Search results for "DATA MINING"

STATBOX Concept for Simulation of Urban Phenomena

2013

Abstract An urban environment is a dynamic system which is constantly changing in terms of space and time. There are two dimensions in any urban environment – the physical dimension and the functional dimension. All of the structures of an urban environment interact and people are the intermediaries in this process. The spatial structure of cities has been studied from various perspectives by architects, urban planners, environmental scientists, economists, geographers etc. Constant monitoring that is based on remote sensing, spatial statistics, simulation etc., is needed to make on going note of transformation in the various types of land use that exist, movement of people and business env…

Intrusion detection applications using knowledge discovery and data mining

2014

Application of selected supervised classification methods to bank marketing campaign

2016

Supervised classification covers a number of data mining methods based on training data. These methods have been successfully applied to solve multi-criteria complex classification problems in many domains, including economical issues. In this paper we discuss features of some supervised classification methods based on decision trees and apply them to the direct marketing campaigns data of a Portuguese banking institution. We discuss and compare the following classification methods: decision trees, bagging, boosting, and random forests. A classification problem in our approach is defined in a scenario where a bank’s clients make decisions about the activation of their deposits. The obtained…

Improvements and applications of the elements of prototype-based clustering

2018

Clustering or cluster analysis is an essential part of data mining, machine learning, and pattern recognition. The most popularly applied clustering methods are partitioning-based or prototype-based methods. Prototype-based clustering methods usually have easy implementability and good scalability. These methods, such as K-means clustering, have been used for different applications in various fields. On the other hand, prototype-based clustering methods are typically sensitive to initialization, and the selection of the number of clusters for knowledge discovery purposes is not straightforward. In the era of big data, in high-velocity, ever-growing datasets, which can also be erroneous, outl…

Rationale and design of the DARWIN-T2D (DApagliflozin Real World evIdeNce in Type 2 Diabetes): A multicenter retrospective nationwide Italian study a…

2017

Background Randomized controlled trials (RCTs) in the field of diabetes have limitations inherent to the fact that design, setting, and patient characteristics may be poorly transferrable to clinical practice. Thus, evidence from studies using routinely accumulated clinical data are increasingly valued. Aims We herein describe rationale and design of the DARWIN-T2D (DApagliflozin Real World evIdeNce in Type 2 Diabetes), a multicenter retrospective nationwide study conducted at 50 specialist outpatient clinics in Italy and promoted by the Italian Diabetes Society. Data synthesis The primary objective of the study is to describe the baseline clinical characteristics (particularly HbA1c) of pa…

TISSBERT: A benchmark for the validation and comparison of NDVI time series reconstruction methods

2018

[EN] This paper introduces the Time Series Simulation for Benchmarking of Reconstruction Techniques (TISSBERT) dataset, intended to provide a benchmark for the validation and comparison of time series reconstruction methods. Such methods are routinely used to estimate vegetation characteristics from optical remotely sensed data, where the presence of clouds decreases the usefulness of the data. As for their validation, these methods have been compared with previously published ones, although with different approaches, which sometimes lead to contradictory results. We designed the TISSBERT dataset to be generic so that it could simulate realistic reference and cloud-contaminated time series …

N,N-Dimethyl-N-propylpropan-1-aminium chloride monohydrate

2008

The title compound, C8H20N+·Cl−·H2O, has been prepared by a simple one-pot synthesis route followed by anion exchange using resin. In the crystal structure, the cations are packed in such a way that channels exist parallel to the b axis. These channels are filled by the anions and water molecules, which interact via O—H...Cl hydrogen bonds [O...Cl = 3.285 (3) and 3.239 (3) Å] to form helical chains. The cations are involved in weak intermolecular C—H...Cl and C—H...O hydrogen bonds. The title compound is not isomorphous with the bromo or iodo analogues.

The Joint Distribution Criterion and the Distance Tests for Selective Probabilistic Causality

2010

A general definition and a criterion (a necessary and sufficient condition) are formulated for an arbitrary set of external factors to selectively influence a corresponding set of random entities (generalized random variables, with values in arbitrary observation spaces), jointly distributed at every treatment (a set of factor values containing precisely one value of each factor). The random entities are selectively influenced by the corresponding factors if and only if the following condition, called the joint distribution criterion, is satisfied : there is a jointly distributed set of random entities, one entity for every value of every factor, such that every subset of this set that corr…

Detecting cellular network anomalies using the knowledge discovery process

2015

Analytical companies unanimously forecast the exponential growth of mobile traffic consumption over the next five years. The densification of a network structure with small cells is regarded as a key solution to meet growing capacity demands. The manual management of a multi-layer network is a very expensive, error prone, and sluggish process. Hence, the automation of the whole life cycle of network operation is highly anticipated. To this aim 3GPP introduces a self-management concept referred to as SON. It is envisioned that SON updates information concerning the latest network conditions through the MDT mecha- nism. MDT enables a network operator to collect radio and service quality measurem…

Advanced performance monitoring for self-healing cellular mobile networks

2015

This dissertation is devoted to development and validation of advanced per- formance monitoring system for existing and future cellular mobile networks. Knowledge mining techniques are employed for analysis of user specific logs, collected with Minimization of Drive Tests (MDT) functionality. Ever increas- ing quality requirements, expansion of the mobile networks and their extend- ing heterogeneity, call for effective automatic means of performance monitoring. Nowadays, network operation is mostly controlled manually through aggregated key performance indicators and statistical profiles. These methods are are not able to fully address the dynamism and complexity of modern mobile networks. Se…