Aggressive driving a reflection of surrounding culture

first_imgAggressive driving behaviour is a reflection of a person’s surrounding culture, both on the road and on a broader social level, says a study.The findings suggest that some countries and cultures may be more susceptible to aggressive or competitive driving behaviours due to their social environment, and that improvements in that arena would also be seen in driving behaviour.“The choice to be competitive versus cooperative always starts with culture, by the influences around us and the way other people behave, ‘said one of the researchers Haizhong Wang, assistant professor of transportation engineering at Oregon State University in the US.  Also Read – ‘Playing Jojo was emotionally exhausting’“And it’s clear there’s a role for education and experience, where studies have shown the value of young drivers participating in driver education programmes and receiving positive guidance from their parents and peers,” Wang noted.The study also implies that different social conditions might ultimately translate into better drivers.However, these dangerous behaviours are becoming a worldwide phenomenon of almost epidemic proportions partly as a reaction to overcrowded road networks, the researchers said. Also Read – Leslie doing new comedy special with NetflixThe findings, published in the journal Procedia Engineering, showed that such behaviour is more pronounced in men than in women.The research was done with drivers in China where competitive driving is very common. The problems in China as it becomes increasingly crowded with drivers, however, reflect similar concerns at varying levels around the world, Wang said. In this analysis, the researchers concluded that drivers in congested situations generally believed that the chaotic traffic state was responsible for their competitive behaviour and they had no option other than to compete for space, the right-of-way, and gain advantages through speed and spacing.In simple terms, it was right and proper that they should try to keep up with or get ahead of traffic; that was the example being set for them, and they drove that way because everyone else did.However, the study also suggested that “personality traits draw on and are influenced by aspects of one’s social environment.” It is prevalent in India too where the surroundings play an important part.last_img read more

How Facebook data scientists use Bayesian optimization for tuning their online systems

first_imgFacebook data scientists had released a paper, Constrained Bayesian Optimization with Noisy Experiments in 2017 where they describe using Bayesian optimization to design rounds of A/B tests based on prior test results. An A/B test is a randomized experiment, used to determine which variant of A and B is more “effective”. They are used for improving a product. Facebook has a large array of backend systems serving billions of people every day. They have a large number of internal parameters that must be tuned carefully using live, randomized experiments, also known as A/B tests. Individual experiments may take a week or longer, so there is a challenge to optimize a set of parameters with the least number of experiments. Bayesian optimization Bayesian optimization is a technique used to solve optimization problems where the objective function (the online metric of interest) does not have an analytic expression. It can only be evaluated through some time consuming operations like a randomized experiment. Bayesian optimization allows joint tuning of more parameters with fewer experiments compared to a grid search or manual tuning. It also helps in finding better values. The Gaussian process (GP) is a Bayesian model that works well for Bayesian optimization. GP provides good uncertainty estimates of how an online metric varies with the parameters of interest. It is illustrated as follows: Source: Facebook research blog The work in the paper was motivated by several challenges in using Bayesian optimization for tuning online systems. The challenges are noise, constraints, and batch experimentation. In the paper, the authors describe a Bayesian approach for handling observation noise in which they include the posterior uncertainty induced by noise in EI’s expectation. In the paper, they describe a Bayesian approach for handling observation noise. A posterior uncertainty is induced by noise in EI’s expectation. Instead of computing the expectation of I(x) under the posterior of f(x), it is computed under the joint posterior of f(x) and f(x*). This expectation no longer has a closed form like El but can easily draw samples of values at past observations f(x_1), …, f(x_n) from the GP posterior. The conditional distribution f(x) | f(x_1), …, f(x_n) has closed form. The results The approach described in the paper is used to optimize various systems at Facebook. Two such optimizations are described in the paper. The first is to optimize six parameters from one of Facebook’s ranking systems. The second one was to optimize seven numeric compiler flags for the HipHop Virtual Machine (HHVM). The web servers powering Facebook use the HHVM to serve requests. The end goal of this optimization was to reduce CPU usage on the web servers, with a constraint of keeping the peak memory usage less. This following figure shows the CPU usage of each configuration tested. There is a 100 total, it also shows the probability that each point satisfied the memory constraint: Source: Facebook research blog The first 30 iterations were randomly generated configurations depicted as a green line. After this, the Bayesian optimization was used to identify parameter configurations to be evaluated. It was observed that Bayesian optimization was able to find better configurations that are more likely to satisfy the constraints. The findings are that Bayesian optimization is an effective and robust tool for optimizing via noisy experiments. For full details, visit the Facebook research blog. You can also take a look at the research paper. Read next NIPS 2017 Special: A deep dive into Deep Bayesian and Bayesian Deep Learning with Yee Whye Teh Facebook’s Glow, a machine learning compiler, to be supported by Intel, Qualcomm and others “Deep meta reinforcement learning will be the future of AI where we will be so close to achieving artificial general intelligence (AGI)”, Sudharsan Ravichandiranlast_img read more

Summer flights from Toronto to Saint Lucia with Sunwing

first_img<< Previous PostNext Post >> TORONTO — Sunwing has extended flights between Toronto and Saint Lucia this coming summer. Flights will depart weekly on Sundays starting May 7 until Oct. 29.Andrew Dawson, President of Tour Operations for Sunwing Vacations, said Saint Lucia has become an increasingly popular destination because it has an all-year-round appeal, from its jazz festivals in May to fishing tournaments in October. “Plus, the fact that this service extension coincides with the opening of two new Royalton Luxury Resorts in Saint Lucia is very exciting. Royalton Luxury Resorts is one of our top hotel partners and we’re sure these latest additions to their ever-expanding lineup of luxury properties will be well received.”Royalton Saint Lucia Resort & Spa is family-friendly and features a supervised Clubhouse Kids Club and Hangout Teen Club, splash pads, non-motorized water sports, and for the parents, The Royal Spa.Hideaway at Royalton Saint Lucia, an adults-only resort, features an infinity pool, exclusive beach area with waiter service and exclusive restaurant while still having access to Royalton Saint Lucia Resort & Spa amenities and features. For more information visit Sunwing.ca. Posted by Wednesday, January 25, 2017 Travelweek Group center_img Summer flights from Toronto to Saint Lucia with Sunwing Tags: Sunwing Sharelast_img read more