• Asia pacific journal of information systems
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• v.19 no.3
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• pp.51-67
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• 2009

Developing an agile recommender system for nomadic users has been regarded as a promising application in mobile and ubiquitous settings. To increase the quality of personalized recommendation in terms of accuracy and elapsed time, estimating future context of the user in a correct way is highly crucial. Traditionally, time series analysis and Makovian process have been adopted for such forecasting. However, these methods are not adequate in predicting context data, only because most of context data are represented as nominal scale. To resolve these limitations, the alignment-prediction algorithm has been suggested for context prediction, especially for future context from the low-level context. Recently, an ontological approach has been proposed for guided context prediction without context history. However, due to variety of context information, acquiring sufficient context prediction knowledge a priori is not easy in most of service domains. Hence, the purpose of this paper is to propose a novel context prediction methodology, which does not require a priori knowledge, and to increase accuracy and decrease elapsed time for service response. To do so, we have newly developed pattern-based context prediction approach. First of ail, a set of individual rules is derived from each context attribute using context history. Then a pattern consisted of results from reasoning individual rules, is developed for pattern learning. If at least one context property matches, say R, then regard the pattern as right. If the pattern is new, add right pattern, set the value of mismatched properties = 0, freq = 1 and w(R, 1). Otherwise, increase the frequency of the matched right pattern by 1 and then set w(R,freq). After finishing training, if the frequency is greater than a threshold value, then save the right pattern in knowledge base. On the other hand, if at least one context property matches, say W, then regard the pattern as wrong. If the pattern is new, modify the result into wrong answer, add right pattern, and set frequency to 1 and w(W, 1). Or, increase the matched wrong pattern's frequency by 1 and then set w(W, freq). After finishing training, if the frequency value is greater than a threshold level, then save the wrong pattern on the knowledge basis. Then, context prediction is performed with combinatorial rules as follows: first, identify current context. Second, find matched patterns from right patterns. If there is no pattern matched, then find a matching pattern from wrong patterns. If a matching pattern is not found, then choose one context property whose predictability is higher than that of any other properties. To show the feasibility of the methodology proposed in this paper, we collected actual context history from the travelers who had visited the largest amusement park in Korea. As a result, 400 context records were collected in 2009. Then we randomly selected 70% of the records as training data. The rest were selected as testing data. To examine the performance of the methodology, prediction accuracy and elapsed time were chosen as measures. We compared the performance with case-based reasoning and voting methods. Through a simulation test, we conclude that our methodology is clearly better than CBR and voting methods in terms of accuracy and elapsed time. This shows that the methodology is relatively valid and scalable. As a second round of the experiment, we compared a full model to a partial model. A full model indicates that right and wrong patterns are used for reasoning the future context. On the other hand, a partial model means that the reasoning is performed only with right patterns, which is generally adopted in the legacy alignment-prediction method. It turned out that a full model is better than a partial model in terms of the accuracy while partial model is better when considering elapsed time. As a last experiment, we took into our consideration potential privacy problems that might arise among the users. To mediate such concern, we excluded such context properties as date of tour and user profiles such as gender and age. The outcome shows that preserving privacy is endurable. Contributions of this paper are as follows: First, academically, we have improved sequential matching methods to predict accuracy and service time by considering individual rules of each context property and learning from wrong patterns. Second, the proposed method is found to be quite effective for privacy preserving applications, which are frequently required by B2C context-aware services; the privacy preserving system applying the proposed method successfully can also decrease elapsed time. Hence, the method is very practical in establishing privacy preserving context-aware services. Our future research issues taking into account some limitations in this paper can be summarized as follows. First, user acceptance or usability will be tested with actual users in order to prove the value of the prototype system. Second, we will apply the proposed method to more general application domains as this paper focused on tourism in amusement park.

• Korean Journal of Organic Agriculture
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• v.22 no.2
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• pp.303-319
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• 2014

The study researched germination of the plants and growth of experimented bacteria according to concentration of water extract in order to provide basic data for developing natural agricultural resources by using naturalized plants including Solidago altissima, Amaranthus retroflexus and Sida spinosa. As concentration of water extract increased, most of test plants showed a decrease in relative germinability. Sida spinosa(r=-0.540, p<0.01), Physalis wrightii(r=-0.693, p<0.01), Amaranthus retroflexu(r=-0.724, p<0.01), Solidago altissima(r=-0.728, p<0.01) and Eclipta prostrata(r=-0.779, p<0.01) showed tendency of decrease in relative germinative power in order, respectively. For average germination period, as concentration of the processed group increased, the time for germination increased (r = 0.769, p<0.01) and according to donor plants and test plants, there was a little difference. Also, as concentration of water extract of donor plant, length of above-aerial part(r=-0.587, p<0.01), length of underground part(r=-0.741, p<0.01), fresh weight(r=-0.574, p<0.01) and generation of root hair decreased. An then, for growth of test fungi according to concentration of water extract of donor plants, growths of Botrytis cinerea(r=-0.266, p<0.05), Diaporthe citri(r=-0.323 p<0.01), Colletotrichum gloeosporioides(r=-0.512, p<0.01), Pythiumultimum(r=-0.581, p<0.01) and Rhizoctonia solani(r=-0.806, p<0.01) were repressed in order, respectively. For total amount of content of phenol with herbicidal and Antifungal activities, S. altissima $17.3{\pm}0.5mg/g$, A. retroflexus $13.1{\pm}0.3mg/g$, P. wrightii $12.0{\pm}0.4mg/g$, S. spinosa $9.5{\pm}0.1mg/g$ and E. prostrata L. $4.1{\pm}0.1mg/g$ showed in order, respectively. As these results are summarized, donor plants which were naturalized, have competitive advantage because they release phenolic compounds with allelopathic effect and affect on germination, growth and fungi growth on underground flora compared to native plants and they have eligibility for natural herbicide and germicide.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

• Clinical and Experimental Pediatrics
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• v.49 no.6
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• pp.623-629
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• 2006

Purpose : The mortality rate of neonatal sepsis has been decreased, however, the incidence has not significantly decreased because of increased invasive procedures. This study was designed to make guidelines for choosing antibiotics by analyzing the causative microorganisms and their antibiotics sensitivity test according to the onset of neonatal sepsis. Methods : One hundred seven cases of culture proven sepsis in 89 patients admitted to the NICU of Chonnam University Hospital from Jan. 2000 to Dec. 2004, were enrolled. By reviewing the medical records, clinical data, laboratory findings, causative organisms and their antibiotics sensitivity, and mortality were analyzed. Results : The incidence of neonatal sepsis was 1.7 percent and more prevalent in premature and low birth weight infants. 85.4 percent of neonatal sepsis was late onset. Almost all microorganisms(92.9 percent) were gram-positive in early onset, however, two thirds were gram-positive and one third were gram-negative and Candida in late onset. Gram-negative organisms and Candida were more prevalent in patients who had central line. Gram-positive organisms were sensitive to vancomycin, teicoplanin, and gram-negative were sensitive to imipenem, and cefotaxime. Conclusion : Neonatal sepsis was more prevalent in premature and low birth weight infants. More than 90 percent were gram-positive in early onset, however, one third was gram-negative and Candida in late onset. The first choice of antibiotics were a combination of third generation cephalosporin and clindamycin in early onset, and third generation cephalosporin and glycopeptide in late onset. If there is no response to antibiotics treatment, the use of antifungal agents should be considered.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.127-132
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• 2010

Purpose: Because of limitation of image acquisition method and acquisition time, scatter correction cannot perform easily in SPECT study. But in our hospital, could provide to clinic doctor of scatter corrected images, through introduction of new generation gamma camera has function of simple scatter correction. Taking this opportunity, we will compare scatter corrected and non-scatter corrected image from image quality of point of view. Materials and Methods: We acquisite the 'Hoffman brain phantom' SPECT image and '1mm line phantom' SPECT image, each 18 times, with GE Infinia Hawkeye 4, SPECT-CT gamma camera. At first, we calculated each contrast from axial slice of scatter corrected and non-scatter corrected SPECT image of 'Hoffman brain phantom'. and next, calculated each FWHM of horizontal and vertical from axial slice of scatter corrected and non-scatter corrected SPECT image of '1mm line phantom'. After then, we attempted T test analysis with SAS program on data, contrast and resolution value of scatter corrected and non-scatter corrected image. Results: The contrast of scatter corrected image, elevated from 0.3979 to 0.3509. And the resolution of scatter corrected image, elevated from 3.4822 to 3.6375. p value were 0.0097 in contrast and <0.0001 in resolution. We knew the fact that do improve of contrast and resolution through scatter correction. Conclusion: We got the improved SPECT image through simple and easy way, scatter correct. We will expect to provide improved images, from contrast and resolution point of view. to our clinic doctor.

• The Journal of Korean Society for School & Community Health Education
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• v.6
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• pp.17-34
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• 2005

The purpose of this study was to examine the sex-consciousness and sexual values of school children by geographic region. It's specifically attempted to make a comparative analysis of sex-consciousness and sexual values between urban and rural elementary schoolers to help provide efficient sex education for them to build the right sexual values. The subjects in this study were 400 elementary schoolers in their sixth year of elementary schools located in Danyang-gun and Chungju city, north Chungcheong province. After a survey was conducted, answer sheets from 387 students that were analyzable were analyzed. For data handling, SPSS program was employed, and t-test was utilized to see if there's any differences between the urban and rural elementary school youngsters in sex consciousness and sexual values. And $x^2$ test was used to make a comparative analysis of their view of sex education. The findings of the study were as follows : First, regarding sex-consciousness, they had general knowledge on sex. Especially, they were highly aware of sexual violence and the generation of baby, but many of them didn't know about where and how egg cells were produced. This indicated that systematic education should be offered in various ways. Concerning geographic gap, there was a significant difference in sexual knowledge between the urban and rural students. As to sexual attitude, they took a relatively positive attitude toward display of affection or sex-related talk on TV or in movies, as they viewed it as natural. This finding implied that the elementary schoolers were recipient toward sex and took an active attitude toward sexual expressions. Concerning geographic gap, there was no difference between the rural and urban students. As for sexual practices, the largest group of the students had a liking for the opposite sex, which showed that their needs for sex were unveiled in the course of having some trouble due to the other sex rather than through firsthand experiences or activities. As to geographic gap, there was a significant difference between the urban and rural students in that regard. Besides, the urban students put their sex-consciousness in practice more often than the rural students did. After they are educated to build the right sexual values, systematic sex-education programs should also be offered for them to be exposed to sustained sex education and to team how to apply their sex-consciousness to real life. Second, as for sexual values, the school children had relatively positive and equalitarian sexual values. Regarding geographic gap, there were significant gaps between the two groups' view of the opposite sex, sexual roles and chastity. Concerning view of the opposite sex, they attached more importance to the inner aspects of the opposite sex than his or her look, and they wanted to date in a natural manner. Regarding sexual roles, they were relatively well cognizant of gender equity and the importance of male and female roles. As to view of chastity, they looked upon sex as natural, not as what's ugly or ashamed of. Third, concerning their outlook on sex education, approximately more than half the students felt the needs for sex education, and there was a significant difference between the urban and rural students. They wanted to receive education about the prevention of sexual violence and physical changes during puberty the most, and there was a significant gap between the urban and rural students in this aspect. As to the time for sex education, they thought that students should start to be exposed to sex education in their fifth or sixth year. This finding signified that fifth or sixth graders who were in the beginning of puberty started to have a lot of interest in their own physical changes. Therefore, sex education would produce better effects when it's provided to fifth or sixth graders. Nearly half them preferred single-gender class when they received sex education, and there's no gap between the urban and rural students in that regard.

• Journal of the Korean Wood Science and Technology
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• v.44 no.1
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• pp.19-29
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• 2016

The purpose of this study is to analyze the combustion and thermal properties in order to establish baseline data for the fire safety evaluation of imported wood. The combustion properties such as heat release rate, total heat release, gas yield, and mass loss were analyzed by the method of cone calorimeter test according to KS F ISO 5660-1 and thermogravimetric analysis (TGA). Analyzed species are five kinds of species as Merbau, Mempening, Garo Garo, Malas, and Dillenia. The heat released rate values showed the highest value of Malas as $375.52kW/m^2$, and Dillenia showed the lowest value as $133.30kW/m^2$. The data values were confirmed in the following order: Malas > Mempening > Garo Garo > Merbau > Dillenia. In case of the total heat release, it was measured in the following order: Mempening > Malas > Garo Garo > Merbau > Dillenia. The gas analysis results were that Dillenia showed the highest value of 0.034. Also, Mempening and Malas showed the lowest at 0.020 in the $CO/CO_2$. Min of mass reduction was shown as 74.79% Sargent cherry, on the other hand, Malas had a 83.52%. It showed a correlation between and of the CO and $CO_2$ generation and combustion characteristics of wood. The thermal decomposition temperature of the wood in the TGA were as follow that Merbau $348.07^{\circ}C$, Mempening $367.57^{\circ}C$, Garo Garo $350.59^{\circ}C$, Malas $352.41^{\circ}C$, Dillenia $364.33^{\circ}C$. The aim of this study is to determine the combustion properties of imported wood according to ISO 5660-1. And, based on the results of this study, we would proceed with further research for improving the fire safety of wood for construction.

• Asia Marketing Journal
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• v.12 no.2
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• pp.155-175
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• 2010

Most of the service industries including finance and telecommunications have become matured and saturated. The competitions have become severe while the differences among brands become smaller. Therefore maintaining good relationships with customers has been critical for the service providers. In case of credit card and debit card, the similar patterns are shown. It is important for them to maintain good relationships with customers, and therefore, they have used marketing program which provides customized services to customers and utilizes the membership programs. Not only do they build and maintain good relationships, but also highlight their brands from the emotional aspects. For example, KB Card or Hyundai Card uses well-known designers' works for their credit card design. As well, they differentiate the designs of credit cards to stress on their brand personalities. BC Card introduced the credit card with perfume that a customer would like. Even though the credit card is small and not shown to public easily, it becomes more important for those companies to touch the customers' feelings with the brand personalities and their images. This is partly because of changes in consumers' lifestyles. Y-generations becomes highly likely to express themselves in many different ways and more emotional than X-generations. For the Y-generations, therefore, even credit cards in the wallet should be personalized and well-designed. In line with it, credit cards with good design can be seen as an example of brand identity, where different design for each customer can be used to recognize the membership groups that customers want to belong. On the other hand, these credit card companies offer the special treatment benefits for those customers who are heavy users for the cards. For example, those customers who love sports will receive some special discounts when they use their credit cards for sports related products. Therefore this study attempted to explore the relationships between relational benefits, brand identification and loyalty. It has been well known that relational benefits and brand identification lead to loyalty independently from many other studies, but there has been few study to review all the three variables all together in a research model. Furthermore, as reviewed above, in the card industry, many companies attempt to associate the brand image with their products to fit their customers' lifestyles while relational benefits are still playing an important role for their business. Therefore in our research model, relational benefits, brand identification, and loyalty are all included. We focus on the mediating effect of brand identification. From the relational benefits perspective, only special treatment benefit and confidence benefit are included. Social benefit is not applicable for this credit card industry because not many cases of face-to-face interaction can be found. From the brand identification perspective, personal brand identity and social brand identity are reviewed and included in the model. Overall, the research model emphasizes that the relationships between relational benefits and loyalty will be mediated by the effect of brand identification. The effects of relational benefits which are confidence benefit and special treatment benefits on loyalty will be realized when they fit to the personal brand identity and social brand identity. In the research model, therefore, the relationships between confidence benefit and social brand identity, and between confidence benefit and personal identity are hypothesized while the effects of special treatment benefit on social brand identity and personal brand identity are hypothesized. Loyalty, then, is hypothesized to have positive relationships with personal brand identity and social brand identity. In addition, confidence benefit among the relational benefits is expected to have a direct, positive relationship with loyalty because confidence benefit has been recognized as a critical factor for good relationships and satisfaction. Data were collected from college students who have been using either credit cards or debit cards. College students were regarded good subjects because they are in Y-generation cohorts and have tendency to express themselves more. Total sample size was two hundred three at the beginning, but after deleting those data with many missing values, one hundred ninety-seven data points were remained and used for the model testing. Measurement items were brought from the previous literatures and modified for this research. To test the reliability, using SPSS 14, chronbach's α was examined and all the values were from .874 to .928 exceeding over .7. Using AMOS 7.0, confirmatory factor analysis was conducted to investigate the measurement model. The measurement model was found good fit with χ²(67)=188.388 (p= .000), GFI=.886, AGFI=.821, CFI=.941, RMSEA=.096. Using AMOS 7.0, structural equation modeling has been used to analyze the research model. Overall, the research model fit were χ²(68)=188.670 (p= .000), GFI=.886, AGFI=,824 CFI=.942, RMSEA=.095 indicating good fit. In details, all the paths hypothesized in the research model were found significant except for the path from social brand identity to loyalty. Personal brand identity leads to loyalty while both confidence benefit and special treatment benefit have a positive relationships with personal and social identities. As well, confidence benefit has a direct positive effect on loyalty. The results indicates the followings. First, personal brand identity plays an important role for credit/debit card usage. Therefore even for the products which are not shown to public easy, design and emotional aspect can be important to fit the customers' lifestyles. Second, confidence benefit and special treatment benefit have a positive effects on personal brand identity. Therefore it will be needed for marketers to associate the special treatment and trust and confidence benefits with personal image, personality and personal identity. Third, this study found again the importance of confidence and trust. However interestingly enough, social brand identity was not found to be significantly related to loyalty. It can be explained that the main sample of this study consists of college students. Those strategies to facilitate social brand identity are focused on high social status groups while college students have not been established their status yet.

• Journal of Sericultural and Entomological Science
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• v.36 no.1
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• pp.8-25
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• 1994

The study was conducted to obtain the genetic information on heterosis and combining ability of the quantitative characters for F1 hybrid breeding in silkworms. Six parental varieties and each set of 30 diallel crosses in F1's were used as materials, and bred on the randomized complete block design with three replications. Fourteen characters were observed with the twenty samples in each tray. The data were analyzed for (1) heterosis and combining ability in F1 hybrid. The heterosis in the weight and the length of cocoon showed positively high at 24.51%, and 23.4%, respectively and the weight of the whole cocoon as well as the weight of the whole cocoon layer showed a siginificant heterosis ranging from 15.56% to 15.71% and from 17.14% to 19.01%, but the fifth and the total instar period showed negative heterosis. It was found that the combination between, C70XRomogua and N9 X Romogua showed highly a negative heterosis on the fifth instar period and for the cocoon weight. The female of N9+Sansuian and the male of Romogua X Sansurian have a high heterosis effect, on the cocoon shell weight, and Sansurian X Romogua(reciprocal) on the length and the weight of cocoon filament with no regard to sexuality. The significant maternal and cytoplasmic effect on heterosis of the cocoon weight and the cocoon shell weight were observed with the combinations, N9 X C5, N63 X C70 and on the length of the cocoon filament with the combinations, Sansurian X N63, Sansurian X C5, Sansurian X C70 and N9 X C70, N63 X C70 on the weight of cocoon filament. As mean squared of GCA, SCA and RCA were significant with these combining ability for all characters resulted from additive and non-additive altogether and there is a significant difference between reciprocals. Sansurian showed a negative GCA effect on the fifth and total larval duration, but the higher positive GCA effects took places with varieties N9 and C5 on the length, width, weight of cocoon, cocoon shell weight, percentage of cocoon shell weight, length and weight of cocoon filament, percentage of raw-silk with no regard to both generations and silkworm sexuality. The values of SCA between the cross combinations varied generation-wise and sex-wise. It was shown that SCA value for the fifth instar period was highly negative for Sansurian X C70, Romogua X C70, Sansurian X C5, Romogua X C5, but it was positive effect on the cocoon weight, cocoon shell weight with N9 X C5, and C70 X Sansurian, on the length of cocoon filament with N9 X C5, Romogua X Sansurian on the weight of cocoon filament between Romogua and N63 and on the percentage of raw-silk between the combination of Sansurian X Romoga.