The market is further segmented on the basis of types and end-user applications. The report also provides an estimation of the segment expected to lead the market in the forecast years. Detailed segmentation of the market based on types and applications along with historical data and forecast estimation is offered in the report. Furthermore, the report provides an extensive analysis of the regional segmentation of the market. The regional analysis covers product development, sales, consumption trends, regional market share, and size in each region.

The market is further segmented on the basis of types and end-user applications. The report also provides an estimation of the segment expected to lead the market in the forecast years. Detailed segmentation of the market based on types and applications along with historical data and forecast estimation is offered in the report. Furthermore, the report provides an extensive analysis of the regional segmentation of the market. The regional analysis covers product development, sales, consumption trends, regional market share, and size in each region.

Facial recognition technology is now common in a growing number of places around the world from public CCTV cameras to biometric identification systems in airports already touching half of the global population on a regular basis. Visualizations from SurfShark classify 194 countries and regions based on the extent of surveillance. More recently, the Department of Homeland Security unveiled its "Biometric Exit" plan, which aims to use facial recognition technology on nearly all air travel passengers by 2023, to identify compliance with visa status. Perhaps surprisingly, 59% of Americans are actually in favour of implementing facial recognition technology, considering it acceptable for use in law enforcement according to a Pew Research survey. Yet, some cities such as San Francisco have pushed to ban surveillance, citing a stand against its potential abuse by the government. Facial recognition technology can potentially come in handy after a natural disaster.

Robots are becoming an important way to deliver health care, and personality is vital to understanding their effectiveness. Despite this, there is a lack of a systematic overarching understanding of personality in health care human robot interaction (H-HRI). To address this, the authors conducted a review that identified 18 studies on personality in H-HRI. This paper presents the results of that systematic literature review. Insights are derived from this review regarding the methodologies, outcomes, and samples utilized. The authors of this review discuss findings across this literature while identifying several gaps worthy of attention. Overall, this paper is an important starting point in understanding personality in H-HRI.

Technovation, a global technology education nonprofit, announced that two teams of girls and two family teams - representing Kazakhstan, Kuwait, India and Ireland - were named winners at its annual Technovation World Summit held virtually August 13-14. The two-day event brought together more than 1,000 members and supporters of the Technovation community from around the world. The Awards Ceremony, held during World Summit, is a culmination of the annual Technovation Girls and Technovation Families programs in which nearly 2,000 teams of girls (ages 10-18) and families (with children ages 8-16) are challenged to develop a mobile application or AI prototype to solve an issue they've identified in their community. This year, teams across 60 countries overcame incredible odds stemming from COVID-19 to participate with the support of more than 3,500 mentors and chapter ambassadors. All finalists will receive a portion of the nearly $30,000 being awarded.

JOHANNESBURG - Artificial Intelligence (AI) is one of the important building blocks of the Fourth Industrial Revolution (4IR) or the age of "intelligentisation." The past few years have seen tremendous advances in machine learning and the building of algorithms from data; deep learning simulating the human brain and the processing power and decreasing costs of powerful and fast computers. Intelligent devices are, therefore, increasingly finding their way into our lives, whether it is a personal assistant such as the Amazon Alexa, Google Home, Apple Siri or Samsung Bixby; satellite navigation; real-time language translation; biometric identification such as fingerprint, iris or facial recognition; or industrial process management and decision-making. Unfortunately, noble AI technology also has the possibility to be misused and exploited for criminal purposes. In 2016 two computational social scientists by the name of Seymour and Tully used AI to convince social media users to click on a phishing link within a mass-produced message.

The use of AI (Artificial Intelligence) technology in commercial aviation has brought some significant changes in the way flights are being operated today. The world's leading airline service providers are now using AI tools and technologies to deliver a more personalized traveling experience to their customers. From building AI-powered airport kiosks to using it for automating airline operations and security checking, AI will play even more critical roles in the aviation industry. The International Air Transport Association (IATA) and Airports Council International (ACI) have noticed AI's value too. Here, a look at how airlines are currently using AI, and emerging areas that show promising results for a better travel experience.

Peter leads us in Project Management with over 30 years experience in industry. He is critical of QA procedures and adherence to industry standards with regards to documentations, drawings and calculations. He is also skilled in SWOT analysis for future business planning. Peter has managed a wide range of European Union funded projects under grants by innovateUK. His exposure cuts across nuclear, marine and civil engineering related projects.

We propose a reward function estimation framework for inverse reinforcement learning with deep energy-based policies. We name our method PQR, as it sequentially estimates the Policy, the $Q$-function, and the Reward function by deep learning. PQR does not assume that the reward solely depends on the state, instead it allows for a dependency on the choice of action. Moreover, PQR allows for stochastic state transitions. To accomplish this, we assume the existence of one anchor action whose reward is known, typically the action of doing nothing, yielding no reward. We present both estimators and algorithms for the PQR method. When the environment transition is known, we prove that the PQR reward estimator uniquely recovers the true reward. With unknown transitions, we bound the estimation error of PQR. Finally, the performance of PQR is demonstrated by synthetic and real-world datasets.

It has been theorized that positive intergroup relations can reduce prejudice and facilitate peace. However, supporting empirical evidence is weak, particularly in the context of real-world conflict. Mousa randomized Christian Iraqi refugees to soccer teams that were composed of either all Christian players or a mixture of Christian and Muslim players (see the Perspective by Paluck and Clark). Playing on the same team as Muslims had positive effects on Christian players' attitudes and behaviors toward Muslims within the context of soccer, but these effects did not generalize to non-soccer contexts. These findings have implications for the potential benefits and limits of positive intergroup contact for achieving peace between groups. Science , this issue p. [866][1]; see also p. [769][2] Can intergroup contact build social cohesion after war? I randomly assigned Iraqi Christians displaced by the Islamic State of Iraq and Syria (ISIS) to an all-Christian soccer team or to a team mixed with Muslims. The intervention improved behaviors toward Muslim peers: Christians with Muslim teammates were more likely to vote for a Muslim (not on their team) to receive a sportsmanship award, register for a mixed team next season, and train with Muslims 6 months after the intervention. The intervention did not substantially affect behaviors in other social contexts, such as patronizing a restaurant in Muslim-dominated Mosul or attending a mixed social event, nor did it yield consistent effects on intergroup attitudes. Although contact can build tolerant behaviors toward peers within an intervention, building broader social cohesion outside of it is more challenging. [1]: /lookup/doi/10.1126/science.abb3153 [2]: /lookup/doi/10.1126/science.abb9990