• Journal of KSNVE
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• v.6 no.3
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• pp.325-332
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• 1996

One of the greatest shortcoming in today's predictive maintenance program is the ability to diagnose the mechanical and electrical problems within the machine when the vibration exceeds preset overall and spectral alarm levels. In this study, auto-diagnosis system is constructed by using A/D converter to convert analog to digital singal. With this device the system analyses input signal to diagonosis machine condition. Many plots, which display machine condition, and input values of every channel are calculated in this system. If the falut is found, the system diagnoses automatically using fuzzy algorithm and trend monitoring. Prediction is also performed by the grey system theory. Operator finds out eh machine operating condition intuitively based on with personal computer CRT in using this system.

• 한국전산유체공학회:학술대회논문집
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• 2004.03a
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• pp.56-61
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• 2004

As the size and dimension of target problems in the field of computational engineering including CFD gets bigger and higher, it is needed to have more efficient and flexible data visualization environment in terms of software and hardware. Even though it is still manageable to use a mouse in controlling 3-dimensional data visualization, it would be beneficial to use 3-D input device for 3-D visualization. 'Data Glove' is one of the best 3-D input devices, because human hands are best tools understanding 3-D space. Signals coming from 'Data Glove' are analog and very sensitive to finger motions, so we decided to use a digital filter. This paper describes our experience and benefits of using data glove in controlling 3-Dimensional Postprocess Software.

• ETRI Journal
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• v.17 no.2
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• pp.11-19
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• 1995

The plasma densities generated from a semiconductor bridge (SCB) device employing a capacitor discharge firing set have been measured by a novel diagnostic technique employing a microwave resonator probe. The spatial resolution of the probe is comparable to the separation between the two wires of the transmission lines (${\approx}$3 mm). This method is superior to Langmuir probes in this application because Langmuir probe measurements are affected by sheath effects, small bridge area, and unknown fraction of multiple ions. Measured electron densities are related to the land material and input energy. Although electron densities in the plasma generated by aluminum or tungsten-land SCB devices show a general tendency to increase steadily with power, at the higher energies, the electron densities generated from tungsten-land SCB devices are found to remain constant.

• Journal of computational fluids engineering
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• v.11 no.2 s.33
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• pp.56-61
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• 2006

As the size and dimension of target problems in the field of computational engineering including CFD gets bigger and higher, it is needed to have more efficient and flexible data visualization environment in terms of software and hardware. Even though it is still manageable to use a mouse in controlling 3-dimensional data visualization, it would be beneficial to use 3-D input device for 3-D visualization. 'Data Glove' is one of the best 3-D input devices, because human hands are best tools for understanding 3-D space and manipulating 3-D objects. Signals coming from 'Data Glove' are analog and very sensitive to finger motions, therefore signal filtering using a digital filter is applied. This paper describes our experience and benefits of using data gloves in controlling 3-dimensional postprocessing softwares.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.309-312
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• 2001

A primitive gas classification system which can classify limited species of gas was designed and simulated. The 'electronic nose' consists of an array of 4 metal oxide gas sensors with different selectivity patterns, signal collecting unit and a signal pattern recognition and decision Part in PLD(programmable logic device) chip. Sensor array consists of four commercial, tin oxide based, semiconductor type gas sensors. BP(back propagation) neutral networks with MLP(Multilayer Perceptron) structure was designed and implemented on CPLD of fifty thousand gate level chip by VHDL language for processing the input signals from 4 gas sensors and qualification of gases in air. The network contained four input units, one hidden layer with 4 neurons and output with 4 regular neurons. The 'electronic nose' system was successfully classified 4 kinds of industrial gases in computer simulation.

• Journal of the Ergonomics Society of Korea
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• v.26 no.4
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• pp.9-16
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• 2007

Input devices of wearable computer are difficult to use, so a lot of alternative pointing devices have been considered in recent years. In order to resolve this problem, this paper proposed a dynamic gain control method which is able to improve the performance of wearable pointing device and showed an experimental result comparing this method with conventional method. Also the effects of methods were compared in terms of device (wearable and desktop). The result of calculating throughputs(index of performance) by Fitts' law showed that the pointing performance in dynamic gain condition was improved 1.4 times more than normal gain.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.16 no.10
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• pp.931-937
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• 2003

The principle of the superconducting vortex flow transistor (SVFT) is based on control of the Abrikosov vortex flowing along a channel. The induced voltage is controlled by a bias current and a control current, instead of external magnetic field. The device is composed of parallel weak links with a nearby current control line. We explained the process to get an I-V characteristic equation and described the method to induce the external and internal magnetic field by the Biot-Savarts law in this paper. The equation can be used to predict the I-V curves for fabricated device. From the equation we demonstrated that the current-voltage characteristics were changed with input parameters. I-V characteristics were simulated to analyze a SVFT with multi-channel by a computer program.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.1-9
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• 2022

In this paper, we propose the Deep Learning-Based Companion Animal Abnormal Behavior Detection Service, which using video and sensor data. Due to the recent increase in households with companion animals, the pet tech industry with artificial intelligence is growing in the existing food and medical-oriented companion animal market. In this study, companion animal behavior was classified and abnormal behavior was detected based on a deep learning model using various data for health management of companion animals through artificial intelligence. Video data and sensor data of companion animals are collected using CCTV and the manufactured pet wearable device, and used as input data for the model. Image data was processed by combining the YOLO(You Only Look Once) model and DeepLabCut for extracting joint coordinates to detect companion animal objects for behavior classification. Also, in order to process sensor data, GAT(Graph Attention Network), which can identify the correlation and characteristics of each sensor, was used.

• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.99-106
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• 2010

In this paper, we propose an industrial fluid monitoring system which performs the flow control function and monitors fluid pressure transmitted from MFC(Mass Flow Controller) unit. This system consists of MFC unit, channel device, and monitoring management software. MFC unit transmits the measured data of the fluid pressure to the channel device which would provide the input/output interface between management software, monitoring and MFC unit. The monitoring and management software control and analyze by monitoring real time measurements of fluid pressure from each channel of MFC unit. This software can process 20 channels and 0.1 monitoring cycle which gives 200 data measurement per second (i.e., 720,000 data/hour). At this time, the storage space increases in proportion to the rise of input data. This growth of data and storage space makes loss of data access efficiency. Therefore, it demands the implementation by sensing scheme of change scope and data, which can effectively manage the data.

• Journal of the Korea Computer Graphics Society
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• v.19 no.2
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• pp.1-8
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• 2013

Captured human motion data has been widely utilized for understanding the mechanism of human motion and synthesizing the animation of virtual characters. Searching for desired motions from given motion data is an important prerequisite of analyzing and editing those selected motions. This paper presents a new method of content-based motion retrieval without the need of additional metadata such as keywords. While existing search methods have focused on skeletal configurations of body pose or planar trajectories of locomotion, our method receives a three-dimensional trajectory as its input query and retrieves a set of motion intervals in which the trajectories of body parts such as hands, foods, and pelvis are similar to the input trajectory. In order to allow the user to intuitively sketch spatial trajectories, we used the Leap Motion controller that can precisely trace finger movements as the input device for our experiments. We have evaluated the effectiveness of our approach by conducting a user study in which the users search for dozens of pre-selected motions from baseketball motion data including a variety of moves such as dribbling and shooting.