• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.728-738
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• 2016

We are currently able to share not only the information from humans but also the data from connected things on the Internet. We are getting close to IoT era because of progress of Information Communication Technology. Therefore, the ways of data transfer are offered between things to things. One of typical way is the HTTP protocol. However, The field of Internet of Things platforms requires more fast and more stable communication protocol to handle massive data. The system supporting HTTP protocol, there is a problem of transmission efficiency in a relatively large header compared to data. also HTTP protocol system overload situations and the problem of data compatibility happens due to each standard of many organizations. Thus, To solve these problems, I suggest the data collection solution based on MQTT protocol for the operation of the stable IoT platforms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.28-36
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• 2016

Recently, owing to the development of ICT industry and wide spread of smart phone, the number of people who use car sharing service are increased rapidly. Currently two-way car sharing system with same rental and return locations are mainly operated since this system can be easily implemented and maintained. Currently the demand of one-way car sharing service has increase explosively. But this system have several obstacle in operation, especially, vehicle stock imbalance issues which invoke vehicle relocation. Hence in this study, we present an optimization approach to depot location and relocation policy in one-way car sharing systems. At first, we modelled as mixed-integer programming models whose objective is to maximize the profits of a car sharing organization considering all the revenues and costs involved and several constraints of relocation policy. And to solve this problem efficiently, we proposed a new method based on particle swarm optimization, which is one of powerful meta-heuristic method. The practical usefulness of the approach is illustrated with a case study involving satellite cities in Seoul Metrolitan Area including several candidate area where this kind systems have not been installed yet and already operating area. Our proposed approach produced plausible solutions with rapid computational time and a little deviation from optimal solution obtained by CPLEX Optimizer. Also we can find that particle swarm optimization method can be used as efficient method with various constraints. Hence based on this results, we can grasp a clear insight into the impact of depot location and relocation policy schemes on the profitability of such systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.228-231
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• 2015

Recently, the electric power consumption concentrated in specific seasons and time causes the unstable power supply. To resolve this problem, smart grid has emerged as an alternative to consume the power, efficiently. Smart grid that combines ICT with the existing electrical grid includes demand response as a core technology. Demand response enable the power consumption effectively by offering a variety of informations, such as power consumption, charges expected, etc., for consumers who voluntarily participate in the electricity markets. In this paper, we design the automatic demand response systems based on SEP 2.0 for the efficient power control of home appliances in the smart grid environments.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.175-180
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• 2017

In accordance with the development of IT industry worldwide, software industry has also grown tremendously, and it is exerting influence on the general society starting from daily life to financial organizations and public institutions. However, various security threats that can inflict serious threat to provided services in proportion to the growing software industry, have also greatly increased. In this thesis, we suggest a smart fuzzing system combined with black box and white box testing that can effectively detectxdistinguish software vulnerability which take up a large portion of the security incidents in application programs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1567-1573
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• 2020

The development of Internet technology has brought the era of one-man media. An individual produces content on user own and uploads it to related online services, and many users watch the content of online services using devices that allow them to use the Internet. Currently, most users find and watch content they want through search functions provided by existing online services. These features are provided based on information entered by the user who uploaded the content. In an environment where content needs to be retrieved based on these limited word data, user unwanted information is presented to users in the search results. To solve this problem, in this paper, the system actively analyzes the video in the online service, and presents a way to extract and reflect the characteristics held by the video. The research was conducted to extract morphemes based on the story content based on the voice data of a video and analyze them with big data technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.942-948
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• 2020

In this paper, we propose a clustered algorithm that possible more efficient user distinction within clustering using context-aware attribute information. In typically, the data provided to classify interrelationships within cluster information in the process of clustering data will be as a degrade factor if new or newly processing information is treated as contaminated information in comparative information. In this paper, we have developed a clustering algorithm that can extract user's recognition information to solve this problem in using K-means algorithm. The proposed algorithm analyzes the user's clustering attributed parameters from user clusters using accumulated information and clustering according to their attributes. The results of the simulation with the proposed algorithm showed that the user management system was more adaptable in terms of classifying and maintaining multiple users in clusters.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1074-1081
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• 2021

It has recently been noticed that the headway of unlicensed wireless technology is necessary as user's demands of wireless tech increase and the development of high-speed data service by using low-power short-range wireless network is needed. Hence, it is inevitable to study sharing and coexistence for broadband spectrum of diverse unlicensed application with wide bandwidth. In this paper, an interference examination between unlicensed WiFi (Wireless Fidelity) in the 6GHz and OB (Outside Broadcasting) system which is an incumbent service in the same frequency band was conducted and it suggests separation distance for the coexistence. Thus, MCL (Minimum Coupling Loss) and MC (Monte Carlo) methods were used to set up interference scenarios for the interference analysis and compute the separation distance between two systems according to the same frequency band and frequency separation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1559-1565
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• 2021

In this paper, an antenna selection scheme is proposed in massive multi-user multiple input multiple output (MU-MIMO) systems. The proposed antenna selection scheme can achieve almost the same performance as a conventional scheme while significantly reducing the overhead of feedback by using deep reinforcement learning (DRL). Each user compares the channel gains of massive antennas in base station (BS) to the L-largest channel gain, converts them to one-bit binary numbers, and feed them back to BS. Thus, the feedback overhead can be significantly reduced. In the proposed scheme, DRL is adopted to prevent the performance loss that might be caused by the reduced feedback information. We carried out extensive Monte-Carlo simulations to analyze the performance of the proposed scheme and it was shown that the proposed scheme can achieve almost the same average sum-rates as a conventional scheme that is almost optimal.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1649-1654
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• 2021

In this paper, we introduce a regularization of long short-term memory (LSTM) based fall detection system using TensorFlow that can detect falls that can occur in the elderly. Fall detection uses data from a 3-axis acceleration sensor attached to the body of an elderly person and learns about a total of 7 behavior patterns, each of which is a pattern that occurs in daily life, and the remaining 3 are patterns for falls. During training, a normalization process is performed to effectively reduce the loss function, and the normalization performs a maximum-minimum normalization for data and a L2 regularization for the loss function. The optimal regularization conditions of LSTM using several falling parameters obtained from the 3-axis accelerometer is explained. When normalization and regularization rate λ for sum vector magnitude (SVM) are 127 and 0.00015, respectively, the best sensitivity, specificity, and accuracy are 98.4, 94.8, and 96.9%, respectively.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.209-213
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• 2023

Currently, 2.4 GHz and 5 GHz bands are used as frequencies for drone operation. In December 2019, the Ministry of Science and ICT newly allocated the 433 MHz band for the invisible long-distance operation of drones. However, since the 433 MHz band is the same as the previously allocated frequency band for amateur radio communication, interference cannot be avoided. Therefore, as a prerequisite for the development of a drone operation system based on the 433 MHz band, interference avoidance technology for this frequency band must be developed and applied. In this paper, we report the results of measurement and analysis of 433 MHz band signals necessary for the development of interference avoidance and reduction technologies for 433 MHz signals. The measurement and analysis of the 433 MHz band signal are performed through the spectrum measured at 5-minute intervals at three locations. Since the measurements and analyzes performed in this study considered spatial characteristics, temporal characteristics, and traffic characteristics, it is considered to be the basic data necessary for the development of interference avoidance technology in the 433 MHz band.