• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.750-762
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• 2019

The importance of the call center as a contact point for the enterprise is growing. However, call centers have difficulty with their operating agents due to the agents' lack of knowledge and owing to frequent agent turnover due to downturns in the business, which causes deterioration in the quality of customer service. Therefore, through an N-bank call center case study, we developed a system to reduce the burden of keeping up business knowledge and to improve customer service quality. It is a "real-time agent advisor" system that provides agents with answers to customer questions in real time by combining AI technology for speech recognition, natural language processing, and questions & answers for existing call center information systems, such as a private branch exchange (PBX) and computer telephony integration (CTI). As a result of the case study, we confirmed that the speech recognition system for real-time call analysis and the corpus construction method improves the natural speech processing performance of the query response system. Especially with name entity recognition (NER), the accuracy of the corpus learning improved by 31%. Also, after applying the agent advisor system, the positive feedback rate of agents about the answers from the agent advisor was 93.1%, which proved the system is helpful to the agents.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.69-76
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• 2020

Global warming is a very important problem as it causes rapid climate change and natural disasters. Therefore, researches related to renewable energy are being actively conducted while promoting policies such as reducing carbon dioxide emission and increasing the proportion of renewable energy. Solar power generation is being applied in urban areas like BIPV as well as existing idle areas outside the city. Therefore, in this study, precast concrete blocks developed for paving roadways capable of solar power generation were designed and constructed. For the evaluation of field applicability for 6 months, skid resistance and block settlement were measured. As a result of the experiment, it was found that skid resistance satisfies the standard of general roadway in Korea, but not the standard of highway. The skid resistance tended to decrease as time passed. In addition, the settlement of the block gradually increased slightly, but it is much smaller than the allowable settlement of the roadway. Therefore, it is necessary to establish a maintenance period and method based on the periodic measurement results in the future.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.141-148
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• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.36-44
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• 2022

Reversible data hiding techniques have been developed to hide confidential data in the image by shifting the histogram of the image. These techniques have a weakness in which the security of hidden confidential data is weak. In this paper, to solve this drawback, we propose a technique of triple encrypting confidential data using pixel value information and hiding it in the cover image. When confidential data is triple encrypted using the proposed technique and hidden in the cover image to generate a stego-image, since encryption based on pixel information is performed three times, the security of confidential data hidden by triple encryption is greatly improved. In the experiment to measure the performance of the proposed technique, even if the triple-encrypted confidential data was extracted from the stego-image, the original confidential data could not be extracted without the encryption keys. And since the image quality of the stego-image is 48.39dB or higher, it was not possible to recognize whether confidential data was hidden in the stego-image, and more than 30,487 bits of confidential data were hidden in the stego-image. The proposed technique can extract the original confidential data from the triple-encrypted confidential data hidden in the stego-image without loss, and can restore the original cover image from the stego-image without distortion. Therefore, the proposed technique can be effectively used in applications such as military, medical, digital library, where security is important and it is necessary to completely restore the original cover image.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.4
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• pp.48-56
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• 2022

Controlling the setting time of cementitious materials is one of the most important factors in securing early-age performance of concrete structures. Recently, the use of retarding admixtures, which enable the inhibition of some hydration products to control the securing time due to average temperature rise is suggested. Although various non-destructive evaluation methods have been proposed to evaluate cement hydration and hardening of cement-based materials to overcome the limitations of Vicat needle test, experimental research is still required to use the non-destructive evaluation method with added retarding admixtures. In this study, measurements of electrical resistivity and ultrasonic wave velocity in early-aged cement pastes were performed according to the addition of retarding admixture(tartaric acid). The setting time of the cement pastes was evaluated by obtained rising time of the both non-destructive measurements. As a result, the possibility of evaluating the setting delay in cement pastes was confirmed through comparative analysis with the initial and final setting times by Vicat test. In addition, X-ray diffraction results at the rising time of electrical resistivity showed a key hydration product affecting the setting delay.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.1-12
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• 2022

Traditional methods of measuring corneal ulcers were difficult to present objective basis for diagnosis because of the subjective judgment of the medical staff through photographs taken with special equipment. In this paper, we propose a method to detect the ulcer area on a pixel basis in corneal ulcer images using a semantic segmentation model. In order to solve this problem, we performed the experiment to detect the ulcer area based on the DeepLab model which has the highest performance in semantic segmentation model. For the experiment, the training and test data were selected and the backbone network of DeepLab model which set as Xception and ResNet, respectively were evaluated and compared the performances. We used Dice similarity coefficient and IoU value as an indicator to evaluate the performances. Experimental results show that when 'crop & resized' images are added to the dataset, it segment the ulcer area with an average accuracy about 93% of Dice similarity coefficient on the DeepLab model with ResNet101 as the backbone network. This study shows that the semantic segmentation model used for object detection also has an ability to make significant results when classifying objects with irregular shapes such as corneal ulcers. Ultimately, we will perform the extension of datasets and experiment with adaptive learning methods through future studies so that they can be implemented in real medical diagnosis environment.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.1-10
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• 2023

This paper proposes a method to extend Inter-Carrier Interference (ICI) canceling Orthogonal Frequency Division Multiplexing (OFDM) receivers for 5G mobile systems to spatial multiplexing 2×2 MIMO (Multiple Input Multiple Output) systems to support high-speed ground transportation services by linear motor cars traveling at 500 km/h. In Japan, linear-motor high-speed ground transportation service is scheduled to begin in 2027. To expand the coverage area of base stations, 5G mobile systems in high-speed moving trains will have multiple base station antennas transmitting the same downlink (DL) signal, forming an expanded cell size along the train rails. 5G terminals in a fast-moving train can cause the forward and backward antenna signals to be Doppler-shifted in opposite directions, so the receiver in the train may have trouble estimating the exact channel transfer function (CTF) for demodulation. A receiver in such high-speed train sees the transmission channel which is composed of multiple Doppler-shifted propagation paths. Then, a loss of sub-carrier orthogonality due to Doppler-spread channels causes ICI. The ICI Canceller is realized by the following three steps. First, using the Demodulation Reference Symbol (DMRS) pilot signals, it analyzes three parameters such as attenuation, relative delay, and Doppler-shift of each multi-path component. Secondly, based on the sets of three parameters, Channel Transfer Function (CTF) of sender sub-carrier number n to receiver sub-carrier number l is generated. In case of n≠l, the CTF corresponds to ICI factor. Thirdly, since ICI factor is obtained, by applying ICI reverse operation by Multi-Tap Equalizer, ICI canceling can be realized. ICI canceling performance has been simulated assuming severe channel condition such as 500 km/h, 8 path reverse Doppler Shift for QPSK, 16QAM, 64QAM and 256QAM modulations. In particular, 2×2MIMO QPSK and 16QAM modulation schemes, BER (Bit Error Rate) improvement was observed when the number of taps in the multi-tap equalizer was set to 31 or more taps, at a moving speed of 500 km/h and in an 8-pass reverse doppler shift environment.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.24.1-24.15
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• 2023

Background: The construction workers are vulnerable to fatigue due to high physical workload. This study aimed to investigate the relationship between overwork and heart rate in construction workers and propose a scheme to prevent overwork in advance. Methods: We measured the heart rates of construction workers at a construction site of a residential and commercial complex in Seoul from August to October 2021 and develop an index that monitors overwork in real-time. A total of 66 Korean workers participated in the study, wearing real-time heart rate monitoring equipment. The relative heart rate (RHR) was calculated using the minimum and maximum heart rates, and the maximum acceptable working time (MAWT) was estimated using RHR to calculate the workload. The overwork index (OI) was defined as the cumulative workload evaluated with the MAWT. An appropriate scenario line (PSL) was set as an index that can be compared to the OI to evaluate the degree of overwork in real-time. The excess overwork index (EOI) was evaluated in real-time during work performance using the difference between the OI and the PSL. The EOI value was used to perform receiver operating characteristic (ROC) curve analysis to find the optimal cut-off value for classification of overwork state. Results: Of the 60 participants analyzed, 28 (46.7%) were classified as the overwork group based on their RHR. ROC curve analysis showed that the EOI was a good predictor of overwork, with an area under the curve of 0.824. The optimal cut-off values ranged from 21.8% to 24.0% depending on the method used to determine the cut-off point. Conclusion: The EOI showed promising results as a predictive tool to assess overwork in real-time using heart rate monitoring and calculation through MAWT. Further research is needed to assess physical workload accurately and determine cut-off values across industries.

• Resources Recycling
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• v.33 no.3
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• pp.38-47
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• 2024

Molybdenite is the primary molybdenum resource and is extracted via flotation due to its unique hydrophobic surface. Meanwhile, the grade and crystal size of mined molybdenite are decreasing. As a result, the size of the molybdenum ore required for liberation is decreasing, and the flotation process's feed size input is also decreasing. Therefore, in order to secure molybdenum, it is necessary to perform research on the flotation for the fine molybdenite. In this study, we developed a method to enhance the flotation efficiency of fine molybdenite particles in the range of 5-30 ㎛. The methodology involved implementing bubble size reduction and particle aggregation. Through simulations of bubble-particle collision probability and flotation experiments, we were able to find the ranges of bubble size and particle aggregate size that make fine particles float more effectively. This range provided the conditions for effective flotation of fine molybdenite particles. Therefore, we will implement the flotation conditions established in this study for fine molybdenum ore to improve the flotation process in molybdenum mineral processing plants in the future.

• Journal of the Microelectronics and Packaging Society
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• v.27 no.4
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• pp.83-89
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• 2020

For the past few decades, as part of efforts to protect the environment where fossil fuels, which have been a key energy resource for mankind, are becoming increasingly depleted and pollution due to industrial development, ecofriendly secondary batteries, hydrogen generating energy devices, energy storage systems, and many other new energy technologies are being developed. Among them, the lithium-ion battery (LIB) is considered to be a next-generation energy device suitable for application as a large-capacity battery and capable of industrial application due to its high energy density and long lifespan. However, considering the growing battery market such as eco-friendly electric vehicles and drones, it is expected that a large amount of battery waste will spill out from some point due to the end of life. In order to prepare for this situation, development of a process for recovering lithium and various valuable metals from waste batteries is required, and at the same time, a plan to recycle them is socially required. In this study, we introduce a nanoscale pattern transfer printing (NTP) process of Li2CO3, a representative anode material for lithium ion batteries, one of the strategic materials for recycling waste batteries. First, Li2CO3 powder was formed by pressing in a vacuum, and a 3-inch sputter target for very pure Li2CO3 thin film deposition was successfully produced through high-temperature sintering. The target was mounted on a sputtering device, and a well-ordered Li2CO3 line pattern with a width of 250 nm was successfully obtained on the Si substrate using the NTP process. In addition, based on the nTP method, the periodic Li2CO3 line patterns were formed on the surfaces of metal, glass, flexible polymer substrates, and even curved goggles. These results are expected to be applied to the thin films of various functional materials used in battery devices in the future, and is also expected to be particularly helpful in improving the performance of lithium-ion battery devices on various substrates.