This document discusses data types and expressions in Objective-C. It covers basic data types like int, float, char, and boolean. It also discusses arithmetic expressions using operators like addition, subtraction, multiplication, division, and modulus. Examples are provided to demonstrate how to use different data types and perform calculations in Objective-C.
OOP Chapter 3: Classes, Objects and MethodsAtit Patumvan
This document discusses object-oriented programming concepts like classes, objects, and methods. It provides an example class for representing fractions that defines instance variables to store the numerator and denominator. It demonstrates creating fraction objects, setting properties on objects by calling methods, and accessing instance variables. The class defines an interface with method signatures and an implementation that includes method definitions to print fractions, set property values, and return property values.
The document discusses separating object-oriented programming code into interface and implementation files. It shows how to define an interface for a Fraction class in a header file and provide the implementation in a separate file. It also covers compiling the code from the command line or using a makefile. The document then demonstrates synthesizing accessor methods to allow accessing properties using dot notation rather than message passing syntax.
OOP: Chapter 2: Programming in Objective-C Atit Patumvan
This document discusses programming in Objective-C. It presents several example programs that demonstrate basic Objective-C syntax like importing frameworks, using NSAutoreleasePool, NSLog functions, and performing calculations. It also explains how to compile and run Objective-C programs on different platforms like OSX, Windows, and Linux. Common filename extensions for different programming languages are also listed.
Chapter 9 : Polymorphism, Dynamic Typing, and Dynamic BindingAtit Patumvan
This document discusses three key concepts in object-oriented programming: polymorphism, dynamic typing, and dynamic binding. Polymorphism allows objects from different classes to define methods with the same name. Dynamic typing determines an object's class at runtime. Dynamic binding determines which actual method to invoke for an object at runtime.
Python Application: Visual Approach of Hopfield Discrete Method for Hiragana ...journalBEEI
Python is a dynamic object-oriented programming language. Python provides strong support for integration with other programming languages and other tools. Python programming is rarely used in the field of artificial intelligence, especially artificial neural networks. This research focuses on running Python programming to recognize hiragana letters. In learning the character of Hiragana, one can experience difficulties because of the many combinations of vowels that form new letters by different means of reading and meaning. Discrete Hopfield network is a fully connected, that every unit is attached to every other unit. This network has asymmetrical weights. At Hopfield Network, each unit has no relationship with itself. Therefore it is expected that a computer system that can help recognize the Hiragana Images. With this pattern recognition Application of Hiragana Images, it is expected the system can be developed further to recognize the Hiragana Images quickly and precisely.
Writing Usable APIs in Practice by Giovanni AsproniSyncConf
Explicitly or implicitly, when working on complex systems, end up designing some APIs to accomplish their tasks, either because the product itself is some kind of general purpose library or because they need to write some libraries and packages to put some common code of their applications.
There is plenty of information available about how to write clean and maintainable code, but not a lot about writing usable APIs. The two things are related, but they are not the same. In fact, clean code is code that is clean from the point of view of its maintainers, usable APIs, on the other hand, refer to code that programmers (other than the original author) find easy to use. We'll see how usable APIs help in writing clean code (and vice-versa).
Object Oriented Approach Within Siebel BoundariesRoman Agaev
This document discusses implementing object-oriented principles within the Siebel environment. It defines key object-oriented concepts like hierarchy, inheritance, abstraction, encapsulation, generalization, polymorphism, and persistence. The document argues that Siebel supports these concepts through mechanisms like business components, services, and classes. It emphasizes that developers must adhere to object-oriented patterns like strong typing and encapsulation when building applications in Siebel. Following these principles helps reuse code and align development with object-oriented analysis and design.
Design and implementation of a java based virtual laboratory for data communi...IJECEIAES
Students in this modern age find engineering courses taught in the university very abstract and difficult, and cannot relate theoretical calculations to real life scenarios. They consequently lose interest in their coursework and perform poorly in their grades. Simulation of classroom concepts with simulation software like MATLAB, were developed to facilitate learning experience. This paper involves the development of a virtual laboratory simulation package for teaching data communication concepts such as coding schemes, modulation and filtering. Unlike other simulation packages, no prior knowledge of computer programming is required for students to grasp these concepts.
OOP Chapter 3: Classes, Objects and MethodsAtit Patumvan
This document discusses object-oriented programming concepts like classes, objects, and methods. It provides an example class for representing fractions that defines instance variables to store the numerator and denominator. It demonstrates creating fraction objects, setting properties on objects by calling methods, and accessing instance variables. The class defines an interface with method signatures and an implementation that includes method definitions to print fractions, set property values, and return property values.
The document discusses separating object-oriented programming code into interface and implementation files. It shows how to define an interface for a Fraction class in a header file and provide the implementation in a separate file. It also covers compiling the code from the command line or using a makefile. The document then demonstrates synthesizing accessor methods to allow accessing properties using dot notation rather than message passing syntax.
OOP: Chapter 2: Programming in Objective-C Atit Patumvan
This document discusses programming in Objective-C. It presents several example programs that demonstrate basic Objective-C syntax like importing frameworks, using NSAutoreleasePool, NSLog functions, and performing calculations. It also explains how to compile and run Objective-C programs on different platforms like OSX, Windows, and Linux. Common filename extensions for different programming languages are also listed.
Chapter 9 : Polymorphism, Dynamic Typing, and Dynamic BindingAtit Patumvan
This document discusses three key concepts in object-oriented programming: polymorphism, dynamic typing, and dynamic binding. Polymorphism allows objects from different classes to define methods with the same name. Dynamic typing determines an object's class at runtime. Dynamic binding determines which actual method to invoke for an object at runtime.
Python Application: Visual Approach of Hopfield Discrete Method for Hiragana ...journalBEEI
Python is a dynamic object-oriented programming language. Python provides strong support for integration with other programming languages and other tools. Python programming is rarely used in the field of artificial intelligence, especially artificial neural networks. This research focuses on running Python programming to recognize hiragana letters. In learning the character of Hiragana, one can experience difficulties because of the many combinations of vowels that form new letters by different means of reading and meaning. Discrete Hopfield network is a fully connected, that every unit is attached to every other unit. This network has asymmetrical weights. At Hopfield Network, each unit has no relationship with itself. Therefore it is expected that a computer system that can help recognize the Hiragana Images. With this pattern recognition Application of Hiragana Images, it is expected the system can be developed further to recognize the Hiragana Images quickly and precisely.
Writing Usable APIs in Practice by Giovanni AsproniSyncConf
Explicitly or implicitly, when working on complex systems, end up designing some APIs to accomplish their tasks, either because the product itself is some kind of general purpose library or because they need to write some libraries and packages to put some common code of their applications.
There is plenty of information available about how to write clean and maintainable code, but not a lot about writing usable APIs. The two things are related, but they are not the same. In fact, clean code is code that is clean from the point of view of its maintainers, usable APIs, on the other hand, refer to code that programmers (other than the original author) find easy to use. We'll see how usable APIs help in writing clean code (and vice-versa).
Object Oriented Approach Within Siebel BoundariesRoman Agaev
This document discusses implementing object-oriented principles within the Siebel environment. It defines key object-oriented concepts like hierarchy, inheritance, abstraction, encapsulation, generalization, polymorphism, and persistence. The document argues that Siebel supports these concepts through mechanisms like business components, services, and classes. It emphasizes that developers must adhere to object-oriented patterns like strong typing and encapsulation when building applications in Siebel. Following these principles helps reuse code and align development with object-oriented analysis and design.
Design and implementation of a java based virtual laboratory for data communi...IJECEIAES
Students in this modern age find engineering courses taught in the university very abstract and difficult, and cannot relate theoretical calculations to real life scenarios. They consequently lose interest in their coursework and perform poorly in their grades. Simulation of classroom concepts with simulation software like MATLAB, were developed to facilitate learning experience. This paper involves the development of a virtual laboratory simulation package for teaching data communication concepts such as coding schemes, modulation and filtering. Unlike other simulation packages, no prior knowledge of computer programming is required for students to grasp these concepts.
This document discusses deep learning and various deep learning techniques such as backpropagation, autoencoders, restricted Boltzmann machines, and dropout. It provides an overview of these concepts and algorithms as well as discussing implementations in Python and Theano. It also proposes future work applying these techniques to tasks like defect classification, speech recognition, and independent component analysis.
On the Semantics of Real-Time Domain Specific Modeling LanguagesJose E. Rivera
This document summarizes Jose E. Rivera's PhD thesis on providing formal semantics for real-time domain specific modeling languages. The thesis defines a framework for specifying the timed behavior of domain specific modeling languages using rewriting logic. It extends in-place model transformations to include time-dependent behavior. Models are formally specified in Maude, enabling simulation and analysis of real-time properties. The work contributes tools and techniques for formally specifying, simulating, and analyzing real-time domain specific modeling languages.
Producing simulation sequences by use of a Java-based FrameworkDaniele Gianni
The document presents jRand, a Java-based generalized framework for producing simulation sequences. jRand increases flexibility in configuring input sequences for simulations. It uses a producer-consumer pattern where random generators produce sequences that are consumed by simulation software. jRand defines interfaces for different types of streams and allows compositions of streams using transformations. An example computer network simulation demonstrates how jRand can be used to model different components with random inputs. Preliminary results suggest jRand has minimal performance overhead.
Extractive Summarization with Very Deep Pretrained Language Modelgerogepatton
The document describes a study that used BERT (Bidirectional Encoder Representations from Transformers), a pretrained language model, for extractive text summarization. The researchers developed a two-phase encoder-decoder model where BERT encoded sentences from documents and classified them as included or not included in the summary. They evaluated the model on the CNN/Daily Mail corpus and found it achieved state-of-the-art results comparable to previous models based on both automatic metrics and human evaluation.
Event-driven Model Transformations in Domain-specific Modeling LanguagesIstvan Rath
This PhD thesis by István Ráth focuses on event-driven model transformations in domain-specific modeling languages. The thesis contains 3 parts: 1) developing concepts for event-driven graph transformations based on incremental pattern matching, 2) applying these concepts to provide advanced language engineering features like simulation, and 3) integrating modeling tools using change-driven transformations. The research aims to address challenges in scalability, usability and tool integration for model-driven software engineering.
This document describes a universal framework called "pse" for creating visual simulation models using the Python programming language. The framework allows building models using components and connecting them with nets. It has a block-based structure that separates the logical and graphical representations. Users can create custom components by inheriting from a base Component class. Examples show simulations of differential equations, oscillators, and maps. The framework is open source and intended to facilitate predictive simulations in fields like engineering without extensive programming knowledge.
The document outlines the rules and topics that will be covered in a data structures and algorithms course. It includes:
- Class rules prohibiting late entry or early exit from classes and announcing unscheduled quizzes.
- An outline of standard data structures and algorithms to be covered, including arrays, stacks, queues, linked lists, trees, sorting, searching, and graphs.
- An introduction to key concepts like data types, algorithms, performance analysis, and asymptotic notation to analyze time and space complexity.
pointer, structure ,union and intro to file handlingRai University
Pointers allow programs to store and pass around memory addresses. Pointers in C can point to primitive data types, arrays, structs, and other pointers. Declaring a pointer requires a * before the pointer name and specifying the type of data it will point to. The & operator returns the memory address of a variable, which can be stored in a pointer. The * operator dereferences a pointer to access the data being pointed to. Pointers enable functions to modify variables in the calling function and return multiple values. They also make structs more efficient to pass to functions. Care must be taken to avoid bugs from misusing pointers.
1. The document discusses functions in programming fundamentals.
2. It defines functions as self-contained program segments that carry out specific tasks, and distinguishes between built-in and user-defined functions.
3. The key aspects of functions covered are defining and prototyping functions, passing values into functions by value and by reference, and returning values from functions.
EXTRACTIVE SUMMARIZATION WITH VERY DEEP PRETRAINED LANGUAGE MODELijaia
The document presents a new model for extractive text summarization that uses BERT (Bidirectional Encoder Representations from Transformers), a pretrained deep bidirectional transformer model, as the text encoder. The model consists of a BERT encoder and a sentence classifier. Sentences are encoded using BERT and classified as to whether they should be included in the summary. Evaluation on the CNN/Daily Mail corpus shows the model achieves state-of-the-art results comparable to other top models according to automatic metrics and human evaluation, making it the first work to apply BERT to text summarization.
Mca 1 pic u-5 pointer, structure ,union and intro to file handlingRai University
Pointers allow programs to store and pass around memory addresses. They enable functions to modify variables in the calling function. Pointers must match the type of the variable being pointed to. Common pointer operators are asterisk (*) to dereference and ampersand (&) to get an address. Pointers can point to primitive types, arrays, structs, and dynamically allocated memory. They require care to avoid bugs but enable memory sharing and dynamic memory allocation. Pointers to structs are commonly passed to functions to efficiently access struct members.
pointer, structure ,union and intro to file handlingRai University
1) Pointers allow programs to store and pass around the memory addresses of variables and dynamically allocated memory. They provide a way to indirectly access and modify data from different parts of a program.
2) Pointers must be declared with a variable type and the * symbol. Common pointer operators are * to dereference a pointer and & to get the address of a variable.
3) Passing pointers to functions allows the function to modify the variables in the caller's scope by dereferencing the pointers. This is commonly used to return multiple values from a function.
Bsc cs 1 pic u-5 pointer, structure ,union and intro to file handlingRai University
1. Pointers allow functions to modify variables in the calling function by passing the address of variables. This allows functions to return multiple values.
2. Structures can be passed to functions using pointers to avoid expensive copying of large structures. Pointers to structures use -> to access members.
3. Pointers must match the type of the variable being pointed to. NULL is used to indicate an empty pointer. Dereferencing NULL causes crashes.
Diploma ii cfpc- u-5.1 pointer, structure ,union and intro to file handlingRai University
This document discusses pointers in C programming. It defines pointers as variables that contain the memory addresses of other variables. Pointers allow functions to modify variables in the calling function and facilitate dynamic memory allocation. The key pointer operators are asterisk (*) for dereferencing and ampersand (&) for getting a variable's address. Examples demonstrate declaring and using pointers, passing pointers to functions, pointers to structures, and the NULL pointer value. Pointer syntax and dereferencing must match the variable type to avoid errors.
IRJET - Speech to Speech Translation using Encoder Decoder ArchitectureIRJET Journal
This document summarizes a research paper on speech-to-speech translation using an encoder-decoder architecture. It describes a system that takes speech in one language as input, recognizes the speech to generate text, translates the text to another language, and synthesizes speech in the other language as output. The system consists of three main modules: speech recognition in the source language, text translation between languages, and speech generation in the target language. It aims to enable two-way translation between spoken sentences in different languages.
The document presents an ensemble model for chunking natural language text that combines a transformer model (RoBERTa) with a bidirectional LSTM and CNN model. The authors train these models on common chunking datasets like CoNLL 2000 and English Penn Treebank. They find that by using an ensemble of the transformer and RNN-CNN models, which compensate for each other's weaknesses, they are able to achieve state-of-the-art results on chunking, with an F1 score of 97.3% on CoNLL 2000, exceeding previous work. The transformer model provides attention-based contextual embeddings while the RNN-CNN model uses custom embeddings including POS tags to improve accuracy on tags that the transformer model struggles with.
IRJET - Analysis of Paraphrase Detection using NLP TechniquesIRJET Journal
This document discusses analyzing paraphrase detection using natural language processing (NLP) techniques. It proposes applying a multi-head attention mechanism in a Siamese deep neural network to detect semantic similarity between texts and determine if they are paraphrases. The system would tokenize, stem, remove stopwords and part-of-speech tag input texts before applying the neural network. It evaluates the approach on datasets like SNLI and QQP and compares performance to existing methods.
Dynamic framed slotted aloha algorithms using fast tag estimationambitlick
This document summarizes a paper that proposes a Dynamic Framed Slotted ALOHA (DFSA) algorithm using a proposed Tag Estimation Method (TEM) to estimate the number of tags around a reader. The DFSA algorithm dynamically allocates the frame size according to the estimated number of tags. Simulation results show the DFSA algorithm has better performance and lower delay than conventional algorithms regardless of the number of tags.
The document proposes a fuzzy incremental feature clustering algorithm to reduce the dimensionality of feature vectors for text classification. Some limitations of existing feature clustering methods include requiring the user to specify the number of clusters in advance and not considering variance within clusters. The new algorithm uses fuzzy logic to automatically determine the number of clusters formed, and each cluster is characterized by a membership function and statistical mean and variance. This results in features being extracted that better match the real distribution of training data.
Without analytics on big data, companies are unable to understand their environment and customers, similar to how deer cannot see or hear approaching vehicles on a highway. Presentations are tools that can be used for lectures, reports, and more. They serve various purposes, making presentations powerful tools for convincing and teaching others. Data science uses techniques from multiple fields like mathematics, statistics, and computer science to analyze large amounts of data and extract meaningful insights for business.
Programming in Civil Engineering_UNIT 2_NOTESRushikesh Kolhe
This document provides an introduction to data types and variables in Python. It discusses that Python is a dynamically typed language where the type of a variable is determined at runtime. It describes various Python data types including numeric, sequence, mapping, set, boolean, and binary types. It also discusses variable naming conventions and that variables are created by assignment. Finally, it explains the differences between mutable and immutable data types.
This document discusses deep learning and various deep learning techniques such as backpropagation, autoencoders, restricted Boltzmann machines, and dropout. It provides an overview of these concepts and algorithms as well as discussing implementations in Python and Theano. It also proposes future work applying these techniques to tasks like defect classification, speech recognition, and independent component analysis.
On the Semantics of Real-Time Domain Specific Modeling LanguagesJose E. Rivera
This document summarizes Jose E. Rivera's PhD thesis on providing formal semantics for real-time domain specific modeling languages. The thesis defines a framework for specifying the timed behavior of domain specific modeling languages using rewriting logic. It extends in-place model transformations to include time-dependent behavior. Models are formally specified in Maude, enabling simulation and analysis of real-time properties. The work contributes tools and techniques for formally specifying, simulating, and analyzing real-time domain specific modeling languages.
Producing simulation sequences by use of a Java-based FrameworkDaniele Gianni
The document presents jRand, a Java-based generalized framework for producing simulation sequences. jRand increases flexibility in configuring input sequences for simulations. It uses a producer-consumer pattern where random generators produce sequences that are consumed by simulation software. jRand defines interfaces for different types of streams and allows compositions of streams using transformations. An example computer network simulation demonstrates how jRand can be used to model different components with random inputs. Preliminary results suggest jRand has minimal performance overhead.
Extractive Summarization with Very Deep Pretrained Language Modelgerogepatton
The document describes a study that used BERT (Bidirectional Encoder Representations from Transformers), a pretrained language model, for extractive text summarization. The researchers developed a two-phase encoder-decoder model where BERT encoded sentences from documents and classified them as included or not included in the summary. They evaluated the model on the CNN/Daily Mail corpus and found it achieved state-of-the-art results comparable to previous models based on both automatic metrics and human evaluation.
Event-driven Model Transformations in Domain-specific Modeling LanguagesIstvan Rath
This PhD thesis by István Ráth focuses on event-driven model transformations in domain-specific modeling languages. The thesis contains 3 parts: 1) developing concepts for event-driven graph transformations based on incremental pattern matching, 2) applying these concepts to provide advanced language engineering features like simulation, and 3) integrating modeling tools using change-driven transformations. The research aims to address challenges in scalability, usability and tool integration for model-driven software engineering.
This document describes a universal framework called "pse" for creating visual simulation models using the Python programming language. The framework allows building models using components and connecting them with nets. It has a block-based structure that separates the logical and graphical representations. Users can create custom components by inheriting from a base Component class. Examples show simulations of differential equations, oscillators, and maps. The framework is open source and intended to facilitate predictive simulations in fields like engineering without extensive programming knowledge.
The document outlines the rules and topics that will be covered in a data structures and algorithms course. It includes:
- Class rules prohibiting late entry or early exit from classes and announcing unscheduled quizzes.
- An outline of standard data structures and algorithms to be covered, including arrays, stacks, queues, linked lists, trees, sorting, searching, and graphs.
- An introduction to key concepts like data types, algorithms, performance analysis, and asymptotic notation to analyze time and space complexity.
pointer, structure ,union and intro to file handlingRai University
Pointers allow programs to store and pass around memory addresses. Pointers in C can point to primitive data types, arrays, structs, and other pointers. Declaring a pointer requires a * before the pointer name and specifying the type of data it will point to. The & operator returns the memory address of a variable, which can be stored in a pointer. The * operator dereferences a pointer to access the data being pointed to. Pointers enable functions to modify variables in the calling function and return multiple values. They also make structs more efficient to pass to functions. Care must be taken to avoid bugs from misusing pointers.
1. The document discusses functions in programming fundamentals.
2. It defines functions as self-contained program segments that carry out specific tasks, and distinguishes between built-in and user-defined functions.
3. The key aspects of functions covered are defining and prototyping functions, passing values into functions by value and by reference, and returning values from functions.
EXTRACTIVE SUMMARIZATION WITH VERY DEEP PRETRAINED LANGUAGE MODELijaia
The document presents a new model for extractive text summarization that uses BERT (Bidirectional Encoder Representations from Transformers), a pretrained deep bidirectional transformer model, as the text encoder. The model consists of a BERT encoder and a sentence classifier. Sentences are encoded using BERT and classified as to whether they should be included in the summary. Evaluation on the CNN/Daily Mail corpus shows the model achieves state-of-the-art results comparable to other top models according to automatic metrics and human evaluation, making it the first work to apply BERT to text summarization.
Mca 1 pic u-5 pointer, structure ,union and intro to file handlingRai University
Pointers allow programs to store and pass around memory addresses. They enable functions to modify variables in the calling function. Pointers must match the type of the variable being pointed to. Common pointer operators are asterisk (*) to dereference and ampersand (&) to get an address. Pointers can point to primitive types, arrays, structs, and dynamically allocated memory. They require care to avoid bugs but enable memory sharing and dynamic memory allocation. Pointers to structs are commonly passed to functions to efficiently access struct members.
pointer, structure ,union and intro to file handlingRai University
1) Pointers allow programs to store and pass around the memory addresses of variables and dynamically allocated memory. They provide a way to indirectly access and modify data from different parts of a program.
2) Pointers must be declared with a variable type and the * symbol. Common pointer operators are * to dereference a pointer and & to get the address of a variable.
3) Passing pointers to functions allows the function to modify the variables in the caller's scope by dereferencing the pointers. This is commonly used to return multiple values from a function.
Bsc cs 1 pic u-5 pointer, structure ,union and intro to file handlingRai University
1. Pointers allow functions to modify variables in the calling function by passing the address of variables. This allows functions to return multiple values.
2. Structures can be passed to functions using pointers to avoid expensive copying of large structures. Pointers to structures use -> to access members.
3. Pointers must match the type of the variable being pointed to. NULL is used to indicate an empty pointer. Dereferencing NULL causes crashes.
Diploma ii cfpc- u-5.1 pointer, structure ,union and intro to file handlingRai University
This document discusses pointers in C programming. It defines pointers as variables that contain the memory addresses of other variables. Pointers allow functions to modify variables in the calling function and facilitate dynamic memory allocation. The key pointer operators are asterisk (*) for dereferencing and ampersand (&) for getting a variable's address. Examples demonstrate declaring and using pointers, passing pointers to functions, pointers to structures, and the NULL pointer value. Pointer syntax and dereferencing must match the variable type to avoid errors.
IRJET - Speech to Speech Translation using Encoder Decoder ArchitectureIRJET Journal
This document summarizes a research paper on speech-to-speech translation using an encoder-decoder architecture. It describes a system that takes speech in one language as input, recognizes the speech to generate text, translates the text to another language, and synthesizes speech in the other language as output. The system consists of three main modules: speech recognition in the source language, text translation between languages, and speech generation in the target language. It aims to enable two-way translation between spoken sentences in different languages.
The document presents an ensemble model for chunking natural language text that combines a transformer model (RoBERTa) with a bidirectional LSTM and CNN model. The authors train these models on common chunking datasets like CoNLL 2000 and English Penn Treebank. They find that by using an ensemble of the transformer and RNN-CNN models, which compensate for each other's weaknesses, they are able to achieve state-of-the-art results on chunking, with an F1 score of 97.3% on CoNLL 2000, exceeding previous work. The transformer model provides attention-based contextual embeddings while the RNN-CNN model uses custom embeddings including POS tags to improve accuracy on tags that the transformer model struggles with.
IRJET - Analysis of Paraphrase Detection using NLP TechniquesIRJET Journal
This document discusses analyzing paraphrase detection using natural language processing (NLP) techniques. It proposes applying a multi-head attention mechanism in a Siamese deep neural network to detect semantic similarity between texts and determine if they are paraphrases. The system would tokenize, stem, remove stopwords and part-of-speech tag input texts before applying the neural network. It evaluates the approach on datasets like SNLI and QQP and compares performance to existing methods.
Dynamic framed slotted aloha algorithms using fast tag estimationambitlick
This document summarizes a paper that proposes a Dynamic Framed Slotted ALOHA (DFSA) algorithm using a proposed Tag Estimation Method (TEM) to estimate the number of tags around a reader. The DFSA algorithm dynamically allocates the frame size according to the estimated number of tags. Simulation results show the DFSA algorithm has better performance and lower delay than conventional algorithms regardless of the number of tags.
The document proposes a fuzzy incremental feature clustering algorithm to reduce the dimensionality of feature vectors for text classification. Some limitations of existing feature clustering methods include requiring the user to specify the number of clusters in advance and not considering variance within clusters. The new algorithm uses fuzzy logic to automatically determine the number of clusters formed, and each cluster is characterized by a membership function and statistical mean and variance. This results in features being extracted that better match the real distribution of training data.
Without analytics on big data, companies are unable to understand their environment and customers, similar to how deer cannot see or hear approaching vehicles on a highway. Presentations are tools that can be used for lectures, reports, and more. They serve various purposes, making presentations powerful tools for convincing and teaching others. Data science uses techniques from multiple fields like mathematics, statistics, and computer science to analyze large amounts of data and extract meaningful insights for business.
Programming in Civil Engineering_UNIT 2_NOTESRushikesh Kolhe
This document provides an introduction to data types and variables in Python. It discusses that Python is a dynamically typed language where the type of a variable is determined at runtime. It describes various Python data types including numeric, sequence, mapping, set, boolean, and binary types. It also discusses variable naming conventions and that variables are created by assignment. Finally, it explains the differences between mutable and immutable data types.
This document discusses strings in Python. It begins by defining strings as sequences of characters that can be represented using single or double quotes. It then discusses some key reasons why strings are important in programming, including text representation, input/output handling, and text processing. It also covers string literals, operations like repetition, membership, slicing, and concatenation. Finally, it discusses some real-world applications of strings like spell checkers, search engines, and information retrieval systems.
This document provides an introduction to algorithms and data structures. It defines key terms like data, data types, data structures, algorithms, complexity analysis, and common algorithm design strategies. Linear and non-linear data structures are described, as are static and dynamic data structures. Examples of common algorithms like sorting, searching and graph algorithms are provided. Complexity analysis techniques like Big O notation are introduced to analyze algorithms. Problem-solving techniques like divide-and-conquer and greedy algorithms are summarized along with examples like minimum spanning trees.
Computer Programming Chapter 6 : Array and ArrayListAtit Patumvan
This document summarizes key aspects of arrays and arraylists in Java. It discusses that an array is a fundamental data structure for storing a collection of data elements of the same type. Each element in an array can be referenced using an index. The document also provides examples of declaring and initializing arrays, accessing array elements, and common operations like finding the sum and average of array elements.
Data Type is a basic classification which identifies.docxtheodorelove43763
Data Type is a basic classification which identifies different types of data.Data Types helps in:Determining the possible values of a variablePossible operations which can be executed on the typeMeaning of the dataDifferent ways to store the data
Data Types are of different types:
Primitive data Types
Composite Data Types
*
Primitive data types are those data types which are not defined in terms of other data types.
Examples are:
Integer
Floating Point
Boolean
Character
*
NOTE: primitive here is not the same as how we use it when referring to the primitive types in Java even though they are mostly the same types. By primitive, we mean directly supported by hardware. Strings do not appear in this list because strings are rarely supported directly in hardware, instead they are stored as individual characters and linked together through some mechanism implemented by the programming language (usually as arrays of characters).
What about pointer types? You’ll notice that they do not appear above. Typically, pointers are just unsigned int values. But we treat pointers differently than ints because we do not permit pointer arithmetic (except in a few languages) and require dereferencing of some kind. Dereferencing may be directly supported in hardware by having indirect addressing modes.
Integers are used to hold integer values only.This is further categorized into:
byte
short
int
long
signed
Unsigned
Examples are:
unsigned int x = 21234;
unsigned int y = 31234;
unsigned int z;
z = x + y;
This data type contains decimal points.Examples are:
float f = 20.0 / 3.0;
Current standard version of floating-point
Single-precision (float)
One word: 1 sign bit, 23 bit fraction, 8 bit exponent
Positive range: 1.17549435 × 10-38 … 3.40282347 × 10+38
Double-precision (double)
Two words: 1 sign bit, 52 bit fraction, 11 bit exponent
Positive range: 2.2250738585072014 × 10-308 … 1.7976931348623157 × 10+308
*
Boolean Data type is used to store logical value.It can have either True or False value.It is a one bit representation0 represents false value1 represents true valueExample: Boolean a;
a=true;
Roman alphabet, punctuation, digits, and other symbols:Can encode within one byte (256 symbols)
In C:
char a_char = ’a’;
char newline_char = ’\n’;
char tab_char = ’\t’;
char backslash_char = ’\\’;
These data types are derived from more than one primitive data type.Examples are:
Arrays
Records
Structure
Union
Arrays are a finite sequence of variables of the same data type These are commonly implemented by the compiler generating array descriptors for each array
here we have
descriptors for
1-D and multi-D
arrays
*
Records are Varied aggregate of data elementsThe elements of a record are known as fields or membersRecords were introduced in COBOLThis data type is used in many languages.In Java, the functionality of records are achieved through the use of classes
Examples:
COBOL (nested structure.
This document discusses using machine learning algorithms to predict employee attrition and understand factors that influence turnover. It evaluates different machine learning models on an employee turnover dataset to classify employees who are at risk of leaving. Logistic regression and random forest classifiers are applied and achieve accuracy rates of 78% and 98% respectively. The document also discusses preprocessing techniques and visualizing insights from the models to better understand employee turnover.
This document proposes a model to detect outliers in online writing samples using stylometry and an outlier detection algorithm. It involves three phases: 1) Analyzing writing samples using stylometric features to determine writing style. 2) Selecting parameters that characterize an individual's writing uniqueness. 3) Detecting outliers, defined as unexpected parameter values, by comparing values to predefined thresholds using an outlier detection algorithm. The goal is to identify authors and detect unauthorized writing samples. Stylometry analyzes linguistic features while the algorithm identifies samples outside normal writing patterns.
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NumPy is the primary library for array programming in Python. It provides a multidimensional array object and array-aware functions that operate on the array. NumPy arrays store data and metadata like data type, shape, and strides to efficiently access and manipulate multidimensional data. Users interact with NumPy arrays using indexing to access elements and subarrays, operators for element-wise operations, and functions that perform vectorized calculations on entire arrays. NumPy handles looping over array elements to optimize performance while providing a simple and powerful programming interface for scientific computing in Python.
This document summarizes different data types including numeric, enumeration, Boolean, character, character strings, pointers, files, and input-output. It provides details on integer, floating-point real numbers, fixed-point real numbers, character strings, and pointers and programmer-constructed data objects. Integer data types can represent a finite set of mathematical integers and have different sizes and may or may not contain negative values. Floating-point numbers use a mantissa-exponent representation similar to scientific notation. Fixed-point numbers have a predefined number of decimal places. Character strings can have fixed or variable lengths and support operations like concatenation and substring selection. Pointers reference data in memory and programmer-constructed objects can be complex data
This document summarizes different data types including numeric, enumeration, Boolean, character, character strings, pointers, files, and input-output. It provides details on integer, floating-point real numbers, fixed-point real numbers, character strings, and pointers and programmer-constructed data objects. Integer data types can represent a finite set of mathematical integers and have different sizes and may or may not contain negative values. Floating-point numbers use a mantissa-exponent representation similar to scientific notation. Fixed-point numbers have a predefined number of decimal places. Character strings can have fixed or variable lengths and support operations like concatenation and substring selection. Pointers reference data in memory and programmer-constructed objects can be complex data
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Introduction to Python Objects and StringsSangeetha S
This document provides an introduction and overview of Python programming presented by Dr. S. Sangeetha from the Department of Computer Applications at the National Institute of Technology in Tiruchirappalli, India. It discusses Python's history and features, working environments like Anaconda and Conda, data types, operators, objects, variables and garbage collection, strings, formatting, and basics of writing Python programs.
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Similar to OOP Chapter 4: Data Type and Expressions (17)
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An Overview of eZee Burrp! (Philus Limited)Atit Patumvan
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Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
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ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...
OOP Chapter 4: Data Type and Expressions
1. Object-Oriented Programming Language
Chapter 4 : Data Types and Expressions
Atit Patumvan
Faculty of Management and Information Sciences
Naresuna University
Monday, February 20, 12
2. 2
Contents
• Data Types and Constants
• Arithmetic Expressions
• Assignment Operators
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
3. 3
Data Type and Constant
data_type identifier = value;
identifier
value
data_type
int number = 25; copy 25
number
25
int
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
4. 4
Data Types in Objective-C
Type Descriptions Size
char A character of the local character set 1 bytes
int An integer (whole numbers) 4 bytes
float Floating point number 4 bytes
short A short integer 2 bytes
long A double short 4 bytes
long long A double long 8 bytes
double Double precision float 8 bytes
BOOL
id An object 4 bytes
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
5. 5
Uses the basic Objective-C data types
Program 4.1
01: #import <Foundation/Foundation.h>
02:
03: int main(int argc, char *argv[]) {
04:! @autoreleasepool {
05:! ! int integerVar = 100;
06:! ! float floatingVar = 331.79;
07:! ! double doubleVar = 8.44e-11;
08:! ! char charVar = 'w';
09:! !
10:! ! NSLog(@"integerVar = %i", integerVar);
11:! ! NSLog(@"floatVar = %f", floatingVar);
12:! ! NSLog(@"doubleVar = %e", doubleVar);
13:! ! NSLog(@"doubleVar = %g", doubleVar);
14:! ! NSLog(@"charVar = %c", charVar);
15: }
integerVar = 100
floatVar = 331.790009
doubleVar = 8.440000e-11
doubleVar = 8.44e-11
charVar = w
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
6. 6
Basic Data Types
Type Constant Example NSLog chars
char a’, ‘n’ %c
short int - %hi, %hx, %ho
unsigned short int - %hu, %hx, %ho
int 12, -97, 0xFFE0, 0177 %i, %x, %o
unsigned int 12u, 100U, 0xFFu %u, %x, %o
long int 12L, -2001l, 0xffffL %li, %lx, %lo
unsigned long int 12UL, 100ul, 0xffeeUL %lu, %lx, %lo
long long int 0xe5e5e5e5LL, 500ll %lli, %llx, %llo
unsigned long long 12ull, 0xffeeULL %llu, % llx,
int
float 12.43f, 3.1e-5f, 0x1.5p10, %llo
%f, %e, %g, %a
double 0x1p-1
12.34, 3.1e-5, 0x.1p3 %f, %e, %g, %a
long double 12.34L, 3.1e-5l %Lf, %Le, %Lg
id nil %p
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
7. 7
Arithmetic Expression
Program 4.3
05:
06: int a = 2; a - b = 98
07:! ! int b = 2; b * c = 50
08:! ! int c = 25; a / c = 4
09:! ! int d = 4; a + b * c = 150
10:! ! int result; a * b + c * d = 300
11:! !
12:! ! result = a - b;!// subtraction
13:! ! NSLog(@"a - b = %i", result);
14:
15:! ! result = b * c;!// multiplication
16:! ! NSLog(@"b * c = %i", result);
17:! !
18:! ! result = a / c;!// division
19:! ! NSLog(@"a / c = %i", result);
20:
21:! ! result = a + b * c;! // precedence
22:! ! NSLog(@"a + b * c = %i", result);
23:! !
24:! ! NSLog(@"a * b + c * d = %i", a * b + c * d);
25:!
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
8. 8
Integer Arithmetic and Unary Minus Operator
Program 4.3
05:
06:! int a = 25;
07:! ! int b = 2;
08:! ! float c = 25.0;
09:! ! float d = 2.0;
10:! !
11:! ! NSLog(@"6 + a / 5 * b = %i", 6 + a / 5 * b);
12:! ! NSLog(@"a / b * b = %i", a / b * b);
13:! ! NSLog(@"c / d * d = %f", c / d * d);
14:! ! NSLog(@"-a = %i", -a);
15:!
6 + a / 5 * b = 16
a / b * b = 24
c / d * d = 25.000000
-a = -25
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
9. 9
The Modulus Operator
Program 4.4
05:
06:! int a = 25, b = 5, c = 10, d =7;
07:!
08:! NSLog(@"a %% b = %i", a % b);
09:! NSLog(@"a %% c = %i", a % c);
10:! NSLog(@"a %% d = %i", a % d);
11:! NSLog(@"a / d * d + a %% d = %i", a / d * d + a % d);
12:!
a % b = 0
a % c = 5
a % d = 4
a / d * d + a % d = 25
a /d * d+ a % d = ((a / d) * d)+(a % d)
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
10. 10
Integer and Floating-Point Conversion
Program 4.5
05:
06:! float f1 = 123.125, f2;
07:! int i1, i2 = -150;
08:!
09:! i1 = f1; // floating to integer convision
10:! NSLog(@"%f assigned to an int produces %i", f1, i1);
11:!
12:! f1 = i2; // integer to floating convision
13:! NSLog(@"%i assigned to a float produces %f", i2, f1);
14:!
15:! f1 = i2 / 100; // integer divided by integer
16:! NSLog(@"%i divided by 100 produces %f", i2, f1);
17:!
18:! f2 = i2 /100.0; // integer divided by float
19:! NSLog(@"%i divided by 100.0 produce %f", i2, f2);
20:!
21:! f2 = (float) i2 / 100; // type cast operator
22:! NSLog(@"(float) %i divided by 100 produces %f", i2, f2);
123.125000 assigned to an int produces 123
-150 assigned to a float produces -150.000000
-150 divided by 100 produces -1.000000
-150 divided by 100.0 produce -1.500000
(float) -150 divided by 100 produces -1.500000
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
11. 11
The Type Case Operator
int i2 = 25;
float f2 = (float) i2 / 5; // type cast operator
int s1 = (int) 29.55 + (int) 21.99;
int s2 = 29 + 21;
float f3 = (float) 6 / (float) 4
float f4 = (float) 6 / 4
id myNumber;
Fraction * myFraction;
myFraction = (Fraction *) myNumber;
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
12. 12
Assignment Operator
count += 10;
count = count +10;
counter -= 5;
counter = counter - 5;
a /= b + c;
a = a / (b + c);
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
13. 13
Increment and Decrement Operator
count++;
count = count + 1;
counter--;
counter = counter - 1;
a /= b + c;
a = a / (b + c);
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12
14. 14
Desk Calculator
Program 4.6
48:
49:! int main(int argc, char *argv[]) {
50:! ! @autoreleasepool {
51:! ! ! Calculator * deskCalc = [[Calculator alloc] init];
52:! ! ! [deskCalc setAccumulator: 100.0];
53:! ! !
54:! ! ! [deskCalc add: 200.];
55:! ! ! [deskCalc divide: 15.0];
56:! ! ! [deskCalc subtract: 10.0];
57:! ! ! [deskCalc multiply: 5]; Calculator
58:! ! !
59:! ! ! NSLog(@"The result is % g", [deskCalc accumulator]);
60:! ! ! accumulator:double
61:! ! ! [deskCalc release];
62:! ! }
63:! } setAccumulator(double):void
64:! clear:void
accumulator:double
add(double):void
The result is 50 subtract(double):void
multiply(double):void
divide(double):void
Atit Patumvan, Faculty of Management and Information Sciences, Naresuan University Object-Oriented Programming Language
Monday, February 20, 12