• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.181-189
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• 2005

Due to grammatical similarities, even a one-to-one mapping between Korean and Japanese morphemes can usually result in a high quality Korean-to-Japanese machine translation. So most of Korean-to-Japanese machine translation are based on a one-to-one mapping relation. Most of Korean '-hada' verbs, which consist of a noun and '-hada', also correspond to Japanese '-suru' verbs, which consist of a noun and '-suru', so we generally use one-to-one mapping relation between them. However, the applications only by one-to-one mapping may sometimes result in incorrect Japanese correspondences in some cases that Korean 'hada' verbs don't correspond to Japanese 'suru' verbs. In these cases, we need to handle a noun and '-hada' as one translation unit. Therefore, this paper examined the characteristics of Korean '-hada' verb and proposed transfer rules of Korean 'hada' verb, applying for various states of input sentences such as discontinuity due to inserted words between a noun and '-hada', passivization, and modification of '-hada' verb. In an experimental evaluation, the proposed method was very effective for handling '-hada' verb in a Korean-to-Japanese machine translation, showing high quality of translation results.

• Journal of Digital Contents Society
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• v.5 no.1
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• pp.35-40
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• 2004

Today`s education is in the 7th education curriculum. But, there is nothing that can be used in the classroom as a tool for education supplement. Easylab is a GUI-programing tool for students who not good at using computers. EasyLab is used in the classroom as a kind of tool to give a rise to ingenuity and creation which need at present education curriculum. When use it, first, learners think of programming-ideas, then program through icon-based software-EasyLab. After programing, the leaner can see the result directly thorough the programing code which are delivered by EasyRobot. So, leaner can study and discuss with the robot`s result. If, the result is incorrect, the robot will do a feedback as a kind of rule. One of the EasyLab`s specific property is that consisted icon-based flow-chart model. And leaner can practice with the robot that have input and output sense.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.341-346
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• 2012

In rehabilitation where ultrasonographic diagnosis is not popular, it could be subjective by medical expert's experience. Thus, it is necessary to develop an objective automative procedure in ultrasonic image analysis. A disadvantage of existing automative analytic procedure in musculoskeletal system is to designate an incorrect muscle area when the figure of fascia is vague. In this study, we propose a new procedure to extract more accurate muscle area in abdomen ultrasonic image for that purpose. After removing unnecessary noise from input image, we apply End-in Search algorithm to enhance the contrast between fascia and muscle area. Then after extracting initial muscle area by Up-Down search, we trace the fascia area with a mask based on morphological and directional information. By this tracing of mask movements, we can emphasize the fascia area to extract more accurate muscle area in result. This new procedure is proven to be more effective than existing methods in experiment using convex ultrasound images that are used in real world rehabilitation diagnosis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1682-1688
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• 2008

The Counterpropagation algorithm(CP) is a combination of Kohonen competition network as a hidden layer and the outstar structure of Grossberg as an output layer. CP has been used in many real applications for pattern matching, classification, data compression and statistical analysis since its learning speed is faster than other network models. However, due to the Kohonen layer's winner-takes-all strategy, it often causes instable learning and/or incorrect pattern classification when patterns are relatively diverse. Also, it is often criticized by the sensitivity of performance on the learning rate. In this paper, we propose an enhanced CP that has multiple Kohonen layers and dynamic controlling facility of learning rate using the frequency of winner neurons and the difference between input vector and the representative of winner neurons for stable learning and momentum learning for controlling weights of output links. A real world application experiment - pattern recognition from passport information - is designed for the performance evaluation of this enhanced CP and it shows that our proposed algorithm improves the conventional CP in learning and recognition performance.

• Korean Journal of Optics and Photonics
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• v.17 no.5
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• pp.401-411
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• 2006

We propose an optical encryption/decryption technique for a security system based on 2-step phase-shifting digital holography. Phase-shilling digital holography is used for recording phase and amplitude information on a CCD device. 2-step phase-shifting is implemented by moving the PZT mirror with phase step of 0 or ${\pi}/2$. The binary data and the key are expressed with random code and random phase patterns. The digital hologram is a Fourier transform hologram and is recorded on CCD with 256 gray level quantization. We remove the DC term of the digital hologram fur data reconstruction, which is essential to reconstruct the original binary input data/image. The error evaluation fer the decrypted binary data is analyzed. One of errors is a quantization error in detecting the hologram intensity on CCD, and the other is generated from decrypting the data with the incorrect key. The technique using 2-step phase-shifting holography is more efficient than a 4-step method because 2-step phase-shifting holography system uses less data than the 4-step method for data storage or transmission. The simulation shows that the proposed technique gives good results fur the optical encryption of binary information.

• Smart Structures and Systems
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• v.23 no.1
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• pp.1-14
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• 2019

Control algorithms are the most important aspects in successful control of structures against earthquakes. In recent years, intelligent control methods rather than classical control methods have been more considered by researchers, due to some specific capabilities such as handling nonlinear and complex systems, adaptability, and robustness to errors and uncertainties. However, due to lack of learning ability of fuzzy controller, it is used in combination with a genetic algorithm, which in turn suffers from some problems like premature convergence around an incorrect target. Therefore in this research, the introduction and design of the Fuzzy Cooperative Coevolution (Fuzzy CoCo) controller and Adaptive Neural-Fuzzy Inference System (ANFIS) have been innovatively presented for semi-active seismic control. In this research, in order to improve the seismic behavior of structures, a semi-active control of building using Magneto Rheological (MR) damper is proposed to determine input voltage of Magneto Rheological (MR) dampers using ANFIS and Fuzzy CoCo. Genetic Algorithm (GA) is used to optimize the performance of controllers. In this paper, the design of controllers is based on the reduction of the Park-Ang damage index. In order to assess the effectiveness of the designed control system, its function is numerically studied on a 9-story benchmark building, and is compared to those of a Wavelet Neural Network (WNN), fuzzy logic controller optimized by genetic algorithm (GAFLC), Linear Quadratic Gaussian (LQG) and Clipped Optimal Control (COC) systems in terms of seismic performance. The results showed desirable performance of the ANFIS and Fuzzy CoCo controllers in considerably reducing the structure responses under different earthquakes; for instance ANFIS and Fuzzy CoCo controllers showed respectively 38 and 46% reductions in peak inter-story drift ($J_1$) compared to the LQG controller; 30 and 39% reductions in $J_1$ compared to the COC controller and 3 and 16% reductions in $J_1$ compared to the GAFLC controller. When compared to other controllers, one can conclude that Fuzzy CoCo controller performs better.

• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.1-8
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• 2022

Elevators are the main means of transport in buildings. A malfunction of an elevator in operation may cause in convenience to users. Furthermore, fatal accidents, such as injuries and death, may occur to the passengers also. Therefore, it is important to prevent failure before accidents happen. In related studies, preventive measures are proposed through analyzing failures, and the lifespan of elevator components. However, these methods are limited to existing an elevator model and its surroundings, including operating conditions and installed environments. Vibration occurs when the elevator is operated. Experts have classified types of faults, which are symptoms for malfunctions (failures), via analyzing vibration. This study proposes an artificial intelligent model for classifying faults automatically with deep learning algorithms through elevator vibration data, hereby preventing failures before they occur. In this study, the vibration data of six elevators are collected. The proposed methodology in this paper removes "the measurement error data" with incorrect measurements and extracts operating sections from the input datasets for proceeding deep learning models. As a result of comparing the performance of training five deep learning models, the maximum performance indicates Accuracy 97% and F1 Score 97%, respectively. This paper presents an artificial intelligent model for detecting elevator fault automatically. The users' safety and convenience may increase by detecting fault prior to the fatal malfunctions. In addition, it is possible to reduce manpower and time by assisting experts who have previously classified faults.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.1-9
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• 2008

In this paper, to extract object regions in stereo image, we propose an enhanced algorithm that extracts objects combining both of brightness information and disparity information. The approach that extracts objects using both has been studied by Ping and Chaohui. In their algorithm, the segmentation for an input image is carried out using the brightness, and integration of segmented regions in consideration of disparity information within the previously segmented regions. In the regions where the brightness values between object regions and background regions are similar, however, the segmented regions probably include both of object regions and background regions. It may cause incorrect object extraction in the merging process executed in the unit of the segmented region. To solve this problem, in proposed method, we adopt the merging process which is performed in pixel unit. In addition, we perform the bi-directional stereo matching process to enhance reliability of the disparity information and supplement the disparity information resulted from a single directional matching process. Further searching for disparity is decided by edge information of the input image. The proposed method gives good performance in the object extraction since we find the disparity information that is not extracted in the traditional methods. Finally, we evaluate our method by experiments for the pictures acquired from a real stereoscopic camera.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.61-72
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• 2008

Leaf area index (LAI) is a key biophysical variable influencing land surface processes such as photosynthesis, transpiration and energy balance, and is a required input to estimate evapotranspiration in various ecological and hydrological models. The development of more correct and useful LAIs estimation techniques is required by these importance, but LAIs had been assumed in most LAI research through simple relations with the normalized difference vegetation index (NDVI) because the field measurement is difficult on wide area. This paper is to evaluate the MODIS LAI Product's practical use by comparing with LAIs that is derived from NOAA AVHRR NDVIs and the 2 years (2003-2004) measured LAIs of Korea Forest Research Institute in Gyeongancheon watershed (561.12 $Km^2$). As a result, the MODIS LAIs of deciduous forests showed higher values about 14 % and 15~30 % than the measured LAIs and NOAA LAIs. In the year of 2003, the MODIS LAIs in coniferous forests were 5 % higher than the measured LAIs, and showed about 7 % differences comparing with the NOAA LAIs except April. These differences come from the insufficient field data measured in partial points of the target area, and the extracted reference data from MODIS LAIs include the limits of spatial resolution and the error of incorrect land cover classification. Thus, using the MODIS data by the proper correction with the measured data can be useful as an input data for ecological and hydrological models which offers the vegetation information and simulates the water balance of a given watershed.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.29-33
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• 2011

Background and Purpose: Uniformity is the one of the important quality control features with respect to gamma cameras. To maintain adequate uniformity, we must acquire suitable flood table (=flood map) data because the flood table effects energy, and the type or dose of input radiation. Therefore, in this study we evaluated the difference in uniformity when uniformity does not match between the type of input radiation and the flood table data or collimator type. Subjects and Methods: For input radiation, we prepared 370 MBq of $^{57}Co$, $^{99m}Tc$, and $^{201}Tl$. Using SKYLight (Philips) and Infinia gamma cameras (GE), we acquired nine uniformity data that were corrected by technetium, cobalt flood table and did not corrected image for the three sources. Additionally, we acquired two uniformity images with a collimator that were corrected by intrinsic and extrinsic flood tables. Using this data, we evaluated and compared the uniformity values. Results: In the case of the SKYLight gamma camera, the uniformities of the images that matched between the input radiation and flood table with respect to $^{99m}Tc$ and $^{57}Co$ were better than the unmatched uniformity (3.96% vs. 5.69% ; 4.9% vs. 5.91%). However, because there was no thallium flood table, the uniformities of images at Tl were significantly incorrect (7.49%, 7.03%). The uniformities of the Infinia gamma camera had the same pattern as the SKYLight gamma camera (3.7% vs. 4.5%). Moreover, the uniformity of the $^{99m}Tc$ image acquired with a collimator and corrected by an extrinsic flood table was better than the intrinsic flood table (3.96% vs. 6.28%). Conclusion: Correcting an image by a suitable flood table can help achieve better uniformity for a gamma camera. Therefore, we have to acquire images with suitable uniformity correction, and update the flood table periodically. Whenever we acquire a nuclear medicine image, we always have to check the appropriate flood table according to the acquired condition.