• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.27-38
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• 2006

The main purpose of rate control is to achieve the highest video quality when bandwidth or storage capacity is limited. For this purpose, we need a rate control algorithm which is adaptively controlled by the motion information of sequences, scene change, buffer capacity and time-varing bandwitdh channels. A rate-control method in the encoder requires the accurate estimation of target bit for each frame and the low end-to-end delay for transmitting video data by intelligent selection of encoding parameters. In this paper, we suggest three kinds of linear relation in the encoder to satisfy the characteristics of rate control. The first relation is that between the percentage of zero quantized transformed coefficients(p) and coded bits. Second relation is that between the PSNR of encoded frame and its Quantization parameter(QP). Finally, we can find out a linear approximation between QP and p. According to the experimental analysis, the proposed method results in an efficient rate control in terms of the bit estimation, the buffer capacity, and PSNR compared with the existing rate control in the H.264 JM 9.3.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.322-327
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• 2003

The water level of a steam generator of pressurized light water nuclear Power generator is known as a subject whose control is difficult because of a shrinking and swelling effect that is been mutually contradictory in a variation of feed water. In this paper, a neural network model selects first coordinative controller by a inappropriate gain of two PI controllers and the selected controller＇s gain is tuned by a fuzzy self-tuner. Model inputs consist of the water level, the feed water, and the stream flow. One controller of both coupling controllers whose gain is handled firstly is decided based upon above data. The proposed method can analyze patterns of signals using the characteristic of neural networks and select one controller that needs to be tuned through the observed result in this paper. If one controller between both the water level controller and the feed water controller is selected by the neural network model then a gain of the PI controller is suitably tuned by the fuzzy self-tuner. Rules of the fuzzy self-tuner drew from the pattern of input and output data. In the summary, the goal of this Paper is to select the suitable controller and tune the control gain of the selected controller suitably through such two processes.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.12-19
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• 2014

A signal plan focused on vehicle traffic could easily overlook vulnerable priority signals, although the importance of vulnerable movements is increasingly recognized in recent years. Especially, the vulnerable are sometimes faced with dangerous situations when crossing roads with a signal plan based on design values of average, non-vulnerable persons. This study is focused on how to minimize the vehicle delay while simultaneously considering traffic flow and providing traffic safety by increasing road crossing time for pedestrians. For this purpose, a priority signal control strategy for the vulnerable, considering vehicle traffic flow, has been tested. Practical implication and a microscopic computer simulation has shown that the proposed method could provide a small decrease (about 6.2%) in pedestrian delay, a small increase (about 8.5~13.3%) in travel speed of passing traffic, and a considerable decrease (16.2~26.9%) in vehicle travel time. These findings suggest that the proposed signal control strategy could increase pedestrian safety and diminish delay of vehicle travel.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.5
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• pp.105-112
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• 2011

Delay reduction of vehicles at the intersection is highly dependent on the signal operation method. Improper traffic operation causes the violation of the traffic regulations and increasing traffic congestion. Delay because of congestion has contributed to the increase in carbon dioxide in the atmosphere. The focus of this paper is to measure the amount of carbon dioxide when the intersection is changed to roundabout. Even though, Intergovernmental Panel on Climate Change(IPCC) recommends Tier 1 method to measure the amount of greenhouse gas from vehicles, this paper used Tier 3 method because we could use the data of average running distance per each vehicle model. Two signalized intersections were selected as the study area and the delay reductions of roundabout operation were estimated by VISSIM microscopic simulation tool. The control delay for boksu intersection reduced from 28.6 seconds to 4.4 seconds and the KRIBB intersection sharply reduced from 156.4 seconds to 23.6 seconds. In addition, carbon dioxide for two intersections reduced to 646.5 ton/year if the intersection is changed to roundabout. Future research tasks include testing the experiment for networks, as well as for various intersection types.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1088-1095
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• 2009

In this paper, we describe the reorientation method of distorted road sign by using projection transformation for improving recognition rate of road sign. RSR (Road Sign Recognition) is one of the most important topics for implementing driver assistance in intelligent transportation systems using pattern recognition and vision technology. The RS (Road Sign) includes direction of road or place name, and intersection for obtaining the road information. We acquire input images from mounted camera on vehicle. However, the road signs are often appeared with rotation, skew, and distortion by perspective camera. In order to obtain the correct road sign overcoming these problems, projection transformation is used to transform from 4 points of image coordinate to 4 points of world coordinate. The 4 vertices points are obtained using the trajectory as the distance from the mass center to the boundary of the object. Then, the candidate areas of road sign are transformed from distorted image by using homography transformation matrix. Internal information of reoriented road signs is segmented with arrow and the corresponding indicated place name. Arrow area is the largest labeled one. Also, the number of group of place names equals to that of arrow heads. Characters of the road sign are segmented by using vertical and horizontal histograms, and each character is recognized by using SAD (Sum of Absolute Difference). From the experiments, the proposed method has shown the higher recognition results than the image without reorientation.

• Journal of the Ergonomics Society of Korea
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• v.17 no.3
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• pp.23-39
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• 1998

Several recent aircraft accidents occurred due to goal conflicts between human and machine actors. To facilitate the management of the cockpit activities considering these observations. a computational aid. the Agenda Manager (AM) has been developed for use in simulated cockpit environments. It is important to know pilot intentions performing cockpit operations accurately to improve AM performance. Without accurate knowledge of pilot goals or intentions, the information from AM may lead to the wrong direction to the pilot who is using the information. To provide a reliable flight simulation environment regarding goal conflicts. a pilot goal communication method (GCM) was developed to facilitate accurate recognition of pilot goals. Embedded within AM, the GCM was used to recognize pilot goals and to declare them to the AM. Two approaches to the recognition of pilots goals were considered: (1) The use of an Automatic Speech Recognition (ASR) system to recognize overtly or explicitly declared pilot goals. and (2) inference of covertly or implicitly declared pilot goals via the use of an intent inferencing mechanism. The integrated mode of these two methods could overcome the covert goal mis-understanding by use of overt GCM. And also could it overcome workload concern with overt mode by the use of covert GCM. Through simulated flight environment experimentation with real pilot subjects, the proposed GCM has demonstrated its capability to recognize pilot intentions with a certain degree of accuracy and to handle incorrectly declared goals. and was validated in terms of subjective workload and pilot flight control performance. The GCM communicating pilot goals were implemented within the AM to provide a rich environment for the study of human-machine interactions in the supervisory control of complex dynamic systems.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.423-434
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• 2004

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the 'conventional' SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials as well as to consider a fixed number of input nodes at polynomial neurons (or nodes) located in each layer. However, this design process does not guarantee that the conventional SOPNN generated through learning results in optimal network architecture. The design procedure applied in the construction of each layer of the SOPNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomials, and input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between the approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented using pH neutralization process data as well as sewage treatment process data. A comparative analysis indicates that the proposed SOPNN is the model having higher accuracy as well as more superb predictive capability than other intelligent models presented previously.reviously.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.632-637
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• 2019

Recent researches on autonomous driving of vehicles are becoming very active, and it is a trend to assist safe driving and improve driver's convenience. Autonomous vehicles are required to combine artificial intelligence, image recognition capability, and Internet communication between objects. Because mobile telecommunication networks have limitations in their processing, they can be easily implemented and scale using an easily expandable Wi-Fi network. We propose a wireless design method to construct such a vehicle control network. We propose the arrangement of AP and the software configuration method to minimize loss of data transmission / reception of mobile terminal. Through the design of the proposed network system, the communication performance of the moving vehicle can be dramatically increased. We also verify the packet structure of GPS, video, voice, and data communication that can be used for the vehicle through experiments on the movement of various terminal devices. This wireless design technology can be extended to various general purpose wireless networks such as 2.4GHz, 5GHz and 10GHz Wi-Fi. It is also possible to link wireless intelligent road network with autonomous driving.

• Journal of IKEEE
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• v.23 no.3
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• pp.883-892
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• 2019

This study is the method which is adapted to control ankle joint movement for resolving the problem of gait imbalance in intervals where gait environments are changed and slope walking, as applying terrain-adaptive technique to intelligent above-knee prosthesis. In this development of above-knee prosthesis, to classify the gait modes is essential. For distinguishing the stance phases and the swing phase depending on roads, a machine learning which combines decision tree and random forest from knee angle data and inertial sensor data, is proposed and adapted. By using this method, the ankle movement state of the prosthesis is controlled. This study verifies whether the problem is resolved through butterfly diagram.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.301-307
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• 2021

In addition to the revival of the Internet of Things, embedded systems, which are at the core of the Internet of Things, require intelligent control as things change. Embedded systems, however, are heavily constrained by resources such as hardware, memory, time and power. When changes are needed to firmware in an embedded system, flash Memory must be initialized and the entire firmware must be uploaded again. Therefore, it is time- and energy-efficient in that areas that do not need to be modified must also be initialized and rewritten. In this paper, we propose how to upload firmware in installments to each sector of flash memory so that only firmware can be replace the firmware in the parts that need to be modified when the firmware needs to be modified. In this paper, the proposed method was evaluated using real target board, and as a result, the time was reduced by about half.