• 반도체디스플레이기술학회지
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• 제22권3호
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• pp.136-141
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• 2023

Artificial intelligence is becoming a global hot topic and is being actively applied in various industrial fields. Not only is artificial intelligence being applied to industrial sites in an on-premises method, but cloud-based artificial intelligence platforms are expanding into "as a service" type. The purpose of this study is to develop and verify a measurement tool for an evaluation framework for the adoption of a cloud-based artificial intelligence platform and test the interrelationships of evaluation variables. To achieve this purpose, empirical testing was conducted to verify the hypothesis using an expanded technology acceptance model, and factors affecting the intention to adopt a cloud-based artificial intelligence platform were analyzed. The results of this study are intended to increase user awareness of cloud-based artificial intelligence platforms and help various industries adopt them through the evaluation framework.

• 정보보호학회논문지
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• 제27권5호
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• pp.1149-1155
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• 2017

최근 활발하게 연구 및 개발 중인 사물인터넷 기술에 있어서 아마존의 AWS, IBM의 Bluemix와 같은 클라우드 플랫폼들이 원활한 서비스 제공을 위해 많이 사용되고 있다. 이러한 클라우드 플랫폼 환경의 사용 증가에 따라 여러 보안 위협들이 제기되고 있다. 본 논문에서는 클라우드 환경 상에서의 보안기술 및 개인정보보호 기법에 대한 연구와 관련 제도 및 법률적 연구의 동향을 살펴보며, 이를 바탕으로 기술적, 법률적 측면에서의 향후 클라우드 플랫폼 환경에서의 보안 및 프라이버시 보호 기법 연구에 대한 전망을 제시한다.

• Journal of Information Processing Systems
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• 제17권6호
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• pp.1035-1043
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• 2021

An Internet of Things (IOT) sensor network is an effective solution for monitoring environmental conditions. However, IOT sensor networks generate massive data such that the abilities of massive data storage, processing, and query become technical challenges. To solve the problem, a Hadoop cloud platform is proposed. Using the time and workload genetic algorithm (TWLGA), the data processing platform enables the work of one node to be shared with other nodes, which not only raises efficiency of one single node but also provides the compatibility support to reduce the possible risk of software and hardware. In this experiment, a Hadoop cluster platform with TWLGA scheduling algorithm is developed, and the performance of the platform is tested. The results show that the Hadoop cloud platform is suitable for big data processing requirements of IOT sensor networks.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.496-499
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• 2016

스마트팜은 현재 농업 환경 모니터링 분야에서 각광받고 있다. 무선 원격 시스템의 사용으로 스마트팜의 응용 프로그램들은 농민이 어디에 있던지 생장 정보를 제공할 수 있다. 부재중에서도 모바일 폰을 사용하여 도표화된 정보를 얻을 수 있다. 우리는 클라우드 플랫폼 기술을 기반으로 스마트팜을 관리, 운영하는데 있어 필요한 시스템 및 서비스의 기술적 요구사항과 구성 내용을 설계한다. 클라우드 플랫폼은 스마트팜을 모니터링, 제어, 관리 및 운영하기 위한 클라우드 기술의 요구사항을 기술하고 있으며, 특히, 클라우드 플랫폼 기반 스마트팜 시스템 및 서비스는 3가지 인터페이스와 3가지 서비스로 구성되어 있다. 또한, 클라우드 플랫폼을 활용한 스마트팜은 재배작목, 농장의 규모, 시설형태 등에 따라 다양한 방식으로 구축, 운영 될 수 있으며, 이에 따라 다양한 유형이 존재한다. 이를 통하여 오픈 (개방/표준) 클라우드 플랫폼의 중요성에 대해 산업계의 관심을 고조시키고 농업에서의 스마트팜의 활성화에 기여할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2434-2454
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• 2021

This paper developed the software testing factory-cloud testing platform (STF-CTP) to address the software compatible issues in various smart devices. Software developers who only require uploading the application under test (AUT) and test script can test plenty of smart devices in STF-CTP. The challenge for the cloud test platform is how to optimize the resource and increase the performance in the limited resource. This paper proposed a new scheduling mechanism and a new process of the system operation which is based on the OpenStack platform. We decrease about 40% memory usage of OpenStack server, increase 3% to 10% Android device usage of STF-CTP, enhance about 80% test job throughput and reduces about 40% test job average waiting time.

• 한국BIM학회 논문집
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• 제10권3호
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• pp.43-53
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• 2020

BIM-based Cloud platform gained popularity coupled with the convergence of Fourth Industrial Revolution technology. However, most of the previous work has not guaranteed sufficient efficiency to meet user requirements according to BIM service. Furthermore, the Cloud environment is only used as a server and it does not consider cloud characteristics. For the processing of High Capacity Data like BIM and using seamless BIM service, Resource management technology is required in the cloud environment. In this paper, to solve the problems, we propose a BIM platform for BaaS and an efficient resource allocation scheme. We also proved the efficiency of resource for the proposed scheme by using existing schemes. By doing this, the proposed scheme looks forward to accelerating the growth of the BaaS through improving the user experience and resource efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.4212-4226
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• 2019

In this paper, a design and implementation for direct deal distribution platform is proposed to bypass the complex traditional distribution structure of agricultural market, as one of the fields where distribution patterns have changed. In the case of domestic agricultural distribution, demand and supply are unstable since the sales market is excessively concentrated in the designated wholesale market. Besides sales must go through multiple stages of distribution leading to problems in freshness and stability of agricultural products and downward pressure on profit margins for producers. To solve the above mentioned issues, we propose a cloud service convergence direct deal distribution platform based on asynchronous-driven Node.js. The proposed platform can facilitate a variety of direct trading functions and also access to visualization information related to agricultural products, which may increase user confidence at an intermediary-free direct transactions platform. First, we describe the requirements of intermediary-free direct transactions of agricultural products and transaction entities. Next the database structure and transaction functions are designed and then implemented according to those requirements. Finally, an API based cloud convergence service structure is designed to provide the analyzed information to ensure a trustworthy system.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.655-657
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• 2014

본 논문은 클라우드 서비스를 위한 초고화질 영상 송수신 미디어 플랫폼인 레고형 UHD(Ultra High Definition) 미디어 플랫폼을 제안한다. 이 플랫폼을 이용하면 옥/내외 환경에서 UHD 영상을 이용할 수 있는 클라우드 서비스를 자유롭게 공유할 수 있고, 차세대 무선 통신기술(802.11ac, LTE Broadcast 등)이 적용된 다양한 미디어 제품과 제안된 플랫폼을 활용한다면 누구나 손쉽게 개발시킬 수 있으며, 다양한 비즈니스 모델에 적용할 수 있어 새로운 시장과 산업 창출을 기대 할 수 있을 것으로 생각한다.

• Asia pacific journal of information systems
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• 제34권1호
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• pp.150-190
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• 2024

This article proposes a framework to elucidate the structural dynamics of the generative AI ecosystem. It also outlines the practical application of this proposed framework through illustrative policies, with a specific emphasis on the development of the Korean generative AI ecosystem and its implications of platform strategies at AI platform-squared. We propose a comprehensive classification scheme within generative AI ecosystems, including app builders, technology partners, app stores, foundational AI models operating as operating systems, cloud services, and chip manufacturers. The market competitiveness for both app builders and technology partners will be highly contingent on their ability to effectively navigate the customer decision journey (CDJ) while offering localized services that fill the gaps left by foundational models. The strategically important platform of platforms in the generative AI ecosystem (i.e., AI platform-squared) is constituted by app stores, foundational AIs as operating systems, and cloud services. A few companies, primarily in the U.S. and China, are projected to dominate this AI platform squared, and consequently, they are likely to become the primary targets of non-market strategies by diverse governments and communities. Korea still has chances in AI platform-squared, but the window of opportunities is narrowing. A cautious approach is necessary when considering potential regulations for domestic large AI models and platforms. Hastily importing foreign regulatory frameworks and non-market strategies, such as those from Europe, could overlook the essential hierarchical structure that our framework underscores. Our study suggests a clear strategic pathway for Korea to emerge as a generative AI powerhouse. As one of the few countries boasting significant companies within the foundational AI models (which need to collaborate with each other) and chip manufacturing sectors, it is vital for Korea to leverage its unique position and strategically penetrate the platform-squared segment-app stores, operating systems, and cloud services. Given the potential network effects and winner-takes-all dynamics in AI platform-squared, this endeavor is of immediate urgency. To facilitate this transition, it is recommended that the government implement promotional policies that strategically nurture these AI platform-squared, rather than restrict them through regulations and stakeholder pressures.

• 유통과학연구
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• 제16권7호
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• pp.67-75
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• 2018

Purpose - In the 21st century, as information technology advances alongside the emergence of the 4th generation, industrial age, industrial environment has become individualized and customized. It is important to hire good quality employees for good service in the industry. The e-learning market is growing every year. Although e-learning companies are finding better quality employees in e-learning, it is not easy to find it. Companies also spend a lot of time and cost to find employee. On the employees side, they want to get a job freely when they want, but they cannot find their job easily. Furthermore, the labor market environment is changing fast. In the 4th generation, industrial age, employers require to find manpower whenever they need and want at little cost. So of their own accord, we have considered the necessity of management of human resources for employees and employers in e-learning. The purpose of this study is to propose a human cloud platform framework for enabling an efficient management of human resources in e-learning industry. Research design, data, and methodology - To pinpoint the items of a human cloud platform framework, the study was initiated according to the following process. First, items of competency relating to e-learning instructional designer was analyzed. Second, based on the items of information from this analysis, selection and validity verification took place with 5 e-learning specialists group. Third, the opinion of experts who were in charge of hiring in e-learning companies were collated with the questionnaire. Lastly, the human cloud platform framework was proposed based on opinion results. Results - The framework was comprised of 7 domains and 27 items in order to develop the human cloud platform for e-learning instructional designer. The analysis results showed that the most highly considered item were 'skill (4.60)' that employee already have the capability. Following this (in order) were 'project type (4.56)', 'work competency (4.56)', and 'strength area of instructional design (4.52)'. Conclusions - The 27 items in the human cloud platform framework were suggested in this study. Following this, we can consider to develop the human cloud platform for finding a job and hiring e-learning instructional designer easily. For successful platform operation, we need to consider reliability between employer and employee. In addition, we need quality assurance system based on operation has public confidence.