In this study, the authors propose a method that combines CNN and LSTM networks to recognize facial expressions. To handle illumination changes and preserve edge information in the image, the method uses two different preprocessing techniques. The preprocessed image is then fed into two independent CNN layers for feature extraction. The extracted features are then fused with an LSTM layer to capture the temporal dynamics of facial expressions. To evaluate the method's performance, the authors use the FER2013 dataset, which contains over 35,000 facial images with seven different expressions. To ensure a balanced distribution of the expressions in the training and testing sets, a mixing matrix is generated. The models in FER on the FER2013 dataset with an accuracy of 73.72%. The use of Focal loss, a variant of cross-entropy loss, improves the model's performance, especially in handling class imbalance. Overall, the proposed method demonstrates strong generalization ability and robustness to variations in illumination and facial expressions. It has the potential to be applied in various real-world applications such as emotion recognition in virtual assistants, driver monitoring systems, and mental health diagnosis.
With the rapid development of society, college students are facing the dual pressure of study and employment, which leads to an endless stream of mental health problems, and has become the focus of society, schools and families. Therefore, it is particularly important to do a good job in college students’ mental health education. College counselors are good teachers and good friends of students. They play an important guiding role in college students’ mental health education. They play an important role in improving students’ personality and mental health. This paper analyzes the advantages of college students’ psychological health education, and puts forward the effective participation strategies of college Students’ psychological health education.
An experiment was conducted to assess the effect of psychoenergetic energy in litchi as positive and negative thoughts using a simple meditation technique at ICAR-NRC on Litchi, Muzaffarpur. The plant produced 24.75 g of fruit given positive energy, while the plant with negative thought energy produced 22.12 g of fruit. The fruit and seed weight increased by 11.88% and 13.63%, respectively, due to positive energy. The number of fruit retentions increased by 23.77% due to positive energy. Anthocyanin content in pericarp was increased by 5.45% in plants given positive energy. Fruit qualities were also significantly affected by psychoenergy. TSS (Brix) was significantly increased by 13.54% in plants given positive energy as compared to negative energy, and titratable acidity was reduced by 25% due to positive energy. Ascorbic acid was also increased by 30% in plant given positive thoughts. Sun burn was reduced by 54.76% and fruit cracking by 63.64% due to energy of thought. Fruit borer infestation was reduced by 70%, and mite infestation was reduced by 90% in plants given positive energy. The psychoenergetic potential is vast, and its ability to improve crop yield and quality cannot be overstated. The hidden power of thought is being practiced by all, but mostly people do not know this power and use it in an improper manner. This is a high time when we need to practice generating powerful thoughts to change present-day agriculture and its dependents.
City planning is becoming more and more crucial as modernization and urbanization progress quickly. Making maps is an essential and helpful way in the city planning process for gathering data about the layout of a city and its elements, including the roads, traffic, buildings, and environment. Thanks to advancements in technology, computer software is now used to create maps, yielding more accurate and varied results. As a result, cartography is now closely related to and plays a crucial part in city planning. This brief essay will discuss the value of cartography in urban development and planning, as well as the connection between the two.
Copyright © by EnPress Publisher. All rights reserved.