Inter-organizational innovation networks play a crucial role in fostering collaborative innovation and knowledge exchange among organizations. However, managing such networks poses unique challenges due to their complex and dynamic nature. This study proposes a multi-level network management method aimed at enhancing the effectiveness of inter-organizational innovation networks. The method integrates both structural and relational aspects of network management and recognizes the importance of different levels of analysis, including the individual, organizational, and network levels. By adopting a holistic approach, the proposed method enables managers to navigate the intricacies of inter-organizational networks, promote collaboration, and facilitate innovation. The effectiveness of the method is demonstrated through a case study of an inter-organizational innovation network in the technology sector. The findings highlight the significance of multi-level network management in achieving successful collaboration and innovation outcomes within inter-organizational contexts.

This study aims to provide additional evidence on the relationship between technology partnership portfolios and firm innovation performance. Technology partnerships have become increasingly important for firms seeking to enhance their innovation capabilities and stay competitive in dynamic markets. The abstract presents a summary of the study's objectives, methodology, findings, and implications.

This article presents a novel approach to optimize capacitive energy storage for load frequency control in wind-diesel hybrid power plants. The study employs the Imperialist Competitive Algorithm (ICA) as a computational tool to achieve efficient and effective control of power generation and frequency regulation in such hybrid systems. The research aims to enhance the stability and reliability of wind-diesel hybrid power plants by optimizing the sizing and placement of capacitive energy storage units. The results demonstrate the effectiveness of the proposed approach in improving load frequency control and overall system performance.

The article presents the results of the optimal parameters of the soil-shifting plates mounted on knives for processing the slopes of the ridges for sowing seeds of gourds.

This study presents a comprehensive analysis of fuel octane numbers using accelerometer-based assessment and statistical metrics. The performance of gasoline engines heavily relies on the octane number of the fuel used, which indicates its resistance to knocking. Traditional methods for measuring octane numbers are time-consuming and expensive. In this research, an innovative approach is proposed, utilizing an accelerometer to measure engine vibrations under controlled conditions. Correlation analysis and regression modeling were performed to establish the relationship between accelerometer readings and octane numbers. The results demonstrate a strong positive correlation and the development of a predictive model for estimating octane numbers based on accelerometer data. This study provides valuable insights for fuel development, engine optimization, and real-time octane number estimation.