Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality assessment of ten fusion techniques applied on Worldview-2

Abstract Fusion or merging or pansharpening is the digital processing that combines the high spatial and multispectral information to obtain a fused multispectral image that retains the spatial information from the high resolution panchromatic image, as well as the spectral characteristics of the lower resolution multispectral image. Many fusion algorithms were developed and tested on different commercial satellite data such as Ikonos and Quickbird, however, the efficacy of these algorithms is weakly assessed on the new satellite images of Worldview-2 with very high spatial resolution. In the present study ten well known fusion techniques namely Color Normalized (CN), Ehlers, Gram-Schmidt, High Pass Filter (HPF), Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Modified IHS (Modihs), Pansharp, PCA and Wavelet are used for the fusion of Worldview-2 panchromatic and multispectral data. Fused images were evaluated for spectral and spatial fidelity using visual inspection and different quality indexes such as the correlation coefficient (CC), ERGAS, the Universal Image Quality Index (Q), the Expanded Quality Index (Q4expand) and the Entropy values. Under each quality metric the fusion algorithms were ranked and best performances were indentified. It has been proved that all fusion algorithms have a different performance with the new multispectral bands of Worldview-2 in comparison to the classical ones. It has also been proved that almost all quality indices present a very strong dependency to the spatial resolution of the input data. The Q4expand quality index is proposed as the main quality discriminator since it gave the most robust results independently of the spectral and spatial input resolution. Pansharp algorithm took the lead in spatial enhancement while Ehlers and HPF are ranked in the first places for spectral preservation.
The SmartTer for ELROB 2006 - a Vehicle for Fully Autonomous Navigation and Mapping in Outdoor Environments

The goal of our participation ELROB 2006 is to show fully autonomous navigation and 3D mapping in outdoor setting. Our robots is based on a standard Smart car that has been equipped with five distance laser sensors, three cameras, a differential GPS and an Inertial Measurement Unit (IMU) and four computers. The car’s systems states are directly accessed through the can bus. Localization and Navigation is realized by fusing all available sensory information in a probabilistic way. This enables us for high precision localization and dynamic local and global path planning. Using the 3D point clouds extracted from the rotating lasers and the omnidirectional image the smartTer is able to consistently register the 3D Maps and Analyze the Scene for regions of interest.
DO HOUSEHOLDS FULLY SHARE RISK? EVIDENCE FROM GHANA

Intrahousehold analyses provide new insights into how households make economic decisions. Much of the work in economics has traditionally treated the household as a single economic actor, but a number of studies are providing evidence that the dynamics among household members affect the outcomes of household economic decisions. This paper contributes to our understanding of such models by incorporating the variability of individual incomes into the analysis of intrahousehold resource allocations, using detailed household survey data from Ghana.
A Multi-FAceted ApproAch to reFerence resolution in english And russiAn

This paper argues that the detection and resolution of referring expressions can be profitably distributed across modules of a language processing system, rather than being bunched at the end of a text analysis pipeline. The approach is being implemented within the OntoAgent cognitive architecture, which supports the development of multi-functional, language-endowed agents that can collaborate with people in task-oriented applications. Although current development within OntoAgent orients around English, the architecture itself and most of its knowledge bases are language-independent. Drawing upon my past descriptive work on reference and ellipsis in Russian, I will suggest how the same reference resolution strategies might be applied to this and other languages. More generally, I will motivate the need to approach linguistic phenomena in a holistic paradigm, rather than as highly compartmentalized subtasks, which has become the norm for natural language processing applications.
Document classification with supervised latent feature selection

The classification of text documents to categories generally deals with large dimensionality of a structured representation of the documents. To favor generality over accuracy of the classifier some dimensionality reduction technique has to be applied. In the text we present classification algorithm that utilize hidden structures of uncorrelated topics extracted from training documents and their known categories not necessarily independent. The classifier is capable to include various methods of hidden feature selection. Three latent feature selection procedures are proposed and tested.
Info-concierge: Proactive multi-modal interaction through mind probing

To close the wide gap between the exploding information world and individual human knowledge, we have investigated a multi-modal interaction strategy called Mind Probing in which a system proactively acts on the user and then estimates his/her internal state by analyzing his/her reaction. We have also developed a system, Info-concierge, that can probe the latent interest of the user, make him/her aware of it, and proactively provide sensible information. The system uses the core techniques of Mind Probing through speech and gaze recognition. In this paper, we present the interaction flow, the core techniques, and a field trial of Info-concierge.
Early termination of a two‐stage study to develop and validate a panel of biomarkers

Two‐stage designs to develop and validate a panel of biomarkers present a natural setting for the inclusion of stopping rules for futility in the event of poor preliminary estimates of performance. We consider the design of a two‐stage study to develop and validate a panel of biomarkers where a predictive model is developed using a subset of the samples in stage 1 and the model is validated using the remainder of the samples in stage 2. First, we illustrate how we can implement a stopping rule for futility in a standard, two‐stage study for developing and validating a predictive model where samples are separated into a training sample and a validation sample. Simulation results indicate that our design has type I error rate and power similar to the fixed‐sample design but with a substantially reduced sample size under the null hypothesis. We then illustrate how we can include additional interim analyses in stage 2 by applying existing group sequential methodology, which results in even greater savings in the number of samples required under both the null and the alternative hypotheses. Our simulation results also illustrate that the operating characteristics of our design are robust to changes in the underlying marker distribution. Copyright © 2012 John Wiley & Sons, Ltd.
Dinâmica de inflação e custo do trabalho no Brasil: Uma abordagem novo-keynesiana pelo modelo de valor presente

This paper derives and estimate a structural model to describe inflation dynamics using a standard new Keynesian Phillips curve(NKPC), where the driving force is the real marginal cost of the firm(NKPC-cost), as proposed by Gali and Gerter(1999). The original contribution of this paper is to provide an estimation for this model for the Brazilian economy, adopting the present value methodology, inspired on the works of Campbell and Shiller(1987) and Sbordone (1999), instead of the usual estimation by GMM. The estimation results show that the degree of rigidity obtained is in line with the expected behavior of firms in the Brazilian economy. In addition, the structural parameter, that measures the sensitivity of inflation to the real marginal cost, is also in line with results obtained by Gali e Gertler (1999), Gali, Gertler e Salido (2001) e Sbordone(1999). The results also show that the increase in labor productivity decreases the degree of rigidity of the economy, increasing the frequency of price adjustments by the firms. Finally, the model does not provide good results on inflation forecasting, where the predicted inflation path has significant higher variance than the actual path.
Land-Use Controls, Natural Restrictions, and Urban Residential Land Prices

Research has focused on how variations in land-use controls explain interurban variations in prices. With the notable exception of the work by Rose (1989a, 1989b), virtually no attention has been focused on how natural restrictions (bodies of water, mountains, etc.) impact land prices. The purpose of this paper is to examine the impact of both land-use controls and natural restrictions on interurban variation in residential land prices. Our results indicate that, as expected, land prices are significantly higher as the land supply decreases both as a result of natural and man-made restrictions.
Option Pricing under Unknown Volatility: An Agent-Based Modeling and Simulation Approach

We modeled an artificial European option market with unknown volatility using an agent-based modeling and simulation approach. Contrary to the standard Black and Scholes model with "known" volatility, there is significant pricing bias (market price/theoretical price) in the presence of unknown volatility. Moreover, the unknown drift has a significant nonlinear effect in the pricing bias. Finally, pricing bias tends to decrease as the drift increasing in the case of low volatility. Our approach may serve as a first step towards the goal of option pricing in disequilibrium with unknown volatility.
Books Cited in Wikipedia: Possibility to Use Their Nippon Decimal Classification Categories for Book Recommendation

This paper investigated the effectiveness of developing a book recommendation system based on books cited in Wikipedia articles, focusing on their Nippon Decimal Classification (NDC). Among 95,194 articles, 28,154 cited books showing ISBNs in their bibliographies. In many cases, all NDCs of books cited in each article were identical and thus consistent. Such articles can be used for automatic assignment of NDCs.
Control of a new structure of twin wind turbine

The control of a new concept of the twin wind turbines is presented in this paper. This structure has two identical wind turbines, ridden on the same tower. The two wind turbines drive two identical permanent magnet synchronous generators (PMSG), and they can pivot face the wind without using the yaw actuator. The control of the full system including the mechanical and electrical parts is ensured respectively by a proportional integral PI and the nonlinear Backstepping. The first one is used to control the yaw angle rotation in order to keep the structure faces the wind. The second one is designed to control the electrical generators to optimize the power. The model of the twin wind turbine and the control strategy are implemented in Matlab/Simulink software.
Detection of Alzheimer's disease signature in MR images seven years before conversion to dementia: Toward an early individual prognosis

Finding very early biomarkers of Alzheimer's Disease (AD) to aid in individual prognosis is of major interest to accelerate the development of new therapies. Among the potential biomarkers, neurodegeneration measurements from MRI are considered as good candidates but have so far not been effective at the early stages of the pathology. Our objective is to investigate the efficiency of a new MR‐based hippocampal grading score to detect incident dementia in cognitively intact patients. This new score is based on a pattern recognition strategy, providing a grading measure that reflects the similarity of the anatomical patterns of the subject under study with dataset composed of healthy subjects and patients with AD. Hippocampal grading was evaluated on subjects from the Three‐City cohort, with a followup period of 12 years. Experiments demonstrate that hippocampal grading yields prediction accuracy up to 72.5% (P < 0.0001) 7 years before conversion to AD, better than both hippocampal volume (58.1%, P = 0.04) and MMSE score (56.9%, P = 0.08). The area under the ROC curve (AUC) supports the efficiency of imaging biomarkers with a gain of 8.4 percentage points for hippocampal grade (73.0%) over hippocampal volume (64.6%). Adaptation of the proposed framework to clinical score estimation is also presented. Compared with previous studies investigating new biomarkers for AD prediction over much shorter periods, the very long followup of the Three‐City cohort demonstrates the important clinical potential of the proposed imaging biomarker. The high accuracy obtained with this new imaging biomarker paves the way for computer‐based prognostic aides to help the clinician identify cognitively intact subjects that are at high risk to develop AD. Hum Brain Mapp 36:4758–4770, 2015. © 2015 Wiley Periodicals, Inc.
Presidential Address: Discount Rates

Discount-rate variation is the central organizing question of current asset-pricing research. I survey facts, theories, and applications. Previously, we thought returns were unpredictable, with variation in price-dividend ratios due to variation in expected cashflows. Now it seems all price-dividend variation corresponds to discount-rate variation. We also thought that the cross-section of expected returns came from the CAPM. Now we have a zoo of new factors. I categorize discount-rate theories based on central ingredients and data sources. Incorporating discount-rate variation affects finance applications, including portfolio theory, accounting, cost of capital, capital structure, compensation, and macroeconomics.
Root structure and functioning for efficient acquisition of phosphorus: Matching morphological and physiological traits.

BACKGROUND Global phosphorus (P) reserves are being depleted, with half-depletion predicted to occur between 2040 and 2060. Most of the P applied in fertilizers may be sorbed by soil, and not be available for plants lacking specific adaptations. On the severely P-impoverished soils of south-western Australia and the Cape region in South Africa, non-mycorrhizal species exhibit highly effective adaptations to acquire P. A wide range of these non-mycorrhizal species, belonging to two monocotyledonous and eight dicotyledonous families, produce root clusters. Non-mycorrhizal species with root clusters appear to be particularly effective at accessing P when its availability is extremely low. SCOPE There is a need to develop crops that are highly effective at acquiring inorganic P (Pi) from P-sorbing soils. Traits such as those found in non-mycorrhizal root-cluster-bearing species in Australia, South Africa and other P-impoverished environments are highly desirable for future crops. Root clusters combine a specialized structure with a specialized metabolism. Native species with such traits could be domesticated or crossed with existing crop species. An alternative approach would be to develop future crops with root clusters based on knowledge of the genes involved in development and functioning of root clusters. CONCLUSIONS Root clusters offer enormous potential for future research of both a fundamental and a strategic nature. New discoveries of the development and functioning of root clusters in both monocotyledonous and dicotyledonous families are essential to produce new crops with superior P-acquisition traits.
A Fast Custom Instructions Identification Algorithm based on Basic Convex Pattern Model for Supporting ASIP Automated Design

To improve the computation efficiency of application specific instruction-set processor (ASIP), a strategy of hardware/software collaborative design is usually utilized. In this process, the auto-customization of instruction set has always been a key part to support the automated design of ASIP. The key issue of this problem is how to effectively reduce the huge exponential exploration space in the instruction identification process. To address this issue, we first formulate it as a sub-graph enumeration problem under multi-constraints, and then propose a fast instruction identification algorithm based on basic convex pattern (BCP) model. The kernel technique in this algorithm is the transformation from the graph exploration to the formula-based computations. Experimental results have indicated that the proposed algorithm has a distinct reduction on the execution time.
A survey on stability analysis of discrete-time piecewise affine systems

Abstract Piecewise affine (PWA) systems are useful models for describing nonlinear and hybrid systems. They also result from LTI systems subject to constrained optimal control. Recently stability analysis of PWA systems has received increased interest since it can help to obtain explicit feedback control laws of low complexity (Grieder et al. , 2003 b ; Grieder and Morari, 2003; Grieder et al. , 2004). A wide range of methods with varying degrees of conservativeness are available, for analyzing stability of PWA systems. This survey introduces the most promising existing methods and adapts them to discrete-time PWA systems. Specifically, we investigate the computation of common quadratic, common quartic, piecewise affine, piecewise quadratic and piecewise quartic Lyapunov functions using linear programming, semi-definite programming and sum-of-squares techniques. Subsequently, the different methods are compared regarding the likelihood of finding a certificate of stability and computation run time. The objective is to provide the reader with a practical ‘recipe' for analyzing PWA systems. To this end, an extensive case study is performed.
Understanding users' experience of interaction

The design of the user experience has increasingly become a goal in developing interactive systems during the last years. Since then, several attempts have been made to broaden interactive system design's traditional focus on the efficient achievement of goals to better understand additional aspects that contribute to user experience. In this paper, I first give an overview of different approaches that have taken this development into account. Based on this review I present an integrative model of user experience. This model emphasizes a combined investigation of traditional and additional quality aspects like hedonics and aesthetics. Moreover their interaction with affect and emotions as an important part of user experience are pronounced. Thus, in next steps, this theoretical basis will be used to develop a framework for user experience evaluation.
Evaluation in Multi-Site Programs

This paper discusses the problem of evaluating and predicting the treatment impact of a program that is implemented at multiple sites. Two issues arise: is information from other sites relevant in estimating the impact at a given site? and how can we account for predictive uncertainty in the site effects? Using data from the Greater Avenues for Independence evaluation, I develop a hierarchical model for earnings which allows both for site effects and for smoothing the estimated impact across sites. I show that the degree to which the estimated impact is smoothed across sites does not affect the estimate; i.e. most of the differences across sites are due to differences in the composition of participants. Second I show that predictive uncertainty regarding site effects is important; for example, when the predictive uncertainty regarding site effects is ignored, the treatment impact at the Riverside sites is significant, but when we consider predictive uncertainty, the impact for the Riverside sites is insignificant. Third, I show that the hierarchical model is able to extrapolate site effects with reasonable accuracy when the site for which the prediction is being made does not differ substantially from the sites already observed. For example, the San Diego treatment effects could have been predicted based on observable site characteristics, but the Riverside effects are consistently underestimated.
Temporal logic and semidirect products: an effective characterization of the until hierarchy

We reveal an intimate connection between semidirect products of finite semigroups and substitution of formulas in linear temporal logic. We use this connection to obtain an algebraic characterization of the 'until' hierarchy of linear temporal logic; the k-th level of that hierarchy is comprised of all temporal properties that are expressible by a formula of nesting depth at most k in the 'until' operator. Applying deep results from finite semigroup theory we are able to prove that each level of the until hierarchy is decidable.
On the duality of strong convexity and strong smoothness : Learning applications and matrix regularization

We show that a function is strongly convex with respect to some norm if and only if its conjugate function is strongly smooth with respect to the dual norm. This result has already been found to be a key component in deriving and analyzing several learning algorithms. Utilizing this duality, we isolate a single inequality which seamlessly implies both generalization bounds and online regret bounds; and we show how to construct strongly convex functions over matrices based on strongly convex functions over vectors. The newly constructed functions (over matrices) inherit the strong convexity properties of the underlying vector functions. We demonstrate the potential of this framework by analyzing several learning algorithms including group Lasso, kernel learning, and online control with adversarial quadratic costs.
Subspace Clustering of High Dimensional Data Streams

In this paper, SOStream, which is a novel algorithm of clustering over high dimensional online data stream is presented, it is based on subspace. -SOStream partitions the data space into grids, and maintains a superset of all dense units in an online way. A deterministic lower and upper bound of the selectivity of each maintained units are also given. With the maintained potential dense units, SOStream is capable of discovering the clusters in different subspaces over high dimensional data stream with arbitrary shape. The experimental results on real and synthetic datasets demonstrate the effectivity of the approach.
A method for the design of parallel algorithms a case study: solving triangular systems

This paper illustrates a method for the design of parallel programs that is based on the separation of computation and coordination. We use Gamma programs to specify computations and show how to prove their correctness using a UNITY-like programming logic. A separate coordination language is used to determine behavioural aspects of the program. We illustrate how behaviour can be structured through a process of successive stepwise refinements. Reasoning about refinement is supported formally by two types of simulation. As an illustration of our method we study the problem of solving triangular systems of linear equations. For this problem we derive a number of known algorithms and show how they are related by our refinement ordering.