• The Journal of the Acoustical Society of Korea
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• v.27 no.7
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• pp.386-393
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• 2008

This paper proposes a new approach for speech enhancement in highly nonstationary noisy environments. The spectral subtraction (SS) is a well known technique for speech enhancement in stationary noisy environments. However, in real world, noise is mostly nonstationary. The proposed method uses an auto control parameter for an adaptive threshold to work well in highly nonstationary noisy environments. Especially, the auto control parameter is affected by a linear function associated with an a posteriori signal to noise ratio (SNR) according to the increase or the decrease of the noise level. The proposed algorithm is combined with spectral subtraction (SS) using a hangover scheme (HO) for speech enhancement. The performances of the proposed method are evaluated ITU-T P.835 signal distortion (SIG) and the segment signal to-noise ratio (SNR) in various and highly nonstationary noisy environments and is superior to that of conventional spectral subtraction (SS) using a hangover (HO) and SS using a minimum statistics (MS) methods.

• The Journal of the Acoustical Society of Korea
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• v.29 no.6
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• pp.402-409
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• 2010

In this paper, we propose an efficient integrated suppression algorithm based on combined power of acoustic echo and background noise. The proposed method combines the acoustic echo and noise power by the weighting parameter derived from the decision rule based on the estimated echo to noise power ratio. Therefore, in the proposed approach, the acoustic echo and noise signal are able to be reduced through only one suppression filter based on the estimated combined power. The proposed unified structure improves the problems of the residual echo and noise resulted from the conventional unified structure where the noise suppression (NS) operation is placed after the acoustic echo suppression (AES) algorithm or vice versa. The performance of the proposed algorithm is evaluated by the objective test under various environments and yields better results compared with the conventional scheme.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.61-69
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• 2009

This paper presents an improved method measuring inter-utterance similarity in an example-based dialogue system, which searches the most similar utterance in a dialogue database to generate a response to a given user utterance. Unlike general inter-sentence similarity measures, the inter-utterance similarity measure for example-based dialogue system should consider not only word distribution but also various linguistic features, such as affirmation/negation, tense, modality, sentence type, which affects the natural conversation. However, previous approaches do not sufficiently reflect these features. This paper proposes a new utterance similarity measure by analyzing and reflecting various linguistic features to improve performance in accuracy. Also, by considering substitutability of the features, the proposed method can utilize limited number of examples. Experimental results show that the proposed method achieves 10%p improvement in accuracy compared to the previous method.

• Smart Media Journal
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• v.13 no.3
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• pp.36-44
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• 2024

Recently, large-scale artificial intelligence (AI) such as ChatGPT have been developed, and as AI is used across various industrial fields, attention is focused on AI chips (semiconductors). AI chips refer to chips designed for calculations for AI algorithms, and many companies at domestic and abroad, such as NVIDIA, Tesla, and ETRI, are developing AI chips. In this paper, we survey research trends on nine types of AI chips. Currently, many attempts have been made to improve the computational performance of most AI chips, and semiconductors for specific purposes are also being designed. In order to compare various AI semiconductors, each chip is analyzed in terms of operation unit, speed, power, and energy efficiency. We introduce currently existing optimization methodologies for AI computation. Based on this, future research directions for AI semiconductors are presented in this paper.

• Applied Chemistry for Engineering
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• v.35 no.1
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• pp.61-65
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• 2024

The effectiveness of CuSCN as a hole injection layer in large-area organic light-emitting diodes, organic solar cells, and thin-film transistors has been well demonstrated. Therefore, in this study, the surface, optical, and electrical analyses of CuSCN were carried out according to the solution process conditions in order to propose optimized film conditions. Various CuSCN solution concentrations were prepared to determine the film surface characteristics and to determine whether the film surface affects the electrical performance of the device. When the CuSCN solution concentration was low, the CuSCN film was not formed and coated in the form of islands, and when the solution concentration was increased, the CuSCN film was formed uniformly, which contributed to improving the conductivity of the device. In addition, a hole-only device was fabricated to demonstrate the role of CuSCN as a hole transport layer.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.67-74
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• 2024

As the number of coffee shops increases, many people are studying or working at coffee shops. Coffee shop operators have been required to analyze customer visits due to customer turnover and profit problems. Methods such as image analysis, QR code authentication, and Bluetooth beacon have been proposed for these statistics and analysis. However, it is difficult to use due to problems such as invasion of privacy and low accuracy. Therefore, in this study, to solve these problem and provide more accurate in-store congestion information, we propose a crowding measurement method of coffee shop using high frequency signal. There is an advantage in that a high frequency signal replaces the Bluetooth signal, and the transmission range of the signal is limited to the store, thereby increasing the accuracy of the method. To verify the performance of the proposed system, we conducted a comparative experiment with a Bluetooth based system, and as a result, the proposed method showed lower misrecognition rate. Thus, the proposed method will be an effective useful service for providing information on crowding at coffee shops and processing statistics.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.30-36
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• 2024

Recently, the Internet of Things (IoT), which has been applied to various industrial fields, is constantly evolving in the process of automation and digitization. However, in the network where IoT devices are built, research on IoT critical information-related data sharing, personal information protection, and data integrity among intermediate nodes is still being actively studied. In this study, we propose a blockchain-based IoT critical information management technique that is easy to implement without burdening the intermediate node in the network environment where IoT is built. The proposed technique allocates a random value of a random size to the IoT critical information arriving at the intermediate node and manages it to become a decentralized P2P blockchain. In addition, the proposed technique makes it easier to manage IoT critical data by creating licenses such as time limit and device limitation according to the weight condition of IoT critical information. Performance evaluation and proposed techniques have improved delay time and processing time by 7.6% and 10.1% on average compared to existing techniques.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.154-168
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• 2024

The Tunnel Boring Machine (TBM) disc cutter is subjected to wear and damage during the rock excavation process, and the worn disc cutter should be replaced on time. The manual inspection by workers is generally required to determine the disc cutter replacement. In this case, the workers are exposed to dangerous environments, and the measurements are sometimes inaccurate. In this study, we developed a technology that measures the disc cutter wear in real time. From a series of laboratory tests, a magnetic sensor was selected as the wear sensor, and the real-time disc cutter measurement system was developed integrating wireless communication modules, power supply and data processing board. In addition, the measurement system was verified in actual TBM excavation circumstances. As a result, it was confirmed that the accuracy and stability of the system.

• Journal of Drive and Control
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• v.21 no.2
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• pp.53-64
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• 2024

Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R²) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.466-475
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• 2024

Matched-Field Processing (MFP) is a model-based approach that requires accurate knowledge of the ocean environment and array geometry (e.g., array tilt) to localize underwater acoustic sources. Consequently, it is inherently sensitive to model mismatches. In contrast, the waveguide invariant-based approach (also known as array invariant) offers a simple and robust means for source-range estimation in shallow waters. This approach solely exploits the beam angles and travel times of multiple arrivals separated in the beam-time domain, requiring no modeling of the acoustic fields, unlike MFP. This paper extends the waveguide invariant-based approach to shallow water environments featuring a shallow pit, where the waveguide invariant is not defined due to the complex bathymetry. An in-depth performance analysis is conducted using experimental data and numerical simulations.