• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.138-145
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• 2010

In this paper, we consider the information processing system, which organizes the collected data to meaningful information when the number of data collected from multiple sources reaches to a predetermined number, and performs any action by processing the collected data, or transmits to other devices or systems. We derive an analytical model to calculate the time until it takes to process information after starting to collect data. Therefore, in order to complete the processing data within certain time constraints, we develop some design criteria to control various parameters of the information processing system. Also, we analyze the discrete time model for packet switching networks considering data with no particular arrival nor drop pattern. We analyze the relationship between the number of required packets and average information processing time through numerical examples. By this, we show that the proposed model is able to design the system to be suitable for user's requirements being complementary the quality of information and the information processing time in the system with time constraints.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1939-1951
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• 1994

This study introduces a new tool breakage detecting technology comprised of an unsupervised neural network combined with adaptive time series autoregressive(AR) model where parameters are estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(Recursive Least Square). Experiment indicates that AR parameters are good features for tool breakage, therefore it can be detected by tracking the evolution of the AR parameters during milling process. an ART 2(Adaptive Resonance Theory 2) neural network is used for clustering of tool states using these parameters and the network is capable of self organizing without supervised learning. This system operates successfully under the wide range of cutting conditions without a priori knowledge of the process, with fast monitoring time.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1048-1054
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• 2003

In laser surface hardening processes, the geometrical parameters such as the depth and the width of a hardened layer can be utilized to assess the hardened layer quality. However, accurate monitoring of the geometrical parameters for on-line process control as well as for on-line quality evaluation is very difficult because the hardened layer is formed beneath a material surface and is not visible. Therefore, temperature monitoring of a point of specimen surface has most frequently been used as a process monitoring method. But, a hardened layer depends on the temperature distribution and the thermal history of a specimen during laser surface hardening processing. So, this paper describes the estimation results of the geometric parameters using multi-point surface temperature monitoring. A series of hardening experiments were performed to find the relationships between the geometric parameters and the measured temperature. Estimation results using a neural network show the enhanced effectiveness of multi-point surface temperature monitoring compared to one-point monitoring.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.1
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• pp.95-101
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• 1998

In this paper, the historical coordinates data of origin SUWON are reviewed and determination procedures are explained with the three dimensional geocentric coordinates of ITRF94 that is determined using VLBI observations. Also three translation parameters are calculated on the origin point. The national transformation parameters between the Korean geodetic system and Korean Terrestrial Reference Frame 1994(KTRF94) system, are determined using least square methods with weigted parameter constraints. The results of transformation show that one set of parameters are applicable to fixing of a position for GPS relative positioning processing and to adjusting of a network for three dimensional geocentric coordinates(KTRF94) computing.

• Fibers and Polymers
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• v.3 no.2
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• pp.80-84
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• 2002

Tension control is an important factor in producing high quality knitted products and in maintaining good processing condition. Yarn tension during knitting is subject to be affected from many elements of the machine and process parameters. Several factors including yam feeding speed, feeding angle, and needle gauge that are considered to influence on the tension variation were investigated. Yam feeding speed did not show high contribution to the tension variation but feeding angle of yam did show high correlation with the tension. No or negative correlation of the tension with needle gauge was found from the results. In order to keep well-determined process condition in the knitting manufacturing, it is strongly suggested that all knitting elements and parameters should be in the integrated control circumstance.

• Transactions of Materials Processing
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• v.9 no.6
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• pp.615-623
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• 2000

The industrial application of hydroforming has a great potential in saying cost and achieving dimensional accuracy in automotive industry presently. The aim of the following article is to investigate the effect of process parameters on hydroformed part. Firstly, we have to investigate the change of mechanical properties for sheet and pipe material according to various radius/thickness ratio(r/t). The change of mechanical properties affects the yield stress more than the total elongation. Increase of yield stress for pipe has a bad influence on formability of hydroforming. Among the roll-forming process, the sizing process didn't change mechanical properties. The process parameters such as the initial pressure, mandrel shape and friction have seriously influenced on formability of hydroforming. Therefore we need to check formability of given material through the FE analysis in the beginning stage of process design and the predicted hydroforming process parameters ate generally a good starting point for the prototype tryout stage. The results of pretending, hydroforming analysis using FE model are good agreement with experimental results.

• Transactions of Materials Processing
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• v.9 no.1
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• pp.17-26
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• 2000

A series of parametric study was performed for the investigation on the influence of analysis parameters to the solution behavior in the elastic-plastic-static analysis of several sheet metal forming processes, such as deflection by a point force under plane strain and axisymmetric conditions, plane strain bending by a punch, axisymmetric stretching by a punch, axisymmetric bulging by hydraulic pressure, and axisymmetric deep drawing by a punch. The parameters considered are kind of element, number of elements, integration scheme for elemental equation and friction coefficient. Results obtained for different selections of those parameters were compared with each other, experimental measurements and analytical solution.

• Transactions of Materials Processing
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• v.3 no.3
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• pp.271-281
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• 1994

Titanium-6242 $({\alpha}+{\beta})$ alloy has been used for aircraft engine components such as disks and blades, because it has an excellent strength/weight ratio at high temperatures. When this material is forged to manufacture disks, process parameters should be carefully designed to control strain and temperature distributions within the process windows by which desirable mechanical properties can be produced. In the present investigation, it was intended to design the process parameters for a conventional hot forging of this material by using a rigid-thermoviscoplastic finite element analysis technique. It was assumed that the process was performed by a screw press which is capable of maintaining a constant ram speed during loading. From the analysis results, it was found out that the initial temperature of the workpiece and the die shape were important parameters to control the forging process. In result, these parameters were properly designed for hot forging of a disk with specific dimensions.

• ETRI Journal
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• v.45 no.2
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• pp.226-239
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• 2023

Challenges in cognitive radio and tactical communications include recognizing anonymously received signals and estimating parameters in a blind or semi-blind manner. In this paper, we examine this issue for orthogonal frequency division multiplexing (OFDM) signaling. There are several parameters in OFDM signaling, and the blind receiver must extract and consider the synchronization issue. We assume that the blind receiver is aware of modulation type, OFDM, and not aware of chip duration and the length of cyclic prefix. First, we present new criteria based on kurtosis to estimate these parameters and compare their performance at different levels of additive white Gaussian noise with methods based on correlation, kurtosis, maximum likelihood, and matched filter. Then, we perform synchronization and estimate the start time based on these criteria and several new criteria in two steps: fine and coarse synchronization. Finally, in a more practical setup, we present the idea of jointly estimating the mentioned parameters and the signal start time as coarse synchronization. We compare different criteria and show that one of the proposed criteria has the highest efficiency.

• Korean Journal of Cognitive Science
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• v.33 no.3
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• pp.155-168
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• 2022

In this paper, we introduce the SNUDM-G, a diffusion model analysis tool with improved computational speed. Although the diffusion model has been applied to explain various cognitive tasks, its use was limited due to computational difficulties. In particular, SNUDM(Koh et al., 2020), one of the diffusion model analysis tools, has a disadvantage in terms of processing speed because it sequentially generates 20,000 data when approximating the diffusion process. To overcome this limitation, we propose to use graphic processing units(GPU) in the process of approximating the diffusion process with a random walk process. Since 20,000 data can be generated in parallel using the graphic processing units, the estimation speed can be increased compared to generating data through sequential processing. As a result of analyzing the data of Experiment 1 by Ratcliff et al. (2004) and recovering the parameters with SNUDM-G using GPU and SNUDM using CPU, SNUDM-G estimated slightly higher values for certain parameters than SNUDM. However, in term of computational speed, SNUDM-G estimated the parameters much faster than SNUDM. This result shows that a more efficient diffusion model analysis for various cognitive tasks is possible using this tool and further suggests that the processing speed of various cognitive models can be improved by using graphic processing units in the future.