• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Korean Chemical Engineering Research
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• v.52 no.5
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• pp.688-693
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• 2014

For investigating NO reduction activity of an catalytic filter, the catalytic performance was measured under the presence of $SO_2$ and $H_2O$, respectively or simultaneously in the simulation gas composed of NO, $NH_3$, and air. The catalytic filter was prepared by coating $V_2O_5-WO_3/TiO_2$ catalyst on the pore surface of SiC filter element of which the superior performance for the particulate removal was well known. At the temperature below $260^{\circ}C$, the catalytic activities were enormously decreased under the presence of $SO_2$ and $H_2O$, respectively or simultaneously, compared with those under the cases of the absence of $SO_2$ and $H_2O$. However, the presence of $SO_2$ promoted the performance of the catalytic filter above $320^{\circ}C$ with showing the NO conversion better than 99.8% for the NO inlet concentration of 500 ppm and at the face velocity of 2 cm/s. In particular, the presence of water showed high NO conversion higher than 99% up to high temperature of $380^{\circ}C$. This effect of water was explained by the reason that it retarded the ammonia oxidation which is the main step into the formation of $N_2O$. The initial NO reduction activity of the catalytic filter maintained for the duration of 100 hours in the presence of $SO_2$ and $H_2O$. Therefore, it was concluded that the catalytic filter was promisingly useful for the industrial NOx reduction catalyst in order to treat the particulate and NO simultaneously.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.17-23
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• 2020

Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.

• Clinical and Experimental Pediatrics
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• v.46 no.2
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• pp.143-153
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• 2003

Purpose : Infection with Shiga-like toxin (SLT)-producing Escherichia coli, an emerging human pathogen found particularly in young children under 5 years of age, causes a spectrum of illnesses with high morbidity and mortality, ranging from diarrhea to hemorrhagic colitis and hemolytic uremic syndrome. Host mediators play an important role in the pathogenesis of SLT-I toxicity. The experiments described here were designed to investigate the effect of SLT-I on TNF-${\alpha}$ production and to understand the effect of TNF-${\alpha}$ on GB3 expression. We also further examine the relationship between the Gb3 level and the differential susceptibility of cells to the cytotoxic action of SLT-I. Methods : The effect of purified SLT-1 from E. coli O157 : H7 (ATCC 43890) on tumor necrosis factor-${\alpha}$ (TNF-${\alpha}$) production in Raw264.7 cells was investigated. Many mediators regulate endothelial cell membrane expression of the glycolipid globotriaosyleramide (Gb3), which serves as the toxin receptor, suggesting that the host response to the toxin or other bacterial products may contribute to pathogenesis by regulating target cell sensitivity to the toxins. Therefore, the relationships between Gb3 expression and cytotoxicity against SLT-I on three types of cells were evaluated. Results : Detectable levels of TNF-${\alpha}$ were produced as early as six hours after induction and continued to increase during 48 hours by SLT-I. It was also found that Vero cells and dendritic cells (DC2.4 cells) expressed high levels of Gb3, 83% and 68%, respectively, and that Raw264.7 cells had a low level of Gb3 (29%) and appeared refractory to cytotoxicity against SLT-I. Vero cells and DC2.4 cells expressing high levels of Gb3 were highly susceptible to SLT-I. Furthermore, macrophages showed a resistance to SLT-I cytotoxicity, despite the fact that Gb3 expression was enhanced. Conclusion : These results strongly suggest that the expression of Gb3 is necessary but not sufficient to confer sensitivity of macrophages to SLT-I and further underpin the important role of SLT-I and its Gb3 receptors in the pathogenesis of E. coli O157 infection.

• Journal of Food Hygiene and Safety
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• v.23 no.2
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• pp.98-107
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• 2008

The ozone has the oxidizing power which is powerful the fluorine and the antimicrobial spectrum of wide scope. Researches were carried out to use the merits that ozone has in various fields including the food industry, and many studies are also conducted nowadays for more efficient use of ozone. The ozone was permitted legally as a food additive and was practically used in the United States, Australia, Japanese etc. In November 2007, ozone water was permitted as a food additive in Korea and the interest in the use of ozone water has been on the rise in the Korea's food industry. As a olisinfectant method, ozone has many advantages. The maintenance and management expenses of ozone are lower than the installation cost at early stages and no by-products are generated after use it compared to others. Recently the demand of ozone as a olisinfectant method is increasing drastically. Although ozone water is popularly used to sterilize raw foods like fruits, vegetables and meats, the cases are still limited and were verified by the survey results. However, the use of ozone water is gradually being increased and is focused on food services. Ozone water refers to a state where ozone is dissolved into water to more conveniently use ozone. Accordingly, ozone water should be managed in regards with the amount and time of water-dissolved ozone, and the control of discharged ozone concentration is required for safe use of ozone water. The items to control mentioned above are directly related to the performance of the devices, and therefore, it is required to newly establish the performance criteria of ozone water manufacturing devices.

• The Korean Journal of Nuclear Medicine
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• v.32 no.5
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• pp.414-424
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• 1998

Purpose: Cross-modality coregistration of positron emission tomography (PET) and magnetic resonance imaging (MR) could enhance the clinical information. In this study we propose a refined technique to improve the robustness of registration, and to implement more realistic visualization of the coregistered images. Materials and Methods: Using the sinogram of PET emission scan, we extracted the robust head boundary and used boundary-enhanced PET to coregister PET with MR. The pixels having 10% of maximum pixel value were considered as the boundary of sinogram. Boundary pixel values were exchanged with maximum value of sinogram. One hundred eighty boundary points were extracted at intervals of about 2 degree using simple threshold method from each slice of MR images. Best affined transformation between the two point sets was performed using least square fitting which should minimize the sum of Euclidean distance between the point sets. We reduced calculation time using pre-defined distance map. Finally we developed an automatic coregistration program using this boundary detection and surface matching technique. We designed a new weighted normalization technique to display the coregistered PET and MR images simultaneously. Results: Using our newly developed method, robust extraction of head boundary was possible and spatial registration was successfully performed. Mean displacement error was less than 2.0 mm. In visualization of coregistered images using weighted normalization method, structures shown in MR image could be realistically represented. Conclusion: Our refined technique could practically enhance the performance of automated three dimensional coregistration.

• Journal of Astronomy and Space Sciences
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• v.22 no.1
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• pp.1-12
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• 2005

The Korean VLBI Network (KVN) will open a new field of research in astronomy, geodesy and earth science using the newest three Elm radio telescopes. This will expand our ability to look at the Universe in the millimeter regime. Imaging capability of radio interferometry is highly dependent upon the antenna configuration, source size, declination and the shape of target. In this paper, imaging simulations are carried out with the KVN system configuration. Five test images were used which were a point source, multi-point sources, a uniform sphere with two different sizes compared to the synthesis beam of the KVN and a Very Large Array (VLA) image of Cygnus A. The declination for the full time simulation was set as +60 degrees and the observation time range was -6 to +6 hours around transit. Simulations have been done at 22GHz, one of the KVN observation frequency. All these simulations and data reductions have been run with the Astronomical Image Processing System (AIPS) software package. As the KVN array has a resolution of about 6 mas (milli arcsecond) at 220Hz, in case of model source being approximately the beam size or smaller, the ratio of peak intensity over RMS shows about 10000:1 and 5000:1. The other case in which model source is larger than the beam size, this ratio shows very low range of about 115:1 and 34:1. This is due to the lack of short baselines and the small number of antenna. We compare the coordinates of the model images with those of the cleaned images. The result shows mostly perfect correspondence except in the case of the 12mas uniform sphere. Therefore, the main astronomical targets for the KVN will be the compact sources and the KVN will have an excellent performance in the astrometry for these sources.

• Investigative Magnetic Resonance Imaging
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• v.12 no.2
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• pp.131-141
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• 2008

Purpose : To investigate the feasibility and accuracy of Proton Resonance Frequency (PRF) shift based magnetic resonance (MR) temperature mapping utilizing the self-developed center array-sequencing phase unwrapping (PU) method for non-invasive temperature monitoring. Materials and Methods : The computer simulation was done on the PU algorithm for performance evaluation before further application to MR thermometry. The MR experiments were conducted in two approaches namely PU experiment, and temperature mapping experiment based on the PU technique with all the image postprocessing implemented in MATLAB. A 1.5T MR scanner employing a knee coil with $T2^*$ GRE (Gradient Recalled Echo) pulse sequence were used throughout the experiments. Various subjects such as water phantom, orange, and agarose gel phantom were used for the assessment of the self-developed PU algorithm. The MR temperature mapping experiment was initially attempted on the agarose gel phantom only with the application of a custom-made thermoregulating water pump as the heating source. Heat was generated to the phantom via hot water circulation whilst temperature variation was observed with T-type thermocouple. The PU program was implemented on the reconstructed wrapped phase images prior to map the temperature distribution of subjects. As the temperature change is directly proportional to the phase difference map, the absolute temperature could be estimated from the summation of the computed temperature difference with the measured ambient temperature of subjects. Results : The PU technique successfully recovered and removed the phase wrapping artifacts on MR phase images with various subjects by producing a smooth and continuous phase map thus producing a more reliable temperature map. Conclusion : This work presented a rapid, and robust self-developed center array-sequencing PU algorithm feasible for the application of MR temperature mapping according to the PRF phase shift property.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.279-287
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• 2018

Sealants are an important element of modern architecture and serve as a building protection against weathering by providing barriers against ingress of moisture, air, and other materials. Exposure to a variety of environments often reduces lifespan due to changes in physical, chemical and mechanical characteristics, and UV, humidity, and temperature expansion are important issues that are directly related to durability. In this study, a combined deterioration test chamber was developed to simulate the environment of the open air as an instrument for verifying the durability of structural sealing materials indoors. In order to replicate special weather conditions, such as yellow dust, acid rain, and contamination by microorganisms, it was deemed impossible to replicate the outdoor environment by 100 %, and the results of the results of the results of the external exposure test of the structural sealant and the combined deterioration testing device. As a result of the displacement test of the outdoor exposure test, it was determined that the sealant was breaking apart and that it would be smooth, and the displacement would be up to three times greater than the initial material value of 1 year. The displacement test results of the combined deterioration test device show the tendency to deteriorate, decreasing the elasticity and tensile characteristics. In the case of denatured silicon, the current 400 cycles have been completed to confirm 12 months of degradation of the external exposure. The deformation of the test specimen cannot be verified with the naked eye, so it is considered that the conditions of the specimen are more stable than the silicon sealant. As a result of the outdoor exposure test, if the combined deterioration test device is structured and proposed in the relevant guidance or specification, the anticipated lifespan of 12 months in the actual use environment can be verified indoors and below 3 months later, economically.

• Journal of the Society of Disaster Information
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• v.11 no.1
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• pp.135-147
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• 2015

Recent underground common utility tunnels are underground facilities for jointly accommodating more than 2 kinds of air-conditioning and heating facilities, vacuum dust collector, information processing cables as well as electricity, telecommunications, waterworks, city gas, sewerage system required when citizens live their daily lives and facilities responsible for the central function of the country but it is difficult to cope with fire accidents quickly and hard to enter into common utility tunnels to extinguish a fire due to toxic gases and smoke generated when various cables are burnt. Thus, in the event of a fire, not only the nerve center of the country is paralyzed such as significant property damage and loss of communication etc. but citizen inconveniences are caused. Therefore, noticing that most fires break out by a short circuit due to electrical works and degradation contact due to combustible cables as the main causes of fires in domestic and foreign common utility tunnels fire cases that have occurred so far, the purpose of this paper is to scientifically analyze the behavior of a fire by producing the model of actual common utility tunnels and reproducing the fire. A fire experiment was conducted in a state that line type fixed temperature detector, fire door, connection deluge set and ventilation equipment are installed in underground common utility tunnels and transmission power distribution cables are coated with fire proof paints in a certain section and heating pipes are fire proof covered. As a result, in the case of Type II, the maximum temperature was measured as $932^{\circ}C$ and line type fixed temperature detector displayed the fire location exactly in the receiver at a constant temperature. And transmission power distribution cables painted with fire proof paints in a certain section, the case of Type III, were found not to be fire resistant and fire proof covered heating pipes to be fire resistant for about 30 minutes. Also, fire simulation was carried out by entering fire load during a real fire test and as a result, the maximum temperature is $943^{\circ}C$, almost identical with $932^{\circ}C$ during a real fire test. Therefore, it is considered that fire behaviour can be predicted by conducting fire simulation only with common utility tunnels fire load and result values of heat release rate, height of the smoke layer, concentration of O2, CO, CO2 etc. obtained by simulation are determined to be applied as the values during a real fire experiment. In the future, it is expected that more reliable information on domestic underground common utility tunnels fire accidents can be provided and it will contribute to construction and maintenance repair effectively and systematically by analyzing and accumulating experimental data on domestic underground common utility tunnels fire accidents built in this study and fire cases continuously every year and complementing laws and regulations and administration manuals etc.