Flux Switching Permanent Magnet Generator Design and Optimization Using Response Surface Methodology

Flux Switching Permanent Magnet Generators (FRPMGs) have been used increasingly in direct drive variable speed wind turbines due to their merit such as their high torque density, easy flux weakening operation and robust rotor structure. Generally, the quality of output power in direct drive systems is lower than multi stage fixed speed systems, because of removing the gears, so it’s important to design these kinds of generators with low ripple and lowest harmful harmonics and cogging torque. This aim is one of the most important terms in increasing the quality of output power of generator simultaneously with back-EMF improvement. The objective of this paper is introducing a simple design method and optimization of high power FRPMG applied in direct drive wind turbine system by lowest possible amplitude of cogging torque and highest possible power factor, efficiency and power density. For optimization reason an optimum method called combined response surface methodology (RSM) and design of experiment has been applied. Also in order to extract the output values of generator and sensitivity analysis for design, 2D-Finite element model, was used. This method has high accuracy and gives us a better insight of generator performance and presents back EMF, cogging torque, flux density and FFT of the FSPMG. This study can help in design approach of such machines

Artificial Intelligence in Creating Virtual Laboratories for Engineering Education

The purpose of this proposed study is to analyze the possibilities of applying artificial intelligence (AI) technologies in creating virtual laboratories for engineering education, identify key technological and pedagogical components of such systems and assess their potential impact on the quality of education. The methodological framework was based on a quasi-experimental design. For this purpose, 124 students were selected and divided into experimental and control groups. Data were collected using the Engineering Skills Assessment, Social Engagement Scale (SES) and AI log files. The analysis was conducted using t-tests. The results noted that students who worked in an AI-supported virtual laboratory demonstrated significantly higher final scores (M = 76.84) compared to the control group (M = 65.37), and the increase in competencies was +18.13 points versus +7.47, respectively. The analysis confirmed the high significance of these differences (t(122) = 4.87, p < 0.001). The conclusions confirm that virtual laboratories, enhanced with adaptive AI algorithms, are an effective tool in engineering education, capable of improving the results of students\u27 practical training

Proposed biology teaching unit using artificial intelligence for third-year secondary students and its impact on developing preventive medicine concepts

This study investigated the effectiveness of an AI-supported Biology 3 unit on preventive medicine concepts among third-year secondary female students in Saudi Arabia, employing an experimental design that utilized virtual simulations, interactive activities, and project-based learning. Results indicated that the experimental group achieved significantly higher scores in health awareness and preventive knowledge with a strong effect size, suggesting that such AI tools effectively bolster student health literacy. While the study’s focus on a single, female-only setting necessitates broader replication across different regions to ensure generalizability, it provides valuable experimental evidence for the originality of AI-supported instruction, advocating for the systematic integration of preventive medicine into biology curricula alongside expanded AI tools and continuous teacher development

Artificial intelligence technologies as a means of improving the digital literacy of future teachers

This study aimed to find out whether artificial intelligence (AI) technologies can improve digital mastery among in-training educators in Kazakhstan. It determines the rate of adoption of AI tools, evaluates their role in enhancing digital competencies, and examines the associated challenges and opportunities. Mixed-method approach was employed, which began with a quantitative phase (pre- and post-intervention tests) and concluded with a qualitative phase (interviews). The survey sample comprised 385 participants while 80 participants (40 each) made up the intervention consisting of traditional instruction and AI integrated instruction (ChatGPT and Google Cloud AI). The result showed that prior the intervention, all participants showed low digital literacy and did not adopt AI. However, a 100% AI adoption rate was observed after the intervention, with 75% having moderate to 25% high digital literacy. A paired t-test found significant improvements in digital literacy (M = 25.34 to 35.32, t(19) = 2.12, p < 0.05) and AI proficiency (M = 19.89 to 30.21, t(19) = 1.03, p < 0.05). Lack of institutional support, tool unfamiliarity, and skepticism were some of the problems people encountered. Conversely, the problems with digitally competent users were informed reflection and pedagogic balance. Despite these challenges, both groups recognized the possibilities of individual learning, better classroom result, and team development. Conclusively, targeted AI interventions in teachers training will greatly improve pre-service teacher\u27s digital literacy. Therefore, when applied, close monitoring and ethical strategies should be put in place to enhance academic integrity

Diagnosis of Organizational Change: A multi-level approach (Case study of a French SME certified ISO 9001)

Since their first certificates issued in 1989, ISO standards have grown considerably with, for example, more than 1,106,356 certificates delivered in 2016 to ISO 9001 granted in the world [1]. Even though these standards have contributed significantly to the formalization of the company\u27s knowledge, little is known about the consequences of implementing this framework in terms of organizational changes and learning dynamics. To better understand this phenomenon, we opted for a qualitative approach based on a single case study. Our approach attempts to consider several levels of analysis: organizational, strategic, cognitive and societal. Hence, we have used a model that superimposes these four levels to analyze the organizational changes that are induced by the implementation of the ISO 9001 management system, and their consequences on the modes of learning within a French SME

Lean Manufacturing: Trends and Implementation Issues

Many manufacturing cost reduction initiatives have been introduced over past three decades including lean manufacturing. Waste reduction and efficiency improvement are the main objectives of this initiative. It is developed from a set of tools and techniques and can fit nicely in cost focus or cost leadership competitive advantage strategies. But, keeping competitive advantage under the market circumstances are getting harder with growth of production quantity and product diversity. Therefore, paper\u27s focus is lean manufacturing implementation trends and issues within the various manufacturing sector. Successes and failures of implementation of lean manufacturing in some industries are discussed. It was found that lean principles are good source of competitive advantage, it is applicable for many industries and its expansion and discussion are significantly progressing. The biggest threat in implementing lean is lack of understanding the concept but those who engage consultants were more successful

Spatial study of causes and effects of the sandstorms using meteorological data and GIS: The case of Nasiriyah city, Iraq

The reoccurrence of sandstorms in Nasiriyah city (Southern Iraq) throughout the Summer season is a very important phenomenon and distinctive case that comes from the nearby regions. These storms restrict the financial activities of the city with expanded municipal effort as well as other well-being and environmental problems, and then bring a huge risk to the local residents. This paper uses Geographic Information System (GIS) and Remote Sensing Imagery to dimensionally discover the reasons causing sandstorms, understand the changes within certain periods of time, and then measure the sand-plume coverage during storms. This work has also made an attempt to get the correlation between meteorological records and spatial outputs to predict the direction and coverage range of the predicted future sandstorms which could help to take protective and preventive measures for the sake of the human being. The periods between 1972 and 2018 have been adopted to study the phenomena by using the information archive of the Nasiriyah Meteorological Center together with NASA\u27s open-source climate data and Landsat satellite imagery

Aspect oriented programming: Concepts, characteristics and implementation

Programming techniques have been passed through many development stages in their progressing path to cope with the increasing complexity of systems requirements. So, one of the main goals of the programming languages designers is how to develop programming language that can handle and manage the spread and overlapping of different functionality concerns. Because unmanageable and uncontrollable scattering of concerns inside the system may cause many problems during system running in present or/and during applying maintenance and developing the system in future. One of the most recent and powerful solutions to overcome these problems is via using Aspect-Oriented Programming (AOP) approach. This research is demonstrates the features and the problems with implying AOP techniques in the software development process

Intelligent comprehensive privacy protection system for location-based services

Recently, location-based systems (LBS) have been proven to be an essential element of smart cities due to the valuable benefits they provide to users searching for their nearest Points of Interest (PoI), facilitating daily life activities. However, privacy protection is a major concern in LBS, where attackers can apply advanced attacks, such as location homogeneity, semantic location and query analyzing attacks, to infer sensitive information about the private lives of LBS users. Therefore, protection of location privacy as well as query privacy is necessary to increase the trust of users in LBS. To address this issue, we present the Intelligent Comprehensive Privacy Protection (IntCPP) system as an enhancement of our previous work by employing a deep-learning technique. The Foursquare weekly trajectory dataset is selected to train the proposed system using the long short-term memory (LSTM) technique with an efficient pre-processing stage to adopt time-series data to the environment of LSTM. Evidence of the IntCPP system’s superiority is provided through comparison to two intelligent dummy-based systems as well as three traditional dummy-based systems. In terms of accuracy, a (0.05) enhancement degree is achieved, while in terms of entropy, cumulative resistance against attacks, and average cumulative cache hit ratio, (2.0, 100%, 0.17) enhancement degrees are achieved, respectively.

Detection of some virulence factors of Salmonella typhi isolated from patients\u27 blood by PCR and Phylogenetic tree

Typhoid fever is brought about by Salmonella enterice serovar typhi, which is a significant general medical issue in many developing nations. The severity the pathogenesis depends on Salmonellaʼs possession of cytolethal distending toxin (CDT) and virulence factors such as fimbriae adhesions, which are important in the adherence, invasion and the development of typhoid fever, was as diagnosed serologically as well as diagnosis of Salmonella typhi causing these fever based on phenotypic and cultural characteristics. Therefore, the coding genes of CdtB protein and fimbriae were detected in molecular methods by PCR technique using special primers. while, the fim gene was 84.21% and CdtB gene was 100%. DNA sequencing was performed and this confirms the isolation obtained in our study. In addition, the phylogenetic tree was analyzed and registered at the gene bank site, where the sequence identity rate fim gene 99.26%, while sequence identity rate for CdtB gene was 99.31%