• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. 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, total misclassification cost is more affected by FNE rather than FPE. 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 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Korean journal of applied entomology
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• v.50 no.3
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• pp.235-245
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• 2011

Temperature-related parameters of Panonychus citri (McGregor) (Acarina: Tetranychidae) development were estimated and a stage-structured matrix model was developed. The lower threshold temperatures were estimated as $8.4^{\circ}C$ for eggs, $9.9^{\circ}C$ for larvae, $9.2^{\circ}C$ for protonymphs, and $10.9^{\circ}C$ for deutonymphs. Thermal constants were 113.6, 29.1, 29.8, and 33.4 degree days for eggs, larvae, protonymphs, and deutonymphs, respectively. Non-linear development models were established for each stage of P. citri. In addition, temperature-dependent total fecundity, age-specific oviposition rate, and age-specific survival rate models were developed for the construction of an oviposition model. P. citri age was categorized into five stages to construct a matrix model: eggs, larvae, protonymphs, deutonymphs and adults. For the elements in the projection matrix, transition probabilities from an age class to the next age class or the probabilities of remaining in an age class were obtained from development rate function of each stage (age classes). Also, the fecundity coefficients of adult population were expressed as the products of adult longevity completion rate (1/longevity) by temperature-dependent total fecundity. To evaluate the predictability of the matrix model, model outputs were compared with actual field data in a cool early season and hot mid to late season in 2004. The model outputs closely matched the actual field patterns within 30 d after the model was run in both the early and mid to late seasons. Therefore, the developed matrix model can be used to estimate the population density of P. citri for a period of 30 d in citrus orchards.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.239-247
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• 2015

Recently, various research studies on frontal collision and rear-ender which occur more frequently compared to others are underway as the public interest on them is growing. This study analyzes scientifically the relationship between effective impact speed and injury incidence for vehicle crash accident reconstruction and presents a relevant model formula. Because real vehicle experiments have certain limitations such as possible injuries, this study efforts to collect and analyze as many materials as possible to substitute real vehicle experiments, including data from various collision tests and human experiments. As a result, this study present a threshold in which head-on collisions and rear impacts do not cause injuries under 7 km/h of effective impact speed, and suggests a model formula showing that injury extent is linearly proportional to effective impact speed through collision speed and amount of plastic deformation. In conclusion, a model formula for estimating effective impact speed and injury incidence newly proposed in this study is expected to be used as a minimum standard of judgment in disputes on the injury extent of passenger in head-on collisions and rear impacts. Furthermore its availability in terms of technological analysis in legal arguments is expected to be very high if this study will be enhanced by referring to scientific analyses of various real accidents so as to apply it in various types of collision accidents.

• Journal of Preventive Medicine and Public Health
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• v.38 no.3
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• pp.283-290
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• 2005

Objectives : The aim of this paper was to examine the relationship between the summertime (June to August) heat index, which quantifies the bioclimatic apparent temperature in sultry weather, and the daily disease-related mortality in Seoul for the period from 1991 to 2000. Methods : The daily maximum (or minimum) summertime heat indices, which show synergetic apparent temperatures, were calculated from the six hourly temperatures and real time humidity data for Seoul from 1991 to 2000. The disease-related daily mortality was extracted with respect to types of disease, age and sex, etc. and compared with the time series of the daily heat indices. Results : The summertime mortality in 1994 exceeded the normal by 626 persons. Specifically, blood circulation-related and cancer-related mortalities increased in 1994 by 29.7% (224 persons) and 15.4% (107 persons), respectively, compared with those in 1993. Elderly persons, those above 65 years, were shown to be highly susceptible to strong heat waves, whereas the other age and sex-based groups showed no significant difference in mortality. In particular, a heat wave episode on the 22nd of July 2004 ($>45^{\circ}C$ daily heat index) resulted in double the normal number of mortalities after a lag time of 3 days. Specifically, blood circulation-related mortalities, such as cerebral infraction, were predominant causes. Overall, a critical mortality threshold was reached when the heat index exceeded approximately $37^{\circ}C$, which corresponds to human body temperature. A linear regression model based on the heat indices above $37^{\circ}C$, with a 3 day lag time, accounted for 63% of the abnormally increased mortality (${\geq}+2$ standard deviations). Conclusions : This study revealed that elderly persons, those over 65 years old, are more vulnerable to mortality due to abnormal heat waves in Seoul, Korea. When the daily maximum heat index exceeds approximately $37^{\circ}C$, blood circulation-related mortality significantly increases. A linear regression model, with respect to lag-time, showed that the heat index based on a human model is a more dependable indicator for the prediction of hot weather-related mortality than the ambient air temperature.

• Journal of Korea Water Resources Association
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• v.42 no.6
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• pp.457-464
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• 2009

This paper proposes methodologies for analyzing the accuracy of the proportional hazards model in predicting consecutive break times of water mains and estimating the time interval for economical water main replacement. By using the survival functions that are based on the proportional hazards models a criterion for the prediction of the consecutive pipe breaks is determined so that the prediction errors are minimized. The criterion to predict pipe break times are determined as the survival probability of 0.70 and only the models for the third through the seventh break are analyzed to be reliable for predicting break times for the case study pipes. Subsequently, the criterion and the estimated lower and upper bound survival functions of consecutive breaks are used in predicting the lower and upper bounds of the 95% confidence interval of future break times of an example water main. Two General Pipe Break Prediction Models(GPBMs) are estimated for an example pipe using the two series of recorded and predicted lower and upper bound break times. The threshold break rate is coupled with the two GPBMs and solved for time to obtain the economical replacement time interval.

• Journal of Environmental Science International
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• v.19 no.11
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• pp.1423-1436
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• 2010

The effects of meteorological and reclaiming conditions on the reduction of suspended particles are investigated using a computational fluid dynamics (CFD) model with the k-$\varepsilon$ turbulence closure scheme based on the renormalization group (RNG) theory. Twelve numerical experiments with different meteorological and reclaiming conditions are performed. For identifying the meteorological characteristics of the target area and providing the inflow conditions of the CFD model, the observed data from the automatic weather station (AWS) near the target area is analyzed. Complicated flow patterns such as flow distortion, horse-shoe vortex, recirculation zone, and channeling flow appeared due to the topography and buildings in the domain. Specially, the flow characteristics around the reclamation area are affected by the reclaiming height, reclaiming size and windbreak height. Reclaiming height affected the wind speed above the reclaiming area. Windbreak induces more complicated flow patterns around the reclaiming area as well as within the reclaiming area. In front of the windbreak, flow is distorted as it impinges on the windbreak. As a result, upward flow is generated there. Behind the windbreak, a secondary circulation, so called, a recirculation zone is generated and flow is reattached at the end of the recirculation zone (reattachment point). At the lower part of the recirculation zone, there is a reverse flow toward the windbreak. Flow passing to the reattachment point starts to be recovered. Total amounts of suspended particles are calculated using the frictional and threshold frictional velocities, erosion potential function, and the number of surface disturbance. In the case of a 10 m-reclaiming and northerly wind, the amount of suspended particles is largest. In the presence of 5 m windbreak, the friction velocity above the reclaiming area is largely reduced. As a result, the total amount of the suspended particles largely decreases, compared to the case with the same reclaiming and meteorological conditions except for the windbreak The calculated suspended particle amounts are used as the emission rate of the dispersion model simulations and the dispersion characteristics of the suspended particles are analyzed.

• Journal of Preventive Medicine and Public Health
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• v.31 no.2 s.61
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• pp.249-264
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• 1998

Reports on a potential relationship between sensory neural hearing loss(SNHL) and cardiovascular or hematologic factor show that the results are controversial. A detailed analysis of risk factors in the development of SNHL was carried out in 3,050 non-noise exposed healthy worker. The mean hearing threshold of both ears at 500, 1000, 2000, 4000, 8000Hz was measured and the effect of age, possible cardiovascular risk factor and hematologic factor (blood viscosity and hemostatic factors) on SNHL were evaluated. first, each of these were associated with loss of hearing sensitivity when univariately and multivariatively analysed. In a multiple regression model, age, sex, body mass index, WBC and total cholesterol level were independently associated with the mean of hearing sensitivity decrease at 4000 and 8000Hz. Second, study subjects were divided into two group (normal vs SNHL) and we compare the possible risk between both groups, and analysed univariate and multivariative logistic model. In a multiple logistic regression model, age, sex, body mass index, WBC and total cholesterol level, total protein, platelet were independently associated with SNHL. Our results show that we have some reliable indices of susceptibility to SNHL using cardiovascular measures or biochemical factor, but future, more extensive studies are required.

• The Journal of Korean Physical Therapy
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• v.22 no.3
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• pp.71-77
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• 2010

Purpose: To determine whether upregulation of inducible nitric oxide synthase (iNOS) transcription and translation is related to radicular pain in a model of lumbar disc herniation. Also, to investigate the temporal changes of mRNA expression of iNOS and the identity of iNOS and transient receptor potential vanilloid (TRPV) 1 channel expression cells in dorsal root ganglion (DRG) of a model of lumbar disc herniation. Methods: A lumbar disc herniated rat model was developed by implantation of the autologous nucleus pulposus, harvested from the coccygeal vertebra of each tail, on the left L5 nerve root just proximal to the DRG. Rats were tested for mechanical allodynia of the plantar surface of both hind paws 2 days before surgery and 1, 5, 10, 20 and 30 days postoperatively. Reverse transcription polymerase chain reaction (RT-PCR) was used to follow iNOS mRNA expression. To stain iNOS and TRPV1 in DRG, an immunohistochemical study was done 10 days after surgery. Results: A significant drop in mechanical withdrawal threshold on the ipsilateral and contralateral hind paws was observed 1 day after surgery and was prolonged to 30 days in rats with lumbar disc herniation. The expression of mRNA for iNOS peaked at postoperative day 10 on both sides of the DRG. iNOS-positive sensory neurons in the DRG varied in size from large to small diameter cells. A majority of small and intermediate sensory neurons were TRPV1-positive cells. Double immunofluorescence staining for TRPV1 and iNOS revealed that most intermediate TRPV1-positive sensory neurons co-localized with iNOS-positive neurons. Conclusion: Nucleus pulposus-induced mechanical allodynia can be generated without mechanical compression. This pain is related to temporal changes in expression of iNOS mRNA in the DRG. Co-localization of TRPV1 and iNOS in intermediate neurons of the DRG is correlated with pain modality and intensity.

• Korean Journal of Acupuncture
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• v.21 no.1
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• pp.113-127
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• 2004

Objectives : The usage of acupuncture has gained popularity as an alternative method of treatment for certain chronic pain conditions. However, the efficacy of acupuncture in various diseases has not been fully established and the underlying mechanism is not clearly understood. In the present study, the effect of electroacupuncture (EA) applied to foot samli$(ST_{36})$ on the carrageenan-induced knee arthritic pain was examined. Methods : A common source of persistent pain in humans is the knee arthritis. Knee arthritis was induced by injection of 2 % carrageenan $50\;{\mu}l$ into the knee joint cavity. When rats developed pain behaviors, EA was applied for 30 min. under enflurane anesthesia with repeated train stimuli at the intensity of 10X of muscle twitch threshold. The weight bearing force of the hind limb was measured for an indicator of pain level after each manipulation. Results : The average weight borne by the hind limb during normal gait was 55% of total body weight, which was reduced to less than 10% after knee arthritis. EA improved the weight bearing of the arthritic hind limb significantly for the duration of 4 hr. EA applied to $ST_{36}$ point produced a significant improvement of stepping force of the arthritic foot lasting for at least 4 h. However, $GB_{31}$ point did not produce any significant increase of weight bearing force. The analgesic effect was specific to the acupuncture point since the analgesic effect on the knee arthritis model could not be mimicked by EA applied to a nearby point, $GB_{31}$. The relations between EA-induced analgesia and endogenous nitric oxide(NO) and inducible NO synthase(iNOS)/neuronal NOS was also examined. Results were turned out that both NO production and nNOS/iNOS protein expression which is increased by arthritis were suppressed by EA stimulation applied to $ST_{36}$ point. Conclusions : The data suggest 1) that EA produces a potent analgesic effect on the rat model of chronic knee arthritis pain in a point specific manner and 2) that EA-induced analgesia modulate endogenous NO through the suppression of nNOS/iNOS protein expression.