• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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• pp.45-50
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• 2021

Machines and facilities are physically or chemically degenerated by continuous usage. The representative type of the degeneration is the wearing of tools, which results in the process mean shift. According to the increasing wear level, non-conforming products cost and quality loss cost are increasing simultaneously. Therefore, a preventive maintenance is necessary at some point. The problem of determining the maintenance period (or wear limit) which minimizes the total cost is called the 'process mean shift problem'. The total cost includes three items: maintenance cost (or adjustment cost), non-conforming cost due to the non-conforming products, and quality loss cost due to the difference between the process target value and the product characteristic value among the conforming products. In this study, we set the production volume as a decreasing function rather than a constant. Also we treat the process variance as a function to the increasing wear rather than a constant. To the quality loss function, we adopted the Cpm+, which is the left and right asymmetric process capability index based on the process target value. These can more reflect the production site. In this study, we presented a more extensive maintenance model compared to previous studies, by integrating the items mentioned above. The objective equation of this model is the total cost per unit wear. The determining variables are the wear limit and the initial process setting position that minimize the objective equation.

• Journal of Biosystems Engineering
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• v.21 no.2
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• pp.123-133
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• 1996

An automatic drum seeder was developed to improve the seeding operation. It consisted of a conveyor to transfer seedling trays, a seed-hopper to supply seeds, a drum to drop seeds on the tray, and an air blower to remove extra seeds. A photo sensor was used to detect the transfer of seedling trays, and its signal was fed into microcomputer which operated a stepping motor driving the drum. The seeds were adhered to the surface of drum by vacuum pressure, and were dropped into tray cells by compressed air. An air connection unit was devised to alternate between vacuum pressure and compressed air. A control program for the system, written in C language, could operate the drum at the given number of revolutions and revolutions per minute. The results showed that the air connection unit could operate well and the seeds were dropped satisfactorily into tray cells. In case of cabbage and perilla seeds, which are regular and spherical shape, the missing rate was low and the single seeding rate was more than 97%. Low missing rate and high multiple seeding rate were observed in lettuce seeds which have narrow ends with tight weight. The missing rate of pepper seed was very high because of heavy weight and irregular shape. To improve the performance of the seeder, adjustment of vacuum pressure based upon shape and weight of the seeds, careful selection of the material of drum, maintenance of consistent air blower pressure, and replacement of stepping motor to DC motor are recommended.

• Science of Emotion and Sensibility
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• v.5 no.2
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• pp.63-72
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• 2002

In order to examine universal design, 1 have developed two analytical methodologies based on 3P(point) task analysis: structured task analysis and task matrix analysis. I also extracted nine universal design items, namely (1) adjustment, (2) redundancy, (3) specification and function transparency, (4) feedback and (5) error tolerance, (6) effective acquisition of information, (7) ease of understanding and judgment, (8) comfortable operation, and (9) continuity of information and operation. Structured task analysis is used to uncover problems in each of the tasks constituting a job for each functionally challenged condition of users, and solutions to the extracted problems are examined in terms of the above-mentioned nine universal design items. Task matrix analysis calls for the production of a table for each task in a job. In each table, nine items form the columns, and the horizontal rows list all disability types. Then, solutions are formulated for each cell formed by the intersecting columns and rows. Using these two analysis methods, 1 have conducted a verification experiment for the universal design of a public bus. The results of the research have enabled me to propose various ,solutions from a system-based perspective, instead of coming up with the superficial and isolated solutions which are normally produced when conventional analytical methods are used.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.144-151
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• 2002

In order to examine universal desist I have developed two analytical methodologies based on 3P(point) task analysis: structured task analysis and task matrix analysis. I also extracted me universal design items, namely (1) adjustment (2) redundancy, (3) specification and function transparency, (4) feedback and (5) error tolerance, (6) effective acquisition of information, (7) ease of understanding and judgment (8) comfortable operation, and (9) continuity of information and operation. Structured task analysis is used to uncover problems in each of the tasks constituting a job for each functionally challenged condition of users, and solutions to the extracted problems are examined in terms of the above-mentioned nine universal design items. Task matrix analysis calls for the production of a table for each task in a job. In each table, nine items from the columns, and the horizontal rows list all disability types. Then, solutions are formulated for each cell formed by the intersecting columns and rows. Using these two analysis methods, T have conducted a verification experiment for the universal design of a public bus. The results of the research have enabled me to propose various solutions from a system-based perspective, instead of coming up with the superficial and isolated solutions which are normally produced when conventional analytical methods are used.

• 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.

• Environmental and Resource Economics Review
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• v.32 no.1
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• pp.47-75
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• 2023

Compared to the EU, which legislates the Carbon Border Adjustment System (CBAM), the United States' carbon border adjustment policy movement is still relatively slow. Recently, however, a related bill has been proposed in the United States, and research institutes have been presenting research results on how to introduce an upstream carbon tax rather than an emission trading system and carry out carbon border adjustment based on it. Therefore, in this study, we looked at the economic and environmental effects of introducing this type of upstream carbon tax and carbon border adjustment in Korea. If an upstream carbon tax of KRW 30,000 per ton of CO₂ is applied to the net supply of domestic fossil energy, the expected carbon tax revenue is approximately KRW 22.9961 trillion, equivalent to about 5.7% of the total revenue of the Korean government of KRW 402 trillion in 2019. In addition, the carbon dioxide content of the steel sector, calculated based on the energy supply and demand status of the steel sector, which emits the most greenhouse gas emissions in Korea and has a considerable amount of overseas exports, was 106.22 million tons of CO₂. On the other hand, assuming that the upstream carbon tax of 30,000 won per ton of CO₂ embodied is directly passed on to the production cost of the steel sector, the carbon tax burden in the steel sector is estimated to reach approximately KRW 3.1865 trillion. Even after deducting KRW 1.1599 trillion in export refunds estimated by using the share of exports of steel products, the net carbon tax burden on steel products for domestic demand amounts to KRW 2.0266 trillion, which is analyzed to act as a factor in increasing the price of steel products.

• Korean Journal of Environment and Ecology
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• v.32 no.6
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• pp.639-645
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• 2018

The objective of the study is to analyze the impact of zone adjustment by comparing the changes from 2011 to 2018 of social and environmental factors such as the special-purpose area, actual construction activities including building development, land use environment, and officially assessed individual land price in the areas released from the National Park Zone during the second National Park Zone adjustment during 2010 to 2011 with the social and environmental factors in the areas that remained in the National Park Zone during the same period. We intended to investigate the problems of the second National Park Zone adjustment and explore alternative implications for the third National Park Zone adjustment. As for the special-purpose area, 80.4% of the released areas were converted to planned, production, and conservation area while 15.6% changed to the agricultural area, and 4.0% remained as the natural environmental conservation area. Regarding the change in building development scale, the average size of construction in the released area since 2011 was $106m^2$ while that in the retained areas was $91m^2$. For the land use environment, the rate of change from the natural area to developed area was 1.9% in the released area and 0.7% in the retained area. The officially assessed individual land price increased by 11,911 won in the released area and 4,413 won in the retained area. Although both areas showed an increase in the land price, the difference of officially assessed individual land prices was about 2.5 times. The problem concerning the private property rights of local residents in the national parks is still a challenge, but the second National Park Zone adjustment has resolved the problem significantly. Accordingly, it is necessary to offer the benefits for the residents in the national park area by analyzing the park zoning and park facility planning to present the rational alternative. It is also necessary to establish a support system that encourages the collaborative cooperation between the park authority and residents and assures that the residents to have pride in the national park.

• International Journal of Quality Innovation
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• v.6 no.1
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• pp.109-118
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• 2005

The parameter design is the most emphasized measure by researchers for a new products development. It is critical for makers to achieve simultaneously in both the time-to-market production and the quality enhancement. However, there are difficulties in practical application, such as (1) complexity and nonlinear relationships co-existed among the system's inputs, outputs and control parameters, (2) interactions occurred among parameters, (3) where the adjustment factors of Taguchi's two-phase optimization procedure cannot be sure to exist in practice, and (4) for some reasons, the data became lost or were never available. For these incomplete data, the Taguchi methods cannot treat them well. Neural networks have a learning capability of fault tolerance and model free characteristics. These characteristics support the neural networks as a competitive tool in processing multivariable input-output implementation. The successful fields include diagnostics, robotics, scheduling, decision-making, prediction, etc. This research is a case study of spherical annealing model. In the beginning, an original model is used to pre-fix a model of parameter design. Then neural networks are introduced to achieve another model. Study results showed both of them could perform the highest spherical level of quality.

• Journal of the Korean association of regional geographers
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• v.17 no.3
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• pp.259-269
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• 2011

The meaning of fengshui was another cultural ecological environment in the pre-modern in Korea. Village residents made interrelations with village natural environment by the medium of the geomantic landscape. The functions of cultural ecology through the village fengshui are as follows: the spatial location, the population inflow, the regulation of the community's production or construction or land-use, the adjustment of the environmental carrying capacity, the environmental management, the forming of the collective environmental perception and attitude. Village fengshui is a cultural adaptation strategy to the local environment for the village residents. Fengshui can be evaluated as a traditional cultural ecological way and knowledge system for keeping sustainable village environment in East Asia.

• 한국공간정보시스템학회:학술대회논문집
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• 2002.03a
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• pp.45-52
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• 2002

Artificial neural networks (ANN) have been successfully used for classifying remotely sensed imagery. However, ANN still is not the preferable choice for classification over the conventional classification methodology such as the maximum likelihood classifier commonly used in the industry production environment. This can be attributed to the ANN characteristic built-in stochastic process that creates difficulties in dealing with unequally represented training classes, and its training performance speed. In this paper we examined some practical aspects of training classes when using a back propagation neural network model for remotely sensed imagery. During the classification process of remotely sensed imagery, representative training patterns for each class are collected by polygons or by using a region-growing methodology over the imagery. The number of collected training patterns for each class may vary from several pixels to thousands. This unequally populated training data may cause the significant problems some neural network empirical models such as back-propagation have experienced. We investigate the effects of training over- or under- represented training patterns in classes and propose the pattern repopulation algorithm, and an adaptive alpha adjustment (AAA) algorithm to handle unequally represented classes. We also show the performance improvement when input patterns are presented in random fashion during the back-propagation training.