• Journal of Environmental Health Sciences
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• v.16 no.2
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• pp.11-20
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• 1990

To investigate ionic characteristics of acid rain by the succeeding rainfall. bulk precipitation was collected every each 5mm rainfall from march to october 1990 at Dae Jeon area. pH, sulfate nitrate, chloride, ammonium ion was measured and analyzed. The result was as follows: 1. The weighted average pH of rain was 5.1$\pm$ 0.72(4.15~7.6) and rain pH less than 5.5 was appeared 51.3% 2. Average ion concentrations of sulfate, nitrate, chloride and ammonium ion was 125.12 $\mu$eq/l, 62.38 $\mu$eq/l, 31.95 $\mu$eq/l, 66.6 $\mu$eq/l and rates of each anions was 57%, 28.4%, 14.6% and rate of sulfate by nitrate was 2 times. 3. There is no correlations time interval of rainfall and Ion concentration change. 4. From initial to 15mm rainfall, each ion concentrations were decreased. and average concentration of pH, SO$^{-2}_{4}$, Cl ion concentration was increased in the succeeding rainfall 5. Only sulfate ion was correlated by the simple regression analysis with pH except NO$^{-}_{3}$, Cl$^{-}$ and NH$_{4}^{+}$ Cl$^{-}$ correlation coefficient was very high at the multiple regression analysis with pH. 6. Simple & multiple correlation coefficient among anions and NH$^{+}_{4}$ was very high especially N$^{+}_{4}$ and SO$^{2-}_{4}$ at simple regression analysis and SO$^{-2}_{4}$ and NO$_{3}^{-}$, Cl$^{-}$, NH$_{4}^{-}$ at multiple regression analysis.

• Journal of Korea Multimedia Society
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• v.16 no.5
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• pp.549-557
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• 2013

This paper proposes a method using the multiple threshold regions in the image preprocessing procedure for container identifier recognition system. The multiple threshold regions are set by considering the container image characteristics and used as the candidates for the final one, The image is transformed to black and white images using these threshold regions, then labeling, panelling and panels merging are executed for each candidate, respectively. Finally the best threshold region is selected through this procedure and the character region can be extracted. Applying the similar method the noises are removed and the characters of identifier are segmented from the extracted region. In the experiments with 162 different images the success rates for extracting of the character region and segmenting the characters are 99.04% and 98.09%, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.467-472
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• 2005

ECG signals are recorded for diagnostic purposes in many clinical situations. Also, In order to permit good clinical interpretation, data is needed at high resolutions and sampling rates. Therefore In this paper, we designed to compression structure using multiple wavelet basis function(SWBF) and compared to single wavelet basis function(SWBF) and discrete cosine transform(DCT). For experience objectivity, Simulation was performed using the arrhythmia data with sampling frequency 360Hz, resolution lIbit at MIT-BIH database. An estimate of performance estimate evaluate the reconstruction error. Consequently compression structure using MWBF has high performance result.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.23-32
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• 2003

Since the data is collected from disparate sources in many actual data mining environments, it is common to have data values in different abstraction levels. This paper shows that such multiple abstraction levels of data can cause undesirable effects in decision tree classification. After explaining that equalizing abstraction levels by force cannot provide satisfactory solutions of this problem, it presents a method to utilize the data as it is. The proposed method accommodates the generalization/specialization relationship between data values in both of the construction and the class assignment phase of decision tree classification. The experimental results show that the proposed method reduces classification error rates significantly when multiple abstraction levels of data are involved.

• BMB Reports
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• v.51 no.1
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• pp.1-2
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• 2018

Positive selection on a new beneficial mutation generates a characteristic pattern of DNA sequence polymorphism when it reaches an intermediate allele frequency. On genome sequences of African Drosophila melanogaster, we detected such signatures of selection at 37 candidate loci and identified "sweeping haplotypes (SHs)" that are increasing or have increased rapidly in frequency due to hitchhiking. Based on geographic distribution of SH frequencies, we could infer whether selective sweeps occurred starting from de novo beneficial mutants under simple constant selective pressure. Single SHs were identified at more than half of loci. However, at many other loci, we observed multiple independent SHs, implying soft selective sweeps due to a high beneficial mutation rate or parallel evolution across space. Interestingly, SH frequencies were intermediate across multiple populations at about a quarter of the loci despite relatively low migration rates inferred between African populations. This invokes a certain form of frequency-dependent selection such as heterozygote advantage. At one locus, we observed a complex pattern of multiple independent that was compatible with recurrent frequency-dependent positive selection on new variants. In conclusion, genomic patterns of positive selection are very diverse, with equal contributions of hard and soft sweeps and a surprisingly large proportion of frequency-dependent selection in D. melanogaster populations.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.27-39
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• 2016

This paper derives and analyzes a novel block fast Fourier transform (FFT) based joint detection algorithm. The paper compares the performance and complexity of the novel block-FFT based joint detector to that of the Cholesky based joint detector and single user detection algorithms. The novel algorithm can operate at chip rate sampling, as well as higher sampling rates. For the performance/complexity analysis, the time division duplex (TDD) mode of a wideband code division multiplex access (WCDMA) is considered. The results indicate that the performance of the fast FFT based joint detector is comparable to that of the Cholesky based joint detector, and much superior to that of single user detection algorithms. On the other hand, the complexity of the fast FFT based joint detector is significantly lower than that of the Cholesky based joint detector and less than that of the single user detection algorithms. For the Cholesky based joint detector, the approximate Cholesky decomposition is applied. Moreover, the novel method can also be applied to any generic multiple-input-multiple-output (MIMO) system.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.3
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• pp.223-229
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• 2004

Recently, OFDM and STC techniques have been considered to be candidate to support multimedia services in the next generation mobile radio communications and have been developed the many communications systems in order to achieve the high data rates. In this paper, we propose the Trellis-Coded Differential Space Time Modulation-OFDM system with multiple symbol detection. The Trellis-code performs the set partition with unitary group codes. The Viterbi decoder containing new branch metrics is introduced in order to improve the bit error rate (BER) in the differential detection of the unitary differential space time modulation. Also, we describe the Viterbi algorithm in order to use this branch metrics. Our study shows that such a Viterbl decoder improves BER performance without sacrificing bandwidth and power efficiency.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.2
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• pp.105-114
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• 2000

In this paper, we propose a bandwidth-efficient channel coding scheme using the turbo trellis-coded modulation with multiple symbol detection. The turbo code can achieve good bit error rates (BER) at low SNR. That comprises two binary component codes and an interleaver. TCM codes combine modulation and coding by optimizing the euclidean distance between codewords. This can be decoded with the Viterbi or the symbol-by- symbol MAP algorithm. But we present the MAP algorithm with branch metrics of the Euclidean distance of the first phase difference as well as the Lth phase difference. The study shows that the turbo trellis-coded modulation with multiple symbol detection can improve the BER performance at the same SNR.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.14-21
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• 2005

Even though mainly statistical methods have been used in anomaly network intrusion detection, to detect various attack types, machine learning based anomaly detection was introduced. Machine learning based anomaly detection started from research applying traditional learning algorithms of artificial intelligence to intrusion detection. However, detection rates of these methods are not satisfactory. Especially, high false positive and repeated alarms about the same attack are problems. The main reason for this is that one packet is used as a basic learning unit. Most attacks consist of more than one packet. In addition, an attack does not lead to a consecutive packet stream. Therefore, with grouping of related packets, a new approach of group-based learning and detection is needed. This type of approach is similar to that of multiple-instance problems in the artificial intelligence community, which cannot clearly classify one instance, but classification of a group is possible. We suggest group generation algorithm grouping related packets, and a learning algorithm based on a unit of such group. To verify the usefulness of the suggested algorithm, 1998 DARPA data was used and the results show that our approach is quite useful.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.75-81
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• 2021

As the number of connected smart devices and applications increases explosively, the existing orthogonal multiple access (OMA) techniques have become insufficient to accommodate mobile traffic, such as artificial intelligence (AI) and the internet of things (IoT). Fortunately, non-orthogonal multiple access (NOMA) in the fifth generation (5G) mobile networks has been regarded as a promising solution, owing to increased spectral efficiency and massive connectivity. In this paper, we investigate the achievable data rate for non-orthogonal multiple access (NOMA) with negatively-correlated information sources (CIS). For this, based on the linear transformation of independent random variables (RV), we derive the closed-form expressions for the achievable data rates of NOMA with negatively-CIS. Then it is shown that the achievable data rate of the negatively-CIS NOMA increases for the stronger channel user, whereas the achievable data rate of the negatively-CIS NOMA decreases for the weaker channel user, compared to that of the positively-CIS NOMA for the stronger or weaker channel users, respectively. We also show that the sum rate of the negatively-CIS NOMA is larger than that of the positively-CIS NOMA. As a result, the negatively-CIS could be more efficient than the positively-CIS, when we transmit CIS over 5G NOMA networks.