• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.3-32
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• 1995

The Highway Capacity Manual specifies procedures for evaluating intersection performance in terms of delay per vehicle. What is lacking in the current methodology is a comparable quantitative procedure for ass~ssing the safety-based level of service provided to motorists. The objective of the research described herein was to develop a computational procedure for evaluating the safety-based level of service of signalized intersections based on the relative hazard of alternative intersection designs and signal timing plans. Conflict opportunity models were developed for those crossing, diverging, and stopping maneuvers which are associated with left-turn and rear-end accidents. Safety¬based level-of-service criteria were then developed based on the distribution of conflict opportunities computed from the developed models. A case study evaluation of the level of service analysis methodology revealed that the developed safety-based criteria were not as sensitive to changes in prevailing traffic, roadway, and signal timing conditions as the traditional delay-based measure. However, the methodology did permit a quantitative assessment of the trade-off between delay reduction and safety improvement. The Highway Capacity Manual (HCM) specifies procedures for evaluating intersection performance in terms of a wide variety of prevailing conditions such as traffic composition, intersection geometry, traffic volumes, and signal timing (1). At the present time, however, performance is only measured in terms of delay per vehicle. This is a parameter which is widely accepted as a meaningful and useful indicator of the efficiency with which an intersection is serving traffic needs. What is lacking in the current methodology is a comparable quantitative procedure for assessing the safety-based level of service provided to motorists. For example, it is well¬known that the change from permissive to protected left-turn phasing can reduce left-turn accident frequency. However, the HCM only permits a quantitative assessment of the impact of this alternative phasing arrangement on vehicle delay. It is left to the engineer or planner to subjectively judge the level of safety benefits, and to evaluate the trade-off between the efficiency and safety consequences of the alternative phasing plans. Numerous examples of other geometric design and signal timing improvements could also be given. At present, the principal methods available to the practitioner for evaluating the relative safety at signalized intersections are: a) the application of engineering judgement, b) accident analyses, and c) traffic conflicts analysis. Reliance on engineering judgement has obvious limitations, especially when placed in the context of the elaborate HCM procedures for calculating delay. Accident analyses generally require some type of before-after comparison, either for the case study intersection or for a large set of similar intersections. In e.ither situation, there are problems associated with compensating for regression-to-the-mean phenomena (2), as well as obtaining an adequate sample size. Research has also pointed to potential bias caused by the way in which exposure to accidents is measured (3, 4). Because of the problems associated with traditional accident analyses, some have promoted the use of tqe traffic conflicts technique (5). However, this procedure also has shortcomings in that it.requires extensive field data collection and trained observers to identify the different types of conflicts occurring in the field. The objective of the research described herein was to develop a computational procedure for evaluating the safety-based level of service of signalized intersections that would be compatible and consistent with that presently found in the HCM for evaluating efficiency-based level of service as measured by delay per vehicle (6). The intent was not to develop a new set of accident prediction models, but to design a methodology to quantitatively predict the relative hazard of alternative intersection designs and signal timing plans.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.147-157
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• 2022

This study tried to propose a smart farm technology strategy suitable for the domestic situation, focusing on the differentiation suitable for the domestic situation of ICT technology. In the case of advanced countries in the overseas agricultural industry, it was confirmed that they focused on the development of a specific stage that reflected the geographical characteristics of each country, the characteristics of the agricultural industry, and the characteristics of the people's demand. Confirmed that no enemy development is being performed. Therefore, in response to problems such as a rapid decrease in the domestic rural population, aging population, loss of agricultural price competitiveness, increase in fallow land, and decrease in use rate of arable land, this study aims to develop smart farm ICT technology in the future to create quality agricultural products and have price competitiveness. It was suggested that the smart farm should be promoted by paying attention to the excellent performance, ease of use due to the aging of the labor force, and economic feasibility suitable for a small business scale. First, in terms of economic feasibility, the ICT technology is configured by selecting only the functions necessary for the small farm household (primary) business environment, and the smooth communication system with these is applied to the ICT technology to gradually update the functions required by the actual farmhouse. suggested that it may contribute to the reduction. Second, in terms of performance, it is suggested that the operation accuracy can be increased if attention is paid to improving the communication function of ICT, such as adjusting the difficulty of big data suitable for the aging population in Korea, using a language suitable for them, and setting an algorithm that reflects their prediction tendencies. Third, the level of ease of use. Smart farms based on ICT technology for the development of the Industry6.0 (1.0(Agriculture, Forestry) + 2.0(Agricultural and Water & Water Processing) + 3.0 (Service, Rural Experience, SCM)) perform operations according to specific commands, finally suggested that ease of use can be promoted by presetting and standardizing devices based on big data configuration customized for each regional environment.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.127-144
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• 2021

The purpose of this study is to derive service factors based on the "Rail Statistical Yearbook" data of railroad service providers from 1990 to 2019, and to analyze the effect of the service factors on the operating profit ratio(OPR), a representative management performance variable of railroad transport service providers. In particular, it has academic significance in terms of empirical research to evaluate whether the management innovation of the KoRail has changed in line with the purpose of establishing the corporation by dividing the research period into the first period (1990-2003) and the latter (2004-2019). The contents of this study investigated previous studies on the quality of railway passenger transportation service and analyzed the contents of government presentation data related to the management performance evaluation of the KoRail. As an empirical analysis model, a research model was constructed using OPR as a dependent variable and service factor variables of infrastructure, economy, safety, connectivity, and business diversity as explanatory variables based on the operation and management activity information during the analysis period 30 years. On the results of research analysis, OPR is that the infrastructure factor is improved by structural reform or efficiency improvement. And economic factors are the fact that operating profit ratio improves by reducing costs. The safety factor did not reveal the significant explanatory power of the regression coefficient, but the sign of influence was the same as the prediction. Connectivity factor reveals a influence on differences between first period and latter, but OPR impact direction is changed from negative in before to positive in late. This is an evironment in which connectivity is actually realized in later period. On diversity factor, there is no effect of investment share in subsidiaries and government subsidies on OPR.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.218-233
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• 2022

The long-term (1986~2020) predictability of the number of days of heat and cold damages for each growth stage of soybean is evaluated using the daily maximum and minimum temperature (Tmax and Tmin) data produced by Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF). The Predictability evaluation methods for the number of days of damages are Normalized Standard Deviations (NSD), Root Mean Square Error (RMSE), Hit Rate (HR), and Heidke Skill Score (HSS). First, we verified the simulation performance of the Tmax and Tmin, which are the variables that define the heat and cold damages of soybean. As a result, although there are some differences depending on the month starting with initial conditions from January (01RUN) to May (05RUN), the result after a systematic bias correction by the Variance Scaling method is similar to the observation compared to the bias-uncorrected one. The simulation performance for correction Tmax and Tmin from March to October is overall high in the results (ENS) averaged by applying the Simple Composite Method (SCM) from 01RUN to 05RUN. In addition, the model well simulates the regional patterns and characteristics of the number of days of heat and cold damages by according to the growth stages of soybean, compared with observations. In ENS, HR and HSS for heat damage (cold damage) of soybean have ranged from 0.45~0.75, 0.02~0.10 (0.49~0.76, -0.04~0.11) during each growth stage. In conclusion, 01RUN~05RUN and ENS of PNU CGCM-WRF Chain have the reasonable performance to predict heat and cold damages for each growth stage of soybean in South Korea.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.63-75
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• 2023

Due to the development of industry, interest in air pollutants has increased. Air pollutants have affected various fields such as environmental pollution and global warming. Among them, environmental diseases are one of the fields affected by air pollutants. Air pollutants can affect the human body's skin or respiratory tract due to their small molecular size. As a result, various studies on air pollutants and environmental diseases have been conducted. Asthma, part of an environmental disease, can be life-threatening if symptoms worsen and cause asthma attacks, and in the case of adult asthma, it is difficult to cure once it occurs. Factors that worsen asthma include particulate matter and air pollution. Asthma is an increasing prevalence worldwide. In this paper, we study how air pollutants correlate with the number of emergency room admissions in asthma patients and predict the number of future asthma emergency patients using highly correlated air pollutants. Air pollutants used concentrations of five pollutants: sulfur dioxide(SO₂), carbon monoxide(CO), ozone(O₃), nitrogen dioxide(NO₂), and fine dust(PM₁₀), and environmental diseases used data on the number of hospitalizations of asthma patients in the emergency room. Data on the number of emergency patients of air pollutants and asthma were used for a total of 5 years from January 1, 2013 to December 31, 2017. The model made predictions using two models, Informer and LTSF-Linear, and performance indicators of MAE, MAPE, and RMSE were used to measure the performance of the model. The results were compared by making predictions for both cases including and not including the number of emergency patients. This paper presents air pollutants that improve the model's performance in predicting the number of asthma emergency patients using Informer and LTSF-Linear models.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6C
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• pp.395-406
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• 2006

Drilled shafts are a common foundation solution for large concentrated loads. Such piles are generally constructed by drilling through softer soils into rock and the section of the shaft which is drilled through rock contributes most of the load bearing capacity. Drilled shafts derive their bearing capacity from both shaft and base resistance components. The length and diameter of the rock socket must be sufficient to carry the loads imposed on the pile safely without excessive settlements. The base resistance component can contribute significantly to the ultimate capacity of the pile. However, the shaft resistance is typically mobilized at considerably smaller pile movements than that of the base. In addition, the base response can be adversely affected by any debris that is left in the bottom of the socket. The reliability of base response therefore depends on the use of a construction and inspection technique which leaves the socket free of debris. This may be difficult and costly to achieve, particularly in deep sockets, which are often drilled under water or drilling slurry. As a consequence of these factors, shaft resistance generally dominates pile performance at working loads. The efforts to improve the prediction of drilled shaft performance are therefore primarily concerned with the complex mechanisms of shaft resistance development. The shaft resistance only is concerned in this study. The nature of the interface between the concrete pile shaft and the surrounding rock is critically important to the performance of the pile, and is heavily influenced by the construction practices. In this study, the influences of asperity characteristics such as the heights and angles, the strength characteristics and elastic constants of surrounding rock masses and the depth and length of rock socket, et. al. on the shaft resistance of drilled shafts are investigated from elasto-plastic analyses( FLAC). Through the parametric studies, among the parameters, the vertical stress on the top layer of socket, the height of asperity and cohesion and poison's ratio of rock masses are major influence factors on the unit peak shaft resistance.

• Journal of Bio-Environment Control
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• v.21 no.3
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• pp.271-275
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• 2012

The average annual and winter ambient air temperatures in Korea have risen by $0.7^{\circ}C$ and $1.4^{\circ}C$, respectively, during the last 30 years. The continuous rise in temperature presents a challenge in growing certain horticultural crops. Chinese cabbage, one most important cool season crop, may well be used as a model to study the influence of climate change on plant growth, because it is more adversely affected by elevated temperatures than warm season crops. This study examined the influence of transplanting time, nitrogen fertilizer level and climate parameters, including air temperature and growing degree days (GDD), on the performance of a Chinese cabbage cultivar (Chunkwang) during the spring growing season to estimate crop yield under the unfavorable environmental conditions. The chinese cabbage plants were transplanted from Apr. 8 to May 13, 2011 when 3~4 leaves were occurred, at internals of 7 days and cultivated with 3 levels of nitrogen fertilization. The data from plants transplanted on Apr. 22 and 29, 2012 were used for the prediction of yield as affected by planting date and nitrogen fertilization for spring production. In our study, plant dry weight was higher when the seedlings were transplanted on 15th (168 g) than on 22nd (139 g) of April. There was no significant difference in the yield when plants were grown with different levels of nitrogen fertilizer. The values of correlation coefficient ($R^2$) between GDD and number of leaves, and between GDD and dry weight of the above-ground plant parts were 0.9818 and 0.9584, respectively. Nitrogen fertilizer did not provide a good correlation with the plant growth. Results of this study suggest that the GDD values can be used as a good indicator in predicting the top biomass yield of Chinese cabbage.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.6
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• pp.185-196
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(Quality of Service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to let only the minimum number of servers needed to handle current user requests ON. Previous studies on energy aware server cluster put efforts to reduce power consumption further or to keep QoS, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management based on autonomous learning for energy aware server clusters. Using parameters optimized through autonomous learning, our method adjusts server power mode to achieve maximum performance with respect to power consumption. Our method repeats the following procedure for adjusting the power modes of servers. Firstly, according to the current load and traffic pattern, it classifies current workload pattern type in a predetermined way. Secondly, it searches learning table to check whether learning has been performed for the classified workload pattern type in the past. If yes, it uses the already-stored parameters. Otherwise, it performs learning for the classified workload pattern type to find the best parameters in terms of energy efficiency and stores the optimized parameters. Thirdly, it adjusts server power mode with the parameters. We implemented the proposed method and performed experiments with a cluster of 16 servers using three different kinds of load patterns. Experimental results show that the proposed method is better than the existing methods in terms of energy efficiency: the numbers of good response per unit power consumed in the proposed method are 99.8%, 107.5% and 141.8% of those in the existing static method, 102.0%, 107.0% and 106.8% of those in the existing prediction method for banking load pattern, real load pattern, and virtual load pattern, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.87-95
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• 2010

Portable multi-media products which can service the highest audio-quality by using lossless audio codec has been released and the international lossless codecs, MPEG-4 audio lossless coding(ALS) and MPEG-4 scalable lossless coding(SLS), were standardized by MPEG in 2006. The simple profile of MPEG-4 ALS, it supports up to stereo, was defined by MPEG in 2009. The lossless audio codec should have low-complexity in stereo to be widely used in portable multi-media products. But the previous researches of MPEG-4 ALS have focused on an improvement of compression ratio, a complexity reduction in multi-channels coding, and a selection of linear prediction coefficients(LPCs) order. In this paper, the complexity and compression ratio of MPEG-4 ALS encoder is analyzed in simple profile of MPEG-4 ALS, the method to reduce a complexity of MPEG-4 ALS encoder is proposed. Based on an analysis of complexity of MPEG-4 ALS encoder, the complexity of short-term prediction filter of MPEG-4 ALS encoder is reduced by using the low-complexity filter that is proposed in previous research to reduce the complexity of MPEG-4 ALS decoder. Also, we propose a joint coding decision method, it reduces the complexity and keeps the compression ratio of MPEG-4 ALS encoder. In proposed method, the operation of joint coding is decided based on the relation between cross-correlation of residual and compression ratio of joint coding. The performance of MPEG-4 ALS encoder that has the method and low-complexity filter is evaluated by using the MPEG-4 ALS conformance test file and normal music files. The complexity of MPEG-4 ALS encoder is reduced by about 24% by comparing with MPEG-4 ALS reference encoder, while the compression ratio by the proposed method is comparable to MPEG-4 ALS reference encoder.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.3
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• pp.166-177
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• 2006

The cache size tends to grow in the embedded processor as technology scales to smaller transistors and lower supply voltages. However, larger cache size demands more energy. Accordingly, the ratio of the cache energy consumption to the total processor energy is growing. Many cache energy schemes have been proposed for reducing the cache energy consumption. However, these previous schemes are concerned with one side for reducing the cache energy consumption, dynamic cache energy only, or static cache energy only. In this paper, we propose a hybrid scheme for reducing dynamic and static cache energy, simultaneously. for this hybrid scheme, we adopt two existing techniques to reduce static cache energy consumption, drowsy cache technique, and to reduce dynamic cache energy consumption, way-prediction technique. Additionally, we propose a early wake-up technique based on program counter to reduce penalty caused by applying drowsy cache technique. We focus on level 1 data cache. The hybrid scheme can reduce static and dynamic cache energy consumption simultaneously, furthermore our early wake-up scheme can reduce extra program execution cycles caused by applying the hybrid scheme.