• KIPS Transactions on Computer and Communication Systems
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• v.10 no.9
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• pp.243-250
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• 2021

Recently, with the development of cloud computing, interest in database outsourcing is increasing. However, when the database is outsourced, there is a problem in that the information of the data owner is exposed to internal and external attackers. Therefore, in this paper, we propose a parallel range query processing algorithm that supports privacy protection. The proposed algorithm uses the Paillier encryption system to support data protection, query protection, and access pattern protection. To reduce the operation cost of a checking protocol (SRO) for overlapping regions in the existing algorithm, the efficiency of the SRO protocol is improved through a garbled circuit. The proposed parallel range query processing algorithm is largely composed of two steps. It consists of a parallel kd-tree search step that searches the kd-tree in parallel and safely extracts the data of the leaf node including the query, and a parallel data search step through multiple threads for retrieving the data included in the query area. On the other hand, the proposed algorithm provides high query processing performance through parallelization of secure protocols and index search. We show that the performance of the proposed parallel range query processing algorithm increases in proportion to the number of threads and the proposed algorithm shows performance improvement by about 5 times compared with the existing algorithm.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.609-621
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• 2021

This study investigates the effect of types of usual source of care on medication adherence among the elderly. Using the Korea Health Panel Survey in 2017, this study includes 3,623 elderly people 65 years of age or older taking prescription drugs for treatment of chronic diseases. The type of usual source of care was considered in three aspects: whether having a usual source of care or not, whether having a regular site only or having a regular site and doctor, size of the regular site. The types of usual source of care are heavily associated with medication adherence. Compared to those who have no usual source of care, those who have a regular site only are 1.4 times, and have both regular site and doctor are 1.8 times more likely to comply with the medication guidelines, respectively. The finding shows usual source of care has a positive effect in improving medication adherence of the elderly. The results can provide an evidence for policies for effective management of chronic diseases and efficient use of medical resources.

• Korean Journal of Food Science and Technology
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• v.53 no.2
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• pp.218-222
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• 2021

This study aimed to investigate bacterial disinfection in drinking water using a water purifier. Water artificially inoculated with Escherichia coli and Listeria monocytogenes at various concentrations was irradiated using ultraviolet (UV)-C at a rate of 3.4 L/min in a water purifier, and the disinfection effects of UV-C were evaluated. Both E. coli and L. monocytogenes were disinfected up to 107 colony-forming units (CFU)/2.8 L by the UV-C irradiation. Additionally, morphological study using fluorescence microscopy in conjunction with live/dead staining revealed that both the bacteria species were disinfected by the UV-C irradiation. Therefore, UV-C in water purifiers can effectively kill high concentrations of bacteria in distilled water. UV irradiation (UV-C: 254 nm wavelength, irradiation dose: 40 mJ/㎠) at a flow rate of 3.4 L/min on drinking water has the potential to sterilize bacteria-contaminated drinking water, at least for 3.2×107 CFU/2.8 L of E. coli and 8.4×107 CFU/2.8 L of L. monocytogenes.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1965-1974
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• 2021

Satellite remote sensing approach can be actively used for forest monitoring. Especially, it is much meaningful to utilize Korea multi-purpose satellites, an independently operated satellite in Korea, for forest monitoring of Korea, Recently, several studies have been performed to exploit meaningful information from satellite remote sensed data via machine learning approaches. The forest information produced through machine learning approaches can be used to support the efficiency of traditional forest monitoring methods, such as in-situ survey or qualitative analysis of aerial image. The performance of machine learning approaches is greatly depending on the characteristics of study area and data. Thus, it is very important to survey the best model among the various machine learning models. In this study, the performance of deep neural network to classify artificial or natural forests was analyzed in Samcheok, Korea. As a result, the pixel accuracy was about 0.857. F1 scores for natural and artificial forests were about 0.917 and 0.433 respectively. The F1 score of artificial forest was low. However, we can find that the artificial and natural forest classification performance improvement of about 0.06 and 0.10 in F1 scores, compared to the results from single layered sigmoid artificial neural network. Based on these results, it is necessary to find a more appropriate model for the forest type classification by applying additional models based on a convolutional neural network.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.129-134
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• 2021

Recently, the demand for electricity is gradually increasing due to the rapid industrial development and the improvement of living standards. In the case of Korea, which is highly dependent on fossil fuels due to such a surge in electricity demand, reduction and freezing of greenhouse gas emissions due to international environmental regulations will immediately lead to a contraction in industrial activities. Accordingly, there are many difficulties in competition with advanced countries that want to link the environment with the country's industrial production activities, and the development of alternative energy as a countermeasure is of great interest around the world. Among these new power generation methods, small-scale power generation facilities with relatively small capacity include photovoltaic generation, wind power generation, and fuel cell generation. Among them, the fuel cell attracts the most attention in consideration of continuous operation, high power generation efficiency, and long-term durability, which are important factors for practical use. Therefore, in this paper, the fuel cell power generation system was researched and constructed by designing the power conversion circuit necessary to finally obtain the AC power used in our daily life by using the DC power generated from the fuel cell as an input.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.479-495
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• 2021

To improve on the efficient management of forest resources, it is necessary to create a forest soil map, which represents a comprehensive database of forest lands. Although a 1:25,000 scale forest site map has been used in Korea, the need for a large-scale forest soil map with high precision and information on forest lands that is specialized for individual purposes has been identified. Moreover, to keep pace with the advancement in forest management and transition to a digital society, it is essential to develop a method for constructing new forest soil maps that can diversify its use. Therefore, this paper presented a developmental process and used a 1:5,000 scale forest soil map to propose future directions. National maps showing the soil type, depth, and texture were produced based on the survey and analysis of forest soils, followed by the Forest Land Soil Map (1:5,000) Production Standard Manual. Alternatively, forest soil map data were the basis on which various other maps that can be used to prevent and predict forest disasters and evaluate environmental capacities were developed. Accordingly, ways to provide appropriate information to achieve the national forest plan, secure forestry big data, and accomplish sustainable forest management that corresponds to the national development plan are proposed based on results from the current study.

• The Korean Journal of Mycology
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• v.49 no.4
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• pp.487-495
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• 2021

Lentinula edodes is a tetrapolar basidiomycete and its mating type is determined by two unlinked genetic loci, A and B. Theoretically, one dikaryotic strain could produce basidiospores with four different mating types in a 1:1:1:1 ratio. Previous studies have described the skewed segregation ratio of mating types among basidiospores of L. edodes. However, they were based only on morphological characteristics, such as clamp connection, to determine mating types. To clarify whether the segregation distortion of mating types is a general phenomenon in L. edodes, we analyzed the mating types of basidiospores obtained from three cultivars of L. edodes using recently developed DNA markers. We found that the skewed segregation of mating types was strain-specific, as reported previously. Among the three cultivars, one cultivar showed balanced segregation, while the other two displayed distorted segregation. We also examined the relationship between mating type and mycelial growth rate of monokaryons derived from each basidiospore. It was found that the monokaryotic mycelial growth rate was related to the A mating type but not to the B mating type. Therefore, homeodomain transcription factor genes that reside on the A locus or other genes linked to the A locus affect the growth rate of monokaryotic mycelia. Considering the importance of mating types in mushroom breeding, this study is informative for establishing an efficient breeding strategy as well as for understanding the mechanism of monokaryotic mycelial growth.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.134-139
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• 2021

Currently, the autonomous vehicle market is commercializing a level 3 autonomous vehicle, but it still requires the attention of the driver. After the level 3 autonomous driving, the most notable aspect of level 4 autonomous vehicles is vehicle stability. This is because, unlike Level 3, autonomous vehicles after level 4 must perform autonomous driving, including the driver's carelessness. Therefore, in this paper, we propose the Emergency-notification and Driver-response Confirmation System(EDCS) for an autonomousvehicle safety that notifies the driver of an emergency situation and recognizes the driver's reaction in a situation where the driver is careless. The EDCS uses the emergency situation delivery module to make the emergency situation to text and transmits it to the driver by voice, and the driver response confirmation module recognizes the driver's reaction to the emergency situation and gives the driver permission Decide whether to pass. As a result of the experiment, the HMM of the emergency delivery module learned speech at 25% faster than RNN and 42.86% faster than LSTM. The Tacotron2 of the driver's response confirmation module converted text to speech about 20ms faster than deep voice and 50ms faster than deep mind. Therefore, the emergency notification and driver response confirmation system can efficiently learn the neural network model and check the driver's response in real time.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.291-303
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• 2021

In the modern society, the number of people in disaster vulnerable groups is rapidly increasing such as the elderly, the disabled, foreigners, and children. The common characteristics of the groups vulnerable to disasters are that they live in residence types that are exposed to disasters because they are impoverished and if they are exposed to disasters, recovery is a slow process. The purpose of this study is to identify the new risk issues by performing risk issue analysis on the targets of disaster vulnerable group and provide base data for the development of the policies. For the research method, this study centered on the cases of children and pregnant women out of the disaster vulnerable groups and focused on the issue data of social media throughout the past 10 years ('10~'19) and performed social network analysis. As a result, first, the development of the issue showed relevance in the occurrence of specific cases. Second, the awareness about the types, targets, and management method of crisis management was analyzed. Third, an analysis was performed on the sentiment words that considered the solution measures of risk issues or the characteristics of the targets and it was analyzed that there were word that triggered negative emotions. Therefore, it is anticipated for the base data to be used for the government and also for the local government to build an effective crisis management system of the rapidly changing disaster environment on the basis of the sentiment analysis performed on the people of the nation as well as public awareness.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.291-304
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• 2021

Updating a forest type map is essential for sustainable forest resource management and monitoring to cope with climate change and various environmental problems. According to the necessity of efficient and wide-area forestry remote sensing, CAS500-4 (Compact Advanced Satellite 500-4; The agriculture and forestry satellite) project has been confirmed and scheduled for launch in 2023. Before launching and utilizing CAS500-4, this study aimed to pre-evaluation the possibility of satellite-based tree species classification using RapidEye, which has similar specifications to the CAS500-4. In this study, the study area was the Chuncheon forest management complex, Gangwon-do. The spectral information was extracted from the growing season image. And the GLCM texture information was derived from the growing and non-growing seasons NIR bands. Both information were used to classification with random forest machine learning method. In this study, tree species were classified into nine classes to the coniferous tree (Korean red pine, Korean pine, Japanese larch), broad-leaved trees (Mongolian oak, Oriental cork oak, East Asian white birch, Korean Castanea, and other broad-leaved trees), and mixed forest. Finally, the classification accuracy was calculated by comparing the forest type map and classification results. As a result, the accuracy was 39.41% when only spectral information was used and 69.29% when both spectral information and texture information was used. For future study, the applicability of the CAS500-4 will be improved by substituting additional variables that more effectively reflect vegetation's ecological characteristics.