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Nokia 3.2: Android One Edge Plus Big Battery Life

The camera, however, was found wanting when it came to low-light photography

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Old Nokia mobile phones are placed on a shelf inside of a private museum of phones in Dobsina, Slovakia
Old Nokia mobile phones are placed on a shelf inside of a private museum of phones in Dobsina, Slovakia. VOA

By Rahul K. Singh

The trend in the crowded sub-Rs 10,000 smartphone market is to offer bigger phones that last longer on a single charge. HMD Global, the house of Nokia phones, also appears to be relying on these features a lot to beat the competition.

The Nokia 3.2, launched last month, comes with a 6.26-inch HD plus display and 4000mAh battery.

These are, however, not the only attractive features that the phone offers. It also comes with a dedicated Google Assistant button, three years of monthly security patches and two major software updates, as guaranteed in the Android One programme.

The phone was launched in two variants — the 2GB RAM+16GB internal storage at Rs 8,990 and the 3GB+32GB at Rs 10,790.

Let’s see how the 3GB+32GB variant fared during our use.

The waterdrop notch display and polycarbonate glossy body make the phone look trendy. The fingerprint sensor placed at the back is fast and accurate. We also found no trouble in accessing the phone with the face unlock feature.

Nokia has made several small to medium-sized acquisitions as part of a strategy to build up a standalone software business to deliver higher profit margins than its classic communications hardware products.
Headquarter of Nokia. Wikimdedia commons

Powered by the Qualcomm Snapdragon 429 chipset, the phone runs Android Pie OS. At moderate usage, the device lasted for a day and a half, thanks to the 4000mAh battery.

The big screen, the thin bezels on sides and the big battery ensured that watching videos and playing games on the device was a decent experience, although it lacked a bit of sharpness. Overall, in terms of media consumption, the phone does not disappoint, considering the price point.

In adequate light, the 5MP front camera captured good selfies and didn’t appear over-exposed. The 13MP rear camera, despite having a single lens, also surprised us with decent pictures.

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What does not work?

The camera, however, was found wanting when it came to low-light photography. The polycarbonate body easily attracted fingerprints and there is nothing to write home about the sound quality.

Conclusion: The dedicated Google Assistant button, battery life and the big display are a huge plus for the Nokia 3.2, but they may not be enough to make the device stand out in comparison to Redmi Note 7, Realme 3 and Galaxy M20, which come with dual rear camera systems and some advanced features. (IANS)

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Researchers Develop System That Can Locate Shooters Using Smartphone Video

Specifically, the system looks at the time delay between the crack caused by a supersonic bullet's shock wave and the muzzle blast, which travels at the speed of sound

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By using Video from three or more smartphones, the direction from which the shots were fired -- and the shooter's location -- can be calculated based on the differences in how long it takes the muzzle blast to reach each camera. Pixabay

Researchers have developed a system that can accurately locate a shooter based on Video recordings from as few as three smartphones.

The system, called Video Event Reconstruction and Analysis (VERA), won’t necessarily replace the commercial microphone arrays for locating shooters that public safety officials already use, although it may be a useful supplement for public safety when commercial arrays aren’t available.

“One key motivation for assembling VERA was to create a tool that could be used by human rights workers and journalists who investigate war crimes, terrorist acts and human rights violations,” study researcher Alexander Hauptmann from Carnegie Mellon University in the US.

When demonstrated using three video recordings from the 2017 mass shooting in Las Vegas that left 58 people dead and hundreds wounded, the system correctly estimated the shooter’s actual location — the north wing of the Mandalay Bay hotel.

The estimate was based on three gunshots fired within the first minute of what would be a prolonged massacre.

VERA uses machine learning techniques to synchronise the video feeds and calculate the position of each camera based on what that camera is seeing.

“But it’s the audio from the video feeds that’s pivotal in localising the source of the gunshots,” Hauptmann said.

Specifically, the system looks at the time delay between the crack caused by a supersonic bullet’s shock wave and the muzzle blast, which travels at the speed of sound.

It also uses audio to identify the type of gun used, which determines bullet speed.

VERA can then calculate the shooter’s distance from the smartphone.

“When we began, we didn’t think you could detect the crack with a smartphone because it’s really short,” Hauptmann said.

“But it turns out today’s cell phone microphones are pretty good,” Hauptmann added.

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Researchers have developed a system that can accurately locate a shooter based on Video recordings from as few as three smartphones. Pixabay

By using video from three or more smartphones, the direction from which the shots were fired — and the shooter’s location — can be calculated based on the differences in how long it takes the muzzle blast to reach each camera.

VERA is not limited to detecting gunshots.

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“It is an event analysis system that can be used to locate a variety of other sounds relevant to human rights and war crimes investigations,” Hauptmann said.

The researchers presented VERA and released it as open-source code at the Association for Computing Machinery’s International Conference on Multimedia in Nice, France. (IANS)