Important advances have been made in the fuzzy quantification field. Nevertheless, some problems remain when we face the decision of selecting the most convenient model for a specific application. In the literature, several desirable adequacy properties have been proposed, but theoretical limits impede quantification models from simultaneously fulfilling every adequacy property that has been defined. Besides, the complexity of model definitions and adequacy properties makes very difficult for real users to understand the particularities of the different models that have been presented. In this work we will present several criteria conceived to help in the process of selecting the most adequate Quantifier Fuzzification Mechanisms for specific practical applications. In addition, some of the best known well-behaved models will be compared against this list of criteria. Based on this analysis, some guidance to choose fuzzy quantification models for practical applications will be provided.

The news and information ecosystem is in the midst of change -- again. Mobile-first consumption is on the rise, smart homes are becoming mainstream and connected cars will soon take over the roads of major cities around the world. Smart devices will require "smart content." It's only a matter of time before artificial intelligence becomes the backbone of the media industry of the future. Today, most people find information via search or social.

The problem is that if robot labor is cheaper and more reliable than human labor, why bother with the latter? The payback period for industrial robots (the time it takes for their extra costs to be paid off) is falling sharply. For a welding robot to be used in a Chinese factory, for example, the period has fallen from 5.3 years in 2010, to 1.7 years in 2015, say analysts from Citi. By 2017, they say it could be as low as 1.3 years. And more robots in factories equals fewer jobs for humans.

WIRE)--Accenture (NYSE:ACN) is expanding its machine learning and operations analytics capabilities by acquiring OPS Rules, a boutique analytics consulting company that specializes in the application of data science to create supply chain and operations analytics solutions. When the acquisition is completed, Accenture will add new operations analytics professionals to its team that apply machine learning and optimization techniques to develop fresh and innovative analytics approaches for clients across many industries. Terms of the transaction were not disclosed. Founded in 2012, OPS Rules has offices in Waltham, Massachusetts and Richardson, Texas. OPS Rules is led by David Simchi-Levi, a Professor of Engineering Systems at the Massachusetts Institute of Technology (MIT) and renowned supply chain and operations analytics expert.

That's the projected galaxy haul of the Large Synoptic Survey Telescope, currently under construction in Chile. Starting around 2023, the LSST camera's 3,200 megapixels will soak up 15 terabytes of data every night, which will fill the biggest astronomical database ever built. Computer scientist Lior Shamir of Lawrence Technological University in Michigan says the amount of data defies comprehension. "With just a mountain of images, no one will ever inspect them one by one. You can never make a discovery," he says. "You need to convert it into something that machines can understand."

SK C&C has continued Korea's efforts to increase the usage and adoption of cloud computing within the region, announcing a new strategic alliance with IBM focused on the Watson cognitive computing platform. As part of the agreement, IBM will train Watson to understand and comprehend Korean, and South Korea-based developers will create a number of localized API's and services to increase adoption rates of such advanced cloud computing technologies in the region. Korean will be Watson's eighth language, lining up with English, French, Italian, Spanish, Brazilian Portuguese, Japanese, and Arabic. "Watson remains at the forefront of cognitive computing: advanced systems that learn at scale, understand with meaning, reason with purpose and interact with humans in natural ways," said David Kenny, GM for IBM Watson. "The South Korean marketplace is moving quickly to embrace the disruptive opportunities from next generation technology.

The refugee crisis is perhaps the single most challenging problem for Europe today. Hundreds of thousands of people have already traveled across dangerous sea passages from Turkish shores to Greek islands, resulting in thousands of dead and missing, despite the best rescue efforts from both sides. One of the main reasons is the total lack of any early warning-alerting system, which could provide some preparation time for the prompt and effective deployment of resources at the hot zones. This work is such an attempt for a systemic analysis of the refugee influx in Greece, aiming at (a) the statistical and signal-level characterization of the smuggling networks and (b) the formulation and preliminary assessment of such models for predictive purposes, i.e., as the basis of such an early warning-alerting protocol. To our knowledge, this is the first-ever attempt to design such a system, since this refugee crisis itself and its geographical properties are unique (intense event handling, little or no warning). The analysis employs a wide range of statistical, signal-based and matrix factorization (decomposition) techniques, including linear & linear-cosine regression, spectral analysis, ARMA, SVD, Probabilistic PCA, ICA, K-SVD for Dictionary Learning, as well as fractal dimension analysis. It is established that the behavioral patterns of the smuggling networks closely match (as expected) the regular burst and pause periods of store-and-forward networks in digital communications. There are also major periodic trends in the range of 6.2-6.5 days and strong correlations in lags of four or more days, with distinct preference in the Sunday-Monday 48-hour time frame. These results show that such models can be used successfully for short-term forecasting of the influx intensity, producing an invaluable operational asset for planners, decision-makers and first-responders.

When you look at cloud skills, it's more important to think about what's coming rather than what's already here. Why? Thousands of IT people will complete cloud certification programs this year. If you delay, the job market may be flooded by the time you're ready. Soon the "Internet of Things" will be keeping watch on jet engines, refrigerators and freezers, factory floors and more, thanks to a series of partnerships announced by Microsoft at the Hannover Messe industrial fair in Germany. Some people spend weeks, months, even years trying to learn machine learning without any success.

Still in the depths of sleep, I reach out and grab it, knocking a cold cup of coffee over the unread mountain of books on my bedside. I swear loudly, mop up the mess with one hand and look blearily at the message on my screen. It's from Otis, 27, who I have apparently just matched with on Tinder: "Hey sexy like ur curls. Wanna come over n get naked and I'll show you my curls." There is no denying that the pursuit of love in the 21st century has become littered with digital landmines. There are now more than 91 million people around the world on dating apps – and most of that is thanks to Tinder.

Very interesting data compiled and analyzed by O'Reilly, using statistical models such as Lasso regression to predict salary based on different factors. It reminds me our own analysis based on simulated (but realistic) data, to assess whether having Python or R (or both) commands a bigger salary, and what is the extra boost provided by these skills, individually. The statistical model used was Jackknife regression, and it was designed for tutorial purposes. The O'Reilly survey is much bigger, based on real data, and it includes many factors, as well as factor selection. It uses standard statistical techniques which might be less robust than Jackknife regression.