Search results for "machine"
showing 10 items of 2592 documents
Design criteria of tubular linear induction motors and generators: A prototype realization and its characterization
2013
In this paper a mathematical model of tubular linear induction machines (TLIM) with hollowed induced part is recalled. Moreover the design criteria of a TLIM with hollowed iron induced part are presented as well as the technological processes to be adopted and the choice of materials to construct the various parts. The methodologies for mechanical assembling and electric wiring are considered too. A prototype with bimetallic induced part has been designed and built. Finally some experimental results on electrical and mechanical variables, when the machines are used as motors, are shown.
FMEA - BASIC CONCEPT IN PRODUCT QUALITY
2018
Failure modes and effects analysis (FMEA) is a systematic procedure for analyzing a system (the entire system or just an assembly, subassembly or component) to identify potential failure modes, causes and effects of each failure on system operation. A somewhat different definition was formulated by Goddard Space Flight Center (USA) : FMEA is a procedure whereby every credible way of defeating each item from the lower decomposition level to the highest level is analyzed to determine effects on the system and classify each potential way of failure according to the severity of its effect.
Ambainis-Freivalds’ Algorithm for Measure-Once Automata
2001
An algorithm given by Ambainis and Freivalds [1] constructs a quantum finite automaton (QFA) with O(log p) states recognizing the language Lp = {ai| i is divisible by p} with probability 1 - Ɛ , for any Ɛ > 0 and arbitrary prime p. In [4] we gave examples showing that the algorithm is applicable also to quantum automata of very limited size. However, the Ambainis-Freivalds algoritm is tailored to constructing a measure-many QFA (defined by Kondacs andWatrous [2]), which cannot be implemented on existing quantum computers. In this paper we modify the algorithm to construct a measure-once QFA of Moore and Crutchfield [3] and give examples of parameters for this automaton. We show for the lang…
Machine Learning Methods for One-Session Ahead Prediction of Accesses to Page Categories
2004
This paper presents a comparison among several well-known machine learning techniques when they are used to carry out a one-session ahead prediction of page categories. We use records belonging to 18 different categories accessed by users on the citizen web portal Infoville XXI. Our first approach is focused on predicting the frequency of accesses (normalized to the unity) corresponding to the user’s next session. We have utilized Associative Memories (AMs), Classification and Regression Trees (CARTs), Multilayer Perceptrons (MLPs), and Support Vector Machines (SVMs). The Success Ratio (SR) averaged over all services is higher than 80% using any of these techniques. Nevertheless, given the …
Spatial noise-aware temperature retrieval from infrared sounder data
2020
In this paper we present a combined strategy for the retrieval of atmospheric profiles from infrared sounders. The approach considers the spatial information and a noise-dependent dimensionality reduction approach. The extracted features are fed into a canonical linear regression. We compare Principal Component Analysis (PCA) and Minimum Noise Fraction (MNF) for dimensionality reduction, and study the compactness and information content of the extracted features. Assessment of the results is done on a big dataset covering many spatial and temporal situations. PCA is widely used for these purposes but our analysis shows that one can gain significant improvements of the error rates when using…
Novel Approaches for Glioblastoma Treatment: Focus on Tumor Heterogeneity, Treatment Resistance, and Computational Tools
2019
BACKGROUND: Glioblastoma (GBM) is a highly aggressive primary brain tumor. Currently, the suggested line of action is the surgical resection followed by radiotherapy and treatment with the adjuvant temozolomide (TMZ), a DNA alkylating agent. However, the ability of tumor cells to deeply infiltrate the surrounding tissue makes complete resection quite impossible, and in consequence, the probability of tumor recurrence is high, and the prognosis is not positive. GBM is highly heterogeneous and adapts to treatment in most individuals. Nevertheless, these mechanisms of adaption are unknown. RECENT FINDINGS: In this review, we will discuss the recent discoveries in molecular and cellular heterog…
Effects of tilling methods on soil penetration resistance, organic carbon and water stable aggregates in a vineyard of semiarid Mediterranean environ…
2018
Tillage, especially in semiarid Mediterranean environment, enhances the mineralization process of soil organic matter (SOM) and, in turn, decreases aggregate stability. Furthermore, continuous tillage leads to the formation of plough pan beneath the tilled layer. In the present study, we investigated the effect of an innovative self-propelled machine (spading machine, SM) for shallow tillage on SOM, water stable aggregates (WSA) and soil penetration resistance (PR). Such effects were compared to those of chisel plough (CP), rotary tiller (RT) and no tillage (NT). Each tilling method was applied up to a depth of 15 cm, whereas in NT only a brush cutter was used for weed control. Soil analyse…
Elia Ovazza, Professor of TMM in Palermo Around the End of the 19th Century
2015
In this paper, the figure of Elia Ovazza, professor of TMM in Palermo around the end of the 19th century, is presented, along with his valuable legacy in regard to his activities in teaching, research, design and technology transfer. Short biographical notes outline his foremost life events and an illustrated survey explains his contributions.
Erratum: De Teresa, J.M. et al. Comparison between Focused Electron/Ion Beam-Induced Deposition at Room Temperature and under Cryogenic Conditions. M…
2020
In Section 3 [...]
Disentangling Derivatives, Uncertainty and Error in Gaussian Process Models
2020
Gaussian Processes (GPs) are a class of kernel methods that have shown to be very useful in geoscience applications. They are widely used because they are simple, flexible and provide very accurate estimates for nonlinear problems, especially in parameter retrieval. An addition to a predictive mean function, GPs come equipped with a useful property: the predictive variance function which provides confidence intervals for the predictions. The GP formulation usually assumes that there is no input noise in the training and testing points, only in the observations. However, this is often not the case in Earth observation problems where an accurate assessment of the instrument error is usually a…