• Asian-Australasian Journal of Animal Sciences
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• v.24 no.2
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• pp.285-294
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• 2011

The abatement of methane emission from ruminants is an important global issue due to its contribution to greenhouse gas with carbon dioxide. Methane is generated in the rumen by methanogens (archaea) that utilize metabolic hydrogen ($H_2$) to reduce carbon dioxide, and is a significant electron sink in the rumen ecosystem. Therefore, the competition for hydrogen used for methanogenesis with alternative reductions of rumen microbes should be an effective option to reduce rumen methanogenesis. Some methanogens parasitically survive on the surface of ciliate protozoa, so that defaunation or decrease in protozoa number might contribute to abate methanogenesis. The most important issue for mitigation of rumen methanogenesis with manipulators is to secure safety for animals and their products and the environment. In this respect, prophylactic effects of probiotics, prebiotics and miscellaneous compounds to mitigate rumen methanogenesis have been developed instead of antibiotics, ionophores such as monensin, and lasalocid in Japan. Nitrate suppresses rumen methanogenesis by its reducing reaction in the rumen. However, excess intake of nitrate causes intoxication due to nitrite accumulation, which induces methemoglobinemia. The nitrite accumulation is attributed to a relatively higher rate of nitrate reduction to nitrite than nitrite to ammonia via nitroxyl and hydroxylamine. The in vitro and in vivo trials have been conducted to clarify the prophylactic effects of L-cysteine, some strains of lactic acid bacteria and yeast and/or ${\beta}$1-4 galactooligosaccharide on nitrate-nitrite intoxication and methanogenesis. The administration of nitrate with ${\beta}$1-4 galacto-oligosaccharide, Candida kefyr, and Lactococcus lactis subsp. lactis were suggested to possibly control rumen methanogenesis and prevent nitrite formation in the rumen. For prebiotics, nisin which is a bacteriocin produced by Lactococcus lactis subsp. lactis has been demonstrated to abate rumen methanogenesis in the same manner as monensin. A protein resistant anti-microbe (PRA) has been isolated from Lactobacillus plantarum as a manipulator to mitigate rumen methanogenesis. Recently, hydrogen peroxide was identified as a part of the manipulating effect of PRA on rumen methanogenesis. The suppressing effects of secondary metabolites from plants such as saponin and tannin on rumen methanogenesis have been examined. Especially, yucca schidigera extract, sarsaponin (steroidal glycosides), can suppress rumen methanogenesis thereby improving protein utilization efficiency. The cashew nutshell liquid (CNSL), or cashew shell oil, which is a natural resin found in the honeycomb structure of the cashew nutshell has been found to mitigate rumen methanogenesis. In an attempt to seek manipulators in the section on methane belching from ruminants, the arrangement of an inventory of mitigation technologies available for the Clean Development Mechanism (CDM) and Joint Implementation (JI) in the Kyoto mechanism has been advancing to target ruminant livestock in Asian and Pacific regions.

• Journal of Digital Convergence
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• v.18 no.4
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• pp.9-21
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• 2020

The Gross Merchandise Volume for the China's Singles day event in 2019 is about $38.4 billion. More than 500 million customers placed about 1.3 billion orders a day, and the related delivery volume is 2.8 billion. The main technologies associated with the 4^th Industrial Revolution are bringing about a big change in the logistics industry. The purpose of this study is to present implications by reviewing the main technologies which are applied to China's Singles day event, the introduction of smart logistics in China, and analyzing the progress of Singles day, smart system of Alibaba, its significance. China still has poor infrastructure in non-capital areas. And many Chinese companies are actively introducing and developing smart logistics to cover the vast continental area of China. Singles Day is a representative case in point where the smart logistics and main technologies related to 4^th Industrial Revolution are applied. The data obtained through smart logistics would be reused for inventory management, production planning, and order processing, contributing to the optimization of the company's operations. In the era of the 4^th Industrial Revolution, domestic companies and governments need to make efforts to expand the introduction of smart logistics to secure competitiveness with global advanced companies.

• Korean Chemical Engineering Research
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• v.45 no.3
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• pp.249-257
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• 2007

The periodic square wave (PSW) model was successfully applied to the optimal design of a batch-storage network. The network structure can cover any type of batch production, distribution and inventory system, including recycle streams. Here we extend the coverage of the PSW model to multitasking semi-continuous processes as well as pure continuous and batch processes. In previous solutions obtained using the PSW model, the feedstock composition and product yield were treated as known constants. This constraint is relaxed in the present work, which treats the feedstock composition and product yield as free variables to be optimized. This modification makes it possible to deal with the pooling problem commonly encountered in oil refinery processes. Despite the greater complexity that arises when the feedstock composition and product yield are free variables, the PSW model still gives analytic lot sizing equations. The ability of the proposed method to determine the optimal plant design is demonstrated through the example of a high density polyethylene (HDPE) plant. Based on the analytical optimality results, we propose a practical process optimality measure that can be used for any kind of process. This measure facilitates direct comparison of the performance of multiple processes, and hence is a useful tool for diagnosing the status of process systems. The result that the cost of a process is proportional to the square root of average flow rate is similar to the well-known six-tenths factor rule in plant design.

• Journal of the Korean Wood Science and Technology
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• v.42 no.3
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• pp.309-317
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• 2014

Harvested wood products (HWP) are known as products from the tree such as sawn wood, plywood, particle board, structural lumber, wooden interior material, wooden furniture, and paper products. Because carbon is locked up in the HWP until eventual end-use of HWP, HWP played a role as the carbon storage which has the effect of stabilizing the concentration of carbon dioxide in the atmosphere. For these reasons, the suggestion that it must admit the carbon storage effect of HWP has been constantly raised. In 2011, the 17th session of the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) which was held in Durban, South Africa, assigned "Production Approach" which targets only the HWP producted by using round wood of domestic forestry as a official method for carbon accounting. Therefore, it is necessary that each country has to determine the half-life of wood in order to correspond to the discussions and negotiations between countries in the future and to develop an inventory of product-specific domestic wood. In this study, some countries' examples of the methods and conditions for determining half-life of HWP were investigated, and it was tried to derive the factor and methodology to determine half-life span of domestic HWP appropriately.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.1
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• pp.43-59
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• 2022

Electronic public records are classified simultaneously as production, a preservation period is granted, and after a certain period, they are transferred to an archive and preserved. This study intends to find a way to improve the efficiency in classifying transferred records and maintain consistent standards. To this end, the current record classification work process carried out by the National Archives of Korea was analyzed, and problems were identified. As a way to minimize the manual work of record classification by converging the required improvement, the process of identifying outlier candidates based on a list consisting of classified information of the transferred records was proposed and systemized. Furthermore, the proposed outlier discrimination process was applied to the actual records transferred to the National Archives of Korea. The results were standardized and constructed as a training data format that can be used for machine learning in the future.

• Korean Journal of Environmental Agriculture
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• v.32 no.3
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• pp.179-184
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• 2013

BACKGROUND: Accurate estimates of total direct $CH_4$ emissions from croplands on a country scale are important for global budgets of anthropogenic sources of $CH_4$ emissions and for the development of effective mitigation strategies. Methane production resulted by the anaerobic decomposition of organic compounds where $CO_2$ acts as inorganic electron acceptor. This process could be affected by the addition of rice straw, water management and rice variety itself. METHODS AND RESULTS: Rice (Oryza sativa L. Japonica type, var Samkwangbyeo) was cultivated in four plots: (1) Nitrogen-Phosphorus-Potassium (NPK) ($N-P_2O_5-K_2O$:90-45-57 kg/ha); (2) NPK plus 3 Mg/ha rice straw (RS3); (3) NPK plus 5 Mg/ha rice straw (RS5); (4) NPK plus 7 Mg/ha rice straw (RS7) for 3 years (2010-2012) and the rice straw incorporated in fall (Nov.) in Gyeonggi-do Hwaseong-si. Gas samples were collected using the closed static chamber which were installed in each treated plot of $152.9m^2$. According to application of 3, 5, 7 Mg/ha of rice straw, methane emission increased by 46, 101, 190%, respectively, compared to that of the NPK plot. CONCLUSION(S): We obtained a quantitative relationship between $CH_4$ emission and the amount of rice straw applied from rice fields which could be described by polynomial regression of order 2. The emission scaling factor estimated by the relationship were in the range of IPCC GPG (2000).

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.705-715
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• 2010

The adoption of carbon foot print system is being activated mostly in the developed countries as one of the long-term response towards tightened up regulations and standards on carbon emission in the agricultural sector. The Korean Ministry of Environment excluded the primary agricultural products from the carbon foot print system due to lack of LCI (life cycle inventory) database in agriculture. Therefore, the research on and establishment of LCI database in the agriculture for adoption of carbon foot print system is urgent. Development of LCA (life cycle assessment) methodology for application of LCA to agricultural environment in Korea is also very important. Application of LCA methodology to agricultural environment in Korea is an early stage. Therefore, this study was carried out to find out the effect of lettuce cultivation on agricultural environment by establishing LCA methodology. Data collection of agricultural input and output for establishing LCI was carried out by collecting statistical data and documents on income from agro and livestock products prepared by RDA. LCA methodology for agriculture was reviewed by investigating LCA methodology and LCA applications of foreign countries. Results based on 1 kg of lettuce production showed that inputs including N, P, organic fertilizers, compound fertilizers and crop protectants were the main sources of major emission factor during lettuce cropping process. The amount of inputs considering the amount of active ingredients was required to estimate the actual quantity of the inputs used. Major emissions due to agricultural activities were $N_2O$ (emission to air) and ${NO_3}^-$/${PO_4}^-$ (emission to water) from fertilizers, organic compounds from pesticides and air pollutants from fossil fuel combustion in using agricultural machines. The softwares for LCIA (life cycle impact assessment) and LCA used in Korea are 'PASS' and 'TOTAL' which have been developed by the Ministry of Knowledge Economy and the Ministry of Environment. However, the models used for the softwares are the ones developed in foreign countries. In the future, development of models and optimization of factors for characterization, normalization and weighting suitable to Korean agricultural environment need to be done for more precise LCA analysis in the agricultural area.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.358-383
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• 2015

The concept of 'carbon footprint' has been developed as a means of quantifying the specific emissions of the greenhouse gases (GHGs) that cause global warming. Although there are still neither clear definitions of the term nor rules for units or the scope of its estimation, it is broadly accepted that the carbon footprint is the total amount of GHGs, expressed as $CO_2$ equivalents, emitted into the atmosphere directly or indirectly at all processes of the production by an individual or organization. According to the ISO/TS 14067, the carbon footprint of a product is calculated by multiplying the units of activity of processes that emit GHGs by emission factor of the processes, and by summing them up. Based on this, 'carbon labelling' system has been implemented in various ways over the world to provide consumers the opportunities of comparison and choice, and to encourage voluntary activities of producers to reduce GHG emissions. In the agricultural sector, as a judgment basis to help purchaser with ethical consumption, 'low-carbon agricultural and livestock products certification' system is expected to have more utilization value. In this process, the 'cradle to gate' approach (which excludes stages for usage and disposal) is mainly used to set the boundaries of the life cycle assessment for agricultural products. The estimation of carbon footprint for the entire agricultural and forestry sector should take both removals and emissions into account in the "National Greenhouse Gas Inventory Report". The carbon accumulation in the biomass of perennial trees in cropland should be considered also to reduce the total GHG emissions. In order to accomplish this, tower-based flux measurements can be used, which provide a direct quantification of $CO_2$ exchange during the entire life cycle. Carbon footprint information can be combined with other indicators to develop more holistic assessment indicators for sustainable agricultural and forestry ecosystems.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.12
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• pp.874-885
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• 2011

In this study, the urban $CO_2$ emission based on energy consumption (Coal, Petroleum, Electricity, and City Gas) in 16 provincial and metropolitan city governments in South Korea was evaluated. For calculation of the urban $CO_2$ emission, direct and indirect emissions were considered. Direct emissions refer to generation of greenhouse gas (GHG) on-site from the energy consumption. Indirect emissions refer to the use of resources or goods that discharge GHG emissions during energy production. The total GHG emission was 497,083 thousand ton $CO_2eq.$ in 2007. In the indirect GHG emission, about 240,388 thousand ton $CO_2eq.$ was occurred, as 48% of total GHG emission. About 256,694 thousand ton $CO_2eq.$ (52% of total GHG emissions) was produced in the direct GHG emission. This amount shows 13% difference with 439,698 thousand ton $CO_2eq.$ which is total national GHG emission data using current calculation method. Local metropolitan governments have to try to get accuracy and reliability for quantifying their GHG emission. Therefore, it is necessary to develop and use Korean emission factors than using the IPCC (Intergovernmental Panel on Climate Change) emission factors. The method considering indirect and direct GHG emission, which is suggested in this study, should be considered and compared with previous studies.