Two papers written by Dr. Tatsuki Fukuda, lecturer at Faculty of Data Science University, were published in Scopus magazine. The journals published are "WSEAS Transactions on Computer Research" and "International Journal of Advanced Computer Science and Applications".

<Dissertation Information>

■Academic journal name: WSEAS Transactions on Computer Research

■Thesis title: Randomized Kaczmarz Algorithm Applied D’Hondt Method for Extremely Massive MIMO Wireless Communication Systems

■Summary: Extremely massive MIMO (Multiple-Input Multiple-Output) is a technique to enable the spatial diversity. The systems employ a large number of antennas at the base stations, resulting in high computational complexity in various processes of wireless communications. The precoding process is one of them because the process requires the calculation of matrix inversion. The randomized Kaczmarz algorithm(rKA) is an iterative method to obtain the approximation so the computational time of precoding can be decreased. Some improvements of rKA were proposed so far, the iteration number required to obtain the approximation of inverse matrix is not so small. In this paper, we propose a new rKA method that applies the D’Hondt method, typically used for seat allocation in elections. In rKA process, the row vector is selected to use for updating approximation. Our method selects the row vector based on the D’Hondt method while the conventional rKA methods select the row vector probabilistic. Some results of simulation showed that the bit error ratio (BER) performance of our method is superior to other rKA methods at higher normalized transmit powers (NTP). The results also showed that the BER performances of our method with small number of iterations are more accurate than the others especially at high NTPs. That means our method can achieve the same BER performance with smaller number of iterations as the others, so the computational complexity of precoding with rKA is decreased.

<Dissertation Information>

■Academic journal name: International Journal of Advanced Computer Science and Applications

■Thesis title: Simulation-Based Analysis of Evacuation Information Sharing Systems Using Geographical Data

■Summary: In this study, we developed an Agent-Based Model (ABM) to simulate and improve evacuation rates during flood disasters. Utilizing the ”Evacuate Now Button,” a previously proposed system for sharing real-time evacuation rates among residents, our experimental findings demonstrate a significant enhancement in evacuation behavior through this system. Simulations were conducted using geographical data from Nobeoka City, Miyazaki Prefecture, and Toyohashi City, Aichi Prefecture. Results showed that the ”Evacuate Now Button” increased evacuation rates from a few percent to approximately 78% in Nobeoka City and 90% in Toyohashi City. We also investigated the effect of varying the range for calculating evacuation rates and the accuracy of the evacuation information shared with residents. It was found that larger calculation ranges led to higher final evacuation rates, while smaller ranges resulted in a quicker initial increase in evacuation behavior. These findings provide valuable insights for enhancing evacuation strategies and disaster preparedness in regions prone to floods.

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