• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.536-542
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• 2022

Cost overruns, schedule delays, and a shortage of skilled labor are common problems the construction industry is currently experiencing. Modularization and standardization strategies have the potential to resolve the various problems mentioned above and have been applied for various construction applications for a long time. However, the level of modularization remains low, and modular construction projects have not been getting the full benefits. Thus, this review investigated the cutting-edge technologies currently being utilized to develop the modular construction field. For this paper, qualified research papers were identified using predetermined keywords from previous related research papers. Identified literature was then filtered and analyzed. According to the included reviews, several technologies are being developed for modular construction. For example, automated design and monitoring systems for modularization were developed. In addition, research labs are utilizing robotic arms for modular construction to achieve a high level of completion in the construction industry, as is seen in the manufacturing industry. Despite these efforts, more research and development are necessary because some automation technologies still require manual activities. Thus, there is great potential for further development of modularization techniques, and further research is recommended to achieve high levels of modularization.

• 전자통신동향분석
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• 제34권4호
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• pp.76-88
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• 2019

With advances in olfactory sensor technologies, the number of reports on various intelligent applications using multiple sensors (sensor arrays) are continuously increasing for fields such as medicine, environment, security, etc. For intelligent and point-of-care applications, it is not only important for the sensor technology to perform chemical or physical measurements rapidly and accurately, but it is also important for artificial intelligence technology to recognize and quantify specific chemicals or diagnose diseases such as lung cancer and diabetes. In particular, great advances in pattern recognition technologies, including deep learning algorithms, as well as sensor array technologies, are expected to enhance the potential of various types of olfactory intelligence applications, including early cancer diagnosis, drug seeking, military operations, and air pollution monitoring.

• 한국실내디자인학회논문집
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• 제21권2호
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• pp.3-13
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• 2012

With the emergence of the smart era, interest in future society and new dwelling spaces is growing. This research analyzes the planning items applied to future house pavilions in Korea to examine which functions will be more emphasized and considered importantly in the dwelling spaces. This research paper aims to identify those dwelling functions that will occupy greater importance from the users' point of view. As for the research methodology, it comprised a literature review and an analysis of case studies. The results of this research were as follows; 1) It was arranged that the dwelling functions were safety, amenity, convenience, independence, economics, society, relaxation, aesthetic appearance. 2) For future dwelling environments, environment-friendly technology for conservation of energy was important in addition to intellectual cutting edge technologies, 3) Safety was most basic among all dwelling functions, 4) Planning items related to amenity and economics were found to be most common, indicating that they were important functions in future dwelling environments, 5) With regard to convenience, planning items related to increasing efficiency of household chores through the application of ubiquitous technology were found to be most common, 6) There was no indication of planning items related to independence and society, 7) Cutting edge technology and emotional technology appear to be integrated in planning items related to relaxation and aesthetic appearance, and 8) Each future dwelling pavilion suggested that over 80% of the planning items were related to amenity, convenience, and economics. We expect that the results from our research will be useful in creating a life-centered design of future dwelling spaces that account for dwelling functions.

• Molecules and Cells
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• 제46권2호
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• pp.99-105
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• 2023

Tumors are surrounded by a variety of tumor microenvironmental cells. Profiling individual cells within the tumor tissues is crucial to characterize the tumor microenvironment and its therapeutic implications. Since single-cell technologies are still not cost-effective, scientists have developed many statistical deconvolution methods to delineate cellular characteristics from bulk transcriptome data. Here, we present an overview of 20 deconvolution techniques, including cutting-edge techniques recently established. We categorized deconvolution techniques by three primary criteria: characteristics of methodology, use of prior knowledge of cell types and outcome of the methods. We highlighted the advantage of the recent deconvolution tools that are based on probabilistic models. Moreover, we illustrated two scenarios of the common application of deconvolution methods to study tumor microenvironments. This comprehensive review will serve as a guideline for the researchers to select the appropriate method for their application of deconvolution.

• 한국멀티미디어학회논문지
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• 제24권1호
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• pp.75-94
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• 2021

The 4th industrial revolution needs a fusion of artificial intelligence, robotics, the Internet of Things (IoT), edge computing, and other technologies. For the fusion of technologies, cloud computing technology can provide flexible and high-performance computing resources so that cloud computing can be the foundation technology of new emerging services. The emerging services become a global-scale, and require much higher performance, availability, and reliability. Public cloud providers already provide global-scale services. However, their services, costs, performance, and policies are different. Enterprises/ developers to come out with a new inter-operable service are experiencing vendor lock-in problems. Therefore, multi-cloud technology that federatively resolves the limitations of single cloud providers is required. We propose a software platform, denoted as Cloud-Barista. Cloud-Barista is a multi-cloud service common platform for federating multiple clouds. It makes multiple cloud services as a single service. We explain the functional architecture of the proposed platform that consists of several frameworks, and then discuss the main design and implementation issues of each framework. To verify the feasibility of our proposal, we show a demonstration which is to create 18 virtual machines on several cloud providers, combine them as a single resource, and manage it.

• 디지털콘텐츠학회 논문지
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• 제17권4호
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• pp.219-226
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• 2016

일반 생활 속에서 우리 인간의 눈으로 정보를 인식하고 그 정보를 이용하는 것에는 한계가 없을 만큼 다양하고 방대하다. 그러나 인공지능이 발달한 현재의 기술로도, 인간의 시각 처리 능력에 비하면 턱없이 능력이 부족하다. 그럼에도 불구하고 많은 연구자들은 실생활 속에서 정보를 얻고자 하고 있고, 특히 글자로 된 정보를 인식하는데 많은 노력을 기울이고 있다. 글자를 인식하는 분야에서 일반적인 문서에서 글자를 추출하는 것은 일부 정보처리 분야에서 이용되고 있지만, 실영상에서 문자를 추출하고 인식하는 부분은 아직도 많이 부족하다. 그 이유는 실영상에서는 색깔, 크기, 방향, 공통점 등에서 다양한 특징을 갖고 있기 때문이다. 본 논문에서는 이런 다양한 환경에서 문자 영역을 추출하기 위하여 적응적 에지 강화 기반의 MSER을 적용하여 장면 텍스트 추출을 시도하고, 비교적 좋은 방법임을 실험으로 보인다.

• 대한지리학회지
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• 제51권2호
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• pp.235-253
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• 2016

중국은 2004년부터 자동차 공업 관련 신산업 정책을 추진하기 시작하였다. 이와 함께 기존의 맹목적인 외자유치에서 높은 기술수준을 지닌 외자기업을 유치하는 방향으로 선회하였다. 이러한 정책적 환경 변화는 수많은 다국적 기업들 및 협력기업들의 중국 진출을 본격화시켰으며, 한국의 완성차 및 부품기업 또한 진출이 이루어졌다. 외자기업의 착근과정에서 나타난 제도적 변화에 의한 혁신적인 기술 적용 필요성은 기업의 기술 혁신 필요성과 조응하였는데, 효율적 공간 전략이 요구되었다. 첫째, 제도적 변화에 따른 로컬 파트너십 활용과 부품기업 동반진출 전략, 둘째, 기술혁신을 통한 모듈화 및 공용 플랫폼 전략, 셋째, 지방정부 인센티브 정책 활용 전략이 그것이다. 특히 생산 네트워크 내 행위자들은 직서열 공급방식을 통한 부품 공급망을 따라 전후방 연계의 흐름이 나타났으며 관계성이 강화되었다. 따라서 부품기업들은 원활한 협력 체제를 위해 전방기업 및 모듈 단위 중심으로 집적하였다. 그 결과 북쪽의 베이징 현대를 중심으로 하는 북쪽 지역, 남쪽의 동풍열달기아를 중심으로 하는 남쪽 지역, 공용 부품을 공급하기 위한 칭다오를 중심으로 하는 중부 지역, 일반 공용 부품 및 원자재를 공급하는 상하이를 중심으로 하는 기타 지역으로 생산 공간의 분화가 나타났다.

• 한국가구학회지
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• 제20권2호
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• pp.166-174
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• 2009

Most of the furniture in the past was dedicated to its original use such as storage and accommodation of articles or sitting tools, but the concept of furniture in contemporary indoor spaces is gradually increasing in its meaning while exchanging close impacts with other spatial components. Indeed, in contemporary furniture, a component other than furniture constituting a space would sometimes serve the common roles of furniture or sometimes furniture would include all indoor objects used to make people's living more convenient. This study reviewed the meaning of furniture and changes in its roles in contemporary indoor spaces and summarized the characteristics presenting a few examples. First, in contemporary indoor spaces, furniture as an independent object does not having a meaning any more. The fusion of functions with other components constituting indoor spaces is the most important characteristics in contemporary furniture and it has been already attempted in diverse ways through fusion with buildings surpassing fusion with other pieces of furniture or electric home appliances. Second, the arrangement conforming to the roles required by spaces and diverse forms of attempts are essential. Since furniture is an item the most closely related to human residential life, studies on human behaviors in spaces must precede. The efforts to enhance work efficiencies and used limited spaces more efficiently will be continued and explorations of new forms should be also continued. Third, with regards to manufacturing methods, new technologies should be applied more widely and furniture materials must be diversified through the use of new materials including not only cutting-edge new materials but also all the materials that can be applied to furniture such as conventional natural materials and environment friendly materials that can be recycled.

• Geomechanics and Engineering
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• 제37권1호
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• pp.65-72
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• 2024

Water ingress poses a common and intricate geological hazard with profound implications for tunnel construction's speed and safety. The project's success hinges significantly on the precision of estimating water inflow during excavation, a critical factor in early-stage decision-making during conception and design. This article introduces an optimized model employing the gene expression programming (GEP) approach to forecast tunnel water inflow. The GEP model was refined by developing an equation that best aligns with predictive outcomes. The equation's outputs were compared with measured data and assessed against practical scenarios to validate its potential applicability in calculating tunnel water input. The optimized GEP model excelled in forecasting tunnel water inflow, outperforming alternative machine learning algorithms like SVR, GPR, DT, and KNN. This positions the GEP model as a leading choice for accurate and superior predictions. A state-of-the-art machine learning-based graphical user interface (GUI) was innovatively crafted for predicting and visualizing tunnel water inflow. This cutting-edge tool leverages ML algorithms, marking a substantial advancement in tunneling prediction technologies, providing accuracy and accessibility in water inflow projections.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.