• Journal of the Korean Society of Environmental Restoration Technology
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• v.16 no.6
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• pp.135-143
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• 2013

Ultrasonic mist fogger and the fan were used for investigating the availability of fog circulation system in greenwall and the potential growing ability of the plant. The mist caused by ultrasonic mist fogger was circulated by the fan through the pipeline and supplied to the pots containing plants. Moisture content of the 3 different soils was measured at different irrigation time points. The moisture content of 15-26% in PP and Co soil was maintained at irrigation of 24H, 18H, 12H in a day. Proper growth condition was found in Ardisia pusilla and Hosta plantaginea at the height of L level after 1 month of growth when the plants were irrigated by the fog circulation system. The results suggest that the fog circulation, by ultrasonic mist fogger to the green walls is system of choice for suppling moisture to plants.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.881-902
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• 2024

Fast decision support systems and accurate diagnosis have become significant in the rapidly growing healthcare sector. As the number of disparate medical IoT devices connected to the human body rises, fast and interrelated healthcare data retrieval gets harder and harder. One of the most important requirements for the Healthcare Internet of Things (HIoT) is semantic interoperability. The state-of-the-art HIoT systems have problems with bandwidth and latency. An extension of cloud computing called fog computing not only solves the latency problem but also provides other benefits including resource mobility and on-demand scalability. The recommended approach helps to lower latency and network bandwidth consumption in a system that provides semantic interoperability in healthcare organizations. To evaluate the system's language processing performance, we simulated it in three different contexts. 1. Polysemy resolution system 2. System for hyponymy-hypernymy resolution with polysemy 3. System for resolving polysemy, hypernymy, hyponymy, meronymy, and holonymy. In comparison to the other two systems, the third system has lower latency and network usage. The proposed framework can reduce the computation overhead of heterogeneous healthcare data. The simulation results show that fog computing can reduce delay, network usage, and energy consumption.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.837-839
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• 2012

When the for occurred, the driver does not get the vision is has difficult on driving. In this case, the probability of occurrence of accidents are very high level. To reduce accidents, this system provide drivers with the safety of ensure to measures that a service inform current situation. in this paper, the crash occur in fog to prevent accident using vehicle safety system to give a alarm and control. The proposed system is installed on the outside of the vehicle, humidity, and ambient light sensors inside the car from the information collected by the system controller for the detection of fog conditions using video equipment and then finally the fog occurs if you do not get the driver's field of events is causing the system.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1317-1328
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• 2021

This study analyzes the early satellite mission marine fog detection results from Geostationary Ocean Color Imager-II (GOCI-II). We investigate optical characteristics of the GOCI-II spectral bands for marine fog between October 2020 and March 2021 during the overlapping mission period of Geostationary Ocean Color Imager (GOCI) and GOCI-II. For Rayleigh-corrected reflection (R_rc) at 412 nm band available for the input of the GOCI-II marine fog algorithm, the inter-comparison between GOCI and GOCI-II data showed a small Root Mean Square Error (RMSE) value (0.01) with a high correlation coefficient (0.988). Another input variable, Normalized Localization Standard (NLSD), also shows a reasonable correlation (0.798) between the GOCI and GOCI-II data with a small RMSE value (0.007). We also found distinctive optical characteristics between marine fog and clouds by the GOCI-II observations, showing the narrower distribution of all bands' R_rc values centered at high values for cloud compared to marine fog. The GOCI-II marine fog detection distribution for actual cases is similar to the GOCI but more detailed due to the improved spatial resolution from 500 m to 250 m. The validation with the automated synoptic observing system (ASOS) visibility data confirms the initial reliability of the GOCI-II marine fog detection. Also, it is expected to improve the performance of the GOCI-II marine fog detection algorithm by adding sufficient samples to verify stable performance, improving the post-processing process by replacing real-time available cloud input data and reducing false alarm by adding aerosol information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.281-298
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• 2020

Fog computing has become a popular concept in the application of internet of things (IoT). With the superiority in better service providing, the edge cloud has become an attractive solution to IoT networks. The data outsourcing scheme of IoT devices demands privacy protection as well as computation verification since the lightweight devices not only outsource their data but also their computation. Existing solutions mainly deal with the operations over encrypted data, but cannot support the computation verification in the same time. In this paper, we propose a data outsourcing scheme based on an encrypted database system with linear computation as well as efficient query ability, and enhance the interlayer program in the original system with homomorphic message authenticators so that the system could perform computational verifying. The tools we use to construct our scheme have been proven secure and valid. With our scheme, the system could check if the cloud provides the correct service as the system asks. The experiment also shows that our scheme could be as effective as the original version, and the extra load in time is neglectable.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1551-1558
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• 2022

We propose a two-tier cooperative computing system comprised of a mobile device and an edge server for partial offloading of multi-branch structures in Fog/Edge Computing environments in this paper. The proposed system includes an algorithm for splitting up application service processing by using reconstructive linearization techniques for multi-branch structures, as well as an optimal collaboration algorithm based on partial offloading between mobile device and edge server. Furthermore, we formulate computation offloading and CNN layer scheduling as latency minimization problems and simulate the effectiveness of the proposed system. As a result of the experiment, the proposed algorithm is suitable for both DAG and chain topology, adapts well to different network conditions, and provides efficient task processing strategies and processing time when compared to local or edge-only executions. Furthermore, the proposed system can be used to conduct research on the optimization of the model for the optimal execution of application services on mobile devices and the efficient distribution of edge resource workloads.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.125-138
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• 2011

The highway visibility reduction caused by fog is one of the major elements of traffic accidents. Though the fog warning systems can lead drivers into safe driving by letting them aware dangerous situations in advance, the optical sensors, such as fog sensor, has been extremely costly. Through recent studies, it is delivered that visibility measurements have become obtainable with relatively cheap cameras and their functionality is as similar as a driver' visual sense. Those measurements however require additional signs or ROI, so it is still costly and unable to utilize the conventional images from the existing systems. This study proposes a new method to detect the visibility in real time based on the conventional images from the existing CCTV cameras. The proposed method builds a road model and extracts and applies vehicle movements and visible lines - those highlight easy and quick visibility measurements. The proposed method has advantages of both (1) having possible day and night visibility measurements similar to drivers' visual sense and (2) being easily applied to the existing CCTV system without additional devices. This paper presents field experiments using images acquired from the Central Inland Expressway and discusses future research directions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2355-2362
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• 2016

Seg fog removal is an important issue concerned by both computer vision and image processing. Sea fog or haze removal is widely used in lots of fields, such as automatic control system, CCTV, and image recognition. Color image dehazing techniques have been extensively studied, and expecially the dark channel prior(DCP) technique has been widely used. This paper propose a fast and efficient image prior - dark channel prior to remove seg-fog from a single digital image based on the GPU. We implement the basic parallel program and then optimize it to obtain performance acceleration with more than 250 times. While paralleling and the optimizing the algorithm, we improve some parts of the original serial program or basic parallel program according to the characteristics of several steps. The proposed GPU programming algorithm and implementation results may be used with advantages as pre-processing in many systems, such as safe navigation for ship, topographical survey, intelligent vehicles, etc.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.35-57
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• 2021

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.

• Journal of Korean Society of Forest Science
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• v.96 no.6
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• pp.676-683
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• 2007

In an attempt to develop an efficient method for the propagation of mature Prunus yedoensis (45 to 55 years old), green wood cuttings from normal branch and sprouts branch were treated with three different kinds of auxin (Rootone < 1-naphthylacetamide 0.4% >, IBA 100 ppm, and control and two different kinds of fog systems (0.9 L/min. and 0.54 L/min.). The Rootone treatment showed higher values in the percentage of rootings (PR) and the mean number of roots per cutting (NR) than the IBA treatment in the early stage. However, in the late stage, the values of PR and NR in the Rootone treatment become lower than those in the IBA 100 ppm treatment. On the other hand, root development ceased 62 days after taking cuttings for all of the treatments. The IBA 100 ppm treatment showed the best performance in root development (PR= 89.5%, NR = 6.5, LR=6.4 cm). The values of PR (76.5%) and NR (6.4) in the 0.9 L/min. of fog treatment was higher than those (PR = 71.7% and NR = 5.4) in the 0.54 L/min. of fog treatment. The cuttings from sprouts (PR: 74.8%, NR: 5.9, LR: 5.7 cm) showed slightly better performance in rooting rate that the cuttings from shoots (PR : 73.3%, NR: 5.9, LR: 5.4 cm). Statistically significant interactions were presented among most of the different combinations of three factors (auxin treatments, fog treatments, and types of cuttings). The PR showed the highest value of 98.0% in the combination of cuttings of shoots+IBA 100 ppm+0.54 L/min. fog treatments. In case of NR, the cuttings from normal branch showed a higher value than the cuttings from sprouts branch under the fog treatment of 0.9 L/min., while this tendency was reversed under the fog treatment of 0.54 L/min.. The perigon development of roots, which reflects the number and the direction of roots, was best in the IBA treatment (85.6%).