• Journal of Korean Port Research
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• v.12 no.1
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• pp.1-8
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• 1998

If a system has a large boundary and complexity, forecast's accuracy will be very low when consider the system's substance as black box. Thus, it is necessary that analysis by structure model. To examine competition in Northeast Asia Ports, it has assumed that the form of structure model, For which the System Dynamics method is adapted in this paper. Northeast Asia Ports Model includes five ports - Pusan, Kobe, Yokohama, Kaoshiung, Keelung, - which are adjacent to each other by geographically and has a competition relation. The Northeast Asia Ports Model has several sub-systems which consists of each unit port models. And, each unit port model found by quantitive, qualititive factors and their feedback loops. All effects which components of one port have influence to components of the rest ports must be surveyed in order to construct Northeast Asia Ports Model, but it may be impossible currently. In this paper Northeast Asia Ports Model was simplified by HFP-Hierarchical Fuzzy Process Method-adapted to integration of level variables of unit port model. Container cargo volumes in Northeast Ports Model is distributed by results of HFP method. And distributed container cargo volumes effected to unit port model. Developed model can estimate change of container cargo volumes in competitive relation by alternation of simple parameter, and reflects dynamics characteristics which are included in model.

• Clean Technology
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• v.29 no.2
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• pp.145-150
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• 2023

Tele-metering systems have been useful tools for managing domestic wastewater treatment plants (WWTP) over the last decade. They mostly generate water quality data for discharged water to ensure that it complies with mandatory regulations and they may be able to produce every operation parameter and additional measurements in the near future. A sub-big data group, comprised of about 150,000 data points from four domestic WWTPs, was ready to be classified and also analyzed to optimize the WWTP process. We used the Statistical Product and Service Solutions (SPSS) 25 package in order to statistically treat the data with linear regression and correlation analysis. The major independent variables for analysis were water temperature, sludge recycle rate, electricity used, and water quality of the influent while the dependent variables representing the water quality of the effluent included the total nitrogen, which is the most emphasized index for discharged flow in plants. The water temperature and consumed electricity showed a strong correlation with the total nitrogen but the other indices' mutual correlations with other variables were found to be fuzzy due to the large errors involved. In addition, a multilayer perceptron analysis method was applied to TMS data along with root mean square error (RMSE) analysis. This study showed that the RMSE in the SS, T-N, and TOC predictions were in the range of 10% to 20%.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.142-142
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• 2022

Adjusting weather radar data is a prerequisite for its use in various hydrological studies. Effect of spatial variables are considered to adjust weather radar data in many of these researches. The existence of diverse topography in South Korea has increased the importance of analyzing these variables. In this study, some spatial variable like slope, elevation, aspect, distance from the sea, plan and profile curvature was considered. To investigate different topographic conditions, tried to use three radar station of Gwanaksan, Gwangdeoksan and Gudeoksan which are located in northwest, north and southeast of South Korea, respectively. To form the suitable fuzzy model and create the best membership functions of variables, ANFIS-PSO model was applied. After optimizing the model, the correlation coefficient and sensitivity of adjusted Quantitative Precipitation Estimation (QPE) based on spatial variables was calculated to find how variables work in adjusted QPE process. The results showed that the variable of elevation causes the most change in rainfall and consequently in the adjustment of radar data in model. Accordingly, the sensitivity ratio calculated for variables shows that with increasing rainfall duration, the effects of these variables on rainfall adjustment increase. The approach of this study, due to the simplicity and accuracy of this method, can be used to adjust the weather radar data and other required models.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.496-500
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• 2015

International construction projects are inherently more risky than domestic projects with multi-dimensional uncertainties that require complementary risk management at both the country and project levels. However, despite a growing need for systematic country evaluations, most studies have focused on project-level decisions and lack country-based approaches for firms in the construction industry. Accordingly, this study suggests data-driven approaches for evaluating countries using two quantitative models. The first is a two-stage country segmentation model that not only screens negative countries based on country attractiveness (macro-segmentation) but also identifies promising countries based on the level of past project performance in a given country (micro-segmentation). The second is a multi-criteria country segmentation model that combines a firm's business objective with the country evaluation process based on Kraljic's matrix and fuzzy preference relations (FPR). These models utilize not only secondary data from internationally reputable institutions but also performance data on Korean firms from 1990 to 2014 to evaluate 29 countries. The proposed approaches enable firms to enhance their decision-making capacity for evaluating and selecting countries at the early stage of corporate strategy development.

• Steel and Composite Structures
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• v.49 no.6
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• pp.645-666
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• 2023

Due to the steadily declining supply of natural coarse aggregates, the concrete industry has shifted to substituting coarse aggregates generated from byproducts and industrial waste. Oil palm shell is a substantial waste product created during the production of palm oil (OPS). When considering the usage of OPSC, building engineers must consider its uniaxial compressive strength (UCS). Obtaining UCS is expensive and time-consuming, machine learning may help. This research established five innovative hybrid AI algorithms to predict UCS. Aquila optimizer (AO) is used with methods to discover optimum model parameters. Considered models are artificial neural network (AO - ANN), adaptive neuro-fuzzy inference system (AO - ANFIS), support vector regression (AO - SVR), random forest (AO - RF), and extreme gradient boosting (AO - XGB). To achieve this goal, a dataset of OPS-produced concrete specimens was compiled. The outputs depict that all five developed models have justifiable accuracy in UCS estimation process, showing the remarkable correlation between measured and estimated UCS and models' usefulness. All in all, findings depict that the proposed AO - XGB model performed more suitable than others in predicting UCS of OPSC (with R², RMSE, MAE, VAF and A_15-index at 0.9678, 1.4595, 1.1527, 97.6469, and 0.9077). The proposed model could be utilized in construction engineering to ensure enough mechanical workability of lightweight concrete and permit its safe usage for construction aims.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.169-177
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• 2024

Interacting Spherical tank has maximum storage capacity is broadly utilized in industries because of its high storage capacity. This two tank level system has the nonlinear characteristics due to its varying surface area of cross section of tank. The challenging tasks in industries is to manage the flow rate of liquid. This proposed work plays a major role in controlling the liquid level in avoidance of time delay and error. Several researchers studied and investigated about reducing the nonlinearity problem and their approaches do not provide better result. Different types of controllers with various techniques are implemented by the proposed system. Intelligent Adaptive Neuro Fuzzy Inference System (ANFIS) based Sliding Mode Controller (SMC) with Fractional order PID controller is a novel technique which is developed for a liquid level control in a interacting spherical tank system to avoid the external disturbances perform better result in terms of rise time, settling time and overshoot reduction. The performance of the proposed system is obtained by analyzing the simulation result obtained from the controller. The simulation results are obtained with the help of FOMCON toolbox with MATLAB 2018. Finally, the performance of the conventional controller (FOPID, PID-SMC) and proposed ANFIS based SMC-FOPID controllers are compared and analyzed the performance indices.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.177-186
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• 2014

Failure mode and effect analysis (FMEA) is a systematic approach for identifying potential failures before they occur, with the intent to minimize the risk associated with them. It has been widely used in the various manufacturing industries as a solution to reliability problems. As the importance of the service sector is increasing, however, it has been recently extended to some applications in services. Despite these attempts, FMEA cannot be directly applied to the reliability problems in a service industry. Due to the heterogeneity and customer participation in service process, we cannot perfectly prevent service failures. For this reason, we suggest a new risk priority number with three input parameters that consist of severity, probability of occurrence, and recoverability. In this paper, we propose an approach for assessing service risk and service reliability using the service-oriented risk priority number (S-RPN). An example regarding a hypermarket service process is used to demonstrate the proposed approach.

• Archives of design research
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• v.16 no.2
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• pp.57-66
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• 2003

In order to develop color image, color simulation based on data processing techniques has been developed and applied to data interpretation tools or product design supporting systems. It has been a commonmethod to use image key words to search for data and provide color coordination samples that determine computer combination in computerized support systems until recently. However, this method does not reflect system designers and users taste or preference on making final choices of color coordination samples because the database was designed based on an assumption of standardized group that was established database from large scaled image evaluation research. In this study, we suggest a color coordination simulator that supports designer's final decision-making procedure on sample groups through the simulation of various color combination. The simulator allows communications with the system to explore a designer's color combination taste and preference, and provides a user for an efficient environment to judge the optimum result. The color coordination simulator was designed based upon Dual mapping model derived from a designer's thought process, and four steps of operations longrightarrowdefining color concept longrightarrowmaking color sample groupslongrightarrow simulation-determining ranking among final combination samples - will be assisting color design process.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.247-254
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• 2006

Biometrics are getting more and more attention in recent years for security and other concerns. So far, only fingerprint recognition has seen limited success for on-line security check, since other biometrics verification and identification systems require more complicated and expensive acquisition interfaces and recognition processes. Hand-Geometry can be used for biometric verification and identification because of its acquisition convenience and good performance for verification and identification performance. It could also be a good candidate for online checks. Therefore, this paper proposes a Hand-Geometry recognition system based on geometrical features of hand. From anatomical point of view, human hand can be characterized by its length, width, thickness, geometrical composition, shapes of the palm, and shape and geometry of the fingers. This paper proposes thirty relevant features for a Hand-Geometry recognition system. This system presents verification results based on hand measurements of 20 individuals. The verification process has been tested on a size of $320{\times}240$ image, and result of the verification process have hit rate of 95% and FAR of 0.020.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.17-31
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• 2002

The new MPEG-4 video coding standard enables content-based functionalities. Image segmentation is an indispensable process for it. This paper addresses an effective segmentation of non-rigid objects. Non-rigid objects are deformable objects with fuzzy, blurred and indefinite boundaries. So it is difficult to segment deformable objects precisely. In order to solve this problem, we propose an effective segmentation of non-rigid objects using watershed algorithms in still pictures. And we propose an automatic segmentation through intra-frame and inter-frame segmentation process in video sequences. Automatic segmentation preforms boundary-based and region-based segmentation to extract precise object boundaries.