• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.8
• /
• pp.754-759
• /
• 2001

In this paper, we propose a TSK(Takagi-Sugeno-Kang)-type fuzzy classifier using PCA(Principal Component Analysis), FCM(Fuzzy c-Means) clustering, ANFIS(Adaptive Neuro-Fuzzy Inference System) and hybrid GA(Genetic Algorithm). First, input data is transformed to reduce correlation among the data components by PCA. FCM clustering is applied to obtain a initial TSK-type fuzzy classifier. Parameter identification is performed by AGA(Adaptive GA) and RLSE(Recursive Least Square Estimate). Finally, we applied the proposed method to Iris data classificationl problems and obtained a better performance than previous works.

• Tunnel and Underground Space
• /
• v.25 no.1
• /
• pp.56-67
• /
• 2015

In this study, a source locating technique applicable to transversely isotropic media was developed. Wave velocity anisotropy was considered based on the partition approximation method, which simply enabled AE source locating. Sets of P wave arrival time were decided by the two-step AIC algorithm and they were later used to locate the AE sources when having the least error compared with the partitioned elements. In order to validate the technique, pencil lead break test on artificial transversely isotropic mortar specimen was carried out. Defining the absolute error as the distance between the pencil lead break point and the located point, 1.60 mm ~ 14.46 mm of range and 8.57 mm of average were estimated therefore it was regarded as thought to be 'acceptable' considering the size of the specimen and the AE sensors. Comparing each absolute error under different threshold levels, results showed small discrepancies therefore this technique was hardly affected by background noise. Absolute error could be decomposed into each coordinate axis error and through it, effect of AE sensor position could be understood so if optimum sensor position was able to be decided, one could get more precise outcome.

• Tunnel and Underground Space
• /
• v.32 no.6
• /
• pp.502-517
• /
• 2022

As the use of TBM increases, research has recently increased to to analyze TBM data with machine learning techniques to predict the exchange cycle of disc cutters, and predict the advance rate of TBM. In this study, a regression prediction of disc cutte wear of slurry shield TBM site was made by combining machine learning based on the machine data and the geotechnical data obtained during the excavation. The data were divided into 7:3 for training and testing the prediction of disc cutter wear, and the hyper-parameters are optimized by cross-validated grid-search over a parameter grid. As a result, gradient boosting based on the ensemble model showed good performance with a determination coefficient of 0.852 and a root-mean-square-error of 3.111 and especially excellent results in fit times along with learning performance. Based on the results, it is judged that the suitability of the prediction model using data including mechanical data and geotechnical information is high. In addition, research is needed to increase the diversity of ground conditions and the amount of disc cutter data.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.9
• /
• pp.1846-1855
• /
• 2015

In this paper, a precise relative positioning with TD(time differenced) carrier phase measurements from a low-cost GNSS(Global Navigation Satellite System) receiver is proposed and analysed. The proposed method is using carrier phase measurement from a single GNSS receiver that reference receiver is not required and stand alone positioning is possible. TD operation removes the troublesome integer ambiguity resolution problem, and if the time interval is short, other error, such as, ionospheric, tropospheric delay and ephemeris error are effectively eliminated. The error analysis of the proposed method shows that a precise and positioning with carrier phase is possible. The implemented system is evaluated using a real car experiments. The results show that the horizontal positioning error was less than 3m during 10 minutes experiments, which is 4 times more precise than the results of normal code based absolute positioning.

• Journal of KIISE:Databases
• /
• v.33 no.3
• /
• pp.261-270
• /
• 2006

Positional data of moving objects can be regularly sampled in order to minimize the cost of data collection in LBS. Since position data which are regularly sampled cannot include the changes of position occurred between sampling periods, sampled position data differ from the data predicted by a time parameterized linear function. Uncertain position data caused by these differences make the accuracy of the range queries for present positions diminish in the TPR tree. In this paper, we propose the uncertainty region to handle the range queries for uncertain position data. The uncertainty region is defined by the position data predicted by the time parameterized linear function and the estimated uncertainty error. We also present the weighted recent uncertainty error policy and the kalman filter policy to estimate the uncertainty error. For performance test, the query processor based by the uncertainty region is implemented in the TPR tree. The experiments show that the Proposed query processing methods are more accurate than the existing method by 15%.

• Journal of Korea Multimedia Society
• /
• v.3 no.2
• /
• pp.121-132
• /
• 2000

Most of video indexing applications depend on fast and efficient archiving, browsing, retrieval techniques. A number of techniques have been approached about only pixel domain analysis until now. Those approaches brought about the costly overhead of decompressing because the most of multimedia data is typically stored in compressed format. But with a compressed video data, if we can analyze the compressed data directly. then we avoid the costly overhead such as in pixel domain. In this paper, we analyze the information of compressed video stream directly, and then extract the available features for video indexing. We have derived the technique for cut detection using these features, and the stream is divided into shots. Also we propose a new brief key frame selection technique and an efficient video indexing method using the spatial informations(DT coefficients) and also the temporal informations(motion vectors).

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.10
• /
• pp.465-472
• /
• 2015

We propose a novel plane detection in disparity space and evaluate its performance. Our method simplifies and makes scenes in disparity space easily dealt with by approximating various surfaces as planes. Moreover, the approximated planes can be represented in the same size as in the real world, and can be employed for obstacle detection and camera pose estimation. Using a stereo matching technique, our method first creates a disparity image which consists of binocular disparity values at xy-coordinates in the image. Slants of disparity values are estimated by exploiting a line simplification algorithm which allows our method to reflect global changes against x or y axis. According to pairs of x and y slants, we label the disparity image. 4-connected disparities with the same label are grouped, on which least squared model estimates plane parameters. N plane models with the largest group of disparity values which satisfy their plane parameters are chosen. We quantitatively and qualitatively evaluate our plane detection. The result shows 97.9%와 86.6% of quality in our experiment respectively on cones and cylinders. Proposed method excellently extracts planes from Middlebury and KITTI dataset which are typically used for evaluation of stereo matching algorithms.

• Journal of Intelligence and Information Systems
• /
• v.7 no.1
• /
• pp.149-159
• /
• 2001

There have been lots of researches for providing a personalized service to a customer using one-to-one marketing and collaborative filtering techniques in E-Commerce. However, there are technical difficulties for providing the recommendation of products far users, which often involve high complexity of computation. In this paper, we have presented an integrated method of classification problem solving method and constraint based configuration techniques. This method can reduce a complexity of computation by classifying a solution domain space that has a higher complexity of composition. Thereafter, we have modeled customers constraints and the components of products to configure a complete system by passing it to constraint processing module in Constraint Satisfaction Problems. Constraint-based configuration uses the constraint propagation using the constraints of buyers and the constraints among PC components to configure a proper product for a customer. We have transformed and applied vector space modeling method in the field of information retrieval to consider a customer satisfaction in addition to the CSP. Finally, we have applied our system to test data fur evaluating a customers satisfaction and performance of the proposed system.

• Journal of Korea Multimedia Society
• /
• v.10 no.8
• /
• pp.1017-1028
• /
• 2007

In this paper we propose an effective method to represent, store, and retrieve video streams efficiently from a video database. We extract features from each video frame, normalize the feature values, and represent them as values in the range [0,1]. In this way a video frame with f features can be represented by a point in the f-dimensional space $[0,1]^f$, and thus the video stream is represented by a trail of points in the multidimensional space. The video stream is partitioned into video segments based on camera shots, each of which is represented by a trend vector which encapsulates the moving trend of points in a segment. The video stream query is processed depending on the comparison of those trend vectors. We examine our method using a collection of video streams that are composed of sports, news, documentary, and educational videos. Experimental results show that our trend vector representation reduces a reconstruction error remarkably (average 37%) and the retrieval using a trend vector achieves the high precision (average 2.1 times) while maintaining the similar response time and recall rate as existing methods.

• Proceedings of the Korea Contents Association Conference
• /
• 2009.05a
• /
• pp.1105-1110
• /
• 2009

To assess the clinical value of time resolved imaging of contrast kinetics(TRICKS) MRA by comparison with conventional time of flight(TOF) MR angiography. Both TOF-MRA and TRICKS-MRA were performed in 17 patients with cerebrovascular disease and in 6 patients with brain tumor. Among 17 cerebraovascular patients, digital subtraction angiography(DSA) data were also obtained in 11 patients. TOF-MRA showed good spatial resolution but short in temporal resolution. Although TRICKS-MRA showed somewhat low spatial resolution, it showed superior temporal resolution by distinguishing vessel and tumor in all patients. Also, from the analysis of vessel-tumor relationship, TRICKS-MRA showed better performance than TOF-MRA. TRICKS-MRA makes it possible to image arterial, capillary and venous phase sequentially with very speedy manner and therefore, the clinical use of this method is highly suggestive for future use.