• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.236-244
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• 2005

In this study, we introduce a new topology of Fuzzy Polynomial Neural Networks(FPNN) that is based on fuzzy relation and evolutionally optimized Multi-Layer Perceptron, discuss a comprehensive design methodology and carry out a series of numeric experiments. The construction of the evolutionally optimized FPNN(EFPNN) exploits fundamental technologies of Computational Intelligence. The architecture of the resulting EFPNN results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks(PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the EFPNN. The consequence part of the EFPNN is designed using PNN. As the consequence part of the EFPNN, the development of the genetically optimized PNN(gPNN) dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the EFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed EFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.4
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• pp.43-54
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• 2007

This paper presents design and verification of a face detection hardware for real time application. Face detection algorithm detects rough face position based on already acquired feature parameter data. The hardware is composed of five main modules: Integral Image Calculator, Feature Coordinate Calculator, Feature Difference Calculator, Cascade Calculator, and Window Detection. It also includes on-chip Integral Image memory and Feature Parameter memory. The face detection hardware was verified by using S3C2440A CPU of Samsung Electronics, Virtex4LX100 FPGA of Xilinx, and a CCD Camera module. Our design uses 3,251 LUTs of Xilinx FPGA and takes about 1.96${\sim}$0.13 sec for face detection depending on sliding-window step size, when synthesized for Virtex4LX100 FPGA. When synthesized on Magnachip 0.25um ASIC library, it uses about 410,000 gates (Combinational area about 345,000 gates, Noncombinational area about 65,000 gates) and takes less than 0.5 sec for face realtime detection. This size and performance shows that it is adequate to use for embedded system applications. It has been fabricated as a real chip as a part of XF1201 chip and proven to work.

• Journal of Navigation and Port Research
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• v.34 no.6
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• pp.479-485
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• 2010

To handle container effectively is one of the most important factors in a port because working time is linked soon into cost. Since the middle of 1990s, RMGC(Rail-Mounted Gantry Crane) and RTGC(Rubber-Tired Gantry Crane) have been developed and widely used to operate containers in the yard. The RTGC is more difficult than RMGC in the automatic control system design. Although, the RTGC is largely advantaged to free driving environment, it has some considerable disadvantages in the system operating. In general, the problems are due to tire slip and lack of tire pressure etc. Therefore, a desirable research result has not been shown in this time. So, in this paper, we propose a new approach to design tracking control system for the RTGC in which the mathematical modeling is included. From the simulation results, the control performance of the designed control systems is evaluated.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.1_2
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• pp.79-91
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• 2006

The intelligent disk can improve the overall performance of the I/O subsystem by processing the I/O operations in the disk side. At present time, however, realizing the intelligent disk seems to be impossible because of the limitation of the I/O subsystem and the lack of the backward compatibility with the traditional I/O interface scheme. In this paper, we proposed new model for the intelligent disk that dynamically optimizes the I/O subsystem using the information that is only related to the physical sector. In this way, the proposed model does not break the compatibility with the traditional I/O interface scheme. For these works, the boosting algorithm that upgrades a weak learner by repeating teaming is used. If the last learner classifies a recent I/O workload as the multimedia workload, the disk reads more sectors. Also, by embedding this functionality as a firmware or a embedded OS within the disk, the overall I/O subsystem can be operated more efficiently without the additional workload.

• Applied Microscopy
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• v.34 no.1
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• pp.13-21
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• 2004

The high voltage electron microscope (HVEM) newly installed in KBSI is an advanced transmission electron microscope capable of atomic resolution (${\leq}1.2{\AA}$ point-to-point resolution) together with high titling function (${\pm}60^{\circ}$), which are suitable to do 3-dimensional atomic imaging of a specimen. In addition, the instrument can be controlled by remote operation system, named as 'FasTEM' for the HVEM, which is favorable to overcome some environmental obstacles resulting from the direct operation. The FasTEM remote operation system has been established between the headquarter of KBSI in Daejeon and the Seoul branch. The server system in the headquarter has been connected with a portable client console system in the Seoul branch using an advanced internet resource, 'KOREN' of 155 Mbps grade. Most of the HVEM functions essential to do remote operation are available on the portable client console. The experiment to acquire the high resolution image of [001] Au has been achieved by excellent transmission of control signals and communication with the HVEM. Real-time reaction like direct operation, such as controls of the illumination and projection parameters, acquisition and adjustment of each detector signal, and electrical steering of each motor-driven system has been realized in remote site. It is positively anticipated that the first remote operation of HVEM in conjunction with IT infraengineering plays a important role in constructing the network based e-Science Grid in Korea for national user s facilities.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.121-131
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• 2007

Despite the close linkage in changes between the ecological and hydrological processes in forest ecosystems, an integrative approach has not been incorporated successfully. In this study, based on the vegetation and hydrologic data of the Gwangneung headwater catchment with the Geographic Information System, we attempted such an integrated approach by employing the Regional Hydro-Ecologic Simulation System (RHESSys). To accomplish this, we have (1) constructed the input data for RHESSys, (2) developed an integrated calibration system that enables to consider both ecological and hydrological processes simultaneously, and (3) performed sensitivity analysis to estimate the optimum parameters. Our sensitivity analyses on six soil parameters that affect streamflow patterns and peak flow show that the decay parameter of horizontal saturated hydraulic conductivity $(s_1)$ and porosity decay by depth (PD) had the highest sensitivity. The optimization of these two parameters to estimate the optimum streamflow variation resulted in a prediction accuracy of 0.75 in terms of Nash-Sutcliffe efficiency (NSec). These results provide an important basis for future evaluation and mapping of the watershed-scale soil moisture and evapotranspiration in forest ecosystems of Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.155-165
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• 2004

Hydrological model which is proper to watershed characteristics and analysis purpose must be used when we analyze water resources. But, although proper model is used, if objectivity and reasonability of data is low it is difficult to get good results from the model. So it is very important to decide the data which is used in selected model and estimate parameters by using the applied data. In this study, temporal and spatial data was constructed as standard data of test site and stored in HyGIS (Hydrological Geographic Information System) DB. A system which extracts temporal and spatial data required to run hydrological model from HyGIS DB by connecting TOPMODEL with HyGIS was developed. In this system, we can extract temporal and spatial data which is needed to run TOPMODEL from HyGIS DB and estimate model parameters by using genetic algorithm. We found that HyGIS and the system connected with TOPMODEL was effective to make temporal and spatial data used in TOPMODEL and estimate model parameters. From this study, we suggested the possibility that HyGIS could be applied properly to another hydrological model, too.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.11
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• pp.1757-1763
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• 2010

Flywheel energy storage system (FESS) is defined as a high speed rotating flywheel system that can save surplus electric power. The FESS is proposed as an efficient energy storage system because it can accumulate a large amount of energy when it is operated at a high rotating speed and no mechanical problems are encountered. The FESS consists of a shaft, flywheel, motor/generator, bearings, and case. It is difficult to simulate rotor dynamics using common structure simulation programs because these programs are based on the 3D model and complex input rotating conditions. Therefore, in this paper, a program for the FESS based on the 2D FEM was developed. The 2D FEM can model easier than 3D, and it can present the multi-layer rotor with different material each other. Stiffness changing of the shaft caused by shrink fitting of the hub can be inputted to get clear solving results. The results obtained using the program were compared with those obtained using the common programs to determine any errors.

• Phonetics and Speech Sciences
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• v.12 no.2
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• pp.63-72
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• 2020

This study aims to develop a video-based smart utterance deep analyser (SUDA) application that analyzes semiautomatically the utterances that child and mother produce during interactions over time. SUDA runs on the platform of Android, iPhones, and tablet PCs, and allows video recording and uploading to server. In this device, user modes are divided into three modes: expert mode, general mode and manager mode. In the expert mode which is useful for speech and language evaluation, the subject's utterances are analyzed semi-automatically by measuring speech and language factors such as disfluency, morpheme, syllable, word, articulation rate and response time, etc. In the general mode, the outcome of utterance analysis is provided in a graph form, and the manger mode is accessed only to the administrator controlling the entire system, such as utterance analysis and video deletion. SUDA helps to reduce clinicians' and researchers' work burden by saving time for utterance analysis. It also helps parents to receive detailed information about speech and language development of their child easily. Further, this device will contribute to building a big longitudinal data enough to explore predictors of stuttering recovery and persistence.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.2
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• pp.101-108
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• 2011

Climate change could have a pronounced impact on natural and agricultural ecosystems. To assess the impact of climate change, projected climate data have been used as inputs to models. Because such studies are conducted occasionally, it would be useful to employ Cloud computing, which provides multiple instances of operating systems in a virtual environment to do processing on demand without building or maintaining physical computing resources. Furthermore, it would be advantageous to use open source geospatial applications in order to avoid the limitations of proprietary software when Cloud computing is used. As a pilot study, Amazon Web Service ? Elastic Compute Cloud (EC2) was used to calculate the number of days with rain in a given month. Daily sets of climate projection data, which were about 70 gigabytes in total, were processed using virtual machines with a customized database transaction application. The application was linked against open source libraries for the climate data and database access. In this approach, it took about 32 hours to process 17 billion rows of record in order to calculate the rain day on a global scale over the next 100 years using ten clients and one server instances. Here I demonstrate that Cloud computing could provide the high level of performance for impact assessment studies of climate change that require considerable amount of data.