• Animal Bioscience
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• v.37 no.4_spc
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• pp.730-741
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• 2024

Pig production is one of the viable enterprises of the livestock sub-sector of agriculture. It contributes significantly to the economy and animal protein supply to enhance food security in Africa and globally. This article explored the present status of pig production in Africa, the challenges, prospects and potentials. The pig population of Africa represents 4.6% of the global pig population. They are widely distributed across Africa except in Northern Africa where pig production is not popular due to religio-cultural reasons. They are mostly reared in rural parts of Africa by smallholder farmers, informing why majority of the pig population in most parts of Africa are indigenous breeds and their crosses. Pig plays important roles in the sustenance of livelihood in the rural communities and have cultural and social significance. The pig production system in Africa is predominantly traditional, but rapidly growing and transforming into the modern system. The annual pork production in Africa has grown from less than a million tonnes in year 2000 to over 2 million tonnes in 2021. Incidence of disease outbreak, especially African swine fever is one of the main constraints affecting pig production in Africa. Others are lack of skills and technical know-how, high ambient temperature, limited access to high-quality breeds, high cost of feed ingredients and veterinary inputs, unfriendly government policies, religious and cultural bias, inadequate processing facilities as well as under-developed value-chain. The projected human population of 2.5 billion in Africa by 2050, increasing urbanization and decreasing farming population are pointers to the need for increased food production. The production systems of pigs in Africa requires developmental research, improvements in housing, feed production and manufacturing, animal health, processing, capacity building and pig friendly policies for improved productivity and facilitation of export.

• The Journal of Society for e-Business Studies
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• v.4 no.3
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• pp.119-137
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• 1999

The World Wide Web(WWW) has provided multi-media cyberspace for electronic markets where suppliers and demanders can do global electronic business with each other directly and conveniently. There are two contradictory views on the roles of intermediaries in electronic markets. One says we may not need intermediaries in doing business because suppliers and demanders can contact with each other directly in electronic markets. The other thinks that the intermediary function may be vertically decomposed from the company's internal value chain because it can be done more efficiently through networks by external intermediaries. Intelligent software agent is a new emerging technology in the field of computer science. An intelligent agent can support and do actions on behalf of users on computer networks. We think that this technology can be utilized to implement more efficient cybermediaries for electronic commerce. This paper proposes an XML-based framework for financial software agent, which selects financial products best fitted for the customer's needs in electronic market environment.

• 한국IT서비스학회:학술대회논문집
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• 2009.11a
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• pp.544-548
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• 2009

The underlying success of logistics depends on the flow of data and information for effective management. Over the last 30 years, we have seen the power of microprocessors double about every 18months. This continuing trend means that computers will become considerably smaller, cheaper, and more abundant; indeed, they are becoming ubiquitous and are even finding their way into everyday objects, resulting in the creation of smart things. In the long term, ubiquitous technologies will take on great economic significance. Industrial products will become smart because of their integrated information processing capacity, or take on an electronic identity that can be queried remotely, or be equipped with sensors for detecting their environment, enabling the development of innovative products and totally new services. The global marketplace runs on logistics, security, speed, agility and flexibility..In this paper we report that pairing these traditional logistics functions with RFID technology can be a huge value-driver for companies. This winning combination yields increased logistics management effectiveness and more efficient visibility into the supply chain management.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Bulletin of the Korean Chemical Society
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• v.23 no.11
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• pp.1595-1603
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• 2002

In this paper we have presented the results of diffusion behavior of model systems for eight liquid n-alkanes ($C_{12}$-$C_{44}$) in a canonical (NVT) ensemble at several temperatures using molecular dynamics simulations. For these n-alkanes of small chain length n, the chains are clearly <$R_{ee}^2$>/6<$R_g^2$>>1 and non-Gaussian. This result implies that the liquid n-alkanes over the whole temperatures considered are far away from the Rouse regime, though the ratio becomes close to the unity as n increases. Calculated self-diffusion constants $D_{self}$ are comparable with experimental results and the Arrhenius plot of self-diffusion constants versus inverse temperature shows a different temperature dependence of diffusion on the chain length. The global rotational motion of n-alkanes is examined by characterizing the orientation relaxation of the end-to-end vector and it is found that the ratio ${\tau}1/{\tau}2$ is less than 3, the value expected for a isotropically diffusive rotational process. The friction constants ${\xi}$of the whole molecules of n-alkanes are calculated directly from the force auto-correlation (FAC) functions and compared with the monomeric friction constants ${\xi}_D$ extracted from $D_{self}$. Both the friction constants give a correct qualitative trends: decrease with increasing temperature and increase with increasing chain length. The friction constant calculated from the FAC's decreases very slowly with increasing temperature, while the monomeric friction constant varies rapidly with temperature. By considering the orientation relaxation of local vectors and diffusion of each site, it is found that rotational and translational diffusions of the ends are faster than those of the center.

• Composites Research
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• v.29 no.4
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• pp.173-178
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• 2016

Graphene oxide (GO) was concurrently reduced and functionalized using long alkyl chain dodecyl amine (DA). The DA functionalized GO (DA-G) was assumed to disperse homogenously in linear low density polyethylene (LLDPE). Subsequently, DA-G was used to fabricate DA-G/LLDPE composites by melt mixing technique. Fourier transform infrared spectra analysis was performed to ascertain the simultaneous reduction and functionlization of GO. Field emission scanning electron microscopy analysis was performed to ensure the homogenous distribution and dispersion of DA-G in LLDPE matrix. The enhanced storage modulus value of the composites validates the homogenous dispersion of DA-G and its good interfacial interaction with LLDPE matrix. An increased in tensile strength value by ~ 64% also confirms the generation of good interface between the two constituents, through which efficient load transfer is possible. However, no significant improvement in glass transition temperature was observed. This simple technique of fabricating LLDPE composites following industrially viable melt mixing procedure could be realizable to developed mechanically strong graphene based LLDPE composites for future applications.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.403-411
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• 2021

This study discusses the influence of economic factors on the clothing exports from China and 15 South and Southeast Asian countries to the United States. A basic gravity trade model with three predictors, including the GDP value produced by exporting and importing countries and their geographical distance was established to explain the bilateral trade patterns. The conventional approach of multiple regression and the novel approach of Artificial Neural Networks (ANNs) were developed based on the value of clothing exports from 2012 to 2018 and applied to the trade pattern prediction of 2019. The results showed that ANNs can achieve a more accurate prediction in bilateral trade patterns than the commonly-used econometric analysis of the basic gravity trade model. Future studies can examine the predictive power of ANNs on an extended gravity model of trade that includes explanatory variables in social and environmental areas, such as policy, initiative, agreement, and infrastructure for trade facilitation, which are crucial for policymaking and managerial consideration. More research should be conducted for the examination of the balance between developing countries' economic growth and their social and environmental sustainability and for the application of more advanced machine-learning algorithms of global trade flow examination.

• Journal of Fashion Business
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• v.23 no.6
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• pp.86-100
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• 2019

This study analyzed the characteristics of vegan fashion produced by H&M and ZARA with respect to materials, design, development, production, and marketing to create social value. The results of this study are significant because they can be used as a reference to develop a vegan fashion market. Regarding the research method, this study assessed the concept and status of veganism through a literature review and examined vegan fashion case studies by analyzing official websites and media content. The study's scope covers the period from 2005, when H&M was the first SPA brand to create a vegan product line, until 2019. The characteristics of Global SPA's vegan fashion were as follows. Regarding materials, alternative materials were developed and an expanded use of organic materials was implemented. Regarding design, development was achieved through design collaboration and upcycling. In terms of production, an animal welfare policy was adopted and a sustainable supply chain was established. Marketing employed a campaign aimed at encouraging increased consumer participation. The findings regarding the social value of H&M and Zara's vegan fashion were as follows. First, a cyclical economy was realized through circular recycling in the entire process of resource selection, production, and waste disposal. Second, because product consumption indicated the importance of ethical consumption and sustainable consumer participation, corporate financial activities were created based on shared values to accomplish the social outcome. Third, collaborations with luxury brands or vegan fashion designers built a collaborative ecosystem in which vegan fashions were released and consumer participation campaigns were implemented.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.515-520
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• 2022

Metaverse is at the center of heated debates in many areas recently. Coupled with real world, metaverse is extending its domain into social and cultural activities in addition to economic value creation as untact activities increase. Global companies are investing in R&D for metaverse. The reason is that metaverse is supposed to create new value by converging virtual and real worlds thanks to technology advancement such as AI, big data, 3D graphic, 5G, cloud computing, etc. Thus, innovative changes are expected in the economic, social and cultural areas. However, there are many problems to be solved yet for connecting virtual world and real one. Also, epoch-making development of products and services should be done for realistic experience and profit creation using virtual space in various industries beyond untact social activities against pandemic situation. The essence, present condition, development and its application areas of metaverse will be analyzed, and expected problems researched so that the strategy and methodology for securing global competitiveness will be addressed in coming metaverse era.

• International Commerce and Information Review
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• v.15 no.1
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• pp.227-256
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• 2013

Existing multinational subsidiary typologies seem to have limitations in two respects. First, the prevalence of subsidiary classification along two-dimensions fails to capture many distinct subsidiary types. Failure to reflect a sufficient richness in dimensionality can give rise to a partial picture of subsidiary typologies in the international business literature. A new typology developed from multi-dimensional approach will be required for reflecting various subsidiary roles in the multinational enterprise. Second, multinational subsidiary performing a number of activities is hard to be defined functionally across the value chain activities. In addition, multinational subsidiary roles can vary dramatically. In conclusion, despite a growing amount of work on subsidiary typologies, there seems to be limited convergence of results. the study regarding subsidiary roles still remain a challenge. In this respect, the purpose of this study is to develop a new typology based on multi-dimensional approach in order to overcome the limitations of traditional typologies. To classify subsidiary types, we propose 8 types of multinational subsidiary according to three dimensions that are adopted: (1) number of required value chain activities (2) subsidiary's sourcing capability and autonomy (3) global orientation (3) The case study analyzing Korean foreign subsidiaries appropriate for 8 types is performed to establish the validity of this study.