The displacement ventilation system (DVS) is one of the mechanical ventilation systems which blow the air with lower temperature than indoor air from the lower part of a room and cause upward moving of indoor air by buoyant force to exhaust it at the ceiling.

As DVS is aimed at meeting only the requirements of workplaces, the thermal and concentration stratification is formed between lower and upper parts. DVS makes the quality of the air better and exhausts the polluted air effectively, and therefore the saving efficiency of energy is remarkable. In the designing of DVS, the height of thermodynamic stratification has to be controlled to be higher than that of the workplace for people, but it should not be too high. This is because being too high might cause an increment in the amount of air blast, which results in waste. Thus, the determination of the height of thermodynamic stratification is one of the vital problems in the application of DVS.

Paek Myong Chol, a section head at the Faculty of Thermal Engineering, analyzed the characteristics of indoor airflow and temperature distribution in the hybrid displacement ventilation system (HDVS) where a vertical supply duct was installed at the middle height of a building by computational fluid dynamics (CFD). Then, he investigated the specific influence of the velocity of air inflow and the length of the supply duct on the air temperature.

The results show that the proposed system saves 35kw of energy compared to the mixing ventilation system, which leads to the annual energy saving of about 80 000kW·h.

If more information is needed, you can refer to his paper “Energy Saving Characteristics of Hybrid Displacement Ventilation System with Vertical Supply Duct” in “GAS Journal of Engineering and Technology” (SCI).

All the digital data stored, copied and distributed on the network have their own specific information, and digital images, as one of the fastest multimedia formats that can deliver their information in a visual way, particularly have a great amount of information. Most of the digital images transmitted through network are private, and especially, those with sensitive information such as medical diagnostic images can lead to irrevocable disaster when they are disclosed to be abused. Therefore, it is very important for digital images to be secured.

In general, digital images, when compared to text data, are characterized by 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, it requires a prompt and secure image encryption algorithm. From this necessity, many precedent researchers have proposed some improved chaotic maps and applied them to various image encryption algorithms.

Song Ok Chol, an institute head at the Institute of Information Technology, configured a novel 3D-ICCM (3D Infinite Collapse Coupling Map) with better chaotic performance by combining three 1D infinite collapse maps that has the best chaotic characteristics among the existing 1D chaotic maps, and analyzed its chaotic characteristics through a comparison with the previous 3D-ICM. Then, he proposed a new simple-structured pixel-level image encryption algorithm and evaluated its performance by applying the proposed 3D-ICCM.

The experimental simulation and analysis show that the proposed 3D-ICCM and image encryption algorithms have excellent performance.

For more information, please refer to his paper “Robust pixel-level image encryption algorithm using 3D infinite collapse coupling map” in “Multimedia Tools and Applications” (SCI).

In the past, users only found the information they needed on the Web, but recently newly-developed information services give convenience to users by automatically providing useful information for users thanks to the development of the Web.

Recently, with the development of cloud computing platforms, mobile Internet applications are constantly emerging. Mobile retrieval is one of the most important applications of mobile Internet. Mobile search must be personalized. This is because different users need different information depending on their environments and interests even if the query required is the same.

Recommendation systems are widely used on the Web as this kind of service. The recommendation system is a personalized information filtering system that provides users with new items that might please users based on the assessment information or purchase information about items that users have already experienced.

Recently, recommendation systems have been adopted in various domains such as recommendation of commodities that users wants to buy, recommendation of films, TV, broadcast, music, restaurants, etc., identification of web pages of interest to users, and selection of appropriate information retrieval methods. However, insufficient user’s personal information and frequent use of other computers increase the difficulty in collecting users’ personal information. Due to the nature of mobile phones in mobile environments, user’s personal information is easily collected by telecommunication and it is no longer a difficult problem.

With a view to further increasing the effectiveness of personalized mobile retrieval method, Kim Kwang Hyok, a researcher at the Institute of Information Technology, proposed a hybrid filtering recommendation method by combining content-based filtering and cooperative filtering.

The experiments demonstrate that the proposed method can significantly improve the effectiveness of personalized mobile retrieval.

You can find his paper “Study on Personalization Information Retrieval Using Hybrid Filtering Recommendation Method” in “2025 10th International Conference on Intelligent Information Technology (ICIIT 2025)”.