• Asia pacific journal of information systems
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• v.19 no.2
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• pp.117-137
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• 2009

Recently, intelligent traffic information systems have enabled people to forecast traffic conditions before hitting the road. These convenient systems operate on the basis of data reflecting current road and traffic conditions as well as distance-based data between locations. Thanks to the rapid development of ubiquitous computing, tremendous context data have become readily available making vehicle route planning easier than ever. Previous research in relation to optimization of vehicle route planning merely focused on finding the optimal distance between locations. Contexts reflecting the road and traffic conditions were then not seriously treated as a way to resolve the optimal routing problems based on distance-based route planning, because this kind of information does not have much significant impact on traffic routing until a a complex traffic situation arises. Further, it was also not easy to take into full account the traffic contexts for resolving optimal routing problems because predicting the dynamic traffic situations was regarded a daunting task. However, with rapid increase in traffic complexity the importance of developing contexts reflecting data related to moving costs has emerged. Hence, this research proposes a framework designed to resolve an optimal route planning problem by taking full account of additional moving cost such as road traffic cost and weather cost, among others. Recent technological development particularly in the ubiquitous computing environment has facilitated the collection of such data. This framework is based on the contexts of time, traffic, and environment, which addresses the following issues. First, we clarify and classify the diverse contexts that affect a vehicle's velocity and estimates the optimization of moving cost based on dynamic programming that accounts for the context cost according to the variance of contexts. Second, the velocity reduction rate is applied to find the optimal route (shortest path) using the context data on the current traffic condition. The velocity reduction rate infers to the degree of possible velocity including moving vehicles' considerable road and traffic contexts, indicating the statistical or experimental data. Knowledge generated in this papercan be referenced by several organizations which deal with road and traffic data. Third, in experimentation, we evaluate the effectiveness of the proposed context-based optimal route (shortest path) between locations by comparing it to the previously used distance-based shortest path. A vehicles' optimal route might change due to its diverse velocity caused by unexpected but potential dynamic situations depending on the road condition. This study includes such context variables as 'road congestion', 'work', 'accident', and 'weather' which can alter the traffic condition. The contexts can affect moving vehicle's velocity on the road. Since these context variables except for 'weather' are related to road conditions, relevant data were provided by the Korea Expressway Corporation. The 'weather'-related data were attained from the Korea Meteorological Administration. The aware contexts are classified contexts causing reduction of vehicles' velocity which determines the velocity reduction rate. To find the optimal route (shortest path), we introduced the velocity reduction rate in the context for calculating a vehicle's velocity reflecting composite contexts when one event synchronizes with another. We then proposed a context-based optimal route (shortest path) algorithm based on the dynamic programming. The algorithm is composed of three steps. In the first initialization step, departure and destination locations are given, and the path step is initialized as 0. In the second step, moving costs including composite contexts into account between locations on path are estimated using the velocity reduction rate by context as increasing path steps. In the third step, the optimal route (shortest path) is retrieved through back-tracking. In the provided research model, we designed a framework to account for context awareness, moving cost estimation (taking both composite and single contexts into account), and optimal route (shortest path) algorithm (based on dynamic programming). Through illustrative experimentation using the Wilcoxon signed rank test, we proved that context-based route planning is much more effective than distance-based route planning., In addition, we found that the optimal solution (shortest paths) through the distance-based route planning might not be optimized in real situation because road condition is very dynamic and unpredictable while affecting most vehicles' moving costs. For further study, while more information is needed for a more accurate estimation of moving vehicles' costs, this study still stands viable in the applications to reduce moving costs by effective route planning. For instance, it could be applied to deliverers' decision making to enhance their decision satisfaction when they meet unpredictable dynamic situations in moving vehicles on the road. Overall, we conclude that taking into account the contexts as a part of costs is a meaningful and sensible approach to in resolving the optimal route problem.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.4
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• pp.467-475
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• 2015

Improvement for carcass traits related to beef quality is the key concern in beef production. Recent reports found that epigenetics mediates the interaction of individuals with environment and nutrition. The present study was designed to analyze the genetic effect of single nucleotide polymorphisms (SNPs) in seven epigenetic-related genes (DNMT1, DNMT3a, DNMT3b, DNMT3L, Ago1, Ago2, and HDAC5) and two meat quality candidate genes (CAPN1 and PRKAG3) on fourteen carcass traits related to beef quality in a Snow Dragon beef population, and also to identify SNPs in a total of fourteen cattle populations. Sixteen SNPs were identified and genotyped in 383 individuals sampled from the 14 cattle breeds, which included 147 samples from the Snow Dragon beef population. Data analysis showed significant association of 8 SNPs within 4 genes related to carcass and/or meat quality traits in the beef populations. SNP1 (13154420A>G) in exon 17 of DNMT1 was significantly associated with rib-eye width and lean meat color score (p<0.05). A novel SNP (SNP4, 76198537A>G) of DNMT3a was significantly associated with six beef quality traits. Those individuals with the wild-type genotype AA of DNMT3a showed an increase in carcass weight, chilled carcass weight, flank thicknesses, chuck short rib thickness, chuck short rib score and in chuck flap weight in contrast to the GG genotype. Five out of six SNPs in DNMT3b gene were significantly associated with three beef quality traits. SNP15 (45219258C>T) in CAPN1 was significantly associated with chuck short rib thickness and lean meat color score (p<0.05). The significant effect of SNP15 on lean meat color score individually and in combination with each of other 14 SNPs qualify this SNP to be used as potential marker for improving the trait. In addition, the frequencies of most wild-type alleles were higher than those of the mutant alleles in the native and foreign cattle breeds. Seven SNPs were identified in the epigenetic-related genes. The SNP15 in CAPN1 could be used as a powerful genetic marker in selection programs for beef quality improvement in the Snow Dragon Beef population.

• KSBB Journal
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• v.29 no.4
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• pp.285-296
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• 2014

Although the problems of the algal blooms have been world-widely observed in freshwater, estuary, and marine throughout the year, it is not yet certain what are the basic causes of such blooms. Consequently, it is very difficult to predict when and where algal blooms occur. The constituents of the Asian dust are in a good agreement with the elements required for the algal growth, which suggests some possible relationship between the algal blooms and the Asian dust. There have been frequently algal blooms in drinking water from rivers or lakes. However, there is no any algal blooms in upwelling waters where the Asian dust cannot penetrate into the soil due to its relatively weak settling velocity (size of particles, $4.5{\pm}1.5{\mu}m$), which implies the possible close relationship of the Asian dust with algal blooms. The present initiative study is thus intended firstly in Korea to illustrate such a relationship by reviewing typical previous studies along with 12 years of weekly iron profiles (2001~2012) and two slant culture experiments with the dissolved Asian dust. The result showed bacterial suspected colonies in the slant culture experiment that are qualitatively in a good agreement with the recent Japanese studies. Since the diatoms require cheap energy (8%) compared to other phytoplankton (100%) to synthesize their cell walls by silicate, the present results can be used to predict algal blooms by diatoms if the concentrations of iron and silicate are available during spring and fall. It can be postulated that the algal blooms occur only if the environmental factors such as light, nutrients, calm water surface layer, temperature, and pH are simultaneously satisfied with the requirements of the micronutrients of mineral ions supplied by the Asian dust as enzymatic cofactors for the rapid bio-synthesis of the macromolecules during algal blooms. Simple eco-friendly methods to regulate the algal blooms are suggested for the initial stage of blooming with limited area: 1) to cover up the water surface with black curtain and inhibit photosynthesis during the day time, 2) to blow air (20.9%) or pure oxygen into the bottom of the water and inhibit rubisco for carbon uptake and nitrate reductase for nitrogen uptake activities in algal growth during the night, 3) to eliminate the resting spores or cysts by suction of bottom sediments as deep as 5 cm to prevent the next year germinations.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.18 no.6
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• pp.519-528
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• 1985

Fillets of mackerel (Scomber japonicus) and flounder (Xystrias grigorjewi) which, are representatives in red fleshed fish and white fleshed fish, respectively, were freeze-dried and stored in tightly sealed containers which were controlled to different relative humidity at $25^{\circ}C$. The changes of lipids were examined periodically by measuring the peroxide value (POV), the thiobarbituric acid (TBA) and the acid value (AV). And the fatty acid composition of lipids was investigated by gas-liquid chromatography (GLC). The results obtained are summarized as foollows: From the changes of POV and TBA value during storage, the oxidation of lipids was distinct at the lower relative humidities, $0\%\;and\;23\%$, while inhibited at the higher relative humidities, $52\%\;and\;81\%$. The changes in acid value during storage were more prominent at the hifger relative himidites than at the lower relative humidities. The content of $C_{16:0},\;C_{18:0}\;and\;C_{22:6}$ acids in the fatty acid composition of total lipids was abundant in both fleshed fishes. The content of $C_{18:1}$ acid in the nonpolar lipid and that of $C_{16:0}$ acid in the polar lipid were higher than other fatty acids. In the fatty acid composition of total lipids during storage, polyenoic acids decreased with storage period at $0\%\;and\;23\%$ relative humidities, while the fatty acid composition didn't show a great change at $52\%\;and\;81\%$ relative humidities. In the non-polar lipid, polyenoic acids coherently decreased under all the conditions of relative humidities but the saturated acids and the monoenoic acids increased. In the polar lipid, polyenoic acids decreased at $0\%\;and\;23\%$ relative humidities, while the saturated acids and monoenoic acids decreased at $52\%\;and\;81\%$ relative humidities. On the other hand, the oxidation of lipids was more significant in mackerel than in the flounder, and the changes of fatty acid composition were shown a similar pattern.

• Asia pacific journal of information systems
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• v.17 no.2
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• pp.123-137
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• 2007

The advent of the Internet and related Web technologies has created an easily accessible link between a firm and its customers, and has provided opportunities to a firm to use information technology to support supplementary after-sale services associated with a product or service. It has been widely recognized that supplementary services are an important source of customer value and of competitive advantage as the characteristics of the product itself. Many of these supplementary services are information-based and need not be co-located with the product, so more and more companies are delivering these services electronically. Net-based customer service, which is defined as an Internet-based computerized information system that delivers services to a customer, therefore, is the core infrastructure for supplementary service provision. The importance of net-based customer service in delivering supplementary after-sale services associated with product has been well documented. The strategic advantages of well-implemented net-based customer service are enhanced customer loyalty and higher lock-in of customers, and a resulting reduction in competition and the consequent increase in profits. However, not all customers utilize such net-based customer service. The digital divide is the phenomenon in our society that captures the observation that not all customers have equal access to computers. Socioeconomic factors such as race, gender, and education level are strongly related to Internet accessibility and ability to use. This is due to the differences in the ability to bear the cost of a computer, and the differences in self-efficacy in the use of a technology, among other reasons. This concept, applied to e-commerce, has been called the "e-commerce divide." High Internet penetration is not eradicating the digital divide and e-commerce divide as one would hope. Besides, to accommodate personalized support, a customer must often provide personal information to the firm. This personal information includes not only name and address, but also preferences information and perhaps valuation information. However, many recent studies show that consumers may not be willing to share information about themselves due to concerns about privacy online. Due to the e-commerce divide, and due to privacy and security concerns of the customer for sharing personal information with firms, limited numbers of customers adopt net-based customer service. The limited level of customer adoption of net-based customer service affects the firm profits and the customers' welfare. We use a game-theoretic model in which we model the net-based customer service system as a mechanism to enhance customers' loyalty. We model a market entry scenario where a firm (the incumbent) uses the net-based customer service system in inducing loyalty in its customer base. The firm sells one product through the traditional retailing channels and at a price set for these channels. Another firm (the entrant) enters the market, and having observed the price of the incumbent firm (and after deducing the loyalty levels in the customer base), chooses its price. The profits of the firms and the surplus of the two customers segments (the segment that utilizes net-based customer service and the segment that does not) are analyzed in the Stackelberg leader-follower model of competition between the firms. We find that an increase in adoption of net-based customer service by the customer base is not always desirable for firms. With low effectiveness in enhancing customer loyalty, firms prefer a high level of customer adoption of net-based customer service, because an increase in adoption rate decreases competition and increases profits. A firm in an industry where net-based customer service is highly effective loyalty mechanism, on the other hand, prefers a low level of adoption by customers.

• Journal of Life Science
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• v.22 no.8
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• pp.1099-1106
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• 2012

The cytotoxicity of the colorant in conjugated linoleic acid (CLA) was investigated in human cancer cell lines and a normal human cell line. Commercially-available CLA with a brown color (designate crude CLA; c-CLA) was distilled in a vacuum (10 mmHg-$220^{\circ}C$, 10 mmHg-$235^{\circ}C$, 10 mmHg-$240^{\circ}C$, and 20 mmHg-$260^{\circ}C$) for 30 min to obtain pure CLA (distilled CLA; d-CLA) and dark brown-colored CLA (residual CLA; r-CLA) samples. No color intensity was shown in the d-CLA sample obtained under 10 mmHg-$220^{\circ}C$ conditions of distillation when the L (brightness), a (red/blue), and b (yellow/green) parameters were analyzed, whereas the r-CLA sample showed a dark brown color. The composition of CLA isomers in both the d- and r-CLA samples, as compared to that of the c-CLA sample, was not significantly different when analyzed by gas chromatography. When the cytotoxicity of the r-CLA and d-CLA samples obtained under 10 mmHg-$220^{\circ}C$ conditions were compared against human breast cancer cells (MCF-7), human lung cancer cells (A-549), human colon cancer cells (HT-29), human prostate cancer cells (PC-3), and human neuroblastoma cells (SK-N-SH), no significant cytotoxicity was seen in the cell lines. These results suggest that the color or colorant in the CLA samples did not have any effects on the proliferation of human cancer and normal cells and imply that the colorant in commercially available CLA samples is safe for human consumption.

• Korean journal of food and cookery science
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• v.15 no.6
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• pp.555-564
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• 1999

The objective of this study was to investigate the preference of root vegetables and the inhibitory effect of the vegetables on harmful enzymes of intestinal bacteria. Two hundred fifty respondents in Seoul area surveyed to obtain information from Sep. 30 to Oct. 30, 1998. Respondents preferred Inpuomoea batatas (sweet potato, 4.05), Solanum tuberosum(potato, 3.97), Allium cepa(onion, 3.68), Codonopsis lanceolata(3.64) and Raponus sativus(redish, 3.60). The growth of B. breve K-110 was effectively increased by adding 0.5% extract of Solanum tuberosum(139%), Codonopsis lamceolate(145%), Dioscorea japonica(164%), Colocisia antiquorum(144%) extract to the medium. B. breve K-100 for beneficial bacteria, and E. coli HGU-3 or Bacteroides JY-6 for harmful bacteria were used to determine the inhibitory effect of root vegetables on harmful intestinal enzymes after co-culturing harmful and beneficial bacteria. The extract of Solanum tuberosum, Codonopsis lanceolata, Dioscorea japonica (yam) and Colocisia antiquorum (taroes) showed inhibitory effect on ${\beta}$-glucuronidase and tryptophanase of intestinal bacteria. The macromolecules were isolated from Solanum tuberosum, Codonopsis lanceolata, Dioscorea japonica and Colocisia antiquorum by Sephadex G-100 column chromatography. By adding these isolated marcromolecules to the medium, the growth of B. breve K-100 were also increased and high inhibitory effects on the ${\beta}$-glucuronidase and tryptophanase were measured. These results suggested that the harmful enzymes of intestinal bacteria were inhibited by consuming Solanum tuberosum, Codonopsis lanceolata, Dioscorea japonica and Colocisia antiquorum. Therefore, they could prevent gastrointestinal diseases.

• Korean Journal of Poultry Science
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• v.30 no.4
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• pp.275-280
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• 2003

This study conducted to investigate the effect of dietary germanium biotite by protein level in laying hen diets. One hundred forty four, 51 weeks old ISA brown commercial layer, were used in experiment. Dietary treatments were 1) low protein diet(LPD), 2) high protein diet(HPD), 3) LPD-GB(LPD + 1.0% germanium biotite) and 4) HPD-GB(HPD + 1.0% germanium biotite). Henday egg production tended to be increased as the concentration of protein in diets increased with significant difference(P<0.01). Egg weight tended to decrease by increasing of supplementation germanium biotite in the diets(P<0.01). Egg shell breaking strength was not influenced by germanium biotite supplementation(P>0.05). Large band of egg decrease as increasing of supplementation germanium biotite in the diets(P<0.02). Sharp and middle band of egg were not influenced by germanium biotite supplementation. Egg yolk index tended to decrease as increasing of supplementation germanium biotite in the diets(p<0.01). Fecal propionic acid(P<0.01) and butyric acid(P<0.03) were decrease as the concentration of germanium biotite in the diet was increased. Also, butyric acid increased as the concentration of protein in diets increased with significant difference(P<0.02). Supplementation germanium biotite in the diet reduced the fecal acetic acid(P<0.01). Fecal $NH_3$-N of hens fed HPD-GB diet was decreased(P<0.05) compared to that LPD-GB diet. In conclusion, germanium biotite supplementation to layer diets can reduce fecal volatile fatty acid compabebts.

• Korean Journal of Soil Science and Fertilizer
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• v.11 no.2
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• pp.89-95
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• 1979

A field experiment was conducted to investigate the effects of season of application and particle-size distribution of silicate fertilizer on rice yields of Indica type, Milyang 23 and Japonica type Jinheung. The application of silicate fertilizer at the rate of 250kg per 10a increased greatly rice yields. Rice yields were a little higher when silicate fertilizer was applied at transplanting time (Spring application) than applied in Autumn of preceding year (Autumn application) and increased with increasing content of fine particles of silicate fertilizer. However, the difference in effects between the season of application was insignificant and the silicate fertilizer of particles to pass by 100% through a 8 mesh sieve and by 60% through a 25 mesh sieve, 8-25(60%) was as effective as the one to meet silicate fertilizer specifications, 10-28(60%). Silica content of plant samples did not show any significant effects of season of application and particle-size distribution of silicate fertilizer, whereas samples taken at 50 days after tran planting showed significant effects of season of application and particle-size distribution. Silica content of straw of Jinheung was highest when 8-25(60%) was applied. Silica content of soils before the experiment was 36.7 ppm and the content increased to range of 159.5-273.8 ppm and 80.3-134.4 ppm in the plots of Spring application and Autumn application respectively.