Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

Summary The paper proposes a small custom CNN for classifying solid waste into four classes: aluminum, cardboard, plastic, and glass. It is designed for real-time use on limited hardware such as a Raspberry Pi or Jetson.

Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance

The current research aims to determine the requirements of Trends of International Mathematics and Science Study (TIMSS 2019) and to find out the extent to which the content of science textbooks for grades (1-4) in the Sultanate of Oman includes the requirements of (TIMSS 2019). Only the Cognitive Process dimension has been considered when conducting the analysis. The study population includes all science books from the first to the fourth grade for the academic year 2021-2022. The study identified and organized the requirements in the study tool, which is a list of requirements of (TIMSS 2019). After confirming its validity and reliability, the analysis was performed, and data were collected and analyzed statistically using frequencies

The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

Abstract

               The research aimed to prepare an audit program focusing on the activities of municipal institutions related to the environmental dimension as one of the dimensions of sustainable development, and applying the program for the purpose of preparing an oversight report related to assessing the impact of the activities of municipal institutions on the environmental reality as the main channel through which municipal institutions contribute to achieving the part related to it. Among the requirements of sustainable development, the proposed program was prepared and applied to the institutions affiliated to the Directorate of Mu