• Korean Journal of Cognitive Science
• /
• v.27 no.1
• /
• pp.1-25
• /
• 2016

The present study investigated the effect size of attention and consciousness on change detection. We confirmed the effect size of consciousness by comparing the condition which combined attention and consciousness and the condition of attention without consciousness. Then, we confirmed the effect size of attention by comparing the condition of attention without consciousness and the control condition which excluded attention and consciousness. For this purpose, change detection task and continuous flash suppression (CFS) were used. CFS renders a highly visible image invisible. In CFS, one eye is presented with a static stimulus, while the other eye is presented with a series of rapidly changing stimuli, such as mondrian patterns. The result is that the static stimulus becomes suppressed from conscious awareness by the stimuli presented in the other eye. We used a customized device with smartphone and google cardboard instead of stereoscope to trigger CFS. In Experiment 1-1, we reenacted some study to validate our experimental setup. Our experimental setup produced the duration of stimulus suppression that were similar to those of preceding research. In Experiment 1-2, we reenacted a study for attention without consciousness using an customized device. The results showed that attention without consciousness more strongly work as a cue. We think that it is reasonable to use CFS treatment employing smartphone and google cardboard for a follow-up study. In Experiment 2, when performing the change detection task, we measured the effect size of consciousness and attention by manipulating the consciousness level of cue. We used the method in which everything but the variable of interest kept being fixed. That way, the difference this independent variable makes to the action of the entire system can be isolated. We found that there was significant difference of correct response rate on change detection performance among different consciousness level of cue. In this study, we investigated that not only the role of attention and consciousness were different also we were able to estimated the effect size.

• The Journal of Korean Society for Radiation Therapy
• /
• v.23 no.2
• /
• pp.97-102
• /
• 2011

Purpose: IMRT QA using 2Dimensional array detector is carried out with condition for discrete dose distribution clinically. And it can affect uncertainty of evaluation using gamma method. We analyze gamma index variation according to grid size and suggest validate range of grid size for IMRT QA in Hospital. Materials and Methods: We performed QA using OniPro I'mRT system software version 1.7b on 10 patients (head and neck) for IMRT. The reference dose plane (grid size, 0.1 cm; location, [0, 0, 0]) from RTP was compared with the dose plane that has different grid size (0.1 cm, 0.5 cm, 1.0 cm, 2.0 cm, 4.0 cm) and different location (along Y-axis 0 cm, 0.2 cm, 0.5 cm, 1.0 cm). The gamma index variation was evaluated by observing the level of changes in Gamma pass rate, Average signal, Standard deviation for each case. Results: The average signal for each grid size showed difference levels of 0%, -0.19%, -0.04%, -0.46%, -8.32% and the standard deviation for each grid size showed difference levels of 0%, -0.30%, 1.24%, -0.70%, -7.99%. The gamma pass rate for each grid size showed difference levels of 0%, 0.27%, -1.43%, 5.32%, 5.60%. The gamma evaluation results according to distance in grid size range of 0.1 cm to 1.0 cm showed good agreement with reference condition (grid size 0.1 cm) within 1.5% and over 5% in case of the grid size was greater than 2.0 cm. Conclusion: We recognize that the grid size of gamma evaluation can make errors of IMRT QA. So we have to consider uncertainty of gamma evaluation according to the grid size and apply smaller than 2 cm grid size to reduce error and increase accuracy clinically.

• Journal of Nutrition and Health
• /
• v.44 no.2
• /
• pp.171-180
• /
• 2011

Assessing human exposure to food-borne hazards requires standardized assessment tools. The objective of this study was to validate a newly developed dietary assessment questionnaire to assess human exposure to food-borne hazards, which include dietary behavior and food consumption patterns such as eating frequency, types of food containers and cooking methods. A total of 216 adults were recruited for two questionnaire surveys (questionnaire 1 and 2) about 1 week apart with a 3 day diet record. Reproducibility was evaluated by comparing responses from questionnaires 1 and 2, and validity was checked by comparing responses from questionnaire 2 and the 3 day diet record. Comparisons were based on the percent agreement and Spearman's rank correlation coefficient. The mean exact agreement of food containers at purchase between questionnaires 1 and 2 was 73.5%, for storing containers it was 71.9%, and for cooking methods it was 83.0%. The mean correlation coefficient for food intake frequency between questionnaires 1 and 2 was 0.71 (range, 0.50-0.83). The mean correlation coefficient of the food intake frequency between questionnaire 2 and the 3 day diet record was 0.21 (range, 0.04-0.48). The exact and adjacent agreement of food intake frequency quartile assessed by questionnaire 2 and the 3 day diet record was 65.4% (range, 51.0-82.1%). Although the correlation coefficient for food intake frequency between questionnaire 2 and the 3 day diet record was low, the exact and adjacent food intake frequency agreement was higher than 50% and reproducibility of the dietary behaviors exceeded 70%. Therefore, the questionnaire developed in this study could be applied to assess diets for the human exposure to food-borne hazards as a qualitative assessment in a large population.

• Journal of Nutrition and Health
• /
• v.53 no.5
• /
• pp.476-487
• /
• 2020

Purpose: This study evaluated the accuracy of the 24-hour diet recall method for estimating energy intakes in elderly women using the doubly labeled water (DLW) method. Methods: The subjects were 23 elderly women with a mean age of 70.3 ± 3.3 years and body mass index (BMI) of 23.9 ± 2.8 kg/㎡. The total energy expenditure (TEE_DLW) was determined by using the DLW and used to validate the 24-hour diet recall method. The total energy intake (TEI) was calculated from the 24-hour diet recall method for three days. Results: TEI (1,489.6 ± 211.1 kcal/day) was significantly lower than TEE_DLW (2,023.5 ± 234.9 kcal/day) and was largely under-reported by -533.9 ± 228.0 kcal/day (-25.9%). The accurate prediction rate of elderly women in this study was 8.7%. The Bland-Altman plot, which was used to evaluate the TEI and the TEE_DLW, showed that the agreement between them was negatively skewed, ranging from -980.8 kcal/day to -86.9 kcal/day. Conclusion: This study showed that the energy intake of elderly women was underreported. Strategies to increase the accuracy of the 24-hour diet recall methods in the elderly women should be studied through analysis of factors that affect underreporting rate. Further studies will be needed to assess the validity of the 24-hour diet recall method in other population groups.

• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.1-18
• /
• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.157-173
• /
• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.40 no.5
• /
• pp.148-159
• /
• 2012

The purpose of this study is to validate the effect of improvement such measures as fence installation or planting of bush and herbaceous plants taken from Pinus densiflora forest in Solbat Neighborhood Park in Seoul, which was damaged by stamping. The study was conducted in 2005 and 2010 in order to analyze changes in planting types, planting structure of Pinus densiflora forest, soil hardness, cross-sectional structure of soil, and physicochemical characteristics of soil. It was also measured by the growth of the branches and the diameter of Pinus densiflora, comparing before and after the improvement to study the effect of restoring Pinus densiflora forest damaged by stamping. When it comes to a change in planting type, Pinus densiflora forest without underlay was reduced from 48.5% in 2005 to 6.8% in 2010. Pinus densiflora forest with bush and herbaceous plants was increased dramatically from 7.4% to 46.8%. Regarding planting structure, in most area of the subject site, Pinus densiflora forest without under layer was transformed into the one with bush and herbaceous plants including Rhododendron mucronulatum, Rhododendron schippenbachii, Hemerocallis fulva, Aceriphyllum rossii, Hosta plantaginea growing in a wide area. The soil in the Solbat Neighborhood Park was very stiff with soil hardness of $54.8kg/cm^2$ in average. After the improvement efforts made in the Park in 2010, the soil hardness was mostly less than $4kg/cm^2$, being in a good condition with little influence on the growth of plants. When it comes to the cross-sectional structure of soil, litter layer didn't exist in 2005 because of stamping and the organic matter layer was only 1.0cm thick, which provided an unfavorable condition for plant growth. However, after improvement, litter layer was formed up to 3.0cm and thickness of the organic matter layer also went up to 1.5~8.0cm in 2010 because the damage from stamping was reduced. Concerning the physicochemical characteristic of soil, in 2005 soil showed pH 5.76~6.70, organic matter content 7.15~10.55%, and available phosphorus 9.38~26.47mg/kg, having no big problems as a soil environment for growth of Pinus densiflora. 15 trees of Pinus densiflora were selected to see branch growth and it was found that the branches tended to grow better after improvement. 70 trees of Pinus densiflora from various grades of soil hardness also were selected to identify changes of diameter growth. In most cases, it was analyzed that Pinus densiflora grew better after improvement. After conducting this study, it was validated that such measures as fence installation or planting of bush and herbaceous plants to restore Pinus densiflora Forest damaged by stamping were effective in improving growth of Pinus densiflora.

• The Korean Journal of Pesticide Science
• /
• v.20 no.2
• /
• pp.93-103
• /
• 2016

A simultaneous analytical method was developed for the determination of isoxaflutole and metabolite (diketonitrile) in agricultural commodities. Samples were extracted with 0.1% acetic acid in water/acetonitrile (2/8, v/v) and partitioned with dichloromethane to remove the interference obtained from sample extracts, adjusting pH to 2 by 1 N hydrochloric acid. The analytes were quantified and confirmed via liquid chromatograph-tandem mass spectrometer (LC-MS/MS) in positive-ion mode using multiple reaction monitoring (MRM). Matrix matched calibration curves were linear over the calibration ranges ($0.02-2.0{\mu}g/mL$) for all the analytes into blank extract with $r^2$ > 0.997. For validation purposes, recovery studies were carried out at three different concentration levels (LOQ, 10LOQ, and 50LOQ) performing five replicates at each level. The recoveries were ranged between 72.9 to 107.3%, with relative standard deviations (RSDs) less than 10% for all analytes. All values were consistent with the criteria ranges requested in the Codex guideline (CAC/GL40, 2003). Furthermore, inter-laboratory study was conducted to validate the method. The proposed analytical method was accurate, effective, and sensitive for isoxaflutole and diketonitrile determination in agricultural commodities.

• Radiation Oncology Journal
• /
• v.21 no.4
• /
• pp.291-298
• /
• 2003

Purpose: We report upon a web-based system for Patterns of Care Study (PCS) devised for Korean radiation oncology. This PCS was designed to establish standard tools for clinical quality assurance, to determine basic parameters for radiation oncology processes, to offer a solid system for cooperative clinical studies and a useful standard database for comparisons with other national databases. Materials and Methods: The system consisted of a main server with two back-ups in other locations. The program uses a Linux operating system and a MySQL database. Cancers with high frequencies in radiotherapy departments in Korea from 1998 to 1999 were chosen to have a developmental priority. Results: The web-based clinical PCS .system for radiotherapy in www.pcs.re.kr was developed in early 2003 for cancers of the breast, rectum, esophagus, larynx and lung, and for brain metastasis. The total number of PCS study items exceeded one thousand. Our PCS system features user-friendliness, double entry checking, data security, encryption, hard disc mirroring, double back-up, and statistical analysis. Alphanumeric data can be input as well as image data. In addition, programs were constructed for IRB submission, random sampling of data, and departmental structure. Conclusion: For the first time in the field of PCS, we have developed a web-based system and associated working programs. With this system, we can gather sample data in a short period and thus save, cost, effort and time. Data audits should be peformed to validate input data. We propose that this system should be considered as a standard method for PCS or similar types of data collection systems.

• Journal of Global Scholars of Marketing Science
• /
• v.17 no.4
• /
• pp.1-22
• /
• 2007

Customer satisfaction is important in an increasingly competitive and global marketplace. This implies that customer service is a critical factor for many organizations. In service encounter context, customer satisfaction is affected by employees' attitudes and behaviors. Accordingly, service firms have been focusing on selecting high quality of service employees, which resulted the ability to identify and select quality service- or customer- oriented employees to become critical for an organization's success. It was suggested that customer service orientation links to performance and subsequent organizational revenue. Moreover, it was found that service encounter failures were among the major reasons for customers' service switch. Therefore, the selection of customer service oriented employees is a key factor in establishing customer service - a potential source of sustained competitive advantage. However, the measurement of employee service orientation is more confusing than that of definitive answers. The difficulty of measuring service orientation is attributed to the use of broad versus narrow measures of personality. Advocates for the broad perspective prefer using basic personality constructs, such as the Big Five personality traits. On the contrary, the latter prefer a construct-oriented approach of personality research that provides a better measure of job performance because it requires the specification of the relationship of the personality traits with multiple dimensions of job performance. The customer service orientation was defined as "a set of basic individual predispositions and an inclination to provide service, to be courteous and to be helpful in dealing with customers and associates." Similarly, it is a fact that the Big five personality traits are predictors of customer orientation, and employee's self- and supervisor performance. They propose that basic personality traits may be too far removed from focal service behaviors to be able to predict specific service behaviors (customer orientation) and service worker performance. Also, customer orientation is defined as "an employee's tendency or predisposition to meet customer needs in an on-the-job context." This means that people who have job-relevant personality traits such as concern, empathy, and conscientiousness will be more adept at customer service than people who do not possess these traits. However, little attention has been given to the exploration of the service orientation of customer-contact employees who play a key role in creating satisfactory service encounters in the hospitality industry except for Kim, McCahon, & Miller (2003)'s study, especially in family restaurants context. Thus, the purposes of this study are to examine and validate the customer service orientation of customer-contact employees using the instrument developed by Donavan (1999) in Korean family restaurants, because the scale was developed to measure the personality traits related job behaviors. And this study explores the relationships between customer service orientation, job satisfaction, organizational commitment, and self service performance using structural equation modeling (SEM). And this study explores the relationships between customer service orientation, job satisfaction, organizational commitment, and self service performance using structural equation modeling (SEM). For these purposes the author developed several hypotheses as follows: H1: Employee's service orientation is associated with service performance. H2: Employee's service orientation is positively associated with job satisfaction. H3: Employee's service orientation is positively associated with organizational commitment. H4: Service performance is positively associated with job satisfaction. H5: Service performance is positively associated with organizational commitment. H6: Job satisfaction is negatively associated with organizational commitment. The data were collected from 278 employees in 5 deluxe hotels located in Pusan, Korea. The researcher contacted the manager of the restaurants, and managers consented to administer surveys to their employees. The survey was executed during one month period in the October of 2007. The data were analyzed with structural equation modeling with LISREL 8.7 W. The result of the overall model analysis appeared as follows: $X^2$=122.638 (p = 0.00), df=59, GFI=.936, AGFI=.901, NFI=.948, CFI=.971, RMSEA=.0625. Since the result of the overall model analysis demonstrated a good fit, we could further analyze our data. The findings can be summarized as follows: First, the greater the employee service orientation, the greater the service performance. Second, the greater the employee service orientation, the greater the job satisfaction. Third, the greater the employee service orientation, the greater the organizational commitment. Fourth, the greater the service performance, the greater the job satisfaction. Fifth, the greater the service performance, the greater the organizational commitment. Finally, the greater the job satisfaction, the greater the organizational commitment. Seventh, the greater the customer satisfaction, the greater the customer loyalty.