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    • By Monty Kiani
      This idea comes from the concept of making a game that specifically, fills the time of a person in travel when the person might not enjoy the adrenaline factor that accompanies many games.  I couldn't come up with anything so I thought about the general vibe I wanted and an action people did in general that emulated that. I found that it mostly happened, amongst other places no doubt, when people go through their messages panel on their devices; a plane traveler/businessperson perfectly calm for a minute eliminating messages, that moment extended. It's a kind of process of elimination. I don't know if this idea is common knowledge but I couldn't find anything and I'd love to see games based on this. 
    • By AFrai
      Hello!
      Question to the experts in the field of gaming analytics. What tools do you use to evaluate the game in Stores?
      Advise something else besides appannie and steamspy.
    • By ptietz
      Hi everyone,
      first of all a little sorry, this is not about "visual arts" but more a GUI topic.
      I didn't know where else to put it, though.
      So, I just wondered if anyone of you has any experience or even real data on Google's material design in games?
      What are the pros and cons? Would players accept it? And can you make material design feel more "gamey"?
      Thanks in advance,
      BG
    • By wuyakuma

      I was reworking on my LightProbe filter, and I wrote some code to generate the Reference Cubemap, but then I noticed some discontinuous on the border of each face.(Top:CPU implementaion, Bottom: GPU implementation, the contrast has been adjusted on the right side)
      At first I think it maybe caused by the interpolation, but then I tried the same algorithm in 2D (like a slice in the normal light probe prefiltering) for better visualization, and the result really confused me.
      See the attachments, the top half is the Prefiltered Color value, displayed per channel, it's upside down because I used the ColorValue directly as the y coordinate. 


      The bottom half is the differential of the color, it's very clearly there is a discontinuous, and the position is where the border should be. And as the roughness goes higher, the plot gets stranger .
      So, I am kinda of stuck in here, what's happening and what to do to remove this artifact? Anybody have any idea? 
      and here is my code
      inline FVector2D Map(int32 FaceIndex, int32 i, int32 FaceSize, float& SolidAngle) {     float u = 2 * (i + 0.5) / (float)FaceSize - 1;     FVector2D Return;     switch (FaceIndex)     {     case 0: Return = FVector2D(-u, -1); break;     case 1: Return = FVector2D(-1, u);  break;     case 2: Return = FVector2D(u, 1); break;     case 3: Return = FVector2D(1, -u); break;     }     SolidAngle = 1.0f / FMath::Pow(Return.SizeSquared(), 3.0f / 2.0f);     return Return.SafeNormal(); } void Test2D() {     const int32 Res = 256;     const int32 MipLevel = 8;     TArray<FLinearColor>    Source;     TArray<FLinearColor>    Prefiltered;     Source.AddZeroed(Res * 4);     Prefiltered.AddZeroed(Res * 4);     for (int32 i = 0; i < Res; ++i)     {         Source = FLinearColor(1, 0, 0);         Source[Res + i] = FLinearColor(0, 1, 0);         Source[Res * 2 + i] = FLinearColor(0, 0, 1);         Source[Res * 3 + i] = FLinearColor(0, 0, 0);     }     const float Roughness = MipLevel / 8.0f;     const float a = Roughness * Roughness;     const float a2 = a * a;     // Brute force sampling with GGX kernel     for (int32 FaceIndex = 0; FaceIndex < 4; ++FaceIndex)     {         for (int32 i = 0; i < Res; ++i)         {             float SolidAngle = 0;             FVector2D N = Map(FaceIndex, i, Res, SolidAngle);             double TotalColor[3] = {};             double TotalWeight = 0;             for (int32 SampleFace = 0; SampleFace < 4; ++SampleFace)             {                 for (int32 j = 0; j < Res; ++j)                 {                     float SampleJacobian = 0;                     FVector2D L = Map(SampleFace, j, Res, SampleJacobian);                     const float NoL = (L | N);                     if (NoL <= 0)                         continue;                     const FVector2D H = (N + L).SafeNormal();                     const float NoH = (N | H);                     float D = a2 * NoL * SampleJacobian / FMath::Pow(NoH*NoH * (a2 - 1) + 1, 2.0f) ;                     TotalWeight += D;                     FLinearColor Sample = Source[SampleFace * Res + j] * D;                     TotalColor[0] += Sample.R;                     TotalColor[1] += Sample.G;                     TotalColor[2] += Sample.B;                 }             }             if (TotalWeight > 0)             {                 Prefiltered[FaceIndex * Res + i] = FLinearColor(                     TotalColor[0] / TotalWeight,                     TotalColor[1] / TotalWeight,                     TotalColor[2] / TotalWeight);             }         }     }     // Save to bmp     const int32 Width = 4 * Res;     const int32 Height = 768;     TArray<FColor> Bitmap;     Bitmap.SetNum(Width * Height);     // Prefiltered Color curve per channel     float MaxDelta = 0;     for (int32 x = 0; x < Width; ++x)     {         FColor SourceColor = Source[x].ToFColor(false);         Bitmap[x] = SourceColor;         FColor Sample = Prefiltered[x].ToFColor(false);         check(Sample.R < 256);         check(Sample.G < 256);         check(Sample.B < 256);         Bitmap[Sample.R * Width + x] = FColor(255, 0, 0);         Bitmap[Sample.G * Width + x] = FColor(0, 255, 0);         Bitmap[Sample.B * Width + x] = FColor(0, 0, 255);         if (x > 0)         {             const FLinearColor Delta = Prefiltered[x] - Prefiltered[x - 1];             MaxDelta = FMath::Max(MaxDelta, FMath::Max3(FMath::Abs(Delta.R), FMath::Abs(Delta.G), FMath::Abs(Delta.B)));         }     }     // Differential per channel     const float Scale = 128 / MaxDelta;     for (int32 x = 1; x < Width; ++x)     {         const FLinearColor Delta = Prefiltered[x] - Prefiltered[x - 1];         Bitmap[int32(512 + Delta.R * Scale) * Width + x] = FColor(255, 0, 0);         Bitmap[int32(512 + Delta.G * Scale) * Width + x] = FColor(0, 255, 0);         Bitmap[int32(512 + Delta.B * Scale) * Width + x] = FColor(0, 0, 255);     }     FFileHelper::CreateBitmap(TEXT("Test"), Width, Height, Bitmap.GetData()); }  
      Roughness 0.5.bmp
      Roughness 1.bmp
    • By khawk
      Nearly 5,000 developers and tech professionals across the world responded to Packt’s third annual Skill Up survey to share their thoughts on the latest tech tools and trends, and how they work and learn. Skill Up 2017 also investigated wider questions about the tech industry - from its status and value in organizations and industry today, through to urgent issues around diversity.
      The aim of Packt’s Skill Up survey is to help those working in tech make better decisions about the tools they decide to use, how they use them, and how they learn about them, in order to stay relevant and gain a competitive edge in their careers. 
      Download the full Skill Up report to discover what it’s like to work in tech today.
      Who took part in Skill Up 2017?
      Skill Up was circulated globally to people working across an array of sectors in tech; from mobile developers to big data engineers, and everyone in between. 4,731 respondents from 43 countries around the world took part. The majority of responses came from men aged between 35 and 45 working full-time in software solutions in the United States. 
      A full breakdown of this year’s demographics can be found in the full Skill Up report.
      Skill Up at a glance
      And the number one tool is…
      Python. Its popularity has surged over recent years and it has clearly gained huge mainstream uptake due to its accessibility, fully featured standard library, rich ecosystem of libraries and frameworks, and highly engaged community. Joining Python in the top 5 are Git, Visual Studio, Eclipse, and Java.
      Discover who’s using Python and the tools they’re most likely to use with it in Skill Up.
      What should people be learning next?
      Python’s popularity won’t be waning any time soon – it came in at second place as the tool to learn over the next 12 months. Python was pipped to pole position by Docker. With the growth of containerization, a surge in people learning Docker makes sense. Angular, Visual Studio, and Jenkins also make the top 5.
      Take a look at Skill Up to explore who will be learning what over the next 12 months.
      Why learn something new?
      ‘There is a problem that I need to fix and don't know how’ is the number one reason why developers and tech professionals choose to learn something new. They also cite solving problems more effectively at work, and curiosity about tools and languages they’ve read about online as reasons to get learning.
      18-34 year olds are most likely to learn something new in order to expand their skillset and apply for a new role. Despite this career focus, they are the most likely to say they are not motivated to learn. The over 45s are very practical about their learning, saying that a new update or change to a language or tool they work with spurs them on to learn. Whilst they have the motivation to learn, they find that lack of time is their biggest barrier. 
      Skill Up also revealed that 18-34 year olds are big Stack Overflow fans, whilst the over 45s are into their reading. Packt is committed to learning to suit everyone; offering eBooks, print books, videos, blogs, and an online learning platform, Mapt.
      Discover more about how those working in tech are learning in the full Skill Up report.
      The skills that pay the bills
      The big question – who’s earning the most? The top five roles to be in for ultimate earning power are C-Suite Level Managers, Big Data Engineers, Mid-level Leads/Managers, Security Engineers, and Information Architects. Unsurprisingly, developers and tech professionals in North America have the highest average salary, whilst those in South and South-East Asia are worst off.
      As for the lowest paid roles, hobbyists came out on top, yet we can assume respondents identifying as hobbyists do not work full-time in a tech role. In terms of full-time professions, Game Developers had the lowest average salary, followed by Web Developers, Technical Support Professionals, and Mobile Developers.
      So what do you need to learn to earn? Respondents with Splunk, Hadoop, Kafka, Chef, or SAS under their belt earn more than the average salary. It seems as though Big Data is the industry to be in.
      Does the tech industry have a gender diversity problem?
      90% of respondents to Skill Up were male, which in itself reveals the industry’s lack of gender diversity. Packt asked respondents if they thought the tech industry does have a gender diversity issue, and a majority of 47.2% agreed. 24.3% didn’t think there was an issue, whilst 28.5% were sat on the fence.
      The biggest gap between gender equality appeared in the Financial Services and Software Solutions sectors, whilst Design and Marketing came out on top for diversity. It may come as no surprise that 18-24 year old males were the least likely to agree there is a gender diversity issue. Perhaps a rose-tinted view stemming from a lack of industry experience?
      The full Skill Up 2017 survey report is free and available for download here.
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Packt's Skill Up Survey Finds New Tech Trends for Developers

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Nearly 5,000 developers and tech professionals across the world responded to Packt’s third annual Skill Up survey to share their thoughts on the latest tech tools and trends, and how they work and learn. Skill Up 2017 also investigated wider questions about the tech industry - from its status and value in organizations and industry today, through to urgent issues around diversity.

The aim of Packt’s Skill Up survey is to help those working in tech make better decisions about the tools they decide to use, how they use them, and how they learn about them, in order to stay relevant and gain a competitive edge in their careers. 

Download the full Skill Up report to discover what it’s like to work in tech today.

Who took part in Skill Up 2017?

Skill Up was circulated globally to people working across an array of sectors in tech; from mobile developers to big data engineers, and everyone in between. 4,731 respondents from 43 countries around the world took part. The majority of responses came from men aged between 35 and 45 working full-time in software solutions in the United States. 

A full breakdown of this year’s demographics can be found in the full Skill Up report.

Skill Up at a glance

And the number one tool is…

Python. Its popularity has surged over recent years and it has clearly gained huge mainstream uptake due to its accessibility, fully featured standard library, rich ecosystem of libraries and frameworks, and highly engaged community. Joining Python in the top 5 are Git, Visual Studio, Eclipse, and Java.

Discover who’s using Python and the tools they’re most likely to use with it in Skill Up.

What should people be learning next?

Python’s popularity won’t be waning any time soon – it came in at second place as the tool to learn over the next 12 months. Python was pipped to pole position by Docker. With the growth of containerization, a surge in people learning Docker makes sense. Angular, Visual Studio, and Jenkins also make the top 5.

Take a look at Skill Up to explore who will be learning what over the next 12 months.

Why learn something new?

‘There is a problem that I need to fix and don't know how’ is the number one reason why developers and tech professionals choose to learn something new. They also cite solving problems more effectively at work, and curiosity about tools and languages they’ve read about online as reasons to get learning.

18-34 year olds are most likely to learn something new in order to expand their skillset and apply for a new role. Despite this career focus, they are the most likely to say they are not motivated to learn. The over 45s are very practical about their learning, saying that a new update or change to a language or tool they work with spurs them on to learn. Whilst they have the motivation to learn, they find that lack of time is their biggest barrier. 

Skill Up also revealed that 18-34 year olds are big Stack Overflow fans, whilst the over 45s are into their reading. Packt is committed to learning to suit everyone; offering eBooks, print books, videos, blogs, and an online learning platform, Mapt.

Discover more about how those working in tech are learning in the full Skill Up report.

The skills that pay the bills

The big question – who’s earning the most? The top five roles to be in for ultimate earning power are C-Suite Level Managers, Big Data Engineers, Mid-level Leads/Managers, Security Engineers, and Information Architects. Unsurprisingly, developers and tech professionals in North America have the highest average salary, whilst those in South and South-East Asia are worst off.

As for the lowest paid roles, hobbyists came out on top, yet we can assume respondents identifying as hobbyists do not work full-time in a tech role. In terms of full-time professions, Game Developers had the lowest average salary, followed by Web Developers, Technical Support Professionals, and Mobile Developers.

So what do you need to learn to earn? Respondents with Splunk, Hadoop, Kafka, Chef, or SAS under their belt earn more than the average salary. It seems as though Big Data is the industry to be in.

Does the tech industry have a gender diversity problem?

90% of respondents to Skill Up were male, which in itself reveals the industry’s lack of gender diversity. Packt asked respondents if they thought the tech industry does have a gender diversity issue, and a majority of 47.2% agreed. 24.3% didn’t think there was an issue, whilst 28.5% were sat on the fence.

The biggest gap between gender equality appeared in the Financial Services and Software Solutions sectors, whilst Design and Marketing came out on top for diversity. It may come as no surprise that 18-24 year old males were the least likely to agree there is a gender diversity issue. Perhaps a rose-tinted view stemming from a lack of industry experience?

The full Skill Up 2017 survey report is free and available for download here.


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