This study observed and compared phenological changes in the spring for some native woody plants growing at Mt. Jumbong and Mt. Bongeui located at central districts of our country, and also inquired into the phenological difference subsequent to microclimate change by measuring its related environment factors as well. The average air temperature at a survey point of Mt. Jumbong from January to May in 2004 was $4.1^{\circ}C$ lower than that of Mt. Bongeui. As for the soil temperature in April by a survey section within Mt. Jumbong, the soil temperature on the west and northwest slopes was $1.8^{\circ}C$ and $4.4^{\circ}C$ lower than that of the south slope, respectively. It was found that the earliest tree species in a flowering period was Lindera obtusiloba among the sample woody plants and its flowering began in late March at Mt. Bongeui and in early April at Mt. Jumbong. The flowering of the same species began faster on the south slope than the west or north slope; in case of the tree species flowering in early spring, there appeared about two-week interval between the survey sites. Likewise, leafing time of the same species was two weeks earlier at Mt. Bongeui(in mid-April) than at Mt. Jumbong(in early May). Nuttonson's Index and Year Day Index for the flowering and leafing time of the same species showed similar value between the survey sites. It is analyzed that the transition in phenological phases between the sites is mainly caused by temperatures; further, it is implied that the climate changes and rise in temperatures could expedite the changes in phenological phases more than ever.
This paper presents an optimal design methodology for the multidimensional nested attribute index (MD-NAI) that uses a multidimensional index structure for indexing the nested attributes in object databases. The MD-NAI efficiently supports complex queries involving both nested attributes and class hierarchies, which are not supported by the nested attribute index using one-dimensional index structure such as $B^+$-tree. However, the performance of the MD-NAI is very degraded in some cases of user's query types. In this paper, for the performance enhancement of the MD-NAI, we first determine the optimal shape of index page region by using the query information about the nested predicates, and then construct an optimal MD NAI by applying a region splitting strategy that makes the shape of the page regions of the MD-NAI as close as possible to the predetermined optimal one. For performance evaluation, we perform extensive experiments with the MD-NAI using various types of nested predicates and object distribution. The results indicate that our proposed method builds optimal MD-NAI regardless of the query types and object distributions. When the interval ratio of a three-dimensional query region is 1:16:236, the performance of the proposed method is enhanced by as much as 5.5 times over that of the conventional method employing the cyclic splitting strategy.
Jiejin Yang;Zeyang Chen;Weipeng Liu;Xiangpeng Wang;Shuai Ma;Feifei Jin;Xiaoying Wang
Korean Journal of Radiology
/
v.22
no.3
/
pp.344-353
/
2021
Objective: The mitotic count of gastrointestinal stromal tumors (GIST) is closely associated with the risk of planting and metastasis. The purpose of this study was to develop a predictive model for the mitotic index of local primary GIST, based on deep learning algorithm. Materials and Methods: Abdominal contrast-enhanced CT images of 148 pathologically confirmed GIST cases were retrospectively collected for the development of a deep learning classification algorithm. The areas of GIST masses on the CT images were retrospectively labelled by an experienced radiologist. The postoperative pathological mitotic count was considered as the gold standard (high mitotic count, > 5/50 high-power fields [HPFs]; low mitotic count, ≤ 5/50 HPFs). A binary classification model was trained on the basis of the VGG16 convolutional neural network, using the CT images with the training set (n = 108), validation set (n = 20), and the test set (n = 20). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated at both, the image level and the patient level. The receiver operating characteristic curves were generated on the basis of the model prediction results and the area under curves (AUCs) were calculated. The risk categories of the tumors were predicted according to the Armed Forces Institute of Pathology criteria. Results: At the image level, the classification prediction results of the mitotic counts in the test cohort were as follows: sensitivity 85.7% (95% confidence interval [CI]: 0.834-0.877), specificity 67.5% (95% CI: 0.636-0.712), PPV 82.1% (95% CI: 0.797-0.843), NPV 73.0% (95% CI: 0.691-0.766), and AUC 0.771 (95% CI: 0.750-0.791). At the patient level, the classification prediction results in the test cohort were as follows: sensitivity 90.0% (95% CI: 0.541-0.995), specificity 70.0% (95% CI: 0.354-0.919), PPV 75.0% (95% CI: 0.428-0.933), NPV 87.5% (95% CI: 0.467-0.993), and AUC 0.800 (95% CI: 0.563-0.943). Conclusion: We developed and preliminarily verified the GIST mitotic count binary prediction model, based on the VGG convolutional neural network. The model displayed a good predictive performance.
KSII Transactions on Internet and Information Systems (TIIS)
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v.3
no.1
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pp.5-25
/
2009
In recent years the popularity of multi-hop wireless networks has been growing. Its flexible topology and abundant routing path enables many types of applications. However, the lack of a centralized controller often makes it difficult to design a reliable service in multi-hop wireless networks. While packet routing has been the center of attention for decades, recent research focuses on data discovery such as file sharing in multi-hop wireless networks. Although there are many peer-to-peer lookup (P2P-lookup) schemes for wired networks, they have inherent limitations for multi-hop wireless networks. First, a wired P2P-lookup builds a search structure on the overlay network and disregards the underlying topology. Second, the performance guarantee often relies on specific topology models such as random graphs, which do not apply to multi-hop wireless networks. Past studies on wireless P2P-lookup either combined existing solutions with known routing algorithms or proposed tree-based routing, which is prone to traffic congestion. In this paper, we present two wireless P2P-lookup schemes that strictly build a topology-dependent structure. We first propose the Ring Interval Graph Search (RIGS) that constructs a DHT only through direct connections between the nodes. We then propose the ValleyWalk, a loosely-structured scheme that requires simple local hints for query routing. Packet-level simulations showed that RIGS can find the target with near-shortest search length and ValleyWalk can find the target with near-shortest search length when there is at least 5% object replication. We also provide an analytic bound on the search length of ValleyWalk.
The concentration of monoterpenes (12 species) was measured from spring to fall in 2008 in ambient air at six different forests located in the southern parts of Korea. Sampling - using a Solid Adsorption Tube - was conducted at 2-hour-interval a day (24 hours) of each season. The highest annual average concentration of total monoterpene was 0.715 ppbv, which occurred at Mt. Baega. ${\alpha}$-Pinene, sabinene and ${\beta}$-pinene were the most abundant compounds throughout the sampling periods and areas. The concentrations of monoterpene were higher in spring than in any other seasons. The compositions and concentrations of monoterpene displayed a distinct pattern by area. Most of monoterpenes had diurnal variations with higher concentrations during the daytime, and lower during the nighttime. This may be due to the fact that the amount of monoterpenes emitted increases at elevated ambient temperatures and increased sunlight intensity. The results of this study showed that each area had distinct monoterpene compositions, which depended on the tree species, topography and local climate at each area.
A stable power supply is very important for the maintenance and operation of the power infrastructure. Accurate power consumption prediction is therefore needed. In particular, a university campus is an institution with one of the highest power consumptions and tends to have a wide variation of electrical load depending on time and environment. For this reason, a model that can accurately predict power consumption is required for the effective operation of the power system. The disadvantage of the existing time series prediction technique is that the prediction performance is greatly degraded because the width of the prediction interval increases as the difference between the learning time and the prediction time increases. In this paper, we first classify power data with similar time series patterns considering the date, day of the week, holiday, and semester. Next, each ARIMA model is constructed based on the classified data set and a daily power consumption forecasting method of the university campus is proposed through the time series cross-validation of the predicted time. In order to evaluate the accuracy of the prediction, we confirmed the validity of the proposed method by applying performance indicators.
Enrichment planting has been used as one of the promising restoration techniques to accelerate the natural restoration process of secondary forests or logged-over forests in Myanmar, The objectives of this study were to examine the growth performances of two commercial species such as Teak (Tectona grandis Linn f.) and Padauk (Pterocarpus macrocarpus Kurz) in response to different canopy opening treatments and to examine the suitability of these species in enrichment planting activities for the restoration of degraded tropical forests in Myanmar. In this study, split plot design was applied, and three levels of canopy openings were experimented. The survival rate and height growth of two species were measured four times with 6 month interval. The root collar diameter (RCD) was also measured in the last assessment. Although the survival rate of seedlings was not significantly different among the three treatments (p>0.05) as well as between two species (p>0.05) for all consecutive measurements, height (p<0.05) and RCD were significantly different (p<0.001) among the treatments, T. grandis seedlings thrived best under complete canopy opening (i.e., 5 m width canopy opening with strip-clear cutting) while P. macrocarpus seedlings under partial canopy opening (without felling of marketable tree species). Because this study is concerned with only for young stage of seedlings, continuous assessment and follow-up tending activities are needed to verify the species suitability and optimum width of canopy opening for enrichment planting activities in restoration of degraded forests of Myanmar.
Journal of the Korean Society of Environmental Restoration Technology
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v.11
no.2
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pp.75-86
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2008
The wetlands have functions those were retention of diverse biota, purification of water quality, control of climate and flood, eco-tourism and supply of agricultural water, and that was the ecosystem of high biodiversity as the zone of transition between inland and water. Therefore, this study showed the conservation and management plan by analyzing in the abiotic and biotic environment of forest swamp, Gyeongsangbuk-do. The results were as follows. Examining the management plan of the abiotic environment, there will need to establish the hydrological plan in continuous expediting the supply of water to maintain a humid soil of swamp, and to try to find the organic farming, use of low toxic agrichemicals and so on to prevent occurring a non-point source pollutants. To prevent changing the flowing of ground water and inflow of earth and sand in modifying the land character, there will be needed to restrict the construction of farmland and slope around swamp. To manage the biotic environment, there needed to offer the habitat by removing the regular interval and individual of a dead tree, and to improve the growth environment of vegetation. Because the naturalized plants disturb the natural vegetation, they will be removed. The afforested trees like Robinia pseudoacacia and Amorpha truticosa will be renewed to prevent the heterogeneity of landscape ecology, and the active conservation plan on wetland species will be established. As this study was carried out to study on the partial swamp, Gyeongsanbuk-do, the ecological environments distributing a swamp in Korea show a some problem. In the future, the study will accomplish to study the accurately and objectively ecological environment and management of a swamp by analyzing the extensive sites.
The conservation treatment and production technique of Yongmuntujoeunpanpi-Angyo(Saddle Ornament) at Hwangnamdaechong were: The conservation treatment removed foreign material by using both chemical method and physical method to reinforce and to recover area by jointing that was destroyed and weakened. Not only Angyogeumgu but also Jwamokseongeumgu was made of 99wt% or more silver (Ag), and Wondujeong, Naeyeongeumgu and Bokryung were produced by amalgam gold plaiting. Not only Angyogeumgu but also Jwamokseongeumgu that was cast with silver plate was jointed by folding both and putting Naeyeongeumgu on it and then nailing gild ofwondujeong at specific interval. A tree that grew up in curve was used, and it was adhered by plain weave fabric of hemp cloth and wool.
Posadas, Brianna B.;Lee, Won Suk;Galindo-Gonzalez, Sebastian;Hong, Youngki;Kim, Sangcheol
Journal of Biosystems Engineering
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v.41
no.3
/
pp.255-262
/
2016
Purpose: Fuji apples are one of the top selling exports for South Korea bringing in over $233.4 million in 2013. However, during the last few decades, about half of the Fuji apple orchards have been infected by Apple Marssonina Blotch disease (AMB), a fungal disease caused by Diplocarpon mali., which takes about 40 days to exhibit obvious visible symptoms. Infected leaves turn yellow and begin growing brown lesions. AMB promotes early defoliation and reduces the quality and quantity of apples an infected tree can produce. Currently, there is no prediction model for AMB on the market. Methods: The Precision Agriculture Laboratory (PAL) at the University of Florida (UF) has been working with the National Academy of Agricultural Science, Rural Development Administration, South Korea to investigate the use of hyperspectral data in creating an early detection method for AMB. The RDA has been researching hyperspectral techniques for disease detection at their Apple Research Station in Gunwi since 2012 and disseminates its findings to the local farmers. These farmers were surveyed to assess the state of knowledge of AMB in the area. Out of a population of about 750 growers, 111 surveys were completed (confidence interval of +/- 8.59%, confidence level of 95%, p-value of 0.05). Results: The survey revealed 32% of the farmers did not know what AMB was, but 45% of farmers have had their orchards infected by AMB. Twenty-five percent could not distinguish AMB from other symptoms. Overwhelmingly, 80% of farmers strongly believed an early detection method for AMB was necessary. Conclusions: The results of the survey will help to evaluate the outreach programs of the RDA so they can more effectively educate farmers on the identifying, treating, and mediating AMB.
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