• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1041-1043
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• 1993

Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)＋dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].

• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.516-521
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• 2004

Background: Radioactive iodine (RAI) therapy and whole-body scanning are the fundamentals of treatment and follow-up of patients with differentiated thyroid cancer. It is generally accepted that a Thyroid-Stimulating Hormone (TSH) level of at least 30 ${\mu}U/ml$ is a prerequisite for the effective use of RAI, and that it requires 4-6 weeks of off-thyroxine to attain these levels. Because thyroxine withdrawal and the consequent hypothyroidism are often poorly tolerated, and occasionally might be hazardous, it is important to be certain that these assumptions are correct. We have measured serial changes in serum TSH after total thyroidectomy or withdrawl of thyroxine in patients with thyroid cancer. Subjects and Methods: Serum TSH levels were measured weekly after thyroidectomy in 10 patients (group A) and after the discontinuation of thyroxine in 12 patients (group B). Symptoms and signs of hypothyroidism were also evaluated weekly by modified Billewicz diagnostic index. Results: By the second week, 78% of group A patients and 17% of group B patients had serum TSH levels ${\geq}30{\mu}U/ml$. By the third week, 89% of group A patients and 90% of group B patients had serum TSH levels ${\geq}30{\mu}U/ml$. By the fourth week, all patients in two groups achieved target TSH levels and there were no overt hypothyroidism. Conclusion: in all patients, serum TSH elevated to the target concentration (${\geq}30{\mu}U/ml$) within 4 weeks without significant manifestation of hypothyroidism. The schedule of RAI administration could be adjusted to fit the needs and circumstances of individual patients with a shorter preparation period than the conventional.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.29-44
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• 2017

In Internet commerce, consumers are heavily influenced by product reviews written by other users who have already purchased the product. However, as the product reviews accumulate, it takes a lot of time and effort for consumers to individually check the massive number of product reviews. Moreover, product reviews that are written carelessly actually inconvenience consumers. Thus many online vendors provide mechanisms to identify reviews that customers perceive as most helpful (Cao et al. 2011; Mudambi and Schuff 2010). For example, some online retailers, such as Amazon.com and TripAdvisor, allow users to rate the helpfulness of each review, and use this feedback information to rank and re-order them. However, many reviews have only a few feedbacks or no feedback at all, thus making it hard to identify their helpfulness. Also, it takes time to accumulate feedbacks, thus the newly authored reviews do not have enough ones. For example, only 20% of the reviews in Amazon Review Dataset (Mcauley and Leskovec, 2013) have more than 5 reviews (Yan et al, 2014). The purpose of this study is to analyze the factors affecting the usefulness of online product reviews and to derive a forecasting model that selectively provides product reviews that can be helpful to consumers. In order to do this, we extracted the various linguistic, psychological, and perceptual elements included in product reviews by using text-mining techniques and identifying the determinants among these elements that affect the usability of product reviews. In particular, considering that the characteristics of the product reviews and determinants of usability for apparel products (which are experiential products) and electronic products (which are search goods) can differ, the characteristics of the product reviews were compared within each product group and the determinants were established for each. This study used 7,498 apparel product reviews and 106,962 electronic product reviews from Amazon.com. In order to understand a review text, we first extract linguistic and psychological characteristics from review texts such as a word count, the level of emotional tone and analytical thinking embedded in review text using widely adopted text analysis software LIWC (Linguistic Inquiry and Word Count). After then, we explore the descriptive statistics of review text for each category and statistically compare their differences using t-test. Lastly, we regression analysis using the data mining software RapidMiner to find out determinant factors. As a result of comparing and analyzing product review characteristics of electronic products and apparel products, it was found that reviewers used more words as well as longer sentences when writing product reviews for electronic products. As for the content characteristics of the product reviews, it was found that these reviews included many analytic words, carried more clout, and related to the cognitive processes (CogProc) more so than the apparel product reviews, in addition to including many words expressing negative emotions (NegEmo). On the other hand, the apparel product reviews included more personal, authentic, positive emotions (PosEmo) and perceptual processes (Percept) compared to the electronic product reviews. Next, we analyzed the determinants toward the usefulness of the product reviews between the two product groups. As a result, it was found that product reviews with high product ratings from reviewers in both product groups that were perceived as being useful contained a larger number of total words, many expressions involving perceptual processes, and fewer negative emotions. In addition, apparel product reviews with a large number of comparative expressions, a low expertise index, and concise content with fewer words in each sentence were perceived to be useful. In the case of electronic product reviews, those that were analytical with a high expertise index, along with containing many authentic expressions, cognitive processes, and positive emotions (PosEmo) were perceived to be useful. These findings are expected to help consumers effectively identify useful product reviews in the future.

• Journal of agricultural medicine and community health
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• v.28 no.2
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• pp.15-29
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• 2003

Objectives: This study was done to find out fatigue and self-reported physical symptoms of Vinylhouse farmers. The results of this study could be used as a basic data to develop health promotion program for Vinylhouse farmers who are suffering from fatigue and physical symptoms. Methods: The 166 respondents, who were working in Vinylhouse and were living in a remoted area where the primary health post located, were participated in this study. Thirty: 30 items of self-reported fatigue scale was used to evaluate the farmers fatigue level which made by Japanese industrial and hygenic association(1988). Twenty four: 24 items of index used by researcher for self-reported physical symptoms was from Lee In Bae's(1999) modified Index which was originated from Cornell Medical Index(1949). Another questionnaires used in this study were developed by researcher through related documents. Results: The results of this study were as follows; Fatigue scores were high in accordance with women(t=-2.212, p<0.05), worse recognized health state(F=20.610, p<.001), lack of sleeping hours(F=3.937, p<0.05), eat irregularly(t=-3.883, p<0.001), don't take a bath after application of chemical(t=-2.950, p<0.01), working time per a day(F=5.633, p<0.01) & working time per a day in Vinylhouse(F=5.247, p<0.01) were long. Subjective physical symptoms were high in accordance with women(t=-3.176, p<0.01), worse recognized health state(F=35.335, p<0.001), and low education(F=3.467, p<0.05). eat irregularly(t=-3.384, p<0.01), alcohol drinking(t=-2.389, p<0.05). When farmers don't take a bath after application of chemical show high(t=-3.188, p<0.01). As a result, the factors affecting to Vinylhouse worker's health were irregular diet habit, scarce exercise, lack of proper rest, symptoms oriented from Vinylhouse work in contaminated environment with high temperature and humidity. Conclusions: Based on this study, health promotion program is necessary for Vinylhouse workers. Also, the development of continuously practical strategy of healthy life style including exercise and comprehensive health promotion program considered the country's social and cultural background are needed.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.12
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• pp.1589-1598
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• 2008

The objective of this study was to investigate the effect of obesity on health by analyzing the factors which are related to obesity through the questionnaires on the dietary pattern, nutrient intake and physical measurements. The subjects, 419 college women aged 20 to 24 year-old, were randomly selected from Seoul and data were collected during March to May, 2008 and classified as under underweight, normal weight, and obesity groups according to BMI. However, weight, skeletal muscle mass, body fat mass, fat free mass, percentage of body fat, and waist to hip ratio showed significant differences among all the groups (p<0.05). In the obese group, 77.8% ate fat-rich foods such as galbi and samgyopsal more than two times per week, 66.7% ate vegetables other than kimchi (p<0.05) as compared to the underweight and normal groups by mini dietary assessment (p<0.05). The cholesterol intakes of the underweight, normal weight, and obese groups were $164.67{\pm}114.52mg/dL$, $143.31{\pm}99.58mg/dL$, and $121.92{\pm}54.91mg/dL$, respectively, and the obese group had a significantly lower intake than the other groups (p<0.05). The serum total cholesterol levels of the underweight, normal, and obese groups were $177.04{\pm}26.36mg/dL$, $189.46{\pm}29.05mg/dL$, and $170.00{\pm}12.75mg/dL$, respectively, and the obese group showed lower total cholesterol level than the other groups (p<0.05). The triacylglycerol level of the obese group ($132.00{\pm}64.60mg/dL$) was significantly higher than the other two groups (p<0.05). The HDL-cholesterol levels of the underweight, normal weight, and obese groups were $51.92{\pm}9.39mg/dL$, $59.20{\pm}13.53mg/dL$, and $43.00{\pm}8.98mg/dL$, respectively, showing that the obese subjects had significantly lower HDL-cholesterol levels as compared to the subjects in the other groups (p<0.05). The HDL-C/LDL-C ratios of the underweight ($0.52{\pm}0.45$) and normal weight ($0.59{\pm}0.23$) groups were higher than the ratio of the obese group ($0.41{\pm}0.06$). Total cholesterol were positively correlated with LDL-cholesterol (r=0.768, p<0.01), but triacylglycerol were adversely correlated with HDL-cholesterol. In conclusion, our results show that college-aged women in Seoul should be encouraged to amend their overall dietary habits, make a dietary plan that fits their individual needs, and maintain an effective exercise schedule.

• The Journal of Small Business Innovation
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• v.19 no.4
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• pp.19-39
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• 2016

With increasing adoption of smart products and complexity, companies have shifted their strategies from stand alone and competitive strategies to business ecosystem oriented and cooperative strategies. The win-win growth of business refers to corporate efforts undertaken by companies to pursue the healthiness of business between conglomerates and partnering companies such as suppliers for mutual prosperity and a long-term corporate soundness based on their business ecosystem and cooperative strategies. This study is designed to validate a theoretical proposition that the win-win growth strategy of Samsung Electronics and cooperative efforts among companies can create a healthy business ecosystem, based on results of case studies and surveys. In this study, a level of global market access of small and mid-sized companies is adopted as the key achievement index. The foreign market entry is considered as one of vulnerabilities in the ecosystem of small and mid-sized enterprises (SMEs). For SMEs, the global market access based on the research and development (R&D) has become the critical component in the process of transforming them into global small giants. The results of case studies and surveys are analyzed mainly based on a model of a virtuous cycle of Creativity, Opportunity, Productivity, and Proactivity (the COPP model) that features the characteristics of the healthiness of a business ecosystem. In the COPP model, a virtuous circle of profits made by the first three factors and Proactivity, which is the manifestation of entrepreneurship that proactively invests and reacts to the changing business environment of the future, enhances the healthiness of a given business ecosystem. With the application of the COPP model, this study finds major achievements of the win-win growth of Samsung Electronics as follows. First, Opportunity plays a role as a parameter in the relations of Creativity, Productivity, and creating profits. Namely, as companies export more (with more Opportunity), they are more likely to link their R&D efforts to Productivity and profitability. However, companies that do not export tend to fail to link their R&D investment to profitability. Second, this study finds that companies with huge investment on R&D for the future, which is the result of Proactivity, tend to hold a large number of patents (Creativity). And companies with significant numbers of patents tend to be large exporters as well (Opportunity), and companies with a large amount of exports tend to record high profitability (Productivity and profitability), and thus forms the virtuous cycle of the COPP model. In addition, to access global markets for sustainable growth, SMEs need to build and strengthen their competitiveness. This study concludes that companies with a high level of proactivity to invest for the future can create a virtuous circle of Creativity, Opportunity, Productivity, and Proactivity, thereby providing a strategic implication that SMEs should invest time and resources in forming such a virtuous cycle which is a sure way for the SMEs to grow into global small giants.

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.245-276
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• 2008

Brand equity is one of the most important concepts in business practice as well as in academic research. Successful brands can allow marketers to gain competitive advantage (Lassar et al.,1995), including the opportunity for successful extensions, resilience against competitors' promotional pressures, and the ability to create barriers to competitive entry (Farquhar, 1989). Branding plays a special role in service firms because strong brands increase trust in intangible products (Berry, 2000), enabling customers to better visualize and understand them. They reduce customers' perceived monetary, social, and safety risks in buying services, which are obstacles to evaluating a service correctly before purchase. Also, a high level of brand equity increases consumer satisfaction, repurchasing intent, and degree of loyalty. Brand equity can be considered as a mixture that includes both financial assets and relationships. Actually, brand equity can be viewed as the value added to the product (Keller, 1993), or the perceived value of the product in consumers' minds. Mahajan et al. (1990) claim that customer-based brand equity can be measured by the level of consumers' perceptions. Several researchers discuss brand equity based on two dimensions: consumer perception and consumer behavior. Aaker (1991) suggests measuring brand equity through price premium, loyalty, perceived quality, and brand associations. Viewing brand equity as the consumer's behavior toward a brand, Keller (1993) proposes similar dimensions: brand awareness and brand knowledge. Thus, past studies tend to identify brand equity as a multidimensional construct consisted of brand loyalty, brand awareness, brand knowledge, customer satisfaction, perceived equity, brand associations, and other proprietary assets (Aaker, 1991, 1996; Blackston, 1995; Cobb-Walgren et al., 1995; Na, 1995). Other studies tend to regard brand equity and other brand assets, such as brand knowledge, brand awareness, brand image, brand loyalty, perceived quality, and so on, as independent but related constructs (Keller, 1993; Kirmani and Zeithaml, 1993). Walters(1978) defined information search as, "A psychological or physical action a consumer takes in order to acquire information about a product or store." But, each consumer has different methods for informationsearch. There are two methods of information search, internal and external search. Internal search is, "Search of information already saved in the memory of the individual consumer"(Engel, Blackwell, 1982) which is, "memory of a previous purchase experience or information from a previous search."(Beales, Mazis, Salop, and Staelin, 1981). External search is "A completely voluntary decision made in order to obtain new information"(Engel & Blackwell, 1982) which is, "Actions of a consumer to acquire necessary information by such methods as intentionally exposing oneself to advertisements, taking to friends or family or visiting a store."(Beales, Mazis, Salop, and Staelin, 1981). There are many sources for consumers' information search including advertisement sources such as the internet, radio, television, newspapers and magazines, information supplied by businesses such as sales people, packaging and in-store information, consumer sources such as family, friends and colleagues, and mass media sources such as consumer protection agencies, government agencies and mass media sources. Understanding consumers' purchasing behavior is a key factor of a firm to attract and retain customers and improving the firm's prospects for survival and growth, and enhancing shareholder's value. Therefore, marketers should understand consumer as individual and market segment. One theory of consumer behavior supports the belief that individuals are rational. Individuals think and move through stages when making a purchase decision. This means that rational thinkers have led to the identification of a consumer buying decision process. This decision process with its different levels of involvement and influencing factors has been widely accepted and is fundamental to the understanding purchase intention represent to what consumers think they will buy. Brand equity is not only companies but also very important asset more than product itself. This paper studies brand equity model and influencing factors including information process such as information searching and information resources in the fashion market in Asia and Europe. Information searching and information resources are influencing brand knowledge that influences consumers purchase decision. Nine research hypotheses are drawn to test the relationships among antecedents of brand equity and purchase intention and relationships among brand knowledge, brand value, brand attitude, and brand loyalty. H1. Information searching influences brand knowledge positively. H2. Information sources influence brand knowledge positively. H3. Brand knowledge influences brand attitude. H4. Brand knowledge influences brand value. H5. Brand attitude influences brand loyalty. H6. Brand attitude influences brand value. H7. Brand loyalty influences purchase intention. H8. Brand value influence purchase intention. H9. There will be the same research model in Asia and Europe. We performed structural equation model analysis in order to test hypotheses suggested in this study. The model fitting index of the research model in Asia was $X^2$=195.19(p=0.0), NFI=0.90, NNFI=0.87, CFI=0.90, GFI=0.90, RMR=0.083, AGFI=0.85, which means the model fitting of the model is good enough. In Europe, it was $X^2$=133.25(p=0.0), NFI=0.81, NNFI=0.85, CFI=0.89, GFI=0.90, RMR=0.073, AGFI=0.85, which means the model fitting of the model is good enough. From the test results, hypotheses were accepted. All of these hypotheses except one are supported. In Europe, information search is not an antecedent of brand knowledge. This means that sales of global fashion brands like jeans in Europe are not expanding as rapidly as in Asian markets such as China, Japan, and South Korea. Young consumers in European countries are not more brand and fashion conscious than their counter partners in Asia. The results have theoretical, practical meaning and contributions. In the fashion jeans industry, relatively few studies examining the viability of cross-national brand equity has been studied. This study provides insight on building global brand equity and suggests information process elements like information search and information resources are working differently in Asia and Europe for fashion jean market.

• Applied Biological Chemistry
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• v.16 no.1
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• pp.18-30
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• 1973

The flag and lower leaves (4th or 5th) of rice plant from the field of NPK simple trial and from three low productive area were analyzed in order to find out certain diagnostic criteria of nutritional status at harvest. 1. Nutrient contents in the leaves from no fertilizer, minus nutrient and fertilizer plots revealed each criterion for induced deficiency (severe deficient case induced by other nutrients), deficiency (below the critical concentration), insufficiency (hidden hunger region), sufficiency (luxuary consumption stage) and excess (harmful or toxic level). 2. Nitrogen contents for the above five status was less than 1.0%, 1.0 to 1.2, 1.2 to 1.6, 1.6 to 1.9 and greater than 1.9, respectively. 3. It was less than 0.3%, 0.3 to 0.4, 0.4 to 0.55 and greater than 0.55 for phosphorus $(P_2O_5)$ but excess level was not clear. 4. It was below 0.5%, 0.5 to 0.9, 0.9 to 1.2, 1.2 to 1.4 and above 1.4 for potassium. 5. It was below 4%, 4 to 6, 6 to 11 and above 11 for silicate $(SiO_2)$ and no excess was appeared. 6. Potassium in flag leaf seemed to crow out nitrogen to ear resulting better growth of ear by the inhibition of overgrowth of flag leaf. 7. Phosphorus accelerated the transport of Mg, Si, Mn and K in this order from lower leaf to flag, and retarded that of Ca and N in this order at flowering while potassium accelerated in the order of Mn, and Ca, and retarded in the order of Mg, Si, P and N at milky stage. 8. Transport acceleration index (TAI) expressed as (F_2L_1-F_1L_2)\;100/F_1L_1$ where F and L stand for other nutrient cotents in flag and lower leaf and subscripts indicate the rate of a nutrient applied, appears to be suitable for the effect of the nutrient on the translocation of others. 9. The content of silicate $(SiO_2)$ in the flag was lower than that of lower leaf in the early season cultivation indicating hinderance in translocation or absorption. It was reverse in the normal season cultivation. 10. The infection rate of Helminthosporium frequently occurred in the potassium deficient field seemed to be related more to silicate and nitrogen content than potassium in the flag leaf. 11. Deficiency of a nutrient occured simultaniously with deficiency of a few other ones. 12. Nutritional disorder under the field condition seems mainly to be attributed to macronutrients and the role of micronutrient appears to be none or secondary.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.31 no.4
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• pp.599-607
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• 1998

To clarify annual reproductive cycle of Korean dark sleeper, Odontobutis platycephala (Iwata et Jeon), we examined the seasonal changes of gonadosomatic index (GSI), the proportional frequency of oocyte development stages in the ovary and the changes of sex steroid hormone levels in blood from December 1995 to November 1997. In July and August, GSI was 0.35 to 0.72 and most oocytes in the ovary were chromatin-nucleolus stage and perinucleolar stage (proportional frequency: $87\%\~96\%$). In September, GSI was 1.20 $\pm$ 0.12, some oocytes in the ovary were yolk vesifle stage (proportional frequency: $22.8\%$) and vitellogenic stage which appeared very rarely(proportional frequency: $2.2\%$). GSI increased gradually from October and reached 4.59± 0.61 to December. During this period, oocytes of vitellogenic stage increased slightly (proportional frequency in December: $22.1\%$). In January, GSI was 4.32 $\pm$ 0.72 but the proportional frequency of oocytes in vitellogenic stage increased (proportional frequency: $51.2\%$). from February, GSI was increased sharply and reached to 10.51 $\pm$ 1.04 in March, the highest value throughout the year and the proportional frequency of oocytes in vitellogenic stage also reached the highest levels (proportional frequency: $60\%$). From April, GSI was gradually decreased and fell down to 1.11 $\pm$ 0.35 in June. During this period, the proportional frequency of mature oocytes was the highest in April (proportional frequency of mature oocyte stage: $40\%$ in April, $12\%$ May, $5\%$ June) throughout the year, and atretic ovarian follicles were appeared. The blood level of estradiol-17$\beta$ ($E_2$), which stimulates the hepatic synthesis and secretion of vitellogenin, was $0.84{\pm}0.20\;ng/m{\ell}$ in August, and thereafter was not changed until December. from January, it increased sharply and reached the highest level of $ 2.85{\pm}0.35\;ng/m{\ell}$ in March throughout the year, but fell to $0.14{\pm}0.02\;ng/m{\ell}$ in July(P<0.05), 17$\alpha$-hydroxprogesterone(17$\alpha$-OHP) was the peak $13.37{\pm}0.52ng/m{\ell}$ in March, but no significant changes in other period(below $3ng/m{\ell}$, P<0.05). 17$\alpha$, 20$\beta$-dihydroxy-4-pregnen-3-one(17$\alpha$, 20$\beta$-P), which was known as the final maturation inducing hormone in teleost, was $0.74{\pm}0.09ng/m{\ell}$ in April and $0.54{\pm}0.07ng/m{\ell}$ in May, but no significant changes in other period (below $0.26\;ng/m{\ell}$, p<0.05). Taken together these results, the annual reproductive cycle of O. platycephala divided into 4 periods as follows: 1) ripe and spawning period from April to June, main spawning period was from April to May, 2) Resting period from July to August, 3) Growing period from September to December, 4) Maturing period from January to March. Moreover, It was showed that the changes of sex steroid hormone in blood played a important roles in the annual reproductive cycle of O. platycephala.