• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.1
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• pp.29-38
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• 2012

Due to the rapid development of network environment and wireless communication technology, the distribution of digital video has made easily and the importance of the protection for digital video has been increased. This paper proposes the digital video encryption system based on multiple chaos maps for MPEG-2 video encoding process. The proposed method generates secret hash key of having 128-bit characteristics from hash chain using Tent map as a basic block and generates $8{\times}8$ lattice cipher by applying this hash key to Logistic map and Henon map. The method can reduce the encryption overhead by doing selective XOR operations between $8{\times}8$ lattice cipher and some coefficient of low frequency in DCT block and it provides simple and randomness characteristic because it uses the architecture of combining chaos maps. Experimental results show that PSNR of the proposed method is less than or equal to 12 dB with respect to encrypted video, the time change ratio, compression ratio of the proposed method are 2%, 0.4%, respectively so that it provides good performance in visual security and can be applied in real time.

• The Journal of Korean Academy of Prosthodontics
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• v.53 no.3
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• pp.234-243
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• 2015

Developing of digital technique, it is possible to fabricate implant prostheses for edentulous area using intraoral 3-dimentional information throughout implant diagnosis and treatment process. It is being changed that from the method using CAD/CAM, producing prostheses by model scanning after conventional impression and model processing, to the method of fabricating implant provisional restorations and customized abutments by digital impression after connecting digital impression copings (scanbody) and implant fixtures without models. But, this digital method has not been actively used for implant prostheses not yet. Specially, it is short of intraoral digital impression cases for immediate provisional restorations of the maxillary anterior implants. The gingival contour impression of maxillary anterior area is very important for esthetic restorations. Accordingly, in this case report, the using a digital impression coping (scanbody) and digital impression by CEREC Omnicam (Sirona, Bensheim, Germany) or Trios (3shape, Copenhagen, Denmark) were introduced for immediate provisional restorations in 3 cases needed a single implant restoration in maxillary anterior area. The clinical results were satisfactory on the convenience and accuracy of digital impression technique and the good esthetics of final restorations.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.33-40
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• 2021

Currently, the shipping and port industries are implementing strategies to improve port processing capabilities through the expansion and efficient operation of port logistics resources to survive fierce competition with rapidly changing trends. The calculation of the port's processing capacity is determined by the loading and unloading equipment installed at the dock, and the port's processing capacity can be improved through various methods, such as additional deployment of logistics resources or efficient operation of resources in use. However, it is difficult to expect an improvement effect in a short period of time because the additional deployment of logistics resources is clearly limited in time is clear. Therefore, it is a feasible way to find an efficient operation method for resources being used to improve processing capacity. Domestic ports are also actively promoting informatization and digitalization with the development of the 4th industrial revolution technology. However, the calculation of the number of Y/T (Yard Tractor) assignments in the current unloading process depends on expert experience, and related previous studies also focus on the allocations of Y/T or Calculation of the total number of Y/T required. Therefore, this study analyzed the factors affecting the number of Y/T allocations using the loading and unloading information of incoming ships, and based on this, cluster analysis, regression analysis, and deep neural network(DNN) model were used.

• Journal of Dental Rehabilitation and Applied Science
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• v.38 no.4
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• pp.242-248
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• 2022

Recently, through the development of CAD/CAM technology, it is also being used for fabricating dentures. Compared to conventional methods, when digital dentures are fabricated, the fabrication process is facilitated, and the number of visits to hospitals is reduced and errors are reduced. In this case, the vertical dimension was increased using a CAD program in a patient who needed vertical dimension recovery due to the use of old dentures, and the final denture was fabricated using a monolithic disc through the milling method. The centric relation was recorded using existing dentures, and using the information from the intraoral scan and the existing denture model scan, a trial denture was fabricated and delivered to the patient to evaluate the midline and occlusion. Based on the evaluation of the trial denture, the final denture was fabricated using a milling method and a monolithic disc, and the final denture showed satisfactory results functionally and aesthetically.

• Korean Journal of Environment and Ecology
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• v.32 no.6
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• pp.686-697
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• 2018

Due to the advance in remote sensing technology, it has become easier to more frequently obtain high resolution imagery to detect delicate changes in an extensive area, particularly including forest which is not readily sub-classified. Time-series analysis on high resolution images requires to collect extensive amount of ground truth data. In this study, the potential of land coverage mapas ground truth data was tested in classifying high-resolution imagery. The study site was Wonju-si at Gangwon-do, South Korea, having a mix of urban and natural areas. KOMPSAT-3A imagery taken on March 2015 and land coverage map published in 2017 were used as source data. Two pixel-based classification algorithms, Support Vector Machine (SVM) and Random Forest (RF), were selected for the analysis. Forest only classification was compared with that of the whole study area except wetland. Confusion matrixes from the classification presented that overall accuracies for both the targets were higher in RF algorithm than in SVM. While the overall accuracy in the forest only analysis by RF algorithm was higher by 18.3% than SVM, in the case of the whole region analysis, the difference was relatively smaller by 5.5%. For the SVM algorithm, adding the Majority analysis process indicated a marginal improvement of about 1% than the normal SVM analysis. It was found that the RF algorithm was more effective to identify the broad-leaved forest within the forest, but for the other classes the SVM algorithm was more effective. As the two pixel-based classification algorithms were tested here, it is expected that future classification will improve the overall accuracy and the reliability by introducing a time-series analysis and an object-based algorithm. It is considered that this approach will contribute to improving a large-scale land planning by providing an effective land classification method on higher spatial and temporal scales.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.6
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• pp.64-79
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• 2021

In Korea, mountains constitute 60 percent of the total land area. For a long time, mountains have been deeply involved in people's daily lives, acting as a significant layer of culture. For those reasons, it would be meaningful to shed light on the values of the mountain culture of Korea and seek various ways to utilize them. Therefore, this study aims to explore Korea's mountain enjoyment culture, considering the mountain leisure in the Joseon Dynasty period, when the heritage of mountain enjoying culture was prevalent, and that of the present era. For the analysis, hiking records of the Joseon Dynasty and present-day hiking blog posts related to three famous mountains in Korea were examined. Findings show that people stayed in the mountains for a long time in the Joseon Dynasty, concentrating on the landscape deeply, and various academic and artistic cultures flourished there. In contrast, contemporary people regard the mountain merely as a space to access the peak and climb down quickly within a day. Therefore, the landscape of the mountain cannot be used as a cultural asset beyond natural scenery. However, there are several positive aspects to today's climbing culture. For example, it is easy to obtain information on climbing and feasible ways to conduct various sizes and concepts of hiking due to the development of technology and transportation. In order to develop Korea's unique mountain enjoyment culture in the future, we should propose a 'leisurely hike' that allows people to enjoy the mountain scenery fully and sublimating it into culture, rather than being hiking that is limited to climbing. In addition, it is essential to create suitable spaces, arranging them appropriately to utilize the history and humanities context of the mountain, and connect local facilities and the workforce, thereby causing the development of various mountain enjoyment cultures.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.119-138
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• 2017

Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.344-351
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• 2019

The purpose of this study was to obtain the basic data for developing more advanced courses on character education by surveying and analyzing the perception and demands of character education of university students and further, to provide useful information for creating institutional protocol on character education. The study was conducted from April 2018 to May 2018 on students attending the departments of non-health science and health science university students. A total of 206 students participated in this study, and all the students in the non-health science and health science departments were found to be highly aware of the need for character education, its importance and the possibility of personality development through learning. Students from all the departments showed high levels on average in terms of self-understanding according to their personality abilities, and especially their high levels of 'consideration' and 'responsibility'. For the differences in perception of self-efficacy, the lowest level of recognition was for 'will' and the average values were not high. In their response to personality level, all students answered that their personality was 'high' (42.1%), and that the personality education courses at the schools they are currently attending were 'not satisfied' with both the non-health science and health science students. As a result, there were higher results overall for the health science students than that for the non-health science students, but there were not many significant differences. To this end, education institutes will have to prepare conditions for university students to cultivate their expertise in character, while at the same time helping them grow into human beings with the qualities demanded by society. In addition, the government should establish curriculums and content by accurately identifying the needs of character education and devising concrete measures for their implementation, and by more faithfully considering quantitative and qualitative context types for the content base of character education.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.18-23
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• 2010

Purpose: PET/CT combines functional and morphologic data and increases diagnostic accuracy in a variety of malignancies. Especially reconstructed Fusion PET/CT images or MIP (Maximum Intensity Projection) images from a 2-dimensional image to a 3-dimensional one are useful in visualization of the lesion. But in Fusion & MIP 3D reconstruction image, due to hot uptake by urine or urostomy bag, lesion is overlapped so it is difficult that we can distinguish the lesion with the naked eye. This research tries to improve a distinction by removing parts of hot uptake. Materials and Methods: This research has been conducted the object of patients who have went to our hospital from September 2008 to March 2009 and have a lot of urine of remaining volume as disease of uterus, bladder, rectum in the result of PET/CT examination. We used GE Company's Advantage Workstation AW4.3 05 Version Volume Viewer program. As an analysis method, set up ROI in region of removal in axial volume image, select Cut Outside and apply same method in coronal volume image. Next, adjust minimum value in Threshold of 3D Tools, select subtraction in Advanced Processing. It makes Fusion & MIP images and compares them with the image no using Region Cut Definition. Results: In Fusion & MIP 3D reconstruction image, it makes Fusion & MIP images and compares them by using Advantage Workstation AW4.3 05's Region Cut Subtraction, parts of hot uptake according to patient's urine can be removed. Distinction of lesion was clearly reconstructed in image using Region Cut Definition. Conclusion: After examining the patients showing hot uptake on account of volume of urine intake in bladder, in process of reconstruction image, if parts of hot uptake would be removed, it could contribute to offering much better diagnostic information than image subtraction of conventional method. Especially in case of disease of uterus, bladder and rectum, it will be helpful for qualitative improvement of image.