• International journal of advanced smart convergence
• /
• v.11 no.1
• /
• pp.11-18
• /
• 2022

Securities and investment services have and use large data. Investors started to invest through their own analysis methods. There are 22 major securities and investment companies in Korea and only 6 companies support open API. Python is effective for requesting and receiving, analyzing text data from open API. Daishin Securities Co. is the only open API that officially supports Python, and eBest Investment & Securities Co. unofficially supports Python. There are two important differences between CYBOS plus of Daishin Securities Co. and xingAPI of eBest Investment & Securities Co. First, we must log in to CYBOS plus to access the server of Daishin Securities Co. And the python program does not require a logon. However, to receive data using xingAPI, users log on in an individual Python program. Second, CYBOS plus receives data in a Request/Reply method, and zingAPI receives data through events. It can be thought that these points will show a difference in response time. Response time is important to users who use open APIs. Data were measured from August 5, 2021, to February 3, 2022. For each measurement, 15 repeated measurements were taken to obtain 420 measurements. To increase the accuracy of the study, both APIs were measured alternately under same conditions. A paired t-test was performed to test the hypothesis that the null hypothesis is there was no difference in means. The p-value is 0.2961, we do not reject null hypothesis. Therefore, we can see that there is no significant difference between means. From the boxplot, we can see that the distribution of the response time of eBest is more spread out than that of Cybos, and the position of the center is slightly lower. CYBOS plus has no restrictions on Python programming, but xingAPI has some limits because it indirectly supports Python programming. For example, there is a limit to receiving more than one current price.

• Proceedings of the Korea Contents Association Conference
• /
• 2006.11a
• /
• pp.3-6
• /
• 2006

The Web2.0(Next Generation Web Service) is receiving attention by computer industry. Therefore Ajax(Asynchonous Javascript And in), a key RIA(Rich Internet Application) technology of Web 2.0 applications, has also been a matter of interest. And multiple Web applications which are based on Ajax are being developed and delivered. This paper deals with 'Scheduler Applications/Services' of the web application that utilize Ajax. Plus, this paper is aimed at developing, Project Management Scheduler and Project Roadmap, using web applications that utilize Ajax.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.5
• /
• pp.2043-2060
• /
• 2020

Developed from Digital Multimedia Broadcasting (DMB), DMB+ changes the application focus fundamentally. The plus symbol "+" indicates that DMB+ is no longer for digital radio/videos, instead it works as a general data transmission technique. The merits of wireless transmission, broad coverage, high quality, information security and low building/maintenance cost make DMB+ suitable for a wide range of applications with numerous terminals and users, such as public information release, alarm and administration etc. The concept of DMB+ base station enables DMB+ to be used in building independent networks and for remote control and management, as well as for Industry 4.0. DMB+ will access into a new field that till now has been dominated by communication techniques, will open a huge commercial opportunity.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.1
• /
• pp.224-241
• /
• 2015

Multiview plus depth (MVD) videos are widely used in free-viewpoint TV systems. The best-known technique to determine depth information is based on stereo vision. In this paper, we propose a novel local stereo matching algorithm which is radiometric invariant. The key idea is to use a combined matching cost of intensity and gradient based similarity measure. In addition, we realize an adaptive cost aggregation scheme by constructing an adaptive support window for each pixel, which can solve the boundary and low texture problems. In the disparity refinement process, we propose a four-step post-processing technique to handle outliers and occlusions. Moreover, we conduct stereo reconstruction tests to verify the performance of the algorithm more intuitively. Experimental results show that the proposed method is effective and robust against local radiometric distortion. It has an average error of 5.93% on the Middlebury benchmark and is compatible to the state-of-art local methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.12
• /
• pp.5015-5027
• /
• 2015

Transceiver optimization in multiple input multiple output (MIMO) cognitive systems is studied in this paper. The joint transceiver beamformer design is introduced to minimize the transmit power at secondary base station (SBS) while simultaneously controlling the interference to primary users (PUs) and satisfying the secondary users (SUs) signal-to-interference-plus-noise ratio (SINR) based on the convex optimization method. Due to the limited cooperation between SBS and PUs, the channel state information (CSI) usually cannot be obtained perfectly at the SBS in cognitive system. In this study, both perfect and imperfect CSI scenarios are considered in the beamformer design, and the proposed method is robust to CSI error. Numerical results validate the effectiveness of the proposed algorithm.

• International journal of advanced smart convergence
• /
• v.9 no.2
• /
• pp.84-89
• /
• 2020

This study multilaterally explores South Korean YouTuber Winter Library's book-related contents uploaded on one's channel. As science and technology have developed, now the ordinary people can produce their videos and share them online. YouTube has been the most popular video storage service, and many Koreans use and enjoy it as well. This study investigates book-related contents produced by YouTuber user Winter Library, often called BookTuber (Book plus YouTuber). More specifically, it analyzes Winter Library's various contents by 1) Components of YouTube Channel 2) Contents of Components 3) Components that help to increase reading rates. This study is contributing as it focuses on book, which is not so common topic in YouTube. As a result, the study discovers unique aspects of YouTube contents, and also explores the book-related industry in South Korea. This YouTube channel could be functional for increasing reading rates, especially among adults.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.6
• /
• pp.1209-1221
• /
• 2010

Three dimensional (3D) video is expected to be an important application for broadcast and IP streaming services. One of the main limitations for the transmission of 3D video over IP networks is network bandwidth mismatch due to the large size of 3D data, which causes fatal decoding errors and mosaic-like damage. This paper presents a novel selective frame discard method to address the problem. The main idea of the proposed method is the symmetrical discard of the two dimensional (2D) video frame and the depth map frame. Also, the frames to be discarded are selected after additional consideration of the playback deadline, the network bandwidth, and the inter-frame dependency relationship within a group of pictures (GOP). It enables the efficient utilization of the network bandwidth and high quality 3D IPTV service. The simulation results demonstrate that the proposed method enhances the media quality of 3D video streaming even in the case of bad network conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.5
• /
• pp.1638-1653
• /
• 2014

A sequential optimization algorithm (SOA) for resource allocation in a cyclic-prefixed single-carrier cognitive relay system is proposed in this study. Both subcarrier pairing (SP) and power allocation are performed subject to a primary user interference constraint to minimize the mean squared error of frequency-domain equalization at the secondary destination receiver. Under uniform power allocation at the secondary source and optimal power allocation at the secondary relay, the ordered SP is proven to be asymptotically optimal in maximizing the matched filter bound on the signal-to-interference-plus-noise ratio. SOA implements the ordered SP before power allocation optimization by decoupling the ordered SP from the power allocation. Simulation results show that SOA can optimize resource allocation efficiently by significantly reducing complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.9
• /
• pp.1596-1612
• /
• 2011

Coordinated Multi-Point (CoMP) transmission / reception is being studied in Long Term Evolution-Advanced (LTE-A) for future evolution of the $3^{rd}$ Generation Partnership Project (3GPP) LTE. Support of soft handover is essential for improving the performance of cell edge users. CoMP provides a natural framework for enabling soft handover in the LTE system. This paper evaluates the soft handover gain in LTE-A downlink. Mathematical analysis of signal to interference plus noise ratio (SINR) gain and the handover margins for soft handover and hard handover are derived. CoMP system model is developed and an inter-cell and intra-cell interference model is derived, taking into account the pathloss, shadowing, cell loading, and traffic activity. Reference signal received power (RSRP) is used to define the triggers and the measurements for soft handover. Our results indicate that parameter choices such as handover margin and the CoMP set size impact CoMP performance gain.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.2
• /
• pp.420-437
• /
• 2024

There are some problems in network traffic classification (NTC), such as complicated statistical features and insufficient training samples, which may cause poor classification effect. A NTC architecture based on one-dimensional Convolutional Neural Network (CNN) and transfer learning is proposed to tackle these problems and improve the fine-grained classification performance. The key points of the proposed architecture include: (1) Model classification--by extracting normalized rate feature set from original data, plus existing statistical features to optimize the CNN NTC model. (2) To apply transfer learning in the classification to improve NTC performance. We collect two typical network flows data from Youku and YouTube, and verify the proposed method through extensive experiments. The results show that compared with existing methods, our method could improve the classification accuracy by around 3-5%for Youku, and by about 7 to 27% for YouTube.