• Journal of KIBIM
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• v.12 no.4
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• pp.1-18
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• 2022

New Fabrication Facility (FAB) construction is performed with Building Information Modeling (BIM) based design. The BIM design data keep updated during the FAB construction. To improve fast-track construction management, a Fabrication Facility Augmented Reality (FABAR) was developed. This study introduces a FABAR system development process and shows performance evaluation results of the FABAR prototype system. The FABAR is implemented with three major modules: Augmented Reality (AR) visualization unit (Room-box) to transfer big BIM data to AR data, AR registration and tracking unit to match AR with real scape and to keep AR coordination in real, and AR data management unit to enhance usability. The prototype performance results were as follows: visualization of design BIM data via AR within 24 hours, precise AR registration and tracking registration, and appropriate usability to support FAB construction management at site. The results indicate that the FABAR is applicable for FAB construction management. Especially, the BIM data transformation method using Room-box in this study signifies a new construction management approach using fluctuating BIM design data in the fast track construction condition.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.49-52
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• 2002

High-resolution satellite image processing software should be able to ensure accurate, fast, compact data processing in offline or online environment. In this paper, component software for high-resolution satellite image processing is developed using OpenGIS components and real-time data processing architecture. The developed component software is composed of three major packages, which are data provide package, user interface package, and fast data processing package. The data provider package encodes and decodes diverse image/vector data formats and give identical data access methods to developers. The user interface package supports menus, toolbars, dialogs, and events to use easier. The fast data processing package follows the OpenGIS's data processing standards, which can deal with several processors as components with standard procedural functionalities.

• Journal of Communications and Networks
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• v.12 no.3
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• pp.275-284
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• 2010

The current multihome-aware protocols (like stream control transmission protocol (SCTP) or parallel TCP for concurrent multipath data transfer (CMT) are not designed for high-capacity and large-latency networks; they often have performance problems transferring large data files over shared long-distance wide area networks. It has been shown that SCTP-CMT is more sensitive to receive buffer (rbuf) constraints, and this rbuf-blocking problem causes considerable throughput loss when multiple paths are used simultaneously. In this research paper, we demonstrate the weakness of SCTP-CMT rbuf constraints, and we then identify that rbuf-blocking problem in SCTP multihoming is mostly due to its loss-based nature for detecting network congestion. We present a simulation-based performance comparison of FAST TCP versus SCTP in high-speed networks for solving a number of throughput issues. This work proposes an end-to-end transport layer protocol (i.e., FAST TCP multihoming as a reliable, delaybased, multihome-aware, and selective ACK-based transport protocol), which can transfer data between a multihomed source and destination hosts through multiple paths simultaneously. Through extensive ns-2 simulations, we show that FAST TCP multihoming achieves the desired goals under a variety of network conditions. The experimental results and survey presented in this research also provide an insight on design decisions for the future high-speed multihomed transport layer protocols.

• Journal of Korea Multimedia Society
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• v.8 no.9
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• pp.1153-1162
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• 2005

In this paper, we developed an XML Document Data Synchronization System for java(XDS4j) based on both SyncML(Synchronization Markup Language) framework Sync4j and embedded database system Berkeley DB XML. Because most existing data synchronization systems are based on file systems, data synchronization times at Fast Sync in those systems are very delayed. In the XDS4j, however, XML documents data produced at SyncML client and SyncML server are managed by embedded database system, and also synchronization time at Fast Sync is reduced because only partial elements are accessed by applying to XPath.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.347-355
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• 2012

A fast algorithm for endmember extraction is proposed in this study which extracts min. and max. pixels from each band after MNF transform as candidate pixels for endmember. This method finds endmembers not from the entire image pixels but only from the previously extracted candidate pixels. The experimental results by N-FINDR using a simulated hyperspectral image data and AVIRIS Cuprite image data showed that the proposed fast algorithm extracts the same endmembers with the conventional methods. More studies on the effect of noise and more adaptive criteria in extracting candidate pixels are expected to increase the usability of this method for more fast and efficient analysis of hyperspectral image data.

• ETRI Journal
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• v.29 no.2
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• pp.143-152
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• 2007

In this paper, we propose a time-varying modified minimum mean-squared error (MMSE) detector for the detection of higher data rate signals in a multirate asynchronous code-division multiple-access (CDMA) system which is signaled in a fast Rayleigh fading channel. The interference viewed by a higher data rate symbol will be periodic due to the presence of a lower data rate symbol which spans multiple higher data rate symbols. The detection is carried out on the basis of a modified MMSE criterion which incorporates differential detection and the ratio of channel coefficients in two consecutive observation intervals inherently compensating the fast variation of the channel due to fading. The numerical results obtained by the MMSE detector with time-varying detection show around 3 dB (M=2) and 6 dB (M=4) performance improvement at a BER of $10^{-3}$ in the AWGN channel, while introducing more computational complexity than the MMSE detector without time-varying detection. At a higher $E_b/N_0$, the proposed scheme can achieve a BER of approximately $10^{-3}$ in the presence of fast channel variation which is an improvement over other schemes.

• The Journal of Economics, Marketing and Management
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• v.9 no.1
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• pp.1-14
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• 2021

Purpose: The article deals with the proposition that consumers' fashion consumption behavior will still follow the consumption behavior of fast fashion, despite recognizing the importance of slow fashion. Research design, data and methodology: The research model to verify this proposition is topic modelling with big data including unstructured textual data. we combined 5,506 news articles posted on Naver news search platform during the 2003-2019 period about fast fashion and slow fashion, high-frequency words have been derived, and topics have been found using LDA model. Based on these, we examined consumers' perception and consumption behavior on slow fashion through the analysis of Topic Network. Results: (1) Looking at the status of annual article collection, consumers' interest in slow fashion mainly began in 2005 and showed a steady increase up to 2019. (2) Term Frequency analysis showed that the keywords for slow fashion are the lowest, with consumers' consumption patterns continuing around 'brand.' (3) Each topic's weight in articles showed that 'social value' - which includes slow fashion - ranked sixth among the 9 topics, low linkage with other topics. (4) Lastly, 'brand' and 'fashion trend' were key topics, and the topic 'social value' accounted for a low proportion. Conclusion: Slow fashion was not a considerable factor of consumption behavior. Consumption patterns in fashion sector are still dominated by general consumption patterns centered on brands and fast fashion.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.29-34
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• 2023

The flow from developing a machine learning model to deploying it in a production environment suffers challenges. Efficient and reliable deployment is critical for realizing the true value of machine learning models. Bridging this gap between development and publication has become a pivotal concern in the machine learning community. FastAPI, a modern and fast web framework for building APIs with Python, has gained substantial popularity for its speed, ease of use, and asynchronous capabilities. This paper focused on leveraging FastAPI for deploying machine learning models, addressing the potentials associated with integration, scalability, and performance in a production setting. In this work, we explored the seamless integration of machine learning models into FastAPI applications, enabling real-time predictions and showing a possibility of scaling up for a more diverse range of use cases. We discussed the intricacies of integrating popular machine learning frameworks with FastAPI, ensuring smooth interactions between data processing, model inference, and API responses. This study focused on elucidating the integration of machine learning models into production environments using FastAPI, exploring its capabilities, features, and best practices. We delved into the potential of FastAPI in providing a robust and efficient solution for deploying machine learning systems, handling real-time predictions, managing input/output data, and ensuring optimal performance and reliability.

• The Journal of Industrial Distribution & Business
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• v.12 no.6
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• pp.7-21
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• 2021

Purpose: Modern globalization and Western markets saturation has catalyzed the growth of culinary globalization into developing countries. The question was whether fast food consumers in frontier markets of Sub-Saharan Africa (Zimbabwe), either upholds national gastronomic tendencies in terms of consumer ethnocentrism and buy local or they adopt global fast food brands. Demographic consumer profiles were also analyzed as antecedents of consumer ethnocentrism. Research design, data and methodology: A sample size of 400 fast food-adult consumers was surveyed in the City of Harare. Data was captured on SPSS and Analysis of Moment Structure (AMOS). Hypothesis testing was done using sample t test (H₁), logistic regression (H₂) and multiple regression (H₃, ₄, ₅) analysis. Results: Consumer ethnocentrism in Zimbabwe was marginally above average and no statistically significant relationship between the levels of consumer ethnocentrism and adoption of foreign fast food brands was noted. Age had an inverse relationship; income had a positive association whilst gender had no statistical significance with consumer ethnocentrism. Conclusions: Despite the Zimbabwean consumers being marginally ethnocentric, international restaurateurs should invest in the Zimbabwean fast food market since their nature of being foreign has got an exotic appeal to the Zimbabwean consumers thereby enhancing their likelihood of success.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.172-177
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• 1988

In this paper, a new fast algorithm of FIR least squares filter with linear phase is presented. The general unknown statistics case is considered, whereby only sample records of the data are available. Taking advantage of the near-to-Toeplitz+Hankel structure of the resulting normal equation, a fast algorithm which gurantees the linear phase constraint, is developed that recursively produces the filter coefficient of linear phase FIR filter for a single block of data.