New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Some advances in mathematical models for preference relations

Preference relations, and their modeling, have played a crucial role in both social sciences and applied mathematics. A special category of preference relations is represented by cardinal preference relations, which are nothing other than relations which can also take into account the degree of relation. Preference relations play a pivotal role in most of multi criteria decision making methods and in the operational research. This thesis aims at showing some recent advances in their methodology. Actually, there are a number of open issues in this field and the contributions presented in this thesis can be grouped accordingly. The first issue regards the estimation of a weight vector given a preference relation. A new and efficient algorithm for estimating the priority vector of a reciprocal relation, i.e. a special type of preference relation, is going to be presented. The same section contains the proof that twenty methods already proposed in literature lead to unsatisfactory results as they employ a conflicting constraint in their optimization model. The second area of interest concerns consistency evaluation and it is possibly the kernel of the thesis. This thesis contains the proofs that some indices are equivalent and that therefore, some seemingly different formulae, end up leading to the very same result. Moreover, some numerical simulations are presented. The section ends with some consideration of a new method for fairly evaluating consistency. The third matter regards incomplete relations and how to estimate missing comparisons. This section reports a numerical study of the methods already proposed in literature and analyzes their behavior in different situations. The fourth, and last, topic, proposes a way to deal with group decision making by means of connecting preference relations with social network analysis.

Sensory evaluation of "dulce de leche" with coffee and whey using different affective data analysis methods

This study sought to evaluate the acceptance of "dulce de leche" with coffee and whey. The results were analyzed through response surface, ANOVA, test of averages, histograms, and preference map correlating the global impression data with results of physical, physiochemical and sensory analysis. The response surface methodology, by itself, was not enough to find the best formulation. For ANOVA, test of averages, and preference map it was observed that the consumers' favorite "dulce de leche" were those of formulation 1 (10% whey and 1% coffee) and 2 (30% whey and 1% coffee), followed by formulation 9 (20% whey and 1.25% coffee). The acceptance of samples 1 and 2 was influenced by the higher acceptability in relation to the flavor and for presenting higher pH, L*, and b* values. It was observed that samples 1 and 2 presented higher purchase approval score and higher percentages of responses for the 'ideal' category in terms of sweetness and coffee flavor. It was found that consumers preferred the samples with low concentrations of coffee independent of the concentration of whey thus enabling the use of whey and coffee in the manufacture of dulce de leche, obtaining a new product.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

La experiencia de los receptores en el trasplante de órganos y tejidos

El trasplante de órganos y/o tejidos es considerado como una opción terapéutica viable para el tratamiento tanto de enfermedades crónicas o en estadios terminales, como de afectaciones no vitales, pero que generen una disminución en la calidad de vida percibida por el paciente. Este procedimiento, de carácter multidimensional, está compuesto por 3 actores principales: el donante, el órgano/tejido, y el receptor. Si bien un porcentaje significativo de investigaciones y planes de intervención han girado en torno a la dimensión biológica del trasplante, y a la promoción de la donación; el interés por la experiencia psicosocial y la calidad de vida de los receptores en este proceso ha aumentado durante la última década. En relación con esto, la presente monografía se plantea como objetivo general la exploración de la experiencia y los significados construidos por los pacientes trasplantados, a través de una revisión sistemática de la literatura sobre esta temática. Para ello, se plantearon unos objetivos específicos derivados del general, se seleccionaron términos o palabras claves por cada uno de estos, y se realizó una búsqueda en 5 bases de datos para revistas indexadas: Ebsco Host (Academic Search; y Psychology and Behavioral Sciences Collection); Proquest; Pubmed; y Science Direct. A partir de los resultados, se establece que si bien la vivencia de los receptores ha comenzado a ser investigada, aún es necesaria una mayor exploración sobre la experiencia de estos pacientes; exploración que carecería de objetivo si no se hiciera a través de las narrativas o testimonios de los mismos receptores

Protonation of phenylboronic acid: comparison of G3B3 and G2MP2 methods

G3B3 and G2MP2 calculations using Gaussian 03 have been carried out to investigate the protonation preferences for phenylboronic acid. All nine heavy atoms have been protonated in turn. With both methodologies, the two lowest protonation energies are obtained with the proton located either at the ipso carbon atom or at a hydroxyl oxygen atom. Within the G3B3 formalism, the lowest-energy configuration by 4.3 kcal . mol(-1) is found when the proton is located at the ipso carbon, rather than at the electronegative oxygen atom. In the resulting structure, the phenyl ring has lost a significant amount of aromaticity. By contrast, calculations with G2MP2 show that protonation at the hydroxyl oxygen atom is favored by 7.7 kcal . mol(-1). Calculations using the polarizable continuum model (PCM) solvent method also give preference to protonation at the oxygen atom when water is used as the solvent. The preference for protonation at the ipso carbon found by the more accurate G3B3 method is unexpected and its implications in Suzuki coupling are discussed. (C) 2006 Wiley Periodicals, Inc.

Carbohydrate preference, acid tolerance and bile tolerance in five strains of Bifidobacterium

Aims: To assess the suitability of bifidobacteria for inclusion in synbiotic products on the basis of carbohydrate preference, acid and bile tolerance. Methods and Results: Five strains of Bifidobacterium were analysed for their carbohydrate preference from 12 substrates. Maximum growth rates were used to compare substrate preferences. Galacto-oligosaccharides and isomalto-oligosaccharides were well utilized by all the test species. Most bacteria tested could also utilize at least one type of fructan molecule. To determine transit tolerance of potentially probiotic bifidobacteria, acid and bile resistance was tested. A wide range acid resistance was found. Bile tolerance also varied. Conclusions: GOS and IMO were generally well utilized by the tested species. Other substrates were used to different degrees by the different species. Most bifidobacteria are poorly resistant to strongly acidic conditions with the exception of Bifidobacterium lactis Bb12. Bile tolerances were widely variable and it was shown that caution should be exercised when using colorimetric methods to assess bile tolerance. Significance and Impact of Study: The study allows the comparison of the properties of bifidobacteria, allowing a cost effective screen for the best species for use in synbiotic products to allow better survival and efficacy.

Flesh colour dominates consumer preference for chicken

Existing research investigating interactions between visual and oral sensory cues has tended to use model food systems. In contrast, this study compared product quality assessments of corn-fed and wheat-fed chicken products among persons recruited in Northern Ireland. Three approaches have been adopted to investigate the effect of colour upon consumer choice of chicken: sensory assessment under normal lighting; focus group discussion; and sensory assessment under controlled lighting conditions. Initial consumer sensory assessment indicated that wheat-fed chicken was perceived to be tenderer and to have a more intense flavour than that which was corn-fed. Qualitative enquiry discerned that this was because consumers perceived the yellow colour of corn-fed chicken negatively. Yellow-coloured corn-fed chicken was therefore again compared with wheat-fed chicken in terms of flavour, texture and overall liking with the flesh colour disguised by means of controlled lighting. Quality ratings for corn-fed chicken were more positive when the yellow flesh colour was disguised, with corn-fed chicken judged to be tenderer than wheat-fed chicken and more flavoursome. This study illustrates the importance of using a combination of methods to gain insight into interactions between different sensory modalities in consumer quality judgements and adds to previous research on the importance of colour upon consumer choice of real foods. (c) 2005 Elsevier Ltd. All rights reserved.

Organic and conventional fertilizer effects on a tritrophic interaction: parasitism, performance and preference of Cotesia vestalis

Interest in sustainable farming methods that rely on alternatives to conventional synthetic fertilizers and pesticides is increasing. Sustainable farming methods often utilize natural populations of predatory and parasitic species to control populations of herbivores, which may be potential pest species. We investigated the effects of several types of fertilizer, including those typical of sustainable and conventional farming systems, on the interaction between a herbivore and parasitoid. The effects of fertilizer type on percentage parasitism, parasitoid performance, parasitoid attack behaviour and responses to plant volatiles were examined using a model Brassica system, consisting of Brassica oleracea var capitata, Plutella xylostella (Lepidoptera) larvae and Cotesia vestalis (parasitoid). Percentage parasitism was greatest for P. xylostella larvae feeding on plants that had received either a synthetic ammonium nitrate fertilizer or were unfertilized, in comparison to those receiving a composite fertilizer containing hoof and horn. Parasitism was intermediate on plants fertilized with an organically produced animal manure. Male parasitoid tibia length showed the same pattern as percentage parasitism, an indication that offspring performance was maximized on the treatments preferred by female parasitoids for oviposition. Percentage parasitism and parasitoid size were not correlated with foliar nitrogen concentration. The parasitoids did not discriminate between hosts feeding on plants in the four fertilizer treatments in parasitoid behaviour assays, but showed a preference for unfertilized plants in olfactometer experiments. The percentage parasitism and tibia length results provide support for the preference–performance hypothesis

Reduced face preference in infancy: a developmental precursor to callous-unemotional traits?

Background Children with callous-unemotional (CU) traits, a proposed precursor to adult psychopathy, are characterized by impaired emotion recognition, reduced responsiveness to others’ distress, and a lack of guilt or empathy. Reduced attention to faces, and more specifically to the eye region, has been proposed to underlie these difficulties, although this has never been tested longitudinally from infancy. Attention to faces occurs within the context of dyadic caregiver interactions, and early environment including parenting characteristics has been associated with CU traits. The present study tested whether infants’ preferential tracking of a face with direct gaze and levels of maternal sensitivity predict later CU traits. Methods Data were analyzed from a stratified random sample of 213 participants drawn from a population-based sample of 1233 first-time mothers. Infants’ preferential face tracking at 5 weeks and maternal sensitivity at 29 weeks were entered into a weighted linear regression as predictors of CU traits at 2.5 years. Results Controlling for a range of confounders (e.g., deprivation), lower preferential face tracking predicted higher CU traits (p = .001). Higher maternal sensitivity predicted lower CU traits in girls (p = .009), but not boys. No significant interaction between face tracking and maternal sensitivity was found. Conclusions This is the first study to show that attention to social features during infancy as well as early sensitive parenting predict the subsequent development of CU traits. Identifying such early atypicalities offers the potential for developing parent-mediated interventions in children at risk for developing CU traits.

Preference reversals for ambiguity aversion

This paper finds preference reversals in measurements of ambiguity aversion, even if psychological and informational circumstances are kept constant. The reversals are of a fundamentally different nature than the reversals found before because they cannot be explained by context-dependent weightings of attributes. We offer an explanation based on Sugden's random-reference theory, with different elicitation methods generating different random reference points. Then measurements of ambiguity aversion that use willingness to pay are confounded by loss aversion and hence overestimate ambiguity aversion.

Sensory and consumer science methods used with older adults: a review of current methods and recommendations for the future

Capturing the sensory perception and preferences of older adults, whether healthy or with particular disease states, poses major methodological challenges for the sensory community. Currently a vastly under researched area, it is at the same time a vital area of research as alterations in sensory perception can affect daily dietary food choices, intake, health and wellbeing. Tailored sensory methods are needed that take into account the challenges of working with such populations including poor access leading to low patient numbers (study power), cognitive abilities, use of medications, clinical treatments and context (hospitals and care homes). The objective of this paper was to review current analytical and affective sensory methodologies used with different cohorts of healthy and frail older adults, with focus on food preference and liking. We particularly drew attention to studies concerning general ageing as well as to those considering age-related diseases that have an emphasis on malnutrition and weight loss. Pubmed and Web of Science databases were searched to 2014 for relevant articles in English. From this search 75 papers concerning sensory acuity, 41 regarding perceived intensity and 73 relating to hedonic measures were reviewed. Simpler testing methods, such as directional forced choice tests and paired preference tests need to be further explored to determine whether they lead to more reliable results and better inter-cohort comparisons. Finally, sensory quality and related quality of life for older adults suffering from dementia must be included and not ignored in our future actions.

Self-concept clarity and compulsive Internet use: the role of preference for virtual interactions and employment status in British and North-American samples

Background and Aims Compulsive Internet Use (CIU) describes a maladaptive relationship with the Internet characterised by loss of control and conflict. Although also affecting adults, most studies use teenage samples, and theoretical development on risk factors is scarce. According to Davis (2001), the social connectivity function of the Internet is key in identifying traits associated with CIU. Since Self-Concept Clarity (SCC) is strongly related to social anxiety, and virtual interactions allow “self-edition”, we hypothesized that individuals low in SCC could choose virtual interactions as safer alternative to satisfy their social needs. This could in turn increase the risk of CIU. Building on a previous study, we also expected CIU to be more harmful in the unemployed. Methods We collected samples from the UK (N = 532) and US (N = 502) with equal distribution of employed and unemployed individuals. We ran Measurement Invariance tests to confirm that the constructs were equivalent across countries. Subsequently, we conducted mediation and moderation analysis to test our hypothesis with Multigroup Confirmatory Factor Analysis. Results Measurement Invariance was confirmed. The relationship between SCC and CIU was partially mediated by preference of virtual interactions in both countries. This preference was significantly related to lower social support. Short term unemployment seemed to accentuate the negative impact of CIU on life satisfaction in both countries, although only marginally significantly in the US. The unemployed reported significantly lower levels of life satisfaction. Conclusion We demonstrated that SCC is a key vulnerability factor to CIU in adults, and confirmed the additional risks for the unemployed.

Women's experiences of two different self-assessment methods for monitoring fetal movements in full-term pregnancy : a crossover trial

Background: Low maternal awareness of fetal movements is associated with negative birth outcomes. Knowledge regarding pregnant women's compliance with programs of systematic self-assessment of fetal movements is needed. The aim of this study was to investigate women's experiences using two different self-assessment methods for monitoring fetal movements and to determine if the women had a preference for one or the other method. Methods: Data were collected by a crossover trial; 40 healthy women with an uncomplicated full-term pregnancy counted the fetal movements according to a Count-to-ten method and assessed the character of the movements according to the Mindfetalness method. Each self-assessment was observed by a midwife and followed by a questionnaire. A total of 80 self-assessments was performed; 40 with each method. Results: Of the 40 women, only one did not find at least one method suitable. Twenty of the total of 39 reported a preference, 15 for the Mindfetalness method and five for the Count-to-ten method. All 39 said they felt calm, relaxed, mentally present and focused during the observations. Furthermore, the women described the observation of the movements as safe and reassuring and a moment for communication with their unborn baby. Conclusions: In the 80 assessments all but one of the women found one or both methods suitable for self-assessment of fetal movements and they felt comfortable during the assessments. More women preferred the Mindfetalness method compared to the count-to-ten method, than vice versa.