• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.52-67
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• 2020

Recently, the Arctic has been exposed to snow-covered land due to melting permafrost every year, and the Korea Geographic Information Institute(NGII) provides polar spatial information service by establishing spatial information of the polar region. However, there is a lack of spatial information on vegetation sensitive to climate change. This research used a multi-temporal Sentinel-2 image to perform land cover classification of the Ny-Ålesund in Arctic Svalbard. In the pre-processing step, 10 bands and 6 vegetation spectral index were generated from multi-temporal Sentinel-2 images. In image-classification step is consisted of extracting the vegetation area through 8-class land cover classification and performing the vegetation species classification. The image classification algorithm used Random Forest to evaluate the accuracy and calculate feature importance through Out-Of-Bag(OOB). To identify the advantages of multi- temporary Sentinel-2 for vegetation classification, the overall accuracy was compared according to the number of images stacked and vegetation spectral index. Overall accuracy was 77% when using single-time Sentinel-2 images, but improved to 81% when using multi-time Sentinel-2 images. In addition, the overall accuracy improved to about 83% in learning when the vegetation index was used additionally. The most important spectral variables to distinguish between vegetation classes are located in the Red, Green, and short wave infrared-1(SWIR1). This research can be used as a basic study that optimizes input characteristics in performing the classification of vegetation in the polar regions.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.1-8
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• 2021

In the political field of news articles, there are polarized and biased characteristics such as conservative and liberal, which is called political bias. We constructed keyword-based dataset to classify bias of news articles. Most embedding researches represent a sentence with sequence of morphemes. In our work, we expect that the number of unknown tokens will be reduced if the sentences are constituted by subwords that are segmented by the language model. We propose a document embedding model with subword tokenization and apply this model to SVM and feedforward neural network structure to classify the political bias. As a result of comparing the performance of the document embedding model with morphological analysis, the document embedding model with subwords showed the highest accuracy at 78.22%. It was confirmed that the number of unknown tokens was reduced by subword tokenization. Using the best performance embedding model in our bias classification task, we extract the keywords based on politicians. The bias of keywords was verified by the average similarity with the vector of politicians from each political tendency.

• The Korean Journal of Franchise Management
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• v.12 no.2
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• pp.7-21
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• 2021

Purpose: One of the characteristics of service companies such as foodservice franchise is that it is easy to imitate, so many brands can imitate the menu that is popular with consumers. Therefore, foodservice franchise company should develop a brand that customers can identify from other brands in order differentiate it from its competitors. In order make the foodservice franchise company identifiable from other brands, it is possible through communication with customers. Therefore, this study proposes a new research model to analyze customer loyalty through online advertising and online word of mouth trust and immersion. Online was provided to customers through a mixture of advertisements and word of mouth, but previous studies have only considered online advertisements or online word of mouth. In addition, we want to verify the difference according to gender, which is an important variable in researching the online information processing behavior of customers. Research design, data, and methodology: The questionnaire of this study was surveyed on 20 years of age or older who have visited the restaurant franchise store within the last 3 months among the foodservice franchise companies operating SNS. During the survey period, 400 surveys were surveyed for a total of 20 days from April 1 to April 20, 2020. Result: The research results are as follows. First, in this study, the effect of online advertisement and online word of mouth on trust and immersion was studied. Second, this study verified the social influence theory in online advertising and online word of mouth. Third, the effect of online advertising and online word of mouth on loyalty according to gender was verified. Fourth, compared to existing advertisements, online advertisements are suitable for marketing by foodservice franchise companies because they can interact with consumers, modify advertisements immediately, execute extensive advertisements at low cost, segment the market, and measure advertisement effectiveness. The recent online expansion has been expanded to mobile-based, allowing foodservice franchisees to provide new communication services such as SMS (Short Message Service), multimedia messaging services, and location-based services. Fifth, a foodservice franchise company can increase brand awareness through online marketing or induce the use of offline stores. Sixth, franchisor can grow into a sustainable company only when they use resources efficiently. Conclusions: Trust is important in foodservice franchise information. This trust has a significant impact on customer commitment and loyalty.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.2
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• pp.39-47
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• 2008

Among previous Side Channel Analysis (SCA) methods, Differential Power Analysis (DPA) based on the statistical characteristics of collected signals has been known as an efficient attack for uncovering secret key of cryptosystems. However, the attack performance of this method is affected very much by the temporal misalignment and noise of collected side channel signals. In this paper, we propose a new method to surmount the noise problem in DPA. The performance of the proposed method is then evaluated while analyzing the power consumption signals of Micro-controller chips during a DES operation. Its performance is then compared to that of the original DPA in the time and frequency domains. When we compare the experimental results with respect to the needed number of traces to uncover the secret key, our proposed method shows the performance enhancement 33% in the time domain and 50% in the frequency domain.

• Journal of Wetlands Research
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• v.23 no.2
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• pp.154-162
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• 2021

The naturally opened Han river estuary is a place where the flows of the Han river, Imjin river, Yaesung river meet with West Sea of Korea, so the hydrodynamic mechanism(Impact-Response) structure of Han river estuary is complex. Continuous observation and measurement due to the morphological characteristics at the estuary are required to maintain the estuary environment and river management facilities. However, the Sannam wetland(the study area) is in the military operation area. Therefore, Sannam wetland has the limited access under the control from military office. In 2020, there had a natural disaster due to flooding in August and COVID-19, and it made a survey hard. The noncontact survey technique, the analysis of LANDSAT images at Sannam wetland, was applied to analyze riverbed fluctuation and morphological transformation around Sannam wetland. LANDSAT images obtained from EarthExplorer, USGS and analyzed by QGIS. The analysis was performed based on the area and the distance near Sannam wetland. As a result, an erosion was happened on the downstream of the study area, and the upstream of the study area did not have any serious sediment transport. Considering the resolution of LANDSAT images, this noncontect survey technique is applicable to manage the study area. From the analysis of LANDSAT images, it is assumed that the tidal effect is greater than the inflow from the upstream. The pattern change of tidal response causes the damage of the river facilities near the Hangang river estuary.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.1-6
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• 2021

In the field of speech recognition, as the DNN is applied, the use of speech recognition is increasing, but the amount of calculation for parallel training needs to be larger than that of the conventional GMM, and if the amount of data is small, overfitting occurs. To solve this problem, we propose an efficient method for robust voice feature extraction and voice signal noise removal even when the amount of data is small. Speech feature extraction efficiently extracts speech energy by applying the difference in frame energy for speech and the zero-crossing ratio and level-crossing ratio that are affected by the speech signal. In addition, in order to remove noise, the noise of the speech signal is removed by removing the noise of the speech signal with an average predictive improved LMS filter with little loss of speech information while maintaining the intrinsic characteristics of speech in detection of the speech signal. The improved LMS filter uses a method of processing noise on the input speech signal by adjusting the active parameter threshold for the input signal. As a result of comparing the method proposed in this paper with the conventional frame energy method, it was confirmed that the error rate at the start point of speech is 7% and the error rate at the end point is improved by 11%.

• Geophysics and Geophysical Exploration
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• v.24 no.2
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• pp.53-66
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• 2021

Velocity model building is an essential procedure in seismic data processing. Conventional techniques, such as traveltime tomography or velocity analysis take longer computational time to predict a single velocity model and the quality of the inversion results is highly dependent on human expertise. Full-waveform inversions also depend on an accurate initial model. Recently, deep neural network techniques are gaining widespread acceptance due to an increase in their integration to solving complex and nonlinear problems. This study investigated cases of seismic velocity model building using deep neural network techniques by classifying items according to the neural networks used in each study. We also included cases of generating training synthetic velocity models. Deep neural networks automatically optimize model parameters by training neural networks from large amounts of data. Thus, less human interaction is involved in the quality of the inversion results compared to that of conventional techniques and the computational cost of predicting a single velocity model after training is negligible. Additionally, unlike full-waveform inversions, the initial velocity model is not required. Several studies have demonstrated that deep neural network techniques achieve outstanding performance not only in computational cost but also in inversion results. Based on the research results, we analyzed and discussed the characteristics of deep neural network techniques for building velocity models.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.1
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• pp.171-197
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• 2021

The purpose of this study is to suggest the ways of improving systematic records management based on the results of analyzing the present records management situation of college and department in an university which is operating archives. To achieve the purpose, survey and interview of the persons in charge of producing and managing the administrative documents of college and department were conducted. Furthermore, actual condition investigation of records management of college and department and university archives were analyzed. According to the results of analysis, the following problems were found: 1) lack of sufficient records management by college and department, 2) lack of understanding of tasks by processing staffs, 3) operational problems of university archives. Based on the results, recommendations were made as follows; First, it is necessary to improve an awareness of records management by operating staffs. Second, it is necessary to educate staffs through the development of training programs reflecting the characteristics of the university and set up guidelines for records management by college and department. Third, it is necessary to execute reorganization and supplement the personnel of university archives.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.261-267
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• 2020

The demand for faster, lighter, and thinner portable electronic devices has brought about a change in semiconductor packaging technology. In response, a stacked chip-scale package(SCSP) is used widely in the assembly industry. One of the key materials for SCSP is a die-attach film (DAF). Excellent flowability is needed for DAF for successful die attachment without voids. For DAF with high flowability, two-step curing is often required to reduce a cure crack, but one-step curing is needed to reduce the processing time. In this study, DAF composition was categorized into three groups: cure (epoxy resins), soft (rubbers), hard (phenoxy resin, silica) component. The effect of the composition on a cure crack was examined when one-step curing was applied. The die-attach void and flowability were also assessed. The cure crack decreased as the amount of hard components decreased. Die-attach voids also decreased as the amount of hard components decreased. Moreover, the decrease in cure component became important when the amount of hard component was small. The flowability was evaluated using high-temperature storage modulus and bleed-out. A decrease in the amount of hard components was critical for the low storage modulus at 100℃. An increase in cure component and a decrease in hard component were important for the high bleed-out at 120℃(BL-120).

• Korean Journal of Food Science and Technology
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• v.53 no.1
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• pp.99-103
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• 2021

The purpose of this study was to investigate how microwave drying, a method to minimize the scent and physicochemical changes of the final products, affects the quality characteristics of various herbs according to treatment intensity (pulse and continuous waves) and time. In the current study, different physicochemical qualities, such as weight change, moisture content, water activity, color, and microbial growth, of five different Korean herbs were analyzed after microwave drying. The results clearly showed that the pulse wave method was a more effective approach than the continuous wave method for maintaining the physicochemical properties of herbs. Furthermore, pulse wave drying lead to efficient microbial death in various herbs after a short time. Thus, microwave drying with a pulse wave can be applied to herb processing and packaging technology while minimizing the quality changes of herbs.