• Proceedings of the Korean Vacuum Society Conference
• /
• 2016.02a
• /
• pp.285-285
• /
• 2016

Resistive random access memory devices have been widely studied due to their high performance characteristics, such as high scalability, fast switching, and low power consumption. However, fluctuation in operational parameters remains a critical weakness that leads to device failures. Although the random formation and rupture of conducting filaments (CFs) in an oxide matrix during resistive switching processes have been proposed as the origin of such fluctuations, direct observations of the formation and rupture of CFs at the device scale during resistive switching processes have been limited by the lack of real-time large-area imaging methods. Here, a novel imaging method is proposed for monitoring CF formation and rupture across the whole area of a memory cell during resistive switching. A hybrid structure consisting of a resistive random access memory and a light-emitting diode enables real-time monitoring of CF configuration during various resistive switching processes including forming, semi-forming, stable/unstable set/reset switching, and repetitive set switching over 50 cycles.

• Journal of KIISE:Computer Systems and Theory
• /
• v.30 no.1
• /
• pp.12-21
• /
• 2003

In this paper, we propose an on-line scheduling algorithm with the goal of maximizing the total reward of IRIS (Increasing Reward with Increasing Service) real-time tasks that have reward functions and arrive dynamically into the system. We focus on enhancing the performance of scheduling algorithm, which W.: based on the following two main ideas. First, we show that the problem to maximize the total reward of dynamic tasks can also be solved by the problem to find minimum of maximum derivatives of reward functions. Secondly, we observed that only a few of scheduled tasks are serviced until a new task arrives, and the rest tasks are rescheduled with the new task. Based on our observation, the Proposed algorithm doesn't schedules all tasks in the system at every scheduling print, but a part of tasks. The performance of the proposed algorithm is verified through the simulations for various cases. The simulation result showed that the computational complexity of proposed algorithm is$O(N_2)$ in the worst case which is equal to those of the previous algorithms, but close to O(N) on the average.

• Applied Microscopy
• /
• v.40 no.1
• /
• pp.47-51
• /
• 2010

The capability of real-time observation in TEM is quite useful to study dynamic phenomena of materials in a certain variable ambience. In performing the experiment, the choice of video recording program is an important factor to obtain high quality of movie streaming. Window Movie Maker (WMM) is generally recommended as a default video recording program if one uses "DV Capture" function in DigitalMicrograph$^{TM}$ (DM) software. However, the image quality does not often satisfy the condition for high-resolution microscopic analysis since the severe information loss in the final result occurs during the conversion process. As a good candidate to overcome this problem, Virtual-Dub is highly recommended since the information loss can be minimized through the streaming process. In this report, we demonstrated how useful VirtualDub works in a high-resolution movie recording. Quantitative comparison of the information quality between the images recorded by each software, WMM and VirtualDub, was carried out based on histogram analysis. As a result, the image recorded by VirtualDub was improved ~13% in brightness and ~122% in contrast compared with the image obtained by WMM at the same imaging condition. Remarkably, the gray gradation (meaning an amount of information) becomes wider up to ~115% than that of the WMM result.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.22 no.1
• /
• pp.11-19
• /
• 2004

Such social structures as bridges,, buildings, dams and towers have been transformed by their own load or fundamental ground. They have been behaved by other external causes. These regular or irregular behaviors threaten to do their users safety. Therefore, to monitor the load of the structures or reaction shown by them could help to verify their behaviors. RTK GPS allows the use of a static base station and remote rover unit to allow f3r data collection within several seconds and in real time. It is useful for monitoring the behaviors of massive structures like bridges. In this Study, Among GPS methods, we used RTK GPS to analyze the precision of monitoring and then on the basis of it, we developed a monitoring system using RTK GPS when measured the behavior of main tower of a suspension bridge by using RTK GPS. Comparing a deviation between observation values, X axis was Imm, Y axis was 1mm and Z axis 2.2mm. It turned out that it was possible to monitor and measure structures by RTK GPS.

• Journal of Advanced Navigation Technology
• /
• v.19 no.6
• /
• pp.507-514
• /
• 2015

The Spatial information research institute of the LX Korea land and geospatial informatix corporation manages infrastructure for the LX global navigation satellite system (GNSS), which comprises 30 monitoring stations nationwide. Since 2014, it has conducted network real-time kinematic (RTK) tests using the master-auxiliary concept (MAC). This study introduces the infrastructure of LX GNSS and presents the results of a performance analysis of the LX RTK service. The analysis was based on a total of 25 cadastral topographic control points in Jeonju, Seoul, and Incheon. For each point, performance was measured over one observation, two repeated observations, and five repeated observations. The measurements obtained from LX MAC and the VRS of the National Geographic Information Institute were compared with the announced coordinates derived from cadastral topographic control points. As a result, the two systems were found to have similar performance with average error and standard deviation differing only by 1 to 2 cm.

• Journal of Astronomy and Space Sciences
• /
• v.22 no.4
• /
• pp.501-512
• /
• 2005

This research supposed when a fictitious KSIV-I space launch vehicle launches from NARO space center. This compared and analyzed the results from real-time trajectory estimation using the Extended Kalman Filter and the Unscented Kalman Filter. A virtual trajectory and observation data are generated for the fictitious KSLV-I and three measurement radars. The performances of both Otters are compared for several simulations with small initial errors, large initial errors, 20Hz and 10Hz data rate. The results show that the Unscented Kalman Filter yields faster convergence and more accurate than the Extended Kalman Filter for the cases with larger initial error and slower data rate conditions.

• Journal of the Korean Geophysical Society
• /
• v.9 no.2
• /
• pp.77-86
• /
• 2006

Aplications of the real-time kinematic GPS surveying and inertial measurement unit have been beingRTK GPS allows the use of a static base station and remote rover unit to allow for data collectionwithin several seconds and in real time. It is useful for monitoring the behaviors of massive structureslike bridges. And this study purposed to implement a method of deciding the acurate dynaimc attitudeof structures by IMU. In this study, among GPS methods, we used RTK GPS to analyze the precisionof monitoring and then on the basis of it, we developed a monitoring system using RTK GPS anda deviation betwen observation values, X axis was 1mm, Y axis was 1mm and Z axis 2.2mm. I tturned out that it was possible to monitor and measure structures by RTK GPS and IMU.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.47 no.8
• /
• pp.549-557
• /
• 2019

In this paper, we focus on the real-time detection method of a seismic ionospheric disturbance using Global Navigation Satellite System (GNSS) signal. First, the monitor for the detection of the seismic ionospheric disturbance is studied based on the estimated ionospheric delay using the GNSS signals. And then, the threshold for the automatic detection is computed. Moreover, to discriminate the seismic ionospheric disturbance against the other ionospheric anomalies due to other error sources such as cycle slips, the signatures of the ionospheric perturbation caused by the seismic wave is investigated. Based on the observation, the detection strategy is proposed. Using GPS observations collected from the 47 permanent stations in South Korea and Japan, the proposed real-time detection method is evaluated.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.1
• /
• pp.46-63
• /
• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• ETRI Journal
• /
• v.35 no.5
• /
• pp.748-756
• /
• 2013

This paper addresses the problem of online hop timing detection and frequency estimation of multiple frequency-hopping (FH) signals with antenna arrays. The problem is deemed as a dynamic one, as no information about the hop timing, pattern, or rate is known in advance, and the hop rate may change during the observation time. The technique of particle filtering is introduced to solve this dynamic problem, and real-time frequency and direction of arrival estimates of the FH signals can be obtained directly, while the hop timing is detected online according to the temporal autoregressive moving average process. The problem of network sorting is also addressed in this paper. Numerical examples are carried out to show the performance of the proposed method.