Analysis and Prediction of Student Performance by Using A Hybrid Optimized BFO-ALO Based Approach: Student Performance Prediction using Hybrid Approach

Data mining offers effective solutions for a variety of industries, including education. Research in the subject of education is expanding rapidly because of thebigquantityof student data that can be utilized to uncover valuable learning behavior patterns. This research presents a method for forecasting the academic presentation of students in Portuguese as well as math subjects, and it is describing with the help of  33 attributes. Forecasting the educationalattainment of students is the most popular field of study in the modern period. Previous research has employed a variety of categorization algorithms to forecast student performance. Educational data mining is a topic that needs a lot of research to improve the precision of the classification technique and predict how well students will do in school. In this study, we made a method to predict how well a student will do that uses a mix of optimization techniques. BFO and ALO-based popular optimization techniques were applied to the data set. Python was used to process all the files and conduct a performance comparison analysis. In this study, we compared our model's performance with various existing baseline models and examined the accuracy with which the hybrid algorithm predicted the student data set. To verify the expected classification accuracy, a calculation was performed. The experiment's findings indicate that the BFO-ALO Based hybrid model, which, out of all the methods, with a 94.5 percent success rate, is the preferred choice

Computational Methods for Medical and Cyber Security

Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields

Hybrid modeling to support the smart manufacturing: concepts, theoretic contributions and real-case applications about Hybrid and Wisdom-based Systems

L'abstract è presente nell'allegato / the abstract is in the attachmen

Flood Forecasting Using Machine Learning Methods

This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Wate

Learning Outcomes of Classroom Research

Personal pronouns are a linguistic device that is used to engage students at various educational levels. Personal pronouns are multifunctional, and their functions range from inclusion to exclusion, and include establishing of rapport with students. In this chapter, we compare the use of personal pronouns at university and secondary school levels. Our previous study (Yeo & Ting, 2014) showed the frequent use of you in lecture introductions (2,170 instances in the 37,373-word corpus) to acknowledge the presence of students. The arts lecturers were more inclusive than the science lecturers, reflected in the less frequent use of exclusive-we and we for one, as well as the frequent use of you-generalised. We have also compiled and analysed a 43,511-word corpus from 15 English lessons in three Malaysian secondary schools. This corpus yielded 2,019 instances of personal pronoun use. The results showed that you was the most frequently used personal pronoun, followed by we and I. You-audience was used more than you-generalised, and the main function was to give instructions to students. The teachers appeared to be more directive than the lecturers in the previous study, who sometimes used the inclusive-we for you and I and we for I to lessen the social distance with students, indicating that the discourse functions of personal pronouns vary with the educational context. The findings suggest that educators can be alerted to the versatility of personal pronouns, for example, for engaging students in the lesson and for asserting authority in the subject matter. Keywords: student engagement; personal pronouns; lecture; classroom; teache

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Abstract— Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can’t store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system. Keywords— Shortest Path, Algorithm Dijkstra, Node Combination, Dynamic Location (key words

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen