Africa
Robotic Process Automation (RPA) Market to Reflect Significant Growth During 2020–2026 Automation Anywhere (U.S.), Blue Prism (U.K.), Celaton Ltd (U.K.), Ipsoft (U.S.), Nice Systems Ltd. (Israel), Pegasystems (U.S.), Redwood Software (U.S.), Uipath (Romania), Verint (U.S.), Xerox Corporation (U.S.), etc – Cole Reports
The Robotic Process Automation (RPA) Market report includes overview, which interprets value chain structure, industrial environment, regional analysis, applications, market size, and forecast. This is a latest report, covering the current COVID-19 impact on the market. The pandemic of Coronavirus (COVID-19) has affected every aspect of life globally. This has brought along several changes in market conditions. The rapidly changing market scenario and initial and future assessment of the impact is covered in the report.
Thermal camera with face detection tech for fever screening procured in Kerala
The first Thermal and Optical Imaging camera with Artificial Intelligence-powered face detection technology for fever screening has been procured for the state capital by former Union Minister Shashi Tharoor. Following a discussion, his team had with district collector K Gopalakrishnan, Congress leader Tharoor said it was brought to his notice that a Thermal imaging camera with face detection technology was urgently needed in the district to scan from a safe distance and isolate those potentially having fever. Using his MPLADS fund, Tharoor, who represents, Thiruvananthapuram in the Lok Sabha, procured the equipment. Bahrain and Dubai before finally reaching Bengaluru, from where it was shipped to Kerala, Tharoor said in a Facebook Post. "The installation will be done at our Airport, Railway Station, MCH. Since all MPLADS funds have been exhausted, we are approaching other corporate groups to partner with us and the district administration to procure more of this highly sophisticated technological device prior to the huge influx of expatriates from the middle east and other areas overseas,"
Social Biases in NLP Models as Barriers for Persons with Disabilities
Hutchinson, Ben, Prabhakaran, Vinodkumar, Denton, Emily, Webster, Kellie, Zhong, Yu, Denuyl, Stephen
Building equitable and inclusive NLP technologies demands consideration of whether and how social attitudes are represented in ML models. In particular, representations encoded in models often inadvertently perpetuate undesirable social biases from the data on which they are trained. In this paper, we present evidence of such undesirable biases towards mentions of disability in two different English language models: toxicity prediction and sentiment analysis. Next, we demonstrate that the neural embeddings that are the critical first step in most NLP pipelines similarly contain undesirable biases towards mentions of disability. We end by highlighting topical biases in the discourse about disability which may contribute to the observed model biases; for instance, gun violence, homelessness, and drug addiction are over-represented in texts discussing mental illness.
The Coronavirus and Our Future
The critic Raymond Williams once wrote that every historical period has its own "structure of feeling." How everything seemed in the nineteen-sixties, the way the Victorians understood one another, the chivalry of the Middle Ages, the world view of Tang-dynasty China: each period, Williams thought, had a distinct way of organizing basic human emotions into an overarching cultural system. Each had its own way of experiencing being alive. In mid-March, in a prior age, I spent a week rafting down the Grand Canyon. When I left for the trip, the United States was still beginning to grapple with the reality of the coronavirus pandemic.
Robot 'spy' gorilla records wild gorillas singing and farting, because nature is beautiful
Mountain gorillas have been caught on camera as they "sing" during their supper, a behavior that has never before been documented on video. Filmmakers captured the astonishing footage of the primate crooners with a little help from a very special camera: a robotic "spy" designed to look like a young gorilla. The singing apes make their television debut on April 29 in the returning PBS series, "Nature: Spy in the Wild 2." Like its predecessor, which first aired in 2017, the program documents remarkable up-close glimpses of elusive wildlife behavior, seen through the "eyes" of robots that are uncanny lookalikes of the creatures that they film. But this time, the robot animals display an even greater range of realistic behaviors, enabling them to interact with the wildlife that they're spying on. Though human camera operators typically keep a safe distance from wild gorillas, the lifelike animatronic gorilla spy was able to infiltrate a troop and film their daily routines, which included an impromptu suppertime serenade. Footage of the singing gorillas is featured in the first episode of "Spy in the Wild 2" and shows the apes reclining amid dense foliage in a sanctuary in Uganda.
Robot gorilla 'spy' captures the first footage of Silverbacks in Uganda singing for their supper
A pack of Silverback Mountain gorillas in Uganda were caught for the first time on camera performing a supper serenade. Filmmakers captured the unique ritual by placing a robotic'spy' that resembles a young gorilla deep in the jungle. The team designed the animatronic machine with realistic eye movements, as wild gorillas communicate with each other through eye contact, and a submissive demeanor with the hopes it would be accepted by the pack. Along with the singing, the footage shows the gorillas screamed a'chorus of appreciation' while eating and provided evidence that they are extremely gassy. A pack of Silverback Mountain gorillas in Uganda were caught for the first time on camera performing a supper serenade.
Integrated Time Series Summarization and Prediction Algorithm and its Application to COVID-19 Data Mining
This paper proposes a simple method to extract from a set of multiple related time series a compressed representation for each time series based on statistics for the entire set of all time series. This is achieved by a hierarchical algorithm that first generates an alphabet of shapelets based on the segmentation of centroids for clustered data, before labels of these shapelets are assigned to the segmentation of each single time series via nearest neighbor search using unconstrained dynamic time warping as distance measure to deal with non-uniform time series lenghts. Thereby, a sequence of labels is assigned for each time series. Completion of the last label sequence permits prediction of individual time series. Proposed method is evaluated on two global COVID-19 datasets, first, for the number of daily net cases (daily new infections minus daily recoveries), and, second, for the number of daily deaths attributed to COVID-19 as of April 27, 2020. The first dataset involves 249 time series for different countries, each of length 96. The second dataset involves 264 time series, each of length 96. Based on detected anomalies in available data a decentralized exit strategy from lockdowns is advocated.
TZH 17 - Artificial intelligence helps tackle agricultural pest FAO
Fall Armyworm is spreading fast across sub-Saharan Africa, devastating crops and farmers' livelihoods. Experts fear the pest could eventually spread to the Middle East and Europe. But a new mobile phone app'Nuru', which uses machine learning and artificial intelligence, offers some hope in tackling the pest problem. Allan Hruska is the Principal Technical Coordinator on the Fall Armyworm response at the Food and Agricultural Organization (FAO).
Cities could face 100 million 'new poor' in post-pandemic world
BOGOTA – About 100 million people living in cities worldwide will likely fall into poverty due to the coronavirus pandemic, urban experts said on Wednesday, calling for mapping tools to identify vulnerable communities and investment focusing on slums. Densely populated cities are at the front line of the contagious outbreak. People living in poverty with little or no running water, sewage systems or health care access have been hit especially hard, said experts at the World Bank, the World Resources Institute (WRI) and other groups studying urban issues. "Within cities we need to focus on those who need help the most, the poor and the vulnerable have been very seriously affected," said Sameh Wahba, global director for the World Bank's urban, disaster risk management, resilience and land global practice. "Our estimate is that there will be possibly upward of a 100 million so-called new poor on account of loses of jobs and livelihoods and income," Wahba told a webinar with members of the media.
UAE drone strike on factory near Tripoli killed 8 civilians: HRW
A United Arab Emirates (UAE) drone strike on a biscuit factory near the Libyan capital Tripoli on November 18 killed eight civilians and injured 27 others, Human Rights Watch (HRW) said. In a report released on Wednesday, the rights group said the UAE appeared to take little or no action to minimise civilian casualties and called on Emirati authorities to conduct a transparent investigation into the incident. "Since the current armed conflict in Tripoli erupted in April 2019, the UAE has been conducting air and drone strikes to support the Libyan Arab Armed forces, previously known as the Libyan National Army [LNA], one of two major parties to the conflict, some of which have resulted in civilian casualties," HRW said. "All causalities in the November incident were civilian factory workers, including seven Libyans and 28 foreign nationals, all of them men." Human Rights Watch visited the site and found remnants of at least four Blue Arrow-7 (BA-7) laser-guided missiles that were launched by a Wing Loong-II drone.