• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.1-5
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• 2002

The purpose of this paper is developing a speech recognition module in a wheelchair for the sake of convenience. of the disability. For this system, we used TMS320C32 as a main processor; eliminated noise by applying Winer filler while considering characteristics of noise environment in pre-processing stage, and; extracted 12 feature patterns per france using LPC&Cepstrum. Then, we implemented the hybrid form combining DTW (Dynamic Time Warping), which is generally used for isolated words in the conventional algorithms, in the recognition Part, and NN (Neural network) to prevent any error of recognition. In this research, we achieved a recognition rate of more than 96% on isolated words when DTW and Hybrid forms were individually experimented in noise environment

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.804-811
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• 1999

The object-oriented methods are being rapidly accepted as the solution for the software crisis. Object-oriented systems are composed of the integration of independent object modules; their merits are such that it is possible to reuse objects already developed, and that, when changes are required, modifications are restricted to some independent objects such that their affects to other objects are so little. In this paper, we deal with the macro assembler for next-generation microprocessors which has the merits of object methods. Whenever a microprocessor is newly developed, new assembler should be developed or the existing assembler be modified. In the former, it leads to the loss of time and money by the repeated developments, and, in the latter, it causes the problem of inefficient productivity since other modules are to be analyzed for the affections followed by modifications of one module, especially in the existing assemblers. To resolve these problems, the object-oriented macro assembler suggested in this paper consists of independent objects separable such that it shows reusability and reduces the inefficient productivity by minimizing the affects to other objects. Moreover, the object-oriented macro assembler integrates a macro pre-processor into an assembler, and uses automata for analyzing input streams to reduce the compile time.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.3
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• pp.97-104
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• 2010

The purpose of this study is to evaluate sediment yield reduction under various field slope conditions with rice straw mat. The Vegetative Filter Strip Model-W (VFSMOD-W) and Soil and Water Assessment Tool (SWAT) were used for simulation of sediment yield reduction effect of rice straw mat. The Universe Soil Loss Equation Practice factor (USLE P factor), being able to reflect simulation of rice straw mat in the agricultural field, were estimated for each slope with VFSMOD-W and measured soil erosion values under 5, 10, and 20 % slopes. Then with the regression equation for slopes, USLE P factor was derived and used as input data for each Hydrological Response Unit (HRU) in the SWAT model. The SWAT Spatially Distributed-HRU (SD-HRU) pre-processor module was utilized, moreover, in order to consider spatial location and topographic features (measured topographic features by field survey) of all HRU within each subwatershed in the study watershed. Result of monthly sediment yield without rice straw mat (Jan. 2000 - Aug. 2007) was 814.72 ton/month, and with rice straw mat (Jan. 2000 - Aug. 2007) was 526.75 ton/month, which was reduced as 35.35 % compared without it. Also, during the rainy season (from Jun. to Sep. 2000 - 2007), when without vs. with rice straw mat, monthly sediment indicated 2,109.54 ton and 1,358.61 ton respectively. It showed about 35.60 % was reduced depending on rice straw mat. As shown in this study, if rice straw mat is used as a Best Management Practice (BMP) in the sloping fields, rainfall-driven sediment yield will be reduced effectively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.5
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• pp.997-1006
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• 2019

To overcome the difficulties and inefficiencies of the existing power analysis attack, we try to extract the secret key embedded in a cryptographic device using attack model based on MLP(Multi-Layer Perceptron) method. The target of our proposed power analysis attack is the AES-128 encryption module implemented on an 8-bit processor XMEGA128. We use the divide-and-conquer method in bytes to recover the whole 16 bytes secret key. As a result, the MLP-based power analysis attack can extract the secret key with the accuracy of 89.51%. Additionally, this MLP model has the 94.51% accuracy when the pre-processing method on power traces is applied. Compared to the machine leaning-based model SVM(Support Vector Machine), we show that the MLP can be a outstanding method in power analysis attacks due to excellent ability for feature extraction.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.293-303
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• 2008

Reservoir turbidity flows degrade the efficiency and sustainability of water supply system in many countries located in monsoon climate region. A decision support system called RTMMS aimed to assist reservoir operations was developed for the real time monitoring, modeling, and management of turbidity flows induced by flood runoffs in Daecheong reservoir. RTMMS consists of a real time data acquisition module that collects and stores field monitoring data, a data assimilation module that assists pre-processing of model input data, a two dimensional numerical model for the simulation of reservoir hydrodynamics and turbidity, and a post-processor that aids the analysis of simulation results and alternative management scenarios. RTMMS was calibrated using field data obtained during the flood season of 2004, and applied to real-time simulations of flood events occurred on July of 2006 for assessing its predictive capability. The system showed fairly satisfactory performance in reproducing the density flow regimes and fate of turbidity plumes in the reservoir with efficient computation time that is a vital requirement for a real time application. The configurations of RTMMS suggested in this study can be adopted in many reservoirs that have similar turbidity issues for better management of water supply utilities and downstream aquatic ecosystem.

• Journal of the Korea Institute of Building Construction
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• v.17 no.6
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• pp.545-557
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• 2017

The study is about the efficient alternative to concrete surface in the field of visual inspection technology for deteriorated infrastructure. By combining industrial drones and deep learning based image analysis techniques with traditional visual inspection and research, we tried to reduce manpowers, time requirements and costs, and to overcome the height and dome structures. On board device mounted on drones is consisting of a high resolution camera for detecting cracks of more than 0.3 mm, a lidar sensor and a embeded image processor module. It was mounted on an industrial drones, took sample images of damage from the site specimen through automatic flight navigation. In addition, the damege parts of the site specimen was used to measure not only the width and length of cracks but white rust also, and tried up compare them with the final image analysis detected results. Using the image analysis techniques, the damages of 54ea sample images were analyzed by the segmentation - feature extraction - decision making process, and extracted the analysis parameters using supervised mode of the deep learning platform. The image analysis of newly added non-supervised 60ea image samples was performed based on the extracted parameters. The result presented in 90.5 % of the damage detection rate.