• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.317-326
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• 2021

The crowdsourcing system relies heavily on the number of crowd participation on the platform to ensure the platform's success. However, exploring factors that motivate the crowds to sustain on the platform remains unclear, and very little literature was found on this matter. Lately, the COVID-19 pandemic has affected the world, including Malaysia. Due to the pandemic, many people have lost their jobs, and hence, most of them have shifted to digital work. Hence, to understand the motivation for continuous participation on the online crowdsourcing platform among low-income crowd workers (B40) in Malaysia, this paper explores the intrinsic and extrinsic motivations for continuous participation. A qualitative method interview was performed where 14 active participants of Upwork.com, under the GLOW program, took part during the data collection process. This paper used the thematic analysis method to extract the data collected from this study. The finding of this study identified eight intrinsic motivation factors: (1) personal development, (2) pastime, (3) fun, (4) passion, (5) task identity, (6) time-workplace flexibility, (7) altruistic, and (8) peers' success and four extrinsic factors: (1) monetary, (2) job security, (3) personal commitment, and (4) environment.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.121-131
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• 2022

We look at the initial stage of Meta (previous Facebook)'s new metaverse platform and investigate its platform design in pre-launch and ignition life stage. From the Rocket Model (RM)'s theoretical logic, the results reveal that Meta firstly focuses on investing in key content developers by acquiring virtual reality (VR), video, music content firms and offering production support platform of the augmented reality (AR) content, 'Spark AR' last three years (2019~2021) for attracting high-potential developers and users. In terms of three matching criteria, Meta develops an Artificial Intelligence (AI) powered translation software, partners with Microsoft (MS) for cloud computing and AI, and develops an AI platform for realistic avatar, MyoSuite. In 'connect' function, Meta curates the game concept submitted by game developers, welcomes other game and SNS based metaverse apps, and expands Horizon Worlds (HW) on VR devices to PCs and mobile devices. In 'transact' function, Meta offers 'HW Creator Funding' program for metaverse, launches the first commercialized Meta Avatar Store on Meta's conventional SNS and Messaging apps by inviting all fashion creators to design and sell clothing in this store. Mata also launches an initial test of non-fungible token (NFT) display on Instagram and expands it to Facebook in the US. Lastly, regarding optimization, especially in the face of recent data privacy issues that have adversely affected corporate key performance indicators (KPIs), Meta assures not to collect any new data and to make its privacy policy easier to understand and update its terms of service more user friendly.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.147-154
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• 2023

With the recent popularity of smartphones, many games are being developed on mobile-based platforms. As a result, it has brought about many changes in the way mobile game is developed. Especially mobile platforms, which are divided into Android and IOS, can now be applied to each platform without additional development through cross-platform. This means that it is necessary to move away from the method of developing each using separate development tools and implement the development process through cross-platform unique features. In this paper, we studied various methods to increase the productivity and quality of game development for the development of mobile games, and a formal framework considering the development process was developed. The framework consists of process, development domain, and platform support parts, each playing its own role. Items of the detailed framework must be reflected so that detailed response data for efficient application of game development can be established in actual mobile game development. The framework was developed by approaching it from two domains, the need for a framework and the framework implementation of key item response data.

• Journal of Drive and Control
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• v.20 no.1
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• pp.16-26
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• 2023

Although the upland field area of Korea is high as 44.8%, the platform optimized for the upland field is insufficient. It is necessary to develop an optimized platform for the upland field because the upland field environment is an irregular environment with many slopes. In addition, due to the characteristic of agricultural operations, the traction power and torque of the platform have to be sufficient. Therefore, in this study, a simulation model that can predict the traction power and driving torque of a crawler-type platform for the upland field was developed and validated using the specifications of the crawler platform. The simulation model was developed using Amesim (19.1, Siemens, Germany). The development of the model was conducted using the specifications of the platform. A measurement system was developed to validate the simulation model. The traction power data of the simulation model was validated with the traction force and vehicle speed. The driving torque data of the simulation model was validated with the torque of the sprocket on the crawler system. As a result of the analysis, the error between measurement and simulation results occurred within 10%, and it was determined that the traction power and driving torque prediction of the crawler platform using this model was possible.

• Bulletin of the Korean Chemical Society
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• v.32 no.4
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• pp.1237-1240
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• 2011

In this study, we have developed a ligand-based in-silico prediction model to classify chemical structures into hERG blockers using Bayesian and random forest modeling methods. These models were built based on patch clamp experimental results. The findings presented in this work indicate that Laplacian-modified naive Bayesian classification with diverse selection is useful for predicting hERG inhibitors when a large data set is not obtained.

• Laser Solutions
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• v.14 no.1
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• pp.6-13
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• 2011

Manufacturing technology platform for automotive and mobile industries has been constructed since 2009, for the platform technology project funded by ministry of knowledge and economics. Technology platform in laser welding has also been developed for automotive steel sheets with a strength up to 1GPa. Laser welding technology platform will provide welding characteristics for various laser sources, steel plates and welding conditions. This article shortly explains outline of laser welding technology platform and partially introduces the developed laser welding data base.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.8
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• pp.181-188
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• 2020

The fisheries industry is rapidly shifting from a traditional fishery to aquaculture paradigm and it faces various problems such as depletion of fishery resources and aging of fishing villages. We need the establishment of a fisheries big data platform that includes both the data of the central and surrounding industries of the fisheries industry for enhancement of establishment of a fisheries, 6th industrialization of fishing villages, establishment of related technical standards, and discovery of the new industries to overcome this. Data center agencies should collect, link, and pre-processing, and the platform organizer should create a water industry data virtuous circle through the establishment, operation, and data market of big data platforms to help overcome the current crisis, secure smart fisheries hegemony, and use it as a key to value transfer. Through this study, I would like to propose a policy and technical big data platform construction plan to successfully promote it.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.3
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• pp.347-370
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• 2022

Most public library websites provide unstructured cultural program data, which cannot be produced and utilized systematically as bibliographic information. It is not sufficiently used in existing library big data research or cases, and there is a risk of disappearing when the website is reorganized or the person in charge is changed. This study developed a data schema that can be used in conjunction with bibliographic data by collecting and analyzing cultural programs and community service data produced in an unstructured manner and proposed to share and utilize public library cultural programs and community service data, and establish a library big data platform that can serve as an information channel between librarians who are cultural program planners. Library program data posted on the library website can be integrated and managed through the platform, securing continuity of work, and systematically managing and preserving the specialized service history of individual libraries.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.119-131
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• 2021

With the boom of platform businesses, digital transformation has become the most important topic for businesses. Digital transformation has now become the most urgent strategy for survival, from a strategy considered as an option to choose in the past. Many companies are desperately seeking the ways to be digitally transformed. Even though there have been many studies on digital transformation, most of them are on strategic and conceptual model levels based on simple case analyses. In this study, we analyze the benefits of data integration and network effects from it, based on platform business model at the core of digital transformation. The change based on platform can be categorized into the internal one for the integration of data and better decision making, and the external one for the expansion of the businesses and better prediction of consumer behaviors through the integration of external data sets by the platform business model based enterprises. While the progress for digital transformation is not mature enough yet, financial industry is one of the most promising industries for the change and realization of the aim of it with its relatively much more advanced IT infrastructure. Many companies are making various efforts for the integration of external data, and if the good results can be accomplished, financial industry will contribute to the advancement of digital transformation in other industries as well. For "My Data" project by Korean government, we suggest the data structure and transaction of data (of Korea) should be advanced and established more quickly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.974-992
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• 2021

Recently, the healthcare field has undergone rapid changes owing to the accumulation of health big data and the development of machine learning. Data mining research in the field of healthcare has different characteristics from those of other data analyses, such as the structural complexity of the medical data, requirement for medical expertise, and security of personal medical information. Various methods have been implemented to address these issues, including the machine learning model and cloud platform. However, the machine learning model presents the problem of opaque result interpretation, and the cloud platform requires more in-depth research on security and efficiency. To address these issues, this paper presents a recent technology for Internet-of-Things-based (IoT-based) health big data processing. We present a cloud-based IoT health platform and health big data processing technology that reduces the medical data management costs and enhances safety. We also present a data mining technology for health-risk prediction, which is the core of healthcare. Finally, we propose a study using explainable artificial intelligence that enhances the reliability and transparency of the decision-making system, which is called the black box model owing to its lack of transparency.