• Journal of Korean Society on Water Environment
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• v.40 no.1
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• pp.19-35
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• 2024

The global pandemic, coronavirus disease caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the implementation of wastewater surveillance as a means to monitor the spread of SARS-CoV-2 prevalence in the community. The challenging aspect of establishing wastewater surveillance requires a well-equipped laboratory for wastewater sample analysis. According to previous studies, RT-PCR-based molecular tests are the most widely used and popular detection method worldwide. However, this approach for the detection or quantification of SARS-CoV-2 from wastewater demands a specialized laboratory, skilled personnel, expensive instruments, and a workflow that typically takes 6 to 8 hours to provide results for a few samples. Rapid and reliable alternative detection methods are needed to enable less-well-qualified practitioners to set up and provide sensitive detection of SARS-CoV-2 within wastewater at regional laboratories. In some cases, the structural and molecular characteristics of SARS-CoV-2 are unknown, and various strategies for the correct diagnosis of COVID-19 have been proposed by research laboratories. The ongoing research and development of alternative and rapid technologies, namely RT-LAMP, ELISA, Biosensors, and GeneXpert, offer a wide range of potential options not only for SARS-CoV-2 detection but also for other viruses. This study aims to discuss the effective regional rapid detection and quantification methods in community wastewater.

• Information Systems Review
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• v.25 no.2
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• pp.31-56
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• 2023

As the COVID-19 pandemic is prolonged, non-contact work has increased, as well as the demand for automation of simple and repetitive questions and tasks with success of using them. Therefore, companies are attempting to expand the area of automated business and apply various technologies such as AI to complex and various business processes of E2E to provide automation of all business. However, the extension to Intelligent Process Automation (IPA) is still in its beginning stage so that it is difficult to find practical use cases and related solutions. In this aspect, it is safe to say that there is insufficient evidence for companies which have various and complex enterprise processes to make a decision about the adoption. In this study, to solve this problem, a Hyper Automation Platform (HAP) that consists of RPA, Chatbot, and AI technology was proposed. Moreover, an implementation method that can bring intelligent process automation using HAP, and practical use-cases were provided so that it makes it possible to review the implementation of the HAP objectively and comprehensively. This study is meaningful and valuable to check the feasibility of the Hyper Automation concept and to actively utilize HAP.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.29-48
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• 2019

Recently, product design innovation to improve user experience has been perceived as a core element of enterprise competitiveness due to the fierce market competition and decrease of the technological gap between companies, but there is insufficient services to support the product experience evaluation of small and medium-sized companies (SMCs). The aim of this study is to develop a web-based product user experience evaluation and certification system supporting product design practices for SMCs. For system interface design, we conducted systematic functional requirement elicitation methods such as user survey, workflow analysis, user task definition, and function definition. Then main functions, information structure, navigation method, and detailed graphic user interfaces were developed with consideration of user interactions and requirements. In particular, it provides the databases for evaluation efficiency to support the evaluation process above a certain level of performance and efficiency, and knowledge databases to utilize in the evaluation and product design improvement. With help of the developed service platform, It is expected that the service platform would enhance SMCs' product development capability with regard to the user experience evaluation by connecting the consulting firms with SMCs.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.223-240
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• 2013

RFID(Radio Frequency Identification) is use of an RFID tag applied to object for the purpose of identification and tracking using radio waves. Recently, it is being actively researched and introduced in logistics and manufacturing. RFID portals in supply chains are meant to identify all the tags within a given interrogation zone. Hence the hardware and software mechanisms for RFID tag identification mostly focus on successful read of multiple tags simultaneously. Such mechanisms, however, are inefficient for determining moving direction of tags, sequence of consecutive tags, and validity of the tag reads from the viewpoint of workflow. These types of problems usually cause many difficulties in RFID portal implementation in manufacturing environment, there by having RFID-system developers waste a considerable amount of time. In this research, we designated an RFID portal system with SDO(Sequence, Direction, and Object-flow)-perception capability by using fundamental data supplied by ordinary RFID readers. Using our work, RFID system developers can save a great amount of time building RFID data-capturing applications in manufacturing environment.

• The KIPS Transactions:PartD
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• v.14D no.2
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• pp.265-272
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• 2007

In this paper, we implement an automated composition system of web services using hybrid techniques that merge the benefit of BPEL techniques, with the advantage of OWL-S, BPEL techniques have practical capabilities that fulfil the needs of the business environment such as fault handling and transaction management. However, the main shortcoming of these techniques is the static composition approach, where the service selection and flow management are done a priori and manually. In contrast, OWL-S techniques use ontologies to provide a mechanism to describe the web services functionality in machine-understandable form, making it possible to discover, and integrate web services automatically. This allows for the dynamic integration of compatible web services, possibly discovered at run time, into the composition schema. However, the development of these approaches is still in its infancy and has been largely detached from the BPEL composition effort. In this work, we describe the design of the SemanticBPEL architecture that is a hybrid system of BPEL4WS and OWL-S, and propose algorithms for web service search and integration. In particular, the SemanticBPEL has been implemented based on the open source tools. The proposed system is compared with existing BPEL systems by functional analysis. These comparisions show that our system outperforms existing systems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.655-664
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• 2008

Lean Construction recommends implementing site production management by measuring the reliability of daily production tasks, collecting the causes for failure of incomplete tasks, and identifying problems in the existing process based on the collected data. Although many research projects have been performed to introduce Lean Construction in Korea, there are not many cases in which day-to-day site production operations has been stringently evaluated based on such methods. This paper introduces three cases in which such techniques were implemented on a residential, civil infrastructure and plant project. On each project, process maps were created with the superintendents and daily production meetings were held for two weeks. Consequently, the average PPC for the three projects was 79% for PPC and 16% for PAT. In addition, the majority of the failures were due to 'Directive/Plan' and 'Prerequisites.' The results show that project stakeholders (owners, contractors, etc.) lack the ability to plan ahead and keep to their plans, and also lack the capability to synchronize workflow between themselves. The results also reveal that project participants need to be more proactive in solving process problems on site and also need to be better educated in Lean concepts and methodologies.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.2
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• pp.81-90
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• 2013

During the past decade, many changes and attempts have been tried and are continued developing new technologies in the computing area. The brick wall in computing area, especially power wall, changes computing paradigm from computing hardwares including processor and system architecture to programming environment and application usage. The high performance computing (HPC) area, especially, has been experienced catastrophic changes, and it is now considered as a key to the national competitiveness. In the late 2000's, many leading countries rushed to develop Exascale supercomputing systems, and as a results tens of PetaFLOPS system are prevalent now. In Korea, ICT is well developed and Korea is considered as a one of leading countries in the world, but not for supercomputing area. In this paper, we describe architecture design of MAHA supercomputing system which is aimed to develop 300 TeraFLOPS system for bio-informatics applications like human genome analysis and protein-protein docking. MAHA supercomputing system is consists of four major parts - computing hardware, file system, system software and bio-applications. MAHA supercomputing system is designed to utilize heterogeneous computing accelerators (co-processors like GPGPUs and MICs) to get more performance/$, performance/area, and performance/power. To provide high speed data movement and large capacity, MAHA file system is designed to have asymmetric cluster architecture, and consists of metadata server, data server, and client file system on top of SSD and MAID storage servers. MAHA system softwares are designed to provide user-friendliness and easy-to-use based on integrated system management component - like Bio Workflow management, Integrated Cluster management and Heterogeneous Resource management. MAHA supercomputing system was first installed in Dec., 2011. The theoretical performance of MAHA system was 50 TeraFLOPS and measured performance of 30.3 TeraFLOPS with 32 computing nodes. MAHA system will be upgraded to have 100 TeraFLOPS performance at Jan., 2013.

• Proceedings of the CALSEC Conference
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• 1998.10b
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• pp.585-594
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• 1998

이미 전자상거래(EC)가 시간적ㆍ공간적 제약을 극복하고 국경을 초월한 새로운 교역시장 (Cyber Market)으로 등장하고 있으며 세계 자동차 산업은 표준부품의 공동개발 및 조달을 통해 중복투자 방지, 신차개발기간 단축 등 전략적 제휴를 통한 공조ㆍ공생체계 구축을 경쟁적으로 추진하고 있으나 국내 자동차업계는 제품개발, 부품조달, 판매 및 A/S 등 모든 부문을 독자적으로 해결함으로써 경쟁력 제고에 역행하는 경향이 있다. 또한 자동차 선진국과는 달리 국제 경쟁력 강화를 위한 CALS/EC 정보 기반 기술의 실질적인 활용이 미흡한 실정이다. 이러한 현실을 개선하기 위해 최근에 자동차공업협회(KAMA)와 현대, 대우, 기아 자동차 3사는 자동차 산업 CALS 추진 모델(Autopia)의 구축을 추진하고 있다. 추진 내용은 자동차 산업의 전체 Life-Cycle인 제품기획 단계부터 설계, 생산, 구매/조달, 고객지원 단계등 전 분야를 3개 부문(신차개발 프로세스, 구매조달 프로세스, 고객지원 서비스)으로 구분되어 있다. 신차개발 프로세스 부문은 차세대 PDM을 통하여 제품개발 사이클 단축을 추구하며 STEP을 통한 범용적 설계정보 교환 체계 구현이 기반이 된다. 또한 업무 흐름의 불투명성으로 인한 업무의 불균형 현상 타파와 설계 변경의 효율적 대응을 위하여 Workflow Management가 동시공학에 바탕을 두고 도입 적용되어야 한다. CAD 데이터를 비롯한 방대한 데이터의 효율적 관리를 위해서는 각 프로세스별로 독립된 정보를 체계적으로 관리할 수 있는 통합 환경(Integrated Data Environment)을 구성하여 각 프로세스에 걸쳐 데이터의 처리효율을 증대하여야 한다. 신차개발 부문의 핵심 기술이면서도 현업 적용이 초기 단계인 Digital Mockup과 Virtual Reality의 적용을 위해서는 3D 모델링이 기본 설계 방법으로 적용되어야 하며 이를 통한 어셈블리 및 부품구조의 관리가 이루어져야 한다. 구매조달 프로세스 부문은 자동차 업계의 공통 EDI/EC 네트워크 구축을 통한 경제적인 인프라 구조와 함께 부품 조달 체계의 간소화를 추구함으로써 자동차 산업의 대외 경쟁력 강화가 이루어 질 수 있다. 공개구매 시스템의 구축을 통하여 완성차별로 전속 계열화된 수직적인 부품조달 체계와 업체간 정보공유의 폐쇄성을 제거할 수 있고 완전 경쟁에 의한 우량 협력업체 발굴 기회의 확대가 용이하다. 이를 통하여 궁극적으로는 Global Vendor망의 구축이 실현될 것이다. 종합물류 시스템이 구현되면 판매는 경쟁체제, 물류는 공동화가 됨으로써 국가적으로 물류 비용의 절감이 엄청날 것으로 예상된다. 전국에 산재되어 있는 1,000여개의 대리점과 7,000여개의 정비업소를 대상으로 한 정비부품 EDI/EC 시스템이 구축되면 고객 서비스의 효율 향상과 함께 정비업소의 물류 및 재고 비용의 감소, 조달 속도의 향상, 조달 업무의 간소화 등의 효과를 보게 될 것이다. 고객지원 서비스는 정비정보 시스템, 산업정보 시스템, 쇼핑몰 시스템, 등록대행 시스템등을 통하여 일반 국민들이 피부로 느낄 수 있는 시스템으로 구축 되어야 할 것이다.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1273-1284
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• 2016

In this paper, we analyzed the patents on machine learning using keyword network analysis and clique analysis. To construct a keyword network, important keywords were extracted based on the TF-IDF weight and their association, and network structure analysis and clique analysis was performed. Density and clustering coefficient of the patent keyword network are low, which shows that patent keywords on machine learning are weakly connected with each other. It is because the important patents on machine learning are mainly registered in the application system of machine learning rather thant machine learning techniques. Also, our results of clique analysis showed that the keywords found by cliques in 2005 patents are the subjects such as newsmaker verification, product forecasting, virus detection, biomarkers, and workflow management, while those in 2015 patents contain the subjects such as digital imaging, payment card, calling system, mammogram system, price prediction, etc. The clique analysis can be used not only for identifying specialized subjects, but also for search keywords in patent search systems.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.3
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• pp.301-315
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• 2010

Recently, competition between companies has intensified and so has the necessity of creating a new business value inventions has increased. A numbers of Business organizations are beginning to realize the importance of business process management. Processes however can often not go the way they were initially designed or non-efficient performance process model could be designed. This can be due to a lack of cooperation and understanding between business analysts and system developers. To solve this problem, business process mining which can be used as the basis of the business process re-engineering has been recognized to an important concept. Current process mining research has only focused their attention on extracting workflow-based process model from competed process logs. Thus there have a limitations in expressing various forms of business processes. The disadvantage in this method is process discovering time and log scanning time in itself take a considerable amount of time. This is due to the re-scanning of the process logs with each new update. In this paper, we will presents a modified FP-Tree algorithm for FP-Tree based business processes, which are used for association analysis in data mining. Our modified algorithm supports the discovery of the appropriate level of process model according to the user's need without re-scanning the entire process logs during updated.