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Recommandé
By Roshan Maharjan
File handling
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What is file handling in qbasic? Types of file mode used in QBASIC
File handling
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A short presentation on indexing data structure and its types
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Shirley Jenifer Joseph
Presentation on File Handling
File handling
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SabahtHussein
Hello guys!! .Let's learn about file handling in Qbasic.
File handling in qbasic
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SmritiGurung4
Modified version of Chapter 18 of the book Fundamentals_of_Database_Systems,_6th_Edition with review questions as part of database management system course
Indexing structure for files
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Zainab Almugbel
File System Object in QTP
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these slides show you how to read, write, delete, move, copy and append a file in vb.net completely with examples.... By Ambreen Gillani
File handling in vb.net
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Everywhere
Recommandé
By Roshan Maharjan
File handling
File handling
RoshanMaharjan13
What is file handling in qbasic? Types of file mode used in QBASIC
File handling
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BeebashPokhrel
A short presentation on indexing data structure and its types
Indexing
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Presentation on File Handling
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SabahtHussein
Hello guys!! .Let's learn about file handling in Qbasic.
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SmritiGurung4
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File System Object in QTP
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Praveen Gorantla
these slides show you how to read, write, delete, move, copy and append a file in vb.net completely with examples.... By Ambreen Gillani
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INCREASE YOUR KNOWLEDGE BY DOUBLE YOU SHOULD HAVE TO READ TECHNOLOGY NOTE RATHER THAN OTHERS
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Meher ppt (1)
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B-TREE, Properties of B-Tree, B-Tree of minimum degree 3, Drawbacks of B-Tree, B+ tree, B+ tree, Structure of the internal nodes of a B+ tree , structure of the leaf nodes of a B+ tree , Example of B+ tree
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This presentation contains a complete understanding of file system Interface, Directory Structure, How operating System access the files and their directories. So I hope you will easily understand the concept of file system interface. Access Methos are also discussed in this presentation.
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What is a name in Distributed Systems? A name in a distributed system is a string of bits or characters that is used to refer to an entity. What is an Entity? An entity in a distributed system can be practically anything. Examples include resources such as hosts, printers, disks, and files, processes, users, mailboxes, newsgroups, Web pages, graphical windows, messages, network connections
Naming Entities and Locating Mobile Entities
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This presentation is a part of the COP2271C college level course taught at the Florida Polytechnic University located in Lakeland Florida. The purpose of this course is to introduce Freshmen students to both the process of software development and to the Python language. The course is one semester in length and meets for 2 hours twice a week. The Instructor is Dr. Jim Anderson. A video of Dr. Anderson using these slides is available on YouTube at: http://youtu.be/YD5Yk6cNsdE
An Introduction To Python - Files, Part 1
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INCREASE YOUR KNOWLEDGE BY DOUBLE YOU SHOULD HAVE TO READ TECHNOLOGY NOTE RATHER THAN OTHERS
Switching & Multiplexing
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Meher ppt (1)
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sarika meher
B-TREE, Properties of B-Tree, B-Tree of minimum degree 3, Drawbacks of B-Tree, B+ tree, B+ tree, Structure of the internal nodes of a B+ tree , structure of the leaf nodes of a B+ tree , Example of B+ tree
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Filehandling
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prateekgemini
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gmbmanikandan
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myrajendra
Linked List
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kalpanasatishkumar
This presentation contains a complete understanding of file system Interface, Directory Structure, How operating System access the files and their directories. So I hope you will easily understand the concept of file system interface. Access Methos are also discussed in this presentation.
File system interface
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Dayan Ahmed
Linked List
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kalpanasatishkumar
What is a name in Distributed Systems? A name in a distributed system is a string of bits or characters that is used to refer to an entity. What is an Entity? An entity in a distributed system can be practically anything. Examples include resources such as hosts, printers, disks, and files, processes, users, mailboxes, newsgroups, Web pages, graphical windows, messages, network connections
Naming Entities and Locating Mobile Entities
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Getting Started - MongoDB
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Indexing Data Structure
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An Introduction To Python - Files, Part 1
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Naming Entities and Locating Mobile Entities
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En vedette
The need to retain customers, and get more out of them, is increasingly apparent in the need for what Loyalty 360 calls expectation matching: building loyalty and engagement by using behavioral insights from customers to meet their expectations in Operations Management
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hi people!!! this is my first presentation hope u like it n might help u for ur further studies and good step for ur future!!!!! I'm pretty much sure u'll like it and if u find interesting plz comment or give a like. your like means a lot...!!!!!! :)
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Web pages not only contain main content, but also other elements such as navigation panels, advertisements and links to related documents. To ensure the high quality of web page, a good boilerplate removal algorithm is needed to extract only the relevant contents from web page. Main textual contents are just included in HTML source code which makes up the files. The goal of content extraction or boilerplate detection is to separate the main content from navigation chrome, advertising blocks, and copyright notices in web pages. The system removes boilerplate and extracts main content. In this system, there are two phases: Feature Extraction phase and Clustering phase. The system classifies the noise or content from HTML web page. Content Extraction algorithm describes to get high performance without parsing DOM trees. After observation the HTML tags, one line may not contain a piece of complete information and long texts are distributed in close lines, this system uses Line-Block concept to determine the distance of any two neighbor lines with text and Feature Extraction such as text-to-tag ratio (TTR), anchor text-to-text ratio (ATTR) and new content feature as Title Keywords Density (TKD) classifies noise or content. After extracting the features, the system uses these features as parameters in threshold method to classify the block are content or non- content.
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Web pages not only contain main content, but also other elements such as navigation panels, advertisements and links to related documents. To ensure the high quality of web page, a good boilerplate removal algorithm is needed to extract only the relevant contents from web page. Main textual contents are just included in HTML source code which makes up the files. The goal of content extraction or boilerplate detection is to separate the main content from navigation chrome, advertising blocks, and copyright notices in web pages. The system removes boilerplate and extracts main content. In this system, there are two phases: Feature Extraction phase and Clustering phase. The system classifies the noise or content from HTML web page. Content Extraction algorithm describes to get high performance without parsing DOM trees. After observation the HTML tags, one line may not contain a piece of complete information and long texts are distributed in close lines, this system uses Line-Block concept to determine the distance of any two neighbor lines with text and Feature Extraction such as text-to-tag ratio (TTR), anchor text-to-text ratio (ATTR) and new content feature as Title Keywords Density (TKD) classifies noise or content. After extracting the features, the system uses these features as parameters in threshold method to classify the block are content or non- content.
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The online News publisher publishes their news in the form of articles. Most of the online news websites provide the facility for their users to comment on the news article and as a result a lot of people comment on the news article. Hence news web page contains huge data in the form of article content and comments data, etc and have a good potential to be a resource for many Information Retrieval Systems and Data Mining Applications. The extraction of the main content (Article content) from a web page has always been a challenging task because a web page contains other information like advertisements and hyperlinks etc. which is not related to Article Text. In this survey, we review various techniques which are proposed by various researchers to extract the article content from a news web site. We also learn various techniques which monitor and analyze the comments for various applications like popularity prediction of articles and identification of discussions thread in the comments data.
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Axa Assurance Maroc - Insurer Innovation Award 2024
The Digital Insurer
We present an architecture of embedding models, vector databases, LLMs, and narrow ML for tracking global news narratives across a variety of countries/languages/news sources. As an example, we explore the real-time application of this architecture for tracking the news narrative surrounding the death of Russian opposition leader Alexei Navalny coming from Russian, French, and English sources.
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Zilliz
As privacy and data protection regulations evolve rapidly, organizations operating in multiple jurisdictions face mounting challenges to ensure compliance and safeguard customer data. With state-specific privacy laws coming up in multiple states this year, it is essential to understand what their unique data protection regulations will require clearly. How will data privacy evolve in the US in 2024? How to stay compliant? Our panellists will guide you through the intricacies of these states' specific data privacy laws, clarifying complex legal frameworks and compliance requirements. This webinar will review: - The essential aspects of each state's privacy landscape and the latest updates - Common compliance challenges faced by organizations operating in multiple states and best practices to achieve regulatory adherence - Valuable insights into potential changes to existing regulations and prepare your organization for the evolving landscape
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc
writing some innovation for development and search
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
sudhanshuwaghmare1
Presented by Mike Hicks
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
ThousandEyes
JAM, the future of Polkadot.
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Juan lago vázquez
Webinar Recording: https://www.panagenda.com/webinars/why-teams-call-analytics-is-critical-to-your-entire-business Nothing is as frustrating and noticeable as being in an important call and being unable to see or hear the other person. Not surprising then, that issues with Teams calls are among the most common problems users call their helpdesk for. Having in depth insight into everything relevant going on at the user’s device, local network, ISP and Microsoft itself during the call is crucial for good Microsoft Teams Call quality support. To ensure a quick and adequate solution and to ensure your users get the most out of their Microsoft 365. But did you know that ‘bad calls’ are also an excellent indicator of other problems arising? Precisely because it is so noticeable!? Like the canary in the mine, bad calls can be early indicators of problems. Problems that might otherwise not have been noticed for a while but can have a big impact on productivity and satisfaction. Join this session by Christoph Adler to learn how true Microsoft Teams call quality analytics helped other organizations troubleshoot bad calls and identify and fix problems that impacted Teams calls or the use of Microsoft365 in general. See what it can do to keep your users happy and productive! In this session we will cover - Why CQD data alone is not enough to troubleshoot call problems - The importance of attributing call problems to the right call participant - What call quality analytics can do to help you quickly find, fix-, and prevent problems - Why having retrospective detailed insights matters - Real life examples of how others have used Microsoft Teams call quality monitoring to problem shoot problems with their ISP, network, device health and more.
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
Architecting Cloud Native Applications
Architecting Cloud Native Applications
WSO2
Scalable LLM APIs for AI and Generative AI Application Development Ettikan Karuppiah, Director/Technologist - NVIDIA Apidays Singapore 2024: Connecting Customers, Business and Technology (April 17 & 18, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
apidays
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Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
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Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
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Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
Exploring the Future Potential of AI-Enabled Smartphone Processors
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Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
Architecting Cloud Native Applications
Architecting Cloud Native Applications
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
20081009 meeting
1.
Blog Post and
Comment Extraction Using Information Quantity of Web Format 4th Asia Infomation Retrieval Symposium, AIRS 2008 Reportor : Che-Min Liao
2.
3.
4.
5.
Locating main text
algorthm
6.
Example
7.
8.
Finding Separator Algorithm
9.
10.
Corpus Distribution
11.
12.
Performance comparison of
three locating main text algorithm
13.
Performance of finding
separator algorithm