The Social Internet of Things (SIoT), integration of Internet of Things and Social networks paradigms, has been introduced to build a network of smart nodes which are capable of establishing social links. In order to deal with misbehavioral service provider nodes, service requestor nodes must evaluate their trustworthiness levels. In this paper, we propose a novel trust management mechanism in the SIoT to predict the most reliable service provider for a service requestor, that leads to reduce the risk of exposing to malicious nodes. We model an SIoT with a flexible bipartite graph (containing two sets of nodes: service providers and requestors), then build the corresponding social network among service requestor nodes, using Hellinger distance. After that, we develop a social trust model, by using nodes' centrality and similarity measures, to extract behavioral trust between the network nodes. Finally, a matrix factorization technique is designed to extract latent features of SIoT nodes to mitigate the data sparsity and cold start problems. We analyze the effect of parameters in the proposed trust prediction mechanism on prediction accuracy. The results indicate that feedbacks from the neighboring nodes of a specific service requestor with high Hellinger similarity in our mechanism outperforms the best existing methods. We also show that utilizing social trust model, which only considers the similarity measure, significantly improves the accuracy of the prediction mechanism. Furthermore, we evaluate the effectiveness of the proposed trust management system through a real-world SIoT application. Our results demonstrate that the proposed mechanism is resilient to different types of network attacks and it can accurately find the proper service provider with high trustworthiness.

When Paul Kay, then an anthropology graduate student at Harvard University, arrived in Tahiti in 1959 to study island life, he expected to have a hard time learning the local words for colors. His field had long espoused a theory called linguistic relativity, which held that language shapes perception. Color was the "parade example," Kay says. His professors and textbooks taught that people could only recognize a color as categorically distinct from others if they had a word for it. If you knew only three color words, a rainbow would have only three stripes.

Suicide car bomber attacks military airstrip used for U.S. drone mission; reaction and analysis from retired four-star Gen. Jack Keane, Fox News senior strategic analyst. The United States Embassy in Mogadishu, Somalia, has reopened after being closed for 28 years, officials said Wednesday. "The reestablishment of Embassy Mogadishu is another step forward in the resumption of regular U.S.-Somali relations, symbolizing the strengthening of U.S.-Somalia relations and advancement of stability, development and peace for Somalia and the region," the embassy said in a statement. The embassy closed on Jan. 5, 1991, after Somalia became engulfed in a civil war and the regime of Siad Barre was overthrown. The United States reestablished a permanent diplomatic presence in Mogadishu back in December, operated out of Nairobi, Kenya.

Demi Lovato deactivates her Twitter account after getting backlash for mocking 21 Savage following his ICE arrest. Demi Lovato is apologizing after some characterized her recent trip to Israel, during which she was baptized in the Jordan River, as a political statement. Lovato, 27, traveled to the Middle East after she "accepted a free trip to Israel in exchange for a few [social media] posts." But her trip apparently sparked backlash, as the singer saw the need to explain the reasoning for her experience in a follow-up Instagram Story. "I'm extremely frustrated," she wrote. "No one told me there would be anything wrong with going or that I could possibly be offending anyone.

Today we are joined by Karim Beguir, Co-Founder and CEO of InstaDeep. InstaDeep, based in Tunisia, Africa, is focused on building advanced decision-making systems for the enterprise. Karim's goal is to show that advanced AI and Deep Learning is taking place in Africa, solving real-world problems and building a new generation of talent in the AI industry. With offices around the world, InstaDeep works with large companies in multiple industries with this episode focusing on logistical challenges, like ride-sharing and container shipping. These problems require decision-making in complex environments with a large number of choices.

BlackBerry Limited BB has created Advanced Technology Development Labs (BlackBerry Labs). This is going to be a new business unit operating at the forefront of R&D in the cybersecurity landscape. With this strategic move, the company aims to ensure that its customers are protected across all endpoints and verticals in the IoT. Headed by chief technology officer, BlackBerry Labs will include a team of more than 120 software developers, architects, researchers, product leads and security experts. They will work toward the common goal of identifying, exploring and creating new technologies to ensure that the company is on the cutting edge of security innovation.

Earthquake Alert! 6.7 temblor, epicenter 3.8 miles west of Ventura, California--impact will be in eleven minutes--evacuate, evacuate!" While you run to the hall closet to grab your earthquake kit, you shout out: "Alexa, where is my emergency evac location?" Walk north to Wilshire, then take a left on Warner," she responds. As you and your neighbors pour into the building stairwell, you hear audio from a phone: "Google Earth Q estimates substantial potential for structural damage in the West San Fernando Valley and Coastal West Los Angeles to pre-2006 code dwellings and buildings. Most of West LA will experience total loss of power for anywhere from six to twenty-four hours in duration."

With technological advancement, IT technology developers are making efforts to develop software that can ease the physical work life. One such advancement in technology is intelligent automation. The intelligent automation is a combination of automation and artificial intelligence. This new technology has revolutionized the way data is handled and processed. The intelligent automation system determines and synthesizes a massive amount of information, automates the business and operational workflows and adapts it.

The critical locus of the loss function of a neural network is determined by the geometry of the functional space and by the parameterization of this space by the network's weights. We introduce a natural distinction between pure critical points, which only depend on the functional space, and spurious critical points, which arise from the parameterization. We apply this perspective to revisit and extend the literature on the loss function of linear neural networks. For this type of network, the functional space is either the set of all linear maps from input to output space, or a determinantal variety, i.e., a set of linear maps with bounded rank. We use geometric properties of determinantal varieties to derive new results on the landscape of linear networks with different loss functions and different parameterizations.

Convolutional neural networks (CNNs) have achieved breakthrough performances in a wide range of applications including image classification, semantic segmentation, and object detection. Previous research on characterizing the generalization ability of neural networks mostly focuses on fully connected neural networks (FNNs), regarding CNNs as a special case of FNNs without taking into account the special structure of convolutional layers. In this work, we propose a tighter generalization bound for CNNs by exploiting the sparse and permutation structure of its weight matrices. As the generalization bound relies on the spectral norm of weight matrices, we further study spectral norms of three commonly used convolution operations including standard convolution, depthwise convolution, and pointwise convolution. Theoretical and experimental results both demonstrate that our bounds for CNNs are tighter than existing bounds.