• Journal of Life Science
• /
• v.28 no.5
• /
• pp.621-626
• /
• 2018

We introduced the physiological responses of aging, active aging and also suggest the impact of physical exercise on body health status and elderly immunity. In this purpose, we searched the Pub Med data base for the articles (include our experimental papers) and review papers having the terms 'Aging', 'Active aging' and 'Physical activity and elderly' in the title, published from 1999 until 2018. The results were as follows: Exercise training has been extensively studied about the reduction of inflammation, oxidative stress, disease, and aging in syndrome X patients and elderly. Combined and aerobic or resistance exercise training could reduce obesity, insulin resistance, type 2 diabetes and hypertension. Exercise training has been extensively studied in cancer settings as part of prevention or treatment strategies. From this research, regular exercise has the potential to target tumor growth through regulation of inflammation and immune responses such as lactate clearance, NK cell activation (innate immunity), activation of cytotoxic immune cells, T cell activation (adaptive immunity), and immune surveillance. However, Endurance physical activity not only induces thermogenesis and diverse sports injuries but also elicits mobilization and functional enhancement of monocytes, neutrophils (which is caused by the cytokine changes such as TNF-alpha, IL-1) whereas it suppresses cell mediated immunity causing to increased susceptibility to inflammation and infections like cough and URTIs (upper respiratory track infections) in young and especially in elderly people. Therefore, Strategies to prevent physical fatigue, sports injuries include avoid overtraining, Adequate recovery and various type of rest during and after physical activity and assuring adequate nutrition supplementation such as glutamine, vitamin B, vitamin C, carbohydrate, ion or berry-contain sports beverages is helpful in physically active elderly.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.18 no.2
• /
• pp.95-100
• /
• 2012

This study was determined to analysis marine environmental and phytoplankton monitoring in Wando coastal waters in August during the period of 2009-2010 and provided the basic environmental data against Southwest Sea of Korea. In August, 2009, the distribution of water temperature and salinity showed an unique characteristics for all of stations, which was associated with a long duration of rainfall after July, 2009 and a lack of sunshine. In the lower of August, 2010, the stratification of water temperature and salinity was shown, which was caused by an intensive sunshine after the middle of August, 2010. Gangjin Bay and Gogeundo waters showed a highly different water temperature and transparency. It is thought that two regions have a distinct water mass and characteristics. In dissolved oxygen and oxygen saturation were higher according to higher water depth regardless of stations. In August, 2009, different dominant species occurred that Gangjin Bay showed a higher cell density of diatom, but Gonyaulax polygramma played an important role in dominant species in Gogeundo waters. It is associated with the introduction red tide water of G. polygramma occurring to southern coastal water in August, 2009. In August, 2010, diatom was extremely higher cell density compared with that of dinoflagellate that regarded as adaptive microrganism against higher quantity of suspended solid in Wando waters. Although Wando has a record of Cochlodinium red tide, this species may be difficult to grow and persist. Dominant species, diatom, play an important role in food organism for shellfish and forming a ecological lineage.

• Korean Journal of Environment and Ecology
• /
• v.32 no.4
• /
• pp.425-439
• /
• 2018

W investigated the environmental factors and inhabiting biota such as macrophytes and zooplankton in 43 sites located on Jeju Island from May and June 2017 to evaluate the spread and ecosystem risk of dotted duckweed (landoltia punctata) which was recently found for the first time in Jeju Island. Dotted duckweeds were found in a total of 18 sites which tended to show low biomass of aquatic macrophyte species other than the dotted duckweed. We conducted a pattern analysis using SOM (Self-Organizing Map), which extracts information through competitive and adaptive properties, to analyze the effect of inhabiting biota on aquatic macrophytes such as the dotted duckweed and environmental factors. The SOM analysis showed that the inhabiting biota such as the zooplankton affected the biomass of aquatic macrophytes than they did the environmental factors. In particular, the biomass of dotted duckweed was positively related to plant-attached species (Alona, Chydorus, and Pleuroxus). Considering that low density of aquatic macrophytes covers the streams and wetlands on Jeju Island because of irregular water source and sharp change of water depth, the dotted duckweeds are likely to play an essential role as the vital habitat for micro-biota including zooplankton in wetlands and streams on Jeju Island. Furthermore, considering that organic matters are utilized as the primary food source in the areas occupied by dotted duckweed, dotted duckweeds have the role of being both habitat and food source. Although the dense growth of dotted duckweed adversely affects growth and development of some aquatic plants due to the shadow effect, it is due to the dominance of floating plants on the water surface should not be regarded as the risk of the dotted duckweed. In conclusion, the dotted duckweeds have spread and settled in most of the water systems on Jeju Island, their impact on inhabiting biota and the aquatic environment was minor. It is necessary to monitor the distribution and spread of dotted duckweeds in the inland areas outside of Jeju Island in the future.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.45 no.4
• /
• pp.9-21
• /
• 2008

In this paper, we propose a GNSS-based RF receiver, A high precision localization architecture, and a high sensitivity localization architecture in order to solve the satellite navigation system's problem mentioned above. The GNSS-based RF receiver model should have the structure to simultaneously receive both the conventional GPS and navigation information data of future-usable Galileo. As a result, it is constructed as the multi-band which can receive at the same time Ll band (1575.42MHz) of GPS and El band (1575.42MHz), E5A band (1207.1MHz), and E4B band (1176.45MHz) of Galileo This high precision localization architecture proposes a delay lock loop with the structure of Early_early code, Early_late code, Prompt code, Late_early code, and Late_late code other than Early code, Prompt code, and Late code which a previous delay lock loop structure has. As we suggest the delay lock loop structure of 1/4chips spacing, we successfully deal with the synchronization problem with the C/A code derived from inaccuracy of the signal received from the satellite navigation system. The synchronization problem with the C/A code causes an acquisition delay time problem of the vehicle navigation system and leads to performance reduction of the receiver. In addition, as this high sensitivity localization architecture is designed as an asymmetry structure using 20 correlators, maximizes reception amplification factor, and minimizes noise, it improves a reception rate. Satellite navigation system repeatedly transmits the same C/A code 20 times. Consequently, we propose a structure which can use all of the same C/A code. Since this has an adaptive structure and can limit(offer) the number of the correlator according to the nearby environment, it can reduce unnecessary delay time of the system. With the use of this structure, we can lower the acquisition delay time and guarantee the continuity of tracking.

• Journal of Korean Society of Forest Science
• /
• v.109 no.3
• /
• pp.259-270
• /
• 2020

Extreme weather events, such as heat and drought, have occurred frequently over the past two decades. This has led to continuous reports of cases of forest damage due to physiological stress, not pest damage. In 2014, pine trees were collectively damaged in the forest genetic resources reserve of Sogwang-ri, Uljin, South Korea. An investigation was launched to determine the causes of the dieback, so that a forest management plan could be prepared to deal with the current dieback, and to prevent future damage. This study aimedto 1) understand the topographic and structural characteristics of the area which experienced pine tree dieback, 2) identify the main causes of the dieback, and 3) predict future risk areas through the use of machine-learning techniques. A model for identifying risk areas was developed using 14 explanatory variables, including location, elevation, slope, and age class. When three machine-learning techniques-Decision Tree, Random Forest (RF), and Support Vector Machine (SVM) were applied to the model, RF and SVM showed higher predictability scores, with accuracies over 93%. Our analysis of the variable set showed that the topographical areas most vulnerable to pine dieback were those with high altitudes, high daily solar radiation, and limited water availability. We also found that, when it came to forest stand characteristics, pine trees with high vertical stand densities (5-15 m high) and higher age classes experienced a higher risk of dieback. The RF and SVM models predicted that 9.5% or 115 ha of the Geumgang Pine Forest are at high risk for pine dieback. Our study suggests the need for further investigation into the vulnerable areas of the Geumgang Pine Forest, and also for climate change adaptive forest management steps to protect those areas which remain undamaged.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.15 no.5
• /
• pp.505-522
• /
• 2013

Previously, a new concept of indexing methodology has been proposed for quantitative assessment of tunnel collapse hazard level at each tunnel face with respect to the given geological data, design condition and the corresponding construction activity (Shin et al, 2009a). In this paper, 'linear' model, in which weights of influence factors are invariable, and 'non-linear' model, in which weights of influence factors are variable, are taken into account with some examples. Then, the 'non-linear' model is validated by using 100 tunnel collapse cases. It appears that 'non-linear' model allows us to have adapted weight values of influence factors to characteristics of given tunnel site. In order to make a better understanding and help for an effective use of the system, a series of operating processes of the system are built up. Then, by following the processes, the system is applied to a real-life tunnel project in very weak and varying ground conditions. Through this approach, it would be quite apparent that the tunnel collapse hazard indices are determined by well interlinked consideration of face mapping data as well as design/construction data. The calculated indices seem to be in good agreement with available electric resistivity distribution and design/construction status. In addition, This approach could enhance effective usage of face mapping data and lead timely and well corresponding field reactions to situation of weak tunnel faces.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.16 no.3
• /
• pp.219-226
• /
• 2014

Evaluation of tree responses to temperature elevation is critical for a development of forest management techniques coping with climate change. We conducted a study on the growth responses of Betula costata, Fraxinus rhynchophylla, and Quercus variabilis seedlings to open-field artificial warming. Artificial warming set-up using infra-red heater was built in 2012 and the temperature in warmed plots was regulated to be consistently $3^{\circ}C$ higher than that of control plots. The seeds of three species were sown, and the responses of growth, biomass allocation, and net photosynthetic rate of newly-germinated seedlings on the open-field artificial warming were determined. As a result, the growth responses of the seedlings differed with the species. B. costata showed decreases in the height to diameter ratio (H/D ratio), biomass, root weight to shoot weight ratio, and net photosynthetic rate. However, root collar diameter (RCD), height, biomass, and net photosynthetic rate of Q. variabilis were increased, while the response of F. rhynchophylla was rather obscure. There was no significant difference between warmed and control plots in seedling growth for 3 species in July, whereas, RCD, height, and H/D ratio of Q. variabilis were increased and H/D ratio of B. costata was decreased in November under warming. Species-specific growth responses to warming were similar to the species-specific responses of net photosynthetic rate and biomass allocation; therefore, net photosynthetic rate and biomass allocation might attribute to growth responses to warming. Besides, a relatively obvious response in autumn compared to summer might be affected by the phenological change following artificial warming. Species-specific responses of three deciduous species to warming in this study could be applied to the development of adaptive forest management policies to climate change.

• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.4
• /
• pp.479-488
• /
• 2002

In recent years the amount of digital video used has risen dramatically to keep pace with the increasing use of the Internet and consequently an automated method is needed for indexing digital video databases. Textual information, both superimposed and embedded scene texts, appearing in a digital video can be a crucial clue for helping the video indexing. In this paper, a new method is presented to extract both superimposed and embedded scene texts in a freeze-frame of news video. The algorithm is summarized in the following three steps. For the first step, a color image is converted into a gray-level image and applies contrast stretching to enhance the contrast of the input image. Then, a modified local adaptive thresholding is applied to the contrast-stretched image. The second step is divided into three processes: eliminating text-like components by applying erosion, dilation, and (OpenClose+CloseOpen)/2 morphological operations, maintaining text components using (OpenClose+CloseOpen)/2 operation with a new Geo-correction method, and subtracting two result images for eliminating false-positive components further. In the third filtering step, the characteristics of each component such as the ratio of the number of pixels in each candidate component to the number of its boundary pixels and the ratio of the minor to the major axis of each bounding box are used. Acceptable results have been obtained using the proposed method on 300 news images with a recognition rate of 93.6%. Also, my method indicates a good performance on all the various kinds of images by adjusting the size of the structuring element.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.26 no.4
• /
• pp.304-310
• /
• 1981

In order to observe the degree and response of drought-resistance and its physiological mechanism in barley and wheat, 5 species (16 cultivars) were tested for changes in plant height, seedling dry weight, chlorophyll content, leaf relative turgidity, soluble protein, reducing sugar and growth of seedling subjected to water stress by withholding watering for 8 days at 10 days (at the 3rd leaf stage) after emergence. The average rate of decrease of all cultivars was 15% in plant height, 24% in seedling dry weight, 32% in chlorophyll content, 27% in leaf relative turgidity, and 27% in protein. But reducing sugar content of control was increased 4 folds more than that of water stress. In the decreased rate of seedling dry weight of each cultivar, rye was shown to be lowest rate, and Baegdong, Mokpo #55, and 3 two-row barley were shown to be the highest rate. The degree of the decreased rate in 5 species was in the order of rye < < wheat < covered barley < naked barley < two-row barley. in the decreased rate of chlorophyll content, rye, Cheonggaemil and Olmil are the lowest group, and the highest one are Milyang #12, Bangsa #6, Hyangmaeg and Sacheon #4. In the decreased rate of leaf relative turgidity, the lowest group (22-25%) were rye, Cheonggaemil and Dongbori #1, and, on the other hand, the highest group (30-33%) were Baegdong and 3 two-row barley. In the decreased rate of soulble protein, the lowest group (14-17%) were Chogwang, Geurumil, Dongbori #1, and Mokpo #55, and the highest one was 3 two-row barley. The increased ratio of reducing sugar of water stress to control was 4 to 5 folds in rye and wheat, and about 2 folds in naked barley and 3 two-row barley. The degree of the increased ratio of 5 species was in the order of rye > wheat > covered barley > naked barley > two-row barley. In terms of the physiological and adaptive metabolism during the processing leading to drought-resistance, the degree of drought-resistance of 5 species to water stress at seedling stage was shown to be in the order of rye > wheat > covered barley > naked barley > two-row-barley.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.119-142
• /
• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.