• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.1
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• pp.50-58
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• 2017

This paper proposes a real-time robotic vision control scheme using the weighting matrix to efficiently process the vision data obtained during robotic movement to a target. This scheme is based on the vision system model that can actively control the camera parameter and robotic position change over previous studies. The vision control algorithm involves parameter estimation, joint angle estimation, and weighting matrix models. To demonstrate the effectiveness of the proposed control scheme, this study is divided into two parts: not applying the weighting matrix and applying the weighting matrix to the vision data obtained while the camera is moving towards the target. Finally, the position accuracy of the two cases is compared by performing the slender bar placement task experimentally.

• Journal of Communications and Networks
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• v.18 no.6
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• pp.892-901
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• 2016

In the multi-user multiple-input multiple-output (MIMO) system, orthogonal random beamforming (ORBF) scheme is proposed to serve multiple users simultaneously in order to achieve the multi-user diversity gain. The opportunistic space-division multiple access system (OSDMA-S) scheme performs multiple weighting matrices during the training phase and chooses the best weighting matrix to be used to broadcast data during the transmitting phase. The OSDMA-S scheme works better than the original ORBF by decreasing the inter-user interference during the transmitting phase. To save more time in the training phase, a partly random multiple weighting matrices selection scheme is proposed in this paper. In our proposed scheme, the Base Station does not need to use several unitary matrices to broadcast pilot symbol. Actually, only one broadcasting operation is needed. Each subscriber generates several virtual equivalent channels with a set of pre-saved unitary matrices and the channel status information gained from the broadcasting operation. The signal-to-interference and noise ratio (SINR) of each beam in each virtual equivalent channel is calculated and fed back to the base station for the weighting matrix selection and multi-user scheduling. According to the theoretical analysis, the proposed scheme relatively expands the transmitting phase and reduces the interactive complexity between the Base Station and subscribers. The asymptotic analysis and the simulation results show that the proposed scheme improves the throughput performance of the multi-user MIMO system.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.43-46
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• 1990

A general scheme for a discrete adaptive observer having exponetial weighting properties is presented for a single-input single-output linear system. In this scheme, all the past measurement data are weighted esponetially both with the weighting factor and the stable matrix F. This observer is then implemented in the design of an indirect adaptive pole placement contoller. To increase nemerical stability in getting the controller parameter, a recusive algorithm is introduced. It is shown that the overall control scheme is globally stable with the persistent excition

• Journal of the Korea Safety Management & Science
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• v.12 no.3
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• pp.257-262
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• 2010

The study investigates the various Acceptance Control Charts (ACCs) based on the factors that include process independence, data weighting scheme, subgrouping, and use of control charts. USL - LSL > $6{\sigma}$ that used in the good condition processes in the ACCs are designed by considering user's perspective, producer's perspective and both perspectives. ACCs developed from the research is efficiently applied by using the simple control limit unified with APL (Acceptable Process Level), RLP (Rejectable Process Level), Type I Error $\alpha$, and Type II Error $\beta$. Sampling interval of subgroup examines i.i.d. (Identically and Independent Distributed) or auto-correlated processes. Three types of weight schemes according to the reliability of data include Shewhart, Moving Average(MA) and Exponentially Weighted Moving Average (EWMA) which are considered when designing ACCs. Two types of control charts by the purpose of improvement are also presented. Overall, $\alpha$, $\beta$ and APL for nonconforming proportion and RPL of claim proportion can be designed by practioners who emphasize productivity and claim defense cost.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.5
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• pp.161-172
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• 2018

This paper proposed the robot vision control method to track a moving rigid body target using the vision system model that can actively control camera parameters even if the relative position between the camera and the robot and the focal length and posture of the camera change. The proposed robotic vision control scheme uses a batch method that uses all the vision data acquired from each moving point of the robot. To process all acquired data, this robot vision control scheme is divided into two cases. One is to give an equal weight for all acquired data, the other is to give weighting for the recent data acquired near the target. Finally, using the two proposed robot vision control schemes, experiments were performed to estimate the positions of a moving rigid body target whose spatial positions are unknown but only the vision data values are known. The efficiency of each control scheme is evaluated by comparing the accuracy through the experimental results of each control scheme.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.101-110
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• 2003

This paper introduces an identification method for nonlinear models in the form of rule-based Fuzzy-Neural Networks (FNN). In this study, the development of the rule-based fuzzy neural networks focuses on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The FNN modeling and identification environment realizes parameter identification through synergistic usage of clustering techniques, genetic optimization and a complex search method. We use a HCM (Hard C-Means) clustering algorithm to determine initial apexes of the membership functions of the information granules used in this fuzzy model. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are then adjusted using the identification algorithm of a GA hybrid scheme. The proposed GA hybrid scheme effectively combines the GA with the improved com-plex method to guarantee both global optimization and local convergence. An aggregate objective function (performance index) with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. According to the selection and adjustment of the weighting factor of this objective function, we reveal how to design a model having sound approximation and generalization abilities. The proposed model is experimented with using several time series data (gas furnace, sewage treatment process, and NOx emission process data from gas turbine power plants).

• International Journal of Contents
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• v.13 no.2
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• pp.66-74
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• 2017

Patent classification is becoming more critical as patent filings have been increasing over the years. Despite comprehensive studies in the area, there remain several issues in classifying patents on IPC hierarchical levels. Not only structural complexity but also shortage of patents in the lower level of the hierarchy causes the decline in classification performance. Therefore, we propose a new method of classification based on different criteria that are categories defined by the domain's experts mentioned in trend analysis reports, i.e. Patent Landscape Report (PLR). Several experiments were conducted with the purpose of identifying type of features and weighting methods that lead to the best classification performance using Support Vector Machine (SVM). Two types of features (noun and noun phrases) and five different weighting schemes (TF-idf, TF-rf, TF-icf, TF-icf-based, and TF-idcef-based) were experimented on.

• Geophysics and Geophysical Exploration
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• v.8 no.2
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• pp.129-136
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• 2005

The damped least-squares inversion has become a most popular method in finding the solution in geophysical problems. Generally, the least-squares inversion is to minimize the object function which consists of data misfits and model constraints. Although both the data misfit and the model constraint take an important part in the least-squares inversion, most of the studies are concentrated on what kind of model constraint is imposed and how to select an optimum regularization parameter. Despite that each datum is recommended to be weighted according to its uncertainty or error in the data acquisition, the uncertainty is usually not available. Thus, the data weighting matrix is inevitably regarded as the identity matrix in the inversion. We present a new inversion scheme, in which the data weighting matrix is automatically obtained from the analysis of the data resolution matrix and its spread function. This approach, named 'extended active constraint balancing (EACB)', assigns a great weighting on the datum having a high resolution and vice versa. We demonstrate that by applying EACB to a two-dimensional resistivity tomography problem, the EACB approach helps to enhance both the resolution and the stability of the inversion process.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.7
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• pp.677-684
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• 2003

This paper addresses the subblock phase weighting(SPW) method to reduce the PAPR in OFDM system. This method divides the input block of OFDM signal into many subblocks and lower the peak power by weighting the phase of each subblocks properly. SPW method can be realized by only one IFFT. PAPR reduction performance is novelly examined when the adjacent, interleaved and random subblock partitioning schemes are used in the SPW system. The random subblock partition scheme has the most effective. More subblocks can effectively reduce the PAPR, but there is a problem that the processing time of iteration is increased. We propose a new weighting factor combination of the complementary sequence characteristic with threshold technique. OFDM data can be recovered by the inserted side information of weighting factor in the feed forward type. Also, BER performance of this SPW system is analyzed when error happens in the side information.

• Survey Research
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• v.12 no.2
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• pp.145-157
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• 2011

There are limitations as to how internet surveys can be used. Applying various weighting procedures has not always resulted in error reduction. A good reference survey would increase the effects of the weighting method, but it is very difficult to get a reference survey for non-demographic weighting variables, which restricts the use of internet surveys. We hypothesized that time use variables could be employed as weighting variables. The time use survey is conducted regularly by KOSTAT and includes various time-related variables. We tested our hypothesis using the 2009 survey results, which had been gathered by KOSTAT in 2009. When we applied weighting variables which were based on the 2004 time use survey results to the online version of the 2009 KOSTAT social survey, the gap between the online and off-line versions was slightly reduced. This result shows that we could use time use survey results to develop a better weighting scheme.