• Journal of Fashion Business
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• v.22 no.4
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• pp.30-46
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• 2018

The purpose of the study was to suggest certain measurements of the skirt block pattern drafting process for the Korean female fashion models, with the aim to improve its fit. For this purpose, the study carried out an analysis of the lower body features of a dress form developed for the study. This form was representative of Korean female fashion models' body features. The study performed a cross-sectional analysis at waist and hip levels and measured the angles from the frontal and lateral silhouettes of the dress forms. The comparisons of the skirt block patterns developed through draping by the use of 2 types of the dress forms developed and existed and through drafting according to the current patternmaking method have led to noticeable findings in terms of implementation of the skirt block drafting process for the Korean female fashion models. The results of the study are as follows: (1) the vertical lengths between the levels at the front waist point and the side waist point in the patterns are 0.7cm; (2) the vertical length between the levels at the front waist point and the back waist point in the back panel is 0.7cm; (3) the horizontal lengths between the perpendicular line from the side hip point and the side waist point in patterns are within a range of 2.0 to 2.2cm; (4) the horizontal length between the original and the adjusted back waist points moved into the waist line, in a range of 0.0 to 1.0cm, differs whether the center back line would be folded or sewn.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.10
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• pp.1174-1180
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• 2011

Not all line or point features capable of being extracted by sonar sensors from cluttered home environments are useful for simultaneous localization and mapping (SLAM) due to their ambiguity because it is difficult to determine the correspondence of line or point features with previously registered feature. Confused line and point features in cluttered environments leads to poor SLAM performance. We introduce a sonar feature structure suitable for a cluttered environment and the extended Kalman filter (EKF)-based SLAM scheme. The reliable line feature is expressed by its end points and engaged togather in EKF SLAM to overcome the geometric limits and maintain the map consistency. Experimental results demonstrate the validity and robustness of the proposed method.

• Journal of Power Electronics
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• v.12 no.3
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• pp.487-494
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• 2012

A new low cost high power density photovoltaic power conditioning system (PV PCS) with an energy storage system is proposed in this paper. Its high power density and cost effectiveness can be achieved through the unification of the maximum power point tracker and the battery charger/discharger. Despite the reduced power stage, the proposed system can achieve the same performance in terms of maximum power point tracking and battery charging/discharging as the conventional system. When a utility power failure happens, the proposed system cannot perform maximum power point tracking at the UPS mode. However, the predetermined battery voltage near the maximum power point of the PV array can effectively generate a reasonable PV power even at the UPS mode. Therefore, it features a simpler structure, less mass, lower cost, and fewer devices. Finally, to confirm the operation, validity, and features of the proposed system, a theoretical analysis and experimental results from a single phase AC 220Vrms/1.5kW prototype are presented.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.787-800
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• 2021

Three-dimensional (3D) object classification tasks using point clouds are widely used in 3D modeling, face recognition, and robotic missions. However, processing raw point clouds directly is problematic for a traditional convolutional network due to the irregular data format of point clouds. This paper proposes a pointwise convolution neural network (CNN) structure that can process point cloud data directly without preprocessing. First, a 2D convolutional layer is introduced to percept coordinate information of each point. Then, multiple 2D convolutional layers and a global max pooling layer are applied to extract global features. Finally, based on the extracted features, fully connected layers predict the class labels of objects. We evaluated the proposed pointwise CNN structure on the ModelNet10 dataset. The proposed structure obtained higher accuracy compared to the existing methods. Experiments using the ModelNet10 dataset also prove that the difference in the point number of point clouds does not significantly influence on the proposed pointwise CNN structure.

• ETRI Journal
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• v.33 no.4
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• pp.517-527
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• 2011

Currently, there is a considerable interest in 3D object reconstruction using terrestrial laser scanner (TLS) systems due to their ability to automatically generate a considerable amount of points in a very short time. To fully map an object, multiple scans are captured. The different scans need to be registered with the help of the point cloud in the overlap regions. To guarantee reliable registration, the scans should have large overlap ratio with good geometry for the estimation of the transformation parameters among these scans. The objective of this paper is to propose a registration method that relaxes/eliminates the overlap requirement through the utilization of photogrammetrically reconstructed features. More specifically, a point-based procedure, which utilizes non-conjugate points along corresponding linear features from photogrammetric and TLS data, will be used for the registration. The non-correspondence of the selected points along the linear features is compensated for by artificially modifying their weight matrices. The paper presents experimental results from simulated and real datasets to illustrate the feasibility of the proposed procedure.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.111-122
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• 2010

In this study, a length adjustment algorithm for cyclic signals in manufacturing process using Time Invariant Feature point Extraction and Matching(TIFEM) is proposed. In order to precisely compensate the length of cyclic signals which have irregular length in the middle of signal as well as in the full length more feature points are needed. The extracted feature must involve information about the pattern of signal and should have invariant properties on time and scale. The proposed TIFEM algorithm extracts features having the intrinsic properties of the signal characteristics at first. By using those extracted features, feature vector is constructed for each time point. Among those extracted features, the only effective features are filtered and are chosen such as basis for the length adjustment. And then the partial length adjustment is performed by matching feature points. To verify the performance of the proposed algorithm, the experiments were performed with the experimental data mimicking the three kinds of signals generated from the actual semiconductor process.

• Journal of the Korean Society of Industry Convergence
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• v.6 no.1
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• pp.23-29
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• 2003

This paper proposes an efficient feature extraction of the images by using independent component analysis(ICA) based on neural networks of the hybrid learning algorithm. The proposed learning algorithm is the fixed point(FP) algorithm based on Newton method and moment. The Newton method, which uses to the tangent line for estimating the root of function, is applied for fast updating the inverse mixing matrix. The moment is also applied for getting the better speed-up by restraining an oscillation due to compute the tangent line. The proposed algorithm has been applied to the 10,000 image patches of $12{\times}12$-pixel that are extracted from 13 natural images. The 144 features of $12{\times}12$-pixel and the 160 features of $16{\times}16$-pixel have been extracted from all patches, respectively. The simulation results show that the extracted features have a localized characteristics being included in the images in space, as well as in frequency and orientation. And the proposed algorithm has better performances of the learning speed than those using the conventional FP algorithm based on Newton method.

• Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.48-54
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• 2014

In this paper, the authors propose a system for assisting mold designers of plastic parts. With a CAD model of a part, the system automatically determines the optimal ejecting direction of the part with minimum undercuts. Since plastic parts are generally very thin, many rib features are placed on the inner side of the part to give sufficient structural strength. Our system extracts the rib features from the CAD model of the part, and determines the possible ejecting directions based on the geometric properties of the features. The system then selects the optimal direction with minimum undercuts. Possible ejecting directions are represented as discrete points on a Gauss map. Our new point distribution method for the Gauss map is based on the concept of the architectural geodesic dome. A hierarchical structure is also introduced in the point distribution, with a higher level "rough" Gauss map with rather sparse point distribution and another lower level "fine" Gauss map with much denser point distribution. A system is implemented and computational experiments are performed. Our system requires less than 10 seconds to determine the optimal ejecting direction of a CAD model with more than 1 million polygons.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.131-138
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• 2006

Recently, data gathering and algorithm developing are in progress for the GIS application using point feature. Several researches prove that verification of the spatial clustering and evaluation of inter-dependencies between event and control are possible. On the other hand, most of the point features as GIS data are gathered by indirect method, such as address geo-coding, rather than by direct method, such as field surveying. Futhermore, lots of statistics by administrative district based on the point features have no coordinates information of the points. In this study, calculating the K-index in GIS environment, to evaluate the effect of aggregation of raw data on K-index, K-indices estimated from raw data (parcel unit), topographically aggregated data (block unit), administratively aggregated data (administrative district unit) are compared and evaluated. As a result, point feature, highly clustered in local area, is largely distorted when aggregated administratively. But, the K-indices of topographically aggregated data is very similar to the K-indices of raw data.

• Phonetics and Speech Sciences
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• v.6 no.4
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• pp.79-90
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• 2014

An intonation curve stylization was used for an acoustical analysis of English speech. For the analysis, acoustical feature values were extracted from 1,848 utterances produced with normal and fast speech rate by 28 (12 women and 16 men) native speakers of English. Men are found to speak faster than women at normal speech rate but no difference is found between genders at fast speech rate. Analysis of pitch point features has it that fast speech has greater Pt (pitch point movement time), Pr (pitch point pitch range), and Pd (pitch point distance) but smaller Ps (pitch point slope) than normal speech. Men show greater Pt, Pr, and Pd than women. Analysis of sentence level features reveals that fast speech has smaller Sr (sentence level pitch range), Sd (sentence duration), and Max (maximum pitch) but greater Ss (sentence slope) than normal speech. Women show greater Sr, Ss, Sp (pitch difference between the first pitch point and the last), Sd, MaxNr (normalized Max), and MinNr (normalized Min) than men. As speech rate increases, women speak with greater Ss and Sr than men.