• Journal of Plant Biotechnology
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• v.45 no.3
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• pp.171-182
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• 2018

Papaya (Carica papaya L.) is one of the crops widely planted in tropical and subtropical areas. The papaya fruit has low calories and are plentiful in vitamins A and C and in minerals. A major problem in papaya production is a plant disease caused by the papaya ringspot virus (PRSV). The first PRSV-resistant GM papaya expressing a PRSV coat protein gene was developed by USA scientists in 1992. The first commercial GM papaya cultivars derived from the event was approved by the US government in 1997. Development of transgenic papayas has been focused on vaccine production and limited agricultural traits, including insect and pathogen resistance, long shelf life, and aluminum and herbicide tolerance. Approximately 17 countries, including the USA and China, produced transgenic papayas and/or commercialized them, which provoked studies on biosafety assessment and development of GM-detection technologies. For the biosafety assessment of potential effects on human health, effects of long-term feeding to model animals have been studied in terms of toxicity and allergenicity. Studies on environmental safety assessment include influence on soil-microbial biodiversity and transfer to soil bacteria of GM selection markers. Many countries, such as Korea, the European Union, and Japan, that have strict regulations for GM crops have serious concerns about unintended introduction of GM cultivars and food commodities using unauthorized GM crops. Transgene- and/or GM event-specific molecular markers and technologies for genomics-based detection of unauthorized GM papaya have been developed and have resulted in the robust detection of GM papayas.

• Management & Information Systems Review
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• v.36 no.5
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• pp.45-60
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• 2017

This study aims to elucidate the key improvements through the current state of customer support for smart home services based on the Internet of things and the evaluation of user's usage. Smart home services typically provide a wide range of value in terms of security, safety, manageability (electricity and water use), convenience, and remote management accessibility. In this study, we analyzed the current state of smart home service based on Internet of Samsung, SKT and LG U + companies in Korea. However, since LG U+ is the only company providing user reviews, there is a limit to generalization, but we are trying to figure out whether the customer value is conveyed properly or not, and in which part the customer support is focused to support the service. As a result of analyzing the results of the study, we found that the smart home service is commercialized and marketed in various forms. However, it is questionable whether the technological level and user satisfaction level are sufficiently satisfied. The results of this study are as follows. First, although each company provides usage guidance, they still ask many questions about joining products and using products. Second, there are many defects in the product itself, and it is found that the companies are not satisfied with the overall response. Third, the three companies are focusing on switches, outlets, sensors, and lamps. This is an individual intelligent product rather than an interlocking or linking level, and it can be seen that there are many parts that are not compatible with the concept of the original Internet of things. In conclusion, this study shows that there are still many areas to improve on the level of customer service provision of smart home service, in particular, the ease of use is low and the quality of products is not reliable. We would like to present the improvement of this in detail through this study and reflect the companies that provide it and the service providers.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.