• Journal of Information Technology Services
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• v.15 no.4
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• pp.1-24
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• 2016

With the innovation of information technology, non-face-to-face robo advisor with high accessibility and convenience is spreading. The current robot advisor recommends appropriate investment products after understanding the investment propensity based on the structured data entered directly or indirectly by individuals. However, it is an inconvenient and obtrusive way for financial consumers to inquire or input their own subjective propensity to invest. Hence, this study proposes a way to deduce the propensity to invest in unstructured data that customers voluntarily exposed during consultation or online. Since prediction performance based on unstructured document differs according to the characteristics of text, in this study, classification algorithm optimized for the characteristic of text left by financial consumers is selected by performing prediction performance evaluation of various learning discrimination algorithms and proposed an intelligent method that automatically recommends investment products. User tests were given to MBA students. After showing the recommended investment and list of investment products, satisfaction was asked. Financial consumers' satisfaction was measured by dividing them into investment propensity and recommendation goods. The results suggest that the users high satisfaction with investment products recommended by the method proposed in this paper. The results showed that it can be applies to non-face-to-face robo advisor.

• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.209-217
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• 2019

Due to the development of artificial intelligence and image recognition technology that play important roles in the field of 4th industry, office automation systems and unmanned automation systems are rapidly spreading in human society. The proposed algorithm first finds the variances of the differences between the tile values constituting the learning characters and the experimental character and then recognizes the experimental character according to the distribution of the three learning characters with the smallest variances. In more detail, for 100 learning data characters and 10 experimental data characters, each character is defined as the number of black pixels belonging to 15 tile areas. For each character constituting the experimental data, the variance of the differences of the tile values of 100 learning data characters is obtained and then arranged in the ascending order. After that, three learning data characters with the minimum variance values are selected, and the final recognition result for the given experimental character is selected according to the distribution of these character types. Moreover, we compare the recognition result with the result made by a neural network of basic structure. It is confirmed that satisfactory recognition results are obtained through the processes that subdivide the learning characters and experiment characters into tile sizes and then select the recognition result using variances.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.219-234
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• 2019

Fake news threaten democratic elections and causes social conflicts, resulting in major damage. However, the concept of fake news is hard to define, as there is a saying, "News is not fake, fake is not news." Fake news, however, has irreversible characteristics that can not be recovered or reversed completely through post-punishment of economic and political benefits. It is also rapidly spreading in the early days. Therefore, it is very important to preemptively detect these types of articles and prevent their blind proliferation. The existing countermeasures are focused on reporting fake news, raising the level of punishment, and the media & academia to determine the authenticity of the news. Researchers are also trying to determine the authenticity by analyzing its contents. Apart from the contents of fake news, determining the behavioral characteristics of the promoters and its qualities can help identify the possibility of having fake news in advance. The online community has a fake news interception and response tradition through its long-standing community-based activities. As a result, I attempted to model the fake news by analyzing the affirmation-denial analysis and posting behavior by securing the web board crawl of the 'M community' bulletin board during the 2017 Korean presidential election period. Random forest algorithm deemed significant. The results of this research will help counteract fake news and focus on preemptive blocking through behavioral analysis rather than post-judgment after semantic analysis.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.2
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• pp.61-68
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• 2023

Multi-band method which allocate the same data to different frequency bands, improves performance by compensating Doppler spreading and selective fading in underwater communications. The drawback of multi-band configuration may have worse performance because performance degradation in a particular band affects the output from the entire bands. It is very important to find which band is superior or inferior band in order to improve performance. Therefore this paper analyzes performance prediction algorithms of each band. This paper proposes three kinds of prediction methods. Through the ocean tests, this paper confirms utilizing the preamble error rates is most efficient algorithm among of them.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.1
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• pp.1-9
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• 2022

Global Navigation Satellite System (GNSS) provides location information using signals from multiple satellites. However, a spoofing attack that forges signals or retransmits delayed signals may cause errors in the location information. To prevent such attacks, authentication protocols considering the navigation message structure of each GNSS can be used. In this paper, we analyze the authentication protocols of Global Positioning System (GPS), Galileo, and BeiDou, and compare the performance of Navigation Message Authentication (NMA) of the above systems, using several performance indicators. According to our analysis, authentication protocols are similar in terms of performing NMA and using Elliptic Curve Digital Signature Algorithm (ECDSA). On the other hand, they are different in several ways, for example, whether to perform Spreading Code Authentication (SCA), whether to use digital certificates and whether to use Timed Efficient Stream Loss-tolerant Authentication (TESLA). According to our quantitative analysis, the authentication protocol of Galileo has the shortest time between authentications and time to first authenticated fix. We also show that the larger the sum of the navigation message bits and authentication bits, the more severely affected are the time between authentications and the time to first authenticated fix.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.119-123
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• 2023

This study is normal orientation technology of slit coating equipment to improve the quality of curved displays. Currently, the demand for curved displays is increasing significantly due to advantages such as screen immersion or design in various industries. Accordingly, changes in the display coating process are essential. In the curved display coating process, unlike the existing flat coating process, the nozzle must be rotated along the curvature of the curved surface to spray the coating solution. The coating solution must be applied while maintaining a uniform thickness. If the thickness of the coating liquid applied to the target surface is non-uniform, the quality of the product may be degraded such as image quality deterioration and light spreading. This paper presents technology and experimental results for keeping the nozzle of slit coating equipment perpendicular to the curved surface and is expected to contribute to the quality improvement of curved displays.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.813-826
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• 2015

This research deals with an estimation method for kinetic reaction model. The kinetic reaction model is a model to explain spread or changing process based on interaction between species on the Biochemical area. This model can be applied to a model for disease spreading as well as a model for system Biology. In the search, we assumed that the spread of species is stochastic and we construct the reaction model based on stochastic movement. We utilized Gillespie algorithm in order to construct likelihood function. We introduced a Bayesian estimation method using Markov chain Monte Carlo methods that produces more stable results. We applied the Bayesian estimation method to the Lotka-Volterra model and gene transcription model and had more stable estimation results.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.169-174
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• 2003

The trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online, or an offline internet, so it is expected to make a problem more and more. The goal of intrusion detection is to identify unauthorized use, misuse, and abuse of computer systems by both system insiders and external penetrators in real time. In fact, the general security system based on Internet couldn't cope with the attack properly, if ever. other regular systems have depended on common vaccine softwares to cope with the attack. But in this paper, we will use the positive selection and negative selection mechanism of T-cell, which is the biologically distributed autonomous system, to develop the self/nonself recognition algorithm and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. For making it come true, we will apply AIS to the network environment, which is a computer security system.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.273-279
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• 2014

In this paper, we propose a novel algorithm for three dimensional positioning system and implement a system over indoor wireless channel. A commercial modules are used for mobile and fixed nodes which are product of German company Nanotron Co. This module adopts chirp spread spreading scheme as modulation method to improve the ranging resolution and the module satisfies the IEEE standard 802.15.4a. The distance computation is based on received signal strength(RSS) levels and trilateration method. A testbed was set up to measure and compare the positioning estimation error of the proposed algorithm. The experiments results showed that the accuracy of location estimation was sufficiently good as much as 1m distance error in a wireless environment in an office building.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.586-594
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• 2012

The drastic growth of mobile communication and spreading of smart phone make the significant attention on Location Based Service. The one of most important things for vitalization of LBS is the accurate estimating position for mobile object. Focusing on AP's probabilistic position estimation, we develop an AP distribution map and new pattern matching algorithm for position estimation. The developed approaches can strengthen the advantages of Radio fingerprint based Wi-Fi Positioning System, especiall on the algorithms and data handling. Compared on the existing approaches of fingerprint pattern matching algorithm, we achieve the comparable higher performance on both of average error of estimation and deviation of errors. Furthermore all fingerprint data have been harvested from the actual measurement of radio fingerprint of Seoul, Kangnam area. This can approve the practical usefulness of proposed methodology.