Pulp and paper industry produces large volumes of wastewater and residual sludge waste, resulting in many issues in relation to wastewater treatment and sludge disposal. Contaminants in pulp and paper wastewater include effluent solids, sediments, chemical oxygen demand (COD), and biological oxygen demand (BOD), which should be treated by wastewater treatment processes such as coagulation and biological treatment. However, few works have been attempted to predict the treatment efficiency of pulp and paper wastewater. Accordingly, this study presented empirical models based on experimental data in laboratory-scale coagulation tests and compared them with statistical models such as artificial neural network (ANN). Results showed that the water quality parameters such as turbidity, suspended solids, COD, and UVA can be predicted using either linear or expoential regression models. Nevertheless, the accuracies for turbidity and UVA predictions were relatively lower than those for SS and COD. On the other hand, ANN showed higher accuracies than the emprical models for all water parameters. However, it seems that two kinds of models should be used together to provide more accurate information on the treatment efficiency of pulp and paper wastewater.

As big data is diffused throughout the industry, big data analytics is regarded as a corporate competitiveness, and data mining techniques are pouring in exponential methodologies and techniques in the field of computational science. Using mathematical and statistical techniques that have sufficient academic depth, we aim to increase mining efficiency by increasing efficiency and applying efficient data to mining procedures and processing procedures.

PURPOSES: The demand for extending national highways is increasing, but traffic monitoring is hindered because of resource limitations. Hence, this study classified highway segments into 5 types to improve the efficiency of short-term traffic count planning. METHODS : The traffic volume trends of 880 highway segments were classified through R-squared and linear regression analyses; the steadiness of traffic volume trends was evaluated through coefficient of variance (COV), and the normality of the data were determined through the Shapiro-Wilk W-test. RESULTS : Of the 880 segments, 574 segments had relatively low COV and were classified as type 1 segments, and 123 and 64 segments with increasing and decreasing traffic volume trends were classified as type 2 and type 3 segments, respectively; 80 segments that failed the normality test were classified as type 4, and the remaining 39 were classified as type 5 segments. CONCLUSIONS : A theoretical basis for biennial count planning was established. Biennial count is recommended for types 1~4 because their mean absolute percentage errors (MAPEs) are approximately 10%. For type 5 (MAPE =19.26%), the conventional annual count can be continued. The results of this analysis can reduce the traffic monitoring budget.

The purpose of this paper is to analyze the problems and the sources of defective products and draw improvement plans in a small plastic boat manufacturing process using TOC (Theory Of Constraints) and statistical analysis. TOC is a methodology to present a scheme for optimization of production process by finding the CCR (Capacity Constraints Resource) in the organization or the all production process through the concentration improvement activity. In this paper, we found and reformed constraints and bottlenecks in plastic boat manufacturing process in the target company for less defect ratio and production cost by applying DBR (Drum, Buffer, Rope) scheduling. And we set the threshold values for the critical process variables using statistical analysis. The result can be summarized as follows. First, CCRs in inventory control, material mix, and oven setting were found and solutions were suggested by applying DBR method. Second, the logical thinking process was utilized to find core conflict factors and draw solutions. Third, to specify the solution plan, experiment data were statistically analyzed. Data were collected from the daily journal addressing the details of 96 products such as temperature, humidity, duration and temperature of heating process, rotation speed, duration time of cooling, and the temperature of removal process. Basic statistics and logistic regression analysis were conducted with the defection as the dependent variable. Finally, critical values for major processes were proposed based on the analysis. This paper has a practical importance in contribution to the quality level of the target company through theoretical approach, TOC, and statistical analysis. However, limited number of data might depreciate the significance of the analysis and therefore it will be interesting further research direction to specify the significant manufacturing conditions across different products and processes.

This study suggests a prediction model of ground motion spectral shape considering characteristics of earthquake records in Korea. Based on the Graizer and Kalkan’s prediction procedure, a spectral shape model is defined as a continuous function of period in order to improve the complex problems of the conventional models. The approximate spectral shape function is then developed with parameters such as moment magnitude, fault distance, and average shear velocity of independent variables. This paper finally determines estimator coefficients of subfunctions which explain the corelation among the independent variables using the nonlinear optimization. As a result of generating the prediction model of ground motion spectral shape, the ground motion spectral shape well estimates the response spectrum of earthquake recordings in Korea.

It has been widely accepted that the pressure management of water distribution systems using pressure reducing valves(PRVs) would be an effective method for controlling leakages. A pressure reducing valve (PRV) regulates outlet pressure regardless of fluctuating flow and varying inlet pressure, thereby reducing leakage and mitigating the stress on the water distribution system. However, the operation of a PRV is vulnerable to its mechanical condition and hydraulic operability. In this research, the effect of PRVs installed in water distribution system are evaluated in terms of hydraulic pressure reduction and mechanical performance by analyzing measured pressure data with statistical approach. A statistical approach using the moving average filter and frequency analysis based on fourier transform is presented to detect abnormally operated PRVs that have been densely installed in water distribution system. The result shows that the proposed approach can be a good performance evaluation method by simply measuring pressures for the PRVs.

This study have been conducted to analyze the feasibility of establishing Contamination Warning System(CWS) that is capable of monitoring early natural or intentional water quality accidents, and providing active and quick responses for domestic C_water supply system. In order to evaluate the water quality data set, pH, turbidity and free residual chlorine concentration data were collected and each statistical value(mean, variation, range) was calculated, then the seasonal variability of those were analyzed using the independent t-test. From the results of analyzing the distribution of outliers in the measurement data using a high-pass filter, it could be confirmed that a lot of lower outliers appeared due to data missing. In addition, linear filter model based on autoregressive model(AR(1) and AR(2)) was applied for the state estimation of each water quality data set. From the results of analyzing the variability of the autocorrelation coefficient structure according to the change of window size(6hours~48hours), at least the window size longer than 12hours should be necessary for estimating the state of water quality data satisfactorily.

This study considered network quotient (NQ) of deluxe hotel employees and schematized characteristic attributes of being selected by employees with image through correspondence analysis in terms of cognition degree. Self-administrated questionnaires were completed by employees (292 samples) and data were analysed by frequency, t-test, one-way ANOVA, reliability and correspondence analysis. First, the hotel employees indicated the high average value in “participating in special education or seminar for improving ability (3.85±0.76). Second, as a result of analyzing difference according to gender, the average value in men was higher than in women. It was indicated that the higher age and career lead to a rise even in the average value of relationship index. Third, in consequence of carrying out correspondence analysis in order to prepare image map according to cognition level on relationship index in hotel employees, the measurement item that is placed in the closest distance to the response as saying of not so very was the response as saying of “having a lunch (dinner) engagement twice or three times a week.” On the other hand, the response as saying of “tending to have many acquaintances compared to coworkers” was schematized in the close distance to the response as saying of very so.

PURPOSES: This study has been conducted to determine a homogeneous segment and integration to improve the efficiency of short-term traffic count. We have also attempted to reduce the traffic monitoring budget. METHODS: Based on the statistical approach, a homogeneous segment in the same road section is determined. Statistical analysis using t-test, mean difference, and correlation coefficient are carried out for 10-year-long (2004-2013) short-term count traffic data and the MAPE of fresh data (2014) are evaluated. The correlation coefficient represents a trend in traffic count, while the mean difference and t-score represent an average traffic count. RESULTS : The statistical analysis suggests that the number of target segments varies with the criteria. The correlation coefficient of more than 30% of the adjacent segment is higher than 0.8. A mean difference of 36.2% and t-score of 19.5% for adjacent segments are below 20% and 2.8, respectively. According to the effectiveness analysis, the integration criteria of the mean difference have a higher effect as compared to the t-score criteria. Thus, the mean difference represents a traffic volume similarity. CONCLUSIONS : The integration of 47 road segments from 882 adjacent road segments indicate 8.87% of MAPE, which is within an acceptable range. It can reduce the traffic monitoring budget and increase the count to improve an accuracy of traffic volume estimation.

This study understood what effect was produced on the purchasing decision making of outdoor wear by a shopping orientation, fashion involvement and demographic characteristics offered practical suggestions as to what effect was produced on the store selection criteria, product selection criteria for purchasing decision making in purchasing outdoor wear. This research was conducted through a questionnaire survey, and 397 males in were collected for analysis. The results were as follows. First, shopping orientation group was classified into hedonic shopping orientation group and utilitarian shopping orientation group. And it was classified into high fashion involvement group and low fashion involvement group according to fashion involvement. Product selection criteria were classified into 2 factors such as intrinsic attributes and extrinsic attributes. And store selection criteria were classified into 4 factors such as store atmosphere, store environment, promotion and salesmen. Second, there was partly significant difference in product selection criteria, and store selection criteria between utilitarian shopping group and hedonic shopping group. Third, there was significant difference in product selection criteria and store selection criteria between high fashion involvement group and low fashion involvement group. Finally, there was significant difference in the and according to age, job, and income among demographic characteristics.

The objective of this study is to investigate consumer preferences, perception and consumption patterns for fish products. To investigate the difference in consumer responses according to the characteristics of the population parameters, data were collected from the survey of 404 Koreans and analyzed. The results are as follows: First, the differences of age; for the question of the reason why do you eat fish products, the younger generation (20〜30s)’s most answer was‘The Taste’while the older age groups(40〜50s and over 60s)’most respond was‘For Health’. Second, the differences of sex; women relatively considered‘The Quality’of fish products more important than men when selecting the products. Whereas, men thought‘The Taste’of fish products more important than women when they choose fish products. In addition, when the bad news or hygiene accidents about fish products are reported on media, women reacted more negatively for fish products purchase than men. Third, the differences of family members; the respondents who lived with 3 or more family members showed higher preference rates about purchasing trimmed fresh fish at the store than respondents who lived with 2 or less family members. On the other hand, single households relatively bought processed fish products and RTE(Ready To Eat) fish products more than other family member groups. In addition, single households preference rates about eating fish products as a main dish were very high compared to other groups.

시중에 유통 중인 샐러드와 김밥을 각각 100종 수거하 여 B. cereus 함량을 정량분석하였다. 샐러드는 불검출이 54종이었으며 10 CFU/g 이하가 8종, 100 CFU/g 이하가 25 종, 1,000 CFU/g 이하가 11종이었으며 1,000 CFU/g 이상인 것이 2종이었다. 샐러드의 대한 모니터링 결과 평균은 1.18 log CFU/g 이었으며 표준편차는 0.71 log CFU/g이었다. 김밥에서는 100개의 검체중 20개의 검체에서 B. cereus가 검출되었으며 평균은 1.01 log CFU/g 이었으며 표준편차는 0.71 log CFU/g이었다. 모니터링 결과를 이용하여 통계적 검체채취 방법을 수립하고자 하였다. 검체채취 방법은 국제미생물위원회에서 제공하는 검체채취프로그램인 NEW sampleplan program을 이용하였으며 검체갯수를 고정한 후 미생물 기준인 m과 M, 그리고 허용한계값인 c 값을 변화 하면서 산출되는 합격률이 0.95에 가장 근사한 값을 선정하였다. 그 결과 샐러드, 김밥에서의 가장 적합한 검체채취 기준은 3분법을 사용하는 것으로 n = 5, c = 0, m = 1,000, M = 10,000과 n = 5, c = 2, m = 100, M = 1,000의 기준이 설정되었다. 특히 후자에 서술된 기준은 현재 뉴질랜드에서 즉석섭취식품에서의 B. cereus에 대한 규격으로 사용하고 있어 국제적인 경향에도 부합함을 알 수 있었다.

본 연구에서는 질병 데이터를 활용한 사망률의 지도화에서 지역별 사망률의 변동성을 안정화할 수 있도록 하는 베이지언 기법을 적용하고, 기본적으로 활용되고 있는 SMR (Standardized mortality ratio)과 그 결과를 비교하였다. 우리나라 전국의 시군구 단위의 전립선암 사망자 수 데이터에 표준화와 베이지언 기법을 적용하고, 산출된 사망률을 지도화하여 기존에 없던 우리나라의 전립선암 사망률 지도를 질병 지도의 예시 자료로 작성하였다. 분석 결과, Bayesian 모델링 기법을 통해 계산된 위험비는 기존 SMR에 비해 좀 더 수렴된 형태의 안정적인 통계량을 가지는 것을 알 수 있었다. 국지적 Bayesian 기법은 이웃 지역들의 정보만을 반영하여 위험비를 평활화하기 때문에 본 연구에서 사용된 전역적 기법들과 비교할 때 평활화의 강도가 크지 않았다.

시중에 유통 중인 샐러드와 김밥을 각각 100종 수거하 여 B. cereus 함량을 정량분석하였다. 샐러드는 불검출이 54종이었으며 10 CFU/g 이하가 8종, 100 CFU/g 이하가 25 종, 1,000 CFU/g 이하가 11종이었으며 1,000 CFU/g 이상 인 것이 2종이었다. 샐러드의 대한 모니터링 결과 평균은 1.18 log CFU/g 이었으며 표준편차는 0.71 log CFU/g이었다. 김밥에서는 100개의 검체중 20개의 검체에서 B. cereus가 검출되었으며 평균은 1.01 log CFU/g 이었으며 표준편차는 0.71 log CFU/g이었다. 모니터링 결과를 이용하여 통계적 검체채취 방법을 수립하고자 하였다. 검체채취 방법은 국제미생물위원회에서 제공하는 검체채취프로그램인 NEW sampleplan program을 이용하였으며 검체갯수를 고정한 후 미생물 기준인 m과 M, 그리고 허용한계값인 c 값을 변화 하면서 산출되는 합격률이 0.95에 가장 근사한 값을 선정 하였다. 그 결과 샐러드, 김밥에서의 가장 적합한 검체채취 기준은 3분법을 사용하는 것으로 n = 5, c = 0, m = 1,000, M = 10,000과 n = 5, c = 2, m = 100, M = 1,000의 기준이 설정되었다. 특히 후자에 서술된 기준은 현재 뉴질랜드에서 즉석섭취식품에서의 B. cereus에 대한 규격으로 사용하고 있어 국제적인 경향에도 부합함을 알 수 있었다.

Among many potential problems associated with automobiles, the problem regarded as most sensitive and important to the customers is the automobile’s quietness. In particular, because the trend toward the high-performance automobiles is increasing, the quietness should be considered reflecting the increasing demand of the customers for the comfort of automobile ride. Road noise is the low-frequency range in the region of 20Hz to 350Hz, generated when the tires are making contacts with the rough road surface while the automobile is running, in which the noises are resonating within the passenger compartment or with the automobile suspension. In this research, among the factors related to the road noise, the influencing factors associated with the suspension and the tire design were investigated. In particular, among the tire design factors, the structure and the rubber material were investigated as the influencing factors, and for the investigative purpose, experimental tires were manufactured and road noise evaluations were conducted thorough actual feeling tests. Then the test results and correlations were analyzed using the 6-Sigma statistical method. Results from this study shows that, among the tire design factors, the apex is the most influencing factor, in which the height of the apex is the key. The influential factors were found out to be apex height, belt angle, and tread hardness, in that order, and when the suspension is of a same kind, the tendency of the road noise was found to be similar.