Er diagrams
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ER diagrams model the conceptual view of a database by representing real-world entities and the relationships between them. Entities have attributes that define their properties. Relationships associate entities and can be binary, ternary, or n-ary. Relationships have cardinalities like one-to-one, one-to-many, many-to-one, or many-to-many to indicate the number of entities that can be related. ER diagrams visually depict these concepts using rectangles for entities, ellipses for attributes, diamonds for relationships, and notation like 1:N to specify cardinalities.
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Here are the entity relationship diagrams and tables for the car insurance company database:
(a) E-R Diagram:
Person - owns - Car
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Car - involved in - Accident
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(b) Tables:
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accident
(report_number primary key,
date, location)
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(driver_id foreign key references person,
license foreign key references car,
report_number foreign key references accident
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This document discusses mapping cardinality and participation constraints in entity-relationship (E-R) modeling. It defines mapping cardinality as specifying how many entities can be related in a relationship set. The main types are many-to-many, many-to-one, one-to-many, and one-to-one. Participation constraints specify the minimum number of relationship instances an entity must participate in. Total participation means each entity must participate in at least one relationship, while partial participation means some entities may not participate. Examples of students enrolling in courses are provided to illustrate these concepts.
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Here are the entity relationship diagrams and tables for the car insurance company database:
(a) E-R Diagram:
Person - owns - Car
(1:M)
Car - involved in - Accident
(0:M)
(b) Tables:
person
(driver_id primary key,
name, address)
car
(license primary key,
year, model, driver_id foreign key references person)
accident
(report_number primary key,
date, location)
participated
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license foreign key references car,
report_number foreign key references accident
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This document discusses mapping cardinality and participation constraints in entity-relationship (E-R) modeling. It defines mapping cardinality as specifying how many entities can be related in a relationship set. The main types are many-to-many, many-to-one, one-to-many, and one-to-one. Participation constraints specify the minimum number of relationship instances an entity must participate in. Total participation means each entity must participate in at least one relationship, while partial participation means some entities may not participate. Examples of students enrolling in courses are provided to illustrate these concepts.
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This document discusses data models and their components. A data model includes entities, attributes, data values, key attributes, and records. Entities represent people, places, things, events or concepts, attributes characterize entities and describe them meaningfully, data values are the attribute values, key attributes uniquely identify records, and records are collections of entity attributes. Relationships between entities can be one-to-one, one-to-many, or many-to-many. Common symbols are used in entity-relationship diagrams to represent these components and relationships.
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The document provides information on the key concepts of an entity-relationship (E-R) model, including:
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2) Relationships represent associations between entities. Relationships have properties like degree, cardinality, and existence.
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Advantages and disadvantages of er model in DBMS. Types of database models ..
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Network model.
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3) Relationship types associate multiple entity types and have structural constraints like cardinality ratios that specify the minimum and maximum number of relationships an entity can participate in.
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1) A relational database represents data using relations (tables) with rows and columns, where each row represents a fact and each column represents an attribute.
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The document provides information on the key concepts of an entity-relationship (E-R) model, including:
1) Entities represent real-world objects like people, places, and things that are stored in a database. Attributes describe the properties of entities.
2) Relationships represent associations between entities. Relationships have properties like degree, cardinality, and existence.
3) Keys like primary keys and foreign keys uniquely identify entities and define relationships between entities.
4) Strong and weak entities differ in whether they have their own primary keys or rely on other entities.
5) E-R diagrams visually depict entities, attributes, relationships, keys and other concepts to model a database.
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This document discusses the entity-relationship (ER) model for conceptual database design. It defines key concepts like entities, attributes, relationships, keys, and participation constraints. Entities can be strong or weak, and attributes can be simple, composite, multi-valued, or derived. Relationships associate entities and can specify cardinality like one-to-one, one-to-many, or many-to-many. The ER model diagrams the structure and constraints of a database before its logical and physical implementation.
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The document discusses the entity relationship (ER) model used for conceptual database design. It describes the key components of an ER diagram including entities represented as rectangles, attributes described as ovals, and relationships shown as diamonds. Different types of relationships are also defined such as one-to-one, one-to-many, many-to-one, and many-to-many. The ER model provides a way to design and visualize the entities, attributes, and relationships within a database in a simple diagram.
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The document discusses key concepts in entity-relationship (ER) modeling including:
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- Relationships define associations between entities, such as a student enrolling in a course. Relationships have cardinalities that specify how many entities can be connected.
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Preprocessor directives are commands that are executed by the C preprocessor before compilation. Common preprocessor directives include #include to add header files, #define for macros, #if/#elif/#else for conditional compilation, and #undef to remove macros. Standard input/output functions like printf(), scanf(), gets(), puts() handle formatted and unformatted console I/O. These functions allow reading user input from the keyboard and displaying output to the monitor.
Window object
The document summarizes various browser objects including the window, form, history, and date objects. The window object represents a browser window and has properties like closed, status, and location. It can be used to open new windows. The form object takes attributes like name, method, and action. The history object represents the browser history and has properties like next, previous, and current. The date object handles date and time values and has methods like getDate(), getMonth(), and setHours().
DTD elements
this presentation covers
1. declaring elements
2. control characters
3. dtd attributes and entities
Html
This document provides an introduction to HTML and discusses why learning it is important for careers in web design and development. It notes that associate degrees or certificate programs in subjects like web design and development can prepare students for entry-level jobs, while bachelor's degrees allow students to learn more advanced skills for jobs in web design, development, and other computer fields. Certificate programs typically include courses in HTML, Flash, JavaScript, and Perl and can help with career changes.
Css font
The document discusses CSS properties for fonts, text, background, positioning, and layers. It defines CSS properties like font-family, font-size, background-color, position, z-index and provides examples of how to use each one. Properties like font-family set the font, font-size sets the text size, background-color sets the background color, position controls element positioning, and z-index controls layer order for overlapping elements.
consumer oriented applications
This document discusses various consumer-oriented applications of personal finance management and home banking. It outlines basic services like ATMs, intermediate services, and advanced services. Basic services discussed ATMs and their cost savings. Advanced services discussed home shopping through television, catalogs both physical and online, and microtransactions for small information services. The key is giving customers control over their banking and purchasing.
architecture framework for ecommerce
The document describes an architecture framework for ecommerce applications consisting of 6 layers: 1) Application services with consumer, business, and intra-organization applications, 2) Brokerage and data management for service integration, 3) Interface layer providing catalogs and directories, 4) Secure messaging for communicating data, 5) Middleware services for interaction between systems, and 6) Network infrastructure including the World Wide Web as an architecture with protocols like HTTP, IP, and TCP. Communication between layers is enabled by protocols such as FTP, HTTP, SMTP, and SSL to securely transfer files and messages.
impact of ecommerce on traditional means
The document discusses the advantages and disadvantages of e-commerce. It also discusses various technical and non-technical limitations of e-commerce including lack of system security, rapidly changing software tools, high costs, and lack of customer trust in online transactions. Additionally, it outlines different types of e-commerce models including business-to-business, business-to-consumer, consumer-to-business, and consumer-to-consumer. Finally, it discusses the impact of e-commerce on traditional business models and the need for new integrated business and e-commerce goals.
electronic data interchange
This document discusses electronic data interchange (EDI) and outlines the key steps involved in a partially integrated EDI system. It also lists the pre-requisites for implementing an EDI system, including identifying needs, weighing costs and benefits, selecting partners, and planning implementation. Finally, it addresses some of the legal, security, and privacy issues related to EDI systems.
consumer oriented applications
This document discusses various consumer-oriented applications of personal finance management and home banking. It describes basic services like ATMs, intermediate services, and advanced services. Advanced services discussed include home shopping through television, catalogs, and microtransactions of information. The key benefits highlighted are avoiding lines, flexibility of banking anytime, and lower costs compared to manual processing.
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structures in C and Union in C, enumerated datatype
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DeFi represents a paradigm shift in the financial industry. Instead of relying on traditional, centralized institutions like banks, DeFi leverages blockchain technology to create a decentralized network of financial services. This means that financial transactions can occur directly between parties, without intermediaries, using smart contracts on platforms like Ethereum.
In 2024, we are witnessing an explosion of new DeFi projects and protocols, each pushing the boundaries of what’s possible in finance.
In summary, DeFi in 2024 is not just a trend; it’s a revolution that democratizes finance, enhances security and transparency, and fosters continuous innovation. As we proceed through this presentation, we'll explore the various components and services of DeFi in detail, shedding light on how they are transforming the financial landscape.
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GNSS spoofing via SDR (Criptored Talks 2024)
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
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This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
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Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
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4. Deployment Using ArgoCD for Edge Devices
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5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
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7. What is Prometheus?
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8. Monitoring Application Metrics with Prometheus
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9. What is Camel K?
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10. Configuring Camel K Integrations for Data Pipelines
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11. What is a Jupyter Notebook?
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5th LF Energy Power Grid Model Meet-up Slides
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
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With Skybuffer AI, various AI models can be integrated into a single communication channel such as Microsoft Teams. This integration empowers business users with insights drawn from SAP backend systems, enterprise documents, and the expansive knowledge of Generative AI. And the best part of it is that it is all managed through our intuitive no-code Action Server interface, requiring no extensive coding knowledge and making the advanced AI accessible to more users.
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Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
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Er diagrams
- 1. ER diagrams The ER model defines the conceptual view of a database. It works around real-world entities and the associations among them. • Entity: An entity can be a real-world object, either animate or inanimate, that can be easily identifiable. • Attributes: Entities are represented by means of their properties, called attributes. All attributes have values.
- 2. Types of Attributes • Simple attribute • Composite attribute • Derived attribute • Single-value attribute • Multi-value attribute
- 3. Relationship The association among entities is called a relationship. Degree of Relationship • The number of participating entities in a relationship defines the degree of the relationship. Binary = degree 2 Ternary = degree 3 n-ary = degree
- 4. Mapping Cardinalities 1. One-to-one − One entity from entity set A can be associated with at most one entity of entity set B and vice versa. 2. One-to-many − One entity from entity set A can be associated with more than one entities of entity set B however an entity from entity set B, can be associated with at most one entity.
- 5. 3. Many-to-one − More than one entities from entity set A can be associated with at most one entity of entity set B, however an entity from entity set B can be associated with more than one entity from entity set A. 4. Many-to-many − One entity from A can be associated with more than one entity from B and vice versa.
- 6. ER Diagram Representation 1. Entity: Entities are represented by means of rectangles. Rectangles are named with the entity set they represent. 2. Attributes: Attributes are the properties of entities. Attributes are represented by means of ellipses. Every ellipse represents one attribute and is directly connected to its entity (rectangle).
- 7. Composite attribute Multi-valued attribute Derived attribute
- 8. Relationship Relationships are represented by diamond-shaped box. All the entities (rectangles) participating in a relationship, are connected to it by a line. Binary Relationship and Cardinality A relationship where two entities are participating is called a binary relationship. Cardinality is the number of instance of an entity from a relation that can be associated with the relation. • One-to-one − When only one instance of an entity is associated with the relationship, it is marked as '1:1'.
- 9. • One-to-many − When more than one instance of an entity is associated with a relationship, it is marked as '1:N‘. • Many-to-one − When more than one instance of entity is associated with the relationship, it is marked as 'N:1'. • Many-to-many - more than one instance of an entity on the left and more than one instance of an entity on the right can be associated with the relationship.