• International conference on construction engineering and project management
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• 2013.01a
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• pp.386-389
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• 2013

Under climate change and urbanization, rainwater harvesting (RWH) systems are emerging as an alternative source of water supply because of growing concern about water sustainability. RWH systems can satisfy the various watering needs and provide the environmental benefits of lessening the damages from flood, drought, and runoff. The economic success of a RWH system is vitally concerned with the determination of the design capacity of storage tank to be built in the system. The design capacity is determined by the factors of average annual rainfall, period of water scarcity, and water price during the whole life-cycles. Despite the high uncertainties inherent in these factors, the current engineering design of RWH system construction often assumes that storage tanks should be built all at once. This assumption implicitly ignores the managerial flexibility in responds to the future as new information comes out-the right to build storage tanks stage by stage depending on the evolution of demand. This study evaluates the value of a multistage storage tank construction using a real option approach. A case study involving a typical RWH system construction in Jeonju, the Republic of Korea is conducted. The managerial flexibility obtained from the real option perspective allows engineers to develop investment strategies to better cope with the issue of water sustainability.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.44-55
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• 2024

High-utility itemset mining (HUIM) is a dominant technology that enables enterprises to make real-time decisions, including supply chain management, customer segmentation, and business analytics. However, classical support value-driven Apriori solutions are confined and unable to meet real-time enterprise demands, especially for large amounts of input data. This study introduces a groundbreaking model for top-N high utility itemset mining in real-time enterprise applications. Unlike traditional Apriori-based solutions, the proposed convolutional sequential embedding metrics-driven cosine-similarity-based multilayer perception learning model leverages global and contextual features, including semantic attributes, for enhanced top-N recommendations over sequential transactions. The MATLAB-based simulations of the model on diverse datasets, demonstrated an impressive precision (0.5632), mean absolute error (MAE) (0.7610), hit rate (HR)@K (0.5720), and normalized discounted cumulative gain (NDCG)@K (0.4268). The average MAE across different datasets and latent dimensions was 0.608. Additionally, the model achieved remarkable cumulative accuracy and precision of 97.94% and 97.04% in performance, respectively, surpassing existing state-of-the-art models. This affirms the robustness and effectiveness of the proposed model in real-time enterprise scenarios.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.6
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• pp.616-625
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• 2017

Measurements using five real-time particle samplers were compared to measurements using three NRM (National Reference Method system) filter-based samplers(Gravimetric method) at Incheon, Korea, between May and August, 2014. The purpose of this study was to suggest the quality assurance/quality control (QA/QC) method of each instrument for use in a real-time continuous particle sampler to measure the mass of airborne particles with an aerodynamic diameter less than $2.5{\mu}m$ ($PM_{2.5}$). Five real-time particle samplers of BAM1020, FH62C_14, TEOM, PM-711 and SPM-613 were evaluated by comparing its measured 23 hr average $PM_{2.5}$ concentrations with those measured with NRM filter-based samplers simultaneously. The parameters(e.g. Inlet heating condition, Slope factor, Film response, Intercept, Background, Span value) of the real-time samplers were optimized respectively by conducting test performance evaluation during 7 days in field sampling. For example, inlet heating temperature of TEOM sampler controls $35{\sim}40^{\circ}C$ to minimize the fluctuation of the real-time measurement data and background value of BAM1020 is the key factor affecting the accuracy of $PM_{2.5}$ mass concentration. We classified the $PM_{2.5}$ concentration according to relative humidity (80%) to identify water absorbed in aerosols by measuring the ${\beta}$-ray samplers(BAM1020, FH62C_14) and TEOM. ${\beta}$-ray samplers were not strongly affected by relative humidity that the difference of the average $PM_{2.5}$ concentration was about 5%. On the other hand, The TEOM sampler overestimated $PM_{2.5}$ mass concentration about 15% at low relative humidity (<80%).

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.24.1-24.15
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• 2023

Background: The construction workers are vulnerable to fatigue due to high physical workload. This study aimed to investigate the relationship between overwork and heart rate in construction workers and propose a scheme to prevent overwork in advance. Methods: We measured the heart rates of construction workers at a construction site of a residential and commercial complex in Seoul from August to October 2021 and develop an index that monitors overwork in real-time. A total of 66 Korean workers participated in the study, wearing real-time heart rate monitoring equipment. The relative heart rate (RHR) was calculated using the minimum and maximum heart rates, and the maximum acceptable working time (MAWT) was estimated using RHR to calculate the workload. The overwork index (OI) was defined as the cumulative workload evaluated with the MAWT. An appropriate scenario line (PSL) was set as an index that can be compared to the OI to evaluate the degree of overwork in real-time. The excess overwork index (EOI) was evaluated in real-time during work performance using the difference between the OI and the PSL. The EOI value was used to perform receiver operating characteristic (ROC) curve analysis to find the optimal cut-off value for classification of overwork state. Results: Of the 60 participants analyzed, 28 (46.7%) were classified as the overwork group based on their RHR. ROC curve analysis showed that the EOI was a good predictor of overwork, with an area under the curve of 0.824. The optimal cut-off values ranged from 21.8% to 24.0% depending on the method used to determine the cut-off point. Conclusion: The EOI showed promising results as a predictive tool to assess overwork in real-time using heart rate monitoring and calculation through MAWT. Further research is needed to assess physical workload accurately and determine cut-off values across industries.

• Korean Journal of Construction Engineering and Management
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• v.15 no.1
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• pp.39-50
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• 2014

After the global financial crisis, domestic construction industry has gone through a rapid recession. This resulted in gradual market shift towards architectural remodeling. Architectural remodeling not only improves residential environment but it has many advantages such as increase of each unit's exclusive area, free space within the horizontal or extension of an annex building, and increase number of household through splitting the household of bigger pyeong, etc. However, in case of the Korean market for apartment remodeling, due to various regulations and problem with business promotion procedures, majority of business is slow despite the figure that remodeling volume is not that small. Also, feasibility study which decides to push ahead public house remodeling business will have a flaw using net present value's law; it has a flaw of not considering properties of each phase of remodeling business and future's uncertainty. Hence, this research will improve the problem of traditional value assessment method of net present value's law. It will also consider one of the real options such as binomial model in order to supplement NPV which is used in current feasibility study. This research was based on real successful cases of public house remodeling and it was possible for feasibility study which was more realistic and valid. This research provided foundation for development of Korean public house remodeling market. There is high anticipation of increasing the validity by improving the problems of current feasibility study and economic efficiency assessment.

• Environmental and Resource Economics Review
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• v.18 no.2
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• pp.217-239
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• 2009

As gas hydrate is recently emerging as a new energy source to solve environmental and exhaustion problems caused by fossil energy, Korea is working on a gas hydrate development project under a 10-year plan from 2005 to 2014. Gas hydrate is expected to have a big effect on the economy and society of Korea, which is largely depending on energy imports besides water energy and atomic energy. However, it is uncertain whether the project will produce successful results. Thus, it is very important to improve its validity and to propose effective execution strategies by evaluating the value of the project in advance. Thus, this study intended to include new information, which had not been evaluated in existing methods, and to reduce biases or errors in value evaluation results by applying a fuzzy risk analysis to the real option model in order to evaluate the value of a gas hydrate development project. It is advantageous that the real option model based on the fuzzy risk analysis modelizes the vagueness and inexactness of intangible element judgment into an appropriate language scale so as to evaluate these elements clearly and integrate them with estimated financial performance results. The application of the fuzzy risk analysis makes it possible to conduct an analysis by dissolving a decision-making issue with complicated and various attributes into several simplified problems. With the continuing high oil prices and today's demand of clean energy, the necessity of energy resources and technology development projects keeps growing. Amid this situation, it is expected that these study results will contribute to proposing a guideline not only for gas hydrate projects but also for policy decision-making related to future energy industries.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.112-121
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• 2016

ADAS(Advanced Driver Assistance Systems) and street furniture information collecting car like as MMS(Mobile Mapping System), they require object location estimation method for recognizing spatial information of object in road images. But, the case of conventional methods, these methods require additional hardware module for gathering spatial information of object and have high computational complexity. In this paper, for a coordinate of road sign in single camera image, a position estimation scheme of object in road images is proposed using the relationship between the pixel and object size in real world. In this scheme, coordinate value and direction are used to get coordinate value of a road sign in images after estimating the equation related on pixel and real size of road sign. By experiments with test video set, it is confirmed that proposed method has high accuracy for mapping estimated object coordinate into commercial map. Therefore, proposed method can be used for MMS in commercial region.

• Journal of Korea Game Society
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• v.12 no.1
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• pp.123-132
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• 2012

There are many of games using smart devices. Voice recognition is can be useful way for input. In the game, voice have to be quickly recognized, at the same time it have to be manipulated promptly as well. In this study, we developed the optimized real-time phoneme recognition using max flow matching that it can be efficiently used in the game field. Firstly, voice wavelength is transformed to FFT, secondly, transformed value is made by a graph in Z plane, thirdly, data is extracted in specific area, and then data is saved in database. After all the value is recognized using weighted bipartite max flow matching. This way would be useful method in game or robot field when researchers hope to recognize the fast voice recognition.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.553-558
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• 2003

The boundary estimation problem is used to estimate the shape of organic depend on the phase of the cardiac cycle or interested in the detection of the location and size of anomalies with resistivity values different from the background tissues such as nuclear reactor. And we can use the method to solve the optimal solution such as modified Newton raphson, kalman filter, extended kalman filter, etc. But, this method consumes much time and is sensitive to the initial value and noise in the estimation of the unknown shape. In the paper, we propose that multi-layer neural networks estimate the boundary of the unknown object using Fourier coefficient. This method can be used at the real time estimation and have strong characteristics at the noise and initial value. It uses voltage change; difference the homogeneous voltage to the non-homogeneous voltage, and change of Fourier coefficient change to train multi-layer neural network. After train, we can have real time estimation using this method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.423-426
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• 2005

In this paper, we proposed a PID tuning algorithm by the fuzzy set theory to improve the performance of the PID controller. The new tuning algorithm for the PID controller has the initial value of parameter Kp, $\tau_{I}$, $\tau_{D}$. by the Ziegler-Nichols formula that uses the ultimate gain and ultimate period from a relay tuning experiment. We will get the error and the error rate of plant output corresponding to the initial value of parameter and fnd the new proportion gain(Kp) and the integral time ($\tau_{I}$) from fuzzy tuner by the error and error rate of plant oueut as a membership function of fuzzy theory. This fuzzy auto tuning algorithm for PID controller considerably reduced the overshoot and rise time as compared to any other PID controller tuning algorithms. And in real parametric uncertainty systems, it constitutes an appreciable improvement of performance. The significant property of this algorithm is shown by simulation