• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.15 no.3
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• pp.160-165
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• 2005

Schools have significant and serious indoor environmental health problem, of which indoor air quality (IAQ) in school building may affect the health of the students and indirectly affect learning performance. Schools are of special concern when regarding indoor exposure to air pollutants, because students are particularly sensitive to pollutants and spend a significant amount of time in that environment. Therefore researches for improvement of indoor air quality have been developed such as installation of air cleaning device, ventilation system, titanium dioxide(TiO2) coating and so on. However, it is difficult to evaluate the magnitude of improvement of indoor air quality in field study because indoor air quality can be affected by source generation, outdoor air level, ventilation, decay by reaction, temperature, humidity, mixing condition and so on. In this study, evaluation of reduction of formaldehyde emission rate in school indoor environments by far-Infrared ray coating material was carried out using mass balance model in indoor environment. we proposed the evaluation method of magnitude of improvement in indoor air quality, considering outdoor level and ventilation. Since simple indoor concentration measurements could not properly evaluate the indoor air quality, outdoor level and ventilation should be considered when evaluate the indoor air quality.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.477-484
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• 1997

In this paper, we proposed the compensation method to evaluate arousal level in different initial arousal states. Arousal level was measured by the relationship between IRI and Nz. Since Nz is affected by BI which is directly proportional to initial arousal state of subjects, the arousal level is underestimated To overcome this problem, we proposed the compensation method using modified Karolinska sleepiness scale, and determined compensation coefficients derived from this scale with five arousal levels. Applying these coefficients to portable arousal monitoring system, the proposed method in this paper could be useful for real-time evaluation and control of arousal level. As a result the developed system can detect and control the arousal state from initial drowsing sate.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.9
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• pp.1237-1247
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• 2012

The objective of this study was to evaluate the predictions of dry matter intake (DMI) and average daily gain (ADG) of Vietnamese Yellow (Vang) purebred and crossbred (Vang with Red Sindhi or Brahman) bulls fed under Vietnamese conditions using two levels of solution (1 and 2) of the large ruminant nutrition system (LRNS) model. Animal information and feed chemical characterization were obtained from five studies. The initial mean body weight (BW) of the animals was 186, with standard deviation ${\pm}33.2$ kg. Animals were fed ad libitum commonly available feedstuffs, including cassava powder, corn grain, Napier grass, rice straw and bran, and minerals and vitamins, for 50 to 80 d. Adequacy of the predictions was assessed with the Model Evaluation System using the root of mean square error of prediction (RMSEP), accuracy (Cb), coefficient of determination ($r^2$), and mean bias (MB). When all treatment means were used, both levels of solution predicted DMI similarly with low precision ($r^2$ of 0.389 and 0.45 for level 1 and 2, respectively) and medium accuracy (Cb of 0.827 and 0.859, respectively). The LRNS clearly over-predicted the intake of one study. When this study was removed from the comparison, the precision and accuracy considerably increased for the level 1 solution. Metabolisable protein was limiting ADG for more than 68% of the treatment averages. Both levels differed regarding precision and accuracy. While level 1 solution had the least MB compared with level 2 (0.058 and 0.159 kg/d, respectively), the precision was greater for level 2 than level 1 (0.89 and 0.70, respectively). The accuracy (Cb) was similar between level 1 and level 2 (p = 0.8997; 0.977 and 0.871, respectively). The RMSEP indicated that both levels were on average under-or over-predicted by about 190 g/d, suggesting that even though the accuracy (Cb) was greater for level 1 compared to level 2, both levels are likely to wrongly predict ADG by the same amount. Our analyses indicated that the level 1 solution can predict DMI reasonably well for this type of animal, but it was not entirely clear if animals consumed at their voluntary intake and/or if the roughness of the diet decreased DMI. A deficit of ruminally-undegradable protein and/or a lack of microbial protein may have limited the performance of these animals. Based on these evaluations, the LRNS level 1 solution may be an alternative to predict animal performance when, under specific circumstances, the fractional degradation rates of the carbohydrate and protein fractions are not known.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.789-793
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• 2023

Evalution of counter drone systems is conducted in order to designate plausible countermeasues against possible drone threats, assess the level of safety of national major facilities and derive complementary measures for detected weakness. Recently drone threats by North Korea have heavily impacted ROK(Republic of Korea) people and it has been stronly stressed to build efficient counter drone system for make the society protected and secured against drone threats. The researchers has conducted field investigations for some of national major facilites. There is, however, no standardized evaluation checklist, so we have proposed an evaluation checklist for counter drone systems though thinking process of RMA(Revolution in Military Affairs). This paper is to introduce the evaluation checklist for properly diagnosing each counter drone system.

• Korean Journal of Computational Design and Engineering
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• v.21 no.1
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• pp.78-89
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• 2016

When a plant owner requests plant 3D CAD models in the format that a shipbuilding company does not use, the shipyard manually re-models plant 3D CAD models according to the owner's requirement. Therefore, it is important to develop a technology to compare the re-modeled plant 3D CAD models with original ones and to quantitatively evaluate similarity between two models. In the previous study, we developed a graphic user interface (GUI)-based comparison system where a user evaluates similarity between original and re-modeled plant 3D CAD models for piping design at the level of unit. However, an offshore plant consists of thousands of units and thus a system which compares several plant 3D CAD models at unit-level without human intervention is necessary. For this, we developed a new batch model comparison system which automatically evaluates similarity of several unit-level plant 3D CAD models using an extensible markup language (XML) file storing file location and name data about a set of plant 3D CAD models. This paper suggests system configuration of a batch-mode-based comparison system and discusses its core functions. For the verification of the developed system, comparison experiments for offshore plant 3D piping CAD models using the system were performed. From the experiments, we confirmed that similarities for several plant 3D CAD models at unit-level were evaluated without human intervention.

• Geomechanics and Engineering
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• v.9 no.1
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• pp.57-81
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• 2015

Water inrush and mud outburst always restricts the tunnel constructions in mountain area, which becomes a major geological barrier against the development of underground engineering. In view of the complex disaster-causing mechanism and difficult quantitative predictions of water inrush and mud outburst, several theoretical methods are adopted to realize dynamic assessment of water inrush in the progressive process of tunnel construction. Concerning both the geological condition and construction situation, eleven risk factors are quantitatively described and an assessment system is developed to evaluate the water inrush risk. In the static assessment, the weights of eight risk factors about the geological condition are determined using Analytic Hierarchy Process (AHP). Each factor is scored by experts and the synthesis scores are weighted. The risk level is ultimately determined based on the scoring outcome which is derived from the sum of products of weights and comprehensive scores. In the secondary assessment, the eight risk factors in static assessment and three factors about construction situation are quantitatively analyzed using fuzzy evaluation method. Subordinate levels and weight of factors are prepared and then used to calculate the comprehensive subordinate degree and risk level. In the dynamic assessment, the classical field of the eleven risk factors is normalized by using the extension evaluation method. From the input of the matter-element, weights of risk factors are determined and correlation analysis is carried out to determine the risk level. This system has been applied to the dynamic assessment of water inrush during construction of the Yuanliangshan tunnel of Yuhuai Railway. The assessment results are consistent with the actual excavation, which verifies the rationality and feasibility of the software. The developed system is believed capable to be back-up and applied for risk assessment of water inrush in the underground engineering construction.

• Korean Journal of Construction Engineering and Management
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• v.12 no.3
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• pp.31-41
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• 2011

The $LCCO_2$ evaluation programs previously developed in Korea involve limitations in establishing strategies of reducing environmental loads to optimal level in a way to put in materials directly after designing. Therefore, this study has the purpose to extract and propose elements required for the establishment of highly accurate system by counteracting swiftly in a method with high energy efficiency over cost at planning stage. To that end, existing $LCCO_2$ evaluation programs in Korea and abroad were compared and analyzed, and in the planning stage, GEM-21P and Carbon-navigator intended for the establishment of building energy performance improving strategy were selected as the evaluation program for survey. On such basis, after comparison and analysis between $LCCO_2$ calculating methods and system structures of the two programs, elements required for system establishment that can evaluate life-cycle environmental loads of building in planning stage were proposed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.2088-2102
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• 2009

This study is the result of meta evaluation for the self evaluation of defense R&D programs in Korea. The overall meta evaluation result gained 74.3 points out of 100, so it was evaluated as 'Good'. T- test and one-way ANOVA were used to identify the difference between groups. As a result of difference analysis between groups, some evaluation items showed difference within significance level. From this analysis, it is attempted to identify possible problems and to find out the ways of improvements related to the self evaluation system of defense R&D Programs. The ultimate objective of this study is to manage the programs effectively and improve the reliability and the objectiveness of the defense R&D performances.

• Journal of Biosystems Engineering
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• v.36 no.3
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• pp.163-170
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• 2011

Analysis of load on major parts of the tractor power drive line is critical for efficient and optimum design of a tractor. The purpose of this study was to evaluate severeness of the tractor PTO driving axle during rotary tillage operation. First, S-N (stress vs. number of cycle) curve of a PTO driving gear was obtained through the fatigue life test using a PTO dynamometer. Second, PTO severeness was evaluated during rotary tillage operation. Torque measurement system was constructed with strain-gauge sensors to measure torque of a PTO axle, an I/O interface to acquire the sensor signals, and an embedded system to calculate severeness. The severeness of PTO was analyzed using measured torque data during rotary tillage. In the PTO gear life fatigue test, breakage time and bending stress of the gear were measured by tooth widths and torque change during the fatigue life test. The S-N curve showed a good linear relationship between bending stress and number of cycle (life) with a coefficient of determination of 0.97. For PTO severenss evaluation, rotary tillage operations were conducted at two PTO rotational speeds (level-1, level-2) under different paddy and upland field sites with different soil conditions. Results of averaged relative severeness for PTO level-1 and PTO level-2 were 1.96 and 3.34, respectively, at paddy field sites, and they were 1.36 and 2.51, respectively, at upland field sites. The results showed that the PTO driving axle experienced more severe load during rotary tillage at paddy fields than at upland sites, and relative severeness was greater at the higher PTO rotational speed under all of the soil conditions.

• IE interfaces
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• v.17 no.1
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• pp.1-12
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• 2004

In a modern semiconductor device manufacturing industry, statistical bin limits on wafer level test bin data are used for minimizing value added to defective product as well as protecting end customers from potential quality and reliability excursion. Most wafer level test bin data show skewed distributions. By Monte Carlo simulation, this paper evaluates methods and sample size effect regarding determination of statistical bin limits. In the simulation, it is assumed that wafer level test bin data follow the Poisson distribution. Hence, typical shapes of the data distribution can be specified in terms of the distribution's parameter. This study examines three different methods; 1) percentile based methodology; 2) data transformation; and 3) Poisson model fitting. The mean square error is adopted as a performance measure for each simulation scenario. Then, a case study is presented. Results show that the percentile and transformation based methods give more stable statistical bin limits associated with the real dataset. However, with highly skewed distributions, the transformation based method should be used with caution in determining statistical bin limits. When the data are well fitted to a certain probability distribution, the model fitting approach can be used in the determination. As for the sample size effect, the mean square error seems to reduce exponentially according to the sample size.