The market needs a deeper and more comprehensive grasp of its insight, where the analytics world and methodologies such as 'Sentiment Analysis' come in. These methods can assist people especially 'business owners' in gaining live insights into their businesses and determining wheatear customers are satisfied or not. This paper plans to provide indicators by gathering real world Amazon reviews from Egyptian customers. By applying both Bidirectional Encoder Representations from Transformers 'Bert' and 'Text Blob' sentiment analysis methods. The processes shall determine the overall satisfaction

Secret Image Sharing (SIS) transfers an image to mutually suspicious receivers as n meaningless shares, where k or more shares must be present to recover the secret. This paper proposes a (k, n)-SIS system for any image type using polynomial interpolation based on Lagrange polynomials, where the generated shares are of size 1/k of the secret image size. A full encryption system, consisting of substitution and permutation stages, is employed by using the generalized Tent map as a source of randomness. In addition to using a long and sensitive system key, steganography using the Least

Retinal retinopathy of prematurity (ROP), an abnormal blood vessel formation, can occur in a baby who was born early or with a low birth weight. It is one of the primary causes of newborn blindness globally. Early detection of ROP is critical for slowing and stopping the progression of ROP-related vision impairment which leads to blindness. ROP is a relatively unknown condition, even among medical professionals. Due to this, the dataset for ROP is infrequently accessible and typically extremely unbalanced in terms of the ratio of negative to positive images and the ratio of each stage of it

Combinations of direct-acting antivirals are needed to minimize drug resistance mutations and stably suppress replication of RNA viruses. Currently, there are limited therapeutic options against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and testing of a number of drug regimens has led to conflicting results. Here, we show that cobicistat, which is an FDA-approved drug booster that blocks the activity of the drug-metabolizing proteins cytochrome P450-3As (CYP3As) and P-glycoprotein (P-gp), inhibits SARS-CoV-2 replication. Two independent cell-to-cell membrane fusion

As a case study for our research, COVID-19, that was caused by a unique coronavirus, has substantially affected the globe, not only in terms of healthcare, but also in terms of economics, education, transportation, and politics. Predicting the pandemic's course is critical to combating and tracking its spread. The objective of our study is to evaluate, optimize and fine-Tune state of the art prediction models in order to enhance its performance and to automate its function as possible. Therefore, a comparison between statistical versus compartmental methods for time series-based modeling and

The exploration of sentiment analysis in multilingual contexts, particularly through the integration of deep learning techniques and knowledge graphs, represents a significant advance in language processing research. This study specifically concentrates on the Arabic language, addressing the challenges presented by its morphological complexity. While the primary focus is Arabic, the research also includes a comprehensive review of related work in other languages such as Bangla and Chinese. This contextualizes the challenges and solutions found in Arabic sentiment analysis within a broader

Structure from Motion is a pipeline for 3D reconstruction in which the true geometry of an object or a scene is inferred from a sequence of 2D images. As feature extraction is usually the first phase in the pipeline, the reconstruction quality depends on the accuracy of the feature extraction algorithm. Fairly evaluating the robustness of feature extraction algorithms in the absence of reconstruction ground truth is challenging due to the considerable number of parameters that affect the algorithms' sensitivity and the tradeoff between reconstruction size and error. The evaluation methodology

Skin cancer is the most annoying type of cancer diagnosis according to its fast spread to various body areas, so it was necessary to establish computer-assisted diagnostic support systems. State-of-the-art classifiers based on convolutional neural networks (CNNs) are used to classify images of skin cancer. This paper tries to get the most accurate model to classify and detect skin cancer types from seven different classes using deep learning techniques; ResNet-50, VGG-16, and the merged model of these two techniques through the concatenate function. The performance of the proposed model was

Radio Frequency (RF) energy harvesting has been employed to power wireless devices. Nevertheless, RF energy harvesting encounters restrictions regarding the quantity of power it can harvest depending on signal accessibility. As a result, accurately predicting energy levels becomes crucial for enhancing the performance of energy harvesting circuits. Most research efforts have concentrated on enhancing power harvesting policies or theoretically estimating the energy obtained through RF energy harvesting. Moreover, the existing literature has primarily focused on single-band prediction approaches

Data privacy regulations have increased significantly recently. As a result, privacy by design (PbD) has become a critical consideration for enterprises that handle personal data. PbD is no longer a plain principle. Rather than that, the General Data Protection Regulation (GDPR) addresses PbD as a required legal requirement for controllers who may face fines for non-compliance with the GDPR. In this paper, we propose a practical solution, 'PbD Microservice,' that can help organizations to achieve privacy regulatory compliance. We will focus on GDPR, one of the most important regulations that