• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.134-145
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• 2021

It is common to optimize the propulsion control system through a so-called tuning process that modifies the parameter values of the propulsion control software during a ship commissioning. However, during this process, if the error of the initial setting value is large, the tuning time may take too long, or the propulsion equipment can be seriously damaged. Therefore, we conducted research on the design of a propulsion controller that applied a Processor lever controller even for inexperienced people with relatively little experience in tuning propulsion control software to be able to reduce the tuning time while protecting the propulsion system. Through simulation, by comparing the execution result of propulsion control lever commands through the PI controller without applying the Processor lever controller. We analyzed the improvement of the Overshoot and propulsion performance. The simulation results showed that the safety of the propulsion system increased because Overshoot of approximately 9.74%, which occurred when the Processor lever function was not applied.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.

• Smart Media Journal
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• v.11 no.11
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• pp.17-24
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• 2022

With the spread of smart speakers based on voice recognition technology and deep learning technology, not only non-disabled people, but also the blind or physically handicapped can easily control home appliances such as lights and TVs through voice by linking home network services. This has greatly improved the quality of life. However, in the case of speech-impaired people, it is impossible to use the useful services of the smart speaker because they have inaccurate pronunciation due to articulation or speech disorders. In this paper, we propose a personalized voice classification technique for the speech-impaired to use for some of the functions provided by the smart speaker. The goal of this paper is to increase the recognition rate and accuracy of sentences spoken by speech-impaired people even with a small amount of data and a short learning time so that the service provided by the smart speaker can be actually used. In this paper, data augmentation and one cycle learning rate optimization technique were applied while fine-tuning ResNet18 model. Through an experiment, after recording 10 times for each 30 smart speaker commands, and learning within 3 minutes, the speech classification recognition rate was about 95.2%.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.1
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• pp.25-31
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• 2011

In this study, model-based $NH_4-N$ predictive control algorithm by using influent pattern was developed and evaluated for effective control application in $A^2/O$ process. A pilot-scale $A^2/O$process at S wastewater treatment plant in B city was selected. The behaviors of organic, nitrogen and phosphorous in the biological reactors were described by using the modified ASM3+Bio-P model. A one-dimensional double exponential function model was selected for modeling of the secondary settlers. The effluent $NH_4-N$ concentration on the next day was predicted according to model-based simulation by using influent pattern. After the objective effluent quality and simulation result were compared, the optimal operational condition which able to meet the objective effluent quality was deduced through repetitive simulation. Next the effluent $NH_4-N$ control schedule was generated by using the optimal operational condition and this control schedule on the next day was applied in pilot-scale $A^2/O$ process. DO concentration in aerobic reactor in predictive control algorithm was selected as the manipulated variable. Without control case and with control case were compared to confirm the control applicability and the study of the applied $NH_4-N$control schedule in summer and winter was performed to confirm the seasonal effect. In this result, the effluent $NH_4-N$concentration without control case was exceeded the objective effluent quality. However the effluent $NH_4-N$ concentration with control case was not exceeded the objective effluent quality both summer and winter season. As compared in case of without predictive control algorithm, in case of application of predictive control algorithm, the RPM of air blower was increased about 9.1%, however the effluent $NH_4-N$ concentration was decreased about 45.2%. Therefore it was concluded that the developed predictive control algorithm to the effluent $NH_4-N$ in this study was properly applied in a full-scale wastewater treatment process and was more efficient in aspect to stable effluent.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.61-77
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• 2019

If a new utility tunnel is planned for high density existing urban areas in Korea, a rational decision-making process such as the determination of optimum design capacity by using the feasibility evaluation system based on quantitative evaluation indexes and the economic evaluation is needed. Thus, the previous study presented the important weight of individual higher-level indexes (3 items) and sub-indexes (16 items) through a hierarchy analysis (AHP) for quantitative evaluation index items, considering the characteristics of each urban type. In addition, an economic evaluation method was proposed considering 10 benefit items and 8 cost items by adding 3 new items, including the effects of traffic accidents, noise reduction and socio-economic losses, to the existing items for the benefit cost analysis suitable for urban utility tunnels. This study presented a quantitative feasibility evaluation method using the important weight of 16 sub-index items such as the road management sector, public facilities sector and urban environment sector. Afterwards, the results of quantitative feasibility and economic evaluation were compared and analyzed in 123 main road sections of the Seoul. In addition, a comprehensive evaluation method was proposed by the combination of the two evaluation results. The design capacity optimization program, which will be developed by programming the logic of the quantitative feasibility and economic evaluation system presented in this study, will be utilized in the planning and design phases of urban community zones and will ultimately contribute to the vitalization of urban utility tunnels.