EXCEPTION HANDLING IN PYTHON For students .py.pptx
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This document discusses exception handling in Python. It defines exceptions as errors that occur at runtime, such as file not found or divide by zero errors. It explains that Python creates an exception object whenever a runtime error occurs. It also discusses try and except blocks for handling exceptions, nested try blocks, handling multiple exceptions in a single except block, raising exceptions with the raise keyword, finally blocks which are always executed, and user-defined exceptions.
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Fluid kinematics is the branch of fluid mechanics that focuses on describing and analyzing the motion of fluids, such as liquids and gases, without considering the forces that cause the motion. It deals with the geometrical and temporal aspects of fluid flow, including velocity and acceleration. Fluid dynamics, on the other hand, considers the forces acting on the fluid.
Fluid dynamics is the study of the effect of forces on fluid motion. It is a branch of continuum mechanics, a subject which models matter without using the information that it is made out of atoms; that is, it models matter from a macroscopic viewpoint rather than from microscopic.
Fluid mechanics, especially fluid dynamics, is an active field of research, typically mathematically complex. Many problems are partly or wholly unsolved and are best addressed by numerical methods, typically using computers. A modern discipline, called computational fluid dynamics (CFD), is devoted to this approach. Particle image velocimetry, an experimental method for visualizing and analyzing fluid flow, also takes advantage of the highly visual nature of fluid flow.
Fundamentally, every fluid mechanical system is assumed to obey the basic laws :
Conservation of mass
Conservation of energy
Conservation of momentum
The continuum assumption
For example, the assumption that mass is conserved means that for any fixed control volume (for example, a spherical volume)—enclosed by a control surface—the rate of change of the mass contained in that volume is equal to the rate at which mass is passing through the surface from outside to inside, minus the rate at which mass is passing from inside to outside. This can be expressed as an equation in integral form over the control volume.
The continuum assumption is an idealization of continuum mechanics under which fluids can be treated as continuous, even though, on a microscopic scale, they are composed of molecules. Under the continuum assumption, macroscopic (observed/measurable) properties such as density, pressure, temperature, and bulk velocity are taken to be well-defined at "infinitesimal" volume elements—small in comparison to the characteristic length scale of the system, but large in comparison to molecular length scale
ELectronics Boards & Product Testing_Shiju.pdf
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"Feed Water Heaters in Thermal Power Plants: Types, Working, and Efficiency G...
"Feed Water Heaters in Thermal Power Plants: Types, Working, and Efficiency G...Infopitaara A feed water heater is a device used in power plants to preheat water before it enters the boiler. It plays a critical role in improving the overall efficiency of the power generation process, especially in thermal power plants.
🔧 Function of a Feed Water Heater:
It uses steam extracted from the turbine to preheat the feed water.
This reduces the fuel required to convert water into steam in the boiler.
It supports Regenerative Rankine Cycle, increasing plant efficiency.
🔍 Types of Feed Water Heaters:
Open Feed Water Heater (Direct Contact)
Steam and water come into direct contact.
Mixing occurs, and heat is transferred directly.
Common in low-pressure stages.
Closed Feed Water Heater (Surface Type)
Steam and water are separated by tubes.
Heat is transferred through tube walls.
Common in high-pressure systems.
⚙️ Advantages:
Improves thermal efficiency.
Reduces fuel consumption.
Lowers thermal stress on boiler components.
Minimizes corrosion by removing dissolved gases.
Data Structures_Introduction to algorithms.pptx
Data Structures_Introduction to algorithms.pptxRushaliDeshmukh2 Concept of Problem Solving, Introduction to Algorithms, Characteristics of Algorithms, Introduction to Data Structure, Data Structure Classification (Linear and Non-linear, Static and Dynamic, Persistent and Ephemeral data structures), Time complexity and Space complexity, Asymptotic Notation - The Big-O, Omega and Theta notation, Algorithmic upper bounds, lower bounds, Best, Worst and Average case analysis of an Algorithm, Abstract Data Types (ADT)
DT REPORT by Tech titan GROUP to introduce the subject design Thinking
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Process Parameter Optimization for Minimizing Springback in Cold Drawing Proc...
Process Parameter Optimization for Minimizing Springback in Cold Drawing Proc...Journal of Soft Computing in Civil Engineering In tube drawing process, a tube is pulled out through a die and a plug to reduce its diameter and thickness as per the requirement. Dimensional accuracy of cold drawn tubes plays a vital role in the further quality of end products and controlling rejection in manufacturing processes of these end products. Springback phenomenon is the elastic strain recovery after removal of forming loads, causes geometrical inaccuracies in drawn tubes. Further, this leads to difficulty in achieving close dimensional tolerances. In the present work springback of EN 8 D tube material is studied for various cold drawing parameters. The process parameters in this work include die semi-angle, land width and drawing speed. The experimentation is done using Taguchi’s L36 orthogonal array, and then optimization is done in data analysis software Minitab 17. The results of ANOVA shows that 15 degrees die semi-angle,5 mm land width and 6 m/min drawing speed yields least springback. Furthermore, optimization algorithms named Particle Swarm Optimization (PSO), Simulated Annealing (SA) and Genetic Algorithm (GA) are applied which shows that 15 degrees die semi-angle, 10 mm land width and 8 m/min drawing speed results in minimal springback with almost 10.5 % improvement. Finally, the results of experimentation are validated with Finite Element Analysis technique using ANSYS.
International Journal of Distributed and Parallel systems (IJDPS)
International Journal of Distributed and Parallel systems (IJDPS)samueljackson3773 The growth of Internet and other web technologies requires the development of new
algorithms and architectures for parallel and distributed computing. International journal of
Distributed and parallel systems is a bimonthly open access peer-reviewed journal aims to
publish high quality scientific papers arising from original research and development from
the international community in the areas of parallel and distributed systems. IJDPS serves
as a platform for engineers and researchers to present new ideas and system technology,
with an interactive and friendly, but strongly professional atmosphere.
Level 1-Safety.pptx Presentation of Electrical Safety
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The Gaussian Process Modeling Module in UQLab
The Gaussian Process Modeling Module in UQLabJournal of Soft Computing in Civil Engineering We introduce the Gaussian process (GP) modeling module developed within the UQLab software framework. The novel design of the GP-module aims at providing seamless integration of GP modeling into any uncertainty quantification workflow, as well as a standalone surrogate modeling tool. We first briefly present the key mathematical tools on the basis of GP modeling (a.k.a. Kriging), as well as the associated theoretical and computational framework. We then provide an extensive overview of the available features of the software and demonstrate its flexibility and user-friendliness. Finally, we showcase the usage and the performance of the software on several applications borrowed from different fields of engineering. These include a basic surrogate of a well-known analytical benchmark function; a hierarchical Kriging example applied to wind turbine aero-servo-elastic simulations and a more complex geotechnical example that requires a non-stationary, user-defined correlation function. The GP-module, like the rest of the scientific code that is shipped with UQLab, is open source (BSD license).
Data Structures_Searching and Sorting.pptx
Data Structures_Searching and Sorting.pptxRushaliDeshmukh2 Sorting Order and Stability in Sorting.
Concept of Internal and External Sorting.
Bubble Sort,
Insertion Sort,
Selection Sort,
Quick Sort and
Merge Sort,
Radix Sort, and
Shell Sort,
External Sorting, Time complexity analysis of Sorting Algorithms.
ADVXAI IN MALWARE ANALYSIS FRAMEWORK: BALANCING EXPLAINABILITY WITH SECURITY
ADVXAI IN MALWARE ANALYSIS FRAMEWORK: BALANCING EXPLAINABILITY WITH SECURITYijscai With the increased use of Artificial Intelligence (AI) in malware analysis there is also an increased need to
understand the decisions models make when identifying malicious artifacts. Explainable AI (XAI) becomes
the answer to interpreting the decision-making process that AI malware analysis models use to determine
malicious benign samples to gain trust that in a production environment, the system is able to catch
malware. With any cyber innovation brings a new set of challenges and literature soon came out about XAI
as a new attack vector. Adversarial XAI (AdvXAI) is a relatively new concept but with AI applications in
many sectors, it is crucial to quickly respond to the attack surface that it creates. This paper seeks to
conceptualize a theoretical framework focused on addressing AdvXAI in malware analysis in an effort to
balance explainability with security. Following this framework, designing a machine with an AI malware
detection and analysis model will ensure that it can effectively analyze malware, explain how it came to its
decision, and be built securely to avoid adversarial attacks and manipulations. The framework focuses on
choosing malware datasets to train the model, choosing the AI model, choosing an XAI technique,
implementing AdvXAI defensive measures, and continually evaluating the model. This framework will
significantly contribute to automated malware detection and XAI efforts allowing for secure systems that
are resilient to adversarial attacks.
"Boiler Feed Pump (BFP): Working, Applications, Advantages, and Limitations E...
"Boiler Feed Pump (BFP): Working, Applications, Advantages, and Limitations E...Infopitaara A Boiler Feed Pump (BFP) is a critical component in thermal power plants. It supplies high-pressure water (feedwater) to the boiler, ensuring continuous steam generation.
⚙️ How a Boiler Feed Pump Works
Water Collection:
Feedwater is collected from the deaerator or feedwater tank.
Pressurization:
The pump increases water pressure using multiple impellers/stages in centrifugal types.
Discharge to Boiler:
Pressurized water is then supplied to the boiler drum or economizer section, depending on design.
🌀 Types of Boiler Feed Pumps
Centrifugal Pumps (most common):
Multistage for higher pressure.
Used in large thermal power stations.
Positive Displacement Pumps (less common):
For smaller or specific applications.
Precise flow control but less efficient for large volumes.
🛠️ Key Operations and Controls
Recirculation Line: Protects the pump from overheating at low flow.
Throttle Valve: Regulates flow based on boiler demand.
Control System: Often automated via DCS/PLC for variable load conditions.
Sealing & Cooling Systems: Prevent leakage and maintain pump health.
⚠️ Common BFP Issues
Cavitation due to low NPSH (Net Positive Suction Head).
Seal or bearing failure.
Overheating from improper flow or recirculation.
15th International Conference on Computer Science, Engineering and Applicatio...
15th International Conference on Computer Science, Engineering and Applicatio...IJCSES Journal #computerscience #programming #coding #technology #programmer #python #computer #developer #tech #coder #javascript #java #codinglife #html #code #softwaredeveloper #webdeveloper #software #cybersecurity #linux #computerengineering #webdevelopment #softwareengineer #machinelearning #hacking #engineering #datascience #css #programmers #pythonprogramming
RICS Membership-(The Royal Institution of Chartered Surveyors).pdf
RICS Membership-(The Royal Institution of Chartered Surveyors).pdfMohamedAbdelkader115 Glad to be one of only 14 members inside Kuwait to hold this credential.
Please check the members inside kuwait from this link:
https://www.rics.org/networking/find-a-member.html?firstname=&lastname=&town=&country=Kuwait&member_grade=(AssocRICS)&expert_witness=&accrediation=&page=1
Process Parameter Optimization for Minimizing Springback in Cold Drawing Proc...
Process Parameter Optimization for Minimizing Springback in Cold Drawing Proc...Journal of Soft Computing in Civil Engineering
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EXCEPTION HANDLING IN PYTHON For students .py.pptx
- 1. EXCEPTION HANDLING IN PYTHON NAME: MIHIR BHARDWAJ CLASS:MCA 2ND SEM SUB :PYTHON MUR:MUR2301439
- 2. TOPIC EXCEPTION EXCEPTION HANDLING TRY AND EXCEPT NESTED TRY BLOCK HANDLING MULTIPLE EXCEPTION IN SINGLE EXCEPT BLOCK RISING EXCEPTION FINALLY BLOCK USER DEFINED EXCEPTIONS
- 3. EXCEPTION Error caused by not following the proper structure(syntax) of the language is called syntax error. Errors are also occur at runtime and these are called exception They occur, for example, when we try to open file and it not exist (file not FoundError),dividing a number by Zero(Zero DivisionError). When ever these type of run error occour, python creates an exception object.
- 4. EXCEPTION
- 6. Raising Exceptions The raise statement in Python is used to raise an exception. The raise keyword is typically used inside a function or method, and is used to indicate an error condition. We can throw an exception and immediately halt the running of your programme by using the raise keyword.
- 7. Finally Block finally block is always executed after leaving the try statement. In case if some exception was not handled by except block, it is re-raised after execution of finally block. finally block is used to deallocate the system resources.
- 8. User define function Functions that we define ourselves to do certain specific task are referred as user- defined functions. Functions that readily come with Python are called built-in functions.