Bio-identification by deep neural networks in such devices with limited computational power and memory capacity as mobile phones has become an essential but challenging task today. As faces have rather invariable features among human biometric features, face recognition is considered as the most important biometric identification task. Face recognition has been widely used for user authentication in security systems such as electronic payment systems as it can identify faces from facial images from photographs or videos, and it has been studied for years.

The face recognition system using convolutional neural networks is considered as the best method among the existing ones. Face recognition network models that have been developed recently and have proved to be superior in performance cannot be used for real-time face recognition in devices with limited computational resources such as low base computers or mobile phones because their structure is very complex and they need a large amount of computation. What is more, reducing the number of layers continuously to reduce computational burden affects recognition performance.

In previous studies, several methods to improve the trade-off between speed and recognition performance were proposed. One of them is GhostFaceNets which uses Ghost module to reduce the feature map redundancy, where the trade-off between speed and recognition performance is improved by extracting less repetitive feature maps with small amount of computation. In GhostFaceNets, they improved the trade-off between speed and accuracy by performing the attention operation using a DFC (decoupled fully-connected) attention. However, the DFC attention has limitations in capturing wide spatial information, which may lead to the degradation of recognition performance.

Jo Kwang Chol, a researcher at the Institute of Information Technology, has designed a network structure with low computational cost and improved performance by combining the self-attention module with the extended Ghost module based on the backbone of GhostFaceNets, and verified its accuracy using international standard databases.

The results showed that the proposed network model brings significant improvement in face recognition performance with 99.74% in LFW and 97.7% in AgeDB-30 and that with 42 MFLOP, it can support stable real-time face recognition in embedded devices.

For more details, you can refer to his paper “GhostFormerNet: A Lightweight Face Recognition Method based on Extended Ghost Module and Self-Attention” in “2025 International Conference on Graphics and Signal Processing” (EI).

Rare earth minerals including pyrochlore contain uranium, thorium and rare earths, and the processing of these rare earth ores must result in a mixed solution containing uranium, thorium and rare earths.

Many studies have been carried out to determine the concentration of individual components in the mixtures of uranium, thorium and rare earth, and thus, various instrumental methods have been widely used. However, these methods have disadvantages such as the need for special analytical tools, the need for sample solidification and the high cost of analysers concerned.

Due to the similar spectroscopic properties of uranium, thorium and rare earths, some analytical methods have been developed to separate uranium, thorium and rare earths and determine the concentration of individual components using various separation methods including extraction and ion exchange. However, these methods have other disadvantages such as long analysis time and complicated operation.

Kwon Myong Gang, a researcher at the Institute of Analysis, has investigated analytical methods for simultaneously determining individual components in a mixture of uranium, thorium and cerium obtained during the pyrochlore hydrometallurgical process, using spectrophotometric methods.

First, he proved that the maximum absorption wavelengths of uranium, thorium and cerium in three different solutions (3, 0.1mol/L HCl, 1mol/L CH₃COOH) were 660, 652 and 660nm, respectively. Then, he used the relationship between the concentration of individual components and the absorbance to determine the absorption coefficients of individual components in different solutions. After that, based on the principle of absorbance additivity, he established a simulation equation between absorbance and concentration and used it to determine the concentration of individual components in the mixture solution. The concentration limit within which the additivity of absorbance in the mixed solution is established was less than 2mg/L of uranium and cerium, and 1.5mg/L of thorium. The error of analysis was less than 3%.

For further details, you can refer to his paper “Simultaneous Spectrophotometric Analysis of Uranium, Thorium, Cerium During Pyrochlore Hydrometallurgical Process” in “Proceedings of KUTIC-2025”.

At present, in rare earth production, double salt precipitation is widely used for separation of rare and non-rare earth elements, and separation of quaternary cerium and trivalent rare earth elements. Rare earth double sulphates are commonly treated by hydroxide, but the filtration is difficult because the rare earth hydroxide obtained during the hydroxide conversion is an amorphous precipitate. In contrast, if RE double sulphates are converted into carbonates, filtration and dissolution by acids become easier because RE carbonates are crystalline precipitates.

Ri Sun Chol, a researcher at the Faculty of Chemistry, conducted a study to convert rare earth double sulphates obtained from monazite sulphate leachates to rare earth carbonates using sodium carbonate.

Aiming to improve the conversion of rare earths and to effectively separate U and Th from RE carbonates, he investigated the influence of reaction parameters using Taguchi-Grey Relation Analysis (Taguchi-GRA), determined the optimum conditions and studied the separation of U and Th.

When reaction temperature is 80℃, reaction time 2h, additive amount of sodium carbonate 1.5 times the theoretical amount, the ratio of solid to liquid 2:1 and stirring speed 200r/min, the RE carbonate conversion was 97.1% and the U and thorium removal 80.8% and 0.3%, respectively.

For more information, please refer to his paper “Study on the Carbonate Conversion of Rare Earth Double Sulfates” in “Proceedings of KUTIC-2025”.