• ETRI Journal
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• v.34 no.6
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• pp.958-961
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• 2012

In this letter, we present a new algorithm for the harmonic and percussive separation of jazz music. Using a short-time Fourier transform and nonnegative matrix factorization, the signal is decomposed into rank components. Each component is then split into harmonic and percussive parts using masks calculated based on their tonalities. Finally, the harmonic and percussive parts are separated after applying the masks and a summation. We evaluate the algorithm based on real audio examples using both objective and subjective assessments. The proposed algorithm performs well for the separation of harmonic and percussive parts of jazz excerpts.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.32-38
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• 2020

The deployment of geographically distributed wireless sensors has greatly elevated the capability of monitoring structural health in social-overhead capital (SOC) public infrastructures. This paper deals with the utilization of a distributed mobility management (DMM) approach for the deployment of wireless sensing devices in a structural health monitoring system (SHM). Then, a wireless sensing mechanism utilizing low-energy adaptive clustering hierarchy (LEACH)-based clustering algorithm for smart sensors has been analyzed to support the seamless data transmission of structural health information which is essentially important to guarantee public safety. The clustering of smart sensors will be able to provide real-time monitoring of structural health and a filtering algorithm to boost the transmission of critical information over heterogeneous wireless and mobile networks.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1645-1654
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• 2007

In this paper, we study the problem of load balancing routing in clustered-based wireless mesh network in order to enhance the overall network throughput. We first address the problems of cluster allocation in wireless mesh network to achieve load-balancing state. Due to the complexity of the problem, we proposed a simplified algorithm using gradient load-balancing model. This method searches for a localized optimal solution of cluster allocation instead of solving the optimal solution for overall network. To support for load-balancing algorithm and reduce complexity of topology control, we also introduce limited broadcasting between two clusters. This mechanism maintain shortest path between two nodes in adjacent clusters while minimizing the topology broadcasting complexity. The simulation experiments demonstrate that our proposed model achieve performance improvement in terms of network throughput in comparison with other clustering methods.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.50-64
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• 2018

This paper describes a visual object detection approach utilizing ensemble based machine learning. Object detection methods employing 1D features have the benefit of fast calculation speed. However, for real image with complex background, detection accuracy and performance are degraded. In this paper, we propose an ensemble learning algorithm that combines a 1D feature classifier and 2D DNF (Disjunctive Normal Form) classifier to improve the object detection performance in a single input image. Also, to improve the computing efficiency and accuracy, we propose a feature selecting method to reduce the computing time and ensemble algorithm by combining the 1D features and 2D DNF features. In the verification experiments, we selected the Haar-like feature as the 1D image descriptor, and demonstrated the performance of the algorithm on a few datasets such as face and vehicle.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.70-74
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• 2018

In order to ensure the flow of goods available and more flexible, reduce labor costs, many factories and industrial zones around the world are gradually moving to use automated solutions. One of them is to use Automated guided vehicles (AGV). Currently, there are a line tracing method as an AGV operating method, and a method of estimating the current position of the AGV and matching with a factory map and knowing the moving direction of the AGV. In this paper, we propose ceiling Light and guided line based moving direction estimation algorithm using multi-camera on the AGV in smart factory that can operate stable AGV by compensating the disadvantages of existing AGV operation method. The proposed algorithm is able to estimate its position and direction using a general - purpose camera instead of a sensor. Based on this, it can correct its movement error and estimate its own movement path.

• International journal of advanced smart convergence
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• v.7 no.2
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• pp.67-72
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• 2018

On the internal based search, the big data inference, which is failed in the president's election in the United States of America in 2016, is failed, because the prediction method is used on the base of the searching numerical value of a candidate for the presidency. Also the Flu Trend service is opened by the Google in 2008. But the Google was embarrassed for the fame's failure for the killing flu prediction system in 2011 and the prediction of presidential election in 2016. In this paper, using the virtual vote algorithm for virtual election and data mining method, the election prediction algorithm is proposed and unpacked. And also the WEKA DB is unpacked. Especially in this paper, using the K means algorithm and XEDOS tools, the prediction of election results is unpacked efficiently. Also using the analysis of the WEKA DB, the smart election prediction system is proposed in this paper.

• ETRI Journal
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• v.29 no.1
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• pp.95-98
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• 2007

A low-profile phased array antenna with a low sidelobe was designed and fabricated using a genetic algorithm (GA). The subarray distances were optimized by GA with chromosomes of 78 bits, a population of 100, a crossover probability of 0.9, and a mutation probability of 0.005. The array antenna has 24 subarrays in 14 rows, and is designed as a mobile terminal for Ku-band satellite communication. The sidelobe level was suppressed by 6.5 dB after optimization, compared to the equal spacing between subarrays. The sidelobe level was verified from the far-field pattern measurement by using the fabricated array antenna with optimized distance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1777-1786
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• 1996

This paper describes theories and implementation techniques of a digital high-definition television(HDTV) modem based on 32-QAM for terrestrial broadcasting. We proposed a digital demodulation scheme and a symbol timing recovery structure based on the band edge component maximization(BECM) method. The adaptive equalizer has 256 complex taps to remove the multipath of delays ranging from -2.mu.s~+24.mu.s with a new T/2-spaced blind equalization algorithm. computer simulation results reveal that the proposed algorithm outperforms other conventional blind equalization algorithm a digital HDTV modem with 4.91MHz symobol rate is implemented by utilizing the proposed algorithms. All processings for modem operations such as demodulation, estimation of symbol timing phase error, adaptive equalization, and carrier recovery except IF signal processing and sampling phase control part of the AD converter are done in digital domain. Especially, the carrier recovery loop can track a carrier offset of upto .+-.350KHz.

• ETRI Journal
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• v.26 no.5
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• pp.501-504
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• 2004

This paper presents a simple gain/phase blind compensation algorithm with an automatic gain control (AGC) function for the adoption of the AGC function and compensation for gain/phase imbalances in quadrature phase shift keying (QPSK) direct conversion receivers (DCRs). The AGC function is interactively operated with the compensation algorithm for gain/phase imbalances. By detecting the gain sum and difference values between the I-channel and Q-channel, the combined AGC and gain imbalance compensation algorithm provides a simpler DCR architecture.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.165-170
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• 2011

The Pfair scheduling algorithm, which is an optimal algorithm in the hard real-time multiprocessor environments, is based on the fixed quantum size. Recently, several methods that can determine the optimal quantum dynamically are developed in the mode change environments. These methods are based on the reach function and in many cases, we have to do the sequential search to find the optimal quantum. In this paper, we propose a new scheduling method, based on the improved reach function, that can determine the optimal quantum more quickly.