Electroencephalography (EEG) recordings of rhythm perception might contain enough information to distinguish different rhythm types/genres or even identify the rhythms themselves. We apply convolutional neural networks (CNNs) to analyze and classify EEG data recorded within a rhythm perception study in Kigali, Rwanda which comprises 12 East African and 12 Western rhythmic stimuli – each presented in a loop for 32 seconds to 13 participants. We investigate the impact of the data representation and the pre-processing steps for this classification tasks and compare different network structures. Using CNNs, we are able to recognize individual rhythms from the EEG with a mean classification accuracy of 24.4% (chance level 4.17%) over all subjects by looking at less than three seconds from a single channel. Aggregating predictions for multiple channels, a mean accuracy of up to 50% can be achieved for individual subjects.
It also provides rigorous Deep Learning System study on the market spike, categorization, and revenue evaluation. This report provides market position from the reader's viewpoint, providing certain Deep Learning System market statistics and business hunch. The global Deep Learning System market serves past and futuristic information about the industry. It also contains company profiles of every Deep Learning System market player, scope, profit, product specification, cost, and so on. Major market vendors comprise in the Worldwide Deep Learning System market research report: Alphabet Inc., Berkeley Vision and Learning Center (BVLC), Facebook, Inc., LISA lab, Microsoft, Nervana Systems, General Vision Inc., Sensory, Inc., Nvidia Corporation, Skymind The geological regions included in the Deep Learning System report: Europe, Asia-Pacific, Africa, The Middle East, North America and Latin America.
Fox News Flash top headlines for Dec. 7 are here. Check out what's clicking on Foxnews.com The U.S. military believes the unarmed drone that went missing over the Libyan capital last month was actually shot down by Russian air defenses. The U.S. Africa Command is demanding the return of the aircraft's wreckage, which had been part of an operation conducted in Libya to assess the area's security and monitor for violent extremist activity. The command didn't give a reason for the drone loss after the Nov. 21 incident, but they had been investigating, Reuters reported.
Our NodeXL #ddj mapping from November 25 to December 1 finds The New York Times profiling Bellingcat and its use of OSINT techniques; the International Consortium of Investigative Journalists and Stanford University collaborating to employ artificial intelligence to solve a journalistic problem; and the Science Communication Lab creating a beautiful interactive scientific poster to explore the world's oceans. Open source journalism might just be the best antidote to spin: the transparency of its authors showing their work during each step of the investigative process helps earn readers' trust. The New York Times profiles Bellingcat, an investigative news site that uses open source techniques. The collaborative Implant Files investigation exposed the lax regulation of the $400 billion medical device industry worldwide. But when the International Consortium of Investigative Journalists wanted to know if women suffered disproportionately from faulty medical devices, it hit a data roadblock.
A large share of countries around the world are now using Chinese AI surveillance technology, including facial recognition technology, in full or in part. This is according to a report by Carnegie Endowment for International Peace. Many countries are combining Chinese tech with U.S.-made surveillance tech, among them the U.S. and China themselves, but also India, Australia, Brazil and several European countries. Many countries in Latin America, South-East Asia, Africa and the Middle East are relying on Chinese technology alone after participating in the Belt and Road initiative, as is Japan, the only developed country to do so. China is not only a prominent user of AI-powered surveillance and facial recognition but also a big producer and exporter of the technology.
With the Essential2020 plan all but complete, Orange has released the details of the Engage2025 strategy to drive growth over the next five years. The new strategy is going to be focused on four key pillars; reinventing the operator business model, accelerating growth in the developing markets and emerging segments, integrate artificial intelligence at the centre of every aspect of the business, and building sustainability goals through the organization. "If I had to summarise Engage2025, Orange's new strategic plan, I would use two words: growth and sustainability," said CEO Stephane Ricard. "The first one is growth. We are going to grow our core business – connectivity – by adding to our competitive edge and by making the most of our network infrastructure. We are also going to foster growth beyond connectivity in Europe thanks to three elements which set us apart from our competitors, namely Africa & the Middle East, B2B IT services and financial services. At Orange we are convinced that in the years ahead strong economic performance will not be possible without exemplary performance on social and environmental issues."
We consider the example of a deployment of an air pollution monitoring network in Kampala, an East African city. Air pollution contributes to over three million deaths globally each year(Lelieveld and others, 2015). Kampala has one of the highest concentrations of fine particulate matter (PM 2.5) of any African city Mead (2017) Hence we know little about its distribution or extent. Lower cost devices do exist, but these do not, on their own, provide the accuracy required for decision makers. In our case study, the Kampala network of sensors consists largely of low cost optical particle counters (OPCs) that give estimates of the PM2.5 particulate concentration.
"It's about saving as many lives as we possibly can," Tim Wood said. Wood spoke to Industrious en route to a meeting with USAID about its Global Health Supply Chain Program-Procurement and Supply Management project, implemented by Chemonics, a development contractor, and a consortium of partners, including IBM. Getting bed nets, HIV medication and other health supplies from medical storage facilities in Washington DC to remote parts of Africa is no small feat. But Wood, a global supply chain VP at IBM, and his GHSC-PSM consortium partners are doing just that. Global supply chains are crucial to any business or operation.
The market study on the global Healthcare Cognitive Computing market will encompass the entire ecosystem of the industry, covering five major regions namely North America, Europe, Asia Pacific, Latin America and Middle East & Africa, and the major countries falling under those regions. The study will feature estimates in terms of sales revenue and consumption from 2019 to 2025, at the global level and across the major regions mentioned above. The study has been created using a unique research methodology specifically designed for this market. Quantitative information includes Healthcare Cognitive Computing market estimates & forecast for a upcoming years, at the global level, split across the key segments covered under the scope of the study, and the major regions and countries. Sales revenue and consumption estimates, year-on-year growth analysis, price estimation and trend analysis, etc. will be a part of quantitative information for the mentioned segments and regions/countries.