Slides in this presentation are based on various talks attended at IIT Bombay. Also papers related to scientific writing published by IEEE are used in this study.
The document discusses various information retrieval models, including:
1) Classic models like Boolean and vector space models that use index terms to represent documents and queries.
2) Probabilistic models that view IR as estimating the probability of relevance between documents and queries.
3) Structured models that incorporate document structure, including models based on non-overlapping text regions and hierarchical document structure.
4) Browsing models like flat, structure-guided, and hypertext models for navigating document collections.
The document discusses search engines and their history and functioning. It explains that search engines use crawler programs to index web pages and gather keywords to help users find relevant information quickly from the vast World Wide Web. The first search engine Archie was released in 1990 and search engines have since evolved, with companies like Google becoming leaders by consistently improving their algorithms to better understand users' search needs.
Vector space model or term vector model is an algebraic model for representing text documents as vectors of identifiers, such as, for example, index terms. It is used in information filtering, information retrieval, indexing and relevancy rankings. Its first use was in the SMART Information Retrieval System
Coupling refers to the interdependence between software modules. There are several types of coupling from loose to tight, with the tightest being content coupling where one module relies on the internal workings of another. Cohesion measures how strongly related the functionality within a module is, ranging from coincidental to functional cohesion which is the strongest. Tight coupling and low cohesion can make software harder to maintain and reuse modules.
This document presents information on cost estimation using the COCOMO model. It discusses the basic, intermediate, and detailed COCOMO models. The basic model uses effort multipliers, staff size, and productivity equations to estimate effort and schedule for projects of different modes (organic, embedded, semidetached). The intermediate model adds 15 cost drivers to improve accuracy. The detailed model incorporates three product levels, phase-sensitive effort multipliers, and effort/time fractions for each development phase.
The document discusses different approaches to generating biographies through natural language processing, including information extraction and language modeling. It describes using information extraction patterns learned from Wikipedia to extract fields like date of birth and place of birth, and bouncing between Wikipedia and Google search results to learn patterns for other fields with less structured data. It also proposes selecting and ranking sentences from search results to improve recall when information extraction may miss relevant sentences. The goal is to build biographies by combining these techniques for high precision on structured fields and better recall on more complex fields.
White box testing involves testing internal program structure and code. It includes static testing like code reviews and structural testing like unit testing. Static testing checks code against requirements without executing. Structural testing executes code to test paths and conditions. Code coverage metrics like statement coverage measure what code is executed by tests. Code complexity metrics like cyclomatic complexity quantify complexity to determine necessary test cases. White box testing finds defects from incorrect code but may miss realistic errors and developers can overlook own code issues.
The document discusses various information retrieval models, including:
1) Classic models like Boolean and vector space models that use index terms to represent documents and queries.
2) Probabilistic models that view IR as estimating the probability of relevance between documents and queries.
3) Structured models that incorporate document structure, including models based on non-overlapping text regions and hierarchical document structure.
4) Browsing models like flat, structure-guided, and hypertext models for navigating document collections.
The document discusses search engines and their history and functioning. It explains that search engines use crawler programs to index web pages and gather keywords to help users find relevant information quickly from the vast World Wide Web. The first search engine Archie was released in 1990 and search engines have since evolved, with companies like Google becoming leaders by consistently improving their algorithms to better understand users' search needs.
Vector space model or term vector model is an algebraic model for representing text documents as vectors of identifiers, such as, for example, index terms. It is used in information filtering, information retrieval, indexing and relevancy rankings. Its first use was in the SMART Information Retrieval System
Coupling refers to the interdependence between software modules. There are several types of coupling from loose to tight, with the tightest being content coupling where one module relies on the internal workings of another. Cohesion measures how strongly related the functionality within a module is, ranging from coincidental to functional cohesion which is the strongest. Tight coupling and low cohesion can make software harder to maintain and reuse modules.
This document presents information on cost estimation using the COCOMO model. It discusses the basic, intermediate, and detailed COCOMO models. The basic model uses effort multipliers, staff size, and productivity equations to estimate effort and schedule for projects of different modes (organic, embedded, semidetached). The intermediate model adds 15 cost drivers to improve accuracy. The detailed model incorporates three product levels, phase-sensitive effort multipliers, and effort/time fractions for each development phase.
The document discusses different approaches to generating biographies through natural language processing, including information extraction and language modeling. It describes using information extraction patterns learned from Wikipedia to extract fields like date of birth and place of birth, and bouncing between Wikipedia and Google search results to learn patterns for other fields with less structured data. It also proposes selecting and ranking sentences from search results to improve recall when information extraction may miss relevant sentences. The goal is to build biographies by combining these techniques for high precision on structured fields and better recall on more complex fields.
White box testing involves testing internal program structure and code. It includes static testing like code reviews and structural testing like unit testing. Static testing checks code against requirements without executing. Structural testing executes code to test paths and conditions. Code coverage metrics like statement coverage measure what code is executed by tests. Code complexity metrics like cyclomatic complexity quantify complexity to determine necessary test cases. White box testing finds defects from incorrect code but may miss realistic errors and developers can overlook own code issues.
1. Incorrect dimension of matrices. Matrix multiplication is only defined if the number of columns of the first matrix is equal to the number of rows of the second matrix.
2. Off-by-one errors in loops. Loop indices may not be correctly iterating over all elements of the matrices.
3. Input/output errors. Matrices may not be input or output correctly, leading to invalid data.
4. Logical errors. The algorithm to multiply matrices cell-by-cell may contain flaws in how it calculates the results.
Stemming And Lemmatization Tutorial | Natural Language Processing (NLP) With ...Edureka!
( **Natural Language Processing Using Python: - https://www.edureka.co/python-natural... ** )
This PPT will provide you with detailed and comprehensive knowledge of the two important aspects of Natural Language Processing ie. Stemming and Lemmatization. It will also provide you with the differences between the two with Demo on each. Following are the topics covered in this PPT:
Introduction to Big Data
What is Text Mining?
What is NLP?
Introduction to Stemming
Introduction to Lemmatization
Applications of Stemming & Lemmatization
Difference between stemming & Lemmatization
Follow us to never miss an update in the future.
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NLP is the branch of computer science focused on developing systems that allow computers to communicate with people using everyday language. Also called Computational Linguistics – Also concerns how computational methods can aid the understanding of human language
Type checking is the process of verifying that each operation in a program respects the type system of the language. There are two types of type checking: static and dynamic. Static type checking is done at compile-time to check for type errors, flow errors, and other semantic checks. Dynamic type checking occurs at runtime by including type information for each data location to check for errors like divide-by-zero or out-of-range indexes. A type system assigns type expressions to program components through a set of rules implemented by a type checker to eliminate runtime type errors.
Coding is new literacy and you shouldn't miss the chance to learn to code. Not only you but your children should learn to code. Learn more about coding in a fun and easy way with RoboGarden.
RoboGarden is an easy to understand, hands-on educational app where students take part in active learning. Fully equipped to teach coding literacy from scratch, RoboGarden reduces the need for a tech-savvy teacher.
For More info Please visit: www.robogarden.ca
The document defines an SRS as the official statement of what system developers should implement, providing a complete description of the system behavior. An SRS precisely defines the software product and is used to understand requirements to design the software. It includes the purpose, product scope, features, interfaces, and other functional and non-functional requirements. The SRS benefits include establishing agreement between customers and suppliers, reducing development effort, and providing a baseline for validation.
The document provides an overview of data science applications and use cases. It defines data science as using computer science, statistics, machine learning and other techniques to analyze data and create data products to help businesses make better decisions. It discusses big data challenges, the differences between data science and software engineering, and key areas of data science competence including data analytics, engineering, domain expertise and data management. Finally, it outlines several common data science applications and use cases such as recommender systems, credit scoring, dynamic pricing, customer churn analysis and fraud detection with examples of how each works and real world cases.
The document discusses several process models for software development projects, including code and fix, waterfall, incremental/iterative, spiral, rapid application development (RAD), and concurrent development models. Each model has advantages and disadvantages depending on factors like project size, requirements stability, and team expertise. Combinations of models may also be suitable in some cases.
The document discusses coding guidelines and best practices for software development. It covers topics like coding standards, programming practices, documentation, and code verification techniques. The key points are that coding follows design, modules should be independently coded and tested, documentation is important, and reviews/testing help verify code quality.
This document discusses different process models used in software development. It describes the key phases and characteristics of several common process models including waterfall, prototyping, V-model, incremental, iterative, spiral and agile development models. The waterfall model involves sequential phases from requirements to maintenance without iteration. Prototyping allows for user feedback earlier. The V-model adds verification and validation phases. Incremental and iterative models divide the work into smaller chunks to allow for iteration and user feedback throughout development.
This document is the preface to the book "Python for Everybody" by Dr. Charles R. Severance. It discusses how the book was created by remixing and adapting the existing book "Think Python" under a more open license, with the goal of shifting the focus from computer science to data analysis using Python. Major changes were made to reorder and replace topics with a data-oriented approach. The preface provides background on the motivation and process for creating this new textbook.
This document provides an overview of problem solving using computers. It discusses the 7 stages of problem solving: 1) problem analysis, 2) algorithm development, 3) flowcharting, 4) coding, 5) compilation and execution, 6) debugging and testing, and 7) documentation. It also covers computer programs, programming languages, and the basic structure of a C program, which typically includes documentation, include libraries, definitions, global declarations, the main function, and subprograms.
This document provides an overview of decision trees, including:
- Decision trees classify records by sorting them down the tree from root to leaf node, where each leaf represents a classification outcome.
- Trees are constructed top-down by selecting the most informative attribute to split on at each node, usually based on information gain.
- Trees can handle both numerical and categorical data and produce classification rules from paths in the tree.
- Examples of decision tree algorithms like ID3 that use information gain to select the best splitting attribute are described. The concepts of entropy and information gain are defined for selecting splits.
Python is a general purpose programming language created by Guido van Rossum in 1991. It is an interpreted, interactive, object-oriented language with a simple syntax. Python supports cross-platform development and is widely used for scripting, game development, and building desktop and mobile applications. To use Python, developers must download the Python interpreter and can write and run code using the interactive shell or integrated development environments like IDLE. The document then discusses Python's multi-paradigm programming style, advantages like rapid development, and how to install Python and write basic programs using variables, operators, and data types.
Software project management Improving Team EffectivenessREHMAT ULLAH
This document discusses improving team effectiveness for software project management. It emphasizes that managing the team is key and a well-managed team can overcome other shortcomings. Some recommendations include using top talent and fewer people, properly matching skills and motivations to jobs, allowing career progression, balancing the team's skills and personalities, and phasing out underperforming team members. Overall, the most important factors for an effective team are teamwork, balance, strong leadership that keeps the team together and recognizes both individual and group needs.
The document discusses modelling and evaluation in machine learning. It defines what models are and how they are selected and trained for predictive and descriptive tasks. Specifically, it covers:
1) Models represent raw data in meaningful patterns and are selected based on the problem and data type, like regression for continuous numeric prediction.
2) Models are trained by assigning parameters to optimize an objective function and evaluate quality. Cross-validation is used to evaluate models.
3) Predictive models predict target values like classification to categorize data or regression for continuous targets. Descriptive models find patterns without targets for tasks like clustering.
4) Model performance can be affected by underfitting if too simple or overfitting if too complex,
Slides from the first week of our Information Ethics module, taught by Jenny Delasalle & Boris Jacob at Humboldt University's institute of library & information science https://www.ibi.hu-berlin.de/en
Made available in accordance with the terms of the Creative Commons Attribution-Noncommercial licence: https://creativecommons.org/licenses/by-nc/3.0/
What is Quality ||
Software Quality Metrics ||
Types of Software Quality Metrics ||
Three groups of Software Quality Metrics ||
Customer Satisfaction Metrics ||
Tools used for Quality Metrics/Measurements ||
PERT and CPM ||
This document discusses various software metrics that can be used for software estimation, quality assurance, and maintenance. It describes black box metrics like function points and COCOMO, which focus on program functionality without examining internal structure. It also covers white box metrics, including lines of code, Halstead's software science, and McCabe's cyclomatic complexity, which measure internal program properties. Finally, it discusses using metrics like change rates and effort adjustment factors to estimate software maintenance costs.
This document provides an overview of natural language processing (NLP). It discusses how NLP analyzes human language input to build computational models of language. The key components of NLP are natural language understanding and natural language generation. Challenges in NLP include ambiguity, context dependence, and the creative nature of language. The document also outlines common NLP techniques like keyword analysis and syntactic parsing, as well as formal grammars and parsing approaches.
Thesis statements and the drafting process helpSusan Bolling
Here are revised thesis statements for the prompts:
- The death penalty is a controversial issue.
While the death penalty remains a controversial issue, DNA evidence has significantly reduced wrongful convictions and shifted the debate by prioritizing accuracy and justice over speedy resolutions.
- This novel had an important impact on my life.
Steinbeck's vivid portrayal of the struggles of migrant farmers during the Great Depression in The Grapes of Wrath ignited my passion for learning how historical forces shape individual lives and communities.
- What would the consequences of censorship on the Internet be?
Unrestricted access to information and freedom of expression are cornerstones of democracy; however, censorship proponents argue it prevents harm. This essay will
This document outlines an assignment for students to write a 4-7 page essay analyzing one of several short stories. It provides guidance on choosing an aspect of the story to analyze, formulating a thesis, including textual evidence, and following MLA formatting standards. Students are instructed to ask critical questions about their chosen aspect and use these questions to develop an argument about the author's style, purpose, characters, symbolism or other elements. The document provides best practices and things for students to avoid in completing the assignment successfully.
1. Incorrect dimension of matrices. Matrix multiplication is only defined if the number of columns of the first matrix is equal to the number of rows of the second matrix.
2. Off-by-one errors in loops. Loop indices may not be correctly iterating over all elements of the matrices.
3. Input/output errors. Matrices may not be input or output correctly, leading to invalid data.
4. Logical errors. The algorithm to multiply matrices cell-by-cell may contain flaws in how it calculates the results.
Stemming And Lemmatization Tutorial | Natural Language Processing (NLP) With ...Edureka!
( **Natural Language Processing Using Python: - https://www.edureka.co/python-natural... ** )
This PPT will provide you with detailed and comprehensive knowledge of the two important aspects of Natural Language Processing ie. Stemming and Lemmatization. It will also provide you with the differences between the two with Demo on each. Following are the topics covered in this PPT:
Introduction to Big Data
What is Text Mining?
What is NLP?
Introduction to Stemming
Introduction to Lemmatization
Applications of Stemming & Lemmatization
Difference between stemming & Lemmatization
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
NLP is the branch of computer science focused on developing systems that allow computers to communicate with people using everyday language. Also called Computational Linguistics – Also concerns how computational methods can aid the understanding of human language
Type checking is the process of verifying that each operation in a program respects the type system of the language. There are two types of type checking: static and dynamic. Static type checking is done at compile-time to check for type errors, flow errors, and other semantic checks. Dynamic type checking occurs at runtime by including type information for each data location to check for errors like divide-by-zero or out-of-range indexes. A type system assigns type expressions to program components through a set of rules implemented by a type checker to eliminate runtime type errors.
Coding is new literacy and you shouldn't miss the chance to learn to code. Not only you but your children should learn to code. Learn more about coding in a fun and easy way with RoboGarden.
RoboGarden is an easy to understand, hands-on educational app where students take part in active learning. Fully equipped to teach coding literacy from scratch, RoboGarden reduces the need for a tech-savvy teacher.
For More info Please visit: www.robogarden.ca
The document defines an SRS as the official statement of what system developers should implement, providing a complete description of the system behavior. An SRS precisely defines the software product and is used to understand requirements to design the software. It includes the purpose, product scope, features, interfaces, and other functional and non-functional requirements. The SRS benefits include establishing agreement between customers and suppliers, reducing development effort, and providing a baseline for validation.
The document provides an overview of data science applications and use cases. It defines data science as using computer science, statistics, machine learning and other techniques to analyze data and create data products to help businesses make better decisions. It discusses big data challenges, the differences between data science and software engineering, and key areas of data science competence including data analytics, engineering, domain expertise and data management. Finally, it outlines several common data science applications and use cases such as recommender systems, credit scoring, dynamic pricing, customer churn analysis and fraud detection with examples of how each works and real world cases.
The document discusses several process models for software development projects, including code and fix, waterfall, incremental/iterative, spiral, rapid application development (RAD), and concurrent development models. Each model has advantages and disadvantages depending on factors like project size, requirements stability, and team expertise. Combinations of models may also be suitable in some cases.
The document discusses coding guidelines and best practices for software development. It covers topics like coding standards, programming practices, documentation, and code verification techniques. The key points are that coding follows design, modules should be independently coded and tested, documentation is important, and reviews/testing help verify code quality.
This document discusses different process models used in software development. It describes the key phases and characteristics of several common process models including waterfall, prototyping, V-model, incremental, iterative, spiral and agile development models. The waterfall model involves sequential phases from requirements to maintenance without iteration. Prototyping allows for user feedback earlier. The V-model adds verification and validation phases. Incremental and iterative models divide the work into smaller chunks to allow for iteration and user feedback throughout development.
This document is the preface to the book "Python for Everybody" by Dr. Charles R. Severance. It discusses how the book was created by remixing and adapting the existing book "Think Python" under a more open license, with the goal of shifting the focus from computer science to data analysis using Python. Major changes were made to reorder and replace topics with a data-oriented approach. The preface provides background on the motivation and process for creating this new textbook.
This document provides an overview of problem solving using computers. It discusses the 7 stages of problem solving: 1) problem analysis, 2) algorithm development, 3) flowcharting, 4) coding, 5) compilation and execution, 6) debugging and testing, and 7) documentation. It also covers computer programs, programming languages, and the basic structure of a C program, which typically includes documentation, include libraries, definitions, global declarations, the main function, and subprograms.
This document provides an overview of decision trees, including:
- Decision trees classify records by sorting them down the tree from root to leaf node, where each leaf represents a classification outcome.
- Trees are constructed top-down by selecting the most informative attribute to split on at each node, usually based on information gain.
- Trees can handle both numerical and categorical data and produce classification rules from paths in the tree.
- Examples of decision tree algorithms like ID3 that use information gain to select the best splitting attribute are described. The concepts of entropy and information gain are defined for selecting splits.
Python is a general purpose programming language created by Guido van Rossum in 1991. It is an interpreted, interactive, object-oriented language with a simple syntax. Python supports cross-platform development and is widely used for scripting, game development, and building desktop and mobile applications. To use Python, developers must download the Python interpreter and can write and run code using the interactive shell or integrated development environments like IDLE. The document then discusses Python's multi-paradigm programming style, advantages like rapid development, and how to install Python and write basic programs using variables, operators, and data types.
Software project management Improving Team EffectivenessREHMAT ULLAH
This document discusses improving team effectiveness for software project management. It emphasizes that managing the team is key and a well-managed team can overcome other shortcomings. Some recommendations include using top talent and fewer people, properly matching skills and motivations to jobs, allowing career progression, balancing the team's skills and personalities, and phasing out underperforming team members. Overall, the most important factors for an effective team are teamwork, balance, strong leadership that keeps the team together and recognizes both individual and group needs.
The document discusses modelling and evaluation in machine learning. It defines what models are and how they are selected and trained for predictive and descriptive tasks. Specifically, it covers:
1) Models represent raw data in meaningful patterns and are selected based on the problem and data type, like regression for continuous numeric prediction.
2) Models are trained by assigning parameters to optimize an objective function and evaluate quality. Cross-validation is used to evaluate models.
3) Predictive models predict target values like classification to categorize data or regression for continuous targets. Descriptive models find patterns without targets for tasks like clustering.
4) Model performance can be affected by underfitting if too simple or overfitting if too complex,
Slides from the first week of our Information Ethics module, taught by Jenny Delasalle & Boris Jacob at Humboldt University's institute of library & information science https://www.ibi.hu-berlin.de/en
Made available in accordance with the terms of the Creative Commons Attribution-Noncommercial licence: https://creativecommons.org/licenses/by-nc/3.0/
What is Quality ||
Software Quality Metrics ||
Types of Software Quality Metrics ||
Three groups of Software Quality Metrics ||
Customer Satisfaction Metrics ||
Tools used for Quality Metrics/Measurements ||
PERT and CPM ||
This document discusses various software metrics that can be used for software estimation, quality assurance, and maintenance. It describes black box metrics like function points and COCOMO, which focus on program functionality without examining internal structure. It also covers white box metrics, including lines of code, Halstead's software science, and McCabe's cyclomatic complexity, which measure internal program properties. Finally, it discusses using metrics like change rates and effort adjustment factors to estimate software maintenance costs.
This document provides an overview of natural language processing (NLP). It discusses how NLP analyzes human language input to build computational models of language. The key components of NLP are natural language understanding and natural language generation. Challenges in NLP include ambiguity, context dependence, and the creative nature of language. The document also outlines common NLP techniques like keyword analysis and syntactic parsing, as well as formal grammars and parsing approaches.
Thesis statements and the drafting process helpSusan Bolling
Here are revised thesis statements for the prompts:
- The death penalty is a controversial issue.
While the death penalty remains a controversial issue, DNA evidence has significantly reduced wrongful convictions and shifted the debate by prioritizing accuracy and justice over speedy resolutions.
- This novel had an important impact on my life.
Steinbeck's vivid portrayal of the struggles of migrant farmers during the Great Depression in The Grapes of Wrath ignited my passion for learning how historical forces shape individual lives and communities.
- What would the consequences of censorship on the Internet be?
Unrestricted access to information and freedom of expression are cornerstones of democracy; however, censorship proponents argue it prevents harm. This essay will
This document outlines an assignment for students to write a 4-7 page essay analyzing one of several short stories. It provides guidance on choosing an aspect of the story to analyze, formulating a thesis, including textual evidence, and following MLA formatting standards. Students are instructed to ask critical questions about their chosen aspect and use these questions to develop an argument about the author's style, purpose, characters, symbolism or other elements. The document provides best practices and things for students to avoid in completing the assignment successfully.
This document provides guidance on various aspects of academic writing such as understanding essay topics, organizing an essay, reading and researching, using sources, revising writing, and specific types of writing. It discusses key elements like introductions, conclusions, paragraphs, topic sentences, taking notes, paraphrasing, summarizing, and identifying and fixing sentence fragments. The document aims to offer students advice to improve their academic writing skills.
This document provides instructions for writing a response essay analyzing a novel read in class. Students are asked to write a 4-7 page thesis-driven essay analyzing one or more aspects of the novel using a critical lens like feminist, psychoanalytic, or trauma theory. The essay should have an introduction with a clear thesis, body paragraphs using evidence from the text to support the thesis, and a conclusion. Guidelines are provided on choosing a topic, asking analytical questions, formulating a thesis, writing each section of the paper, using proper MLA citation style, and expected learning outcomes.
The document provides guidance on effective note-taking strategies for research. It discusses preparing for note-taking by knowing what information to include or exclude. It also discusses different note-taking strategies like quoting, paraphrasing, summarizing, and précis writing. The document emphasizes the importance of avoiding plagiarism by properly citing sources and strategies for developing bibliographies.
This document provides instructions for writing an essay analyzing one of several short stories read in class. Students are asked to choose an aspect of the story to analyze, such as the author's style or symbolism, and write a 4-7 page thesis-driven essay making an argument about their chosen aspect. The essay should include an introduction with thesis, body paragraphs with analysis supported by evidence from the story, and a conclusion. Guidelines are provided on developing a thesis, writing each section of the paper, and citing sources. The goal is for students to practice critical analysis and writing skills.
This document provides guidance for writing an essay analyzing a short story from the assigned reading list. Students are instructed to write a 4-7 page thesis-driven essay analyzing one or more aspects of one of the stories through close reading and using rhetorical strategies and critical lenses discussed in class. The essay should have an introduction with a clear thesis statement, body paragraphs developing the analysis with evidence from the text, and a conclusion wrapping up the argument. Formatting should follow MLA style. The document outlines steps for choosing a focal point, asking analytical questions, formulating a thesis, writing the introduction and body, and concluding the essay.
How to publish a technical paper in SCI Journals?Ajay Kumar
This document provides instructions on how to write a technical research paper and publish it in a scientific journal. It discusses choosing a topic and narrowing it, creating an outline, avoiding plagiarism by paraphrasing sources, including a bibliography, and proofreading. The key steps are choosing a narrow topic, writing an introduction sentence stating the main argument, explaining the differences between primary and secondary sources, learning how to paraphrase properly, and editing the paper by fact checking citations and references.
This document provides guidance on writing research papers. It discusses the importance of having substantive results to present and how style and format varies between subjects and journals. The title should convey why the work stands out, and the abstract and keywords should be concise yet informative. The introduction motivates the work and conveys the key ideas and strategy, while reviewing relevant previous work. Sections clearly present new results, and concluding remarks discuss implications and directions for future work.
This document provides guidance for writing a response essay analyzing one of three novels: Night by Elie Wiesel, Outer Dark by Cormac McCarthy, or Room by Emma Donoghue. Students are instructed to write a 4-7 page thesis-driven essay analyzing an aspect of the novel using a critical lens from class. The document outlines choosing a focal point, asking analytical questions, formulating a thesis, writing an introduction, body paragraphs with evidence, and conclusion. It also lists learning outcomes, required skills, best practices, and things to avoid.
How to Write A Research Paper? - Useful Tips For Successful Academic WritingResearchLeap
Academic writing is a style of writing that makes your work easier to read and understand. No matter how well versed you are with grammar, punctuation and other areas that come into play for writing papers, making a mistake with the content hurts your overall academic writing.
The purpose of academic writing is to make your work clear and understandable to whoever is reading and/or evaluating it. Another important part of academic writing is ensuring that your work is fully and correctly referenced. The tips in Research Leap Manual on Academic Writing contain practical methods of creating an academic paper which your readers will easily follow. With this guide, you will learn how to:
Choose a topic
Think (brainstorm)
Build an organized text
Write good introduction, thesis, body and conclusion parts
Format your writing
Reference your work
Get expert academic writing tips straight to your inbox, and become a better academic writer. Download our PDF manual right now from the attachment.
Your comment and feedback are highly appreciated. To receive other tips and manuals, and to expand your research network and access research opportunities, join us on Linked In or FB.
This document provides tips for successful academic writing. It discusses the importance of considering your readers, choosing an appropriate topic and narrowing its scope, outlining the purpose and goals of academic writing, brainstorming and researching the topic, and structuring the paper with an introduction, body, and conclusion. It emphasizes clear organization, language, and the use of signposting to help readers follow the discussion. The conclusion should restate the thesis and main points covered in the paper.
How to Write A Research Paper? - Useful Tips For Successful Academic WritingAlina Stepanova
Academic writing is a style of writing that makes your work easier to read and understand. No matter how well versed you are with grammar, punctuation and other areas that come into play for writing papers, making a mistake with the content hurts your overall academic writing.
The purpose of academic writing is to make your work clear and understandable to whoever is reading and/or evaluating it. Another important part of academic writing is ensuring that your work is fully and correctly referenced. The tips in Research Leap Manual on Academic Writing contain practical methods of creating an academic paper which your readers will easily follow. With this guide, you will learn how to:
Choose a topic
Think (brainstorm)
Build an organized text
Write good introduction, thesis, body and conclusion parts
Format your writing
Reference your work
Get expert academic writing tips straight to your inbox, and become a better academic writer. Download our PDF manual right now from the attachment.
Your comment and feedback are highly appreciated. To receive other tips and manuals, and to expand your research network and access research opportunities, join us on Linked In or FB.
This document provides guidance on drafting a research paper with documented sources in 3 stages: planning and preparation, drafting, and revising. It discusses establishing a writing process, developing a thesis, organizing with an outline, integrating sources, and improving the paper by revising content, flow, paragraphs, voice and style. The goal is to engage the reader with a clear introduction and conclusion, support the thesis throughout with reasoning and evidence, and smoothly integrate sources while documenting them correctly.
The document provides tips for various aspects of writing a research paper, including developing a thesis, incorporating sources, crafting an introduction and conclusion, and choosing an appropriate structure. It recommends framing the topic in a way that establishes relevance for readers. When including sources, it advises blending quotes into your own writing and citing borrowed material. The document stresses allowing room for surprises from research and focusing on the research question.
The document provides guidance on writing for academic and professional purposes. It discusses why people write as well as common barriers to writing. Some key points covered include choosing topics you are interested in; developing ideas through discussion, current issues, and REM sleep; focusing topics; and structuring articles with outlines and paragraphs. The document also emphasizes using active voice and varying sentence structure to engage readers. Overall, the document offers advice on the writing process from developing ideas to structuring articles for different types of writing.
University of Brighton: Planning and Writing a Literature Review (BA Broadca...Lance Dann
Lecture describing how students should organise data acquired through their literature review and how they should map and analyse the ideas they are working with. Includes tips on how to work with and address literature critically, how to write an introduction to their review and what tutors are looking for in a literature review. This slideshow is intended for students of the BA (Hons) Broadcast Media at the University of Brighton.
This document provides advice on various aspects of academic writing. It discusses including an argument and thesis in essays, using proper organization and structure. Successful writing involves starting early, keeping overall purpose and organization in mind, extensive revision and sentence-level editing, and proofreading. The transition from high school to university writing involves moving from set formulas to developing individual structures and focusing on critical thinking over knowledge demonstration. Other topics covered include dealing with writer's block, outlining and planning essays, writing introductions and conclusions, using topic sentences, critical reading and source use, vocabulary building, research techniques, summarization, documentation formats, and revising and editing.
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Professor Sanjay Shitole gave a presentation on understanding intellectual property rights. He began by defining intellectual property and listing the main types: copyright, patents, trademarks, and trade secrets. He described how each type protects creative works, inventions, brands, and confidential information. The presentation explained that intellectual property rights are important as they encourage innovation, provide legal protections for creators and inventors, and foster economic growth. It also discussed balancing these rights with public interests and the need for intellectual property education.
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The document discusses modern trends in engineering, science and technology that will impact the future. It identifies several major trends such as cloud computing, high performance computing, big data analytics, machine learning, and others. Examples of companies leveraging these trends are provided. The document emphasizes that to be ready for the future, one needs to have the necessary skill set including skills in domains like mathematics, statistics, programming and databases. It also notes that the technological shift will make current practices redundant and that stability is important for long term survival.
Xfig is a vector graphics editor used to create diagrams. Vector images store graphics as collections of lines and vectors, allowing the images to be scaled to any size without losing quality. In contrast, bitmap images store graphics as collections of dots at fixed resolutions. Vector editors are generally better for page layout, logos, illustrations with sharp edges, technical diagrams, and flowcharts, as they can be easily modified. Bitmap editors are more suitable for photo editing and realistic illustrations.
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A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
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it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
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This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
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Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
1. Outline Research Plagiarism Writing a quality manuscript
Scientific Paper Writing
Sanjay Shitole
HOD and Associate Professor
Department of Information Technology
Usha Mittal Institute of Technology for Women
SNDT Women’s University, Santacruz(w), Mumbai.
15 Sept 2014
2. Outline Research Plagiarism Writing a quality manuscript
Outline of Topics
Research
Plagiarism
Writing a quality manuscript
Useful tips
3. Outline Research Plagiarism Writing a quality manuscript
Why to do a Research
• Knowledge Creation
• To look at the things differently
4. Outline Research Plagiarism Writing a quality manuscript
How To
Find the similarities between the Unrelated
Find the differences between related
12. Outline Research Plagiarism Writing a quality manuscript
Research is to see what everybody else has seen and to think what
nobody else has thought.
13. Outline Research Plagiarism Writing a quality manuscript
If I cite the source, can I still be accused of plagiarism?
You are allowed to borrow ideas or phrases from other sources
provided you cite them properly and your usage is consistent with
the guidelines set by fair use laws.
If you follow the words of a source too closely, and do not use
quotation marks, it can be considered plagiarism even if you cite
the source.
14. Outline Research Plagiarism Writing a quality manuscript
What is quoting?
Taking the exact words from an original source is called quoting.
You should quote material when you believe the way the original
author expresses an idea is the most effective means of
communicating the point you want to make. If you want to borrow
an idea from an author, but do not need his or her exact words,
you should try paraphrasing instead of quoting.
15. Outline Research Plagiarism Writing a quality manuscript
Paraphrasing
To paraphrase is to include the ideas or information from an
original source in your paper by rephrasing those ideas or
information in your own words. The key to successful paraphrasing
is to use as few words as possible from the original text–be mindful
not to change the meaning that you are trying to convey as you
rephrase–and to cite your paraphrase. Without proper citation,
your paraphrase could be construed as plagiarism.
16. Outline Research Plagiarism Writing a quality manuscript
Title
A good title should contain the fewest possible words that
adequately describe the contents of a paper
17. Outline Research Plagiarism Writing a quality manuscript
Abstract
The quality of an abstract will strongly influence the editor’s
decision
• Is precise and honest
• Can stand alone
• Uses little to no technical jargon
• Is brief and specific
• Cites no references
Use the abstract to “sell” your article
19. Outline Research Plagiarism Writing a quality manuscript
Introdction
• Open up the subject.
• Survey past work relevant to this paper.
20. Outline Research Plagiarism Writing a quality manuscript
Introdction
• Open up the subject.
• Survey past work relevant to this paper.
• Describe the problem addressed in this paper, and show how
this work relates to, or augments, previous work.
21. Outline Research Plagiarism Writing a quality manuscript
Introdction
• Open up the subject.
• Survey past work relevant to this paper.
• Describe the problem addressed in this paper, and show how
this work relates to, or augments, previous work.
• Describe the assumptions made in general terms, and state
what results have been obtained. (This gives the reader an
initial overview of what problem is addressed in the paper and
what has been achieved.)
22. Outline Research Plagiarism Writing a quality manuscript
Introdction
• Open up the subject.
• Survey past work relevant to this paper.
• Describe the problem addressed in this paper, and show how
this work relates to, or augments, previous work.
• Describe the assumptions made in general terms, and state
what results have been obtained. (This gives the reader an
initial overview of what problem is addressed in the paper and
what has been achieved.)
• Overview the contents of the paper. (“Section II contains our
formulation of the problem. Section III contains the
experimental data...”)
23. Outline Research Plagiarism Writing a quality manuscript
Methodology (Formulation of the Problem)
• Define the problem to be considered in detail.
24. Outline Research Plagiarism Writing a quality manuscript
Methodology (Formulation of the Problem)
• Define the problem to be considered in detail.
• Define all terminology and notation used. Usually the
terminology and notation are defined along with the problem
itself.
25. Outline Research Plagiarism Writing a quality manuscript
Methodology (Formulation of the Problem)
• Define the problem to be considered in detail.
• Define all terminology and notation used. Usually the
terminology and notation are defined along with the problem
itself.
• Develop the equations on which your results will be based
and/or describe any experimental systems.
26. Outline Research Plagiarism Writing a quality manuscript
Results
• This section presents the detailed results you have obtained.
27. Outline Research Plagiarism Writing a quality manuscript
Results
• This section presents the detailed results you have obtained.
• Provide a careful interpretation of what your results mean and
why they behave as they do.
28. Outline Research Plagiarism Writing a quality manuscript
Conclusion
The Conclusion should be written so they can be understood by
someone who has not read the main work of the paper.
29. Outline Research Plagiarism Writing a quality manuscript
Useful tips
• You must always present the big picture first and then work
towards the details (in Introduction section).
30. Outline Research Plagiarism Writing a quality manuscript
Useful tips
• You must always present the big picture first and then work
towards the details (in Introduction section).
• If you get stuck and cannot figure out how to explain
something, a useful trick is to imagine that you are telling a
very good friend what you are working on: just put down the
words as you would say them to your friend.
31. Outline Research Plagiarism Writing a quality manuscript
Useful tips
• You must always present the big picture first and then work
towards the details (in Introduction section).
• If you get stuck and cannot figure out how to explain
something, a useful trick is to imagine that you are telling a
very good friend what you are working on: just put down the
words as you would say them to your friend.
• After first draft, polish it after few days.
32. Outline Research Plagiarism Writing a quality manuscript
Useful tips
• You must always present the big picture first and then work
towards the details (in Introduction section).
• If you get stuck and cannot figure out how to explain
something, a useful trick is to imagine that you are telling a
very good friend what you are working on: just put down the
words as you would say them to your friend.
• After first draft, polish it after few days.
• It is easiest to leave the Introduction and Conclusion until
after the main body of the paper is written.
33. Outline Research Plagiarism Writing a quality manuscript
Useful tips cont...
• Ask yourself: “Can the reader understand every passage
strictly from the material up to that point?”
34. Outline Research Plagiarism Writing a quality manuscript
Useful tips cont...
• Ask yourself: “Can the reader understand every passage
strictly from the material up to that point?”
• If not, add material or move ideas around.
35. Outline Research Plagiarism Writing a quality manuscript
Useful tips cont...
• Ask yourself: “Can the reader understand every passage
strictly from the material up to that point?”
• If not, add material or move ideas around.
• Make sure there are not gaps in your logical arguments.
36. Outline Research Plagiarism Writing a quality manuscript
Useful tips cont...
• Ask yourself: “Can the reader understand every passage
strictly from the material up to that point?”
• If not, add material or move ideas around.
• Make sure there are not gaps in your logical arguments.
• Make sure you are not implicitly assuming that the reader
understands something, though you have not stated it.
37. Outline Research Plagiarism Writing a quality manuscript
Useful tips cont...
• Ask yourself: “Can the reader understand every passage
strictly from the material up to that point?”
• If not, add material or move ideas around.
• Make sure there are not gaps in your logical arguments.
• Make sure you are not implicitly assuming that the reader
understands something, though you have not stated it.
• The reader probably understands less than you think.
38. Outline Research Plagiarism Writing a quality manuscript
Useful tips cont...
• Make sure the ideas in the paper are in the right order.
39. Outline Research Plagiarism Writing a quality manuscript
Useful tips cont...
• Make sure the ideas in the paper are in the right order.
• At the beginning of each section ⇒ the purpose of that
section.
40. Outline Research Plagiarism Writing a quality manuscript
Useful tips cont...
• Make sure the ideas in the paper are in the right order.
• At the beginning of each section ⇒ the purpose of that
section.
• At the end of each section, ⇒ remind completed task.
Then point out what the purpose of the next section will be,
and so forth.
41. Outline Research Plagiarism Writing a quality manuscript
Useful tips cont...
• Make sure the ideas in the paper are in the right order.
• At the beginning of each section ⇒ the purpose of that
section.
• At the end of each section, ⇒ remind completed task.
Then point out what the purpose of the next section will be,
and so forth.
• Check each paragraph for unity. means, you should not mix
different ideas together in the same paragraph.
42. Outline Research Plagiarism Writing a quality manuscript
Useful tips cont...
• Make sure the ideas in the paper are in the right order.
• At the beginning of each section ⇒ the purpose of that
section.
• At the end of each section, ⇒ remind completed task.
Then point out what the purpose of the next section will be,
and so forth.
• Check each paragraph for unity. means, you should not mix
different ideas together in the same paragraph.
• Each sentence should clearly communicate your thought.
43. Outline Research Plagiarism Writing a quality manuscript
Useful tips cont...
• Make sure the ideas in the paper are in the right order.
• At the beginning of each section ⇒ the purpose of that
section.
• At the end of each section, ⇒ remind completed task.
Then point out what the purpose of the next section will be,
and so forth.
• Check each paragraph for unity. means, you should not mix
different ideas together in the same paragraph.
• Each sentence should clearly communicate your thought.
• Polish and polish.