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.NET, ActiveX, and COM
Published in Rick Bitter, Taqi Mohiuddin, Matt Nawrocki, LabVIEW™ Advanced Programming Techniques, 2017
Rick Bitter, Taqi Mohiuddin, Matt Nawrocki
Operating system properties available are the version, build number, and platform. “Platform” indicates which Win32 system is running on the machine. The “Build Number” indicates which particular compile number of the operating system you are running. Actually, this property will not be particularly useful because the build number is not likely to change. Service packs are applied to original operating systems to fix bugs. The version number also indicates which version number of Windows you are currently running.
Enterprise Sustenance
Published in Kirk Hausman, Sustainable Enterprise Architecture, 2011
Patches and hotfixes are released regularly by software vendors to correct small groups of vulnerabilities, while rollups of these small changes are produced as service packs that allow easier update to new systems beyond the sequential application of all minor updates since the base software edition was released. New features may also be introduced in service pack updates, requiring significantly more testing before deployment into an enterprise to ensure that changes do not degrade enterprise service availability.
A Fully Bayesian Inference with Gibbs Sampling for Finite and Infinite Discrete Exponential Mixture Models
Published in Applied Artificial Intelligence, 2022
Xuanbo Su, Nuha Zamzami, Nizar Bouguila
In this section, we aim at comparing the proposed algorithms and their corresponding finite mixture models learned in a deterministic way using EM algorithm in different data clustering applications. The first experiment and second one concentrate on textual data for sentiment analysis and fake news detection. The last one considers images data for distinguishing male and female faces. All experiments were conducted using optimized python code on Inter (R) Core (TM) i7-9750 H processor PC with Windows 10 Enterprise Service Pack 1 operating system with a 16 GB main memory. The results that we will present in the following subsections represent the average over 20 runs of the proposed algorithms. For our proposed algorithm, The empirical assessment of MCMC convergence is delicate, especially in high dimensional spaces. In our experiments we applied the widely used one-long run technique as proposed in Raftery and Lewis (1992).
Solving the next release problem by means of the fuzzy logic inference system with respect to the competitive market
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2020
Hamidreza Alrezaamiri, Ali Ebrahimnejad, Homayun Motameni
In Table 9, four tests are considered with different threshold times. For example, one of the constraints is the 730-day time limit for the next release. This dataset can be a real example of large projects such as the introduction of the next service pack of an operating system. In these tests, the proposed algorithm has had better choices than the genetic one. For example, within the 730-day time limit, the proposed algorithm with the lom defuzzifier could choose a subset of requirements which could yield a satisfaction rate equal to 2256 in 723 days at a 726-unit cost, while the genetic algorithm yields a lower satisfaction rate than the proposed one in 728 days on average at a cost of about 727 units. Another example of Table 9, within the 1-year time limit, the proposed algorithm with the centroid and bisector defuzzifier could choose a subset of requirements which could yield a satisfaction rate equal to 1389 in 354 days at a 343-unit cost. Whereas the genetic algorithm achieves a satisfaction rate 1252.8, in 356 days on average at a cost of about 353 units.
Order reduction of linear time-invariant systems using Eigen permutation and Jaya algorithm
Published in Engineering Optimization, 2019
Akhilesh K. Gupta, Deepak Kumar, Paulson Samuel
In this article, ISE is considered as a fitness function which is defined as the integral of the squared error between the step responses of the original and reduced models over the interval [0, ∞], which is represented as However, the proposed approach selects [0, ] as an interval for the reduction problem to minimize the approximation error, where is the settling time. The computational resources used for implementation of the proposed approach are MATLAB® version 8.1.0.604 (R2013a) on the operating system Microsoft Windows 7 version 6.1 (Build 7601: Service Pack 1). The primary objective of the proposed work is to obtain an ROM with a close approximation to that of the original system, which is performed by minimization of the fitness function. The unit step response provides information about the stability as well as the dynamic behaviour of the system. Therefore, the minimization of the ISE between the step responses preserves the dynamic behaviour of the original system into the ROM. The other error indices, integral time square error (ITSE), IAE and integral time absolute error (ITAE), are defined as