• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.18-24
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• 2010

In this paper, we address an active ranging system based on laser structured light image for mobile robot application. Since the burdensome correspondence problem is avoidable, the structured light image processing has efficient computation in comparison with the conventional stereo image processing. By using a cylindrical lens in the laser generation, it is possible to convert a point laser into a stripe laser without motorized scan in the proposed system. In order to achieve robustness against environmental illumination noise, we propose an efficient integro-differential image processing algorithm. The proposed system has embedded image processing module and transmits distance data to reduce the computational burden in main control system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.887-890
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• 1993

By introducing the notion of constraint-oriented fuzzy inference, we will show that it provides us ways of fuzzy control methods that has abilities of adaptation, learning and self-organization. The basic supporting techniques behind these abilities are“hard”processing by Artificial Intelligence or traditional computational framework and“soft”processing by Neural Network or Genetic Algorithm techniques. The reason that these techniques can be incorporated to fuzzy control systems is that the notion of“constraint”itself has two fundamental properties, that is, the“modularity”property due to its declarativeness and the“logicality”property due to its two-valuedness. From the former property, the modularity property, decomposing and integrating constraints can be done easily and efficiently, which enables us to carry out the above“soft”processing. From the latter property, the logicality property, Qualitative Reasoning and Instance Generalization by Symbolic Reasoning an be carried out, thus enabling the“hard”processing.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.399-408
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• 2024

The moisture content of crude oil notably affects various aspects of oil production, storage, transportation, and exploration. However, accurately measuring this moisture content is challenging because of numerous influencing factors, leading to a lack of precision in existing detection methods. This inadequacy hinders the progress of China's petroleum industry. To overcome these challenges, this paper proposes a conductivity-based method for measuring crude oil moisture content. By employing an embedded system, we designed a sensor comprising five electrodes. Additionally, we developed signal excitation and signal processing circuits. Moreover, a software program was designed to analyze and compute the output signal using fast Fourier transform operations. This facilitated the identification of flow patterns, computation of relevant flow rates, and establishment of correlation rates based on frequency spectral characteristics. Based on experimental results, we established a functional relationship between measurement parameters and crude oil moisture content. This study enhanced the precision of moisture content measurement, thereby addressing existing limitations and fostering the advancement of China's petroleum industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.81-88
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• 2016

This research investigated the sensory processing ability and selected subjects who had sensory processing problems, and divided the subjects into an experimental group and control group. The experimental group was educated with sensory processing intervention on the activities of daily living to determine its influence on the quality of life. The study was based on 230 university students with similar majors in 3 universities of Chungcheong area in the beginning of May, 2013. From here, 32 subjects who had issues with their sensory processing ability were selected. The 230 students were given a survey on the quality of life, individual characteristics, and sensory processing ability. Later, the 32 subjects who had problems with their sensory processing ability were divided into an experimental group and control group. The control group performed sensory processing intervention, whereas the control group did not. After the sensory processing intervention method for 6 weeks, the quality of life was re-evaluated. As a result, the total score of the quality of life after intervention was 98.69 in the experimental group and 84.81 in the control group (p=0.001). The physical score was 16.43 in the experimental group and 14.64 in the control group (p=0.008). The psychological score was 14.71 in the experimental group and 11.75 in the control group (p<0.001). The social score was 14.67 in the experimental group and 13.17 in the control group (p=0.032). The environment score was 14.66 in the experimental group and 12.34 in the control group (p=0.006). The experimental group showed a significant increase in all areas of the quality of life, whereas the control group did not. Through this result, it can be seen that a sensory processing intervention method in daily life can increase the quality of life for subjects with problems in sensory processing ability. Overall, it will be necessary to apply a treatment of various sensory intervention programs for adults and promote a better quality of life.

• Journal of Biomedical Engineering Research
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• v.6 no.2
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• pp.13-14
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• 1985

We have developed a microprogramir!able signal processor for real-time ultrasonic signal processing. Processing speed was increased by the parallelism in horizontal microprogram using 104bits microcode and the Pipelined architecture. Control unit of the signal processor was designed by microprogrammed architec- ture and writable control store (WCS) which was interfaced with host computer, APPLE- ll . This enables the processor to develop and simulate various digital signal processing algorithms. The performance of the processor was evaluated by the Fast Fourier Transform (FFT) program. The execution time to perform 16 bit 1024 points complex FF7, radix-2 DIT algorithm, was about 175 msec with IMHz master Clock. We can use this processor to Bevelop more efficient signal processing algorithms on the biological signal processing.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.11
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• pp.1059-1064
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• 2012

In this paper, some applications of natural language processing techniques for information retrieval have been introduced, but the results are known not to be satisfied. In order to find the roles of some classical natural language processing techniques in information retrieval and to find which one is better we compared the effects with the various natural language techniques for information retrieval precision, and the experiment results show that basic natural language processing techniques with small calculated consumption and simple implementation help a small for information retrieval. Senior high complexity of natural language processing techniques with high calculated consumption and low precision can not help the information retrieval precision even harmful to it, so the role of natural language understanding may be larger in the question answering system, automatic abstract and information extraction.

• Journal of Biomedical Engineering Research
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• v.6 no.2
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• pp.15-22
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• 1985

We have developed a microprogramir!able signal processor for real-time ultrasonic signal processing. Processing speed was increased by the parallelism in horizontal microprogram using 104bits microcode and the Pipelined architecture. Control unit of the signal processor was designed by microprogrammed architec- ture and writable control store (WCS) which was interfaced with host computer, APPLE- ll . This enables the processor to develop and simulate various digital signal processing algorithms. The performance of the processor was evaluated by the Fast Fourier Transform (FFT) program. The execution time to perform 16 bit 1024 points complex FF7, radix-2 DIT algorithm, was about 175 msec with IMHz master Clock. We can use this processor to Bevelop more efficient signal processing algorithms on the biological signal processing.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.1
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• pp.111-121
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• 1995

A fuzzy control algorithm of bell-type membership functions and 9 rules is constructed for narrow range level control of steam generators in nuclear power plants. It is implemented at a field digital distributed controller, a Westinghouse-made controller called Westinghouse Distributed Processing Family(WDPF). Performance for level control of the developed fuzzy controller is compared with that of conventional controller, both at the field controller. For these comparisons, both the fuzzy control algorithm and the conventional PI control algorithm were carefully tuned. Also the sampling time for optimal performance was investigated. The results show that the fuzzy control algorithm is not only better in performance than the conventional algorithm but also much easier to be tuned by operators in the field.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.510-523
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• 2022

Considering the problems of poor control effect, weak disturbance rejection ability and adaptive ability of two-wheeled self-balanced robot (TWSBR) systems on undulating roads, this paper proposes a fuzzy neural network active disturbance rejection controller (FNNADRC), that is based on fuzzy neural network (FNN) for online correction of active disturbance rejection controller (ADRC)'s nonlinear control rate. Firstly, the dynamic model of the TWSBR is established and decoupled, the extended state observer (ESO) is used to compensate dynamically and linearize the upright and displacement subsystems. Then, the nonlinear PD control rate and FNN are designed, and the FNN is used to modify the control parameters of the nonlinear PD control rate in real time. Finally, the proposed control strategy is simulated and compared with the traditional ADRC and fuzzy active disturbance rejection controller (FADRC). The simulation results show that the control effect of the proposed control strategy is slightly better than ADRC and FADRC.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.58-65
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• 2003

This paper studies a steering control method using a neural network algorithm for an intelligent autonomous driving robot. Previous horizontal steering control methods were made by various possible situation on the road. However, it isn't possible to make out algorithms that consider all sudden variances on the road. In this paper, an intelligent steering control algorithm for an autonomous driving robot system is presented. The algorithm is based on Self Organizing Maps(SOM) and the feature points on the road are used as training datum. In a simulation test, it is available to handle a steering control using SOM for an autonomous steering control. The algorithm is evaluated on an autonomous driving robot. The algorithm is available to control a steering for an autonomous driving robot with better performance at the experiments.