• Journal of Bio-Environment Control
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• v.13 no.1
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• pp.51-55
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• 2004

The most commonly used inorganic nutrient compositions such as Murashige & Skoog medium have been optimized for heterotrophic growth. Therefore, they may not be optimal for photomixotrophic and photoautotrophic growth of plantlets. In photomixotrophic micropropagation, emdium sugar level is often lowered, while light and $CO_2$ levels in vessel are raised, and chlorophyllous explants are used to facilitate photosynthetic carbon acquisition. In a factorial experiment effect of addition (+) and omission(_) of organic materials (OM, 0.5 g ${\cdot}$ $m^{-3}$ each of thiamine, nicotinic acid and pyridoxine and 100 ${\cdot}$ $m^{-3}$ myo-inositiol) combined with three sucrose levels (0, 15, and 30 kg ${\cdot}$ $m^{-3}$) was tested on the growth of potato plantlets. Each of nodal cuttings with a leaf was cultured on 0.1${\times}$$10^{-4}m^{-3}$) MS agar ( 8 kg ${\cdot}$ $m^{-3}$) medium (pH 5.80 before autoclave) in glass test tubes (100 mm${\times}$25mm) capped with a sheet of transparent film with a 6 mm diameter gas permeable filter (5.1 air exchanges ${\cdot}$$h^{-1}$). Cultures were maintained in a room for 27 days at $23^{\circ}C$, 50% RH, 350-450${\mu}mol\;{\codt}\;mol^{-1}CO_2$, 16 h ${\cdot}$ $d^{-1}$ photoperiod at 13${\mu}mol\;{\codt}\;m\;{\codt}\;s^{-1}$ PPFD provided by white cool fluorescent lamps. Growth of potato plantlet in the +OM and -OM treatments were similar, while medium pH was 0.2 scale lower in the latter. Dry weight, % dry matter, and stem diameter enhanced, while shoot to root dry weight ratio, leaf area, chlorophyll concentration per gram dry weight, and medium pH decreased with increasing initial sucrose level. Interaction between OM and sucrose levels was observed in shoot length and medium pH. Results indicate that OM can be omitted from the medium without detrimental effect while addition of sucrose was beneficial for the photomixotrophic growth of potato plantlets under raised light and $CO_2$.

• Geophysics and Geophysical Exploration
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• v.1 no.1
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• pp.25-30
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• 1998

Time-lapse crosswell seismic data, recorded before and after the cavity filling, showed that the filling increased the velocity at a known cavity zone in an old mine site in Inchon area. The seismic response depicted on the tomogram and in conjunction with the geologic data from drillings imply that the size of the cavity may be either small or filled by debris. In this study, I attempted to evaluate the filling effect by analyzing velocity measured from the time-lapse tomograms. The data acquired by a downhole airgun and 24-channel hydrophone system revealed that there exists measurable amounts of source statics. I presented a methodology to estimate the source statics. The procedure for this method is: 1) examine the source firing-time for each source, and remove the effect of irregular firing time, and 2) estimate the residual statics caused by inaccurate source positioning. This proposed multi-step inversion may reduce high frequency numerical noise and enhance the resolution at the zone of interest. The multi-step inversion with different starting models successfully shows the subtle velocity changes at the small cavity zone. The inversion procedure is: 1) conduct an inversion using regular sized cells, and generate an image of gross velocity structure by applying a 2-D median filter on the resulting tomogram, and 2) construct the starting velocity model by modifying the final velocity model from the first phase. The model was modified so that the zone of interest consists of small-sized grids. The final velocity model developed from the baseline survey was as a starting velocity model on the monitor inversion. Since we expected a velocity change only in the cavity zone, in the monitor inversion, we can significantly reduce the number of model parameters by fixing the model out-side the cavity zone equal to the baseline model.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.140-146
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• 2019

In order to manage non-point sources, the paradigm of the system should be changed so that the management of non-point sources will be systematized from the beginning of the use and development of the land. It is necessary to change the method of national subsidy support and poeration plan for the non-point source management area. In order to increase the effectiveness of the non-point source reduction project, it is necessary to provide a minimum support ratio and to provide additional support according to the performance of the local government. A new system should be established to evaluate the performance of non-point source reduction projects and to monitor the operational effectiveness. It is necessary to establish the related rules that can lead the local government to take responsible administration so that the local governments faithfully carry out the non-point source reduction project and achieve the planned achievement and become the sustainable maintenance. Alternative solutions are needed, such as problems with the use of $100{\mu}m$ filter in automatic sampling and analysis, timely acquisition of water sampling and analysis during rainfall, and effective management of non-point sources network operation management. As an alternative, it is necessary to consider improving the performance of sampling and analysis equipment, and operate the base station. In addition, countermeasures are needed if the amount of pollutant reduction according to the non-point source reduction facility promoted by the national subsidy is required to be used as the development load of the TMDLs. As an alternative, it is possible to consider supporting incentive type of part of the maintenance cost of the non-point source reduction facility depending on the amount of pollutants reduction.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• The Korean Journal of Nuclear Medicine
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• v.1 no.1
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• pp.55-66
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• 1967

In view of its prevalence in the Far East area, a more detailed knowledge on the hookworm infection is one of the very important medical problems. The present study was aimed to; determine the infectivity of the artificially hatched ancylostoma duodenale larvae in man after its oral administration, evaluate the clinical symptomatology of such infection, determine the date of first appearance of the ova in the stool, calculate the blood loss per worm per day, assess the relation-ships between the ova count, infectivity(worm load), blood loss and severity of anemia. An erythrokinetic study was also done to analyse the characteristics of hookworm anemia by means of $^{59}Fe\;and\;^{51}Cr$. Materials and Methods Ten healthy male volunteers(doctors, medical students and laboratory technicians) with the ages ranging from 21 to 40 years were selected as the experimental materials. They had no history of hookworm infection for preceding several years, and care was taken not to be exposed to reinfection. A baseline study including a through physical examinations and laboratory investigations such as complete blood counts, stool examination and estimation of the serum iron levels was done, and a vermifuge, bephenium hydroxynaphoate, was given 10 days prior to the main experiment. The ancylostoma duodenale filariform larvae were obtained in the following manner; The pure ancylostoma duodenale ova were obtained from the hookworm anemia patients and a modified filter paper method was adopted to harvest larger number of infective larvae, which were washed several times with saline. The actively moving mature larvae were put into the gelatine capsules, 150 in each, and were given to the volunteers in the fasting state with 300ml. of water. The volunteers were previously treated with intramuscular injection of 15mg. of chlorpromazine in order to prevent the eventual nausea and vomiting after the larvae intake. The clinical symptoms and signs mainly of the respiratory and gastrointestinal tracts, appearance of the ova and occult blood in the stool etc. were checked every day for the first 20 days and then twice weekly until the end of the experiment, which usually lasted for about 3 months. Roentgenological survey of the lungs was also done. The hematological changes such as the red blood cell, white blood cell and eosinophil cell counts, hemoglobin content and serum iron levels were studied. The appearance of the ova in the stool was examined by the formalin ether method and the ova were counted in triplicate on two successive days using the Stoll's dilution method. The ferrokinetic data were calculated by the modified Huff's method and the apparent half survival time of the red blood cells by the modified Gray's method. The isotopes were simultaneously tagged and injected intravenously, and then the stool and blood samples were collected as was described by Roche et al., namely, three separate 4-day stool samples with the blood sample drawing before each 4-day stool collection. The radio-activities of the stools ashfied and the blood were separately measured by the pulse-height analyser. The daily blood loss was calculated with the following formula; daily blood loss in $ml.=\frac{cpm/g\;stool{\times}weight\;in\;g\;of\;4-day\;stool}{cpm/ml\;blood{\times}4}$ The average of these three 4-day periods was given as the daily blood loss in each patient. The blood loss per day per worm was calculated by simply dividing the daily blood loss by the number of the hookworm recovered after the vermifuge given twice a week at the termination of the experiment. The iron loss in mg. through the gastrointestinal tract was estimated with the daily iron loss in $mg=\frac{g\;Hgb/100ml{\times}ml\;daily\;blood\;loss{\times}3.40}{100}$ 3.40=mg of iron per g Hgb following formula; Results 1. The respiratory symptoms such as cough and sputum were noted in almost all cases within a week after the infection, which lasted about 2 weeks. The roentgenological findings of the chest were essentially normal. A moderate degree of febril reaction appeared within 2 weeks with a duration of 3 or 4 days. 2. The gastrointestinal symptoms such as nausea, epigastric fullness, abdominal pain and loose bowel appeared in all cases immediately after the larvae intake. 3. The reduction of the red blood cell count was not remarkable, however, the hemoglobin content and especially the serum iron level showed the steady decreases until the end of the experiment. 4. The white blood cells and eosinophil cells, on the contrary, showed increases in parallel and reached peaks in 20 to 30 days after the infection. A small secondary rise was noted in 2 months. 5. The ova first appeared in the stool in 40. 1 days after the infection, ranging from 29 to 51 days, during which the occult blood reaction of the stool became also positive in almost cases. 6. The number of ova recovered per day was 164, 320 on the average, ranging from 89,500 to 253,800. The number of the worm evacuated by vermifuge was in rough correlation with the number of ova recovered. 7. The infectivity of ancylostoma duodenale was 14% on the average, ranging from 7.3 to 20.0%, which is relatively lower than those reported by other workers. 8. The mean fecal blood loss was 5.78ml. per day, with a range of from 2.6 to 11.7ml., and the mean blood loss per worm per day was 0.30ml., with a range of from 0.13 to 0.73ml., which is in rough coincidence with those reported by other authors. There appeared to exist, however, no correlation between the blood loss and the number of ova recovered. 9. The mean fecal iron loss was 2.02mg. per day, with a range of from 1.20 to 3.89mg., which is less than those appeared in the literature. 10. The mean plasma iron disappearance rate was 0.80hr., with a range of from 0.62 to 0.95hr., namely, a slight accerelation. 11. The hookworm anemia appeared to be iron deficiency in origin caused by continuous intestinal blood loss.