• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.187-193
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• 2015

The ICT healing platform sets a couple of goals including preventing chronic diseases and sending out early disease warnings based on personal information such as bio-signals and life habits. The 2-step open system(TOS) had a relay designed between the healing platform and the storage of personal health data. It also took into account a publish/subscribe(pub/sub) service based on large-scale connections to transmit(monitor) the data processing process in real time. In the early design of TOS pub/sub, however, the same buffers were allocated regardless of connection idling and type of message in order to encode connection messages into a deflate algorithm. Proposed in this study, the dynamic buffer allocation was performed as follows: the message transmission type of each connection was first put to queuing; each queue was extracted for its feature, computed, and converted into vector through tf-idf, then being entered into a k-means cluster and forming a cluster; connections categorized under a certain cluster would re-allocate the resources according to the resource table of the cluster; the centroid of each cluster would select a queuing pattern to represent the cluster in advance and present it as a resource reference table(encoding efficiency by the buffer sizes); and the proposed design would perform trade-off between the calculation resources and the network bandwidth for cluster and feature calculations to efficiently allocate the encoding buffer resources of TOS to the network connections, thus contributing to the increased tps(number of real-time data processing and monitoring connections per unit hour) of TOS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.43-48
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• 2018

This study was conducted to reproduce digital colour based on the lightness of the background and size of the colour stimulus so that colour can be similarly perceived under different conditions. With the evolution of display technologies, display devices of various sizes can now reproduce more accurate colour and enhanced images, thus affecting the overall quality of display images. This study reproduced digital colour by considering the visual characteristics of the digital media environment. To accomplish this, we developed a colour appearance model which distinguishes the properties of foveal and peripheral vision. The proposed model is based on existing research on the lightness of the background and size of the colour stimulus. Based on experimental results, an analysis of variance was performed in order to develop the colour appearance model. The algorithm and modelling were verified based on the proposed model. In addition, to apply this model to display technologies, a practical colour control system and a method for handling complex input images were developed. Through this research, colour conversion errors which might occur when the input image is converted to fit a specific display size are resolved from the perspective of the human visual system. As a result, more accurate colour can be displayed and enhanced images can be reproduced.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.143-148
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• 2020

In the case of a system that detects and controls the phase of an alternating voltage, the analog control method compensates the phase offset part by filtering for the detected phase and applies it to the control. However, in the digital control method, precise control cannot be achieved due to an error between the operating frequency of the microprocessor or the microcontroller and the input phase time when controlled using such phase detection. In general, when the method used is a certain time, the accumulated error is compensated and adjusted at random. To solve this problem, a method of detecting a zero point in real time and compensating for the operating frequency of the microprocessor is needed. Therefore, the research to be performed in this paper to reduce these errors and apply them to precise digital control is as follows. 1) Research on how to implement Zero Crossing Detection algorithm through simulation modeling to compensate the zero point to match the operating frequency through detection. 2) A study on the method of detecting zero points in real time through the Zero Crossing Detection design using a microcontroller and compensating for the operating frequency of the microprocessor. 3) A study on the estimation of the rotor position of BLDC motors using the Zero Crossing Detection circuit.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.78-89
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• 2013

This paper proposes a high-throughput and multi-mode quasi-cyclic (QC) low-density parity-check (LDPC) decoder based on a fully parallel structure. The proposed QC-LDPC decoder employs the fully parallel structure to provide very high throughput. The high interconnection complexity, which is the general problem in the fully parallel structure, is solved by using a broadcasting-based sum-product algorithm and proposing a low-complexity cyclic shift network. The high complexity problem, which is caused by using a large amount of check node processors and variable node processors, is solved by proposing a combined check and variable node processor (CCVP). The proposed QC-LDPC decoder can support the multi-mode decoding by proposing a routing-based interconnection network, the flexible CCVP and the flexible cyclic shift network. The proposed QC-LDPC decoder is operated at 100 MHz clock frequency. The proposed QC-LDPC decoder supports multi-mode decoding and provides 8.1 Gbps throughput for a (1944, 1620) QC-LDPC code.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.25-32
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• 2019

The purpose of this study is to investigate how to make a proper investment in ICO in the market. Previously, companies used to borrow money from banks or to obtain investments from venture capital (VC) and angel investors, but now ICOs are used as a new type of funding and financing model. The ICO sells the tokens or coins created on the blockchain openly online to raise the necessary funds, and provides the market value by paying the tokens or coins as much as the investment amount. According to this study, the limitations of the ICO market are (1) difficulties in evaluating the company, (2) uncertainties in investments, (3) lack of legal safeguards, and (4) measures to secure corporate stability after recruitment. At present, there is no way to cope with this systematically since the ICO is not protected in the legal framework. Nevertheless, we investigated the ways to make proper investment in the existing ICO market. In investing in ICO, investors should (1) consider investment methods and profitability, and (2) verify and judge investment fraud through various channels (ex. Homepage, composition team profile, etc.) and make investments based on this. This study will contribute to the formation of a healthy ICO market by understanding the newly emerged ICO market and studying the considerations when investing in it, thereby contributing to the right investor training and reducing the mass production of consumer damages caused by fraud. The limitation of this study is that the domestic ICO has not yet been examined in the legal framework, so further research is needed when policy changes occur in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.157-165
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• 2020

Aiming at the development of neural network and self-driving data set, it is also an idea to improve the performance of network model to detect moving objects by dividing the data set. In Darknet network framework, the YOLOv4 (You Only Look Once v4) network model was used to train and test Udacity data set. According to 7 proportions of the Udacity data set, it was divided into three subsets including training set, validation set and test set. K-means++ algorithm was used to conduct dimensional clustering of object boxes in 7 groups. By adjusting the super parameters of YOLOv4 network for training, Optimal model parameters for 7 groups were obtained respectively. These model parameters were used to detect and compare 7 test sets respectively. The experimental results showed that YOLOv4 can effectively detect the large, medium and small moving objects represented by Truck, Car and Pedestrian in the Udacity data set. When the ratio of training set, validation set and test set is 7:1.5:1.5, the optimal model parameters of the YOLOv4 have highest detection performance. The values show mAP50 reaching 80.89%, mAP75 reaching 47.08%, and the detection speed reaching 10.56 FPS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.59-66
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• 2021

Humans mainly recognize surrounding objects using visual and auditory information among the five senses (sight, hearing, smell, touch, taste). Major research related to the latest object recognition mainly focuses on analysis using image sensor information. In this paper, after emitting various chirp audio signals into the observation space, collecting echoes through a 2-channel receiving sensor, converting them into spectral images, an object recognition experiment in 3D space was conducted using an image learning algorithm based on deep learning. Through this experiment, the experiment was conducted in a situation where there is noise and echo generated in a general indoor environment, not in the ideal condition of an anechoic room, and the object recognition through echo was able to estimate the position of the object with 83% accuracy. In addition, it was possible to obtain visual information through sound through learning of 3D sound by mapping the inference result to the observation space and the 3D sound spatial signal and outputting it as sound. This means that the use of various echo information along with image information is required for object recognition research, and it is thought that this technology can be used for augmented reality through 3D sound.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.163-169
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• 2022

According to the Credit Information Act, in order to protect customer information by relationship of credit information subjects, it is destroyed and stored separately in two stages according to the period after the financial transaction effect is over. However, there is a limitation in that the destruction of personal credit information of customers whose financial transaction effect has expired cannot be collectively destroyed when the transaction has been terminated, depending on the nature of the financial product and transaction. To this end, the IT person in charge is developing a computerized program according to the target and order of destruction by investigating the business relationship by transaction type in advance. In this process, if the identification of the upper relation between tables is unclear, a compliance issue arises in which personal credit information cannot be destroyed or even information that should not be destroyed because it depends on the subjective judgment of the IT person in charge. Therefore, in this paper, we propose a model and algorithm for identifying the referenced table based on SQL executed in the computer program, analyzing the upper relation between tables with the primary key information of the table, and visualizing and objectively selecting the range to be destroyed. presented and implemented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.77-85
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• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.

• Journal of Broadcast Engineering
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• v.22 no.2
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• pp.193-206
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• 2017

In this paper, we propose a rate control method based on the $R-{\lambda}$ model that supports a parallel encoding structure in GOP levels or IDR period levels for 4K UHD input video in real-time. For this, a slice-level bit allocation method is proposed for parallel encoding instead of sequential encoding. When a rate control algorithm is applied in the GOP level or IDR period level parallelism, the information of how many bits are consumed cannot be shared among the frames belonging to a same frame level except the lowest frame level of the hierarchical B structure. Therefore, it is impossible to manage the bit budget with the existing bit allocation method. In order to solve this problem, we improve the bit allocation procedure of the conventional ones that allocate target bits sequentially according to the encoding order. That is, the proposed bit allocation strategy is to assign the target bits in GOPs first, then to distribute the assigned target bits from the lowest depth level to the highest depth level of the HEVC hierarchical B structure within each GOP. In addition, we proposed a processing method that is used to improve subjective image qualities by allocating the bits according to the coding complexities of the frames. Experimental results show that the proposed bit allocation method works well for frame-level parallel HEVC software encoders and it is confirmed that the performance of our rate controller can be improved with a more elaborate bit allocation strategy by using the preprocessing results.