• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.431-439
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• 2021

Since the sensor nodes are randomly arranged in the region of interest, it may happen that the sensor network area is separated or there is no sensor node in some area. In addition, after the sensor nodes are deployed in the sensor network, a coverage hole may occur due to the exhaustion of energy or physical destruction of the sensor nodes. The coverage hole can greatly affect the overall performance of the sensor network, such as reducing the data reliability of the sensor network, changing the network topology, disconnecting the data link, and worsening the transmission load. Therefore, sensor network coverage hole recovery has been studied. Existing coverage hole recovery studies present very complex geometric methods and procedures in the two-step process of finding a coverage hole and recovering a coverage hole. This study proposes a method for discovering and recovering a coverage hole in a sensor network, discovering that the sensor node is a boundary node by itself, and determining the location of a mobile node to be added. The proposed method is expected to have better efficiency in terms of complexity and message transmission compared to previous methods.

• Journal of Distribution Science
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• v.18 no.4
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• pp.39-50
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• 2020

Purpose: This paper aimed to study the current locations of post offices to analyze service coverage area for parcel delivery in the Eastern Economics Corridor (EEC), which must be considered in the last mile to extend delivery service for e-commerce growth. Thailand Post was the case study in this paper. Research design, data and methodology: To involve solving the delivery service area under the last mile condition, the authors proposed a network analysis to determine service radius by employing a Geographic Information System (GIS). Furthermore, this paper applied Dijkstra's algorithm as a network analysis tool from GIS for analyzing the last mile service coverage area in a new economics zone. At the same time, the authors suggested an approach as a solution to locate last mile delivery center in EEC. Results: The results of the study pointed out that Thailand Post should consider more last mile delivery centers in EEC to support its express service in urban areas as well as improve the efficiency of service coverage for parcel delivery and create more advantages against competitors. Conclusions: This paper proposes a network analysis to extend the last mile service for parcel delivery by following Dijkstra's algorithm from GIS and a solution approach to add more last mile delivery centers. The results of the research will contribute to boosting customer satisfaction for last mile delivery service and enabling easy accessibility to a service center in EEC.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.304-309
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• 2007

This paper describes an efficient path generation method for area coverage. Its applications include robots for de-mining, cleaning, painting, and so on. Our method is basically based on a divide and conquer strategy. We developed a novel cell decomposition algorithm that divides a given area into several cells. Each cell is covered by a robot motion that requires minimum time to cover the cell. Using this method, completeness and time efficiency of coverage are easily achieved. For the completeness of coverage in dynamic environments, we also propose a path following method that makes the robot cover missed areas as a result of the presence of unknown obstacles. The effectiveness of the method is verified using computer simulations.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.64-72
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• 2016

The coverage area of a GNSS regional ionospheric delay model is mainly determined by the distribution of GNSS ground monitoring stations. Extrapolation of the ionospheric model data can extend the coverage area. An extrapolation algorithm, which combines observed ionospheric delay with the environmental parameters, is proposed. Neural network and least square regression algorithms are developed to utilize the combined input data. The bi-harmonic spline method is also tested for comparison. The IGS ionosphere map data is used to simulate the delays and to compute the extrapolation error statistics. The neural network method outperforms the other methods and demonstrates a high extrapolation accuracy. In order to determine the directional characteristics, the estimation error is classified into four direction components. The South extrapolation area yields the largest estimation error followed by North area, which yields the second-largest error.

• Korean Journal of Agricultural Science
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• v.50 no.3
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• pp.427-435
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• 2023

This study was conducted to evaluate the spraying performance according to the flight conditions of agricultural drones for the development of a variable control system. The analyzed flight conditions comprised six factors: spraying direction, flight speed, altitude, wind speed, wind direction, and rotor rotational speed. The ratio of the area sprayed on the water-sensitive paper was used as the coverage, and the distribution and amount of the coverage were evaluated. The coverage distribution based on the distance from the drone was used to evaluate a spray pattern, and the distribution was expressed as a Gaussian function approximation. In addition, the probability distribution based on coverage was expressed as the cumulative probability via Gamma function approximation to analyze the spraying efficiency in the target area. The results showed that the averaged coverage decreased significantly as the flight speed and wind speed increased, and the wind direction changed the spray pattern without a coverage decrease. This study contributes to the development of a control technique for the precision control system of agricultural drones.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.1
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• pp.80-86
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• 2007

The concept of the coverage has been played an important role in the area of reliability evaluation of a system. The widely used measures of reliability include the m time between failures, the availability and so on. In this paper, we propose an estimator of the coverage probability in a redundant system with a control unit and investigate some moments of the proposed estimator. And assuming exponential distribution of all units, we conduct a simulation study for calculating the estimates of the coverage probability and its confidence bounds. An example of evaluating the availability of an optical transportation system is illustrated.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1757-1766
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• 2021

The green coverage ratio is the ratio of the land area to green coverage area, and it is used as a practical urban greening index. The green coverage ratio is calculated based on the land cover map, but low spatial resolution and inconsistent production cycle of land cover map make it difficult to calculate the correct green coverage area and analyze the precise green coverage. Therefore, this study proposes a new method to calculate green coverage area using aerial images and deep neural networks. Green coverage ratio can be quickly calculated using manned aerial images acquired by local governments, but precise analysis is difficult because components of image such as acquisition date, resolution, and sensors cannot be selected and modified. This limitation can be supplemented by using an unmanned aerial vehicle that can mount various sensors and acquire high-resolution images due to low-altitude flight. In this study, we proposed a method to calculate green coverage ratio from manned or unmanned aerial images, and experimentally verified the proposed method. Aerial images enable precise analysis by high resolution and relatively constant cycles, and deep learning can automatically detect green coverage area in aerial images. Local governments acquire manned aerial images for various purposes every year and we can utilize them to calculate green coverage ratio quickly. However, acquired manned aerial images may be difficult to accurately analyze because details such as acquisition date, resolution, and sensors cannot be selected. These limitations can be supplemented by using unmanned aerial vehicles that can mount various sensors and acquire high-resolution images due to low-altitude flight. Accordingly, the green coverage ratio was calculated from the two aerial images, and as a result, it could be calculated with high accuracy from all green types. However, the green coverage ratio calculated from manned aerial images had limitations in complex environments. The unmanned aerial images used to compensate for this were able to calculate a high accuracy of green coverage ratio even in complex environments, and more precise green area detection was possible through additional band images. In the future, it is expected that the rust rate can be calculated effectively by using the newly acquired unmanned aerial imagery supplementary to the existing manned aerial imagery.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.8 no.6
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• pp.69-79
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• 2005

This study was carried out to select proper species for early stage replantation in highway cut-slope area. In highway cut-slope area, sample plots of 106 were selected, and their vegetations and environmental factors were investigated. 1. We found total 172 species in the 106 cutting area of highway. The species of high frequency of highway cut-slope were found in the order of Lespedeza bicolor, Artemisia princeps var. orientalis, Festuca arundinacea, Erigeron annuus, Lespedeza cuneata, Lactuca indica var. laciniata, Eragrostis curvula, Dactylis glomerata, Oenothera lamarckiana, Wistaria floribunda, Humulus japonica, Commelina communis, Miscanthus sinensis, Pueraria thunbergiana, Pinus densiflora, etc. 2. The average vegetation coverage was over 90% in the study sites and the average coverage was 91.4% in the total cut-slope area. The species of high coverage of highway cut-slope area were found in the order of Festuca arundinacea, Eragrostis curvula, Lespedeza bicolor, Wistaria floribunda, Lespedeza cuneata, Dactylis glomerata, Artemisia princeps var. orientalis, Humulus japonica, Pueraria thunbergiana, Robinia pseudoacacia, Poa pratensis, Medicago sativa, Festuca ovina, Pinus densiflora, Parthenocissua tricuspidata, etc. 3. The total coverage in the foreign plants of Festuca arundinacea, Eragrostis curvula, Dactylis glomerata, Poa pratensis, Medicago sativa, Coreopsis drummondii and native plants of Lespedeza bicolor, Wistaria floribunda, Lespedeza cuneata, Amorpha fruticosa, Indigofera pseudotinctoria, Lespedeza cyrtobotrya were 57.52%. That is, the ecological succession of native herbs and parachute shrubs have delayed because the afforested plants occupy 57.52%. In future, the coverage of foreign herbs have to reduce, and the coverage of the native herbs and parachute shrubs must be increased. 4. The native seed of Artemisia sp., Miscanthus sinensis, Smilax china, Pueraria thunbergiana, Rubus crataegifolius, Rubus parvifolius, Pinus densiflora, Rhus chinensis, Albizzia julibrissin, Rhododendron mucronulatum, Clematis apiifolia, Zanthoxylum schinifolium, Prunus sargentii could be added in the seedling of the temperate south zone highway with the used seeds. The native seed of Artemisia sp., Miscanthus sinensis, Rubus crataegifolius, Rhododendron mucronulatum, Weigela subsessilis, Stephanandra incisa, Rhus chinensis, Pinus densiflora, Salix koreensis, Cocculus trilobus, Populus alba, Spiraea prunifolia for. simpliciflora, Clematis apiifolia, Lindera obtusiloba, Quercus serrata, etc., could be added in the seedling of the temperate middle zone highway with the used seeds. 5. We have some recommendation. The native plants have to growth in the highway cut-slope area instead of foreign plants to have good environmental ecology. The role of the foreign plants should be the plant for the initial several years in the highway cut-slope area. And, the native plants should growth in the next season. 6. We should protect shrubs and trees in the highway slope area because shrubs and trees can be more helpful in stabilizing of the slope area than herbs.

• Membrane and Water Treatment
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• v.10 no.1
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• pp.57-65
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• 2019

This study assessed the contribution of emergent vegetation (Phragmites australis, Typha latifolia, and Nelumbo nucifera) to the submerged surface area, the amount of biofilms attached to the submerged portions of the plants, and the treatment performance of a free water surface (FWS) constructed wetland. Results showed that a 1% increase ($31m^2$) in the vegetative area resulted in an increase of $220m^2$ of submerged surface area, and 0.48 kg Volatile Suspended Solids (VSS) of attached biofilm. As the vegetation coverage increased, effluent organic matter and total Kjeldahl nitrogen decreased. Conversely, a higher nitrate concentration was found in the effluent as a result of increased nitrification and incomplete denitrification, which was limited by the availability of a carbon source. In addition, a larger vegetation coverage resulted in a higher phosphorus in the effluent, most likely released from senescent biofilms and sediments, which resulted from the partial suppression of algal growth. Based on the results, it was recommended that constructed wetlands should be operated with a vegetation coverage of just under 50% to maximize pollutant removal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7A
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• pp.697-705
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• 2010

In Wireless Sensor Networks (WSNs), blanket (area) coverage analysis is generally carried to find the minimum number of active sensor nodes required to cover a monitoring interest area with the desired fractional coverage-threshold. Normally, the coverage analysis is performed using the stochastic geometry as a tool. The major component of such coverage analysis is the assumed sensing model. Hence, the accuracy of such analysis depends on the underlying assumption of the sensing model: how well the assumed sensing model characterizes the real sensing phenomenon. In this paper, we review the coverage analysis for different deterministic and probabilistic sensing models like Boolean and Shadow-fading model; and extend the analysis for Exponential and hybrid Boolean-Exponential model. From the analytical performance comparison, we demonstrate the redundancy (in terms of number of sensors) that could be resulted due to the coverage analysis based on the detection capability mal-characterizing sensing models.