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This document discusses random number generators and reviews Intel's random number generator. It begins with an introduction to random number generation and common pseudorandom number generators like linear congruential generators. It then describes Intel's true random number generator which uses thermal noise from resistors to modulate the frequency of an oscillator. The random bits generated from the clock drift are then processed digitally before being made available through Intel's software library. Empirical and theoretical tests for evaluating random number generators are also summarized.

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Generate and test random numbers

This document discusses methods for generating and testing random numbers. There are two main types of random number generators discussed: combined generators and inversive generators. Combined generators work by combining the outputs of two or more simpler random number generators. They are useful for simulating highly reliable systems or complex networks. The document also discusses how to test random numbers using the Kolmogorov-Smirnov test and runs tests. The Kolmogorov-Smirnov test compares the cumulative distribution function of observed values to expected values, while runs tests examine the arrangements of values in a sequence. Both can be used to determine if a random number generator is producing independent and identically distributed values.

Big o notation

this is a briefer overview about the Big O Notation. Big O Notaion are useful to check the Effeciency of an algorithm and to check its limitation at higher value. with big o notation some examples are also shown about its cases and some functions in c++ are also described.

Two Pseudo-random Number Generators, an Overview

This document provides an overview of two pseudorandom number generators: the linear congruential generator (LCG) and the Blum-Blum-Shub (BBS) pseudorandom bit generator. It describes how LCGs work using a linear recurrence formula to generate pseudorandom numbers from a seed value. It also explains that BBS generators are cryptographically secure as they pass the next-bit test, making the sequence unpredictable. The document concludes by thanking the audience for their time and inviting comments and questions.

Back propagation

The document discusses artificial neural networks and backpropagation. It provides an overview of backpropagation algorithms, including how they were developed over time, the basic methodology of propagating errors backwards, and typical network architectures. It also gives examples of applying backpropagation to problems like robotics, space robots, handwritten digit recognition, and face recognition.

COA-QUESTION-BANK.pdf

This document contains a question bank prepared by students for the Computer Organization and Architecture course taught by Prof. Debashis Hati at KIIT University. It includes 73 multiple choice and short answer questions covering various topics in computer organization such as basic computer structure, machine instructions, addressing modes, and subroutines. The questions are intended to test students' understanding of concepts like Von Neumann architecture, instruction formats, memory addressing, condition codes, and subroutine calls.

EULER AND FERMAT THEOREM

This document discusses Fermat's and Euler's theorems regarding prime numbers and their applications in cryptography. It begins by defining prime numbers, prime factorization, and greatest common divisors. It then explains Fermat's theorem that any integer to the power of a prime number minus one is congruent to one modulo that prime number. Next, it defines Euler's totient function and proves Euler's theorem, which generalizes Fermat's theorem. It concludes by providing an example of how these theorems can be applied to encrypt and decrypt messages in a public-key cryptography system.

Modern Block Cipher- Modern Symmetric-Key Cipher

Introduction to Modern Symmetric-Key Ciphers- This lecture will cover only "Modern Block Cipher".
Slide Credit: Maleka Khatun & Mahbubur Rahman
Dept. of CSE, JnU, BD.

Rsa cryptosystem

Cryptography is the practice and study of techniques for conveying information security.
The goal of Cryptography is to allow the intended recipients of the message to receive the message securely.
The most famous algorithm used today is RSA algorithm

Midsquare method- simulation system

This topic based on Mid square method in random number.Actually this is not in random number but in pseudo random number

predicate logic example

John likes all foods, apples and chicken are foods, anything that does not kill someone who eats it is a food, Bill eats peanuts and is still alive so peanuts are food, and Sue eats everything that Bill eats. This document translates statements about people and foods into logical forms using predicates and quantifiers, and then expresses them in conjunctive normal form.

Fuzzy logic - Approximate reasoning

This presentation discusses about the following topics:
Truth values and tables,
Fuzzy propositions,
Formation of rules decomposition of rules,
Aggregation of fuzzy rules,
Fuzzy reasoning‐fuzzy inference systems
Overview of fuzzy expert system‐
Fuzzy decision making.

Cryptography.ppt

This document provides an overview of cryptography. It defines cryptography as the science of securing messages from attacks. It discusses basic cryptography terms like plain text, cipher text, encryption, decryption, and keys. It describes symmetric key cryptography, where the same key is used for encryption and decryption, and asymmetric key cryptography, which uses different public and private keys. It also covers traditional cipher techniques like substitution and transposition ciphers. The document concludes by listing some applications of cryptography like e-commerce, secure data, and access control.

Information and network security 35 the chinese remainder theorem

In number theory, the Chinese remainder theorem states that if one knows the remainders of the Euclidean division of an integer n by several integers, then one can determine uniquely the remainder of the division of n by the product of these integers, under the condition that the divisors are pairwise coprime.

P, NP, NP-Complete, and NP-Hard

P, NP, NP-Complete, and NP-Hard
Reductionism in Algorithms
NP-Completeness and Cooks Theorem
NP-Complete and NP-Hard Problems
Travelling Salesman Problem (TSP)
Travelling Salesman Problem (TSP) - Approximation Algorithms
PRIMES is in P - (A hope for NP problems in P)
Millennium Problems
Conclusions

IP Security

This document provides an overview of IP security (IPSec). It begins by explaining the need for IPSec due to the lack of security in standard Internet protocols. It then covers the basic architecture and components of IPSec, including authentication headers, encapsulating security payloads, and how security associations combine these elements. The document also discusses key management and provides examples of how IPSec can be implemented in transport and tunnel modes. In under 3 sentences, this document provides an introduction to IPSec, outlines its main architectural components, and discusses how it establishes security associations to encrypt and authenticate network traffic.

Multiplexers & Demultiplexers

Multiplexers and demultiplexers allow digital information from multiple sources to be routed through a single line. A multiplexer has multiple data inputs, select lines to choose an input, and a single output. A demultiplexer has a single input, select lines to choose an output, and multiple outputs. Bigger multiplexers and demultiplexers can be built by cascading smaller ones. Multiplexers can implement logic functions by using the select lines as variables and routing the input lines to the output.

Random number generation

Random Number Generation techniques, Pseudo Random Number generation techniques. How Random numbers are generated? Linear Congruential Generator.
My References : https://www.youtube.com/watch?v=fEWigU1dcp8 .
Short Summary : https://www.slideshare.net/VinitDantkale/summary-of-random-number-generation
Used in Information Theory and Coding, Cryptography, Information network and Security, mathematics.

AES-Advanced Encryption Standard

Advanced Encryption Standard. What is AES? Why AES? Cryptography. Working of AES. Attacks on AES. Full working description of AES.

Fuzzy relations

Fuzzy relations, fuzzy graphs, and the extension principle are three important concepts in fuzzy logic. Fuzzy relations generalize classical relations to allow partial membership and describe relationships between objects to varying degrees. Fuzzy graphs describe functional mappings between input and output linguistic variables. The extension principle provides a procedure to extend functions defined on crisp domains to fuzzy domains by mapping fuzzy sets through functions. These concepts form the foundation of fuzzy rules and fuzzy arithmetic.

Realibity design

The document discusses reliability design problems where multiple devices are connected in series to increase overall system reliability. It describes how connecting more instances of a device in parallel at each stage increases the stage reliability. The goal is to determine the optimal number of device instances that maximizes reliability while minimizing cost, given reliability and cost values for each type of device. Sample calculations are shown to illustrate calculating reliability at each stage and finding the solution that provides the highest reliability within the total cost budget.

Generate and test random numbers

Generate and test random numbers

Big o notation

Big o notation

Two Pseudo-random Number Generators, an Overview

Two Pseudo-random Number Generators, an Overview

Back propagation

Back propagation

COA-QUESTION-BANK.pdf

COA-QUESTION-BANK.pdf

EULER AND FERMAT THEOREM

EULER AND FERMAT THEOREM

Modern Block Cipher- Modern Symmetric-Key Cipher

Modern Block Cipher- Modern Symmetric-Key Cipher

Rsa cryptosystem

Rsa cryptosystem

Midsquare method- simulation system

Midsquare method- simulation system

predicate logic example

predicate logic example

Fuzzy logic - Approximate reasoning

Fuzzy logic - Approximate reasoning

Cryptography.ppt

Cryptography.ppt

Information and network security 35 the chinese remainder theorem

Information and network security 35 the chinese remainder theorem

P, NP, NP-Complete, and NP-Hard

P, NP, NP-Complete, and NP-Hard

IP Security

IP Security

Multiplexers & Demultiplexers

Multiplexers & Demultiplexers

Random number generation

Random number generation

AES-Advanced Encryption Standard

AES-Advanced Encryption Standard

Fuzzy relations

Fuzzy relations

Realibity design

Realibity design

Pseudo Random Number Generators

This presentation on Pseudo Random Number Generator enlists the different generators, their mechanisms and the various applications of random numbers and pseudo random numbers in different arenas.

Random Number Generation

This document discusses tests for random number generation, including the autocorrelation test, gap test, and poker test. The autocorrelation test examines dependence between numbers in a sequence. The gap test analyzes the length of gaps between numbers that fall within a given range. The poker test categorizes groups of five consecutive numbers based on arrangements like pairs, three of a kind, etc. and applies a chi-squared test to assess randomness.

Parallel Random Generator - GDC 2015

Generating random numbers in a highly parallel program is surprising non-trivial. A lot of good generators have lots of state and is purely serial. Simple generators like LCG can leapfrog ahead but of limited quality and depends on #cores. We want our code to be independent of the degree of parallelism.

Random Number Generators

An overview of the history of Random Numbers and Random Number Generators (RNGs), followed by a brief description of two specific generators (Linear Congruential and Mersenne Twister). Finally some speculations about how these generators might be improved by incorporating random seeds from physical processes.

Pseudorandom number generators powerpoint

This document summarizes and tests four different pseudorandom number generators. Generator 1, which uses modular exponentiation, produces well-distributed numbers and differences but is too computationally intensive. Generator 2, which uses a sine wave function, generates numbers that are clustered on the sides and has differences centered around 0. Generator 3, which uses exponential functions, has near-perfect number distribution but a limited difference range of two values. Generator 4, based on logarithms, fails to produce a consistent distribution and has differences that converge to a single value. In conclusion, creating effective pseudorandom number generators is very challenging.

Pseudo Random Bit Sequence Generator

This document describes the design and implementation of a PRBS (pseudorandom bit sequence) generator module using a linear feedback shift register (LFSR). It includes the theoretical background of LFSRs, a 4-bit example, hardware implementation on a breadboard and printed circuit board, and results showing the output sequences for different feedback configurations. The generator can be extended to output any desired 8-bit sequence using a parallel-to-serial converter. Maximum randomness was achieved with feedback from the 1st and 2nd shift registers.

Random Number Generation

The document contains solutions to 3 problems involving generating random numbers using different linear congruential methods. The first problem uses the linear congruential method to generate 3 two-digit random integers: 63, 51, and 55. The second problem uses the multiplicative congruential method to generate 4 three-digit random integers: 333, 319, 717, and 831. The third problem uses the mixed congruential method to generate 3 two-digit random numbers: 88, 45, and 44.

Random Number Generator

This document describes two random number generation algorithms:
1. The mid-square method, which squares a seed number and takes the middle digits as the next number.
2. The modified mod-square method, which squares the seed, sums the removed higher and lower order digits to the middle digits, and squares that number to generate the next random number.
The document provides examples of both methods and compares their statistical test results to analyze the randomness of the generated numbers.

omp-and-k-svd - Gdc2013

This document summarizes orthogonal matching pursuit (OMP) and K-SVD, which are algorithms for sparse encoding of signals using dictionaries. OMP is a greedy algorithm that selects atoms from an overcomplete dictionary to sparsely represent a signal. It uses an orthogonal projection to the residual to ensure selected atoms are not reselected. K-SVD learns an optimized dictionary for sparse encoding by iteratively sparse encoding training data and updating dictionary atoms to minimize representation error.

Dictionary Learning in Games - GDC 2014

I gave a brief introduction on apply dictionary learning to the problem of compressing skinning in a gpu friendly way.

Uniform and non-uniform pseudo random numbers generators for high dimensional...

This document outlines various topics related to pseudo-random number generators (PRNGs). It begins by discussing uniform PRNGs and the goal of approximating independent and uniformly distributed random variables. It then discusses linear congruential generators and multiplicative congruential generators as examples of uniform PRNGs. It notes some weaknesses of these generators, such as short periods and poor distribution in high dimensions. Finally, it briefly discusses statistical tests that can be used to validate PRNGs, such as the gap test and spectral test.

Random number generation (in C++) – past, present and potential future

In numerical calculation, Monte Carlo simulations plays very important role. The Monte Carlo simulations are solid numerical equations sailing on thousands of random numbers and converges to a result. This presentation briefs about random number generations.

Simulation and Modeling

Simulation is used to create models that represent real world systems and allow experimenting with different strategies without impacting the actual system. Models simplify real systems for analysis while maintaining key behaviors and results. Successful simulation models are easy to understand, represent the system accurately, produce fast results, and allow control and updating. Simulators are used when real experimentation is unsafe, too expensive, or when systems are still in development. Common uses of simulation include modeling systems in fields like military, education, healthcare, and engineering.

Simulation Techniques

The document discusses using simulation to model queuing problems with random numbers. It describes queuing systems as having arrivals, a waiting line, service, and departure components. A single queue-single service point queuing structure is examined, with first-come, first-served queue discipline and random inter-arrival and service times. An example problem simulates 10 customer arrivals at a retail store using random numbers to estimate average waiting time and server idle time percentage. The solution shows calculating arrival and service time probabilities, simulating customer service, and finding total 4 minutes of waiting time and 12 minutes of idle time over 53 minutes.

SIMULATION

This document discusses simulation modeling and its applications. It begins with definitions of simulation as operating a model of a system over time to study its behavior. Simulation is used to evaluate system performance under different configurations before implementation. The key advantages are exploring "what if" scenarios without disrupting real systems and testing new designs. Common applications include manufacturing, construction, military, logistics and transportation. The document outlines the steps in a simulation study and discusses when simulation is appropriate versus not. It concludes with references on modeling and simulation.

Chp. 2 simulation examples

This document discusses simulation examples and simulation of queuing systems. It provides three key steps to carry out a simulation: 1) determine input characteristics, 2) construct a simulation table to track the system state over time, and 3) initialize and run the simulation. It then gives an example of simulating a single-channel queue, including generating random interarrival and service times from distributions and constructing a simulation table. Key performance measures like average wait time and server idle time are calculated from the table.

Simulation Powerpoint- Lecture Notes

The information in this slide is very useful for me to do the assignment regarding the simulation in which we have to report together with the presentation...

Pseudo Random Number Generators

Pseudo Random Number Generators

Random Number Generation

Random Number Generation

Parallel Random Generator - GDC 2015

Parallel Random Generator - GDC 2015

Random Number Generators

Random Number Generators

Pseudorandom number generators powerpoint

Pseudorandom number generators powerpoint

Pseudo Random Bit Sequence Generator

Pseudo Random Bit Sequence Generator

Random Number Generation

Random Number Generation

Random Number Generator

Random Number Generator

omp-and-k-svd - Gdc2013

omp-and-k-svd - Gdc2013

Dictionary Learning in Games - GDC 2014

Dictionary Learning in Games - GDC 2014

Uniform and non-uniform pseudo random numbers generators for high dimensional...

Uniform and non-uniform pseudo random numbers generators for high dimensional...

Random number generation (in C++) – past, present and potential future

Random number generation (in C++) – past, present and potential future

Simulation and Modeling

Simulation and Modeling

Simulation Techniques

Simulation Techniques

SIMULATION

SIMULATION

Chp. 2 simulation examples

Chp. 2 simulation examples

Simulation Powerpoint- Lecture Notes

Simulation Powerpoint- Lecture Notes

DSP Third Class.ppsx

This document provides an overview of digital signal processing (DSP). It discusses:
- Continuous and discrete-time signals, with continuous signals defined for all time values and discrete signals defined only at certain time instances.
- How continuous signals are converted to discrete signals through sampling, such as by an analog-to-digital converter, so they can be processed digitally.
- Examples of physical systems that can be modeled as continuous-time systems, like electrical circuits, and the equations used to model elements like resistors, inductors, and capacitors.
- Key components in DSP systems like sample and hold circuits, which create samples of an input signal and hold them for processing.

Multidimensional Approaches for Noise Cancellation of ECG signal

Multidimensional Approaches for Noise Cancellation of ECG signalSikkim Manipal Institute Of Technology

In many situations, the Electrocardiogram (ECG) is
recorded during ambulatory or strenuous conditions such that the
signal is corrupted by different types of noise, sometimes
originating from another physiological process of the body. Hence,
noise removal is an important aspect of signal processing. Here five
different filters i.e. median, Low Pass Butter worth, FIR, Weighted
Moving Average and Stationary Wavelet Transform (SWT) with
their filtering effect on noisy ECG are presented. Comparative
analyses among these filtering techniques are described and
statically results are evaluated.Computation of Electromagnetic Fields Scattered from Dielectric Objects of Un...

Computation of Electromagnetic Fields Scattered from Dielectric Objects of Un...Alexander Litvinenko

1) The document describes a method called Multilevel Monte Carlo (MLMC) to efficiently compute electromagnetic fields scattered from dielectric objects of uncertain shapes. MLMC balances statistical errors from random sampling and numerical errors from geometry discretization to reduce computational time.
2) A surface integral equation solver is used to model scattering from dielectric objects. Random geometries are generated by perturbing surfaces with random fields defined by spherical harmonics.
3) MLMC is shown to estimate scattering cross sections accurately while requiring fewer overall computations compared to traditional Monte Carlo methods. This is achieved by optimally allocating samples across discretization levels.Quantum computing

A brief description on the basic working of Quantum computers ,it's applications and future prospects.

Teknik Simulasi

This document discusses properties of pseudo-random numbers and methods for generating random numbers computationally. It covers:
- Properties of pseudo-random numbers including being continuous between 0 and 1 and uniformly distributed.
- Common methods for generating pseudo-random numbers including table lookup, linear congruential generators (LCG), and feedback shift registers.
- Desirable properties for random number generators including being fast, requiring little memory, having a long cycle or period, and producing numbers that are close to uniform and independent.

Mobile_Lec6

1. The document provides an overview of digital modulation for mobile communication systems. It discusses key concepts like sampling, bandwidth, modulation theory, and digital modulation schemes.
2. The document covers sampling theory including the sampling theorem and concepts like energy, power, power spectral density, and pulse shaping filters. It explains how sampling works by modeling the sampling function as a train of Dirac impulse functions.
3. Key learning outcomes are listed and cover understanding principles of sampling and digital modulation, as well as modulation schemes like BPSK and QPSK. Concepts of bit error probability, eye diagrams, and spectrum analyzers are also introduced.

Lecture 3 (ADSP).pptx

The document summarizes key concepts about even and odd signals from a lecture on signals and systems:
1) Even signals have the property that x(-t)=x(t), while odd signals have the property that x(-t)=-x(t). Any signal can be expressed as the sum of an even and an odd component.
2) Discrete time linear and time-invariant (LTI) systems can be characterized by their impulse response h[n]. The output of an LTI system is the convolution of the input signal with the impulse response.
3) Convolution is a mathematical operation that mixes two signals together. It has applications in areas like edge detection. The output of an LTI system

arduino

This document provides an introduction to line follower competitions using Arduino microcontrollers. It discusses what a microcontroller and Arduino are, different types of Arduino boards like UNO and sensors like light and infrared sensors. It describes the basic coding structure in Arduino including data types, functions, control statements, loop statements and common functions. It also outlines a workshop on using these concepts to control a DC motor's direction for set time periods.

State estimation

This document discusses state estimation in power systems. It begins by defining state estimation as assigning values to unknown system state variables based on measurements according to some criteria. It then discusses that the most commonly used criterion is the weighted least squares method. It provides an example of using measurements to estimate voltage angles as state variables and calculate other power flows. Finally, it discusses the weighted least squares state estimation technique in detail including developing the measurement function matrix and solving the weighted least squares optimization.

Introduction to arduino

This document provides an introduction to line follower competitions using Arduino microcontrollers. It discusses what a microcontroller is and types of Arduino boards. The coding structure is explained, covering data types, functions, control statements and loop statements. A workshop section describes how to control a DC motor using Arduino to rotate clockwise for 2 seconds and counter-clockwise for 5 seconds in an infinite loop.

No Cloning Theorem with essential Mathematics and Physics

This is the first project report at my University. This report describes No Cloning Theorem, an introductory topic of Quantum Computation and Quantum Information Theory. The report also covers the necessary mathematics and physics.

introductiontoarduino-130219180141-phpapp01.pdf

This document provides an introduction to line follower competitions using Arduino microcontrollers. It discusses what a microcontroller and Arduino are, different types of Arduino boards like UNO and sensors like light and infrared sensors. It describes the basic coding structure in Arduino including data types, functions, control statements like if/else and loops. It also outlines a workshop on using these concepts to control a DC motor's direction for set time periods.

Tools for computational finance

1) The document discusses generating random numbers with specified distributions for use in simulations and finance modeling.
2) It describes how linear congruential generators are commonly used to generate uniformly distributed random numbers by calculating values modulo a large integer.
3) Quality requirements for random number generators include having a long period before repeating, passing statistical tests for the desired distribution, and being uniformly distributed in multi-dimensional spaces without clustering along hyperplanes.

U4301106110

International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.

quantumComputers.ppt

Quantum computing detailed description.
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quantumComputers.ppt

Quantum computing uses quantum bits (qubits) that can exist in superpositions of states and become entangled. Shor's algorithm shows how a quantum computer could factor large numbers much faster than a classical computer by using quantum parallelism and the quantum Fourier transform. It works by first preparing the input in a superposition, applying a modular exponentiation operation, measuring the output qubit to partially collapse the input, applying a quantum Fourier transform to reveal periodicity, and using the period to determine the factors of the original number. This algorithm demonstrates the power of quantum computing for certain problems.

quantumComputers.ppt

Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.

quantumComputers.ppt

Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.

quantumComputers.ppt

Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.

quantumComputers.ppt

Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.

DSP Third Class.ppsx

DSP Third Class.ppsx

Multidimensional Approaches for Noise Cancellation of ECG signal

Multidimensional Approaches for Noise Cancellation of ECG signal

Computation of Electromagnetic Fields Scattered from Dielectric Objects of Un...

Computation of Electromagnetic Fields Scattered from Dielectric Objects of Un...

Quantum computing

Quantum computing

Teknik Simulasi

Teknik Simulasi

Mobile_Lec6

Mobile_Lec6

Lecture 3 (ADSP).pptx

Lecture 3 (ADSP).pptx

arduino

arduino

State estimation

State estimation

Introduction to arduino

Introduction to arduino

No Cloning Theorem with essential Mathematics and Physics

No Cloning Theorem with essential Mathematics and Physics

introductiontoarduino-130219180141-phpapp01.pdf

introductiontoarduino-130219180141-phpapp01.pdf

Tools for computational finance

Tools for computational finance

U4301106110

U4301106110

quantumComputers.ppt

quantumComputers.ppt

quantumComputers.ppt

quantumComputers.ppt

quantumComputers.ppt

quantumComputers.ppt

quantumComputers.ppt

quantumComputers.ppt

quantumComputers.ppt

quantumComputers.ppt

quantumComputers.ppt

quantumComputers.ppt

EFFLUENT TREATMENT PLANT For PHARMA INDUSTRY

For Environment Protection against harmful emisison and aquatic life, It is necessary to implement the standard in order to control the Chemcial Oxygen demand, Biological oxygen demand, Total suspended solid, Total dissolved solid, Oil & Greece Etc.

Electrical Safety Audit

This document discusses safety audits and compliance with NFPA 70E standards. It notes that safety audits ensure organizations follow proper safety regulations to avoid injuries, damage, and costs. NFPA 70E specifically addresses electrical safety in workplaces and complying with it helps save lives, reduce liability, and prevent downtime and revenue losses. The document provides details on NFPA 70E's definitions, requirements for personal protective equipment, and establishing electrically safe work environments. It also gives examples of other NFPA standards related to fire safety and prevention.

Asset Integrity _ Asset Managment ISO 55001 Certification

The document discusses asset integrity management and maintenance strategies to achieve ISO 55001 certification for electrical asset fleets. It outlines condition-based testing methods to increase asset reliability and reduce failures. Maintaining assets based on their condition through techniques like predictive maintenance can extend their useful life. Asset health monitoring and life cycle analysis can inform decision making around repair and replacement. The goal is to ensure reliability, availability and maintainability of assets over the long term.

EMS ISO 50001

The document outlines the road map for ISO 50001 energy management system audit certification. It discusses establishing an energy baseline and measuring energy performance indicators. The presentation covers analyzing energy consumption trends, transformer efficiency, load factors, and harmonics using standards like IEEE 519. Significant energy uses are identified and energy savings projects discussed, including work done in Pakistan on efficiency of assets like HVAC and compressors. Monitoring and control dashboards are presented as tools to reduce maximum demand and power quality issues like power factor to minimize downtime.

Electrical & Energy Audit 22 Nov.pptx

Electrical and Energy Audit performs in order to apply safety procedure to electrical distribution network along with energy saving protocol in order to reduce the carbon foot print. Energy efficiency solution is required to control the consumption of electricity thus reduce the dependence on fossil fuel usage and economy import policy f fossil fuel.

Electrical & Energy Audit (2).pptx

The document summarizes an electrical and energy audit conducted by F&M Private Limited at Bank Islamic. The audit included a visual inspection of electrical panels and distribution boards, earth testing, thermography to detect abnormal temperatures, analysis of electrical drawings and load distribution, and an analysis of lighting, computer, and AC systems to identify savings opportunities. Key recommendations included rectifying issues with panels and distribution boards, addressing unsafe earth readings, balancing overloaded circuits, improving unbalanced three-phase loading, reducing unused computer and AC runtime, and replacing non-inverter AC units. Total estimated monthly savings identified were 336,815 Pakistani Rupees.

Electrical FM Compiled.pdf

This document provides information on the electrical department of F&M Pvt. Ltd., including a list of engineers and their roles. It then discusses various services offered by the department, such as electrical audits, safety audits, load analysis, and projects. Electrical audits are described as examining the electrical parameters and efficiency of an energy system to identify issues and optimize performance. Safety audits ensure compliance with standards to improve safety and reduce risks. The department uses various tools and follows international standards in conducting its services.

Energy Audit..pptx

An energy audit was performed that found significant power losses occurring in the transformers due to underloading and high current harmonics in the system from VFD usage. Specifically:
- Transformers were operating at only 30-20% capacity, resulting in poor efficiency and higher copper and core losses.
- Current harmonics were measured at 10-20%, above the acceptable limit, increasing transformer losses.
- These losses were unaccounted for and led to discrepancies between energy meter readings.
Recommendations included balancing the transformer load, installing harmonic filters, and testing the transformers to check their health due to long-term underloading.

Electrical Safety Audit - FM Pvt ltd.pptx

An electrical safety audit was conducted for F&M Pvt. Ltd. to ensure compliance with international safety standards such as NFPA. Safety audits evaluate processes, equipment, and the work environment to assess safety. Without regular audits, organizations risk injuries, lost productivity, legal issues, and costs. F&M follows NFPA standards which provide detailed and practical guidance around electrical safety, fire safety systems, workplace safety, and hazard identification. An analysis was performed to calculate incident energy and appropriate personal protective equipment. The audit included visual inspections, energy control procedures, and assessing compliance to minimize fire hazards and protect the area.

Electrical Audit (Bill's Inc ).pptx

The document summarizes an electrical audit conducted by F&M Private Limited at a client's site. The audit included a visual inspection of electrical panels and distribution boards, earth testing, thermography to detect overheating equipment, analysis of electrical drawings, and examining load management. Several issues were observed, such as panels lacking identification markings and earthing not meeting standards. Recommendations included rectifying earthing problems, shifting loads to balance three-phase load, and changing cables and circuit breakers as needed. The conclusion states the audit helped evaluate the existing electrical system and identify points for improvement.

Neural Network to identify fault in distribution network of smart grid

The document summarizes a paper presented at the 4th International Electrical Engineering Conference titled "Intelligent Control System to Identify Fault in Distribution Network of Smart Grid through Neural Network". The paper proposes using a neural network model with inputs like voltage, current, reactive power, etc. to identify different types of electric faults (SLG, LL, DLG, 3-phase) in a distribution network. The neural network was able to accurately identify fault types and improve reliability metrics like SAIDI and SAIFI. The model provides a method to efficiently detect, classify, and locate faults for utility crews in a smart grid distribution network.

ELECTRIC VEHICLE

The document summarizes a conference paper presented at the 4th International Electrical Engineering Conference (IEEC 2019) on electric vehicles (EVs) as a sustainable policy recommendation for zero greenhouse gas emissions in Pakistan. The paper discusses EVs and renewable energy sources in Pakistan, proposes several policies to promote EVs, and concludes that Pakistan should promote an EV culture and install more charging stations.

Energy storage Technologies

This document discusses a new paradigm for energy policies in Turkey and Pakistan using renewable energy technologies and energy storage. It presents information on the problem of unreliable renewable energy supply due to environmental conditions, and the high cost of energy storage technologies. The objective is to discuss energy storage options that can integrate with renewable energy sources to provide reliable power. Energy storage demand is expected to significantly increase by 2030 and can help reduce CO2 emissions. The document outlines various energy storage technologies and provides data on renewable energy usage and policies in Turkey and Pakistan. It recommends policy changes to promote investment in renewable technologies and energy storage through tax exemptions and subsidies.

Asset management

This document discusses challenges in managing aging transmission and distribution assets for electric utilities. It outlines how utilities previously relied on routine-based maintenance schedules rather than advanced analytics. The document proposes building an analytical asset management approach using real-time performance data and predictive models to measure asset health and criticality. This would help utilities prevent failures, target high-priority assets, and lower costs through an optimized maintenance and replacement plan. A case study example on power transformer fleet management is also provided.

Probability Estimation for the Fault Detection and Isolation of PMU-Based Tra...

For fault detection in the transmission line and isolate the faulty transmission line with in the limited period, phasor measurement unit is installed at the buses of smart grid in order to communicate with other PMU’s (Phasor Measurement Unit). For its reliability analysis, formal verification is necessary in order to investigate its accuracy, stability and efficiency when fault is occurred on the network. Through probabilistic analysis of PMU based transmission network via PRISM model checker tool, we can estimate the failure probability of network and take a corrective action and maintenance so that, faulty component can be replaced in advance to avoid the complete failure of system

Formal verification of FDIR

This thesis develops probabilistic models to formally verify a fault detection and service restoration system in a smart grid using a probabilistic model checker. It develops discrete time Markov chain models for fault detection, isolation and supply restoration for a Tianjin electric power network with 3 and 6 load switches. It also develops a communication protocol model. Temporal logic properties are defined and the models are verified. Results show the effect of wireless communication on failure probabilities compared to an ideal network.

Reduction in Current leakage in CMOS VLSI Circuits

This document presents techniques for reducing leakage current in CMOS VLSI circuits by controlling input vectors. It discusses sources of leakage current like junction leakage and subthreshold leakage. An algorithm is described for finding minimum leakage vectors using Boolean satisfiability. Experimental results show energy savings from up to 30% in combinational circuits and up to 50% in sequential circuits by applying minimum leakage vectors during idle periods and using scan chains to control inputs. The techniques allow circuits to spend less time in idle modes with minimum leakage.

SMART GRID

The document discusses smart grids and existing power grids. It defines a smart grid as using digital technology to improve reliability, security and efficiency of the electric system by enabling two-way communication between utilities and customers. This allows customers to participate through options like demand response and helps accommodate different generation sources. The document contrasts key aspects of smart grids with existing grids and outlines drivers for the transition like rising energy costs and climate change goals.

Insulation testing of power cable

This document discusses voltage testing and partial discharge measurement techniques for power cable accessories. It provides:
1) An overview of the objective to compare cable testing best practices and determine cable defects using partial discharge methods.
2) A description of an ACRF test system used, including its components like an HV reactor, control unit, and voltage divider.
3) Details on partial discharge measurement methods like using high frequency current transformers and coupling capacitors to detect discharges in cables.
4) The conclusion that resonant testing between 20-300Hz along with partial discharge detection reduces risks from cable systems after installation by locating faults.

Monitoring System

The document describes a monitoring system for a Saudi plastic factory. It summarizes:
1) The system monitors 70 computers connected to a monitoring server and SPF server.
2) It monitors sensors in 5 buildings that measure things like temperature, pressure, humidity, and transformer outputs.
3) The monitoring screens display real-time sensor readings from each building in an easy-to-read format.

EFFLUENT TREATMENT PLANT For PHARMA INDUSTRY

EFFLUENT TREATMENT PLANT For PHARMA INDUSTRY

Electrical Safety Audit

Electrical Safety Audit

Asset Integrity _ Asset Managment ISO 55001 Certification

Asset Integrity _ Asset Managment ISO 55001 Certification

EMS ISO 50001

EMS ISO 50001

Electrical & Energy Audit 22 Nov.pptx

Electrical & Energy Audit 22 Nov.pptx

Electrical & Energy Audit (2).pptx

Electrical & Energy Audit (2).pptx

Electrical FM Compiled.pdf

Electrical FM Compiled.pdf

Energy Audit..pptx

Energy Audit..pptx

Electrical Safety Audit - FM Pvt ltd.pptx

Electrical Safety Audit - FM Pvt ltd.pptx

Electrical Audit (Bill's Inc ).pptx

Electrical Audit (Bill's Inc ).pptx

Neural Network to identify fault in distribution network of smart grid

Neural Network to identify fault in distribution network of smart grid

ELECTRIC VEHICLE

ELECTRIC VEHICLE

Energy storage Technologies

Energy storage Technologies

Asset management

Asset management

Probability Estimation for the Fault Detection and Isolation of PMU-Based Tra...

Probability Estimation for the Fault Detection and Isolation of PMU-Based Tra...

Formal verification of FDIR

Formal verification of FDIR

Reduction in Current leakage in CMOS VLSI Circuits

Reduction in Current leakage in CMOS VLSI Circuits

SMART GRID

SMART GRID

Insulation testing of power cable

Insulation testing of power cable

Monitoring System

Monitoring System

- 1. Random- number generatorS & reVIEW ON Intel rng Presented by syed atif chishti IE 508 – SYSTEM SIMULATION & MODELING
- 2. overview Topics to be covered 1. Introduction 2.Linear Congruential Generators 3. Composite Generators 4.Testing Random-Number Generator 5. Intel Random Number Generator
- 3. Introduction A simulation of process in which random Component requires A method of generating Numbers that are random Methods of generating random variates from uniform distribution On the interval [0 1] denoted as U(0,1) Random variates generated from U(0,1) distribution will be Called as random numbers.
- 4. Introduction Casting lots, throwing dice, dealing out cards Electronic random number indicator equipment(ERNIE) Was used by British GPO to pick winners in lottery .
- 6. Properties of Arithmetic rng It is distributed uniformly on U(0,1).No correlation. Fast and avoid the need of storage. Stream reproduce second times. Produce separate streams easily Generator to be portable i.e produce the number up to Machine accuracy. .
- 7. Linear congruential generators It can be defined by the recursive formula Z=(az+c)(mod m) M= modulus A= multiplier C= increment Z= seed or starting value U= Z/m .
- 8. Objection on lcg Pseudo random number generator as Z is completely Determined by m,a,c,z parameter. U’s can take only the rational values 0,1/m,2/m,…,(m-1)/m
- 9. example M=16, a=5,c=3 & Z=7.
- 10. Mixed generator Conditions to get full period of a generator. Only positive integer that divides both m and c is 1. If q is a prime number that divides m, then q divides a-1. If 4 divides m,then 4 divides a-1. For C>0 ,condition 1 is possible and we get full period. M=2expb, since b is the bits(binary digits) to store the data.
- 11. Multiplicative generators C is not needed. Don’t have full period, condition 1 not satisfied. M=2expb-2, only one fourth of integers 0-m-1 can be obtain If a= 2exp l + J then it is called RANDU. Prime modulus multiplicative LCG(PMMLCG) M is prime and the period is m-1 and if a is primitive Element modulo m i.e smallest integer l for which al-1/m Gives l=m-1.
- 12. Alternatives types to LCG It can be expressed as Z=g(Zi-1,Zi-2,…)(mod m) = a’z^2+az+c Similar to midsquare method Better statistical properties Period of QCG=m Quadratic Congruential Generator
- 13. Alternatives types to LCG Two or more separate generators and combine them to Generate the final random numbers. Second LCG to shuffle the output from the first LCG Initially a vector V=(v1,v2,,,,,vk) is filled sequentially with the First KU from the first LCG where k=128 and second LCG is Used to generate a random integer I distributed uniformly. V1 returns as first U(0,1) variate ,first LCG replaces its Ith Location in V with the next U and second LCG randomly Chooses the random number from this updated V COMPOSITE GENERATORS
- 14. Alternatives types to LCG These generators are called cryptographic ,operate directly On bits to form random numbers. Bi=(c1bi-1+c2bi-2+….+cqbi-q)(mod 2) c1=c2=cq-1= 0 or 1 Cq=1 In most application c =0 thus it become Bi=(bi-r+bi-q)(mod2) Or Bi=[ 0 if bi-r = bi-q , 1 if bi-r not= bi-q] FEEDBACK SHIFT REGISTER GENERATORS
- 15. Testing Random-Number Generators Empirical test are the kinds of statistical tests and are based on U’s Produced by generator. Theoretical test use numerical parameters of a generator To assess it globally without actually generating U’s EMPIRICAL TESTS VS THEORETICAL TEST
- 16. EMPIRICAL TESTS The direct way to test any generator is to generate some U’s and then statistically examined to see the result to IID U(0,1) Test 1 Chi – Square method: Check whether U’s appear to be uniformly distributed b/w 0 & 1 Divide the [0,1] into k sub intervals of equal length & Generate U1,U2,U3….Un
- 17. EMPIRICAL TESTS Test 2 Serial Test method: Generalization of Chi-square test to higher dimension. If the U’s are really from IID U(0,1) random variates, the overlap D –tuples is U1=(U1,U2,…,Ud), U2=(Ud+1,Ud+2,…,U2d) ….. Should be IID random vectors distributed uniformly on the d Dimensional unit hypercube [0,1]d. Divide [0,1] into k subintervals of equal size and generate U1, U2,….Un.
- 18. EMPIRICAL TESTS Test 3 runs (runs –up) test: Examine the Ui sequence for unbroken sequence of maximal Length with in which the Ui’s increase monotonically Such Subsequence is called a run up. Let U1,U2…U10 : 0.86,0.11,0.23,0.03,0.13,0.06,0.55,0.64,0.87 0.10. the sequence starts with run up of length 1(0.86) followed By run up of length 2(0.11,0.23) then run up of length 2(0.03,0.13) Then a run up of length 4(0.06,0.55,0.64,0.87) and finally run up Of length 1(0.10) R=1/n ∑∑aij(ri-nbi)(rj-nbj)
- 19. EMPIRICAL TESTS Test 4 Discernible correlation: Estimate the generated Ui’s correlation at lags j=1,2…l. It is defined as Pj= Cj/Co Where Cj =COV (Xi,Xi+j)= E(XiXi+J)-E(Xi)E(Xi+j) Covariance between entries in the sequence separated by j.
- 20. THEORETICAL TESTS Best known theoretical test are based on upsetting observation that random numbers fall mainly in the planes. .
- 21. True Random Number Generator Uses a non deterministic source to produce randomness. It measuring unpredictable natural process such as thermal (resistance or shot) noise or nuclear decay. INTEL RANDOM NUMBER GENERATOR
- 22. True Random Number Generator Uses a non deterministic source to produce randomness. It measuring unpredictable natural process such as thermal (resistance or shot) noise or nuclear decay. Through mouse movement ,keys can be generated. INTEL RANDOM NUMBER GENERATOR
- 23. Architecture Analysis Of Intel RNG
- 24. Noise Source: Johnson noise also called thermal noise ,shot noise and Flicker noise are all present in resistor. They have electrically measurable characteristics and are the Result of random electron & material behavior. Intel RNG first samples thermal noise by amplifying the voltage Measured across resistor. Apart from large random component , this measurement are Correlated to electromagnetic radiation,temperature and power Supply fluctuation. Intel RNG reduces the coupled component by subtract the signals sampled from two adjacent resistor.
- 25. Dual Oscillator Architecture : Intel RNG uses a random source that is derived from two free –running oscillator. one is fast and one is slow. Thermal noise source use to modulate the Frequency of slower clock The variable, noise modulated slower clock is used To trigger the measurement of fast clock. Drift between the two clocks thus provides the Source of random binary digits.
- 26. Digital Post Processing : The initial random measurement are processed by hardware Corrector based concept to produce a balanced distribution Of 0 & 1 bits.
- 27. Statistical Evaluation : Intel RNG uses a random source that is derived from two free –running oscillator. one is fast and one is slow. Thermal noise source use to modulate the Frequency of slower clock The variable, noise modulated slower clock is used To trigger the measurement of fast clock. Drift between the two clocks thus provides the Source of random binary digits.
- 28. Intel Software Library Software Architecture
- 30. Thank you