Author: longdnguyen

I am a person who loves family and science.

Commercial UAV Expo Europe: PwC Names 7 Trends in the Drone Industry

Posted By Harry McNabbon on April 09, 2019 Michael Mazur, Consulting Partner and head of PwC Drone Powered Solutionsdelivered one of the Keynote addresses at the Commercial UAV Expo Europetoday in Amsterdam, naming 7 trends that the investment firm sees shaping the industry. 1) Telecom will be a major beneficiary of the drone industry. Mazur says that…
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Research Report – Speed is King: How Digital Manufacturing Can Accelerate Lean Production

Entrepreneurs, project managers and engineers know the importance of time-to-market for a successful product launch. No matter where a manufactured part or product is headed, it’s critical to maximize the speed and efficiency of its production.  Lean manufacturing is synonymous with this goal. But beyond kaizen, kanban and a whole glossary of other Japanese terms,…
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5 Innovative Ways Procurement Can Use Data Analytics

Bridget McCrea on Apr 08, 2019 We’re all inundated with data in this digital age, but here are some truly useful ways it’s helping buyers work more efficiently and effectively in this competitive business environment. Big data. Key performance metrics. Predictive data analytics. Structured and unstructured data. The list of terms used to describe the…
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The First Galaxy Discovered Was Called a “Universe Beyond Our Own”

March 21, 2019 by Written by Ashley Hamer Imagine if you’d lived your whole life indoors, believing your little room was all of reality, only to wake up one morning to learn that there are millions of other buildings just like yours and that the world was much, much bigger than you thought. That’s what…
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7 Innovative Uses of Clustering Algorithms in the Real World

on 04 April Clustering algorithms are a powerful technique for machine learning on unsupervised data. The most common algorithms in machine learning are hierarchical clustering and K-Means clustering. These two algorithms are incredibly powerful when applied to different machine learning problems. Both k-means and hierarchical clustering have been applied to different scenarios to help gain new insights into the problem. Before…
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Blockchain Applications in Telecommunication

Piotr Jurowiec on Oct 26, 2018 New blockchain applications emerge every day. Many companies are now looking into implementing it and utilize all the usefulness that it brings. Blockchain is one of the new technologies that deal with peer to peer data connection and gives an open, decentralized network to use. Powered by consensus algorithms…
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Tiny, fast, accurate technology on the radar

APRIL 18, 2019 by King Abdullah University of Science and Technology A tiny, portable radar device could allow visually impaired people, or unmanned moving devices to detect objects in real time. Radar technology has been used for decades in aviation, defense and speed-camera technology. Now, a team at KAUST, in collaboration with scientists at the…
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A novel data-compression technique for faster computer programs

APRIL 16, 2019 by Rob Matheson, Massachusetts Institute of Technology A novel technique developed by MIT researchers rethinks hardware data compression to free up more memory used by computers and mobile devices, allowing them to run faster and perform more tasks simultaneously. Data compression leverages redundant data to free up storage capacity, boost computing speeds, and provide…
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Optimizing network software to advance scientific discovery

APRIL 16, 2019 by Ariana Tantillo, Brookhaven National Laboratory High-performance computing (HPC)—the use of supercomputers and parallel processing techniques to solve large computational problems—is of great use in the scientific community. For example, scientists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory rely on HPC to analyze the data they collect at the…
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Transfer Learning

Niklas Donges on Apr 23, 2018 Transfer Learning is the reuse of a pre-trained model on a new problem. It is currently very popular in the field of Deep Learning because it enables you to train Deep Neural Networks with comparatively little data. This is very useful since most real-world problems typically do not have…
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