• Journal of The Korean Society of Grassland and Forage Science
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• v.30 no.4
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• pp.343-354
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• 2010

The present study was conducted to examine the fermentation characteristics and effective degradability (ED) in the rumen, and whole tract digestibility of whole crop silage based TMR in comparison with conventional separate feeding of concentrate and roughage. Three ruminally fistulated non-lactating Holstein cattle were used in a 3 $\times$ 3 Latin square design. The cattle were fed 8kg of whole crop barley silage based TMR (BS-TMR) or 8kg (DM basis) of whole crop rye silage based TMR (RS-TMR) twice (08:00 and 18:00) daily in an equal amount. The cattle were also fed concentrate (5.6kg) and rice straw (1.4kg) seperately (DM basis, Control) twice daily in an equal amount. The both silages were included in TMR at 20% level (as fed basis). pH in the rumen fluid was not influenced by the diets but was slightly higher from TMR than from control. No difference was found in ammonia-N concentration between diets. Total VFA concentration was relatively increased in the cattle fed RS-TMR to the other diets up to 6h post feeding. The proportion of acetate was increased in the TMR feeding at right before feeding (0 h, p<0.005) and 9 h (p<0.048) post feeding compared with control. Propionate proportion was increased (p<0.046) in both TMRs while butyrate proportion was increased (p<0.029) at 1h post feeding compared to other diets. Effective degradability (ED) of DM and CP of RS-TMR was relatively increased to other diets, and EDNDF of both TMRs was higher than that of control diet due to the increased parameters b (p<0.039) and c (p<0.006) in TMR treatments. Whole track digestibility of most components in the TMRs was slightly increased compared to that in control diet, and RS-TMR had a tendency to be increased whole track digestibility except for NDF compared to BS-TMR. Based on the results observed from the present study, nutrient availability of whole crop silage based TMR looked slightly better than conventional separate feeding of concentrate and rice straw, mainly due to the improved stabilization of fermentation in the rumen and increased NDF digestibility of whole crop silage in TMR.

• Economic and Environmental Geology
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• v.20 no.4
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• pp.289-303
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• 1987

당(當) 광산(鑛山)은 1936년(年) 금(金), 은(銀) 광종(鑛種)으로 출원(出願)하였다가 1940년(年) 망간을 추가(追加)하여 망간 광산(鑛山)으로 1975년(年)까지 Mn(30~35%) 110,000여(餘)톤을 생산(生産), 국내생산량(國內生産量)의 70%를 점(占)하였고 1976년(年) Mn광상(鑛床) 하부(下部)에 연(鉛), 아연(亞鉛) 유화광(硫化鑛)을 발견(發見), 현재(現在)까지 Pb十Zn=10% 이상(以上) 원광석(原鑛石) 500,000여(餘)톤을 처리(處理), 연정광(鉛精鑛)(Pb : 62%) 37,000여(餘)톤, 아연정광(亞鉛精鑛)(Zn : 46.5%) 37,000여(餘)톤, 유비광정광(硫砒鑛精鑛)(As : 30%) 5,000여(餘)톤을 생산(生産)하였다. 현재(現在) 일처리(日處理) 220톤 선광장(選鑛場)을 일처리(日處理) 400톤 규모(規模)로 증설계획중(增設計劃中)이다. 당(當) 광산(鑛山)에서 현재(現在)까지 시행(施行)한 갱외시추(坑外試錐)는 75개공(個孔) 18,500여(餘)m, 갱내시추(坑內試錐) 750개공(個孔) 40,000여(餘)m 갱도(坑道) 총연장(總延長) 13,000m에 달(達)하며 지표(地表)(623ML)로 부터 수직(垂直) 300m 하부(下部)까지 갱도(坑道)가 개착(開鑿)되어 있다. 당(當) 광산(鑛山)의 지질(地質)은 여러 조사서(調査書)에 의(依)하여 견해(見解) 차이(差異)를 보여주고 있으나 대체(大體)로 다음과 같은 쪽으로 인정되고 있다. 즉(卽) 본지역(本地域) 루층군(累層群)의 층순(層順)을 하위(下位)로 부터 상위(上位)로 향(向)하여 원남층(遠南層)${\rightarrow}$율리통(栗里統)${\rightarrow}$장산규암층(壯山珪岩層)${\rightarrow}$두음리층(斗音里層)${\rightarrow}$장군석회암층(將軍石灰岩層)${\rightarrow}$동수곡층(東水谷層)${\rightarrow}$재산층(才山層)의 순위(順位)로 보며 장산규암층(壯山珪岩層)과 두음리층(斗音里層)을 조선계(朝鮮系)의 양덕통(陽德統)으로, 장군석회암층(將軍石灰岩層)을 대석회암통(大石灰岩統)으로, 동수곡층(東水谷層)과 함탄층(含炭層)인 재산층(才山層)을 평안계(平安系) 지층(地層)으로 대비(對比)한다. 이들은 본지역(本地域) 북(北)쪽에서는 선(先)캠브리아기(紀)의 원남층(遠南層)과 율리통(栗里統)을 불정합(不整合)으로 덮고 남측(南側)에서는 재산층(才山層)과 원남층(遠南層)이 단층접촉(斷層接觸)하고 있다. 이들 지층(地層)의 주향(走向)은 $N60^{\circ}{\sim}80^{\circ}W$, $N60^{\circ}{\sim}80^{\circ}E$이며 경사(傾斜)는 대체(大體)로 $50^{\circ}{\sim}80^{\circ}N$이며 전체적(全體的)으로 역전(逆轉)된 층서(層序)를 보여주는 바 지질구조(地質構造)에 있어서 단사구조(單斜構造)인지 등사(等斜)습곡의 향사(向斜), 또는 등사(等斜)습곡이 배사구조(背斜構造)인지 아직 밝혀지지 않고 있다. 화성암체(火成岩體)는 본지역(本地域) 서측(西側)에 쥬라기(紀) 춘양화강암(春陽花崗岩)이 불규칙(不規則)한 실입(實入) 접촉면(接觸面)을 보여주며 시대미상(時代未詳)(백악기(白堊紀)?)의 거정화강암(巨晶花崗岩), 반화강암(半花崗岩)이 소암주상(小岩株狀)으로 몇 곳 실입(實入)하고 산성(酸性)~중성(中性)의 맥암(脈岩)과 염기성(鹽基性) 안산암질암(安山岩質岩)이 실입(實入)해 있다. 광상(鑛床)은 장군석회암층(將軍石灰岩層)에 배태(胚胎)되어 있는 열수교대(熱水交代) 연(鉛), 아연(亞鉛), 은등(銀等)의 혼합(混合) 유화광상(硫化鑛床)으로 다량(多量)의 Mn분(分)을 수반(隨伴)하며 지표부(地表部)에 Mn광상(鑛床)을 형성(形成)하고 있다. 광상(鑛床)의 형태(形態)는 괴상(塊狀), 각력(角礫)pipe상(狀), 맥상(脈狀)으로 나타난다. 광상(鑛床)의 성인(成因)과 생성시기(生成時期)에 대(對)하여 많은 논란(論難)이 있다. 즉(卽) 열수교대(熱水交代)냐, 접촉교대(接觸交代)냐, 동시퇴적기원(同時堆積起源)이냐, 또는 생성시기(生成時期)가 쥬라기(紀)인지 백악기(白堊紀)인지에 대해 이론(異論)이 있다. 본지역(本地域) 광상(鑛床)은 남본(南本), 100우(右), 북(北), 유비철(硫砒鐵), 동(東), 서(西), 재남(才南), 재동(才東), 110호(號) 등(等)이 지표(地表) Mn로두광화대(露頭鑛化帶)와 관련(關聯) 명명(命名)된 바 전(前)4자(者)는 하부(下部)에서 유화광상(硫化鑛床)이 확인(確認)되었으나 나머지 후자(後者)에서는 아직 하부(下部)에 유화광상(硫化鑛床)이 확인(確認)되지 않고 있으며 남본광상(南本鑛床)으로 부터 남동(南東) 300여(餘)m 지점에 장군석회암층(將軍石灰岩層)과 동수곡층(東水谷層) 경계부(境界部)에 Fe 55~60% 자철광상(磁鐵鑛床)이 확인(確認)된 바 신례미(新禮美) 자철광상(磁鐵鑛床)과 유사성(類似性)이 있는 것 같아 흥미(興味)롭다. 당(當) 광산(鑛山)의 현재(現在)까지의 탐광(探鑛)은 남본광상(南本鑛床) 지표로두(地表露頭)(Mn) 하부(下部)에서 확인(確認)된 연(鉛), 아연(亞鉛), 은(銀) 유화광체(硫化鑛體) 하부(下部)와 전탐(電探)에 의(依)해 확인(確認)된 북광체(北鑛體), 갱도접근중(坑道接近中)에 확인(確認)된 100우광체(右鑛體), 유비철광체(硫砒鐵鑛體) 등(等)의 하부(下部) 탐광(探鑛)을 주(主)로 하고 지표(地表) Mn로두(露頭) 하부(下部)에 대(對)한 시추탐광(試錐探鑛0을 병행(竝行)하고 있으며 시추(試錐)에 의(依)해서 지표(地表)로 부터 790m 하부(下部)(해발(海拔) 200ML)까지 광화대(鑛化帶)가 확인(確認)되었다. 향후(向後) 탐광방침(探鑛方針)을 확고(確固)히 수립(樹立)하기 위(爲)하여는 광상(鑛床)의 성인구명(成因究明)은 물론(勿論) 광상(鑛床)의 배태조건(胚胎條件)에 있어 지질구조규제(地質構造規制)와 화강암(花崗岩)의 실입상(實入狀)과의 관계(關係), 광액(鑛液)의 통로(通路)에 대(對)한 지질구조(地質構造), 모암(母岩)의 화학(化學) 물리적(物理的) 특성(特性)에 대(對)한 연구(硏究) 검토(檢討)가 었어야 하겠다.

• Korean Journal of Weed Science
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• v.7 no.2
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• pp.186-199
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• 1987

This study was carried out to investigate the growth of Korean lawn grass (Zoysia japonica Steud.), penncross bentgrass (Agrostis palustris Huda) and seaside bentgrass (Agrostis spp.) under application of 21 pre- and post-emergence herbicides and the weeding effect of 14 annual and 4 perennial weeds with them for the purpose of the systematic chemical weed control in turf. The results obtained were as follows; 1. Napropamide, napropamide + triclopyr and benefin were safe for Korean lawn grass and two kinds of bentgrasses when they were treated at 4 and 25 days after transplanting of turfgrasses. Simazine, lenacil and bentazon inhibited the growth of bentgrasses, but not Korean lawn grass. 2. The preemergence application of simazine, benefin and napropamide + simazine showed excellent control for Digitaria sanguinalis, Cyperus amuricus, Chenopodium album, Portulaca oleracea and Centipeda minima. Lenacil was excellent for control of all the tested weeds except Chenopodium album, napropamide excellent for them except Cyperus amuricus and Portulaca oleraces, and bentazon good for them except Digitaria sanguinalis. When simazine was treated with either napropamide or triclopyr at preemergence of weeds, weeding effect increased without inhibition of lawn growth. 3. The postemergence application of mecoprop, bentazon, benefin + dicamba and benefin + mecoprop was safe to bentgrasses. All the tested postemergence herbicides except simazine + atrazine did not inhibit the growth of Korean lawn grass. 4. Other postemergence herbicides mecoprop and triclopyr were excellent for the control of Echinochloa crusgalli and those except benefin and mecoprop excellent for Kummerovia striata. Digitaria sanguinalis was controlled by treating with all the tested post emergence herbicides and Cyperus amuricus controlled only by bentazon. 5. The growth rates of bentgrasses treated with simazine, lenacil and napropamide + simazine were lower than that of hand-weeded check, and those of benefin, bentazon, napropamide, napropamide + triclopyr, stomp, bensulide and triclopyr were higher than that one when applied at spring season. Korean lawn grass growth appeared to be good under application of all the tested preemergence herbicides at spring. Lanacil and bentazone showed poor control of Echinochloa crusgalli, and bensulide showed poor control of Erigeron canadensis. Also, napropamide and bentazon were not good for Kummerovia striata control. However, at the respective rates of all the tested herbicides, these three weeds were greatly controlled by 85-100% of weeding effect. 6. At the application of autumn season, bentazon, napropamide, pendimethalin, benefin, napropamide + triclopyr, bensulide and triclopyr seemed to be safe against three kinds of turfgrasses. But simazine, napropamide + simazine inhibited the growth of bentgrasses except Korean lawn grass. In terms of weed control performance, triclopyr was poor for controlling Echinochloa crusgalli and bentazon and stomp for Poa annua, napropamide, benefin and bensulide for Stellaria medico. Stellaria uliginosa and Cerastium caespitosum were well controlled by all the tested preemergence herbicides. 7. Korean lawn grass was safe when paraquat and glyphosate were treated at the dormanant season of turfgrass. These herbicides showed excellent controll of Poa annua but poor control of perennials in order of Trifolium repens < Miscanthus sinensis < Calystegia japonica < Artemisia asiatica. 8. In field test, all of 19 herbicides seemed to be safe when treated at Korean lawn grass. All of 10 preemergence herbicides were excellent for controlling annual weeds, but poor for perennial ones. All of 9 postemergence herbicides showed a excellent control for broad-leaf weeds.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.62-68
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• 2016

Purpose In a cyclosporine experiment using a robotic liquid handing system has found a deviation of its standard curve and low reproducibility of patients's results. The difference of the test is that methanol is mixed with samples and the extractions are used for the test. Therefore, we assumed that the abnormal test results came from using methanol and conducted this test. In a manual of a robotic liquid handling system mentions that we can choose several setting parameters depending on the viscosity of the liquids being used, the size of the sampling tips and the motor speeds that you elect to use but there's no exact order. This study was undertaken to confirm pipetting ability depending on types of liquids and investigate proper setting parameters for the optimum dispensing ability. Materials and Methods 4types of liquids(water, serum, methanol, PEG 6000(25%)) and $TSH^{125}I$ tracer(515 kBq) are used to confirm pipetting ability. 29 specimens for Cyclosporine test are used to compare results. Prepare 8 plastic tubes for each of the liquids and with multi pipette $400{\mu}l$ of each liquid is dispensed to 8 tubes and $100{\mu}l$ of $TSH^{125}I$ tracer are dispensed to all of the tubes. From the prepared samples, $100{\mu}l$ of liquids are dispensed using a robotic liquid handing system, counted and calculated its CV(%) depending on types of liquids. And then by adjusting several setting parameters(air gap, dispense time, delay time) the change of the CV(%)are calcutated and finds optimum setting parameters. 29 specimens are tested with 3 methods. The first(A) is manual method and the second(B) is used robotic liquid handling system with existing parameters. The third(C) is used robotic liquid handling system with adjusted parameters. Pipetting ability depending on types of liquids is assessed with CV(%). On the basis of (A), patients's test results are compared (A)and(B), (A)and(C) and they are assessed with %RE(%Relative error) and %Diff(%Difference). Results The CV(%) of the CPM depending on liquid types were water 0.88, serum 0.95, methanol 10.22 and PEG 0.68. As expected dispensing of methanol using a liquid handling system was the problem and others were good. The methanol's dispensing were conducted by adjusting several setting parameters. When transport air gap 0 was adjusted to 2 and 5, CV(%) were 20.16, 12.54 and when system air gap 0 was adjusted to 2 and 5, CV(%) were 8.94, 1.36. When adjusted to system air gap 2, transport air gap 2 was 12.96 and adjusted to system air gap 5, Transport air gap 5 was 1.33. When dispense speed was adjusted 300 to 100, CV(%) was 13.32 and when dispense delay was adjusted 200 to 100 was 13.55. When compared (B) to (A), the result increased 99.44% and %RE was 93.59%. When compared (C-system air gap was adjusted 0 to 5) to (A), the result increased 6.75% and %RE was 5.10%. Conclusion Adjusting speed and delay time of aspiration and dispense was meaningless but changing system air gap was effective. By adjusting several parameters proper value was found and it affected the practical result of the experiment. To optimize the system active efforts are needed through the test and in case of dispensing new types of liquids proper test is required to check the liquid is suitable for using the equipment.