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9L0-008 - Macintosh Service Certification - BrainDump Information

Vendor Name : Apple
Exam Code : 9L0-008
Exam Name : Macintosh Service Certification
Questions and Answers : 89 Q & A
Updated On : Click to Check Update
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developing the area's First good value AR Headset experience | 9L0-008 PDF Braindumps and Latest Questions

With the AR MultiPendulum app, I created the world's first AR headset adventure that doesn't count on expensive specialized hardware. using Google Cardboard, a standard iPhone, and pictures acquired using the cell's camera, the app creates an AR headset experience with the aid of rendering the user's surroundings in VR. To do this, I combined energy-productive innovations for actual-time hand tracking and scene colour reconstruction to create an immersive user event.

Introduction

Augmented fact (AR) is a expertise that overlays digital objects over the genuine world. For years, AR experiences were available on smartphones through handheld AR apps. In 2016, Pokemon Go popularized AR, protecting virtual characters on a map of the world. beyond that, AR has only performed a minor function in the commonplace adult's life, being used for a number of occasional initiatives reminiscent of measuring objects or trying out out furniture (Ayoubi, 2017).

A year earlier than the free up of Pokemon Go, Microsoft launched Hololens, a $3000 AR headset that items holograms via reflecting light into the user's eyes. not like VR headsets, Hololens enables users to peer their atmosphere whereas viewing digital content and interacting using their arms as an alternative of a controller. After releasing Hololens, Microsoft posted demos of a wide selection of use circumstances, and the demo of Minecraft went viral (Kuchera, 2015). Minecraft became prevalent to many individuals, and AR's promise of interplay and immersion meshed perfectly with the video game. for instance, users may engage with a Minecraft world the usage of intuitive hand gestures, enabling them to adventure creating buildings in Minecraft in ways that had been no longer viable earlier than. regardless of all the attention it got, Microsoft on no account grew to become the demo into an app. After 2015, Microsoft shifted its focus on Hololens from customer functions to the corporate enterprise atmosphere, and its expense continues to be at thousands of bucks to at the present time.

in the industries that put it to use, Hololens brings game-altering opportunities to enhance productiveness and even store lives. In hospitals, Hololens helps surgeons teach for prime-possibility surgeries (Microsoft, 2018). with the aid of interacting with precise 3D fashions of the human physique, surgeons can run in the course of the steps of surgical procedure and be taught from blunders in an environment on the way to now not endanger a patient's existence. If Hololens had been more cost-effective, it might enable first responders to provide extra types of existence-saving counsel to americans on the web page of an emergency.

within the mid-2020s, AR headset know-how is expected to move mainstream through sensible glasses that cost as a lot as a smartphone. sensible glasses were in building for a couple of years. despite the fact, their small size items a enormous hurdle that has under no circumstances been overcome. Hololens will also be huge and hulking because it is utilized in really good environments, where form component isn't a priority (Bohn, 2019). not like Hololens, wise glasses must fit a processor, mild projectors, and a battery into the equal footprint as a glasses frame while lasting for a few hours below a standard workload. To conserve energy, wise glasses might offload most of their computations to a paired smartphone.

Contents history MultiPendulum

In late 2019, i was concerned about the double pendulum, a physics simulation with chaotic motion. This movement is unpredictable yet fluid and aesthetically pleasing. I questioned what it might be want to event a simulation with three or more pendulums, greater complicated conduct, and no damping (a variety of friction that causes the simulation to decelerate and at last halt).

due to the fact my programming talents allowed me to bring a frictionless multi-pendulum simulation into reality, I challenged myself to create it. When gaining knowledge of the physics at the back of the simulation, I could not be mindful tons of the maths terminology and formulation. So, I went on an accelerated self-examine path. I absorbed a couple of years of math and physics course cloth in lower than a month, the usage of Khan Academy and a free electronic textbook. After this, I created an algorithm that simulates up to one hundred pendulums with out damping. A 12 months later, right before starting work on AR MultiPendulum, i'd publish the simulation online for gratis.

After finishing my normal multi-pendulum simulation, I began exploring 3D photos. I downloaded a laptop graphics textbook, read online utility documentation, and adopted an academic on OpenGL, a low-degree framework for rendering 3D pictures. When experimenting with OpenGL in Xcode 10, I discovered that my 9-12 months-ancient iMac couldn't run Xcode 11. Then, I spent a week discovering Swift, Apple's contemporary programming language that replaced aim-C, however Xcode 10 could not run the newest edition of Swift. annoyed, I bought a new Mac Mini to benefit access to both Xcode 11 and Swift.

With the most accurate edition of Xcode, I won purposeful experience with developing iOS apps. I attempted to learn metallic, a low-stage 3D images framework that changed OpenGL. however, I couldn't understand Apple's courses and demo code. I had simply invested weeks researching Swift, yet all of the demo code was in aim-C. After translating most of Apple's metallic pattern code from aim-C to Swift, I nevertheless didn't consider it. I gave up on getting to know metallic and tried solidarity and Unreal Engine (high-level frameworks which are much less demanding to study and greater beginner-pleasant). youngsters, i was not convinced with the path of any of my work in 3D images.

Augmented reality

on the iPhone 12 experience in October 2020, Apple became rumored to be unveiling its AR sensible glasses (Smith, 2020). I had been eagerly looking ahead to Apple's smart glasses for years and suspected that Apple would unencumber new equipment to put together utility builders for working with smart glasses after their announcement, but this didn't take place. I grew to become unsatisfied with expecting Apple to release an inexpensive AR headset.

With my potential as a software developer, I determined to create an AR headset experience myself. I repurposed the Google Cardboard VR viewer (which turns a smartphone into a VR headset) and my iPhone to create an AR headset, proposing a cheap option to Microsoft Hololens devoid of anticipating Apple's AR sensible glasses. by presenting a video of my surroundings in VR, I could overlay digital objects and create an AR headset event. given that neither team spirit nor Unreal Engine offers satisfactory flexibility to render a video in VR, my handiest alternative became to learn steel and make a custom game engine.

I began over with getting to know metallic and translated the metal pattern code from aim-C to Swift twice. After finding a web guide to using metallic for AR apps written in Swift, I created a simple app that introduced a video stream from AR as a flat rectangle in VR. After experiencing this preliminary effort at growing an AR headset, i was disappointed that I couldn't engage with digital objects. i'd need to construct on this foundation before I could share it with others.

In November 2020, I purchased an iPhone 12 pro Max with a constructed-in LiDAR scanner—a video game-changer for AR (Wilson, 2020). as an alternative of simply recording a video of my atmosphere, my cell additionally recorded its 3D form. This supposed I may present the realm as a 3D mesh as an alternative of a flat rectangle in VR, making it look an awful lot more functional and significantly enhancing the AR headset adventure.

despite the fact i used to be making development, there have been huge problems with my AR headset event. I couldn't interact with digital objects via hand gestures (like Hololens or future smart glasses). in addition, offering my surroundings in 3D removed all color, forcing me to outline the mesh as a wireframe to differentiate geometry.

First applications

by December 2020, I figured out how to render my atmosphere as a 3D mesh in VR (known as the "scene mesh"). I had additionally began working on a 3D hand reconstruction algorithm for interacting with virtual objects via advanced hand gestures. In January 2021, i used to be assigned a lengthy, unbiased college venture. I planned to create the first software for my work—a 3D modeling event best feasible on an AR headset.

per week into the project, i noticed that controlling digital objects in an AR headset with two palms became unattainable with my hand reconstruction algorithm (i'd later swap to at least one hand in AR MultiPendulum and use a form of interplay that labored without LiDAR). within the conclusion, I made a handheld AR app that could best be used on LiDAR-enabled gadgets. It became fantastic, however my most efficient purpose changed into to create a few applications for my work.

After the college project, I tackled the problem of presenting the scene in color as an alternative of as a wireframe mesh (scene color reconstruction). The uncooked 3D form of the scene mesh had no colour, now not even grayscale. To make triangles seen, I up to now had to define their edges by means of rendering the mesh as a wireframe or color triangles in line with their distance from the digital camera. My solution to this difficulty became the primary software that tracks the colour of a scene mesh in precise-time (Turner, 2021).

In April 2021, I discussed my work with a technology marketing knowledgeable who informed me to focal point on some thing less complicated and consumer-pleasant. to achieve this, I went again to the multi-pendulum simulation I made a 12 months in the past. as opposed to developing a large number of apps, I vital to demonstrate americans that a cheap AR headset journey is possible on a mobile equipment. So, I revised my fashioned purpose of creating a set of impartial apps and created one unified app built on my framework. The resulting app, AR MultiPendulum, offered a captivating instance that proven what my work delivered to AR and could capture the consideration of a larger audience.

strategyThe problem of Hand Reconstruction

youngsters I could latest my environment in VR and whole color, an immersive AR journey requires interacting with digital objects the usage of hand motions. In iOS 14, Apple brought a hand detection algorithm that scans photographs and acknowledges the 2nd position of every joint in a human hand (Peterson, 2020). This algorithm will also be repurposed to tune the user's hand actions in an AR journey, allowing them to have interaction with digital objects (like they would when donning Hololens or sensible glasses).

This algorithm turned into no longer designed for AR and consumed a enormous volume of energy. running it on every video body (60 times per 2nd) made an iPhone's processor extraordinarily heat in minutes. iOS would lower power consumption via throttling the monitor's refresh fee from 60 to 30 times per 2nd to steer clear of overheating. This broke the fluidity of the AR headset experience and improved the chance of the event inflicting nausea. To prevent iOS from throttling the refresh fee, I ran the algorithm on every sixth video frame (10 times per second). besides the fact that children doing so decreased the high-quality of hand tracking, I had arrived at a a bit achievable answer.

due to the fact that Apple's hand detection algorithm operates on a 2d photograph, it could not reconstruct a hand's 3D place or orientation. despite the fact, raw LiDAR statistics took the form of a depth photograph, which can be superimposed over the colour graphic handed into the hand tracking algorithm. After receiving second positions of the joints in the user's hand, they might then be mapped to the depth image to create 3D positions. while this answer turned into promising, the hand's illustration in the raw depth photo didn't at all times in shape the output of Apple's 2nd hand detection algorithm, so joints frequently had fallacious depths. in addition, when one part of the hand blocked an extra part from the digicam's view, depth was assigned incorrectly.

To account for the inaccuracy in joint depth, I made a heuristic that restricted the 3D joint positions to anything that appeared like a human hand. additionally, I created a mechanism to enhance the satisfactory of hand reconstruction while decreasing power consumption. with the aid of measuring optical stream (how much a picture alterations over time), it could estimate the pace at which the hand was moving. If the hand became moving slowly, the mechanism skipped updates to the hand's position to conserve energy. It may pattern as high as 20 instances per 2nd for brief periods and fall to as little as 2.5 instances per second when the hand became absent.

After creating a reasonably a success 3D hand reconstruction algorithm, i attempted the use of it to copy the adventure of the use of "The force" from celebrity Wars. I might choose and appeal to or repel digital objects through pointing my hand toward an object and opening or closing my fingers. although, this variety of interaction changed into challenging to use because the hand reconstruction changed into still now not precise. This become a significant setback in my aspiration to copy the journey of the use of Hololens or wise glasses. To provide an interactive experience on Hololens, Microsoft created superior algorithms that might music the person's hand in 3D with excessive accuracy (Immersiv.io, 2020). I had neither the time nor the expertise to create those algorithms from scratch. I decided to set aside the challenge of specific hand reconstruction and circulation on.

moving far from LiDAR

My failure to make use of hand reconstruction for exact 3D interactions made me shift my center of attention in a greater practical route. For months, I had created utility that most effective ran on LiDAR-enabled devices. If I had published an app in July 2021, it might only be accessible to americans with the newest iOS instruments. this may defeat my intention of creating AR headset experiences accessible to the general public earlier than the unlock of wise glasses.

additionally, i spotted that my present AR headset application could also enhance handheld AR experiences. Most americans with iPhones did not have Google Cardboard, so releasing an app that most effective supplied an AR headset adventure would slim the variety of individuals who may adventure my work. relocating ahead, I concentrated on designing my AR application to feature with out LiDAR-enabled elements and supply handheld experiences that complemented headset experiences. despite the fact, scene colour and hand reconstruction would nevertheless be attainable on contraptions with a constructed-in LiDAR scanner.

AR MultiPendulum

After environment myself on the appropriate route, I started rendering the multi-pendulum simulation in AR. To make the simulation's movement appear easy when relocating directly, the simulation turned into rendered at a couple of regional positions called keyframes, recorded at slightly diverse times. When the variety of keyframes become massive, the GPU (images processing unit) become overloaded with geometry, resulting in stuttering, a phenomenon where the app freezes for a fraction of a 2nd. to beat this, I made an algorithm that mixed geometry from adjacent keyframes and reduced the computational burden of rendering pendulums to keep away from stuttering.

The algorithm took up to a millisecond to function on the CPU (important processing unit). If the CPU changed into overloaded with other work, this algorithm's long execution time could cause stuttering. A CPU runs a small variety of threads (laborers that operate one computation at a time), while on a GPU, hundreds of threads run concurrently to deliver a massive amount of processing vigor. To velocity up the algorithm for combining geometry, I ran it on the GPU as an alternative of the CPU.

firstly, each and every pendulum changed into assigned to at least one thread, resulting in a small number of threads and underutilizing the GPU's processing vigour. To raise the variety of threads, every pendulum became assigned to a thread neighborhood, a small group of threads that can speak with every other. via dividing colossal computations among assorted threads, a thread group processed a pendulum more promptly than someone thread did.

while getting to know how to use thread groups, i noticed that a GPU has a SIMD (single-guideline, numerous-facts) structure, where companies of threads execute the identical operation on different pieces of statistics. I had thought that every thread on an iPhone's GPU runs independently when in actuality, organizations of 32 threads (SIMD organizations) should run the identical code. If one thread in a SIMD community does whatever thing distinctive from the others, the other 31 threads pause and watch for the first thread to finish. now not understanding this conduct resulted in inefficiencies early on when implementing scene color reconstruction, causing my code to be slow and unnecessarily complicated. So, I rewrote my GPU code for scene color reconstruction to make the highest quality use of the SIMD architecture.

I essential a holographic interface to permit clients to interact with the simulation and replicate an AR headset journey. To create that, I needed to render text in 3D, which became complicated. historically, textual content objects are rendered by referring to a bitmap (an image where pixels are either on or off). using this method in 3D pixelates the outlines of letters, creating jagged edges that can't be cleaned up with commonplace antialiasing concepts.

To resolve pixelated edges, letters' outlines need to be just a little blurred. To obtain a visually attractive variety of blurring, textual content need to be rendered the usage of a signed distance container in its place of a bitmap (Moore, 2015). I said Moore's work to generate signed distance fields, however made them more correct and generated them on the GPU in its place of the CPU.

preparing for unlock

earlier than August 2021, my app only labored on an iPhone 12 pro Max. It required the complete capabilities of the cellphone's A14 GPU, and that i had to difficult-code my iPhone's genuine measurements into code that rendered the AR headset journey. To enable my app to work on different devices, I revised my code to calculate a device's physical measurements at runtime. furthermore, I compensated for the inability of points on the GPUs found in older contraptions (i.e., variable rasterization price and vertex amplification) by way of growing two types of a number of shaders (GPU courses)—one for contraptions with or devoid of a specific capability.

apart from compatibility considerations, I confronted a few bugs with rendering pendulums when working my app on older contraptions. to beat this, I averted using thread organizations on old gadgets, which had the facet effect of creating some GPU code run greater slowly. besides the fact that children this is now not most appropriate, it provided a solution for expanding compatibility with a broader range of gadgets.

while profiling my app, I found a bottleneck within the technique of scene colour reconstruction. every time the scene mesh changed, all of its colour information was copied, which took assorted frames to comprehensive and brought about stuttering. So, I rewrote GPU code for processing colour in the surrounding scene. the brand new code managed colour records greater efficaciously and averted copying colour records after every mesh update.

next, I created a transparent holographic interface for controlling and customizing the multi-pendulum simulation. Having an interface in the AR reveal that a person can navigate through with hand motions became a vital part of my app. To handle hand manage, I arrived at a solution that makes use of the 2nd positions generated via Apple's hand reconstruction algorithm and projects them as a 3D ray that intersects with the interface. while now not based, the solution works. This interesting adventure replicates a essential part of an AR headset adventure for individuals devoid of Google Cardboard (many of the app's users).

discussion

On September 6, 2021, I launched AR MultiPendulum on the Apple App save. per week earlier than that, I posted the source code for my app to enable other utility builders to beginning building apps the usage of my work.

at the moment, the usage of my code is a tedious method as a result of a developer need to replica lots of strains of code into their app. furthermore, the copied source code will not update every time my app updates. To remedy these problems, I should create a framework that builders can use to include AR headset experiences into iOS apps. This framework, ARHeadsetKit, could be my next project.

My app at present best works on iPhones and iPads. It is not purchasable to Android users. I plan to deliver AR MultiPendulum to Android so that anyone with a smartphone can event the application.

Conclusion

The purpose of creating AR MultiPendulum was to elevate cognizance that AR headset experiences are now inexpensive to the widespread public via Google Cardboard. while my app doesn't deliver a fully authentic Hololens-esque AR experience, it allows for individuals to have interaction with virtual objects in a simulated illustration of their ecosystem and improved bear in mind what AR is in a position to. This adventure is available to any person with an iPhone 6S or later, with or devoid of Google Cardboard (but I strongly inspire all and sundry to get Google Cardboard and take a look at the wholly immersive AR MultiPendulum event).




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