With convolutional neural networks and state-of-the-art image recognition techniques it is possible to make old movie classics shine again. Neural networks polish the image, reduce the noise and apply colors to the aged images. The first movies were created in the late nineteenth century with celluloid photographic film used in conjunction with motion picture cameras. Skip ahead to 2018, when the global movie industry was worth $41.7 billion globally. Serving entertainment, cultural and social purposes, films are a hugely important heritage to protect.

Surveying over 100 IT decision-makers across the construction industry, Zen's Bricks, Mortar and Digital Transformation report found that over half (55%) of large construction firms, and almost a third (28%) of smaller organisations are already using artificial intelligence (AI). The construction industry is looking at what technologies could help them in the future, with virtual reality (28%), cloud computing (24%), software-defined networking (20%), blockchain (19%) and Internet of Things (17%) all seen as key to future development by those in larger organisations. According to Tech Nation's 2018 report, technology is expanding 2.6 times faster than the rest of the UK economy, and yet the construction industry has been slow to implement digitalisation strategies that could bring increased efficiency and collaboration as well as reduced costs. Digital transformation appears to be a strategic priority for the leaders of construction firms, with CEOs (52%), CIOs and CTOs (32%) amongst the biggest drivers of such projects. Despite this top down approach, cultural change (51%) is cited as one of the biggest challenges to implementing a digital transformation project highlighting the need to get companywide buy-in. This is only topped by the importance of communicating the value of digital transformation to key stakeholders and investors (62%).

A new robotic contact lens which is controlled by small eye movements, including double blinks to zoom in and out, has been created by scientists. The contact lens, which is made from just salt water, works by mimicking the natural electric signals in the human eyeball. There is a steady electrical potential between the eyeball's front and back, even when your eyes are closed or in total darkness. When you move your eyes to look around or blink, the motion of the electrical potential can be measured. Researchers from the University of California, San Diego, developed the lens using these signals, called electro-oculograms, to control a soft lens.

A robotic exoskeleton and performance art installation is automating the discipline of synchronized dance. At San Francisco's Gray Area Festival, an annual event that combines art, technology, and music, an exhibit called'Inferno' is employing robotics to turn people into puppets. With an exoskeleton and a'dark industrial' soundtrack, Inferno is commandeering participants' limbs for an enthralling -- if off-putting -- performance. Participants in the piece are subject to the input of a'DJ' who controls both the music and how subjects dance to it'Each robot is designed to perform dynamic movements choreographed and activated by the artists, mobilizing the performers to dance in time to the dark, industrial techno soundtrack for the audience,' says a description on the event's website. The installation, which described by one Twitter user as a'forced rave' is not just fascinating to watch, but according to the routine's creators, Louis-Philippe Demers and Bill Vorn, is designed to stoke conversations about agency and technology.

Technology needed to doctor images and videos is advancing rapidly and getting easier to use, experts have warned. Government agencies and academics are racing to combat so-called deepfakes, amid the spreading threat that they impose on societies. Advances in artificial intelligence could soon make creating convincing fake audio and video relatively easy, which the Pentagon fears will be used to sow discord ahead of next year's US presidential election. Deepfakes combine and superimpose existing images and videos onto source images or videos using a machine learning technique known as generative adversarial network. The video that kicked off the concern last month was a doctored video of Nancy Pelosi, the speaker of the US House of Representatives.

LONDON - In decades to come, African farmers may pool their money to buy small robot vehicles to weed their fields or drones that can hover to squirt a few drops of pesticide only where needed. Smartphones already allow farmers in remote areas to snap photos of sick plants, upload them and get a quick diagnosis, plus advice on treatment. Researchers also are trying to train crops like maize and wheat to produce their own nitrogen fertilizer from the air -- a trick soybeans and other legumes use -- and exploring how to make wheat and rice better at photosynthesis in very hot conditions. As warmer, wilder weather linked to climate change brings growing challenges for farmers across the globe -- and as they try to curb their own heat-trapping emissions -- a rush of innovation aimed at helping both rich and poor farmers is now converging in ways that could benefit them all, scientists say. In a hotter world, farmers share "the same problems, the same issues," said Svend Christensen, head of plant and environmental sciences at the University of Copenhagen.

If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA TODAY's newsroom and any business incentives. A lot of the time, we approach shopping with the mentality that more expensive products equals better products. Don't get me wrong--there are definitely some items worth splurging on, but the most expensive option is rarely the best. Here are 25 product categories where a less expensive model out-performs a high-end product. Just think of all the money you could save! Robotic vacuums are cool to begin with, and when you add smart technology, these hands-off cleaning gadgets are even more efficient.

In recent years, air traffic communication data has become easy to access, enabling novel research in many fields. Exploiting this new data source, a wide range of applications have emerged, from weather forecasting to stock market prediction, or the collection of intelligence about military and government movements. Typically these applications require knowledge about the metadata of the aircraft, specifically its operator and the aircraft category. armasuisse Science + Technology, the R&D agency for the Swiss Armed Forces, has been developing Classi-Fly, a novel approach to obtain metadata about aircraft based on their movement patterns. We validate Classi-Fly using several hundred thousand flights collected through open source means, in conjunction with ground truth from publicly available aircraft registries containing more than two million aircraft. We show that we can obtain the correct aircraft category with an accuracy of over 88%. In cases, where no metadata is available, this approach can be used to create the data necessary for applications working with air traffic communication. Finally, we show that it is feasible to automatically detect sensitive aircraft such as police and surveillance aircraft using this method.

-- In this paper, in following of the first part (which ADF tests using ACI evaluation) has conducted, Time Series (TSs) are analyzed using decomposition analysis. In fact, TSs are composed of four components including trend (long term be - haviour or progression of series), cyclic component ( non - periodic fluctuation behaviour which are usually long term), seasonal component (periodic fluctuations due to seasonal variations like temperature, weather condition and etc.) and error term. The first method is additive decomposition and the second is mu ltiplicative method to decompose a TS into its components. After decomposition, the error term is tested using Durbin - Watson and Breusch - Godfrey test to see whether the error follows any predictable pattern, it can be concluded that there is a chance of cy ber - attack to the system. In this paper, to find out that TS errors (or called residual's interchangeably)follows any particular patterns or not and to obtain t he residual values of TSs, we conducted two classical methods of TS decomposition and then we analyzed the residual terms of TSs for both decomposition method to find anomaly in residual distributions.

Collagen fiber orientations in bones, visible with Second Harmonic Generation (SHG) microscopy, represent the inner structure and its alteration due to influences like cancer. While analyses of these orientations are valuable for medical research, it is not feasible to analyze the needed large amounts of local orientations manually. Since we have uncertain borders for these local orientations only rough regions can be segmented instead of a pixel-wise segmentation. We analyze the effect of these uncertain borders on human performance by a user study. Furthermore, we compare a variety of 2D and 3D methods such as classical approaches like Fourier analysis with state-of-the-art deep neural networks for the classification of local fiber orientations. We present a general way to use pretrained 2D weights in 3D neural networks, such as Inception-ResNet-3D a 3D extension of Inception-ResNet-v2. In a 10 fold cross-validation our two stage segmentation based on Inception-ResNet- 3D and transferred 2D ImageNet weights achieves a human comparable accuracy.