text:
I Come Off A Beautiful Creature, Which Soars In The Sky. I Come Off A Peckish Creature, Which Has A Tail As Mighty As The Sun! I Am Sometimes Dirty, And Parents Beg You Not To Pick Me Up. What Am I?
I come off a beautiful creature, which soars in the sky. I come off a peckish creature, which has a tail as mighty as the sun! I am sometimes dirty, and parents beg you not to pick me up. What am I? – Riddle Answer
I come off a beautiful creature, which soars in the sky. I come off a peckish creature, which has a tail as mighty as the sun! I am sometimes dirty, and parents beg you not to pick me up. What am I? riddle
I come off a beautiful creature, which soars in the sky. I come off a peckish creature, which has a tail as mighty as the sun! I am sometimes dirty, and parents beg you not to pick me up. What am I? riddle answer
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(Don't worry, "I come off a beautiful creature, which soars in the sky. I come off a peckish creature, which has a tail as mighty as the sun! I am sometimes dirty, and parents beg you not to pick me up. What am I? riddle" answer is included.)
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"I come off a beautiful creature, which soars in the sky. I come off a peckish creature, which has a tail as mighty as the sun! I am sometimes dirty, and parents beg you not to pick me up. What am I?."
The correct answer to "I come off a beautiful creature, which soars in the sky. I come off a peckish creature, which has a tail as mighty as the sun! I am sometimes dirty, and parents beg you not to pick me up. What am I? riddle" is: Feather.

redpajama_set_name: RedPajamaCommonCrawl


text:
Q: Passwords, Salts, And Security Concepts Introduction
I have done a lot of research, today, and have learned a lot about hashes and encryption (and the important difference between the two). One thing I have learned is this: people disagree on the efficacy of salting.
In the responses to this question (and particularly in the comments to the accepted answer), people conclude - it seems - that storing a randomly generated salt next to the hashed password in a database is the best way to secure passwords. There are several resources that state this and this will be the basis for my question.
In this question, the accepted answer states that with access to the all the possible hashed data values, the salt doesn't do much - conecptually - to make things anymore secure (though, that would be an unfeasibly large amount of stored data). Salts and hashing algorithms serve the purpose of increasing the number of possibilities for a single password entry, making the use of a dictionary-based attack against a database exponentially less efficient (here, I use the term "dictionary-based" more liberally, refering - really - to a table, whether that be a rainbow table, a table utilized for brute-force attacks (re-computing each time), or a simple lookup table).
 The Bits and Pieces
From my understanding, a well encrypted password needs three (3) things:

*

*To be hashed.

*To be hashed in conjunction with a salt.

*To be hashed in conjunction with a random salt (one salt for each password entry)

In order for  a cracker to understand the resulting stored hash, he or she needs four (4) things:

*

*Knowledge of the hashing algorithm

*Knowledge of the salt

*The correct plaintext password value (perhaps supplied as input from a dictionary-based attack (running a dictionary through the algorithm in conjunction with the salt)).

The Security Bit
The disagreement seems to surround what to do with the salt, i.e. where to store the salt. The phrase I keep seeing passes around Stack Overflow is "security by obscurity" - which appears to be the premise of a salt ("let's make this bit of information less 'seeable'"); however, from my reading, I have come to understand that security by obscurity doesn't really work. The premise of which seems to be: if the attacker has access to the algorithm and - if provided - the salt, he or she can figure it out.
The premise, then, of security is not solely the mixing around and changing of the values, but the means the database, transactions, or server use of stopping the types of attacks that would:

*

*Yield the salt to the attacker

*Allow the attacker to brute-force the database

Another user commented that it shouldn't matter if the code is exposed to the attacker as good code - or a good security algorithm - would prevent the attack from succeeding.
So, security then is a combination of three (3) things:

*

*Preventing access to the server where everything is stored

*Creating an algorithm that prevents brute-force entry to the database

*Encrypting transactional information

*Hashing (obscuring) sensitive data

The concern over the efficacy salts seems to stem from the assumption that the attacker has access to the database, itself.
Scenario: I've got a dictionary, your salt, and your hashing algorithm. Grabbing your password should be of no real trouble (this is why we work to stop brute-force attacks).
So, my question as a result of these conclusions (which are now on the Stack Overflow chopping block) are:
 Questions

*

*Does security also involve the protection of the location of the code, e.g. access to the hashing algorithm?

*Why does generating a random salt for each password matter, particularly if the database has been exposed, i.e. does salt randomness really add anything to the security of information? Is this simply a matter of the exponential increase in time for an attack as a result of the random salt (e.g. making an attack less appealing)?

The security of the salt seems to lie in the attacker not having it, not strictly its randomness

*Why store the salt in a database, at all?

Essentially, is all of this security 'stuff' (about the efficacy of hashes, etc.) just myth? Maybe I am just responding to the idea that nothing really will ever be entirely hacker proof (we just do everything we can)?
 Why I Am Motivated To Ask
It seems to me that if your database is exposed, the salt - random or not - doesn't matter, especially if the database stores the salt.
Best practice, then, would be twofold (salts only adding a bit more security): (1) the hashing of sensitive information; (2) the protection - in the context of this question - of the database from brute-force attacks. There seems to be a lot of misinformation floating around SO (some of it probably resides in my derived understandings, above).
Here, I am assuming guards against Cross-site Scripting, etc. are already in place.

A:
Is security more about the protection of the location of the code than it is hashing the stored information?

Security is about building mitigations for attack vectors.  There are many types of attacks and many types of mitigations.  You've stumbled across a few of them.
Salt (a random string stored along with the hash) protects against a specific attack vector-- a rainbow attack  launched by a malicious user with access to the entire table.
Pepper (a cryptographically random, secret salt value stored in a different location) protects against something else-- a dictionary or brute force attack launched by a malicious user with access to the hashed value and salt for a particular user, but without access to other systems (especially the system that stores the pepper).
If you are reading up on this you will find that a lot of experts think that pepper is more or less useless and amounts to "security by obscurity."  The reason they feel this way is they believe, at least in principle, that if a cracker has access to your DB then he almost certainly has access to the storage location holding the pepper.

Why does generating a random salt for each (in this case) password matter, particularly if the database has been exposed, i.e. does salt randomness really add anything to the security of information?

In order to understand why this is important, you must understand how a rainbow table can be used to speed up an attack.  With a rainbow table, a cracker can compute all the known hash values for common passwords and scan your entire database table to find them.  This is much faster than a brute force attack on each individual entry.  If a salt is combined with the passwords, it renders the rainbow table useless.   In the end it is all about slowing the cracker down by making the problem computationally infeasible.

The security of the salt seems to lie in the attacker not having it, not its randomness

This is absolutely incorrect.  It is all about changing the input of the hash from something predictable (e.g. a word from a dictionary) to something unpredictable (a word combined with a random string), which again is to thwart a rainbow table.

Why store the salt in a database, at all?

When the user signs on, he provides his password and not the salt (he doesn't even know the salt).  The entered value must then be combined with the salt and then hashed.  The system compares this hash to the hash stored in the database.  If there is an exact match, the system can infer that the hashed value was created with the same password entered by the user, and therefore validate the authentication attempt.
Since the user doesn't know the salt, the database has to store it.

A: Salting a password is a counter measure against rainbow table attacks.
Consider a database with the following entries
User   |  Password
Jim    |  x7291s
Jane   |  m09var
Jill   |  x7291s
Jack   |  983d2w

and consider the following rainbow table that stores common passwords which a hacker may use to try and find password hashes in a db:
Hash    | Password
x7291s  | password1
983d2w  | puppies
34980f  | 12345
302jf0  | opensesame

A hacker can easily find commonly used passwords without having to compute or crack any hashes themselves. Jim Jack and Jill have been compromised while jane who uses a more obscure password has been saved from compromise.
without a salt, the hashing function always looks like:
hash_me("password1") -> x7291s

however with a salt:
hash_me("password1 208ejd209kj4ed02" ) -> mt2d89 // using Jack's salt
hash_me("password1 3094kf04390f0s9k" ) -> 3409fk // using Jill's salt
hash_me("password1 saf890af9k3049kf" ) -> f7g6s7 // using Jim's salt

you can see that the rainbow table looses its efficacy and is no longer usable. none of mt2d89 3409fk or f7g6s7 will match x7291s of password1

A: The purpose of the salt is to provide additional protection if the database is compromised. If you assume the database cannot be compromised, you can just store everything in plaintext and a password-based authentication system will work fine. The problem is that password databases are compromised all the time.
John Wu and Michael Burr have already covered why you want a salt to prevent passwords that are the same from appearing as the same hash in the database.
If you use a salt, it must be stored in the database. Otherwise a legitimate user cannot be authenticated without hashing the given password with all possible salts. So if the attacker gets access to a database entry, the attacker gets access to the salt too.
If an attacker gets access to database entries, we want to maximize the amount of work and time it takes for the attacker to discover the password by brute force. If there is no salt, the attacker can precompute (before getting access to the database) and store a rainbow table, which is basically a list of potential passwords that are run through the hash function. Looking up a database entry in the rainbow table is very fast, so if the attacker can store one and has access to the database, passwords are discovered immediately. When using a salt, the size of the required rainbow table increases exponentially with the salt length, so using a sufficiently large salt will effectively preclude the use of the rainbow table.
The attacker can still brute force the database entry. With the known salt and hash algorithm the attacker will check a dictionary. This is slow because the attacker cannot precompute anything; the attacker must use the salt discovered in the database. If the password is not in the dictionary, the attacker must resort to guessing passwords. Eventually, they will discover the password. This is also why password expiration is useful. If the expected time to brute force the hash is greater than the password expiration period, you will have changed the password before the attacker brute forces it.

redpajama_set_name: RedPajamaStackExchange


The System.Reflection.Emit namespace contains classes that allow a compiler or tool to emit metadata and Microsoft intermediate language (MSIL) and optionally generate a PE file on disk. The primary clients of these classes are script engines and compilers.
Defines and represents a dynamic assembly.
Defines and represents a constructor of a dynamic class.
Provides support for alternative ways to generate the Microsoft intermediate language (MSIL) and metadata for a dynamic method, including methods for creating tokens and for inserting the code, exception handling, and local variable signature blobs.
Defines and represents a dynamic method that can be compiled, executed, and discarded. Discarded methods are available for garbage collection.
Describes and represents an enumeration type.
Defines events for a class.
Defines and represents a field. This class cannot be inherited.
Defines and creates generic type parameters for dynamically defined generic types and methods. This class cannot be inherited.
Generates Microsoft intermediate language (MSIL) instructions.
Represents a local variable within a method or constructor.
Defines and represents a method (or constructor) on a dynamic class.
Provides a fast way to swap method body implementation given a method of a class.
Defines and represents a module in a dynamic assembly.
Provides field representations of the Microsoft Intermediate Language (MSIL) instructions for emission by the ILGenerator class members (such as Emit(OpCode)).
Creates or associates parameter information.
Defines the properties for a type.
Provides methods for building signatures.
Defines and creates new instances of classes during run time.
Represents the class that describes how to marshal a field from managed to unmanaged code. This class cannot be inherited.
Represents the Token returned by the metadata to represent an event.
Represents an exception handler in a byte array of IL to be passed to a method such as SetMethodBody(Byte, Int32, Byte, IEnumerable<ExceptionHandler>, IEnumerable<Int32>).
The FieldToken struct is an object representation of a token that represents a field.
Represents a label in the instruction stream. Label is used in conjunction with the ILGenerator class.
The MethodToken struct is an object representation of a token that represents a method.
Describes an intermediate language (IL) instruction.
The ParameterToken struct is an opaque representation of the token returned by the metadata to represent a parameter.
The PropertyToken struct is an opaque representation of the Token returned by the metadata to represent a property.
Represents the Token returned by the metadata to represent a signature.
Represents a token that represents a string.
Represents the Token returned by the metadata to represent a type.
Defines the access modes for a dynamic assembly.
Describes how an instruction alters the flow of control.
Describes the types of the Microsoft intermediate language (MSIL) instructions.
Describes the operand type of Microsoft intermediate language (MSIL) instruction.
Specifies one of two factors that determine the memory alignment of fields when a type is marshaled.
Specifies the type of the portable executable (PE) file.
Describes how values are pushed onto a stack or popped off a stack.


Did you know that as a Believer in Jesus, you are not "trying" to get the victory? You actually already have it. It's yours because Jesus finished the work and stripped the devil of his authority over you!
Now you get to fight from a place of victory, not for the victory because the victory has already been won! Fighting from victory looks a whole lot different than fighting for victory!
31 So, what does all this mean? If God has determined to stand with us, tell me, who then could ever stand against us? 32 For God has proved his love by giving us His greatest treasure, the gift of His Son. And since God freely offered Him up as the sacrifice for us all, He certainly won't withhold from us anything else He has to give.
34 Who then is left to condemn us? Certainly not Jesus, the Anointed One! For he gave His life for us, and even more than that, he has conquered death and is now risen, exalted, and enthroned by God at his right hand. So how could he possibly condemn us since he is continually praying for our triumph?
38 So now I live with the confidence that there is nothing in the universe with the power to separate us from God's love. I'm convinced that his love will triumph over death, life's troubles, fallen angels, or dark rulers in the heavens. There is nothing in our present or future circumstances that can weaken his love. 39 There is no power above us or beneath us—no power that could ever be found in the universe that can distance us from God's passionate love, which is lavished upon us through our Lord Jesus, the Anointed One!
10 Now my beloved ones, I have saved these most important truths for last: Be supernaturally infused with strength through your life-union with the Lord Jesus. Stand victorious with the force of his explosive power flowing in and through you.
14 Put on truth as a belt to strengthen you to stand in triumph. Put on holiness as the protective armor that covers your heart. 15 Stand on your feet alert, then you'll always be ready to share the blessings of peace.
16 In every battle, take faith as your wrap-around shield, for it is able to extinguish the blazing arrows coming at you from the Evil One! 17–18 Embrace the power of salvation's full deliverance, like a helmet to protect your thoughts from lies. And take the mighty razor-sharp Spirit-sword of the spoken Word of God.
Pray passionately in the Spirit, as you constantly intercede with every form of prayer at all times. Pray the blessings of God upon all his believers.
I hope you enjoy week 5 of this video series!
Janet, what a great testimony about how you received the healing provided for you through Jesus' finished work! You followed the leading of the Spirit in this instance and went with peace, rested in God's grace and received what He had already provided for you 2000 years ago through His death and resurrection!
And yes, when I say "trust Jesus" it does mean trust God – Father, Son & Holy Spirit! Our triune God. Simple amazing!


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How to get to Rancha Oland?
From the south of Poland, we take the route to Gdynia. Coming from Gdynia, we head towards Rumia and Reda. In Redza we turn right onto Władysławowo.
We are going straight ahead all the time, up to the roundabout in Władysławowo, where we turn left towards Jastrzębia Góra.
We have Chlapowo just behind Władysławów. We pass the entire town and when we reach the border of Chlapowo with Rozew on the left we see the Rancha Oland area, it is at the height of the "Rozewie" sign.
1. By train, we reach the Gdynia Główna station.


text:
Eddie Cooper may refer to:

 Eddie Cooper (actor) (born 1987), British actor
 Eddie Cooper (cricketer) (1915–1968), English cricketer
 Eddie Cooper (footballer), English footballer

See also
 Edward Cooper (disambiguation)

redpajama_set_name: RedPajamaWikipedia


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Group: 1 paddle boat, 1 cat boat, 1 kayak and three IK's.
Summary: Great day overall, no portages, one scary surf at the dam, lots of tree hazards to avoid, but clean routes if you take the right lines.
Details: There are two completely blocked channels that are not obvious and not easily seen: Jeff's Island (right side blocked, run left the same as last year) and Russian Island (very long island, downstream of Jeff's 1/2 mile or maybe a little more, left side blocked run right). It's important to know where those are. Jeff's Island is the least visible and was well documented last year.
The other routes were visible, but as always on this river you have to be very, very diligent and look very far ahead. As others have reported, there is more wood than in past years and lots of hazards to avoid. Some of it looks to have been cleaned up some from what has been reported earlier. But openings were narrow and a few could get more restricted as flows drop.
The dam is a serious hazard and should be scouted. The hydraulic extends further left than I recall, there is a log below the right side of the hydraulic and the recirc. in the middle was huge. The left channel sneak route is still blocked by a log and not availabe. There is a very safe option (in my opinion) by running left of the hydraulic, beaching the boat temporarily on the shallow rocks at the head and to the right of the island and then pushing off well clear of the hydraulic. Most of us did that with no problems and very minimal risk. The commercial trips were punching the far left side of the hydraulic and skirting the island. That line is fine, but it is hard to see as you approach the horizon, there is rebar that can tempt you to make last minute corrections that kill your momentum, the line is easily missed and if you don't have enough momentum you will get pulled back in. The recirc. is very decieving and very strong. Our cat boater missed the line entirely, tried to maneuver around the rebar instead of gaining momentum, got surfed sideways to the right and was there for a very long time until we could get a rope out to him. After several unsuccessful attempts from the right bank immediately below the dam, we were able to get a good long toss from the upstream side of the dam from the shallow rocky water out from the right bank. At this flow the hydraulic would not flush him out to the right, even though he was very, very close to where it looked like it should flush. I know that many boaters can easily hit the line and run the left side route, but I have also seen several people underestimate the strength of that hydraulic and the recirculation and end up getting sucked into the hydraulic. It has always ended ok, but it can be a very dangerous situation.
All in all, in spite of the incident at the dam, it was a great day.


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Ahhhhh these past five days have been AWESOME.
If you don't typically go to the NAEA conventions.. you NEED to! There is no better place to learn, get ideas, collaborate, and celebrate being an art teacher (with people that absolutely appreciate and understand what you do everyday)!
Special thanks to those of you that stopped by the session that Mollie and I presented!
Some pretty cool outdoor art!
New Orleans had a great artist market as well!!
Mollie from Art with Ms. K and myself!
And I will most definitely be there! Can't wait for Chicago - I've never been there before!
Your friend Mollie looks like Renee Zellweger!


The New Wave Design and Verification (New Wave DV) 1394b PHY core includes all functionality needed to meet the AS5643 protocol, and provides a complete IP solution for the PHY layer of the 1394b. The 1394b core includes all functionality needed to meet the 1394b and AS5643 support specification, including: comma alignment, 8b/10b encode/decode, primitive decode, scrambling, port state machine, connection manager, arbitration controller, elastic FIFO, and phase FIFO.
At the physical layer, the core of 1394b is built for connecting to FPGA/ASIC embedded SERDES, discrete SERDES parts, or general-purpose IO with AS5643 performance protocol. The Link Layer interface of 1394b PHY IP's core provides the industry standard PHY-Link interface. This PHY-Link interface connects directly to New Wave DV's Link Layer IP cores, discrete Link Layer integrated circuits, or to custom logic developed by the end user.
Our 1394b core includes AS5643 performance protocol functionality, and is targeted towards applications in aerospace and industrial vision. The 1394 b core has also been used on a wide range of parts at varying operating rates. Additionally, our 1394b core includes AS5643 support protocol, and includes test-benches, and example code, which helps to make design integration as straightforward as possible.


The practice of meditation has been around for centuries. In simple terms, meditation uses the practice of mindful breathing and guided imagery to help clear your mind of clutter. Studies have shown that meditation is beneficial to your mental health as well as your physical health. Nowadays you can practice it with simply using the right app on your phone. So, we looked and we have for you one amazing meditation app. Let's discuss about the app.
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With the app's visualization the users can go easily into a state of deep relaxation and feel the happiness within. All users need to do is to listen to this meditation every day for at least for 6 weeks and it will result in feeling real happiness. The app is quite easy to use, offering its users to learn how to appreciate the things in their lives with the three elements of the app for gratefulness, aromatherapy and crystals.
On the app users are getting info how to fight the stress and depression with the aromatherapy, learning about the sunstone that help them to calm and feel confident. The meditation is quite efficient, offering users to follow 5 simple steps to complete peace, as introduction, start, body relaxation, awareness, and returning happy. All of this is beautifully read by the creator of the app. Download the app now from the App Store.


text:
KM Birla Says, Vodafone Idea Will Shut Down In Absence Of Govt. Relief
by Pritish raj
in News, Tech
Two Telecom Giants were merged last year. Source- Business Standard
Vodafone Idea Limited (VIL) will have to be shut down if the government does not provide the company's sought relief, its chairman, Kumar Mangalam Birla, said at an event in Delhi on Friday.
. His comments follow the decision of the Supreme Court on the Adjusted Gross Revenue (AGR) of 24 October, after which the company reported a mammoth loss of Rs 50,921.9 crore in the second quarter, pulled down by provisions on AGR dues.
Vodafone Idea Limited (VIL) will have to be shut down if the government does not provide the company's sought relief, its chairman, Kumar Mangalam Birla, said at an event in Delhi on Friday. His comments follow the decision of the Supreme Court on the Adjusted Gross Revenue (AGR) of 24 October, after which the company reported a mammoth loss of Rs 50,921.9 crore in the second quarter, pulled down by provisions on AGR dues.
"If we don't get help, we're going to shut down shop, it could be the end of the story for us. There's no business in the world that could get that kind of money in three months," Birla said.
"The room's big elephant is AGR. What, in truth, I think is something that lies in the judiciary trial. I assume a conversation should take place between the government.
This was a lawsuit filed by the government against telecommunications service providers, "he said. AGR (adjusted gross revenue) is an amount of which telecommunications companies pay as legal duties.
The Supreme Court upheld the government's position that non-telecom income should be included in the AGR to measure duties.
Recently, Airtel reported its highest loss of approximately 23,045 crores compared to a net profit of approximately 119 crores in the corresponding period last year, Vodafone Idea recorded a loss of approximately 50,921 crores, the highest ever loss for a company in India.
Both operators said they hoped to receive government relief on AGR payments. "After the recent Supreme Court ruling, we are in active discussions with the government seeking financial assistance," said Ravinder Takkar, Vodafone Idea, Managing Director and Chief Executive Officer. This even happens as the Telecom Department issued notices to all operators to deposit the license fee duties in accordance with the SC decision. Total duties are estimated to exceed ~2 lakh crore for the entire industry.
Analysts monitoring the telecom sector said that if the government insists on raising duties without providing any relief, then there will be no choice but to shut down their operations. "Apart from Reliance Jio, it will be difficult for all other operators to continue operations with this form of a payout. Telecom, once the reforms poster boy, is set for a huge crash unless the government steps in, "an analyst said.
These are the most viewed Indian ads according to Youtube Ad Leaderboard 2019
The most-viewed creators on YouTube in 2019 include PewDiePie, Dude Perfect, Azzyland and others
Pritish raj
Pritish Raj is a content writer at Next Big Brand. Hailing from the diversified state of Bihar, he is an engineer by education who chooses the way of poetry, photography, and writing to kick off his career. Highly enthusiastic about brands and startups, he aims to be a travel content creator.
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text:
CS Video: SPECTRE's Monica Bellucci and Léa Seydoux
By Silas Lesnick
Monica Bellucci and Léa Seydoux discuss SPECTRE and its apparent Inglourious Basterds Easter Egg
North America is just two days away from the big screen release of the latest James Bond adventure, SPECTRE. All this week, ComingSoon.net is bringing you exclusive interviews with the film's cast, conducted on location in Mexico City (where SPECTRE's elaborate opening sequence takes place). Following our Dave Bautista SPECTRE interview earlier this week, we've got a conversation with two of SPECTRE's lovely ladies. In the player below, you can hear about what production was like from stars Monica Bellucci and Léa Seydoux.
Earlier this year, ComingSoon.net had the opportunity to visit the SPECTRE and learned that an Easter Egg had been filmed that made a slight reference to Léa Seydoux's first performance opposite SPECTRE co-star Christoph Waltz in Quentin Tarantino's Inglourious Basterds. Although Seydoux was delighted to discuss it, Waltz had a very, very different opinion about the meaning of the line in question. Check out his interview cameo in the below video and come back tomorrow for the full Christoph Waltz interview. We'll then wrap the week up with Bond himself, Daniel Craig!
In SPECTRE, a cryptic message from the past sends James Bond (Daniel Craig) on a rogue mission to Mexico City and eventually Rome, where he meets Lucia Sciarra (Monica Bellucci), the beautiful and forbidden widow of an infamous criminal. Bond infiltrates a secret meeting and uncovers the existence of the sinister organisation known as SPECTRE.
Meanwhile back in London, Max Denbigh (Andrew Scott), the new head of the Centre for National Security, questions Bond's actions and challenges the relevance of MI6, led by M (Ralph Fiennes). Bond covertly enlists Moneypenny (Naomie Harris) and Q (Ben Whishaw) to help him seek out Madeleine Swann (Léa Seydoux), the daughter of his old nemesis Mr White (Jesper Christensen), who may hold the clue to untangling the web of SPECTRE. As the daughter of an assassin, she understands Bond in a way most others cannot.
As Bond ventures towards the heart of SPECTRE, he learns of a chilling connection between himself and the enemy he seeks.
Directed once again by Sam Mendes, SPECTRE is written by John Logan and Neal Purvis & Robert Wade.
Are you excited to see Monica Bellucci and Léa Seydoux in SPECTRE? What do you make of the Easter Egg? Let us know in the comments below!
Naomie Harris in Metro-Goldwyn-Mayer Pictures/Columbia Pictures/EON Productions' action adventure SPECTRE.
Léa Seydoux in Metro-Goldwyn-Mayer Pictures/Columbia Pictures/EON Productions' action adventure SPECTRE.
Monica Bellucci and Daniel Craig in Metro-Goldwyn-Mayer Pictures/Columbia Pictures/EON Productions' action adventure SPECTRE.
Stephanie Sigman in Metro-Goldwyn-Mayer Pictures/Columbia Pictures/EON Productions' action adventure SPECTRE.
Stephanie Sigman plays Estrella in the opening sequence of Metro-Goldwyn-Mayer Pictures/Columbia Pictures/EON Productions' action adventure SPECTRE, on location in Mexico City.
Bond (Daniel Craig) runs along the rooftops in pursuit of Sciarra in Mexico City in Metro-Goldwyn-Mayer Pictures/Columbia Pictures/EON Productions' action adventure SPECTRE.
Director Sam Mendes on location in Mexico City shooting the opening sequence of Metro-Goldwyn-Mayer Pictures/Columbia Pictures/EON Productions' action adventure SPECTRE.
The Day Of The Dead parade is recreated in Mexico City for Metro-Goldwyn-Mayer Pictures/Columbia Pictures/EON Productions' action adventure SPECTRE.
Oberhauser played by Christoph Waltz (centet) in Metro-Goldwyn-Mayer Pictures/Columbia Pictures/EON Productions' action adventure SPECTRE.
Daniel Craig stars as James Bond in Metro-Goldwyn-Mayer Pictures/Columbia Pictures/EON Productions' action adventure SPECTRE.
Spectre Teaser Poster
Spectre behind-the-scenes
Empire Spectre cover
Silas Lesnick
Christoph Waltz James Bond Lea Seydoux Monica Bellucci Movie News SPECTRE
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Various embodiments dynamically generate relevant items for a user based on a user's location and an item's popularity. In at least some embodiments, a probability component generates a ranked list of items that are relevant to users at a particular location using probability data associated with the list of items and the particular location. The probability data is based on user selections of items in the list of items.
Some websites include user interfaces that are configured to display lists or groups of items that can be selected or interacted with by users. Oftentimes these lists can include hundreds or even thousands of different items. With limited screen space available on computing devices to display items, web site editors would like to provide different users with relevant items as opposed to items that are less relevant. Similarly, users would like to be presented with a relevant list of items, rather than items that are less relevant.
In at least some embodiments, the probability component receives a request for a list of items from a client device and determines a location associated with the client device. The probability component then determines whether probability data for the list of items is available for the location associated with the client device. The probability data is based on selections of items in the list of items from sources other than the client device. Responsive to determining that probability data is available, the probability component generates a ranked list of items using the probability data associated with the location of the client device. The probability component then transmits the list of items to the client device for display.
In at least some embodiments, the probability component is configured to update probability data for items in a list of items based on user selections of items in the list. Responsive to receiving a user selection of an item in the list of items, the probability component increases a probability associated with the selected item and decreases probabilities associated with other items in the list of items.
FIG. 2 illustrates an example graph of initial item probabilities in accordance with one or more embodiments.
FIG. 3 illustrates an example graph of item probabilities after user selections are received in accordance with one or more embodiments.
FIG. 4 illustrates an example web browser displaying a list of items in an item display area in accordance one or more embodiments.
FIG. 6 is a block diagram of an example system that can be utilized to implement one or more embodiments.
Some websites include user interfaces that are configured to display items that can be selected or interacted with by users. A social media user interface, for example, can be configured to display items associated with social media web sites (e.g., Facebook, Twitter, MySpace, and LinkedIn) that can be selected to navigate to a respective social media web site. Today, there are literally hundreds of social media web sites, with more being created all the time. With limited available screen space on computing devices to display items, web site editors would like to configure websites to dynamically select and provide items in a list or grouping of items that are most relevant to users. However, the relevancy of items can vary at different geographic locations. Social media web sites, for instance, can fluctuate in popularity for users at different geographic locations. For example, users in Seattle may use Facebook more frequently than users in Wyoming who might prefer MySpace. It can be difficult, therefore, for web site editors to automatically provide and display a relevant list of items that match usage patterns for users at varying locations. It is to be appreciated and understood that while social media websites are used as examples throughout this document, the inventive techniques can be applied to items associated with other websites without departing from the spirit and scope of the claimed subject matter.
In the discussion that follows, a section entitled "Operating Environment" describes but one operating environment that can be utilized to practice the inventive principles described herein, in accordance with one or more embodiments. Following this, a section entitled "Probability Component" is provided and describes an example probability component in accordance with one or more embodiments. Next, a section entitled "Example Method" describes an example method in accordance with one or more embodiments. Last, a section entitled "Example System" describes an example system that can be utilized to implement the described embodiments.
FIG. 1 illustrates an operating environment in accordance with one or more embodiments, generally at 100. Operating environment 100 includes a computing device 102 having one or more processors 104, one or more computer-readable storage media 106 and one or more applications 108 that reside on the computer-readable storage media and which are executable by the processor(s). The computer-readable storage media can include, by way of example and not limitation, all forms of volatile and non-volatile memory and/or storage media that are typically associated with a computing device. Such media can include ROM, RAM, flash memory, hard disk, removable media and the like. One specific example of a computing device is shown and described below in FIG. 6.
In addition, computing device 102 includes a software application in the form of a web browser 110. Any suitable web browser can be used examples of which are available from the assignee of this document and others.
In addition, environment 100 includes a network 112, such as a local network or the Internet, and one or more servers 114 via which information can be requested and sent. Server 114 includes one or more processors 116, one or more computer-readable storage media 118 and one or more applications 120 that reside on the computer-readable storage media and which are executable by the processor(s). The computer-readable storage media can include, by way of example and not limitation, all forms of volatile and non-volatile memory and/or storage media that are typically associated with a computing device. Such media can include ROM, RAM, flash memory, hard disk, removable media and the like. One specific example of a computing device that can implement a server is shown and described below in FIG. 6.
In addition, server 114 also includes a probability component 122 that operates as described above and below. Probability component 122 can be implemented as a standalone component or one that is integrated with other applications. In operation, the probability component can be used to dynamically generate relevant items for a user based on a user's location and an item's popularity, as will become apparent below.
Computing device 102 can be embodied as any suitable computing device such as, by way of example and not limitation, a desktop computer, a portable computer, a handheld computer such as a personal digital assistant (PDA), cell phone, and the like.
Having discussed the general notion of an example operating environment in which various embodiments can operate, consider now a more detailed discussion of a probability component in accordance with one or more embodiments.
A probability component, such as probability component 122 illustrated in FIG. 1, can generate a ranked list of items that are relevant to users at a particular location. It can do so using probability data associated with the list of items and the particular location. The probability data is based on previous user selections of items that can appear in the list of items. As described throughout, an item "selection" can include any selection, action, or interaction with an item by a user. An "item" can refer to any selectable item, button, link, or control that can be selected by a user on a computing device display. Items of the same type, or that share one or more similar characteristics, can be grouped into lists. For example, a list of items based on a type of item can include, by way of example and not limitation, a list of restaurants, a list of sports web sites (e.g., www.espn.com, www.cnnsi.com, and www.cbssports.com), a list of movie theatres, a list of shopping web sites, or a list of products (e.g., shoes, books, and cars). A list of items based on a shared characteristic could include, by way of example and not limitation, a list of movie theatres, restaurants, bars, and cafes located in Seattle. In at least some embodiments, a list of items can include a list of social media web sites, such as Facebook, Twitter, or LinkedIn, and the like.
In accordance with various embodiments, the probability component can create and update probability data for items that appear in the list of items. In the illustrated and described embodiments, probability data can be created and updated based on user selections of items that appear in the list. The probability component can increase a probability associated with an item when the item is selected and decrease the item's probability when the item is not selected. As described throughout, the probability associated with an item is a measure of the likelihood that an item will be selected by the probability component when generating a ranked list of items. Probabilities can be represented in decimal form (e.g., 0.5) or in percentage form (e.g., 50%), but will be discussed as percentages herein. The total probability for items in a list typically adds up to 100%. Therefore, it is to be appreciated that when the probability of one item in a list of items increases, the probability or probabilities of other item(s) in the list decreases so that the total probability remains at 100%. For example, if a first item and a second item both have probabilities of 50%, and the probability of the first item increases to 75%, the probability of the second item decreases to 25%.
Prior to receiving a user's item selection, the probability component assigns an equal probability to each item in a particular list. This ensures that when the probability component generates a ranked list, each item in the list will have an equal chance of being selected at the top of the list. As an example, consider FIG. 2. There, a graph is shown generally at 200 and includes initial item probabilities before any user selections are received. Graph 200 includes a horizontal line 202 indicating that Item1 through Itemn have the same probability of being selected by the probability component. Consider for example, that if there are 100 items in an associated list, each item will have a 1% chance of being selected by the probability component because the total probability adds up to 100%.
In accordance with various embodiments, responsive to receiving a user's item selection, the probability component increases the probability of the selected item and decreases the probabilities of other items in the list. As an example, consider FIG. 3. There, a graph is illustrated generally at 300 and includes item probabilities after user selections of items have been received by the probability component. In contrast to the horizontal line of graph 200, graph 300 includes a power law distribution curve 302 indicating that Item1 through Itemn have a higher probability of being selected than Itemn. It is to be appreciated, therefore, that items that are frequently selected by users will have higher probabilities than items that are rarely selected.
When generating a ranked list of items, therefore, the probability component is more likely to place items that are frequently selected at the top of the list by virtue of the fact that items that are frequently selected will have higher probabilities. However, because the probability component uses probabilities to generate ranked lists, it is theoretically possible for items with lower probabilities to be ranked at the top of the list. In other words, the fact that an item has a low associated probability does not guarantee that the item will be ranked near the bottom of the list. The low probability simply decreases the likelihood that the item will be ranked at the top of the list. Furthermore, if an item with a low probability is placed at the top of a ranked list, and subsequently is selected or interacted with, the item's associated probability will increase thereby increasing the likelihood that the item will be selected again.
In accordance with various embodiments, the probability component can create and update item probabilities for multiple different locations. For example, when an item selection from a user is received, the probability component can determine a location associated with the user or the user's device. Any suitable technique can be utilized to ascertain the user's location, examples of which are provided below. The probability component can then update the probability of the selected item and other items in the list for the specific location of the user. In other words, an item selection by a user in a particular location can cause the probability component to update the probability of the selected item for the particular location. Therefore, when the probability component generates a ranked list of items for a user associated with a particular location, the list can be ranked based on previous item selections by users associated with the same location as the user. In this way, the list of items can be tailored to a user at a specific location based on what items other users at the same location have previously selected.
In various embodiments, the probability component can update item probabilities for multiple regions or sub-regions associated with a location of a client device. Consider, for example, that the probability component receives an item selection from a client device located at a specific address in the Queen Anne neighborhood of Seattle, Wash. The probability component can update probabilities associated with the selected item for a variety of different regions associated with the specific location, such as the specific address, the Queen Anne neighborhood, the city of Seattle, Wash. State, the West Coast, and the United States. In this way, probabilities can be associated with regions or sub-regions at different levels of granularity.
In accordance with various embodiments, a client device, such as device 102, can request a list of items. This request can be performed, for example, by a user on a client device who navigates to a web page via a web browser. Consider for example, FIG. 4, which illustrates an example web browser user interface 400 comprising part of a web browser that can be executed on a client device to facilitate navigation to and from various web sites. In this example, web browser user interface 400 has been navigated to www.msn.com and is displaying a web page 402. Web page 402 includes an item display area 404 in which Item 1 to Item 5 are displayed at 406, 408, 410, 412, and 414, respectively. Item display area 404 can be embodied as any type of web page user interface that is configured to display items.
In at least some embodiments, the item display area is configured to display a limited number of items in a list of items. In FIG. 4, for example, item display area 404 is configured to display just five items from the list of items. It is to be appreciated of course that that item display area 404 can be configured to display any number of items.
In at least some embodiments, item display area 404 can be embodied as a social toolbar that is configured to display indications in the form of links to various social media websites, such as Facebook, Twitter, and LinkedIn to enable users to quickly and efficiently navigate to their favorite social media web sites. As noted above, when a user navigates to a website that includes an item display area, the probability component can cause the item display area to be populated with the relevant items.
As discussed above, the probability component can determine a location associated with a client device responsive to receiving a request for a list of items from the client device. The location associated with a client device can be used by the probability component to provide the client with a list of items that is tailored to the specific location associated with the client device and/or a location associated with a user of the client device.
The probability component can determine a location of a client device in a variety of different ways, including, by way of example and not limitation, using a user-specified location, GPS data, or an IP address of the client device. For example, a user can manually provide user-specified location data (e.g., a specific country, state, city, or address), as part of a request, to the probability component. Alternately or additionally, a client device equipped with GPS sensors can transmit GPS data, as part of the request, to the probability component so that the probability component can determine a current location of the client device that changes as the user and/or client device changes locations.
In at least some embodiments, the probability component can determine a location associated with a user of the client device that may not be the actual current location of the user and/or the client device. For instance, the probability component can receive and save a user-specified location associated with a user so that the user-specified location does not change as the user and/or client device changes locations. Consider for example, that a user from California could set a home location to be California so that even if the user travels to Europe with his laptop, the probability component will determine the location associated with the user to be California.
Responsive to determining a location associated with a client device, the probability component can determine, through a search, whether probability data is available for the determined location. In some cases, however, the specific location may be very precise, such as a specific address, and probability data may be unavailable. In these instances, the probability component can use various alternatives to discover probability data. As described above, items may have associated probability data for specific regions (e.g., countries), as well as sub-regions within the specific regions (e.g., states, counties, cities, and neighborhoods within the specific region).
Therefore, in accordance with various embodiments, if probability data associated with the determined location of a client device is not available, the probability component can zoom out to a less specific, or more general location or region. The probability component can then determine whether probability data associated with the less specific location or region is available. For example, if the probability component determines that probability data is not available for the specific Queen Anne neighborhood location of a client device, the probability component can zoom out to a less specific region, such as the city of Seattle. The probability component then determines whether probability data is available for the city of Seattle. If probability data is unavailable for Seattle, the probability component can again zoom out and search for probability data at a less specific region such as the state of Washington. This process can continue until the probability component finds probability data.
As noted above, the probability component can generate a ranked list of items using probability data associated with a location of a client device. Since the probability data is based on user selections by users associated with a same or similar location as the user, the probability component can provide the user with a list of items that is tailored to the location associated with the user.
In accordance with various embodiments, the probability component can generate a ranked list of items by selecting items from a list of items using probability values associated with each item until all of the items have been placed in the ranked list. Items with high probability values, therefore, have a greater likelihood of being included higher in the ranked list than items with low probability values. For example, an item with a probability value of 50% has a much better chance of being selected first in the ranked list than an item with a probability value of 1%.
After generating a ranked list of items, the probability component transmits the ranked list to a client device. For example, in FIG. 1, probability component 122 at server 114 can transmit a ranked list of items via network 112 to computing device 102.
Responsive to receiving the ranked list of items, the client device can display the ranked list of items in an item display area, such as the one described above. At web page 402 (FIG. 4), for example, a ranked list of items is displayed in item display area 404. In at least some embodiments, there may be limited space available to display items in the item display area. For example, item display area 404 has limited space to display just five items. The item display area can be configured to fill the limited spaces in the display area by sequentially selecting items from the top of the list and placing the selected items in the item display area until the item display area is filled with items.
The client device can receive user selections of items from the item display area. In FIG. 4 for example, a user can select Item 1, Item 2, Item 3, Item 4, and/or Item 5 from item display area 404 using a cursor. In this example, notice that a user's cursor has selected a more control 416 which causes a scrollable display list of items 418 to be displayed. Scrollable display list of items 418 is configured to display other items from the list of items that are not currently displayed in the display area because they were not ranked high enough in the generated ranked list of items. While users can still access items in the scrollable display list, it may be less likely that users will select these items over items displayed in the display area. After receiving a user selection of an item, the client device can transmit the user selection to the probability component.
The probability component can update probability data responsive to receiving user selections of items. In at least some embodiments, the probability component updates probability data by increasing a selected item's probability and decreasing the probability of other items in a list, as discussed above. The probability component can update probability data in real time as user selections are received to ensure that the probability data is current. The effect of a user selection of an item on the selected item's probability can vary. It is to be appreciated that the effect of a user selection of an item at a particular location may be based, at least in part, on the number of previous user selections at the particular location. For instance, in a specific location or region where there have been a limited number of previous user selections, the user selection may greatly increase the selected item's probability. Alternately, in more general locations or regions where there have been many previous user selections, the user selection may only slightly increase the selected item's probability. For example, a user selection of an item by a user associated with Seattle may increase the selected item's probability by 1% for Seattle, and have a negligible effect on the item's probability for Washington State because there may be more previous user selections associated with the larger region of Washington State.
Having considered an example probability component, consider now an example method that the probability component can implement, in accordance with one or more embodiments.
FIG. 5 is a flow diagram that describes steps in a method in accordance with one or more embodiments. The method can be implemented in connection with any suitable hardware, software, firmware, or combination thereof. In at least some embodiments, aspects of the method can be performed by a client device, and other aspects of the method can be performed by a probability component, such as probability component 122, executing on a server, such as server 114 illustrated in FIG. 1.
Step 500 requests, from a server, a list of items. For example, a client device, such as device 102, can request a list of items through a navigation to a web page that includes an item display area in which items are displayed.
Step 502 receives, at the server, the request for the list of items. Step 504 determines a location associated with the client device. Location can be determined in a variety of different ways, including using a user-specified location, GPS data, or an IP address of the client device, to name just a few. Step 506 determines whether probability data is available for the particular location of the client device. If probability data is not available, step 508 zooms out to less specific locations until probability data is found. Examples of how this can be done are provided above. When probability data is available, step 510 generates a ranked list of items using the probability data associated with the location of the client device. As noted above, the ranked list of items can be tailored to the user's or client device's particular location. Step 512 transmits the ranked list of items back to the client device.
Step 514 receives the ranked list of items from the server. Step 516 displays the ranked list of items. Examples of how this can be done are provided above. Step 518 receives a user selection of an item in the ranked list of items. Step 520 transmits the user selection back to the server.
Step 522 receives the user selection and step 524 updates probability data based on the user's selection. For example, the probability component can update probability data by increasing the probability of a selected item in a list and decreasing the probability of other items in the list, as discussed above.
Having discussed an example method in accordance with one or more embodiments, consider now an example system that can be utilized to implement the embodiments described above.
FIG. 6 illustrates an example computing device 600 that can implement the various embodiments described above. Computing device 600 can be, for example, various computing devices or servers, such as those illustrated in FIG. 1 or any other suitable computing device.
Computing device 600 includes one or more processors or processing units 602, one or more memory and/or storage components 604, one or more input/output (I/O) devices 606, and a bus 608 that allows the various components and devices to communicate with one another. Bus 608 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. Bus 608 can include wired and/or wireless buses.
Memory/storage component 604 represents one or more computer storage media. Component 604 can include volatile media (such as random access memory (RAM)) and/or nonvolatile media (such as read only memory (ROM), Flash memory, optical disks, magnetic disks, and so forth). Component 604 can include fixed media (e.g., RAM, ROM, a fixed hard drive, etc.) as well as removable media (e.g., a Flash memory drive, a removable hard drive, an optical disk, and so forth).
One or more input/output devices 606 allow a user to enter commands and information to computing device 600, and also allow information to be presented to the user and/or other components or devices. Examples of input devices include a keyboard, a cursor control device (e.g., a mouse), a microphone, a scanner, and so forth. Examples of output devices include a display device (e.g., a monitor or projector), speakers, a printer, a network card, and so forth.
updating the probability data associated with the list of items using the user selection, the probability data being updated by at least increasing a probability associated with the selected item and decreasing probabilities associated with each of the other items in the list of items such that a total amount of decrease of the decreased probabilities is equal to an amount of increase of the probability of the selected item.
2. One or more computer-readable storage media devices as recited in claim 1, wherein updating the probability data includes updating the probability data associated with the list of items for one or more regions associated with the location associated with the client device.
3. One or more computer-readable storage media devices as recited in claim 1, wherein updating the probability data includes updating the probability data associated with the list of items in real time.
4. One or more computer-readable storage media devices as recited in claim 1, wherein the list of items comprises a list of social media websites.
5. One or more computer-readable storage media devices as recited in claim 1, wherein the probability data corresponding to the location associated with the client device is further based on selections of items from said sources having a same location as the location associated with the client device.
6. One or more computer-readable storage media devices as recited in claim 1, wherein determining a location associated with the client device includes determining a location using a user-specified location, GPS data, or an IP address of the client device.
7. One or more computer-readable storage media devices as recited in claim 1, wherein an increase of a probability associated with a particular item is further based on a quantity of previous user selections from a list of items.
transmitting the user selection to the server to enable the server to increase an associated probability of the selected user-selectable item and decrease respective associated probabilities of each of the other user-selectable items in the item display area such that a total amount of decrease of the decreased probabilities equals an amount of increase of the probability of the selected user-selectable item.
9. The computer-implemented method as recited in claim 8, further comprising displaying one or more other user-selectable items corresponding to one or more of the social media websites in a scrollable display list.
10. The computer-implemented method as recited in claim 8, wherein the item display area is configured to display a limited number of user-selectable items corresponding to the social media websites.
decreasing probabilities associated with all other items in the list of items for the location of the client device to cause a total amount of decrease of the decreased probabilities to equal an amount of increase of the probability of the selected item.
12. The computer-implemented method as recited in claim 11, wherein increasing the probability includes increasing the probability associated with the selected item for one or more regions associated with the location of the client device.
13. The computer-implemented method as recited in claim 11, wherein the list of items comprises a list of social media websites.
14. The computer-implemented method as recited in claim 11, wherein the probability data is based on selections of items from sources other than the client device.
15. The computer-implemented method as recited in claim 14, wherein the probability data is further based on selections of items from said sources having a same location as the location of the client device.
16. The computer-implemented method as recited in claim 11, wherein updating the probability data further comprises updating the probability data for multiple regions that are associated with the location of the client device and which each include a different level of granularity.
17. The computer-implemented method as recited in claim 11, wherein the amount of increase of the probability of the selected item is based on a number of previous selections of the selected item from sources associated with a same location as the location of the client device.
18. The computer-implemented method as recited in claim 11, wherein at least two of the decreased probabilities are decreased by different amounts, the different amounts being based on a respective number of previous selections of each item associated with the at least two decreased probabilities.
19. The computer-implemented method as recited in claim 11, wherein the probability data defines a measure of a likelihood that an associated item will be selected.
responsive to determining that the probability data corresponding to the location of the client device is not available, zooming out to a less precise location to determine whether probability data is available at the less precise location.
Challenger, et al., "Efficiently Serving Dynamic Data at Highly Accessed Web Sites", Retrieved >, IEEE/ACM Transactions on Networking, vol. 12, No. 2, Apr. 2004, pp. 233-246.
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10,000 THB for a delivery of 60 photos with integration of your logo.
8,000 THB for a delivery of 30 photos with integration of your logo.


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Despite using the highest possible in-game quality settings we see that the RX 460 and other mid-range to low-end graphics cards have no issue delivering over 100fps at 1080p. With ultra-affordable previous-generation GPUs such as the R7 250 providing over 100fps, the RX 460 doesn't really break new ground here.
The RX 460 looks a bit more impressive in CS:GO. I'm told that seriously competitive CS:GO players aim for at least 200fps and if true the RX 460 delivers that with 8xMSAA enabled. Still, for essentially everyone else, the old R7 250's 88fps would no doubt suffice.


Are you ready for a Spooktacular Reading Month? Or like some folks, did you get an early start in September. If you haven't read Mary Shelley's Frankenstein or Bram Stoker's Dracula, now would be a perfect time to do so. Wait, come back. Not right this minute, but this month. *grin* I've read them already, and thoroughly enjoyed them, although was really quite surprised because neither was quite what I expected. Which is actually a good thing, because it keeps one from getting bored. The mantra this month is expect the unexpected.
Spooky doesn't have to necessarily mean horror. I'm definitely not into the blood and guts type of books, but do love a great nail biting, give me goose bumps, don't turn off the lights read. And there are plenty of scary, spooky, chilling, thrilling books that are psychological fiction, paranormal or just plain old thrillers.
In that vein, I have a few spooky books on the shelves I will be reading and essentially still continuing with a Frankenstein and Dracula theme.
I've fallen in love with Dean Koontz and his Odd Thomas series so I am happy to say he wrote a series in which he reworked the Frankenstein theme. I'll be tackling the first book Frankenstein: Prodigal Son. I'll let you know what I think or if I manage to make it through the whole book.
Every city has secrets. But none as terrible as this. His name is Deucalion, a tattooed man of mysterious origin, a sleight-of-reality artist who's traveled the centuries with a secret worse than death. He arrives as a serial killer stalks the streets, a killer who carefully selects his victims for the humanity that is missing in himself. Detective Carson O'Connor is cool, cynical, and every bit as tough as she looks. Her partner Michael Maddison would back her up all the way to Hell itself–and that just may be where this case ends up. For the no-nonsense O'Connor is suddenly talking about an ages-old conspiracy, a near immortal race of beings, and killers that are more—and less—than human. Soon it will be clear that as crazy as she sounds, the truth is even more ominous. For their quarry isn't merely a homicidal maniac—but his deranged maker.
An unapologetic tale about a man who endured great losses and was driven by intense passion for his country and religion...the novel is aimed much more at readers interested in the historical origins of the Dracula stories than at those looking for another vampire story. As such, it succeeds admirably.
Neither do I think I could go wrong with Edgar Allan Poe's The Narrative of Arthur Gordon Pym and Jules Verne's An Antarctic Mystery which was inspired by Poe's story and supposedly completes the mystery. Plus H.P. Lovecraft's At the Mountain of Madness which was also inspired by Pym and takes place in the Antarctic.
But I really enjoyed Mathematics: Is God Silent. It's a must-read for every classical or CM home educator and fascinating for anyone with an interest in philosophy, mathematics, or science.
Perfectly understandable. I'll check out Mathematics. Sounds interesting.


Was Your Identity Compromised by Equifax?
Two Equifax executives are retiring after a massive data breach affected nearly 150 million people in the U.S., and the company has come under fire for its response.
The hack involved names, Social Security numbers, birth dates, addresses, and driver's license numbers, according to Equifax. Nobody knows – at least according to the company – who carried out the cyberattack or what they're doing with the information.
Equifax has set up a website – www.EquifaxSecurity2017.com – and a call center that you can reach at 866-447-7559 to offer impacted Americans access to a free credit-monitoring service. Despite a shaky rollout, the program seems to be working now.
A large number of states have begun class-action lawsuits against the company for those affected, which experts say will soon be consolidated into regional suits.
"Equifax probably injured 143 million people, which is kind of a record," said John Coffee, the professor at Columbia Law School who directs the schools Center on Corporate Governance.
Was your information affected by Equifax's data breach, and if it was, have you enrolled in the company's indentity theft protection program? Will you participate in one of the class-action lawsuits? I'd love to hear your thoughts on the company's month-long cover-up and the executives' sales of $2 million in stock, too, so please let me know what you're thinking on my Twitter feed or on my Facebook page – and use the hashtag #EquifaxDataBreach to join the conversation.


Where to get the perfect spring skiing gear for your head.
Who in the world would want a manhole? Lots of people, apparently.
Vail-based company SYNC creates unique products for the race hill.
Vail Magazine's weekly roundup of the best free and fun things to do this week.


Thread: Mongol....to be or not to be ???
I am an avid total war fan and have all of the total war games with exception of a few add-ons.
I intend to get the penninsula (sp) campaign, Warpath & Alexander from Steam.
The only one I will not have is Mongol Invasion the expansion for STW.
The only way it seems to get this is to purchase either STW Gold edition, STW Warlords or ERA's.
I despise buying games that I already have as that makes my existing copy worthless.
My question: Is Mongol invasion worth it?
PS: I love STW as it reminds me of an awesome real-life (for the time it came out) version of a game I loved and spent many hours on the NES playing called Nobunaga's Ambition.
Re: Mongol....to be or not to be ???
and No, no stand out features. BUT you get a new campaign!!! Wayhey!
eXtended Cultures-Challenge Accepted! an AAR so awesome you HAVE to read it.
The mongols, both to be played and to be faced, are fantastic!
And it's not just A new campaign: there are something like 6 campagin (maybe i don't remember) everyone of them set in a different period!
It worth to be bought in my opinion!
Last edited by Cinuz; September 12, 2010 at 03:31 PM.
Moved to Shogun Total War.


text:
Question: When Was The Democratic Republican Party Formed?
What political party was Abraham Lincoln?
Why do party realignments occur?
What color are Republicans?
How was the Democratic Republican Party formed?
When did the Democratic and Republican party switch?
When did the Republican party start?
What does a Democrat believe in?
When were the political parties formed?
Who started the Democratic Party in the US?
Who founded the Republican Party?
Are Republicans left or right?
National Union PartyAbraham Lincoln/Parties.
During party realignments, some groups of people who used to vote for one party vote for the other one. Sometimes, political parties end and new ones begin. Party realignments can happen because of important events in history or because of changes in the kinds of people in the country.
Since around the 2000 United States presidential election, red states and blue states have referred to states of the United States whose voters predominantly choose either the Republican Party (red) or Democratic Party (blue) presidential and senatorial candidates.
The Democratic-Republican Party originated as a faction in Congress that opposed the centralizing policies of Alexander Hamilton, who served as Secretary of the Treasury under President George Washington.
After being the dominant party in U.S. politics from 1800 to 1829, the Democratic-Republicans split into two factions by 1828: the federalist National Republicans, and the Democrats. The Democrats and Whigs were evenly balanced in the 1830s and 1840s. However, by the 1850s, the Whigs disintegrated.
March 20, 1854, Ripon, Wisconsin, United StatesRepublican Party/Founded
The modern Democratic Party emphasizes egalitarianism, social equality, protecting the environment, and strengthening the social safety net through liberalism. They support voting rights and minority rights, including LGBT rights, multiculturalism, and religious secularism.
The GOP supports lower taxes, free market capitalism, restrictions on immigration, increased military spending, gun rights, restrictions on abortion, deregulation and restrictions on labor unions.
Political factions or parties began to form during the struggle over ratification of the federal Constitution of 1787.
Andrew JacksonMartin Van BurenDemocratic Party/FoundersFoundation: 1820-28. The modern Democratic Party emerged in the late 1820s from former factions of the Democratic-Republican Party, which had largely collapsed by 1824. It was built by Martin Van Buren, who assembled a cadre of politicians in every state behind war hero Andrew Jackson of Tennessee.
Horace GreeleyHenry Jarvis RaymondRepublican Party/Founders
Those on the Left often called themselves "republicans", while those on the Right often called themselves "conservatives".
Quick Answer: How Do You Say I Really Appreciate It?
What is another way to say greatly appreciated?
What Is Another Word For Rhetorical Question?
What are the most common rhetorical devices?
Question: Do Planes Fly Over Everest?
What countries can planes not fly over? Flights are
Quick Answer: What Are The 10 Names Of God?
What is God number? The term "God'
Question: What Is The Best Way To Draw On A Computer?
What software do digital artists use? The best digital


Anyone who has a blog or WordPress site knows that one thing you will for sure need is images. Posts without images are boring, they look overly long, and they don't keep the users attention. Today I'm doing WP FotoPress Review for wordpress plugin called FotoPress to add a photoshop like editor in 1-Click.
What Is WP FotoPress ?
People are visual creatures and you for sure should have some visuals for them to look at on all your blog posts or website pages.
The problem is that WordPress has very limited image functionality. You can upload an image but beyond that there is little more you can do. You cant edit an image, you cant add text or crop it. Even worse you need to actually have an image in the first place.
Unless you have a huge library of images just sitting on your hard drive what you will find yourself doing when you need one is something similar to this. You head over to Google and start searching for an image in the image search tab. Then you look through all of the search results trying to find one that both looks good, and that is not water marked or copyrighted. Once you finally find one you download it to your computer. Then you use an image editor to resize it, crop it, add any effects or text and save again. Finally when all that is done you can upload it to WordPress and use it in your post.
WP FotoPress aims to solve these problems my making this entire process happen quickly, and right inside of WordPress itself. Every single wordpress site owner needs this plugin because images are an integral part of content and marketing.
To start off with it adds a special FotoPress button inside of the WordPress WYSIWYG editor.
Clicking that button will then give you the option to pull images from your computer, from your Youzign account if your a Youzign user or to search for images. Of these three options the most useful for many people is going to be the image search functionality.
You can search for images on Pixabay, Flickr, Open Clip Art, or Instagram. You can also tell the search to only find images that do not require attribution (credit to the author) and that are licensed as free to modify if you like. In my testing, searching Pixabay only the plugin found 500 results for my search in about a second or two.
Once you select the image you want you can then insert it into your post as it is, or you can edit it. I think most people are going to want to edit it. At the very least your going to want to resize the image and possibly crop it. Fortunately FotoPress is not just an image search tool. Its also an image editor.
Besides being able to crop and resize you can also add PhotoShop like effects, text, other images, shapes or free hand drawings to your image.
Step 1 – Download the FotoPress plugin.
Step 3 – BOOM it's done!
Should You Buy WP FotoPress ?
I think that this WP FotoPress Review has already showed you all cool & powerful features of this plugin. With only $27, you can own WP FotoPress and save a ton of your TIME & MONEY for adding photos to your blogs & WP sites.
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text:
Cake Hole may refer to:

 As a crude phrase, the mouth

In music
Cakehole, a song by The Crystal Method on their Community Service album
A remix by Evil Nine for Distinct'ive Records' Y4K series on the ILS Presents: Y4K album.
"Cakewhole", a remix by Ferocious Mullet for Distinct'ive Records' Y4K series on the Überzone Presents: Y4K album.