• Korean Journal of Soil Science and Fertilizer
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• 제10권3호
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• pp.103-134
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• 1977

The physiological and biochemical role of potassium for upland crops according to recent research reports and the nutritional status of potassium in Korea were reviewed. Since physical and chemical characteristics of potassium ion are different from those of sodium, potassium can not completely be replaced by sodium and replacement must be limited to minimum possible functional area. Specific roles of potassium seem to keep fine structure of biological membranes such as thylacoid membrane of chloroplast in the most efficient form and to be allosteric effector and conformation controller of various enzymes principally in carbohydrate and protein metabolism. Potassium is essential to improve the efficiency of phoro- and oxidative- phosphorylation and involve deeply in all energy required metabolisms especially synthesis of organic matter and their translocation. Potassium has many important, physiological functions such as maintenance of osmotic pressure and optimum hydration of cell colloids, consequently uptake and translocation of water resulting in higher water use efficiency and of better subcellular environment for various physiological and biochemical activities. Potassium affects uptake and translocation of mineral nutrients and quality of products. potassium itself in products may become a quality criteria due to potassium essentiality for human beings. Potassium uptake is greatly decreased by low temperature and controlled by unknown feed back mechanism of potassium in plants. Thus the luxury absorption should be reconsidered. Total potassium content of upland soil in Korea is about 3% but the exchangeable one is about 0.3 me/100g soil. All upland crops require much potassium probably due to freezing and cold weather and also due to wet damage and drought caused by uneven rainfall pattern. In barley, potassium should be high at just before freezing and just after thawing and move into grain from heading for higher yield. Use efficiency of potassium was 27% for barley and 58% in old uplands, 46% in newly opened hilly lands for soybean. Soybean plant showed potassium deficiency symptom in various fields especially in newly opened hilly lands. Potassium criteria for normal growth appear 2% $K_2O$ and 1.0 K/(Ca+Mg) (content ratio) at flower bud initiation stage for soybean. Potassium requirement in plant was high in carrot, egg plant, chinese cabbage, red pepper, raddish and tomato. Potassium content in leaves was significantly correlated with yield in chinese cabbage. Sweet potato. greatly absorbed potassium subsequently affected potassium nutrition of the following crop. In the case of potassium deficiency, root showed the greatest difference in potassium content from that of normal indicating that deficiency damages root first. Potatoes and corn showed much higher potassium content in comparison with calcium and magnesium. Forage crops from ranges showed relatively high potassium content which was significantly and positively correlated with nitrogen, phosphorus and calcium content. Percentage of orchards (apple, pear, peach, grape, and orange) insufficient in potassium ranged from 16 to 25. The leaves and soils from the good apple and pear orchards showed higher potassium content than those from the poor ones. Critical ratio of $K_2O/(CaO+MgO)$ in mulberry leaves to escape from winter death of branch tip was 0.95. In the multiple croping system, exchangeable potassium in soils after one crop was affected by the previous crops and potassium uptake seemed to be related with soil organic matter providing soil moisture and aeration. Thus, the long term and quantitative investigation of various forms of potassium including total one are needed in relation to soil, weather and croping system. Potassium uptake and efficiency may be increased by topdressing, deep placement, slow-releasing or granular fertilizer application with the consideration of rainfall pattern. In all researches for nutritional explanation including potassium of crop yield reasonable and practicable nutritional indices will most easily be obtained through multifactor analysis.

• Asia pacific journal of information systems
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• 제17권4호
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Proceedings of the KOR-KST Conference
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• 대한교통학회 1995년도 제27회 학술발표회
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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.

• Journal of the Korean Society of Food Science and Nutrition
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• 제41권8호
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• pp.1118-1133
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• 2012

This research aimed to suggest an efficient improvement plan for school food services by investigating the operating situation and recognition of menu management in school food services for school food service dietitians (and nutrition teachers) in Chungbuk. A total of 328 questionnaires were distributed to school food service dietitians (and nutrition teachers) in Chungbuk by e-mail in September, 2010. A total of 265 questionnaires (80.8%) were used for the analysis. The highest allocation of nutrients and calories per day in school food services was 1:1.5:1.5 (breakfast : lunch : dinner) (38.5%). The reasoning for applying a flexible allocation of nutrients and calories per day was 'considering the ratio of students who do not eat breakfast' (59.2%). And the way to apply the flexible allocation for nutrients and calories per day was 'by agreement from the school operating committee in arbitrary data without situation surveys' (86 respondents, 49.4%), and 'by agreement from the school operating committee in analysis data through situation surveys' (80 respondents, 46.0%). The operational method of standardized recipes was 'cooking management site of national education information systems' (87.5%) and the items included in standardized recipes were menu name, food material name, portion size, cooking method, nutrition analysis, and critical control point in HACCP. The main reason for not utilizing all items of a cooking management site of the national education information system was 'no big trouble in menu management even though it is used partly (29.1%). In addition, the highest use of standardized recipe was for 'maintaining consistency of food production quantity' (74.0%).

• Journal of Korean Society of Forest Science
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• 제80권1호
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• pp.72-81
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• 1991

This study was carried out to provide necessary information for improving quarrying industry management in Korea. The results of the study are summarized as follows : 1. In aggregate and building-stone quarrying firms the managers over 40 years of age are 97% and 89.1%, the ones above education level of high school are 90% and 85% and the ones not more than 10 years of quarrying experience are 70% and 52%, respectively. Accordingly it can be pointed out that most of the managers of two types of firms are relatively old, have high educational background, while quarrying experiences of building-stone firm managers are longer than that of aggregate firm managers. 2. Most of the management forms are social corporation(60%) for aggregate quarry firms and private management(76%) for building-stone firms. Average areas of permitted stone-pits of aggregate and building-stone quarries are about 2.86ha and 1.66ha respectively. That is, aggregate quarrying firms are carried on a larger scale than building-stone quarrying firms. 3. The yearly average product of aggregate quarrying firms has increased steadily from $88.961m^3$ in 1985 to $144.028m^3$ in 1988, while, in case of building-stone quarry firms, it has significantly increased from $4.155m^3$ to $19.462m^3$ from 1985 to 1987, but reduced to $13.400m^3$ in 1988. Unstable production activities of building-stone quarrying firms may require continuous government support. 4. Major cost items are equipment rental, depreciation, salaries, repair, maintenance for aggregate quarrying firms, and salaries, depreciation, fuel, tax for building-stone quarrying firms. The yearly average rate of return is about 9.7% for aggregate quarry firms and 2.6% for building-stone quarry firms. It can be pointed out that aggregate quarrying firms is better managed than building-stone quarrying firms. 5. The production elasticity of salary for aggregate quarrying firms is 0.495, that of employees is 0.559, and that of capital service is 0.513. The sum of the elasticities is 1.257>1. Fur building-stone quarrying firms, that of employees is 0.492, that of variable costs is 0.192, and that of capital service is 0.498. The sum of elasticities is 1.172>1, thus denotes the increasing returns to scale for both types quarrying firms. 6. The ratio of marginal value product to opportunity cost of empolyees is 2.54, that of variable costs is 3.62, and that of capital service is 1.45, in aggregate quarrying firms. That of employees is 2.47, that is variable costs was 2.34, and that of capital service is 19.67 in building-stone quarrying firms. Therefore the critical factors for more expansion of management scale in aggregate quarrying firms are variable cost and employees, and are capital service in building-stone quarry ing firms. 7. The break-even points of stone sales are about 0.587 billion won and 0.22 billion won in aggregate and building-stone quarrying firms respectively. The optimum sales Level for profit maximization are about 2.0 billion and 0.5 billion in aggregate and building-stone quarry firms respectively.