• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.439-450
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• 2018

The lineament is a linear or curved terrain element to discriminate adjacent geological structures in each other. It has been widely used for analysis of geology, mineral exploration, natural disasters, and earthquake, etc. In the past, the lineament has been extracted using cartographic map or field survey. However, it is possible to extract more efficiently the lineament for a very wide area thanks to development of remote sensing technique. Remotely sensed observation by aircraft, satellite, or digital elevation model (DEM) has been used for visual recognition for manual lineament extraction. Automatic approaches using computer science have been proposed to extract lineament more objectively. In this study, we evaluate the characteristics of lineament which is automatically extracted with respect to difference of spatial resolution of DEM. We utilized two types of DEM: one is Shuttle Radar Topography Mission (SRTM) with spatial resolution of about 90 m (3 arc sec), and the other is the latest world DEM of TerraSAR-X add-on for Global DEM with 12 m spatial resolution. In addition, a global DEM was resampled to produce a DEM with a spatial resolution of 30 m (1 arc sec). The shaded relief map was constructed considering various sun elevation and solar azimuth angle. In order to extract lineament automatically, we used the LINE module in PCI Geomatica software. We found that predominant direction of the extracted lineament is about $N15-25^{\circ}E$ (NNE), regardless of spatial resolution of DEM. However, more fine and detailed lineament were extracted using higher spatial resolution of DEM. The result shows that the lineament density is proportional to the spatial resolution of DEM. Thus, the DEM with appropriate spatial resolution should be selected according to the purpose of the study.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.139-151
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• 2022

SAGD (Steam-Assisted Gravity Drainage) method is widely used for oil recovery in oil sands regions. The SAGD operation causes surface displacement, which can affect the stability of oil recovery plants and trigger various geological disasters. Therefore, it isimportant to monitor the surface displacement due to SAGD in the oil sands region. In this study, the surface displacement due to SAGD operations of the Athabasca oil sands region in Alberta, Canada, was observed by applying Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique to the Sentinel-1 time series SAR data acquired from 2016 to 2021. We also investigated the construction and expansion of SAGD facilitiesfrom Landsat-7/8 time seriesimages, from which the characteristics of the surface displacement according to the oil production activity of SAGD were analyzed. Uplift rates of 0.3-2.5 cm/yr in the direction of line of sight were observed over the SAGDs and their vicinity, whereas subsidence rates of -0.3--0.6 cm/yr were observed in areas more than several kilometers away from the SAGDs and not affected by oil recovery activities. Through the analysis of Landsat-7/8 images, we could confirm that the SAGDs operating after 2012 and showing high oil production activity caused uplift rates greater than 1.6 cm/yr due to the subsurface steam injection. Meanwhile, very small uplift rates of several mm per year occurred over SAGDs which have been operated for a longer period of time and show relatively low oil production activity. This was probably due to the compression of reservoir sandstone due to continuous oil recovery. The subsidence observed in areas except for the SAGDs and their vicinity estimated to be a gradual land subsidence caused by melting of the permafrost. Considering the subsidence, it was expected that the uplift due to SAGD operation would be greater than that observed by the PSInSAR. The results of this study confirm that the PSInSAR can be used as an effective means for evaluating productivity and stability of SAGD in the extreme cold regions.

• 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 Korean Society of Forest Science
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• v.80 no.1
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• pp.32-41
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• 1991

This study is focusted to the national park of Korean typical mountain Chi-ri, its visual resources of forests, and practiced inspectind course by way of hypothesis and tests, to show visual resource management objectively, and that of quantitative basic data. spatial image structure measured by Semantic Differential(S.D.) Scale was shown through factor analysis algorithm for the analyzing psychological amount and examined the flowing out of decisive factor and the objective importance related mutual factors by appling the measurement of visual quality. Also, it has been investigated the differences between the degrees of expectation which is used before and of satisfaction which is used, by appling instrumental expectation theory. And showed patterns of investigation area through factor analyzing algorithm. As a national Park, visual factors that have natural landscape harmonized forest, sky, surface of the water, curious stones and rocks, temples should be escalate their values affirmatively so as to be the scenery of pointed direction and enjoyable, and it is needs the techniques visual resource management and its controlling technique to make artificial structures more intentional planning and systemical setting. Manmade distinctive quality in the spatials that affect complementally or harmonizingly, should be received considering relations between the distifution and joining which in line with various visual presenting massive factors. More than that, it is needed united basic standard to the beauty of arrangements which contain visual continuity considered balance between nature and human work, simplicity of structural types, assimilation, emphasis, unification of different factors and pro rata.

• Korean Security Journal
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• no.40
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• pp.209-242
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• 2014

This study is to understand sure the primary crime prevention has been incidence as a social problem intended for parents through the analysis of the Crime Prevention Design (CPTED) CPTED element of recognize elements that target crime prevention strategy to effectively help students be and an object of the present invention is to provide a policy suggestion haryeoneunde proposed basic data required for orientation. To achieve the study objectives such as the core framework in this study IPA: Importance-Performance Analysis) also was selected. Subjects of study in 2010 Gyeongju Elementary parents name and were 203 first research group investigating the secondary school population of the region in 2014 to nomadic parents of 297 people sampled selection. Questionnaire that use by this study applies "Important-Performance Analysis : IPA" technique that Martilla & James(1977) presented and analyzed awareness for CPTED elements of strategy for student's crime prevention to elementary school pupil students' parentse. It was the first group, 0.886, 0.920, 0.895 and 2nd group 0.880, 0.906, 0.878 that reliability of (Cronbach' s ${\alpha}$) the importance, and believability of run chart was the first group, 0.880, 0.917, 0.878 and 2nd group, 0.735, 0.840, 0.830. Analysis of the data carried out frequency analysis, reliability analysis, Frequency analysis was performed, paired sample t-Test for the reliability analysis, and the technical statistical analysis of the data is. The analysis of lattice bars execution through the IPA, the importance of the primary parents elements of CPTED strategies are generally very high, but found that the variation depending on the components that Performance. This study, an important element of the strategy to eliminate the school building for students from inside and outside the criminal fears CPTED is a mechanical surveillance in the first group, organizational surveillance, and the second group is the region intensified I'll showed mechanically and organizational factors in the investigation, and request that the investment is urgently important element is also execution low, crime prevention personnel security higher importance than expanding the front door. The analysis result of this study expects that basic data can be used in policy direction presentation that examines closely CPTED elements of strategy for crime prevention of students and applies CPTED's component effectively at elementary school hereafter.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.93-102
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• 2016

Vehicle-to-Grid (V2G) system, bi-direction power trading technology, enables drivers possessing electric vehicle to sell the spare electricity charged in the vehicle to power distribution company. The drivers gain profit by charging electricity in the day time of high electricity rate. In this regard, the government is preparing the policies of building and supporting V2G infrastructure and demanding the potential consumers' preference for the V2G system. This paper attempts to analyze the consumers' preference using the data from obtained a survey of randomly selected 1,000 individuals. To this end, choice experiment, an economic technique, is employed here. The attributes considered in the study are residual amount of electricity, electricity trading hours, required plug-in time, and price measured as an amount additional to current gasoline vehicle price. The multinomial logit model, which requires the assumption of 'independence of irrelevant alternatives', is applied but the assumption could not be satisfied in our data. Thus, we finally utilized nested logit model which does not require the assumption. All the parameter estimates in the utility function are statistically significant at the 10% level. The estimation results show that the marginal willingness to pay (MWTP) for one hour increase in electricity trading hours is estimated to be KRW 1,601,057. On the other hand, a one percent reduction in residual amount of electricity and one hour reduction in required plug-in time in V2G system are computed to be KRW -91,911 and -470,619, respectively. The findings can provide policy makers with useful information for decision-making about introducing and managing V2G system.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.17-24
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• 2023

A post-processing technique for the measurement signal of a solenoid-type sensor is introduced. The solenoid-type sensor nondestructively evaluates an external tendon of prestressed concrete using the total flux leakage (TFL) method. The TFL solenoid sensor consists of primary and secondary coils. AC electricity, with the shape of a sinusoidal function, is input in the primary coil. The signal proportional to the differential of the input is induced in the secondary coil. Because the amplitude of the induced signal is proportional to the cross-sectional area of the tendon, sectional loss of the tendon caused by ruptures or corrosion can be identified by the induced signal. Therefore, it is important to extract amplitude information from the measurement signal of the TFL sensor. Previously, the amplitude was extracted using local maxima, which is the simplest way to obtain amplitude information. However, because the sampling rate is dramatically decreased by amplitude extraction using the local maxima, the previous method places many restrictions on the direction of TFL sensor development, such as applying additional signal processing and/or artificial intelligence. Meanwhile, the proposed method uses amplitude demodulation to obtain the signal amplitude from the TFL sensor, and the sampling rate of the amplitude information is same to the raw TFL sensor data. The proposed method using amplitude demodulation provides ample freedom for development by eliminating restrictions on the first coil input frequency of the TFL sensor and the speed of applying the sensor to external tension. It also maintains a high measurement sampling rate, providing advantages for utilizing additional signal processing or artificial intelligence. The proposed method was validated through experiments, and the advantages were verified through comparison with the previous method. For example, in this study the amplitudes extracted by amplitude demodulation provided a sampling rate 100 times greater than those of the previous method. There may be differences depending on the given situation and specific equipment settings; however, in most cases, extracting amplitude information using amplitude demodulation yields more satisfactory results than previous methods.

• Restorative Dentistry and Endodontics
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• v.27 no.6
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• pp.577-586
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• 2002

The purpose of this in vitro study was to compare the effects of root canal cleanness following two Ni-Ti rotary instruments with different rake angle. Thirty-six sound, extracted human premolars with single root were randomly divided into three groups. The used rotary instruments were HEROShaper (Group 1, Micro-Mega, Besancon, France, n=12) and ProFile (Group 2, Maillefer, Ballaigues, Switzerland, n=12). Control group (n=12) was only extirpated with barbed broach (Mani, Matsutani Seisakusho Co., Japan) Group 1 & 2 teeth were prepared to a #40/.04 taper at the apex followed by 1 mm using crown-down technique. After canal preparation and frequent irrigation with 5.25% sodium hypochlorite, the roots split longitudinally into a bucco-lingual direction. Root halves were cross-sectioned in apical third portion again. All root specimens were processed for SEM investigation and photographed. Separate evaluations by one endodontist were undertaken for smear layer on prepared walls with a five score-index for each using reference photograph in root halves. The penetration depth of smear layer into dentinal tubules was also estimated in the other halves. Following results were obtained: 1. Smear layer was observed on all the prepared walls with two experimental groups except control group. 2. Smear layer characteristics in two experimental groups; 1) HEROShaper group showed snowy, dusty appearance and were shown open dentinal tubuli on the prepared walls of almost specimens, and the thickness of smear layer covering onto dentinal surfaces was within 1-2 ${\mu}m$ in a few specimens. 2) ProFile group showed shiny, burnished appearance and complete root canal wall covered by a homogenous smear layer with no open dentinal tubuli in all specimens. The penetration of smear layer into dentinal tubules was found in all specimens and the thickness was at 2-4 ${\mu}m$ in all specimens. These results demonstrated that a completely clean root canal could not be achieved regardless of positive or negative rake angle, which is in accordance with the majority of previous studies on root canal cleanliness In conclusion, through irrigation with antibacterial solutions or chelating agents is recommended to remove the smear layer on prepared canal wall in spite of Ni-Ti instrumentation.

• Journal of Nutrition and Health
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• v.6 no.1
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• pp.39-46
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• 1973

This study was projected to get basic data which can provide a basis for future direction in nutritional education, and also to find the way how to improve the nutritional supply by evaluating the current nutritional intake of average high school students through the survey study of their daily packed lunch. Five hundred twenty seven students from two boys high school and two girls high school including one general and one vocational school respectively were chosen as random sampling technique. Four hundred forty nine among the 527 students had brought lunch. The contents of lunch box were weighed and converted into nutritional values according to the food composition table and compared with recommended dietary allowances. The results compared and classified by sex, School and housewives' educational level were as follows: 1. The nutritional supply in the lunch box was 671 Cal of energy and 22.3 gm of protein for male students which were respectively 55.9% and 74.2% of the dietary recommendations. On the other side female student's lunch boxes were found to contain 495 Cal of energy and 21.3gm of protein which are respectively 61.8% and 80% of the dietary prescriptions. Excluding niacin, all vitamins and minerals were found to be short. 2. Calorie intake in the vocational high school was found to be higher than in the general high school but lower in protein intake especially significant difference (P<0.01) in animal protein. 3. From the nutritional point of view the educational backgrouud of the housewives was not found to have any influence in the way of preparing the lunch boxes. 4. Nutrients of lunch box were heavily inclined to grain rather than to side dishes.