Electric vehicles (EVs) can only provide lower carbon emissions than conventional, internal combustion-powered vehicles if they are charged using green energy. They also have the drawback of long charging times to 'refuel' them. To combat these two problems, a solar-powered battery charging and swapping station was developed using centered-human design and systems engineering. The design focuses on electric two-wheeled vehicles (e-scooters) due to the easier handling of their light and low-capacity batteries compared to electric cars. These stations are easy to maintain and manage and can be

Following cybersecurity st and ards nowadays is becoming one of the highest priorities to the digital specialists. Due to the global direction to apply digital transformation, data security is a concern. It becomes crucial to ensure data confidentiality, integrity, and availability whether while transmitting, at rest or even while processing it. The difficulty being faced by organizations, is the challenge of applying the needed security measures. Also, implementing, and maintaining the cryptographic algorithms that ensure the wellness of the data encryption. Having a crypto library or a

This study introduces an innovative approach to sentiment analysis, specifically tailored for the Arabic language, a domain that poses unique challenges due to its complex morphology and diverse dialects. Utilizing a substantial dataset of over 108,000 reviews related to Arabic companies, our primary objective was to develop a robust and reliable sentiment scoring system that caters to the intricacies of the Arabic language, aimed at assisting businesses in understanding customer sentiments more effectively.Our methodology encompassed an extensive preprocessing phase, crucial for preparing the

Internet of Vehicles is considered one of the most unprecedented outputs of the Internet of Things. No one has realized or even expected the rapidly-growing revolution regarding autonomous connected vehicles. Nowadays, Internet of Vehicles is massively progressing from Vehicular Ad-Hoc Networks as a huge futuristic research and development discipline. This paper proposes a novel reliable and secure architecture for ubiquitously controlling remote connected cars' internal systems, such as engine, doors' locks, sunroof, horn, windows' and lights' control systems. The main contribution is that

The accelerated rise of new technologies has reshaped the manufacturing industry of contemporary vehicles. Numerous technologies and applications have completely revolutionized the driving experience in terms of both safety and convenience. Although vehicles are now connected and equipped with a multitude of sensors and radars for collision avoidance, millions of people suffer serious accidents on the road, and unfortunately, the death rate is still on the rise. Collisions are still a dire reality for vehicles and pedestrians alike, which is why the improvement of collision prevention

Background: Remarkable work has been recently introduced to enhance the usage of Electromyography (EMG) signals in operating prosthetic arms. Despite the rapid advancements in this field, providing a reliable, naturalistic myoelectric prosthesis remains a significant challenge. Other challenges include the limited number of allowed movements, lack of simultaneous, continuous control and the high computational power that could be needed for accurate decoding. In this study, we propose an EMG-based multi-Kalman filter approach to decode arm kinematics; specifically, the elbow angle (θ), wrist

Background: The novel coronavirus (SARS-CoV-2) caused lethal infections worldwide during an unprecedented pandemic. Identification of the candidate viral epitopes is the first step in the design of vaccines against the viral infection. Several immunoinformatic approaches were employed to identify the SARS-CoV-2 epitopes that bind specifically with the major histocompatibility molecules class I (MHC-I). We utilized immunoinformatic tools to analyze the whole viral protein sequences, to identify the SARS-CoV-2 epitopes responsible for binding to the most frequent human leukocyte antigen (HLA)

Medicines based on messenger RNA (mRNA) hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limited by their thermostability, which is fundamentally limited by the intrinsic instability of RNA molecules to a chemical degradation reaction called in-line hydrolysis. Predicting the degradation of an RNA molecule is a key task in designing more stable RNA-based therapeutics. Here, we describe a crowdsourced machine learning competition (‘Stanford OpenVaccine’) on Kaggle, involving single-nucleotide

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

This paper tries to alleviate some challenges facing blind and visually impaired people in public transportation systems by providing them with in-station navigation information and real-time schedule information. Novel system architecture for the Intelligent Transportation Systems (ITS) navigation for blind and visually impaired people based on recent Radio Frequency Identification (RFID) localization technologies, commonly used in robotics, is proposed. Furthermore, a live timetable using a new ZigBee network broadcasting protocol with detailed frame structure is used for provision of real