• Asian-Australasian Journal of Animal Sciences
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• v.27 no.4
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• pp.511-517
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• 2014

This study examined the effects of bacterial inoculants on chemical composition and fermentation indices of barley silage. Barley forage (Youngyang) was harvested at 24% dry matter (DM) and wilted to 47.9% DM. The wilted barley forage was chopped to 3-5 cm length and applied with no inoculant (CON), L. plantarum ($1{\times}10^{10}cfu/g$, LP) or Effective Microorganisms ($0.5{\times}10^9cfu/g$, EM). Then the forages were ensiled in four replications for each treatment in 20 L mini silos and stored for 100 days. The contents of crude protein and ether extract were higher in CON silage ensiled for 100-d, while the contents of DM and crude ash were higher in EM silage (p<0.05). The contents of ADF, NDF and hemicellulose as well as the in vitro DM digestibility were not affected by microbial inoculation (p>0.05). The pH, ammonia-N concentration and lactate to acetate ratio were higher (p<0.05) in CON silage, while lactate concentrations were higher (p<0.05) in CON and LP silage. Acetate concentration and lactic acid bacteria was increased (p<0.05) by both inoculants (LP and EM), but propionate concentration and yeast was increased (p<0.05) by EM and LP, respectively. These results indicated that the fermentation quality of barley silage was improved by the application of bacterial inoculants.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.225-229
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• 2012

A reformer for a small fuel cell system is an apparatus which converts hydrocarbon fuel into hydrogen-rich gas. Among many indices of a reformer, the most crucial index of a reformer is CO concentration in the off-gas out of reformer which must be controled under 5ppm for the efficiency and performance of a system. This paper suggests the criteria of a reformer operation for the stability of a reformer in a fuel cell system by deducing crucial indices and improving processes. The six-sigma technique was applied to verify the optimum control and operation of a reformer of a fuel cell combined heat and power system. The result of temperature control of each parts of a reformer system is the concentration of CO which is the most important factor for the operation of a fuel cell system. The temperature of the parts of a reformer, MTS, LTS and Prox, were controled so that the concentration of CO.

• The korean journal of orthodontics
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• v.47 no.2
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• pp.130-141
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• 2017

The aim of this case report was to describe an innovative orthodontic treatment method that combined surgical and orthodontic techniques. The novel method was used to achieve a positive result in a case of moderate crowding by employing a computer-guided piezocision procedure followed by the use of clear aligners. A 23-year-old woman had a malocclusion with moderate crowding. Her periodontal indices, oral health-related quality of life (OHRQoL), and treatment time were evaluated. The treatment included interproximal corticotomy cuts extending through the entire thickness of the cortical layer, without a full-thickness flap reflection. This was achieved with a three-dimensionally printed surgical guide using computer-aided design and computer-aided manufacturing. Orthodontic force was applied to the teeth immediately after surgery by using clear appliances for better control of tooth movement. The total treatment time was 8 months. The periodontal indices improved after crowding correction, but the oral health impact profile showed a slight deterioration of OHRQoL during the 3 days following surgery. At the 2-year retention follow-up, the stability of treatment was excellent. The reduction in surgical time and patient discomfort, increased periodontal safety and patient acceptability, and accurate control of orthodontic movement without the risk of losing anchorage may encourage the use of this combined technique in appropriate cases.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.237-242
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• 2014

In this paper, we find out the lifetime index in order to determine the time-dependent trend of deteriorating performance of 6.6kV high-voltage power cable in operation at a power station. The cable systems used in our study have been in operation for 13 years. With measurements for the 13 years, we analyzed the insulation resistances. By developing measuring equipment (comprized mainly of transformer, temperature sensor, and LPF) operating by the three-phase electric power, we analyzed the changing characteristics of insulation resistance of power cable. In contrast to 22kV cables, 6.6 kV cables have thicker insulation. Therefore the characteristics of 6.6kV cables are different from that of 22kV cables. The study found that as time passes, the insulation resistance does not decrease continuously; it decreases to a certain value, then does not decrease any more and shows properties of oscillation. We could not detect the process of deterioration in the preceding twelve years. The cable system showed great stability so that deterioration was not apparent. In this case, it is not possible to measure the future life indices of power cables because the lifetime indices are not predictable

• Biomedical Science Letters
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• v.18 no.4
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• pp.384-390
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• 2012

Diabetes mellitus (DM) is considered to be a serious metabolic disease which may cause systemic complications. The present study was designed to clarify a difference on stress, physiological variables and their correlation between diabetic (DM group) and nondiabetic adults (control group). The levels of body weight, waist circumference, blood pressure, body mass index, body fat mass, total cholesterol (TcH), triglyceride (TG), aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyltransferase (GGT), total bilirubin (TB), autonomic balance (AB), stress index (SI), fatigue index (FI), and heart rate (HR) were all significantly higher in the DM group than in the control group. However, the levels of autonomic activity (AA), stress resistance (SR), and electrocardiac stability (ES) were significantly lower in the DM group than in the control group. The percentages of persons with abnormal levels in the Tch, high density lipoprotein, low density lipoprotein, TG, AST, ALT and GGT were significantly greater in the DM group than in the control group. In the correlation of glucose and hemoglobin A1c (HBA1c) to stress indices, the DM group had a significant relationship with AB, SR, SI, FI, ES, and HR, whereas the control group had no significant relationship with these, excepting AB. These results suggest that DM was harmfully associated with body, biochemical and stress indices and that blood glucose and HBA1c levels must be exhaustively regulated.

• Applied Biological Chemistry
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• v.41 no.5
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• pp.367-371
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• 1998

The characteristics of four samples of noodle flours milled from Australian Standard White(ASW) wheat were compared with one sample of noodle flour prepared from a blend of hard red winter(HRW) and western white(WW) American wheats. The ASW flours had lower content of protein and ash. Farinograms revealed that the absorption of the ASW flours was slightly higher than that of the HRW-WW flour. The mixing time, however, showed no difference between ASW flours and HRW-WW flour. The stability and the mechanical tolerance index were different among ASW flours, which were lower than HRW-WW flour. The ratios of resistance to extention determined by extensigraph for ASW flours were higher except one flour than HRW-WW flour. The flours showed characteristic mean particle sizes, which may reflect the differences in hardness of wheat used in the flour production. Farinograph indices showed no correlations with protein content and extensigraph indices. The amylograph peak viscosity was inversely correlated with the protein content (p<0.05).

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.3 s.49
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• pp.13-20
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• 2006

Substations in electric power transmission network systems (EPTS) operate using several transformers in parallel to increase the efficiency in terms of stability of energy supply. We present a seismic reliability assessment method of EPTS considering the parallel operation of transformers. Two methods for damage state model are compared in this paper: bi-state and multi-damage model. Simulation results showed that both models yielded similar network reliability indices and the reliability indices of the demand nodes using hi-state model exhibited higher damage probability. Particularly, the corresponding EENS (Expected Energy Not Supplied) index was significantly larger than that of the multi-damage state.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.563-570
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• 2022

Industrialized and modular construction is a growing construction technique that can transfer a large portion of the construction process to off-site fabrication yards. This method of construction often involves the fabrication, pre-assembly, and transportation of massive and long volumetric modules. The module weight keeps increasing as the modules become more complete (with infill) to minimize the work at the site and, as higher productivity can be achieved at the fabrication shop. Thus, a volumetric module delivery gets more challenging and risky. Despite its importance, past research paid relatively insufficient attention to the problem related to the lifting of heavy modules. This can be a complex and time-consuming problem with multiple lifting for transportation-and-installation operations both in fabrication yard and jobsite, and require complex crane operations (sometimes, more than one crane) due to crane load capacity and load balance/stability. This study investigates this problem by focusing on the structural perspective of lifting such long volumetric modules through simulation studies. Various scenarios of lifting a weighty module from the top using four lifting cables attached to crane hooks (either a single crane or double crane) are simulated in SAP software. The simulations account for various factors pertaining to structural indices, e.g., bending stress and deflection, to identify a proper method of module lifting from a structural point of view. The method can identify differences in structural indices allowing identification of structural efficiency and safety levels during lifting, which further allows the selection of the number of cranes and location of lifting points.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.4
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• pp.29-41
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• 2015

Abandoned paddy field provides an excellent opportunity to improve the species diversity and habitat quality. Ecological characteristic on the changing of plant communities at different seral stages is a major basis data for ecological restoration. In this study, we investigated changes of the species composition and community indices on the plant community associated with abandonment of cultivated rice paddies. The ecological stability of the habitat was evaluated by using eco-floristic characters(Di; Disturbance index, AUI; Actual urbanization index). Survey sites were grouped into six stages(stageI (${\leq}3years$), stageII(3-5years), stageIII(5-7years), stageIV(7-10years), stageV(10-15years), stageVI(${\geq}20years$). Vegetation investigation was done from May 2009 to October 2012 and carried out phytosociological approach. The total flora were summarized as 176 taxa including 58 families, 127 genera, 157 species, 3 subspecies, 15 varieties and 1 forms. At each of successional stages, 64 taxa in stage I, 34 taxa in stage II, 84 taxa in stage III, 83 taxa in stage IV, 92 taxa in stage V, 23 taxa in stage VI were identified. Of the occurrence plants, the species with the highest r-NCD value were Alopecurus aequalis, Juncus effuusus var. decipiens, Persicaria thunbergii, Artemisia princeps, Salix koreensis and Alnus japonica at each stages. Herbaceous annual plants were dominated in the early stage, but its r-NCD value declined in the middle stage and the late stage. On the other hand, herbaceous perennial plants and Persicaria thunbergii, annual hydrophytes, increases in the middle stage. Woody plant and herbaceous plant which appeared in the forest edge increases in the late stage. Community indices correlate with successional stages. Richness and diversity index increase along the successional gradient. But dominance index decrease along the successional gradient. Evenness index was correlated with lower. In the ecological stability analysis of the habitat that evaluated by eco-floristic characters, stage I was the most unstable habitat. And the stability of the habitat has improved according to the successional stage.