• KIEAE Journal
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• 제12권3호
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• pp.53-60
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• 2012

This research is an illustrative research to verify the thermo environmental change created after introduction of indoor pond through abridged model test and simulation analysis. Especially, temperature and comfort level are analyzed by adjusting factors like size of water space, distance length, and location. Summary of the research is as follows. First, the most effective size of water space is 7% of the indoor size, from southern side. Temperature reduction effect is about $1.6^{\circ}C$(5.5%), and for the comfort level, it is found that pmv index increases 8%. Second, based on the simulation of distance length with the sphere, it is more effective as it is close to the surface. If distance length is more than 0.5m, there is no effect on reduction of temperature and comfort level of indoor environment. Lastly, for the analysis by location of the introduced water space, simulation is undertaken by dividing the water space (14% of the indoor size) with front, side, rear and center types. Temperature reduction effect is found to be : front type ($-1.53^{\circ}C$), side type ($-0.82^{\circ}C$), rear type ($-0.44^{\circ}C$), center type ($-0.28^{\circ}C$), respectively. The indoor environment change data by introduction of water space, found in this research, is at initial phase, but it is deemed to be a basic data to refer when planning actual water space.

• 한국인공지능학회지
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• 제11권1호
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• pp.17-24
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• 2023

With the continuous growth in the amount of data collected and analyzed, deep learning has become increasingly popular for extracting meaningful insights from various fields. However, hardware limitations pose a challenge for achieving meaningful results with limited data. To address this challenge, this paper proposes an algorithm that leverages the characteristics of convolutional neural networks (CNNs) to reduce the size of image datasets by 20% through smoothing and shrinking the size of images using color elements. The proposed algorithm reduces the learning time and, as a result, the computational load on hardware. The experiments conducted in this study show that the proposed method achieves effective learning with similar or slightly higher accuracy than the original dataset while reducing computational and time costs. This color-centric dataset construction method using image smoothing techniques can lead to more efficient learning on CNNs. This method can be applied in various applications, such as image classification and recognition, and can contribute to more efficient and cost-effective deep learning. This paper presents a promising approach to reducing the computational load and time costs associated with deep learning and provides meaningful results with limited data, enabling them to apply deep learning to a broader range of applications.

• Geomechanics and Engineering
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• 제14권2호
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• pp.151-159
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• 2018

Annually, the global production of construction aggregates reaches over 40 billion tons, making aggregates the largest mining sector by volume and value. Currently, the aggregate industry is shifting from sand to hard rock as a result of legislation limiting the extraction of natural sands and gravels. A major implication of this change in the aggregate industry is the need for understanding rock fragmentation and energy absorption to produce more cost-effective aggregates. In this paper, we focused on incorporating dynamic rock and soil mechanics to understand the effects of loading rate and water saturation on the rock fragmentation and energy absorption of three different sandstones (Red, Berea and Buff) with different pore sizes. Rock core samples were prepared in accordance to the ASTM standards for compressive strength testing. Saturated and dry samples were subsequently prepared and fragmented via fast and dynamic compressive strength tests. The particle size distributions of the resulting fragments were subsequently analyzed using mechanical gradation tests. Our results indicate that the rock fragment size generally decreased with increasing loading rate and water content. In addition, the fragment sizes in the larger pore size sample (Buff sandstone) were relatively smaller those in the smaller pore size sample (Red sandstone). Notably, energy absorption decreased with increased loading rate, water content and rock pore size. These results support the conclusion that rock fragment size is positively correlated with the energy absorption of rocks. In addition, the rock fragment size increases as the energy absorption increases. Thus, our data provide insightful information for improving cost-effective aggregate production methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.523-524
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• 2008

Proposed battery charger is a economic candidate because that is simple and small size. The circuit has linearly operational power stage. That use small size buffer with small driving current and large power MOS gate capacitance. The simulation result show that charging current is stable and has low ripple.

• 한국방사선학회논문지
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• 제12권2호
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• pp.179-184
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• 2018

본 연구는 표준 감마선 조사장치의 유효빔 크기를 실측과 시뮬레이션의 결과를 비교하여 유효빔 영역의 결정에 유용한 수단을 제공하고자 하였다. 시뮬레이션과 전리함을 이용한 실측의 결과는 공기커마율의 경우는 상대오차 4.5~7.3% 범위에 분포하였다. 유효빔 영역의 크기는 시뮬레이션의 경우 수평 방향 27cm, 수직 방향 21.6cm로 구현되었고, 필름을 이용한 실측결과는 수평 방향 26.5cm, 수직 방향 21.9cm로 유사한 결과가 도출되었다. 수평방향의 상대오차는 1.85%, 수직 방향은 1.38% 이며 유효빔 영역도 감마선장을 중심으로 유사하게 분포하였다. 감마선 조사장치에 있어서 시뮬레이션의 유효성이 충분함을 확인하였다. 특히 공기커마율보다 유효빔 크기의 상대오차가 적은 것은 빔의 크기가 표준선원의 용량보다는 기하학적 요인으로 결정되기 때문인 것으로 판단된다. 향후 시뮬레이션을 이용한 광자 에너지 분포도의 신뢰성을 높이기 위한 연구가 필요 할 것이다.

• 한국산림과학회지
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• 제96권5호
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• pp.528-532
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• 2007

Clonal differences in fertility (expressed as the number of female and male strobili) were determined for five consecutive years (2002-2006) in a clonal seed orchard of Chamaecyparis obtusa. Fertility varied among clones and among years with producing five-year averages of 378.8 and 871.2 for female and male strobili per ramet, respectively. Correlation between female and male strobilus production was positive over the five years and statistically significant. Based on the observed fertility variation, the effective population sizes (estimated by status numbers, $N_e$) were calculated and varied from 24.3 to 47.9 (48.6% to 95.8% of census number, N) among the five studied years. On average (pooled), the relative effective population size was 82% of the N. Variation in female fertility was higher than that in male fertility, and this variation was reflected on female and male parents' status numbers. Pooled $N_e$ estimated from the five years was higher than that from poor seed production years. From our results, it was concluded that genetic diversity collected from good flowering years would be higher than that from poor flowering years.

• Journal of Biosystems Engineering
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• 제18권2호
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• pp.100-109
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• 1993

The aim of this study was to provide the reasonable data for design of the nozzle which produces finer droplets on the same level of the effective travel distance or which transports droplets to the farther target on the reasonable atomization in comparison with the commercial nozzles being used much in Korean rural areas. Newly designed twin-fluid atomizers with some commercial nozzles were tested in this study, and their results were as follows : 1. The characteristics of the spray deposit distribution of No.1 nozzles for farther target were nearly same in the near or nearer travel distance less than 8m. Therefore it was reasonable to combine the characteristics of the spray deposit distributions of No.2 and No.3 nozzles to those of No.1 nozzle. 2. The effective travel distance was increased with increase of the sectional area of the jet ligament, and the maximum effective travel distance was reached to about 17m. 3. The droplet size was increased with increase of the sectional area of the jet ligament, and the maximum droplet size was produced in the front of the point of the maximum spray deposit distribution. 4. The atomization was excellent in the twin-fluid atomizer in comparison with the hydraulic atomizer and also the effective travel distances were nearly same level in both atomizers.

• Advances in nano research
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• 제14권2호
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• pp.155-164
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• 2023

Grain size in sheet metals in one of the main parameters in determining formability. Grain size control in industry requires delicate process control and equipment. In the present study, effects of grain size on the formability of steel sheets is investigated. Experimental investigation of effect of grain size is a cumbersome method which due to existence of many other effective parameters are not conclusive in some cases. On the other hand, since the average grain size of a crystalline material is a statistical parameter, using traditional methods are not sufficient for find the optimum grain size to maximize formability. Therefore, design of experiment (DoE) and artificial intelligence (AI) methods are coupled together in this study to find the optimum conditions for formability in terms of grain size and to predict forming limits of sheet metals under bi-stretch loading conditions. In this regard, a set of experiment is conducted to provide initial data for training and testing DoE and AI. Afterwards, the using response surface method (RSM) optimum grain size is calculated. Moreover, trained neural network is used to predict formability in the calculated optimum condition and the results compared to the experimental results. The findings of the present study show that DoE and AI could be a great aid in the design, determination and prediction of optimum grain size for maximizing sheet formability.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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• pp.119-128
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• 1993

Effective machine capacity is affected by the physical and geometrical conditions of the fields. In the small and scattered farmland structure field efficiency is greatly influenced by plot geometry. In this paper, a method for estimating field efficiency and effective machine capacity was developed . The developed method was applied to Korean paddy cultivation. Various time elements related to farm operations for small and scattered plots are discussed in this paper . Available working time is divided into two parts, viz. the preparation time for machine operation and actual working time. Two kinds of machine efficiencies, namely , Machine Efficiency 1, applicable on a single large plot or set of well consolidated plots ; and Machine Efficiency 2, applicable on small and scattered multiple plots, are considered. Based assumptions made and steps followed to construct the model are discussed. Effective capacity of each machine based on different plot geometries are calculated y the model. Machine efficiency on a single plot increases with increase in the dimension of longer side of the plot . Low speed, low theoretical capacity machines have higher machine efficiency which is only slightly influenced by plot geometry. As plot geometry is improved , the machine efficiency of high speed, high capacity machines increases rapidly. The effects of short side length and plot size on machine efficiency on a single plot depend on the type of farm operation. For a particular plot shape, as plot size increases, machine efficiency on multiple plots increases rapidly. The effects of consolidation on machine efficiency is highly significant if the plot size is small and/or machine size is large.

• Asian-Australasian Journal of Animal Sciences
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• 제25권8호
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• pp.1063-1072
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• 2012

Effective population size ($N_e$) is an important measure to understand population structure and genetic variability in animal species. The objective of this study was to estimate $N_e$ in Sapsaree dogs using the information of rate of inbreeding and genomic data that were obtained from pedigree and the Illumina CanineSNP20 (20K) and CanineHD (170K) beadchips, respectively. Three SNP panels, i.e. Sap134 (20K), Sap60 (170K), and Sap183 (the combined panel from the 20K and 170K), were used to genotype 134, 60, and 183 animal samples, respectively. The $N_e$ estimates based on inbreeding rate ranged from 16 to 51 about five to 13 generations ago. With the use of SNP genotypes, two methods were applied for $N_e$ estimation, i.e. pair-wise $r^2$ values using a simple expectation of distance and $r^2$ values under a non-linear regression with respective distances assuming a finite population size. The average pair-wise $N_e$ estimates across generations using the pairs of SNPs that were located within 5 Mb in the Sap134, Sap60, and Sap183 panels, were 1,486, 1,025 and 1,293, respectively. Under the non-linear regression method, the average $N_e$ estimates were 1,601, 528, and 1,129 for the respective panels. Also, the point estimates of past $N_e$ at 5, 20, and 50 generations ago ranged between 64 to 75, 245 to 286, and 573 to 646, respectively, indicating a significant $N_e$ reduction in the last several generations. These results suggest a strong necessity for minimizing inbreeding through the application of genomic selection or other breeding strategies to increase $N_e$, so as to maintain genetic variation and to avoid future bottlenecks in the Sapsaree population.