Data modeling
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Data modeling is the process of visually representing what data an application or system will use and how the data will flow. It involves defining data objects called entities, their attributes, and the relationships between entities. Common data modeling techniques include UML and ERD. Entities represent composite information and have attributes. Relationships show how entities relate to each other. Cardinality specifies the number of relationships between entities, such as one-to-one, one-to-many, and many-to-many. Examples of data modeling for a person, online course, and banking system are provided.
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Optimal use of resources, including energy, is one of the most important principles in modern and sustainable agricultural systems. Exergy analysis and life cycle assessment were used to study the efficient use of inputs, energy consumption reduction, and various environmental effects in the corn production system in Lorestan province, Iran. The required data were collected from farmers in Lorestan province using random sampling. The Cobb-Douglas equation and data envelopment analysis were utilized for modeling and optimizing cumulative energy and exergy consumption (CEnC and CExC) and devising strategies to mitigate the environmental impacts of corn production. The Cobb-Douglas equation results revealed that electricity, diesel fuel, and N-fertilizer were the major contributors to CExC in the corn production system. According to the Data Envelopment Analysis (DEA) results, the average efficiency of all farms in terms of CExC was 94.7% in the CCR model and 97.8% in the BCC model. Furthermore, the results indicated that there was excessive consumption of inputs, particularly potassium and phosphate fertilizers. By adopting more suitable methods based on DEA of efficient farmers, it was possible to save 6.47, 10.42, 7.40, 13.32, 31.29, 3.25, and 6.78% in the exergy consumption of diesel fuel, electricity, machinery, chemical fertilizers, biocides, seeds, and irrigation, respectively. Turbocor Product and Technology Review.pdf
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High Efficiency Chiller System in HVAC
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Preface: The ReGenX Generator innovation operates with a US Patented Frequency Dependent Load Current Delay which delays the creation and storage of created Electromagnetic Field Energy around the exterior of the generator coil. The result is the created and Time Delayed Electromagnetic Field Energy performs any magnitude of Positive Electro-Mechanical Work at infinite efficiency on the generator's Rotating Magnetic Field, increasing its Kinetic Energy and increasing the Kinetic Energy of an EV or ICE Vehicle to any magnitude without requiring any Externally Supplied Input Energy. In Electricity Generation applications the ReGenX Generator innovation now allows all electricity to be generated at infinite efficiency requiring zero Input Energy, zero Input Energy Cost, while producing zero Greenhouse Gas Emissions, zero Air Pollution and zero Nuclear Waste during the Electricity Generation Phase. In Electric Motor operation the ReGen-X Quantum Motor now allows any magnitude of Work to be performed with zero Electric Input Energy.
Demonstration Protocol: The demonstration protocol involves three prototypes;
1. Protytpe #1, demonstrates the ReGenX Generator's Load Current Time Delay when compared to the instantaneous Load Current Sine Wave for a Conventional Generator Coil.
2. In the Conventional Faraday Generator operation the created Electromagnetic Field Energy performs Negative Work at infinite efficiency and it reduces the Kinetic Energy of the system.
3. The Magnitude of the Negative Work / System Kinetic Energy Reduction (in Joules) is equal to the Magnitude of the created Electromagnetic Field Energy (also in Joules).
4. When the Conventional Faraday Generator is placed On-Load, Negative Work is performed and the speed of the system decreases according to Lenz's Law of Induction.
5. In order to maintain the System Speed and the Electric Power magnitude to the Loads, additional Input Power must be supplied to the Prime Mover and additional Mechanical Input Power must be supplied to the Generator's Drive Shaft.
6. For example, if 100 Watts of Electric Power is delivered to the Load by the Faraday Generator, an additional >100 Watts of Mechanical Input Power must be supplied to the Generator's Drive Shaft by the Prime Mover.
7. If 1 MW of Electric Power is delivered to the Load by the Faraday Generator, an additional >1 MW Watts of Mechanical Input Power must be supplied to the Generator's Drive Shaft by the Prime Mover.
8. Generally speaking the ratio is 2 Watts of Mechanical Input Power to every 1 Watt of Electric Output Power generated.
9. The increase in Drive Shaft Mechanical Input Power is provided by the Prime Mover and the Input Energy Source which powers the Prime Mover.
10. In the Heins ReGenX Generator operation the created and Time Delayed Electromagnetic Field Energy performs Positive Work at infinite efficiency and it increases the Kinetic Energy of the system.Introduction to Safety, Health & Environment
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Duplicate Frankfurt University of Applied Science urkunde, make a Frankfurt UAS degree.How to Make an RFID Door Lock System using Arduino
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Learn how to build an RFID-based door lock system using Arduino to enhance security with contactless access control.How to Build a Maze Solving Robot Using Arduino
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Learn how to make an Arduino-powered robot that can navigate mazes on its own using IR sensors and "Hand on the wall" algorithm.
This step-by-step guide will show you how to build your own maze-solving robot using Arduino UNO, three IR sensors, and basic components that you can easily find in your local electronics shop.Mathematics behind machine learning INT255 INT255__Unit 3__PPT-1.pptx
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This PPT covers the index and engineering properties of soil. It includes details on index properties, along with their methods of determination. Various important terms related to soil behavior are explained in detail. The presentation also outlines the experimental procedures for determining soil properties such as water content, specific gravity, plastic limit, and liquid limit, along with the necessary calculations and graph plotting. Additionally, it provides insights to understand the importance of these properties in geotechnical engineering applications.
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The cost in USD/kwh for H2
Daniel Donatelli
Secure Supplies Group
Index
• Introduction - Page 3
• The Need for Hydrogen Fueling - Page 5
• Pure H2 Fueling Technology - Page 7
• Blend Gas Fueling: A Transition Strategy - Page 10
• Performance Metrics: H2 vs. Fossil Fuels - Page 12
• Cost Analysis and Economic Viability - Page 15
• Innovations Driving Leadership - Page 18
• Laminar Flame Speed Adjustment
• Heat Management Systems
• The Donatelli Cycle
• Non-Carnot Cycle Applications
• Case Studies and Real-World Applications - Page 22
• Conclusion: Secure Supplies’ Leadership in Hydrogen Fueling - Page 27
Optimization of Cumulative Energy, Exergy Consumption and Environmental Life ...
Optimization of Cumulative Energy, Exergy Consumption and Environmental Life ...J. Agricultural Machinery
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US Patented ReGenX Generator, ReGen-X Quatum Motor EV Regenerative Accelerati...
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Data modeling
- 2. Data Modeling • Requirements modeling includes many sub-stages, one of them being data modeling. • Once a use case exists, one of the stages that follow will be data modeling. • Data modeling, sometimes also called information modeling, is the process of visually representing what data the application or system will use, and how the data will flow.
- 3. Data Modeling • The fundamental elements that a data model needs to include and describe are the data objects, more frequently called 'entities', the attributes of those objects/entities, and the relationships between the objects/entities. • The two most widely used are UML (Unified Modeling Language), and ERD (Entity-Relationship Diagrams). • The software engineer defines all the data object that proceeds within the system and the relationship between data objects are identified.
- 5. Data Object • The data object is the representation of composite information. • The composite information means an object has a number of different properties or attribute. • For example, Height is a single value so it is not a valid data object, but dimensions contain the height, the width and depth these are defined as an object. • Data Entity /Object • An entity is something that exists as itself, as a subject or as an object, actually or potentially, concretely or abstractly, physically or not. • Data Attributes Each of the data object has a set of attributes. • Relationship Relationship shows the relationship between data objects and how they are related to each other. • Cardinality Cardinality state the number of events of one object related to the number of events of another object.
- 6. Cardinality  The cardinality expressed as: One to one (1:1) One event of an object is related to one event of another object. For example, one employee has only one ID. One to many (1:N) One event of an object is related to many events. For example, One collage has many departments. Many to many(M:N) Many events of one object are related to many events of another object. For example, many customer place order for many products.
- 7. Example of Person Object