Korean Statistical Society
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• v.14 no.1
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• pp.29-38
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• 1985

Cyclic Factorial Association Scheme (CFAS) for incomplete block designs in a factorial experiment is defined. It is a generalization of EGD/($2^n-1$)-PBIB designs defined by Hinkelmann (1964) or Binary Number Association Scheme (BNAS) named by Paik and Federer (1973). A property of PBIB designs having CFAS is investigated and it is shown that the structural matrix NN' of such designs has a pattern of multi-nested block circulant matrix. The generalized inverse of (rI-NN'/k) is obtained. Generalized Cyclic incomplete block designs for factorial experiments introduced by John (1973) are presented as the examples of CFAS-PBIB designs. Finally, the relationship between CFAS and BNAS in block designs is briefly discussed.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.37-46
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• 2015

The wireless electrocardiographic monitoring system(WDMS) is designed to be long term monitoring for the early detection of cardiac disorders. The current version of the WDMS can identify two types of cardiac rhythms in real-time, such as atrial fibrillation(AF) and normal sinus rhythm(NSR), which are very important to track cardiac-rhythm disorders. In this study, we proposed the analysis method to discriminate the characteristics statistically evaluated in both time and frequency domains between AF and NSR using various parameters in the heart rate variability(HRV). And we applied various ECG detection methods (e.g., difference operation method) and compared the results with those of the discrete wavelet transform(DWT) method. From the statistically results, we found that the parameters such as STD RR, STD HR, RMSSD, NN50, pNN50, RR Trian, and TNN(p<0.05) are significantly different between the AF and NSR patients in time domain. On the other hand, the frequency domain analysis results showed a significant difference in VLF power($ms^2$), LF power($ms^2$), HF power($ms^2$), VLF(%), LF(%), and HF(%). In particular, the parameters such as STD RR, RMSSD, NN50, pNN50, VLF power, LF power and HF power were considered as the most useful parameters in both AF and NSR patient groups. Our proposed method can be efficiently applied to early detection of abnormal conditions and prevent the such abnormals from becoming serious.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.639-650
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• 2008

Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (i) a heuristic technique, (ii) a simulation model used by Ontario's Independent Electricity System Operator (IESO), (iii) a Multiple Linear Regression (MLR) model, (iv) NN model, (v) Auto Regressive Integrated Moving Average (ARIMA) model, (vi) Dynamic Regression (DR) model, and (vii) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.

• Journal of Society of Preventive Korean Medicine
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• v.14 no.2
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• pp.105-120
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• 2010

Objectives : This study aims to evaluate the effects of expiration-to-inspiration time ratio (E/I-ratio) on heart rate, which represents cardiac autonomic function, and cold-heat in the healthy people. Methods : 49 healthy young volunteers(male : female = 32 : 17) were recruited in the study. The participants completed the questionnaire for yin-yang pattern identification and then we measured the chest plethysmogram for respiration signal and the electrocardiogram for NN intervals during different E/I-ratio from 1 to 2. We compared heart rate variability including RMS-SD, VLF, LF and HF, and the trend-cycle factors decomposed from NN interval data by time series analysis among the respective E/I-ratio. We also confirmed the difference on the trend-cycle factors according to the score of the questionnaire for cold and heat pattern identification. Results : There were differences on the trend-cycle factors from NN interval data, but no significant difference on heart rate variability, among the respective E/I-ratio. We also found significant relationship between the trend-cycle factors and the heat pattern identification scores. Conclusions : The results indicate that cardiac autonomic function can be modulated by the E/I-ratio and the modulation will be slower and more tendencious than respiratory sinus arrhythmia.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.448-453
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• 2008

This study describes design and development techniques of estimation models for process modeling. One case study is undertaken to design a model using standard gas furnace data. Neural networks (NN) and genetic programming (GP) are each employed to model the crucial relationships between input factors and output responses. In the case study, two models were generated by using 70% training data and evaluated by using 30% testing data for genetic programming and neural network modeling. The model performance was compared by using RMSE values, which were calculated based on the model outputs. The average RMSE for training and testing were 0.8925 (training) and 0.9951 (testing) for the NN model, and 0.707227 (training) and 0.673150 (testing) for the GP model, respectively. As concern the results, the NN model has a strong advantage in model training (using the all data for training), and the GP model appears to have an advantage in model testing (using the separated data for training and testing). The performance reproducibility of the GP model is good, so this approach appears suitable for modeling physical fabrication processes.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1483-1495
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• 2007

Thanks to IEEE 802.11 technique, accessing Internet through a wireless LAN(Local Area Network) is possible in the most of the places including university campuses, shopping malls, offices, hospitals, stations, and so on. Most of the APs(access points) for wireless LAN are supporting 2.4 GHz band 802.11b and 802.11g protocols. This paper is introducing a C# library function which can be used to read RSSIs(Received Signal Strength Indicator) from APs. An LBS(Location Based Service) estimates the current location of the user and provides useful user's location-based services such as navigation, points of interest, and so on. Therefore, indoor, LBS is very desirable. However, an indoor LBS cannot be realized unless indoor position ing is possible. For indoor positioning, techniques of using infrared, ultrasound, signal strength of UDP packet have been proposed. One of the disadvantages of these techniques is that they require special equipments dedicated for positioning. On the other hand, wireless LAN-based indoor positioning does not require any special equipments and more economical. A wireless LAN-based positioning cannot be realized without reading RSSIs from APs. Therefore, our C# library function will be widely used in the field of indoor positioning. In addition to providing a C# library function of reading RSSI, this paper introduces implementation of indoor positioning modules making use of the library function. The methods used in the implementation are K-NN(K Nearest Neighbors), Bayesian and trilateration. K-NN and Bayesian are kind of fingerprinting method. A fingerprint method consists of off-line phase and realtime phase. The process time of realtime phase must be fast. This paper proposes a decision tree method in order to improve the process time of realtime phase. Experimental results of comparing performances of these methods are also discussed.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.127-132
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• 2006

K-NN (k-Nearest Neighbors), which is a well-known instance-based learning algorithm, simply stores entire training patterns in memory, and uses a distance function to classify a test pattern. K-NN is proven to show satisfactory performance, but it is notorious formemory usage and lengthy computation. Various studies have been found in the literature in order to minimize memory usage and computation time, and NGE (Nested Generalized Exemplar) theory is one of them. In this paper, we propose RPA (Recursive Partition Averaging) and IRPA (Incremental RPA) which is an incremental version of RPA. RPA partitions the entire pattern space recursively, and generates representatives from each partition. Also, due to the fact that RPA is prone to produce excessive number of partitions as the number of features in a pattern increases, we present IRPA which reduces the number of representative patterns by processing the training set in an incremental manner. Our proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory.

• The korean journal of orthodontics
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• v.27 no.4 s.63
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• pp.585-597
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• 1997

The purpose of this study was to evaluate the effect of estrogen on the periodontium and alveolar bone tissue response during experimental tooth movement in ovariectomized rats. Eighty female rats, 250gm in body weight, were classified into four groups ; sham operated group(NN), ovariectomized group(ON), ovariectomized & estrogen injected group(OE), sham operated & estrogen injected group(NE). flats were ovariectomized before 3 weeks to begin the experiment, which resulted in estrogen-deficient osteoporosis. In OE group & NE group, estrogen was injected $50{\mu}g/kg\;B.W.$ every other days. The left maxillary 1st molar was moved mesially with 60g force. Each foot rats were sacrificed after 1, 3, 7, 15 days from application of orthodontic appliance and alter additional 7 days from removal of orthodontic appliance. Histological findings on mesial roots of upper 1st molar in pressure and tension side are observed. The results were summarized as follows ; 1. In pressure side of alveolar bone, the number of osteoclasts and Howship's lacuna of ON group was significantly more than that of NN group from 1 day to 15 days(P<0.05). Especially the number of Howship's lacuna of ON group was significantly more than that of OE group during all experimental period(P<0.05). 2. In tension side of alveolar tune, the number of osteoclasts of ON group was significantly increased from 1 day to 3 days and decreased after 7 days. But the number of osteoclast of ON group was significantly mote than that of NN group during all experimental period(P<0.05). Also the number of Howship's lacuna of all groups was abruptly increased at 1 day, but slowly decreased till experimental 15 days. And the number of Howship's lacuna of of group was significantly more than that of NN group from 0 hr to 7 days(P<0.05). 3. The speed of tooth movement of OE group & NE group was similar to that of NN group(P>0.05). The amount of tooth movement of ON group between 7 days and 15 days was significantly greater than those of other groups(P<0.05). 4. The degree of relapse of ON group after 7 days from removal of orthodontic appliance was similar to those of other groups(P>0.05).

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.3
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• pp.27-38
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• 2000

This paper proposes how the recurrent neural network controller for a Khepera mobile robot with an obstacle avoiding ability can be determined by co-adaptation of the evolution and learning, The proposed co-adaptation scheme consists of two folds： a population of NN controllers are evolved by the genetic algorithm so that the degree of obstacle avoidance might be reduced through the global searching and each NN controller is trained by CRBP learning so that the running behavior is adapted to its outer environment through the local searching. Experimental results shows that the NN controller coadapted by evolution and learning outperforms its non-learning equivalent evolved by only genetic algorithm in both the ability of obstacle avoidance and the convergence speed reaching to the required running behavior.

• Preventive Nutrition and Food Science
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• v.20 no.3
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• pp.198-203
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• 2015

The present study was conducted to assess the status of vitamin C among healthy young adults in relation to serum antioxidant parameters [glutathione (GSH), thiols, and total antioxidant capacity, (TAC)], and oxidative stress markers [malondialdehyde (MDA), and nitrites plus nitrates (NN)]. A prospective study included 200 young adults, and their dietary intake was assessed by using food diaries. Fasting plasma vitamin C, serum levels of GSH, thiols, TAC, MDA, and NN were measured using biochemical assays. It was observed that 38% of the enrolled subjects, n=76, had an adequate dietary intake of vitamin C (ADI group). Meanwhile, 62%, n=124, had a low dietary intake of vitamin C (LDI group) as compared to the recommended dietary allowances. The fasting plasma level of vitamin C was significantly higher in the ADI group as compared to the LDI group. Oxidative stress in the sera of the LDI group was evidenced by depletion of GSH, low thiols levels, impairment of TAC, an elevation of MDA, and increased NN. In the ADI group, positive correlations were found between plasma vitamin C and serum antioxidant parameters (GSH, thiols, and TAC). Meanwhile, the plasma vitamin C was negatively correlated with serum MDA and NN levels. This study reveals a significant increase of oxidative stress status and reduced antioxidant capacity in sera from healthy young adults with low intake of the dietary antioxidant, vitamin C.