• Knowledge Management Research
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• v.25 no.2
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• pp.219-243
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• 2024

This study investigates the impact of privacy concerns, perceived utility, and awareness of the right to personal data self-determination on the effective use and expansion of MyData services, which are critical to the data economy. Integrating the value-based adoption model with privacy calculus theory, the research examines how perceived utility, privacy concerns, trust, and personal innovativeness influence perceived value, perceived privacy, and the intention to provide personal information. Data collected from an online survey of 442 MyData service users and prospective users were analyzed using PLS-SEM and Bootstrapping methods via SmartPLS 4. The results indicate that perceived utility positively affects the intention to provide personal information, while privacy concerns have a negative impact. Trust and personal innovativeness positively influence the intention to adopt MyData services, and the awareness of personal data self-determination rights moderates these intentions. The findings underscore the importance of developing beneficial services that mitigate users' privacy concerns and build trust for the successful implementation of MyData services. Additionally, the study highlights the need for education and awareness campaigns to enhance understanding of the right to personal data self-determination.

• Research in Plant Disease
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• v.29 no.4
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• pp.363-376
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• 2023

Alternaria black spots or blights in cruciferous crops have been devastating diseases worldwide and led to economic losses in broccoli, Chinese cabbage, kale, radish, rapeseed, etc. These diseases are caused by different Alternaria spp., including A. brassicae, A. brassicicola and A. raphani transmitted from infected seeds or insect vectors. Efforts to excavate disease resistance traits of cruciferous crops against Alternaria black spots or blights have been demonstrated. Genetic resource of disease resistance was investigated in the wild relatives of cruciferous crops, and different cultivars were screened under different inoculation conditions. Development of the disease-resistant lines against Alternaria black spots or blights was also tried via genetic transformation of the cruciferous crops using diverse plant defence-associated genes. Plant immunity activated by pre-treatment with chemicals, i. e. β-amino-n-butyric acid and melatonin, was suggested for reducing Alternaria black spots or blights in cruciferous crops. The disease resistance traits have also been evaluated in model plant Arabidopsis originating from different habitats. Various plant immunity-related mutants showing different disease responses from wild-type Arabidopsis provided valuable information for managing Alternaria black spots or blights in cruciferous crops. In particular, redox regulation and antioxidant responses altered in the Alternaria-infected mutants were discussed in this review.

• Resources Recycling
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• v.33 no.4
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• pp.3-14
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• 2024

The preheating and calcination processes in cement manufacturing, which are crucial for producing the cement intermediate product clinker, require a substantial quantity of fossil fuels to generate high-temperature thermal energy. However, owing to the ever-increasing severity of environmental pollution, considerable efforts are being made to reduce carbon emissions from fossil fuels in the cement industry. Several preliminary studies have focused on increasing the usage of alternative fuels like refuse-derived fuel (RDF). Alternative fuels offer several advantages, such as reduced carbon emissions, mitigated generation of nitrogen oxides, and incineration in preheaters and kilns instead of landfilling. However, owing to the diverse compositions of alternative fuels, estimating their calorific value is challenging. This makes it difficult to regulate the preheater stability, thereby limiting the usage of alternative fuels. Therefore, in this study, a model based on deep neural networks is developed to accurately predict the preheater temperature and propose optimal fuel input quantities using explainable artificial intelligence. Utilizing the proposed model in actual preheating process sites resulted in a 5% reduction in fossil fuel usage, 5%p increase in the substitution rate with alternative fuels, and 35% reduction in preheater temperature fluctuations.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.75-100
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• 2018

Mobile devices have become an important channel for news content usage in our daily life. However, online news content readers' resistance to online news monetization is more serious than other digital content businesses, such as webtoons, music sources, videos, and games. Since major portal sites distribute online news content free of charge to increase their traffics, customers have been accustomed to free news content; hence this makes online news providers more difficult to switch their policies on business models (i.e., monetization policy). As a result, most online news providers are highly dependent on the advertising business model, which can lead to increasing number of false, exaggerated, or sensational advertisements inside the news website to maximize their advertising revenue. To reduce this advertising dependencies, many online news providers had attempted to switch their 'free' readers to 'paid' users, but most of them failed. However, recently, some online news media have been successfully applying the Pay-What-You-Want (PWYW) payment model, which allows readers to voluntarily pay fees for their favorite news content. These successful cases shed some lights to the managers of online news content provider regarding that the PWYW model can serve as an alternative business model. In this study, therefore, we collected 379 online news articles from Ohmynews.com that has been successfully employing the PWYW model, and analyzed the comparative importance of systematic attributes of online news content on readers' voluntary payment. More specifically, we derived the six systematic attributes (i.e., Type of Article Title, Image Stimulation, Article Readability, Article Type, Dominant Emotion, and Article-Image Similarity) and three or four levels within each attribute based on previous studies. Then, we conducted content analysis to measure five attributes except Article Readability attribute, measured by Flesch readability score. Before conducting main content analysis, the face reliabilities of chosen attributes were measured by three doctoral level researchers with 37 sample articles, and inter-coder reliabilities of the three coders were verified. Then, the main content analysis was conducted for two months from March 2017 with 379 online news articles. All 379 articles were reviewed by the same three coders, and 65 articles that showed inconsistency among coders were excluded before employing conjoint analysis. Finally, we examined the comparative importance of those six systematic attributes (Study 1), and levels within each of the six attributes (Study 2) through conjoint analysis with 314 online news articles. From the results of conjoint analysis, we found that Article Readability, Article-Image Similarity, and Type of Article Title are the most significant factors affecting online news readers' voluntary payment. First, it can be interpreted that if the level of readability of an online news article is in line with the readers' level of readership, the readers will voluntarily pay more. Second, the similarity between the content of the article and the image within it enables the readers to increase the information acceptance and to transmit the message of the article more effectively. Third, readers expect that the article title would reveal the content of the article, and the expectation influences the understanding and satisfaction of the article. Therefore, it is necessary to write an article with an appropriate readability level, and use images and title well matched with the content to make readers voluntarily pay more. We also examined the comparative importance of levels within each attribute in more details. Based on findings of two studies, two major and nine minor propositions are suggested for future empirical research. This study has academic implications in that it is one of the first studies applying both content analysis and conjoint analysis together to examine readers' voluntary payment behavior, rather than their intention to pay. In addition, online news content creators, providers, and managers could find some practical insights from this research in terms of how they should produce news content to make readers voluntarily pay more for their online news content.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.107-127
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• 2022

Global challenges such as the corona pandemic, climate change and the war-on-tech ensure that the demand who the technologies of the future develops and monitors prominently for will be on the agenda. Development of, and applications in, agrifood, biotech, high-tech, medtech, quantum, AI and photonics are the basis of the future earning capacity of the Netherlands and contribute to solving societal challenges, close to home and worldwide. To be like the Netherlands and Europe a strategic position in the to obtain knowledge and innovation chain, and with it our autonomy in relation to from China and the United States insurance, clear choices are needed. Brainport Eindhoven: Building on Philips' knowledge base, there is create an innovative ecosystem where more than 7,000 companies in the High-tech Systems & Materials (HTSM) collaborate on new technologies, future earning potential and international value chains. Nearly 20,000 private R&D employees work in 5 regional high-end campuses and for companies such as ASML, NXP, DAF, Prodrive Technologies, Lightyear and many others. Brainport Eindhoven has a internationally leading position in the field of system engineering, semicon, micro and nanoelectronics, AI, integrated photonics and additive manufacturing. What is being developed in Brainport leads to the growth of the manufacturing industry far beyond the region thanks to chain cooperation between large companies and SMEs. South-Holland: The South Holland ecosystem includes companies as KPN, Shell, DSM and Janssen Pharmaceutical, large and innovative SMEs and leading educational and knowledge institutions that have more than Invest €3.3 billion in R&D. Bearing Cores are formed by the top campuses of Leiden and Delft, good for more than 40,000 innovative jobs, the port-industrial complex (logistics & energy), the manufacturing industry cluster on maritime and aerospace and the horticultural cluster in the Westland. South Holland trains thematically key technologies such as biotech, quantum technology and AI. Twente: The green, technological top region of Twente has a long tradition of collaboration in triple helix bandage. Technological innovations from Twente offer worldwide solutions for the large social issues. Work is in progress to key technologies such as AI, photonics, robotics and nanotechnology. New technology is applied in sectors such as medtech, the manufacturing industry, agriculture and circular value chains, such as textiles and construction. Being for Twente start-ups and SMEs of great importance to the jobs of tomorrow. Connect these companies technology from Twente with knowledge regions and OEMs, at home and abroad. Wageningen in FoodValley: Wageningen Campus is a global agri-food magnet for startups and corporates by the national accelerator StartLife and student incubator StartHub. FoodvalleyNL also connects with an ambitious 2030 programme, the versatile ecosystem regional, national and international - including through the WEF European food innovation hub. The campus offers guests and the 3,000 private R&D put in an interesting programming science, innovation and social dialogue around the challenges in agro production, food processing, biobased/circular, climate and biodiversity. The Netherlands succeeded in industrializing in logistics countries, but it is striving for sustainable growth by creating an innovative ecosystem through a regional industry-academic research model. In particular, the Brainport Cluster, centered on the high-tech industry, pursues regional innovation and is opening a new horizon for existing industry-academic models. Brainport is a state-of-the-art forward base that leads the innovation ecosystem of Dutch manufacturing. The history of ports in the Netherlands is transforming from a logistics-oriented port symbolized by Rotterdam into a "port of digital knowledge" centered on Brainport. On the basis of this, it can be seen that the industry-academic cluster model linking the central government's vision to create an innovative ecosystem and the specialized industry in the region serves as the biggest stepping stone. The Netherlands' innovation policy is expected to be more faithful to its role as Europe's "digital gateway" through regional development centered on the innovation cluster ecosystem and investment in job creation and new industries.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• Land and Housing Review
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• v.6 no.2
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• pp.67-77
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• 2015

Now that it is the current situation that the smooth supply and demand are necessary for 2nd phase of beginning construction and stable development of Gaesung Industrial Complex, this study was willing to offer the planning criteria and model to establish the lodging for the workers in Gaesung Industrial Complex based on the agreement that both South and North Korea agreed in 2007. Regarding the plan, its standard and the alternative were reviewed considering welfare of workers, economic efficiency, technical validity, possibility of agreement and long-term development. The exclusive area per capita was calculated through Labor Standards Act of Korea and status survey of lodging for the workers provided to border line area between China and North Korea and the economic alternative based on one room for 6 persons with the public restroom was compared with that of development type based on one room for 4 persons with indoor restroom. Especially regarding the proposed site, the area with the optimized position was set by considering gradient, accessibility and convenience of development out of the area of Dongchang-ri where was agreed already and the priority of the proposed site that can keep the existing building site and provide was offered. The necessary period for whole construction was set as approximately 36 months. Regarding construction method, RC Rahmen method was selected as the optimized alternative considering the workmanship of manpower of North Korea and conditions of supply and demand of materials and cluster-type vehicle allocation plan based on 4~6 units considering the efficiency of supplying service facilities and convenient facilities along the simultaneous accommodation of 15,000 people was offered. It was analyzed that total business expenses of approximately 80~100 billion Korean Won would required though there were the difference for each alternative in the charged rental way that the development business owner develops by lending the inter-Korea Cooperation Fund and withdraws the rent by the benefit principle. The possibility of withdrawing the rent was analyzed assuming that the period of withdrawing the investment is 30 years. Especially for the operation management after moving, the establishment of the committee of operating the lodging for the workers of Gaesung Industrial Complex (tentative name) was offered with the dualized governance that the constructor takes charge of operational management, collecting fees and management of infrastructure and human resource management is delegated to North Korea.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.221-234
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• 2020

The role of entrepreneurship has become important for the continuous growth (scale-up) of companies in a rapidly changing economic environment. However, research has focused mainly on business-oriented growth that emphasizes efficiency only. However, in the era of the fourth industrial revolution, people have become more important than corporate efficiency. In particular, there are few studies on SMEs. The purpose of this study is to investigate how the characteristics of human - centered organizational culture affects the business ecosystem and firm excellence of SMEs, and how business ecosystem and firm excellence affect the performance of corporations. Therefore, this study focuses on the empathy, enablement, empowerment, and engagement of the corporate culture characteristics of the enterprise and the effects of the independent variables on the business ecosystem and the flower excellence as the parameters and the business ecosystem and company excellence. The main research subjects are the causality analysis that examines the effects on the management performance. The results of the study are as follows. Empathy, enablement, empowerment, engagement have a significant impact on the business ecosystem. In addition, the engagement have a positive effect on firm excellence. The results of empirical studies on the causal relationship between business ecosystem, corporate competence, and company excellence and business performance show that business ecosystem has no statistically significant effect on business performance. Corporate excellence has a significant effect on business performance Respectively. In addition to the above findings, this study can suggest the following implications. First, it is an empirical study of small and medium-sized enterprises (SMEs) by utilizing people-oriented entrepreneurship in addition to existing research. Small and medium-sized enterprises (SMEs) are expected to have lower perceptions of people-oriented management than large corporations or public institutions, but the analysis shows that people-centered entrepreneurship has a significant impact on the business ecosystem. Second, the research results of the serial multiple mediating effect analysis show that the higher the atmosphere of entrepreneurship in a company, the higher the atmosphere of entrepreneurship, and the parameters of business ecosystem and company excellence in the effect of people-oriented entrepreneurship on management performance. It is that the path through which people-oriented entrepreneurship influences management performance was verified by verifying the mediating effect by inputting. Lastly, it is hoped that research on people-oriented entrepreneurship in Korea's SMEs will be activated, providing a theoretical basis for transforming SMEs' business models into innovative types.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1149-1154
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• 2003

Due to various requirements for the user access control to large databases in the hospitals and the banks, database security has been emphasized. There are many security models for database systems using wide variety of policy-based access control methods. However, they are not functionally enough to meet the requirements for the complicated and various types of access control. In this paper, we propose a database security system that can individually control user access to data groups of various sites and is suitable for the situation where the user's access privilege to arbitrary data is changed frequently. Data group(s) in different sixes d is defined by the table name(s), attribute(s) and/or record key(s), and the access privilege is defined by security levels, roles and polices. The proposed system operates in two phases. The first phase is composed of a modified MAC (Mandatory Access Control) model and RBAC (Role-Based Access Control) model. A user can access any data that has lower or equal security levels, and that is accessible by the roles to which the user is assigned. All types of access mode are controlled in this phase. In the second phase, a modified DAC(Discretionary Access Control) model is applied to re-control the 'read' mode by filtering out the non-accessible data from the result obtained at the first phase. For this purpose, we also defined the user group s that can be characterized by security levels, roles or any partition of users. The policies represented in the form of Block(s, d, r) were also defined and used to control access to any data or data group(s) that is not permitted in 'read ' mode. With this proposed security system, more complicated 'read' access to various data sizes for individual users can be flexibly controlled, while other access mode can be controlled as usual. An implementation example for a database system that manages specimen and clinical information is presented.

• Horticultural Science & Technology
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• v.28 no.3
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• pp.449-455
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• 2010

'Moulinrouge' was selected as the best regenerating cultivar among 18 different spray-type chrysanthemum cultivars bred in the Gyeongnam Flowers Breeding Research Institute. When the leaf explants from standard- and spray-type chrysanthemum 'Jinba' and 'Moulinrouge' were incubated on MS basal medium supplemented with $0.5mg{\cdot}L^{-1}$ BA and $1.0mg{\cdot}L^{-1}$ NAA, both 'Jinba' and 'Moulinrouge' induced adventitious shoots that can be regenerated into plantlets. Based on these regeneration conditions, we developed an efficient $Agrobacterium$-mediated chrysanthemum 'Moulinrouge' transformation method by using sequential selection of shoots from low ($10mg{\cdot}L^{-1}$) to high ($30mg{\cdot}L^{-1}$) concentrations of kanamycin after co-cultivation of leaf explants with $Agrobacterium$ for 10 days and induction of shoots. All kanamycin resistant plants investigated with genomic PCR analysis carried the report gene, $AtSICKLE$, in their genome. Although expression levels of the report gene in the transgenic plants investigated with RT-PCR were relatively low because of inefficiency of CaMV 35S promoter in chrysanthemum, transgenic lines expressing $AtSICKLE$ efficiently showed leaf epinasty phenotype. We expect that our results will provide a useful method that can perform a high-throughput investigation of genes isolated and studied well in model plants for molecular breeding of chrysanthemum.