• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.1-8
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• 2022

In order to manufacture feed suitable for consumer use and provide feed value information, we analyzed the feed components of the four main forage rice varieties by plant parts harvested 30 days after heading. The contents of the six feed ingredients were significantly different (p<0.05) among harvested parts. In the panicle, the crude protein (CP) (6.97%) and lignin (3.11%) were the highest, while the crude ash (CA) and neutral detergent fiber (NDF) contents were significantly lower, resulting in a total digestible nutrient (TDN) content of 77.29%, which is higher than that of the stem (64.82%) and leaf blade and sheath (LBS) (63.57%) (p<0.05). In contrast, the content of crude fat (CF) did not differ significantly among parts (p<0.05). In panicles from 'Jonong', 'Nokyang' and 'Yeongwoo', the TDN content of each cultivar was 78.48-79.07%, with no significant difference among the varieties. In 'Mogwoo' (Mw), the CP content was 8.70%, which was much higher than that of other varieties (p<0.05). In particular, the Mw TDN content was slightly lower in the panicle (72.95%) but higher in the stem (75.37%) and LBS (66.49%) than in the other varieties. The CA, NDF, acid detergent fiber (ADF), and lignin contents were also very low compared to other varieties; therefore, the feed value of the stem and LBS was excellent. In addition, the total dry matter weight (DMW) was 123 g per hill, which was much higher than 82-105 g per hill for other varieties. The distribution of DMW by part was LBS (56.9 g), stem (36.8 g), and panicle (29.3 g), and because the parts, except the panicles, were much higher than the 43-57% of other varieties (grain straw ratio: 76%), rice straw is advantageous in terms of quantity and feed value when used as forage on farms. The relative feed value (RFV) of the four cultivars ranged from 86.79-403.74 across all parts, and hay of grade 3 or higher with an RFV of 100 or more increased with delayed heading in both stems and LBS. This is due to the accumulation of starch into grains during ripening, which supports the observation that the RFV of the early flowering 'Jonong' and 'Nokyang' panicles increased.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.9
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• pp.1172-1181
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• 2007

This research involved 226 Jeonbuk Province school dietitians as subjects to investigate intake and perceptions of the healthy functional foods. Sixty nine percent of the school dietitians didn't even know about the law enforcement concerning the health functional foods. Although 68.1% of the respondents said that they slightly knew about health functional foods, only 25% knew exactly what it was. As shown in the survey, most didn't have the cognitive understanding did not understand which should be obtained by education. Sixty two percent of the answerers said they had experience of taking health various functional food products of various kinds such as supplements (57.9%), red ginseng products (52.9%), and chlorella products (30.0%). The motive of intake was in the order of fatigue restoration (25.7%), sickness prevention (22.9%), and nutrient replenishment (22.9%). A fascinating fact from this study was that the reason for healthy functional product intake was different between groups that was primarily interested in the products and those that was not. For those who had interest, the reason for intake was for sickness prevention. On the other hand, for those who didn't have any interest, the reasons was primarily for fatigue restoration and they were mostly persuaded by close friends and relatives. Main concerns were in the order of side effects (4.72), efficacy after intake (4.59), cleanliness (4.51), reliability of the company (4.29), and price (4.23). In view of the study, it is clear that a lot of people are showing interest in healthy functional food products. However, dietitians who are experts in food and nutrition lacked knowledge and information on healthy functional food.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.6
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• pp.185-196
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(Quality of Service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to let only the minimum number of servers needed to handle current user requests ON. Previous studies on energy aware server cluster put efforts to reduce power consumption further or to keep QoS, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management based on autonomous learning for energy aware server clusters. Using parameters optimized through autonomous learning, our method adjusts server power mode to achieve maximum performance with respect to power consumption. Our method repeats the following procedure for adjusting the power modes of servers. Firstly, according to the current load and traffic pattern, it classifies current workload pattern type in a predetermined way. Secondly, it searches learning table to check whether learning has been performed for the classified workload pattern type in the past. If yes, it uses the already-stored parameters. Otherwise, it performs learning for the classified workload pattern type to find the best parameters in terms of energy efficiency and stores the optimized parameters. Thirdly, it adjusts server power mode with the parameters. We implemented the proposed method and performed experiments with a cluster of 16 servers using three different kinds of load patterns. Experimental results show that the proposed method is better than the existing methods in terms of energy efficiency: the numbers of good response per unit power consumed in the proposed method are 99.8%, 107.5% and 141.8% of those in the existing static method, 102.0%, 107.0% and 106.8% of those in the existing prediction method for banking load pattern, real load pattern, and virtual load pattern, respectively.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• Journal of Plant Biotechnology
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• v.35 no.4
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• pp.307-316
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• 2008

Transposon-mediated insertional mutagenesis is one of powerful strategy for assessing functions of genes in higher plants. In this report, we have selected highly susceptible and tolerance plant by screening about high salt (3% NaCl) and cold stresses ($4^{\circ}C$) from F2 seeds of 30,000 Ac/Ds insertional mutagenesis lines in rice (Oryza sativa L. cv. Dongjin). In order to identify the gene tagging, insertion of Ds element was analyzed by Southern blot and these results revealed that 19 lines were matched genotype of selected lines with phenotype from the first selected 212 lines, and 13 lines have one copy of Ds elements. The Franking Sequence Tags (FSTs) of selected mutant lines showed high similarities with the following known function genes: signal transduction and regulation of gene expression (transpoter, protease family protein and apical meristem family protein), osmotic stress response (heat shock protein, O-methyltransferase, glyceraldehyde-3-phosphate dehydrogenase and drought stress induce protein), vesicle trafficking (SYP 5 family protein) and senescence associated protein. The expression pattern of 19 genes were analyzed using RT-PCR under the abiotic stresses of 9 class; 250mM NaCl, osmotic, drought, 3% $H_2O_2$, $100{\mu}M$ ABA, $100{\mu}M$ IAA, 0.1 ppm 2,4-D, $4^{\circ}C$ cold and $38^{\circ}C$ high temperature. Isolated knock-out genes showed the positive response about 250 mM NaCl, drought, $H_2O_2$, PEG, IAA, 2,4-D, ABA treatment and low ($4^{\circ}C$) and high temperature ($38^{\circ}C$). The results from this study indicate that function of selected knock-out genes could be useful in improving of tolerance to abiotic stresses as an important transcriptional activators in rice.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.

• Clinical and Experimental Pediatrics
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• v.48 no.7
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• pp.701-705
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• 2005

Purpose : Parents' genetic information plays an important role in their children's genetic expression. Human chromosome has 23-paternal chromosomes and 23-maternal chromosomes. Parental chromosomal translocation can induce clinical problems in their children because of imbalance in genetic information. We intent to analyze the cytogenentic and clinical features about children with maternal balanced translocation between chromosome 15 and 18. Methods : We detected by one family's FISH study of chromosome 15. We have evaluated children born to clinically normal parents about peripheral bood analysis, endocrine, metabolic, radiologic study, electroencephalogram and social & intelligence scale. and We analysis their clinical manifestation by hospital records. Results : Patient's father and elder sister are normal clinically and genetically. Her mother's chromosome show balanced translocation, 46, XX, t(15;18)(p11.2;p11.3). One child has 46, XX, der(18) t(15;18)(p11.2;p11.3), mental retardation, growth retardation, speech & social developmental delay, recurrent infection and mild mitochondria dysfunction. Her young brother has 46, XY, der(15) t(15;18) (p11.2;p11.3), mental retardation, aggressive behavior, obesity and speech developmental delay. Conclusion : In this study we observed the children with developmental delay, dysmorphic facial features, mental retardation, growth retardation associated with growth hormone deficiency and aggressive behavior due to unbalanced translocation between chromosome 15 and 18.

• Journal of agricultural medicine and community health
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• v.37 no.3
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• pp.167-180
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• 2012

Objective: This study was conducted to evaluate an education program for cardiocerebrovascular high-risk patients. Methods: This program was developed according to Tyler's model for curriculum development. To evaluate the effects of this program, we measured clinical outcome change (weight, waist circumference, systolic blood pressure, diastolic blood pressure) and behavior change stages (checking blood pressure, blood sugar levels, doing physical activity, consistent maintenance of food intake, eating low amounts of salt, abstention from tobacco and alcohol) before and 4 weeks after participation in the education program. The group of subjects consisted of High-risk group patients who attended basic program(32 patients), and staged program(37 patients) during KHyDDI meetings from Oct. 2009 to May 2010. Results: The staged educational program was developed three aspects(disease, nutrition and exercise)and three stages(basic, in-depth and individual education). In the staged education program, the evaluations were made by measuring clinical outcome and stage of behavior before and after education. Significant differences were found in waist circumference, systolic blood pressure, diastolic blood pressure, consistent maintenance of food intake(p<0.05), and eating low salt(p<0.001)and their self efficacy. Conclusion: In the practice-oriented staged education program, significant differences were found in the clinical outcomes and stage of behavior before and after education. Possible limitations of the study include the small number of participating subjects and the short follow-up management period, but the results indicate that continued application of this program could contribute to the prevention of cardiocerebrovascular diseases for the elderly patients with long periods of chronic diseases.

• Korean Security Journal
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• no.39
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• pp.37-61
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• 2014

Nowadays the world is threatened because of terrors that take aim at Soft-Targets available and easy to access to the people rather than more secured Hard-Targets. The inspection department of the Presidential Security Service develops and acts a perfect safety plan wherever the President stays so that it is possible to get immediate actions for various contingencies. Some events, in which the President take part, could be held in a lower or higher store in a tall building. Additional to the routine work at this case it is to emphasize on a plan of fire precaution to check the spot and respond to a real fire situation, so that the damage could be minimized. First, the agents of the President Security Service should possess basic knowledge concerning to the fire accidents and be trained on their manuals, even in a busy events plan. An organization, whatever it is, could be improved in that it tries to develop not only the personal abilities, but also education programs of the organization continually. And enhanced abilities of the members lead to the driving force for the advance. The knowledge of fire accident should be able to adapt to the real situation. Second, related to the event, it should be cooperated with the relevant departments, so that it is possible to conduct and control the system. It is urgently required to know that the security event could not be done perfectly with only one part or department. Third, from the time of recognizing of the event it is necessary for the fire department to get an action plan with fire fighting measures, evacuation measures based of the instructions given by the Security Service. Fourth, on the knowledge of the action plan of the fire department the Security Service should inspect the safety activities of the spot and establish the practical operation plan through the fire fighting and evacuation plan. Fifth, the Security Service should share final informations and plan of fire fighting in a high-rise building with the other relevant departments. If not, it could cause a great confusion that could lead to a great damage.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.377-391
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• 2018

In order to efficiently monitor red tide over a wide range, the need for red tide detection using remote sensing is increasing. However, the previous studies focus on the development of red tide detection algorithm for ocean colour sensor. In this study, we propose the use of multi-sensor to improve the inaccuracy for red tide detection and remote sensing data in coastal areas with high turbidity, which are pointed out as limitations of satellite-based red tide monitoring. The study area were selected based on the red tide information provided by National Institute of Fisheries Science, and spatial fusion and spectral-based fusion were attempted using GOCI image as ocean colour sensor and Landsat OLI image as terrestrial sensor. Through spatial fusion of the two images, both the red tide of the coastal area and the outer sea areas, where the quality of Landsat OLI image was low, which were impossible to observe in GOCI images, showed improved detection results. As a result of spectral-based fusion performed by feature-level and rawdata-level, there was no significant difference in red tide distribution patterns derived from the two methods. However, in the feature-level method, the red tide area tends to overestimated as spatial resolution of the image low. As a result of pixel segmentation by linear spectral unmixing method, the difference in the red tide area was found to increase as the number of pixels with low red tide ratio increased. For rawdata-level, Gram-Schmidt sharpening method estimated a somewhat larger area than PC spectral sharpening method, but no significant difference was observed. In this study, it is shown that coastal red tide with high turbidity as well as outer sea areas can be detected through spatial fusion of ocean colour and terrestrial sensor. Also, by presenting various spectral-based fusion methods, more accurate red tide area estimation method is suggested. It is expected that this result will provide more precise detection of red tide around the Korean peninsula and accurate red tide area information needed to determine countermeasure to effectively control red tide.