• 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 Korean Society of Environmental Engineers
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• v.33 no.12
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• pp.913-921
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• 2011

This study examined the overall feasibility of low carbon green village formed in rural area. The check method is analyzing its environmental and economic feasibility and energy self-reliance. The biomass of the villages was set as 28 ton/day of livestock feces and 2 ton/day of cut fruit tree branches which make up the total of 30 ton/day. The facility consisted of a bio gasfication facility using wet (livestock feces) biomass and combined heat power generator, composting facility and wood boiler using dry (cut fruit tree branches) biomass. When operating the system, 540,540 kWh/yr of electricity and 1,762 Gcal/yr of heat energy was produced. The region's electricity energy and heat energy self-reliance rate will be 100%. The economic feasibility was found as a loss of 140 million won where the facility installation cost is 5.04 billion won, operation cost is 485.09 million won and profit is 337.12 million won. There will be a loss of about 2.2 billion won in 15 years but in the environmental analysis, it was found that crude replacement effect is about 178 million won, greenhouse gas reduction effect is about 92 million won making up the total environmental benefit of 270 million won. This means, there will be a yearly profit of about 130 million won. In terms of its environmental and economic feasibility and energy self-reliance, this project seemed to be a feasible project in overall even if it manages to get help from the government or local government.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.27-47
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• 1992

Engineers have developed new instruments that aid in diagnosis and therapy Ultrasonic imaging has provided a nondamaging method of imaging internal organs. A complex transducer emits ultrasonic waves at many angles and reconstructs a map of internal anatomy and also velocities of blood in vessels. Fast computed tomography permits reconstruction of the 3-dimensional anatomy and perfusion of the heart at 20-Hz rates. Positron emission tomography uses certain isotopes that produce positrons that react with electrons to simultaneously emit two gamma rays in opposite directions. It locates the region of origin by using a ring of discrete scintillation detectors, each in electronic coincidence with an opposing detector. In magnetic resonance imaging, the patient is placed in a very strong magnetic field. The precessing of the hydrogen atoms is perturbed by an interrogating field to yield two-dimensional images of soft tissue having exceptional clarity. As an alternative to radiology image processing, film archiving, and retrieval, picture archiving and communication systems (PACS) are being implemented. Images from computed radiography, magnetic resonance imaging (MRI), nuclear medicine, and ultrasound are digitized, transmitted, and stored in computers for retrieval at distributed work stations. In electrical impedance tomography, electrodes are placed around the thorax. 50-kHz current is injected between two electrodes and voltages are measured on all other electrodes. A computer processes the data to yield an image of the resistivity of a 2-dimensional slice of the thorax. During fetal monitoring, a corkscrew electrode is screwed into the fetal scalp to measure the fetal electrocardiogram. Correlations with uterine contractions yield information on the status of the fetus during delivery To measure cardiac output by thermodilution, cold saline is injected into the right atrium. A thermistor in the right pulmonary artery yields temperature measurements, from which we can calculate cardiac output. In impedance cardiography, we measure the changes in electrical impedance as the heart ejects blood into the arteries. Motion artifacts are large, so signal averaging is useful during monitoring. An intraarterial blood gas monitoring system permits monitoring in real time. Light is sent down optical fibers inserted into the radial artery, where it is absorbed by dyes, which reemit the light at a different wavelength. The emitted light travels up optical fibers where an external instrument determines O2, CO2, and pH. Therapeutic devices include the electrosurgical unit. A high-frequency electric arc is drawn between the knife and the tissue. The arc cuts and the heat coagulates, thus preventing blood loss. Hyperthermia has demonstrated antitumor effects in patients in whom all conventional modes of therapy have failed. Methods of raising tumor temperature include focused ultrasound, radio-frequency power through needles, or microwaves. When the heart stops pumping, we use the defibrillator to restore normal pumping. A brief, high-current pulse through the heart synchronizes all cardiac fibers to restore normal rhythm. When the cardiac rhythm is too slow, we implant the cardiac pacemaker. An electrode within the heart stimulates the cardiac muscle to contract at the normal rate. When the cardiac valves are narrowed or leak, we implant an artificial valve. Silicone rubber and Teflon are used for biocompatibility. Artificial hearts powered by pneumatic hoses have been implanted in humans. However, the quality of life gradually degrades, and death ensues. When kidney stones develop, lithotripsy is used. A spark creates a pressure wave, which is focused on the stone and fragments it. The pieces pass out normally. When kidneys fail, the blood is cleansed during hemodialysis. Urea passes through a porous membrane to a dialysate bath to lower its concentration in the blood. The blind are able to read by scanning the Optacon with their fingertips. A camera scans letters and converts them to an array of vibrating pins. The deaf are able to hear using a cochlear implant. A microphone detects sound and divides it into frequency bands. 22 electrodes within the cochlea stimulate the acoustic the acoustic nerve to provide sound patterns. For those who have lost muscle function in the limbs, researchers are implanting electrodes to stimulate the muscle. Sensors in the legs and arms feed back signals to a computer that coordinates the stimulators to provide limb motion. For those with high spinal cord injury, a puff and sip switch can control a computer and permit the disabled person operate the computer and communicate with the outside world.

• Journal of radiological science and technology
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• v.37 no.3
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• pp.187-193
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• 2014

The purpose of this study was to analyze the effect on the selectivity on of high-voltage rectification device that measured the performance of the grid, and the contrast improvement ability (K factor) by measuring the scattered radiation content of the transmitted X-rays. The scattered radiation generated when the X-ray flux comes from the diagnostic X-ray generator that passes through an object. Targeting four different rectifications of X-ray generators, the mean value of the tube voltage and the tube current was measured in order to maximize the accuracy of the generating power dose within the same exposure condition. Using fluorescence meter, the content of the scattered rays that are transmitted through the acrylic was measured depending on the grid usage. When grid is not used, the content of the scattered rays was the lowest (34.158%) with the single-phase rectifier, was increased with the inverter rectifier (37.043%) and the three-phase 24-peak rectification method (37.447%). The difference of the scattered radiation content of each device was significant from the lowest 0.404% to the highest 3.289% while using 8:1 grid, the content of the scattered ray was the lowest with the single content of the scattered ray was the lowest with the single-phase rectifier (18.258%), was increased with the rectifier (25.502%) and the 24-peaks rectification (24.217%). Furthermore, there was difference up to content 7.244% to the lowest content 1.285% within three-phase 24-peaks rectification, inverter rectifications, and single-phase rectifier depending on the selectivity of the grid. Drawn from the statistical analysis, there was a similar relationship between the contrast improvement factor and the K factor. As a result, the grid selectivity and the contrast were increased within the single-phase rectifier rather than the constant voltage rectifier.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.9 no.1
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• pp.13-25
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• 1998

Aim：We think that the most important etiology in parent abuse is the psychodynamic and psychopathology in the family. So, we investigated the adolescents being admitted in SNMH, whose chief complaints were parent abuse. We were trying to explore families psychodynamic and psychopathology, especially mother-child interaction and to differentiate them in according to developmental psychopathology. Method：Our objects were the adolescent patients admitted in SNMH from 1987 to 1997 because they attacked parents verbally and physically. We examined 21 adolescents except those with psychosis, organic mental disorder, autism and mental retardation by means of interview or chart review. Result and Conclusion：The number of male patients was 14 and the number of female patients was 7. The most common diagnosis was conduct disorder and borderline personality disorder. The mean age was in the mid-teens. We observed 4 subgroups that were divided developmentally in object relation. 1) Symbiotic group with mother：(1) They did not separate and remain in symbiotic relationships with their mothers based on insecure attachment. Fathers were abscent emotionally and physically, and their mothers were prominent in close relationships with the patients in their family , where as the patients were the only man in the family. Adolescents entered the second separation-individuation. They expressed anger and internal tension involved with the close attachment with their mothers and also attempted separation from their mothers through physically attacking them. (2) These patients had suffered from physical illness and developmental delay since birth. Therefore the parents overprotected their children. The children had persistent infantile omnipotence and fantasies of power, so they could not deal with unrealistic states, adapt to reality, and depended on their parents overtly. They easily acted out unless their demands were fulfilled. 2) Borderline personality disorder：We observed deficiencies in care taking. Their parents had personality problems and immaturity. They coulden’t help their children to be separated in the rapproachment phase. Their conflict about dependence-independence was revived in the second separation-individuation adolescent period. We understand parent abuse as an attempt to overcome the conflict. 3) Conduct disorder：They did not build up basic attachment with their parents. They think of their parents as only a means of fulfilling their needs. When patients’ need were not fulfilled and remained in a conflicted state, they attacked their parents, unable to control their aggressions and impulses.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Journal of the Korea Concrete Institute
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• v.25 no.3
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• pp.321-329
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• 2013

Recently, the medium-low level radioactive waste from nuclear power plant must be transported from temporary storage to the final repository. Medium-low level radioactive waste, which is composed mainly of the liquid ion exchange resin, has been consolidated with cementitious material in the plastic or iron container. Since cementitious material is brittle, it would generate cracks by impact load during transportation, signifying leakage of radioactive ray. In order to design the safety transporting equipment, there is a need to check the compressive strength of the current waste. However, because it is impossible to measure strength by direct method due to leakage of radioactive ray, we will estimate the strength indirectly by the dynamic modulus of elasticity. Therefore, it must be identified the relationship between of strength and dynamic modulus of elasticity. According to the waste acceptance criteria, the compressive strength of cement based solid is defined as more than 3.44 MPa (500 psi). Compressive strength of the present solid is likely to be significantly higher than this baseline because of continuous hydration of cement during long period. On this background, we have tried to produce the specimens of the 28 day's compressive strength of 3 to 30 MPa having the same material composition as the solid product for the medium-low level radioactive waste, and analyze the relationship between the strength and the dynamic modulus of elasticity. By controling the addition rates of AE agent, we made the mixture containing the ion exchange resin and showing the target compressive strength (3~30 MPa). The dynamic modulus of elasticity of this mixtures is 4.1~10.2 GPa, about 20 GPa lower in the equivalent compressive strength level than that of ordinary concrete, and increasing the discrepancy according to increase strength. The compressive strength and the dynamic modulus of elasticity show the liner relationship.

• Journal of the Korean Recycled Construction Resources Institute
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• v.1 no.1
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• pp.89-97
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• 2005

Recently, for the problem solution of demand and supply imbalance of fine aggregate due to the shortage of natural fine aggregate resource and the environment regulation on sea sand extraction in the construction field, the studies for the application of recycled fine aggregate using waste concrete are being progressed versatilely. On the other hand, the treatment of fly-ashes that of industrial by-product originated in the steam power plant is discussed by the continuous increasing of origination quantities. In the ease of using fly-ash, advantages are the improvement of workability, viscosity and long-time strength, and the reduction of hydration heat under the early ages, as the admixtures for concrete, but the studies for the application of fly-ash as recycled concrete admixtures are inadequacy. There fore, in this study, through investigating the properties of fresh, hardened and durability according to the replacement of recycled fine aggregate and fly-ash, it is intended to propose the fundamental data for structural application of recycled concrete using recycled fine aggregate and fly-ash. As the result of this study, they arc shown that the engineering properties and durability, in the case of replacement ratio 100% of recycled fine aggregate, arc similar to those of concrete using natural fine aggregate, so it is considered that recycled fine aggregate could be used as the fine aggregate for concrete. Also, the performances of recycled concrete are improved by replacing fly-ash.

• Journal of the korean academy of Pediatric Dentistry
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• v.47 no.4
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• pp.446-453
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• 2020

The purpose of this study was to evaluate the effect of Indocyanine Green (ICG) and near-infrared (NIR) diode laser on Streptococcus mutans biofilms depending on ICG concentrations. S. mutans biofilms were formed on a Hydroxyapatite disk, and 0.5, 1.0, 2.0, 3.0, 4.0, 5.0 mg/mL ICG solutions dissolved in sterile distilled water and a NIR diode laser having a power of 300 mW and a wavelength of 808 nm were applied to the biofilms. The temperature changes of the biofilm surface according to the concentrations of the ICG solution were measured using a 1-channel thermocouple thermometer. Compared to the control group, in the groups with only the 3.0, 4.0, 5.0 mg/mL ICG solution application, and in the groups with the 1.0, 2.0, 3.0, 4.0, 5.0 mg/mL ICG solution application and light irradiation, a statistically significant decrease in the bacterial counts were observed. The temperature increase according to the concentration of the ICG solutions was 9.53℃, 10.43℃, 11.40℃, 12.10℃, 12.67℃, and 13.63℃ in ICG solutions of 0.5, 1.0, 2.0, 3.0, 4.0, and 5.0 mg/mL respectively. This study presents the potential for clinical application of ICG and NIR diode lasers as a new method for preventing dental caries.

• Korean Journal of Biological Psychiatry
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• v.5 no.1
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• pp.95-101
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• 1998

The changes of electroencephalogram(EEG) in patients with dementia of Alzheimer's type are most commonly studied by analyzing power or magnitude in traditionally defined frequency bands. However because of the absence of an identified metric which quantifies the complex amount of information, there are many limitations in using such a linear method. According to the chaos theory, irregular signals of EEG can be also resulted from low dimensional deterministic chaos. Chaotic nonlinear dynamics in the EEG can be studied by calculating the largest Lyapunov exponent($L_1$). The authors have analyzed EEG epochs from three patients with dementia of Alzheimer's type and three matched control subjects. The largest $L_1$ is calculated from EEG epochs consisting of 16,384 data points per channel in 15 channels. The results showed that patients with dementia of Alzheimer's type had significantly lower $L_1$ than non-demented controls on 8 channels. Topographic analysis showed that the $L_1$ were significantly lower in patients with Alzheimer's disease on all the frontal, temporal, central, and occipital head regions. These results show that brains of patients with dementia of Alzheimer's type have a decreased chaotic quality of electrophysiological behavior. We conclude that the nonlinear analysis such as calculating the $L_1$ can be a promising tool for detecting relative changes in the complexity of brain dynamics.