http://www.kdip.ir/ Intelligent Knowledge Exploration and Processing en daily 1 Fri, 20 Feb 2026 00:00:00 +0330 Fri, 20 Feb 2026 00:00:00 +0330 http://www.kdip.ir/article_242474.html Accurate and rapid detection of brain tumors in MRI images is one of the major challenges in the field of medical imaging and clinical decision-making. The limitation of labeled data and the structural diversity of tumors highlight the necessity of efficient, interpretable, and robust deep learning models that can handle data scarcity. In this study, a hybrid deep learning model for brain tumor classification is proposed, which integrates the architectures of ResNet50 and DenseNet121 along with the CBAM attention module. The ResNet50 architecture, through residual connections, enables deep and stable learning, while DenseNet121, with its densely connected structure, facilitates more effective feature transfer and improves the overall performance of the model. The CBAM module, by applying channel and spatial attention, directs the model’s focus to critical image regions, thereby enhancing classification accuracy.In the proposed model design, strategies have been employed to strengthen the model’s robustness against limited data, improving its stability and generalizability. A review of previous studies indicates that the integrated use of these three components can significantly boost the performance of neural networks in brain tumor MRI classification. Furthermore, this research addresses the challenges arising from data limitations and explores solutions such as transfer learning, data augmentation, and the incorporation of uncertainty estimation. http://www.kdip.ir/article_242475.html Wireless sensor networks (WSNs) have become a cornerstone of modern monitoring systems due to their wide-ranging applications in environmental observation, industrial automation, and military operations. Despite their growing importance, these networks face two persistent challenges: maximizing network lifetime and ensuring robust security against threats, particularly distributed denial-of-service (DDoS) attacks, which can severely disrupt operations. This research introduces the MITDCPS protocol as a novel solution addressing both energy efficiency and security simultaneously. MITDCPS operates by intelligently balancing cluster sizes and optimizing intra-cluster transmission distances, which significantly reduces energy consumption and prolongs the network’s operational life. The protocol’s structure comprises four systematically designed stages that manage clusters efficiently while minimizing intra-cluster communication distances. Beyond energy optimization, MITDCPS incorporates a security mechanism capable of identifying abnormal traffic patterns and isolating malicious nodes, thereby providing effective resistance against DDoS attacks. Experimental results indicate that MITDCPS not only enhances energy efficiency but also substantially strengthens network security, creating a stable and reliable environment for critical WSN applications. By integrating energy management with threat mitigation, MITDCPS offers a comprehensive framework that ensures both longevity and protection, highlighting its potential as a practical approach for real-world wireless sensor network deployments. Overall, this study demonstrates that careful cluster management and proactive security measures can coexist in a single protocol, addressing two of the most pressing challenges in the field. http://www.kdip.ir/article_242476.html This research addresses the problem of global path planning for a mobile robot in grid-based environments, where the path must simultaneously be short, collision-free, and dynamically smooth. The use of crisp fitness functions in such problems typically leads to severe discontinuities in the search space and high fluctuations in solution quality across repeated runs. The objective of this study is to improve stability and reduce the variance of the results of an improved version of the Bat Algorithm, without modifying its core update equations. To achieve this, a Mamdani-type fuzzy fitness system is designed. This system evaluates three linguistic inputs using continuous, overlapping triangular and trapezoidal membership functions. The fuzzy rule base is configured such that safety is prioritized over efficiency and smoothness, and its output is a normalized cost in the range [0,1] that replaces the crisp fitness value. The implementation is compared with a purely crisp version across multiple independent runs. Experimental results show that the average path length in the fuzzy case remains within an acceptable range, while the coefficient of variation of path length and fitness value decreases from approximately 0.38 to about 0.15 and 0.16, respectively, and the variance is reduced by approximately 90–95%. This significant reduction in dispersion indicates a smoother optimization landscape and more stable algorithmic convergence. The findings demonstrate that adding a fuzzy fitness layer on top of metaheuristics can substantially enhance the robustness and reliability of mobile robot path planning and can be readily generalized to other grid-based planning problems. http://www.kdip.ir/article_242956.html The present research was conducted with the aim of examining the impact of corporate social responsibility on consumer citizenship behavior, considering the mediating role of perceived consumer effectiveness and consumer trust in chain stores in Mashhad. This research is applied in terms of objective and descriptive-survey in terms of method. To collect information, a combination of library and field research methods was used. The statistical population of this research includes all customers in chain stores in Mashhad, which is unlimited in number. According to Morgan's table, the sample size is 384 people, and to ensure the return of questionnaires, 400 questionnaires were distributed randomly among them. The data were analyzed using structural equations and with the help of LISREL software. The results indicate that corporate social responsibility has a significant impact on consumer citizenship behavior, considering the mediating role of perceived consumer effectiveness and consumer trust in chain stores in Mashhad.The present research was conducted with the aim of examining the impact of corporate social responsibility on consumer citizenship behavior, considering the mediating role of perceived consumer effectiveness and consumer trust in chain stores in Mashhad. This research is applied in terms of objective and descriptive-survey in terms of method. To collect information, a combination of library and field research methods was used. The statistical population of this research includes all customers in chain stores in Mashhad, which is unlimited in number. According to Morgan's table, the sample size is 384 people, and to ensure the return of questionnaires, 400 questionnaires were distributed randomly among them. The data were analyzed using structural equations and with the help of LISREL software. The results indicate that corporate social responsibility has a significant impact on consumer citizenship behavior, considering the mediating role of perceived consumer effectiveness and consumer trust in chain stores in Mashhad.