Condition monitoring is one of the routine tasks in all major process industries. The mechanical parts such as a motor, gear, bearings are the major components of a process industry and any fault in them may cause a total shutdown of the whole process, which may result in serious losses. Therefore, it is very crucial to predict any approaching defects before its occurrence. Several methods exist for this purpose and many research are being carried out for better and efficient models. However, most of them are based on the processing of raw sensor signals, which is tedious and expensive. Recently, there has been an increase in the feature based condition monitoring, where only the useful features are extracted from the raw signals and interpreted for the prediction of the fault. Most of these are handcrafted features, where these are manually obtained based on the nature of the raw data. This of course requires the prior knowledge of the nature of data and related processes. This limits the feature extraction process. However, recent development in the autoencoder based feature extraction method provides an alternative to the traditional handcrafted approaches; however, they have mostly been confined in the area of image and audio processing. In this work, we have developed an automated feature extraction method for on-line condition monitoring based on the stack of the traditional autoencoder and an on-line sequential extreme learning machine(OSELM) network. The performance of this method is comparable to that of the traditional feature extraction approaches. The method can achieve 100% detection accuracy for determining the bearing health states of NASA bearing dataset. The simple design of this method is promising for the easy hardware implementation of Internet of Things(IoT) based prognostics solutions.

As autonomy becomes prevalent in many applications, ranging from recommendation systems to fully autonomous vehicles, there is an increased need to provide safety guarantees for such systems. The problem is difficult, as these are large, complex systems which operate in uncertain environments, requiring data-driven machine-learning components. However, learning techniques such as Deep Neural Networks, widely used today, are inherently unpredictable and lack the theoretical foundations to provide strong assurance guarantees. We present a compositional approach for the scalable, formal verification of autonomous systems that contain Deep Neural Network components. The approach uses assume-guarantee reasoning whereby {\em contracts}, encoding the input-output behavior of individual components, allow the designer to model and incorporate the behavior of the learning-enabled components working side-by-side with the other components. We illustrate the approach on an example taken from the autonomous vehicles domain.

Amazon CEO Jeff Bezos knocks Google for turning down a military contract. So while Google kills contracts that help our nation's defenses, opting instead to help China's artificial intelligence -- Amazon puts America first. Despite getting flak from sheltered employees who think national security is for losers, CEO Jeff Bezos sticks to his guns. He recently said this, "We are going to continue to support the DOD, and I think we should, it doesn't make any sense to me – sometimes, one of the jobs of senior leadership is to make the right decision, even when it's unpopular. And if big tech companies are going to turn their back on the U.S. Department of Defense, this country is going to be in trouble."

Squeezed by the U.S. military, the power of the terror group has shrunk. But, as Lucas Tomlinson reports, the fight is far from over. ISIS has threatened a drone attack on the Eiffel Tower with a chilling new poster. The threat comes just four months after Paris installed a 10ft anti-terror wall around the landmark, using bulletproof glass to protect visitors from potential attacks. The red and black poster shows a drone carrying a sizeable object while flying next to the Eiffel Tower, which is framed in crosshairs.

Pepper has become the first robot to appear at a UK parliamentary meeting, talking to MPs about the future of artificial intelligence in education. The robot is currently based at Middlesex University, working with students and appearing at events. MPs smiled when the robot was wheeled in, although both questions and answers were pre-arranged. Tory MP Lucy Allan joked that Pepper was "better than some of the ministers we have had before us". The Education Committee is looking at the impact technologies such as AI and robotics will have on education.

Examples include China's chillingly precise surveillance apparatus and "social credit system," by which the government monitors its citizens and assigns them a "score" according to their behavior. The big picture: Until now, the challenge to the post-World War II system has appeared to flow from mainly three public trends -- a rejection of immigration, globalization and establishment leaders. These have led to a tribal mentality, in which nations and groupings within them are championing their own, and demonizing those viewed as outsiders. But these are just the threats from within. "These tools make it easier for authorities to track what is going on, influence the flow of information, and marginalize dissident voices," Darrell West, director of the center for technology innovation at the Brookings Institution, tells Axios.

The notion of deploying armed human soldiers on the ground to fight wars will disappear over time, according to one of America's top military scientists. "We have to get used to the radical idea that we, human beings, will be just one species of intelligent beings," Alexander Kott, chief of the Network Science Division of the US Army Research Laboratory, told the Conference on Applied Machine Learning for Information Security (CAMLIS) on Friday. Kott predicted a dystopian future where human warriors share the battlefield with intelligent agents in the form of robots, sensors, smart weapons, autonomous vehicles, and wearable gizmos. These exist today to some degree, however, in the future they will be much more intelligent, and use machine-learning software to automatically take in fresh information and make decisions in a constantly changing environment. "It's coming and will be a reality in 20 years," Kott said.

In September, after one of the most violent wildfire seasons in California history, Gov. Jerry Brown signed a bill that would allow utility companies to charge customers for future legal settlements from the 2017 wildfires--even if they were the utility company's fault. It's meant to prevent Pacific Gas & Electric Co. from going bankrupt; as the AP reported, the company would have to pay billions of dollars if investigators found the company's equipment at fault for sparking the Tubbs Fire that killed 22 people in Santa Rose and made thousands more homeless. Consumer advocates have criticized it as a bailout, with utilities having to augment their efforts to reduce the risk of fires. Furthermore, the law requires to pay the entire cost of accidental fires if they fail to properly maintain electrical transmission stations and distribution power lines. After yet another devastating summer of flames raging through California's parched forests, utility executives are forced to figure out one thing: How can they limit the danger of electrical transmission equipment and distribution power lines igniting vegetation and sparking yet another devastating wildfire?

The comments, during an on stage interview Monday at a Wired technology conference in San Francisco, followed reports several weeks ago about Google's secret China search project that sparked a backlash from human-rights advocates and Washington lawmakers, who warn the effort could aid a repressive regime. Google, a unit of Alphabet Inc., also faces pressure from its own employees to only do work that adheres to the company's values. In August, hundreds of employees signed a letter asking Google to give rank-and-file workers a voice in the ethics-review process and the ability to opt out of working on certain projects. Google decided in 2010 to withdraw its search engine from China to protest government censorship and attempts to hack into the Gmail accounts of Chinese human-rights activists. Google co-founder Sergey Brin then described the government as having the "earmarks of totalitarianism" of the Soviet Union, where he was born.

USA Today is no stranger to using technology as a hook for political coverage, but this time it could be particularly helpful in performing your civic duty. It's rolling out chat bots across its properties that will help you keep tabs on various aspects of the 2018 midterm elections, including national news, regional election info and the hot-button issues of the day. And crucially, the bots will help you find polling stations -- you'll know both where local politicians stand as well as where to vote on November 6th. The news outlet has been gradually introducing the chat bot technology in October, but it will be widely available through the company's Android and iOS mobile apps and should reach the web by the end of the week. There's a certain novelty factor here, just as get-out-the-vote social tools were fresh in 2016.