• Journal of Haehwa Medicine
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• v.8 no.1
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• pp.115-129
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• 1999

To evaluate radioprotective effects of Kamisagoonjatang(KST), Kamijihwangtang (KJT) and Kamigoonjajihwangtang(KKJT), studies were done experimentally. The results were obtained as follows: 1. By FACS analysis after exposure to radiation by Liniac, T cell and T-helper cell were significantly increased in KST treated group and also B cell and macrophage in KJT treated group while splenocytes were significantly decreased in control group. 2. WBC, PLT were significantly increased in KKJT treated group as compared with control group after exposure to radiation by Liniac. 3. In histological changes of jejunum of $BALB{\backslash}C$ mice after after exposure to radiation by Liniac, exclusion and fusion of villi were decreased in all groups as compared with control group. 4. In the observation of morphological changes by SEM and TEM after radiation by Liniac, KKJT, KJT and KST inhibited demage of internal structures such as mitochondria, ESR and golgi of jejunum cells in order as compared with control group. From above results it was concluded that KJT, KST and KKJT could be usefully applied for protection from damage by radiotherapy to cancer.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.255-261
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• 2003

Recently, the enormous increase in the volume of remotely sensed data is being acquired by an ever-growing number of earth observation satellites. The combining of diversely sourced imagery together is an important requirement in many applications such as data fusion, city modeling and object recognition. Aerial triangulation is a procedure to reconstruct object space from imagery. However, since the different kinds of imagery have their own sensor model, characteristics, and resolution, the previous approach in aerial triangulation (or georeferencing) is purformed on a sensor model separately. This study evaluated the advantages of aerial triangulation of large number of images from multi-sensors simultaneously. The incorporated multi-sensors are frame, push broom, and whisky broom cameras. The limits and problems of push-broom or whisky broom sensor models can be compensated by combined triangulation with other sensors The reconstructed object space from multi-sensor triangulation is more accurate than that from a single model. Experiments conducted in this study show the more accurately reconstructed object space from multi-sensor triangulation.

• Journal of Powder Materials
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• v.29 no.1
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• pp.8-13
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• 2022

In this study, we have prepared a Ti-6Al-4V/V/17-4 PH composite structure via a direct energy deposition process, and analyzed the interfaces using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The joint interfaces comprise two zones, one being a mixed zone in which V and 17-4PH are partially mixed and another being a fusion zone in the 17-4PH region which consists of Fe+FeV. It is observed that the power of the laser used in the deposition process affects the thickness of the mixed zone. When a 210 W laser is used, the thickness of the mixed zone is wider than that obtained using a 150 W laser, and the interface resembles a serrated shape. Moreover, irrespective of the laser power used, the expected σ phase is found to be absent in the V/17-4 PH stainless steel joint; however, many VN precipitates are observed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1200-1215
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• 2023

With the development of IoT and artificial intelligence, location-based services are getting more and more attention. For solving the current problem that indoor positioning error is large and generalization is poor, this paper proposes a Model Stacking Algorithm for Indoor Positioning System using WiFi fingerprinting. Firstly, we adopt a model stacking method based on Bayesian optimization to predict the location of indoor targets to improve indoor localization accuracy and model generalization. Secondly, Taking the predicted position based on model stacking as the observation value of particle filter, collaborative particle filter localization based on model stacking algorithm is realized. The experimental results show that the algorithm can control the position error within 2m, which is superior to KNN, GBDT, Xgboost, LightGBM, RF. The location accuracy of the fusion particle filter algorithm is improved by 31%, and the predicted trajectory is close to the real trajectory. The algorithm can also adapt to the application scenarios with fewer wireless access points.

• Current Optics and Photonics
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• v.7 no.5
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• pp.545-556
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• 2023

This paper introduces volume-sharing multi-aperture imaging (VMAI), a potential approach proposed for volume reduction in space-borne imagers, with the aim of achieving high-resolution ground spatial imagery using deep learning methods, with reduced volume compared to conventional approaches. As an intermediate step in the VMAI payload development, we present a phase-1 design targeting a 1-meter ground sampling distance (GSD) at 500 km altitude. Although its optical imaging capability does not surpass conventional approaches, it remains attractive for specific applications on small satellite platforms, particularly surveillance missions. The design integrates one wide-field and three narrow-field cameras with volume sharing and no optical interference. Capturing independent images from the four cameras, the payload emulates a large circular aperture to address diffraction and synthesizes high-resolution images using deep learning. Computational simulations validated the VMAI approach, while addressing challenges like lower signal-to-noise (SNR) values resulting from aperture segmentation. Future work will focus on further reducing the volume and refining SNR management.

• Anatomy and Cell Biology
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• v.55 no.2
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• pp.155-160
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• 2022

The mandibular second molars show various morphological features in the roots and root canal, and a gutter-shaped root (GSR) caused by fusion of the mesial and distal roots is frequently encountered. In this study the number of the roots associated with mandibular second molars were observed using dental cone-beam computed tomography (CBCT). For those with a GSR, determination of root morphology and root canal classification were performed. CBCT image data from 173 Japanese mandibular second molars were obtained. Using sliced images, the number of the roots and root morphology were determined. In cases with a GSR, the ratio for the fused roots was determined and root canal morphology features were classified. A GSR was found in 61 (35.3%), with greater prevalence in females. In addition, the overall ratio of the fused part to root thickness in those with a GSR was 48.7%, with no significant difference related to sex. Furthermore, a C-shaped root canal morphology was commonly observed in both males and females with a GSR. In the present cohort examined in Japanese, most of the mandibular second molar were found to have two roots, with a GSR noted in 35.5%. While a GSR was more often observed in females, a C-shaped root canal was the most common root canal morphology in both sexs. It is considered that assessment using CBCT findings is helpful for precise determination of root canal morphology and presence of a GSR in mandibular second molars.

• Convergence Security Journal
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• v.17 no.5
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• pp.41-47
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• 2017

The Marine Environment Observation Information System supplies oceanographic information elements such as water temperature, chlorophyll, float, etc. based on satellite images to consumers. The data produced by the Korean marine environmental observatories are located in the coastal areas of Korea. But if the range is too far from a particular area of interest, due to distance or spatial constraints, the accuracy and up-to-dateness of the data can not be relied upon. Therefore, it is necessary to perform fusion and complex operation to solve the difference between the field observation and the marine satellite image. In this study, we develop a system that can process marine environmental information in the user's area of interest in the form of layered character (numeric) information considering the readability and light weight rather than the satellite image. In order to intuitively understand satellite image information, we characterize (quantify) the marine environmental information of the area of interest and we process the satellite image band values into layered characters to minimize the absolute amount of transmitted / received data. Also we study modular location-based interest information service method to be able to flexibly extend and connect interested items that diversify various observation fields as well as application technology to serve this.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.234-243
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• 2022

In Korea, hail damage occurs every year, and in the case of agriculture, it causes severe field crop and cultivation facility losses. Therefore, it is necessary to develop a hail information service system customized for Korea's primary production and crop-growing areas to minimize hail damage. However, the observation of hail is relatively more difficult than that of other meteorological variables, and the available data are also spatially and temporally variable. A hail information service system was developed to understand the temporal and spatial distribution of hail occurrence. As part of this, a hail observation database was established that integrated the observation data from Korea Meteorological Administration with the information from newspaper reports. Furthermore, a hail risk map was produced based on this database. The risk map presented the nationwide distribution and characteristics of hail showers from 1970 to 2018, and the northeastern region of South Korea was found to be relatively dangerous. Overall, hail occurred nationwide, especially in the northeast and some inland areas (Gangwon, Gyeongbuk, and Chungbuk province) and in winter, mainly on the north coast and some inland areas as graupel (small and soft hail). Analyzing the time of day, frequency, and hailstone size of hail shower occurrences by region revealed that the incidence of large hail stones (e.g., 10 cm at Damyang-gun) has increased in recent years and that showers occurred mainly in the afternoon when the updraft was well formed. By integrating multidisciplinary data, the temporal and spatial gap in hail data could be supplemented. The hail risk map produced in this study will be helpful for the selection of suitable crops and growth management strategies under the changing climate conditions.

• Cartoon and Animation Studies
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• s.36
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• pp.237-257
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• 2014

This study is the process of performing the interdisciplinary fusion study between multiple fields by identifying the status on the previous artistic education considering the brain scientific mechanism of image creativity and brain-based learning principles. In recent years, producing the educational methods of each field as the fusion study activities are emerging as the trend and thanks to such, the results of brain-based educational fusion studies are being presented for each field. It includes artistic fields such as music, art and dance. In other words, the perspective is that by understanding the operating principles of the brain while creativity and learning is taking place, when applying various principles that can develop the corresponding functions as a teaching method, it can effectively increase the artistic performance ability and creativity. Since the animation drawing should be able to intuitively recognize the elements of movement and produce the communication with the target beyond the delineative perspective of simply drawing the objects to look the same, it requires the development of systematic educational method including the methods of communication, elements of higher cognitive senses as well as the cognitive perspective of form implementation. Therefore, this study proposes a literature study results on the artistic education applied with brain-based principles in order to design the educational model considering the professional characteristics of animation drawing. Therefore, the overseas and domestic trends of the cases of brain-based artistic education were extracted and analyzed. In addition, the cases of artistic education studies applied with brain-based principles and study results from cases of drawing related education were analyzed. According to the analyzed results, the brain-based learning related to the drawing has shown a common effect of promoting the creativity and changes of positive emotion related to the observation, concentration and image expression through the training of the right brain. In addition, there was a case of overseas educational application through the brain wave training where the timing ability and artistic expression have shown an enhancement effect through the HRV training, SMR, Beta 1 and neuro feedback training that strengthens the alpha/seta wave and it was proposing that slow brain wave neuro feedback training contributes significantly in overcoming the stress and enhancing the creative artistic performance ability. The meaning of this study result is significant in the fact that it was the case that have shown the successful application of neuro feedback training in the environment of artistic live education beyond the range of laboratory but the use of the machine was shown to have limitations for being applied to the teaching methods so its significance can be found in providing the analytical foundation for applying and designing the brain-based learning principles for future animation drawing teaching methods.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.351-360
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• 2018

Human emotion recognition is a research topic that is receiving continuous attention in computer vision and artificial intelligence domains. This paper proposes a method for classifying human emotions through multiple neural networks based on multi-modal signals which consist of image, landmark, and audio in a wild environment. The proposed method has the following features. First, the learning performance of the image-based network is greatly improved by employing both multi-task learning and semi-supervised learning using the spatio-temporal characteristic of videos. Second, a model for converting 1-dimensional (1D) landmark information of face into two-dimensional (2D) images, is newly proposed, and a CNN-LSTM network based on the model is proposed for better emotion recognition. Third, based on an observation that audio signals are often very effective for specific emotions, we propose an audio deep learning mechanism robust to the specific emotions. Finally, so-called emotion adaptive fusion is applied to enable synergy of multiple networks. The proposed network improves emotion classification performance by appropriately integrating existing supervised learning and semi-supervised learning networks. In the fifth attempt on the given test set in the EmotiW2017 challenge, the proposed method achieved a classification accuracy of 57.12%.