• KIPS Transactions on Computer and Communication Systems
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• v.13 no.1
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• pp.10-20
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• 2024

As the online commerce market continues to expand with an increase of diverse products and content, users find it challenging in navigating and in the selection process. Thereafter both platforms and shopping malls are actively working in conducting continuous research on recommendations system to select and present products that align with user preferences. Most existing recommendation studies have relied on user data which is relatively easy to obtain. However, these studies only use a single type of event and their reliance on time dependent data results in issues with reliability and complexity. To address these challenges, this paper proposes a recommendation system that analysis user preferences in consideration of the relationship between various types of event data. The proposed recommendation system analyzes the correlation of multiple events, extracts weights, learns the recommendation model, and provides recommendation services through it. Through extensive experiments the performance of our system was compared with the previously studied algorithms. The results confirmed an improvement in both complexity and performance.

• Journal of Plant Biotechnology
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• v.5 no.3
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• pp.143-148
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• 2003

Bax, a mammalian pro-apoptotic member of the Bcl-2 family induces cell death when expressed in yeast. To investigate whether Bax expression can induce cell death in plant, we produced transgenic Arabidopsis plants that contained murine Bax cDNA under control of a glucocorticoid-inducible promoter. Transgenic plants treated with dexamethasone, a strong synthetic glucocorticoid, induced Bax accumulation and cell death, suggesting that some elements of cell death mechanism by Bax may be conserved among various organisms. Therefore, we developed novel yeast genetic system, and cloned several Plant Bax Inhibitors (PBIs). Here, we report the function of two PBIs in detail. PBI1 is ascorbate peroxidase (sAPX). Fluorescence method of dihydrorhodamine123 oxidation revealed that expression of Bax in yeast cells generated reactive oxygen species (ROS), and which was greatly reduced by co-expression with sAPX. These results suggest that sAPX inhibits the generation of ROS by Bax, which in turn suppresses Baxinduced cell death in yeast. PBI2 encodes nucleoside diphosphate kinase (NDPK). ROS stress strongly induces the expression of the NDPK2 gene in Arabidopsis thaliana (AtNDPK2). Transgenic plants overexpressing AtNDPK2 have lower levels of ROS than wildtype plants. Mutants lacking AtNDPK2 had higher levels of ROS than wildtype. $H_2O_2$ treatment induced the phosphorylation of two endogenous proteins whose molecular weights suggested they are AtMPK3 and AtMPK6. In the absence of $H_2O_2$ treatment, phosphorylation of these proteins was slightly elevated in plants overexpressing AtNDPK2 but markedly decreased in the AtNDPK2 deletion mutant. Yeast two-hybrid and in vitro protein pull-down assays revealed that AtNDPK2 specifically interacts with AtMPK3 and AtMPK6. Furthermore, AtNDPK2 also enhances the MSP phosphorylation activity of AtMPK3 in vitro. Finally, constitutive overexpression of AtNDPK2 in Arabidopsis plants conferred an enhanced tolerance to multiple environmental stresses that elicit ROS accumulation in situ. Thus, AtNDPK2 appears to playa novel regulatory role in $H_2O_2$-mediated MAPK signaling in plants.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.25 no.1
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• pp.84-103
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• 2012

Objectives : The middle school students'life style were studied with focus on Body Mass Index(BMI). Information was collected during 1st June 2009 to 10th July from 397 students(both male and female) by the subjective survey centered on personal characteristic, understanding about health in general, everyday activities, eating habits, preference in food, understanding about diet and obesity, and thoughts about fitness and diet. Methods : Students were selected from six classes by convenience sampling, then the final analysis was performed on 397 self-administered questionnaires, excepting 5 questionnaires, which have insincere answers. The data collection was carried out by SPSS(V.14.0 English Version), and the data was verified by $x^2$-test, ANOVA, multiple regression analysis. Results and Conclusion : The survey subjects were in the following distribution of body weights - underweight: 63.6%, normal weight: 29.5% and 6.9% were overweight. There was significantly different between BMI and mothers' occupation and satisfaction with school life(p<0.05). As for the analysis(multiple regression analysis) on understanding about health, the factors that affect BMI are self recognition of figure and efforts to reduce weight. In terms of efforts for one's own health, 78.2% of under weight and 82.3% of normal weight were taking active initiatives. But 85.2% of the overweight students were not giving any efforts. As for the free time activities, more than half answered, 'playing with computers'(48.4 - 66.7%, 1.57 hours on average). As for TV, on average, 2.03 hours were spent in overall. And it turned out that the overweight students spent more time watching TV by 46.49 minutes(0.77 hours) on average(p<0.05). 7.4 hours was the average sleeping time. As for the eating habit,'quantity of meal, snack, meal between meals, fat reduction, and supplementary food'were shown to be related to the BMI(p<0.05). The instant food, meat and sweet food were shown to be also related to the BMI. In terms of knowledge about overweight and diet, only 8 students(2% of the total) answered all 10 questions correct. On average, 7-8 questions were correctly answered(53.9 %). When the scores were analyzed against the BMI by classifying the scores to high, middle and low categories, it showed a relationship by different weight group(p<0.02), and the overweight students had higher score by 0.82 compared to the underweight students. When thoughts and attitude on fitness and diet were analyzed in relationship to the BMI, the result was only - "I try to eat fruits more often"(fruits)(p<0.00).

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2003.04a
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• pp.65-71
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• 2003

Bax, a mammalian pro-apoptotic member of the Bcl-2 family, induces cell death when expressed in yeast. To investigate whether Bax expression can induce cell death in plant, we produced transgenic Arabidopsis plants that contained murine Bax cDNA under control of a glucocorticoid-inducible promoter. Transgenic plants treated with dexamethasone, a strong synthetic glucocorticoid, induced Bax accumulation and cell death, suggesting that some elements of cell death mechanism by Bax may be conserved among various organisms. Therefore, we developed novel yeast genetic system, and cloned several Plant Bax Inhibitors (PBIs). Here, we report the function of two PBIs in detail. PBI1 is ascorbate peroxidase (sAPX). Fluorescence method of dihydrorho-damine 123 oxidation revealed that expression of Bax in yeast cells generated reactive oxygen species (ROS), and which was greatly reduced by co-expression with sAPX. These results suggest that sAPX inhibits the generation of ROS by Bax, which in turn suppresses Baxinduced cell death in yeast. PBI2 encodes nucleoside diphosphate kinase (NDPK). ROS stress strongly induces the expression of the NDPK2 gene in Arabidopsis thaliana (AtNDPK2). Transgenic plants overexpressing AtNDPK2 have lower levels of ROS than wildtype plants. Mutants lacking AtNDPK2 had higher levels of ROS than wildtype. $H_2O_2$ treatment induced the phosphorylation of two endogenous proteins whose molecular weights suggested they are AtMPK3 and AtMPK6. In the absence of $H_2O_2$ treatment, phosphorylation of these proteins was slightly elevated in plants overexpressing AtNDPK2 but markedly decreased in the AtNDPK2 deletion mutant. Yeast two-hybrid and in vitro protein pull-down assays revealed that AtNDPK2 specifically interacts with AtMPK3 and AtMPK6. Furthermore, AtNDPK2 also enhances the MBP phosphorylation activity of AtMPK3 in vitro. Finally, constitutive overexpression of AtNDPK2 in Arabidopsis plants conferred an enhanced tolerance to multiple environmental stresses that elicit ROS accumulation in situ. Thus, AtNDPK2 appears to play a novel regulatory role in $H_2O_2$-mediated MAPK signaling in plants.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.1-9
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• 2006

In this paper, we propose a MIMO-OFDMA (Multi Input Multi Output-Orthogonal Frequency Division Multiple Access) system based on beamforming for performance improvement of downlink real-time traffic transmission in harsh channel conditions with low CIR (Carrier-to-Interference Ratio). In the proposed system, we first consider the M-GTA-SBA (Modified-Grouped Transmit Antenna-Simple Bit Allocation) using effective CSI (Channel State Information) calculation procedure based on spatial resource grouping, which is adequate for the combination of MRT (Maximum Ratio Transmission) in the transmitter and MRC (Maximum Ratio Combining) in the receiver. In addition, to reduce feedback information for the beamforming, we also apply QEGT (Quantized Equal Gain Transmission) based on quantization of amplitudes and phases of beam weights. Furthermore, considering multi-user environments, we propose the P-SRA (Proposed-Simple Resource Allocation) algorithm for fair and efficient resource allocation. Simulation results reveal that the proposed MIMO-OFDMA system achieves significant improvement of spectral efficiency in low CRI region as compared to a typical open-loop MIMO-OFDMA system using pseudo-orthogonal space time block code and H-ARQ IR (Hybrid-Automatic Repeat Request Incremental Redundancy).

• The Journal of the Acoustical Society of Korea
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• v.22 no.1
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• pp.1-6
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• 2003

This paper analyses the performance of either the minimum variance distortionless response (MVDR) or the recursive least square (RLS) beamformer structured on the systolic array. Provided that the snapshot vector including the desired user's signal and the interferences with the noise is received at the array antenna. In order to improve the quality of received signal, MVDR or RLS algorithm can be utilized to update the beamformer weights recursively. Furthermore to increase the channel capacity, by the usage of the above schemes, the effect of the spatial filtering can be obtained which constructively combining multipath components corresponding to the desired user whereas the multiple access interferences (MAI) is nulled out on spatial domain. This paper introduces the MVDR and RLS beamformer structured on systolic array conducting the spatial filtering, and its performance under the multipath fading channel in the presence of multiple access interferences will be analyzed. To show the superior spatial filtering performances of the proposed scheme employing the systolic way structured beamformer, the computer simulations are carried out. And the validity of practical deployment of the proposed scheme will be confirmed throughout showing the BER behaviors and the beampatterns.

• Journal of KIISE
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• v.43 no.10
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• pp.1085-1093
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• 2016

Community-based Question Answering system is a system which provides answers for each question from the documents uploaded on web communities. In order to enhance the capacity of question analysis, former methods have developed specific rules suitable for a target region or have applied machine learning to partial processes. However, these methods incur an excessive cost for expanding fields or lead to cases in which system is overfitted for a specific field. This paper proposes a multiple machine learning method which automates the overall process by adapting appropriate machine learning in each procedure for efficient processing of community-based Question Answering system. This system can be divided into question analysis part and answer selection part. The question analysis part consists of the question focus extractor, which analyzes the focused phrases in questions and uses conditional random fields, and the question type classifier, which classifies topics of questions and uses support vector machine. In the answer selection part, the we trains weights that are used by the similarity estimation models through an artificial neural network. Also these are a number of cases in which the results of morphological analysis are not reliable for the data uploaded on web communities. Therefore, we suggest a method that minimizes the impact of morphological analysis by using character features in the stage of question analysis. The proposed system outperforms the former system by showing a Mean Average Precision criteria of 0.765 and R-Precision criteria of 0.872.

• Journal of Animal Science and Technology
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• v.44 no.6
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• pp.685-692
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• 2002

This study was carried out to estimate the genetic correlations for the carcass and growth traits of Hanwoo bulls measured at 12 and 18 months of age on the basis of the data form 1,823 heads of Hanwoo bulls raised at the Livestock Improvement Main Center from 1991 to 1998. Genetic correlations were estimated with multiple trait animal model using MTDFREML. The genetic correlations of the body weight at 12 months with average daily gain during 6${\sim}$12 months and with the body length were 0.76 and 0.79, respectively. The genetic correlations of the body weight at 18 months with average daily gain during 6${\sim}$18 months and with the body length were 0.86 and 0.82, respectively. The genetic correlations of the carcass weight with dressing percent, eye muscle area, backfat thickness and carcass length were 0.39, 0.37, 0.44 and 0.63, respectively. And estimate of 0.36 was obtained for the genetic correlation between backfat thickness and marbling score. The high and positive genetic correlations of 0.71 and 0.96 were estimated for the carcass weight with the body weights at 12 and 18 months. The genetic correlations of the carcass weight with body lengths at 12 and 18 months were 0.63 and 0.75, respectively. Positive genetic correlations were estimated for the dressing percentage with the body weight, average daily gain, body length, thurls width and chest girth. Low genetic correlations were estimated between eye muscle area and the growth traits ranging from -0.07 to 0.32. Dressing percentage was low correlated genetically with the growth traits except for the chest girth at 18 months. The genetic correlation between marbling score and chest girth at 18 months estimated was 0.25.

• Tuberculosis and Respiratory Diseases
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• v.41 no.5
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• pp.521-530
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• 1994

Background : The past studies on prediction formulas of pulmonary function parameters in healthy nonsmoking Korean adults have been performed in relatively small number of subjects and the reported results were restricted on a few parameters. Also there was no systematic investigation into the effect of smoking on pulmonary function parameters in smokers who have no respiratory symptoms. Therefore we attempted to establish prediction formulas of pulmonary function parameters and examined the effect of smoking on pulmonary function parameters. Methods We analyzed the result of parameters derived from the forced expiratory spirogram in 1,067 nonsmoking subjects from June in 1990 to December in 1991. They consisted of 306 males and 761 females and had neither respitatory symptoms nor history of respiratory disease. We derived prediction formulas by multiple linear regression method from their age, heights, and weights in each sex. To examine the effect of smoking on pulmonary function parameters, we classified 383 smoking men into three groups according to the past amount of smoking as follows : i.e. group of smokers who have smoked below 10 pack-years, 10-20 pack-years and above 20 pack-years. Regarding each group of past smoking as an independent dummy variable, we analyzed pulmonary function parameters including nonsmoking men as a baseline by multiple linear regression. We evaluated the smoking effect on pulmonary function parameters according to estimated p-value. Result : 1) Prediction formulas for pulmonary function parameters in each sex were derived. 2) The past smoking less than 10 pack-years does not give any effect on pulmonary function parameters. The past smoking of 10~20 pack-years showed significant negative correlation with $FEV_1$/FVC and FEF 25~75%, and the smoking above 20 pack years showed negative correlation with $FEV_1$ and $FEV_1$/FVC. Conclusion : We have got prediction formulas of pulmonary function parameters which is driven from forced expiratory spirogram in nonsmoking Korean adults by multiple linear regression from age, heights and weights of subjects. The past smoking more than 10 pack-years showed negative correlation with some pulmonary function parameters of airflow obstruction.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.