Air quality assessment has been discussed for urban environments with a high degree of industrialization, as they are infested with hazardous chemicals and airborne pollutants. The assessment is carried out by monitoring stations, that basically support limited areas while leaving large geographical areas uncovered. The expansion in the agriculture sector directed us towards air quality assessment

Diabetic patients need a management tool that combines multiple features and tracks and views detailed data time-efficiently. Effective food logging is an important element of health monitoring. In this paper, we propose 'Suger.ly', a lightweight mobile application with artificial intelligence food recognition for diabetes management. The system has been trained to recognize 101 distinct types of

Food is an integral aspect of daily life in all cultures. It highly affects people's diets, eating behaviors, and overall health. People with poor eating habits are usually overweight or obese, which leads to chronic diseases such as diabetes and cardiovascular disease. Today, the classification of food images has several uses in managing medical conditions and dieting. Deep convolutional neural

Today, automatic food/non-food classification became extremely important for many real-time applications, specifically since the pandemic of the COVID-19 virus. Such that the 'no food policy' now became applied more than ever to help decrease the spread of the COVID-19 virus. Consequently, many studies used deep neural networks for the food/non-food classification task, yet these deep neural

Epilepsy is a chronic nervous disorder, which disturbs the normal daily routine of an epileptic patient due to sudden seizure onset that may cause loss of consciousness. Seizures are periods of aberrant brain activity patterns. Early prediction of an epileptic seizure is critical for those who suffer from it as it will give them time to prepare for an incoming seizure and alert anyone in their

Mobile Ad hoc networks (MANETs) facilitate the communication of devices with a limited communication range. A MANET can be described as a decentralized network with a constantly changing topology. This makes it vulnerable to different attacks. The black hole is one of the most dangerous attacks in MANETs. This paper discusses the Blackhole attack in a random mobility environment and analyses its

The fast expansion of the Internet of Things (IoT) in the technology and communication industries necessitates a continuously updated cyber-security mechanism to keep protecting the systems' users from any possible attack that might target their data and privacy. Botnets pose a severe risk to the IoT, they use malicious nodes in order to compromise other nodes inside the network to launch several

A recommender system is a set of tools for information retrieval. It improves access and proactively recommends items and services that match users' tastes by considering their explicit and implicit preferences and behaviors. Recommender systems have become very popular in the e-commerce field. Today, the internet is flooded with diverse information that makes it very difficult for the end-users

Computers and systems are vulnerable to many threats. Security researchers identified the malware as the major computers and systems threat. Malware can be classified into different types depending on the infection, attacking target, and persistence technique. In this paper, Malware detection techniques are observed with the identification of each technique's strengths and weaknesses points

Multiply-Accumulate (MAC) is one of the most commonly used operations in modern computing systems due to its use in matrix multiplication, signal processing, and in new applications such as machine learning and deep neural networks. Ternary number system offers higher information processing within the same number of digits when compared to binary systems. In this paper, a MAC is proposed using a