Every day the programming environment is not only rapidly growing but also changing and languages are constantly evolving. Learning of object-oriented paradigm is compulsory in every computer science major so the choice of language to teach object-oriented principles is very important. Due to large pool of object-oriented languages, it is difficult to choose which should be the first programming language in order to teach object-oriented principles. Many studies shown which should be the first language to tech object-oriented concepts but there is no method to compare and evaluate these languages. In this article we proposed a comprehensive framework to evaluate the widely used object-oriented languages. The languages are evaluated basis of their technical and environmental features. Furthermore, we have constructed a scoring function based on proposed evaluation framework which provides us a language's quantitative score allow us to determine which language is acceptable as first object-oriented language to teach. Moreover, we have also calculated the conformance of widely used object-oriented languages.

Cal Fire and other agencies use a network of over 1,000 cameras statewide to track wildfires before, during and after. The public can now access the network, too. Wildfire season is almost here, and there's a new way you can help firefighters -- from anywhere. The University of California San Diego and state fire agencies have partnered to launch a public website for people to watch live camera feeds across the state. The program called ALERTCalifornia also helps firefighters fight fires by using a network of more than 1,000 live camera sensors to track the fires before, during and after.

Law makers ask President Obama for more water pumping from Sacramento Delta.

House Speaker Nancy Pelosi has given us a unique opportunity to perfectly understand the modern Democrats' belief in aristocratic superiority. The California Democrat's recent hypocrisy in going to her hair salon, which was supposed to be shut down due to San Francisco's stringent (and Pelosi-supported) COVID-19 rules, is just one more example of Democratic members of the political aristocracy believing they are superior to citizens (the opposite of the founding premise of America). The American people have long resented the hypocrisy and arrogance by which a political aristocracy believes one set of rules applies to the public and a totally different set of rules applies to its interests and its family members. We knew that this double standard deeply offended most Americans in 1994. That is why the first commitment of the Contract with America was to "require all laws that apply to the rest of the country also apply equally to the Congress."

Normative expert systems have not become commonplace because they have been difficult to build and use. Over the past decade, however, researchers have developed the influence diagram, a graphical representation of a decision maker's beliefs, alternatives, and preferences that serves as the knowledge base of a normative expert system. Most people who have seen the representation find it intuitive and easy to use. Consequently, the influence diagram has overcome significantly the barriers to constructing normative expert systems. Nevertheless, building influence diagrams is not practical for extremely large and complex domains. In this book, I address the difficulties associated with the construction of the probabilistic portion of an influence diagram, called a knowledge map, belief network, or Bayesian network. I introduce two representations that facilitate the generation of large knowledge maps. In particular, I introduce the similarity network, a tool for building the network structure of a knowledge map, and the partition, a tool for assessing the probabilities associated with a knowledge map. I then use these representations to build Pathfinder, a large normative expert system for the diagnosis of lymph-node diseases (the domain contains over 60 diseases and over 100 disease findings). In an early version of the system, I encoded the knowledge of the expert using an erroneous assumption that all disease findings were independent, given each disease. When the expert and I attempted to build a more accurate knowledge map for the domain that would capture the dependencies among the disease findings, we failed. Using a similarity network, however, we built the knowledge-map structure for the entire domain in approximately 40 hours. Furthermore, the partition representation reduced the number of probability assessments required by the expert from 75,000 to 14,000.

The robot takeover will start in the smaller cities. Towns and small cities have a smaller proportion of jobs that will be resilient to automation than larger urban centres, according to a new study. By looking at the jobs that are most susceptible to automation and their distribution across different US cities, Iyad Rahwan at the Massachusetts Institute of Technology Media Lab and his team have found a trend between the size of a city and the impact we should expect artificial intelligence and robots to have on human workers. Roughly speaking, cities with fewer than 100,000 inhabitants are more at risk. The East Coast cities are full of jobs that should be resilient to automation. Washington DC, for example, has many government-related roles that are hard to automate, and New York, with its population of 8.5 million, is able to support many specialist jobs too.

The death of a Valley State Prison inmate is being investigated as a possible homicide, officials said Monday. The 44-year-old man, whose name is being withheld pending notification of next of kin, was found unresponsive on Thanksgiving morning in a dormitory at the Chowchilla facility, according to a prison statement. "Life-saving measures were initiated and an ambulance was called to the scene, but the inmate was pronounced dead at 9:45 a.m.," the statement read. Officials are awaiting an autopsy to determine the cause of death, said Lt. Ronald Ladd, a public information officer with the prison. The inmate was received by the California Department of Corrections and Rehabilitation from Los Angeles County in June 2015 and was serving a two-year, eight-month sentence for second-degree burglary and possession of a controlled substance, officials said.