• Journal of The Korean Astronomical Society
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• v.52 no.1
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• pp.23-30
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• 2019

The KVN(Korean VLBI Network)-style simultaneous multi-frequency receiving mode is demonstrated to be promising for mm-VLBI observations. Recently, other Very long baseline interferometry (VLBI) facilities all over the globe start to implement compatible optics systems. Simultaneous dual/multi-frequency VLBI observations at mm wavelengths with international baselines are thus possible. In this paper, we present the results from the first successful simultaneous 22/43 GHz dual-frequency observation with KaVA(KVN and VERA array), including images and astrometric results. Our analysis shows that the newly implemented simultaneous receiving system has brought a significant extension of the coherence time of the 43 GHz visibility phases along the international baselines. The astrometric results obtained with KaVA are consistent with those obtained with the independent analysis of the KVN data. Our results thus confirm the good performance of the simultaneous receiving systems for the nonKVN stations. Future simultaneous observations with more global stations bring even higher sensitivity and micro-arcsecond level astrometric measurements of the targets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.504-509
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• 2019

Recently, both wireless communications technology and the performance of small devices have developed exponentially, while the number of services using various types of Internet of Things (IoT) devices has also massively increased in line with the ongoing technological and environmental changes. Furthermore, ever more devices that were previously used in the offline environment-including small-size sensors and CCTV-are being connected to the Internet due to the huge increase in IoT services. However, many IoT devices are not equipped with security functions, and use vulnerable open source software as it is. In addition, conventional network equipment, such as switches and gateways, operates with vulnerabilities, because users tend not to update the equipment on a regular basis. Recently, the simple vulnerability of IoT devices has been exploited through the distributed denial of service (DDoS) from attackers creating a large number of botnets. This paper proposes a system that is capable of identifying Internet-connected devices quickly, analyzing and managing the vulnerability of such devices using Internet-wide scan technology. In addition, the vulnerability analysis rate of the proposed technology was verified through collected banner information. In the future, the company plans to automate and upgrade the proposed system so that it can be used as a technology to prevent cyber attacks.

• Journal of IKEEE
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• v.23 no.3
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• pp.1096-1099
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• 2019

In this paper, we propose the protocol for construction of smart factory. The proposed protocol for construction of smart factory consists of an OPC UA Server/Client, a technology of TSN realtime communication, a NTP & PTP time synchronization protocol, a FieldBus protocol and conversion module, a technology of saving data for data transmit latency and synchronization protocol. OPC UA server/client is a system integration protocol which makes interface industrial hardware device and supports standardization which allows in all around area and also in not independent from any platform. A technology of TSN realtime communication provides an high sensitive time management and control technology in a way of sharing specific time between devices in the field of high speed network. NTP & PTP time synchronization protocol supports IEEE1588 standardization. A fieldbus protocol and conversion module provide an extendable connectivity by converting industrial protocol to OPC. A technology of saving data for data transmit latency and synchronization protocol provide a resolution function for a loss and latency of data. Results from testing agencies to assess the performance of proposed protocol for construction of smart factory, response time was 0.1367ms, synchronization time was 0.404ms, quantity of concurrent access was 100ea, quantity of interacting protocol was 5ea, data saving and synchronization was 1,000 nodes. It produced the same result as the world's highest level.

• The Korean Journal of Archival Studies
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• no.29
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• pp.35-78
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• 2011

This study is intended to recommend for acquisition methods of the theatre collection. Theatre activities is representative of the performing arts, and the Korea theatre history start from the modern history of Korea. In the meantime, theatre collections has already been lost by a lack of effort and management, and scattered most of the collections. In particular, a one-off nature and volatility of theatrical performances make future generations to enjoy the performances and to study should consult the relevant records. Therefore, collecting records can be very serious mission. In this study, theatre collections of the country which aims to collect and analyze the characteristics and type of theatre collections. Based on this information, collection scope, targets, priorities, acquisition level, method of collecting are proposed the following. First, collection scope is defined for the theatre related collections which was performed nationwide in the 1900s, the times that modern theatre was begun. The object includes related information of planning, administration, drama (script), directing, stage design, public relations, production, evaluation, personal records, biographical data, group data and space data. Second, the theatre collections are divided into records and historical records. Priority of collections object is determined by the historical value and the theatre performed by the support of public organization. Third, the acquisition level is divided into archived, mirrored, web linked and database, which is proposed by the determined levels of mandatory, recommend and discretion according to the characteristic of performance. Fourth, acquisition methods are suggested by the general acquisition methods of transfer, donation and purchase as well as the methods of copy, production, legal deposit, entry and web link etc. The acquisition of theatre collections is executed on digital-based environment, and a centralized authority control should be establishmented. And through the development of network with theatre's stakeholders and the cooperation of related organizations, theatre collections acquisition is feasible.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.48-57
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• 2019

The purpose of this study is to understand the intention of the inquirer from the single text type question in Goal-oriented dialogue. Goal-Oriented Dialogue system means a dialogue system that satisfies the user's specific needs via text or voice. The intention analysis process is a step of analysing the user's intention of inquiry prior to the answer generation, and has a great influence on the performance of the entire Goal-Oriented Dialogue system. The proposed model was used for a daily chemical products domain and Korean text data related to the domain was used. The analysis is divided into a speech-act which means independent on a specific field concept-sequence and which means depend on a specific field. We propose a classification method using the word embedding model and the CNN as a method for analyzing speech-act and concept-sequence. The semantic information of the word is abstracted through the word embedding model, and concept-sequence and speech-act classification are performed through the CNN based on the semantic information of the abstract word.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.36-46
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• 2019

The number of hosts connected to the Internet has increased dramatically, introducing the Domain Name System(DNS) in 1984. DNS is now an important key point for all users of the Internet by allowing them to use a convenient character address without memorizing a series of numbers of complex IP address. However, relative to the importance of DNS, there still exist many problems such as the authorization allocation issue, the disputes over public registration, security vulnerability such as DNS cache poisoning, DNS spoofing, man-in-the-middle attack, DNS amplification attack, and the need for many domain names in the age of hyper-connected networks. In this paper, to effectively improve these problems of existing DNS, we proposed a method of implementing DNS using distributed ledger technology, blockchain, and implemented using a Ethereum-based platform. In addition, the qualitative analysis performance comparative evaluation of the existing domain name registration and domain name server was conducted, and conducted security assessments on the proposed system to improve security problem of existing DNS. In conclusion, it was shown that DNS services could be provided high security and high efficiently using blockchain.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.1-11
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• 2021

As the Internet developed, various and complex cyber attacks began to emerge. Various detection systems were used outside the network to defend against attacks, but systems and studies to detect attackers inside were remarkably rare, causing great problems because they could not detect attackers inside. To solve this problem, studies on the lateral movement detection system that tracks and detects the attacker's movements have begun to emerge. Especially, the method of using the Remote Desktop Protocol (RDP) is simple but shows very good results. Nevertheless, previous studies did not consider the effects and relationships of each logon host itself, and the features presented also provided very low results in some models. There was also a problem that the model could not explain why it predicts that way, which resulted in reliability and robustness problems of the model. To address this problem, this study proposes an interpretable RDP-based lateral movement detection system using page rank algorithm and SHAP(Shapley Additive Explanations). Using page rank algorithms and various statistical techniques, we create features that can be used in various models and we provide explanations for model prediction using SHAP. In this study, we generated features that show higher performance in most models than previous studies and explained them using SHAP.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.31-39
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• 2018

Recently, there has been active studies to provide a user-friendly interface in a virtual reality environment by recognizing user hand gestures based on deep learning. However, most studies use separate sensors to obtain hand information or go through pre-process for efficient learning. It also fails to take into account changes in the external environment, such as changes in lighting or some of its hands being obscured. This paper proposes a hand gesture recognition method based on deep learning that is strong in external environments without the need for pre-process of RGB images obtained from general webcam. In this paper we improve the VGGNet and the GoogLeNet structures and compared the performance of each structure. The VGGNet and the GoogLeNet structures presented in this paper showed a recognition rate of 93.88% and 93.75%, respectively, based on data containing dim, partially obscured, or partially out-of-sight hand images. In terms of memory and speed, the GoogLeNet used about 3 times less memory than the VGGNet, and its processing speed was 10 times better. The results of this paper can be processed in real-time and used as a hand gesture interface in various areas such as games, education, and medical services in a virtual reality environment.

• Journal of the Korea Society for Simulation
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• v.30 no.2
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• pp.41-48
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• 2021

As the rural population continues to decline and aging, the improvement of agricultural productivity is becoming more important. Early prediction of crop quality can play an important role in improving agricultural productivity and profitability. Although many researches have been conducted recently to classify diseases and predict crop yield using CNN based deep learning and transfer learning technology, there are few studies which predict postharvest crop quality early in the planting stage. In this study, a early quality prediction model is proposed for sprout ginseng, which is drawing attention as a healthy functional foods. For this end, we took pictures of ginseng seedlings in the planting stage and cultivated them through hydroponic cultivation. After harvest, quality data were labeled by classifying the quality of ginseng sprout. With this data, we build early quality prediction models using several pre-trained CNN models through transfer learning technology. And we compare the prediction performance such as learning period and accuracy between each model. The results show more than 80% prediction accuracy in all proposed models, especially ResNet152V2 based model shows the highest accuracy. Through this study, it is expected that it will be able to contribute to production and profitability by automating the existing seedling screening works, which primarily rely on manpower.

• Knowledge Management Research
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• v.22 no.2
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• pp.1-17
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• 2021

In this study, we predicted the bitcoin prices of Bithum and Coinbase, a leading exchange in Korea and USA, using ARIMA and Recurrent Neural Networks(RNNs). And we used news articles from each country to suggest a separated RNN model. The suggested model identifies the datasets based on the changing trend of prices in the training data, and then applies time series prediction technique(RNNs) to create multiple models. Then we used daily news data to create a term-based dictionary for each trend change point. We explored trend change points in the test data using the daily news keyword data of testset and term-based dictionary, and apply a matching model to produce prediction results. With this approach we obtained higher accuracy than the model which predicted price by applying just time series prediction technique. This study presents that the limitations of the time series prediction techniques could be overcome by exploring trend change points using news data and various time series prediction techniques with text mining techniques could be applied to improve the performance of the model in the further research.