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With more and more auto manufacturers jumping the electric vehicles bandwagon, there is an urgent need to improve assisting technologies such as charging and battery technologies.

Electric car charges have been around for years but couple of major issues includes their sizes and loss of power during charging. Addressing these two issues, researchers at North Carolina State University have come up with an electric vehicle fast charger that is not only 10 times smaller than existing systems, but also wastes 60 per cent less power during the charging process, without sacrificing the charging time. The new technology is called a medium voltage fast charger (MVFC).

Conventional, 50 kilowatt (kW) state-of-the-art chargers include a distribution transformer, which weighs 1000 kilograms, and a separate fast charger unit, which weighs 200 to 600 kg. To support the weight, this transformer-and-charger system usually needs to be installed on a concrete slab.

The transformer takes power from a utility medium-voltage line and steps down the voltage to 480 V so that it that can be used by the fast charger. The fast charger takes the AC voltage and converts it to DC voltage that is compatible with the electric vehicle’s battery.

The new 50-kW MVFC weighs only around 100 kilograms and can be wall- or pole-mounted. The MVFC does the work of both the transformer and the fast charger, taking power directly from a medium-voltage utility line and converting it for use in an electric vehicle battery.

The researchers were able to make the technology so much smaller, in part, because they used wide bandgap semiconductor devices. This also made the technology more energy efficient.

At present, the best transformer-and-charger stations are reported as having an efficiency of up to 93 percent, meaning that at least 7 percent of the power is lost to heat during the charging process.

In testing, the prototype MVFC has an efficiency of at least 97.5 percent, meaning an additional 4.5 percent of the power is used to charge the vehicle, rather than being wasted as heat. This reduces operating costs, increasing revenue without increasing the cost to consumers.

The team says they are now working towards development of a charger that is capable of charing vehicles more rapidly and that too multiple vehicles at the same time.

Researchers at the Ben-Gurion University of the Negev (BGU) Malware Lab have developed a new method to detect malicious emails that they claim is better than 60+ antivirus software available in the market today.

According to the researchers, almost all the antivirus solutions out there make sure of rule-base engine to detect malicious emails. Signature based detection has an inherent flaw wherein if a signature of a malware isn’t konwn, the antivirus software isn’t going to protect the users’s PC.

This method, called Email-Sec-360°, is based on machine learning methods and leverages 100 general descriptive features extracted from all email components, including the header, body and attachments. The methodology does not require internet access, so it can be deployed by individuals and organizations, and it provides enhanced threat detection in real time.

For their experiments, the researchers used a collection of 33,142 emails (12,835 malicious and 20,307 benign) obtained between 2013 and 2016. They compared their detection model to 60 industry-leading antivirus engines as well as previous research, and found their system outperformed the next best antivirus engine by 13 percent — significantly better than such products including Kaspersky, MacAfee and Avast.

The Malware Lab researchers are also considering developing an online system that evaluates the security risk posed by an email message. It would be based on advanced machine learning methods and allow users worldwide to submit suspicious email messages and instantly obtain a maliciousness score and a recommendation on how to treat the email. In addition, the system would assist in collecting benign and malicious emails for research purposes which, due to privacy issues, is currently a very difficult task for researchers in this arena.