• Korean Journal of Optics and Photonics
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• v.14 no.6
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• pp.623-629
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• 2003

In this paper, we have proposed a full phase encryption scheme based on phase-encoded XOR operation. The proposed scheme encrypts a gray-level image by slicing an original image and combining with XORed images which resulted from phase-encoded XOR operations between sliced images and phase-encoded binary random images. Then we produce an encrypted image by combining only XORed images and a key image by only phase-encoded binary random images. The encrypted image and key image are converted into encrypted data and key data by a phase-encoding method. The merits are that the proposed encryption scheme can basically fulfill a high-level encryption using a full phase encryption scheme which has nonlinear and invisible characteristics. The scheme also improves security by encrypting the phase information before full phase encryption. The decryption system based on the principle of interference between a reference wave and a direct pixel-to-pixel mapping image of encrypted data with key data can be simply implemented using a phase-visualization system. Simulation results indicate that our proposed encryption scheme is effective and simple for a gray-scale image and optical decryption system.

• Korean Journal of Plant Resources
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• v.11 no.3
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• pp.345-352
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• 1998

A Korean endemic and evergreen small tree ' Dendropanax morbifera $L_{EV}$.(Araliaceae)' is a component of evergreen forest and mainly idstributein sourthern region and islands in Korea. A local population of D. morbifera which is located between evergreen and deciduous forest within 50m x 50m quadrate was investigated to ascertain the change of population structure, emergence and growth dynamics of seedlings and saplings, and pattern of spatial distribution by the temproal and spatial expansion of population . The result of analysis of population structure by Importnace Value(IV), evergreen forest showed a high species diversity of evergreen tree species such as Cinnamomum japonicum, Machilus japonica, Neolitsea serica, Daphniphyllum macropodum, Ligustrum japonicum, and etc, in middle and under story than in upper story where Camelia japonica and Quercus acuta were dominant. And in conterminous deciduous fores, the major component of evergreen forest in this region, Camellia japonica, Quercus acuta, evergreen tree of Lauraceae and etc. were abundant in only under story. IV of D. morbifera differed from among three story. In comparative analysis of emergence and growth dynamics of D. morbifera seedlings and saplings between evergreen and deciduous forest, emergece and density of seedlings were significantly greater in evergreen than in deciduous forest, and growth of height and basal diameter of seedlings and saplings were slightly larger in evergreen than in deciduous forest. The spatial distribution patterns by Moristia's index mapping of indivuduals using a lattice method of XY axis within this population showed that seedlings(age up to 2 years) and saplings (age>2 years and height<1m) both evergreen and deciduous forest were more or less aggregated apart from mature trees, and thougth intermediate trees(height>1m and dbh<10cm) had a aggregated distribution pattern, mature trees(dbh>10cm were uniform. In conclusion , the expansion of D. morbfera population from evergreen to deciduous forest accompanied with a mumber of evergreen woody species, and also, emergence and recruitment, and growth of seedlings were greatly influenced moisture and canopy by around community structure.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1020-1033
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• 2021

Nowadays, online or mobile social network services (SNS) are very popular and widely spread in our society and daily lives to instantly share, disseminate, and search information. In particular, SNS such as YouTube, Flickr, Facebook, and Amazon allow users to upload billions of images or videos and also provide a number of multimedia information to users. Information retrieval in multimedia-rich SNS is very useful but challenging task. Content-based media retrieval (CBMR) is the process of obtaining the relevant image or video objects for a given query from a collection of information sources. However, CBMR suffers from the dimensionality curse due to inherent high dimensionality features of media data. This paper investigates the effectiveness of the kernel trick in CBMR, specifically, the kernel principal component analysis (KPCA) for dimensionality reduction. KPCA is a nonlinear extension of linear principal component analysis (LPCA) to discovering nonlinear embeddings using the kernel trick. The fundamental idea of KPCA is mapping the input data into a highdimensional feature space through a nonlinear kernel function and then computing the principal components on that mapped space. This paper investigates the potential of KPCA in CBMR for feature extraction or dimensionality reduction. Using the Gaussian kernel in our experiments, we compute the principal components of an image dataset in the transformed space and then we use them as new feature dimensions for the image dataset. Moreover, KPCA can be applied to other many domains including CBMR, where LPCA has been used to extract features and where the nonlinear extension would be effective. Our results from extensive experiments demonstrate that the potential of KPCA is very encouraging compared with LPCA in CBMR.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.8-15
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• 2021

This study was conducted with the purpose of exploring the dilemma and improvement strategies for the integrated management of extracurricular education programs at Duksung Women's University. The research method was finally composed of a procedure with a meeting of experts based on the procedure of collecting and analyzing the previous research literature. As for the contents of the study, the dilemma of the integrated management of the extracurricular education program at Duksung Women's University was presented first. Examples of dilemmas include difficulties in organizing and operating programs from the perspective of a roadmap customized for each grade level, difficulties in establishing a foundation for balanced mapping of core competencies and cultivating programs, difficulties in managing the performance of regular program monitoring and feedback improvement, and activating the linkage system between subjects and extracurricular education programs difficulties and difficulties in establishing a support system for the operation of the extracurricular education integrated management system were reflected. In addition, a strategy to complement and improve this dilemma was presented in a linkage. As a result of the study, the integrated management dilemma of Duksung Women's University's extracurricular education programs needs to be resolved in the long term through formal infrastructure such as external expert advice and expert exchange, and the development and use of related manuals should be considered aspects were analyzed. In addition, the content of this study was analyzed not only in the educational case of Duksung Women's University, but also in that it deals with cases that can be usefully referenced in most universities that develop and operate extracurricular education programs. Finally, this study presents an evidence-based practices that can be referenced in promoting the integrated management of extracurricular education programs in university sites, and the position and identity of extracurricular education throughout the university curriculum. It is judged that the significance and expected effect of the study can be obtained in that it provides an opportunity to improve from the management point of view.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1464-1479
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• 2018

In face recognition, sometimes the number of available training samples for single category is insufficient. Therefore, the performances of models trained by convolutional neural network are not ideal. The small sample face recognition algorithm based on novel Siamese network is proposed in this paper, which doesn't need rich samples for training. The algorithm designs and realizes a new Siamese network model, SiameseFacel, which uses pairs of face images as inputs and maps them to target space so that the $L_2$ norm distance in target space can represent the semantic distance in input space. The mapping is represented by the neural network in supervised learning. Moreover, a more lightweight Siamese network model, SiameseFace2, is designed to reduce the network parameters without losing accuracy. We also present a new method to generate training data and expand the number of training samples for single category in AR and labeled faces in the wild (LFW) datasets, which improves the recognition accuracy of the models. Four loss functions are adopted to carry out experiments on AR and LFW datasets. The results show that the contrastive loss function combined with new Siamese network model in this paper can effectively improve the accuracy of face recognition.

• Korean Journal of Heritage: History & Science
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• v.48 no.4
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• pp.44-61
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• 2015

Mural tomb in Goa-ri(Goryeong) built in the 6th Century Gaya period investigated precisely by the scientific method. They were used to optical equipments for investigation and made a damage map according to the damaging types. The mortar layer was mostly exfoliated from the rest of the wall except for the burial chamber ceiling and corridor ceiling. Also painting layers rarely not observed. Most of the paintings were damaged except lotus painting in burial chamber ceiling. Various damage types that exfoliation, earthen dirt, film coating were found in murals. Damage factors of mural were the porous characteristics of mortar layer and the movement of moisture in the murals. They were caused physical damage such as crack, exfoliation. It was getting worse and causing to secondary damage like earthen dirt, film coating.

• Journal of the Korean Geotechnical Society
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• v.35 no.9
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• pp.37-45
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• 2019

Quick identification of the condition of tunnel face and optimized determination of support patterns during tunnel excavation in underground construction projects help engineers prevent tunnel collapse and safely excavate tunnels. This study investigates a CNN technique for quick determination of rock quality classification depending on the condition of tunnel face, and presents the procedure for rock quality classification using a deep learning technique and the improved method for accurate prediction. The VGG16 model developed by tens of thousands prestudied images was used for deep learning, and 1,469 tunnel face images were used to classify the five types of rock quality condition. In this study, the prediction accuracy using this technique was up to 83.9%. It is expected that this technique can be used for an error-minimizing rock quality classification system not depending on experienced professionals in rock quality rating.

• Journal of Korean Academy of Nursing
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• v.49 no.4
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• pp.472-485
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• 2019

Purpose: This study aimed to develop and evaluate the effectiveness of an adapted health literacy self-management intervention for elderly cancer patients undergoing chemotherapy. Methods: The intervention in this study was systematically developed through the six stages of Intervention Mapping Protocol and was based on Fransen et al's causal pathway model. A quasi-experimental trial was conducted on a total of 52 elderly patients (26 in an experimental group and 26 in a control group) undergoing chemotherapy in Korea. The intervention consisted of seven sessions over 5 weeks. The experimental tool for this study was an adapted health literacy self-management intervention, which was designed to promote a reduction in the symptom experience and distress of elderly cancer patients through the promotion of self-management behavior. To develop efficient educational materials, the participants' health literacy was measured. To educate participants, clear communication and the teach-back method were used. In addition, for the improvement of self-efficacy, four sources were utilized. For the promotion of self-management behavior, five self-management skills were strengthened. Data were collected before and after the intervention from June 4 to September 14, 2018. The data were analyzed with SPSS/WIN 21.0. Results: Following the intervention, self-management knowledge and behavior and, self-efficacy significantly improved in experimental group. Symptom experience and distress decreased in the experimental group compared to the control group. Conclusion: The self-management intervention presented in this study was found to be effective in increasing self-management knowledge and behavior and, self-efficacy, and ultimately in reducing symptom experience and distress for elderly patients undergoing chemotherapy.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.32 no.2
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• pp.100-103
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• 2019

The change in vanadium amount according to the growth direction of vanadium-doped semi-insulated (SI) SiC single crystals using high-purity SiC powder was investigated. High-purity SiC powder and a porous graphite (PG) inner crucible were placed on opposite sides of SiC seed crystals. SI SiC crystals were grown on 2 inch 6H-SiC Si-face seeds at a temperature of $2,300^{\circ}C$ and growth pressure of 10~30 mbar of argon atmosphere, using the physical vapor transport (PVT) method. The sliced SiC single crystals were polished using diamond slurry. We analyzed the polytype and quality of the SiC crystals using high-resolution X-ray diffraction (XRD) and Raman spectroscopy. The resistivity of the SI SiC crystals was analyzed using contactless resistivity mapping (COREMA) measurements.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.211-217
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• 2019

In an complicated battlefield environment, information from enemy's camp is an important factor in carrying out military operations. For obtaining this information, the number of UAVs that can be deployed to the mission without our forces' loss and at low cost is increasing. Because the mission environment has anti-aircraft weapons, mission space is needed for UAV to guarantee survivability without being killed. The concept of Configuration Space is used to define the mission space considering with range of weapons and detect range of UAV. UAV must visit whole given area to obtain the information and perform Coverage Path Planning for this. Based on threats to UAV and importance of information that will be obtained, area that UAV should visit first is defined. Grid Map is generated and mapping threat information to each grid for UAV path planning. On this study, coverage conditions and path planning procedures are presented based on the threat information on Grid Map, and mission space is expanded to improve detection efficiency. Finally, simulations are performed, and results are presented using the suggested UAV path planning method in this study.