• Journal of the Korea Society of Computer and Information
• /
• v.10 no.5 s.37
• /
• pp.141-150
• /
• 2005

Wireless Sensor Networks have been rapidly developed due to the advances of sensor technology and are expected to be applied to various applications in many fields. In Wireless Sensor Networks, schemes for managing the network energy-efficiently are most important. For this purpose, there have been a variety of researches to suggest routing protocols. However, existing researches have ideal assumption that all sensor nodes have sensing data to transmit. In this paper, we designed and implemented a sensing-aware cluster selection algorithm based on LEACH-C for the sensor network in which part of sensors have sensing data. We also simulated proposed algorithm on several network situation and analyzed which situation is suitable for the algorithm. By the simulation result, selecting cluster head among the sensing nodes is most energy-efficient and the result shows application of sensing-awareness in cluster head selection when not all sensors have sensing data.

• Nuclear Engineering and Technology
• /
• v.37 no.2
• /
• pp.177-184
• /
• 2005

The Multivariate State Estimation Technique (MSET) is being used in Nuclear Power Plants for sensor and equipment condition monitoring. This paper presents the use of regularization methods for optimizing MSET's predictive performance. The techniques are applied to a simulated data set and a data set obtained from a nuclear power plant currently implementing empirical, on-line, equipment condition monitoring techniques. The results show that regularization greatly enhances the predictive performance. Additionally, the selection of prototype vectors is investigated and a local modeling method is presented that can be applied when computational speed is desired.

• Proceedings of the KSME Conference
• /
• 2007.05b
• /
• pp.2009-2014
• /
• 2007

Hydrogen is a fuel of fuel cell system, which has powerful explosion possibility. Hence, the fuel cell system needs safety evaluation to prevent risk of hydrogen leakage. We use a actual size chamber of a common fuel cell module to analyze hydrogen. Hydrogen injection holes are located in lower part of the chamber in order to simulated hydrogen leakage. The hydrogen sensor can detect range of 0${\sim}$4%. Since the hydrogen gas, of which leaked amount is controled by MFC, are injected at the bottom holes, the transient sensor signals are measured. At a condition of 10cc/s of hydrogen leakage, the sensor detects hydrogen leakage after 22sec and there is also several seconds of time delay depending on the position of the sensor. This experimental data can be applied for the design of the hydrogen detection system and ventilation system of a residential fuel cell system.

• Journal of Internet Computing and Services
• /
• v.10 no.3
• /
• pp.35-49
• /
• 2009

In electronic warfare settings, battlefield helicopters identify various threats based upon threat data, which are acquired using their multi-sensors of aircraft survivability equipment (ASE). To continually function despite of potential threats and successfully execute their missions, the battlefield helicopters have to repeatedly report threats in simulated battlefield situations. Toward this ends, the paper presents threat unification using multi-sensor simulator and its implementation. The simulator consists of (1) threat attributes generator, which models threats against battlefield helicopters and defines their specific attributes, (2) threat data generator, which generates threats, being similar to real ones, using normal, uniform, and exponential distributions, and (3) graphic display for threat analysis and unification, which shows unified threat information, for example, threat angle and its level. We implement a multi-sensor threat simulator that can be repeatedly operable in various simulated battlefield settings. Further, we report experimental results that, in addition to tangibly modeling the threats to battlefield helicopters, test the capabilities of threat unification using our simulator.

• Journal of Radiation Industry
• /
• v.9 no.1
• /
• pp.1-7
• /
• 2015

The trend of x-ray image sensor has been evolved from an amorphous silicon sensor to a crystal silicon sensor. A crystal silicon X-ray sensor, meaning a X-ray CIS (CMOS image sensor), is consisted of three transistors (Trs), i.e., a Reset Transistor, a Source Follower and a Select Transistor, and a photodiode. They are highly sensitive to radiation exposure. As the frequency of exposure to radiation increases, the quality of the imaging device dramatically decreases. The most well known effects of a X-ray CIS due to the radiation damage are increments in the reset voltage and dark currents. In this study, a pixel array of a X-ray CIS was made of $20{\times}20pixels$ and this pixel array was exposed to a high radiation dose. The radiation source was Co-60 and the total radiation dose was increased from 1 to 9 kGy with a step of 1 kGy. We irradiated the small pixel array to get the increments data of the reset voltage and the dark currents. Also, we simulated the radiation effects of the pixel by MCNP (Monte Carlo N-Particle) simulation. From the comparison of actual data and simulation data, the most affected location could be determined and the cause of the increments of the reset voltage and dark current could be found.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.4
• /
• pp.676-682
• /
• 2018

In wireless sensor networks, we propose an optimization algorithm in order to minimize the consumed energy of nodes for maritime search and rescue. In the marine environment, search and rescue operations are mainly performed on the surveillance side and passively on the rescued side. A self-configurable wireless sensor network can build a system that can send rescue signals in the operations. A simulated annealing algorithm is proposed to minimize the consumed energy of nodes in the networks with many nodes. As the density of nodes becomes higher, the algorithmic computation will increase highly. To search the good result in a proper execution time, the proposed algorithm proposes a new neighborhood generating operation and improves the efficiency of the algorithm. The proposed algorithm was evaluated in terms of the consumed energy of the nodes and algorithm execution time, and the proposed algorithm performed better than other optimization algorithms in the performance results.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.3
• /
• pp.573-577
• /
• 2009

Piezoresistive pressure sensor have become the successfully-commercialized MEMS product and the related technologies have been well developed over the past decades. Regarding the design methodology, however, the coupled-physics FEM analyses of the transducer itself and the signal-processing circuitry design based on the conventional EDA are separated and both of the analyses were sequentially processed for the full design of the pressure sensor. For the fast and effective R&D, new design methodology is proposed in this paper where the FEM results are linked to the EDA environment and therefore most of the design works can be done in the EDA environments, which means the time-consuming FEM analyses can be minimized. In order to verify the proposed approach, a typical piezoresistive pressure sensor having the silicon diaphragm and piezoresistors was modeled and analyzed based on the proposed methodology. The verification results showed that the simulated results were matched well with the measured data within the 7% difference while the simulation time was reduced less than 5% compared to the conventional methodology. Through the proposed approach, various types of the piezoresistive pressure sensors can be developed in more effective way.

• Progress in Medical Physics
• /
• v.33 no.4
• /
• pp.136-141
• /
• 2022

Purpose: This study aimed to develop a breath control training system for breath-hold technique and respiratory-gated radiation therapy wherein the patients can learn breath-hold techniques in their convenient environment. Methods: The breath control training system comprises a sensor device and software. The sensor device uses a loadcell sensor and an adjustable strap around the chest to acquire respiratory signals. The device connects via Bluetooth to a computer where the software is installed. The software visualizes the respiratory signal in near real-time with a graph. The developed system can signal patients through visual (software), auditory (buzzer), and tactile (vibrator) stimulation when breath-holding starts. A motion phantom was used to test the basic functions of the developed breath control training system. The relative standard deviation of the maxima of the emulated free breathing data was calculated. Moreover, a relative standard deviation of a breath-holding region was calculated for the simulated breath-holding data. Results: The average force of the maxima was 487.71 N, and the relative standard deviation was 4.8%, while the average force of the breath hold region was 398.5 N, and the relative standard deviation was 1.8%. The data acquired through the sensor was consistent with the motion created by the motion phantom. Conclusions: We have developed a breath control training system comprising a sensor device and software that allow patients to learn breath-hold techniques in their convenient environment.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.19 no.2
• /
• pp.473-482
• /
• 2024

This study utilized virtual reality to construct a simulated public restroom environment to identify potential hazards. The objective was to discern actual risks in real-world public restrooms through this virtual setup. During the virtual restroom experience, data from the built-in 3-axis accelerometer and gyroscope sensors of testor's smart phones were collected. Analysis of this data helped in identifying spatio temporal factors impacting the users. The determination of these factors as risk elements was based on an evaluation algorithm grounded in data analysis.

• Korean Journal of Remote Sensing
• /
• v.26 no.3
• /
• pp.297-304
• /
• 2010

Since the change in Doppler centroid according to moving targets brings alteration to the phase in azimuth differential signals of synthetic aperture radar (SAR) data, one can measure the velocity of the moving targets using this effect. In this study, we will investigate theoretically measuring the velocity of an object from azimuth differential signals by using range compressed data which is the interim outcome of treatment from the simulated SAR raw data of moving targets on the background of sea clutter. Also, it will provide evaluation for the elements that affect the estimation error of velocity from a single SAR sensor. By making RADARSAT-1 simulated image as a specific case, the research includes comparisons for the means of velocity measurement classified by the directions of movement in the four following cases. 1. A case of a single target without currents, 2. A case of a single target with tidal currents of 0.5 m/s, 1 m/s, and 3 m/s, 3. A case of two targets on a same azimuth line moving in a same direction and velocity, 4. A case of a single target contiguous to land where radar backscatter is strong. As a result, when two moving targets exist in SAR image outside the range of approximately 256 pixels, the velocity of the object can be measured with high accuracy. However, when other moving targets exist in the range of approximately 128 pixels or when the target was contiguous to the land of strong backscatter coefficient (NRCS: normalized radar cross section), the estimated velocity was in error by 10% at the maximum. This is because in the process of assuming the target's location, an error occurs due to the differential signals affected by other scatterers.