• Agribusiness and Information Management
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• v.9 no.1
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• pp.7-17
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• 2017

Agricultural water management has gained enormous attention in the developing world to alleviate poverty, reduce hunger and conserve ecosystems in small-scale production systems of resource-poor farmers. The story of food security in the $21^{st}$ century in India is likely t o be closely linked to the story of water security. Today, the water resource is under severe threat. The past experiences in India in general and in Andhra Pradesh in particular, indicated inappropriate management of irrigation has led to severe problems like excessive water depletion, reduction in water quality, water logging, salinization, marked reduction in the annual discharge of some of the rivers, lowering of ground water tables due to pumping at unsustainable rates, intrusion of salt water in some coastal areas etc. Considering the importance of irrigation water resource efficiency, Krishna Western Delta (KWD) of Andhra Pradesh was purposively selected for this in depth study, as the farming community in this area are severely affected due to severe soil salinity and water logging problems and hence, adoption of different water saving crop production technologies deserve special mention. It is quite disappointing that, canals, tube wells and filter points and other wells could not contribute much to the irrigated area in KWD. Due to less contribution from these sources, the net area irrigated also showed declining growth at a rate of -6.15 per cent. Regarding paddy production, both SRI and semi-dry cultivation technologies involves less irrigation cost (Rs. 2475.21/ha and Rs. 3248.15/ha respectively) when compared to transplanted technology (Rs. 4321.58/ha). The share of irrigation cost in Total Operational Cost (TOC) was highest for transplanted technology of paddy (11.06%) followed by semi-dry technology (10.85%) and SRI technology (6.21%). The increased yield and declined cost of cultivation of paddy in SRI and semi-dry production technologies respectively were mainly responsible for the low cost of production of paddy in SRI (Rs. 495.22/qtl) and semi-dry (Rs. 532.81/qtl) technologies over transplanted technology (Rs. 574.93/qtl). This clearly indicates that, by less water usage, paddy returns can be boosted by adopting SRI and semi-dry production technologies. Both the system-level and field-level interventions should be addressed to solve the issues/problems of water management. The enabling environment, institutional roles and functions and management instruments are posing favourable picture for executing the water management interventions in the State of Andhra Pradesh in general and in KWD in particular. This facilitates the farming community to harvest good crop per unit of water resource used in the production programme. To achieve better results, the Farmers' Organizations, Water Users Associations, Department of Irrigation etc., will have to aim at improving productivity per unit of water drop used and this must be supported through system-wide enhancement of water delivery systems and decision support tools to assist farmers in optimizing the allocation of limited water among crops, selection of crops based on farming situations, and adoption of appropriate alternative crops in drought years.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.1
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• pp.107-120
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• 2020

In a performance-based evaluation of structures in use, the current performance is assessed by summing up the weighting of the evaluation indices for each performance. In this study, to suggest a performance-based evaluation technique for NATM tunnels in use, the performance evaluation indices were derived by examining the characteristics and similarities of each index developed from previous study. The weighting of the evaluation indices was derived by calculating the relative importance of each evaluation indices from the AHP analysis. In order to develop a quantitative evaluation model, grading criteria for each performance index was derived through literature review, and performance evaluation tables for road and railway tunnels were presented. In order to verify the significance of the proposed performance evaluation model, the correlation analysis was performed between each evaluation index and the final evaluation result. In the correlation analysis, the survey data measured through precision safety diagnosis in the tunnel in use was applied. It may be said that the proposed evaluation indices, weighting, criteria and evaluation models for tunnels in use can be applied to the performance-based maintenance system of tunnels.

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.1-14
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• 2004

Visualization of documents will help users when they do search similar documents. and all research in information retrieval addresses itself to the problem of a user with an information need facing a data source containing an acceptable solution to that need. In various contexts. adequate solutions to this problem have included alphabetized cubbyholes housing papyrus rolls. microfilm registers. card catalogs and inverted files coded onto discs. Many information retrieval systems rely on the use of a document surrogate. Though they might be surprise to discover it. nearly every information seeker uses an array of document surrogates. Summaries. tables of contents. abstracts. reviews, and MARC recordsthese are all document surrogates. That is, they stand infor a document allowing a user to make some decision regarding it. whether to retrieve a book from the stacks, whether to read an entire article, etc. In this paper another type of document surrogate is investigated using a grouping method of term list. lising Multidimensional Scaling Method (MDS) those surrogates are visualized on two-dimensional graph. The distances between dots on the two-dimensional graph can be represented as the similarity of the documents. More close the distance. more similar the documents.

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

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

• Asia Marketing Journal
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• v.12 no.4
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• pp.165-181
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• 2011

In 2005, Yuhan Kimberly found interesting points in the existing customers' U&A survey on the kitchen towel. The usage of Korean consumers is usually restricted to getting rid of the oil from the fans and the fried food. This usage limits could be the barrier to the diffusion of kitchen towel. Although consumers were worried about the hygiene situations about the dishcloth, they also percieved that the existing paper kitchen towels were short of something to soothe their inconveniences. As a result, the company made a decision to seek out the solution for the consumers' worries. The relative shortage of the paper kitchen towel compared to that of the unhygienic and inconvenient dishcloth was its lack of water-endurance. The dishcloth could be reliable in the wet environment which is very common in Korean kitchen, whereas the paper kitchen towel was perceived as very weak and unreliable in removing water form the dishes and the sink. To overcome the common sense of the consumers, it is important to shift the consumers' perception of the kitchen towel category. It is needed to expand the usage time from one time to several times in a day. So it is needed to redesign the customers' kitchen life. The company adopted the brand "Scott^®" to meet the global brand strategy of the parent company, Kimberley Clark. This brand was also adopted and made a succesful launch of the similar product lines in Latin America. Furthermore, to make an emphasis on the differentiation from the existing paper kitchen towels, the company made the slogan, "Scott^® washable kitchen towel." This slogan was designed to expand the familiar product image of convenient paper towels to water-resistance. As a result, consumers show the changes in usage behavior of paper towels and apply them for more various purposes such as cleaning the decks and tables. This change results in the rapid sales increase of "Scott^® washable kitchen towel."