• Journal of Korea Multimedia Society
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• v.22 no.8
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• pp.913-922
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• 2019

The Internet of Things (IoT) envisions smart objects collecting and sharing data at a massive scale via the Internet. One challenging issue is how to disseminate data to relevant data consuming objects efficiently. In such a massive IoT network, Mission critical data dissemination imposes constraints on the message transfer delay between objects. Due to the low power and communication range of IoT objects, data is relayed over multi-hops before arriving at the destination. In this paper, we propose a quorum-based adaptive dissemination algorithm (QADA) for the critical data in the monitoring-based applications of massive IoTs. To design QADA, we first design a new stepped-triangular grid structures (sT-grid) that support data dissemination, then construct a triangular grid overlay in the fog layer on the lower IoT layer and propose the data dissemination algorithm of the publish/subscribe model that adaptively uses triangle grid (T-grid) and sT-grid quorums depending on the mission critical in the overlay constructed to disseminate the critical data, and evaluate its performance as an analytical model.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.76-80
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• 2018

In recent years, with the development of automobile technology, smart system technology that assists safe driving has been developed. A camera is installed on the front and rear of the vehicle as well as on the left and right sides to detect and warn of collision risks and hazards. Beyond the technology of simple black-box recording via cameras, we are developing intelligent systems that combine various computer vision technologies. However, most related studies have been developed to optimize performance in laboratory-like environments that do not take environmental factors such as weather into account. In this paper, we propose a method to detect object by restoring visibility in image with degraded image due to weather factors such as fog. First, the image quality degradation such as fog is detected in a single image, and the image quality is improved by restoring using an intermediate value filter. Then, we used an adaptive feature extraction method that removes unnecessary elements such as noise from the improved image and uses it to recognize objects with only the necessary features. In the proposed method, it is shown that more feature points are extracted than the feature points of the region of interest in the improved image.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.3
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• pp.70-81
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• 2019

The effects of weather on aircraft operations are predominant. In particular, severe weather, such as fog, strong winds, rainfall and snow, can cause delays, diversion or cancellation of operations. Of these, fog is considered the main reason for restricting aircraft operations. Meanwhile, Precision instrument approach using instrument landing system(ILS) has allowed aircraft to land safely even in situations where visibility is limited. However, the precision instrument approach require not only the performance of the aircraft but also the enhancement of the runway. In November 2018, Gimpo international Airport raised the category of the runway 14R from CAT-IIIa to CAT-IIIb to improve aviation safety and operational efficiency. Based on this, the research presented a methodology for estimating benefits according to the category upgrade of the precision approach runway, and estimated the benefits to Gimpo International Airport based on the methodology presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1141-1163
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• 2019

In an effort to minimize operational expenses and supply users with more scalable services, distributed applications are actually going towards the Cloud. These applications, sent out over multiple environments and machines, are composed by inter-connecting independently developed services and components. The implementation of such programs on the Cloud is difficult and generally carried out either by hand or perhaps by composing personalized scripts. This is extremely error prone plus it has been found that misconfiguration may be the root of huge mistakes. We introduce AutoBot, a flexible platform for modeling, installing and (re)configuring complex distributed cloud-based applications which evolve dynamically in time. AutoBot includes three modules: A simple and new model describing the configuration properties and interdependencies of components; a dynamic protocol for the deployment and configuration ensuring appropriate resolution of these interdependencies; a runtime system that guarantee the proper configuration of the program on many virtual machines and, if necessary, the reconfiguration of the deployed system. This reduces the manual application deployment process that is monotonous and prone to errors. Some validation experiments were conducted on AutoBot in order to ensure that the proposed system works as expected. We also discuss the opportunity of reusing the platform in the transition of applications from Cloud to Fog computing.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_2
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• pp.1075-1080
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• 2020

The control on temperature and humidity on the cow-house is essential to assure production efficiency and the control on disease of cows. Fog system and screen fence are typical methods to drop the temperature inside of cow-house during the summer season. This study focused on the change in temperature and humidity under the condition of application of those methods. The results indicate that the installation of atomizer and insulation curtain cause decrease in temperature and increase in humidity. However, Using both of methods at the same time doesn't make any additional meaningful effects on temperature and humidity.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.103-112
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• 2022

This study aims to obtain empirical evidence regarding the link between tax avoidance (TA) and the readability of financial statements. This is a quantitative research using Ordinary Least Squares regression analysis which is then processed using STATA 14.0. A total of 278 companies listed on the Indonesia Stock Exchange during the period 2017-2019 is the data of this study. In detecting TA in a company, this study uses the ETR and CashETR and for the measurement of financial statement readability, this study uses gunning fog index and length of the document. The findings of this study suggest that tax avoidance and clear financial statements are mutually exclusive in the sense that when tax avoidance is practiced, companies will tend to conceal the information conveyed by financial statements. In other words, it is concluded that the more a company engages in tax avoidance, the lower the readability of the company's financial statements. This study provides in-depth evidence that tax avoidance is indirectly related to the disclosure of information by the company. Users of financial statements will realize that the company seeks to make disclosures that are in their best interests to avoid their tax avoidance strategy being detected.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.591-593
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• 2022

This paper proposes a partial offloading system for minimizing application service processing latency in an FEC (Fog/Edge Computing) environment, and it analyzes the offloading effect of the proposed system against local-only and edge-server-only processing based on network load. A partial offloading algorithm based on reconstruction linearization of multi-branch structures is included in the proposed system, as is an optimal collaboration algorithm between mobile devices and edge servers [1,2]. The experiment was conducted by applying layer scheduling to a logical CNN model with a DAG topology. When compared to local or edge-only executions, experimental results show that the proposed system always provides efficient task processing strategies and processing latency.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.96-110
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• 2017

Most of vehicle detection studies using the existing general lens or wide-angle lens have a blind spot in the rear detection situation, the image is vulnerable to noise and a variety of external environments. In this paper, we propose a method that is detection in harsh external environment with noise, blind spots, etc. First, using a fish-eye lens will help minimize blind spots compared to the wide-angle lens. When angle of the lens is growing because nonlinear radial distortion also increase, calibration was used after initializing and optimizing the distortion constant in order to ensure accuracy. In addition, the original image was analyzed along with calibration to remove fog and calibrate brightness and thereby enable detection even when visibility is obstructed due to light and dark adaptations from foggy situations or sudden changes in illumination. Fog removal generally takes a considerably significant amount of time to calculate. Thus in order to reduce the calculation time, remove the fog used the major fog removal algorithm Dark Channel Prior. While Gamma Correction was used to calibrate brightness, a brightness and contrast evaluation was conducted on the image in order to determine the Gamma Value needed for correction. The evaluation used only a part instead of the entirety of the image in order to reduce the time allotted to calculation. When the brightness and contrast values were calculated, those values were used to decided Gamma value and to correct the entire image. The brightness correction and fog removal were processed in parallel, and the images were registered as a single image to minimize the calculation time needed for all the processes. Then the feature extraction method HOG was used to detect the vehicle in the corrected image. As a result, it took 0.064 seconds per frame to detect the vehicle using image correction as proposed herein, which showed a 7.5% improvement in detection rate compared to the existing vehicle detection method.

• Journal of Bio-Environment Control
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• v.22 no.2
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• pp.138-145
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• 2013

In order to develop the efficient control algorithm of the two-fluid fogging system, cooling experiments for the many different types of fogging cycles were conducted in tomato greenhouses. It showed that the cooling effect was 1.2 to $4.0^{\circ}C$ and the cooling efficiency was 8.2 to 32.9% on average. The cooling efficiency with fogging interval was highest in the case of the fogging cycle of 90 seconds. The cooling efficiency showed a tendency to increase as the fogging time increased and the stopping time decreased. As the spray rate of fog in the two-fluid fogging system increased, there was a tendency for the cooling efficiency to improve. However, as the inside air approaches its saturation level, even though the spray rate of fog increases, it does not lead to further evaporation. Thus, it can be inferred that increasing the spray rate of fog before the inside air reaches the saturation level could make higher the cooling efficiency. As cooling efficiency increases, the saturation deficit of inside air decreased and the difference between absolute humidity of inside and outside air increased. The more fog evaporated, the difference between absolute humidity of inside and outside air tended to increase and as the result, the discharge of vapor due to ventilation occurs more easily, which again lead to an increase in the evaporation rate and ultimately increase in the cooling efficiency. Regression analysis result on the saturation deficit of inside air showed that the fogging time needed to change of saturation deficit of $10g{\cdot}kg^{-1}$ was 120 seconds and stopping time was 60 seconds. But in order to decrease the amplitude of temperature and to increase the cooling efficiency, the fluctuation range of saturation deficit was set to $5g{\cdot}kg^{-1}$ and we decided that the fogging-stopping time of 60-30 seconds was more appropriate. Control types of two-fluid fogging systems were classified as computer control or simple control, and their control algorithms were derived. We recommend that if the two-fluid fogging system is controlled by manipulating only the set point of temperature, humidity, and on-off time, it would be best to set up the on-off time at 60-30 seconds in time control, the lower limit of air temperature at 30 to $32^{\circ}C$ and the upper limit of relative humidity at 85 to 90%.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.429-440
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• 2021

During the growing period, the integrated solar radiation inside the greenhouse was 12.7MJ·m^-2d^-1, and which was 90% of the average daily global radiation outside the greenhouse, 14.1MJ·m^-2d^-1. The 24-hour average temperature inside the greenhouse from July to August, which has the highest temperature of the year, was 3.04℃ lower than the outside temperature, and 4.07℃ lower after the rainy season. Before the operation of fog cooling system, the average daily RH (%) was lowered to a minimum of 40% (20% for daytime), making it inappropriate for paprika cultivation, but after the operation of fog system, the daily RH during the daytime increased to 70 to 85%. The average humidity deficit increased to a maximum of 12.7g/m³ before fog supply, but decreased to 3.7g/m³ between July and August after fog supply, and increased again after October. The daytime residual CO₂ concentration inside the greenhouse was 707 ppm on average during the whole growing period. The marketable yield of paprika harvested from July 27th to November 23rd, 2020 was higher in 'DSP-7054' and 'Allrounder' with 14,255kg/10a and 14,161kg/10a, respectively, followed by 'K-Gloria orange', 'Volante' and 'Nagono'. There were significant differences between paprika cultivars in fruit length, fruit diameter, soluble solids (°Brix), and flash thickness (mm) of paprika produced in summer season at large single-span plastic greenhouse. The soluble solids content was higher in the orange cultivars 'DSP-7054' and 'Naarangi' and the flesh thickness was higher in the yellow and orange cultivars, with 'K-Gloria orange' and 'Allrounder' being the thickest. The marketable yield of paprika, which was treated with cooling and heating treatments in the root zone, increased by 16.1% in the entire cultivars compared to the untreated ones, increased by 16.5% in 'Nagano', 10.3% in the 'Allrounder', 20.2% in the 'Naarangi', and 17.3% in 'Raon red'.