In this study, we undertook detailed experiments to increase hydrogen production efficiency by optimizing the thickness of titanium dioxide (TiO2) thin films. TiO2 films were deposited on p-type silicon (Si) wafers using atomic layer deposition (ALD) technology. The main goal was to identify the optimal thickness of TiO2 film that would maximize hydrogen production efficiency while maintaining stable operating conditions. The photoelectrochemical (PEC) properties of the TiO2 films of different thicknesses were evaluated using open circuit potential (OCP) and linear sweep voltammetry (LSV) analysis. These techniques play a pivotal role in evaluating the electrochemical behavior and photoactivity of semiconductor materials in PEC systems. Our results showed photovoltage tended to improve with increasing thickness of TiO2 deposition. However, this improvement was observed to plateau and eventually decline when the thickness exceeded 1.5 nm, showing a correlation between charge transfer efficiency and tunneling. On the other hand, LSV analysis showed bare Si had the greatest efficiency, and that the deposition of TiO2 caused a positive change in the formation of photovoltage, but was not optimal. We show that oxide tunneling-capable TiO2 film thicknesses of 1~2 nm have the potential to improve the efficiency of PEC hydrogen production systems. This study not only reveals the complex relationship between film thickness and PEC performance, but also enabled greater efficiency and set a benchmark for future research aimed at developing sustainable hydrogen production technologies.

In this study, refer to cases of domestic flower exporters, important factors for flower export logistics were categorized and analyzed and efficient logistics processes were suggested. According to export profitability and product quality, important factors were categorized as quarantine, costs, lead time. By applying important factors, commonly using route- SHIMONOSEKI, reverse distribution prevented route-HAKATA, Excellent market access routes-OSAKA were analyzed and efficient logistics processes were suggested.

Data Envelopment Analysis (DEA) is a useful tool to analyze the relative efficiency of decision making units (DMU) characterized by multiple inputs and multiple outputs. This method has been popularly used as an analytical tool to suggest some strategic improvement. To do this, the results of DEA provide decision makers with a single efficiency score, efficient frontier, return to scale, benchmarking decision making units, etc. The purpose of this paper is to evaluate research performance of 38 universities and provide an inefficient university with the way of organizational changes to be an efficient university by using DEA. Various input and output variables are used to identify technical and scale inefficiency. Additionally, we analyze how an inefficient DMU could be changed an efficient DMU based on a case university. This result will give an insight of constructive directions for increasing of research performance to university decision makers.

  The enormous budget of government and manpower are invested to the government funded institutes every year. The R&D investment focused on input has to be turned toward the investment based on the effectiveness of R&D activities. Measuring the efficiency

Six sigma, contrary to TQM, offers the concrete process for accomplishing the management innovation. Nowadays it has become as a standard means. Many companies claim to stand for durable management and would like to get customers' satisfaction and more profit with total six sigma activities. Under the present conditions we propose how to maximize efficiency with six sigma application on transportation management that is an issue among many companies.

The purpose of this study is to analyze the efficiency of research institutes of futures companies, and to promote the development of futures market and real economy. This study employs DEA-solver software to conduct super-efficiency data envelopment analysis (SE-DEA), and also selects 40 representative futures research institutes in China as decision-making units (DMUs). For data of input and output indicators, we collect from the China Futures Association, Futures Daily, Hexun.com and Webstock.com respectively, and the time duration is the 103 trading days between from October 2019 to February 2020. Then the indicator for the strategy accuracy rate is calculated separately by analyzing the strategies published by each DMUs in public media. In conclusions, most institutes have excessive investment in human resources, and also have insufficient strategy accuracy rate and insufficient published research reports. The findings of this study suggest that Chinese futures companies need to improve the efficiency of research institutes, and better meet the demand of the financial market. In fact, the analysis of the efficiency of the futures company research institute has not been found in the literature worldwide, Application of DEA model in efficiency analysis of securities and futures research institutions and establishment of indicators are the innovations of this paper.