• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.220-226
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• 2000

A novel audio watermark algorithm, the Modified Patchwork Algorithm, is applied to the speech to show that it is effective for digital broadcasting systems. Digital broadcasting system does not separate speech from audio data. However. speech data is very important especially for educational broadcasting. Speech can carry more information than video data. Thus, intellectual property management and protection for speech data is urgent. This paper addresses the technical issues, speech watermark algorithm, and its robustness against malicious attacks.

• ETRI Journal
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• v.28 no.5
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• pp.664-667
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• 2006

We propose an efficient audio transcoding algorithm that can convert audio streams from terrestrial digital television broadcasting service stations to those for terrestrial digital multimedia broadcasting hand-held receivers. The proposed algorithm avoids the complicated psychoacoustic analysis by calculating the scalefactors of the bit-sliced arithmetic coding encoder directly from the signal-to-noise ratio parameters of the AC-3 decoder. The bit-allocation process is also simplified by cascading the nested distortion control loop. Through subjective evaluation, it is shown that the proposed algorithm provides comparable audio quality to tandem coding but it requires much smaller complexity.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.475-478
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• 1998

The matrix hypercube MH(2,n) is the interconnection network which improves the network cost of the hypercube. In this paper, we propose an algorithm for one-to-all broadcasting in the matrix hypercube MH(2,n). The algorithm can broadcast a message to 22n nodes in O(n) time. The algorithm uses the rich structure of the matrix hypercubes and works by recursively partitioning the original matrix hypercubes into smaller matrix hypercubes.

• ETRI Journal
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• v.26 no.1
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• pp.53-56
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• 2004

In this letter, we propose a novel design scheme for an optimal non-uniform planar array geometry in view of maximum side-lobe reduction. This is implemented by a thinned array using a genetic algorithm. We show that the proposed method can maintain a low side-lobe level without pattern distortion during beam steering.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.12
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• pp.716-722
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• 2005

In this paper, we propose the audio watermarking algorithm based on the critical band of HAS(human auditory system) without audibly affecting the quality of the watermarked audio and implement the detecting algorithm on the BSS(broadcast synchronizing system) for testing the proposed algorithm. According to the audio quality test, the SNR(signal to noise ratio) of the watermarked audio objectively is 66dB above. In the robustness test, the proposed algorithm can detect the watermark more than $90\%$ from various compression(MP3, AAC), A/D and D/A conversions, sampling rate conversions and especially asynchronizing attacks. The BSS automatically switches the programs between the key station and the local station in broadcasting system. The result of reliability test of implemented system by using the real broadcasting audio has no false positive error during 30 days. Because of detecting once processing per 0.5 second, we can judge that the false positive error does not occur.

• ETRI Journal
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• v.32 no.6
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• pp.901-910
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• 2010

As a supplement to X-ray mammography, microwave imaging is a new and promising technique for breast cancer detection. Through solving the nonlinear inverse scattering problem, microwave tomography (MT) creates images from measured signals using antennas. In this paper, we describe a developed MT system and an iterative Gauss-Newton algorithm. At each iteration, this algorithm determines the updated values by solving the set of normal equations using Tikhonov regularization. Some examples of successful image reconstruction are presented.

• Journal of electromagnetic engineering and science
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• v.3 no.1
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• pp.17-21
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• 2003

In this paper, we design an optimal planar array geometry for maximum side-lobe reduction. The concept of thinned array is applied to obtain an optimal two dimensional(2-D) planar array structure. First, a 2-D rectangular array with uniform spacing is used as an initial planar array structure. Next, we modify the initial planar array geometry with the aid of thinned array theory in order to reduce the maximum side-lobe level. This is implemented by a genetic algorithm under some constraint, minimizing the maximum side-lobe level of the 2-D planar array. It is shown that the optimized planar array structure can achieve low side-lobe level without optimizing the excitations of the array antennas.

• Journal of Broadcast Engineering
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• v.12 no.3
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• pp.266-277
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• 2007

Recently, Transmitter Identification(TxID) technology has been issued as a technology of ATSC DTV. ATSC DTV networks are comprised of a plurality of transmitters, broadcasting the same signal sing one frequency network(SFN) connected to EDOCR. In this single frequency network, TxID technology has been recognized as a technology in the ATSC DTV system since it enables the broadcast authorities and classify multiple transmitters. However, conventional TxID uses extremely long spreading sequence to identifying transmitters, so it increases H/W complexity and registers. Thus, to solve those hardware problems, we propose an efficient signal processing technology using decimation algorithm. Furthermore, we certified the availability of the proposed algorithm via various simulations.

• Journal of Internet Computing and Services
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• v.8 no.4
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• pp.71-79
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• 2007

The communicative behaviors in Wireless Sensor Networks(WSNs) can be characterized by two different types: routing and broadcasting. The broadcasting is used for effective route discoveries and packet delivery. However, broadcasting shorten the network lifetime due to the energy overconsumption by redundant transmissions. In this paper, we proposed a algorithm that remove redundant forward nodes based on Dominant Pruning method using 2-hop neighbors knowledge. Simulation results show that the proposed algorithm appears superior performance in respect of the number of forward nodes and the network lifetime.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.321-328
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• 2024

This paper designs a disease prediction algorithm to diagnose migraine among the types of diseases in advance by learning algorithms using machine learning-based time series analysis. This study utilizes patient data statistics, such as electroencephalogram activity, to design a prediction algorithm to determine the onset signals of migraine symptoms, so that patients can efficiently predict and manage their disease. The results of the study evaluate how accurate the proposed prediction algorithm is in predicting migraine and how quickly it can predict the onset of migraine for disease prevention purposes. In this paper, a machine learning algorithm is used to analyze time series of data indicators used for migraine identification. We designed an algorithm that can efficiently predict and manage patients' diseases by quickly determining the onset signaling symptoms of disease development using existing patient data as input. The experimental results show that the proposed prediction algorithm can accurately predict the occurrence of migraine using machine learning algorithms.