Linking and referencing
•Download as PPTX, PDF•
1 like•233 views
This document discusses linking, referencing, and plagiarism. It defines plagiarism as copying or closely paraphrasing from other sources without proper citation. Examples of plagiarism include copying text word-for-word or piecing together text from multiple sources only with linking sentences. The document also defines a hyperlink as a reference to a document that the reader can directly follow, and defines a reference as a mention or direction to another source for purposes of information or testimony. It provides definitions of "reference" from an online dictionary.
Report
Share
Report
Share
![What is Plagiarism Examples of plagiarism ,[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommended
Plagiarism
Plagiarism involves taking credit for another person's words, ideas or work as your own. It is considered a form of cheating and an ethical issue. Some examples of plagiarism include copying text from the internet without citation, using a paper from another class, and failing to properly cite sources when paraphrasing, quoting or summarizing another's work in an assignment. Students must cite sources using in-text citations and ensure the majority of their paper consists of their own thoughts, while only supplementing with citations. Quotes, whether used in full or part, must always be cited with the original source. Resources for learning proper citation include the MLA Handbook and writing guides from Purdue and Northwestern University.
Edmedia2011 online.surveys
Presentation by Dr. Valerie Irvine at EdMedida 11 in Lisbon, Portugal for the Graduate Training Stream
Course Introduction
This document provides information about an introduction to physical geography course being offered in spring 2013. It outlines the instructor's contact information and office hours, required textbook, an overview of what the class covers, learning outcomes, grading policy, tips for success, academic honesty policy, and other important information for students. The class utilizes a systems approach to explore the atmosphere, hydrosphere, lithosphere, and biosphere and their interactions.
Linked Data – challenges for Imagiology and Radiology
This document discusses the challenges and opportunities of using linked data approaches in radiology and imagiology. It describes how linked data can help connect related medical images and text-based patient reports even if they are not similar. However, issues around language translation, privacy, and encouraging data sharing must be addressed. Multilingual systems and focusing on metadata instead of images directly can help overcome some barriers while maintaining patient privacy.
PhD Viva - Disambiguating Identity Web References using Social Data
This document summarizes Matthew Rowe's PhD thesis on automatically disambiguating identity web references. The thesis claims that automated techniques can replace humans in performing disambiguation at scale and with high accuracy by leveraging seed data from social web platforms. It outlines three disambiguation techniques evaluated in the thesis: 1) inference rules, 2) random walks on graphs, and 3) self-training classifiers. Evaluation results show the self-training approach achieves recall comparable to humans while the rule-based approach has the highest precision. The document also discusses generating metadata models from web resources and requirements for seed data and disambiguation techniques.
Academic dishonesty
The document discusses various issues related to research ethics including types of plagiarism, levels of plagiarism, reasons for academic dishonesty, the impact of plagiarism, and guidelines for collaborative research, authorship, acknowledgments, and addressing fabrication and falsification of data. It also outlines key pillars of research ethics like honesty, integrity, and social responsibility as well as concepts like predatory journals, contract cheating, and software-generated papers.
Clare llewellyn Lasiuk July 5th 2013
This document summarizes Clare Llewellyn's research on analyzing argumentation structures in user-generated online content. It discusses identifying topics and core points in discussions, classifying text spans into argumentation relationships like claims and counterclaims, and using machine learning techniques to automatically classify tweets into an argument structure. Key steps involve topic modeling, rule-based extraction of argument components, and training classifiers on feature sets like n-grams and part-of-speech tags to identify argumentative moves. The goal is to structure unstructured online discussions to better understand persuasive conversations on the web.
Plagiarism
The document discusses plagiarism, defining it as using another's work and passing it off as one's own. It notes that students are responsible for any plagiarism in their work according to the AVC Student Code of Conduct. The document provides examples of plagiarism and signs that indicate plagiarized work, such as a change in writing style or outdated references. It also gives tips on avoiding plagiarism by properly citing sources. Statistics are presented showing increases in cheating and plagiarism at universities over time.
Recommended
Plagiarism
Plagiarism involves taking credit for another person's words, ideas or work as your own. It is considered a form of cheating and an ethical issue. Some examples of plagiarism include copying text from the internet without citation, using a paper from another class, and failing to properly cite sources when paraphrasing, quoting or summarizing another's work in an assignment. Students must cite sources using in-text citations and ensure the majority of their paper consists of their own thoughts, while only supplementing with citations. Quotes, whether used in full or part, must always be cited with the original source. Resources for learning proper citation include the MLA Handbook and writing guides from Purdue and Northwestern University.
Edmedia2011 online.surveys
Presentation by Dr. Valerie Irvine at EdMedida 11 in Lisbon, Portugal for the Graduate Training Stream
Course Introduction
This document provides information about an introduction to physical geography course being offered in spring 2013. It outlines the instructor's contact information and office hours, required textbook, an overview of what the class covers, learning outcomes, grading policy, tips for success, academic honesty policy, and other important information for students. The class utilizes a systems approach to explore the atmosphere, hydrosphere, lithosphere, and biosphere and their interactions.
Linked Data – challenges for Imagiology and Radiology
This document discusses the challenges and opportunities of using linked data approaches in radiology and imagiology. It describes how linked data can help connect related medical images and text-based patient reports even if they are not similar. However, issues around language translation, privacy, and encouraging data sharing must be addressed. Multilingual systems and focusing on metadata instead of images directly can help overcome some barriers while maintaining patient privacy.
PhD Viva - Disambiguating Identity Web References using Social Data
This document summarizes Matthew Rowe's PhD thesis on automatically disambiguating identity web references. The thesis claims that automated techniques can replace humans in performing disambiguation at scale and with high accuracy by leveraging seed data from social web platforms. It outlines three disambiguation techniques evaluated in the thesis: 1) inference rules, 2) random walks on graphs, and 3) self-training classifiers. Evaluation results show the self-training approach achieves recall comparable to humans while the rule-based approach has the highest precision. The document also discusses generating metadata models from web resources and requirements for seed data and disambiguation techniques.
Academic dishonesty
The document discusses various issues related to research ethics including types of plagiarism, levels of plagiarism, reasons for academic dishonesty, the impact of plagiarism, and guidelines for collaborative research, authorship, acknowledgments, and addressing fabrication and falsification of data. It also outlines key pillars of research ethics like honesty, integrity, and social responsibility as well as concepts like predatory journals, contract cheating, and software-generated papers.
Clare llewellyn Lasiuk July 5th 2013
This document summarizes Clare Llewellyn's research on analyzing argumentation structures in user-generated online content. It discusses identifying topics and core points in discussions, classifying text spans into argumentation relationships like claims and counterclaims, and using machine learning techniques to automatically classify tweets into an argument structure. Key steps involve topic modeling, rule-based extraction of argument components, and training classifiers on feature sets like n-grams and part-of-speech tags to identify argumentative moves. The goal is to structure unstructured online discussions to better understand persuasive conversations on the web.
Plagiarism
The document discusses plagiarism, defining it as using another's work and passing it off as one's own. It notes that students are responsible for any plagiarism in their work according to the AVC Student Code of Conduct. The document provides examples of plagiarism and signs that indicate plagiarized work, such as a change in writing style or outdated references. It also gives tips on avoiding plagiarism by properly citing sources. Statistics are presented showing increases in cheating and plagiarism at universities over time.
Tips On Answering Reference Questions 6 25 07
This document provides tips for answering reference questions as a librarian. It outlines the main types of reference questions, including directional questions, database access questions, instructional questions, ready reference questions, research questions, and technical problems. It recommends conducting a reference interview by greeting the patron, asking what they need help with, asking follow up questions, and repeating the question back. It also provides guidance on how to answer different types of questions, including searching databases, using print and online resources, and referring patrons to subject specialists or other departments when needed.
Is our two way communication a one way street? Informal Surveys & Polls in Li...
This document discusses using informal surveys and polls to gather feedback from library patrons. It compares the benefits and disadvantages of web-based survey software versus installed survey software. It then describes the Memorial University of Newfoundland Libraries' experience using quick polls to gather focused feedback from patrons on a variety of topics over a 2-week period. Results were tabulated and shared internally, and comments provided additional useful feedback. Challenges encountered included lack of data from some branches and contradictory responses. Tips for success include having a clear purpose, keeping polls simple, designing questions carefully, sharing results, and being able to act on the feedback received.
AAAS 2014: How the Web Changes Collaboration
The document discusses how social tools and networks can enable more collaboration in research. It argues that while industries like music initially resisted the internet, networks ultimately provided new ways to discover and access content that users want. Similarly, blogging changed communication and professional media still exists online. The document advocates applying lessons from other online domains to scholarly communication by better utilizing the web for research collaboration and discovery through open infrastructure and aggregating research data in the cloud. This would allow new forms of recommendation and discovery beyond traditional websites.
Electronic Laboratory Notebooks
Talk given for UW-Madison Ebling Library and School of Medicine and Public Health on 3 Dec 2013. It covers electronic laboratory notebooks and what to look for in the software.
Trials by Juries: Suggested Practices for Database Trials
This panel discussion focused on tools and techniques for gathering feedback on database trials from librarians and library users. The panelists from Golden Gate University, University of Nebraska-Kearney, and Clemson University discussed criteria for selecting database trials, scheduling trials, soliciting and recording trial feedback, and closing the loop with participants and vendors after a trial. Key points included using web surveys to gather feedback, timing trials to maximize participation, and maintaining records of past trials and decisions.
Blogs for Information Management
Blogs can be useful tools for both personal information management and project team collaboration. For individuals, blogs allow one to easily capture and organize ideas, notes, and research in a searchable online format. This makes it simple to retrieve information later. For teams, blogs provide a shared space where members can linearly communicate updates and have discussions. This forces information into a centralized archive that new members can access to quickly get up to speed. Key benefits include automatic version control, attribution of contributions, and the ability to access the blog from anywhere.
Lab Notebooks: A Librarian's Primer
This document discusses the importance of lab notebooks for scientific data management, both currently and in the future. It identifies that lab notebooks are a critical tool for organizing pre-publication research data but practices vary widely. Ideal notebooks would contain all raw data, metadata, analyses, and citations in an electronic, searchable format. The document outlines how librarians can help by developing resources on best practices for organizing digital data and recording this in notebooks, as well as instruction on electronic notebook software. It recognizes that notebooks are shifting to fully digital formats and this will further impact data management.
Plagiaatinformatica2014 hf
The document discusses plagiarism and provides strategies to avoid it. It defines plagiarism as copying texts, ideas, pictures or software from other sources and presenting them as one's own work without properly citing sources. It emphasizes the importance of citing sources to avoid plagiarism and notes that plagiarism violates academic integrity and copyright. It recommends starting with a literature review, quoting and citing others' work, and demonstrating research as ways to prevent plagiarism in one's writing.
ECE 4445 Tools for Gathering Information 2009
The document provides an overview of various tools and resources for gathering information on engineering topics, including books, articles, databases, and library resources. It describes searching different databases like Google Scholar, IEEE Xplore, Scopus, and Web of Science and presents example searches on topics like "image segmentation" and "deformable models" to demonstrate their capabilities and availability of full text articles.
Lab Notebooks as Data Management (SLA Winter Virtual Conference 2012)
This talk, aimed at librarians, describes the data management issues surrounding paper and electronic lab notebooks. It offers several ways for librarians to support good practices and the transition from paper to electronic.
Anti-plagiarism tools for our repositories
Presentation focuses on a test and a comparative analysis of systems for detecting duplicates (so-called anti-plagiarism systems) used for the repositories of higher education theses and dissertations in the CR. A text corpus containing the most frequent sources of plagiarism was created for the needs of the test, and the modifications made by plagiarists were simulated.
The success of duplicity detection by the most important anti-plagiarism systems was verified experimentally, and a comparative analysis and verification of stipulated hypotheses were performed. The evaluation was also performed on the author’s own prototype application
using the Google search engine.
Academic Integrity Lecture Nov 08 Eg And Rh
This document discusses academic integrity and plagiarism. It defines plagiarism and different types of plagiarism such as copy-paste plagiarism, disguised plagiarism, mosaic plagiarism, and paraphrasing. The document provides guidance on when attribution is required, such as when using others' words, ideas, data, or images. Acceptable practices like quoting with attribution and permission to reuse images are covered. Resources for learning citation styles and avoiding plagiarism are also listed.
FAQs
This document discusses plagiarism and provides guidance on how to avoid it. It explains that all internet content is copyrighted unless explicitly marked as public domain, and ideas from others must be properly cited. While paraphrasing is allowed, direct quotes require citation and following the original too closely would be unacceptable. Intentional plagiarism through actions like copying others' work or buying essays is a serious offense. Unintentional plagiarism can be avoided by properly citing sources when using others' words or ideas. Students are advised to take careful notes while researching and cite any uncertain sources.
What Makes an outstanding dissertation or thesis?
These slides were presented by www.doctoralnet.com at a regular Sunday dissertation help conference on https://www.bigmarker.com/doctoralnet. Based on international assessment standards, our conversation looked in depth at the various parts of the dissertation or thesis document and what differentiates "normal" from "outstanding or award winning."
Data Science Master Specialisation
The document describes the Data Science Master Specialisation program at Radboud University, which includes courses in machine learning, information retrieval, and Bayesian networks. Students can choose tracks in areas like medical imaging, language technology, and chemometrics. The program aims to help students gain skills to solve scientific questions and improve society through data science research projects and a master's thesis.
AGU2012: Creating a Collaborative Network for Scientists
Mendeley is a London- and New York-based company that provides a collaborative network for scientists and researchers to organize papers, annotate documents, and communicate. The company has over 2 million users and has extracted data from 300 million uploaded documents to provide analytics on research trends and impact. Mendeley aims to instrument the entire research workflow and provide tools to accelerate the scientific process.
Arazágurt
Este documento presenta un plan de negocios para una nueva empresa dedicada a la elaboración y comercialización de yogurt con sabor a araza en Quito, Ecuador. La empresa se formará con tres accionistas y producirá yogurt utilizando la fruta araza. El objetivo es ofrecer un producto saludable que responda a las necesidades de los consumidores y captar una parte del mercado de yogurt. El precio de venta se ha fijado en $0.60 por unidad.
1 st CALL FOR PAPERS
The document announces a call for papers for the Cuba-Flanders Workshop on Machine Learning and Knowledge Discovery to be held in Santa Clara, Cuba from February 3-5, 2010. The workshop is hosted by Universidad Central de Las Villas and sponsored by the Flemish Interuniversity Council. The purpose is to provide a forum for researchers and students to present projects and discuss recent trends in machine learning and data mining. Authors are invited to submit original research papers and PhD results by December 15, 2009 and registration closes on February 2, 2010.
Machine Learning
The document is a summary of the topics covered in a CSE 471 class over 15 weeks. It includes a list of chapters covered from the textbook as well as brief summaries of the material covered each week, including search techniques, planning, logical inference, probabilistic reasoning, learning methods, and conclusions about AI. It also notes that the take-home exam will be released this week and provides instructions for completing online course evaluations.
Machine Learning Approach to Report Prioritization with an ...
The document describes a machine learning approach to prioritize reports in a vehicle communication network. Reports contain information like travel times and are stored in local databases with limited size. A model is developed to learn the relevance of reports using attributes like age and road type. The model is applied to prioritize travel time reports to disseminate updated speeds to vehicles for route planning. Evaluation shows logistic regression accurately predicts relevant reports to change routes.
Mustele si arta
Iata ce efecte benefice si creative pot avea asupra omului o doza buna de plictis si cateva muste. OK, mai multe muste.
Proceedings
The document describes the design of an upgraded dual-head LightGage Metrology System that can simultaneously measure both sides of a part and report thickness. Key aspects include using invar posts and vee pads to minimize thermal drift, pneumatic isolation for vibration stability, and Dyadic linear actuators integrated with TMS software for automated coarse motion and positioning of the dual sensor heads.
More Related Content
What's hot
Tips On Answering Reference Questions 6 25 07
This document provides tips for answering reference questions as a librarian. It outlines the main types of reference questions, including directional questions, database access questions, instructional questions, ready reference questions, research questions, and technical problems. It recommends conducting a reference interview by greeting the patron, asking what they need help with, asking follow up questions, and repeating the question back. It also provides guidance on how to answer different types of questions, including searching databases, using print and online resources, and referring patrons to subject specialists or other departments when needed.
Is our two way communication a one way street? Informal Surveys & Polls in Li...
This document discusses using informal surveys and polls to gather feedback from library patrons. It compares the benefits and disadvantages of web-based survey software versus installed survey software. It then describes the Memorial University of Newfoundland Libraries' experience using quick polls to gather focused feedback from patrons on a variety of topics over a 2-week period. Results were tabulated and shared internally, and comments provided additional useful feedback. Challenges encountered included lack of data from some branches and contradictory responses. Tips for success include having a clear purpose, keeping polls simple, designing questions carefully, sharing results, and being able to act on the feedback received.
AAAS 2014: How the Web Changes Collaboration
The document discusses how social tools and networks can enable more collaboration in research. It argues that while industries like music initially resisted the internet, networks ultimately provided new ways to discover and access content that users want. Similarly, blogging changed communication and professional media still exists online. The document advocates applying lessons from other online domains to scholarly communication by better utilizing the web for research collaboration and discovery through open infrastructure and aggregating research data in the cloud. This would allow new forms of recommendation and discovery beyond traditional websites.
Electronic Laboratory Notebooks
Talk given for UW-Madison Ebling Library and School of Medicine and Public Health on 3 Dec 2013. It covers electronic laboratory notebooks and what to look for in the software.
Trials by Juries: Suggested Practices for Database Trials
This panel discussion focused on tools and techniques for gathering feedback on database trials from librarians and library users. The panelists from Golden Gate University, University of Nebraska-Kearney, and Clemson University discussed criteria for selecting database trials, scheduling trials, soliciting and recording trial feedback, and closing the loop with participants and vendors after a trial. Key points included using web surveys to gather feedback, timing trials to maximize participation, and maintaining records of past trials and decisions.
Blogs for Information Management
Blogs can be useful tools for both personal information management and project team collaboration. For individuals, blogs allow one to easily capture and organize ideas, notes, and research in a searchable online format. This makes it simple to retrieve information later. For teams, blogs provide a shared space where members can linearly communicate updates and have discussions. This forces information into a centralized archive that new members can access to quickly get up to speed. Key benefits include automatic version control, attribution of contributions, and the ability to access the blog from anywhere.
Lab Notebooks: A Librarian's Primer
This document discusses the importance of lab notebooks for scientific data management, both currently and in the future. It identifies that lab notebooks are a critical tool for organizing pre-publication research data but practices vary widely. Ideal notebooks would contain all raw data, metadata, analyses, and citations in an electronic, searchable format. The document outlines how librarians can help by developing resources on best practices for organizing digital data and recording this in notebooks, as well as instruction on electronic notebook software. It recognizes that notebooks are shifting to fully digital formats and this will further impact data management.
Plagiaatinformatica2014 hf
The document discusses plagiarism and provides strategies to avoid it. It defines plagiarism as copying texts, ideas, pictures or software from other sources and presenting them as one's own work without properly citing sources. It emphasizes the importance of citing sources to avoid plagiarism and notes that plagiarism violates academic integrity and copyright. It recommends starting with a literature review, quoting and citing others' work, and demonstrating research as ways to prevent plagiarism in one's writing.
ECE 4445 Tools for Gathering Information 2009
The document provides an overview of various tools and resources for gathering information on engineering topics, including books, articles, databases, and library resources. It describes searching different databases like Google Scholar, IEEE Xplore, Scopus, and Web of Science and presents example searches on topics like "image segmentation" and "deformable models" to demonstrate their capabilities and availability of full text articles.
Lab Notebooks as Data Management (SLA Winter Virtual Conference 2012)
This talk, aimed at librarians, describes the data management issues surrounding paper and electronic lab notebooks. It offers several ways for librarians to support good practices and the transition from paper to electronic.
Anti-plagiarism tools for our repositories
Presentation focuses on a test and a comparative analysis of systems for detecting duplicates (so-called anti-plagiarism systems) used for the repositories of higher education theses and dissertations in the CR. A text corpus containing the most frequent sources of plagiarism was created for the needs of the test, and the modifications made by plagiarists were simulated.
The success of duplicity detection by the most important anti-plagiarism systems was verified experimentally, and a comparative analysis and verification of stipulated hypotheses were performed. The evaluation was also performed on the author’s own prototype application
using the Google search engine.
Academic Integrity Lecture Nov 08 Eg And Rh
This document discusses academic integrity and plagiarism. It defines plagiarism and different types of plagiarism such as copy-paste plagiarism, disguised plagiarism, mosaic plagiarism, and paraphrasing. The document provides guidance on when attribution is required, such as when using others' words, ideas, data, or images. Acceptable practices like quoting with attribution and permission to reuse images are covered. Resources for learning citation styles and avoiding plagiarism are also listed.
FAQs
This document discusses plagiarism and provides guidance on how to avoid it. It explains that all internet content is copyrighted unless explicitly marked as public domain, and ideas from others must be properly cited. While paraphrasing is allowed, direct quotes require citation and following the original too closely would be unacceptable. Intentional plagiarism through actions like copying others' work or buying essays is a serious offense. Unintentional plagiarism can be avoided by properly citing sources when using others' words or ideas. Students are advised to take careful notes while researching and cite any uncertain sources.
What Makes an outstanding dissertation or thesis?
These slides were presented by www.doctoralnet.com at a regular Sunday dissertation help conference on https://www.bigmarker.com/doctoralnet. Based on international assessment standards, our conversation looked in depth at the various parts of the dissertation or thesis document and what differentiates "normal" from "outstanding or award winning."
Data Science Master Specialisation
The document describes the Data Science Master Specialisation program at Radboud University, which includes courses in machine learning, information retrieval, and Bayesian networks. Students can choose tracks in areas like medical imaging, language technology, and chemometrics. The program aims to help students gain skills to solve scientific questions and improve society through data science research projects and a master's thesis.
AGU2012: Creating a Collaborative Network for Scientists
Mendeley is a London- and New York-based company that provides a collaborative network for scientists and researchers to organize papers, annotate documents, and communicate. The company has over 2 million users and has extracted data from 300 million uploaded documents to provide analytics on research trends and impact. Mendeley aims to instrument the entire research workflow and provide tools to accelerate the scientific process.
What's hot (16)
Is our two way communication a one way street? Informal Surveys & Polls in Li...
Is our two way communication a one way street? Informal Surveys & Polls in Li...
Trials by Juries: Suggested Practices for Database Trials
Trials by Juries: Suggested Practices for Database Trials
Lab Notebooks as Data Management (SLA Winter Virtual Conference 2012)
Lab Notebooks as Data Management (SLA Winter Virtual Conference 2012)
AGU2012: Creating a Collaborative Network for Scientists
AGU2012: Creating a Collaborative Network for Scientists
Viewers also liked
Arazágurt
Este documento presenta un plan de negocios para una nueva empresa dedicada a la elaboración y comercialización de yogurt con sabor a araza en Quito, Ecuador. La empresa se formará con tres accionistas y producirá yogurt utilizando la fruta araza. El objetivo es ofrecer un producto saludable que responda a las necesidades de los consumidores y captar una parte del mercado de yogurt. El precio de venta se ha fijado en $0.60 por unidad.
1 st CALL FOR PAPERS
The document announces a call for papers for the Cuba-Flanders Workshop on Machine Learning and Knowledge Discovery to be held in Santa Clara, Cuba from February 3-5, 2010. The workshop is hosted by Universidad Central de Las Villas and sponsored by the Flemish Interuniversity Council. The purpose is to provide a forum for researchers and students to present projects and discuss recent trends in machine learning and data mining. Authors are invited to submit original research papers and PhD results by December 15, 2009 and registration closes on February 2, 2010.
Machine Learning
The document is a summary of the topics covered in a CSE 471 class over 15 weeks. It includes a list of chapters covered from the textbook as well as brief summaries of the material covered each week, including search techniques, planning, logical inference, probabilistic reasoning, learning methods, and conclusions about AI. It also notes that the take-home exam will be released this week and provides instructions for completing online course evaluations.
Machine Learning Approach to Report Prioritization with an ...
The document describes a machine learning approach to prioritize reports in a vehicle communication network. Reports contain information like travel times and are stored in local databases with limited size. A model is developed to learn the relevance of reports using attributes like age and road type. The model is applied to prioritize travel time reports to disseminate updated speeds to vehicles for route planning. Evaluation shows logistic regression accurately predicts relevant reports to change routes.
Mustele si arta
Iata ce efecte benefice si creative pot avea asupra omului o doza buna de plictis si cateva muste. OK, mai multe muste.
Proceedings
The document describes the design of an upgraded dual-head LightGage Metrology System that can simultaneously measure both sides of a part and report thickness. Key aspects include using invar posts and vee pads to minimize thermal drift, pneumatic isolation for vibration stability, and Dyadic linear actuators integrated with TMS software for automated coarse motion and positioning of the dual sensor heads.
A machine learning approach to web page filtering using ...
This document describes a machine learning approach to web page filtering that combines content and structural analysis. The proposed approach represents web pages with features extracted from content, such as terms and phrases, and from links. These features are used as input for machine learning algorithms like neural networks and support vector machines to classify pages. An experiment compares this approach to keyword-based and lexicon-based filtering, finding the proposed approach generally performs better, especially with few training examples. The approach could benefit topic-specific search engines and other applications.
SEAT Fall 2009
Cover Story:
An Idea Whose Time Has Come
Feature Stories:
Introducing the New Leader of the Pack
Coming the Next Age
slides
ALADIN is an active learning system that uses machine learning to help security analysts identify anomalies and malware in network traffic logs. It combines active anomaly detection and active learning to minimize the amount of labeling an analyst needs to do. The system was tested on a real Microsoft network logs and was able to discover rare classes, maintain low error rates, and scale well while identifying network intrusions and malware.
Printable Resume 2
Bobbie Isas is an IT specialist and web developer based in Los Angeles, California with over 15 years of experience. She has strong skills in HTML, CSS, JavaScript, Java, PHP, SQL, graphic design and web animation software. She has designed and developed over 150 websites, and has worked as an independent contractor, at IBM, LA Internet and Transcontinental. She is proficient in English, Russian, Serbian, Macedonian and Bulgarian.
Sethia Grandeur Brochure - Zricks.com
For more information about http://www.zricks.com/Sethia-Grandeur-Bandra-East-Mumbai/15082
Sethia Grandeur, Bandra East, Mumbai. Visit: http://www.zricks.com
Check out:
Walkthrough ☛ http://www.zricks.com/walkthrough
Compare ☛ http://www.zricks.com/compare
Brochure ☛ http://www.zricks.com/brochure
5 trekking
This document discusses hiking and trekking. It begins by providing context on the historical relationship between humans and nature. It then defines hiking as moving from place to place using only one's feet, and trekking as a popular outdoor activity for enjoying scenery. Next, it provides tips for preparing one's rucksack for hiking, including proper packing of items. It recommends comfortable, insulated shoes that have already been worn in. Finally, it lists advice for safely carrying out hiking, such as obtaining information about terrain and conditions, bringing water, choosing appropriate clothing, hiking in groups for safety, maintaining a uniform pace with stops, and respecting the environment by staying on paths and not littering.
Word Format
Kimberly Beall has over 12 years of experience in web design, graphic design, content management, and technical writing. She has expertise in designing accessible and scalable websites using technologies like HTML, CSS, and JavaScript. Her goal is to combine technical skills with optimizing the end-user experience. She has worked on projects for companies like IBM, Nortel Networks, and small businesses.
Interim Report.docx - vsiogap3d.googlecode.com
This document provides a midterm report on a final year project to develop a 3D visualization Android application to display sensor data stored in an OWL format repository. It outlines the project objectives of developing an application in Java using the Android SDK that can retrieve and display updated sensor readings from a building model in 3D. The report describes the tools used, including the Android SDK and Eclipse IDE. It also reviews literature on software development methodologies and similar projects for gathering requirements and designing the application. The work completed so far is documented and future work plans are presented.
Microsoft PowerPoint - ml4textweb00
This document summarizes machine learning methods for text and web data mining. It discusses several machine learning techniques including neural networks, probabilistic models, and other methods. It provides examples of applying these techniques to tasks like text categorization, topic word extraction from documents, and customer analysis from web data. Experimental results on text and web datasets demonstrate the effectiveness of techniques like Helmholtz machines, Bayesian networks, and latent variable models for text and web mining applications.
Media Arts: Web Design
The document provides information on the Associate in Applied Science degree in Media Arts: Web Design offered at Phoenix College. The 61-credit program aims to develop marketable skills in web design and provides an understanding of storyboards, layout tools, graphics, presentation techniques, and web design. Required courses include introduction to computer graphics, digital photography, two-dimensional computer design, computer-aided graphic arts, web site design, web presentation design, digital studio, and internet/web development. The program also includes general education requirements in areas such as composition, oral communication, critical reading, mathematics, humanities, social sciences and natural sciences.
web design
The document provides guidance on developing an effective website structure. It recommends beginning by identifying the target audience and defining the site's purpose. The main types of website structures discussed are linear narrative, hierarchy, and web formats. It also emphasizes the importance of organization, consistent navigation, dividing content into digestible chunks, and ensuring all links work properly. The document concludes by highlighting common mistakes like failing to keep the site updated and not completing construction before posting.
Learning for Optimization: EDAs, probabilistic modelling, or ...
Marcus Gallagher gave a talk on explicit modelling in metaheuristic optimization. He discussed estimation of distribution algorithms which use probabilistic models to represent promising regions of the search space. He provided examples of modelling approaches like PBIL, MIMIC, COMIT and BOA. Finally, he summarized that EDAs take an explicit modelling approach to optimization using existing statistical models and can solve challenging problems by visualizing the model.
Design.doc
The document provides guidance on designing accessible and usable web applications. It discusses defining goals and user requirements, establishing usability requirements, considering disabilities, and addresses design issues like color, wording, layout, widgets, navigation, and accessibility. References on user-centered design and accessibility best practices are also included.
CSE333 project initial spec: Learning agents
This document provides an initial specification for a CSE333 project on learning agents. The project aims to build a distributed learning agent system that can find a policy for navigating a maze. Four key components are identified: perception, action, communication, and learning. The project will investigate reinforcement learning and Q-learning approaches. Team members are assigned areas of focus: machine learning, agent computing, distributed computing, and tools/implementation. Activities over the semester are outlined and will include research, design, prototyping, and implementation of a learning agent system to solve a maze problem using Q-learning.
Viewers also liked (20)
Machine Learning Approach to Report Prioritization with an ...
Machine Learning Approach to Report Prioritization with an ...
A machine learning approach to web page filtering using ...
A machine learning approach to web page filtering using ...
Learning for Optimization: EDAs, probabilistic modelling, or ...
Learning for Optimization: EDAs, probabilistic modelling, or ...
Similar to Linking and referencing
Plagiarism: What it is & How to Avoid it
Plagiarism involves using others' words or ideas without giving them proper credit. It can be intentional or unintentional and includes directly copying information from sources without citation, purchasing papers, or having someone else write papers. Plagiarism violates ECU's Code of Conduct and can result in failing grades, probation, or expulsion. To avoid plagiarism, students should allow time for research, take good notes, paraphrase information in their own words, cite direct quotations, and give credit to all sources used.
Plagiarism
The document discusses plagiarism, defining it as using another's work without proper citation or credit. It notes plagiarism can involve copying text, images, or ideas without attribution. The document outlines how to properly cite sources using a citation style and take notes to avoid plagiarism. It also reviews the consequences of plagiarism such as failing grades or legal punishment. Finally, it provides a short quiz to test the reader's understanding of what actions constitute plagiarism.
Plagiarism
The document discusses plagiarism, defining it as using another's work without proper citation or credit. It notes plagiarism can involve directly copying text, paraphrasing without citation, or using copyrighted images without permission. The document outlines consequences like failing grades or legal punishment and provides tips for preventing plagiarism through proper note-taking, citing sources, and understanding what constitutes a direct quote or paraphrase. It concludes with a short quiz to test the reader's understanding of plagiarism.
Plagiarism
The document discusses plagiarism, defining it as using another's work without giving proper credit. It notes plagiarism can involve directly copying text, paraphrasing without citation, or using copyrighted images without permission. The document outlines how to properly cite sources using a citation style and take notes to avoid plagiarism. It lists consequences like failing grades or legal punishment and provides tips for preventing plagiarism like organizing sources and checking citations. It concludes with a plagiarism quiz to test the reader's understanding.
Plagiarismtutorial
This document defines plagiarism and discusses its consequences. It begins by defining plagiarism as passing off another's work as one's own according to the Merriam-Webster Dictionary. It then outlines the college's policies on plagiarism from the student handbook. The document discusses both intentional and unintentional plagiarism and how to avoid it through proper citation of sources. It stresses giving credit to original authors and distinguishing common knowledge from unique ideas. The consequences of plagiarism discussed are academic penalties from instructors as well as potential professional repercussions. Research tips provided include knowing citation styles and completing assignments early to avoid sloppy citations.
Plagiarism tutorial
This document defines plagiarism and discusses its consequences. Plagiarism is defined as passing off another's work as one's own without crediting the source. The document outlines both intentional and unintentional plagiarism. It also discusses common knowledge, paraphrasing, and provides examples. Consequences of plagiarism include penalties from instructors like failing grades or disciplinary action. Research tips are provided to avoid plagiarism like knowing citation styles and giving proper credit.
Plagiarism tutorial
This document defines plagiarism and discusses its consequences. Plagiarism is defined as passing off another's work as one's own without crediting the source. The document outlines both intentional and unintentional plagiarism. It also discusses common knowledge versus using another's ideas without citation. Consequences of plagiarism include penalties from instructors like failing grades or referral to the Dean. Research tips are provided to avoid plagiarism like knowing citation styles and giving proper credit.
Types of plagiarism harvard
This document provides an introduction to plagiarism, outlining good academic practice, different types of plagiarism such as direct copying, paraphrasing, and concealing sources. It discusses how to avoid plagiarism by correctly citing sources. Working alone on assignments and not buying work are emphasized as good practice, while activities like sharing written work or having another student write the assignment are considered plagiarism. Reusing significant portions of previous work without development is also discouraged.
Types of plagiarism law
This document provides an introduction to plagiarism, including definitions of good and bad academic practices. It discusses different types of plagiarism such as direct copying, paraphrasing, concealing sources, and collusion. Examples of plagiarized and properly attributed work are presented. The document emphasizes completing all academic work independently and honestly while properly citing sources to avoid plagiarism. It notes that purchasing assignments or reusing substantial parts of previous work without development are forms of plagiarism. The goal is to help students understand plagiarism and how to properly attribute sources in their academic work.
Literature search, referencing
This document provides guidance on conducting literature searches and properly referencing sources to avoid plagiarism in social science research, particularly for history. It discusses choosing a research topic and question, conducting a literature search to identify existing work and research gaps, and verifying the topic has not been duplicated. The document also covers primary, secondary and tertiary sources; online search strategies using keywords, Boolean operators, and truncation; types of plagiarism and how to avoid it; plagiarism detection tools; and common referencing standards.
PLAG PPT.pdf
This document discusses plagiarism, including definitions, types, causes, and prevention. It defines plagiarism as copying others' work without attribution, whether copying words, ideas, or results. Types of plagiarism include direct copying, paraphrasing without citation, and mosaic plagiarism. Self-plagiarism is also discussed. Reasons why people plagiarize include pressure, ambition, and believing chances of getting caught are low. Prevention methods include educating about academic integrity and using plagiarism detection software.
Plagiarism tutorial
The document defines plagiarism and discusses its consequences. It begins by providing definitions of plagiarism from dictionaries and colleges. It notes that plagiarism can be intentional, such as copying others' work, or unintentional through careless citation. Common knowledge is distinguished from needing citation. The document recommends properly citing direct quotes, summaries, and paraphrases. Consequences of plagiarism include academic penalties from instructors and colleges as well as professional consequences. Research tips to avoid plagiarism include knowing citation styles and attributing all sources.
Plagiarism: Detect and Prevent
Presented By: Nur Ahammad,
Senior Assistant Librarian & Adjunct Faculty
Department of Information Science and Library Management
Daffodil International University
FACULTY INDUCTION PROGRAMME PLAGIARISM.pptx
FACULTY INDUCTION PROGRAMME PLAGIARISM.pptxUNIVERSITY DEPARTMENT OF PSYCHOLOGY B.N.MANDAL UNIVERSITY, MADHEPURA, BIHAR, PIN-852113, INDIAI AM
Promotion of Academic Integrity and Prevention of Plagiarism in Higher Educational Institutions (HEI). Academic honesty
This document discusses academic honesty and plagiarism. It defines plagiarism as presenting another's work as one's own by copying without citing sources. Plagiarism can be unintentional by failing to cite sources or intentional by copying directly from the internet or another student's work. Teachers check for plagiarism by searching online and comparing students' work. To avoid plagiarism, students must cite sources within their work using in-text citations and reference lists. Direct quotes, paraphrases and summaries all require citations.
Plagiarism and referencing
The document discusses plagiarism and referencing. It defines plagiarism as taking someone else's work and passing it off as one's own without providing proper acknowledgement. Correct referencing avoids plagiarism by providing the correct acknowledgement and citation of sources. The document provides guidance on how to reference sources using the Harvard referencing style, including how to cite sources in-text and structure reference list entries. It also addresses referencing online resources and secondary sources.
Developing Master’s-Level Writing SkillsNurses are busy. Man.docx
Developing Master’s-Level Writing Skills
Nurses are busy. Many develop habits that help them work quickly: writing in short-hand on the job or in text message abbreviations in everyday life. When starting a Master’s program, however, nursing students must use scholarly writing or academic writing. The objective of academic writing, which has a high level of rigor and a specific structure, is to provide clear, concise insights and to support them with evidence. The transition from short hand or casual writing to scholarly writing requires using the five-paragraph essay format.
The Five-Paragraph Essay Format
The five-paragraph essay format is a classic structure used for building an essay and is helpful in organizing and developing ideas.
The basic five-paragraph essay contains the following:
· One introductory paragraph to introduce the topic and a thesis statement
· Three body paragraphs that support, defend, and develop the topic of the essay
· One concluding paragraph to summarize and synthesize the information provided on the topic
The body paragraphs can be expanded for a more robust discussion. Please review the American Psychological Association’s (APA) style manual for further guidance in paragraph and sentence development.
Planning Your Paragraphs With the “MEAL Plan”
Presenting information to your reader in a clear and concise manner requires writing organized and effective paragraphs. Paragraphing is a core skill in building paraphrase that convey mastery of your academic writing abilities. Students at Duke University are encouraged to think of a paragraph as a complete MEAL that includes a Main idea, Evidence, Analysis, and a Link. Understanding the MEAL Plan will provide you with an effective strategy to ensure each paragraph contains a main idea, evidence to support the idea, analysis of evidence, and a link of the information to what already exists and to the next topic in the discussion.
M – The Main Idea
Every paragraph should have one main idea. If you find that your paragraphs have more than one main idea, separate your paragraphs so that each has only one main point. The idea behind a paragraph is to introduce an idea and expand on it. If you veer off into a new topic, begin a new paragraph.
E – Evidence (or Examples)
Your main idea needs support, either in the form of evidence that buttresses your argument or examples that explain your idea. If you don’t have any evidence or examples to support your main idea, your idea may not be strong enough to warrant a complete paragraph. In this case, re-evaluate your idea and see whether you need even to keep it in the paper.
A – Analysis
Analysis is the heart of academic writing. While your readers want to see evidence or examples of your idea, the real “meat” of your idea is your interpretation of your evidence or examples: how you break them apart, compare them to other ideas, use them to build a persuasive case, demonstrate their strengths or weaknesses, and so on. Analysis i.
Plagiarism tutorial
This document defines plagiarism and discusses its consequences. It begins by defining plagiarism using dictionary definitions and noting that most colleges and universities have their own definitions. Unintentional plagiarism can occur through incomplete citations or paraphrasing, while intentional plagiarism involves knowingly passing off others' work as one's own. The consequences of plagiarism are also outlined, including potential academic penalties like failing a course, as well as reputational damage professionally. Research tips are provided to help avoid plagiarism, such as being familiar with citation expectations and accurately citing sources.
Plagiarism
This document defines plagiarism and discusses its consequences. Plagiarism is presenting another's work as one's own without crediting the source. It defines intentional plagiarism as copying others' work and unintentional plagiarism as incomplete citations. Consequences include academic penalties like failing courses and professional consequences like losing licenses. The document provides tips to avoid plagiarism such as citing sources properly, distinguishing common from unique knowledge, and rewriting in one's own words. It includes links to exercises and other plagiarism resources.
Academic Integrity Handbook.Pdf
The document provides guidelines for students at the Massachusetts Institute of Technology (MIT) regarding academic integrity and avoiding plagiarism. It discusses what constitutes plagiarism and other violations of academic integrity such as cheating. It outlines best practices for citing sources, paraphrasing, summarizing, quoting, collaborating on assignments, and writing code. The document emphasizes the importance of doing original work and giving proper attribution to the ideas and words of others. It notes that violations of academic integrity can result in failure on assignments, failure of courses, suspension, or expulsion from MIT. The goal of the handbook is to ensure all MIT students understand and uphold the high standards of academic integrity expected at the Institute.
Similar to Linking and referencing (20)
Developing Master’s-Level Writing SkillsNurses are busy. Man.docx
Developing Master’s-Level Writing SkillsNurses are busy. Man.docx
Linking and referencing
- 1. Linking and Referencing By Craig Betts
- 3. Closely paraphrasing sentences, paragraphs, ideas or themes without proper citation
- 4. Piecing together text from one or more sources and adding only linking sentences;
- 5. Copying or submitting whole or parts of computer files without acknowledging their sources;
- 6. Copying designs or works or art and submitting them as your original work;
- 7. Copying a whole or any part of another student’s work; and
- 8. Submitting work as your own that someone else has done for you.If you have used someone else's work without acknowledging your source, you have plagiarised. Source: Academic Policy Branch, 2002-12-03, Plagiarism Policy [Online, Composite], Student Affairs, Melbourne, Vic, Available from: http://www.rmit.edu.au//browse;ID=1oavdg0bdd1.pdf Source: http://www.dlsweb.rmit.edu.au/lsu/content/1_StudySkills/study_tuts/plagiarism_LL/examples.html
- 9. What is a Link? In computing, a hyperlink (or link) is a reference to a document that the reader can directly follow, or that is followed automatically. The term "hyperlink" was coined in 1965 (or possibly 1964) by Ted Nelson and his assistant Calvin Curtin at the start of Project Xanadu. Nelson had been inspired by "As We May Think," a popular essay by VannevarBush. http://en.wikipedia.org/wiki/Hyperlink
- 10. What is a Reference 1.an act or instance of referring. 2.a mention; allusion. 3.something for which a name or designation stands;denotation. 4.a direction in a book or writing to some other book, passage,etc. 5.a book, passage, etc., to which one is directed. 6.reference mark ( def. 2 ) . 7.material contained in a footnote or bibliography, or referredto by a reference mark. 8.use or recourse for purposes of information: a library forpublic reference. 9.a person to whom one refers for testimony as to one'scharacter, abilities, etc. 10.a statement, usually written, as to a person's character,abilities, etc. 11.relation, regard, or respect: all persons, without reference toage. –verb (used with object)12.to furnish (a book, dissertation, etc.) with references: Eachnew volume is thoroughly referenced. 13.to arrange (notes, data, etc.) for easy reference: Statisticaldata is referenced in the glossary. 14.to refer to: to reference a file. http://dictionary.reference.com/browse/reference
- 11. Thanks Very Much Craig Betts