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1. Matlab® programming for engineers [2020]
 Chapman, Stephen J., author.
 Sixth edition.  Boston, MA : Cengage, [2020]
 Description
 Book — xxviii, 828 pages, 8 pages of color plates : illustrations (some color) ; 24 cm
 Summary

 1. INTRODUCTION TO MATLAB. The Advantages of MATLAB. Disadvantages of MATLAB. The MATLAB Environment. Using MATLAB as a Calculator. MATLAB Script Files. Summary. Exercises.
 2. MATLAB BASICS. Variables and Arrays. Creating and Initializing Variables in MATLAB. Multidimensional Arrays. Subarrays. Special Values. Displaying Output Data. Data Files. Scalar and Array Operations. Hierarchy of Operations. Builtin MATLAB Functions. Introduction to Plotting. Examples. MATLAB Applications: Vector Mathematics. MATLAB Applications: Matrix Operations and Simultaneous Equations. Debugging MATLAB Programs. Summary. Exercises.
 3. TWODIMENSIONAL PLOTS. Additional Plotting Features for TwoDimensional Plots. Polar Plots. Annotating and Saving Plots. Additional Types of TwoDimensional Plots. Using the plot function with TwoDimensional Arrays. Plots with Two YAxes. Summary. Exercises.
 4. BRANCHING STATEMENTS AND PROGRAM DESIGN. Introduction to TopDown Design Techniques. Use of Pseudocode. The Logical Data Type. Branches. More on Debugging MATLAB Programs. Code Sections. MATLAB Applications: Roots of Polynomials. Summary. Exercises.
 5. LOOPS AND VECTORIZATION. The while Loop. The for Loop. Logical Arrays and Vectorization. The MATLAB Profiler. Additional Examples. The textread Function. MATLAB Applications: Statistical Functions. MATLAB Applications: Curve Fitting and Interpolation. Summary. Exercises.
 6. BASIC USERDEFINED FUNCTIONS. Introduction to MATLAB Functions. Variable Passing in MATLAB: The PassByValue Scheme. Optional Arguments. Sharing Data Using Global Memory. Preserving Data Between Calls to a Function. Builtin MATLAB Functions: Sorting Functions. Builtin MATLAB Functions: Random Number Functions. Summary. Exercises.
 7. ADVANCED FEATURES OF USERDEFINED FUNCTIONS. Function Functions. Function Handles. Functions eval and feval. Local Functions, Private Functions, and Nested Functions. An Example Application: Solving Ordinary Differential Equations. Anonymous Functions. Recursive Functions. Plotting Functions. Histograms. An Example Application: Numerical Integration. Summary. Exercises.
 8. COMPLEX NUMBERS AND ADDITIONAL PLOTS. Complex Data. Multidimensional Arrays. Gallery of MATLAB Plots. Line Plots. Discrete Data Plots. Polar Plots. Contour Plots. Surface and Mesh Plots. Pie Charts, Bar Plots, and Histograms. Color Order, Color Maps, and Color Bars. Summary. Exercises.
 9. ADDITIONAL DATA TYPES. Character Arrays versus Strings. Character Arrays and Character Functions. The string Data Type. Summary of Character Array and String Functions. The single Data Type. Integer Data Types. Limitations of the single and Integer Data Types. The datetime and duration Data Types. Summary. Exercises.
 10. SPARSE ARRAYS, CELL ARRAYS, STRUCTURES, AND TABLES. Sparse Arrays. Cell Arrays. Structure Arrays. Table Arrays. Summary. Exercises.
 11. INPUT/OUTPUT FUNCTIONS. The textread Function. More about the load and save Commands. An Introduction to MATLAB File Processing. File Opening and Closing. Binary I/O Functions. Formatted I/O Functions. Comparing Formatted and Binary I/O Functions. File Positioning and Status Functions. The textscan Function. Function uiimport. Summary. Exercises.
 12. USERDEFINED CLASSES AND OBJECTORIENTED PROGRAMMING. An Introduction to ObjectOriented Programming. The Structure of a MATLAB Class. Value Classes versus Handle Classes. Destructors: The delete Method. Access Methods and Access Controls. Static Methods. Defining Class Methods in Separate Files. Overriding Operators. Events and Listeners. Exceptions. Superclasses and Subclasses. Summary. Exercises.
 13. HANDLE GRAPHICS AND ANIMATION. Handle Graphics. The MATLAB Graphics System. Object Handles. Examining and Changing Object Properties. Using set to List Possible Property Values. UserDefined Data. Finding Objects. Selecting Objects with the Mouse. Position and Units. Printer Positions. Default and Factory Properties. Restoring Default Properties. Graphics Object Properties. Animations and Movies. Summary. Exercises.
 14. MATLAB APPS AND GRAPHICAL USER INTERFACES. How a Graphical User Interface Works. Creating and Displaying a Graphical User Interface. Object Properties. Additional Containers: Panels, Tab Groups, and Button Groups. Dialog Boxes. Menus. Summary. Exercises.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
Engineering Library (Terman)
Engineering Library (Terman)  Status 

Stacks  
QA297 .C418 2020  Unknown 
2. 100 questions and answers to help you land your dream iOS job : or to hire the right candidate! [2019]
 Mañas, Enrique López, author.
 [New York, New York] : Apress, [2019] New York, NY : Distributed by Springer Science+Business Media New York
 Description
 Book — 1 online resource (1 volume) : illustrations
 Summary

 Chapter 1. Get a Junior Developer Question
 1: What is a Struct in iOS? Question
 2: Explain what is a framework in iOS Question
 3: How can you store information within your iOS app? UserDefaults can be used to persist a small amount of data. Typical examples are part of the configuration required to run the application. UserDefaults can persist the primitive types in iOS (String, Data, Number, Date, Array and Dictionary) Question
 4: What is a Dictionary? Is it similar to other structures in other programming languages? Question
 5: What is a provisioning profile? Question
 6: What is ARC? Question
 7: What is an AutoLayout? Question
 8: How do you manage dependencies in iOS? Question
 9: How do you debug and profile on iOS? Question
 10: What is the difference between an 'app id' and a 'bundle id' in iOS? Question
 11: Explain how Code Signing Works? Question
 12: What is the difference between frame and bounds? Question
 13: How do you cast between types? Question
 14: Which method would you call to find an object type?Question
 15: What's the difference between #if and #ifdef? Question
 16: Tell us about iOS compilers Question
 17: How can you keep different flavours for production and development releases? Question
 18: What is the difference between viewDidLoad and viewDidAppear? Which one would you use to load data from a remote server and display it in the screen? Question
 19: How do you track bugs? What are your tools of choice? Question
 20: Explain NSUserDefaultsQuestion
 21: How do you test your code? How do you make your code testable? Question
 22: What is the difference between atomic and nonatomic properties? Which is the default for synthesized properties? When would you use one vs. the other? Question
 23: What are 'strong' and 'weak' references? Why are they important and how can they be used to help control memory management and avoid memory leaks? Question
 24: Explain your process for tracing and fixing a memory leak. Question
 25: List six instruments that are part of the standard iOS set Question
 26: How do I add resources to my app? Question
 27: What are blocks? Question
 28: How do you insert a sanity check that will be disabled in release builds? Question
 29: When is let appropriate in Swift? var?Question
 30: What is a protocol, how do you define your own and when is it used? Question
 31: What is MVC? How is it implemented in iOS? Are there any alternatives to MVC? Question
 32: What are different ways that you can specify the layout of elements in a UIView? Question
 33: What format code is used to print a formatted message with NSString?
 Chapter 2. That guy who has already been working with iOS for some time. Question
 34: How memory management is handled on iOS? Question
 35: What do you know about singletons? Where would you use one and where you wouldn't? Question
 36: How do you typically do networking? Question
 37: How would you download a JSON from a web server and serialize it and save in your local storage? Question
 38: What design patterns are you aware of in iOS and use them? Question
 39: How do you handle async tasks? Question
 40: Describe managed object context, and which kind of functionality they provide. Question
 41: Compare and contrast the different ways of achieving concurrency in OS X and iOS. Question
 42: Explain me the different background modes in iOS Question
 43: List and explain the different types of iOS Application States.Question
 44: What are the differences between copy and retain? Question
 45: What can force an object destruction with ARC? Question
 46: What happens when you invoke a method on a nil pointer? Question
 47: When it is mandatory to synthetise properties? When they are declared in protocolsQuestion
 48: What is NSAssert? Question
 49: What is a category in iOS? Question
 50: What could you use to add a new method to NSString? Question
 51: What's your preference when writing UI's? Xib files, Storyboards or programmatic UIView? Advantages with StoryboardsAdvantages with views created programmatically Question
 52: How would you securely store private user data offline on a device? What other security best practices should be taken? Question
 53: Have you ever worked with NSOperationQueue? Can you explain it? Question
 54: How would you serialize an array to disk? Question
 55: How does instancetype work and how is it useful? Question
 56: What means the term reflection? Question
 57: What are layer objects and what do they represent? Question
 58: In Swift enumerations, what's the difference between raw values and associated values? Question
 59: Explain what does @synthesize do Question
 60: Mention what are the collection types available in Swift? Question
 61: What is a custom operator in swift? Question
 62: Any issues you are aware of working with blocks? Question
 63: What is an iOS extension? Question
 64: Explain application sandboxingQuestion
 65: How do you develop applications for iPad and iPhone? Question
 66: Explain me the different background modes in iOS
 Chapter 3. We need that guy on board, we want to do great things! Question
 67: Could you explain what is the difference between Delegate and KVO? Question
 68: Explain method swizzling. When you would use it? Question
 69: Take three objects: a grandparent, parent and child. The grandparent retains the parent, the parent retains the child and the child retains the parent. The grandparent releases the parent. Explain what happens. Question
 70: Give two separate and independent reasons why retainCount should never be used in shipping code. Question
 71: Explain how an autorelease pool works at the runtime level.Question
 72: Which is faster: to iterate through an NSArray or an NSSet? Question
 73: Which is faster: to iterate through an NSArray or an NSSet? Question
 74: Do you have to implement all the declarations from an adopted protocol? Question
 75: What is a shortcut for calling alloc and init? Originally in ObjectiveC, objects were created with new. As the OpenStep/Cocoa framework evolved, the designers developed the opinion that allocating the memory for an object and initializing its attributes were separate concerns and thus should be separate methods (for example, an object might be allocated in a specific memory zone). So the allocinit style of object creation came into favor. Basically, new is old and almostbutnotquite deprecated
 thus you'll see that Cocoa classes have a lot of init methods but almost never any custom new methods. Question
 76: What kind of pointer can help to safely avoid a memory leak? Question
 77: What can help to prevent an out of memory crash If you have a long running execution loop? Question
 78: What considerations do you need when writing a UITableViewController which shows images downloaded from a remote server? Question
 79: What is KVC and KVO? Give an example of using KVC to set a value.Question
 80: What mechanisms does iOS provide to support multithreading? Question
 81: What is the Responder Chain?Question
 82: What's the difference between using a delegate and notification? Question
 83: How would you securely store private user data offline on a device? What other security best practices should be taken? Question
 84: Are SQL injection attacks valid in iOS? How would you prevent them? Question
 85: What are the common reasons for app rejections in the Store? Question
 86: How can you make a code snippet thread safe? Question
 87: Why should we release the outlets in viewDidUnload? Question
 88: What is the difference between a shallow copy and a deep copy? Question
 89: How would you pass an unknown type as a parameter? Question
 90: What is deinitializer and how it is written in Swift? Question
 91: Explain what is optional chaining Question
 92: What is the Fallthrough statement? What does it do?Question
 93: Explain what Lazy stored properties is and when it is useful?QuestionHave you heard of Handoff? Question
 95: Can you have more UIWindows in iOS? Question
 96: What is Metal?Question
 97: Can you come up with strategies to increase efficiency in your networking?Question
 98: Tell me the most complex problem you had to solve at your previous work Question
 99: What is autorealease pool? Question
 100: Outline the class hierarchy for a UIButton until NSObject. Can I Ask you for a favor?.
 Garcia, Stephan Ramon, author.
 Providence, Rhode Island : American Mathematical Society, [2019]
 Description
 Book — xiii, 581 pages ; 26 cm
 Summary

 1913. Paul Erdos
 1914. Martin Gardner
 1915. General relativity and the absolute differential calculus
 1916. Ostrowski's theorem
 1917. Morse theory, but really Cantor
 1918. Georg Cantor
 1919. Brun's theorem
 1920. Waring's problem
 1921. Mordell's theorem
 1922. Lindeberg condition
 1923. The circle method
 1924. The BanachTarski paradox
 1925. The Schrodinger equation
 1926. Ackermann's function
 1927. William Lowell Putnam Mathematical Competition
 1928. Random matrix theory
 1929. Godel's incompleteness theorems
 1930. Ramsey theory
 1931. The ergodic theorem
 1932. The $3x+1$ problem
 1933. Skewes's number
 1934. Khinchin's constant
 1935. Hilbert's seventh problem
 1936. Alan Turing
 1937. Vinogradov's theorem
 1938. Benford's law
 1939. The power of positive thinking
 1940. A mathematician's apology
 1941. The Foundation triology
 1942. Zeros of $\zeta(s)$
 1943. Breaking Enigma
 1944. Theory of games and economic behavior
 1945. The Riemann hypothesis in function fields
 1946. Monte Carlo method
 1947. The simplex method
 1948. Elementary proof of the prime number theorem
 1949. Beurling's theorem
 1950. Arrow's impossibility theorem
 1951. Tennenbaum's proof of the irrationality of $\sqrt{2}$
 1952. NSA founded
 1953. The Metropolis algorithm
 1954. KolmogorovArnoldMoser theorem
 1955. Roth's theorem
 1956. The GAGA principle
 1957. The Ross program
 1958. Smale's paradox
 1959. $QR$ decomposition
 1960. The unreasonable effectiveness of mathematics
 1961. Lorenz's nonperiodic flow
 1962. The GaleShapely algorithm and the stable marriage problem
 1963. Continuum hypothesis
 1964. Principles of mathematical analayis
 1965. Fast Fourier transform
 1966. Class number one problem
 1967. The Langlands program
 1968. AtiyahSinger index theorem
 1969. Erdos numbers
 1970. Hilbert's tenth problem
 1971. Society for American Baseball Research
 1972. Zaremba's conjecture
 1973. Transcendence of $e$ centennial
 1974. Rubik's Cube
 1975. Szemeredi's theorem
 1976. Four color theorem
 1977. RSA encryption
 1978. Mandlebrot set
 1979. TeX
 1980. Hilbert's third problem
 1981. The MasonStothers theorem
 1982. Two envelopes problem
 1983. Julia Robinson
 1984.
 1984
 1985. The Jones polynomial
 1986. Sudokus and Look and Say
 1987. Primes, the zeta function, randomness, and physics
 1988. Mathematica
 1989. PROMYS
 1990. The Monty Hall problem
 1991. arXiv
 1992. Monstrous moonshine
 1993. The 15theorem
 1994. AIM
 1995. Fermat's last theorem
 1996. Great Internet Mersenne Prime Search (GIMPS)
 1997. The Nobel Prize of Merton and Scholes
 1998. The Kepler conjecture
 1999. Baire category theorem
 2000. R
 2001. Colin Hughes founds Project Euler
 2002. PRIMES in P
 2003. Poincare conjecture
 2004. Primes in arithmetic progression
 2005. William Stein developed Sage
 2006. The strong perfect graph theorem
 2007. Flatland
 2008. 100th anniversary of the $t$test
 2009. 100th anniversary of Brouwer's fixedpoint theorem
 2010. Carmichael numbers
 2011. 100th anniversary of Egorov's theorem
 2012. National Museum of Mathematics Index of people Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
SAL3 (offcampus storage)
SAL3 (offcampus storage)  Status 

In process  Request 
QA27 .U5 G37 2019  Unavailable In transit 
4. 2017 MATRIX Annals [2019]
 Cham, Switzerland : Springer, [2019]
 Description
 Book — 1 online resource Digital: text file; PDF.
 Summary

 Intro; Preface; Hypergeometric Motives and CalabiYau Differential Equations; Computational Inverse Problems; Integrability in LowDimensional Quantum Systems; Elliptic Partial Differential Equations of Second Order: Celebrating
 40 Years of Gilbarg and Trudinger's Book; Combinatorics, Statistical Mechanics, and Conformal Field Theory; Mathematics of Risk; Tutte Centenary Retreat; Geometric RMatrices: From Geometry to Probability; Contents; Part I Refereed Articles; A MetropolisHastingsWithinGibbs Sampler for Nonlinear HierarchicalBayesian Inverse Problems;
 1 Introduction
 2 The RandomizeThenOptimize Proposal Density3 RTOMetropolisHastings and Its Embedding Within Hiererichical Gibbs; 3.1 RTOMHWithinHierarchical Gibbs;
 4 Numerical Experiment;
 5 Conclusions; References; Sequential Bayesian Inference for Dynamical Systems Using the Finite Volume Method;
 1 Introduction; 1.1 A Stylized Problem;
 2 Sequential Bayesian Inference for Dynamical Systems; 2.1 The FrobeniusPerron Operator is a PDE;
 3 Finite Volume Solver;
 4 ContinuousTime FrobeniusPerron Operator and Convergence of the FVM Approximation;
 5 Computed Examples
 5.1 FVF Tracking of a Pendulum from Measured Force6 Conclusions; References; Correlation Integral Likelihood for Stochastic Differential Equations;
 1 Introduction;
 2 Background; 2.1 Likelihood via Filtering; 2.2 Correlation Integral Likelihood;
 3 Numerical Experiments; 3.1 OrnsteinUhlenbeck with Modification for Dynamics; 3.2 Stochastic Chaos;
 4 Conclusions; References; A Set Optimization Technique for Domain Reconstruction from SingleMeasurement Electrical Impedance Tomography Data;
 1 Introduction;
 2 The Convex Source Support in Electrical Impedance Tomography
 3 An Optimization Problem in Kc(Rd)4 Galerkin Approximations to Kc(R2);
 5 Gradients of Functions on GA;
 6 A First Numerical Simulation; References; Local Volatility Calibration by Optimal Transport;
 1 Introduction;
 2 Optimal Transport;
 3 Formulation; 3.1 The Martingale Problem; 3.2 Augmented Lagrangian Approach;
 4 Numerical Method;
 5 Numerical Results;
 6 Summary; References; Likelihood Informed Dimension Reduction for Remote Sensing of Atmospheric Constituent Profiles;
 1 Introduction;
 2 Methodology; 2.1 Bayesian Formulation of the Inverse Problem; 2.2 Prior Reduction
 2.3 LikelihoodInformed Subspace3 Results;
 4 Conclusions; References; Wider Contours and Adaptive Contours;
 1 Introduction;
 2 Three Fundamental Models; 2.1 Monomolecular, Bimolecular and Trimolecular Models;
 3 Pseudospectra Are Important for Stochastic Processes;
 4 A MittagLeffler Stochastic Simulation Algorithm;
 5 Computing a MittagLeffler Matrix Function; 5.1 Computing Contour Integrals; 5.2 Estimating the Field of Values;
 6 Conclusion; References; Bayesian Point Set Registration;
 1 Introduction;
 2 Problem Statement and Statistical Model; 2.1 Bayesian Formulation
(source: Nielsen Book Data)
 International Conference on Software Testing, Verification, and Validation (12th : 2019 : Xi'an Shi, China)
 Los Alamitos, California : IEEE Computer Society, Conference Publishing Services, [2019]
 Description
 Book — 1 online resource (xxv, 502 pages) : illustrations (some color) Digital: text file.
 International Conference on Big Data and Smart Computing (6th : 2019 : Kyoto, Japan)
 Piscataway, NJ : IEEE, [2019]
 Description
 Book — 1 online resource (various pagings) : illustrations (some color) Digital: text file.
 IEEE Conference on Cognitive and Computational Aspects of Situation Management (9th : 2019 : Las Vegas, Nev.)
 [Piscataway, New Jersey] : IEEE, [2019]
 Description
 Book — 1 online resource (various pagings) : illustrations (some color) Digital: text file.
 IEEE International Symposium on Performance Analysis of Systems and Software (2019 : Madison, Wis.)
 Los Alamitos, California : IEEE Computer Society, Conference Publishing Services, [2019]
 Description
 Book — 1 online resource (xiii, 318 pages) : illustrations (some color) Digital: text file.
 IEEE International Conference on Big Data Analysis (4th : 2019 : Suzhou, Jiangsu Sheng, China)
 [Piscataway, New Jersey] : Institute of Electrical and Electronics Engineering, Inc., [2019]
 Description
 Book — 1 online resource (various pagings) : illustrations (some color) Digital: text file.
 Assam, Lee, speaker.
 [Place of publication not identified] : Packt Publishing, 2019.
 Description
 Video — 1 online resource (1 streaming video file (4 hr., 30 min., 53 sec.)) : digital, sound, color
 Summary

"Master the Raspberry Pi 3! Work with Python, GPIO pins and sensors, and the Pi Camera Module, and build an Amazon Echo Clone! This course will provide the information you need to master the Raspberry Pi 3! It assumes no prior programming or electronics knowledge and walks you through everything you need to know to use the platform to the fullest!"Resource description page.
 Elumalai, Aarthi, speaker.
 [Place of publication not identified] : Packt Publishing, 2019.
 Description
 Video — 1 online resource (1 streaming video file (5 hr., 22 min., 14 sec.)) : digital, sound, color
 Summary

"Practice makes perfect. Start your journey into becoming a professional front end web developer here! At DigiFisk, we like making learning fun. Our courses are interactive and fun with a ton of practical elements to it. We've decided to take it a step further with our Web app development practice series. Once you learn the syntax of a programming language, the next logical step is to start creating software and apps. But that's where most students get stuck. Problemsolving isn't as easy as learning a bunch of syntaxes. But we aim to make it easy for you. The course is structured in such a way that each section will handle one of the 3 languages covered here."Resource description page.
 Elumalai, Aarthi, speaker.
 [Place of publication not identified] : Packt Publishing, 2019.
 Description
 Video — 1 online resource (1 streaming video file (7 hr., 43 min., 54 sec.)) : digital, sound, color
 Summary

"In this course, you'll learn how to build a randomized, dynamic 2D memory game with a timer, scorecard, and a customized result display from the ground up with just HTML5, JavaScript, and CSSS and using 2D game development concepts—all in just a couple of hours. In this course you will learn how to build a completely randomized, intelligent 2D memory game with stellar design with JavaScript, HTML5, and CSS3; how to design game logic for games and implement it as code; how to make the game intelligent and interesting by introducing a randomization element into it and making it unpredictable even for the programmer; how to set up the skeleton of a web app or web game using HTML5; how to design a sophisticated 2D game using advanced CSS and CSS3 concepts; how to make a 2D game playable using JavaScript concepts; how to build a fully featured timer for your game; how to make CSS3 card flipping work using CSS3 transitions and CSS3 transformations. Logical problem solving; how to create completely customized popup boxes (you can use this knowledge in a number of other projects as well); how to build a score display for your game that dynamically updates itself. How 2D game development works on the web (with JavaScript and HTML5); the basics of HTML5 & CSS3 … The basics of JavaScript; frontend design and development."Resource description page.
13. 2nd International Conference on Applied Mathematics, ICAM'2018 : 2627 October 2018, Fez, Morocco [2019]
 International Conference on Applied Mathematics (2nd : 2018 : Fez, Morocco)
 [Melville, New York] : AIP Publishing LLC, 2019.
 Description
 Book — 1 online resource : illustrations (some color). Digital: text file.
 Konczyk, Jakub, speaker.
 [Place of publication not identified] : Packt, [2019]
 Description
 Video — 1 online resource (1 streaming video file (55 min., 33 sec.)) : digital, sound, color
 Summary

"TensorSpace is a neural network 3D visualization framework built by TensorFlow.js, Three.js, and Tween.js. TensorSpace provides Keraslike APIs to build deep learning layers, load pretrained models, and generate a 3D visualization in the browser. By applying TensorSpace API, it is more intuitive for Data Scientists to visualize and understand any pretrained models built by TensorFlow, Keras, TensorFlow.js, and so on. In this quick and short course, you’ll learn how to present the inner workings of your pretrained Neural Network models with easytoaccess 3D visualizations in a web browser. By the end of this course, you’ll be able to create compelling 3D visualizations that will show the neural network architecture and how pretrained models work in real time with TensorSpace."Resource description page.
 Smith, Margaret Schwan, author.
 Thousand Oaks, California : Corwin : National Council of Teachers of Mathematics, [2019]
 Description
 Book — xxix, 194 pages : color illustrations ; 26 cm
 Summary

 Setting goals and selecting tasks
 Anticipating student responses
 Monitoring student work
 Selecting and sequencing student solutions
 Connecting student solutions
 Looking back and looking ahead.
 Online
Education Library (Cubberley)
Education Library (Cubberley)  Status 

Stacks  
QA135.6 .S56518 2019  Unknown 
 Lucas, Michael W. (Michael Warren), 1967 author.
 3rd edition.  San Francisco : No Starch Press, [2019]
 Description
 Book — 1 online resource (1 volume)
17. Abstract recursion and intrinsic complexity [2019]
 Moschovakis, Yiannis N., author.
 Cambridge : Cambridge University Press, 2019.
 Description
 Book — 1 online resource (vii, 243 pages) : digital, PDF file(s).
 Summary

 Introduction
 1. Preliminaries Part I. Abstract (First Order) Recursion:
 2. Recursive (McCarthy) programs
 3. Complexity theory for recursive programs Part II. Intrinsic Complexity:
 4. The homomorphism method
 5. Lower bounds from Presburger primitives
 6. Lower bounds from division with remainder
 7. Lower bounds from division and multiplication
 8. Nonuniform complexity in N
 9. Polynomial nullity (0testing) References Symbol index General index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
18. Accelerate deep learning on Raspberry Pi [2019]
 Benke, Laszlo, speaker.
 [Place of publication not identified] : Packt Publishing, 2019.
 Description
 Video — 1 online resource (1 streaming video file (1 hr., 17 min., 32 sec.)) : digital, sound, color
 Summary

"Learn how we implemented deep learning object detection models on Raspberry Pi and accelerated them with Intel Movidius Neural Compute Stick. When we first got started in deep learning particularly in computer vision, we were really excited at the possibilities of this technology to help people. The only problem is, that image classification and object detection run just fine on our expensive, power consuming and bulky deep learning machines. However, not everyone can afford or implement AI for their practical applications. This is when we went searching for an affordable, compact, less power hungry alternative. Generally, if we'd want to shrink our IoT and automation projects, we'd often look to the Raspberry Pi which is a versatile computing solution for numerous problems. This made us ponder about how we can port out deep learning models to this compact computing unit. Not only that but how could we run it at close to realtime? Amongst the possible solutions, we arrived at using the raspberry pi in conjunction with an AI Accelerator USB stick that was made by Intel to boost our object detection framerate. However, it was not so simple to get it up and running. Implementing the documentation, we landed up with a series of bugs after bugs, which became a bit tedious. After endless posts on forums, tutorials and blogs, we have documented a seamless guide in the form of this course; which will show you, stepbystep, on how to implement your own Deep Learning Object Detection models on video and webcam without all the wasteful debugging. So essentially, we've structured this training to reduce debugging, speed up your time to market and get you results sooner."Resource description page.
19. Access 2019 advanced [2019]
 McCrae, Edward, onscreen presenter.
 [Place of publication not identified] : Intellezy, 2019.
 Description
 Video — 1 online resource (1 streaming video file (1 hr., 24 min., 23 sec.)) : digital, sound, color
 Summary

"Access 2019 Advanced will further build upon the topics covered in the Access 2019 Introduction and Intermediate courses. Students will review how to improve the structure of an Access database, maintain an Access database, create backups, create and modify Navigation Forms, set startup options, split a database, configure security and multiuser environments, automate processes with VBA (Visual Basic for Applications), convert macros to VBA, and use Table Events."Resource description page.
20. Access 2019 beginner [2019]
 [Place of publication not identified] : Intellezy, 2019.
 Description
 Video — 1 online resource (1 streaming video file (4 hr., 27 min., 27 sec.)) : digital, sound, color
 Summary

"This course is an introduction to Microsoft Access 2019. In this course, students will become familiar with various database components, concepts, and terminology. Students will tour the user interface, create databases, create objects, perform calculations, navigate and work with tables, understand and work with queries, review and work with various reports and reporting features, and review forms and the various tools that go along with them. This course will give the student the required knowledge to complete the Access 2019 Intermediate course."Resource description page.