• Korean Journal of Environmental Agriculture
• /
• v.32 no.3
• /
• pp.201-206
• /
• 2013

BACKGROUND: Kiwifruit, which was introduced to Korea in late 1970s, is a warm-temperate fruit tree, whose leaves are easily damaged by wind because of their large size. To produce high quality fruits, efficient windbreak is necessary to protect leaves until harvest. In Korea, typhoons from July onwards usually influence the production of kiwifruit. Damages from typhoons include low fruit quality in the current year and low flowering ratio the following year. This study was conducted to investigate the effect of early defoliation of kiwifruit vines from July to October on the regrowth of shoot axillary buds the current year and bud break and flowering the following year. METHODS AND RESULTS: Scions of kiwifruit cultivar 'Goldrush' were veneer grafted onto five-year-old Actinidia deliciosa rootstocks, planted in Wagner pots (13L) and grown in a rain shelter. Kiwifruit leaves in the proximity of leaf stalk were cut by lopping shears to simulate mechanical damage from typhoon since only leaf stalks were left when kiwifruit vines were damaged by typhoons. Kiwifruit vines were defoliated from July 15 to October 14 with one monthintervals and degrees of defoliation were 0, 25, 50, 75 and 100%. All experiments were conducted in the rain shelter and replicated at least five times. Defoliation in July 15 resulted in a high regrowth ratio of 20-40% regardless of degree of defoliation but that in August 16 showed only 5.8% of regrowth ratio in the no defoliation treatment; however, more than 25% of defoliation in August 16 showed 17-23% of regrowth ratio. In September 15, regrowth ratio decreased further to less than 10% in all treatments and no regrowth was observed in October 14. Percent bud break of all defoliation treatments were not significant in comparison to 64.7% in no defoliation except for 42.1% and 42.9% in 100% defoliation in July 15 and August 16, respectively. Floral shoot in the no defoliation treatment was 70.2% and defoliation of 50% or less resulted in the same or increased floral shoot ratio in July 15, August 16, and September 15; however, defoliation in October 14 showed no difference in all treatments. In flower number per floral shoot, 2-3 flowers appeared in no defoliation and only 1 flower was observed when the vines were defoliated more than 50% in July 15 and September 15. In October 14, contrary to the floral shoot ratio, flower number decreased with increased defoliation. CONCLUSION(S): Therefore, it is suggested that dormancy of 'Goldrush' axillary buds, was started in August and completed in October. The effect of defoliation on bud break of axillary buds the following year was insignificant, except for 100% defoliation in July 15 and August 16. From July 15 to September 15, floral bud ratio was significantly reduced when more than 50% of leaves were defoliated compared to no defoliation. Also, the number of flowers per flower-bearing shoot the following year decreased by less than 50% when compared to no defoliation, and this decrease was more prominent in September 15 than July 15 and August 16.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.21 no.2
• /
• pp.55-64
• /
• 2017

Purpose Recently, with the spread of SPECT/CT, various image correction methods can be applied quickly and accurately, which enabled us to expect quantitative accuracy as well as image quality improvement. Among them, the Collimator Detector Response(CDR) recovery is a correction method aiming at resolution recovery by compensating the blurring effect generated from the distance between the detector and the object. The purpose of this study is to find out quantitative change depending on the change in detection distance in SPECT/CT images with CDR recovery applied. Materials and Methods In order to find out the error of acquisition count depending on the change of detection distance, we set the detection distance according to the obit type as X, Y axis radius 30cm for circular, X, Y axis radius 21cm, 10cm for non-circular and non-circular auto(=auto body contouring, ABC_spacing limit 1cm) and applied reconstruction methods by dividing them into Astonish(3D-OSEM with CDR recovery) and OSEM(w/o CDR recovery) to find out the difference in activity recovery depending on the use of CDR recovery. At this time, attenuation correction, scatter correction, and decay correction were applied to all images. For the quantitative evaluation, calibration scan(cylindrical phantom, $^{99m}TcO_4$ 123.3 MBq, water 9293 ml) was obtained for the purpose of calculating the calibration factor(CF). For the phantom scan, a 50 cc syringe was filled with 31 ml of water and a phantom image was obtained by setting $^{99m}TcO_4$ 123.3 MBq. We set the VOI(volume of interest) in the entire volume of the syringe in the phantom image to measure total counts for each condition and obtained the error of the measured value against true value set by setting CF to check the quantitative accuracy according to the correction. Results The calculated CF was 154.28 (Bq/ml/cps/ml) and the measured values against true values in each conditional image were analyzed to be circular 87.5%, non-circular 90.1%, ABC 91.3% and circular 93.6%, non-circular 93.6%, ABC 93.9% in OSEM and Astonish, respectively. The closer the detection distance, the higher the accuracy of OSEM, and Astonish showed almost similar values regardless of distance. The error was the largest in the OSEM circular(-13.5%) and the smallest in the Astonish ABC(-6.1%). Conclusion SPECT/CT images showed that when the distance compensation is made through the application of CDR recovery, the detection distance shows almost the same quantitative accuracy as the proximity detection even under the distant condition, and accurate correction is possible without being affected by the change in detection distance.

• Journal of the korean academy of Pediatric Dentistry
• /
• v.48 no.1
• /
• pp.77-94
• /
• 2021

The purpose of this study was to investigate the three-dimensional characteristics of mesiodens using Cone-beam Computed Tomography(CBCT) and analyze the factors affecting complications and anesthetic methods of extraction. This study evaluated 602 mesiodens of 452 patients who underwent extraction of mesiodens at the department of Pediatric Dentistry in Seoul National University Dental Hospital between 2017 and 2019. The ratio of mesiodens patients over total patient per year was gradually increased over the past 20 years. Mesiodens with labio-palatally horizontal direction while root directing labial were the most common among the mesiodens with horizontal direction. Mesiodens were the most common at the cervical side of the adjacent teeth(37.0%) and mesiodens located in the near-palatal side were observed about 3.83 times higher than the far-palatal side. Most of the mesiodens(82.1%) were in contact with adjacent permanent teeth on all three sides of the CBCT and 46.2% of mesiodens had curved roots. The patient's age, vertical position, presence of complications, and proximity showed a significant difference in the selection of general anesthesia among anesthetic methods. The direction and vertical position of mesiodens had a significant effect on complications. These results provide a better understanding of mesiodens for establishing an accurate diagnosis and treatment plan.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.47 no.5
• /
• pp.66-77
• /
• 2019

This study investigated the feasibility of wintering evergreen broad-leaf trees in the Incheon coastal area through a climate analysis. The coldest monthly mean air temperature ranged from $-2.9^{\circ}C{\sim}-1.6^{\circ}C$. The warmth index of the coastal area of Incheon ranged from $98.89^{\circ}C{\cdot}month-109.03^{\circ}C{\cdot}month$, while the minimum air temperature year ranged from $-13.9^{\circ}C{\sim}-3.6^{\circ}C$. This proved that the Incheon coastal area was not suitable for evergreen broad-leaf trees to grow as the warmth index ranges from $101.0^{\circ}C{\cdot}month{\sim}117.0^{\circ}C{\cdot}month$, and the temperature year-round is $-9.2^{\circ}C$ or higher. This suggests the coastal areas of Incheon is not suitable for the growth of evergreen broad-leaf trees, however some evergreen broad-leaf trees lived in some parts of the area. Wind speed reduction and temperature effect simulations were done using Landschaftsanalyse mit GIS program. As a result of the simulations of wind speed reduction and temperature effects affecting the evergreen broad-leaf trees, it was discovered that a coastal wind velocity of 8.6m/sec was alleviated to be 5m/sec~7m/sec when the wind reached the areas where evergreen broad-leaf trees were present. It was also discovered that species that grew in contact with buildings benefited from a temperature increase of $1.1^{\circ}C{\sim}3.4^{\circ}C$ due to the radiant heat released by the building. Simulation results show that the weather factors affecting the winter growth damages of evergreen broad-leaved trees were wind speed reduction and local warming due to buildings. The wind speed reduction by shielding and local warming effects by buildings have enabled the wintering of evergreen broad-leaved trees. Also, evergreen broad-leaved trees growing in the coastal area of Incheon could be judged to be gradually adapting to low temperatures in winter. This study reached the conclusion that the blockage of wind, and the proximity of buildings, are required for successfully wintering evergreen broad-leaf trees in the coastal area of Incheon.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.23-46
• /
• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.22 no.1
• /
• pp.67-75
• /
• 2018

Purpose The purpose of this study is to investigate and analyze the external dose rates of $^{18}F-FDG$ Whole Body PET/CT patients by distance, and to identify the main factors that contribute to the reduction of radiation dose by checking the cumulative doses of nuclear medicine technologist(NMT). Materials and Methods After completion of the $^{18}F-FDG$ Whole Body PET/CT scan($75.4{\pm}3.3min$), the external dose rates of 106 patients were measured at a distance of 0, 10, 30, 50, and 100 cm from the chest. Gender, age, BMI(Body Mass Index), fasting time, diabetes mellitus, radiopharmaceutical injection information, creatine value were collected to analyze individual factors that could affect external dose rates from a patient's perspective. From the perspective of NMT, personal pocket dosimeters were worn on the chest to record accumulated dose of NMT who performed the injection task($T_1$, $T_2$ and $T_3$) and scan task($T_4$, $T_5$ and $T_6$). In addition, patient contact time with NMT was measured and analyzed. Results External dose rates from the patient for each distance were calculated as $246.9{\pm}37.6$, $129.9{\pm}16.7$, $61.2{\pm}9.1$, $34.4{\pm}5.9$, and $13.1{\pm}2.4{\mu}Sv/hr$ respectively. On the patient's aspect, there was a significant difference in the proximity of gender, BMI, Injection dose and creatine value, but the difference decreased as the distance increased. In case of dialysis patient, external dose rates for each distance were exceptionally higher than other patients. On the NMT aspect, the doses received from patients were 0.70, 1.09, $0.55{\mu}Sv/person$ for performing the injection task($T_1$, $T_2$, and $T_3$), and were 1.25, 0.82, $1.23{\mu}Sv/person$ for performing the scan task($T_4$, $T_5$, $T_6$). Conclusion we found that maintaining proper distance with patient and reducing contact time with patient had a significant effect on accumulated doses. Considering those points, efforts such as sufficient water intake and encourage of urination, maintaining the proper distance between the NMT and the patient(at least 100 cm), and reducing the contact time should be done for reducing dose rates not only patient but also NMT.