• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.477-479
• /
• 2018

This study was carried out to utilize LSTM(Long Short-Term Memory) technique which is one kind of artificial neural network. Among the 27 types of motion data released by the UTD(University of Texas at Dallas), 3-axis acceleration and angular velocity data were applied to the basic LSTM and Deep Residual Bidir-LSTM techniques to classify the behavior.

• Journal of Korean Neurosurgical Society
• /
• v.62 no.3
• /
• pp.302-312
• /
• 2019

Stereoelectroencephalography (SEEG) is an invasive technique used during the surgical management of medically refractory epilepsy. The utility of SEEG rests in its ability to survey the three-dimensional organization of the epileptogenic zone as well as nearby eloquent cortices. Once concentrated to specialized centers in Europe and Canada, the SEEG methodology has gained worldwide popularity due to its favorable morbidity profile, superior coverage of deep structures, and ability to perform multi-lobar explorations without the need for craniotomy. This rapid shift in practice represents both a challenge and an opportunity for pediatric neurosurgeons familiar with the subdural grid approach. The purpose of this review is to discuss the indications, technique, and safety of long-term SEEG monitoring in children. In addition to reviewing the conceptual and technical points of the diagnostic evaluation, attention will also be given to SEEG-based interventions (e.g., radiofrequency thermo-coagulation).

• ETRI Journal
• /
• v.35 no.5
• /
• pp.859-868
• /
• 2013

The active noise control (ANC) technique attenuates acoustic noise in a flexible and effective way. Traditional ANC design aims to minimize the residual noise energy, which is indiscriminative in the frequency domain. However, human hearing perception exhibits selective sensitivity for different frequency ranges. In this paper, we aim to improve the noise attenuation performance in perceptual perspective by incorporating noise weighting into ANC design. We also introduce psychoacoustic analysis to evaluate the sound quality of the residual noise by using a predictive pleasantness model, which combines four psychoacoustic parameters: loudness, sharpness, roughness, and tonality. Simulations on synthetic random noise and realistic noise show that our method improves the sound quality and that ITU-R 468 noise weighting even performs better than A-weighting.

• ETRI Journal
• /
• v.32 no.6
• /
• pp.921-931
• /
• 2010

It has been shown that the principal subspace-based multichannel Wiener filter (MWF) provides better performance than the conventional MWF for suppressing interference in the case of a single target source. It can efficiently estimate the target speech component in the principal subspace which estimates the acoustic transfer function up to a scaling factor. However, as the input signal-to-interference ratio (SIR) becomes lower, larger errors are incurred in the estimation of the acoustic transfer function by the principal subspace method, degrading the performance in interference suppression. In order to alleviate this problem, a principal subspace modification method was proposed in previous work. The principal subspace modification reduces the estimation error of the acoustic transfer function vector at low SIRs. In this work, a frequency-band dependent interpolation technique is further employed for the principal subspace modification. The speech recognition test is also conducted using the Sphinx-4 system and demonstrates the practical usefulness of the proposed method as a front processing for the speech recognizer in a distant-talking and interferer-present environment.

• Journal of Korean Neurosurgical Society
• /
• v.64 no.5
• /
• pp.740-750
• /
• 2021

Objective : Retrograde suction decompression (RSD) is an adjuvant technique used for the microsurgical treatment of large and giant internal carotid artery (ICA) aneurysms. In this study, we analyzed the efficacy and safety of the RSD technique for the treatment of large and giant ICA aneurysms relative to other conventional microsurgical techniques. Methods : The aneurysms were classified into two groups depending on whether the RSD method was used (21 in the RSD group vs. 43 in the non-RSD group). Baseline characteristics, details of the surgical procedure, angiographic outcomes, clinical outcomes, and procedure-related complications of each group were reviewed retrospectively. Results : There was no significant difference in the rates of complete neck-clipping between the RSD (57.1%) and non-RSD (67.4%) groups. Similarly, there was no difference in the rates of good clinical outcomes (modified Rankin Scale score, 0-2) between the RSD (85.7%) and non-RSD (81.4%) groups. Considering the initial functional status, 19 of 21 (90.5%) patients in the RSD group and 35 of 43 (81.4%) patients in the non-RSD group showed an improvement or no change in functional status, which did not reach statistical significance. Conclusion : In this study, the microsurgical treatment of large and giant intracranial ICA aneurysms using the RSD technique obtained competitive angiographic and clinical outcomes without increasing the risk of procedure-related complications. The RSD technique might be a useful technical option for the microsurgical treatment of large and giant intracranial ICA aneurysms.

• Structural Monitoring and Maintenance
• /
• v.6 no.2
• /
• pp.125-145
• /
• 2019

Bridge scour is one of the predominant causes of bridge failure. Current climate deterioration leads to increase of flooding frequency and severity and thus poses a higher risk of bridge scour failure than before. Recent studies have explored extensively the vibration-based scour monitoring technique by analyzing the structural modal properties before and after damage. However, the state-of-art of this area lacks a systematic approach with sufficient robustness and credibility for practical decision making. This paper attempts to develop a data-driven methodology for bridge scour monitoring using support vector machines. This study extracts features from the bridge dynamic responses based on a generic sensitivity study on the bridge's modal properties and selects the features that are significantly contributive to bridge scour detection. Results indicate that the proposed data-driven method can quantify the bridge scour damage with satisfactory accuracy for most cases. This paper provides an alternative methodology for bridge scour evaluation using the machine learning method. It has the potential to be practically applied for bridge safety assessment in case that scour happens.