Search results for "Computer engineering. Computer hardware"
showing 10 items of 108 documents
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
2020
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…
DeepEva: A deep neural network architecture for assessing sentence complexity in Italian and English languages
2021
Abstract Automatic Text Complexity Evaluation (ATE) is a research field that aims at creating new methodologies to make autonomous the process of the text complexity evaluation, that is the study of the text-linguistic features (e.g., lexical, syntactical, morphological) to measure the grade of comprehensibility of a text. ATE can affect positively several different contexts such as Finance, Health, and Education. Moreover, it can support the research on Automatic Text Simplification (ATS), a research area that deals with the study of new methods for transforming a text by changing its lexicon and structure to meet specific reader needs. In this paper, we illustrate an ATE approach named De…
Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation
2019
Abstract Recent advances in intrusion detection systems based on machine learning have indeed outperformed other techniques, but struggle with detecting multiple classes of attacks with high accuracy. We propose a method that works in three stages. First, the ExtraTrees classifier is used to select relevant features for each type of attack individually for each (ELM). Then, an ensemble of ELMs is used to detect each type of attack separately. Finally, the results of all ELMs are combined using a softmax layer to refine the results and increase the accuracy further. The intuition behind our system is that multi-class classification is quite difficult compared to binary classification. So, we…
High temperature solid-catalized transesterification for biodiesel production
2010
Biodiesel has become more attractive recently because of its environmental benefits and the fact that it is made from renewable resources. Biodiesel is a mixture of monoalkyl esters of long chain fatty acids derived from renewable feed stock like vegetable oils and animal fats, mainly made of fatty acid glycerides. It is produced by transesterification processes in which oil or fat are reacted with a monohydric alcohol in the presence of a catalyst. The transesterification process is affected by reaction conditions, alcohol to oil molar ratio, type of alcohol, type and amount of catalysts, temperature and purity of reactants. Heterogeneous acid catalysts are quite efficient in promoting the…
Batch Test Evaluation of Four Organic Substrates Suitable for Biological Groundwater Denitrification
2014
Nitrates pollution represents nowadays a serious issue related to the quality of groundwater; continuous growth of industrial-scale agricultures lead to an increase of nitrates content in groundwater in the last years. Several technologies have been validated as capable to promote in situ biological nitrates remediation, such as permeable reactive barriers (PRB), biotrench, biobarriers etc. These technologies are all characterised by the use of organic substrate that act as a slow release carbon source. In free dissolved oxygen absence, such organic carbon is further oxidised, by heterotrophic bacteria naturally present in soil, in compliance to anoxic metabolism by using nitrates bound oxy…
Agronomic Evaluation of Ethiopian Mustard (brassica Carinata A. Braun) Germplasm and Physical-energy Characterization of Crop Residues in a Semi-arid…
2017
Brassica carinata A. Braun is one of the most interesting oilseed crops suited to arid and semi-arid areas for energy purposes. Several studies have highlighted the possibility of introducing this species into cropping systems, typical of Mediterranean region. The aims of this study were to evaluate the agronomic performance of Brassica carinata germplasm under Mediterranean climatic conditions and to assess the physical and energy characteristics of crop residues and pellets made from the residues. A total of 20 different accessions of Brassica carinata were compared in a semi-arid area of Sicily (Italy). In the two-year test period, the main morphological and yield parameters of the acces…
Traditional Enterprise Business Intelligence Software Compared to Software as a Service Business Intelligence
2016
IntroductionBusiness Intelligence is a broad field of study. The major thrust of business intelligence theory analyzes certain factors to make highquality decisions. These factors include customers, competitors, business partners, economic environment and internal operations. Business Intelligence has the power to change the way people work, so that enterprises can compete more effectively and efficiently.A successful business intelligence solutions and successful implementation holds the key to the technological innovations together with the people, processes and culture of an organization to achieve a competitive and profitable BI strategy.Business Intelligence (BI) is the process of acqu…
Restoration of Videos Degraded by Local Isoplanatism Effects in the Near-Infrared Domain
2008
When observing a scene horizontally at a long distance in the near-infrared domain, degradations due to atmospheric turbulence often occur. In our previous work, we presented two hybrid methods to restore videos degraded by such local perturbations. These restoration algorithms take advantages of a space-time Wiener filter and a space-time regularization by the Laplacian operator. Wiener and Laplacian regularization results are mixed differently depending on the distance between the current pixel and the nearest edge point. It was shown that a gradation between Wiener and Laplacian areas improves results quality, so that only the algorithm using a gradation will be used in this article. In …
Extension of luminance component based demosaicking algorithm to 4- and 5-band multispectral images
2021
Abstract Multispectral imaging systems are currently expanding with a variety of multispectral demosaicking algorithms. But these algorithms have limitations due to the remarkable presence of artifacts in the reconstructed image. In this paper, we propose a powerful multispectral image demosaicking method that focuses on the G band and luminance component. We've first identified a relevant 4-and 5-band multispectral filter array (MSFA) with the dominant G band and then proposed an algorithm that consistently estimates the missing G values and other missing components using a convolution operator and a weighted bilinear interpolation algorithm based on the luminance component. Using the cons…
Non-Model Based Method for an Automation of 3D Acquisition and Post-Processing
2008
Most of the automation for 3D acquisition concerns objects with simple shape, like mechanical parts. For cultural heritage artefacts, the process is more complex, and it doesn't exist general solution nowadays. This paper presents a method to generate a complete 3D model of cultural heritage artefacts. In a first step, MVC is used to solve the view planning problem. Then, holes remaining in 3D model are detected, and their features are calculated to finish acquisition. Different post-processing are applied on each view to increase quality of the 3D model. This procedure has been tested with simulated scanner, before being implemented on a motion system with five degrees of freedom.