The document discusses standard input and output in programming. It explains that standard input comes from keyboard input while standard output displays on the screen. It then covers different methods for file input/output like fopen, fstream, freopen, and their performance. The document concludes with recommendations to use buffered reading/writing techniques like fgets/puts for better performance compared to scanf/printf.
The document discusses the history and evolution of testing in Perl from its early days in the 1980s to modern techniques. It covers key topics like the development of Test Anything Protocol (TAP), important testing modules like Test::More, Test::Simple, and tools for testing documentation, code quality, and more. Various commands for running tests are also presented.
The analyzer detected over 40 bugs in the OpenToonz source code related to memory management, pointer usage, string handling and exception handling. Specifically, it found issues like dynamic memory being allocated with new and freed with delete, pointers being dereferenced before being checked for null, function return values being ignored and exceptions being caught by value instead of reference. Addressing these issues would improve the quality and robustness of the code.
The document describes the closest pair problem and an algorithm to solve it in 3 steps:
1. Sort the points by their x-coordinates
2. Recursively divide the points into halves and solve the sub-problems
3. Merge the solutions of the sub-problems and consider additional point pairs near the dividing line to find the overall minimum distance.
Presentation by Haroon Meer and Marco Slaviero at BlackHat USA in 2007.
This presentation is about timing attacks against web applications. Squeeza, a SQLi tool developed by Marco Slaviero that returns data through various channels (dns,timing,http error messages) is introduced. An attack called Cross site request timing is also discussed.
Down the rabbit hole, profiling in DjangoRemco Wendt
The document discusses various tools for profiling Python code such as cProfile, profile, hotshot, line profiler, and trace to identify inefficient code and bottlenecks. It covers using these tools to profile CPU and I/O bound problems as well as memory profiling issues. The document also demonstrates how to optimize code through caching, removing unnecessary function calls, and memoization.
The document provides an overview of basic penetration testing techniques including buffer overflow vulnerabilities, return oriented programming (ROP), format string vulnerabilities, and ways to bypass data execution prevention (DEP) and address space layout randomization (ASLR). It discusses stack-based buffer overflows, the structure of the x86 stack, overwriting the return address, and controlling the instruction pointer. It also covers ROP techniques like ret2libc, gadgets, chaining, and using libc functions. Finally, it briefly mentions tools like pwntools, ROPgadget, and techniques like IO wrapping and LD_PRELOAD hijacking.
Pygrunn 2012 down the rabbit - profiling in pythonRemco Wendt
The document discusses various tools for profiling Python code such as cProfile, profile, hotshot, line profiler, and trace to identify inefficient code and potential bottlenecks. It also covers memory profiling tools like Heapy and Meliae. Effective profiling requires understanding different profiling techniques, tools, and how to analyze the output to optimize performance and memory usage.
Columnar processing for SQL-on-Hadoop: The best is yet to comeWang Zuo
Apache Parquet is an open-source file-format which arranges all of its data into columns – this is distinct from the traditional row-oriented layout, which stores entire rows consecutively. Columnar data offers lots of advantages to modern data engines – like Impala, Apache Spark, and Apache Flink – in terms of IO efficiency, but the full benefits of the format are yet to be realized.
We have been working with Intel to apply modern CPU instruction sets to the common programming tasks associated with querying data in Parquet format: decompression, predicate evaluation, and row-reconstruction. Our work has yielded significant speedups in standard query benchmarks running on Cloudera’s Impala SQL query engine, and very high speedups in targeted microbenchmarks.
In this talk we’ll describe the symbiosis between modern CPU architectures and the requirements of columnar data processing. We’ll show how vectorization – processing many items with a single instruction – is a widely applicable technique that can provide real performance benefits to all application frameworks that use columnar formats. We’ll present the changes that we have made to Impala’s ‘scanner,’ which reads Parquet data, and map out even more future enhancements.
This talk will be of interest to audiences interested in the internals of big data processing engines, or the impact of recent advances in modern CPU architectures.
The document discusses the history and evolution of testing in Perl from its early days in the 1980s to modern techniques. It covers key topics like the development of Test Anything Protocol (TAP), important testing modules like Test::More, Test::Simple, and tools for testing documentation, code quality, and more. Various commands for running tests are also presented.
The analyzer detected over 40 bugs in the OpenToonz source code related to memory management, pointer usage, string handling and exception handling. Specifically, it found issues like dynamic memory being allocated with new and freed with delete, pointers being dereferenced before being checked for null, function return values being ignored and exceptions being caught by value instead of reference. Addressing these issues would improve the quality and robustness of the code.
The document describes the closest pair problem and an algorithm to solve it in 3 steps:
1. Sort the points by their x-coordinates
2. Recursively divide the points into halves and solve the sub-problems
3. Merge the solutions of the sub-problems and consider additional point pairs near the dividing line to find the overall minimum distance.
Presentation by Haroon Meer and Marco Slaviero at BlackHat USA in 2007.
This presentation is about timing attacks against web applications. Squeeza, a SQLi tool developed by Marco Slaviero that returns data through various channels (dns,timing,http error messages) is introduced. An attack called Cross site request timing is also discussed.
Down the rabbit hole, profiling in DjangoRemco Wendt
The document discusses various tools for profiling Python code such as cProfile, profile, hotshot, line profiler, and trace to identify inefficient code and bottlenecks. It covers using these tools to profile CPU and I/O bound problems as well as memory profiling issues. The document also demonstrates how to optimize code through caching, removing unnecessary function calls, and memoization.
The document provides an overview of basic penetration testing techniques including buffer overflow vulnerabilities, return oriented programming (ROP), format string vulnerabilities, and ways to bypass data execution prevention (DEP) and address space layout randomization (ASLR). It discusses stack-based buffer overflows, the structure of the x86 stack, overwriting the return address, and controlling the instruction pointer. It also covers ROP techniques like ret2libc, gadgets, chaining, and using libc functions. Finally, it briefly mentions tools like pwntools, ROPgadget, and techniques like IO wrapping and LD_PRELOAD hijacking.
Pygrunn 2012 down the rabbit - profiling in pythonRemco Wendt
The document discusses various tools for profiling Python code such as cProfile, profile, hotshot, line profiler, and trace to identify inefficient code and potential bottlenecks. It also covers memory profiling tools like Heapy and Meliae. Effective profiling requires understanding different profiling techniques, tools, and how to analyze the output to optimize performance and memory usage.
Columnar processing for SQL-on-Hadoop: The best is yet to comeWang Zuo
Apache Parquet is an open-source file-format which arranges all of its data into columns – this is distinct from the traditional row-oriented layout, which stores entire rows consecutively. Columnar data offers lots of advantages to modern data engines – like Impala, Apache Spark, and Apache Flink – in terms of IO efficiency, but the full benefits of the format are yet to be realized.
We have been working with Intel to apply modern CPU instruction sets to the common programming tasks associated with querying data in Parquet format: decompression, predicate evaluation, and row-reconstruction. Our work has yielded significant speedups in standard query benchmarks running on Cloudera’s Impala SQL query engine, and very high speedups in targeted microbenchmarks.
In this talk we’ll describe the symbiosis between modern CPU architectures and the requirements of columnar data processing. We’ll show how vectorization – processing many items with a single instruction – is a widely applicable technique that can provide real performance benefits to all application frameworks that use columnar formats. We’ll present the changes that we have made to Impala’s ‘scanner,’ which reads Parquet data, and map out even more future enhancements.
This talk will be of interest to audiences interested in the internals of big data processing engines, or the impact of recent advances in modern CPU architectures.
Python 3.6 includes several new features and improvements related to asynchronous programming and language syntax. PEP 525 introduces asynchronous generators to allow async and await in generator functions. PEP 530 adds asynchronous comprehensions for concise creation of asynchronous iterators. Other PEPs improve class attribute definition order preservation, string formatting syntax, and the addition of asynchronous APIs to the standard library. Python 3.6 continues Python's progress towards native asynchronous programming capabilities.
Fragmentation manifests itself in virtual storage systems in the following ways:
1. In segmentation, unused memory segments cause internal fragmentation as the space within segments may not be contiguous or aligned.
2. In paging, unused pages cause internal fragmentation. Additionally, pages may become scattered across disk causing external fragmentation.
3. In combined segmentation and paging, both internal fragmentation from unused segments and pages can occur along with external fragmentation from scattered pages on disk.
The Ring programming language version 1.5.4 book - Part 25 of 185Mahmoud Samir Fayed
This document describes various file handling functions in Ring programming language including Read(), Write(), Dir(), Rename(), Remove(), Fopen(), Fclose(), Fflush(), Freopen(), Tempfile(), Tempname(), Fseek(), Ftell(), and provides examples of how to use each function to read, write, modify and get information about files. It also covers opening and closing files, seeking to different positions in a file, generating temporary file names and more.
The Ring programming language version 1.9 book - Part 32 of 210Mahmoud Samir Fayed
The document describes various file handling functions in Ring including Read(), Write(), Dir(), Rename(), Remove(), fopen(), fclose(), fflush(), freopen(), tempfile(), tempname(), fseek(), ftell(), rewind(), fgetpos(), fsetpos(), clearerr(), feof(), ferror(), perror(), fgetc(), fgets(), fputc(), fputs(), ungetc(), fread(), fwrite(), fexists(), and how to use numbers and bytes. It provides examples of using these functions to read and write files, get directory listings, open/close files, seek within files, and more.
This document summarizes an advanced Python programming course, covering topics like performance tuning, garbage collection, and extending Python. It discusses profiling Python code to find bottlenecks, using more efficient algorithms and data structures, optimizing code through techniques like reducing temporary objects and inline functions, leveraging faster tools like NumPy, writing extension modules in C, and parallelizing computation across CPUs and clusters. It also explains basic garbage collection algorithms like reference counting and mark-and-sweep used in CPython.
Golang Performance : microbenchmarks, profilers, and a war storyAerospike
Slides for Brian Bulkowski's talk about Golang performance:
microbenchmarks, profilers, and a war story about optimizing the Aerospike Database Go client.
http://www.meetup.com/Go-lang-Developers-NYC/events/216650022/
Beyond PHP - it's not (just) about the codeWim Godden
Most PHP developers focus on writing code. But creating Web applications is about much more than just writing PHP. Take a step outside the PHP cocoon and into the big PHP ecosphere to find out how small code changes can make a world of difference on servers and network. This talk is an eye-opener for developers who spend over 80% of their time coding, debugging and testing.
( ** Python Certification Training: https://www.edureka.co/python ** )
This Edureka PPT on Advanced Python tutorial covers all the important aspects of using Python for advanced use-cases and purposes. It establishes all of the concepts like system programming , shell programming, pipes and forking to show how wide of a spectrum Python offers to the developers.
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Writing concurrent program is hard; maintaining concurrent program even is a nightmare. Actually, a pattern which helps us to write good concurrent code is available, that is, using “channels” to communicate.
This talk will share the channel concept with common libraries, like threading and multiprocessing, to make concurrent code elegant.
It's the talk at PyCon TW 2017 [1] and PyCon APAC/MY 2017 [2].
[1]: https://tw.pycon.org/2017
[2]: https://pycon.my/pycon-apac-2017-program-schedule/
Gotcha! Ruby things that will come back to bite you.David Tollmyr
The document discusses various performance optimizations for JRuby applications. It covers techniques like avoiding unnecessary string creation, using java.util.concurrent utilities for concurrency instead of Ruby's Mutex, and avoiding shelling out from JRuby when possible. The author also shares lessons learned around array joins, queue implementations, and passing binary strings between Ruby and Java.
Performance tweaks and tools for Linux (Joe Damato)Ontico
The document discusses various Linux performance analysis tools including lsof to list open files, strace to trace system calls, tcpdump to dump network traffic, perftools from Google for profiling CPU usage, and a Ruby library called perftools.rb for profiling Ruby code. Examples are provided for using these tools to analyze memory usage, slow queries, Ruby interpreter signals, thread scheduling overhead, and identifying hot spots in Ruby web applications.
Winnyp is an anonymous P2P filesharing software based on Winny. It uses its own encryption key generation algorithm that is more complex than Winny's algorithm, making it more difficult to analyze. The report details Winnyp's internal workings, including how it initializes and patches itself, generates encryption keys through multiple algorithms, and specifies the version of connected nodes by using different encryption keys. It also describes how Winnyp sends packets with dummy data and receives packets to communicate with both Winny and other Winnyp nodes.
The Ring programming language version 1.5.3 book - Part 89 of 184Mahmoud Samir Fayed
The document describes embedding Ring code in Ring programs without sharing state. It allows quick integration of Ring programs and applications together without conflicts by executing Ring code in isolated environments. Functions like ring_state_init(), ring_state_runcode(), and ring_state_delete() are used to initialize a state, run code in it, and delete it. This prevents variables from one state being accessible from another. Serial execution of Ring applications is also demonstrated using ring_state_main().
This document provides an overview of Python fundamentals including basic concepts like data types, operators, flow control, functions and classes. It begins with an introduction to Python versions and environments. The outline covers topics like Hello World, common types and operators for numeric, string and container data types. It also discusses flow control structures like if/else, while loops and for loops. Finally, it briefly mentions functions, classes, exceptions and file I/O.
Swift.berlin, this time kindly hosted by Wooga, invited Crispy's own Christian Weyer to speak about whether Apple's new programming language Swift is ready for primetime use in corporate, production environments. In order to answer that question, Christian ported an existing OS X application to Swift and created a new iOS application from scratch. Watch the video to see his results and the conclusions he drew from these experiences.
Video available at https://vimeo.com/113089291
This document provides an introduction to Python programming including installation, basic syntax, data types, control flow, modules, sockets, structs, pwntools, vulnerabilities, practice problems, and references for further learning. It covers topics such as printing, taking input, lists, arithmetic, conditional statements, loops, functions, importing modules, sending/receiving data over sockets, packing/unpacking integers, using pwntools, and exploiting vulnerabilities like pickle injection. Example code is provided throughout to demonstrate the concepts.
Rust is a systems programming language that provides memory safety without using a garbage collector. It achieves memory safety through rules of ownership, borrowing, and lifetimes that are checked at compile time. These rules prevent common memory bugs like memory leaks, dangling pointers, and use-after-free errors that are common in C and C++.
The document discusses rendering dropdown menus in the content process. It notes there are performance, styling, and event behavior issues with the current e10s-select approach. An alternative approach called content-select would render the dropdown as normal content in the content process to achieve better performance, stronger style support, and more accurate events without these issues. It provides an example of complex styling that can be applied to options in the dropdown.
Python 3.6 includes several new features and improvements related to asynchronous programming and language syntax. PEP 525 introduces asynchronous generators to allow async and await in generator functions. PEP 530 adds asynchronous comprehensions for concise creation of asynchronous iterators. Other PEPs improve class attribute definition order preservation, string formatting syntax, and the addition of asynchronous APIs to the standard library. Python 3.6 continues Python's progress towards native asynchronous programming capabilities.
Fragmentation manifests itself in virtual storage systems in the following ways:
1. In segmentation, unused memory segments cause internal fragmentation as the space within segments may not be contiguous or aligned.
2. In paging, unused pages cause internal fragmentation. Additionally, pages may become scattered across disk causing external fragmentation.
3. In combined segmentation and paging, both internal fragmentation from unused segments and pages can occur along with external fragmentation from scattered pages on disk.
The Ring programming language version 1.5.4 book - Part 25 of 185Mahmoud Samir Fayed
This document describes various file handling functions in Ring programming language including Read(), Write(), Dir(), Rename(), Remove(), Fopen(), Fclose(), Fflush(), Freopen(), Tempfile(), Tempname(), Fseek(), Ftell(), and provides examples of how to use each function to read, write, modify and get information about files. It also covers opening and closing files, seeking to different positions in a file, generating temporary file names and more.
The Ring programming language version 1.9 book - Part 32 of 210Mahmoud Samir Fayed
The document describes various file handling functions in Ring including Read(), Write(), Dir(), Rename(), Remove(), fopen(), fclose(), fflush(), freopen(), tempfile(), tempname(), fseek(), ftell(), rewind(), fgetpos(), fsetpos(), clearerr(), feof(), ferror(), perror(), fgetc(), fgets(), fputc(), fputs(), ungetc(), fread(), fwrite(), fexists(), and how to use numbers and bytes. It provides examples of using these functions to read and write files, get directory listings, open/close files, seek within files, and more.
This document summarizes an advanced Python programming course, covering topics like performance tuning, garbage collection, and extending Python. It discusses profiling Python code to find bottlenecks, using more efficient algorithms and data structures, optimizing code through techniques like reducing temporary objects and inline functions, leveraging faster tools like NumPy, writing extension modules in C, and parallelizing computation across CPUs and clusters. It also explains basic garbage collection algorithms like reference counting and mark-and-sweep used in CPython.
Golang Performance : microbenchmarks, profilers, and a war storyAerospike
Slides for Brian Bulkowski's talk about Golang performance:
microbenchmarks, profilers, and a war story about optimizing the Aerospike Database Go client.
http://www.meetup.com/Go-lang-Developers-NYC/events/216650022/
Beyond PHP - it's not (just) about the codeWim Godden
Most PHP developers focus on writing code. But creating Web applications is about much more than just writing PHP. Take a step outside the PHP cocoon and into the big PHP ecosphere to find out how small code changes can make a world of difference on servers and network. This talk is an eye-opener for developers who spend over 80% of their time coding, debugging and testing.
( ** Python Certification Training: https://www.edureka.co/python ** )
This Edureka PPT on Advanced Python tutorial covers all the important aspects of using Python for advanced use-cases and purposes. It establishes all of the concepts like system programming , shell programming, pipes and forking to show how wide of a spectrum Python offers to the developers.
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Writing concurrent program is hard; maintaining concurrent program even is a nightmare. Actually, a pattern which helps us to write good concurrent code is available, that is, using “channels” to communicate.
This talk will share the channel concept with common libraries, like threading and multiprocessing, to make concurrent code elegant.
It's the talk at PyCon TW 2017 [1] and PyCon APAC/MY 2017 [2].
[1]: https://tw.pycon.org/2017
[2]: https://pycon.my/pycon-apac-2017-program-schedule/
Gotcha! Ruby things that will come back to bite you.David Tollmyr
The document discusses various performance optimizations for JRuby applications. It covers techniques like avoiding unnecessary string creation, using java.util.concurrent utilities for concurrency instead of Ruby's Mutex, and avoiding shelling out from JRuby when possible. The author also shares lessons learned around array joins, queue implementations, and passing binary strings between Ruby and Java.
Performance tweaks and tools for Linux (Joe Damato)Ontico
The document discusses various Linux performance analysis tools including lsof to list open files, strace to trace system calls, tcpdump to dump network traffic, perftools from Google for profiling CPU usage, and a Ruby library called perftools.rb for profiling Ruby code. Examples are provided for using these tools to analyze memory usage, slow queries, Ruby interpreter signals, thread scheduling overhead, and identifying hot spots in Ruby web applications.
Winnyp is an anonymous P2P filesharing software based on Winny. It uses its own encryption key generation algorithm that is more complex than Winny's algorithm, making it more difficult to analyze. The report details Winnyp's internal workings, including how it initializes and patches itself, generates encryption keys through multiple algorithms, and specifies the version of connected nodes by using different encryption keys. It also describes how Winnyp sends packets with dummy data and receives packets to communicate with both Winny and other Winnyp nodes.
The Ring programming language version 1.5.3 book - Part 89 of 184Mahmoud Samir Fayed
The document describes embedding Ring code in Ring programs without sharing state. It allows quick integration of Ring programs and applications together without conflicts by executing Ring code in isolated environments. Functions like ring_state_init(), ring_state_runcode(), and ring_state_delete() are used to initialize a state, run code in it, and delete it. This prevents variables from one state being accessible from another. Serial execution of Ring applications is also demonstrated using ring_state_main().
This document provides an overview of Python fundamentals including basic concepts like data types, operators, flow control, functions and classes. It begins with an introduction to Python versions and environments. The outline covers topics like Hello World, common types and operators for numeric, string and container data types. It also discusses flow control structures like if/else, while loops and for loops. Finally, it briefly mentions functions, classes, exceptions and file I/O.
Swift.berlin, this time kindly hosted by Wooga, invited Crispy's own Christian Weyer to speak about whether Apple's new programming language Swift is ready for primetime use in corporate, production environments. In order to answer that question, Christian ported an existing OS X application to Swift and created a new iOS application from scratch. Watch the video to see his results and the conclusions he drew from these experiences.
Video available at https://vimeo.com/113089291
This document provides an introduction to Python programming including installation, basic syntax, data types, control flow, modules, sockets, structs, pwntools, vulnerabilities, practice problems, and references for further learning. It covers topics such as printing, taking input, lists, arithmetic, conditional statements, loops, functions, importing modules, sending/receiving data over sockets, packing/unpacking integers, using pwntools, and exploiting vulnerabilities like pickle injection. Example code is provided throughout to demonstrate the concepts.
Rust is a systems programming language that provides memory safety without using a garbage collector. It achieves memory safety through rules of ownership, borrowing, and lifetimes that are checked at compile time. These rules prevent common memory bugs like memory leaks, dangling pointers, and use-after-free errors that are common in C and C++.
The document discusses rendering dropdown menus in the content process. It notes there are performance, styling, and event behavior issues with the current e10s-select approach. An alternative approach called content-select would render the dropdown as normal content in the content process to achieve better performance, stronger style support, and more accurate events without these issues. It provides an example of complex styling that can be applied to options in the dropdown.
The document discusses Rust's ownership system and borrowing. It explains that variables own the memory for their values, and when a variable goes out of scope that memory is returned. References allow borrowing values without transferring ownership. References must live shorter than the values they reference. Mutable references also allow changing borrowed values, but there can only be one mutable reference at a time.
The document discusses concurrency in C++ and the use of std::async and std::future. It recommends preferring task-based programming over thread-based due to easier management. It notes that the default launch policy for std::async allows asynchronous or synchronous execution, creating uncertainty. It advises specifying std::launch::async if asynchronicity is essential to ensure concurrent execution and avoid issues with thread-local variables and timeout-based waits.
Use C++ to Manipulate mozSettings in GeckoChih-Hsuan Kuo
If you want to manipulate mozSettings with JavaScript, you can reference to Settings API on MDN (https://developer.mozilla.org/en-US/docs/Web/API/Settings_API).
But if you want to manipulate it with C++, we can only reference to the codebase of Gecko. Now, let me show you some example.
The document describes how Necko handles data URLs in Firefox. It discusses:
1. The data URL protocol syntax and how Necko parses data URLs to determine the MIME type, encoding, and data.
2. How Necko gets the protocol handler for data URLs and uses the nsDataHandler to create an nsDataChannel for the URL.
3. How the nsDataChannel establishes a listener chain with the nsInputStreamPump and nsHtml5StreamParser/Listener to read the data in chunks and parse the HTML content.
4. The states the nsInputStreamPump goes through - START, TRANSFER, STOP - to read the data from the nsDataChannel and
The document discusses protocol handlers in Gecko. It explains that protocol handlers allow Gecko to interact with different URI schemes like http, ftp, file etc. It provides an overview of how the awesome bar, browser UI, DocShell and Necko components work together to handle protocol requests from inputting a URL in the awesome bar to creating a channel and loading content. It also briefly introduces channels and stream listeners in Necko which are used for asynchronous loading of content.
This document provides an introduction to Linux, including what it is, some popular Linux distributions like Ubuntu, and reasons why one might use Linux instead of Windows. It notes that while Linux's desktop market share is still lower than Windows, it is widely used in servers, Android devices, and supercomputers. The document discusses how to install Ubuntu and some basic features and software available in Ubuntu. It argues that Linux is more secure, customizable, and liberating for users compared to Windows. However, it acknowledges Linux still lacks versions of some essential software and may not support all hardware.
Python is an easy to read, easy to learn, easy to write programming language. It is interpreted rather than compiled, making it easy to execute without needing to compile code first. Python is a multi-paradigm language supporting object-oriented, imperative and functional programming. The Python logo depicts a python snake to represent the name of the language. The Zen of Python outlines design philosophies for the language, preferring simple and readable code.
VP8 is an open source video codec developed by On2 Technologies and acquired by Google in 2010. It is designed for web-based video applications with a focus on low bandwidth and support for heterogeneous hardware. VP8 uses intra-frame and inter-frame prediction, 4x4 transform coding with an adaptive loop filter to reduce artifacts, and entropy coding with adaptive probability distributions. It achieves good quality at low bitrates and supports parallel processing for improved decoding performance on modern hardware.
Python is an interpreted, object-oriented programming language that is easy to read, write, and learn. It is ranked among the top 10 languages by popularity according to TIOBE and is widely used on GitHub. The Python logo depicts a snake to represent the Pythonidae family. The language emphasizes readability and uses English keywords frequently.
This document describes an algorithm for determining if two trees are isomorphic by hashing the trees. It hashes each subtree and sorts the hashes to get a unique representation of the tree. It recursively hashes subtrees from leaves to root. The hash of the whole tree represents the tree and trees are isomorphic if they have the same hash value. The time complexity is O(N log N) where N is the number of vertices. Pseudocode and examples are provided.
The document describes Dinic's algorithm for finding the maximum flow in a flow network. It involves building a level graph of the network and finding blocking flows by finding augmenting paths from the source to the sink, then identifying bottlenecks on those paths and pushing flow along reverse paths from the bottlenecks to the sink in an iterative manner until no more augmenting paths exist. An example applying these steps on a sample network is provided to illustrate the algorithm.
The document discusses graph traversal algorithms depth-first search (DFS) and breadth-first search (BFS). It provides examples of how DFS and BFS traverse graphs using a stack and queue respectively. Pseudocode for DFS and BFS algorithms is presented. The time complexity of both algorithms is O(V+E) where V is the number of nodes and E is the number of edges. Examples of DFS and BFS traversing a mouse maze are also shown.
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
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إضغ بين إيديكم من أقوى الملازم التي صممتها
ملزمة تشريح الجهاز الهيكلي (نظري 3)
💀💀💀💀💀💀💀💀💀💀
تتميز هذهِ الملزمة بعِدة مُميزات :
1- مُترجمة ترجمة تُناسب جميع المستويات
2- تحتوي على 78 رسم توضيحي لكل كلمة موجودة بالملزمة (لكل كلمة !!!!)
#فهم_ماكو_درخ
3- دقة الكتابة والصور عالية جداً جداً جداً
4- هُنالك بعض المعلومات تم توضيحها بشكل تفصيلي جداً (تُعتبر لدى الطالب أو الطالبة بإنها معلومات مُبهمة ومع ذلك تم توضيح هذهِ المعلومات المُبهمة بشكل تفصيلي جداً
5- الملزمة تشرح نفسها ب نفسها بس تكلك تعال اقراني
6- تحتوي الملزمة في اول سلايد على خارطة تتضمن جميع تفرُعات معلومات الجهاز الهيكلي المذكورة في هذهِ الملزمة
واخيراً هذهِ الملزمة حلالٌ عليكم وإتمنى منكم إن تدعولي بالخير والصحة والعافية فقط
كل التوفيق زملائي وزميلاتي ، زميلكم محمد الذهبي 💊💊
🔥🔥🔥🔥🔥🔥🔥🔥🔥
How to Setup Default Value for a Field in Odoo 17Celine George
In Odoo, we can set a default value for a field during the creation of a record for a model. We have many methods in odoo for setting a default value to the field.
How to Manage Reception Report in Odoo 17Celine George
A business may deal with both sales and purchases occasionally. They buy things from vendors and then sell them to their customers. Such dealings can be confusing at times. Because multiple clients may inquire about the same product at the same time, after purchasing those products, customers must be assigned to them. Odoo has a tool called Reception Report that can be used to complete this assignment. By enabling this, a reception report comes automatically after confirming a receipt, from which we can assign products to orders.
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
CapTechTalks Webinar Slides June 2024 Donovan Wright.pptxCapitolTechU
Slides from a Capitol Technology University webinar held June 20, 2024. The webinar featured Dr. Donovan Wright, presenting on the Department of Defense Digital Transformation.
18. Improve Stream I/O
Stream I/O need to keep
themselves in sync with
the underlying C library.
Add this line in code,
std::ios::sync_with_stdio(false);
if you won’t use C I/O.
22. Buffered Technique
Base on fgets/puts function.
fgets/puts are faster than scanf/printf.
23. Buffered Read
Read mass data, and parse by self.
char buf[ 1000 ];
int a, b;
fgets( buf, sizeof( buf ), stdin );
sscanf( buf, “%d %d”, &a, &b );
24. Buffered Write
Store mass data into temporal buffer,
and write them once.
char buf[ 1000 ];
int ret = a + b;
sprintf( buf, “%d”, ret );
puts( buf );
28. strtok
original string:
A “corpus” is a collection of texts of written (or
spoken) language presented in electronic form.
take out all words:
A corpus is a
collection of texts of
written or spoken language
presented in electronic form
29. char str = “A “corpus” is a collection of texts of
written (or spoken) language presented in electronic
form.”
for ( char *token = strtok( str, “ ”().” ); token !=
NULL; token = strtok( NULL, “ ”().” ) ) {
puts( token );
}
30. start position
delimiters: “ ”().”
global pointer
A “ c o r p u s ” i s a c o l l
e c t i o n o f t e x t s o f w
r e t t e n ( o r s p o k e n ) l
a n g u a g e p r e s e n t e d i n
e l e t r o n i c f o r m . 0
31. start position
delimiters: “ ”().”
global pointer
A 0 “ c o r p u s ” i s a c o l l
e c t i o n o f t e x t s o f w
r e t t e n ( o r s p o k e n ) l
a n g u a g e p r e s e n t e d i n
e l e t r o n i c f o r m . 0
33. start position
delimiters: “ ”().”
global pointer
A 0 “ c o r p u s ” i s a c o l l
e c t i o n o f t e x t s o f w
r e t t e n ( o r s p o k e n ) l
a n g u a g e p r e s e n t e d i n
e l e t r o n i c f o r m . 0
34. start position
delimiters: “ ”().”
global pointer
A 0 0 c o r p u s 0
“ ” i s a c o l l
e c t i o n o f t e x t s o f w
r e t t e n ( o r s p o k e n ) l
a n g u a g e p r e s e n t e d i n
e l e t r o n i c f o r m . 0
36. start position
delimiters: “ ”().”
global pointer
A 0 0 c o r p u s 0 i s a c o l l
e c t i o n o f t e x t s o f w
r e t t e n ( o r s p o k e n ) l
a n g u a g e p r e s e n t e d i n
e l e t r o n i c f o r m . 0
37. start position
delimiters: “ ”().”
global pointer
A 0 0 c o r p u s 0 0 i s 0 a c o l l
e c t i o n o f t e x t s o f w
r e t t e n ( o r s p o k e n ) l
a n g u a g e p r e s e n t e d i n
e l e t r o n i c f o r m . 0
39. start position
delimiters: “ ”().”
global pointer
A 0 0 c o r p u s 0 0 i s 0 a c o l l
e c t i o n o f t e x t s o f w
r e t t e n ( o r s p o k e n ) l
a n g u a g e p r e s e n t e d i n
e l e t r o n i c f o r m . 0
40. start position
delimiters: “ ”().”
global pointer
A 0 0 c o r p u s 0 0 i s 0 a 0 c o l l
e c t i o n o f t e x t s o f w
r e t t e n ( o r s p o k e n ) l
a n g u a g e p r e s e n t e d i n
e l e t r o n i c f o r m . 0
43. start position
delimiters: “ ”().”
global pointer
A 0 0 c o r p u s 0 0 i
“ ” s 0 a 0 c o l l
e c t i o n 0 o f 0 t e x t s 0 o f 0 w
r e t t e n 0 0 o r 0 s p o k e n 0 0 l
a n g u a g e 0 p r e s e n t e d 0 i n
0 e l e t r o n i c 0 f o r m . 0
44. start position
delimiters: “ ”().”
global pointer
A 0 0 c o r p u s 0 0 i
“ ” s 0 a 0 c o l l
e c t i o n 0 o f 0 t e x t s 0 o f 0 w
r e t t e n 0 0 o r 0 s p o k e n 0 0 l
a n g u a g e 0 p r e s e n t e d 0 i n
0 e l e t r o n i c 0 f o r m 0 0
.
46. start position
delimiters: “ ”().”
global pointer
A 0 0 c o r p u s 0 0 i
“ ” s 0 a 0 c o l l
e c t i o n 0 o f 0 t e x t s 0 o f 0 w
r e t t e n 0 0 o r 0 s p o k e n 0 0 l
a n g u a g e 0 p r e s e n t e d 0 i n
0 e l e t r o n i c 0 f o r m 0 0
.
48. • include <cstring> or <string.h>
• first time use string variable as
parameter to setup global pointer
• others use NULL as parameter to avoid
changing global pointer
• strtok will modify the original string
• whitespace character (n, r, t ...)