• Korean Journal of Metals and Materials
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• v.49 no.8
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• pp.596-600
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• 2011

Thermal degradation behavior of a $WO_3-TiO_2$ monolithic catalyst was investigated in terms of structural, morphological, and physico-chemical analyses. The catalyst with 4 wt.% $WO_3$ contents were prepared by a wet-impregnation method, and a durability test of the catalysts were performed in a temperature range between $400^{\circ}C$ and $800^{\circ}C$ for 3 h. An increase of thermal stress decreased the specific surface area, which was caused by grain growth and agglomeration of the catalyst particles. The phase transition from anatase to rutile occurred at around $800^{\circ}C$ and a decrease in the Brønsted acid sites was confirmed by structural analysis and physico-chemical analysis. A change in Brønsted acidity can affect to the catalytic efficiency; therefore, the thermal degradation behavior of the $WO_3-TiO_2$ catalyst could be explained by the transition to a stable rutile phase of $TiO_2$ and the decrease of specific surface area in the SCR catalyst.

• Journal of the Korea Institute of Building Construction
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• v.21 no.4
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• pp.377-386
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• 2021

In April 2019, this study was enacted as a test method for the performance of waterproof layers in an environment where complex deterioration and structural behavior are simultaneously applied, but some existing standards were implemented to point out the errors of the method that should be supplemented. Thus, in establishing standards for (tentative) adhesive waterproofing sheets, field workability and quantification of test results were studied on the structural behavior response performance test methods included as test items. In addition, the performance evaluation of adhesive-type composite waterproof sheets was conducted based on the considered contents to review improvements such as applicability as an item of standard standards and field workability related problems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.115-117
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• 2022

Whitebox encryption technique is a method of preventing exposure of encryption keys by mixing encryption key information with a software-based encryption algorithm. Whitebox encryption technique is attracting attention as a technology that replaces conventional hardware-based security encryption techniques by making it difficult to infer confidential data and keys by accessing memory with unauthorized reverse engineering analysis. However, in the encryption and decryption process, a large lookup table is used to hide computational results and encryption keys, resulting in a problem of slow encryption and increased memory size. In particular, it is difficult to apply whitebox cryptography to low-cost, low-power, and light-weight Internet of Things products due to limited memory space and battery capacity. In addition, in a network environment that requires real-time service support, the response delay time increases due to the encryption/decryption speed of the whitebox encryption, resulting in deterioration of communication efficiency. Therefore, in this paper, we analyze whether the AES-based whitebox(WBC-AES) proposed by S.Chow can satisfy the speed and memory requirements based on the experimental results.

• Journal of the Korea Institute of Building Construction
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• v.23 no.1
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• pp.11-22
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• 2023

In this work, a depth-by-depth evaluation on the deterioration of concrete is suggested by utilizing disk shaped concrete specimens. Dynamic elastic modulus of cylindrical concrete was measured using a free-free resonance column method and compared with dynamic elastic modulus of disk-shaped concrete measured by impulse excitation technique(IET) and impact resonance(IR). According to the results of the experiment, both IET and IR methods showed a smaller difference in dynamic elastic modulus with smaller deviation in data when thickness of the disk specimen was increased. This trend was more evident from dynamic elastic modulus measured by IR method compared to that measured by IET. Variation in data was also smaller with the IR result. To increase the accuracy of the data, it is recommended to use the IR method for disk specimen with a diameter of 100mm and a thickness of 25mm.

• Journal of Digestive Cancer Research
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• v.1 no.1
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• pp.29-35
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• 2013

Peritoneal carcinomatosis (PC) is defined as the dissemination of cancer cells in the peritoneal cavity resulting in deposition of malignant cells onto parietal or visceral peritoneal surfaces, and is associated with malignant ascites. In general, PC has been treated similarly to metastatic cancers of the primary tumor, but associated with unfavorable outcomes as compared to other sites of metastatic disease from the same primary tumor origin. It has been known to have the median survival of only 3-6 months with supportive care alone. PC is an intractable problem to physicians because of its poor prognosis and limited treatment options. Recent studies have reported that a combination of cytoreductive surgery and hyperthermic intraperitoneal chemotherapy improved survival in PC of colorectal cancer. This paper gives overviews of the characteristics, symptoms, prognosis, and diagnosis of PC and current treatment options on PC of stomach, colorectal, and unknown primary origin.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.123-138
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• 2023

The Fourth Industrial Revolution and sensor technology have led to increased utilization of sensor data. In our modern society, data complexity is rising, and the extraction of valuable information has become crucial with the rapid changes in information technology (IT). Recurrent neural networks (RNN) and long short-term memory (LSTM) models have shown remarkable performance in natural language processing (NLP) and time series prediction. Consequently, there is a strong expectation that models excelling in NLP will also excel in time series prediction. However, current research on Transformer models for time series prediction remains limited. Traditional RNN and LSTM models have demonstrated superior performance compared to Transformers in big data analysis. Nevertheless, with continuous advancements in Transformer models, such as GPT-2 (Generative Pre-trained Transformer 2) and ProphetNet, they have gained attention in the field of time series prediction. This study aims to evaluate the classification performance and interval prediction of remaining useful life (RUL) using an advanced Transformer model. The performance of each model will be utilized to establish a health index (HI) for cutting blades, enabling real-time monitoring of machine health. The results are expected to provide valuable insights for machine monitoring, evaluation, and management, confirming the effectiveness of advanced Transformer models in time series analysis when applied in industrial settings.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.130-135
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• 2023

Plasma-resistant ceramic (PRC) is a material used to prevent internal damage in plasma processing equipment for semiconductors and displays. The challenge is to suppress particles falling off from damaged surfaces and increase retention time in order to improve productivity and introduce the latest miniaturization process. Here, we confirmed the effect of suppressing plasma deterioration and reducing the etch rate through surface treatment of existing PRC with an initial illumination level of 200 nm. In particular, quartz glass showed a decrease in etch rate of up to 10%. Furthermore, it is believed that micro-scale secondary particles formed on the microstructure of each material grow as crystals during the fluoridation process. This is a factor that can act as a killer defect when dropped, and is an essential consideration when analyzing plasma resistance. The plasma etching suppression effect of the initial illumination is thought to be due to partial over etching at the dihedral angle of the material due to the sputtering of re-emission of Ar+-based cations. This means that plasma damage due to densification can also be interpreted in existing PRC studies. The research results are significant in that they present surface treatment conditions that can be directly applied to existing PRC for mass production and a new perspective to analyze plasma resistance in addition to simple etching rates.

• Journal of Sensor Science and Technology
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• v.33 no.1
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• pp.56-61
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• 2024

The quality of the display can be managed by effectively managing the temperature generated by the panel during use. Conventional display panels rely on an external reference resistor for temperature monitoring. However, this approach is easily affected by external factors such as temperature variations from the driving circuit and chips. These variations reduce reliability, causing complicated mounting owing to the external chip, and cannot monitor the individual pixel temperatures. However, this issue can be simply and efficiently addressed by integrating temperature sensors during the display panel manufacturing process. In this study, we fabricated and analyzed a temperature sensor integrated into an a-IGZO (amorphous indium-gallium-zinc-oxide) TFT array that was to precisely monitor temperature and prevent the deterioration of OLED display pixels. The temperature sensor was positioned on top of the oxide TFT. Simultaneously, it worked as a light shield layer, contributing to the reliability of the oxide. The characteristics of the array with integrated temperature sensors were measured and analyzed while adjusting the temperature in real-time. By integrating a temperature sensor into the TFT array, monitoring the temperature of the display became easier and more accurate. This study could contribute to managing the lifetime of the display.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.383-391
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• 2009

In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. The waveform which is stationary region of voiced speech is very correlated by pitch period. So we can estimate the SNR by correlation of near waveform after dividing a frame for each pitch. For unvoiced speech signal, vocal track characteristic is reflected by noise, so we can estimate SNR by using spectral distance between spectrum of received signal and estimated vocal track. Lastly, energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced.

• The Journal of the Acoustical Society of Korea
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• v.29 no.2
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• pp.148-153
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• 2010

In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. A Speech signal consists of Voice and Unvoiced Band in The MBE excitation model. And the energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced. We use the IMBE vocoder for the Voice or Unvoice band of segmented speech signal. Continuously we calculate the segmented SNR using that information and the energy of each band. And we estimate the SNR of continuous speech signal.