• Convergence Security Journal
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• v.14 no.5
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• pp.17-24
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• 2014

This study proposed LDP (Local Directional Pattern) as a new local micro pattern for facial expression recognition to solve noise sensitive problem of LBP (Local Binary Pattern). The proposed method extracts 8-directional components using $m{\times}m$ mask to solve LBP's problem and choose biggest k components, each chosen component marked with 1 as a bit, otherwise 0. Finally, generates a pattern code with bit sequence as 8-directional components. The result shows better performance of rotation and noise adaptation. Also, a new local facial feature can be developed to present both PFF (permanent Facial Feature) and TFF (Transient Facial Feature) based on the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10A
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• pp.839-846
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• 2011

Link Adaptation should select the best modulation and coding scheme (MCS) which gives the highest throughput as channel conditions vary. Several link adaptation algorithms for wireless local area network (WLAN) have been proposed but for the future WLAN systems such as 802.11n system, these algorithms do not guarantee the best performance. In this paper, we propose a new link adaptation algorithm in which an MCS level is chosen by the received SNR plus the offset value obtained from the transmission results. The performance of proposed algorithm is simulated by an IEEE 802.11n system. From the analysis, we conclude the proposed algorithm performs better than the well-known link adaptation algorithms such as auto rate fallback and general SNR-based techniques. Particularly, the proposed algorithm improves throughput when the packet error ratio (PER) is constrained for fast fading channels.

• Proceedings of the Ginseng society Conference
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• 1998.06a
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• pp.96-102
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• 1998

A lot of individual ginseng plants were selected in the farmer's fields to develop new ginseng varieties with desirable traits. Among them, a promising line has been developed through comparative cultivation of several lines selected with pure line separation of local raced. It was then designated as "KC (denotes Korean Ginseng)" and tested in the regional yield and adaptation trials for 10 years. KG lines grew vigorously after 4 years of age. Especially, KG 102 line arson운 them showed traits of multiple and short stems. As for the root characters, the length of taproot of KG 101 line was longer than that of local race, Jakyung-jong, or other lines ailed the root weight of KG 102 line waIn 15 % higher than that of local race. In general, KG 101, KG 103, KG 104, and Hwangsauk-jong had good root shape. Total amount of ginsenosides of ginseng taproot was the highest in KG 103 line than in local race and other lines. In these studies, we, elected three superior lines, KG 101, KG 102, and KG 103, having characteristic of good root shape, high yield, and large amount of ginsenoside, respectively.

• Journal of Ginseng Research
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• v.22 no.1
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• pp.11-17
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• 1998

To develop a new ginseng varieties with good quality and high yielding, a lot of individual ginseng plants were selected in the farmer's fields in 1972. Among them, a promising line, 7259-3-1, has been developed through comparative cultivation of several lines selected with pure line separation of local races in Korea Ginseng '||'&'||' Tobacco Research Institute. Preliminary and advanced yield trials were performed for 8 years. It was then designated as "KG 101" and tested in the regional yield and adaptation trials for 10 years (1981-1990). KG101 has a green stem with light violet and orange-yellow fruit and flowers 3-7 days later than local race, Takyungjong. Taproot of KG101 was longer than local race Jakyungjong, and root yield of KG101 was 9% higher than local race Jakyungjong. In red ginseng quality, the rates of Chun-Jeesam (Chun and Jee means 1st and 2nd grade, respectively) were 22.3% and 9.4% for KG101 and Jakyungjong, respectively. In these results, it was clarified that KG101 was superior ginseng line with good quality.y.

• Journal of Climate Change Research
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• v.3 no.1
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• pp.51-69
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• 2012

This work aims to propose a vulnerability assessment methodology of ecosystem at present time, and an to suggest an adaptation strategy of ecosystem in the future for local government, in the fields of plant, animal and conservation area, which would occurred due to climate change. Vulnerability assessment in ecosystem includes first, tree growth and distribution part, mainly for conifers, secondly, insect part for pest and bee, and thirdly conservation area management part, especially at the national parks. To evaluate the degree of vulnerability of each substitute variables, such as exposure of climatic element, sensitivity, and adaptation ability, are respectively selected. Vulnerabilities of conifer growth and distribution, pest and bee, and national park management seem to be strongly influenced by the exposure of climatic element than other factors, such as sensitivity and adaptation ability. With time regional gaps of ecosystem vulnerability are expected to be greater in both conifers growth and distribution, and national park management, but reduced in pest and bee in 2100 in comparison with present time.

• Korean Journal of Ecology and Environment
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• v.49 no.1
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• pp.42-50
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• 2016

The purpose of this study is to set the direction to manage national parks to cope with climate change, and offer basic data to establish the relevant policies. Towards this end, this study analyzed the current and future climate change vulnerability of national parks using the 24 proxy variables of vulnerability in the LCCGIS program, a tool to evaluate climate change vulnerability developed by the National Institute of Environmental Research. To analyze and evaluate the current status of and future prospect on climate change vulnerability of national parks, the proxy variable value of climate exposure was calculated by making a GIS spatial thematic map with $1km{\times}1km$ grid unit through the application of climate change scenario (RCP8.5). The values of proxy variables of sensitivity and adaptation capability were calculated using the basic statistics of national parks. The values of three vulnerability evaluation items were calculated regarding the present (2010s) and future (2050s). The current values were applied to the future equally under the assumption that the current state of the proxy variables related to sensitivity and adaptation capability without a future prediction scenario continues. Seoraksan, Odaesan, Jirisan and Chiaksan National Parks are relatively bigger in terms of the current (2010s) climate exposure. The national park, where the variation of heat wave is the biggest is Wolchulsan National Park. The biggest variation of drought occurs to Gyeryongsan National Park, and Woraksan National Park has the biggest variation of heavy rain. Concerning the climate change sensitivity of national parks, Jirisan National Park is the most sensitive, and adaptation capability is evaluated to be the highest. Gayasan National Park's sensitivity is the lowest, and Chiaksan National Park is the lowest in adaptation capability. As for climate change vulnerability, Seoraksan, Odaesan, Chiaksan and Deogyusan National Parks and Hallyeohaesang National Park are evaluated as high at the current period. The national parks, where future vulnerability change is projected to be the biggest, are Jirisan, Woraksan, Chiaksan and Sobaeksan National Parks in the order. Because such items evaluating the climate change vulnerability of national parks as climate exposure, sensitivity and adaptation capability show relative differences according to national parks' local climate environment, it will be necessary to devise the adaptation measures reflecting the local climate environmental characteristics of national parks, rather than establishing uniform adaptation measures targeting all national parks. The results of this study that evaluated climate change vulnerability using climate exposure, sensitivity and adaptation capability targeting Korea's national parks are expected to be used as basic data for the establishment of measures to adapt to climate change in consideration of national parks' local climate environmental characteristics. However, this study analyzed using only the proxy variables presented by LCCGIS program under the situation that few studies on the evaluation of climate change vulnerability of national parks are found, and therefore this study may not reflect overall national parks' environment properly. A further study on setting weights together with an objective review on more proper proxy variables needs to be carried out in order to evaluate the climate change vulnerability of national parks.

• Journal of Forest and Environmental Science
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• v.39 no.4
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• pp.213-224
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• 2023

As abnormal weather events due to climate change continue to rise, landslide damage is also increasing. Given the substantial time and financial resources required for post-landslide recovery, it becomes imperative to formulate a proactive response plan. In this regard, landslide susceptibility analysis has emerged as a valuable tool for establishing preemptive measures against landslides. Accordingly, this study conducted an annual landslide susceptibility analysis using the history of landslides that occurred over many years in the Jeolla region, and analyzed areas with a high potential for landslides in the Jeolla region. The analysis employed an ensemble model that amalgamated 10 data-based models, aiming to mitigate uncertainties associated with a single-model approach. Furthermore, based on the cumulative data regarding landslide susceptible areas, this research identified regions vulnerable to recurring landslide damage in Jeolla region and proposed specific strategies for utilizing this information at various levels, including local government initiatives, adaptation plan development, and development approval processes. In particular, this study outlined approaches for local government utilization, the determination of adaptation plan types, and considerations for development permits. It is anticipated that this research will serve as a valuable opportunity to underscore the significance of information concerning regions vulnerable to recurring landslide damage.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.827-835
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• 2019

In the pooling stage of a full reference image quality assessment (FR-IQA) technique, the global perceived quality for any distorted image is usually measured from the quality of its local image patches. But all the image patches do not have equal contribution when estimating the overall visual quality since the degree of degradation on those patches depends on various considerations i.e., types of the patches, types of the distortions, distortion sensitivities of the patches, saliency score of the patches, etc. As a result, weighted pooling strategy comes into account and different weighting mechanisms are used by the existing FR-IQA methods. This paper performs a thorough analysis and proposes a novel weighting function by considering the luminance adaptation as well as the visual saliency effect to offer more appropriate local weights, which can be adopted in the existing FR-IQA frameworks to improve their prediction accuracy. The extended experimental results show the effectiveness of the proposed weighting function.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.471-480
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• 2012

Reliable detection of primary user activity increases the opportunity to access temporarily unused bands and prevents harmful interference to the primary system. By extracting a global decision from local sensing results, cooperative sensing achieves high reliability against multipath fading. For the effective combining of sensing results, which is generalized by a likelihood ratio test, the fusion center should learn some parameters, such as the probabilities of primary transmission, false alarm, and detection at the local sensors. During the training period in supervised learning, the on/off log of primary transmission serves as the output label of decision statistics from the local sensor. In this paper, we extend unsupervised learning techniques with an expectation maximization algorithm for cooperative spectrum sensing, which does not require an external primary transmission log. Local sensors report binary hard decisions to the fusion center and adjust their operating points to enhance learning performance. Increasing the number of sensors, the joint-expectation step makes a confident classification on the primary transmission as in the supervised learning. Thereby, the proposed scheme provides accurate parameter estimates and a fast convergence rate even in low signal-to-noise ratio regimes, where the primary signal is dominated by the noise at the local sensors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1253-1272
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• 2010

In this paper, we propose a new affine shape adaptation scheme for the affine invariant feature detector, in which the convergence stability is still an opening problem. This paper examines the relation between the integration scale matrix of next iteration and the current second moment matrix and finds that the convergence stability of the method can be improved by adjusting the relation between the two matrices instead of keeping them always proportional as proposed by previous methods. By estimating and updating the shape of the integration kernel and differentiation kernel in each iteration based on the anisotropy of the current second moment matrix, we propose a coarse-to-fine affine shape adaptation scheme which is able to adjust the pace of convergence and enable the process to converge smoothly. The feature matching experiments demonstrate that the proposed approach obtains an improvement in convergence ratio and repeatability compared with the current schemes with relatively fixed integration kernel.