Jo Apr 21, 2025
Detecting and characterizing lineaments using satellite images or digital elevation model data is a field of satellite image processing, providing a lot of useful information for geological structure analysis and mineral exploration. In recent years, many studies have been devoted to the identification of lineaments and their relationship with their distribution characteristics, geological structure and mineral deposit distribution.
Song Man Hyok, a section head at the Faculty of Earth Science and Technology, has proposed a new method for extracting the image features and lineaments related to the local extrema of an image or a digital elevation model (DEM) such as ridges and valleys, based on the continuous wavelet transform (CWT) of a set of variously illuminated hillshades.
The method is based on the principle that a hillshade can exactly reflect the lineaments nearly perpendicular to the illumination direction of the hillshade, but not other ones.
The method consists of four steps: (1) preparation of a set of differently illuminated hillshades of the input data, (2) detection of directional edges nearly perpendicular to the illumination direction from each hillshade based on the CWT, (3) a combination of multidirectional edges into an omnidirectional feature image, and (4) identification of lineaments through linkage and linearization of image feature lines.
He applied this method to the geological structure analysis of the study areas to provide a prerequisite for resource exploration and land development.
For detailed information, please refer to his paper “A Method to Extract Image Features and Lineaments Based on a Multi-hillshade Continuous Wavelet Transform” in “Mathematical Geosciences” (SCI).
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Jo Apr 20, 2025
In general, there are different types of uncertain systems with small samples and poor information in the real world. The grey system is a system with partially known (white) and partially unknown (black) information. Grey models play an important role in modeling, prediction, evaluation, decision making, control and system analysis in many fields because of their simple expression and computation, and excellent prediction performance with insufficient data.
GM(1, 1) model is an important part of the grey model, where ‘GM’ stands for ‘grey model’ while the first number ‘1’ in brackets indicates the first order differential equation and the second number ‘1’ indicates the differential equation of one variable. It is mathematically based on the first order linear ordinary differential equation and least square method. It requires a relatively small amount of data (four or more samples) to develop a mathematical model, and a simple calculation process to analyze the behavior of an unknown system. It has been widely used because it does not require a large number of samples and has low computational complexity and there is no limitation of statistical assumptions.
Up to now, many research works to improve the accuracy of the GM(1, 1) have been carried out on the following aspects. Most of them have used mean absolute error (MAE), mean absolute percentage error (MAPE), mean squared error (MSE) and root mean squared error (RMSE). The accuracy measures are calculated using the arithmetic average operation of errors at the fitting points, and they include no sufficient information about prediction accuracy. Consequently, most of the previous works may be regarded as the works for improving the fitting accuracy of the GM(1, 1). It may be a common drawback of the previous works for improving the performance of the GM(1, 1).
Yang Won Chol, a researcher at the Faculty of Materials Science and Technology, has proposed an improved GM(1, 1) model based on weighted mean squared error (MSE) and optimal weighted background value: OB-WMSE-GM(1, 1). He applied it to one simulation example and two application examples to verify its effectiveness.
In the simulations and applications, the errors for GM(1, 1) were much smaller than conventional GM(1, 1).
You can find the details in his paper “An improved GM(1, 1) model based on weighted MSE and optimal weighted background value and its application” in “Scientific Reports” (SCI).
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Jo Apr 18, 2025
Water is one of the most important natural resources for humans, and water quality is closely related to human health and life. Therefore, water quality evaluation (WQE) is very important for human health, life and environment and for water management. Since there are many water quality parameters that characterize the quality of water, it is very difficult to evaluate water quality levels.
Water quality index (WQI) is the most widely used WQE method that measures the comprehensive effect of the water quality parameters and ensures integration. It transforms multiple water quality parameters into a single value that quantifies the water quality level based on different mathematical approaches. It evaluates the water quality based on the relative weighted summation of multiple water quality parameters. The aim of WQI is to quantitatively evaluate water quality levels, and rank and classify water bodies according to their chemical, physical and biological water quality parameters.
Many international and local organizations have developed about twenty WQIs by making great efforts for water quality evaluation in different environments.
However, the WQE methods have non-negligible disadvantages. Their common drawback is the lack of visualization of WQE results.
Yang Won Chol, a researcher at the Faculty of Materials Science and Technology, has proposed a new visualized pointer meter-type virtual water qualimeter (VWQ-meter) based on a quadrant circular constellation graph (QCCG), by introducing the pointer meter and CG for WQE.
The proposed water qualimeter has a changeable broken linear pointer with variable lengths and shapes. It can evaluate water quality quantitatively as well as intuitively like traditional water qualimeters.
For more information, please refer to his paper “A new virtual water qualimeter with a changeable broken linear pointer based on a quadrant circular constellation graph” in “Water Science & Technology” (SCI).
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Jo Apr 16, 2025
Nuclear medicine testing is an important test that quantifies various functions and metabolism of human organs as images or graphs to provide not only morphological images but also functional information. In nuclear medicine diagnosis, radiopharmaceuticals are administered into the body and the target atoms are integrated in the given organ, which is then analyzed by means of time and image to obtain the function and properties of the organ. As a result, a foreign body is introduced in the body, and the measurement of drug must be done properly in order to avoid any unexpected phenomenon in the body.
The dose of radiopharmaceuticals is determined primarily by considering diagnostic information such as image quality, patient damage dose, test time, etc. In other words, the minimum dose available for diagnostic validation is set to be possible. Usually, in the case of radiopharmaceuticals with high enrichment for target organs or radioactive drugs labeled with relatively long half-life nuclides, low dose (radiation capacity) is set.
Kim Min U, a researcher at the Bioengineering Institute, has conducted a theoretical study of the type and decay characteristics of medical radiopharmaceuticals used in nuclear medicine, and presented a new method of spectral analysis available for medical radiopharmaceutical measurement.
First, he described a new baseline restorer with improved baseline recovery characteristics for radiation signals. Then, he performed a radiation spectrum analysis by using a new algorithm for peak detection and radioisotope estimation.
He conducted an analysis in two steps. First, he detected the photoelectric peak in the measured radiation spectrum using wavelet transform. Then, he compared the peaks detected using fuzzy inference with those of the previously published isotope peak library.
He compared the performance of the new spectral analysis method with the results of multiple regression analysis, which showed that the new method is superior.
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Jo Apr 15, 2025
In-situ gamma-ray spectrometry is widely used for not only exploration of radioactive mineral deposits but geological mapping and mineral exploration based on native radioactivity of minerals and rocks.
Jong Pok Yon, a researcher at the Faculty of Earth Science and Technology, has applied in-situ gamma-ray spectrometry to epithermal deposit survey in Ryongha area of Ryanggang Province.
First, he applied in-situ gamma-ray spectrometry to the Solryong alunite-kaolinite deposit well-known as a typical epithermal deposit to explain its gamma-ray spectrometric characteristics. The result showed the higher anomalies of K/(eU+eTh) ratio and K/eTh ratio in the area of alunite-kaolinite distribution. Second, he applied gamma-ray spectrometry in the new target about 5km west of the Solryong deposit, and mapped the gamma-ray spectrometry results.
The outlined anomalies of K/(eU+eTh) and K/eTh ratios are consonant with alunite-kaolinite outcrops. This indicates that the high anomalies of K/(eU+eTh) and K/eTh ratios can be utilized as the indicators for targeting epithermal deposits in this region.
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Jo Apr 14, 2025
It is well known that industrial processes generally have nonlinearity, time-varying features and uncertainty and that active disturbance rejection control is effective in controlling these industrial processes. The control of industrial processes, especially those with time delay, is becoming more difficult.
In several different production processes of industrial practice exist time delays such as state delay, input delay, transmission delay, output measurement delay, capacity delay, etc. Because of the time delay, the manipulated value cannot immediately reflect the disturbance that the system receives, the response characteristic has a large overshoot, adjustment time gets long, and even the system becomes unstable. Thus, the time-delay system is accepted as a difficult one to control.
Although a number of control schemes have been proposed to overcome the effect of time delay, it is very difficult to build accurate mathematical models for systems that are becoming increasingly complex, which results in the limitation of the application of current control theory and methods.
Applying active disturbance rejection control to time-delay systems can achieve good effects. The design methods for the active disturbance rejection control system of time-delay systems include time-delay neglect, dimensionality increase, output prediction, input prediction and input delay. In all these methods, a delay object is approximated or transformed into a delay-free object, and then an extended state observer is designed for observation.
Kim Ho, dean of the Faculty of Automation Engineering, has proposed a strategy for applying a multivariable linear active disturbance suppression control method to the brine heating process where there is a bias interference between the time delay and the control variables.
To compensate for the time delay, he used the input delay method in the extended state observer design. In addition, he constructed and introduced the decoupling matrix using the mathematical model information of the object to further enhance the decoupling effect.
The simulation results show that the performance of the proposed control system is very high.
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