• Current Optics and Photonics
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• v.2 no.2
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• pp.134-139
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• 2018

A novel approach for frequency-tripling vector signal generation via balanced detection without precoding and optical filter is proposed. The scheme is mainly utilizing an integrated dual-polarization quadrature phase shift keying (DPQPSK) modulator. In the DPQPSK modulator, one QPSK modulator is driven by an RF signal to generate high-order optical sidebands, while the other QPSK modulator is modulated by I/Q data streams to produce baseband vector signal as an optical carrier. After that, a frequency-tripling 16-quadrature-amplitude-modulation (16QAM) vector millimeter-wave (mm-wave) signal can be obtained by balanced detection. The proposed scheme can reduce the complexity of transmitter digital signal processing. The results show that, a 4 Gbaud baseband 16QAM vector signal can be generated at 30 GHz by frequency-tripling. After 10 km single-mode fiber (SMF) transmission, the constellation and eye diagrams of the generated vector signal perform well and a bit-error-rate (BER) below than 1e-3 can be achieved.

• Proceedings of the Optical Society of Korea Conference
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• 2006.07a
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• pp.381-382
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• 2006

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.9-11
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• 2022

Community detection is a hot topic in social network analysis, and many existing studies use graph theory analysis methods to detect communities. This paper focuses on detecting absolute fair maximal balanced cliques in signed attributed social networks, which can satisfy ensuring the fairness of complex networks and break the bottleneck of the "information cocoon".

• Journal of Digital Convergence
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• v.20 no.2
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• pp.241-250
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• 2022

Due to the COVID-19 pandemic, with increased 'untact' services and with unstable household economy, the bike insurance fraud is expected to surge. Moreover, the fraud methodology gets complicated. However, the fraud detection model for bike insurance is absent. we deal with the issue of skewed class distribution and reflect the criterion of fraud detection expert. We utilize a balanced random-forest algorithm to develop an efficient bike insurance fraud detection model. As a result, while the predictive performance of balanced random-forest model is superior than it of non-balanced model. There is no significant difference between the variables used by the experts and the confirmatory models. The important variables to detect frauds are turned out to be age and gender of driver, correspondence between insured and driver, the amount of self-repairing claim, and the amount of bodily injury liability.

• Journal of the Optical Society of Korea
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• v.20 no.2
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• pp.223-227
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• 2016

The impact of optical receiver configuration on in-band crosstalk-induced penalty has been investigated in both theoretical and experimental analyses, for differential phase-shift keying (DPSK) and differential quadrature phase-shift keying (DQPSK) signals. Previously it has been shown that DPSK signals are ~6 dB more tolerant to in-band crosstalk than on-off keying (OOK) signals. However, we find that the tolerance difference between the two signals is reduced to ~3 dB when the decision threshold of the receiver is optimized to minimize the bit-error rate for each signal. Then we derive simple equations for the in-band crosstalk-induced penalty in DPSK and DQPSK signals with two different optical receiver configurations: balanced and single-ended direct-detection receivers. We confirm that the penalties obtained from our simple equations agree well with the measured results.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.200-214
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• 2024

Amid the flood of data, social network analysis is beneficial in searching for its hidden context and verifying several pieces of information. This can be used for detecting the spread model of infectious diseases, methods of preventing infectious diseases, mining of small groups and so forth. In addition, community detection is the most studied topic in social network analysis using graph analysis methods. The objective of this study is to examine signed attributed social networks and identify the maximal balanced cliques that are both absolute and fair. In the same vein, the purpose is to ensure fairness in complex networks, overcome the "information cocoon" bottleneck, and reduce the occurrence of "group polarization" in social networks. Meanwhile, an empirical study is presented in the experimental section, which uses the personal information of 77 employees of a research company and the trust relationships at the professional level between employees to mine some small groups with the possibility of "group polarization." Finally, the study provides suggestions for managers of the company to align and group new work teams in an organization.

• Korean Journal of Optics and Photonics
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• v.11 no.6
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• pp.441-446
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• 2000

Wigner functions and density matrices are computer simulated for various quantum mechanical states of light. Wigner function and density matrices are evaluated by filtered back projection which includes inverse Radon transform from the distribution function of the photocurrents, which are calculated in the balanced homodyne detection scheme. The density matrix is also directly obtained by using the pattern function from the simulated phase independent photocurrent distribution function. ction.

• Proceedings of the Optical Society of Korea Conference
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• 1990.02a
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• pp.242-247
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• 1990

By self-homodyne method we measured the relative phase fluctuation of a light wave. Balanced detection system can eliminate local oscillator excess noise and multiport detection makes it possible ot measure the phase change of the signal beam. Deriving the SB(Signal Beam) and the LO(Local Oscillator) from the same laser source, we find the SB maintain constant phase relative to that of the LO. We have introduced a phase fluctuation in the SB by modulating the beam path of the SB. The measured phase fluctuation agreed well with the predicted one, thereby we confirmed the reliability of our system.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.29-32
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• 2003

This paper proposes an automatic pronunciation correction system which provides users with correction guidelines for each pronunciation error. For this purpose, we develop an HMM speech recognizer which automatically classifies pronunciation errors when Korean speaks foreign language. And, we collect speech database of native and nonnative speakers using phonetically balanced word lists. We perform analysis of mispronunciation types from the experiment of automatic mispronunciation detection using speech recognizer.

• Journal of Korea Multimedia Society
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• v.22 no.4
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• pp.432-442
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• 2019

Most current human action recognition methods based on deep learning methods. It is required, however, a very high computational cost. In this paper, we propose an action change detection method to reduce repetitive human action recognition tasks. In reality, simple actions are often repeated and it is time consuming process to apply high cost action recognition methods on repeated actions. The proposed method decides whether action has changed. The action recognition is executed only when it has detected action change. The action change detection process is as follows. First, extract the number of non-zero pixel from motion history image and generate one-dimensional time-series data. Second, detecting action change by comparison of difference between current time trend and local extremum of time-series data and threshold. Experiments on the proposed method achieved 89% balanced accuracy on action change data and 61% reduced action recognition repetition.