Search results for " Mach"
showing 10 items of 1388 documents
2014
This paper investigates the proficiency of support vector machine (SVM) using datasets generated by Tennessee Eastman process simulation for fault detection. Due to its excellent performance in generalization, the classification performance of SVM is satisfactory. SVM algorithm combined with kernel function has the nonlinear attribute and can better handle the case where samples and attributes are massive. In addition, with forehand optimizing the parameters using the cross-validation technique, SVM can produce high accuracy in fault detection. Therefore, there is no need to deal with original data or refer to other algorithms, making the classification problem simple to handle. In order to…
2020
Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), and Bayesian generalized linear models (Bayesian GLM) machine learning algorithms. For this goal, due to the importance of various geo-environmental and soil properties in the evolution and creation of piping erosion, 18 variables were considered for modeling the piping erosion susceptibility in the Zarandieh watershed. A total of 152 points of piping erosion were recognized in the study area that…
Utilizzo di tecniche di machine learning e previsioni stagionali per la stima dei volumi di invaso
Nanosecond laser surface modification of AISI 304L stainless steel: Influence the beam overlap on pitting corrosion resistance
2014
Abstract Surface modifications of AISI 304L stainless steel by laser surface melting (LSM) were investigated using a nanosecond pulsed laser-fibre doped by ytterbium at different overlaps. The objective was to study the change in the corrosion properties induced by the treatment of the outer-surface of the stainless steel without modification of the bulk material. Different analytical techniques such as scanning electron microscopy (SEM), X-ray diffraction (XRD), and glow discharge optical emission spectrometry (GDOES) were used to characterize the laser-melted surface. The corrosion resistance was evaluated in a chloride solution at room temperature by electrochemical tests. The results sh…
On the role of internationalization of firm-level corporate governance: The case of audit committees
2022
Research Question/IssueMotivated by the agency theory and the findings of linguistic studies, we analyze the association between the internationalization of a firm's audit committee and its corporate governance.Research Findings/InsightsBased on data from 2159 publicly traded European firms from 15 countries for the period 2000–2018, we find that firms with foreign directors on their audit committees are associated with lower financial reporting quality. The association is mitigated by stronger country-level investor protection and a higher similarity among intra-committee languages. We further find that foreign directors on the audit committee are related to stock prices being less informa…
Achieving Intelligent Traffic-aware Consolidation of Virtual Machines in a Data Center Using Learning Automata
2016
Cloud Computing (CC) is becoming increasingly pertinent and popular. A natural consequence of this is that many modern-day data centers experience very high internal traffic within the data centers themselves. The VMs with high mutual traffic often end up being far apart in the data center network, forcing them to communicate over unnecessarily long distances. The consequent traffic bottlenecks negatively affect both the performance of the application and the network in its entirety, posing nontrivial challenges for the administrators of these cloudbased data centers. The problem can, quite naturally, be compartmentalized into two phases which follow each other. First of all, the VMs are co…
Semisupervised nonlinear feature extraction for image classification
2012
Feature extraction is of paramount importance for an accurate classification of remote sensing images. Techniques based on data transformations are widely used in this context. However, linear feature extraction algorithms, such as the principal component analysis and partial least squares, can address this problem in a suboptimal way because the data relations are often nonlinear. Kernel methods may alleviate this problem only when the structure of the data manifold is properly captured. However, this is difficult to achieve when small-size training sets are available. In these cases, exploiting the information contained in unlabeled samples together with the available training data can si…
Parallel Algorithms for Listing Well-Formed Parentheses Strings
1998
We present two cost-optimal parallel algorithms generating the set of all well-formed parentheses strings of length 2n with constant delay for each generated string. In our first algorithm we generate in lexicographic order well-formed parentheses strings represented by bitstrings, and in the second one we use the representation by weight sequences. In both cases the computational model is based on an architecture CREW PRAM, where each processor performs the same algorithm simultaneously on a different set of data. Different processors can access the shared memory at the same time to read different data in the same or different memory locations, but no two processors are allowed to write i…
GRID STABILITY IMPROVEMENT BY RES-BASED GENERATORS AND BATTERY ENERGY STORAGE SYSTEMS IN SMALL ISLANDS
2021
The integration of Renewable Energy Sources (RES) with power electronics interface to the grid, without the back-up of rotating inertia, endangers frequency stability. This issue becomes particularly critical in isolated power systems, like those of small islands not supplied by the main grid, in the case of high shares of production from unpredictable renewables such as photovoltaic and wind sources. Consequently, to preserve the security and the reliability of these systems, it is necessary to adopt new frequency adjustments mechanisms. In this context, the thesis investigates the transition toward an economically and technically feasible generating system based on RES, to achieve specifi…