Interactive Stepwise Discriminant Analysis in Matlab

2000 Mathematics Subject Classification: 62-04, 62H30, 62J20

Comparing Several Methods of Discriminant Analysis on the Case of Wine Data

2000 Mathematics Subject Classification: 62H30, 62J20, 62P12, 68T99

Theory for Optical Absorption in Small Clusters: Dependence on Atomic Structure and Cluster Size

We present a theory which permits for the first time a detailed analysis of the dependence of the absorption spectrum on atomic structure and cluster size. Thus, we determine the development of the collective excitations in small clusters and show that their broadening depends sensitively on the tomic structure, in particular at the surface. Results for Hg_n^+ clusters show that the plasmon energy is close to its jellium value in the case of spherical-like structures, but is in general between w_p/ \wurzel{3} and w_p/ \wurzel{2} for compact clusters. A particular success of our theory is the identification of the excitations contributing to the absorption peaks.

Coordinated ground-based, low altitude satellite and Cluster observations on global and local scales during a transient post-noon sector excursion of the magnetospheric cusp

On 14 January 2001, the four Cluster spacecraft passed through the northern magnetospheric mantle in close conjunction to the EISCAT Svalbard Radar (ESR) and approached the post-noon dayside magnetopause over Greenland between 13:00 and 14:00 UT During that interval, a sudden reorganisation of the high-latitude dayside convection pattern accurred after 13:20 UT most likely caused by a direction change of the Solar wind magnetic field. The result was an eastward and poleward directed flow-channel, as monitored by the SuperDARN radar network and also by arrays of ground-based magnetometers in Canada, Greenland and Scandinavia. After an initial eastward and later poleward expansion of the flow-channel between 13:20 and 13:40 UT, the four Cluster spacecraft, and the field line footprints covered by the eastward looking scan cycle of the Sondre Stromfjord incoherent scatter radar were engulfed by cusp-like precipitation with transient magnetic and electric field signatures. In addition, the EISCAT Svalbard Radar detected strong transient effects of the convection reorganisation, a poleward moving precipitation, and a fast ion flow-channel in association with the auroral structures that suddenly formed to the west and north of the radar. From a detailed analysis of the coordinated Cluster and ground-based data, it was found that this extraordinary transient convection pattern, indeed, had moved the cusp precipitation from its former pre-noon position into the late post-noon sector, allowing for the first and quite unexpected encounter of the cusp by the Cluster spacecraft. Our findings illustrate the large amplitude of cusp dynamics even in response to moderate solar wind forcing. The global ground-based data proves to be an invaluable tool to monitor the dynamics and width of the affected magnetospheric regions.

Estimates of genetic parameters, and cluster and principal components analyses of breeding values related to egg production traits in a White Leghorn population

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Approccio network-based alla discriminant analysis mediante HPC per la ricerca di signature ottimali in dati ad alta dimensionalità

Il presente lavoro di tesi si inserisce nell’ambito della classificazione di dati ad alta dimensionalità, sviluppando un algoritmo basato sul metodo della Discriminant Analysis. Esso classifica i campioni attraverso le variabili prese a coppie formando un network a partire da quelle che hanno una performance sufficientemente elevata. Successivamente, l’algoritmo si avvale di proprietà topologiche dei network (in particolare la ricerca di subnetwork e misure di centralità di singoli nodi) per ottenere varie signature (sottoinsiemi delle variabili iniziali) con performance ottimali di classificazione e caratterizzate da una bassa dimensionalità (dell’ordine di 101, inferiore di almeno un fattore 103 rispetto alle variabili di partenza nei problemi trattati). Per fare ciò, l’algoritmo comprende una parte di definizione del network e un’altra di selezione e riduzione della signature, calcolando ad ogni passaggio la nuova capacità di classificazione operando test di cross-validazione (k-fold o leave- one-out). Considerato l’alto numero di variabili coinvolte nei problemi trattati – dell’ordine di 104 – l’algoritmo è stato necessariamente implementato su High-Performance Computer, con lo sviluppo in parallelo delle parti più onerose del codice C++, nella fattispecie il calcolo vero e proprio del di- scriminante e il sorting finale dei risultati. L’applicazione qui studiata è a dati high-throughput in ambito genetico, riguardanti l’espressione genica a livello cellulare, settore in cui i database frequentemente sono costituiti da un numero elevato di variabili (104 −105) a fronte di un basso numero di campioni (101 −102). In campo medico-clinico, la determinazione di signature a bassa dimensionalità per la discriminazione e classificazione di campioni (e.g. sano/malato, responder/not-responder, ecc.) è un problema di fondamentale importanza, ad esempio per la messa a punto di strategie terapeutiche personalizzate per specifici sottogruppi di pazienti attraverso la realizzazione di kit diagnostici per l’analisi di profili di espressione applicabili su larga scala. L’analisi effettuata in questa tesi su vari tipi di dati reali mostra che il metodo proposto, anche in confronto ad altri metodi esistenti basati o me- no sull’approccio a network, fornisce performance ottime, tenendo conto del fatto che il metodo produce signature con elevate performance di classifica- zione e contemporaneamente mantenendo molto ridotto il numero di variabili utilizzate per questo scopo.

EU Policies and Cluster Developments of Hydrogen Communities. Bruges European Economic Research (BEER) Papers 14/December 2008

This study takes on the issue of political and socio-economic conditions for the hydrogen economy as part of a future low carbon society in Europe. It is subdivided into two parts. A first part reviews the current EU policy framework in view of its impact on hydrogen and fuel cell development. In the second part an analysis of the regional dynamics and possible hydrogen and fuel cell clusters is carried out. The current EU policy framework does not hinder hydrogen development. Yet it does not constitute a strong push factor either. EU energy policies have the strongest impact on hydrogen and fuel cell development even though their potential is still underexploited. Regulatory policies have a weak but positive impact on hydrogen. EU spending policies show some inconsistencies. Regions with a high activity level in HFC also are generally innovative regions. Moreover, the article points out certain industrial clusters that favours some regions' conditions for taking part in the HFC development. However, existing hydrogen infrastructure seems to play a minor role for region's engagement. An overall well-functioning regional innovation system is important in the formative phase of an HFC innovation system, but that further research is needed before qualified policy implications can be drawn. Looking ahead the current policy framework at EU level does not set clear long term signals and lacks incentives that are strong enough to facilitate high investment in and deployment of sustainable energy technologies. The likely overall effect thus seems to be too weak to enable the EU hydrogen and fuel cell deployment strategy. According to our analysis an enhanced EU policy framework pushing for sustainability in general and the development of hydrogen and fuel cells in particular requires the following: 1) A strong EU energy policy with credible long term targets; 2) better coordination of EU policies: Europe needs a common understanding of key taxation concepts (green taxation, internalisation of externalities) and a common approach for the market introduction of new energy technologies; 3) an EU cluster policy as an attempt to better coordinate and support of European regions in their efforts to further develop HFC and to set up the respective infrastructure.

STORM - a novel information fusion and cluster interpretation technique

Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, useful for better understanding of a problem at hand, than by looking only at the data itself. Although abundant expert knowledge exists in many areas where unlabelled data is examined, such knowledge is rarely incorporated into automatic analysis. Incorporation of expert knowledge is frequently a matter of combining multiple data sources from disparate hypothetical spaces. In cases where such spaces belong to different data types, this task becomes even more challenging. In this paper we present a novel immune-inspired method that enables the fusion of such disparate types of data for a specific set of problems. We show that our method provides a better visual understanding of one hypothetical space with the help of data from another hypothetical space. We believe that our model has implications for the field of exploratory data analysis and knowledge discovery.

Charged particles and cluster ions produced during cooking activities

Previous studies showed that a significant number of the particles present in indoor air are generated by cooking activities, and measured particle concentrations and exposures have been used to estimate the related human dose. The dose evaluation can be affected by the particle charge level which is usually not considered in particle deposition models. To this purpose, in this paper we show, for the very first time, the electric charge of particles generated during cooking activities and thus extending the interest on particle charging characterization to indoor micro-environments, so far essentially focused on outdoors. Particle number, together with positive and negative cluster ion concentrations, was monitored using a condensation particle counter and two air ion counters, respectively, during different cooking events. Positively-charged particle distribution fractions during gas combustion, bacon grilling, and eggplant grilling events were measured by two Scanning Mobility Particle Sizer spectrometers, used with and without a neutralizer. Finally, a Tandem Differential Mobility Analyzer was used to measure the charge specific particle distributions of bacon and eggplant grilling experiments, selecting particles of 30, 50, 80 and 100 nm in mobility diameter. The total fraction of positively-charged particles was 4.0%, 7.9%, and 5.6% for gas combustion, bacon grilling, and eggplant grilling events, respectively, then lower than other typical outdoor combustion-generated particles.

Preformation of clusters in heavy nuclei and cluster radioactivity

Within the preformed cluster model approach, the values of the preformation factors have been deduced from the experimental cluster decay half-lives assuming that the decay constant of the heavy-ion emission is the product of the assault frequency, the preformation factor and the penetrability. The law according to which the preformation factors follow a simple dependence on the mass of the cluster was confirmed. Then predictions for some of the most possible cluster decays are provided.

On the choice of posittioning and cluster size for fixed relay stations in a LTE network

The long term evolution (LTE) is one of the latest standards in the mobile communications market. To achieve its performance, LTE networks use several techniques, such as multi-carrier technique, multiple-input-multiple-output and cooperative communications. Inside cooperative communications, this paper focuses on the fixed relaying technique, presenting a way for determining the best position to deploy the relay station (RS), from a set of empirical good solutions, and also to quantify the associated performance gain using different cluster size configurations. The best RS position was obtained through realistic simulations, which set it as the middle of the cell's circumference arc. Additionally, it also confirmed that network's performance is improved when the number of RSs is increased. It was possible to conclude that, for each deployed RS, the percentage of area served by an RS increases about 10 %. Furthermore, the mean data rate in the cell has been increased by approximately 60 % through the use of RSs. Finally, a given scenario with a larger number of RSs, can experience the same performance as an equivalent scenario without RSs, but with higher reuse distance. This conduces to a compromise solution between RS installation and cluster size, in order to maximize capacity, as well as performance.

Studies on the optical band gap and cluster size of the polyaniline thin films irradiated with swift heavy Si ions

Polyaniline thin films prepared by RF plasma polymerisation were irradiated with 92MeV Si ions for various fluences of 1 1011, 1 1012 and 1 1013 ions/cm2. FTIR and UV–vis–NIR measurements were carried out on the pristine and Si ion irradiated polyaniline thin films for structural evaluation and optical band gap determination. The effect of swift heavy ions on the structural and optical properties of plasma-polymerised aniline thin film is investigated. Their properties are compared with that of the pristine sample. The FTIR spectrum indicates that the structure of the irradiated sample is altered. The optical studies show that the band gap of irradiated thin film has been considerably modified. This has been attributed to the rearrangement in the ring structure and the formation of CRC terminals. This results in extended conjugated structure causing reduction in optical band gap