Application of ergonomics' rules has become a necessity in today's world. Due to the lack of knowledge of what these rules are and the resources needed to fund them, a lot of people develop health issues. One of the most common health issues relate to sitting in a wrong posture for extended period.In this document, a framework that can help in minimizing the existence of the sitting posture anomaly is proposed. This framework takes into account using limited resources as well as being able to apply it in a home environment. © 2022 IEEE.

This paper proposes using entity2rec [1] which utilizes knowledge graph-based embeddings (node2vec) instead of traditional embedding layers in embedding based recommender systems. This opens the door to increasing the accuracy of some of the most implemented recommender systems running in production in many companies by just replacing the traditional embedding layer with node2vec graph embedding without the risk of completely migrating to newer SOTA systems and risking unexpected performance issues. Also, Graph embeddings will be able to incorporate user and item features which can help in

Nowadays events stream processing is one of the top demanding field(s) because of the business urgent need for ongoing real time analytics & decisions. Most business domains avail huge amount of data aiming to make use of each data point efficiently. Corporate(s) have a cloud of events vary from internal business transactions, social media feeds, IoT devices logs,.. etc. In this paper we would discuss state of the art event stream processing technologies using cloud of events by summarizing event stream processing definition, data flow architectures, common use cases, frameworks 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

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

Because of the widespread availability of low-cost printers and scanners, document forgery has become extremely popular. Watermarks or signatures are used to protect important papers such as certificates, passports, and identification cards. Identifying the origins of printed documents is helpful for criminal investigations and also for authenticating digital versions of a document in today’s world. Source printer identification (SPI) has become increasingly popular for identifying frauds in printed documents. This paper provides a proposed algorithm for identifying the source printer and

The open Source Software (OSS) became the backbone of the most heavily used technologies, including operating systems, cloud computing, AI, Blockchain, Bigdata Systems, IoT, and many more. Although the OSS individual contributors are the primary power for developing the OSS projects, they do not contribute to the OSS project's decisionmaking as much as their contributions in the OSS Projects development. This paper proposes a framework to democratize the OSS Project's decision-making using a blockchain-related technology called Decentralized Autonomous Organization (DAO). Using DAO

Social media platforms are used widely by all people to express their feelings, opinions, and emotional states. Billions of people worldwide use them daily to share what they think and feel in their posts. Amongst all social media available platforms, Facebook only contains around three billion personal accounts. In this work Reddit dataset is used to automatically detect mental illness from social media posts. This study is not only limited to early detection of already existing mental illness or disorder like depression and anxiety from social posts, but also and most importantly the study

—Ultrasound imaging is a unique medical imaging modality due to its clinical versatility, manageable biological effects, and low cost. However, a significant limitation of ultrasound imaging is the noisy appearance of its images due to speckle noise, which reduces image quality and hence makes diagnosis more challenging. Consequently, this problem received interest from many research groups and many methods have been proposed for speckle suppression using various filtering techniques. The common problem with such methods is that they tend to distort the edge detail content within the image and

Rice is considered a strategic crop in Egypt as it is regularly consumed in the Egyptian people’s diet. Even though Egypt is the highest rice producer in Africa with a share of 6 million tons per year [5], it still imports rice to satisfy its local needs due to production loss, especially due to rice disease. Rice blast disease is responsible for 30% loss in rice production worldwide [9]. Therefore, it is crucial to target limiting yield damage by detecting rice crops diseases in its early stages. This paper introduces a public multispectral and RGB images dataset and a deep learning pipeline