• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.442-448
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• 2023

This study aimed to develop an optimal greenhouse model for strawberry seedling during the summer high-temperature period based on the results of field surveys. We conducted a survey on the structure types of 46 strawberry seedling farms nationwide, including width, ridge height, eaves height, ventilation method, seedling bed width, and spacing. Based on the survey results, we derived the optimal greenhouse model by considering various factors. The greenhouse width was set at 14 meters to maximize the efficiency of seedling beds and overall space. The height was determined at 2 meters, taking into account ventilation during the summer season. To reduce stress on the supporting structure due to snow loads, we established a reinforcement installation angle of 50 degrees. We analyzed two different models that use support beams with dimensions of φ48.1×2.1t and φ59.9×3.2t, respectively, to ensure structural safety against meteorological disasters, considering regional design wind speeds and snow accumulation. We utilized these developed greenhouse model to conduct strawberry seedling experiments, resulting in a high survival rate of average 93.2%. These findings confirm the usefulness of the strawberry seedling greenhouse in improving the seedling environment and enhancing overall efficiency.

• The Journal of the Acoustical Society of Korea
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• v.43 no.5
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• pp.484-493
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• 2024

This paper discusses the process and results of experimental research aimed at reducing Underwater Radiated Noise (URN) using air injection technology. Air Lubrication System (ALS) is an air injection technology mainly installed and operated to improve the propulsion efficiency of large commercial ship, such as LNGC. Recently, research institutes have been studying the potential of reducing URN using ALS. This paper performs an experiment as part of such research. The experiment was conducted in the Large Cavitation Tunnel (LCT), and the major devices applied in the experiment fall into two categories: ALS, which is directly applied to the model in use for LNGC and a modified air injection belt developed from the Masker-Air System (MAS), which is being developed to reduce URN of naval ships. The environmental conditions for the experiment mainly include the air injection flow rate and flow speed in the LCT. The flow rate was set to the actual air injection conditions of ALS, and the flow speed was adjusted to two different levels, considering the actual speeds of LNGC. The noise reduction performance was confirmed by calculating insertion loss with and without air injection.

• Journal of Technology Innovation
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• v.11 no.1
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• pp.147-176
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• 2003

This Paper Presents a new measurement technique to derive the level of BSRC (Basic Science and Research Capacity) index by use of the factor analysis which is extended with the assumption of the standard normal probability distribution of the selected explanatory variables. The new measurement method is used to forecast the gap of Korea's BSRC level compared with those of major OECD countries in terms of time lag and to make their international comparison during the time period of 1981∼1999, based on the assumption that the BSRC progress function of each country takes the form of the logistic curve. The US BSRC index is estimated to be 0.9878 in 1981, 0.9996 in 1990 and 0.99991 in 1999, taking the 1st place. The US BSRC level has been consistently the top among the 16 selected variables, followed by Japan, Germany, France and the United Kingdom, in order. Korea's BSRC is estimated to be 0.2293 in 1981, taking the lowest place among the 16 OECD countries. However, Korea's BSRC indices are estimated to have been increased to 0.3216 (in 1990) and 0.44652 (in 1999) respectively, taking 10th place. Meanwhile, Korea's BSRC level in 1999 (0.44652) is estimated to reach those of the US and Japan in 2233 and 2101, respectively. This means that Korea falls 234 years behind USA and 102 years behind Japan, respectively. Korea is also estimated to lag 34 years behind Germany, 16 years behind France and the UK, 15 years behind Sweden, 11 years behind Canada, 7 years behind Finland, and 5 years behind the Netherlands. For the period of 1981∼1999, the BSRC development speed of the US is estimated to be 0.29700. Its rank is the top among the selected OECD countries, followed by Japan (0.12800), Korea (0.04443), and Germany (0.04029). the US BSRC development speed (0.2970) is estimated to be 2.3 times higher than that of Japan (0.1280), and 6.7 times higher than that of Korea. German BSRC development speed (0.04029) is estimated to be fastest in Europe, but it is 7.4 times slower than that of the US. The estimated BSRC development speeds of Belgium, Finland, Italy, Denmark and the UK stand between 0.01 and 0.02, which are very slow. Particularly, the BSRC development speed of Spain is estimated to be minus 0.0065, staying at the almost same level of BSRC over time (1981 ∼ 1999). Since Korea shows BSRC development speed much slower than those of the US and Japan but relative]y faster than those of other countries, the gaps in BSRC level between Korea and the other countries may get considerably narrower or even Korea will surpass possibly several countries in BSRC level, as time goes by. Korea's BSRC level had taken 10th place till 1993. However, it is estimated to be 6th place in 2010 by catching up the UK, Sweden, Finland and Holland, and 4th place in 2020 by catching up France and Canada. The empirical results are consistent with OECD (2001a)'s computation that Korea had the highest R&D expenditures growth during 1991∼1999 among all OECD countries ; and the value-added of ICT industries in total business sectors value added is 12% in Korea, but only 8% in Japan. And OECD (2001b) observed that Korea, together with the US, Sweden, and Finland, are already the four most knowledge-based countries. Hence, the rank of the knowledge-based country was measured by investment in knowledge which is defined as public and private spending on higher education, expenditures on R&D and investment in software.

• Journal of Life Science
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• v.20 no.4
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• pp.549-554
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• 2010

Increased external rotation and decreased internal rotation have been noted to occur progressively in the throwing shoulders of baseball pitchers. The purpose of this study was to provide descriptive data for terminal range eccentric antagonist/concentric agonist shoulder muscle strength in collegiate baseball pitchers with humeral head retroversion diagnosed through MRI. The dominant and non-dominant shoulders of 9 asymptomatic baseball pitchers were tested through a range of 20 degrees of external rotation to 90 degrees of internal rotation using the Biodex system 3 isokinetic dynamometer at speeds of $90^{\circ}/s$ and $180^{\circ}/s$. Differences between the dominant and non-dominant shoulders were assessed using the paired samples t-test. Total range of motion, measured at $90^{\circ}$ of glenohumeral abduction, was $180.1^{\circ}$ for dominant shoulders and $183.7^{\circ}$ for non-dominant shoulders. Humeral head retroversion measured $47.6{\pm}6.1^{\circ}$ in dominant and $37.8{\pm}5.3^{\circ}$ in non-dominant extremities. The mean internal rotator concentric contraction (IR-Con) showed a significant difference compared to $31.5{\pm}5.1$ (Nm) in dominant and $38.7{\pm}5.2$ (Nm) in non-dominant shoulders at $180^{\circ}/s$ (p<0.05). The mean external rotator eccentric contraction (ER-Ecc) showed a significant difference compared to $20.3{\pm}4.7$ (Nm) in dominant and $25.1{\pm}3.7$ (Nm) in non-dominant shoulders at $90^{\circ}/s$ (p<0.05). There is a pattern of increased external rotation and decreased internal rotation in the dominant extremity that significantly correlates with an increase in humeral retroversion.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.477-487
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• 2012

Sea surface winds in the sea off the east coast of Korea were derived from L-band ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) data and their characteristics of errors were analyzed. We could retrieve high-resolution wind vectors off the east coast of Korea including the coastal region, which has been substantially unavailable from satellite scatterometers. Retrieved SAR-wind speeds showed a good agreement with in-situ buoy measurement by showing relatively small an root-mean-square (RMS) error of 0.67 m/s. Comparisons of the wind vectors from SAR and scatterometer presented RMS errors of 2.16 m/s and $19.24^{\circ}$, 3.62 m/s and $28.02^{\circ}$ for L-band GMF (Geophysical Model Function) algorithm 2009 and 2007, respectively, which tended to be somewhat higher than the expected limit of satellite scatterometer winds errors. L-band SAR-derived wind field exhibited the characteristic dependence on wind direction and incidence angle. The previous version (L-band GMF 2007) revealed large errors at small incidence angles of less than $21^{\circ}$. By contrast, the L-band GMF 2009, which improved the effect of incidence angle on the model function by considering a quadratic function instead of a linear relationship, greatly enhanced the quality of wind speed from 6.80 m/s to 1.14 m/s at small incident angles. This study addressed that the causes of wind retrieval errors should be intensively studied for diverse applications of L-band SAR-derived winds, especially in terms of the effects of wind direction and incidence angle, and other potential error sources.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.100-119
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• 2020

During recent years, the heat environment and particulate matter (PM₁₀) have become serious environmental problems, as increases in heat waves due to rising global temperature interact with weakening atmospheric wind speeds. There exist urban heat islands and urban pollution islands with higher temperatures and air pollution concentrations than other areas. However, few studies have examined these issues together because of a lack of micro-scale data, which can be constructed from spatial data. Today, with the help of satellite images and big data collected by private telecommunication companies, detailed spatial distribution analyses are possible. Therefore, this study aimed to examine the spatial distribution patterns of urban heat islands and urban pollution islands within Busan Metropolitan City and to compare the distributions of the two phenomena. In this study, the land surface temperature of Landsat 8 satellite images, air temperature and particulate matter concentration data derived from a private automated meteorological observation system were gridded in 30m × 30m units, and spatial analysis was performed. Analysis showed that simultaneous zones of urban heat islands and urban pollution islands included some vulnerable residential areas and industrial areas. The political migration areas such as Seo-dong and Bansong-dong, representative vulnerable residential areas in Busan, were included in the co-occurring areas. The areas have a high density of buildings and poor ventilation, most of whose residents are vulnerable to heat waves and air pollution; thus, these areas must be considered first when establishing related policies. In the industrial areas included in the co-occurring areas, concrete or asphalt concrete-based impervious surfaces accounted for an absolute majority, and not only was the proportion of vegetation insufficient, there was also considerable vehicular traffic. A hot-spot analysis examining the reliability of the analysis confirmed that more than 99.96% of the regions corresponded to hot-spot areas at a 99% confidence level.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

• Journal of the korean academy of Pediatric Dentistry
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• v.30 no.3
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• pp.373-384
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• 2003

The purpose of this study was to evaluate the eruption pattern of a cyst-associated mandibular premolar after marsupialization of a dentigerous cyst in children. The result from the twenty two pairs of normalized panoramic radiographs of twenty two patients who underwent neither extraction nor orthodontic traction of the cyst-associated mandibular after marsupialization were as follows. 1. The eruption speed of a cyst-associated premolar was 3.5 times faster than that of the normal contra-lateral premolar(p<0.05). The angulation change of test group was an average of $2.7^{\circ}$ per month. 2. In the change of the level of root formation, the group which had a little root maturity tended to be faster in the eruption speed(p>0.05) and the R1/4 group had a great change in the angulation change(p>0.05). 3. In the change to be with the cusp position index, the eruption speeds were increased to the 30% deviation groups. But, the eruption speed was decreased above that(p>0.05). 4. Group with cyst diminishment rate of more than $80mm^2$ per month showed the fastest eruption speed of all(p<0.05). 5. The mesial angulated teeth in the test group were decreased more rapidly than the distal angulated teeth in the eruption speed(p>0.05). But, increased in the angulation change(p<0.05). 6. There was a tendency of faster tooth eruption with less deviation of tooth axis. Group with tooth axis deviation of less than $15^{\circ}$ showed the fastest angulation change of all(p<0.05). 7. The eruption speed and the angulation change rapidly decreased during the first 6 months following marsupialization. Based on the results of this study, a cyst-associated mandibular premolar erupted more rapidly after marsupializaton. We thought so that it's prognosis was good if the tooth had a little root maturity, a little devitation and cyst lesion healed faster. We recommend that if there is enough space for eruption, orthodontic traction and surgical treatment of the cyst-associated tooth should be postponed 6 months after marsupialization.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.29-42
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• 2016

Remote sensing allows acquisition of information across a large area without contacting objects, and has thus been rapidly developed by application to different areas. Thus, with the development of remote sensing, satellites are able to rapidly advance in terms of their image resolution. As a result, satellites that use remote sensing have been applied to conduct research across many areas of the world. However, while research on remote sensing is being implemented across various areas, research on data processing is presently insufficient; that is, as satellite resources are further developed, data processing continues to lag behind. Accordingly, this paper discusses plans to maximize the performance of satellite image processing by utilizing the CUDA(Compute Unified Device Architecture) Library of NVIDIA, a parallel processing technique. The discussion in this paper proceeds as follows. First, standard KOMPSAT(Korea Multi-Purpose Satellite) images of various sizes are subdivided into five types. NDVI(Normalized Difference Vegetation Index) is implemented to the subdivided images. Next, ArcMap and the two techniques, each based on CPU or GPU, are used to implement NDVI. The histograms of each image are then compared after each implementation to analyze the different processing speeds when using CPU and GPU. The results indicate that both the CPU version and GPU version images are equal with the ArcMap images, and after the histogram comparison, the NDVI code was correctly implemented. In terms of the processing speed, GPU showed 5 times faster results than CPU. Accordingly, this research shows that a parallel processing technique using CUDA Library can enhance the data processing speed of satellites images, and that this data processing benefits from multiple advanced remote sensing techniques as compared to a simple pixel computation like NDVI.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.2049-2056
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• 2013

With the advance in information communication, the information age has come, and desire of human being in increasing. In this circumstance, the necessity for design for building of superhighways is arising to improve the mobility in the field of transportation, too. This study was conducted to analyze if driver can drive at a design speed on a superhighway with a design speed exceeding 120km/h. For this study, it was experimented if the running speed that makes a driver feel anxious, increased, when road alignment and standard improved, due to the differences of design speed. For the experiment, 30 subjects were asked to attach brain wave analyzers to bodies. Then, this study compared powers of ${\beta}$ waves generated, when they felt anxious, driving on the roads with different design speeds, and driving virtually through a simulator. Here, Kangbyeonbukro (90km/h), Jayuro(100km/h), Joongang Expressway(110km/h), and Seohaean Expressway(120km/h) were selected as experimental sections. While drivers drove on the Kangbyeonbukro and Jayuro at a speed of 80km/h - 130km/h, on the Joongang Expressway at a speed of 100km/h - 150km/h, and Seohaean Expressway at a speed of 110km/h - 180km/h, powers of anxiety EEGs(electroencephalogram) were compared, and during the simulation driving at the same speed of 110km/h - 180km/h, powers of anxiety EEGs were compared and analyzed. Moreover, the speed when anxiety EEGs increased, was statistically verified through paired t-test. As the result, the speed when anxiety EEGs increased during the simulation driving was nearly 30km/h higher than when they increased during the actual driving on the expressways, and anxiety EEGs increased at the same speed, when subjects drove on the roads with a design speed of 90km/h and 100km/h. It means that there were small differences in road alignment and standard. However, the running speed to make drivers feel anxious was increased at both roads with a design speed of 110km/h and 120km/h. It implies that drivers can drive at a higher speed, as road alignment and standard improve.