近年、証券業界ではFinTechサービスを積極的に検討、導入している。本報告では、大手・準大手証券におけるFinTechサービスの一つであるスマートフォン専業証券に着目する。野村ホールディン グスは2019年に

This research has focused on the fuzzy logic model for evaluating the necessity of expanding the rail transit network to achieve sustainable transport development. It is essential to distinguish input parameters that can be obtained and updated frequently in a cost-effective way. A framework that can be employed to systemize the planning process by using the ‘Rail Transit Fuzzy Logic Model’. It can be characterized as a spatial suitability oriented fuzzy approach by using five inputs (slope, geology, population, land use and stream), 1 output (Suitability Score) and 108 If-Then rules to assist in combining these data sources in the MATLAB environment. This study consists of three main steps: (i) development of a fuzzy inference system (FIS), (ii) design of the graphical user interface (GUIDE toolbox), and (iii) suitability score database production for the study area. Fuzzy rule-based systems have been applied with parameters represented by fuzzy diagrams that are integrated into an aggregate form to obtain a spatial suitability score. This analysis allows us to assign suitability scores for any specific type of study area. The study area is composed of 208 rows and 216 columns that are uploaded and modelled in MATLAB R2021b as a 216-by-208 matrix. This method commonly has not been employed and processed for a rail network that covers a large geographical area spanning several regions in a city. The proposed methodology offers systematic qualitative data available for decision-makers to be used in the evaluation of rail transportation investments.

Recent automotive systems require various data, including data from on-board sensors and external sources to recognize environmental conditions. As the amount of sensor data used in automotive systems increases, processes that use such data become increasingly complicated. In addition, similar data processing can be duplicated over multiple applications. To address these issues, a data stream management system (DSMS) for automotive systems based on a data integration architecture has been developed. However, hard real-time deadlines cannot be guaranteed due to unpredictable load changes caused by data streams. For example, the arrival time and CPU utilization requested by data streams from vehicle-to-vehicle communications change rapidly depending on environmental conditions. We propose the reservation-based operator path earliest deadline first (ROP-EDF) scheduling algorithm for an automotive DSMS under overload conditions. The proposed algorithm reserves processor time preferentially for hard real-time tasks so that tasks can meet deadlines under overload conditions. ROP-EDF can be used for load testing on a single processor system. Experimental results show the effectiveness of the proposed algorithm compared with existing algorithms relative to the deadline miss ratio under overload conditions.

This paper examines the definitions and measurement scales for financial literacy presented in previous studies in order to develop a new financial literacy scale. The early definition of financial literacy basically meant “financial knowledge,” but the latest definition has been extended to include or refer to consumers’ financial behaviours, consumers’ interactions with their social and economic environments, and the effect of cognitive biases on consumers’ financial behaviours. On the other hand, conventional measurement scales for financial literacy are generally composed of declarative knowledge questions and numerical ability tests concerning personal finance. This paper addresses the fact that previous financial literacy scales have been based on the traditional concept of “Homo economicus”. We suggest that it is necessary to develop a new financial literacy scale that is comprised of critical thinking disposition such as “awareness for logical thinking” or “evidence-based judgment.”