Developing A Neural Network-Based Model for Identifying Medicinal Plant Leaves Using Image Recognition Techniques

Herbal plants contribute an important role in people's health and the environment, as they can provide both medical benefits and oxygen. Many herbal plants contain valuable therapeutic elements that can be passed down to future generations. Traditional methods of identifying plant species, such as manual measurement and examination of characteristics, are labor-intensive and time-consuming. To address this, there has been a push to develop more efficient methods using technology, such as digital image processing and pattern recognition techniques. The exact recognition of plants uses methodologies like computer vision and neural networks, which have been proposed earlier. This approach involves neural network models such as CNN, ALexnet, and ResNet for identifying the medical plants based on their respective features. Classification metrics give the 96.82 average accuracies. These results have been promising, and further research will involve using a larger dataset and going more into deep-learning neural networks to improve the accuracy of medicinal plant identification. It is hoped that a web or mobile-based system for automatic plant identification can help increase knowledge about medicinal plants, improve techniques for species recognition, and participate in the preservation of species that are considered ad endangered

Wind generation forecasting methods and proliferation of artificial neural network:A review of five years research trend

To sustain a clean environment by reducing fossil fuels-based energies and increasing the integration of renewable-based energy sources, i.e., wind and solar power, have become the national policy for many countries. The increasing demand for renewable energy sources, such as wind, has created interest in the economic and technical issues related to the integration into the power grids. Having an intermittent nature and wind generation forecasting is a crucial aspect of ensuring the optimum grid control and design in power plants. Accurate forecasting provides essential information to empower grid operators and system designers in generating an optimal wind power plant, and to balance the power supply and demand. In this paper, we present an extensive review of wind forecasting methods and the artificial neural network (ANN) prolific in this regard. The instrument used to measure wind assimilation is analyzed and discussed, accurately, in studies that were published from May 1st, 2014 to May 1st, 2018. The results of the review demonstrate the increased application of ANN into wind power generation forecasting. Considering the component limitation of other systems, the trend of deploying the ANN and its hybrid systems are more attractive than other individual methods. The review further revealed that high forecasting accuracy could be achieved through proper handling and calibration of the wind-forecasting instrument and method

Factors Influencing the Acceptance of Mobile Learning in K-12 Education in Saudi Arabia: Towards a Shift in the Saudi Education System vis-à-vis Saudi 2030 Vision

The Saudi Arabian government is committed to updating and improving its education system. Thus, in March 2017, a project was declared to convert the existing book-based methodology to modern, mobile technology in the K-12 education space by 2021. As part of this process, a deep-dive literature review of student acceptance of mobile learning confirmed that there was limited research into what elements had an effect on how much students were likely to accept learning with mobile applications in the five to 18-year-old demographic of K-12. The conclusion of the literature review was that the Saudi Arabian Education Ministry must acquire an understanding of these elements in order to strategize the implementation of the new technology. This study approached high school students, aged 16 – 18, in Saudi Arabia, to examine the elements which would influence their acceptance of mobile learning technology. The research consolidated known elements of education, namely learning self-management, system quality, and hedonic motivation with the Unified Theory of Acceptance and Use of Technology (UTAUT) to create a significant theoretical model for the new technology in a high school setting. Conclusions were drawn that societal influence did not affect the student’s approach to mobile learning, but that learning self-management, the expectancy of effort and performance, hedonic motivation and the quality of the system did affect the acceptance behaviour of the students. It was also noted that gender was not a significant factor in the stud

Impact of ICT in Modernizing the Global Education Industry to Yield Better Academic Outreach

The advancements made by information technology have redefined the concept, scope, and significance of communication. The barriers in the communication process have been wiped out by the recent advances in information and communication technology(ICT) backed by high-speed data connectivity. People are free to communicate without bothering about physical borders distancing them from one another. Information and communication technology has diversified its dynamism by creating an e-environment, where people exploit the power of technology and communication to deliver many services. This research used the conceptual framework for ICT-enabled learning management systems and described their dimensions and scope in ICT-enabled education. The ubiquity of ICT has revamped the education industry worldwide by introducing new approaches, tools, and techniques to modernize education. The widespread popularity of ICT has forced educational establishments to endorse this to update the academia to leverage its bounders and enhance productivity to yield productive outcomes at different levels of education. This paper describes different ICT approaches and investigates the importance, influence, and impact of ICT-enabled technologies on various educational practices to achieve productive educational outcomes. This research investigates the role of ICT in teaching and learning at different levels of education, explores various modulates and their influence on the overall development of educational activities, and identifies the research gaps that are bridged to achieve the primary aim of ICT and education. This research extended its ICT projections and scope to overcome the challenges emerging from pandemic circumstances and design and develop an online platform in proper consultation with market demand to make students more job-oriented or skill-oriented. This paper describes different ICT approaches adopted by various educational institutions across the globe to modernize student−teacher interaction. This paper further investigates the influence and impact of ICT-enabled technologies on various educational practices that are prerequisites for achieving productive educational outcomes

Applying Adaptive Security Techniques for Risk Analysis of Internet of Things (IoT)-Based Smart Agriculture

In modern times, the Internet of Things (IoT) is having a major impact on agriculture. Risk and security parameters are always linked when researching, developing, implementing and deploying IoT-based devices. It is a myth that security does not play a major role in IoT applications in agriculture. Data accuracy and availability is a high-priority requirement for farmers who help achieve high yields. A secure IoT network requires a situational approach, often referred to as dynamic security. An advanced security approach to improving IoT security is adaptive security, a cybersecurity-based approach. The lack of security in a smart farming environment is a very important factor for agricultural growth. In this study, we introduce IoT together with adaptive security operations and integrate it into a smart farming environment. We propose an evaluation framework that can be applied to diverse smart farming environments. Several scenarios of an agricultural environment with smart devices and sensors are described for execution. Storylines with real-time environments are then derived from these scenarios to extend and incorporate adaptive security frameworks and scenarios in IoT-based agriculture