The study aims to build a proposed training program for school leaders in the Sultanate of Oman on the planning practices of the Kaufman model in light of the needs and challenges of reality. It also aims to identify the challenges facing school leaders in practicing the stages of strategic planning. To achieve these objectives, the study adopted the descriptive approach due to its suitability to the nature of the study. A questionnaire was used to collect the needed data. The study sample included (225) individuals from school principals, their assistants and senior teachers in post-basic education in the Sultanate of Oman. After processing the data statistically, the study concluded that the reality of planning practices for school lea

Nowadays, information systems constitute a crucial part of organizations; by losing security, these organizations will lose plenty of competitive advantages as well. The core point of information security (InfoSecu) is risk management. There are a great deal of research works and standards in security risk management (ISRM) including NIST 800-30 and ISO/IEC 27005. However, only few works of research focus on InfoSecu risk reduction, while the standards explain general principles and guidelines. They do not provide any implementation details regarding ISRM; as such reducing the InfoSecu risks in uncertain environments is painstaking. Thus, this paper applied a genetic algorithm (GA) for InfoSecu risk reduction in uncertainty. Finally, the ef

Background The Transportation Problem (TP) is a detailed model in operations study with applications in logistics, supply chain management, and resource allocation. The classical IBFS methods including North-West Corner, Least Cost and Vogel’s Approximation have competitive computational efficiency, but they are very sensitive to the structure of the problem and usually lead to a solution that is far from the global optimum. Classic enhancement strategies like the Generalized Distribution (MODI) and Stepping-Stone (SS) approaches have low computational complexity but may fall into a local optimum quickly, which makes them ineffective in large-scale or unbalanced problems. Methods We propose the first generic hybrid algorithm, calle

With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev

The research aims to reveal the impact of developmental leadership in its dimensions (ideal model, interest in employees, inspiration and motivation) as an independent variable in achieving adaptive performance in its dimensions (Creative problem solving, learning and motivation, Training efforts, adaptability, work stress management, dealing with crises and emergencies) as a dependent variable, and the research aims to enhance the quality of developmental leadership in the research sample through this leadership style, which is a modern style and is still under research and study with a focus on the benefit of adaptive performance From a psychological and organizational research sample consisting of (106) respondents from the middle adm

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has