This study was conducted to investigate the effect of the addition of glycine betaine to the diet on growth performance in pigs. A total of 400 pigs were divided into 4 feeding stages(Growing I: 23.10 $\pm$ 1.43, Growing II: 37.69$\pm$ 1.62, Finishing I: 66.51 $\pm$3.44 and Finishing II: 90.42$\pm$ 2.17 kg of initial body weight) then each feeding stage was divided into 4 treatment groups(Control: 0 0/0, Tl : 0.2 0/0, T2: 0.4% and T3 : 0.6 % of glycine betaine, respectively). The average daily gain and feed efficiency of T2 and T3 were significantly increased(p< 0.05) by dietary glycine betaine in stage I, 2 and 3. This result indicates that dietary glycine betaine could influence the pig growth performance. In feeding stage 4, the average daily gain and feed efficiency were significantly increased in 0.4% glycine betaine feeding group compared with other dietary groups(p < 0.05). Results suggest that feeding the pigs 0.4 % glycine betaine could be the most efficient dietary level. Crude protein, ether extract and crude ash digestibilities of 0.4% glycine betaine fed group were significantly increased compared with those of control group(p < 0.05). However, no significant difference was found in nutrient digestibilities among glycine betaine fed groups. Apparent faecal amino acid digestibilities of 0.4% glycine betaine fed group were more significantly higher than that of control group. The 0.4% glycine betaine fed group was significantly increased in apparent faecal amino acid digestibility compared with those of other glycine betaine fed group. No significant difference was shown in amount of microflora population between control and glycine betaine fed groups. Ammonia and hydrogen sulfide gas emission were significantly decreased in 0.4% glycine betaine feeding group compared with other dietary groups(p < 0.05).
The Transactions of The Korean Institute of Electrical Engineers
/
v.60
no.3
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pp.639-647
/
2011
In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.
Kim, Kyoung-Bum;Jang, Yong-Ho;Kim, Chang-Il;Jeong, Young-Hun;Lee, Young-Jin;Jo, Jeong-Ho;Paik, Jong-Hoo;Nahm, Sahn
Journal of the Korean Institute of Electrical and Electronic Material Engineers
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v.24
no.10
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pp.839-843
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2011
ZnO nanostructures were developed on a Si (100) substrate from powder mixture of ZnO and 5 mol% Pd (ZP-5) as reactants by ${\times}$ sccm oxygen pressures(x= 0, 10, 20, 40). DTA (differential thermal analysis) result shows the Pd(5 mol%)+ZnO mixtured powder(PZ-5) is easily evaporated than pure ZnO powder. The PZ-5 mixtured powder was characterized by DTA to determine the thermal decomposition which was found to be at $800^{\circ}C$, $1,100^{\circ}C$. Weight loss(%) and ICP (inductively coupled plasma) analysis reveal that Zn vaporization is decreased by increased oxygen pressures from the PZ-5 at $1,100^{\circ}C$ for 30 mins. Needle-like ZnO nanostructures array developed from 10 sccm oxygen pressure, was well aligned vertically on the Si substrate at $1,100^{\circ}C$ for 30 mins. The lengths of the Needle-like ZnO nanostructures is about 2 ${\mu}m$ with diameters of about 65 nm. The developed ZnO nanostructures exhibited growth direction along [001] with defect-free high crystallinity. It is considered that Zn vaporization is responsible for the growth of Needle-like ZnO nanostructures by controlling the oxygen pressures. The photoluminescence spectra of ZnO nanostructures exhibited stronger 376.7 nm NBE (near band-edge emission) peak and 529.3 nm DLE (deep level energy) peak.
Land use statistics calculation is very informative data as the activity data for calculating exact carbon absorption and emission in post-2020. To effective interpretation by land use category, This study classify automatically image interpretation by land use category applying forest aerial photography (FAP) to deep learning model and calculate national unit statistics. Dataset (DS) applied deep learning is divided into training dataset (training DS) and test dataset (test DS) by extracting image of FAP based national forest resource inventory permanent sample plot location. Training DS give label to image by definition of land use category and learn and verify deep learning model. When verified deep learning model, training accuracy of model is highest at epoch 1,500 with about 89%. As a result of applying the trained deep learning model to test DS, interpretation classification accuracy of image label was about 90%. When the estimating area of classification by category using sampling method and compare to national statistics, consistency also very high, so it judged that it is enough to be used for activity data of national GHG (Greenhouse Gas) inventory report of LULUCF sector in the future.
Kim, Min-Jeong;Jeon, Dong-Gyung;Ahn, Ho-Sung;Yoon, Il-Gyu;Moon, Eun-Seo;Lee, Chai-Hyun;Lim, Yong;Jang, In-Surk
Korean Journal of Poultry Science
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v.47
no.3
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pp.169-180
/
2020
This study examined the effects of a probiotic complex (PC) containing Lactobacillus plantarum, Bacillus subtilis, and Saccharomyces cerevisiae on growth performance, organ weight, immune parameters, fecal microbial count, and noxious odor in broiler chicks. A total of 216 birds (4-day-old) were fed a basal diet (CON) and a diet supplemented with 0.25% (PC1) and 0.5% (PC2) of PC until 35 days of age. No difference in body weight, feed intake, and FCR was observed among the groups. The intestinal mucosal weight of the PC1 group was greater than that of the CON group without affecting weights of the other organs. Intestinal secretory immunoglobulin A (sIgA) levels in the PC2 group increased significantly (P<0.05) compared with that in the CON group. The PC2 group also had a strong tendency for elevated blood sIgA levels. Dietary PC did not affect the level of interleukin-1β in the blood and mucosal tissues or alter maltase, sucrase, and leucine aminopeptidase activities in the intestinal mucosa. The PC2 group had higher colony-forming units (cfu) for L. plantarum and S. cerevisiae, but lower cfu for E. coli than those in the CON group. Compared to the CON diet, the PC2 diet resulted in a decreased H2S concentration and a tendency toward decreased CH3SH concentration. In conclusion, a 0.5% PC diet showed increased sIgA and desirable microbial population, and decreased noxious odor in the feces, suggesting that PC could be applied as an environmentally friendly feed additive in broiler chicks.
This study was conducted to evaluate effects of halogenated compounds on in vitro rumen fermentation characteristics and methane emissions. A fistulated Holstein cow of 650 kg body weight was used as a donor of rumen fluid. Five kinds of halogenated compounds (bromochloromethane (BCM), 2-bromoethane sulfonic acid (BES), 3-bromopropanesulfonic acid (BPS), chloroform (CLF), and pyromellitic diimide (PMDI) known to inhibit methyl-coenzyme M reductase activity were added to an in vitro fermentation incubated with rumen fluid. The microbial population including bacteria, protozoa, and fungi were enumerated, and gas production including methane and fermentation characteristics were observed in vitro. The pH values ranged from 6.25 to 6.72 in all the treatments, and these showed a similar level at 48 hr. The total gas production in the treatments showed a similar pattern with C at 48 hr, whereas methane production in the treatments was lower (p<0.05) than C. Concentrations of total volatile fatty acids (VFAs) and propionic acid were higher (p<0.05) in the treatments than in C at 12 hr. Therefore, halogenated compounds (BCM, BES, BPS, CLF, and PMDI) inhibited in vitro methane emissions by inhibiting methanogens in the rumen. Further studies on safety are needed.
Noise and air pollution, which accompany the development of industry and the increase of population, contribute to the deterioration of urban environment. The air pollution level of Seoul has gradually increased and the city residents are suffering from a high pollution of noise. If no measures were taken against pollution, the amount of emission of pollutant into air would be 36.7 thousand tons per year per square kilometer in 1975, three times more than that of 1970, and it would be the same level as that of United States in 1968. The main sources of air pollution in Seoul are the exhaust has from vehicles and the combustion of bunker-C oil for heating purpose. Thus, it is urgent that an exhaust gas cleaner should be instaled to every car and the fuel substituted by less sulfur-contained-oil to prevent the pollution. Transportation noise (vehicular noise and train noise) is the main component of urban noise problem. The average noise level in downtown area is about 75㏈ with maximum of 85㏈ and the vehicular homing was checked 100㏈ up and down. Therefore, the reduction of the number of bus-stop the strict regulation of homing in downtown area and a better maintenance of car should be an effective measures against noise pollution in urban areas. Within the distance of 200 metres from railroad, the train noise exceeds the limit specified by the pollution control law in Korea. Especially, the level of noise and steam-whistle of train as measured by the ISO evaluation can adversely affect the community activities of residents. To prevent environmental destruction, many developed countries have taken more positive action against worsening pollution and such an action is now urgently required in this country.
The nature of distant faint blue field galaxies remains a mystery, despite the fact that much attention has been devoted to this subject in the last decade. Galaxy counts, particularly those in the optical and near ultraviolet bandpasses, have been demonstrated to be well in excess of those expected in the 'no-evolution' scenario. This has usually been taken to imply that galaxies were brighter in the past, presumably due to a higher rate of star formation. More recently, redshift surveys of galaxies as faint as B$\~$24 have shown that the mean redshift of faint blue galaxies is lower than that predicted by standard evolutionary models (de-signed to fit the galaxy counts). The galaxy number count data and redshift data suggest that evolutionary effects are most prominent at the faint end of the galaxy luminosity function. While these data constrain the form of evolution of the overall luminosity function, they do not constrain evolution in individual galaxies. We are carrying out a series of observations as part of a long-term program aimed at a better understanding of the nature and amount of luminosity evolution in individual galaxies. Our study uses the luminosity-linewidth relation (Tully-Fisher relation) for disk galaxies as a tool to study luminosity evolution. Several studies of a related nature are being carried out by other groups. A specific experiment to test a 'no-evolution' hypothesis is presented here. We have used the AUTOFIB multifibre spectro-graph on the 4-metre Anglo-Australian Telescope (AAT) and the Rutgers Fabry-Perot imager on the Cerro Tolalo lnteramerican Observatory (CTIO) 4-metre tele-scope to measure the internal kinematics of a representative sample of faint blue field galaxies in the red-shift range z = 0.15-0.4. The emission line profiles of [OII] and [OIII] in a typical sample galaxy are significantly broader than the instrumental resolution (100-120 km $s^{-l}$), and it is possible to make a reliable de-termination of the linewidth. Detailed and realistic simulations based on the properties of nearby, low-luminosity spirals are used to convert the measured linewidth into an estimate of the characteristic rotation speed, making statistical corrections for the effects of inclination, non-uniform distribution of ionized gas, rotation curve shape, finite fibre aperture, etc.. The (corrected) mean characteristic rotation speed for our distant galaxy sample is compared to the mean rotation speed of local galaxies of comparable blue luminosity and colour. The typical galaxy in our distant sample has a B-band luminosity of about 0.25 L$\ast$ and a colour that corresponds to the Sb-Sd/Im range of Hub-ble types. Details of the AUTOFIB fibre spectroscopic study are described by Rix et al. (1996). Follow-up deep near infrared imaging with the 10-metre Keck tele-scope+ NIRC combination and high angular resolution imaging with the Hubble Space Telescope's WFPC2 are being used to determine the structural and orientation parameters of galaxies on an individual basis. This information is being combined with the spatially resolved CTIO Fabry-Perot data to study the internal kinematics of distant galaxies (Ing et al. 1996). The two main questions addressed by these (preliminary studies) are: 1. Do galaxies of a given luminosity and colour have the same characteristic rotation speed in the distant and local Universe? The distant galaxies in our AUTOFIB sample have a mean characteristic rotation speed of $\~$70 km $s^{-l}$ after correction for measurement bias (Fig. 1); this is inconsistent with the characteristic rotation speed of local galaxies of comparable photometric proper-ties (105 km $s^{-l}$) at the > $99\%$ significance level (Fig. 2). A straightforward explanation for this discrepancy is that faint blue galaxies were about 1-1.5 mag brighter (in the B band) at z $\~$ 0.25 than their present-day counterparts. 2. What is the nature of the internal kinematics of faint field galaxies? The linewidths of these faint galaxies appear to be dominated by the global disk rotation. The larger galaxies in our sample are about 2"-.5" in diameter so one can get direct insight into the nature of their internal velocity field from the $\~$ I" seeing CTIO Fabry-Perot data. A montage of Fabry-Perot data is shown in Fig. 3. The linewidths are too large (by. $5\sigma$) to be caused by turbulence in giant HII regions.
The Korean government made the 2nd Energy Basic Plan to achieve 11% of new and renewable energies distribution rate until 2035 as a response to cope with international discussion about greenhouse gas emission reduction. Renewable energies include solar thermal, photovoltaic, bioenergy, wind power, small hydropower, geothermal energy, ocean energy, and waste energy. New energies contain fuel cells, coal gasification and liquefaction, and hydrogen. As public and private investment to enhance the distribution of new and renewable energies, it is necessary to clarify the economic effects of the new and renewable energies sector. To the end, this study attempts to apply an input-output analysis and analyze the economic effects of new and renewable energies sector using 2012 input-output table. Three topics are dealt with. First, production-inducing effect, value-added creation effect, and employment-inducing effect are quantified based on demand-driven model. Second, supply shortage effects are analyzed employing supply-driven model. Lastly, price pervasive effects are investigated applying Leontief price model. The results of this analysis are as follows. First, one won of production or investment in new and renewable energies sector induces 2.1776 won of production and 0.7080 won of value-added. Moreover, the employment-inducing effect of one billion won of production or investment in new and renewable energies sector is estimated to be 9.0337 persons. Second, production shortage cost from one won of supply failure in new and renewable energies sector is calculated to be 1.6314 won, which is not small. Third, the impact of the 10% increase in new and renewable energies rate on the general price level is computed to be 0.0123%, which is small. This information can be utilized in forecasting the economic effects of new and renewable energies sector.
Korean Journal of Construction Engineering and Management
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v.24
no.6
/
pp.24-35
/
2023
Recently, the Ministry of Land, Infrastructure and Transport presented the '6th Construction Technology Promotion Basic Plan' and 'Smart Construction Revitalization Plan (2022.7.20)'. Off-Site Construction (OSC), which involves construction and production of PC (Precast Concrete) and Modular, etc., has advantages in shortening the construction period, reducing costs, improving quality, reducing construction waste, and reducing safety accidents. However, the construction cost is high compared to the traditional RC construction method, which has hindered its utilization and spread. In this study, OSC utilization was improved. An economic analysis indicator and methodology that can support decision-making in the planning and design stages for multi-unit housing were proposed. The factors used in the economic analysis of OSC (based on the PC method) of apartment houses were reviewed. As for the indicators used in the cost and benefit section, 'Construction Period', 'Disaster Occurrence', 'Waste Generation', and 'Greenhouse gas Emission', which reflect the technical advantages of OSC, were derived. In addition, a scenario analysis was conducted based on actual apartment housing case data for the presented economic analysis indicators and benefit calculation standards. The level of benefit that offsets the difference between the existing RC construction method and the construction cost was reviewed. In future studies, it will be necessary to conduct additional case studies to apply the measurement criteria for detailed indicators and supplement the benefit indicators.
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