Use of Data Mining for Intelligent Evaluation of Imputation Methods

In real-world situations, researchers frequently face the difficulty of missing values (MV), i.e., values not observed in a data set. Data imputation techniques allow the estimation of MV using different algorithms, by means of which important data can be imputed for a particular instance. Most of the literature in this field deals with different imputation methods. However, few studies deal with a comparative evaluation of the different methods as to provide more appropriate guidelines for the selection of the method to be applied to impute data for specific situations. The objective of this work is to show a methodology for evaluating the performance of imputation methods by means of new metrics derived from data mining processes, using quality metrics of data mining models. We started from the complete dataset that was amputated with different amputation mechanisms to generate 63 datasets with MV; these were imputed using Median, k-NN, k-Means and Hot-Deck imputation methods. The performance of the imputation methods was evaluated using new metrics derived from quality metrics of the data mining processes, performed with the original full file and with the imputed files. This evaluation is not based on measuring the error when imputing (usual operation), but on considering the similarity of the values of the quality metrics of the data mining processes obtained with the original file and with the imputed files. The results show that –globally considered and according to the new proposed metric, the imputation methods that showed the best performance were k-NN and k-Means. An additional advantage of the proposed methodology is that it provides predictive data mining models that can be used a posteriori

Food patterns in intake of dietary fibre in small group of Croatian adults

The aim of this study was to determine the intake of total dietary fibre, soluble and insoluble dietary fibre, as well as their food sources. Additionally, a relationship between dietary fibre intake and intake of foods that do not contain dietary fibre was examined. Forty-five adult subjects (22-52 yr; 28 women and 17 men) took part in the study. A method of 7-day weighed dietary records was used. An average daily total dietary fibre intake for the whole group was 21.0 g, i.e. 2.6 g/MJ. The mean soluble dietary fibre intake was 7.5 g. Cereals and products made the greatest contribution to daily dietary fibre intake (45% total, 53% soluble and 40% insoluble dietary fibre). This group of subjects had a mean daily consumption of fruits and vegetables of 482 g, and 241 g of cereals. Aside to an expected higher intake of fruits, vegetables and cereals, subjects with high intake of total dietary fibre (4th quartile), also had a higher intake of meat and products and fats and oils, as opposed to subjects from the lowest quartile of total dietary fibre intake. Daily intake of total dietary fibre is best correlated with intakes of vegetables (without potatoes) and cereals

GRB 081024B and GRB 140402A: two additional short GRBs from binary neutron star mergers

Theoretical and observational evidences have been recently gained for a two-fold classification of short bursts: 1) short gamma-ray flashes (S-GRFs), with isotropic energy $E_{iso}<10^{52}$~erg and no BH formation, and 2) the authentic short gamma-ray bursts (S-GRBs), with isotropic energy $E_{iso}>10^{52}$~erg evidencing a BH formation in the binary neutron star merging process. The signature for the BH formation consists in the on-set of the high energy ($0.1$--$100$~GeV) emission, coeval to the prompt emission, in all S-GRBs. No GeV emission is expected nor observed in the S-GRFs. In this paper we present two additional S-GRBs, GRB 081024B and GRB 140402A, following the already identified S-GRBs, i.e., GRB 090227B, GRB 090510 and GRB 140619B. We also return on the absence of the GeV emission of the S-GRB 090227B, at an angle of $71^{\rm{o}}$ from the \textit{Fermi}-LAT boresight. All the correctly identified S-GRBs correlate to the high energy emission, implying no significant presence of beaming in the GeV emission. The existence of a common power-law behavior in the GeV luminosities, following the BH formation, when measured in the source rest-frame, points to a commonality in the mass and spin of the newly-formed BH in all S-GRBs.Comment: 16 pages, submitted to ApJ, second version addressing the comments by the refere

GRB 170817A-GW170817-AT 2017gfo and the observations of NS-NS, NS-WD and WD-WD mergers

The LIGO-Virgo Collaboration has announced the detection of GW170817 and has associated it with GRB 170817A. These signals have been followed after 11 hours by the optical and infrared emission of AT 2017gfo. The origin of this complex phenomenon has been attributed to a neutron star-neutron star (NS-NS) merger. In order to probe this association we confront our current understanding of the gravitational waves and associated electromagnetic radiation with four observed GRBs originating in binaries composed of different combinations NSs and white dwarfs (WDs). We consider 1) GRB 090510 the prototype of NS-NS merger leading to a black hole (BH); 2) GRB 130603B the prototype of a NS-NS merger leading to massive NS (MNS) with an associated kilonova; 3) GRB 060614 the prototype of a NS-WD merger leading to a MNS with an associated kilonova candidate; 4) GRB 170817A the prototype of a WD-WD merger leading to massive WD with an associated AT 2017gfo-like emission. None of these systems support the above mentioned association. The clear association between GRB 170817A and AT 2017gfo has led to introduce a new model based on on a new subfamily of GRBs originating from WD-WD mergers. We show how this novel model is in agreement with the exceptional observations in the optical, infrared, X- and gamma-rays of GRB 170817A-AT 2017gfo.Comment: version accepted for publication in JCAP. Missing references adde

USPOREDBA HRVATSKOG I MAKEDONSKOG MEDLJIKOVCA

The aim of this research was to compare physicochemical characteristics of honeydew honeys originating from Croatia and Macedonia. 11 samples of Macedonian and 17 samples of Croatian honeydew honey were collected during the harvest season 2005 and 2006, respectively. All collected samples were subjected to the melissopalynological analysis, and afterwards physicochemical characteristics were determined. In comparison with Croatian samples, the samples of Macedonian honeydew honey show statistically significant higher electrical conductivity, prolin content, free and total acidity, glucose and sucrose, as well as fructose and glucose content (F + G), and lower specific rotation, almost negative values. Croatian samples have higher content of maltose (with celobiose and trehalose) and raffinose, until melezitose (with erlose) content in both sample groups is low.Zadatak ovog istraživanja bio je usporedba fizikalno-kemijskih parametara medljikovca podrijetlom iz Hrvatske i Makedonije. Prikupljeno je 11 uzoraka proizvedenih u Makedoniji 2005. i 17 uzoraka proizvedenih u Hrvatskoj 2006. godine. Po provedenoj melisopalinološkoj analizi, određeni su fizikalno-kemijski parametri uzoraka. U usporedbi s hrvatskim uzorcima, makedonski uzorci pokazuju statistički značajno višu električnu provodnost, udio prolina, slobodnu i ukupnu kiselost, udio glukoze i saharoze, udio fruktoze i glukoze (F + G), te nižu specifičnu rotaciju, uglavnom negativnu. Hrvatske uzorke karakterizira viši udio maltoze (sa celobizom i trehalozom) i rafinoze, dok je udio melecitoze (sa erlozom) u obje skupine uzoraka nizak

The microscopic structure of cold aqueous methanol mixtures

The evolution of the micro-segregated structure of aqueous methanol mixtures, in the temperature range 300 K-120 K, is studied with computer simulations, from the static structural point of view. The structural heterogeneity of water is reinforced at lower temperatures, as witnessed by a pre-peak in the oxygen-oxygen structure factor. Water tends to form predominantly chain-like clusters at lower temperatures and smaller concentrations. Methanol domains have essentially the same chain-like cluster structure as the pure liquid at high concentrations and becomes mono- meric at smaller ones. Concentration uctuations decrease with temperature, leading to quasi-ideal Kirkwood-Bu integrals, despite the enhanced molecular interactions, which we interpret as the signature of non-interacting segregated water and methanol clusters. This study throws a new light on the nature of the micro-heterogeneous structure of this mixture: the domain segregation is essentially based on the appearance of linear water clusters, unlike other alcohol aqueous mixtures, such as with propanol or butanol, where the water domains are more bulky.

Modelo de decisión para la validación de métodos de imputación mediante la utilización de algoritmos de minería de datos

Muchos de los conjuntos de datos (data sets) existentes u obtenidos en investigaciones científicas contienen valores faltantes (MVs: Missing Values) y anomalías (outliers) asociados a procedimientos de entrada manuales deficientes, mediciones incorrectas o errores en los instrumentos de medición. En minería de datos (DM: Data Mining) estas imperfecciones pueden afectar negativamente la calidad del proceso de aprendizaje supervisado o el rendimiento de algoritmos de agrupamiento de datos. La imputación es una técnica para reemplazar MVs con valores sustituidos. Pocos estudios informan una evaluación global de los métodos existentes con el fin de proporcionar directrices para hacer la elección metodológica más apropiada en la práctica. El propósito general de este trabajo es determinar un modelo de decisión que permita encontrar los métodos de imputación más adecuados para completar información faltante en un conjunto de datos mediante la utilización de algoritmos de DM.Eje: Bases de Datos y Minería de Datos.Red de Universidades con Carreras en Informátic