Chaotic map which has excellent unpredictability and complexity is extensively used in various fields such as information security, information communication, system control, etc., and thus, there is an intensive research work to improve its chaotic characteristics.

Generally, digital images, compared to text data, have some characteristics different from ordinary data, such as very large capacity, high overlap and strong correlation between adjacent pixels. On the other hand, digital image data requires strong real-time property in communication, storage and distribution, and hence a fast and secure algorithm is needed for its encryption.

Jong Chol Min, a researcher at the Institute of Information Technology, studied the excellent chaotic performance of 2D-ICCM (2D Infinite Collapse Coupling Map) proposed by a researcher and proposed a simple-structured and fast-speed pixel-level image encryption algorithm using 2D-ICCM.

In image encryption algorithms using chaotic maps, it is common to repeat permutation and diffusion processes several times in order to increase the complexity of encryption and decryption processes. However, it results in degradation of the whole performance of encryption scheme, especially degradation of the ability to resist against cropping and noise attacks in the decryption process. Therefore, he bolstered the system complexity by using the chaotic output sequence used in each step interchangeably while repeating the permutation and diffusion process only twice.

He verified through various experiments that the pixel-level image encryption algorithm using 2D-ICCM has comparatively better chaotic performance than the previous 2D chaotic maps and algorithms.

His paper “A New Color Image Encryption Algorithm Using 2D Chaotic Map” was presented at “2025 10th International Conference on Intelligent Information Technology (ICIIT 2025)”.

In neural machine translation (NMT), BPE is usually used to limit vocabularies since a large number of vocabularies have a negative impact on training. Use of BPE could limit the number of vocabularies to some extent, but word alignment by attention mechanism cannot be done correctly since vocabularies are not properly segmented into word stems.

In neural machine translation, a huge number of vocabularies from the corpus have a negative impact on its training, and the longer the length of sentences which reflects the number of tokens is, the longer the training time gets. Therefore, it is important to perform good tokenization for minimizing the number of vocabularies and the length of sentences.

Kim Tong Gwon, a researcher at the Institute of Information Technology, proposed a stem and ending based tokenization (SEBT) method for improving the accuracy of word alignment by applying to tokenization a stem and ending dictionary which was made by segmenting BPE tokens into stems and endings.

This method has four advantages:

First, it is possible to reduce the number of vocabularies by correctly segmenting the stems and endings of Russian and Korean.

Second, it can improve learning efficiency by relieving the sparse word problem.

Third, it can improve the alignment accuracy between Russian and Korean tokens in the attention mechanism.

Fourth, it can reduce the training time since the sentence length is not increased after tokenization.

The experiments showed that this approach improves the performance of Russian-Korean NMT by improving the alignment between Russian and Korean tokens during the training of Russian-Korean neural machine translation and by reducing the number of Russian and Korean vocabularies.

You can find more information in his paper “SEBT: Word Stem and Ending based Tokenization in Russian-Korean Neural Machine Translation” in “2025 10th International Conference on Intelligent Information Technology (ICIIT 2025)”.

Since the impact performance of a drill is the main parameter for determining the drilling efficiency, study of the impact performance of a drill has a crucial influence on its productivity. As the impact energy of a rock drill is an important characteristic to evaluate its performance, many researchers have proposed various methods of measuring impact energy in order to evaluate it accurately.

Evaluating the impact performance of a rock drill by their methods requires a standardized rock sample in advance. Therefore, it is difficult to apply them to the performance test of a rock drill in batch production processes.

Yang Un Hyok, a section head at the Faculty of Mining Engineering, proposed a new structure of measuring device for estimating the impact energy of a percussive drill and analyzed its characteristics.

In the newly proposed measurement device, the maximum value of the pressure wave generated by the impact of 33-56J is approximately linear, with a range of 12-15MPa. It is shown that the error in the new proposed measurement device is less than 5% when the oil temperature is 10-70℃, air content is less than 2% and oil leakage is 10%.

The results of the study show that the proposed device ensures high measurement accuracy and significantly reduces damage to the sensor.

For more information, please refer to his paper “Influence of Oil Temperature, Air Content and Leakage in Hydraulic Measuring Device for Estimating Impact Energy of Rock Drill” in “Proceedings of KUTIC-2025”.