• Korean Journal of Organic Agriculture
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• v.7 no.2
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• pp.115-124
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• 1999

This study was conducted to investigate the effects of fertigation level such as 50%, 75% and 100% N of standard amount of chemical fertilizer,m and fertigation interval such as every irrigation, intervals of 1 and 2 weeks of piggery waste water(PWW) on the growth, yield of red pepper plant and the chemical properties of soil used. In early stage, growth of red pepper plant fertigated with PWW and that of red pepper plant applicated standard chemical fertilezer was the same, while it were increased as increasing application amounts of PWW, and later growth and total yield of red pepper plant were much more at 75% N fertigation of PWW. Inorganic content such as nitrogen, phosphate and potassium and chlorophyll content of red pepper leaves were increased as increasing fergigation amount of PWW. 50% fertigation level showed the lowest rate of fruit setting of red peper plant. For soil chemical properties, pH was slightly decreased, but available $P_2O_5$, and exchangeable K content were increased as increasing fertigation amount of PWW. Because there was not statistically significant difference in the growth, the yield of red pepper and chemical properties of soil used according to various fertigation intervals, and no need to artificially supply PWW, therefore fertigation by simple automatic system with tensiometer was thought to be better.

• Journal of Biomedical Engineering Research
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• v.43 no.5
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• pp.341-352
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• 2022

Medical image segmentation is the most important task in radiation therapy. Especially, when segmenting medical images, the liver is one of the most difficult organs to segment because it has various shapes and is close to other organs. Therefore, automatic segmentation of the liver in computed tomography (CT) images is a difficult task. Since tumors also have low contrast in surrounding tissues, and the shape, location, size, and number of tumors vary from patient to patient, accurate tumor segmentation takes a long time. In this study, we propose a method algorithm for automatically segmenting the liver and tumor for this purpose. As an advantage of setting the boundaries of the tumor, the liver and tumor were automatically segmented from the CT image using the 2D CoordConv DeepLab V3+ model using the CoordConv layer. For tumors, only cropped liver images were used to improve accuracy. Additionally, to increase the segmentation accuracy, augmentation, preprocess, loss function, and hyperparameter were used to find optimal values. We compared the CoordConv DeepLab v3+ model using the CoordConv layer and the DeepLab V3+ model without the CoordConv layer to determine whether they affected the segmentation accuracy. The data sets used included 131 hepatic tumor segmentation (LiTS) challenge data sets (100 train sets, 16 validation sets, and 15 test sets). Additional learned data were tested using 15 clinical data from Seoul St. Mary's Hospital. The evaluation was compared with the study results learned with a two-dimensional deep learning-based model. Dice values without the CoordConv layer achieved 0.965 ± 0.01 for liver segmentation and 0.925 ± 0.04 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.927 ± 0.02 for liver division and 0.903 ± 0.05 for tumor division. The dice values using the CoordConv layer achieved 0.989 ± 0.02 for liver segmentation and 0.937 ± 0.07 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.944 ± 0.02 for liver division and 0.916 ± 0.18 for tumor division. The use of CoordConv layers improves the segmentation accuracy. The highest of the most recently published values were 0.960 and 0.749 for liver and tumor division, respectively. However, better performance was achieved with 0.989 and 0.937 results for liver and tumor, which would have been used with the algorithm proposed in this study. The algorithm proposed in this study can play a useful role in treatment planning by improving contouring accuracy and reducing time when segmentation evaluation of liver and tumor is performed. And accurate identification of liver anatomy in medical imaging applications, such as surgical planning, as well as radiotherapy, which can leverage the findings of this study, can help clinical evaluation of the risks and benefits of liver intervention.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.11
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• pp.109-119
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• 2018

This study investigates the effect of urban and architectural forms on the microclimate in urban areas. It applies urban and architectural elements such as urban form and tissue and building form and characteristics as the main influences on the microclimate within urban area. Among the 23 Automated Weather Stations (AWS) installed within Seoul city by the Korea Meteorological Administration, 6 sites were selected for the analysis, based on their different urban and architectural characteristics, and actual measurements were conducted in August 2017 using individual AWS equipment. Also, the measurements of microclimate and urban and architectural elements within a 500m radius of the AWS measurement points were collected and analyzed. The result of the analysis shows that the microclimate elements, such as wind speed, solar radiation, and temperature, were affected by the direction of the streets, the width, depth, and height of the buildings, the topographic elevation and direction and the traffic volume. This study is expected to contribute to mitigating urban heat island effect and setting the foundation for sustainable cities through development of urban management methods and techniques including the relationship between built environment elements and microclimate.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.57-62
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• 2023

This research is a comparative analysis of the U.S. S&P 500 index using the volatility breakout strategy against the Buy and Hold approach. The volatility breakout strategy is a trading method that exploits price movements after periods of relative market stability or concentration. Specifically, it is observed that large price movements tend to occur more frequently after periods of low volatility. When a stock moves within a narrow price range for a while and then suddenly rises or falls, it is expected to continue moving in that direction. To capitalize on these movements, traders adopt the volatility breakout strategy. The 'k' value is used as a multiplier applied to a measure of recent market volatility. One method of measuring volatility is the Average True Range (ATR), which represents the difference between the highest and lowest prices of recent trading days. The 'k' value plays a crucial role for traders in setting their trade threshold. This study calculated the 'k' value at a general level and compared its returns with the Buy and Hold strategy, finding that algorithmic trading using the volatility breakout strategy achieved slightly higher returns. In the future, we plan to present simulation results for maximizing returns by determining the optimal 'k' value for automated trading of the S&P 500 index using artificial intelligence deep learning techniques.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.110-126
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• 2024

Several studies have focused on developing the safest and most efficient path from the current location to the available parking area for vehicles entering a parking lot. In the present study, the parking lot structure and parking environment such as the lane width, width, and length of the parking space, were vaired by referring to the actual parking lot with vertical and horizontal parking. An automatic parking path planning model was proposed by collecting path data by various setting angles and environments such as a starting point and an arrival point, by putting the collected data into a deep learning model. The existing algorithm(Hybrid A-star, Reeds-Shepp Curve) and the deep learning model generate similar paths without colliding with obstacles. The distance and the consumption time were reduced by 0.59% and 0.61%, respectively, resulting in more efficient paths. The switching point could be decreased from 1.3 to 1.2 to reduce driver fatigue by maximizing straight and backward movement. Finally, the path generation time is reduced by 42.76%, enabling efficient and rapid path generation, which can be used to create a path plan for autonomous parking during autonomous driving in the future, and it is expected to be used to create a path for parking robots that move according to vehicle construction.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.28-41
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• 2023

The objective of the study was to develop an Urban Windway Forest Creation Planning Technique for the Improvement of the Urban Environment using the case of Daejeon Metropolitan City. Through a spatial analysis of fine dust and heat waves, a basin zone, in which the concentration was relatively serious, was derived, and an area with the potential of cold air flow was selected as the target area for the windway forest development by analyzing the climate and winds in the relevant zone. Extreme fine dust areas included the areas of the Daejeon Industrial Complex Regeneration Business District in Daedeok-gu and Daedeok Techno Valley in Yuseong-gu. Heat wave areas included the areas of Daedeok industrial Complex in Moksang-dong, the Daejeon Industrial Complex Regeneration Business District in Daehwa-dong, and the high-density residential area in Ojeong-dong. As a result of measuring the wind speeds in Daejeon with an Automatic Weather System, the average wind speeds during the day and night were 0.1 to 1.7 m/s,, respectively. So, a plan of for a windway forest that smoothly induces the movement of cold air formed in outer forests at night is required. The fine dust/heat wave intensive management zones of Daejeon Metropolitan City were Daejeoncheon, Yudeungcheon, Gapcheon-Yudeungcheon, and Gapcheon. The windway forest formation plan case involved the old city center of Daejeon Metropolitan City among the four zones, the Gapcheon-Yudeungcheon area, in which the windway formation effect was presumed to be high. The Gapcheon-Yudeungcheon area is a downtown area that benefits from the cold and fresh air generated on Mt. Gyejok and Mt. Wuseong, which are outer forests. Accordingly, the windway forest was planned to spread the cold air to the city center by connecting the cold air generated in the Seosa-myeon forest of Mt. Gyejok and the Namsa-myeon forest of Mt. Wuseong through Gapcheon, Yudeungcheon, and street forests. After selecting the target area for the wind ventilation forest, a climate map and wind formation function evaluation map were prepared for the area, the status of variation wind profiles (night), the status of fine dust generation, and the surface temperature distribution status were grasped in detail. The wind ventilation forest planning concept and detailed target sites by type were identified through this. In addition, a detailed action plan was established according to the direction of creation and setting of the direction of creation for each type of wind ventilation forest.

• Journal of the Korean Society of Radiology
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• v.83 no.3
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• pp.669-679
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• 2022

Purpose To evaluate the feasibility of pediatric low-dose facial CT reconstructed with filtered back projection (FBP) using adequate kernels. Materials and Methods We retrospectively reviewed the clinical and imaging data of children aged < 10 years who underwent facial CT at our emergency department. The patients were divided into two groups: low-dose CT (LDCT; Group A, n = 73) with a fixed 80-kVp tube potential and automatic tube current modulation (ATCM) and standard-dose CT (SDCT; Group B, n = 40) with a fixed 120-kVp tube potential and ATCM. All images were reconstructed with FBP using bone and soft tissue kernels in Group A and only bone kernel in Group B. The groups were compared in terms of image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Two radiologists subjectively scored the overall image quality of bony and soft tissue structures. The CT dose index volume and dose-length product were recorded. Results Image noise was higher in Group A than in Group B in bone kernel images (p < 0.001). Group A using a soft tissue kernel showed the highest SNR and CNR for all soft tissue structures (all p < 0.001). In the qualitative analysis of bony structures, Group A scores were found to be similar to or higher than Group B scores on comparing bone kernel images. In the qualitative analysis of soft tissue structures, there was no significant difference between Group A using a soft tissue kernel and Group B using a bone kernel with a soft tissue window setting (p > 0.05). Group A showed a 76.9% reduction in radiation dose compared to Group B (3.2 ± 0.2 mGy vs. 13.9 ± 1.5 mGy; p < 0.001). Conclusion The addition of a soft tissue kernel image to conventional CT reconstructed with FBP enables the use of pediatric low-dose facial CT protocol while maintaining image quality.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.7-15
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• 2020

Purpose: In modern radiotherapy technology, several methods of image guided radiation therapy (IGRT) are used to deliver accurate doses to tumor target locations and normal organs, including CBCT (Cone Beam Computed Tomography) and other devices, ExacTrac System, other than CBCT equipped with linear accelerators. In previous studies comparing the two systems, positional errors were analysed rearwards using Offline-view or evaluated only with a Yaw rotation with the X, Y, and Z axes. In this study, when using CBCT and ExacTrac to perform 6 Degree of the Freedom(DoF) Online IGRT in a treatment center with two equipment, the difference between the set-up calibration values seen in each system, the time taken for patient set-up, and the radiation usefulness of the imaging device is evaluated. Materials and Methods: In order to evaluate the difference between mobile calibrations and exposure radiation dose, the glass dosimetry and Rando Phantom were used for 11 cancer patients with head circumference from March to October 2017 in order to assess the difference between mobile calibrations and the time taken from Set-up to shortly before IGRT. CBCT and ExacTrac System were used for IGRT of all patients. An average of 10 CBCT and ExacTrac images were obtained per patient during the total treatment period, and the difference in 6D Online Automation values between the two systems was calculated within the ROI setting. In this case, the area of interest designation in the image obtained from CBCT was fixed to the same anatomical structure as the image obtained through ExacTrac. The difference in positional values for the six axes (SI, AP, LR; Rotation group: Pitch, Roll, Rtn) between the two systems, the total time taken from patient set-up to just before IGRT, and exposure dose were measured and compared respectively with the RandoPhantom. Results: the set-up error in the phantom and patient was less than 1mm in the translation group and less than 1.5° in the rotation group, and the RMS values of all axes except the Rtn value were less than 1mm and 1°. The time taken to correct the set-up error in each system was an average of 256±47.6sec for IGRT using CBCT and 84±3.5sec for ExacTrac, respectively. Radiation exposure dose by IGRT per treatment was measured at 37 times higher than ExacTrac in CBCT and ExacTrac at 2.468mGy and 0.066mGy at Oral Mucosa among the 7 measurement locations in the head and neck area. Conclusion: Through 6D online automatic positioning between the CBCT and ExacTrac systems, the set-up error was found to be less than 1mm, 1.02°, including the patient's movement (random error), as well as the systematic error of the two systems. This error range is considered to be reasonable when considering that the PTV Margin is 3mm during the head and neck IMRT treatment in the present study. However, considering the changes in target and risk organs due to changes in patient weight during the treatment period, it is considered to be appropriately used in combination with CBCT.