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Evaluation of Different Sarcasm Detection Models for Arabic News Headlines

Being sarcastic is to say something and to mean something else. Detecting sarcasm is key for social media analysis to differentiate between the two opposite polarities that an utterance may convey. Different techniques for detecting sarcasm are varying from rule-based models to Machine Learning and Deep Learning models. However, researchers tend to leverage Deep Learning in detecting sarcasm

Artificial Intelligence
Software and Communications

AutoDLCon: An Approach for Controlling the Automated Tuning for Deep Learning Networks

Neural networks have become the main building block on revolutionizing the field of artificial intelligence aided applications. With the wide availability of data and the increasing capacity of computing resources, they triggered a new era of state-of-the-art results in diverse directions. However, building neural network models is domain-specific, and figuring out the best architecture and hyper

Artificial Intelligence
Software and Communications

Transverse momentum spectra of strange hadrons within extensive and nonextensive statistics

Using generic (non)extensive statistics, in which the underlying system likely autonomously manifests its extensive and nonextensive statistical nature, we extract various fit parameters from the CMS experiment and compare these to the corresponding results obtained from Tsallis and Boltzmann statistics. The present study is designed to indicate the possible variations between the three types of

Artificial Intelligence
Software and Communications

DiSGD: A distributed shared-nothing matrix factorization for large scale online recommender systems

With the web-scale data volumes and high velocity of generation rates, it has become crucial that the training process for recommender systems be a continuous process which is performed on live data, i.e., on data streams. In practice, such systems have to address three main requirements including the ability to adapt their trained model with each incoming data element, the ability to handle

Artificial Intelligence

A Transfer Learning Approach for Emotion Intensity Prediction in Microblog Text

Emotional expressions are an important part of daily communication between people. Emotions are commonly transferred non verbally through facial expressions, eye contact and tone of voice. With the rise in social media usage, textual communication in which emotions are expressed has also witnessed a great increase. In this paper automatic emotion intensity prediction from text is addressed

Artificial Intelligence

Effect of solar canals on evaporation, water quality, and power production: An optimization study

Both energy and availability of water with good quality are essential for the well-being of humans. Thus, it is very important to study the parameters that would affect water quality, so as to come up with mitigation measures if water quality would be at risk or negatively affected. Moreover, it is very important to always search for new energy resources, especially if they are renewable. This

Energy and Water

D-SmartML: A distributed automated machine learning framework

—Nowadays, machine learning is playing a crucial role in harnessing the value of massive data amount currently produced every day. The process of building a high-quality machine learning model is an iterative, complex and time-consuming process that requires solid knowledge about the various machine learning algorithms in addition to having a good experience with effectively tuning their hyper

Acoustic Attacks in IOT Era: Risks and Mitigations

Usage of Internet of Things (IoT) devices became ubiquitous. IoT is expected to be of more spread, as new ideas emerge on the level of devices and applications. Such--Things-are smart in a manner that they are in connection with each other. Things form some sort of a collaborative network, where they communicate and share data with each other; as well, they are possibly remotely controlled. One

J-V characteristics of plasmonic photovoltaics with embedded conical and cylindrical metallic nanoparticles

Plasmonic photovoltaics (PVs) are promising structures that improve thin-film photovoltaics performance, where optical absorption is improved via embedding metallic nanoparticles in the PV's active layer to trap the incident optical wave into the photovoltaic cell. The presented work investigates the design of PV with both structures of conical and cylindrical metallic nanoparticles through

Healthcare
Energy and Water
Circuit Theory and Applications

Egypt x.0 ? moving behind industry 4.0 towards industry X.0

Industry X.0 is becoming a “buzz” word. Governments and businesses around the world believe that missing the new wave of industrialization would jeopardize their competitiveness for a long time, and harm their capacity to play a significant role in a connected globalized economy. Therefore, the paper examines the major drivers shaping this new wave of industrialization. Moreover, the paper