• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.1
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• pp.30-39
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• 2003

In SRM driving, the current rate is directly related to the rate of switching device and in cost reduction, the Parallel switching operation is the alternatives because it has the smaller current rate through current division. There ire many investigations for the parallel switching operations to equaling the current division. However it remains many problems for practical usage. The reason Is that the switching characteristics are mainly relied on the different saturation voltage of each device etc. and these factors are not altered by a circuit designer. In order to compensate this problem, a proper resistance is experimently inserted to the switching device. But this method can not be the optimal solution. Therefore this paper propose a new parallel operation of SRM which uses a parallel phase winding to remove the traditional effect of switching device such as saturation voltage according to the division of current. Also the reliable and stable driving is improved through experiments and the detailed principles.

• Journal of the Korean Geotechnical Society
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• v.16 no.1
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• pp.227-234
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• 2000

Soilcrete has been a traditional material for pavement and soft ground improvement techniques. However, since the durability is not excellent and the quality is not consistent, it has not been used for various purposes up to date. However, with the increase of naturally oriented needs for light traffic roads such as pedestrian roads of garden, golf courses and sidewalks, the cases of the high strength soilcrete paving have been increased lately. This study aims at making a reference table of mix design in accordance with the required design specifications fur the high strength soilcrete admixtured with the pozzolanic cement by using a statistical experimental method. The treated soil is the clay which is widely found in Korea. As the results of this study, we could derive an effective reference mix design table for the clay treated with the pozzolanic cement stabilizer in accordance with the compressive strength of $50~150kg/cm^2$ soilcrete.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.509-516
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• 2004

The measurement of abnormal change of temperature(temperature anomaly) will help determine the safety of various engineering constructions, as the measurement in body often used to diagnose one's health. Temperature anomaly can be occurred in leakage or seepage of water flow in rocks, and in ground water table etc. Grouting materials injected in fractured rocks generate heat during hardening process. The degree of temperature change is associated directly with heat flow characteristics, that is, thermal conductivity, specific heat capacity. density of the surrounding rocks and can afford to assess the grouting efficiency. However, in practice, the use of traditional temperature measuring technique composed of only one single thermal sensor has been fundamentally limited to acquire thermal data sufficient to use for that, partly due to the time-consuming measuring work, partly due to the non-consecutive quality of data. Thus, in this paper, a new concept of temperature measuring technique, what we call, thermal line sensor technique is introduced. In this, the sensors with an accuracy of $0.02^{\circ}$ are inserted at regular intervals in one line cable and addressed by a control device, which enables to fundamentally enhance the capability of data acquisition in time and space. This new technology has been demonstrated on diverse field model experiments. The results were simply meant to be illustrative of a potential to be used for various kinds of temperature measurements encountered in grouting and leakage problems.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.611-618
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• 2015

By Wikipedia, big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Data mining is the computational process of discovering patterns in huge data sets involving methods at the intersection of association rule, decision tree, clustering, artificial intelligence, machine learning. Association rule is a well researched method for discovering interesting relationships between itemsets in huge databases and has been applied in various fields. There are positive, negative, and inverse association rules according to the direction of association. If you want to set the evaluation criteria of association rule, it may be desirable to consider three types of association rules at the same time. To this end, we proposed a balanced comparative confidence considering sensitivity, specificity, false positive, and false negative, checked the conditions for association threshold by Piatetsky-Shapiro, and compared it with comparative confidence and inversely comparative confidence through a few experiments.

• Journal of ILASS-Korea
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• v.11 no.4
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• pp.251-265
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• 2006

To prevent the ozonosphere from being destroyed by Halon, it is an urgent task to find out Halon replacement. As one of the replacements water mist have showed broad applications by its advantages: little pollution to environment (not destroying the ozone layer or bring green house effect), extinguishing fire quickly, consuming a small quantity of water and having little damage to the protected objects. The methods of generating water mist strongly influence fire suppression effectiveness, which determine the cone angle, drop size distribution, flux uniformity, and momentum of the generating spray. The traditional water mist nozzle included pressure jet nozzles, impingement nozzles and twin-fluid nozzles. All of them have more or less disadvantages for fire suppression. Therefore, many research institutes and corporations are taking up with innovations in mist generation. This article provided some recent studies in State Key Laboratory of Fire Science (SKLFS) of University of Science and Technology of China. SKLFS have investigated new methods of generating water mist (i.e. effervescent atomization and ultrasonic atomization). and self developed a series of nozzles and developed advanced DPIVS (Digital Particle Image Velocimetry and Sizing) technique. Characteristics of water mist (the distribution of droplet sizes, flux density, spray dynamics and cone angle) produced by these nozzles were measured under different conditions (work pressure, nozzle geometry, etc.) using LDV/APV and DPTVS systems. A series of experiments were performed to study the fire suppression effectiveness in different fire scenario (different kindsof the fuel, fire size and ventilation conditions). The fire extinguishing mechanisms of water mist was also discussed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.72-78
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• 2003

A new self-organizing neuro-fuzzy network based rate control algorithm for MPEG-4 video encoder is proposed in this paper. Contrary to the traditional methods that construct the rate-distorion (RD) model based on experimental equations, the proposed method effectively exploits the non-stationary property of the video date with neuro-fuzzy network that self-organizes the RD model online and adaptively updates the structure. The method needs not require off-line pre-training; hence it is geared toward real-time coding. The comparative results through the experiments suggest that our proposed rate control scheme encodes the video sequences with less frame skip, providing good temporal quality and higher PSNR, compared to VM18.0.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2480-2496
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• 2020

Considering that high-dose X-ray radiation during CT scans may bring potential risks to patients, in the medical imaging industry there has been increasing emphasis on low-dose CT. Due to complex statistical characteristics of noise found in low-dose CT images, many traditional methods are difficult to preserve structural details effectively while suppressing noise and artifacts. Inspired by the deep learning techniques, we propose a densely connected residual network (DCRN) for low-dose CT image noise cancelation, which combines the ideas of dense connection with residual learning. On one hand, dense connection maximizes information flow between layers in the network, which is beneficial to maintain structural details when denoising images. On the other hand, residual learning paired with batch normalization would allow for decreased training speed and better noise reduction performance in images. The experiments are performed on the 100 CT images selected from a public medical dataset-TCIA(The Cancer Imaging Archive). Compared with the other three competitive denoising algorithms, both subjective visual effect and objective evaluation indexes which include PSNR, RMSE, MAE and SSIM show that the proposed network can improve LDCT images quality more effectively while maintaining a low computational cost. In the objective evaluation indexes, the highest PSNR 33.67, RMSE 5.659, MAE 1.965 and SSIM 0.9434 are achieved by the proposed method. Especially for RMSE, compare with the best performing algorithm in the comparison algorithms, the proposed network increases it by 7 percentage points.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.05a
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• pp.97-105
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• 1999

An important task for any software project manager is to be able to predict and control project size. Unfortunately, there is comparatively little work that deals with the problem of building estimation methods for software size in fourth-generation languages systems. In this paper, we propose a new estimation method for estimating for software size based on minimum relative error(MRE) criterion. The characteristic of the proposed method is insensitive to the extreme values of the observed measures which can be obtained early in the development life cycle. In order to verify the performance of the proposed estimation method for software size in terms of both quality of fit and predictive quality, the experiments has been conducted for the dataset I and II, respectively. For the data set I and II, our proposed estimation method was shown to be superior to the traditional method LS and RLS in terms of both the quality of fit and predictive quality when applied to data obtained from actual software development projects.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.3
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• pp.47-56
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• 2011

To apply Genetic algorithm toward document clustering, appropriate individual structure is required. Document clustering with the genetic algorithms (DCGA) uses the centroid vector type individual structure. New document clustering with the genetic algorithm (NDAGA) uses document allocated individual structure. In this paper, to find more suitable object structure and process for the document clustering, calculation, amount of calculation, run-time, and performance difference between the two methods were analyzed. In this paper, we have performed various experiments using both DCGA and NDCGA. Result of the experiment shows that compared to DCGA, NDCGA provided 15% faster execution time, about 5~10% better performance. This proves that the document allocated structure is more fitted than the centroid vector type structure when it comes to document clustering. In addition, NDCGA showed 15~25% better performance than the traditional clustering algorithms (K-means, Group Average).

• Korean Journal of Computational Design and Engineering
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• v.21 no.2
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• pp.196-203
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• 2016

In this paper, we propose a virtual surgical planning system specialized to mandible reconstruction surgery. Mandible reconstruction surgery is one of the most difficult surgeries, even for experienced surgeons. Compared to the traditional surgical procedures, virtual surgical planning can reduce the operation time in operating room while expecting better surgical outcome with optimized planning. However, with existing software systems, it requires much time and manual operations in virtual surgical planning. To reduce preparation time and improve accuracy of virtual surgical planning, we have developed optimized functions for virtual surgical simulation of mandible reconstruction with user-friendly interface. We found that the proposed system shortened the preparation time by half compared to the existing system from the experiments. The proposed system supports surgeons to make accurate plan faster and easier. The virtually planned results are used to make surgical cutting guide by 3D printing, and this will enhance surgical performance in operating room.