• Journal of Korean Society of Environmental Engineers
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• v.29 no.1
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• pp.23-30
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• 2007

The ultimate objective of this study is to develop oxygen-enriched combustion techniques applicable to the system of practical industrial boiler. To this end the combustion characteristics of lab-scale LNG combustor were investigated as a first step using the method of numerical simulation by analyzing the flame characteristics and pollutant emission behaviour as a function of oxygen enrichment level. Several useful conclusions could be drawn based on this study. First of all, the increase of oxygen enrichment level instead of air caused long and thin flame called laminar flame feature. This was in good agreement with experimental results appeared in open literature and explained by the effect of the decrease of turbulent mixing due to the decrease of absolute amount of oxidizer flow rate by the absence of the nitrogen species. Further, as expected, oxygen enrichment increased the flame temperatures to a significant level together with concentrations of $CO_2$ and $H_2O$ species because of the elimination of the heat sink and dilution effects by the presence of $N_2$ inert gas. However, the increased flame temperature with $O_2$ enriched air showed the high possibility of the generation of thermal $NO_x$ if nitrogen species were present. In order to remedy the problem caused by the oxygen-enriched combustion, the appropriate amount of recirculation $CO_2$ gas was desirable to enhance the turbulent mixing and thereby flame stability and further optimum determination of operational conditions were necessary. For example, the adjustment of burner with swirl angle of $30\sim45^{\circ}$ increased the combustion efficiency of LNG fuel and simultaneously dropped the $NO_x$ formation.

• Analytical Science and Technology
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• v.23 no.1
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• pp.1-14
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• 2010

It is of importance that all countries in worldwide, including EU and China, have adopted the Restrictions on the use of certain Hazardous Substances (RoHS) for all electronics. IEC62321 document, which was published by the International Electronics Committee (IEC) can have conflicts with the standards in the market. On the contrary Publicly Accessible Specification (PAS) for sampling published by IEC TC111 can be adopted for complementary application. In this work, we tried to find a route to disassemble and disjoint cellular phone sample, based on PAS and compare the screening methods available in the market. For this work, the cellular phone produced in 2001, before the regulation was born, was chosen for better detection. Although X-ray Fluorescence (XRF) showed excellent performance for screening, fast and easy handling, it can give information on the surface, not the bulk, and have some limitations due to significant matrix interference and lack of variety of standards for quantification. It means that screening with XRF sometimes requires supplementary tool. There are several techniques available in the market of analytical instruments. Laser ablation (LA) ICP-MS, energy dispersive (ED) XRF and scanning electron microscope (SEM)-energy dispersive X-ray (EDX) were demonstrated for screening a cellular phone. For quantitative determination, graphite furnace atomic absorption spectrometry (GF-AAS) was employed. Experimental results for Pb in a battery showed large difference in analytical results in between XRF and GF-AAS, i.e., 0.92% and 5.67%, respectively. In addition, the standard deviation of XRF was extremely large in the range of 23-168%, compared with that in the range of 1.9-92.3% for LA-ICP-MS. In conclusion, GF-AAS was required for quantitative analysis although EDX was used for screening. In this work, it was proved that LA-ICP-MS can be used as a screening method for fast analysis to determine hazardous elements in electrical products.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.3
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• pp.485-494
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• 2000

According to the worldwide interest in controlling $CO_2$ which contributes to green house effect. new techniques of reducing $CO_2$ are under development. We have developed new technique for reducing $CO_2$. In low $CO_2$ concentration. the chemical absorption method is useful. In this study. the kinetics of the reaction between $CO_2$ and the sterically hindered amine solution with piperazine. have been investigated from measurements of the rate of absorption of $CO_2$ in the stirred vessel that has a horizontal liquid-gas interface, in the temperature range $30{\sim}70^{\circ}C$. The experiments were carried out in the range 10.130~20.260 kPa of partial pressure of $CO_2$, and in aqueous $2.0kmol/m^3$ AMP solution with $0{\sim}0.4kmol/m^3$ piperazine The experimental results are as follows: 1) The absorption rate of $CO_2$ into aqueous AMP + piperazine solution is gett ng faster than that of aqueous AMP absorbents with temperature. Because the activation energy of piperazine 57.147 kJ/mol is higher than that of AMP 41.7kJ/mol. therefore the effect of piperazine on absorption rate increases with temperature. 2) Compared with aqueous AMP solution. the absorption rate of $CO_2$ into AMP + piperazine solution increases from 6.33% at $30^{\circ}C$ to 12% at $70^{\circ}C$, so AMP + piperazine solution is thought to be a better than AMP solution, 3) The reaction rate constants of piprazine in aqueous AMP solution with $CO_2$ have been determined as 217.21, 420.46, 707.00 and $3162.167m^3/kmol{\cdot}s$ respectively at 30, 40, 50 and $70^{\circ}C$ but these results are higher than those of Xu which were 186.7. 367.32. 693.01. $2207.65m^3/kmol{\cdot}s$ at 30, 40, 55, $70^{\circ}C$in aqueous MDEA solution. So the regression analysis of the data has led to the following equation In $k_p$ =28.324-6934.7/T.

• Clinical and Experimental Pediatrics
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• v.45 no.4
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• pp.459-465
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• 2002

Purpose : The aim of this study was to evaluate the latest tendency of esophageal foreign body's extraction and to obtain a consensus from recent trends of indications and techniques of flexible endoscopy of esophageal FB in children. Methods : We retrospectively reviewed medical records of 127 cases with foreign bodies in esophagus at Dept. of Pediatrics and Otorhinolaryngology, Gyeongsang National University Hospital (GNUH) from Jun, 1987 to July, 2001. They were divided into two groups by the kinds of endoscopy : flexible endoscope(66 cases) or rigid endoscope(61 cases). Rigid endoscopy was performed under general anesthesia at Dept. of Otorhinolaryngology but flexible endoscopy was performed without general anesthesia or sedative drugs(midazolam or diazepam). Results : An annual number of cases of two groups were similar from 1991 to 1998. But from 1999, flexible endoscopy was performed actively. Asymptomatic cases were frequently observed in flexible endoscopy(28 cases/66 cases) but swallowing difficulties were frequently observed in the rigid endoscopy group(25 cases/61 cases). Other symptoms were vomiting, irritability, chest discomfort and abdominal pain. The total number of cases with underlying disease(esophageal stenosis, cerebral palsy) was 8. The total number of cases with complications (erosion, ulcer, bleeding, perforation) was 11. The above cases were not correlated between the two groups. In 55 cases(83.3%) of the flexible endoscopic group and 53 cases(86.8%) of the rigid endoscopic group, foreign bodies in the esophagus were removed within 24 hours. Conclusion : We could not find any benefit in rigid endoscopic technique. Flexible endoscopic FB removal can be performed safely and effectively in children by an experienced endoscopist.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Journal of Chest Surgery
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• v.31 no.12
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• pp.1147-1158
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• 1998

Background: Portable cardiopulmonary bypass(CPB) technique has been used increasingly as a potent and effective option for emergency cardiopulmonary resuscitation(CPR) because it can maintain more stable hemodynamics and provide better survival than conventional CPR techniques. This study was designed to develop a prototype of Korean portable CPB system and, by applying it to CPR, to discriminate whether it would be superior to standard open-chest CPR. Material and Method: By using adult mongrel dogs, open-chest CPR(OCPR group, n=4) and portable-CPB CPR(CPB group, n=4) were compared with respects to restoration of spontaneous circulation(ROSC), hemodynamics, effects on blood cells, blood gas patterns, biochemical markers, and survivals. Ventricular fibrillation-cardiac arrest(VF-CA) of arrest(VF-CA) of 4 minutes followed by basic life support(BLS) of 15 minutes was applied in either group, which was standardized by the protocol of American Heart Association. Then, advanced life support(ALS) was applied to either group under the support of internal cardiac massage or CPB. ALS was maintained until ROSC was achieved but not longer than 30 minutes regardless of the presence of ROSC. All of the measured values were expressed as means±SD percent change from baseline. Result: During the early ALS, higher mean arterial pressure was maintained in CPB group than in OCPR group(90±19 vs. 71±32 %; p<.05) and lower mean pulmonary arterial pressure was also maintained in CPB group than in OCPR group(105±24 vs. 146±6%; p<.05). ROSC was achieved in all dogs. Post-ROSC levels of hematocrit, RBC, and platelet were decreased and plasma free hemoglobin was increased significantly in CPB group compared to OCPR group(p<.05). Changes in blood gas patterns, lactate, and CK-MB levels were not different between groups. Early mortality was seen in 3 dogs in OCPR group(survival time 31±36 hours) and 2 in CPB group(228±153 hours, p=ns). The remainders in both groups showed prolonged survival. Conclusion: These findings indicate that portable CPB can be effective to maintain stable hemodynamics during cardiac arrest, to achieve ROSC and to prolong survival. Further study is needed to refine the portable CPB system and to meet clinical challenges.

• The korean journal of orthodontics
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• v.29 no.4 s.75
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• pp.445-456
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• 1999

As a result of increased education and communication, the field of orthodontics has recently been expanded to include a greater number of adult treatment procedures. With this increased demand for adult orthodontic treatment, a problem that frequently arises is the placement of appliances on teeth restored with porcelain. But conventional acid-etching is ineffective in the preparation of porcelain surface for mechanical retention of orthodontic attachments. Also, it is possible to damage on porcelain. The purpose of this study was to evaluate the effect of composite bonding materials and the porcelain surface treatment methods on shear bond strength, and to observe the porcelain fracture rates. To accomplish this purpose, this study was carried out with feldsphatic porcelain, Ceram II. Porcelain surface treatment methods were divided into intact glazed porcelain which had not treatment and surface roughening. Surface roughening by etching with Hydroluoric acid(HF), sandblasting with Microetcher II and compound treatment with etching and sandblasting. Bonding materials were Ortho-two and Transbond. All porcelain specimens were applicated with porcelain primer. 1. In comparision according to porcelain surface treatment, surface roughening groups by HF etching and sandblasting had higher shear bond than intact group. No significant difference was found in Transbond group. 2. Ortho-two group had the higher shear bond strength than that of Transbond group in B:.u etching and sandblasting. 3. E(Transbond. Intact)group had the lowest shear bond strength in all experimental group. The bond strength was higher than clinically successful bond strength. 4. Non-treated group had very higher porcelain rates than treated group. 5. This study indicates that porcelain surface-roughening may not be necessary to attachment of orthodontic brackets to porcelain surfaces.

• Journal of Aquaculture
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• v.11 no.3
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• pp.371-380
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• 1998

This study has been conducted to develop the techniques for spat production of the sun and moon scallop from January 1995 to December 1996. With the adult scallops collected from the Sogwipo area, spawning induction and larvae rearing were attempted several times and monthly changes of GSI were also monitored during the experimental period. The results obtained wre as follows. 1. GSI started to increase from June and showed the maximum value of 22.17 and 14.98 in female and male respectively in November, and then gradually decreased from December. 2. Spawning induction by heating method turned out to the most efficient way showing the responding rate of 64.8~91.5%. The responding temperature was $21.4~26.4{\circ}C$ which was $3.1~8.5{\circ}C$ increased from the rearing temperature of $16.3~18.3{\circ}C$. An average number of eggs spawned was $9.2{\times}10^5$ 3. the average size of eggs after fertilization was about $72{\mu}m$ in diameter. The first polar body discharge, blastula formation, and trochopore larvae appearance occurred 30 mininutes, 18 hours, and 22 hours after fertilization respectively. 4. Settling rates in various collectors were similar one another, whereas pouring larvae in the mesh was the most efficient way for larval setting. 5. The spates grew to be 1mm in their shell length for the first 50 days after fertilization and 9.6mm in 135days. 6. Correlation between shell length (SL) of the spat and the number of days (X) after spat settlement could be expressed as $SL=257.75e ^{0.0272x}$(r=0.9100).

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.