Blizzard Seeks Patent For 'Play Of The Game' System In 'Overwatch'



Overwatch's Play of the Game has always had its issues. Just today , Kaplan asked players to keep sending him clips of their disappointing Play of the Game moments, so that the team can continue figuring out what works and what doesn't. As it stands, many Play of the Games tend to be a massive kill streak, or a support doing a whole lot of saving and healing (Mercy for example, features often if she gets a mass revive).

We constantly look at Play of the Game, and we've got a whole bunch of data on Play of the Games are actually happening out there in the wild, and we can kind of see patterns about this character getting a lot of PoTG for these killstreaks, they're getting a lot of damage, or they're getting a Play of the Game for that.

Regardless, it seems as though players will still have a long wait before they can get the promised Play of the Game 2.0. Although being rewarded play of the game doesn't necessarily correlate to a player's skill or game sense, it feels nice to be recognized.

Its definitely got to be based on your standing on your team, I noticed in matches where I get a great headstart (like five to ten kills in the first few minutes) and proceed to get royally wrecked for a long period and not gain any kills, my medals started going down from gold to silver to bronze, which I think must mean it's because someone got more kills than me and so.

Blizzard has filed a patent for their ‘Play of the Game' system. However, if the highest score for a particular category — like "high score", which tracks the amount of kills achieved in a short space of time — falls under a particular threshold, then Overwatch selects the play of the game from another category.

Support: Supports, like Swiss medic Mercy, repair damage to teammates and provide them with other tangible benefits. Blizzard Entertainment's multiplayer first-person shooter Overwatch” boasts many unique gameplay features, including the Play of the Game highlights that roll shortly after every match.

It was up to these shorts to impart narrative that was not included in the main Hammond Gameplay multiplayer game, which shipped without the traditional story mode. The Caduceus Staff targets whoever you aim it at, even if they don't need any healing, which makes it difficult to track damaged players when you're all clustered in a small space.

An improvement to the highlights system has been a wildly requested feature since launch, and we're looking forward to being able to show our Overwatch League worthy big plays to our friend. Whether you ran in battle, enemies in your sight, or dared the opposite team to nerf this, POTGs remains one of the most satisfying element of the game.

Other complaints were that the algorithm would sometimes catch random, completely un-noteworthy instances of players wandering around the map. If an Overwatch player strings together a particularly high combo of kills and points in a single moment, they're prowess is shown off at the end of the match.

So while Bastion and Hanzo might dominate play of the game from time to time with their ultimate moves, the balance could shift at any time based on any number of things. A sliding window” then passes over the recorded events, picking one category and then choosing the top player for said category before displaying a replay of the event selected.

The intent behind the Play of the Game feature is to showcase the most exciting moments that might be missed in the fast-paced matches, so that teammates can enjoy them together afterward. Play of the Game is supposed to show off Overwatch players' coolest moments, but even the game's director admits that the feature could use some more tweaking to meet its full potential.

Internal Affairs Cover Up



A longtime Virginia Seaside Police sergeant was arrested Saturday night and charged with assaulting his wife, according to police and court records.

Sgt. Shawn Walter Hoffman, 57, who works as a supervisor in the inner affairs division, was billed with one count of misdemeanor assault and electric battery of a family member.

Emergency responders were called to Hoffman’s home, in the 2400 block of Smokehouse Road, about 11:45 p.m., relating to court public records and police. The home is usually near Nimmo Parkway and Seaboard Road in debt Mill community.

Hoffman’s wife informed arriving officers that her hubby pushed her down the stairs. She had noticeable injuries to her elbow and knee consistent with a fall, according to a criminal complaint filed Monday morning in Juvenile and Domestic Relations District Court.

The complaint states that Hoffman denied pushing her.

Hoffman’s stepdaughter, who filed a handwritten incident record Sunday, mentioned that she walked in to the house that evening and found her mom sitting in the bottom of the stairs.

“I asked her what happened and she shook her head,” the stepdaughter wrote. “Then my stepdad said loudly, ‘I didn’t push her.’ And she responded with, ‘Yes he did.’ ”

The stepdaughter went on to say that a dog gate used on the stairs was broken in half and lying on the floor, and her mother’s elbow was bleeding.

“My dad kept saying, ‘We didn’t press her,’ and ‘I’d end my profession,’ ” she wrote in the declaration. “Then he began crying intensly (sic) and went upstairs and proceeded to go in his closet and I noticed him load a gun.

“I QUICKLY heard a click. He ... halfway stepped out of his area sobbing and stated, ‘I didn't push your mother.’ ”

The stepdaughter wrote that she then went a back again door and called police.

Hoffman could not end up being reached for comment Mon. He’s a lifelong resident of Child Abuse Virginia Beach and has been with the department for 36 years, according to a bail determination sheet in his court file.

He’s one of six sergeants assigned to the inner affairs division and a supervisor there, stated Linda Kuehn, a law enforcement spokeswoman. He proved helpful as a homicide detective before that.

In 2016, he was offered a Lifetime Accomplishment Award at the very top Cop Awards Dinner sponsored by Better Hampton Roads Crime Lines.

He’s probably most widely known for securing confessions in two high-profile Virginia Seaside murder cases: the 1991 killing of two youthful boys that Shawn Paul Novak, then 16, was later on convicted ; and a quadruple murder at the Witchduck Inn in 1994. In that case, he got a confession from Denise Holsinger for her role in the killings.

He’s at the center of an effort to obtain a conviction trashed for Darnell Phillips, a Virginia Seaside man sentenced in 1991 to a century in prison for the rape and defeating of a 10-year-old young lady. Hoffman testified at trial that he got a confession from Phillips within minutes of talking to him and shortly after two other detectives failed to get one after hours of questioning.

Phillips offers denied confessing to Hoffman rather than signed a declaration. Hoffman informed jurors he didn’t record the confession because he didn’t have a notebook with him.

While the department conducts an administrative investigation stemming from the misdemeanor charge, Hoffman will be reassigned and relocated, police said.

He was released on an unsecured bond after his arrest. A short court time has been planned for July 12.

If convicted, Hoffman could face up to a yr in jail and a $2,500 fine.

Different Spark Tutorials



Write custom Scala code for GeoMesa to generate histograms and spatial densities of GDELT event data. While the Spark contains multiple closely integrated components, at its core, Spark is a computational engine that is responsible for scheduling, distributing, and monitoring applications consisting of many computational tasks on a computing cluster.

Apache Spark provides in-memory, distributed computing. Spark supports text files, SequenceFiles, and any other Hadoop InputFormat. Although a relatively newer entry to the realm, Apache Spark has earned immense popularity among enterprises and data Analysts within a short period.

I focus on Discrete Applied Mathematics, Machine Learning Theory and Applications, and Large-Scale Distributed Computing. Apache Spark, an open source cluster computing system, is growing fast. For an explanation on the MovieLens data and how to build the model using Spark, have a look at the tutorial about Building the Model.

The tutorial is also set up as a using the build tool SBT The popular IDEs, like IntelliJ with the Scala plugin (required) and Eclipse with Scala , can import an SBT project and automatically create an IDE project from it. It is must that Spark job is manually optimized and is adequate to specific datasets.

We demonstrated Apache Spark to provide an in-memory, distributed computing environment and just how easy it is to use and grasp. Distributed graph processing framework ‘GraphX' works on the top of Spark and it enabled the speed of data processing at a large scale.

Spark is 100 times faster than Bigdata Hadoop and 10 times faster than accessing data from disk. For doing this, find Apache Spark in the Data and Analytics section of the Bluemix catalog, open the service, and then click Create. RDDs are the building blocks of Spark.

You just created a program that gets and stores data with MongoDB, processes it in Spark and creates intelligent recommendations for users. After loading the collection in a DataFrame, we can now use the Spark API to query and transform the Apache Spark Tutorial data. First, let's create a Python project with the structure seen below and download and add the file into the static directory.

By using the PySpark kernel to create a notebook, the SQL contexts are automatically created for you when you run the first code cell. In this article, we'll show you how to use Apache Spark to analyze data in both Python and Spark SQL. Enroll for Big Data and Hadoop Spark Training with Acadgild and become a successful hadoop developer.

Just make sure that you can run pyspark or spark-shell from your Home directory, so that we could compile and run our code in this tutorial. In this example, we will merge the dataframe dfTags and the dataframe dfMoreTags which we created from the previous section.

Churn through lots of data with cluster computing on Apache's Spark platform. It contains different components: Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX. To show the dataframe schema which was inferred by Spark, you can call the method printSchema() on the dataframe dfTags.

By default, each transformed RDD may be recomputed each time you run an action on it. However, you may also persist an RDD in memory using the persist (or cache) method, in which case Spark will keep the elements around on the cluster for much faster access the next time you query it. There is also support for persisting RDDs on disk, or replicated across multiple nodes.

Spark 2.0.x Online Tutorials



This tutorial provides a quick introduction to using Spark. We're making the power and capabilities of Spark - and a new platform for creating big data analytics and application design - available to developers, data scientists, and business analysts, who previously had to deal with IT for support or simply do without.

A Dataset is a new experimental interface added in Spark 1.6. Datasets try to provide the benefits of RDDs with the benefits of Spark SQL's optimized execution engine. And exactly because you let Spark worry about the most efficient way to do things, DataFrames are optimized: more intelligent decisions will be made when you're transforming data and that also explains why they are faster than RDDs.

After Spark 2.0, RDDs are replaced by Dataset, which is strongly-typed like an RDD, but with richer optimizations under the hood. We can re-write the dataframe tags distinct example using Spark SQL as shown below. Data is managed through partitioning with the help of which parallel distributed processing can be performed even in minimal traffic.

Because of the disadvantages that you can experience while working with RDDs, the DataFrame API was conceived: it provides you with a higher level abstraction that allows you to use a query language to manipulate the data. When the data grows beyond what can fit into the memory on your cluster, the Hadoop Map-Reduce paradigm is still very relevant.

Consider the section above to see whether you should use RDDs or DataFrames. However, Spark Streaming use Spark Core's fast scheduling capability to complete these mini batches in a way that the application acts like a pure streaming application. RDDs are automatically processed on workers co-located with the associated MongoDB shard to minimize data movement across the cluster.

Note also that we will only take a subset of the questions dataset using the filter method and join method so that it is easier to work with the examples in this section. There are Spark APIs written in Scala, Java, R, and Python. Basically, across live streaming, Spark Streaming enables a powerful interactive and data analytics application.

In addition, an extension of the core Spark API Streaming was added to Apache Spark in 2013. Spark Streaming is a near real time processing framework that allows the user to take in data in mini batches and perform operations on it. Because Spark Streaming uses mini batches, it's not like a pure streaming framework such as Flink.

Learn Apache Spark from the best online Spark tutorials & courses recommended by the programming community. Hence, if we want efficiency in our processing, the RDDs should be repartitioned into some manageable format. Jupyter Notebook is a Apache Spark Tutorial popular application that enables you to edit, run and share Python code into a web view.

The tutorial is also set up as a using the build tool SBT The popular IDEs, like IntelliJ with the Scala plugin (required) and Eclipse with Scala , can import an SBT project and automatically create an IDE project from it. It is must that Spark job is manually optimized and is adequate to specific datasets.

Knowing the extensively excellent future growth and rapid adoption of Apache Spark in today's business world, we have designed this Spark tutorial to educate the mass programmers on interactive and expeditious framework. Spark presents an abstraction called a Resilient Distributed Dataset (RDD) that facilitates expressing transformations, filters, and aggregations, and efficiently executes the computation across a distributed set of resources.

Random Forests - Apache Spark Tutorial to understand the usage of Random Forest algorithm in Spark MLlib. You might already know Apache Spark as a fast and general engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

How To Hire The Best In The Carpet Cleaning Business



Avoid hiring a cleaning company that you've only seen in an ad on television. Many times, these companies are very inexperienced, but they are trying to attract people using flashy advertisements. You need to meet with all prospective cleaning companies in person and you should "interview" several before hiring one.

After completing your steam cleaning session, turn on the humidifier in the room. This will help to suck out the excess moisture from your carpet, allowing it to dry faster. Also, you can turn on the air conditioning unit if it is a hot summer day to have the same effect.

If there is a spill on your carpet, make sure to blot the area immediately. Utilizing dry towels, soak up as much liquid as you can. Once the stain is set in, your only option is to hire a professional carpet cleaning company to come in and thoroughly remove it. If the stain is deeply embedded in the carpet, you may have to resort to using a steam cleaner.

Spend time learning about the company's history. You do not want to have a company come into your home that has a bad reputation for bad service, untrustworthy employees or for overcharging. You can use the Internet to find reviews from former customers to find the one with a solid history.

If you are thinking about having your carpets professionally cleaned, call around to a few different companies. Ask about any specials they are currently running such as multiple room discounts, or your first carpeted room free. Some companies will do one free room, in hopes that you will hire them for additional rooms.

Vacuum your carpeting before you have it cleaned. Before using cleaning products or water, use a good vacuum to remove any dirt. Always blot wet stains because rubbing stains will cause them to spread. After treating a stain, do not vacuum the area until it is fully dry.

Check the validity and security of any carpet cleaner you will use. Research the company and any Better Business Bureau claims that may be available. Verify that all employees receive background checks and drug screenings. The safety of your family and belongings should come first as you make your decisions about service.

When looking for a professional carpet cleaning company, always consider the cleaning process. There are different ways professionals use to clean carpets. Dry treatments, wet treatments, steam cleaning and a variety of others are available. Some require significant drying time or could require that you leave the home. Choose the one that works best for you.

Even if you are good at keeping your carpet clean yourself, a regular steam-cleaning has its benefits. Steam cleaning your carpet cleans it more thoroughly than many other methods, like cleaning by hand. It also kills bacteria that are residing in the carpet fibers. This will eliminate carpet odors.

Ask the cleaners what you must do after they are done. Some products will require you to avoid walking or placing furniture back on the carpet before it is dry. grout and tile cleaning services Knowing what is expected of you after they are done will help ensure you are happy with the results.

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