• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1229-1233
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• 2010

In event-driven wireless sensor networks, network congestion occurs when event data, which have higher transmission rates than periodic sensing data, arc forwarded to bottleneck links. As the congestion continues, congestion collapse is triggered, so most of packets from source nodes are failed to transmit to a sink node. Rate control schemes can be a solution for preventing the congestion collapse problem. In this paper, a rate control scheme that each node controls child node's data rate based on congestion patterns is proposed. Experiments show that the proposed scheme effectively controls network congestion and successfully transmits more event data packets to a sink node than existing rate control schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1183-1188
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• 2011

The novel metal position detection method is proposed where conventional techniques, in high temperature, moisture and particle environment, are not able to be applied. It is known that electronic devices, utilizing microwave, ultrasonic or optical technique, are hard to apply for sensing application where temperature is exceeding above 300 degree centigrade. Metal position detection technique, which was consisted with passive elements facing hot sensing surface, utilizing electromagnetic wave was investigated, and the metal detection sensitivity was measured by varying sensor frequency and sensing distance. Measurement result in laboratory test set-up showed position measurement resolution up to 1mm, when distance between two sensing elements were 500mm, and possibility to measure position of hot metal sheet having very high surface temperature.

• Proceedings of the KSRS Conference
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• 2000.04a
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• pp.49-54
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• 2000

Conventional methods for measuring winds provide wind velocity observations over limited area and time period. The use of satellite imagery for measuring wind velocity overcomes some of these limitations by providing wide area and near condinuous coverage. And its accurate depiction is essential for operational weather forecasting and for initialization of NWP models. GMS-5 provides full disk images at hourly intervals. At four times each day - 0500, 1100, 1700, 2300 hours UTC-a series of three images is received, separated by thirty minutes, centered at the four times. The current wind system generates winds from sets of 3 infrared(IR) images, separated by an hour, four times a day. It also produces visible(VIS) and water vapor(WV) image-based winds from half-hourly imagery four times a day. The derivation of wind from satellite imagery involves the identification of suitable cloud targets. tracking the targets on sequential images, associating a pressure height with the derived wind vector, and quality control. The aim of this research is to incorporate imagery from other available spectral channels and examine the error characteristics of winds derived from these images.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1048-1063
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• 2020

In this study, we propose a reinforcement learning agent to control the data transmission rates of nodes in carrier sensing multiple access with collision avoidance (CSMA/CA)-based wireless networks. We design a reinforcement learning (RL) agent, based on Q-learning. The agent learns the environment using the timeout events of packets, which are locally available in data sending nodes. The agent selects actions to control the data transmission rates of nodes that adjust the modulation and coding scheme (MCS) levels of the data packets to utilize the available bandwidth in dynamically changing channel conditions effectively. We use the ns3-gym framework to simulate RL and investigate the effects of the parameters of Q-learning on the performance of the RL agent. The simulation results indicate that the proposed RL agent adequately adjusts the MCS levels according to the changes in the network, and achieves a high throughput comparable to those of the existing data transmission rate adaptation schemes such as Minstrel.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.45-51
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• 2000

In this Paper a basic technique of gantry robot control system has been developed to weld the curved part of a large structure. A welding robot is designed to rotate torch and make the torch angle normal to the welding surface. The Kalman filter is applied to obtain the smooth welding path signal from the noised Sensing data. A welding path finding algorithm has been developed in Turbo-C language.

• Journal of Biosystems Engineering
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• v.11 no.1
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• pp.31-36
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• 1986

As a part of study on automatic control system for green houses, an automatic irrigation system was developed by using microcomputer. For the study, gypsum block was used as a sensing device of soil moisture and its data was designed to transfer to microcomputer through A/D converter. Also, software which be able to control the irrigation time and flow rate by the solenoid valve was developed. This system was tested by using practical data and the following results were summarized. 1. Since the gypsum was very accurate in addition with chiep and easy to manufacture, it turned out to be a very good device to detect the soil moisture in this system. 2. Also, solenoid valve was very excellent device for controlling the water flow rate since its control error is less then 1% when the irrigation time is over 100 seconds.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.642-645
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• 2004

This paper focuses on recovering systematic biases during LIDAR calibration, particularly using natural surfaces as control features. Many previous approaches have utilized all the points overlapping with the control features and often experienced with an inaccurate value converged with a poor rate due to wrong correspondence in pairing a point and the corresponding control features. To overcome these shortcomings, we establish a preventive scheme to select the pairs of high confidence, where the confidence value is based on the error budget associated with the point measurement and the linearity and roughness of the control feature. This approach was then applied to calibraring the LIDAR data simulated with the given systematic biases. The parameters were successfully recovered using the proposed approach with the accuracy and convergence rate superior to those using the previous approaches.

• Korean Journal of Remote Sensing
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• v.19 no.4
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• pp.291-305
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• 2003

The cost of deploying Geological and Environmental information gathering systems, especially when such systems obtain remote sensing and photographic data through the use of commercial satellites and aircraft. Besides the high cost equipment required, adverse weather conditions can further restrict a researcher's ability to collect data anywhere and anytime. To mitigate this problem, we have developed a compact, multi-spectral automatic Aerial photographic system. This system's Multi-spectral camera is capable of the visible (RGB) and infrared (NIR) bands (3032*2008 pixel). It consists of a thermal infrared camera and automatic balance control, and can be managed by a palm-top computer. Other features includes a camera gimbal system, GPS receiver, weather sensor among others. We have evaluated the efficiency of this system in several field tests at the following locations: Kyongsang-bukdo beach, Nakdong river (at each site of mulkeum-namji and koryung-gumi), and Kyungahn River. Its tested ability in aerial photography, weather data, as well as GPS data acquisition demonstrates its flexibility as a tool for environmental data monitoring.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.1
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• pp.179-187
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• 2019

With the recent development of small computing devices, IoT sensor network can be widely deployed and is now readily available with sensing, calculation and communi-cation functions at low cost. Sensor data management is a major component of the Internet of Things environment. The huge volume of data produced and transmitted from sensing devices can provide a lot of useful information but is often considered the next big data for businesses. New column-wise compression technology is mounted to the large data server because of its superior space efficiency. Since sensor nodes have narrow bandwidth and fault-prone wireless channels, sensor-based storage systems are subject to incomplete data services. In this study, we will bring forth a short overview through providing an analysis on IoT sensor networks, and will propose a new storage management scheme for IoT data. Our management scheme is based on RAID storage model using column-wise segmentation and compression to improve space efficiency without sacrificing I/O performance. We conclude that proposed storage control scheme outperforms the previous RAID control by computer performance simulation.

• Smart Structures and Systems
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• v.25 no.2
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• pp.123-133
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• 2020

Compressive sensing (CS) is a newly developed data acquisition and processing technique that takes advantage of the sparse structure in signals. Normally signals in their primitive space or format are reconstructed from their compressed measurements for further treatments, such as modal analysis for vibration data. This approach causes problems such as leakage, loss of fidelity, etc., and the computation of reconstruction itself is costly as well. Therefore, it is appealing to directly work on the compressed data without prior reconstruction of the original data. In this paper, a direct approach for modal analysis of damped systems is proposed by decomposing the compressed measurements with an appropriate dictionary. The damped free vibration function is adopted to form atoms in the dictionary for the following sparse decomposition. Compared with the normally used Fourier bases, the damped free vibration function spans a space with both the frequency and damping as the control variables. In order to efficiently search the enormous two-dimension dictionary with frequency and damping as variables, a two-step strategy is implemented combined with the Orthogonal Matching Pursuit (OMP) to determine the optimal atom in the dictionary, which greatly reduces the computation of the sparse decomposition. The performance of the proposed method is demonstrated by a numerical and an experimental example, and advantages of the method are revealed by comparison with another such kind method using POD technique.