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الكلية الجامعية للعلوم والتكنولوجيا - خان يونس
University college of science & technology
Classes and objects
Classes and objectsbaabtra.com - No. 1 supplier of quality freshers This document provides an overview of classes and objects in Python. It defines a class as a way to bind data and functions together. An object is an instance of a class and represents an entity with unique identity, state, and behaviors. The document discusses class attributes like __dict__, __doc__, and __name__. It also covers access specifiers like private, protected, and public and provides examples of declaring a class and defining methods in Python.
Java chapter 5
Java chapter 5Abdii Rashid This document discusses key object-oriented programming concepts including encapsulation, inheritance, polymorphism, abstract classes, and interfaces. It provides examples of how encapsulation hides implementation details and inheritance allows classes to inherit properties from superclasses. Polymorphism allows objects to take on multiple forms through inheritance. Abstract classes cannot be instantiated directly but provide a common definition that concrete subclasses implement. Interfaces define behaviors for classes to implement but do not provide implementations.
Inheritance in oop
Inheritance in oopMuskanNazeer The document discusses inheritance in object-oriented programming (OOP) using Java. It defines key inheritance terms like subclass, superclass, and reusability. It provides an example of a Programmer subclass inheriting from the Employee superclass, allowing the Programmer object to access fields and methods from the Employee class. The document also describes different types of inheritance in Java including single inheritance, multilevel inheritance, and multiple inheritance.
Is2215 lecture2 student(2)
Is2215 lecture2 student(2)dannygriff1 This document provides an overview of object-oriented programming and concepts like classes, objects, properties, and methods. A class defines common attributes and behaviors for a group of objects. Properties represent an object's attributes, while methods represent its behaviors. The key concepts of object-oriented programming - encapsulation, inheritance, and polymorphism - are explained. Encapsulation hides implementation details and promotes reusability. Inheritance allows classes to share and extend attributes and behaviors. Polymorphism enables different classes to respond appropriately to the same method name. The document concludes with examples of how to define classes and instantiate objects in code.
OOPS Characteristics
OOPS Characteristicsbaabtra.com - No. 1 supplier of quality freshers This document discusses the key concepts of object-oriented programming (OOP) including objects, classes, encapsulation, inheritance, polymorphism, and abstraction. It defines objects as instances of classes that have data fields and methods. Classes contain both data and functions and can have private, public, or protected members. Encapsulation binds data and functions into a class. Inheritance allows deriving new classes from existing ones. Polymorphism enables classes to provide different implementations of methods with the same name. Abstraction simplifies complexity by modeling appropriate classes for a problem.
Lab 4 (1).pdf
Lab 4 (1).pdfMohammedAlobaidy16 Here is the Cal class to calculate the area of a rectangle:
#include <iostream>
using namespace std;
class Cal {
private:
double width, height;
public:
void setnum(double a, double b) {
width = a;
height = b;
}
double cal_area() {
return width * height;
}
double getnum() {
return cal_area();
}
};
OOAD notes.pptx
OOAD notes.pptxRAJESH S The document discusses key concepts in object-oriented analysis and design (OOAD) including abstraction, encapsulation, class hierarchy, persistence, dynamic binding, inheritance, polymorphism, and metaclasses. It provides definitions and examples for each concept to illustrate how they are applied in OOAD.
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Down the Rabbit Hole – Solving 5 Training Roadblocks
Down the Rabbit Hole – Solving 5 Training RoadblocksRustici Software Feeling stuck in the Matrix of your training technologies? You’re not alone. Managing your training catalog, wrangling LMSs and delivering content across different tools and audiences can feel like dodging digital bullets. At some point, you hit a fork in the road: Keep patching things up as issues pop up… or follow the rabbit hole to the root of the problems.
Good news, we’ve already been down that rabbit hole. Peter Overton and Cameron Gray of Rustici Software are here to share what we found. In this webinar, we’ll break down 5 training roadblocks in delivery and management and show you how they’re easier to fix than you might think.
LSNIF: Locally-Subdivided Neural Intersection Function
LSNIF: Locally-Subdivided Neural Intersection FunctionTakahiro Harada Neural representations have shown the potential to accelerate ray casting in a conventional ray-tracing-based rendering pipeline. We introduce a novel approach called Locally-Subdivided Neural Intersection Function (LSNIF) that replaces bottom-level BVHs used as traditional geometric representations with a neural network. Our method introduces a sparse hash grid encoding scheme incorporating geometry voxelization, a scene-agnostic training data collection, and a tailored loss function. It enables the network to output not only visibility but also hit-point information and material indices. LSNIF can be trained offline for a single object, allowing us to use LSNIF as a replacement for its corresponding BVH. With these designs, the network can handle hit-point queries from any arbitrary viewpoint, supporting all types of rays in the rendering pipeline. We demonstrate that LSNIF can render a variety of scenes, including real-world scenes designed for other path tracers, while achieving a memory footprint reduction of up to 106.2x compared to a compressed BVH.
https://arxiv.org/abs/2504.21627
Oracle Cloud Infrastructure Generative AI Professional
Oracle Cloud Infrastructure Generative AI ProfessionalVICTOR MAESTRE RAMIREZ Oracle Cloud Infrastructure Generative AI Professional
TimeSeries Machine Learning - PyData London 2025
TimeSeries Machine Learning - PyData London 2025Suyash Joshi Timeseries Machine Learning - forecasting and anomaly detection with InfluxDB
Scaling GenAI Inference From Prototype to Production: Real-World Lessons in S...
Scaling GenAI Inference From Prototype to Production: Real-World Lessons in S...Anish Kumar Presented by: Anish Kumar
LinkedIn: https://www.linkedin.com/in/anishkumar/
This lightning talk dives into real-world GenAI projects that scaled from prototype to production using Databricks’ fully managed tools. Facing cost and time constraints, we leveraged four key Databricks features—Workflows, Model Serving, Serverless Compute, and Notebooks—to build an AI inference pipeline processing millions of documents (text and audiobooks).
This approach enables rapid experimentation, easy tuning of GenAI prompts and compute settings, seamless data iteration and efficient quality testing—allowing Data Scientists and Engineers to collaborate effectively. Learn how to design modular, parameterized notebooks that run concurrently, manage dependencies and accelerate AI-driven insights.
Whether you're optimizing AI inference, automating complex data workflows or architecting next-gen serverless AI systems, this session delivers actionable strategies to maximize performance while keeping costs low.
cnc-drilling-dowel-inserting-machine-drillteq-d-510-english.pdf
cnc-drilling-dowel-inserting-machine-drillteq-d-510-english.pdfAmirStern2 CNC מכונות קידוח drillteq d-510
Establish Visibility and Manage Risk in the Supply Chain with Anchore SBOM
Establish Visibility and Manage Risk in the Supply Chain with Anchore SBOMAnchore Over 70% of any given software application consumes open source software (most likely not even from the original source) and only 15% of organizations feel confident in their risk management practices.
With the newly announced Anchore SBOM feature, teams can start safely consuming OSS while mitigating security and compliance risks. Learn how to import SBOMs in industry-standard formats (SPDX, CycloneDX, Syft), validate their integrity, and proactively address vulnerabilities within your software ecosystem.
Agentic AI: Beyond the Buzz- LangGraph Studio V2
Agentic AI: Beyond the Buzz- LangGraph Studio V2Shashikant Jagtap Presentation given at the LangChain community meetup London
https://lu.ma/9d5fntgj
Coveres
Agentic AI: Beyond the Buzz
Introduction to AI Agent and Agentic AI
Agent Use case and stats
Introduction to LangGraph
Build agent with LangGraph Studio V2
Domino IQ – What to Expect, First Steps and Use Cases
Domino IQ – What to Expect, First Steps and Use Casespanagenda Webinar Recording: https://www.panagenda.com/webinars/domino-iq-what-to-expect-first-steps-and-use-cases/
HCL Domino iQ Server – From Ideas Portal to implemented Feature. Discover what it is, what it isn’t, and explore the opportunities and challenges it presents.
Key Takeaways
- What are Large Language Models (LLMs) and how do they relate to Domino iQ
- Essential prerequisites for deploying Domino iQ Server
- Step-by-step instructions on setting up your Domino iQ Server
- Share and discuss thoughts and ideas to maximize the potential of Domino iQ
Introduction to Typescript - GDG On Campus EUE
Introduction to Typescript - GDG On Campus EUEGoogle Developer Group On Campus European Universities in Egypt Interested in leveling up your JavaScript skills? Join us for our Introduction to TypeScript workshop.
Learn how TypeScript can improve your code with dynamic typing, better tooling, and cleaner architecture. Whether you're a beginner or have some experience with JavaScript, this session will give you a solid foundation in TypeScript and how to integrate it into your projects.
Workshop content:
- What is TypeScript?
- What is the problem with JavaScript?
- Why TypeScript is the solution
- Coding demo
DevOps in the Modern Era - Thoughtfully Critical Podcast
DevOps in the Modern Era - Thoughtfully Critical PodcastChris Wahl https://youtu.be/735hP_01WV0
My journey through the world of DevOps! From the early days of breaking down silos between developers and operations to the current complexities of cloud-native environments. I'll talk about my personal experiences, the challenges we faced, and how the role of a DevOps engineer has evolved.
Improving Developer Productivity With DORA, SPACE, and DevEx
Improving Developer Productivity With DORA, SPACE, and DevExJustin Reock Ready to measure and improve developer productivity in your organization?
Join Justin Reock, Deputy CTO at DX, for an interactive session where you'll learn actionable strategies to measure and increase engineering performance.
Leave this session equipped with a comprehensive understanding of developer productivity and a roadmap to create a high-performing engineering team in your company.
Trends Artificial Intelligence - Mary Meeker
Trends Artificial Intelligence - Mary MeekerClive Dickens Mary Meeker’s 2024 AI report highlights a seismic shift in productivity, creativity, and business value driven by generative AI. She charts the rapid adoption of tools like ChatGPT and Midjourney, likening today’s moment to the dawn of the internet. The report emphasizes AI’s impact on knowledge work, software development, and personalized services—while also cautioning about data quality, ethical use, and the human-AI partnership. In short, Meeker sees AI as a transformative force accelerating innovation and redefining how we live and work.
Integration of Utility Data into 3D BIM Models Using a 3D Solids Modeling Wor...
Integration of Utility Data into 3D BIM Models Using a 3D Solids Modeling Wor...Safe Software Jacobs has developed a 3D utility solids modelling workflow to improve the integration of utility data into 3D Building Information Modeling (BIM) environments. This workflow, a collaborative effort between the New Zealand Geospatial Team and the Australian Data Capture Team, employs FME to convert 2D utility data into detailed 3D representations, supporting enhanced spatial analysis and clash detection.
To enable the automation of this process, Jacobs has also developed a survey data standard that standardizes the capture of existing utilities. This standard ensures consistency in data collection, forming the foundation for the subsequent automated validation and modelling steps. The workflow begins with the acquisition of utility survey data, including attributes such as location, depth, diameter, and material of utility assets like pipes and manholes. This data is validated through a custom-built tool that ensures completeness and logical consistency, including checks for proper connectivity between network components. Following validation, the data is processed using an automated modelling tool to generate 3D solids from 2D geometric representations. These solids are then integrated into BIM models to facilitate compatibility with 3D workflows and enable detailed spatial analyses.
The workflow contributes to improved spatial understanding by visualizing the relationships between utilities and other infrastructure elements. The automation of validation and modeling processes ensures consistent and accurate outputs, minimizing errors and increasing workflow efficiency.
This methodology highlights the application of FME in addressing challenges associated with geospatial data transformation and demonstrates its utility in enhancing data integration within BIM frameworks. By enabling accurate 3D representation of utility networks, the workflow supports improved design collaboration and decision-making in complex infrastructure projects
Introduction to Typescript - GDG On Campus EUE
Introduction to Typescript - GDG On Campus EUEGoogle Developer Group On Campus European Universities in Egypt
Python Class | Python Programming | Python Tutorial | Edureka
- 1. www.edureka.co/devopsEDUREKA DEVOPS CERTIFICATION TRAINING Python Classes
- 2. www.edureka.co/devopsEDUREKA DEVOPS CERTIFICATION TRAINING Agenda Classes and Objects 1 Classes in Python 2 Inheritance 3 Abstract Class 4
- 3. www.edureka.co/devopsEDUREKA DEVOPS CERTIFICATION TRAINING Classes and Objects Objects Employee Name Age Salary Class Sarah 37 10000 Neel 43 21000 Jessica 26 24000 Object1 Object2 Object3
- 4. www.edureka.co/devopsEDUREKA DEVOPS CERTIFICATION TRAINING Classes in Python Syntax: ❑ A class is the blueprint from which specific objects are created. Class Data MemberClass Variable A variable that is shared by all instances of a class. A class variable or instance variable that holds data associated with a class and its objects. Instance Variable instance variable unique to each instance
- 5. www.edureka.co/devopsEDUREKA DEVOPS CERTIFICATION TRAINING Class Inheritance ❑ A class can inherit attributes and behavior methods from another class, called the superclass. ❑ A class which inherits from a superclass is called a subclass, also called heir class or child class. Vehicle Trucks Bikescars Medium Heavy PedalVans MotorSportsConvertible Pick-up Superclass Baseclass Baseclass Baseclass Derivedclass Derivedclass
- 6. www.edureka.co/devopsEDUREKA DEVOPS CERTIFICATION TRAINING Abstract Class ❑ Abstract Class cannot be instantiated. ❑ It can only be inherited. Abstract Class Object of Abstract Class Inherit Abstract Class Object of Class1 Class1
- 7. www.edureka.co/devopsEDUREKA DEVOPS CERTIFICATION TRAINING Session In A Minute Classes and Objects Inheritance Classes in Python Abstract Class
- 8. www.edureka.co/devopsEDUREKA DEVOPS CERTIFICATION TRAINING Thank You