In the past era, acquisition and utilization of useful information was the main origin of competition. Nowadays, unlike that era, is the era of knowledge information(management) in which we should create a new knowledge on the basis of information and apply it to the field of practice. And more acquisition of information is no more the competitive power of any person, any company and any nation because in such the era of knowledge management, anyone can access and get the information he needs, utilizing internet-based searching system. Such demands of the times of knowledge management change rapidly in each field through knowledge management system and researches about knowledge management are actively processed in various academic branches. However, in our field of design, researches about those demands(knowledge management) still remain on the level of one-dimensional searching service for general data about design. Therefore, in this study, we developed building database of researches on form, color, aesthetical elements, preference image word, satisfaction etc. about CI/BI of home electronics goods, living goods, apparels, and food goods companies, also suggesting searching system through which you can obtain useful data and information helpful for designers to process CI/BI works of new product by using that database. Especially, in case of developing specific CI/BI, various search results through help of suggested system will supply a useful design concept. And more, cross table which is the result of analysis two-dimensional categorical data about existing design factors(such as form, color, aesthetical elements, preference image word, and satisfaction) will make contribution for designers to create a new design knowledge.
Ko, Ho Kyoung;Kim, Dong Won;Lee, Hwan Chul;Choi, Tae Young
Journal of the Korean School Mathematics Society
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v.17
no.1
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pp.73-92
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2014
This study was performed in part with the task to find measures to improve the defining characteristics of feelings, value, interest, self-efficacy, and others aspects in regards to learning math among elementary and middle school students. For this study, it was essential to understand the appropriate questions that are needed to be asked during a consultation at a math clinic, for students that are having a hard time learning math. As a method for performing this study, the content of scheduled counseling over 2 years from a math clinic were collected and the questions that were given and taken were analyzed in order to figure out the types of questions needed in order to effectively examine students that are facing difficulty with learning math. The analysis was performed using Grounded theory analysis by Strauss & Corbin(1998) and went through the process of open coding, axial coding, and selective coding. For the paradigm in the categorical analysis stage, 'attitude towards learning math' was set as the casual condition, 'feelings towards learning math' was set as the contextual condition, 'confidence in one's ability to learn math' was set as the phenomenon, 'individual tendencies when learning math' was set as the intervening condition, 'self-management of learning math' was set as the action/interaction strategy, and 'method of learning' was set as the consequence. Through this, the questions that appeared during counseling were linked into categories and subcategories. Through this process, 81 concepts were deducted, which were grouped into 31 categories. I believe that this data can be used as grounded theory for standardization of consultation in clinics.
The health status of workers in a foundry was analyzed in a study which consisted of evaluations of respiratory health together with environmental measurements. The results from environmental measurements showed values exceeding permissible exposure limits. A t-test was done with log transformed and untransformed data to examine the statistical significance for the noncompliance with exposure standards. For the analysis of categorical health outcomes, $\chi$-square test with 2 $\times$ 2 tables and logistic regression analysis were employed. For continuous variables, multiple linear regression was done against assessed risk factors. Pros and cons of different parameters in the compliance (or noncompliance) testing were presented. Respiratory function did not show any relation with occupational exposures, which may be due to the healthy worker effects. Strategies for controlling time dependent covariates were discussed in relation to the healthy worker effect. The scope of statistical analysis in occupational health studies is still limited in Korea without a suitable external comparison group such as credible vital statistics for the whole nation. Internal comparisons between different exposure status often result in unstable estimates of effect, and proportional morbidity study is discussed as an alternative potential research tool.
The purpose of this study was to propose a product planning and design direction for smart fitness wear that will improve the impact of personal training based on researching the requirements of smart fitness wear and its acceptance level, as well as the functional demand. The study conducted in-depth interviews with professional fitness trainers and derived five categories and thirteen keywords by analyzing the categorical data analysis using the interview data. In addition, we surveyed general consumers to measure the acceptance level of smart fitness wear and the functional demand for product development. The results revealed that the difference in the acceptance level of smart fitness wear generally depended on the characteristics related to exercise involvement and exercise-related culture rather than on the demographic characteristics. With regard to the difference in the functional demand of smart fitness wear, the results showed that professional trainers focused on the scientific improvement of the effect of exercise while general consumers focused on the function that considers the sustainability of exercise. Based on the results, we proposed product planning and design directions such as 'mounting of heart rate sensing, muscle activity sensing, motion angle or posture sensing, and motion sensing', 'development of concepts and contents for expert line, ordinary line', 'compression wear design', and 'differentiation of product development according to exercise areas'.
Ulas, Arife;Silay, Kamile;Akinci, Sema;Dede, Didem Sener;Akinci, Muhammed Bulent;Sendur, Mehmet Ali Nahit;Cubukcu, Erdem;Coskun, Hasan Senol;Degirmenci, Mustafa;Utkan, Gungor;Ozdemir, Nuriye;Isikdogan, Abdurrahman;Buyukcelik, Abdullah;Inanc, Mevlude;Bilici, Ahmet;Odabasi, Hatice;Cihan, Sener;Avci, Nilufer;Yalcin, Bulent
Asian Pacific Journal of Cancer Prevention
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v.16
no.5
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pp.1699-1705
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2015
Background: Medication errors in oncology may cause severe clinical problems due to low therapeutic indices and high toxicity of chemotherapeutic agents. We aimed to investigate unintentional medication errors and underlying factors during chemotherapy preparation and administration based on a systematic survey conducted to reflect oncology nurses experience. Materials and Methods: This study was conducted in 18 adult chemotherapy units with volunteer participation of 206 nurses. A survey developed by primary investigators and medication errors (MAEs) defined preventable errors during prescription of medication, ordering, preparation or administration. The survey consisted of 4 parts: demographic features of nurses; workload of chemotherapy units; errors and their estimated monthly number during chemotherapy preparation and administration; and evaluation of the possible factors responsible from ME. The survey was conducted by face to face interview and data analyses were performed with descriptive statistics. Chi-square or Fisher exact tests were used for a comparative analysis of categorical data. Results: Some 83.4% of the 210 nurses reported one or more than one error during chemotherapy preparation and administration. Prescribing or ordering wrong doses by physicians (65.7%) and noncompliance with administration sequences during chemotherapy administration (50.5%) were the most common errors. The most common estimated average monthly error was not following the administration sequence of the chemotherapeutic agents (4.1 times/month, range 1-20). The most important underlying reasons for medication errors were heavy workload (49.7%) and insufficient number of staff (36.5%). Conclusions: Our findings suggest that the probability of medication error is very high during chemotherapy preparation and administration, the most common involving prescribing and ordering errors. Further studies must address the strategies to minimize medication error in chemotherapy receiving patients, determine sufficient protective measures and establishing multistep control mechanisms.
Objective: Aim of the current comparative study was to evaluate production outputs, reproduction efficiency and functional traits in dual-purpose Fleckvieh and Braunvieh cows, reared under temperate European conditions. Methods: A data-set from 414 Fleckvieh and 42 Braunvieh cows and 799 lactations was analysed. ID tag number, milk yield per milking session, number of steps/interval and milk conductivity were recorded and collected daily using AfiMilk 3.076 A-DU software (Afimilk Ltd., Kibbutz, Israel). Production and milk quality data were taken from the results of the official performance recordings and the reproductive outputs of cows were recorded by the research stations veterinarians. Comparisons between the two genotypes were carried out using the one way analysis of variance protocol, with categorical factor being considered the breed of cows. All the statistical inferences were carried out using Statistica software (StatSoft Inc., Tulsa, OK, USA). Results: Fleckvieh cows significantly outperformed ($p{\leq}0.05$) the Braunvieh herd, with average milk yields of $5,252.1{\pm}35.79kg$ and $4,897.6{\pm}128.94kg$, respectively. Age at first calving was significantly ($p{\leq}0.01$) influenced by the breed, with Fleckvieh heifers being more precocious ($32.8{\pm}0.29mo$) compared to those of Braunvieh breed ($35.7{\pm}0.84mo$). Reproduction efficiency as defined by the number of inseminations per gestation, calving interval, dystocia, days dry and days open, was not influenced by genotype (p>0.05). Incidences of sub-clinical mastitis, clinical mastitis, lameness and abortions were not influenced by the breed factor (p>0.05). Stay-ability of cows was significantly ($p{\leq}0.001$) influenced by genotype, with Braunvieh cows having an average age at culling of $117.88{\pm}11.78$ months compared to $90.88{\pm}2.89$ months in Fleckvieh. Conclusion: Overall, results have shown that genotype significantly influenced milk yield, age at first calving and longevity.
In this study, open inquiry reports of 165 eighth graders in Daegu were analyzed in terms of content area, the types of inquiry hypothesis, and the types of inquiry variables. Before summer vacation, students learned about inquiry process and explored their own inquiry topic for two class hours. During summer vacation, students performed open inquiry including problem selection, designing and performing experiment, data collection, data analysis, and writing report. After the vacation, students submitted their reports, and answered to additional survey regarding the source of inquiry idea, the definition of hypothesis, and the most difficult step of inquiry process. As a result, chemistry was the most dominant content area of the reports and biology and life science were the next. 130 out of 165 reports included inquiry hypotheses, and most of them were predictive hypotheses. In many reports, dependent and independent variables could not be identified because of their ambiguity. However, inquiry variables described in experimental design, which were mostly categorical variables, were clearer than those described in inquiry subject and inquiry hypothesis. The most difficult step of inquiry process for students was to generate an idea for open inquiry.
1. Purpose Rural tourism is made by individuals with different characteristics, needs and wants. It is important to have information on the characteristics and preferences of the consumers of the different types of existing rural accommodation. The stud aims to identify the determinants of consumer preference by type of accommodations. 2. Methodology 2.1 Sample Data were collected from 1000 people by telephone survey with three-stage stratified random sampling in seven metropolitan areas in Korea. Respondents were chosen by sampling internal on telephone book published in 2006. We surveyed from four to ten-thirty 0'clock afternoon so as to systematic sampling considering respondents' life cycle. 2.2 Two-step cluster Analysis Our study is accomplished through the use of a two-step cluster method to classify the accommodation in a reduced number of groups, so that each group constitutes a type. This method had been suggested as appropriate in clustering large data sets with mixed attributes. The method is based on a distance measure that enables data with both continuous and categorical attributes to be clustered. This is derived from a probabilistic model in which the distance between two clusters in equivalent to the decrease in log-likelihood function as a result of merging. 2.3 Multinomial Logit Analysis The estimation of a Multionmial Logit model determines the characteristics of tourist who is most likely to opt for each type of accommodation. The Multinomial Logit model constitutes an appropriate framework to explore and explain choice process where the choice set consists of more than two alternatives. Due to its ease and quick estimation of parameters, the Multinomial Logit model has been used for many empirical studies of choice in tourism. 3. Findings The auto-clustering algorithm indicated that a five-cluster solution was the best model, because it minimized the BIC value and the change in them between adjacent numbers of clusters. The accommodation establishments can be classified into five types: Traditional House, Typical Farmhouse, Farmstay house for group Tour, Log Cabin for Family, and Log Cabin for Individuals. Group 1 (Traditional House) includes mainly the large accommodation establishments, i.e. those with ondoll style room providing meals and one shower room on family tourist, of original construction style house. Group 2 (Typical Farmhouse) encompasses accommodation establishments of Ondoll rooms and each bathroom providing meals. It includes, in other words, the tourist accommodations Known as "rural houses." Group 3 (Farmstay House for Group) has accommodation establishments of Ondoll rooms not providing meals and self cooking facilities, large room size over five persons. Group 4 (Log Cabin for Family) includes mainly the popular accommodation establishments, i.e. those with Ondoll style room with on shower room on family tourist, of western styled log house. While the accommodations in this group are not defined as regards type of construction, the group does include all the original Korean style construction, Finally, group 5 (Log Cabin for Individuals)includes those accommodations that are bedroom western styled wooden house with each bathroom. First Multinomial Logit model is estimated including all the explicative variables considered and taking accommodation group 2 as base alternative. The results show that the variables and the estimated values of the parameters for the model giving the probability of each of the five different types of accommodation available in rural tourism village in Korea, according to the socio-economic and trip related characteristics of the individuals. An initial observation of the analysis reveals that none of variables income, the number of journey, distance, and residential style of house is explicative in the choice of rural accommodation. The age and accompany variables are significant for accommodation establishment of group 1. The education and rural residential experience variables are significant for accommodation establishment of groups 4 and 5. The expenditure and marital status variables are significant for accommodation establishment of group 4. The gender and occupation variable are significant for accommodation establishment of group 3. The loyalty variable is significant for accommodation establishment of groups 3 and 4. The study indicates that significant differences exist among the individuals who choose each type of accommodation at a destination. From this investigation is evident that several profiles of tourists can be attracted by a rural destination according to the types of existing accommodations at this destination. Besides, the tourist profiles may be used as the basis for investment policy and promotion for each type of accommodation, making use in each case of the variables that indicate a greater likelihood of influencing the tourist choice of accommodation.
Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.
Lee, Soo Hyung;Park, Hong In;Choe, Michael Sung Pil;Je, Dong Wook;Nho, Woo Young;Kim, Seong Hun;Lee, Mi Jin;Ahn, Jae Yun;Moon, Sung Bae;Lee, Dong Eun;Park, Jung Bae
Journal of The Korean Society of Clinical Toxicology
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v.14
no.2
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pp.136-143
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2016
Purpose: In patients with altered mentality caused by drugs or unknown causes, ammonia is checked to facilitate differential diagnosis or diagnose hepatic coma. This helps early prevention and treatment of brain damage due to hyperammonemia. This study was conducted to evaluate clinical characteristics of intoxicated adult patients with hyperammonemia. Methods: We evaluated 95 patients with hyperammonemia among intoxicated patients above the age of 15 who visited our ED from January 2013 to December 2015. We analyzed the demographic characteristics and type of poisoning substance, reason for ingestion, toxicological characteristics such as elapsed time from ingestion to hospital visit, lab, clinical progression and complications. Data were evaluated using the student's t test or Mann-Whitney U test for continuous variables, and Chi-square test and Fisher's exact test for frequency analysis of categorical variables. Results: When compared to healthy individuals, patients with hyperammonemia showed statistical significance on their SOFA score (p=0.016) and poison severity score (p<0.001). Additionally, patients with hyperammonemia showed significantly different initial serum AST level (p=0.012) and maximum serum AST level during the hospital stay (p=0.026) when compared to healthy individuals. Moreover, individuals with sustained hyperammonemia compared to transient hyperammonemia showed clinically significant SOFA scores (p<0.001), poison severity scores (p=0.007), mortality rates in the ICU (p=0.021), as well as different duration of hospital stay (p=0.037), serum creatinine level (p=0.002), erythrocyte sedimentation rate (p=0.025), and serum myoglobin (p=0.015). Conclusion: Most poisoning-induced hyperammonemia cases were transient and recovered without special treatment. Therefore, hyperammonemia is almost non-specific among poisoning patients.
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