Jo Sep 15, 2023
A research team led by Song Yong Dok, a researcher at the Faculty of Distance Education, has developed a new analysis system based on face-image recognition for evaluating students’ study attitude.
The system can analyze students’ emotions by recognizing, detecting and verifying their face-images. Emotion affects study attitude to such a great degree that emotion analysis plays a big part in analysis of study attitude.
The system consists of image input module, image recognition module, emotion detection module, expression detection module, attitude analysis module, etc. In the image input module, images or real-time images taken by an IP camera and a Web camera are fed. In the image recognition module, one or more students are identified and feature points on their faces are extracted. In the emotion detection module, students’ main feelings are detected in 8 kinds including happy, sad and surprised and they are presented on value-charts. In the expression detection module, expressions like smile, laugh, blink, opened mouth, frowning, etc. are detected.
This system can put education management on a scientific basis by analyzing students’ study-attitude and automatically checking their attendance.
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Jo Sep 14, 2023
Mun Chol Su, a researcher at the Faculty of Metal Engineering, has developed an analytical method and analytical instrument for analyzing rapidly and accurately group of pitch binder that used to take a long time.
Rapid and accurate evaluation of the quality of pitch binder used for electrode production is important for scientific production and active and timely quality control of products.
Group composition is a very important parameter for evaluating the properties of binders used for electrode production and for determining the appropriate process conditions, but long analysis time limits their wide application on production sites.
In order to reduce the time spent on group composition analysis, he employed a reduced pressure filtration method, and a method of simultaneous analysis with different solvents for one sample, thus greatly shortening the analysis time.
Then, he designed and manufactured an instrument for rapid analysis of the group composition to minimize errors made by unskilled analyzers and to prevent environmental pollution inside analytical chambers by organic solvents.
The instrument consists of a thermostatic dissolver, a suction filter, and an exhaust fan, and temperature measurement and time adjustment in each section are automatically controlled by a microprocessor.
The thermostatic dissolver is designed so that solvents and samples can be heated in a water bath at a specified temperature, and temperature measurement and temperature control are carried out by an intelligent PID thermostat.
The suction filter is designed to allow rapid filtration of dissolved pitch samples and solutions in the thermostatic dissolver under reduced pressure.
The exhaust fan is placed inside the instrument to discharge volatile organic solvent to the outside and to work all the time of analysis.
Now, it only takes about five hours for one analyzer to perform a group analysis that used to take over 50 hours, which means reduction in the consumption of labour and power.
The analytical method and instrument might help the factories and enterprises that use pitch as binder quickly and actively control their production processes in accordance with the changing conditions of raw material supply.
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Jo Sep 8, 2023
A research team led by Pak Kwang Hyok, a researcher at the Faculty of Distance Education, has conducted a study of GloVe (Global vector) for extracting the features of Korean.
While CBOW or skip-gram is the prediction task of a contextual word, GloVe is the presentation method by the number of co-appearance of words.
Skip-gram can reflect longer-distance information through skips between some words but this reveals a defect, that is, hard to reflect contextual information.
Therefore, Korean sentence corpora segmented by Byte Pair Encoder (BPE) are needed for extracting the features of Korean by means of GloVe.
The research team used an analysis engine based on the Long-Short Term Memory for BPE.
The research result showed that Korean feature extraction by GloVe was better in F-score estimation than that by CBOW or skip-gram.
This method can be applied to Korean sentence similarity evaluation for online exams and bibliographic search systems.
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Jo Sep 4, 2023
A research team led by Chae Wi Song, a researcher at the Faculty of Distance Education, has developed an authentication system in which users are authenticated by analysis of keystroke dynamics.
Biometric authentication systems identify individuals by their physiological features (fingerprint, skin, retina, iris, etc.).
Each individual’s keystroke pattern is unique and a unique profile can be constructed by their typing speed, key press release timing, pressure applied, and finger positions on a keyboard.
The user authentication system based on this keystroke pattern is appealing for many reasons: simple and transparent authentication and no need for any extra equipment for feature capture.
The research team chose key press time and key release time among many keystroke patterns.
Key press time and key release time enable extraction of four features ― key hold time, key press latency, intervals between key press and release, and release and press. They used random forest algorithm for user authentication. The basic idea is to construct many trees using random vectors sampled from a data set.
This system guarantees fair online exams by automatically blocking several kinds of cheating attempts such as taking exams in place of examinees, keying in answers read by others, etc.
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Jo Aug 30, 2023
Android-based oscilloscopes have been developed for research and educational purposes because they are able to acquire, transmit, display, and analyze any electrical signals since they are mobile and easy to operate.
Due to the speed limitation of wireless transmission channels, android oscilloscopes have some limited performances on several aspects such as bandwidth, waveform capturing rate (WCR), etc.
Kim Mun Hyok, a section head at the Faculty of Automation Engineering, has proposed a real-time lossless data compression scheme to solve a bottleneck of continuous data flow from a data acquisition device (DAQ) to a smartphone. This scheme consists of triggering a signal and encoding differences between waveforms (DBWs).
He also proposed an advanced structure of android bluetooth oscilloscope (ABO) to implement the proposed compression algorithm with field programmable gate array (FPGA)-based hardware and software.
To evaluate WCR improvement, he first analyzed relationship between WCR and compression ratio, and then, verified the compression efficiency by MATLAB simulations using various waveforms, such as simple sinusoidal, complex periodic, square, and chirp waveforms.
He finally studied the robustness of this instrument within the range of 0–15% noise amplitude and 0–2rad phase offset. All the experimental results showed that the proposed scheme can enhance WCR and at the same time it can also be applied to the wireless transmission fields collecting and displaying electrical waveforms.
If further information is needed, please refer to his paper “A Triggering-and-Encoding Lossless Compression Scheme for Waveform Capturing Rate Enhancement of Android Bluetooth Oscilloscope” in “IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT” (SCI).
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