• Journal of Animal Science and Technology
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• v.57 no.1
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• pp.1.1-1.11
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• 2015

Background: Due to increased interest in animal welfare, there is now a need for a comprehensive assessment protocol to be used in intensive pig farming systems. There are two current welfare assessment protocols for pigs: Welfare Quality$^{(R)}$ Assessment Protocols (applicable in the Europe Union), that mostly focuses on animal-based measures, and the Swine Welfare Assurance Program (applicable in the United States), that mostly focuses on management- and environment-based measures. In certain cases, however, animal-based measures might not be adequate for properly assessing pig welfare status. Similarly, welfare assessment that relies only on environment- and management-based measures might not represent the actual welfare status of pigs. Therefore, the objective of this paper was to develop a new welfare protocol by integrating animal-, environment-, and management-based measures. The background for selection of certain welfare criteria and modification of the scoring systems from existing welfare assessment protocols are described. Methods: The developed pig welfare assessment protocol consists of 17 criteria that are related to four main principles of welfare (good feeding, good housing, good health, and appropriate behavior). Good feeding, good housing, and good health were assessed using a 3-point scale: 0 (good welfare), 1 (moderate welfare), and 2 (poor welfare). In certain cases, only a 2-point scale was used: 0 (certain condition is present) or 2 (certain condition is absent). Appropriate behavior was assessed by scan sampling of positive and negative social behaviors based on qualitative behavior assessment and human-animal relationship tests. Results: Modification of the body condition score into a 3-point scale revealed pigs with a moderate body condition (score 1). Moreover, additional criteria such as feed quality confirmed that farms had moderate (score 1) or poor feed quality (score 2), especially those farms located in a high relative humidity region. Conclusions: The developed protocol can be utilized to assess welfare status in an intensive pig farming system. Although further improvements are still needed, this study is a first step in developing a pig welfare assessment protocol that combines animal-, environment-, and management-based measures.

• Journal of Korea Technology Innovation Society
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• v.15 no.3
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• pp.649-674
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• 2012

The purpose of this study is to investigate the effects of public R&D subsidies on private R&D. We have analyzed rationales for the public R&D subsidy from different perspectives. On the basis of literature review, a two step research model is constructed: participation phase (when firms benefit from public subsidies) and decision phase (when firms make decision on additional R&D investments). Using propensity score matching(PSM) method, we compare the potential outcome of the treated group to a matched controlled group of non-subsidized firms. The data used in this paper was collected from various sources. The Korean Innovation Survey 2008(manufacturing sector) is a main source of data. Financial data such as revenue, asset and capital stock, and number of employees were supplemented from the Nice Information Service KIS Value database. The R&D survey, conducted by MEST(Ministry of Education, Science and Technology) each year, was also used for the R&D expenditures of the manufacturing firms. This study comes up with the following empirical results. First, a firm's innovation capability, financial constraints, and sector appear to influence the selection of firms who were benefited from government's financial supports for R&D. Second, empirical results show that public R&D funding complements private investment on average and appear to have perpetual effects on the following year. Finally, sectoral difference in the effect of public subsidies on firms' R&D investment was confirmed. In addition, SMEs show more positive effects than large firms.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.11
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• pp.1725-1731
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• 2020

Objective: An initial RNA-Sequencing study revealed that UDP-galactose-4-epimerase (GALE) was one of the most promising candidates for milk protein concentration in Chinese Holstein cattle. This enzyme catalyzes the interconversion of UDP-galactose and UDP-glucose, an important step in galactose catabolism. To further validate the genetic effect of GALE on milk protein traits, genetic variations were identified, and genotypes-phenotypes associations were performed. Methods: The entire coding region and the 5'-regulatory region (5'-UTR) of GALE were re-sequenced using pooled DNA of 17 unrelated sires. Association studies for five milk production traits were performed using a mixed linear animal model with a population encompassing 1,027 Chinese Holstein cows. Results: A total of three variants in GALE were identified, including two novel variants (g.2114 A>G and g.2037 G>A) in the 5'-UTR and one previously reported variant (g.3836 G>C) in an intron. All three single nucleotide polymorphisms (SNPs) were associated with milk yield (p<0.0001), fat yield (p = 0.0006 to <0.0001), protein yield (p = 0.0232 to <0.0001) and protein percentage (p<0.0001), while no significant associations were detected between the SNPs and fat percentage. A strong linkage disequilibrium (D' = 0.96 to 1.00) was observed among all three SNPs, and a 5 Kb haplotype block involving three main haplotypes with GAG, AGC, and AGG was formed. The results of haplotype association analyses were consistent with the results of single locus association analysis (p<0.0001). The phenotypic variance ratio above 3.00% was observed for milk protein yield that was explained by SNP-g.3836G >C. Conclusion: Overall, our findings provided new insights into the polymorphic variations in bovine GALE gene and their associations with milk protein concentration. The data indicate their potential uses for marker-assisted breeding or genetic selection schemes.

• Environmental and Resource Economics Review
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• v.23 no.2
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• pp.187-224
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• 2014

We present key issues to consider in estimating damages from price-fixing cases and then apply the procedure addressing those issues to a transportation fuel market. Among the five methods of overcharge calculation, the regression analysis incorporating the yardstick method is the best. If the price equation relates the domestic price to the foreign price and the exchange rate as in the transportation fuel market, the functional form satisfying both logical consistency and modeling flexibility is the log-log functional form. If the data under analysis is of time series in nature, then the ARDL model should be the base model for each market and the regression analysis incorporating the yardstick method combines these ARDL equations to account for inter-market correlation and arrange constant terms and collusion-period dummies across component equations appropriately so as to identify the overcharge parameter. We propose a two-step test for the benchmarked market: (a) conduct market-by-market Spearman or Kendall test for randomness of the individual market price series first and (b) then conduct across-market Friedman test for homogeneity of the market price series. Statistical significance is the minimal requirement to establish the alleged proposition in the world of uncertainty. Between the sensitivity analysis and the model selection process for the best fitting model, the latter is far more important in the economic analysis of damage in price-fixing litigation. We applied our framework to a transportation fuel market and could not reject the null hypothesis of no overcharge.

• Journal of Science Education
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• v.41 no.1
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• pp.36-59
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• 2017

The purpose of this study was to develop a theory appropriate to the context by identifying the career motivation formation process from the perspective of academic high school students using a grounded theory approach. In this study, participants were selected among non probability sampling was used for sampling by artificially reputational case selection methods. Forty two highschool students(21 male, 21 female) were participated in this study. Research data were collected mainly collected using in-depth interview data were analyzed by applying the grounded theory method of Strauss and Corbin (1998). According to the results, 319 concepts and 56 sub-categories, and 19 categories were derived n the open coding process. Academic high school students' formation of STEM career motivation were influenced by contextual conditions of "STEM-related career think that the instruments' causal conditions and 'STEM education experience in inside and outside of school' named 'STEM career understanding and self-understanding' using the strategy of being influenced in interventional conditions of social support and obstacle 'for the central phenomenon of "STEM efforts to achieve career goals, it appeared as a result of" satisfaction for STEM careers. And it had a 5-step process over time that the formation process of STEM career motivation. This is expected to provide homes, schools, communities, and contribute to have a new insight on the education of the country, given the direction of career education and counseling intervention and the basic data used to develop and apply STEM career education.

• Magazine of the Korean Society of Agricultural Engineers
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• v.21 no.2
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• pp.28-36
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• 1979

One of most important problems in the Monsoon Asia today is the production of rice paddy to meet the needs of the ever increasing population. Diversemeans are being employed to meet this demand, both by increasing productivity of existing farm land and by bringing further areas into cultivation. The primary step in either field is to ensure that there is sufficient moisture in the soil to suit the paddy, and at the same this means that excess moisture has to be drained off the land, while in others irrigat ion has to be employed to bring sufficient water to an area. In view of the fact that the project comprises a huge amount of earthwork, it can be carried out by extensive use of construction machinery in order to shorten the period. As farm ditch has a comparatively small section with shallow cutting depth, inaddition, there is lack of access road in the field, the excavation equipment with bulldozer or tracter-shovel (backhoe) type are not applicable because there are mostly adapted for the excavation of deep and wide section. Mini-backhoe with its bucket width not larger than 0. 3m, and width of blade not larger than 1. 00m seems to be more adaptable. About 80% of excavation of ditch section will be done by the machinery while the other 20% of excavation together with the finishing of the section are supposed to be done by man-power. The embankment of ditch section can be compacted by the crawler of backhoe when it is moving along the ditch for excavation. However, Lowland paddy field in the Monsoon Asia are made particulary in rain season, therefore, heavy machinery is not easy excavation for ditch. It is very important to know exact ground support power of the working site and select machines with corresponding ground pressure. Ground support power is variable subject to quality and water content of soil and therefore selection of machines should be made duly considering ground condition of the site at the time of construction works. Farm ditches dug and compacted by mannual labar are of poor quality and subject to destruction after one or two years of operation. On the other hand, excavation and compaction by bulldozer is not practical for ditches. Backboe is suitable for slope land, but this is required cycle time of bucket excavation and dumped out. If a small-scale farm ditch trencher adaptable to lowland paddy field is invented, such a machine could greatly accelerate the massive construction work envisaged in many countries and thus significantly speed up the most difficult part of irrigation development and management in Monsoon Asia.

• Korean Journal of Plant Tissue Culture
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• v.25 no.4
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• pp.283-288
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• 1998

The bialaphos is a potent inhibitor of glutamine synthease in higher plants and is used as a non-selective herbicide. We have used the bialaphos resistant gene(Bar) encoding for an acetyltransferase isolated from Streptomyces hygroscopicus SF1293. Callus derived from mature seeds of rice(Oryza sativa L. cv. Dong Jin) were co-cultivated with Agrobacterium tumefaciens EHA101 carring a plasmid pGPTV-HB containing genes for hygromycin resistance (HygR) and Bar. Transgenic plants showing in vitro resistance to 50 mg/L hygromycin and 10 mg/L bialaphos were obtained by using a two-step selection/regeneration procedure. Transformation efficiency of rice was about 30% which was as high as reported in other dicotyledons. Progenies ($\textrm{T}_{1}$ generation) derived from primary transformant of 17 lines were segregated with a 3 resistant : 1 sensitive ratio in medium containing hygromycin and bialaphos. Stable integration of Bar gene into chromosomal DNA was proven by Southern blot analysis of genomic DNA isolated from $\textrm{T}_{2}$ progenies. Transgenic plants ($\textrm{T}_{3}$) grown in the field were resistant to bialaphos (Basta) at a dosage lethal to wild type plants.

• The Journal of Engineering Geology
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• v.33 no.4
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• pp.673-687
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• 2023

Exploratory data analysis is the process of observing and understanding data collected from various sources to identify their distributions and correlations through their structures and characterization. This process can be used to identify correlations among conditioning factors and select the most effective factors for analysis. This can help the assessment of landslide susceptibility, because landslides are usually triggered by multiple factors, and the impacts of these factors vary by region. This study compared two stages of exploratory data analysis to examine the impact of the data exploration procedure on the landslide prediction model's performance with respect to factor selection. Deep-learning-based landslide susceptibility analysis used either a combinations of selected factors or all 23 factors. During the data exploration phase, we used a Pearson correlation coefficient heat map and a histogram of random forest feature importance. We then assessed the accuracy of our deep-learning-based analysis of landslide susceptibility using a confusion matrix. Finally, a landslide susceptibility map was generated using the landslide susceptibility index derived from the proposed analysis. The analysis revealed that using all 23 factors resulted in low accuracy (55.90%), but using the 13 factors selected in one step of exploration improved the accuracy to 81.25%. This was further improved to 92.80% using only the nine conditioning factors selected during both steps of the data exploration. Therefore, exploratory data analysis selected the conditioning factors most suitable for landslide susceptibility analysis and thereby improving the performance of the analysis.

• Asia pacific journal of information systems
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• v.23 no.4
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• pp.103-128
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• 2013

When a consumer needs a product or service and multiple sellers are available online, the process of selecting a seller to buy online from is complex since the process involves many behavioral dimensions that have to be taken into account. As a part of this selection process, consumers may set minimum trust expectation that can be used to screen out less trustworthy sellers. In the previous research, the level of consumers' trust expectation has been anchored on two important factors: product involvement and perceived risk. Product involvement refers to the extent to which a consumer perceives a specific product important. Thus, the higher product involvement may result in the higher trust expectation in sellers. On the other hand, other related studies found that when consumers perceived a higher level of risk (e.g., credit card fraud risk), they set higher trust expectation as well. While abundant research exists addressing the relationship between product involvement and perceived risk, little attention has been paid to the integrative view of the link between the two constructs and their impacts on the trust expectation. The present paper is a step toward filling this research gap. The purpose of this paper is to understand the process by which a consumer chooses an online merchant by examining the relationships among product involvement, perceived risk, trust expectation, and intention to buy from an e-tailer. We specifically focus on the mediating role of perceived risk in the relationships between enduring product involvement and the trust expectation. That is, we question whether product involvement affects the trust expectation directly without mediation or indirectly mediated by perceived risk. The research model with four hypotheses was initially tested using data gathered from 635 respondents through an online survey method. The structural equation modeling technique with partial least square was used to validate the instrument and the proposed model. The results showed that three out of the four hypotheses formulated were supported. First, we found that the intention to buy from a digital storefront is positively and significantly influenced by the trust expectation, providing support for H4 (trust expectation ${\rightarrow}$ purchase intention). Second, perceived risk was found to be a strong predictor of trust expectation, supporting H2 as well (perceived risk ${\rightarrow}$ trust expectation). Third, we did not find any evidence of direct influence of product involvement, which caused H3 to be rejected (product involvement ${\rightarrow}$ trust expectation). Finally, we found significant positive relationship between product involvement and perceived risk (H1: product involvement ${\rightarrow}$ perceived risk), which suggests that the possibility of complete mediation of perceived risk in the relationship between enduring product involvement and the trust expectation. As a result, we conducted an additional test for the mediation effect by comparing the original model with the revised model without the mediator variable of perceived risk. Indeed, we found that there exists a strong influence of product involvement on the trust expectation (by intentionally eliminating the variable of perceived risk) that was suppressed (i.e., mediated) by the perceived risk in the original model. The Sobel test statistically confirmed the complete mediation effect. Results of this study offer the following key findings. First, enduring product involvement is positively related to perceived risk, implying that the higher a consumer is enduringly involved with a given product, the greater risk he or she is likely to perceive with regards to the online purchase of the product. Second, perceived risk is positively related to trust expectation. A consumer with great risk perceptions concerning the online purchase is likely to buy from a highly trustworthy online merchant, thereby mitigating potential risks. Finally, product involvement was found to have no direct influence on trust expectation, but the relationship between the two constructs was indirect and mediated by the perceived risk. This is perhaps an important theoretical integration of two separate streams of literature on product involvement and perceived risk. The present research also provides useful implications for practitioners as well as academicians. First, one implication for practicing managers in online retail stores is that they should invest in reducing the perceived risk of consumers in order to lower down the trust expectation and thus increasing the consumer's intention to purchase products or services. Second, an academic implication is that perceived risk mediates the relationship between enduring product involvement and trust expectation. Further research is needed to elaborate the theoretical relationships among the constructs under consideration.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.761-774
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• 2022

Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.