• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8B
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• pp.691-700
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• 2006

Based on the destination IP address of incoming packets, the Internet routers determine next hops and forward packets toward final destinations through If address lookup. The bandwidth of communication links increases exponentially fast as well as the routing table size grows significant as the number of single host networks attached to the Internet increases. Since packets should be processed at wire-speed, the increased link speed reduces the processing time of a packet in routers, and hence more efficient and fast IP address lookup algorithms and architectures are required in the next generation routers. Most of the previous IP lookup schemes compare routing prefixes of shorter length first with a given input IP address. Since IP address lookup needs to find the most specific route of the given input, search continues until the longest matched prefix is found while it keeps remembering the current test matching prefix. In this paper, based on binary search on prefix length, we proposed a new IP address lookup algorithm which compares longer prefixes first. The proposed scheme is consisted of multiple tries with prefixes on leaves only. The trie composed of the longest prefixes is primarily searched whether there is a match with the given input. This processing is repeated for the trio of the next longer prefixes until there finds a match. Hence the proposed algorithm provides the fast search speed. The proposed algorithm also provides the incremental update of prefixes while the previous binary search on length scheme does not provide the incremental update because of pre-processing requirement. In this paper, we performed extensive simulations and showed the performance comparisons with related works.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.77-92
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• 2014

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

• The Korean Society of Law and Medicine
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• v.19 no.2
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• pp.41-72
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• 2018

In the division of labor (or teamwork) in medicine, the responsibility of medical and nursing staff should be separated or distributed to justify negligent criminal offenses. The present work refers to the standards by which the due diligence and responsibility of the individual persons are to be determined and delimited. In this context, it has been proven that objective theory as a measure of due diligence is appropriate. From a moral point of view, when assessing due diligence, it makes sense to impose greater individual or higher performance demands on the perpetrator, but law and order require that due diligence should result from socially relevant human behavior. To give objective measure of negligence and to provide the highest level of personal responsibility, so that man can not be burdened too much responsibility and it is accordingly with an equality theorem. Afterwards some points are presented, which should be considered in a concrete fact in the determination of the medical negligence. Medical action has specific characteristics such as professionalism, discretionary and exclusive, unbalance of information. These characteristics distinguish medical actions from general negligence. The general level of knowledge, the urgency, working condition and working environment of the medical facility, duration of the professional practice, assessment of the medical activity are crucial in this context. As a standard of delineation of due diligence, I have used the permitted risk and the principle of trust. In the horizontal division of labor, the principle of trust applies. The principle of trust applies in principle in cases of division of labor interaction, when doctors in the same hospital exercise their own specific occupational field or everyone works in another hospital. However, this is not true for every case. In the vertical division of labor, the principle of trust does not apply and the senior physician can not trust the assistant doctors. In this case, the principle of trust is converted into a duty of supervision for assistant doctors by the senior physician. This supervision requirement could be used as a random check.

• Journal of The Korean Society of Grassland and Forage Science
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• v.33 no.4
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• pp.298-303
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• 2013

This study investigates the effect of a feed concentrate on the growth performance, feed requirement, and rearing expenses of growing black goats. Forty female growing black goats were divided into four groups and fed rice straw (ad libitum) mixed with different levels of the feed concentrate: T1 (1.5%), T2 (1.8%), T3 (2.1%), and T4 (0%, control). The average daily weight gain (body weight per day) was as follows: T1 < T2 < T3 < T4 (50.23, 60.37, 71.46 and 98.90 g/day, respectively) (p<0.05). The intake of rice straw decreased significantly with increase in the concentrate level (p<0.05). Rearing expenses amounted to 46,704, 49,998, 54,701, and 74,613 won for feed concentrate levels of 1.5%, 1.8%, 2.1%, and ad libitum, respectively. Increase in feed concentrate levels led to an increase in rearing expenses. In conclusion, a concentrate level of 2.1% was determined to be idea for a rice-straw-based feed for growing black goats.

• Journal of the Korean Society of Food Science and Nutrition
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• v.12 no.4
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• pp.395-400
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• 1983

The experiment was conducted to study the effect of protein level on weight gain, feed consumption and the efficiencies of feed, energy and protein when the broiler chick was fed the diet of different protein level with the iso-calorie content. The energy and protein level of the basal ration was 3200 kcal and 22.85% for starter period and 3265 Kcal and 18.58% for finisher period, respectively. In order to increase the protein level of the experimental diet, the basal diet was substituted by fish meal by the ratio of 3, 6, 9, and 12%. The male Abor Acre broiler chicks were employed for 8 weeks and the result obtained were as follows. 1. The weekly body weight gain was significantly greater for Diet C than for Diet A and E in the starter period and greater for Diet A than for Diet E in the finisher period (P<0.05). 2. In stater period the feed intake was not affected by the protein level but in finisher period the feed intake for Diet C, D, and E was significantly reduced compared with Diet A. 3. As for feed conversion ratio, Diet C of 1.43 was improved significantly compared with Diet A of 1.58(P<0.05). 4. As the protein level of diet increased, the energy efficiency ratio increased and however, the protein efficiency ratio decreased in starter and finisher period. In conclusion the best performance of broiler is thought to be realized when the protein and energy level was 23% and 3200 Kcal for starter period and 20% and 3250 Kcal for finisher period, respectively.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.213-222
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• 1998

Electro-Optical Camera(EOC) is the main payload of the KOrea Multi-Purpose SATellite(KOMPSAT) with the mission of cartography to build up a digital map of Korean territory including a Digital Terrain Elevation Map(DTEM). This instalment which comprises EOC Sensor Assembly and EOC Electronics Assembly produces the panchromatic images of 6.6 m GSD with a swath wider than 17 km by push-broom scanning and spacecraft body pointing in a visible range of wavelength, 510~730 nm. The high resolution panchromatic image is to be collected for 2 minutes during 98 minutes of orbit cycle covering about 800 km along ground track, over the mission lifetime of 3 years with the functions of programmable gain/offset and on-board image data storage. The image of 8 bit digitization, which is collected by a full reflective type F8.3 triplet without obscuration, is to be transmitted to Ground Station at a rate less than 25 Mbps. EOC was elaborated to have the performance which meets or surpasses its requirements of design phase. The spectral response, the modulation transfer function, and the uniformity of all the 2592 pixel of CCD of EOC are illustrated as they were measured for the convenience of end-user. The spectral response was measured with respect to each gain setup of EOC and this is expected to give the capability of generating more accurate panchromatic image to the users of EOC data. The modulation transfer function of EOC was measured as greater than 16 % at Nyquist frequency over the entire field of view, which exceeds its requirement of larger than 10 %. The uniformity that shows the relative response of each pixel of CCD was measured at every pixel of the Focal Plane Array of EOC and is illustrated for the data processing.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1209-1215
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• 2022

The selective catalytic reduction (SCR) is known as a very efficient method to reduce nitrogen oxides (NOx) and the catalyst performs reduction from nitrogen oxides (NOx) to nitrogen (N₂) and water vapor (H2O). The catalyst, which is one of the factors determining the performance of the nitrogen oxide (NOx) ruduction method, is known to increase catalyst efficiency as cell density increases. In this study, the reduction characteristics of nitrogen oxides (NOx) under various engine loads investigated. A 100CPSI(60Cell) catalysts was studied through a laboratory-sized simulating device that can simulate the exhaust gas conditions from the power generation engine installed in the training ship SEGERO. The effect of 100CPSI(60Cell) cell density was compared with that of 25.8CPSI(30Cell) cell density that already had NOx reduction data from the SCR manufacturing. The experimental catalysts were honeycomb type and its compositions and materials of V₂O₅-WO₃-TiO₂ were retained, with only change on cell density. As a result, the NOx concentration reduction rate from 100CPSI(60Cell) catalyst was 88.5%, and IMO specific NOx emission was 0.99g/kwh satisfying the IMO Tier III NOx emission requirement. The NOx concentration reduction rate from 25.8CPSI(30Cell) was 78%, and IMO specific NOx emission was 2.00g/kwh. Comparing the NOx concentration reduction rate and emission of 100CPSI(60Cell) and 25.8CPSI(30Cell) catalysts, notably, the NOx concentration reduction rate of 100CPSI(60Cell) catalyst was 10.5% higher and its IMO specific NOx emission was about twice less than that of the 25.8CPSI(30Cell) catalysts. Therefore, an efficient NOx reduction effect can be expected by increasing the cell density of catalysts. In other words, effects to production cost reduction, efficient arrangement of engine room and cargo space can be estimated from the reduced catalyst volume.