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ProbWorks: Excel Tools enable a wide range of probabilistic and statistical applications in Excel. Among these applications are: Monte Carlo Simulation Discrete Probability Distributions Optimal Matching Distributions Response Surface Methodologies (RSM) The ProbWorks tools focus on these applications. Each tool has its own unique features that can be used to solve different problems. The software also comes with a full set of demonstrations that are included with the software trial. File Notes: ProbWorks Includes: – Python v3.7.4 32-bit – Python v3.6.5 64-bit – NetBeans IDE v8.2 The new version of the benchtop NIST-F1 frequency generator incorporates a wider range of input frequencies. It can produce test frequencies ranging from 17 MHz to 26.5 GHz. The source of the signals at the test frequencies are sourced from one or more klystrons at the NIST-F1. This module demonstrates the functionality of the toolkit in Python programming language. This module provides a number of utility functions in Python that can be used for numeric computations and math functions. Other modules can be accessed from the toolkit. This module also helps you learn Python programming language. The default configuration of the model provides a three-phase voltage of 330 VAC at the output. This module is used to configure the model for different voltages at the output. The different inputs available are shown in the figure. There are three different modes: Mode 1: Single Signal (Normal) Mode 2: Simultaneous (Twin) Mode 3: Sequential (Awaiting Signal) It is important that the three sources are connected to the inductor first in ascending order of frequency. After successful configuration, simulation will be performed. The figure below shows the three different modes: As the name suggests, it is used to display the frequencies at the input of a signal generator. It can be used to test the frequencies generated by the signal generator. Once the desired frequency is obtained, it can be saved to another file. Joule heaters are simple and efficient electrical heaters. Their heaters may be configured to either heating or cooling effect depending on the polarity of the input current. Switching mode control adds another dimension of efficiency to the use of these heaters. When the voltage applied is high enough to reach the breakdown voltage of Z
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ProbWorks is a suite of advanced sensitivity analysis capabilities in Excel that can help you visualize and manage your spreadsheets. The components of ProbWorks are: ￭ Graphical Display ￭ Monte Carlo Simulation ￭ Sensitivity Analysis ￭ Optimal Matching Distribution Advanced Monte Carlo (AMC) is a Monte Carlo simulation package designed to help users make management decisions based on probabilistic scenarios. ￭ Simulations ￭ Truth Tables ￭ Probability Output Tables ￭ Cost Graphs ￭ Stochastic Optimization Discrete Probability Optimal Matching Distribution (DPOMD) is a discrete probability modeling tool that simulates outcomes in discrete probability scenarios and then outputs the probability of each outcome. This component is also a Monte Carlo simulator. ￭ Simulations ￭ Truth Tables ￭ Probability Output Tables ￭ Cost Graphs ￭ Stochastic Optimization Pareto Sensitivity Analysis (PSA) is a tool that simultaneously solves multiple optimization problems by ranking the relative importance of the input variables. ￭ Simulations ￭ Truth Tables ￭ Response Surface Equation (RSE) Generator The output variable from PSA’s output is a rank ordered sensitivities table that directly guides your next experimental design step. ￭ RSE Generator ￭ Truth Tables ￭ Response Surface Equation (RSE) Generator RSE’s output is a new external “response surface” that expresses the response as a smooth nonlinear function of input variables. ￭ Simulations ￭ Truth Tables ￭ Response Surface Equation (RSE) Generator Example Applications: ￭ Reduce Pumping Frequency in Chemical Compounding Manufacturing ￭ Determine Optimal Sampling Window for Analytical Assay Screening ￭ Prepare for a Monovariate Optimization ￭ Simulate the Relation between the Properties of a Boltzmann Machine and its Fitness ￭ Improve a Protein Structure Prediction Model ￭ Optimize the High-Resolution Cryo-EM Structure of the Human SIRT2 Protein ￭ Evaluate the Effect of Polycaprolactone Content on the Equilibrium Release Profile of Dexamethasone in PVA Dissolution ￭ Provide an Alternate Design for a Biological 2f7fe94e24
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ProbWorks is a useful program that comes with a suite of uncertainty and sensitivity analysis tools for use within Microsoft Excel. Each driver component has a particular benefit or utility to different classes of problems. The individual drivers in the current release are: Advanced Monte Carlo Discrete Probability Optimal Matching Distribution (DPOMD) Pareto Sensitivity Response Surface Equation (RSE) Generator The probabilistic capabilities in the ProbWorks: Excel tools are useful when trying to minimize the computational expense for Monte Carlo simulations, ranking the influence of input variables, and design space approximation through Response Surface Methodologies (RSM). A manual and several examples are included. Requirements: ￭ Excel 2000 ￭ 64 MB of RAM Limitations: ￭ 30-day trial, see description Inventory Management Software for the Retail Industry Decision Focusing is a decision-making and decision-analysis software package for inventory managers in the retail industry. It is generally used in conjunction with PERT and FSM analysis. Decision focusing is a very powerful tool for inventory managers. In addition to the traditional format, the software is available in an electronic format, PC based, or on the Palm V handheld device. This software is available in two versions, a base version and a relational database version. Theory Workflow Assessment and Modeling (WAM) is an Excel-based analysis tool that evaluates various functional workflows and models using probabilistic methods. The power of WAM is in the ability to assess and evaluate complex models, evaluate the dependencies, and evaluate the parametric effects of each individual component. WAM supports four task types including: workflow analysis, object analysis, task analysis, and conditional analysis. Workflow Assessment and Modeling Workflow Assessment and Modeling (WAM) is an Excel-based analysis tool that evaluates various functional workflows and models using probabilistic methods. The power of WAM is in the ability to assess and evaluate complex models, evaluate the dependencies, and evaluate the parametric effects of each individual component. WAM supports four task types including: workflow analysis, object analysis, task analysis, and conditional analysis. State-Of-The-Art Methods For Structural Steel Engineers This is a one page reference covering the basic methodologies of structural design and fabrication. It is a compact self-instructional package that includes an introduction to these areas along with several specific, current examples.
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ProbWorks is a useful program that comes with a suite of uncertainty and sensitivity analysis tools for use within Microsoft Excel. Each driver component has a particular benefit or utility to different classes of problems. The individual drivers in the current release are: Advanced Monte Carlo The “Advanced Monte Carlo” driver allows for the calculation of a continuous range of derivatives of a function using a set of discrete Monte Carlo iterations. This driver is useful when one is interested in the sensitivity of a model with respect to parameters related to time, or if a functional of a function is required. 2. Discrete Probability Optimal Matching Distribution Discrete Probability Optimal Matching Distribution (DPOMD) DPOMD is part of a multidisciplinary software package developed by scientists at Lancaster University and the University of Bergen. The package is freely available and is available under the GNU GPL. The DPOAMD driver does not perform “at once” or all probabilities simultaneously. That is, it can quickly calculate normal distributions for any parameters entered but the calculation does not account for correlations between the parameters. In other words, it does not solve the inverse of a matrix (e.g. the system of equations below can be solved to give b in terms of a, or by using a constant matrix approach, the resulting matrix is linearly dependent). In all cases, the inverse matrix must be solved by hand. When DPOAMD is used to calculate probabilities one must consider the correlations between the inputs. Unlike the standard Monte Carlo method, DPOAMD does not account for correlations between the parameters. In addition, DPOAMD solves for joint probabilities, not just marginal probabilities, that is DPOAMD does not calculate the probability of event “A” and “B” when event “A” occurs first and then event “B”, nor does it calculate the probability of event “A” and “B” when the events are completely unrelated. When calculating correlations in DPOAMD, there are no degrees of freedom for the calculation of the parameters that are fixed. That is, once one has used DPOAMD to calculate P(A), it cannot be used to calculate P(B|A). DPOAMD assumes that the inputs are independent but not identically distributed and the mathematical theory for when this assumption is valid has been discussed extensively elsewhere on this website. When using DPOAMD for uncertainty propagation, it is customary to use a form of orthogonalization of the
Minimum Requirements: OS: Windows 7 Processor: Intel Core i3-2350M 2.3GHz, 2.5GHz or AMD Athlon II X4 635 2.7GHz Memory: 4 GB RAM Graphics: NVIDIA GTX 460 / AMD HD 4850 Hard Drive: 16 GB available hard drive space Recommended Requirements: OS: Windows 8.1 Processor: Intel Core i5-3570K 3.4GHz, 3.8GHz or AMD Phenom