• The Korean Journal of Nuclear Medicine Technology
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• v.25 no.2
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• pp.35-40
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• 2021

Purpose Glomerular filtration rate(GFR) is an important indicator for the diagnosis, treatment, and follow-up of kidney disease and is also used by healthy individuals for drug use and evaluating kidney function in donors. The gold standard method of the GFR test is to measure by continuously injecting the inulin which is extrinsic marker, but it takes a long time and the test method is complicated. so, the method of measuring the serum concentration of creatinine is used. Estimated glomerular filtration rate (eGFR) is used instead. However, creatinine is known to be affected by age, gender, muscle mass, etc. eGFR formulas that are currently used include the Cockroft-Gault formula, the modification of diet in renal disease (MDRD) formula, and the chronic kidney disease epidemilogy collaboration (CKD-EPI) formula for adults. For children, the Schwartz formula is used. Measurement of GFR using ⁵¹Cr-EDTA (diethylenetriamine tetraacetic acid), ^99mTc-DTPA (diethylenetriamine pentaacetic acid) can replace inulin and is currently in use. Therefore, We compared the GFR measured using ^99mTc-DTPA with the eGFR using CKD-EPI formula. Materials and Methods For 200 kidney transplant donors who visited Asan medical center.(96 males, 104 females, 47.3 years ± 12.7 years old) GFR was measured using plasma(Two-plasma-sample-method, TPSM) obtained by intravenous administration of ^99mTc-DTPA(0.5mCi, 18.5 MBq). eGFR was derived using CKD-EPI formula based on serum creatinine concentration. Results GFR average measured using ^99mTc-DTPA for 200 kidney transplant donors is 97.27±19.46(ml/min/1.73m²), and the eGFR average value using the CKD-EPI formula is 96.84±17.74(ml/min/1.73m²), The concentration of serum creatinine is 0.84±0.39(mg/dL). Regression formula of ^99mTc-DTPA GFR for serum creatinine-based eGFR was Y = 0.5073X + 48.186, and the correlation coefficient was 0.698 (P<0.01). Difference (%) was 1.52±18.28. Conclusion The correlation coefficient between the ^99mTc-DTPA and the eGFR derived on serum creatinine concentration was confirmed to be moderate. This is estimated that eGFR is affected by external factors such as age, gender, and muscle mass and use of formulas made for kidney disease patients. By using ^99mTc-DTPA, we can provide reliable GFR results, which is used for diagnosis, treatment and observation of kidney disease, and kidney evaluation of kidney transplant patients.

• Korea Science and Art Forum
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• v.32
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• pp.319-334
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• 2018

This research is a case study to make sure the enhancement of students' imagination and creativity through developing and applying the Literature-Art-Science Integrated Education Program. Its research object was totally 25 persons of 29 students of the 1st to the 4 th Grades from Gunsan Sulsan Elementary School. Its research period lasted for 4 months from September to December, 2017, and I, as the research place, used the art room at Gunsan Sulsan Elementary School. The programs were totally 10 sessions with a unit of 1 session per each grade for 2 hours from 1:00 to 3:00 in the afternoon from Monday through Friday. I fixed ten themes of this program-eight plane modeling, and two solid modeling, and finished the work of storytelling during summer vacation. And I arranged their levels as low:middle:high(3:5:2) ones. The former was 'A Film of Monster Gorilla'(L), 'Learning the Spirit of Gyeongju Choi's Family'(M), 'A Tale of My Friend Made of Natural Materials'(L), 'The Reading of My Dream'(M), 'Gathering the Objects in My Mobile'(M), 'A Mock Trial of Marrying Off'(M), 'Painting My Favorite Children's Poem'(H), and 'Painting My Favorite Children's Song'(H), and the latter was 'Seeking for a Bluebird in My Mind'(L), and 'Making My Cherished Object' (M). Then I used the unique art expression technique per each theme, which were in sequence marbling, Korean paper art, combine painting, collage, imaginary painting, imaginary painting, play dough art, imaginary painting techniques. And I delivered to the students the scientific knowledge in terms of growing or manufacturing processes of materials used for making artworks. Prior to and after the processing this program, I surveyed about the students' ability of integrated thinking and emotional experience by 'Figure B Type' and 'Figure A Type' of The Torrance Tests of Creative Thinking, and took statistics with the resultant data. And I executed a paired t-test in order to verify the significance of mean difference in the result of investigation with those data. From the analyzed result according to the elements of creativity and the mean quotients of creativity, there showed a significant difference (t=3.47, p<.01) in 'fluency', and also a significant difference(t=3.59, p<.01) in 'creativity.' Judging from the statistic values of two fields such as the student's ability of integrated thinking and emotional experience, I estimate that over the majority of the students showed the enhancement in self-confident creative expression as well as higher interest and concern through this program. The result that I arranged and analyzed the making process of artworks, the photos of the resultant, etc. as such is as follows : Firstly, from this program being proceeded as art-centered STEAM class, the student's systematic problem-solving ability was improved in his ability of integrated thinking to transform the literary contents into artistic one. Secondly, the student obtained the emotional experience such as interest in the class, self-confidence, intellectual satisfaction, self-fulfillment, etc. through art-centered STEAM class using ten art expression techniques. Thirdly, the student's mind willing to cooperate, communicate with his friends, and care for them was ripened in the process of problem-solving. Fourth, the student's self-confidence was further instilled when presenting famous artists and their artworks in the introduction and finale of ten art expression techniques. Likewise, the statistic values on the fields of student's ability of integrated thinking and emotional experience illustrate that over the majority of the students showed improvement in the ability of creative expression with confidence as well as higher interest and concern upon this program.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• MISULJARYO - National Museum of Korea Art Journal
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• v.96
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• pp.18-53
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• 2019

The paintings Gyeongpodae Pavilion and Chongseokjeong Pavilion were recently donated to the National Museum of Korea and unveiled to the public for the first time at the 2019 special exhibition "Through the Eyes of Joseon Painters: Real Scenery Landscapes of Korea." These two paintings carry significant implications for understanding Joseon art history. Because the fact that they were components of a folding screen produced after a sightseeing tour of the Gwandong regions in 1557 has led to a broadening of our understanding of sixteenth-century landscape painting. This paper explores the art historical meanings of Gyeongpodae Pavilion and Chongseokjeong Pavilion by examining the contents in the two paintings, dating them, analyzing their stylistic characteristics, and comparing them with other works. The production background of Gyeongpodae Pavilion and Chongseokjeong Pavilion can be found in the colophon of Chongseokjeong Pavilion. According to this writing, Sangsanilro, who is presumed to be Park Chung-gan (?-1601) in this paper, and Hong Yeon(?~?) went sightseeing around Geumgangsan Mountain (or Pungaksan Mountain) and the Gwandong region in the spring of 1557, wrote a travelogue, and after some time produced a folding screen depicting several famous scenic spots that they visited. Hong Yeon, whose courtesy name was Deokwon, passed the special civil examination in 1551 and has a record of being active until 1584. Park Chung-gan, whose pen name was Namae, reported the treason of Jeong Yeo-rip in 1589. In recognition of this meritorious deed, he was promoted to the position of Deputy Minister of the Ministry of Punishments, rewarded with the title of first-grade pyeongnan gongsin(meritorious subject who resolved difficulties), and raised to Lord of Sangsan. Based on the colophon to Chongseokjeong Pavilion, I suggest that the two paintings Gyeongpodae Pavilion and Chongseokjeong Pavilion were painted in the late sixteenth century, more specifically after 1557 when Park Chung-gan and Hong Yeon went on their sightseeing trip and after 1571 when Park, who wrote the colophon, was in his 50s or over. The painting style used in depicting the landscapes corresponds to that of the late sixteenth century. The colophon further states that Gyeongpodae Pavilion and Chongseokjeong Pavilion were two paintings of a folding screen. Chongseokjeong Pavilion with its colophon is thought to have been the final panel of this screen. The composition of Gyeongpodae Pavilion recalls the onesided three-layered composition often used in early Joseon landscape paintings in the style of An Gyeon. However, unlike such landscape paintings in the An Gyeon style, Gyeongpodae Pavilion positions and depicts the scenery in a realistic manner. Moreover, diverse perspectives, including a diagonal bird's-eye perspective and frontal perspective, are employed in Gyeongpodae Pavilion to effectively depict the relations among several natural features and the characteristics of the real scenery around Gyeongpodae Pavilion. The shapes of the mountains and the use of moss dots can be also found in Welcoming an Imperial Edict from China and Chinese Envoys at Uisungwan Lodge painted in 1557 and currently housed in the Kyujanggak Institute for Korean Studies at Seoul National University. Furthermore, the application of "cloud-head" texture strokes as well as the texture strokes with short lines and dots used in paintings in the An Gyeon style are transformed into a sense of realism. Compared to the composition of Gyeongpodae Pavilion, which recalls that of traditional Joseon early landscape painting, the composition of Chongseokjeong Pavilion is remarkably unconventional. Stone pillars lined up in layers with the tallest in the center form a triangle. A sense of space is created by dividing the painting into three planes(foreground, middle-ground, and background) and placing the stone pillars in the foreground, Saseonbong Peaks in the middle-ground, and Saseonjeong Pavilion on the cliff in the background. The Saseonbong Peaks in the center occupy an overwhelming proportion of the picture plane. However, the vertical stone pillars fail to form an organic relation and are segmented and flat. The painter of Chongseokjeong Pavilion had not yet developed a three-dimensional or natural spatial perception. The white lower and dark upper portions of the stone pillars emphasize their loftiness. The textures and cracks of the dense stone pillars were rendered by first applying light ink to the surfaces and then adding fine lines in dark ink. Here, the tip of the brush is pressed at an oblique angle and pulled down vertically, which shows an early stage of the development of axe-cut texture strokes. The contrast of black and white and use of vertical texture strokes signal the forthcoming trend toward the Zhe School painting style. Each and every contour and crack on the stone pillars is unique, which indicates an effort to accentuate their actual characteristics. The birds sitting above the stone pillars, waves, and the foam of breaking waves are all vividly described, not simply in repeated brushstrokes. The configuration of natural features shown in the above-mentioned Gyeongpodae Pavilion and Chongseokjeong Pavilion changes in other later paintings of the two scenic spots. In the Gyeongpodae Pavilion, Jukdo Island is depicted in the foreground, Gyeongpoho Lake in the middle-ground, and Gyeongpodae Pavilion and Odaesan Mountain in the background. This composition differs from the typical configuration of other Gyeongpodae Pavilion paintings from the eighteenth century that place Gyeongpodae Pavilion in the foreground and the sea in the upper section. In Chongseokjeong Pavilion, stone pillars are illustrated using a perspective viewing them from the sea, while other paintings depict them while facing upward toward the sea. These changes resulted from the established patterns of compositions used in Jeong Seon(1676~1759) and Kim Hong-do(1745~ after 1806)'s paintings of Gwandong regions. However, the configuration of the sixteenth-century Gyeongpodae Pavilion, which seemed to have no longer been used, was employed again in late Joseon folk paintings such as Gyeongpodae Pavilion in Gangneung. Famous scenic spots in the Gwandong region were painted from early on. According to historical records, they were created by several painters, including Kim Saeng(711~?) from the Goryeo Dynasty and An Gyeon(act. 15th C.) from the early Joseon period, either on a single scroll or over several panels of a folding screen or several leaves of an album. Although many records mention the production of paintings depicting sites around the Gwandong region, there are no other extant examples from this era beyond the paintings of Gyeongpodae Pavilion and Chongseokjeong Pavilion discussed in this paper. These two paintings are thought to be the earliest works depicting the Gwandong regions thus far. Moreover, they hold art historical significance in that they present information on the tradition of producing folding screens on the Gwandong region. In particular, based on the contents of the colophon written for Chongseokjeong Pavilion, the original folding screen is presumed to have consisted of eight panels. This proves that the convention of painting eight views of Gwangdong had been established by the late sixteenth century. All of the existing works mentioned as examples of sixteenth-century real scenery landscape painting show only partial elements of real scenery landscape painting since they were created as depictions of notable social gatherings or as a documentary painting for practical and/or official purposes. However, a primary objective of the paintings of Gyeongpodae Pavilion and Chongseokjeong Pavilion was to portray the ever-changing and striking nature of this real scenery. Moreover, Park Chung-gan wrote a colophon and added a poem on his admiration of the scenery he witnessed during his trip and ruminated over the true character of nature. Thus, unlike other previously known real-scenery landscape paintings, these two are of great significance as examples of real-scenery landscape paintings produced for the simple appreciation of nature. Gyeongpodae Pavilion and Chongseokjeong Pavilion are noteworthy in that they are the earliest remaining examples of the historical tradition of reflecting a sightseeing trip in painting accompanied by poetry. Furthermore, and most importantly, they broaden the understanding of Korean real-scenery landscape painting by presenting varied forms, compositions, and perspectives from sixteenth-century real-scenery landscape paintings that had formerly been unfound.

• Journal of Chest Surgery
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• v.39 no.12 s.269
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• pp.879-890
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• 2006

Background: The dysfunction of multiple organs is found to be caused by reactive oxygen species as a major modulator of microvascular injury after hemorrhagic shock. Hemorrhagic shock, one of many causes inducing acute lung injury, is associated with increase in alveolocapillary permeability and characterized by edema, neutrophil infiltration, and hemorrhage in the interstitial and alveolar space. Aggressive and rapid fluid resuscitation potentially might increased the risk of pulmonary dysfunction by the interstitial edema. Therefore, in order to improve the pulmonary dysfunction induced by hemorrhagic shock, the present study was attempted to investigate how to reduce the inflammatory responses and edema in lung. Material and Method: Male Sprague-Dawley rats, weight 300 to 350 gm were anesthetized with ketamine(7 mg/kg) intramuscular Hemorrhagic Shock(HS) was induced by withdrawal of 3 mL/100 g over 10 min. through right jugular vein. Mean arterial pressure was then maintained at $35{\sim}40$ mmHg by further blood withdrawal. At 60 min. after HS, the shed blood and Ringer's solution or 5% albumin was infused to restore mean carotid arterial pressure over 80 mmHg. Rats were divided into three groups according to rectal temperature level($37^{\circ}C$[normothermia] vs $33^{\circ}C$[mild hypothermia]) and resuscitation fluid(lactate Ringer's solution vs 5% albumin solution). Group I consisted of rats with the normothermia and lactate Ringer's solution infusion. Group II consisted of rats with the systemic hypothermia and lactate Ringer's solution infusion. Group III consisted of rats with the systemic hypothermia and 5% albumin solution infusion. Hemodynamic parameters(heart rate, mean carotid arterial pressure), metabolism, and pulmonary tissue damage were observed for 4 hours. Result: In all experimental groups including 6 rats in group I, totally 26 rats were alive in 3rd stage. However, bleeding volume of group I in first stage was $3.2{\pm}0.5$ mL/100 g less than those of group II($3.9{\pm}0.8$ mL/100 g) and group III($4.1{\pm}0.7$ mL/100 g). Fluid volume infused in 2nd stage was $28.6{\pm}6.0$ mL(group I), $20.6{\pm}4.0$ mL(group II) and $14.7{\pm}2.7$ mL(group III), retrospectively in which there was statistically a significance between all groups(p<0.05). Plasma potassium level was markedly elevated in comparison with other groups(II and III), whereas glucose level was obviously reduced in 2nd stage of group I. Level of interleukine-8 in group I was obviously higher than that of group II or III(p<0.05). They were $1.834{\pm}437$ pg/mL(group I), $1,006{\pm}532$ pg/mL(group II), and $764{\pm}302$ pg/mL(group III), retrospectively. In histologic score, the score of group III($1.6{\pm}0.6$) was significantly lower than that of group I($2.8{\pm}1.2$)(p<0.05). Conclusion: In pressure-controlled hemorrhagic shock model, it is suggested that hypothermia might inhibit the direct damage of ischemic tissue through reduction of basic metabolic rate in shock state compared to normothermia. It seems that hypothermia should be benefit to recovery pulmonary function by reducing replaced fluid volume, inhibiting anti-inflammatory agent(IL-8) and leukocyte infiltration in state of ischemia-reperfusion injury. However, if is considered that other changes in pulmonary damage and inflammatory responses might induce by not only kinds of fluid solutions but also hypothermia, and that the detailed evaluation should be study.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.

• Korean Journal of Agricultural Science
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• v.9 no.2
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• pp.546-555
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• 1982

To evaluate the digestibility and absorbability of proteins, and the rates of energy and nitrogen(N) metabolism of the Korean native goats, studies were carried out with open type respiration apparatus based on the nitrogen-carbon method. The results on the nitrogen retention and the metabolic rate of energy, which was obtained with one male (10-month-old) and one female (24-month-old) goats, both weighing ${\simeq}20kg$, are summarized as follows. 1. When the goats were fed ad libitum the medium quality orchard grass hay, they consumed hay about 0.66 to 0.92% of body weight per day. The hay intake was remained the same even when high quality hay was provided. This amount of hay intake was relatively lower than that of dairy goat and sheep. It was believed to be partly due to the change in feeding enviroment. When fed with hay and soybean meal together, the goats ate hay about 1.06% and soybean meal about 0.60% of body weight, corresponding to 1.66% of body weight as fed basis. 2. The $CO_2$ gas produced from the goat in the open type respiration chamber and absorbed with KOH solution was estimated to be 99~117g/day. The difference in feed intake did not influence the $CO_2$ production; however, these seems to be a linea relationship between body weight and $CO_2$ production. 3. When fed orchard grass hay only, the goats showed protein digestibility of 24~41%. The protein digestibility incresed to 58.2% when fed hay and soybean meal together. A negative nitrogen balance(-0.16g N/day) was observed with goats fed 11.53g N originated from 212g hay and 150g soybean meal. Converting that nitrogen ingested to a crude protein, the amount of crude protein intake by the goats per day was 77.9g compared to 40~45g N known to be required in a day by goat weighing 20kg, indicating that the extra protein ingested was metabolized to provide energy. 4. When the male and female goats comsumed 624 kcal gross energy and 824 kcal gross energy by consuming 158g and 213g of hay, respectively, the digestible energy intake was calculated to be 260kcal for the male and 199kcal for the female goat. The daily heat production of male and female goats were 338kcal and 334kcal, respectively, when fed hay only. However, the female goat fed 212g hay and 150g soybean meal produced about 591kcal per day. Consequently, the energy requirment of the Korean native goats weighing ${\simeq}20kg$ was concluded to be $${\geq_-}$$600kcal net energy per day. 5. The fasting heat product ion of a male goat weighing 27.7kg was 412kcal per day when fasted for 2~3 days. When fasted for 3~4 days, the value decresed to 240kcal. The enviromental temperatures during the expreimental period were ranged from 19 to $34.5^{\circ}C$. The goats seemed to be panting when the chamber temperature rose to $32^{\circ}C$ or above. 6. When fed low levels of dietary protein, serum protein levels of the goats were decresed slightly ($${\leq_-}$$10%); however, urea content in the serum was observed to decrese to a great extent (3X).

• Journal of the Korean Wood Science and Technology
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• v.14 no.1
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• pp.3-44
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• 1986

In order to obtain the basic physical and mechanical properties of steel wire reinforced particleboard, particleboards were formed with large particles through 2.11 mm (12 meshes) and retained on 1.27mm (20 meshes) sieves and small particles through 1.27mm (20 meshes) and retained on 0.42mm (60 meshes) sieves from the plywood mill wastes of meranti (Shorea spp.) in the form of pallmanchips, applying urea-formaldehyde resin as an adhesive on the particle surface in 10 percent on the oven dried weight of particles, and arranging steel wires of 1mm in diameter 5,10,15,20, and 25mm in longitudinal and transverse direction with crossing in the mid of the board depth in single layer boards, 10mm in longitudinal or transverse direction without crossing in two layers and 10mm in longitudinal and transverse directions with and without crossing in three steel wire layers boards. The stepwise 9-minutes-multi-pressing schedule in 5 minutes at 35 kgf/$cm^2$, 2.5 minutes at 25 kgf/$cm^2$. and 1.5 minutes at 15 kgf/$cm^2$ was applied for $300{\times}200{\times}13$mm board at the temperature of 160$^{\circ}C$ in a hot press. Specific gravity, thickness swelling, bending properties of modulus of rupture (MOR), modulus of elasticity(MOE), work to proportional limit, and work to ultimate load, internal bond (IB), and screw holding power(SHP) of the reinforced boards were analyzed on the wire openings and wire layers. The results obtained are summarized as follows; 1) In specific gravity, particleboards with large particles and small particles had higher value with more steel wire placements and more steel layers composition, 2) Particleboards with large particles in accordance with more steel wire liners composition gave very poor thickness swelling. 3) The mechanical properties of particleboards formed with large or small particles were reinforced with more steel wire layers. Therefore, bending strength was improved in modulus of rupture, modulus of elasticity, and work to ultimate load. Especiallv, particleboards with two or three steel wire layers showed the tension lamination effect when the steels in lower steel wire layer were oriented parallel to the board length. 4) The modulus of rupture, modulus of elasticity, and work to ultimate load in bending varied with opening area, distance of lengthwise wires multipled by distance of transverse wires. Particleboards formed with large particles resulted in higher value in modulus of rupture with 1.5-3 $cm^2$ opening area, 1-2cm distance between transverse wires, and 1.5-2.5cm distance between lengthwise wires. Particle boards formed with small particles showed higher value with 0.5-1.5$cm^2$ or 3.75-6.25 $cm^2$ opening area, 0.5 or 2.5cm distance between transverse wires. 5) In modulus of elasticity, particleboards formed with large particles with one steel wire layer suggested higher value with 5-3$cm^2$ opening area, 1-2.5cm distance between transverse wires and also 1-2.5 cm distance between lengthwise wires. Particleboards formed with small particles showed higher value with 0.75-1.25$cm^2$ or 3-6.25$cm^2$ opening area and 0.5 or 2.5cm distance between transverse wires. 6) Particleboards formed with large particles gaved higher value in work to ultimate load with 1-3$cm^2$ opening area. Particleboards formed with small particles showed increasing tendancy with decreasing opening area. 7) In internal bond and screw holding power, particleboards formed with large particles had increasing value in two and three steel wire layers compositions, but particleboards formed with small particles showed no difference. Particleboards formed with large particles containing one steel wire layer showed no difference in internal bond and screw holding power, and particleboards formed with small panicles containing one steel wire layer resulted in increasing value in internal bond and decreasing value in screw holding power in accordance with increase in opening area.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.175-191
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• 2011

With the MICE(Meeting, Incentive travel, Convention, Exhibition) industry coming into the spotlight, there has been a growing interest in the domestic exhibition industry. Accordingly, in Korea, various studies of the industry are being conducted to enhance exhibition performance as in the United States or Europe. Some studies are focusing particularly on analyzing visiting patterns of exhibition visitors using intelligent information technology in consideration of the variations in effects of watching exhibitions according to the exhibitory environment or technique, thereby understanding visitors and, furthermore, drawing the correlations between exhibiting businesses and improving exhibition performance. However, previous studies related to booth recommendation systems only discussed the accuracy of recommendation in the aspect of a system rather than determining changes in visitors' behavior or perception by recommendation. A booth recommendation system enables visitors to visit unplanned exhibition booths by recommending visitors suitable ones based on information about visitors' visits. Meanwhile, some visitors may be satisfied with their unplanned visits, while others may consider the recommending process to be cumbersome or obstructive to their free observation. In the latter case, the exhibition is likely to produce worse results compared to when visitors are allowed to freely observe the exhibition. Thus, in order to apply a booth recommendation system to exhibition halls, the factors affecting the performance of the system should be generally examined, and the effects of the system on visitors' unplanned visiting behavior should be carefully studied. As such, this study aims to determine the factors that affect the performance of a booth recommendation system by reviewing theories and literature and to examine the effects of visitors' perceived performance of the system on their satisfaction of unplanned behavior and intention to reuse the system. Toward this end, the unplanned behavior theory was adopted as the theoretical framework. Unplanned behavior can be defined as "behavior that is done by consumers without any prearranged plan". Thus far, consumers' unplanned behavior has been studied in various fields. The field of marketing, in particular, has focused on unplanned purchasing among various types of unplanned behavior, which has been often confused with impulsive purchasing. Nevertheless, the two are different from each other; while impulsive purchasing means strong, continuous urges to purchase things, unplanned purchasing is behavior with purchasing decisions that are made inside a store, not before going into one. In other words, all impulsive purchases are unplanned, but not all unplanned purchases are impulsive. Then why do consumers engage in unplanned behavior? Regarding this question, many scholars have made many suggestions, but there has been a consensus that it is because consumers have enough flexibility to change their plans in the middle instead of developing plans thoroughly. In other words, if unplanned behavior costs much, it will be difficult for consumers to change their prearranged plans. In the case of the exhibition hall examined in this study, visitors learn the programs of the hall and plan which booth to visit in advance. This is because it is practically impossible for visitors to visit all of the various booths that an exhibition operates due to their limited time. Therefore, if the booth recommendation system proposed in this study recommends visitors booths that they may like, they can change their plans and visit the recommended booths. Such visiting behavior can be regarded similarly to consumers' visit to a store or tourists' unplanned behavior in a tourist spot and can be understand in the same context as the recent increase in tourism consumers' unplanned behavior influenced by information devices. Thus, the following research model was established. This research model uses visitors' perceived performance of a booth recommendation system as the parameter, and the factors affecting the performance include trust in the system, exhibition visitors' knowledge levels, expected personalization of the system, and the system's threat to freedom. In addition, the causal relation between visitors' satisfaction of their perceived performance of the system and unplanned behavior and their intention to reuse the system was determined. While doing so, trust in the booth recommendation system consisted of 2nd order factors such as competence, benevolence, and integrity, while the other factors consisted of 1st order factors. In order to verify this model, a booth recommendation system was developed to be tested in 2011 DMC Culture Open, and 101 visitors were empirically studied and analyzed. The results are as follows. First, visitors' trust was the most important factor in the booth recommendation system, and the visitors who used the system perceived its performance as a success based on their trust. Second, visitors' knowledge levels also had significant effects on the performance of the system, which indicates that the performance of a recommendation system requires an advance understanding. In other words, visitors with higher levels of understanding of the exhibition hall learned better the usefulness of the booth recommendation system. Third, expected personalization did not have significant effects, which is a different result from previous studies' results. This is presumably because the booth recommendation system used in this study did not provide enough personalized services. Fourth, the recommendation information provided by the booth recommendation system was not considered to threaten or restrict one's freedom, which means it is valuable in terms of usefulness. Lastly, high performance of the booth recommendation system led to visitors' high satisfaction levels of unplanned behavior and intention to reuse the system. To sum up, in order to analyze the effects of a booth recommendation system on visitors' unplanned visits to a booth, empirical data were examined based on the unplanned behavior theory and, accordingly, useful suggestions for the establishment and design of future booth recommendation systems were made. In the future, further examination should be conducted through elaborate survey questions and survey objects.