• Journal of Information Processing Systems
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• v.19 no.5
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• pp.576-589
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• 2023

To upgrade home style recommendations and user satisfaction, this paper proposes a personalized and optimized recommendation algorithm for interior design style based on local social network, which includes data acquisition by three-dimensional (3D) model, home-style feature definition, and style association mining. Through the analysis of user behaviors, the user interest model is established accordingly. Combined with the location-based social network of association rule mining algorithm, the association analysis of the 3D model dataset of interior design style is carried out, so as to get relevant home-style recommendations. The experimental results show that the proposed algorithm can complete effective analysis of 3D interior home style with the recommendation accuracy of 82% and the recommendation time of 1.1 minutes, which indicates excellent application effect.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.103-110
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• 2018

Studies on artificial intelligence have been developed for the past couple of decades. After a few periods of prosperity and recession, a new machine learning method, so-called Deep Learning, has been introduced. This is the result of high-quality big- data, an increase in computing power, and the development of new algorithms. The main targets for deep learning are 1D audio and 2D images. The application domain is being extended from a discriminative model, such as classification/segmentation, to a generative model. Currently, deep learning is used for processing 3D data. However, unlike 2D, it is not easy to acquire 3D learning data. Although low-cost 3D data acquisition sensors have become more popular owing to advances in 3D vision technology, the generation/acquisition of 3D data remains a very difficult problem. Moreover, it is not easy to directly apply an existing network model, such as a convolution network, owing to the variety of 3D data representations. In this paper, we summarize the 3D deep learning technology that have started to be developed within the last 2 years.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.2 s.93
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• pp.144-148
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• 2005

In this paper, we have proposed VGA fur MB-OFDM UWB application using $CMOS\;0.18\;{\mu}m$ technique. The proposed VGA can vary power gain from 45 dB to -6 dB and 3 dB band width is more than 264 MHz. It has 3-stage cascade structure and DC offset cancellation. It consumes less, than 4 mA for 1.8 V bias voltage.

• Journal of Platform Technology
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• v.6 no.1
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• pp.3-8
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• 2018

This paper proposes a technique for recognizing online handwritten cursive data obtained by tracing a motion trajectory while a user is in the 3D space based on a convolution neural network (CNN) algorithm. There is a difficulty in recognizing the virtual character input by the user in the 3D space because it includes both the character stroke and the movement stroke. In this paper, we divide syllable into consonant and vowel units by using labeling technique in addition to the result of localizing letter stroke and movement stroke in the previous study. The coordinate information of the separated consonants and vowels are converted into image data, and Korean handwriting recognition was performed using a convolutional neural network. After learning the neural network using 1,680 syllables written by five hand writers, the accuracy is calculated by using the new hand writers who did not participate in the writing of training data. The accuracy of phoneme-based recognition is 98.9% based on convolutional neural network. The proposed method has the advantage of drastically reducing learning data compared to syllable-based learning.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.773-775
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• 2002

This paper deals with 3 Dimensional(3D) analysis of magnetic flux density of High Temperature Superconducting(HTS) motor using 3D Equivalent Magnetic Circuit Network (EMCN). When the Finite Element Method (FEM) is applied to an analysis of 3D models, it takes much time to the pre-process work required for 3D modeling and to solve the differential equation. Compare with 3D FEM, the result of 3D EMCN by using the magnetic resistance and magnetomotive force is exact and rapid. The accuracy of 3D EMCN is verified by comparing the 3D EMCN analysis with that of 3D FEM in HTS motor.

• ETRI Journal
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• v.36 no.4
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• pp.643-653
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• 2014

To reduce interconnect delay and power consumption while improving chip performance, a three-dimensional integrated circuit (3D IC) has been developed with die-stacking and through-silicon via (TSV) techniques. The power supply problem is one of the essential challenges in 3D IC design because IR-drop caused by insufficient supply voltage in a 3D chip reduces the chip performance. In particular, power bumps and TSVs are placed to minimize IR-drop in a 3D power delivery network. In this paper, we propose a design methodology for 3D power delivery networks to minimize the number of power bumps and TSVs with optimum mesh structure and distribute voltage variation more uniformly by shifting the locations of power bumps and TSVs while satisfying IR-drop constraint. Simulation results show that our method can reduce the voltage variation by 29.7% on average while reducing the number of power bumps and TSVs by 76.2% and 15.4%, respectively.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.32-35
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• 1996

This paper analyzes characteristics of PMLSM using 3 dimensional equivalent magnetic circuit network method (3-D EMC). PMLSM of which the effective electric-airgap is not only very large, but also the width is finite width lateral edges has much leakage flux. Therefore, 2-D analysis method cannot consider it so carefully that 3-D analysis method must required. 3-D EMC which will be used for analysis of PMLSM performs modeling of it including solt and teeth structure, uses the magnetic motive force of stator winding and permanent magnet as source. and calculates magnetic flux density and force considering nonlinear characteristics of materials. we verified analysis validity by comparing simulation results with expermental results.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11b
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• pp.643-646
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• 2003

호서 3D 온라인 게임 엔진은 렌더링등의 기능을 담당하는 3D 엔진(클라이언트 부분)과 네트워크 기능을 담당하는 서버 엔진(서버 부분)으로 구성되어 있다. 본 논문은 호서 3D 온라인 게임 엔진을 이용한 3D Tank 데모 게임을 제작하기 위해 일반적인 게임 진행 루프를 분석한 후, 분석 결과를 게임의 목적에 따라 설계하였다. 또한, 설계에 따른 실제 3D Tank 데모 게임을 개발하였으며 이를 바탕으로 3D 온라인 게임 엔진 요소의 효율적인 통합에 대해 고찰한다.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.8-15
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• 2018

This paper proposes a convolutional neural network model for distinguishing areas occupied by obstacles from a LiDAR image converted from a 3D point cloud. The channels of a LiDAR image used as input consist of the distances to 3D points, the reflectivities of 3D points, and the heights of 3D points from the ground. The proposed model uses a LiDAR image as an input and outputs a result of a segmented LiDAR image. The proposed model adopts refinement modules with skip connections to segment a LiDAR image. The refinement modules with skip connections in the proposed model make it possible to construct a complex structure with a small number of parameters than a convolutional neural network model with a linear structure. Using the proposed model, it is possible to distinguish areas in a LiDAR image occupied by obstacles such as vehicles, pedestrians, and bicyclists. The proposed model can be applied to recognize surrounding obstacles and to search for safe paths.

• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.2
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• pp.38-45
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• 2019

The present work suggests a numerical approach using a thermoacoustic network model for the eigenvalue calculation of thermoacoustic instability problems in an aero gas turbine combustor. The model is developed based on the conservation laws for mass, momentum, and energy between acoustic network elements with an area change. Acoustic field in a practical aero gas turbine combustor which has a complicated flow path is analyzed using the current model. The predictive capabilities of the current modeling approach are compared with the acoustic characteristics calculated using Helmholtz solver based on 3D finite element method(FEM).