Research addressing Sentiment Analysis has witnessed great attention over the last decade especially after the huge increase in social media networks usage. Social networks like Facebook and Twitter generate an incredible amount of data on a daily basis, containing posts that discuss all kinds of different topics ranging from sports and products to politics and current events. Since data generated

Understanding both of job-seekers and employers behavior in addition to analyzing the text of job-seekers and job profiles are two important missions for the e-recruitment industry. They are important tasks for matching job-seekers with jobs to find the top relevant suggestions for each job-seeker. Recommender systems, information retrieval and text mining are originally targeted to assist users

With the continuous and aggressive competition in advertising businesses, uncontrollably desires have emerged to identify and classify consumers. It is proven that companies must have a clear definition of its target market. Based on this we have seen different ways to identify, analyze, and track consumers, either voluntarily or without their consent. Browser fingerprinting techniques have

Mobile communication networks are using signaling protocols to allow mobile users to communicate using short messages, phone calls and mobile data. Signaling protocols are also used to manage billing for operators and much more. The design flaws that signaling inherits made them vulnerable to attacks such as location tracking of subscriber, fraud, calls and SMS interception. With the high rate of

Semantic Segmentation of satellite images is one of the most challenging problems in computer vision as it requires a model capable of capturing both local and global information at each pixel. Current state of the art methods are based on Fully Convolutional Neural Networks (FCNN) with mostly two main components: an encoder which is a pretrained classification model that gradually reduces the

Background/Aim: Using machine learning approaches as non-invasive methods have been used recently as an alternative method in staging chronic liver diseases for avoiding the drawbacks of biopsy. This study aims to evaluate different machine learning techniques in prediction of advanced fibrosis by combining the serum bio-markers and clinical information to develop the classification models

N2O is a major greenhouse gas and the majority of anthropogenic N2O emissions originate from agriculturally managed soils. Therefore, developing N2O mitigation strategies is a key challenge for the agricultural sector and biochar soil treatment is one reported option. Biochar's capacity to increase soil pH and to foster activity of specialized N2O reducers has been proposed as possible mechanisms

Let-7a, miR-34a, and miR-199 a/b have gained a great attention as master regulators for cellular processes. In particular, these three micro-RNAs act as potential onco-suppressors for hepatocellular carcinoma. Bioinformatics can reveal the functionality of these micro-RNAs through target prediction and functional annotation analysis. In the current study, in silico analysis using innovative

Personal health record service avail patients to store and dominate their healthy information data through the cloud. Many users like medical doctors, health care providers and family members can access this data through the internet. However, there are privacy issues related to data exposure and data breaches, causing risk to patients' lives. Encryption techniques like public key encryption are

For the past decade, Internet of Things (IoT) had an important role in our lives. It connects a large number of embedded devices. These devices fulfill very difficult and complicated tasks, which facilitate our work. Till now the security of IoT faces many challenges such as privacy, authentication, confidentiality, trust, middleware security, mobile security and policy enforcement. In order to