• International conference on construction engineering and project management
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• 2022.06a
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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.

• Electronics and Telecommunications Trends
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• v.34 no.4
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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.

• Korean Institute of Interior Design Journal
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• v.21 no.2
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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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• v.46 no.2
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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.

• Journal of Korea Multimedia Society
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• v.24 no.1
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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.

• Journal of Digital Contents Society
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• v.17 no.4
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• pp.219-226
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• 2016

In our general life, what we recognize information with our human eyes and use it is diverse and massive. But even the current technologies improved by artificial intelligence are exorbitantly deficient comparing to human visual processing ability. Nevertheless, many researchers are trying to get information in everyday life, especially concentrate effort on recognizing information consisted of text. In the fields of recognizing text, to extract the text from the general document is used in some information processing fields, but to extract and recognize the text from real image is deficient too much yet. It is because the real images have many properties like color, size, orientation and something in common. In this paper, we applies an adaptive edge enhanced MSER(Maximally Stable Extremal Regions) to extract the text area in those diverse environments and the scene text, and show that the proposed method is a comparatively nice method with experiments.

• Journal of the Korean Geographical Society
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• v.51 no.2
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• pp.235-253
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• 2016

China has been developing a new auto industry growth plan since 2004. In line with this initiative, China actively adopted its policy favoring foreign companies' investment which had a competitive edge over their technologies and manufacturing methodologies. To meet this demand in policy and market change, many foreign auto companies and their parts' manufacturers including Korean auto companies joined this stream. Policy change favoring higher technologies applicable in China requested auto companies' swift adaptation to meet the policy requirements by higher technologies with innovation and introduction of those foreign technologies to China. The spatial (excellence) strategy was followed by the increase in its efficiency and competiveness of each region, which were materialized by or in the form of; Firstly, strategic partnership with China auto companies and encouragement of Korea auto parts manufacturing companies to set up its own factories in China. Secondly, modularization and platform sharing strategy by applying enhanced technologies. Thirdly, strategic utilization of China local government's incentive policies. As production management methodology, JIS was adopted all across the board to meet the on-demand market requirements in the manufacturing processes. Auto part manufacturers had been integrated regionally based on forward linkages and modules. As a result, regional-specific auto industry complexes have been made in the places such as Beijing-Hyundai in the north, Dongfeng-Yueda-Kia in the south, common auto parts at central area like Qingdao, and other parts and raw materials in the vicinity of Shanghai.

• Journal of the Korea Furniture Society
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• v.20 no.2
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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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• v.37 no.1
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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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• v.11 no.10
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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.