• Journal of Sericultural and Entomological Science
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• v.13 no.2
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• pp.81-94
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• 1971

This research is conducted to study the effect to rebbuding, death atop, yielding and occurrence of twig blight disease with the interemediate cutting periods of mulberry branch and at the picking levels of leaf remains in autumn. The results obtained are as follows: 1. Re-budding branches are decreased with delaying of interval cutting period, and that more leaves remained lesser both re-budding branches and buds are observed. Therefore, it is better that leaves remained are placed on the upper part of branch, practically with 3-5 leaf remains. It has decreased re-budding branches, in case cutting is conducted in Sept. 20 with picking leaving 3-5 leaf on. 2. With regard that all picking increases the percentage of death atop of the branch and upper half part picking increases slightly over the other treats. Although it seems unlikely to be different in the other treats with cutting period, exception of all picking, it is elucidated better that the all picking after cutting in Sept. 15 represents unusually high, seemingly effected by the temperature contition preferable to the life of twig blight disease along with the lack of branch nutrition caused by the all picking. 3. In view of yielding, it has no difference in autumn yielding with cutting period, but more picking levels of leaf remains, more yielding. In spring yield, both no picking and all picking is the lowest, in spite of cutting period. Each treat produces high yielding except the no picking if rutting is done in Sept. 15 and Sept. 20, respectively; otherwise it is done earlier or later, each treat produces low yielding. It is suggested that yielding ability in following spring affected by the autumn picking because all picking treats represent lower yielding ability than no picking ones except of cutting in Sept. 15 and Sept. 20. With respect to total yield in spring and autumn, it is represented that other treats, among which cutting in Sept. 15 and Sept. 20 is especially high, produce higher yielding than both no picking and all picking. But no difference seemed in leaf remained treats. In these respects, it may be concluded that 3-5 leaf remains after the interval cutting in Sept. 15 to Sept. 20 increases the yielding throughout two seasons and it is suggested that 3-5 leaf remains after cutting in Sept. 5 to Sept. 10 has no difference with no picking and cutting after that day. 4. Diseases in the branch remained are twig blight, massaria-bye, and Die-back, of which twig blight attacks tremendously and slight ouurence in messaria-byo and Die-back. In ouurence of twig blight, it is appeared much in all picking and seasonal occurence high in Sept. 15 with 92.9, and in Sept. 30 with 100 as index, respectively. Also it occurs ,considerably in upper part picking but little occurrence in no picing. 5. It is considered that negative correlation among re-budding percentage. No. of re-budding leaf, and spring yielding is found, seemingly without heavy correlation at -0.42, and -0.27, respectively. However, death atop of branch and occurence of twig blight has little correlation with spring yield. On the other hand, positive correlation highly appeared with the correlation coefficient at 0.8 between occurence of twig blight and death atop of branch.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.56-60
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• 2009

Purpose: The various studies and efforts to develop program are in progress in the field of nuclear medicine for the purpose of reducing scan time. The Oncoflash is one of the programs used in whole body bone scan which allows to maintain the image quality while to reduce scan time. When Those applications are used in clinical setting, both the image quality and reduction of scan time should be considered, therefore, the purpose of this study was to determine the criteria for proper scan speed. Materials and Methods: The subjects of this study were the patients who underwent whole body bone scan at the departments of nuclear medicine in the Asan Medical Center located in Seoul from 1st to 10th, July, 2008. The whole body bone images obtained in the scan speed of 30cm/min were classified by the total counts into under 800 K, and over 800 K, 900 K, 1,000 K, 1,500 K, and 2,000 K. The image quality were assessed qualitatively and the percentages of those of 1,000K and under of total counts were calculated. The FWHM before and after applying the Oncoflash were analyzed using images obtained in $^{99m}Tc$ Flood and 4-Quadrant bar phantom in order to compare the resolution according to the amount of total counts by the application of the Oncoflash. Considering the counts of the whole body bone scan, the dosed 2~5 mCi were used. 152 patients underwent the measurement in which the counts of Patient Postioning Monitor (PPM) were measured with including head and the parts of chest which the starting point of whole body bone scan from 7th to 26th, August, 2008. The correlations with total counts obtained in the scan speed of 30cm/min among them were analyzed (The exclusion criteria were after over six hours of applying isotopes or low amount of doses). Results: The percentage of the whole body bone image which has the geometric average of total counts of under 1,000K among them obtained in the scan speed of 30cm/min were 17.6%(n=58) of 329 patients. The qualitative analysis of the image groups according to the whole body counts showed that the images of under 1,000K were assessed to have coarse particles and increased noises. The analysis on the FWHM of the images before and after applying the Oncoflash showed that, in the case of PPM counts of under 3.6 K, FWHM values after applying the Oncoflash were higher than that before applying the Oncoflash, whereas, in the case of that of over 3.6 K, the FWHM after applying the Oncoflash were not higher than that before applying the Oncoflash. The average of total counts at 2.5~3.0 K, 3.1~3.5 K, 3.6~4.0 k, 4.1~4.5 K, 4.6~5.0 K, 5.1~6.0 K, 6.1~7.0 K, and 7.1 K over (in PPM) were $965{\pm}173\;K$, $1084{\pm}154\;K$, $1242{\pm}186\;K$, $1359{\pm}170\;K$, $1405{\pm}184\;K$, $1640{\pm}376\;K$, $1,771{\pm}324\;K$, and $1,972{\pm}385\;K$, respectively and the correlations between the counts in PPM and the total counts of image obtained in the scan speed of 30 cm/min demonstrated strong correlation (r=.775, p<.01). Conclusions: In the case of PPM coefficient over 3.6 K, the image quality obtained in the scan speed of 30cm/min and after applying the Oncoflash was similar to that obtained in the scan speed of 15 cm/min. In the case of total counts over 1,000 K, it is expected to reduce scan time without any damage on the image quality. In the case of total counts under 1,000 K, however, the image quality were decreased even though the Oncoflash is applied, so it is recommended to perform the re-image in the scan speed of 15 cm/min.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.37 no.3
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• pp.196-213
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• 2001

A split beam ultrasonic transducer operating at a frequency of 70 kHz to use in the fish sizing echo sounder was developed and the acoustic radiation characteristics were experimentally analyzed. The amplitude shading method utilizing the properties of the Chebyshev polynomials was used to obtain side lobe levels below -20 dB and to optimize the relationship between main beam width and side lobe level of the transducer, and the amplitude shading coefficient to each of the elements was achieved by changing the amplitude contribution of elements with 4 weighting transformers embodied in the planar array transducer assembly. The planar array split beam transducer assembly was composed of 36 piezoelectric ceramics (NEPEC N-21, Tokin) of rod type of 10 mm in diameter and 18.7 mm in length of 70 kHz arranged in the rectangular configuration, and the 4 electrical inputs were supplied to the beamformer. A series of impedance measurements were conducted to check the uniformity of the individual quadrants, and also in the configurations of reception and transmission, resonant frequency, and the transmitting and receiving characteristics were measured in the water tank and analyzed, respectively. The results obtained are summarized as follows : 1. Average resonant and antiresonant frequencies of electrical impedance for four quadrants of the split beam transducer in water were 69.8 kHz and 83.0 kHz, respectively. Average electrical impedance for each individual transducer quadrant was 49.2$\Omega$ at resonant frequency and 704.7$\Omega$ at antiresonant frequency. 2. The resonance peak in the transmitting voltage response (TVR) for four quadrants of the split beam transducer was observed all at 70.0 kHz and the value of TVR was all about 165.5 dB re 1 $\mu$Pa/V at 1 m at 70.0 kHz with bandwidth of 10.0 kHz between -3 dB down points. The resonance peak in the receiving sensitivity (SRT) for four combined quadrants (quad LU+LL, quad RU+RL, quad LU+RU, quad LL+RL) of the split beam transducer was observed all at 75.0 kHz and the value of SRT was all about -177.7 dB re 1 V/$\mu$Pa at 75.0 kHz with bandwidth of 10.0 kHz between -3 dB down points. The sum beam transmitting voltage response and receiving senstivity was 175.0 dB re 1$\mu$Pa/V at 1 m at 75.0 kHz with bandwidth of 10.0 kHz, respectively. 3. The sum beam of split beam transducer was approximately circular with a half beam angle of $9.0^\circ$ at -3 dB points all in both axis of the horizontal plane and the vertical plane. The first measured side lobe levels for the sum beam of split beam transducer were -19.7 dB at $22^\circ$ and -19.4 dB at $-26^\circ$ in the horizontal plane, respectively and -20.1 dB at $22^\circ$ and -22.0 dB at $-26^\circ$ in the vertical plane, respectively. 4. The developed split beam transducer was tested to estimate the angular position of the target in the beam through split beam phase measurements, and the beam pattern loss for target strength corrections was measured and analyzed.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.6
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• pp.642-652
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• 2008

The aim of our research was to apply experimental design methodology in the optimization condition of Photo-Fenton oxidation of the residual livestock wastewater after the coagulation process. The reactions of Photo-Fenton oxidation were mathematically described as a function of parameters amount of Fe(II)($x_1$), $H_2O_2(x_2)$ and pH($x_3$) being modeled by the use of the Box-Behnken method, which was used for fitting 2nd order response surface models and was alternative to central composite designs. The application of RSM using the Box-Behnken method yielded the following regression equation, which is an empirical relationship between the removal(%) of livestock wastewater and test variables in coded unit: Y = 79.3 + 15.61x$_1$ - 7.31x$_2$ - 4.26x$_3$ - 18x$_1{^2}$ - 10x$_2{^2}$ - 11.9x$_3{^2}$ + 2.49x$_1$x$_2$ - 4.4x$_2$x$_3$ - 1.65x$_1$x$_3$. The model predicted also agreed with the experimentally observed result(R$^2$ = 0.96) The results show that the response of treatment removal(%) in Photo-Fenton oxidation of livestock wastewater were significantly affected by the synergistic effect of linear terms(Fe(II)($x_1$), $H_2O_2(x_2)$, pH(x$_3$)), whereas Fe(II) $\times$ Fe(II)(x$_1{^2}$), $H_2O_2$ $\times$ $H_2O_2$(x$_2{^2}$) and pH $\times$ pH(x$_3{^2}$) on the quadratic terms were significantly affected by the antagonistic effect. $H_2O_2$ $\times$ pH(x$_2$x$_3$) had also a antagonistic effect in the cross-product term. The estimated ridge of the expected maximum response and optimal conditions for Y using canonical analysis were 84 $\pm$ 0.95% and (Fe(II)(X$_1$) = 0.0146 mM, $H_2O_2$(X$_2$) = 0.0867 mM and pH(X$_3$) = 4.704, respectively. The optimal ratio of Fe/H$_2O_2$ was also 0.17 at the pH 4.7.

• Journal of the Korean Society for Marine Environment & Energy
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• v.18 no.1
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• pp.1-8
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• 2015

To evaluate accuracy and precision of determination of total alkalinity ($Alk_T$) and carbon dioxide ($TCO_2$) derived from present study, experiment was applied with $CO_2$ CRM (Batch 132, Scripps Institution of Oceanography; $Alk_T=2229.24{\pm}0.39{\mu}mol/kg$, $TCO_2=2032.65{\pm}0.45{\mu}mol/kg$). As the result, average concentration of $Alk_T$ and $TCO_2$ was $2354.09{\mu}mol/kg$ (~5.6% difference with $CO_2$ CRM) and $2089.60{\mu}mol/kg$ (~2.3% difference with $CO_2$ CRM), respectively. For previous method (Gran Titration) by addition $NaHCO_3$ to deionized water($Alk_T$ $2023.33{\mu}mol/kg$), average concentration was $2193.39{\mu}mol/kg$ (sd=57.15, n=7). Whereas, average concentration was $2017.02{\mu}mol/kg$ (sd=10.98, n=7) for the present study. Recovery yield experiments of total alkalinity in deionized water and seawater were implemented by addition of $NaHCO_3$. The recovery yield of deionized water in the range 0 to $4952.39{\mu}mol/kg$ was 100.8% ($R^2$=0.999), and seawater in the range 0 to $2041.32{\mu}mol/kg$ was 102.3% ($R^2$=0.999). Comparison of $pCO_2$ sensor (PSI $CO_2-Pro^{TM}$) with present method showed very meaningful correlation coefficient ($R^2$=0.977) in the range of 427 to $705{\mu}atm$ and 9.16 to $15.24{\mu}mol/kg$ throught elapsed time for two weeks. Field experiment of diurnal variation of total carbon dioxide was accomplished at Sachon harbor in the coastal waters of East Sea of Korea. Concentration of $Alk_T$ and $TCO_2$ was increased during night, and decreased during daylight hours. The results showed mirror type between $TCO_2$ and dissolved oxygen, which was attributable to photosynthesis and respiration of phytoplankton. Also, open ocean field study was performed to obtain vertical profile of $Alk_T$ and $TCO_2$ in C-C zone (Clarion-Clipperton Fracture Zone), Northeastern Pacific. Average concentrations of $Alk_T$ in the surface mixed layer (0~60 m) and deeper layer below 200 m were $2422.38{\mu}mol/kg$ (sd=78.73, n=20) and $2465.87{\mu}mol/kg$ (sd=57.68, n=103), respectively. And average concentrations of $TCO_2$ were $2134.47{\mu}mol/kg$ (sd=65.4, n=20) and $2431.87{\mu}mol/kg$ (sd=65.02, n=103) in the same depth ranges such as $Alk_T$. Vertical distributions of $Alk_T$ and $TCO_2$ concentrations tended to increase with depth, and analyzed concentrations showed slightly higher than those of previous studies in this area.

• Clinical and Experimental Reproductive Medicine
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• v.35 no.4
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• pp.309-317
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• 2008

Objectives: The aim of this study was to evaluate the usefulness of Anti-mullerian hormone (AMH) as a predictive marker for ovarian response and cycle outcome in IVF cycles. Methods: From Jan., to Aug., 2007, 111 patients undergoing IVF/ICSI stimulated by short or antagonist protocol were selected. On cycle day 3, basal serum AMH level and FSH level were measured. The correlation between basal serum AMH or FSH, and COH outcome was analyzed and IVF outcome was compared according to the AMH levels. To determine the threshold value of AMH for poor- and hyper-response, ROC curve was analyzed. Results: Serum AMH showed higher correlation coefficient (r=0.792, p<0.001) with the number of retrieved mature oocyte than serum FSH (r=-0.477, p<0.001). According to ovarian response, FSH and AMH leves showed significant differences among poor, normal, and hyperresponder. For predicting poor (${\leq}2$ oocytes) and hyperresponse (${\geq}17$ oocyets), AMH cut-off values were 0.5 ng/ml (the sensitivity 88.9% and the specificity 89.5%) and 2.5 ng/ml (sensitivity 85.7%, specificity 87.0%), respectively. According to the AMH level, patients were divided into 3 groups: low (${\leq}0.60\;ng/ml$), normal ($0.60{\sim}2.60\;ng/ml$), and high AMH (${\geq}2.60\;ng/ml$). The number of retrieved mature oocytes was significantly higher ($2.7{\pm}2.2$, $8.1{\pm}4.8$, $16.5{\pm}5.7$) and total gonadotropin dose was lower ($3530.5{\pm}1251.0$, $2957.1{\pm}1057.6$, and $2219.2{\pm}751.9\;IU$) in high AMH group (p<0.001). There was no significant difference in fertilization rates and pregnancy rates (23.8%, 34.0%, 37.5%) among the groups. Conclusions: Basal serum AMH level correlated better with the number of retrieved mature oocytes than FSH level, suggesting its usefulness for predicting ovarian response. However, IVF outcome was not significantly different according to the AMH levels. Serum AMH level presented good cut-off value for poor- or hyper-responders, therefore it could be useful in prediction of cycle cancellation, gonadotropin dose, and OHSS risk in IVF cycles.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Nutrition and Health
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• v.48 no.2
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• pp.180-191
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• 2015

Purpose: There is a lack of data on the energy cost of children's everyday activities, adult values are often used as surrogates. In addition, the influence of body weight on the energy cost of activity when expressed as metabolic equivalents (METs) has not been vigorously explored. Methods: In this study 20 elementary school students 9~12 years of age completed 18 various physical activities while energy expenditure was measured continuously using a portable telemetry gas exchange system ($K_4b^2$, Cosmed, Rome, Italy). Results: The average age was 10.4 years and the average height and weight was 145.1 cm and 43.6 kg, respectively. Oxygen consumption ($VO_2$), energy expenditure and METs at the time of resting of the subjects were 5.41 mL/kg/min, 1.44 kcal/kg/h, and 1.5 METs, respectively. METs values by 18 physical activities were as follows: Homework and reading books (1.6 METs), playing game with a mobile phone or video while sitting (1.6 METs), watching TV while sitting on a comfortable chair (1.7 METs), playing video game or mobile phone game while standing (1.9 METs), sweeping a room with a broom (2.7 METs) and playing a board game (2.8 METs) belong to light intensity physical activities. By contrary, speedy walking and running were 6.6 and 6.7 METs, respectively, which belong to high intensity physical activities over 6.0 METs. When the effect of body weight on physical activity energy expenditure was determined, $R^2$ values increased with 0.116 (playing a game at sitting), 0.176 (climbing up and down stairs), 0.246 (slow walking), and 0.455 (running), which showed that higher activity intensity increased explanation power of body weight on METs value. Conclusion: This study is important for direct evaluation of energy expenditure by physical activities of children, and it could be used directly for revising and complementing the existing activity classification table to fit for children.

• Korean Journal of Soil Science and Fertilizer
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• v.6 no.1
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• pp.17-26
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• 1973

A survey on nutrient recovery by rice plant was carried out countrywide in 1967 and 1968. The relationships between percent recovery of fertilizer nutrient and climatic zone or deposition mode, drainage grade, and texture of paddy soil profile, or chemical characteristics of surface soil were as follows. 1. The percent recovery of fertilizer nitrogen was highest in south and least in north, and that of potassium was highest in south and least in middle climatic zone. 2. Since the percent recovery of Phosphorus variates yearly with climatic zone, mode of deposition drainage grade or soil texture, it seemed to depend greatly on soil-weather interaction. 3. Nitrogen recovery was highest in alluvial colluvial (AC) and it was followed by alluvial (A), fluvomarine (FM) and old alluvial in decreasing order while potassium recovery was OA>AC>A>FM. 4. The greater the drainage was, the higher the nitrogen recovery. The recovery of potassium and phosphorus tended to show high in moderately well drain, and low in poorly and well drain. 5. Nitrogen recovery was highest in fine silty and gradually decreased with coarseness. That of potassium or phosphorus was greater in those below fine loamy than in those above coarse silty. 6. Nitrogen recovery was high in Jisan, Geugrag, and Sindab series, and low in Hwadong, Gyuam, Yongji and Hwabong series. 7. Nitrogen recovery showed significant positive correlation with the content of organic matter (OM), Ca, CEC of surface soil and only in the year of high phosphorus recovery it had significant negative correlation with soil phosphorus. Phosphorus recovery had significant posititive correlation with CEC, Mg or Ca. 8. Potassium recovery showed negative correlation with K/(Ca+Mg), P, OM or K while positive correlation with Ca, Mg, CEC but significant only with K/(Ca+Mg) in the year of low potassium recovery. In the year of high K recovery it showed positive correlation with P, OM, K/(Ca+Mg) or K while negative with CEC, Mg or Ca but significant only with P, OM or CEC. Soil potassium has significant positive correlation with soil OM and P only in the year of low potassium recovery. 9. The percent recovery of N, P or K showed negative correlation coefficient with pH without significant. 10. There was significant positive correlation between OM and P, K or K/(Ca+Mg), P and K or K/(Ca+Mg), K and K/(Ca+Mg), Mg or CEC, Ca and K/(Ca+Mg), Mg, CEC or pH, Mg and CEC while significant negative correlation between Mg and OM, P or K/(Ca+Mg), P and CEC, Ca and K/(Ca+Mg). 11. From the percent rcovery of fertilizer and soil chemical characteristics it was known that soil organic matter increase nitrogen uptake, that K uptake has closer relation to K/(Ca+Mg) than K, that Mg affects P ugtake, and that the annual difference of P and K recovery was partly explainable.