• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.58-63
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• 2015

Due to GPS signal's vulnerability of jamming attack, various enhancement techniques are needed. Among variety of techniques, we focused on GPS receiver's anti-jamming techniques. There are many anti-jamming methods at GPS receivers which include filtering methods in time domain, frequency domain and space domain. However, these methods are ineffective to signals, which include both jamming and noise. To solve the problem, this paper proposes a jamming separation scheme by using a BSS method in a jamming environment. As separated GPS signals include noise after the jamming separation method, it is difficult to receive accurate GPS signals. For this reason, this paper also proposes a wavelet de-noising method to effectively eliminate noise. Experimental results of this paper are based on a real field test data of an integrated GPS/QZSS/Wi-Fi positioning system. At the end, the simulation result demonstrates its superiority by showing improved positioning accuracy.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.56-63
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• 2009

Nowdays, Most of Internet Contents delivered as a compressed file. It gives many advantages like deduction of communication bandwidth and transmission time etc. In case of JPEG Compression, Quantization is the most important procedure which accomplish the compression. In general signal processing, Quantization is the process which converts continuous analog signal to discrete digital signal. As you known already, Quantization over JPEG compression is to reduce magnitude of pixel value in spatial domain or coefficient in frequency domain. A lot of Data Hiding algorithms also developed to applicable for those compressed files. In this paper, we are going to unveil the influence of quantization table which used in the process of JPEG compression. Even thought most of algorithm modify frequency coefficients with considering image quality, they are ignoring the influence of quantization factor corresponding with the modified frequency coefficient. If existing algorithm adapt this result, they can easily evaluate their performances.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.4
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• pp.386-392
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• 2009

This paper reports on the research which investigates acoustic signals acquired in progressive compressing, hole blanking, shearing and burr compacting process. The work piece is the head pin of the electric connector, whose raw material is the preformed steel bar. An acoustic sensor was set on the bed of hydraulic press. Because the acquired signals include the dynamic characteristics generated for all the processes, it is required to investigate signal characteristics corresponding to unit process. The corresponding dynamic characteristics to the respective process were first studied by analyzing the signals respectively acquired from compressing, blanking and compacting process. The combined signals were then periodically analyzed from the grinding to the grinding in the sound frequency domain and in the ultrasonic wave. The frequency of around 9 kHz in the sound frequency domain was much correlated to the tool wear. The characteristic frequency in the acoustic emission domain between 100 kHz and 500 kHz was not only clearly observed right after tool grinding but its amplitude was also related to the wear. The frequency amplitudes of 160 kHz and 320 kHz were big enough to be classified by the noise. The noise amplitudes are getting bigger, and their energy was much bigger as coming to the next regrinding. The signal analysis was based on the real time data and its frequency spectrum by Fourier Transform. As a result, the acousto-ultrasonic signals were much related to the tool wear progression.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.59-73
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• 2009

Keyword extraction is an important and essential technique for text mining applications such as information retrieval, text categorization, summarization and topic detection. A set of keywords extracted from a large-scale electronic document data are used for significant features for text mining algorithms and they contribute to improve the performance of document browsing, topic detection, and automated text classification. This paper presents a keyword extraction technique that can be used to detect topics for each news domain from a large document collection of internet news portal sites. Basically, we have used six variants of traditional TF-IDF weighting model. On top of the TF-IDF model, we propose a word filtering technique called 'cross-domain comparison filtering'. To prove effectiveness of our method, we have analyzed usefulness of keywords extracted from Korean news articles and have presented changes of the keywords over time of each news domain.

• Proceedings of the Microbiological Society of Korea Conference
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• 2002.10a
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• pp.68-72
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• 2002

While the biosynthetic gene cluster encoding the pigmented antibiotic actinorhodin is present in the two closely related bacterial species, Streptomyces lividans and Streptomyces coelicolor, it normally is expressed only in S. coelicolor---generating the deep blue colonies responsible for the S. coelicolor name. However, multiple copies of the afsR2 gene, which activates actinorhodin synthesis, result in the ability of S. lividansto also synthesize large amounts of actinorhodin. Here we report that the phenotypic property that historicially distinguishes these two Streptomycesspecies is determined conditionally by the carbon source used for culture. Whereas growth on glucose repressed actinorhodin production in S. lividans, culture on solid media containing glycerol as the sole carbon source dramatically increased the expression of afsR2 mRNA---leading to extensive actinorhodin synthesis by S. lividansand obliterating its phenotypic distinction from S. coelicolor. afsR2 transcription under these conditions was developmentally regulated, rising sharply at the time of aerial mycelium formation and coinciding temporally with the onset of actinorhodin production. Our results, which identify media-dependent parallel pathways that regulate actinorhodin synthesis in S. lividans, demonstrate carbon source control of actinorhodin production through the regulation of afsR2 mRNA synthesis. The nucleotide sequences of afsR2 revealed two putative important domains; the domain containing direct repeats in the middle and the domain homologous to sigma factor sequence in the C-terminal end. In this work, we constructed various sized afsR2-derivatives and compared the actinorhodin stimulating effects in S. lividans TK21. The experimental data indicate that the domain homologous to sigma factor sequence in the C-terminal end of afsR2 plays a critical role as an antibiotic stimulating function. In addition, we also observed that the single copy integration of afsR2 regulatory gene into S. lividans TK21 chromosome significantly activates antibiotic overproduction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10A
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• pp.1471-1479
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• 1999

This paper presents an adaptive beamforming algorithm for an MC-CDMA system with an adaptive array antenna. By employing an antenna array at the receiver of an MC-CDMA system, the performance of an MC-CDMA system, which is known to be effective for high data rate transmission due to its robustness to multipath fading and its simplicity for using a simple one-tap equalizer, is shown to be significantly improved. The proposed algorithm for adaptive beanforming in an MC-CDMA system is derived by (1) calculating the error signals between the pilot symbols of desired user and the received pilot signals in frequency domain, (2) transforming the frequency-domain error signals into time-domain error signals, (3) updating the filter coefficients of the adaptive beamformer in the direction of minimizing the MSE. Convergence behavior and performance improvement of the proposed approach are demonstrated through computer simulation by applying it to the conventional MC-CDMA system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.19-26
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• 2006

In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor (EHD) is time consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by the only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

• Smart Structures and Systems
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• v.16 no.2
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.48-55
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• 2020

Recently, a study of prognosis and health management (PHM) was conducted to diagnose failure and predict the life of air craft engine parts using sensor data. PHM is a framework that provides individualized solutions for managing system health. This study predicted the remaining useful life (RUL) of aeroengine using degradation data collected by sensors provided by the IEEE 2008 PHM Conference Challenge. There are 218 engine sensor data that has initial wear and production deviations. It was difficult to determine the characteristics of the engine parts since the system and domain-specific information was not provided. Each engine has a different cycle, making it difficult to use time series models. Therefore, this analysis was performed using machine learning algorithms rather than statistical time series models. The machine learning algorithms used were a random forest, gradient boost tree analysis and XG boost. A sliding window was applied to develop RUL predictions. We compared model performance before and after applying the sliding window, and proposed a data preprocessing method to develop RUL predictions. The model was evaluated by R-square scores and root mean squares error (RMSE). It was shown that the XG boost model of the random split method using the sliding window preprocessing approach has the best predictive performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.3
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• pp.179-196
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• 1986

In this paper, the peformance of a statistical packet voice/data multiplexer is studied. In ths study we assume that in the packet voice/data multiplexer two separate finite queues are used for voice and data traffics, and that voice traffic gets priority over data. For the performance analysis we divide the output link of the multiplexer into a sequence of time slots. The voice signal is modeled as an (M+1) - state Markov process, M being the packet generation period in slots. As for the data traffic, it is modeled by a simple Poisson process. In our discrete time domain analysis, the queueing behavior of voice traffic is little affected by the data traffic since voice signal has priority over data. Therefore, we first analyze the queueing behavior of voice traffic, and then using the result, we study the queueing behavior of data traffic. For the packet voice multiplexer, both inpur state and voice buffer occupancy are formulated by a two-dimensional Markov chain. For the integrated voice/data multiplexer we use a three-dimensional Markov chain that represents the input voice state and the buffer occupancies of voice and data. With these models, the numerical results for the performance have been obtained by the Gauss-Seidel iteration method. The analytical results have been verified by computer simylation. From the results we have found that there exist tradeoffs among the number of voice users, output link capacity, voic queue size and overflow probability for the voice traffic, and also exist tradeoffs among traffic load, data queue size and oveflow probability for the data traffic. Also, there exists a tradeoff between the performance of voice and data traffics for given inpur traffics and link capacity. In addition, it has been found that the average queueing delay of data traffic is longer than the maximum buffer size, when the gain of time assignment speech interpolation(TASI) is more than two and the number of voice users is small.