• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.333-343
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• 2015

This research aims at identifying the goshawk's possible and replaceable breeding ground by using the MaxEnt prediction model which has so far been insufficiently used in Korea, and providing evidence to expand possible protection areas for the goshawk's breeding for the future. The field research identified 10 goshawk's nests, and 23 appearance points confirmed during the 3rd round of environmental research were used for analysis. 4 geomorphic, 3 environmental, 7 distance, and 9 weather factors were used as model variables. The final environmental variables were selected through non-parametric verification between appearance and non-appearance coordinates identified by random sampling. The final predictive model (MaxEnt) was structured using 10 factors related to breeding ground and 7 factors related to appearance area selected by statistics verification. According to the results of the study, the factor that affected breeding point structure model the most was temperature seasonality, followed by distance from mixforest, density-class on the forest map and relief energy. The factor that affected appearance point structure model the most was temperature seasonality, followed by distance from rivers and ponds, distance from agricultural land and gradient. The nature of the goshawk's breeding environment and habit to breed inside forests were reflected in this modeling that targets breeding points. The northern central area which is about $189.5 km^2$(2.55 %) is expected to be suitable breeding ground. Large cities such as Cheongju and Chungju are located in the southern part of Chungcheongbuk-do whereas the northern part of Chungcheongbuk-do has evenly distributed forests and farmlands, which helps goshawks have a scope of influence and food source to breed. Appearance point modeling predicted an area of $3,071 km^2$(41.38 %) showing a wider ranging habitat than that of the breeding point modeling due to some limitations such as limited moving observation and non-consideration of seasonal changes. When targeting the breeding points, a specific predictive area can be deduced but it is difficult to check the points of nests and it is impossible to reflect the goshawk's behavioral area. On the other hand, when targeting appearance points, a wider ranging area can be covered but it is less accurate compared to predictive breeding point since simple movements and constant use status are not reflected. However, with these results, the goshawk's habitat can be predicted with reasonable accuracy. In particular, it is necessary to apply precise predictive breeding area data based on habitat modeling results when enforcing an environmental evaluation or establishing a development plan.

• Journal of Environmental Impact Assessment
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• v.30 no.1
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• pp.13-23
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• 2021

In this study, we performed a Random Walker analysis to predict the Major Movement Paths of otters. The scope of the research was a simulation analysis with a radius of 7.5 km set as the final range centered on the Ansim-wetland in Daegu City, and a field survey was used to verify the model. The number of virtual otters was set to 1,000, the number of moving steps was set to 1,000 steps per grid, and simulations were performed on a total of 841 grids. As a result of the analysis, an average of 147.6 objects arrived at the boundary point under the condition of an interval of 50 m. As a result of the simulation verification, 8 points (13.1%) were found in the area where the movement probability was very high, and 9 points (14.8%) were found in the area where the movement probability was high. On the other hand, in areas with low movement paths probabilities, there were 8 points (13.1%) in low areas and 4 points (6.6%) in very low areas. Simulation verification results In areas with high otter values, the actual otter format probability was particularly high. In addition, as a result of investigating the correlation with the otter appearance point according to the unit area of the evaluation star of the movement probability, it seems that 6.8 traces were found per unit area in the area where the movement probability is the highest. In areas where the probability of movement is low, analysis was performed at 0.1 points. On the side where otters use the major movement paths of the river area, the normal level was exceeded, and as a result, in the area, 23 (63.9%), many form traces were found, along the major movement paths of the simulation. It turned out that the actual otter inhabits. The EN-Simulator analysis can predict how spatial properties affect the likelihood of major movement paths selection, and the analytical values are used to utilize additional habitats within the major movement paths. It is judged that it can be used as basic data such as to grasp the danger area of road kill in advance and prevent it.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.3
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• pp.11-21
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• 2015

Emergency Medical Service(EMS) has become focused due to all kinds of disaster and a great number of casualties. The 119 emergency vehicles' dispatching methods are now being focused, for travel time of ambulances are the critical components in terms of saving human lives. Therefore, this study tried to rearrange 119 EMS regions more efficiently. For this study, Daejeon Metropolitan City's real call cases were analyzed. In order to rearrange the regions, OD Cost Matrix analysis was performed between 800 thousands random points and 26 departments in the Daejoen Metropolitan City. By creating Thiessen Polygon from the random points, a new region was created. As a results, average areas of the regions were reduces from 32 square kilometers to 20 square kilometers, and average time of arrivals are were also improved. Hence, if related organizations plan to rearrange EMS regions, they may utilize this study.

• Journal of Microbiology
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• v.35 no.4
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• pp.347-353
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• 1997

We have characterized a phage library displaying random 22mer peptides which were produced as N-terminal fusions to the pIII coat protein of M13 filamentous phages. Among the sixty phages randomly picked from the library, 25 phages had the 22mer peptide inserts. The DNA sequence analysis of the 25 inserts showed the following results: first, each nucleotide was represented almost equally at each codon position except that there were some biases toward G bases at the first position of the codons. Secondly, the expected 47 sense codons were represented. The deduced amino acid sequences of the 25 inserts were analyzed to examine its diversity. Glycine and glutamate were the two most overrepresented residues above the expected value, whereas cysteine and threonine residues were underrepresented. The range of dicersity in dipeptide sequences showed that the amino acid residues were randomly distributed along the peptide insert. Acidic, basic, polar, and nonpolar amino acid residues were represented to the extent expected at most positions of the peptide inserts. The predicted isoelectric points and hydropathy indices of the 25 peptides showed that a variety of the peptide were represented in the library. These results indicate that this phage display library could be useful in fiuding ligands for a broad spectrum of receptors by affinity screening.

• Korean Journal of Logic
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• v.19 no.3
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• pp.369-400
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• 2016

If we learn that 'Mrs Lee has two children and at least one of them is a daughter', what is our credence that her two children are all girls? Obviously it is 1/3. By assuming some other obvious theses it seem to be argued that our credence is 1/2. Also by just supposing we learn trivial information about the future, it seem to be argued that we must change our credence 1/3 into 1/2. However all of these arguments are fallacious, cannot be sound. When using the conditionalization rule to evaluate conformation of a hypothesis by an evidence, or to estimate credence change by information intake, there are some points to keep in mind. We must examine whether relevant information was given through a random procedure or a biased procedure. If someone with full information releases to us particular partial information, an observation, a testimony, an evidence selected intentionally by him, which means the particular partial information was not given by chance, or was not given accidentally or naturally to us, then the conditionalization rule should be employed very cautiously or restrictedly.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.5 s.96
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• pp.472-481
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• 2005

This paper reports the design of RFID reader antennas working in UHF band. The reader antennas were designed using a Pareto Genetic Algorithm(Pareto GA). Antennas were optimized to have circular polarization(CP) with less than 3 dB axial ratio, impedance matching with less than VSWR=2 within the frequency range of UHF, an adequate readable range, a restricted size(kr<2.22) considering the practical condition. After Pareto GA optimization, we selected and built the most suitable antenna design and compared the measured results to the simulations. Operating principle of the antenna was explained by investigating the amplitude and the phase of the induced current on the antenna body. We also researched the stability of the antenna with respect to the manufacturing error and studied the critical design parameters by applying the random error method on the antenna bent points.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.353-366
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• 2018

This study uses mixed-effects models to predict thigh soft tissue artefact (STA), relative movement of soft tissue such as skin to femur occurring during hip joint motions. The random effects in the model were defined as STA and the fixed effects in the model were considered as skeletal motion. Five male subjects without musculoskeletal disease were selected to perform various hip joint rotational motions. Linear mixed-effects models were applied to markers' position vectors acquired from non-invasive method, photogrammetry. Predicted random effects showed similar patterns of STA among subjects. Large magnitudes of STA appeared on the points near the hip joint regardless of sides; however, small values appeared on the distal anterior.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.539-554
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• 2018

Effective interaction between user and device is considered an important ability of IoT devices. For some applications, it is necessary to recognize human facial expressions in real time and make accurate judgments in order to respond to situations correctly. Therefore, many researches on facial image analysis have been preceded in order to construct a more accurate and faster recognition system. In this study, we constructed an automatic recognition system for facial expressions through two steps - a facial recognition step and a classification step. We compared various models with different sets of data with pixel information, landmark coordinates, Euclidean distances among landmark points, and arctangent angles. We found a fast and efficient prediction model with only 30 principal components of face landmark information. We applied several prediction models, that included linear discriminant analysis (LDA), random forests, support vector machine (SVM), and bagging; consequently, an SVM model gives the best result. The LDA model gives the second best prediction accuracy but it can fit and predict data faster than SVM and other methods. Finally, we compared our method to Microsoft Azure Emotion API and Convolution Neural Network (CNN). Our method gives a very competitive result.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.4
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• pp.569-579
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• 2013

A steel-type breakwater that uses a submerged dual horizontal porous plate was originally proposed by Kweon et al. (2005), and its hydrodynamic characteristics and design methodology were investigated in a series of subsequent researches. In particular, Kweon et al. (2011) proposed a method of estimating the vertical uplift force that acts on the horizontal plate, applicable to the design of the pile uplift drag force. However, the difference between the method proposed by Kweon et al. (2011), and the wave force measured at a different time without a phase difference, have not yet been clearly analyzed. In this study, such difference according to the method of estimating the wave force was analyzed, by measuring the wave pressure acting on a breakwater model. The hydraulic model test was conducted in a two-dimensional wave flume of 60.0 m length, 1.5 m height and 1.0 m width. The steepness range of the selected waves is 0.01~0.03, with regular and random signals. 20 pressure gauges were used for the measurement. The analysis results showed that the wave force estimate in the method of Kweon et al. (2011) was smaller than the wave force calculated from the maximum pressure at individual points, under a random wave action. Meanwhile, the method of Goda (1974) that was applied to the horizontal plate produced a smaller wave force, than the method of Kweon et al. (2011). The method of Kweon (2011) was already verified in the real sea test of Kweon et al. (2012), where the safety factor of the pile uplift force was found to be greater than 2.0. Based on these results, it was concluded that the method of estimating the wave force by Kweon et al. (2011) can be satisfactorily used for estimating the uplift force of a pile.