• Management & Information Systems Review
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• v.37 no.4
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• pp.41-62
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• 2018

As the volume of unstructured data increases through various social media, Internet news articles, and blogs, the importance of text analysis and the studies are increasing. Since text analysis is mostly performed on a specific domain or topic, the importance of constructing and applying a domain-specific dictionary has been increased. The quality of dictionary has a direct impact on the results of the unstructured data analysis and it is much more important since it present a perspective of analysis. In the literature, most studies on text analysis has emphasized the importance of dictionaries to acquire clean and high quality results. However, unfortunately, a rigorous verification of the effects of dictionaries has not been studied, even if it is already known as the most essential factor of text analysis. In this paper, we generate three dictionaries in various ways from 39,800 news articles and analyze and verify the effect each dictionary on the accuracy of document classification by defining the concept of Intrinsic Rate. 1) A batch construction method which is building a dictionary based on the frequency of terms in the entire documents 2) A method of extracting the terms by category and integrating the terms 3) A method of extracting the features according to each category and integrating them. We compared accuracy of three artificial neural network-based document classifiers to evaluate the quality of dictionaries. As a result of the experiment, the accuracy tend to increase when the "Intrinsic Rate" is high and we found the possibility to improve accuracy of document classification by increasing the intrinsic rate of the dictionary.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.245-251
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• 2021

As the trend of steadily increasing the number of single or double household, there is a growing demand to see who is the outsider visiting the home during the free time. Various models of face recognition technology have been proposed through many studies, and Harr Cascade of OpenCV and Hog of Dlib are representative open source models. Among the two modes, Dlib's Hog has strengths in front of the indoor and at a limited distance, which is the focus of this study. In this paper, a face recognition visitor access system based on Dlib was designed and implemented. The whole system consists of a front module, a server module, and a mobile module, and in detail, it includes face registration, face recognition, real-time visitor verification and remote control, and video storage functions. The Precision, Specificity, and Accuracy according to the change of the distance threshold value were calculated using the error matrix with the photos published on the Internet, and compared with the results of previous studies. As a result of the experiment, it was confirmed that the implemented system was operating normally, and the result was confirmed to be similar to that reported by Dlib.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.79-85
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• 2022

Anomaly detection is a method to detect and block abnormal data flows in general users' data sets. The previously known method is a method of detecting and defending an attack based on a signature using the signature of an already known attack. This has the advantage of a low false positive rate, but the problem is that it is very vulnerable to a zero-day vulnerability attack or a modified attack. However, in the case of anomaly detection, there is a disadvantage that the false positive rate is high, but it has the advantage of being able to identify, detect, and block zero-day vulnerability attacks or modified attacks, so related studies are being actively conducted. In this study, we want to deal with these anomaly detection mechanisms, and we propose a new mechanism that performs both anomaly detection and classification while supplementing the high false positive rate mentioned above. In this study, the experiment was conducted with five configurations considering the characteristics of various algorithms. As a result, the model showing the best accuracy was proposed as the result of this study. After detecting an attack by applying the Extra Tree and Three-layer ANN at the same time, the attack type is classified using the Extra Tree for the classified attack data. In this study, verification was performed on the NSL-KDD data set, and the accuracy was 99.8%, 99.1%, 98.9%, 98.7%, and 97.9% for Normal, Dos, Probe, U2R, and R2L, respectively. This configuration showed superior performance compared to other models.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.296-301
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• 2021

This study is a study dealing with the empirical test of standardized multimedia disaster warning broadcasting linked with the next-generation prediction and warning platform and the disaster warning additional data service of terrestrial UHD broadcasting. The next-generation prediction and warning platform used in the demonstration test complies with the CAP-based TTA standardization standard, and the UHD disaster warning additional data service complies with the AEAT standard. As a result of the experiment, when a standardized CAP disaster warning message is issued and delivered to a broadcasting company, a system was established so that it is automatically converted to AEAT, a UHD disaster warning additional data message, and transmitted. The receiver unit was configured by connecting a set-top capable of receiving disaster alert data and a TV with an HDMI cable. When a disaster is announced, the set-top displays the AEAT message on the TV broadcasting screen, customized to the priority of the disaster and the area where it is issued. In addition, incoming messages are displayed in a language suitable for user settings among 5 languages. Additional multimedia functions such as images and alarm sounds could also be linked. In particular, it was confirmed that the receiver message was displayed within 3 seconds of issuing the disaster alert, enabling prompt delivery of the disaster alert.

• Advances in nano research
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• v.12 no.5
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• pp.501-514
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• 2022

This study aimed to investigate the effects and potential mechanisms of Chikusetsusaponin V (CsV) on endothelial nitric oxide synthase (eNOS) and vascular endothelial cell functions. Different concentrations of CsV were added to animal models, bovine aorta endothelial cells (BAECs) and human umbilical vein endothelial cells (HUVECs) cultured in vitro. qPCR, Western blotting (WB), and B ultrasound were performed to explore the effects of CsV on mouse endothelial cell functions, vascular stiffness and cellular eNOS mRNA, protein expression and NO release. Bioinformatics analysis, network pharmacology, molecular docking and protein mass spectrometry analysis were conducted to jointly predict the upstream transcription factors of eNOS. Furthermore, pulldown and ChIP and dual luciferase assays were employed for subsequent verification. At the presence or absence of CsV stimulation, either overexpression or knockdown of purine rich element binding protein A (PURA) was conducted, and PCR assay was employed to detect PURA and eNOS mRNA expressions, Western blot was used to detect PURA and eNOS protein expressions, cell NO release and serum NO levels. Tube formation experiment was conducted to detect the tube forming capability of HUVECs cells. The animal vasodilation function test detected the vasodilation functions. Ultrasonic detection was performed to determine the mouse aortic arch pulse wave velocity to identify aortic stiffness. CsV stimulus on bovine aortic cells revealed that CsV could upregulate eNOS protein levels in vascular endothelial cells in a concentration and time dependent manner. The expression levels of eNOS mRNA and phosphorylation sites Ser1177, Ser633 and Thr495 increased significantly after CsV stimulation. Meanwhile, CsV could also enhance the tube forming capability of HUVECs cells. Following the mice were gavaged using CsV, the eNOS protein level of mouse aortic endothelial cells was upregulated in a concentration- and time-dependent manner, and serum NO release and vasodilation ability were simultaneously elevated whereas arterial stiffness was alleviated. The pulldown, ChIP and dual luciferase assays demonstrated that PURA could bind to the eNOS promoter and facilitate the transcription of eNOS. Under the conditions of presence or absence of CsV stimulation, overexpression or knockdown of PURA indicated that the effect of CsV on vascular endothelial function and eNOS was weakened following PURA gene silence, whereas overexpression of PURA gene could enhance the effect of CsV upregulating eNOS expression. CsV could promote NO release from endothelial cells by upregulating the expression of PURA/eNOS pathway, improve endothelial cell functions, enhance vasodilation capability, and alleviate vessel stiffness. The present study plays a role in offering a theoretical basis for the development and application of CsV in vascular function improvement, and it also provides a more comprehensive understanding of the pharmacodynamics of CsV.

• Journal of the Korean Institute of Gas
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• v.26 no.6
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• pp.30-36
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• 2022

In commercial transactions of energy sources using hydrogen charging stations, high-accuracy flow meters are needed to prevent accidents such as overcharging due to inaccurate measurements and to ensure transparency in hydrogen commercial transactions through accurate measurements. This research developed a Corioli-type flowmeter prototype and conducted a risk assessment to prevent accidents during a process change comparison experiment for existing charging stations to verify the measurement performance. A process change section was defined for the installation of measurement facilities for empirical experiments and HAZOP was conducted. In addition, JSA was also conducted to secure the safety of experimenters, such as preventing valve mis-opening during empirical experiments. Measures were established to improve the risk factors derived through HAZOP, and work procedures were established to minimize human errors and ensure the safety of workers through JSA. The design change and system manufacturing for the installation of the metering system were completed by reflecting the risk assessment results, and safety could be confirmed through the performance comparison test of the developed meter prototype. The developed prototype flow meter showed a total of 30 flow measurements under the operating conditions of 70 MPa, and the average error was -1.58% to 3.96%. Such a metering error was analyzed to have the same performance as a flow meter installed and operated for commercial use.

• Journal of the Korean Society of Radiology
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• v.16 no.6
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• pp.735-740
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• 2022

In order to reduce side effects such as rectal bleeding in the Brachytherapy, the rectal retractor and wet gauze have been used to increase the distance between the rectum and the tandem. However, there were disadvantages that it was difficult to insert through a narrow entrance into the vagina and poor reproducibility. Also, based on the CT image of the selected catheter, the distance from the tandem to the rectum with or without the balloon catheter was checked and the reduction of the dose to the rectum was confirmed. As a result of the experiment, catheter No. 7 was selected considering the maximum balloon size at a level that does not affect the distance between the start point of the balloon and the end of the catheter, and the ovoid applicator. Based on the CT image of the selected catheter, the degree of expansion according to the presence or absence of the balloon catheter was compared, and it was found that the distance difference was 0.3 - 1 cm. In addition, it was confirmed that a decrease of about 32% was observed due to this distance difference. Therefore, the actual clinical application of the selected catheter can be used as a substitute for the existing rectal retractor and wet gauze.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.149-158
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• 2023

As data utilization is becoming more important recently, the importance of data centers is also increasing. However, the data center is a problem in terms of environment and economy because it is a massive power-consuming facility that runs 24 hours a day. Recently, studies using deep learning techniques to reduce power used in data centers or servers or predict traffic have been conducted from various perspectives. However, the amount of traffic data processed by the server is anomalous, which makes it difficult to manage the server. In addition, many studies on dynamic server management techniques are still required. Therefore, in this paper, we propose a dynamic server management technique based on Long-Term Short Memory (LSTM), which is robust to time series data prediction. The proposed model allows servers to be managed more reliably and efficiently in the field environment than before, and reduces power used by servers more effectively. For verification of the proposed model, we collect transmission and reception traffic data from six of Wikipedia's data centers, and then analyze and experiment with statistical-based analysis on the relationship of each traffic data. Experimental results show that the proposed model is helpful for reliably and efficiently running servers.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.1
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• pp.13-21
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• 2023

As problems such as difficulties in securing stable energy resources and global warming due to the emission of greenhouse gases due to the use of fossil fuels have emerged, interest in the development of renewable energy is increasing. Since the tidal phenomenon has a regularity that occurs regularly with a certain period, it is possible to predict accurately in advance, which has a advantage in terms of energy recovery. Therefore, various methods have been devised to utilize the tide as an energy source. Tidal power using barrages is a representative method that is widely operated, but the promotion of tidal power generation projects is being delayed or stopped due to the decrease in the level of water in the tidal basin, changes in water quality and in the ecosystem. In this study, a field experiment was conducted to develop and verify the performance of a tidal power device applicable to sea areas where dykes are already installed. As a result of carrying out four cases of experiments using two water tanks, pipe lines, open channels, weirs, and water turbine and generator, the possibility of developing a power generation system capable of 10 kW output or more and 60% efficiency or more was confirmed. These research results can be used for small-scale tidal power by utilizing the existing dykes.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.173-191
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• 2022

In this study, the shear wave velocity of the ground was measured using Flat TDR, and the precision analysis of the measured value and the verification of field applicability were performed. The shear wave velocity measurement value was derived in the field using the piezo-stack combined in the Flat TDR. analyzed. As a result of the experiment, the average value of the change in shear wave speed at the time of grout material injection was 10.15 m/s at the beginning of age, and the average value of the change in shear wave speed after the 7th to 14th days was 65.99 m/s, showing a tendency to increase with age. Also, it was found that dry density and shear wave speed increased as the water content increased on the dry side, and that the dry density and shear wave rate decreased as the water content increased on the wet side as the water content increased. The shear modulus value derived from the field test was confirmed to be a minimum of 17.36 MPa and a maximum of 28.13 MPa, confirming a measurement value similar to the reference value. Through this, it can be seen that the measured value of the shear modulus using Flat TDR is reliable data, and it can be determined that the compaction management of the site can be effectively managed in the future.