• Journal of Intelligence and Information Systems
• /
• v.21 no.4
• /
• pp.93-110
• /
• 2015

The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.

• The Korean Journal of Pesticide Science
• /
• v.20 no.1
• /
• pp.14-22
• /
• 2016

A trial of combining and quantifying the effects of food processing on various pesticides was carried out using a meta-analysis. In this study, weighted mean response ratios and confidence intervals about the reduction of pesticide residue levels in fruits and vegetables treated with various food processing techniques were calculated using a statistical tool of meta-analysis. The weighted mean response ratios for tap water washing, peeling, blanching (boiling) and oven drying were 0.52, 0.14, 0.34 and 0.46, respectively. Among the food processing methods, peeling showed the greatest effect on the reduction of pesticide residues. Pearsons's correlation coefficient (r=0.624) between weighted mean response ratios and octanolwater partition coefficients ($logP_{ow}$) for twelve pesticides processed with tap water washing was confirmed as having a positive correlation in the range of significance level of 0.05 (p=0.03). This means that a pesticide having the higher value of $logP_{ow}$ was observed as showing a higher weighted mean response ratio. These results could be used effectively as a reference data for processing factor in risk assessment and as an information for consumers on how to reduce pesticide residues in agricultural products.

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.163-178
• /
• 2014

Following research proposes "Virtualization of Smart Cards (ViSCa)" which is a security system that aims to provide a multi-device platform for the deployment of services that require a strong security protocol, both for the access & authentication and execution of its applications and focuses on analyzing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service by comparing with other similar cases. At the present day, the appearance of new ICT, the diffusion of new user devices (such as smartphones, tablet PC, and so on) and the growth of internet penetration rate are creating many world-shaking services yet in the most of these applications' private information has to be shared, which means that security breaches and illegal access to that information are real threats that have to be solved. Also mobile payment service is, one of the innovative services, has same issues which are real threats for users because mobile payment service sometimes requires user identification, an authentication procedure and confidential data sharing. Thus, an extra layer of security is needed in their communication and execution protocols. The Virtualization of Smart Cards (ViSCa), concept is a holistic approach and centralized management for a security system that pursues to provide a ubiquitous multi-device platform for the arrangement of mobile payment services that demand a powerful security protocol, both for the access & authentication and execution of its applications. In this sense, Virtualization of Smart Cards (ViSCa) offers full interoperability and full access from any user device without any loss of security. The concept prevents possible attacks by third parties, guaranteeing the confidentiality of personal data, bank accounts or private financial information. The Virtualization of Smart Cards (ViSCa) concept is split in two different phases: the execution of the user authentication protocol on the user device and the cloud architecture that executes the secure application. Thus, the secure service access is guaranteed at anytime, anywhere and through any device supporting previously required security mechanisms. The security level is improved by using virtualization technology in the cloud. This virtualization technology is used terminal virtualization to virtualize smart card hardware and thrive to manage virtualized smart cards as a whole, through mobile cloud technology in Virtualization of Smart Cards (ViSCa) platform-based mobile payment service. This entire process is referred to as Smart Card as a Service (SCaaS). Virtualization of Smart Cards (ViSCa) platform-based mobile payment service virtualizes smart card, which is used as payment mean, and loads it in to the mobile cloud. Authentication takes place through application and helps log on to mobile cloud and chooses one of virtualized smart card as a payment method. To decide the scope of the research, which is comparing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service with other similar cases, we categorized the prior researches' mobile payment service groups into distinct feature and service type. Both groups store credit card's data in the mobile device and settle the payment process at the offline market. By the location where the electronic financial transaction information (data) is stored, the groups can be categorized into two main service types. First is "App Method" which loads the data in the server connected to the application. Second "Mobile Card Method" stores its data in the Integrated Circuit (IC) chip, which holds financial transaction data, which is inbuilt in the mobile device secure element (SE). Through prior researches on accept factors of mobile payment service and its market environment, we came up with six key factors of comparative analysis which are economic, generality, security, convenience(ease of use), applicability and efficiency. Within the chosen group, we compared and analyzed the selected cases and Virtualization of Smart Cards (ViSCa) platform-based mobile payment service.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.24 no.4
• /
• pp.547-555
• /
• 2014

Objective: This study was conducted to investigate the association between subjective distress symptoms and argon welding among workers in Gyeongnam Province shipyard. Method: 31 argon and 29 non-argon welding workers were selected as study subjects in order to measure concentrations of personal dust, welding fumes and other hazardous materials such as ZnO, Pb, Cr, FeO, MnO, Cu, Ni, $TiO_2$, MgO, NO, $NO_2$, $O_3$, $O_2$, $CO_2$, CO and Ar. An interviewer-administered questionnaire survey was also performed on the same subjects. The items queried were as follows: age, height, weight, working duration, welding time, welding rod amounts used, drinking, smoking, and rate of subjective distress symptoms including headache and other symptoms such as fever, vomiting and nausea, metal fume fever, dizziness, tingling sensations, difficulty in breathing, memory loss, sleep disorders, emotional disturbance, hearing loss, hand tremors, visual impairment, neural abnormality, allergic reaction, runny nose and stuffiness, rhinitis, and suffocation. Statistical analysis was performed using SPSS software, version 18. Data are expressed as the mean ${\pm}SD$. An ${\chi}^2$-test and a normality test using a Shapiro wilk test were performed for the above variables. Logistic regression analysis was also conducted to identify the factors that affect the total score for subjective distress symptoms. Result: An association was shown between welding type (argon or non-argon welding) and the total score for subjective distress symptoms. Among the rate of complaining of subjective distress symptoms, vomiting and nausea, difficulty breathing, and allergic reactions were all significantly higher in the argon welding group. Only the concentration of dust and welding fumes was shown to be distributed normally after natural log transformation. According to logistic regression analysis, the correlations of working duration and welding type (argon or non-argon) between the total score of subjective distress symptoms were found to be statistically significant (p=0.041, p=0.049, respectively). Conclusion: Our results suggest that argon welding could cause subjective distress symptoms in shipyard workers.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.10
• /
• pp.4769-4774
• /
• 2016

Objective: To analyze the survival of elderly patients with breast cancer according to the type of treatment used. Methods: A cohort study of women aged 80 or over with breast cancer registered with the Brazilian National Cancer Institute (Instituto Nacional do $C{\hat{a}}ncer$ - INCA) between 2008 and 2009 was conducted. Prognosis was analyzed according to the cancer treatment performed: surgery, radiotherapy, or hormone therapy. Analysis of the overall 5-year survival rate was performed using the Kaplan - Meier method, and comparisons of curves were undertaken using the log-rank test. For multiple regression analysis, Cox regression was used, adjusting for age and clinical stage, considering values of p < 0.05 as significant. Data were all analyzed using the statistical package SPSS version 20. Results: 70 women with a mean age of $84.0{\pm}3.7years$ at diagnosis participated in the study. The median follow-up time was 37.1 months (range 0.5-75.5), and 31 deaths (44.3%) occurred during this time. The median survival time was 51.2 months (95% CI, 44.9-57.4), higher in those who underwent surgery (p = 0.012) and those who had hormone therapy (p=0.001). Treatment with surgery reduced the risk of death by 61.7% (HR 0.3; 95% CI, 0.1-0.6; p = 0.001) when adjusted for clinical stage and age at diagnosis. However, there was no significant benefit from radiotherapy (HR 1.2; 95% CI, 0.5-2.5; p = 0.694). Conclusion: Treatment with surgery and hormone therapy increased the survival of our Brazilian patients with breast cancer aged 80 or over.

• Korean Journal of Biological Psychiatry
• /
• v.3 no.2
• /
• pp.216-221
• /
• 1996

The quantitative EEGs of obsessive-compulsive disorder patients were analyzed using spectral analysis and compared to age and sex-matched controls. The subjects were 19 patients(men=15, women=4) suffering from obsessive-compulsive disorder(DSM-III-R). Absolute power, relative power and interhemispheric asymmetry of EEG were used to compare obsessive-compulsive disorder patients with controls. In order to fit the EEG data to a normal distribution, a log transformation of power values of every bandwidth in each deviation was calculated prior statistical analysis. The Wilcoxon rank test was performed to compare obsessive-compulsive group to the control group. In obsessive-compulsive disorder, abnormalities of quantitative EEGs are prominent in fronto-central. These results ore compatible with other brain imaging studies of obsessive-compulsive disorder and suggested that fronto-central area plays an important role in the pathophysiology of obsessive-compulsive disorder.

• Radiation Oncology Journal
• /
• v.33 no.2
• /
• pp.109-116
• /
• 2015

Purpose: To analyze prognostic factors for locoregional recurrence (LRR), distant metastasis (DM), and overall survival (OS) in cervical cancer patients who underwent radical hysterectomy followed by postoperative radiotherapy (PORT) in a single institute. Materials and Methods: Clinicopathologic data of 135 patients with clinical stage IA2 to IIA2 cervical cancer treated with PORT from 2001 to 2012 were reviewed, retrospectively. Postoperative parametrial resection margin (PRM) and vaginal resection margin (VRM) were investigated separately. The median treatment dosage of external beam radiotherapy (EBRT) to the whole pelvis was 50.4 Gy in 1.8 Gy/fraction. High-dose-rate vaginal brachytherapy after EBRT was given to patients with positive or close VRMs. Concurrent platinum-based chemoradiotherapy (CCRT) was administered to 73 patients with positive resection margin, lymph node (LN) metastasis, or direct extension of parametrium. Kaplan-Meier method and log-rank test were used for analyzing LRR, DM, and OS; Cox regression was applied to analyze prognostic factors. Results: The 5-year disease-free survival was 79% and 5-year OS was 91%. In univariate analysis, positive or close PRM, LN metastasis, direct extension of parametrium, lymphovascular invasion, histology of adenocarcinoma, and chemotherapy were related with more DM and poor OS. In multivariate analysis, PRM and LN metastasis remained independent prognostic factors for OS. Conclusion: PORT after radical hysterectomy in uterine cervical cancer showed excellent OS in this study. Positive or close PRM after radical hysterectomy in uterine cervical cancer correlates with poor prognosis even with CCRT. Therefore, additional treatments to improve local control such as radiation boosting need to be considered.

• Health Policy and Management
• /
• v.4 no.2
• /
• pp.77-110
• /
• 1994

This study is an empiriacl analysis of effects of government intervention on the health care delivery system in Korea. The purposes of this study are to find out the effects of government intervention on the per capita national health expenditure(per capita NHE), crude mortality rate(CMR), and institutional efficiency. Here, the institutional efficiency is defined as a formula shown below: log$\frac{100-curde mortality rate }{per capita NHE}$$\times$100. The formula indicates that the instiutional efficiency increases if the CMR and/or per capita NHE goes down. In the meantime the government intervention is measured by six independent variables: I) the degree of social developments, ii) the numberr of physicians per 100, 000 population, iii) the proportion of specialists among the total physicians, iv) the proportion of public expenditure among the NHE, v) the proportion of public beds to the total number of beds, vi) the proportion of physicians working at the public sector to the total number of physicians. In the above six independent variables iv), v) and vi) are the ones that reflect the degree of government intervention. In actual calculation, the two independent variables v) and vi) are integrated into a new variable based on one to one correspondence. The materials used are the time-series data from 1970 through 1990 in Korea. A path analysis and the time-series regression analysis were adopted to estimate and examine the causal relationship between variables involved. And decomposition of the effect of causal relationship is made to find net effect, direct and indirect effect. The major findings are as follows; 1. The effect of public expenditure, number of physicians per 100, 000 population, the proportion of specialists among the total physicians and social development shows a positive relationship with per capita NHE. Only if the government intervention would be counted, the effects of the number of physicians and the proportion of specialists succeed in containing per capita NHE. 2. In additionn to the above four variables, one additional variable, per capita NHE, was also responsible for the reduction of CMR. The factor of social development found to be the most potent predictor of the CMR reduction. However, the CMR reduction due to government intervention was negligible. 3. Meanwhile, the above four variables were found to was have negative effects on the institutional efficiency. The reverse is true when the government intervention is counted. For example, the number of physicians and the proportion of specialists have played a positive role in raising institutional efficiency via goverment intervention. This comes from the factual effect that the increment of institutional efficiency via the reduction of per capita NHE is bigger than via the reduction of CMR.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.62 no.3
• /
• pp.1-13
• /
• 2020

The management of agricultural water can be divided into management of agricultural infrastructure and operation to determine the timing and quantity of water supply. The target of water management is classified as water-supply facilities, such as reservoirs, irrigation water supply, sluice gate control, and farmland. In the case of agricultural drought, there is a need for water supply capacity in reservoirs and for drought assessment in paddy fields that receive water from reservoirs. Therefore, it is necessary to analyze the water supply amount from intake capacity to irrigation canal network. The analysis of the irrigation canal network should be considered for efficient operation and planning concerning optimized irrigation and water allocation. In this study, we applied a hydraulic analysis model for agricultural irrigation networks by adding the functions of irrigation canal network analysis using the SWMM (Storm Water Management Model) module and actual irrigation water supply log data from May to August during 2015-2019 years in Sinsong reservoir. The irrigation satisfaction of ponding depth in paddy fields was analyzed through the ratio of the number of days the target ponding depth was reached for each fields. This hydraulic model can assist with accurate irrigation scheduling based on its simulation results. The results of evaluating the irrigation efficiency of water supply can be used for efficient water distribution and management during the drought events.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.11
• /
• pp.6715-6719
• /
• 2013

Objective: To explore the incidence, clinical characteristics, diagnosis and treatment strategies, prognosis of patients with malignancy-associated hypercalcemia (MAH). Methods: The data of 115 patients with MAH who were treated at the Medical Oncology Department of Chinese PLA General Hospital from Jan., 2001 to Dec., 2010 was retrospectively reviewed. Survival analysis was performed using the Kaplan-Meier method and the Cox proportional hazard model with statistic software SPSS 18.0. Results: The patients had blood calcium levels ranging from 2.77 to 4.87 mmol/L. Except for 9 cases who died or were discharged within 5 days after admission, all other patients recovered to normal blood calcium level after treatment with bisphosphonates or intravenous hydration and diuretics; their survival after occurrence of MAH was from 1 day to 4,051 days, and the median survival time was only 50 days. In the log-rank test, the male, renal metastasis, central nervous system symptoms and hypercalcemia occurring over 140 days after cancer diagnosis were predictors of poor survival (P=0.002, P=0.046, P=0.000, P=0.009). In the COX analysis, being male, central nervous system symptoms and hypercalcemia lasting over 140 days after cancer diagnosis were independent prognostic factors for survival time (RR=2.131, P=0.027; RR=3.054, P=0.002; RR=2.403, P=0.001). According to these factors, a score system was established to predict the patient prognosis and adjust the treatment. Conclusion: Cancer patients with MAH have an extremely poor median survival. Some independent factors indicate poor prognosis, including male gender, central nervous system symptoms and hypercalcemia lasting over 140 days after cancer diagnosis. The prognostic score can serve as a reference for MAH prognosis and treatment, worthy of further investigation.