• KOREAN JOURNAL OF CROP SCIENCE
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• v.40 no.5
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• pp.580-586
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• 1995

Soil temperatures at depths of 1~5cm are important to the germination and emergence of dry seeded-rice. An automated weather station was used to monitor the hourly weather parameters at Experiment Farm, Kyung Hee University from April 21 to May 30 in 1994. The data was analyzed to figure out the 24-hour temporal changes in air 1.5m above ground and soil temperatures under ground of 0, 2.5, 5, 10 and 20cm. The fluctuations of soil temperature were greatest at the soil surface and decreased with increasing depth. Mean soil temperatures at depth of 2.5cm were about 3$^{\circ}C$ higher than mean air temperatures during the observation period. Although mean soil temperatures at depth of 2.5cm during 10 or 15 days after April 21, May 1 and May 11 showed almost same temperatures, the distribution patterns of temperature regime were different from each other. Rice cultivars, Hwasung, Seohae, Nampung, IR60 and CR155, were seeded at depth of 2.5cm on April 21, May 1 and May 11, respectively. The periods of seedling emergence(PSE) varied in accordance with cultivars and seeding dates. PSE was correlated with accumulated daily mean air temperatures and accumulated hours classified by temperature regimes.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Korean Journal of Agricultural Science
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• v.13 no.1
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• pp.1-16
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• 1986

This experiment was carried out to obtain genetic information for future corn breeding. The materials used for the study were obtained from the nationwide collection of Korean local corn lines. A total of 262 lines were used for the study of morphological characters and for the classification of lines. Results obtained are summarized as follows; 1. The days to flowering of lines ranged from 57 days to 87 days. Most lines had an average of 67 days of flowering days. 2. The number of tillers of lines showed a lot of variation among lines with 49.2% of coefficient of variation. 3. The coefficients of variation computed based on the phenotypic observation or measurement of each line were 36.1%, 27.2%, 20.0%, 16.4% and 16.3% for kernel weight per ear, 100 kernel weight, ear height, plant height and ear length, respectively. 4. Ear height, ear length, ear diameter, tiller number and days to flowering were highly and positively correlation with the plant height. Kernel size, ear size, and plant height were highly correlated with 100 kernel weight and kernel weight per ear. 5. The 262 corn lines were possibly classified into four major groups by the Euclidean distance. Group I comprised 110 lines, group II 74 lines, group III 66 lines and group IV 12 lines, respectively. Group I was characterized as having early maturity, medium plant height large kernel size and large ear size. Group II had medium maturity, short plant height, medium kernel size and small ear size. Group III had medium maturity, medium plant height, large kernel size and medium ear size. Group IV had late maturity, long plant height, small kernel size, small ear size and many tillering. 6. The plant height showed significant difference between group I and II, II and III, and II and IV group. No statistical differences were observed between group III and IV. The ear size of group I was significantly different from those of group II, III and IV. Also difference of ear size between group II and III was significant. The kernel size, 100 kernel weight and kernel weight per ear were all significantly different among all groups classified. The row number was different between group I and II. The row number of lines in group IV was significantly different with group I, II, III respectively. The number of tillers and flowering days of lines in group IV were greatly different from those of group I, II and III. 7. The corn lines collected from northwest plain regions and middle hilly regions in Korea had medium maturity, medium plant height, large ear and large kernels. The corn lines from middle eastern hilly regions had medium size of ear kernels. The corn lines from middle southern hilly regions had late maturity, small kernel size and many tillers. The corn lines from southwest plain areas had late maturity, long plant height and many tillers.

• Tuberculosis and Respiratory Diseases
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• v.45 no.3
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• pp.553-564
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• 1998

Background: The immediate hoot response to LPS is the production of proinflammatory cytokines that act as intercellular mediators in inflammatory reactions, including acute lung injury. These "early response" cytokines transmit signals from recognition cells to target or effector cells. This host response is further amplified by the expression of leukocyte chemoattractants, growth factors, and adhesion molecules, resulting in an array of proinflammatory events. This experiment was performed to define the lung origin of proinflammatory cytokines, such as TNF-$\alpha$, IL 6 in early periods of endotoxin induced acute lung injury (ALI). Method: The healthy male Sprague-Dawley, weighted 150 - 250g, were divided into saline control (NC) and endotoxemia-induced ALI (ETX-), and leukopenic endotoxemia-induced ALI (CPA-ETX-Group) which was induced by cyclophosphamide, 70 mg/kg i.p. injection. Acute lung injury was evoked by LPS, 5 mg/kg, intravenously administered. Bronchoalveolar lavage was performed at 0, 3, 6 h after LPS-treated to estimate the influx of phagocytes and concentration of total protein, and cytokines as TNF-$\alpha$ and IL 6 by a bioassy using MIT method. We also examined the localization of TNF-$\alpha$ and IL 6 protein in endotoxemia-challenged lung tissue by immunohistochemical stain (IH). Results: The total cell, macrophage and PMN count in BALF were elavated in ETX group compared to NC(p<0.05). In CPA-ETX group, total cell and macrophage count in BALF were not changed compared to NC. but PMN count was markedly reduced and it took part in less than 0.1 % of total BAL cells (p<0.01). The protein concentration in BALF were significantly increased in ETX and CPA-ETX group Compared to NC (p<0.05), but there was significant difference between ETX- and CPA-ETX group only at 6 h (p<0.05). This observation suggested that even if PMNs are involved in the pathogenesis of acute lung injury, their role cannot be viewed as essential The concentration of TNF-$\alpha$ and IL 6 in BALF was significantly increased in the ETX- and CPA-ETX group compared to NC. There was no difference between ETX- and CPA-ETX group. In IH, anti-TNF-$\alpha$- and anti-IL 6 antibody was strongly localized at interstitial monocytes and alveolar macrophages in endotoxemia-challenged lung tissue. From above point of view, activated alveolar macrophage/monocyte considered as a prominent source of proinflammatory cytokines in endotoxemia-challenged lung injury. Conclusion: The prominent source of proinflammatory cytokines in early periods of endotoxemia-induced lung injury will be the activated resident macrophages like an alveolar macrophage and interstitial monocytes. The pulmonary macrophage/monocyte will impact the initiation and continuance of lung injury without PMNs's certain inflammatory role, particularly in endotoxemia-induced acute lung injury.

• Journal of Korean Academy of Nursing
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• v.12 no.2
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• pp.1-26
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• 1982

The main purpose of this study was to test the effect of the structured information on the sleep amount of the patients undergoing open heart surgery. This study has specifically addressed to the Following two basic research questions: (1) Would the structed in formation influence in the reduction of sleep disturbance related to anxiety and Physical stress before and after the operation? and (2) that would be the effects of the structured information on the level of preoperative state anxiety, the hormonal change, and the degree of behavioral change in the patients undergoing an open heart surgery? A Quasi-experimental research was designed to answer these questions with one experimental group and one control group. Subjects in both groups were matched as closely as possible to avoid the effect of the differences inherent to the group characteristics, Baseline data were also. collected on both groups for 7 days prior to the experiment and found that subjects in both groups had comparable sleep patterns, trait anxiety, hormonal levels and behavioral level. A structured information as an experimental input was given to the subjects in the experimental group only. Data were collected and compared between the experimental group and the control group on the sleep amount of the consecutive pre and post operative days, on preoperative state anxiety level, and on hormonal and behavioral changes. To test the effectiveness of the structured information, two main hypotheses and three sub-hypotheses were formulated as follows; Main hypothesis 1: Experimental group which received structured information will have more sleep amount than control group without structured information in the night before the open heart surgery. Main hypothesis 2: Experimental group with structured information will have more sleep, amount than control group without structured information during the week following the open heart surgery Sub-hypothesis 1: Experimental group with structured information will be lower in the level of State anxiety than control group without structured information in the night before the open heart surgery. Sub-hypothesis 2 : Experimental group with structured information will have lower hormonal level than control group without stuctured information on the 5th day after the open heart surgery Sub-hypothesis 3: Experimental group with structured information will be lower in the behavioral change level than control group without structured information during the week after the open heart surgery. The research was conducted in a national university hospital in Seoul, Korea. The 53 Subjects who participated in the study were systematically divided into experimental group and control group which was decided by random sampling method. Among 53 subjects, 26 were placed in the experimental group and 27 in the control group. Instruments; (1) Structed information: Structured information as an independent variable was constructed by the researcher on the basis of Roy's adaptation model consisting of physiologic needs, self-concept, role function and interdependence needs as related to the sleep and of operational procedures. (2) Sleep amount measure: Sleep amount as main dependent variable was measured by trained nurses through observation on the basis of the established criteria, such as closed or open eyes, regular or irregular respiration, body movement, posture, responses to the light and question, facial expressions and self report after sleep. (3) State anxiety measure: State Anxiety as a sub-dependent variable was measured by Spi-elberger's STAI Anxiety scale, (4) Hormornal change measure: Hormone as a sub-dependent variable was measured by the cortisol level in plasma. (5) Behavior change measure: Behavior as a sub-dependent variable was measured by the Behavior and Mood Rating Scale by Wyatt. The data were collected over a period of four months, from June to October 1981, after the pretest period of two months. For the analysis of the data and test for the hypotheses, the t-test with mean differences and analysis of covariance was used. The result of the test for instruments show as follows: (1) STAI measurement for trait and state anxiety as analyzed by Cronbachs alpha coefficient analysis for item analysis and reliability showed the reliability level at r= .90 r= .91 respectively. (2) Behavior and Mood Rating Scale measurement was analyzed by means of Principal Component Analysis technique. Seven factors retained were anger, anxiety, hyperactivity, depression, bizarre behavior, suspicious behavior and emotional withdrawal. Cumulative percentage of each factor was 71.3%. The result of the test for hypotheses show as follows; (1) Main hypothesis, was not supported. The experimental group has 282 minutes of sleep as compared to the 255 minutes of sleep by the control group. Thus the sleep amount was higher in experimental group than in control group, however, the difference was not statistically significant at .05 level. (2) Main hypothesis 2 was not supported. The mean sleep amount of the experimental group and control group were 297 minutes and 278 minutes respectively Therefore, the experimental group had more sleep amount as compared to the control group, however, the difference was not statistically significant at .05 level. Thus, the main hypothesis 2 was not supported. (3) Sub-hypothesis 1 was not supported. The mean state anxiety of the experimental group and control group were 42.3, 43.9 in scores. Thus, the experimental group had slightly lower state anxiety level than control group, howe-ver, the difference was not statistically significant at .05 level. (4) Sub-hypothesis 2 was not supported. . The mean hormonal level of the experimental group and control group were 338 ㎍ and 440 ㎍ respectively. Thus, the experimental group showed decreased hormonal level than the control group, however, the difference was not statistically significant at .05 level. (5) Sub-hypothesis 3 was supported. The mean behavioral level of the experimental group and control group were 29.60 and 32.00 respectively in score. Thus, the experimental group showed lower behavioral change level than the control group. The difference was statistically significant at .05 level. In summary, the structured information did not influence the sleep amount, state anxiety or hormonal level of the subjects undergoing an open heart surgery at a statistically significant level, however, it showed a definite trends in their relationships, not least to mention its significant effect shown on behavioral change level. It can further be speculated that a great degree of individual differences in the variables such as sleep amount, state anxiety and fluctuation in hormonal level may partly be responsible for the statistical insensitivity to the experimentation.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.79-104
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• 2020

Recently, as deep learning has attracted attention, the use of deep learning is being considered as a method for solving problems in various fields. In particular, deep learning is known to have excellent performance when applied to applying unstructured data such as text, sound and images, and many studies have proven its effectiveness. Owing to the remarkable development of text and image deep learning technology, interests in image captioning technology and its application is rapidly increasing. Image captioning is a technique that automatically generates relevant captions for a given image by handling both image comprehension and text generation simultaneously. In spite of the high entry barrier of image captioning that analysts should be able to process both image and text data, image captioning has established itself as one of the key fields in the A.I. research owing to its various applicability. In addition, many researches have been conducted to improve the performance of image captioning in various aspects. Recent researches attempt to create advanced captions that can not only describe an image accurately, but also convey the information contained in the image more sophisticatedly. Despite many recent efforts to improve the performance of image captioning, it is difficult to find any researches to interpret images from the perspective of domain experts in each field not from the perspective of the general public. Even for the same image, the part of interests may differ according to the professional field of the person who has encountered the image. Moreover, the way of interpreting and expressing the image also differs according to the level of expertise. The public tends to recognize the image from a holistic and general perspective, that is, from the perspective of identifying the image's constituent objects and their relationships. On the contrary, the domain experts tend to recognize the image by focusing on some specific elements necessary to interpret the given image based on their expertise. It implies that meaningful parts of an image are mutually different depending on viewers' perspective even for the same image. So, image captioning needs to implement this phenomenon. Therefore, in this study, we propose a method to generate captions specialized in each domain for the image by utilizing the expertise of experts in the corresponding domain. Specifically, after performing pre-training on a large amount of general data, the expertise in the field is transplanted through transfer-learning with a small amount of expertise data. However, simple adaption of transfer learning using expertise data may invoke another type of problems. Simultaneous learning with captions of various characteristics may invoke so-called 'inter-observation interference' problem, which make it difficult to perform pure learning of each characteristic point of view. For learning with vast amount of data, most of this interference is self-purified and has little impact on learning results. On the contrary, in the case of fine-tuning where learning is performed on a small amount of data, the impact of such interference on learning can be relatively large. To solve this problem, therefore, we propose a novel 'Character-Independent Transfer-learning' that performs transfer learning independently for each character. In order to confirm the feasibility of the proposed methodology, we performed experiments utilizing the results of pre-training on MSCOCO dataset which is comprised of 120,000 images and about 600,000 general captions. Additionally, according to the advice of an art therapist, about 300 pairs of 'image / expertise captions' were created, and the data was used for the experiments of expertise transplantation. As a result of the experiment, it was confirmed that the caption generated according to the proposed methodology generates captions from the perspective of implanted expertise whereas the caption generated through learning on general data contains a number of contents irrelevant to expertise interpretation. In this paper, we propose a novel approach of specialized image interpretation. To achieve this goal, we present a method to use transfer learning and generate captions specialized in the specific domain. In the future, by applying the proposed methodology to expertise transplant in various fields, we expected that many researches will be actively conducted to solve the problem of lack of expertise data and to improve performance of image captioning.

• Applied Biological Chemistry
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• v.6
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• pp.61-77
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• 1965

In this experiment, Akiochi was studied especially on plant growth on the degraded soils. Besides, such soils were carefully examined on its character and plant body was analysed to know the difference in various mineral contents. For this purpose, paddy cultivation was done with the variety Pal Dal at Suwon, Sosa and Pyungtak. Three plots were chosen at each location as the normal and 2 levels of akiochi, a-the stronger and b-the weaker. Harvests from these 9 plots were measured agronomically and also chemically analysised. As for soil, after an observation on vertical section of soil, samples from each layer were also studied both physically and chemically. The results are summarized as follows. 1. Outer changes in rice plant and changes in yield components. 1) Rice from Akiochi soil showed remarkably shortened culm length, head length, protrusoion length, blade length of boot leaf, and coleoptile length, compared with that from the normal paddy field. 2) There was a tendency for Akiochi rice to have more heads per plant. 3) Akiochi rice showed poorer intercalary growth of upper 3 internodes. The ratio of this upper internode length to total culm length was also smaller in this case. Consquently the ratio of lower internode length to total culm length became larger than that from normal peddy field. 4) Akiochi rice showed significantly fewer first spikelets and attached grains of head at main stem. 5) Maturing rate of both this main seem of whole plant body was remarkably lower than that of normal rice. 6) Akiochi rice showed lower head weight of main stem, total hulled rice weight, total grain yield, 1000-grain weight, straw weight and straw-hulled rice ratio. 2. Physical and chemical study on soil. 1) Akiochi soil showed thinner upper layer and total thickness of upper and lower parts was smaller than that of normal. 2) Akiochi soil of Suwon was mainly composed of sand, while that of Sosa and Pyungtak was composed of heavy clay. 3) Chemical analysis indicated that content of $SiO_2$ in upper layer is always lower than that of normal. But no other common tendencies were found. 4) This analysis further lillustrates lower content of Fe, & Mn at Suwon ; of Mn at Sosa and higher content of Fe at Sosa and organic matters at Pyungtak. 5) Some differences in the content of N in each plot could be marked though irregular. 3. Chemical Composition of plant body. 1) Chemical analysis on grain, boot leaf and straw did not suggest any remarkable differences between normal and Akiochi rice, except that the latter contains less Si in boot leaf and less Mn in straw. 2) Contents of each chemical element were measured in grain and straw to calculate the percentage of element content in grain to that of whole plant body including both grain and straw. Here, Akiochi rice always showed lower value in N, K and Mn. 4. Relationship between chemical composition of plant body and that of soil. Akiochi soil at Sosa marked lower content of Mn. This caused another lower content of this element in grain, boot leaf and straw. But except that, no remarkable relationship could be found in this study.

• Journal of Korean Society of Forest Science
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• v.25 no.1
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• pp.13-47
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• 1975

Among the many species of bamboo, it is well known that the dwarf-type is widely distributed in the tropical regions, and the slender type in temperated zone. In the temperated zone the trees have extensively differentiated into one hundred species in 50 genera. In many oriental countries, the bamboo wood is being used as a material for construction and for the manufacture of technical instruments. The bamboo shoot is also regarded as a good and delicious edible resource. Moreover, recent medical investigation verifies that the sap of certain species of the bamboo is an antibiotic effect against cancer. Fortunately, it is very easy to propagate the bamboo trees by using cutting from southeastern Asian countries. This important resource can further be used as a significant source of pulp, which is becoming increasingly important. The classification system of this significant resource has not been completely established to date, even though its importance has been emphasized. Initiated by Canlevon Linne in the 18th century, a classification method concerning the morphological characteristics of flowers was the first step in developing a classification. But it was not an easy task to accomplish, because this type of classification system is based on the sexual organs in bamboo trees. Because the bamboo has a long life cycle of 60-120 years and classification according to this method was very difficult as the materials for the classification are not abundant and some species have changed, even though many references related to the morphological classification of bamboo trees are available nowadays. So, the certification of bamboo trees according to the morphological classification system is not reasonable for us. Consequently, the classification system of bamboo trees on the basis of endomorphological characteristics was initiated by Chinese-born Liese. And classification method based on the morphological characteristics of the vascular bundle was developed by Grosser. These classification methods are fundamentally related to Holltum's classification method, which stressed the morphology of the ovary. The author investigated to re-establish a new classification method based on the vascular sheath. Twenty-six species in 11 genera which originated from Formosa where used in the study. The results obtained from the investigation were somewhat coordinated with those of Crosser. Many difficulties were found in distinguishing the species of Bambusa and Dendrocalamus. These two species were critically differentiated under the new classification system, which is based on the existence of a separated vascular bundle sheath in the bamboo. According to these results, it is recommended that Babusa divided into two groups by placing it into either subspecies or the lower categories. This recommendation is supported by the observation that the evolutional pattern of the bamboo thunk which is from outward to inward. It is also supported by the viewpoint that the fundamental hypothesis in evolution is from simple to complex. There remained many problems to be solved through more critical examination by comparing the results to those of the classification based on the sexual organs method. The author observed the figure of the cross-sectional area of vascular trunk of bamboo tree and compared the results with those of Grosser and Liese, i.e. A, $B_1$, $B_2$, C, and D groups in classification. Group A and $B_2$ were in accordance with the results of those scholars, while group D showed many differences, Grosser and Liese divided bamboo into "g" type and "h" type according to the vascular bundle type; and they included Dendrocalamus and Bambusa in Group D without considering the type of vascular bundle sheath. However, the results obtained by the author showed that Dendrocalamus and Bambusa are differentiated from each other. By considering another group, "i" identified according to the existence of separated vascular bundle sheath. Bambusa showed to have a separated vascular bundle sheath while Dendrocalamus does not have a separated vascular bundle sheath. Moreover, Bambusa showed peculiar characteristics in the figure of vascular development, i.e., one with an inward vascular bundle sheath and the other with a bivascular bundle sheath (inward and outward). In conclusion, the bamboo species used in this experiment were classified in group D, without any separated vascular bundle sheath, and in group E, with a vascular bundle sheath. Group E was divided into two groups, i.e., and group $E_1$, with bivascular sheath, and group $E_2$, with only an inward vascular sheath. Therefore, the Bambusa in group D as described by Grosser and Liese was included in group E. Dendrocalamus seemed to be the middle group between group $E_l$ and group $E_2$ under this classification system which is summarized as follows: Phyllostachys-type: Group A - Phyllostachys, Chymonobambus, Arundinaria, Pseudosasa, Pleioblastus, Yashania Pome-type: Group $B_2$ - Schizostachyum, Melocanna Hemp-type: Group D - Dendrocalamu Bambu-type: Group $E_1$ - Bambusa ghi.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.2
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• pp.51-58
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• 2019

Purpose In in-vitro laboratories of nuclear medicine department, when the reagent lot or reagent lot changes Comparability test or parallel test is performed to determine whether the results between lots are reliable. The most commonly used standard domestic laboratories is to obtain %difference from the difference in results between two lots of reagents, and then many laboratories are set the standard to less than 20% at low concentrations and less than 10% at medium and high concentrations. If the range is deviated from the standard, the test is considered failed and it is repeated until the result falls within the standard range. In this study, several tests are selected that are performed in nuclear medicine in-vitro laboratories to analyze parallel test results and to establish criteria for customized percent difference for each test. Materials and Methods From January to November 2018, the result of parallel test for reagent lot change is analyzed for 7 items including thyroid-stimulating hormone (TSH), free thyroxine (FT4), carcinoembryonic antigen (CEA), CA-125, prostate-specific antigen (PSA), HBs-Ab and Insulin. The RIA-MAT 280 system which adopted the principle of IRMA is used for TSH, FT4, CEA, CA-125 and PSA. TECAN automated dispensing equipment and GAMMA-10 is used to measure insulin test. For the test of HBs-Ab, HAMILTON automated dispensing equipment and Cobra Gamma ray measuring instrument are used. Separate reagent, customized calibrator and quality control materials are used in this experiment. Results 1. TSH [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(low concentration) [14.8 / 4.4 / 3.7 / 0.0 ] C-2(middle concentration) [10.1 / 4.2 / 3.7 / 0.0] 2. FT4 [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(low concentration) [10.0 / 4.2 / 3.9 / 0.0] C-2(high concentration) [9.6 / 3.3 / 3.1 / 0.0 ] 3. CA-125 [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(middle concentration) [9.6 / 4.3 / 4.3 / 0.3] C-2(high concentration) [6.5 / 3.5 / 4.3 / 0.4] 4. CEA [%diffrence Max / Mean / median] (P-value by t-test > 0.05) C-1(low concentration) [9.8 / 4.2 / 3.0 / 0.0] C-2(middle concentration) [8.7 / 3.7 / 2.3 / 0.3] 5. PSA [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(low concentration) [15.4 / 7.6 / 8.2 / 0.0] C-2(middle concentration) [8.8 / 4.5 / 4.8 / 0.9] 6. HBs-Ab [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(middle concentration) [9.6 / 3.7 / 2.7 / 0.2] C-2(high concentration) [8.9 / 4.1 / 3.6 / 0.3] 7. Insulin [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(middle concentration) [8.7 / 3.1 / 2.4 / 0.9] C-2(high concentration) [8.3 / 3.2 / 1.5 / 0.1] In some low concentration measurements, the percent difference is found above 10 to nearly 15 percent in result of target value calculated at a lower concentration. In addition, when the value is measured after Standard level 6, which is the highest value of reagents in the dispensing sequence, the result would have been affected by a hook effect. Overall, there was no significant difference in lot change of quality control material (p-value>0.05). Conclusion Variations between reagent lots are not large in immunoradiometric assays. It is likely that this is due to the selection of items that have relatively high detection rate in the immunoradiometric method and several remeasurements. In most test results, the difference was less than 10 percent, which was within the standard range. TSH control level 1 and PSA control level 1, which have low concentration target value, exceeded 10 percent more than twice, but it did not result in a value that was near 20 percent. As a result, it is required to perform a longer period of observation for more homogenized average results and to obtain laboratory-specific acceptance criteria for each item. Also, it is advised to study observations considering various variables.