Aggressive 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.
Kolkata: The weather condition in the city will improve from Wednesday, leading to a further drop in temperature, predicted the Regional Metereological Centre at Alipore on Tuesday. Meanwhile, Sandakphu witnessed mild snowfall on Tuesday, for the first time this winter season. It was a light drizzle accompanied by snowfall.The weather office also predicted that the city’s sky may remain cloudy from Wednesday morning and there will be a little drizzle in some parts of the city as well as South Bengal districts. The districts may witness bright sunshine from Thursday, as the cyclonic storm ‘Phethai’ has been weakened. Also Read – Rain batters Kolkata, cripples normal life”As the cyclonic condition clears, the mercury will start to drop further from Wednesday. There will be light drizzle in some parts of the city, even on Wednesday. The cyclonic storm has lost momentum due to the constant blowing of the northwesterly wind in the state. The wind will intensify further, as soon as the sky gets cleared,” a senior official of the Alipore Met office said. It may be mentioned that the city and South Bengal districts witnessed light to moderate rainfall on Tuesday, as was predicted. ‘Phethai’ has been hovering in the coastal areas of Odisha after it turned into a low-pressure zone. Also Read – Speeding Jaguar crashes into Mercedes car in Kolkata, 2 pedestrians killedIt may be mentioned that during last week, the minimum temperature had shot up as moisture in the air had been rising after the formation of a low pressure trough over Bay-of-Bengal. The mercury had started climbing due to the incursion of moisture since last week. The districts like North 24-Parganas, South 24-Parganas, Hooghly and Howrah received light rainfall overnight, while districts like East Midnapore, West Midnapore, Purulia and Bankura received light to moderate rainfall on Tuesday. The districts also experienced strong gusty winds. According to a weather official, the temperature may dip to 9 degree Celsius during Christmas this year. Traffic movement in various parts of the city was slow on Tuesday morning, due to the drizzle. The temperature on Tuesday remained around 16 degree Celsius. “The temperature on Wednesday may hover around 14 degree Celsius, while it will drop further from Thursday. As the clouds start disappearing from Wednesday, the mercury will slide further down,” the weather official said.
Facebook 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 Ravichandiran