• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.696-706
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• 2008

In this paper we show the performance of the network-adaptive high-definition scalable video streaming using QWLAN board with IEEE 802.11e MAC monitoring and control. Realtime collected MAC parameters are used to determine which video data is extracted for the predicted available bandwidth. To achieve performance, extraction through R-D is proposed instead of the standard video packet extraction. It is shown through experiments that streaming video quality can be enhanced by fast adaptation to network conditions by using the proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.39-43
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• 2020

In this paper, we propose the multi-channel interference cancellation algorithm for visible light communication (VLC) in smart building. The VLC system is communication technology using visible rays that come out in Light Emitting Diode (LED) device. It has energy curtailment effect and possible to use in ubiquitous network service applications. When a large number of users communicate indoors, the performance can be reduced due to channel interference. To remove interference, at the first, the minimum mean square error (MMSE) scheme as interference cancellation methods used, and then the successive interference cancellation (SIC) is applied to obtain additional diversity gain and improve interference cancellation performance. Indoor VLC channel model is employed. The performance is evaluated in terms of bit error rate (BER). From the simulation results, it is confirmed that the proposed scheme has better BER performance compared to the previous systems. As a result, the proposed interference cancellation improves the signal quality of VLC systems by effectively removing the channel noise. The results of the paper can be applied to VLC for smart building and general communication systems.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.5
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• pp.229-234
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• 2017

Because of the invisible nature of software and the bad coding habits (bad smell) of the existing developers, there are many redundant codes and unnecessary codes, which increases the complexity and makes it difficult to upgrade software. Therefore, it is required a code visualization so that developers can easily and automatically identify the complexity of the source code. To do this, it is necessary to construct SW visualization tool based on open source software and redefine the coupling and cohesion according to the object oriented viewpoint. Specially to identify a bad smell code pattern, we suggest how to plug-in diverse parsers within our tool. In this paper, through redefining coupling and cohesion from an object oriented perspective, we will extract bad smell code patterns within source code from inputting any pattern into the tool.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.473-480
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• 2019

The smart home is a technology that can monitor and control by connecting everything to a communication network in various fields such as home appliances, energy consumers, and security devices. The Smart home is developing not only automatic control but also learning situation and user's taste and providing the result accordingly. This paper proposes a model that can provide a comfortable indoor environment control service for the user's characteristics by detecting the user's behavior as well as the automatic remote control service. The whole system consists of ESP 8266 with sensor and Wi-Fi, Firebase as a real-time database, and a smartphone application. This model is divided into functions such as learning mode when the home appliance is operated, learning control through learning results, and automatic ventilation using indoor and outdoor sensor values. The study used moving averages for temperature and humidity in the control of home appliances such as air conditioners, humidifiers and air purifiers. This system can provide higher quality service by analyzing and predicting user's characteristics through various machine learning and deep learning.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.6
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• pp.211-222
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• 2021

Recently, frozen and refrigerated appliances on the market are being released with additional IoT functions, but there are few tests on IoT functions. In particular, the existing test system does not have IoT test items for IoT-based frozen and refrigerated appliances, making it difficult for companies to find the cause even if defects occur, and test institutions are also restricted from selecting IoT-related test items and conducting correct performance tests. In this paper, we design a test item framework that can identify product defects and identify causes in the performance test process of frozen and refrigerated products with IoT functions among products in the home appliance field, and propose test methods and management measures using them. Through the proposed research, manufacturers and testing institutions can test the correct performance of IoT-based frozen and refrigerated products, thereby enhancing the completeness and securing reliability of the products.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.327-336
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• 2019

Soybean is one of the most important crops of which the grains contain high protein content and has been consumed in various forms of food. Soybean plants are generally cultivated on the field and their yield and quality are strongly affected by climate change. Recently, the abnormal climate conditions, including heat wave and heavy rainfall, frequently occurs which would increase the risk of the farm management. The real-time assessment techniques for quality and growth of soybean would reduce the losses of the crop in terms of quantity and quality. The objective of this work was to develop a simple model to estimate the growth of soybean plant using a multispectral sensor mounted on a rotor-wing unmanned aerial vehicle(UAV). The soybean growth model was developed by using simple linear regression analysis with three phenotypic data (fresh weight, dry weight, leaf area index) and two types of vegetation indices (VIs). It was found that the accuracy and precision of LAI model using GNDVI (R²= 0.789, RMSE=0.73 ㎡/㎡, RE=34.91%) was greater than those of the model using NDVI (R²= 0.587, RMSE=1.01 ㎡/㎡, RE=48.98%). The accuracy and precision based on the simple ratio indices were better than those based on the normalized vegetation indices, such as RRVI (R²= 0.760, RMSE=0.78 ㎡/㎡, RE=37.26%) and GRVI (R²= 0.828, RMSE=0.66 ㎡/㎡, RE=31.59%). The outcome of this study could aid the production of soybeans with high and uniform quality when a variable rate fertilization system is introduced to cope with the adverse climate conditions.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.889-898
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• 2013

Due to the popularization of high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy to make high-quality counterfeit money. However, the probability of detecting counterfeit money to the general public is extremely low and the detection device is expensive. In this paper, a counterfeit money detection algorithm using a general purpose scanner and computer system is proposed. First, the printing features of color printers are calculated using morphological operations and gray-level co-occurrence matrix. Then, these features are used to train a support vector machine classifier. This trained classifier is applied for identifying either original or counterfeit money. In the experiment, we measured the detection rate between the original and counterfeit money. Also, the printing source was identified. The proposed algorithm was compared with the algorithm using wiener filter to identify color printing source. The accuracy for identifying counterfeit money was 91.92%. The accuracy for identifying the printing source was over 94.5%. The results support that the proposed algorithm performs better than previous researches.

• Journal of Aerospace System Engineering
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• v.12 no.3
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• pp.86-96
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• 2018

The High Agility and Remote Control Camera System Can-Satellite ($HA+RC^2S$ CanSat) proposed in this study is a satellite designed by the authors of this work and submitted as an entry in the 2017 CanSat competition in Goheung gun, Jeonnam, Korea. The primary mission of this work is to develop a high agility camera system (HACS) that can obtain high quality images in the air. This objective is achieved by using a tuned mass damper (TMD) to attenuate the residual vibration that occurs immediately after rotating the camera. The secondary objective is to obtain a self-image of CanSat in the air using a remote control self-camera system (RCSS) that is wirelessly controlled using a joystick from a ground station. This paper describes the development process of the $HA+RC^2S$ CanSat, including mission definition, system design, manufacturing, function and performance tests carried out on the ground, and final launch test.

• Journal of the Korea Concrete Institute
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• v.28 no.5
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• pp.611-620
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• 2016

In the construction of nuclear power plants, only 420 MPa reinforcing bars are allowed and, therefore, so many large-diameter bars are placed, which results in steel congestion. Consequently, re-bar works are difficult and the quality of RC structures may be deteriorated. To solve the steel congestion, 550 MPa bars are necessary. Among many items for verifying structural performance of reinforced concrete with 550 MPa bars, the 43 mm hooked bars are examined in this study. All specimens failed by side-face blowout and the side cover explosively spalled at maximum loads. The bar force was initially transferred to the concrete primarily by bond along a straight portion. At the one third of maximum load, the bond reached a peak capacity and began to decline, while the hook bearing component rose rapidly. At failure, most load was resisted by the hook bearing. For confined specimens with hoops, the average value of test-to-prediction ratios by KCI code is 1.45. The modification factor of confining reinforcement which was not allowed for larger than 35 mm bars can be applied to 43 mm hooked bars. For specimens with 70 MPa concrete, the average value of test-to-prediction ratios by KCI code is 1.0 which is less than the values of the other specimens. The effects of concrete compressive strength should be reduced. An equation to predict anchorage capacity of hooked bars was developed from regression analysis including the effects of compressive strength of concrete, embedment length, side cover thickness, and transverse reinforcement index.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.21-29
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• 2018

The purpose of this study is to explore supporting strategies for teaching and learning based on students' effect recognition and continuous intention in college flipped learning. It was analyzed 426 data by multivariate analysis of variance (MANOVA) by examining student's effect recognition and continuous intention on 15 flipped learning classes of K-university in Chungnam. The characteristics of learners were male, senior students, students who knew flipped learning, students who did not have previous experience, and students who were learning video at anytime. As a teaching strategy, it was found that effect recognition and continuous intention were high in the supplementary deepening flipped learning class and natural science or engineering area. As a teaching and learning supporting strategies, First, the university should develop and operate flipped class learning strategy program for females and low-grade students. Second, it should support the development of good flipped learning design and operation model of instructor. Third, it should support the development of high quality online learning contents that students can learn from time to time. Fourth, it should support the strengthening of teaching competency to develop and operate flipped learning classes. This study can be used as basic data to support and spread the effective flipped learning classes of the university in the future.