• Economic and Environmental Geology
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• v.8 no.1
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• pp.1-23
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• 1975

The subject of this study deals with phase relations between stannite ($Cu_2FeSnS_4$) and sphalerite (${\beta}-ZnS$)/wurtzite (${\alpha}-ZnS$). The phase relations were systematically investigated from liquidus temperature to $400^{\circ}C$ under controlled conditions. ${\beta}-stannite$ (tetragonal) is stable up to $706{\pm}5^{\circ}C$, where it inverts to a high-temperature polymorph ${\alpha}-stannite$ (cubic) melting congruently at $867{\pm}5^{\circ}C$. Sphalerite (cubic, ${\beta}-ZnS$) inverts at $1013{\pm}3^{\circ}C$ to wurtzite, which is the hexagonal hightemperature polymorph of ZnS. Between ${\alpha}-stannite$ and sphalerite a complete solid solution series exists above approximately $870^{\circ}C$ up to solidus temperature. The melting temperature of ${\alpha}-stannite$ rises towards sphalerite and reaches a maximum at $1074{\pm}3^{\circ}C$, which is the peritectic with the composition of 91 wt. % sphalerite and 9 wt. % ${\alpha}-stannite$. At this temperature, wurtzite takes only 5wt. % ${\alpha}-stannite$ in solid solution which decreases with increasing temperature. The inverson temperature of ${\alpha}/{\beta}-stannite$ is lowered with increasing amounts of sphalerite in solid solution down to $614{\pm}7^{\circ}C$, which is the eutectoid with the composition of 13 wt. % sphalerite and 87 wt. % ${\alpha}-stannite$. Here, ${\beta}-stannite$ contains only 10wt. % sphalerite in solid solution. With decreasing temperature, the ranges of the solid solution on both sides of the system narrow. The phase relations in the above pure system changed due to the FeS impurities in the sphalerite solid solution. The eutectoid increased from $614{\pm}7^{\circ}C$ up to $695{\pm}5^{\circ}C$ (5 wt. % FeS) and $700{\pm}5^{\circ}C$ (10wt. % FeS), while the peritectic decreased from $1074{\pm}3^{\circ}C$ down to $1036{\pm}3^{\circ}C$ (wt. %FeS) and $987{\pm}3^{\circ}C$ (10wt. %FeS). A most notable change is the appearance of non-binary regions. An important feature is the combination of this study system with the experimental results reported by Sprinfer (1972). If a stannite-kesterite solid solution is used in the place of stannite as a bulk composition, the inversion temperature is lowered to less than $400^{\circ}C$ which belongs to temperatures of the hydrothermal region.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.27-31
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• 2016

Purpose $^{99m}Tc-DMSA$ renal scan is a test for the comparison of the function by imaging the parenchyma of the kidneys by the cortex of a kidney and by computing the intake ratio of radiation by the left and right kidney. Since the distance between the kidneys and the bladder is not far given the bodily structure of an infant, the bladder is included in the examination domain. Research was carried out with the presumption that counts of bladder would impart an influence on the kidneys at the time of this renal scan. In consideration of the special feature that only a trace amount of a RI is injected in a pediatric examination, research on the method of injection was also carried out concurrently. Materials and Methods With 34 infants aged between 1 month to 12 months for whom a $^{99m}Tc-DMSA$ renal scan was implemented on the subjects, a Post IMAGE was acquired in accordance with the test time after having injected the same quantity of DMSA of 0.5mCi. Then, after having acquired an additional image by shielding the bladder by using a circular lead plate for comparison purposes, a comparison was made by illustrating the percentile of (Lt. Kidney counts + Rt. Kidney counts)/ Total counts, by drawing the same sized ROI (length of 55.2mm X width of 70.0mm). In addition, in the format of a 3-way stopcock, a Heparin cap and direct injection into the patient were performed in accordance with RI injection methods. The differences in the count changes in accordance with each of the methods were compared by injecting an additional 2cc of saline into the 3-way stopcock and Heparin cap. Results The image prior to shielding of the bladder displayed a kidney intake rate with a deviation of $70.9{\pm}3.18%$ while the image after the shielding of the bladder displayed a kidney intake rate with a deviation of $79.4{\pm}5.19%$, thereby showing approximately 6.5~8.5% of difference. In terms of the injection method, the method that used the 3-way form, a deviation of $68.9{\pm}2.80%$ prior to the shielding and a deviation of $78.1{\pm}5.14%$ after the shielding were displayed. In the method of using a Heparin cap, a deviation of $71.3{\pm}5.14%$ prior to the shielding and a deviation of $79.8{\pm}3.26%$ after the shielding were displayed. Lastly, in the method of direct injection into the patient, a deviation of $75.1{\pm}4.30%$ prior to the shielding and a deviation of $82.1{\pm}2.35%$ after the shielding were displayed, thereby illustrating differences in the kidney intake rates in the order of direct injection, a Heparin cap and the 3-way methods. Conclusion Since a substantially minute quantity of radiopharmaceuticals is injected for infants in comparison to adults, the cases of having shielded the bladder by removing radiation of the bladder displayed kidney intake rates that are improved from those of the cases of not having shielded the bladder. Although there are difficulties in securing blood vessels, it is deemed that the method of direct injection would be more helpful in acquisition of better images since it displays improved kidney intake rate in comparison to other methods.

• Pediatric Infection and Vaccine
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• v.8 no.2
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• pp.191-198
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• 2001

Purpose : The purpose of this study was to investigate clinical features of hospitalized infants 28~90 days of age with fever without source and to analyze those of young febrile infants using risk criteria for serious bacterial infection. Methods : The clinical features of 131 infants 28~90 days of age admitted to the Ulsan Dong-Kang General Hospital Pediatric Department because of fever(temperature ${\geq}38^{\circ}C$ rectally) without source, from January 2000 to December 2000, were investigated by retrospective chart review. The clinical features of 131 febrile infants were analyzed using Rochester criteria. Results : Among 131 cases, there were 60 cases(45.8%) of urinary tract infection, 33 cases (25.2%) of aseptic meningitis, 2 cases(1.5%) of bacteremia and 36 cases(27.5%) of no specific diagnosis. Among 131 cases, there were 57 cases(43.5%) in low risk group and 74 cases(56.5%) in not low risk one by Rochester criteria. A significant difference in the incidence of urinary tract infection, aseptic meningitis and no specific diagnosis was not found between both groups. Male to female ratio was 1.8 : 1. Sex ratio between both groups was not significantly different. Most febrile infant were noted in spring(35.1%) and the summer(36.7%). The peak incidence of aseptic meningitis was noted in May and June. The fever subsided mostly within 48~72 hours after administering antimicrobial agents(61.8~83.2%). A significant difference in duration of fever after administering antimicrobial agents was not found between both groups. Conclusion : A selected group of low risk infants 28~90 days of age with fever without source can be managed as outpatients provided that a thorough initial evaluation is performed, that parents can reliably monitor their infant closely at home and that careful follow up can be assured. Because bag collected specimens were more likely to yield indeterminate urine culture result, a suprapubic or catheter obtained urine specimen for culture is a necessary part of the evaluation of all febrile infants 28~90 days of age. The further prospective study on evaluation and management of young febrile infant should be performed in our hospital.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.931-946
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• 2017

The purpose of this study is to observe and analyze soil moisture conditions with high resolution and to evaluate its application feasibility to agriculture. For this purpose, we used three Landsat-8 OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) optical and thermal infrared satellite images taken from May to June 2015, 2016, and 2017, including the rural areas of Jeollabuk-do, where 46% of agricultural areas are located. The soil moisture conditions at each date in the study area can be effectively obtained through the SPI (Standardized Precipitation Index)3 drought index, and each image has near normal, moderately wet, and moderately dry soil moisture conditions. The temperature vegetation dryness index (TVDI) was calculated to observe the soil moisture status from the Landsat-8 OLI/TIRS images with different soil moisture conditions and to compare and analyze the soil moisture conditions obtained from the SPI3 drought index. TVDI is estimated from the relationship between LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) calculated from Landsat-8 OLI/TIRS satellite images. The maximum/minimum values of LST according to NDVI are extracted from the distribution of pixels in the feature space of LST-NDVI, and the Dry/Wet edges of LST according to NDVI can be determined by linear regression analysis. The TVDI value is obtained by calculating the ratio of the LST value between the two edges. We classified the relative soil moisture conditions from the TVDI values into five stages: very wet, wet, normal, dry, and very dry and compared to the soil moisture conditions obtained from SPI3. Due to the rice-planing season from May to June, 62% of the whole images were classified as wet and very wet due to paddy field areas which are the largest proportions in the image. Also, the pixels classified as normal were analyzed because of the influence of the field area in the image. The TVDI classification results for the whole image roughly corresponded to the SPI3 soil moisture condition, but they did not correspond to the subdivision results which are very dry, wet, and very wet. In addition, after extracting and classifying agricultural areas of paddy field and field, the paddy field area did not correspond to the SPI3 drought index in the very dry, normal and very wet classification results, and the field area did not correspond to the SPI3 drought index in the normal classification. This is considered to be a problem in Dry/Wet edge estimation due to outlier such as extremely dry bare soil and very wet paddy field area, water, cloud and mountain topography effects (shadow). However, in the agricultural area, especially the field area, in May to June, it was possible to effectively observe the soil moisture conditions as a subdivision. It is expected that the application of this method will be possible by observing the temporal and spatial changes of the soil moisture status in the agricultural area using the optical satellite with high spatial resolution and forecasting the agricultural production.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Journal of Nutrition and Health
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• v.42 no.5
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• pp.423-433
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• 2009

Folate and vitamin $B_{12}$ are essential cofactors for homocysteine (Hcy) metabolism. Homocysteinemia has been related with cardiovascular and neurodegenerative disease. We examined the effect of folate and/or vitamin $B_{12}$ deficiency on biomarkers of one carbon metabolism in blood, liver and brain, and analyzed the correlation between vitamin biomarkers in mild and moderate homocysteinemia. In this study, Sprague-Dawley male rats (5 groups, n = 10) were fed folatesufficient diet (FS), folate-deficient diet (FD) with 0 or 3 g homocystine (FSH and FDH), and folate-/vitamin $B_{12}$-deficient diet with 3 g homocystine (FDHCD) for 8 weeks. The FDH diet induced mild homocysteinemia (plasma Hcy 17.41 ${\pm}$ 1.94 nmol/mL) and the FDHCD diet induced moderate homocysteinemia (plasma Hcy 44.13 ${\pm}$ 2.65 nmol/mL), respectively. Although liver and brain folate levels were significantly lower compared with those values of rats fed FS or FSH (p < 0.001, p < 0.01 respectively), there were no significant differences in folate levels in liver and brain among the rats fed FD, FDH and FDHCD diet. However, rats fed FDHCD showed higher plasma folate levels (126.5 ${\pm}$ 9.6 nmol/L) compared with rats fed FD and FDH (21.1 ${\pm}$ 1.4 nmol/L, 22.0 ${\pm}$ 2.2 nmol/L)(p < 0.001), which is the feature of "ethyl-folate trap"by vitamin $B_{12}$ deficiency. Plasma Hcy was correlated with hepatic folate (r = -0.641, p < 0.01) but not with plasma folate or brain folate in this experimental condition. However, as we eliminated FDHCD group during correlation test, plasma Hcy was correlated with plasma folate (r = -0.581, p < 0.01), hepatic folate (r = -0.684, p < 0.01) and brain folate (r = -0.321, p < 0.05). Hepatic S-adenosylmethionine (SAM) level was lower in rats fed FD, FDH and FDHCD than in rats fed FS and FSH (p < 0.001, p < 0.001 respectively) and hepatic S-adenosylhomocysteine (SAH) level was significantly higher in those groups. The SAH level in brain was also significantly increased in rats fed FDHCD (p < 0.05). However, brain SAM level was not affected by folate and/or vitamin $B_{12}$ deficiency. This result suggests that dietary folate- and vitamin B12-deficiency may inhibit methylation in brain by increasing SAH rather than decreasing SAM level, which may be closely associated with impaired cognitive function in nutritional homocysteinemia.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• Korean Journal of Weed Science
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• v.5 no.2
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• pp.202-210
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• 1985

Requirements in weed control in a mulberry field are much similar to those in orchards, but also feature a longer period of weed control of various kinds of persistent weeds, i.e., spring, summer, and winter annuals as well as perennials. In addition the mulberry tree is relatively more sensitive to herbicide injury. Hence, very few herbicides have been used in mulberry field. The present study was conducted to evaluate the usefulness of oxyfluorfen in comparison with alachlor and simazine, which are registered for ordinary mulberry field in Korea, for weed control efficacy in the new, rapidly increasing practice of transparent polyethylene-film mulched and densely planted younger mulberry culture. Dominant spring weeds were Galium spp., Erigeron spp., Polygonum senticosum, and Chenopodium spp. in the non-mulched interbed area in contrast to the Digitaria spp. and Potulaca spp, under mulch. Dominant summer weeds were Digitaria spp., Portulaca spp., Erigeron spp., Artemisia spp. and Calystegia japonica in the non-mulched interbed area while weeds did not occur significantly during summer under mulch which were shaded by vigorously growing mulberry trees. The weeds occurred under mulch in spring reduced shoot growth of young mulberry tree resulting in the reduced yield of mulberry leaves for silkworms. The weeds occurred in the interbed area did not affect until May, but interfered later summer- and fall-growth of mulberry tree. Early single spring application of alachlor(EC), simazine(WP) or oxyfluorfen(EC) at a rate of 650 g, 750 g or 350 g ai per ha, respectively, controlled most annuals satisfactorily to fall in the mulched bed area. In the nonmulched interbed area, however, thrice does of alchlor or simazine was necessary for satisfactory control of spring weeds, followed by summer application of alachlor or simazine at twice dose level as tank mixture with paraquat at 490 g ai per ha for satisfactory control of summer to fall weeds. Single spring application of oxyfluorfen at a rate of 1400 g ai per ha was persistently effective to control satisfactorily even summer and fall weeds. However, heavy rainfall splashed soil borne oxyfluorfen to the lower branch leaves causing some leaf burns. Spring application of oxyfluorfen at a rate of 350 g ai per ha followed by summer application of oxyfluorfen and paraquat tank mixture (350 g ai + 490 g ai) was the best choice for the non-mulched interbed area weed control among the treatments.

• Journal of Acupuncture Research
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• v.29 no.1
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• pp.139-150
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• 2012

Objectives : The puropse of this study was to report the availability of Hyeongsang diagnosis compensating for visceral pattern identification in applying Sa-am acupuncture therapy. Methods : Eight cases was presented to substantiate the above. Results : According to the characteristic diagnostic method of Hyeongsang medicine by feature such as face, ears, eyes, nose and mouth shape, There are 8 pattern differentiations, including essence family, Qi family, spirit family, blood family, fish type, bird type, beast(running) type and crust(crustacea) type which are correlated with essence deficiency, heat harassing the heart spirit, Qi stagnation, blood stasis, kidney essence deficiency, intense heart fire, liver blood deficiency and lung Qi deficiency in the established visceral pattern identification, respectively. Eight patients was diagnosed by the above Hyeongsang 8 pattern differentiations, of whom Sinjeonggyeok(kidney reinforcing prescription) was applied to a patient with fish type and essence family to nourish kidney essence, and Giul prescription(Qi stagnation prescription) was given to a patient with Qi family for regulating Qi, and Sanghwa priscription(ministerial fire prescription) was delivered to a patient with Spirit family to clear the heart fire and tranquilize, and Sojangjeonggyeok(small intestine reinforcing prescription) was used for a patient with blood family to nourish blood and remove blood stasis, and Sinjeonggyeok(kidney reinforcing prescription), Simhangyeok(heart heat clearing prescription), Ganjeonggyeok(liver reinforcing prescription) and Pyejeonggyeok(lung reinforcing prescription) were utilized for fish type, bird type, beast(running) type and crust(crustacea) type respectively to reinforce the relevant visceral function. Conclusions : It was suggested that characteristic diagnostic method of Hyeongsang medicine should be helpful for enhancing the accuracy of the established visceral pattern identification, applying Sa-am acupuncture therapy more appropriately.