The experimental proton resonance data for the reaction P+48Ti have been used to calculate and evaluate the level density by employed the Gaussian Orthogonal Ensemble, GOE version of RMT, Constant Temperature, CT and Back Shifted Fermi Gas, BSFG models at certain spin-parity and at different proton energies. The results of GOE model are found in agreement with other, while the level density calculated using the BSFG Model showed less values with spin dependence more than parity, due the limitation in the parameters (level density parameter, a, Energy shift parameter, E1and spin cut off parameter, σc). Also, in the CT Model the level density results depend mainly on two parameters (T and ground state back shift energy, E0), which are app

The fuzzy assignment models (FAMs) have been explored by various literature to access classical values, which are more precise in our real-life accomplishment. The novelty of this paper contributed positively to a unique application of pentagonal fuzzy numbers for the evaluation of FAMs. The new method namely Pascal’s triangle graded mean (PT-GM) has presented a new algorithm in accessing the critical path to solve the assignment problems (AP) based on the fuzzy objective function of minimising total cost. The results obtained have been compared to the existing methods such as, the centroid formula (CF) and centroid formula integration (CFI). It has been demonstrated that operational efficiency of this conducted method is exquisitely deve

The fuzzy assignment models (FAMs) have been explored by various literature to access classical values, which are more precise in our real-life accomplishment. The novelty of this paper contributed positively to a unique application of pentagonal fuzzy numbers for the evaluation of FAMs. The new method namely Pascal's triangle graded mean (PT-GM) has presented a new algorithm in accessing the critical path to solve the assignment problems (AP) based on the fuzzy objective function of minimising total cost. The results obtained have been compared to the existing methods such as, the centroid formula (CF) and centroid formula integration (CFI). It has been demonstrated that operational efficiency of this conducted method is exquisitely develo

Interface evaluation has been the subject of extensive study and research in human-computer interaction (HCI). It is a crucial tool for promoting the idea that user engagement with computers should resemble casual conversations and interactions between individuals, according to specialists in the field. Researchers in the HCI field initially focused on making various computer interfaces more usable, thus improving the user experience. This study's objectives were to evaluate and enhance the user interface of the University of Baghdad's implementation of an online academic management system using the effectiveness, time-based efficiency, and satisfaction rates that comply with the task questionnaire process. We made a variety of interfaces f

XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.

A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.

Digital Models of Elevations (DEMs) Using Surfer 16, which are interpolated to create three-dimensional controls for the entire terrain, are typically used in visualization of geospatial entities. The interpolation method used determines how accurate the resulting terrain model will be, hence it is necessary to compare the effectiveness of various approaches in this situation. Numerous generic interpolation techniques, using inverse distance to a power, triangulation as with linear interpolation, the nearest neighbor, and kriging, have been studied. These interpolation techniques produced DEMs. With the aid of SURFER software 16, the primary goal of this effort was to introduce the DEM using a spatial interpolation method and to pre

Digital Models of Elevations (DEMs) Using Surfer 16, which are interpolated to create three-dimensional controls for the entire terrain, are typically used in visualization of geospatial entities. The interpolation method used determines how accurate the resulting terrain model will be, hence it is necessary to compare the effectiveness of various approaches in this situation. Numerous generic interpolation techniques, using inverse distance to a power, triangulation as with linear interpolation, the nearest neighbor, and kriging, have been studied. These interpolation techniques produced DEMs. With the aid of SURFER software 16, the primary goal of this effort was to introduce the DEM using a spatial interpolation method and to pre

This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark