Miracle-dz/UniFAR-FTUs huggingface dataset:
An Analysis of Bayesian Classiiers Probabilistic Approaches to Induction

In this paper we present an average-case analysis of the Bayesian classiier, a simple induction algorithm that fares remarkably well on many learning tasks. Our analysis assumes a monotone conjunc-tive target concept, and independent, noise-free Boolean attributes. We calculate the probability that the algorithm will induce an arbitrary pair of concept descriptions and then use this to compute the probability of correct classiication over the instance space. The analysis takes into account the number of training instances, the number of attributes , the distribution of these attributes, and the level of class noise. We also explore the be-havioral implications of the analysis by presenting predicted learning curves for artiicial domains, and give experimental results on these domains as a check on our reasoning. One goal of research in machine learning is to discover principles that relate algorithms and domain characteristics to behavior. To this end, many researchers have carried out systematic experimentation with natural and artiicial domains in search of empirical regularities (e.g., Kibler & Langley, 1988). Others have focused on theoretical analyses, often within the paradigm of probably approximately correct learning (e.g., Haus-sler, 1990). However, most experimental studies are based only on informal analyses of the learning task, whereas most formal analyses address the worst case, and thus bear little relation to empirical results. A third approach, proposed by Cohen and Howe (1988), involves the formulation of average-case models for speciic algorithms and testing them through experimentation. Pazzani and Sarrett's (1990) study of conjunctive learning provides an excellent example of this technique, as does Hirschberg and Pazzani's (1991) work on inducing k-CNF concepts. By assuming information about the target concept, the num-Also aaliated with RECOM Technologies y Also aaliated with Sterling Software. ber of attributes, and the class and attribute frequencies , they obtain predictions about the behavior of induction algorithms and used experiments to check their analyses. 1 However, their research does not focus on algorithms typically used by the experimental and practical sides of machine learning, and it is important that average-case analyses be extended to such methods. Recently, there has been growing interest in proba-bilistic approaches to inductive learning. For example, Fisher (1987) has described Cobweb, an incremental algorithm for conceptual clustering that draws heavily on Bayesian ideas, and the literature reports a number of systems that build on this work (e. have outlined Auto-Class, a nonincremental system that uses Bayesian methods to cluster instances into …
Learning Deep Latent Space for Multi-Label Classification

Multi-label classification is a practical yet challenging task in machine learning related fields, since it requires the prediction of more than one label category for each input instance. We propose a novel deep neural networks (DNN) based model, Canonical Correlated AutoEncoder (C2AE), for solving this task. Aiming at better relating feature and label domain data for improved classification, we uniquely perform joint feature and label embedding by deriving a deep latent space, followed by the introduction of label-correlation sensitive loss function for recovering the predicted label outputs. Our C2AE is achieved by integrating the DNN architectures of canonical correlation analysis and autoencoder, which allows end-to-end learning and prediction with the ability to exploit label dependency. Moreover, our C2AE can be easily extended to address the learning problem with missing labels. Our experiments on multiple datasets with different scales confirm the effectiveness and robustness of our proposed method, which is shown to perform favorably against state-of-the-art methods for multi-label classification.
Regulatory Reform in the Wake of the Financial Crisis of 2007-2008

Purpose - The purpose of this paper is to analyse regulatory reform in the wake of the financial crisis of 2007-2008. Design/methodology/approach - The paper proposes a framework for regulatory reform that begins with the observation that financial manias and panics cannot be legislated away, and may be an unavoidable aspect of modern capitalism. Findings - Financial crises are unavoidable when hardwired human behavior – fear and greed, or “animal spirits” – is combined with free enterprise, and cannot be legislated or regulated away. Like hurricanes and other forces of nature, market bubbles, and crashes cannot be entirely eliminated, but their most destructive consequences can be greatly mitigated with proper preparation. In fact, the most damaging effects of financial crisis come not from loss of wealth, but rather from those who are unprepared for such losses and panic in response. This perspective has several implications for the types of regulatory reform needed in the wake of the financial crisis of 2007-2008, all centered around the need for greater transparency, improved measures of systemic risk, more adaptive regulations, including counter-cyclical leverage constraints, and more emphasis on financial literacy starting in high school, including certifications for expertise in financial engineering for the senior management and directors of all financial institutions. Originality/value - The paper stresses how we must resist the temptation to react too hastily to market events, and deliberate thoughtfully and broadly, instead, craft new regulations for the financial system of the twenty-first century. Financial markets do not need more regulation; they need smarter and more effective regulation.
West Antarctic Surface Mass Balance: Do Synoptic Scale Modes of Climate Contribute to Observed Variability?

West Antarctic Surface Mass Balance: Do Synoptic Scale Modes of Climate Contribute to Observed Variability? McLean K. Carpenter Department of Geological Sciences, BYU Master of Science Western Antarctica has been experiencing significant warming for at least the past fifty years. While higher Net Surface Mass Balance (SMB) over West Antarctica during this period of warming is expected, SMB reconstructions from ice cores reveal a more complex pattern during the period of warming. The mechanisms giving rise to SMB variability over the West Antarctic Ice Sheet (WAIS) are not well understood due to lack of instrumental data. The Southern Annular Mode (SAM) and El Nino Southern Oscillation (ENSO) are believed to contribute to WAIS SMB variability but the assumption has not been rigorously tested. SMB during years where SAM and ENSO are in extreme phases is compared to average SMB from the period 1979-2010. Additionally, atmospheric circulation anomalies are used to assess what circulation patterns accompany extreme modes of climate during the same period. The results suggest that significantly lower SMB occurs when SAM is in an extremely positive phase or ENSO is in an extremely negative phase. Additionally, atmospheric circulation anomalies show that certain circulation patterns accompany extreme modes of climate, which contribute to SMB variability over the WAIS. Ultimately, the location of low and high pressure cells is the best predictor for extreme accumulation events over the WAIS. These results are verified by assessing observed net SMB trends from a network of firn cores located from the central WAIS. Seven new firn cores are added to improve the spatial network of regional net SMB measurements. Reconstructed net SMB is calculated from new firn core records, and compared to the existing cores. The new suite of preliminary firn core records show the same significant decreasing trend that is observed in existing cores. This represents a negative regionwide SMB trend that is likely in part due to trends in SAM and ENSO.
Specification by Reformulation: A Paradigm for Building Integrated User Support Environments

Specification by reformulation is a general interface paradigm. It is an abstraction of retrieval by reformulation, a paradigm used in previous systems for assisting users in formulating database queries. Specification by reformulation serves as a general foundation upon which domain specific applications can be built. To illustrate its usage, we describe three services built within it: a database retrieval aid, a notecards facility, and an electronic-mail interface to an on-line procurement system. Building systems in this way illustrates the concept of an integrated user support environment - a set of cooperating tools for end users that can be extended by application builders.
Verification of the stomatal conductance of Nebbiolo grapevine

Abstract: Wine is one of the most important Italian export products, and Nebbiolo is one of the most respected Italian grapes. In the summer of 2007, a measurement campaign was carried out in a Nebbiolo vineyard located in Vezza d’Alba, near Cuneo, Italy. Using a gauge of trade gases and some other instruments, we recorded the stomatal conductance and also some physiological parameters useful for estimating the dependence of stomatal conductance on environmental variables. The goal of this experiment was improving the parameterization of grapevine evapotranspiration through the assessment of the stomatal conductance and, in particular, of the functional dependence of the stomatal conductance on the following variables: the photosynthetically active radiation, the atmospheric temperature, the atmospheric moisture deficit, and the carbon dioxide concentration. The observations allowed us to check and, in some cases, to adapt the existing general parameterizations found in literature. The results showed some significant differences with the existing parameterizations concerning the atmospheric temperature, the atmospheric moisture deficit, and the carbon dioxide concentration. The parameterizations obtained in this experiment, although referring to a specific plant and site (namely the Nebbiolo at Vezza d’Alba), could allow assessment of the best environmental conditions under which the Nebbiolo grapevine production is the best, and in future could be tested for other grapevines or climates.
ITS: An Efficient Limited-Memory Heuristic Tree Search Algorithm

This paper describes a new admissible tree search algorithm called Iterative Threshold Search (ITS). ITS can be viewed as a much-simplified version of MA* [1], and a generalized version of MREC [12]. We also present the following results: 1. Every node generated by ITS is also generated by IDA*, even if ITS is given no more memory than IDA*. In addition, there are trees on which ITS generates O(N) nodes in comparison to O(N log N) nodes generated by IDA*, where N is the number of nodes eligible for generation by A*. 2. Experimental tests show that if the node-generation time is high (as in most practical problems), ITS can provide significant savings in both number of node generations and running time. Our experimental results also suggest that in the average case both IDA* and ITS are asymptotically optimal on the traveling salesman problem. not common enough
Trends and Drivers of Tax Effort: International Empirical Evidence

This paper aims to identify the tax effort and its macroeconomic determinants in a sample composed of 13 countries from the MENA region and European countries using a set of macroeconomic variables considered by previous studies. This study employs two empirical methods to capture tax effort, and to analyze macroeconomic determinants of tax effort. Firstly, the paper uses a panel-stochastic frontier method to identify the tax effort and inefficiency term. Then, it uses a panel data regression model to analyze the determinants of tax effort in the years between 2005 to 2013. However, the selected sample includes two groups; the first group involves 6 European countries known with their high tax collections and low corruption. And the second group contains 7 developing countries with low tax collections and high corruption levels from the MENA region. The main findings of the study indicate that trade openness, inflation, and corruption are vital determinants for tax effort in sample countries. It is also found that developed countries have a higher tax effort than developing countries in general. However, Algeria has the most efficient tax administration with more than 98% tax effort, while Jordan is the least efficient among sample countries with 75% tax effort.
Estimation on semi-functional linear errors-in-variables models

Abstract Semi-functional linear regression models are important in practice. In this paper, their estimation is discussed when function-valued and real-valued random variables are all measured with additive error. By means of functional principal component analysis and kernel smoothing techniques, the estimators of the slope function and the non parametric component are obtained. To account for errors in variables, deconvolution is involved in the construction of a new class of kernel estimators. The convergence rates of the estimators of the unknown slope function and non parametric component are established under suitable norm and conditions. Simulation studies are conducted to illustrate the finite sample performance of our method.
Visual preferences for a coastal landscape including oil and gas development

Siting of oil and gas facilities can disrupt the visual quality of coastal landscapes. However, some views of coastal oil and gas development were considered to be attractive by residents and visitors interviewed on a Louisiana Gulf Coast island. These views tended to include development that was tidy, created a night-time light display, blended into the larger landscape, or generated interesting activity. Descriptions of 393 views from the island and ratings of the attractiveness of the views were obtained in 40 interviews. Landscape feature presence and feature attractiveness in each view were determined in a content analysis. For the 99 features identified, attractiveness frequencies and variances were determined. A factor analysis of feature presence classifications identified features that tended to appear together in the landscape. Factor scores were then regressed on view attractiveness ratings. Both the attractiveness frequencies and the regression equation indicate that oil and gas development is not always seen as unattractive. 24 references, 2 figures, 4 tables.
Distribution-aware sampling and weighted model counting for sat

Given a CNF formula and a weight for each assignment of values to variables, two natural problems are weighted model counting and distribution-aware sampling of satisfying assignments. Both problems have a wide variety of important applications. Due to the inherent complexity of the exact versions of the problems, interest has focused on solving them approximately. Prior work in this area scaled only to small problems in practice, or failed to provide strong theoretical guarantees, or employed a computationally-expensive most-probable-explanation (MPE) queries that assumes prior knowledge of a factored representation of the weight distribution. We identify a novel parameter, tilt, which is the ratio of the maximum weight of satisfying assignment to minimum weight of satisfying assignment and present a novel approach that works with a black-box oracle for weights of assignments and requires only an NP-oracle (in practice, a SAT-solver) to solve both the counting and sampling problems when the tilt is small. Our approach provides strong theoretical guarantees, and scales to problems involving several thousand variables. We also show that the assumption of small tilt can be significantly relaxed while improving computational efficiency if a factored representation of the weights is known.
REACHING THE POOR: SOME OBSERVATIONS ON FORMAL AND INFORMAL CREDIT IN HAITI

The article traces the evolution of credit to the poor in Haiti, mainly from the 1950s to the present Two phases may be distinguished. The first one, characterized on the one hand by the dominance of informal lenders and on the other by unsuc cessful efforts sponsored by the government to reach the peasant majority, extends from the beginning of the 1950s until the end of the 1970s. This was a period of fail ure from the point of view of formal credit, with a number of institutions that lent little to the needy and which had to be closed down for financial reasons. The second period, from the beginning of the 1980s to the present time, has seen the evolution of a new institutional framework: that of organized micro credits, mainly in urban areas, beginning in the capital and gradually extending into provincial towns as well. This approach is much more promising than the old one, and possibly it can be extended ito rural areas as well.
A Novel Change Detection Method for Multitemporal Hyperspectral Images Based on Binary Hyperspectral Change Vectors

Hyperspectral (HS) images provide a dense sampling of target spectral signatures. Thus, they can be used in a multitemporal framework to detect and discriminate between different kinds of fine spectral change effectively. However, due to the complexity of the problem and the limited amount of multitemporal images and reference data, only a few works in the literature addressed change detection (CD) in HS images. In this paper, we present a novel method for unsupervised multiple CD in multitemporal HS images based on a discrete representation of the change information. Differently from the state-of-the-art methods, which address the high dimensionality of the data using band reduction or selection techniques, in this paper, we focus our attention on the representation and exploitation of the change information present in each band. After a band-by-band pixel-based subtraction of the multitemporal images, we define the hyperspectral change vectors (HCVs). The change information in the HCVs is then simplified. To this end, the radiometric information of each band is separately analyzed to generate a quantized discrete representation of the HCVs. This discrete representation is explored by considering the hierarchical nature of the changes in HS images. A tree representation is defined and used to discriminate between different kinds of change. The proposed method has been tested on a simulated data set and two real multitemporal data sets acquired by the Hyperion sensor over agricultural areas. Experimental results confirm that the discrete representation of the change information is effective when used for unsupervised CD in multitemporal HS data.
Discrete-time adaptive iterative learning control with incorporation of a priori process knowledge

This work explores utilization of a priori model knowledge to achieve better control performance of iterative learning control systems. Two specific discrete-time adaptive iterative learning control approaches are proposed for different control cases to exactly utilize known information in order to improve control performance. In more detail, a novel time-difference estimator based discrete-time adaptive iterative learning control system is proposed for a time-invariant parametric uncertain system, and a mixed-difference estimator based discrete-time adaptive iterative learning control is proposed for a hybrid parametric uncertain system. Both of these control methods are shown to perform well even though the initial states and the reference trajectories vary randomly along the iteration direction. We show that superior control performance can be achieved compared with the existing iteration-difference estimator based discrete-time adaptive iterative learning control systems by applying the two proposed control methods, which fully utilize known information about the model. Mathematical proof and a simulation study on a permanent magnet linear motor verify the efficiency of the proposed discrete-time adaptive iterative learning control approaches.
Improving the absorption of solar cells using antenna‐inspired cavities

We present new types of nanocavities to improve the absorption of solar cells for energy harvesting in wide frequency ranges of the optical spectrum. Using a full‐wave approach, as opposed to the commonly used ray‐based modeling of the light, antenna‐inspired cavities with horn shapes are proposed and introduced. The effectiveness of the designed cavities is demonstrated in comparison to the conventional textures involving inverted pyramids and nanocones. Highly accurate numerical results show that solar‐cell structures with horn‐type cavities can provide excellent absorbance rates, even without using any matching layer.
Quaderni Del Dipartimento Di Economia Politica E Statistica

An original dataset referring to a medium-sized Italian university is implemented for analyzing the determinants of scientific research production at individual level. Three different indicators, based on the number of publications and/or citations, are considered. Their distributions are highly skewed, displaying an excess of zero-valued observations, thus zero-inflated and hurdle regression models are introduced. Among them, the Hurdle Negative Binomial model exhibits a good fitting and appears to be reasonably coherent with the underlying generating data process. Indeed, the performance of active researchers is described by the count component of the model, while the odds to be in a non-active status is modelled by the zero component. Individual characteristics, teaching and administrative activities, as well as the features of the department the researcher belongs to, are considered as explanatory variables. The analysis of the results highlights that scientific productivity is lower for oldest active researchers, and that there is a significant effect of academic position on research production. Evidence of clear-cut and significant substitution or complementarity effect between teaching and research activities is not found. Indeed, a major teaching load does not apparently affect the odds to be a non-active researcher, while it has mixed and very weak effects on publication performance of active researchers. A negative relationship among productivity and administrative tasks is highlighted. Finally, the analysis points out the effects of department composition on both the odds to be non-active and the value of the production indicators of active researchers.
Post-print version : Multivariable PID control with setpoint weighting via BMI optimisation

Here, a methodology is presented which considers the interpolation of LTI controllers designed for different operating points of a nonlinear system in order to produce a gain-scheduled controller. Guarantees of closed-loop quadratic stability and performance at intermediate interpolation points are presented in terms of a set of LMIs. The proposed interpolation scheme can be applied in cases where the system must remain at the operating points most of the time and the transitions from one point to another rarely occur, e.g. chemical processes, satellites.
EFFECTS OF THE ATMOSPHERIC AEROSOL ON THE OPTICAL PROPERTIES OF CLOUD

The work is focussed o n the role that pre-cloud aerosol (number concentration and spectral dispersion) plays in cloud reflectivity. Rural and marine ae rosols have been d escribed b y lognormal aerosol size distributions, and the c loud condensation nu clei were obtained b ased on Abdul-Razzak's activation p arameterisation. Cloud albedo including dispersion in the scattering asymmetry factor and specified aerosol properties has been estimated. The sensitivity of cloud albedo to changes in cloud d roplet number concentration in connection to the changes in liquid water content and the cloud droplet effective radius has been investigated. For the same liquid water path, clouds over rural areas have more and smaller cloud droplets and thus a higher cloud albedo than marine clouds.