• Journal of Acupuncture Research
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• v.17 no.1
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• pp.89-105
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• 2000

In order to obtain the clinical data on the different effects of the three different methods of indirect moxibustion, moxa-combustion time, peak temperature, average temperature, maximum gradient temperature, average gradient temperature, and moxa-combustion calorie rate of the input period in ARIRANG, JANG, PUNG were measured through this experiment. The results of the experiment were as follows : 1. In the combustion time, during the input period ARIRANG had the longest combustion time followed by PUNG, JANG in a descending order but these were not acknowledged to have significant difference each other. 2. In the peak temperature of the input period, PUNG had the highest temperature followed by ARIRANG, JANG in a descending order. ARIRANG and JANG were acknowledged to have significant difference with PUNG. ARIRANG and JANG however were not acknowledged to have difference each other. 3. In the average temperature, during the input period, PUNG had the highest temperature followed by JANG, ARIRANG in a descending order. ARIRANG and JANG were acknowledged to have significant difference with PUNG. ARIRANG and JANG however were not acknowledged to have difference each other. 4. In the maximum gradient temperature, during the input period, PUNG had the highest temperature followed by ARIRANG, JANG in a descending order. ARIRANG and JANG were acknowledged to have significant difference with PUNG. ARIRANG and JANG however were not acknowledged to have difference each other. 5. In the average gradient temperature, during the input period, PUNG had the highest temperature followed by ARIRANG, JANG in a descending order. ARIRANG and JANG were acknowledged to have significant difference with PUNG. ARIRANG and JANG however were not acknowledged to have difference each other. 6. In the moxa-combustion calorie rate, during the input period, JANG had the highest temperature followed by ARIRANG, PUNG in a descending order. ARIRANG and PUNG were acknowledged to have significant difference with JANG. ARIRANG and PUNG however were not acknowledged to have difference each other.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.8-14
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• 2019

Most of the data envelopment analysis (DEA) models evaluate the relative efficiency of a decision making unit (DMU) based on the assumption that inputs in a specific period are consumed to produce the output in the same period of time. However, there may be some time lag between the consumption of input resources and the production of outputs. A few models to handle the concept of the time lag effect have been proposed. This paper suggests a new multi-period input DEA model considering the consistent time lag effects. Consistency of time lag effect means that the time delay for the same input factor or output factor are consistent throughout the periods. It is more realistic than the time lag effect for the same output or input factor can vary over the periods. The suggested model is an output-oriented model in order to adopt the consistent time lag effect. We analyze the results of the suggested model and the existing multi period input model with a sample data set from a long-term national research and development program in Korea. We show that the suggested model may have the better discrimination power than existing model while the ranking of DMUs is not different by two nonparametric tests.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.127-134
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• 2023

Recently, various input shapers have been introduced to reduce residual vibrations of flexible robots. However, there have been no studies on the design of an input shaper that can suppress residual vibration at an arbitrarily specified duration. In this paper, a novel input shaper called an SD (specified-duration) shaper is proposed for an undamped or underdamped system, which can suppress residual vibration at an arbitrarily given specified duration. If the specified duration is larger than a half period, a positive SD shaper composed of all positive impulses is designed, and if the specified duration is smaller than a half period, a negative SD shaper including a negative impulse is designed. As the specified duration is increased every half period after a half period, the number of impulses of the positive SD shaper is increased one by one, and the robustness of the SD shaper to modeling errors is increased. The performance of the SD shaper is analyzed through simulation studies for an undamped and underdamped second-order systems. The validity of the SD shapers is demonstrated experimentally using an experimental device that can generate container transport motions.

• Journal of the Korean Society of Safety
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• v.21 no.4 s.76
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• pp.102-107
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• 2006

Construction accidents have not decreased in spite of much effort such as new work methods, education and research related to safety works. Specially, many fatal accidents happened in construction works which involve the apartment, building, school, church, hotel, hospital, bank work and the other works. These accidents are mainly caused by unanticipated risk factors. From these reasons, this study researched fatal accidents which happened in construction works during last 13 years($1992{\sim}2004$) and analyzed the input workers and a work period of construction work. According to the input workers and a work period, the results are as following. During 13years($1992{\sim}2004$), the fatal accidents, related to the construction work, were happened to the 1,977 cases. These results were occupied the 21.32% of the total industry accidents. According to the result of the construction, the fatal accident rate of a concrete form work was the highest rate of 16.24% (321 cases) and a temporary work, a steel frame work was the each rate of 12.39%(245 cases), 10.07%(199 cases). Comparing to other work types, the fatal accident rate of those three work types(concrete form work, temporary work, steel work) was represented highly. We surveyed input workers and work period of construction work site. From the result of survey, input workers of a concrete form work were occupied with 13,720. The risk rate of the work type, which was considered input workers and work period, was represented 0.3622(a steel frame work), 0.1142(a temporary work), 0.0782(a tower crane) and 0.0772(a concrete work).

• Journal of the Earthquake Engineering Society of Korea
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• v.18 no.2
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• pp.89-94
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• 2014

Spatial variations of a seismic wave are mainly wave passage and wave scattering. Wave passage effect is produced by changed characteristics of exciting seismic input motions applied to the bedrock. Modified input motions travel horizontally with time differences determined by apparent shear wave velocity of the bedrock. In this study, wave passage effect on the seismic response of a structure-soil system is investigated by modifying the finite element software of P3DASS (Pseudo 3-Dimensional Dynamic Analysis of a Structure-soil System) to apply inconsistent (time-delayed) seismic input motions along the soft soil-bedrock interface. Study results show that foundation size affected on the seismic response of a structure excited with inconsistent input motions in the lower period range below 0.5 seconds, and seismic responses of a structure were decreased considerably in the lower period range around 0.05 seconds due to the wave passage. Also, shear wave velocity of the bedrock affected on the seismic response of a structure in the lower period range below 0.3 seconds, with significant reduction of the seismic response for smaller shear wave velocity of the bedrock reaching approximately 20% for an apparent shear wave velocity of 1000m/s at a period of 0.05 seconds. Finally, it is concluded that wave passage effect reduces the seismic response of a structure in the lower period range when the bedrock under a soft soil is soft or the bedrock is located very deeply, and wave passage is beneficial for the seismic design of a short period structure like a nuclear container building or a stiff low-rise building.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.57-65
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• 2022

DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU's input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.

• Fisheries and Aquatic Sciences
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• v.6 no.4
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• pp.194-202
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• 2003

Budgets for water, nitrogen, and chemical oxygen demand (COD) were determined in two 0.012 ha earthy-bottom ponds stocked with Israeli strain common carp at an initial stocking density of $20\;fish/m^3$. Total ammonia nitrogen (TAN) concentrations increased continuously but later decreased in pond A as a consequence of high nitrification. COD concentrations increased during the experimental period due to the accumulation of feed input. Nutrient budgets showed that feed represented $94-95\%$ of nitrogen input and about 99% of organic matter input. Fish harvest accounted for $40\%$ of nitrogen and organic matter input. Seepage and water exchange removed $15-17\%$ of nitrogen input but only $1-2\%$ of organic matter. Draining of the ponds removed $20-26\%$ of input nitrogen, mostly in inorganic forms, but removed only minus organic matter. Fish and water column respiration accounted for $39\%$ of organic matter input, and benthic respiration accounted for $7-12\%$ of organic matter input. No significant change of nitrogen and organic matter in both pond bottoms were found during the three-month growth period. The unrecovered input nitrogen, about $6.3-13\%$, was lost through denitrification and ammonia volatilization. On a dry matter basis, fish growth removed $31\%$ of total feed input and left $69\%$ as metabolic wastes.

• Earthquakes and Structures
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• v.23 no.2
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• pp.115-128
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• 2022

One common method to select input ground motions to predict dynamic behavior of structures subjected to seismic excitation requires spectral acceleration (S_a) match target mean response spectrum. However, dispersion of ground motions, which explicitly affects the structural response, is rarely discussed in this method. Generally, selecting ground motions matching target mean and variance has been utilized as an appropriate method to predict reliable seismic response. The goal of this paper is to investigate the impact of target spectra variance of ground motions on structural seismic response. Two sets of ground motions with different target variances (zero variance and minimum variance larger than inherent variance of the target spectrum) are selected as input to two different structures. Structural responses at different heights are compared, in terms of peak, mean and dispersion. Results show that increase of target spectra variance tends to increase peak floor acceleration, peak deformation and dispersions of response of interest remarkably. To short-period structures, dispersion increase ratios of seismic response are close to that of S_a of input ground motions at the first period. To long-period structures, dispersions of floor acceleration and floor response spectra increase more significantly at the bottom, while dispersion increase ratios of IDR and deformation are close to that of S_a of input ground motions at the first period. This study could further provide useful information on selecting appropriate ground motion to predict seismic behavior of different types of structures.

• International Journal of Highway Engineering
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• v.16 no.5
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• pp.99-108
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• 2014

PURPOSES : The travel times of expressway buses have been estimated using the travel time data between entrance tollgates and exit tollgates, which are produced by the Toll Collections System (TCS). However, the travel time data from TCS has a few critical problems. For example, the travel time data include the travel times of trucks as well as those of buses. Therefore, the travel time estimation of expressway buses using TCS data may be implicitly and explicitly incorrect. The goal of this study is to improve the accuracy of the expressway bus travel time estimation using DSRC-based travel time by identifying the appropriate analysis period of input data. METHODS : All expressway buses are equipped with the Hi-Pass transponders so that the travel times of only expressway buses can be extracted now using DSRC. Thus, this study analyzed the operational characteristics as well as travel time patterns of the expressway buses operating between Seoul and Dajeon. And then, this study determined the most appropriate analysis period of input data for the expressway bus travel time estimation model in order to improve the accuracy of the model. RESULTS : As a result of feasibility analysis according to the analysis period, overall MAPE values were found to be similar. However, the MAPE values of the cases using similar volume patterns outperformed other cases. CONCLUSIONS : The best input period was that of the case which uses the travel time pattern of the days whose total expressway traffic volumes are similar to that of one day before the day during which the travel times of expressway buses must be estimated.

• Asia pacific journal of information systems
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• v.7 no.1
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• pp.67-83
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• 1997

The utility of learning techniques in investment analysis has been demonstrated in many areas, ranging from forecasting individual stocks to entire market indexes. To date, however, the application of artificial intelligence to financial forecasting has focused largely on short predictive horizons. Usually the forecast window is a single period ahead; if the input data involve daily observations, the forecast is for one day ahead; if monthly observations, then a month ahead; and so on. Thus far little work has been conducted on the efficacy of long-term prediction involving multiperiod forecasting. This paper examines the impact of alternative procedures for extended prediction using knowledge discovery techniques. One dimension in the study involves temporal granularity: a single jump from the present period to the end of the forecast window versus a web of short-term forecasts involving a sequence of single-period predictions. Another parameter relates to the numerosity of input variables: a technical approach involving only lagged observations of the target variable versus a fundamental approach involving multiple variables. The dual possibilities along each of the granularity and numerosity dimensions entail a total of 4 models. These models are first evaluated using neural networks, then compared against a multi-input jump model using case based reasoning. The computational models are examined in the context of forecasting the S&P 500 index.