• Korean Journal of Environment and Ecology
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• v.26 no.1
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• pp.46-56
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• 2012

Benthic macroinvertebrates were investigated in Hoeongseong Lake region from March to October 2010, Korea. Macroinvertebrate communities, composition of the functional feeding groups, habitiat oriented groups and the biological water quality were assessed above and below Hoeongseong Dam in the lake region. Six sites, two (St.1~2) above the lake, two (St. 3~4) into the lake, and two (St. 5~6) below the dam, were selected for quantitative (Surber sampler $30cm{\times}30cm$, mesh size 0.2 mm) and qualitative (Hand net) samplings of benthic macroinvertebrates. As a result, a total of 83 species belonging to 43 families, 17 orders, 8 classes, and 5 phyla were recognized. The EPT-group (50 spp. : 60.24%) that is major taxa or EPT-group plus Diptera (61 spp. : 73.49%) occupied most of benthic macroinvertebrates community. Based on quantitative sampling, the number of benthic maroinvertebrates above the lake was 2,399 individuals including 54 species, 28 families, 11 orders, 4 classes, and 4 phyla, whereas 510 individuals including 16 species, 12 families, 7 orders, 4 classes, and 3 phyla in the lake and 626 individuals including 62 species, 33 families, 13 orders, 6 classes, and 4 phyla below the dam were collected respectively. Dominance index was the highest, with 0.82-0.93 ($0.87{\pm}0.05$) in Hoeongseong lake (St. 3-4), diversity index was 3.04-3.16 ($3.10{\pm}0.06$), evenness index was 0.79-0.85 ($0.82{\pm}0.03$), and richness index was 7.27-8.52 ($7.90{\pm}0.63$), which were relatively higher below the dam sites. In the functional feeding groups, collector-gatherers and collector-filterers were the highest in the whole sites, and predators (Micronecta sedula) was appeared highly in the lake. Moreover, swimmers, burrowers, and clingers were considerably occupied in all collecting sites. The result of the DCA, similarity analysis, and MRPP were well reflective of the composition of lake and stream macroinvertebrates. ESB indicate that the lake sites were evaluated heavily polluted under priority improvement waters. Also, Semisulcospira gottschei, Ecdyonurus kibunensis, Epeorus pellucidus, Rhoenanthus coreanus, Stenelmis sp., and Cheumatopsyche brevilineata are considered as an indicator species above and below Hoeongseong Lake, whereas Macrobrachium nipponense and Micronecta sedula are indicated in the lake.

• The Korean Journal of Soil Zoology
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• v.6 no.1_2
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• pp.25-31
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• 2001

Oribatid mite communities in the process of litter decomposition were analyzed In Korean pine (Pinus koraiensis) forests of Namsan and Kwangreung, which were supposed to be under different environmental selective pressures. Oribatid mites were collected bimonthly from the litter bags (mesh size 0.4 mm, 1.7 mm) which was set up in the forest floor of study sites. This study had been carried out from Jan., 1997 to Sept., 1998. Species abundance of Kwangreung (mesh size 1.7 mm) was significantly higher than that of Namsan (mesh size 1.7 mm), but total no. of species did not exceed 30 species in all study sites. Concerning body length, medium sized oribatid mites (0.3-0.7mm) were more abundant than small ( < 0.3 mm) and large ( > 0.7 mm) sized mites. In Kwangreung, species whose body lengths were 0.2 mm to 0.5 mm were major group. However, a little larger species than Kwangreung's major group were dominant in Namsan. Sorenson similarity index and cluster analysis suggested that there were qualitative and quantitative differences in species composition in Namsan and Kwangreung. More species were collected in May through September than the other sampling times, but the pattern was rather different between first year and second year. Newly immigrant species were high in May in the first year and many of them regained on next year. Diversity indices suggested that species diversity of Kwangreung was higher than that of Namsan. Nearly 70% of total individual abundance was occupied by several dominant species in Namsan and Kwangreung . In the litter bags of mesh size 1.7 mm, the most dominant species was Trichogalumna nipponica in Namsan and Kwangreung, but in the litter bags of mesh size 0.4 mm in Kwangreung it was Ramusella sengbuschi which is smaller than T. nipponica. And important species related to litter decomposition were selected as follows; T. nipponica, Epidamaeus coreanus, Scheloribates latipes, Ceratozetes japonicus, Ramusella sengbuschi, Eohypochthonius crassisetiger, and Cultroribula lata.

• Korean Journal of Environmental Agriculture
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• v.16 no.4
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• pp.295-303
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• 1997

To investigate the transformation characteristics of nitrogen and carbon from cow manure compost amended in soil under different moisture conditions, dynamics of nitrogen and carbon were determined periodically for 15 weeks of aerobic incubation at room temperature during July${\sim}$November, 1996. Cow manure compost matured with mixing saw dust was amended with the 4 ratios (0, 2, 4, 6%(wt/wt)) in Ap horizon soil, which collected from green house in Yesan, Chungnam. Moisture was controlled with 0.2, 0.3, 0.4, and 0.5 of mass water conte nt (${\theta}$m) to air dried soil, and water loss was compensated at every sampling. During incubation, soil pH was decreased continuously, that was caused by hydrogen generated from nitrification of ammonium nitrogen. And pH became higher with inclining cow manure compost amendment and water treatment, that meaned the increase of mineralization of organic-N to $NH_4\;^+-N$. Total nitrogen was reduced with increasing water content, but total carbon showed the contrast tendency with that of nitrogen. Therefore, C/N ratio slightly decreased in the low water condition (${\theta}$m 0.2) during incubation, but increased continuously in high water condition over ${\theta}$m 0.4. As a result, it was assumed that soil fertility is able to be reduced in the high water content over available water content. Nitrate transformation rate increased lasting in the low water content less than ${\theta}$m 0.3. Itdropped significantly in the first $2{\sim}3$ weeks of incubation over ${\theta}$m 0.4. In particular, nitrate was not detected in ${\theta}$m 0.5 of water content after the first $2{\sim}3$ weeks. In contrast, ammonium transformation was inclined with increasing water treatment. Nitrogen mineralization rate, which calculated with percentage ratio of (the sum of ex.$NH_4\;^+-N$ and $NO_3\;^--N$)/total nitrogen, was continuously increased in the low water content of ${\theta}$m 0.2 and 0.3. But it saw the different patterns in high water content over ${\theta}$m 0.4 that was drastically declined in the initial stage and then gradually inclined . From the above results, nitrogen transformation patterns differentiated decisively in water content between ${\theta}$m 0.3 and 0.4 in soil. Thus, it is very important for the maintain of suitable soil water content to enhance fertility of soil amended with manure compost. However, excess treatment of manure compost might enhance the possibility of contamination of small watershed and ground water around agricultural area.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Korean Journal of Soil Science and Fertilizer
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• v.33 no.1
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• pp.24-31
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• 2000

This study was conducted to determine the effect of soil physical characteristics on rhizome rot incidence of platycodon. Sampling sites were Keochang 4, Kimhae 7, Haman 6, Chinju 6 and Koseong 3 fields in Kyongnam province and Hongcheon 6 fields in Kangwon province. The root disease incidence rate was correlated with soil depth Y=-0.747X+88.19($R^2=0.394^{***}$), soil hardness Y=4.36X+8.93($R^2=0.201^*$), bulk density Y=104.7X-80.99($R^2=0.295^{**}$), clay content Y=1.24X+14.14($R^2=0.196^*$), porosity Y=-3.11X+215.9($R^2=0.220^*$) and silt content Y=-0.75X+67.85($R^2=0.178^*$). The yield was correlated with soil depth Y=0.263X+0.971($R^2=0.105^*$), clay content Y=-0.688X+32.74($R^2=0.158^*$), porosity Y=1.974X-93.19($R^2=0.231^{**}$) and silt content Y=53.05X-108.65($R^2=0.232^*$), The optimum cultivated land of perennial platycodon was soil depth over 1m, soil hardness under $5kg\;cm^{-2}$, bulk density $1.0Mg\;m^{-3}$, moisture content 13~17%. clay content 5~10%, porosity 58~63%, silt content 38~64% and soil texture of silt loam.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.11 no.3
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• pp.229-234
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• 2001

The EDXRF(Energy Dispersive X-ray Fluorescence Spectrometer) technique was applied to the determination of heavy metals in welding fume. The EDXRF method designed in this study was a non-destructive analysis method. Samples were analyzed directly by EDXRF without any pre-treatment such as digestion and dilution. The samples used to evaluate this method were laboratory samples exposed in a chamber connected with a welding fume generator. The samples were first analyzed using a non-destructive EDXRF method. The samples subsequently were analyzed using AAS method to verify accuray of the EDXRF method. The purpose of this study was to evaluate the possibility of the non-destructive analysis of heavy metals in welding fume by EDXRF. The results of this study were as follow: 1.When the samples were collected under the open-face sampling condition, a surface distribution of welding fume particles on sample filters was uniform, which made non-destructive analysis possible. 2. The method was statistically evaluated according to the NIOSH(National Institute for Occupational Safety and Health) and HSE(Health and Safety Executive) method. 3. The overall precision of the EDXRF method Was calculated at 3.45 % for Cr, 2.57 % for Fe and 3.78 % for Mn as relative standard deviation(RSD), respectively. The limits of detection were calculated at $0.46{\mu}g$/sample for Cr, $0.20{\mu}g$/sample for Fe and $1.14{\mu}g$/sample for Mn, respectively. 4. A comparison between the results of Cr, Fe, Mn analyzed by EDXRF and AAS was made in order to assess the accuracy of EDXRF method. The correlation coefficient between the results of EDXRF and AAS was 0.9985 for Cr, 0.9995 for Fe and 0.9982 for Mn, respectively. The overall uncertainty was determined to be ${\pm}12.31%$, 8.64 % and 11.91 % for Cr, Fe and Mn, respectively. In conclusion, this study showed that Cr, Fe, Mn in welding fume were successfully analyzed by the EDXRF without any sample pre-treatment such as digestion and dilution and a good correlation between the results of EDXRF and AAS was obtained. It was thus possible to use the EDXRF technique as an analysis method of working environment samples. The EDXRF method was an efficient method in a non-destructive analysis of heavy metals in welding fume.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.954-961
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• 2010

Ground-based remote sensing can be used as one of the non-destructive, fast, and real-time diagnostic tools for quantifying yield, biomass, and nitrogen (N) stress during growing season. This study was conducted to assess biomass and nitrogen (N) status of paddy rice (Oryza sativa L.) plants under N stress using passive and active ground-based remote sensors. Nitrogen application rates were 0, 70, 100, and 130 kg N $ha^{-1}$. At each growth stage, reflectance indices measured with active sensor showed higher correlation with DW, N uptake and N concentration than those with the passive sensor. NIR/Red and NIR/Amber indices measured with Crop Circle active sensors generally had a better correlation with dry weight (DW), N uptake and N content than vegetation indices from Crop Circle passive sensor and NDVIs from active sensors. Especially NIR/Red and NIR/amber ratios at the panicle initiation stage were most closely correlated with DW, N content, and N uptake. Rice grain yield, DW, N content and N uptake at harvest were highly positively correlated with canopy reflectance indices measured with active sensors at all sampling dates. N application rate explains about 91~92% of the variability in the SI calculated from NIR/Red or NIR/Amber indices measured with Crop Circle active sensors on 12 July. Therefore, the in-season sufficiency index (SI) by NIR/Red or NIR/Amber index from Crop Circle active sensors can be used for determination of N application rate.

• 한국노년학
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• v.29 no.2
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• pp.629-643
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• 2009

The purpose of this study is, by using the demographic variables, to identify self-efficacy, social support, and quality of life of the elderly with depression and to assess the impacts of these factors upon their quality of life. By analyzing the factors which have an impact upon the life quality of the elderly with depression, this study aims to provide important information which help understand them, and to find out what kind of care is necessary for their happy and satisfactory life. The study took purposive sampling and survey of 215 people among the elderly with depression who were under care of the outpatient clinics, day hospitals, and mental health clinics located in Seoul and Kyunggi Province, Korea. This study was conducted from November 10th to 20th, 2008 and the data were collected using the questionnaires of self-efficacy, social support, and quality of life scales. Using a SPSS/WIN 15.0 program, the analysis of the data showed the following results. First, among the demographic characteristics, the elderly with depression who were male, had spouse, higher education, no public assistance, shorter period of depression, and were healthy turned out to have higher self-efficacy. In terms of social support, the participants who had higher education, no public assistance, and were healthy turned out to have more social support. Further, in terms of quality of life, the variables of spouse, public assistance, period of depression, and health condition were statistically significant. Second, as a result of hierarchical regression, it appeared that the elderly with depression, who had higher self-efficacy, more social support, spouse, good health, no public assistance, and shorter period of depression, turned out to have higher quality of life. Based on the study findings, the implications of social work practice, policy, and future research were discussed.

• Journal of Global Scholars of Marketing Science
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• v.20 no.2
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• pp.179-187
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• 2010

Understanding consumers' preferences and use of media types is imperative for marketing and advertising managers, especially in today's fragmented market. A clear understanding assists managers in making more effective selections of appropriate media outlets, yet individuals' choices of type and use of media are based on a variety of characteristics. This paper examines one personality trait, sensation seeking, which has not appeared in the literature examining "new" media preferences and use. Sensation seeking is a personality trait defined as "the need for varied, novel, and complex sensations and experiences and the willingness to take physical and social risks for the sake of such experiences" (Zuckerman 1979). Six hypotheses were developed from a review of the literature. Particular attention was given to the Uses and Gratification theory (Katz 1959), which explains various reasons why people choose media types and their motivations for using the different types of media. Current theory suggests that High Sensation Seekers (HSS), due to their needs for novelty, arousal and unconventional content and imagery, would exhibit higher frequency of use of new media. Specifically, we hypothesize that HSS will use the internet more than broadcast (H1a) or print media (H1b) and more than low (LSS) (H2a) or medium sensation seekers (MSS) (H2b). In addition, HSS have been found to be more social and have higher numbers of friends therefore are expected to use social networking websites such as Facebook/MySpace (H3) and chat rooms (H4) more than LSS (a) and MSS (b). Sensation seekers can manifest into a range of behaviors including disinhibition,. It is expected that alternative social networks such as Facebook/MySpace (H5) and chat rooms (H6) will be used more often for those who have higher levels of disinhibition than low (a) or medium (b) levels. Data were collected using an online survey of participants in extreme sports. In order to reach this group, an improved version of a snowball sampling technique, chain-referral method, was used to select respondents for this study. This method was chosen as it is regarded as being effective to reach otherwise hidden population groups (Heckathorn, 1997). A final usable sample of 1108 respondents, which was mainly young (56.36% under 34), male (86.1%) and middle class (58.7% with household incomes over USD 50,000) was consistent with previous studies on sensation seeking. Sensation seeking was captured using an existing measure, the Brief Sensation Seeking Scale (Hoyle et al., 2002). Media usage was captured by measuring the self reported usage of various media types. Results did not support H1a and b. HSS did not show higher levels of usage of alternative media such as the internet showing in fact lower mean levels of usage than all the other types of media. The highest media type used by HSS was print media, suggesting that there is a revolt against the mainstream. Results support H2a and b that HSS are more frequent users of the internet than LSS or MSS. Further analysis revealed that there are significant differences in the use of print media between HSS and LSS, suggesting that HSS may seek out more specialized print publications in their respective extreme sport activity. Hypothesis 3a and b showed that HSS use Facebook/MySpace more frequently than either LSS or MSS. There were no significant differences in the use of chat rooms between LSS and HSS, so as a consequence no support for H4a, although significant for MSS H4b. Respondents with varying levels of disinhibition were expected to have different levels of use of Facebook/MySpace and chat-rooms. There was support for the higher levels of use of Facebook/MySpace for those with high levels of disinhibition than low or medium levels, supporting H5a and b. Similarly there was support for H6b, Those with high levels of disinhibition use chat-rooms significantly more than those with medium levels but not for low levels (H6a). The findings are counterintuitive and give some interesting insights for managers. First, although HSS use online media more frequently than LSS or MSS, this groups use of online media is less than either print or broadcast media. The advertising executive should not place too much emphasis on online media for this important market segment. Second, social media, such as facebook/Myspace and chatrooms should be examined by managers as potential ways to reach this group. Finally, there is some implication for public policy by the higher levels of use of social media by those who are disinhibited. These individuals are more inclined to engage in more socially risky behavior which may have some dire implications, e.g. by internet predators or future employers. There is a limitation in the study in that only those who engage in extreme sports are included. This is by nature a HSS activity. A broader population is therefore needed to test if these results hold.