• Korean Chemical Engineering Research
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• v.45 no.6
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• pp.596-603
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• 2007

Rapid or on-line coal analysis is of great interest in coal industry as it would allow efficient plant operation. Multivariate analysis has been applied to near-infrared(NIR) spectra coal for investigating the relationship between coal properties(%) (moisture, ash, volatile matter, fixed carbon, carbon, hydrogen, nitrogen, oxygen, sulfur), heating value(kcal/kg) and corresponding near-infrared spectral data. The quantitative analysis was carried out by applying PLS(partial least squares regression) to determine a methodology able to establish a relationship between coal properties and NIR spectral data being applied mathematical pre-treatments for minimizing the physical features of the samples. As a results of the analysis, this technique is able to classify the species of coals and to predict the all coal properties except ash, nitrogen and sulfur. The efficient operation of coal fired power plant is expected owing to real time on-line coal analysis of moisture and heating value.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2412-2420
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• 2018

The thermal degradation of low density polyethylene (LDPE) will accelerate the production of carbonyl groups (C=O), which can act as the induced dipoles under high voltage. In this paper, we researched the dielectric properties and space charge behavior of LDPE after thermal aging, which can help us to understand the correlation between carbonyl groups (C=O) and electrical properties of LDPE. The spectra results show that LDPE exhibit obvious thermooxidative reactions when the aging time is 35 days and the productions mainly contain carboxylic acid, carboxylic eater and carboxylic anhydride, whose amount increase with the increasing of aging time. The dielectric properties show that the real permittivity of LDPE is inversely proportional to temperature before aging and subsequently become proportional to temperature after thermal aging. Furthermore, both the real and imaginary permittivity increase sharply with the increasing of aging time. The fitting results of imaginary permittivity show that DC conductivity become more sensitive about temperature after thermal aging. On this basis, the active energies of materials calculated from DC conductivity increase first and then decrease with the increasing of aging time. In addition, the space charge results show that the heterocharges accumulated near electrodes in LDPE change to the homocharges after thermal aging and the mean volume charge density increase with the increasing of aging time. It is considered that the overlaps caused by electrical potential area is the main reason for the increase of DC conductivity.

• Journal of Astronomy and Space Sciences
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• v.22 no.4
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• pp.431-440
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• 2005

Local K-index is an indicator representing local geomagnetic activity in every 3 hour. For estimation of the local K-index, a reasonable determination of solar quiet curve (undisturbed daily variation of geomagnetic field) is quiet essential. To derive the solar quiet curve, the FMI method, which is one of representative algorithms, uses horizontal components (H and D) of 3 days magnetometer data from the previous day to the next day for a specific day. However, this method is not applicable to real time forecast since it always requires the next day data. In this study, we have devised a new method to estimate local K-index in near real-time by modifying the FMI method. The new method selects a recent quiet day whose $K_p$ indices, reported by NOAA/SEC are all lower than 3, and replace the previous day and the next day data by the recent quiet day data. We estimated 2,672 local K indices from Gyeongzu magnetometer in 2003, and then compared the indices with those from the conventional FMI method. We also compared the K indices with those from Kakioka observatory. As a result, we found that (1) K indices from the new method are nearly consistent with those of the conventional FMI method with a very high correlation (R=0.96); (2) onr local K indices also have a relatively high correlation (R=0.81) with those from Kakioka station. Our results show that the new method can be used for near real-time estimation of local K indices from Gyeongzu magnetometer.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.911-920
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• 2004

Intensive studies have been made in the area of VOD server. Multimedia files in the VOD sever are characterized with the large volume of data, the requirements of synchronization and real-time playback of streams. The basic goal of the study is to find an efficient mechanism to allow maximum number of users under the limited resources such as Bu11er size and disk bandwidth. we propose a efficient user-grouping policy for multi-casting services with dynamic monitoring and management of VOD sever resources. Simulation results show that the rate of buffer usage and QOS change of proposed scheme are about 23% performance improved than that of traditional methods. This implies that our method can allow much more users for given resources.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.112-127
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• 2002

A useful pattern is a pattern that contributes much to learning. For a classification problem those patterns near the class boundary surfaces carry more information to the classifier. For a regression problem the ones near the estimated surface carry more information. In both cases, the usefulness is defined only for those patterns either without error or with negligible error. Using only the useful patterns gives several benefits. First, computational complexity in memory and time for learning is decreased. Second, overfitting is avoided even when the learner is over-sized. Third, learning results in more stable learners. In this paper, we propose a pattern 'utility index' that measures the utility of an individual pattern. The utility index is based on the bias and variance of a pattern trained by a network ensemble. In classification, the pattern with a low bias and a high variance gets a high score. In regression, on the other hand, the one with a low bias and a low variance gets a high score. Based on the distribution of the utility index, the original training set is divided into a high-score group and a low-score group. Only the high-score group is then used for training. The proposed method is tested on synthetic and real-world benchmark datasets. The proposed approach gives a better or at least similar performance.

• The Journal of Industrial Distribution & Business
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• v.9 no.10
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• pp.63-72
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• 2018

Purpose - This thesis is to develop a management plan and checklist by analyzing the prevention of accidents in advance by presenting the management plan for the major causes of railway accidents. Research design, data and methodology - In recent 5 years, we have analyzed the cases of railway accident, presented the management plan for the accident, and made a practical safety checklist focusing on the main measures according to the management plan. Results - The analysis of the cases of near-railway accidents suggests more concrete and practical safety management measures because the similar accidents are continuously occurring due to formal safety management. Conclusions - It is more valuable to apply to the adjacent construction of the railway line by creating a detailed checklist based on cases rather than the existing checklist. This study is written only as a human factor. For future real - time safety management, it is necessary to study more precisely cause analysis and safety equipment as a big data - based safety control system for more systematic safety management.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.9
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• pp.1117-1123
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• 2004

The characteristics of soot near the soot inception point for an ethene-air flame was carried out in a WSR (well-stirred reactor). The new sampling tool like the temperature controlled filter system was introduced to minimize the condensation during sampling. The new analysis tools applied include the real time size distribution analysis with the Nano-DMA, particle size by transmission electron microscopy, C/H analysis, g filter analysis, and thermogravimetric analysis using both non-oxidative and oxidative pyrolysis. The WSR can generate young soot particles that can be collected and examined to gain insight into inception. For the current conditions, soot does not form for ${\Phi}$=1.9, inception occurs at or before ${\Phi}$=2.0, and inception combined with soot surface growth and/or coagulation occurs for ${\Phi}$=2.1. The filter samples for ${\Phi}$=1.9 are composed of volatile compounds that evolve at relatively low temperatures when heated in the presence or absence of O$_2$. The samples collected from the WSR at ${\Phi}$=2.0 and ${\Phi}$=2.1 are precursor-like in morphology and size. They have higher C/H ratios and lower organic percentages than precursor particles, but they are clearly not fully carbonized soot. The WSR PAH distribution is similar to that in young soot from inverse flames.

• Fire Science and Engineering
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• v.24 no.3
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• pp.20-24
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• 2010

When the fire occurred in building, the fire-resistance-structure has to be constructed to prevent collapse of building and to have a time for evacuation of peoples. because of the features of the fireresistance test is similar with real scale, there is no way to confirm quality of fire-resistive-structure in building construction site. Therefore the purpose of this study, a study by spectroscopic analysis using near-infrared spectroscopy (NIR), is to suggest of useful and scientific testing-methods in building construction site by identification-analysis-study for fire resistive paint.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1298-1303
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• 2004

The characteristics of soot near the soot inception point for an ethene-air flame was carried out in a WSR (well-stirred reactor). The new sampling tool like the temperature controlled filter system was introduced to minimize the condensation during sampling. The new analysis tools applied include the real time size distribution analysis with the Nano-DMA, particle size by transmission electron microscopy, C/H analysis, g filter analysis, and thermogravimetric analysis using both non-oxidative and oxidative pyrolysis. The WSR can generate young soot particles that can be collected and examined to gain insight into inception. For the current conditions, soot does not form for ${\Phi}=1.9$, inception occurs at or before ${\Phi}=2.0$, and inception combined with soot surface growth and/or coagulation occurs for ${\Phi=2.1}$. The filter samples for ${\Phi}$=1.9 are composed of volatile compounds that evolve at relatively low temperatures when heated in the presence or absence of $O_2$. The samples collected from the WSR at ${\Phi}=2.0$ and ${\Phi}=2.1$ are precursor-like in morphology and size. They have higher C/H ratios and lower organic percentages than precursor particles, but they are clearly not fully carbonized soot. The WSR PAH distribution is similar to that in young soot from inverse flames.

• Journal of Semiconductor Engineering
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• v.2 no.2
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• pp.130-135
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• 2021

Recently, deep neural networks (DNNs) are actively used for action control so that an autonomous system, such as the robot, can perform human-like behaviors and operations. Unlike recognition tasks, the real-time operation is essential in action control, and it is too slow to use remote learning on a server communicating through a network. New learning techniques, such as reinforcement learning (RL), are needed to determine and select the correct robot behavior locally. In this paper, we propose an energy-efficient DNN processor with a LUT-based processing engine and near-zero skipper. A CNN-based facial emotion recognition and an RNN-based emotional dialogue generation model is integrated for natural HRI system and tested with the proposed processor. It supports 1b to 16b variable weight bit precision with and 57.6% and 28.5% lower energy consumption than conventional MAC arithmetic units for 1b and 16b weight precision. Also, the near-zero skipper reduces 36% of MAC operation and consumes 28% lower energy consumption for facial emotion recognition tasks. Implemented in 65nm CMOS process, the proposed processor occupies 1784×1784 um2 areas and dissipates 0.28 mW and 34.4 mW at 1fps and 30fps facial emotion recognition tasks.