• Journal of Advanced Navigation Technology
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• v.10 no.2
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• pp.113-120
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• 2006

In this paper, a vision-based robust controller for tracking the desired trajectory a robot manipulator is proposed. The trajectory is generated to move the feature point into the desired position which the robot follows to reach to the desired position. To compensate the parametric uncertainties of the robot manipulator which contain in the control input, the robust controller is proposed. In addition, if there are uncertainties in the Jacobian, to compensate it, a vision-based robust controller which has control input is proposed as well in this paper. The stability of the closed-loop system is shown by Lyapunov method. The performance of the proposed method is demonstrated by simulations and experiments on a two degree of freedom 5-link robot manipulators.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.217-231
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• 2015

A novel fuzzy learning framework that employs fuzzy inference to solve the problem of Multiple Instance Learning (MIL) is presented. The framework introduces a new class of fuzzy inference systems called Multiple Instance Mamdani Fuzzy Inference Systems (MI-Mamdani). In multiple instance problems, the training data is ambiguously labeled. Instances are grouped into bags, labels of bags are known but not those of individual instances. MIL deals with learning a classifier at the bag level. Over the years, many solutions to this problem have been proposed. However, no MIL formulation employing fuzzy inference exists in the literature. Fuzzy logic is powerful at modeling knowledge uncertainty and measurements imprecision. It is one of the best frameworks to model vagueness. However, in addition to uncertainty and imprecision, there is a third vagueness concept that fuzzy logic does not address quiet well, yet. This vagueness concept is due to the ambiguity that arises when the data have multiple forms of expression, this is the case for multiple instance problems. In this paper, we introduce multiple instance fuzzy logic that enables fuzzy reasoning with bags of instances. Accordingly, a MI-Mamdani that extends the standard Mamdani inference system to compute with multiple instances is introduced. The proposed framework is tested and validated using a synthetic dataset suitable for MIL problems. Additionally, we apply the proposed multiple instance inference to fuse the output of multiple discrimination algorithms for the purpose of landmine detection using Ground Penetrating Radar.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.53-63
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• 2017

The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.

• Analytical Science and Technology
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• v.32 no.6
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• pp.225-232
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• 2019

Traceability establishment in chemical measurements is a like a linkage established through an unbroken chain from the measured results to the international system (SI) of units. The primary process for traceability establishment is the purity assignment of a target material to be measured. In this study, we studied the purity assignment of 17α-hydroxyprogesterone (17-OHP). The presence of 17-OHP is indicative of congenital adrenal hyperplasia (CAH) and it builds up due to the deficiency of 21-hydroxylase and 11β-hydroxylase enzyme in the human blood. The purity assignment of 17-OHP was performed by the mass balance method, in which the impurities are categorized into four classes: total related structural impurities, water, residual organic solvents, and nonvolatiles/inorganics. The total related structural impurities were characterized by HPLC-UV; water content was determined by Karl-Fisher coulometer; and the total residual solvents and nonvolatiles/inorganics were determined by TGA. The purity of 17-OHP from a commercial manufacturer was calculated as 993.30 mg/g, and the expanded uncertainty was 0.58 mg/g. The proposed method was validated by uncertainty evaluation and comparing with the actual value of purity.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.6
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• pp.463-474
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• 1997

Metallic elements in dustfall have been known as notable air pollutants directly or indirectly influencing human health and wealth. The first aim of this study was to obtain precise spatial distribution patterns of 5 elements (Pb, Zn, K, Cr, and Al) in dustfall around Suwon area. To predict isometric lines of metal fluxes deposited on unsupervised random sites, the study has applied both spatial statistics as a receptor model and a GIS (geographic information system). Total of 31 sampling sites were selected in the study area (roughly 3 by 3 km grid basis) and dustfall samples were then collected monthly basis by the British deposit gauges from Dec., 1995 to Nov., 1996. The metallic elements in the dustfall were then analyzed by an atomic absorption spectrometer (AAS). On the other hand, a base map overlapped by 7 layers was constructed by using the AutoCAD R13 and ARC/INFO 3.4D. Four different spatial interpolation and expolation techniques such as IDW (inverse distance weighted averaging), TIN (triangulated irregular network), polynomial regression, and kriging technique were examined to compare spatial distribution patterns. Each pattern obtained by each technique was substantally different as varing pollutant types, land of use types, and topological conditions, etc. Thus, our study focused intensively on uncertainty analysis based on a concept of the jackknife and the sum of error distance. It was found that a kriging technique was the best applicalbe in this study area.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.3
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• pp.171-177
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• 2011

The decision making process is based on accurate and timely available information. To obtain precise information from the internet is becoming more difficult due to the continuous increase in vagueness and uncertainty from online information resources. This also poses a problem for blind people who desire the full use from online resources available to other users for decision making in their daily life. Ontology is considered as one of the emerging technology of knowledge representation and information sharing today. Fuzzy logic is a very popular technique of artificial intelligence which deals with imprecision and uncertainty. The classical ontology can deal ideally with crisp data but cannot give sufficient support to handle the imprecise data or information. In this paper, we incorporate fuzzy logic with heavyweight ontology to solve the imprecise information extraction problem from heterogeneous misty sources. Fuzzy ontology consists of fuzzy rules, fuzzy classes and their properties with axioms. We use Fuzzy OWL plug-in of Protege to model the fuzzy ontology. A prototype is developed which is based on OWL-2 (Web Ontology Language-2), PAL (Protege Axiom Language), and fuzzy logic in order to examine the effectiveness of the proposed system.

• Journal of Mechanical Science and Technology
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• v.17 no.4
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• pp.484-491
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• 2003

For most of linear time-varying (LTV) systems, it is difficult to design time-varying controllers in analytic way. Accordingly, by approximating LTV systems as uncertain linear time-invariant, control design approaches such as robust control have been applied to the resulting uncertain LTI systems. In particular, a robust control method such as quantitative feedback theory (QFT) has an advantage of guaranteeing the frozen-time stability and the performance specification against plant parameter uncertainties. However, if these methods are applied to the approximated linear. time-invariant (LTI) plants with large uncertainty, the resulting control law becomes complicated and also may not become ineffective with faster dynamic behavior. In this paper, as a method to enhance the fast dynamic performance of LTV systems with bounded time-varying parameters, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.645-648
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• 2005

Microscopy has enabled the development of many advanced technologies, and higher level microscopic techniques are required according to the increase of research in nano-technology and bio-technology fields. Therefore, in many applications, we need to measure the dimension of micro-scale parts accurately, not just to observe their shapes. To establish the meter-traceability in microscopy, gratings have been widely used as a magnification standard. KRISS provides the certification service of magnification standards using an optical diffractometer and a metrological AFM (MAFM). They are based on different measurement principles, and so can give complementary information for each other. In this paper, we describe the configuration of each system and measurement procedures to certificate grating pitch values of magnification standards. Several measurement results are presented, and the discussion about them are also given. Using the optical diffractometer, we can calibrate a grating specimen with uncertainty of less than 50 pm. The MAFM can measure a grating specimen of down to 100 nm pitch value, and the calibrated values usually have uncertainty less than 500 pm.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.26
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• pp.143-172
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• 2005

The biggest exchange of international environment of shipping logistics in 21 century should appear ultra-mega container ships on the shipping market. The competitive trend of large size container ship was based on economics of scale among the international shipping business. In the environment, shipping firms consider the integration of freight forwarder and shipper in the international logistics process. The aims of this research analyse a relation between the environment uncertainty and logistics information system(LIS) and the integration and resolve the integration and its impact on logistics performance. The research methodology of this research analyse structural equation modeling on the relation of variables. The results of research are as follows. First, Environmental uncertainty significantly influences the internal integration and the external integration. Second, LIS has an influence on the logistics integration by providing the foundation for LIS utilization in international logistics process. Third, the internal integration significantly influences a logistics performance, which implies that firms should promote interaction and collaboration through internal process integration to achieve logistics performance as the logistical cost and service. But the external integration is not significantly a logistics performance.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.22-43
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• 2017

It is urgently-needed to construct a green supply chain (GSC) from collection of used products through recycling of them to sales of products using the recycled parts. Besides, it is necessary to consider the uncertainty in product demand as a risk in a GSC. This study proposes the optimal operations for a GSC with a retailer and a manufacturer. A retailer pays an incentive for collection of used products from customers and sells a single type of products in a market. A manufacturer produces the products ordered by the retailer, using recyclable parts with acceptable quality and compensates the collection cost of used products as to the recycled parts. This paper discusses the following risk attitudes: risk-neutral attitude, risk-averse attitude, and risk-prone attitude. Using mean-variance analysis, the optimal decisions for product order quantity, collection incentive, and lower limit of quality level, in the decentralized GSC (DGSC) and the integrated GSC (IGSC) are made. DGSC optimizes the utility function of each member. IGSC does that of the whole system. The analysis numerically investigates how (i) risk attitude and (ii) quality of recyclable parts affect the optimal operations. Supply chain coordination between GSC members to shift IGSC from DGSC is discussed.