Anomaly Detection of Breast Cancer Using Deep Learning.

Cancer is one of the deadliest diseases facing humanity, one of the which is breast cancer, and it can be considered one of the primary causes of death for most women. Early detection and treatment can significantly improve outcomes and reduce the death rate and treatment costs. This article proposes an efficient and accurate deep learning-based anomaly detection framework. The framework aims to recognize breast abnormalities (benign and malignant) by considering normal data. Also, we address the problem of imbalanced data, which can be claimed to be a popular issue in the medical field. The framework consists of two stages: (1) data pre-processing (i.e., image pre-processing); and (2) feature extraction through the adoption of a MobileNetV2 pre-trained model. After that classification step, a single-layer perceptron is used. Two public datasets were used for the evaluation: INbreast and MIAS. The experimental results showed that the proposed framework is efficient and accurate in detecting anomalies (e.g., 81.40% to 97.36% in terms of area under the curve). As per the evaluation results, the proposed framework outperforms recent and relevant works and overcomes their limitations.

Artificial Intelligence-Based Robotic Technique for Reusable Waste Materials.

Waste management is a critical problem for every country, whether it is developed or developing. Selecting and managing waste are a critical part of preserving the environment and maximizing resource efficiency. In addition to reducing trash and disposal, reusable items are predicted to be of great benefit since they lessen our dependence on raw materials. The usage of compostable trash may be expanded outside fertilizers and dung after the metallic, chemicals, and glass items have been recycled. After a good scrubbing, the glass may be broken down and remelted to create new items. Reusing waste items via garbage recovery is one of the best methods to do so. This document outlines the steps that must be taken to maximize the use of garbage. This work describes a reusable industrial robot arm for grasping and sorting things depending on the resources they contain. Gripping, motion control, and object material categorization are all integrated into a full-automation, reusable system architecture in this study. LeNet also was adjusted to classify garbage into cartons and plastics using an artificial intelligent technique, with the use of a customized LeNet model. Movement in terms of moving the robot in the most efficient way possible, the robot's grabbing, and categorization were incorporated into the movement design process. The system's grabbing and object categorization success rates and computation time are calculated as metrics for evaluation.

Advanced biomedical applications of iron oxide nanostructures based ferrofluids.

Ferrofluids or magnetic nanofluids are highly stable colloidal suspensions of magnetic nanoparticles (NPs) dispersed into various base fluids. These stable ferrofluids possess high thermal conductivity, improved thermo-physical properties, higher colloidal stability, good magnetic properties, and biocompatibility, which are the primary driving forces behind their excellent performance, and thus enable them to be used for a wide range of practical applications. The most studied and advanced ferrofluids are based on iron oxide nanostructures especially NPs, because of their easy and large-scale synthesis at low costs. Although in the last decade, several review articles are available on ferrofluids but mainly focused on preparations, properties, and a specific application. Hence, a collective and comprehensive review article on the recent progress of iron oxide nanostructures based ferrofluids for advanced biomedical applications is undeniably required. In this review, the state of the art of biomedical applications is presented and critically analyzed with a special focus on hyperthermia, drug delivery/nanomedicine, magnetic resonance imaging, and magnetic separation of cells. This review article provides up-to-date information related to the technological advancements and emerging trends in iron oxide nanostructures based ferrofluids research focused on advanced biomedical applications. Finally, conclusions and outlook of iron oxide nanostructures based ferrofluids research for biomedical applications are presented.