Search results for "Mining"

Effect of the mineralogical composition on the elastoplastic hydromechanical response of Opalinus Clay shale

2021

Abstract Opalinus Clay is the shale currently under investigation as the host formation for geological radioactive waste disposal in Switzerland. Its hydromechanical response has been widely studied, and the experimental results show a range of values whose dispersion needs to be clarified. This work aims to explain the dispersion in the literature results by correlating the hydro-mechanical response to the mineralogical variability of the tested specimens . Based on published microstructural studies, the Opalinus Clay shale is herein schematised as a sequence of two kinds of layers: the shaly (high in clay-mineral content) and the sandy (low in clay-mineral content) layers. The mineralogic…

Discriminating Graph Pattern Miningfrom Gene Expression Data

2016

We consider the problem of mining gene expression data in order to single out interesting features characterizing healthy/unhealthy samples of an input dataset. We present an approach based on a network model of the input gene expression data, where there is a labelled graph for each sample. To the best of our knowledge, this is the first attempt to build a different graph for each sample and, then, to have a database of graphs for representing a sample set. Our main goal is that of singling out interesting differences between healthy and unhealthy samples, through the extraction of "discriminative patterns" among graphs belonging to the two different sample sets. Differently from the other…

Novel Combinatorial and Information-Theoretic Alignment-Free Distances for Biological Data Mining

2010

Among the plethora of alignment-free methods for comparing biological sequences, there are some that we have perceived as representative of the novel techniques that have been devised in the past few years and as being of a fundamental nature and of broad interest and applicability, ranging from combinatorics to information theory. In this chapter, we review these alignment free methods, by presenting both their mathematical definitions and the experiments in which they are involved in.

A Fuzzy One Class Classifier for Multi Layer Model

2009

The paper describes an application of a fuzzy one-class classifier (FOC ) for the identification of different signal patterns embedded in a noise structured background. The classification phase is applied after a preprocessing phase based on a Multi Layer Model (MLM ) that provides a preliminary signal segmentation in an interval feature space. The FOC has been tested on synthetic and real microarray data in the specific problem of DNA nucleosome and linker regions identification. Results have shown, in both cases, a good recognition rate.

L'Opinion Mining nelle Scienze Cognitive: espressione dei sentimenti e reti sociali

2015

Speeding up the Consensus Clustering methodology for microarray data analysis

2010

Abstract Background The inference of the number of clusters in a dataset, a fundamental problem in Statistics, Data Analysis and Classification, is usually addressed via internal validation measures. The stated problem is quite difficult, in particular for microarrays, since the inferred prediction must be sensible enough to capture the inherent biological structure in a dataset, e.g., functionally related genes. Despite the rich literature present in that area, the identification of an internal validation measure that is both fast and precise has proved to be elusive. In order to partially fill this gap, we propose a speed-up of Consensus (Consensus Clustering), a methodology whose purpose…

Techno-economic analysis of integrated processes for the treatment and valorisation of neutral coal mine effluents

2020

Abstract The disposal of highly-concentrated neutral coal mine effluents into the environment constitutes a severe threat to the natural ecosystem. This work proposes and compares five novel treatment chains to purify the effluent and recover raw materials. The chains present different combinations of pre-treatment and concentration technologies. In all cases, the solution sent to the concentration step is concentrated up to saturation to recover water and sodium chloride. Concerning the technical performances, the treatment chains are compared in terms of total energy demand and salt recovery. Furthermore, the economic feasibility assessment is performed via a novel global parameter, i.e. …

Electrodialysis with Bipolar Membranes for the Sustainable Production of Chemicals from Seawater Brines at Pilot Plant Scale

2023

Environmental concerns regarding the disposal of seawater reverse osmosis brines require the development of new valorization strategies. Electrodialysis with bipolar membrane (EDBM) technology enables the production of acid and base from a salty waste stream. In this study, an EDBM pilot plant with a membrane area of 19.2 m2 was tested. This total membrane area results much larger (i.e., more than 16 times larger) than those reported in the literature so far for the production of HCl and NaOH aqueous solutions, starting from NaCl brines. The pilot unit was tested both in continuous and discontinuous operation modes, at different current densities (200-500 A m-2). Particularly, three differe…

An Ambient Intelligence Architecture for Extracting Knowledge from Distributed Sensors

2009

Precisely monitoring the environmental conditions is an essential requirement for AmI projects, but the wealth of data generated by the sensing equipment may easily overwhelm the modules devoted to higher-level reasoning, clogging them with irrelevant details. The present work proposes a new approach to knowledge extraction from raw data that addresses this issue at different levels of abstraction. Wireless sensor networks are used as the pervasive sensory tool, and their computational capabilities are exploited to remotely perform preliminary data processing. A central intelligent unit subsequently extracts higher-level concepts represented in a geometrical space and carries on symbolic re…

An Adaptive Bayesian System for Context-Aware Data Fusion in Smart Environments

2017

The adoption of multi-sensor data fusion techniques is essential to effectively merge and analyze heterogeneous data collected by multiple sensors, pervasively deployed in a smart environment. Existing literature leverages contextual information in the fusion process, to increase the accuracy of inference and hence decision making in a dynamically changing environment. In this paper, we propose a context-aware, self-optimizing, adaptive system for sensor data fusion, based on a three-tier architecture. Heterogeneous data collected by sensors at the lowest tier are combined by a dynamic Bayesian network at the intermediate tier, which also integrates contextual information to refine the infe…