• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.8
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• pp.1-7
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• 2006

In the present study, A 3-D chimera technique for overlapped bodies in relative motion is studied using unstructured meshes. If all node points of a mesh element at solid boundary are in another body, this element is excluded from computational domain. For computation of unsteady flow, non-active cells have proper variables using interpolation and extrapolation. These variables are used in next time step. The motion of a launching trajectory ejected from a wing and the motion of deploying fins of a trajectory which have not been simulated are computed to conform practicality of this technique.

• International Journal of High-Rise Buildings
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• v.6 no.2
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• pp.139-147
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• 2017

Analyzing morphological evolution over a long period of time is deemed an effective way to identify problems occurring in the process of urban development, in addition to achieving a fundamental understanding of socio-cultural changes and growth rooted from the context. As far as the urban morphology is concerned, Hong Kong is characterized by its unique high-density and compact layout patterns, which have aroused the interest of a number of authors in the urban design domain. Whilst an increasing number of redevelopment projects in Hong Kong were criticized for ignoring and destroying the old urban fabric, there is a need for research to investigate the origins and changes of various urban patterns and their implications for society. By employing the theories and techniques of space syntax, this paper accordingly provides a morphological analysis based on the Wanchai District - a 'Segment-line' city, which particularly epitomizes various urban grids of Hong Kong and may have different implications for functional aspects. By axial-mapping the urban layouts of five stages of growth since 1842 and subsequently investigating their spatial and functional transformation over the past 170 years, this paper identifies a series of spatial characteristics underlying different grid patterns, as well as achieves a precise understanding of their ever changing relationship. Based on these understandings, this paper intends to provide valuable reference and guidance for upcoming spatial development in Hong Kong and other regions.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1566-1577
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• 2018

This paper presents a stability analysis of AC-DC power system feeding a speed controlled DC motor in which this load behaves as a constant power load (CPL). A CPL can significantly degrade power system stability margin. Hence, the stability analysis is very important. The DQ and generalized state-space averaging methods are used to derive the mathematical model suitable for stability issues. The paper analyzes the stability of power systems for both speed control natural frequency and DC-link parameter variations and takes into account controlled speed motor dynamics. However, accurate DC-link filter and DC motor parameters are very important for the stability study of practical systems. According to the measurement errors and a large variation in a DC-link capacitor value, the system identification is needed to provide the accurate parameters. Therefore, the paper also presents the identification of system parameters using the adaptive Tabu search technique. The stability margins can be then predicted via the eigenvalue theorem with the resulting dynamic model. The intensive time-domain simulations and experimental results are used to support the theoretical results.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.3
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• pp.474-484
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• 2017

This paper studies the applicability of an efficient numerical model based on artificial neural networks (ANNs) to predict the dynamic responses of the wing structure of an airplane due to atmospheric turbulence in the time domain. The turbulence velocity is given in the form of a stationary Gaussian random process with the von Karman power spectral density. The wing structure is modeled by a classical beam considering bending and torsional deformations. An unsteady vortex-lattice method is applied to estimate the aerodynamic pressure distribution on the wing surface. Initially, the trim condition is obtained, then structural dynamic responses are computed. The numerical solution of the wing structure's responses to a random turbulence profile is used as a training data for the ANN. The current ANN is a three-layer network with the output fed back to the input layer through delays. The results from this study have validated the proposed low-cost ANN model for the predictions of dynamic responses of wing structures due to atmospheric turbulence. The accuracy of the predicted results by the ANN was discussed. The paper indicated that predictions for the bending moments are more accurate than those for the torsional moments of the wing structure.

• Journal of Power System Engineering
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• v.7 no.2
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• pp.29-35
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• 2003

The monitoring and diagnostics of the rotating machinery have been received considerable attention for many years. The objectives are to classify the machinery condition and to find out the cause of abnormal condition. This paper describes a classification method of diagnosing the small reciprocating compressor for refrigerators using the artificial neural network and the wavelet transform. In order to extract salient features, the wavelet transform are used from primary noise signals. Since the wavelet transform decomposes raw time-waveform signals into two respective parts in the time space and frequency domain, more and better features can be obtained easier than time-waveform analysis. In the training phase for classification, self-organizing feature map(SOFM) and learning vector quantization(LVQ) are applied, and the accuracies of them ate compared with each other. This paper is focused on the development of an advanced signal classifier to automatize the vibration signal pattern recognition. This method is verified by small reciprocating compressors, for refrigerator and normal and abnormal conditions are classified with high flexibility and reliability.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.102-106
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• 2008

Forensic Marking is the technology that enables the service providers (SP) to identify the illegal digital contents distributors by first inserting markings (data indicating the user information and playback time) in realtime into the digital contents at time of playback of digital contents, and then later by extracting inserted markings from the contents which are illegally captured from the multimedia device such as IPTV STBs and distributed over the Internet. Digital Rights Management (DRM), which is a very popular content protection technology, has the security hole that can be vulnerable because the encrypted digital contents are transformed into their original plaintext forms after the decrypting process on the STBs. Therefore Forensic Marking (FM) has now become a companion content protection solution to DRM. This article describes a new way of tracking up to 4 illegal content users in FM implementation using the blue-difference chroma component of YCbCr color space. This FM technology has many advantages like fast processing time and easy portability to STB devices compared to that of the traditional watermarking processing in the frequency domain.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.796-801
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• 2000

The monitoring and diagnostics of the rotating machinery have been received considerable attention for many years. The objectives are to classify the machinery condition and to find out the cause of abnormal condition. This paper describes a signal classification method for diagnosing the rotating machinery using the artificial neural network and the wavelet transform. In order to extract salient features, the wavelet transform are used from primary noise signals. Since the wavelet transform decomposes raw time-waveform signals into two respective parts in the time space and frequency domain, more and better features can be obtained easier than time-waveform analysis. In the training phase for classification, self-organizing feature map(SOFM) and learning vector quantization(LVQ) are applied, and the accuracies of them are compared with each other. This paper is focused on the development of an advanced signal classifier to automatise the vibration signal pattern recognition. This method is verified by small reciprocating compressors, for refrigerator and normal and abnormal conditions are classified with high flexibility and reliability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2473-2489
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• 2022

Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

• Journal of Information Processing Systems
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• v.20 no.4
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• pp.491-500
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• 2024

In hopes of resolving the issue of poor quality of information input for teaching spoken English online, the study creates an English teaching assistance model based on a recognition algorithm named dynamic time warping (DTW) and relies on automated voice recognition technology. In hopes of improving the algorithm's efficiency, the study modifies the speech signal's time-domain properties during the pre-processing stage and enhances the algorithm's performance in terms of computational effort and storage space. Finally, a simulation experiment is employed to evaluate the model application's efficacy. The study's revised DTW model, which achieves recognition rates of above 95% for all phonetic symbols and tops the list for cloudy consonant recognition with rates of 98.5%, 98.8%, and 98.7% throughout the three tests, respectively, is demonstrated by the study's findings. The enhanced model for DTW voice recognition also presents higher efficiency and requires less time for training and testing. The DTW model's KS value, which is the highest among the models analyzed in the KS value analysis, is 0.63. Among the comparative models, the model also presents the lowest curve position for both test functions. This shows that the upgraded DTW model features superior voice recognition capabilities, which could significantly improve online English education and lead to better teaching outcomes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11C
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• pp.673-681
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• 2011

In this paper, we design multiple antenna relay transmission schemes of low complexity to enhance the spatial diversity in orthogonal frequency division multiplexing (OFDM) systems. The relay scheme underlined, can provide space time block coding (STBC) of OFDM signals in the time domain without IFFT and FFT operations with much reduced complexity. In this paper, we modify the conventional low-complexity STBC-OFDM relaying scheme to be compatible to the existing OFDM systems. In addition, we extend the proposed scheme for multiple antenna relays and provide performance enhancement strategies according to the channel quality information available at the relay. The proposed scheme is shown to improve the diversity and thereby to reduce the outage probability and coded bit error rate. Therefore, the proposed scheme will be promising for service quality improvement or coverage extension based on OFDM like wireless LANs and maritime communications.