• Geophysics and Geophysical Exploration
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• v.5 no.4
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• pp.223-235
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• 2002

Since weak Bones or geological lineaments are likely to be eroded, there may develop weak Bones beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. DC resistivity method, however, has seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of a case history, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing them at the water bottom, because the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the DC resistivity method can provide fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio (S/N ratio) data as well as the high resolving power. Some of the modified electrode arrays can provide the data having reasonably high S/N ratio and need not to install remote electrode(s), and thus, they may be suitable to the resistivity survey at the water-covered area.

• Journal of Radiation Industry
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• v.7 no.1
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• pp.69-74
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• 2013

This study examined radiation detection characteristics of spices (cumin, caper and turmeric), other small fruits (hut-gae berry and boxthorn), and pollen extract product. Each samples were irradiated at dose of 1, 5, and 10 kGy and analyzed by the thermoluminescence (TL) and electron spin resonance (ESR) methods. To compare between non-irradiated and irradiated food, all samples were irradiated with $^{60}Co$ gamma-ray source. In TL analysis, most of samples could be applied to detect irradiated foods because of showing TL ratio above 0.1. The glow curves examined by TL method were estimated in the range of $150{\sim}250^{\circ}C$ in irradiated samples. In ESR measurements, the intensity of ESR signal (single-line) increased as the increase of irradiation dose. In particular, the specific ESR signals of irradiation-induced radical were detected in hut-gae berry and pollen extract product. As a results, it is considered that TL and ESR methods can be used to detect both hut-gae berry and pollen extract product. But cumin, caper, turmeric and boxthorn irradiated with gamma ray could be detected only by TL method. It is concluded that TL and ESR methods are suitable for detection of irradiated samples and a combined method is recommendable for enhancing the reliability of detection results.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.781-788
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• 2021

Due to the high sensitivity to radiation, excessive exposure needs to be prevented by accurately measuring the dose irradiated to the skin during radiation therapy. Although clinical trials use dosimeters such as film, OSLD, TLD, glass dosimeter, etc. to measure skin dose, these dosimeters have difficulty in accurate dosimetry on skin curves. In this study, to solve these problems, we developed a skin dosimeter that can be attached according to human flexion and evaluated its response characteristics. For the manufacture of the dosimeter, lead oxide (PbO) with high atomic number (Z_Pb: 82, Z_O: 8) and density (9.53 g/cm³) and silicon binders that can bend according to human flexion were used. In the case of a dosimeter made of PbO material, the performance degradation has been prevented by using parylene and others due to the presence of degradation due to oxidation, but the previously used parylene is affected by bending, so a new form of passive layer was produced and applied to the skin dosimeter. The characteristic evaluation of the skin dosimeter was evaluated by analyzing SEM, reproducibility, and linearity. Through SEM analysis, bending was evaluated, reproducibility and linearity at 6 MeV energy were evaluated, and applicability was assessed with a skin dosimeter. As a result of observing the dosimeter surface through SEM analysis, the parylene passive layer PbO dosimeter with the positive layer raised to the parylene produced cracks on the surface when bent. On the other hand, no crack was observed in the silicon passive layer PbO dosimeter, which was raised to silicon passive layer. In the reproducibility measurement results, the RSD of the silicon passive layer PbO dosimeter was 1.47% which satisfied the evaluation criteria RSD 1.5% and the linearity evaluation results showed the R² value of 0.9990, which satisfied the evaluation criteria R² 9990. The silicon passive layer PbO dosimeter was evaluated to be applicable to skin dosimeters by demonstrating high signal stability, precision, and accuracy in reproducibility and linearity, without cracking due to bending.

• Journal of Life Science
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• v.31 no.2
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• pp.199-208
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• 2021

Euonymus porphyreus, a species of plant in the Celastraceae family, is widely distributed in East Asia, especially in Southern China. The botanical characteristics of E. porphyreus have been reported, but its antioxidative and anticancer activities remain unclear. In this study, we evaluated the antioxidative and anticancer effects of ethanol extracts of E. porphyreus (EEEP) and the molecular mechanism of its anticancer activity in human lung adenocarcinoma A549 cells. The total polyphenol and flavonoid compound contents from EEEP were 115.42 mg/g and 23.07 mg/g, respectively. EEEP showed significant antioxidative effects with a concentration at 50% of the inhibition (IC50) value of 11.09 ㎍/ml, as measured by 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay. EEEP showed cytotoxic activity by increasing the SubG1 cell population of A549 cells in a dose-dependent manner. Apoptosis in A549 cells treated with EEEP was evident due to increased apoptotic cells and apoptotic bodies, as detected by Annexin V and 4,6-diamidino-2-phenylindole (DAPI) staining, respectively. EEEP-induced apoptosis resulted in increased expression of the First apoptosis signal (Fas), p53, and Bax, with decreased expression of Bcl-2 and subsequent activation of caspase-8, -9, and caspase-3, leading to cleavage of poly (ADP-ribose) polymerase (PARP). Collectively, these results suggest that EEEP may exert an anticancer effect by inducing apoptosis in A549 cells through both intrinsic and extrinsic pathways.

• Journal of Apiculture
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• v.34 no.3
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• pp.245-254
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• 2019

We investigated the anti-tumor effects and molecular mechanism of Brazil, China and Korean regional propolis on HeLa ovarian cancer cell line. Each propolis extracts was prepared by ethanol extraction method. Cytotoxicity of propolis extracts was determinated by EZ-cytox cell viability assay. To necessity of anti-tumor effect and molecular mechanism of propolis, we must be adjusting propolis concentration. Due to 100 ㎍/mL of propolis extract were reduced cell viability to less than 50%, we adjusted all of propolis concentration to 100 ㎍/mL. By Western blotting analysis, we confirmed that anti-tumor mechanism of Brazil, China and Korea regional propolis has significantly difference. All of propolis was activated apoptosis related molecules such as PARP, caspase-3. However, cell proliferation signaling molecules including Akt1, ERK and Bcl-2 were reduced the protein expression level. Especially, the expression of tumor suppressor protein p53 was significantly increased in propolis-treated group such as Gyeonggi, Chungbuk, Chungnam, Jeonbuk, Gyeongnam and China. The phosphorylation of Bax which as apoptosis indicator was appeared in propolis-treated group such as Gyeonggi, Gangwon, Chungnam, Gyeongbuk, China. In this results showed that the regional propolis has completely different mechanism in anti-tumor. Thus, propolis extracts may be useful source of functional materials on anti-cancer and it will be able to choose the suitable propolis for cancer therapy by analyzing individual characteristics.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.17-32
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• 2021

Speaker recognition is generally divided into speaker identification and speaker verification. Speaker recognition plays an important function in the automatic voice system, and the importance of speaker recognition technology is becoming more prominent as the recent development of portable devices, voice technology, and audio content fields continue to expand. Previous speaker recognition studies have been conducted with the goal of automatically determining who the speaker is based on voice files and improving accuracy. Speech is an important sociolinguistic subject, and it contains very useful information that reveals the speaker's attitude, conversation intention, and personality, and this can be an important clue to speaker recognition. The final ending used in the speaker's speech determines the type of sentence or has functions and information such as the speaker's intention, psychological attitude, or relationship to the listener. The use of the terminating ending has various probabilities depending on the characteristics of the speaker, so the type and distribution of the terminating ending of a specific unidentified speaker will be helpful in recognizing the speaker. However, there have been few studies that considered speech in the existing text-based speaker recognition, and if speech information is added to the speech signal-based speaker recognition technique, the accuracy of speaker recognition can be further improved. Hence, the purpose of this paper is to propose a novel method using speech style expressed as a sentence-final ending to improve the accuracy of Korean speaker recognition. To this end, a method called sentence sequencing that generates vector values by using the type and frequency of the sentence-final ending appearing in the utterance of a specific person is proposed. To evaluate the performance of the proposed method, learning and performance evaluation were conducted with a actual drama script. The method proposed in this study can be used as a means to improve the performance of Korean speech recognition service.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.145-154
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• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Investigative Magnetic Resonance Imaging
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• v.8 no.1
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• pp.32-41
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• 2004

Purpose : To measure the NMR relaxation properties of MnPC, to observe the characteristics of liver enhancement patterns on MR images in experimentally implanted rabbit VX2 tumor model, and to estimate the possibility of tissue specific contrast agent for MnPC in comparison with the hepatobiliary agent. Materials and Methods : Phthalocyanine (PC) was chelated with paramagnetic ions, manganese (Mn). 2.01 g (5.2 mmol) of phthalocyanine was mixed with 0.37 g (1.4 nlmol) of Mn chloride at $310^{\circ}C$ for 36 hours and then purified by chromatography ($CHCl_3:\;CH_3OH=98:2$, volume ratio) to obtain 1.04 g $(46\%)$ of MnPC (molecular weight = 2000 daltons). The T1/T2 relaxivity (R1/R2) for MnPC were determined at a 1.5 T (64 MHz) MR spectrometer. VX2 tumor model was experimentally implanted in the liver parenchyma of rabbits. All MR studies were performed on 1.5 T. The human extremity radio frequency coil of a bird cage type was employed. MR images were acquired at 17 to 24 days after VX2 carcinoma implantation.4 mmol/kg MnPC and 0.01 mmol/kg Mn-DPDP were injected via the ear vein of rabbits. T1-weighted images were obtained with spin-echo (TR/TE=516/14 msec) and fast multiplanar spoiled gradient recalled (TR/TE : 80/4 msec, $60^{\circ}$ flip angle) pulse sequence. Fast spin-echo (TR/TE=1200/85 msec) was used to obtain the T2-weighted images. Results : The value of T1/T2 relaxivity (R1/R2) of MnPC was $7.28\;mM^{-1}S^{-1}$ and $55.56\;mM^{-1}S^{-1}$ respectively at 1.5 T (64 MHz). Because the T2 relaxivity of MnPC that bonded strongly, covalently manganese with phthalocyanine was very high, the signal intensity of liver parenchyma was decreased on postcontrast T2-weighted images and we could easily distinguish the VX2 carcinoma within the liver parenchyma. When MnPC was administrated intravenously, the tumor margin delineation was more remarkable than Mn-DPDP-enhanced images. The enhancement of liver parenchyma with MnPC persisted at relatively high levels over at least one hour after injection of the contrast agents. Conclusion : The hepatic uptake and biliary excretion of MnPC, which are similar to Mn-DPDP, suggest that this agent is a new liver-specific agent. Also, MnPC seems to be used as a dual contrast agent (T1 and T2) with high T2 relaxivity. However, it is warranted that MnPC needs further investigation as a potential contrast agent for MR imaging of the liver. That is, further characterizations of MnPC are needed in vivo and in vitro before clinical trials. The diagnostic potential of MnPC will also have to be examined more in the animal models of additional types.

• 한국지구물리탐사학회:학술대회논문집
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• 2002.09a
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• pp.139-162
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• 2002

Since weak zones or geological lineaments are likely to be eroded, weak zones may develop beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. Dc resistivity surveys, however, have seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of case histories, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing at the water bottom, since the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the dc resistivity method can provide the fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio data as well as the high resolving power. The method installing electrodes at the water bottom is suitable to the detailed survey because of much higher resolving power, whereas the method floating them, especially streamer dc resistivity survey, is to the reconnaissance survey owing of very high speed of field work.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.