• The Korean Journal of Mycology
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• v.39 no.2
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• pp.148-150
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• 2011

Cordyceps militaris(CM) has been used as a traditional folk medicine to strengthen the immune system and regain energy for hundreds of years in Far East Asian countries. In the present studies, we determined that the stimulatory effect of Cordyceps militaris on testosterone production in male mouse rats. Results illustrated that changes of the body weight, food and water intake of the rats were not observed in this study but the concentration of testosterone in the serum of the rats was significantly increased by CM(p < 0.05). Therefore fruiting bodies of CM grown on the drone bee medium may be an integrative medicine for the treatment of reproductive problems caused by insufficient testosterone levels in human males.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.9-14
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• 2019

In modern society drones are actively utilized in the fields of security, defense, agriculture, communication and so on. Smart technology and artificial intelligence software have been developed with convergence, and the field of use is expected to expand further. On the point of the excellent performance of drones one of the essential technologies is the wireless communication that make the ground facility receive the video streaming obtained by the drones in the air. In the research the concept of communication region is proposed to cover the both the low altitude region for Wi-Fi communication and the high altitude region for LTE communication for the sake of video transmission. Also the hybrid communication structure is designed along the proposed concept and the proposed system is implemented as a communication system in the small size which can be mounted in a small size of drone. It is confirmed that the proposed system contains the effectiveness by showing the ability to successfully transmit HD video streaming in the range of 500 meters and the transfer time between two different communication systems is measured in 200msec by the experiments.

• Convergence Security Journal
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• v.18 no.5_2
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• pp.3-10
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• 2018

The drone is an unmanned aircraft that can be steered and controlled using radio waves on the ground, and the pilot moves unmanned without boarding. The history of the unmanned airplane began with military use, and the first unmanned aerial flight was the first successful flight of the 'Sperry Aerial Torpedo' drones built in the United States in 1917 with a bomb. With the development of unmanned aerial technology, the use of military drones has expanded to a wider field. Recently, the use of drones has been utilized in various fields such as agriculture, industry, logistics, broadcasting, and safety, and the scale of the market is also expanding. Although the drones are becoming indispensable to penetrate our lives, they can be used for bad purposes depending on the intended use of the user, but the risk factors are overlooked. Therefore, technical defects related to drones and accidents caused by operator's mistakes can not be completely prevented. However, privacy infringement, security leakage, and terrorism, which may be caused by illegal use of drones, It will not be inhibited and will accelerate.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.565-572
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• 2018

Recently, UAVs (Unmanned Aerial Vehicles) or drones have gained popularity for the engineering surveying and mapping because they enable the rapid data acquisition and processing as well as their operation cost is low. The applicable fields become much wider including the topographic monitoring, agriculture, and forestry. It is reported that the high geospatial accuracy is achievable with the drone photogrammetry for many applications. However most studies reported the best achievable mapping results using well-distributed ground control points though some studies investigated the impact of control points on the accuracy. In this study, we focused on the drone mapping of corridors such as roads and pipelines. The distribution and the number of control points along the corridor were diversified for the accuracy assessment. In addition, the effects of the camera self-calibration and the number of the image strips were also studied. The experimental results showed that the biased distribution of ground control points has more negative impact on the accuracy compared to the density of points. The prior camera calibration was favored than the on-the-fly self-calibration that may produce poor positional accuracy for the case of less or biased control points. In addition, increasing the number of strips along the corridor was not helpful to increase the positional accuracy.

• The Korean Journal of Food And Nutrition
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• v.31 no.6
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• pp.802-810
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• 2018

This study estimated the effect of drone pupa meal (DPM) added as replacement of sodium nitrite (SN) and vitamin C (VC) on physico-chemical quality characteristics of emulsion-type sausages. Samples were prepared either with 150 ppm SN+200 ppm VC (control); 75 ppm SN+100 ppm VC+6.015% DPM (T1); or 12.03% DPM (T2) and then stored at $4^{\circ}C$ for 30 days. The pH value decreased (p<0.05) with increase in the levels of DPM. Moisture and protein content decreased (p<0.05) but fat and ash content increased (p<0.05) with higher levels of DPM. T1 and T2 had higher (p<0.05) saturated fatty acids content and lower (p<0.05) unsaturated and polyunsaturated fatty acids content compared to the control. Lower (p<0.05) $L^*$ and $a^*$ values and higher (p<0.05) $b^*$ and $h^{\circ}$ values were exhibited in the T1 and T2 than in the control; and $C^*$ value was the lowest (p<0.05) in T2. The TBARS content was the highest (p<0.05) in T2, especially, 2 times higher (p<0.05) than in the control. T1 and T2 had harder (p<0.05) texture compared to the control. These findings suggest that the DPM has no replacement effects against SN and VC in emulsion-type sausage, but it has negative effects on color, lipid oxidation stability, and texture.

• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.133-143
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• 2023

As drones (also known as UAV) become popular with advanced information and communication technology (ICT), they have been utilized for various fields (agriculture, architecture, and so on). However, malicious attackers with advanced drones may pose a threat to critical national infrastructures. Thus, anti-drone systems have been developed to respond to drone threats. In particular, remote identification data (R-ID)-based UAV detection and identification systems that detect and identify illegal drones with R-ID broadcasted by drones have been developed, and are widely employed worldwide. However, this R-ID-based UAV detection/identification system is vulnerable to security due to wireless broadcast characteristics. In this paper, we analyze the security vulnerabilities of DJI Aeroscope, a representative example of the R-ID-based UAV detection and identification system, and propose a replay-attack-based neutralization method using the analyzed vulnerabilities. To validate the proposed method, it is implemented as a software program, and verified against four types of attacks in real test environments. The results demonstrate that the proposed neutralization method is an effective neutralization method for R-ID-based UAV detection and identification systems.

• Land and Housing Review
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• v.14 no.2
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• pp.125-135
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• 2023

Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1669-1683
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• 2021

AI intelligent agriculture and digital agriculture are important for the science of agriculture. Leaf chlorophyll contents(LCC) are one of the most important indicators to determine the growth status of vegetable crops. In this study, a support vector machine (SVM) regression model was produced using an unmanned aerial vehicle-based RGB camera and a multispectral (MSP) sensor for onions and garlic, and the LCC estimation applicability of the RGB camera was reviewed by comparing it with the MSP sensor. As a result of this study, the RGB-based LCC model showed lower results than the MSP-based LCC model with an average R² of 0.09, RMSE 18.66, and nRMSE 3.46%. However, the difference in accuracy between the two sensors was not large, and the accuracy did not drop significantly when compared with previous studies using various sensors and algorithms. In addition, the RGB-based LCC model reflects the field LCC trend well when compared with the actual measured value, but it tends to be underestimated at high chlorophyll concentrations. It was possible to confirm the applicability of the LCC estimation with RGB considering the economic feasibility and versatility of the RGB camera. The results obtained from this study are expected to be usefully utilized in digital agriculture as AI intelligent agriculture technology that applies artificial intelligence and big data convergence technology.

• Journal of Apiculture
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• v.33 no.4
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• pp.261-268
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• 2018

Queen honey bees (Apis cerana) can be reared artificially on demand by the use of grafting technique. The technique consists of grafting young worker larvae into queen cell cups and raising in a queenless strong colony. As the age of grafted larvae for queen rearing exhibited several aspects related to quality and reproductive potential of queen, this study were conducted to investigate the influence of age of grafted larva on morphological characteristics and lifespan of queen, and the growth of colony she headed. Our results demonstrated that queens reared from young worker larvae (i.e., less than 1-day old larvae) were significantly larger in size (i.e., body weight and thorax width) than that of queens reared from 2-day old worker larvae. Moreover, queens reared from younger worker larvae initiated egg-laying earlier, stored more spermatozoa in spermatheca and had a longer lifespan compared to queens raised from older worker larvae. We also found a significant positive effect of queen grafting age on the production of worker and drone brood, adult worker population in colonies headed by queens reared from younger larvae. These findings suggested that rearing queens from brood grafted at the earliest possible age could increase the reproductive potential of queen as well as fitness of colony she head.

• Journal of Apiculture
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• v.33 no.4
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• pp.251-260
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• 2018

Instrumental insemination of honey bee is an attractive alternative to natural mating in breeding program as it allows mating crosses between desirable queen and specific drone. However, nursery condition that the queen is kept before and after insemination is major factor affected to the performance of instrumentally inseminated queen. In this study, we evaluated the influences of three different nursery-conditions of push-in cages, mini nuclei and normal colonies on number of spermatozoa stored in the spermatheca, body weight, onset of ovipositon and performance of instrumentally inseminated Apis cerana queen. Our results demonstrated that instrumentally inseminated queens kept in mini nuclei and in normal hives showed no significant difference in queen's weight (159.8 and 166.2mg, respectively), number of spermatozoa in spermatheca ($2.02{\times}10^6$ and $2.76{\times}10^6$, respectively), proportion of queen supersedure (33.3 and 66.7% queen survival at 11 months after oviposition, respectively) and brood production, compared to naturally mated queens. In contrast, instrumentally inseminated queens kept in push-in cages showed significant difference of those above data in comparison to queens mated naturally. Our results suggested that instrumentally inseminated queens could be kept in mini nuclei containing about 1.000 attendant bees to have desirable performance of queen whereas the push-in method should be practiced for the purpose of using queen in the length of time less than 7 months.