• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.183-194
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• 2020

Recently, in Korea, financial institutions such as banks are most severely affected by the universalization of the Internet and smartphones. On the other hand, the use of online systems by financial institutions keeps increasing; the convenience of online services has a significant influence on the attraction and the retention of financial customers; consumer needs are also diversely expressed. This paper deduces from the precedent researches a mechanism that online financial system enhances the trust of customers -the medium of the online system and other customers- and its perceived easiness affects its perceived effectiveness and then all these internal variables induce satisfaction. Plus, this paper aims at verification of the hypothesis in terms of an extended technology acceptance model, based on the hypothesis that word of mouth and repurchase are significantly linked to this mechanism. Through this study, the researchers tried to check how the online service quality and emotional factors of financial institutions affect the users in accordance with the trend of changes in the service usage method of financial institutions, and confirmed that the hypothesis was not rejected.

• Journal of the Earthquake Engineering Society of Korea
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• v.3 no.3
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• pp.63-74
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• 1999

A sliding mode fuzzy control (SMFC) algorithm is presented for vibration of large structures. Rule-base of the fuzzy inference engine is constructed based on the sliding mode control, which is one of the nonlinear control algorithms. Fuzziness of the controller makes the control system robust against the uncertainties in the system parameters and the input excitation. Non-linearity of the control rule makes the controller more effective than linear controllers. Design procedure based on the present fuzzy control is more convenient than those of the conventional algorithms based on complex mathematical analysis, such as linear quadratic regulator and sliding mode control(SMC). Robustness of presented controller is illustrated by examining the loop transfer function. For verification of the present algorithm, a numerical study is carried out on the benchmark problem initiated by the ASCE Committee on Structural Control. To achieve a high level of realism, various aspects are considered such as actuator-structure interaction, modeling error, sensor noise, actuator time delay, precision of the A/D and D/A converters, magnitude of control force, and order of control model. Performance of the SMFC is examined in comparison with those of other control algorithms such as $H_{mixed 2/{\infty}}$ optimal polynomial control, neural networks control, and SMC, which were reported by other researchers. The results indicate that the present SMFC is an efficient and attractive control method, since the vibration responses of the structure can be reduced very effectively and the design procedure is simple and convenient.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.117-126
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• 2018

The threat to information security is growing globally. To this, organizations are increasing the weight of adapting and operating the more specialized information security policy and system. Information security requires participation from the employees who execute the security system and policy, and to increase the level of organization's internal security, requires organization's systematic support to improve employees' information security compliance intention. This research finds the mechanism for improving employee's information security compliance intention by applying justice theory and goal setting theory in information security. We use structural equation modeling to verify the research hypothesis, and conducted a survey on the employees of organization with information security policy. In other words, this research performs verification of the research model based hypothesis which claims that security policy goal setting has positive influence on employee's level of security related justice recognition, and claims that justice has positive influence on compliance intention. The object of study is the employees of the organization that adapts information security policy, and 383 valid samples were collected via survey. Structural equation modeling was performed to verify the research hypothesis. The result shows that security policy goal factor (goal difficulty, goal specificity) improves employee's security related justice recognition, and that security related justice (distribution, process, and information justice) has positive influence on compliance intention. The result suggests the strategic approach directions for improving employees' compliance intention on organization's security policy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.5
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• pp.393-398
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• 2007

According to the Korean datum change to a world geodetic system, the EDM area should be readjusted to provide consistent product over the country. The data set for EDM area is extracted from the previous KTN1987 DB and checked for the moved markers in XY network adjustment which provides quality verification. Then, EDM data set for the seven areas are rebuilt for the adjustment. Since the data is still based on the old datum, the coordinates of the data are transformed by applying the coordinate transformation parameters. Here, the transformation parameters, which were determined for the conversion of 1:50,000 topographic maps by NGII, were used. For each EDM point, the geoidal height from EGM96 model is applied to obtain the ellipsoidal height based on the GRS80. The measured distance projected onto GRS80 is adjusted using BL network adjustment by fixing 2nd order or 3rd order GPS control points. The results from the readjustment show the minimum standard error of 1.37" and the maximum standard error of 2.13". Considering the measurement accuracy of EDM (1.6" corresponding to about 2cm) and GPS position for fixed points (2cm), this result is considered to be reasonable and it is good for the practical use.

• Economic and Environmental Geology
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• v.37 no.2
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• pp.207-223
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• 2004

The purpose of this study is to reveal spatial relationships between landslide and geospatial data set, to map the landslide susceptibility using the relationship and to verify the landslide susceptibility using the landslide occurrence data in Boun area in 1998. Landslide locations were detected from aerial photography and field survey, and then topography, soil, forest, and land cover data set were constructed as a spatial database using GIS. Various spatial parameters were used as the landslide occurrence factors. They are slope, aspect, curvature and type of topography, texture, material, drainage and effective thickness of soil. type, age, diameter and density of wood, lithology, distance from lineament and land cover. To calculate the relationship between landslides and geospatial database, Bayesian probability methods, weight of evidence. were applied and the contrast value that is >$W^{+}$->$W^{-}$ were calculated. The landslide susceptibility index was calculated by summation of the contrast value and the landslide susceptibility maps were generated using the index. The landslide susceptibility map can be used to reduce associated hazards, and to plan land cover and construction.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.161-168
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• 2007

Web attack uses structural, logical and coding error or web application rather than vulnerability to Web server itself. According to the Open Web Application Security Project (OWASP) published about ten types of the web application vulnerability to show the causes of hacking, the risk of hacking and the severity of damage are well known. The detection ability and response is important to deal with web hacking. Filtering methods like pattern matching and code modification are used for defense but these methods can not detect new types of attacks. Also though the security unit product like IDS or web application firewall can be used, these require a lot of money and efforts to operate and maintain, and security unit product is likely to generate false positive detection. In this research profiling method that attracts the structure of web application and the attributes of input parameters such as types and length is used, and by installing structural database of web application in advance it is possible that the lack of the validation of user input value check and the verification and attack detection is solved through using profiling identifier of database against illegal request. Integral security management system has been used in most institutes. Therefore even if additional unit security product is not applied, attacks against the web application will be able to be detected by showing the model, which the security monitoring log gathering agent of the integral security management system and the function of the detection of web application attack are combined.

• Journal of Aerospace System Engineering
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• v.13 no.3
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• pp.23-31
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• 2019

The design requirements of modern satellites vary depending on the purpose of operation. Like conventional medium and large-scale satellites, small satellites which operate on low orbit may also serve military purposes. As a result, there is increased demand for high-resolution photos and videos and multi-target observation becomes important. The most important design parameter for multi-target observation is the satellites' maneuverability. For increased maneuverability, the miniaturization is required to increase the stiffness of the satellite as this decreases the mass moment of inertia of the satellite. In the case of a solar panel having relatively low stiffness compared to the satellites' body, vibrations are generated when the attitude maneuver is performed, which greatly influences the image acquisition. For verification of such vibrational characteristics, the satellites is modeled as a reduced model, and experimental zig for simulating attitude maneuver is introduced. A rigidity simulator for simulating the stiffness of the satellite is also proposed. Additionally, the objective of the experimental method is to simulate the maneuvering angle of the satellite based on the winding length of the wire using a step motor, and to experimentally verify the vibration characteristics of the satellite body and the solar panel generated during the maneuvering test.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.85-91
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• 2021

The DAPA (Defense Acquisition Program Administration) has been operating the DQ mark certification since 2012 to certify the superior technology and quality of munitions. On the other hand, the current DQ mark certification can not directly provide DQ mark certification to software because it is impossible to verify the quality of software alone. Therefore, this study analyzed domestic/overseas software quality evaluation/certification standards to find a way to verify the quality of software in the DQ mark certification. Among them, the method of applying the GS certification according to the international standard ISO/IEC 25000 series to the DQ mark certification was suggested as an improvement plan, and DQ mark certification verified the quality of software and provided certification. An attempt was made to expand the certification scope of DQ mark certification. This paper proposes that the DQ mark can be given to the system software by introducing GS certification to the DQ mark certification. To this end, an improved procedure for omitting the factory audit and verification by submitting a GS certificate for product evaluation is proposed. This is expected to increase defense exports using the granted DQ mark and improve the quality of defense software products through GS certification.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.139-156
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• 2021

The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.221-241
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• 2018

As we enter the knowledge society, the importance of information as a new form of capital is being emphasized. The importance of information classification is also increasing for efficient management of digital information produced exponentially. In this study, we tried to automatically classify and provide tailored information that can help companies decide to make technology commercialization. Therefore, we propose a method to classify information based on Korea Standard Industry Classification (KSIC), which indicates the business characteristics of enterprises. The classification of information or documents has been largely based on machine learning, but there is not enough training data categorized on the basis of KSIC. Therefore, this study applied the method of calculating similarity between documents. Specifically, a method and a model for presenting the most appropriate KSIC code are proposed by collecting explanatory texts of each code of KSIC and calculating the similarity with the classification object document using the vector space model. The IPC data were collected and classified by KSIC. And then verified the methodology by comparing it with the KSIC-IPC concordance table provided by the Korean Intellectual Property Office. As a result of the verification, the highest agreement was obtained when the LT method, which is a kind of TF-IDF calculation formula, was applied. At this time, the degree of match of the first rank matching KSIC was 53% and the cumulative match of the fifth ranking was 76%. Through this, it can be confirmed that KSIC classification of technology, industry, and market information that SMEs need more quantitatively and objectively is possible. In addition, it is considered that the methods and results provided in this study can be used as a basic data to help the qualitative judgment of experts in creating a linkage table between heterogeneous classification systems.