Miracle-dz/UniFAR-FTUs huggingface dataset:
The R/sub a/*-tree: an improved R*-tree with materialized data for supporting range queries on OLAP-data

OLAP applications make use of fast indexes and materialization of data. Most research treats just one topic. Either the materialized values or the design of index structures are considered. The paper examines a possible combination of both techniques. The R* tree is taken as an example of a multidimensional index structure. Aggregated data is stored in the inner nodes of the index structure in addition to the references to the successor nodes. We describe how this mechanism works in detail and present results of performance evaluation.
Multiple Choice Strategy For PSO Algorithm - Performance Analysis On Shifted Test Functions

A new promising strategy for the PSO (Particle swarm optimization) algorithm is proposed and described in this paper. This new strategy presents alternative way of assigning new velocity to each individual in particle swarm (population). This new multiple choice particle swarm optimization (MC-PSO) algorithm is tested on two different shifted test functions to show the performance on problems that are not constant in time. The promising results of this alternative strategy are compared with the not modified PSO version.
Evidence for a Symmetrical Requirement for Rab5-GTP in in Vitro Endosome-Endosome Fusion*

Early endosome fusion, which has been extensively characterized using an in vitro reconstitution assay, is Rab5-dependent. To examine the requirement for Rab5 on both fusion partners, we prepared cytosol and endosomes depleted of Rab5. Unlike control cytosol, Rab5-depleted cytosol was only marginally active in the in vitro endosome fusion. However, fusion could be restored by the addition of wild-type Rab5 or Rab5 D136N, a mutant whose nucleotide specificity favors xanthine over guanine. The addition of Rab5 D136N restored fusion only in the presence of XTP. In the absence of XTP or in the presence of XDP, Rab5 D136N failed to restore fusion. When fusion was carried out with endosomal vesicles depleted of Rab GTPases (by preincubation of vesicles with GDP dissociation inhibitor), together with cytosol immunodepleted of Rab5, fusion was virtually absent. We then used immunodepleted cytosol and GDP dissociation inhibitor-treated vesicles to determine whether Rab5 is required by both fusion partners. Using separate sets of endosomal vesicles, we found that priming both sets of Rab5-depleted vesicles with Rab5 Q79L, a GTPase-defective mutant, substantially stimulated endosome fusion. Priming one set of vesicles with Rab5 Q79L and a second set of vesicles with Rab5 S34N failed to activate fusion. When both sets of Rab5-depleted vesicles were primed with Rab5 D136N supplemented with XTP, endosome fusion was stimulated, similar to that observed with Rab5 Q79L. However, when one set of vesicles was preincubated with Rab5 D136N plus XTP and the second set with Rab5 D136N and XDP, no stimulation of fusion was observed. We conclude that Rab5-GTP is required on both fusion partners for docking and fusion of early endosomes. To confirm the fusion of Rab5-GTP-positive vesiclesin vivo, we expressed GFP-Rab5 Q79L in fibroblasts and observed fusion of Rab5-positive vesicles. We failed to record fusion of Rab5-positive vesicles with Rab5-negative vesicles. We conclude that Rab5-GTP is required on both sets of endosomes for fusion in vitro and in living cells.
Path-Reduced Costs for Eliminating Arcs in Routing and Scheduling

In many branch-and-price algorithms, the column generation pricing problem consists of computing feasible paths in a network. In this paper, we show how, in this context, path-reduced costs can be used to remove some arcs from the underlying network without compromising optimality, and we introduce a bidirectional search technique to compute these reduced costs. This arc elimination method can lead to a substantial speedup of the pricing process and the overall branch-and-price algorithm. Special attention is given to variants of shortest-path problems with resource constraints. Computational results obtained for the vehicle routing problem with time windows show the efficiency of the proposed method.
Social Influence and Network Effects in the Diffusion of a Healthcare Information Exchange System

The current paper analyzes the diffusion of a Healthcare Information Exchange system. We analyze 2.25 million Emergency Room referrals in seven hospitals during three years since the deployment of the system. We find that social learning within hospitals is a good predictor of physicians’ decisions to use the new system. Similarly, the existence of data on the system, a type of network effects, is also significantly associated with system usage. The paper contributes by addressing both social-influence and indirect-network-effects and testing their effects empirically. We also show that social influence is much stronger than network effects, as can be expected in the strong professional culture of healthcare. Thus, healthcare organizations that deploy technology should focus on social and organizational influence and invest only gradually in populating data in systems and networks.
A Quantitative Analysis of WCAG 2.0 Compliance For Some Indian Web Portals

Web portals have served as an excellent medium to facilitate user centric services for organizations irrespective of the type, size, and domain of operation. The objective of these portals has been to deliver a plethora of services such as information dissemination, transactional services, and customer feedback. Therefore, the design of a web portal is crucial in order that it is accessible to a wide range of user community irrespective of age group, physical abilities, and level of literacy. In this paper, we have studied the compliance of WCAG 2.0 by three different categories of Indian web sites which are most frequently accessed by a large section of user community. We have provided a quantitative evaluation of different aspects of accessibility which we believe can pave the way for better design of web sites by taking care of the deficiencies inherent in the web portals.
Identifying and Classifying Value Propositions in Brand Tweets - a Study of Top-10 coffee Brands

Brand owners have increasingly adopted social media for propositioning the values of products and services. This work scrutinizes the nature of ‘values’ embedded in the tweets as propositioned by brand owners. We extract and analyse the tweets (658 of them) posted by the owners of the top-10 coffee chains in a period of three months (August to October of 2015) for their value propositions. This paper identifies 16 different categories of values propositioned by brands. Using consumption value theory as the theoretical basis, the value categories are grouped into four broader category themes (functional, emotional, social and epistemic). The presence of values in a tweet is classified using content analysis undertaken by 4 independent raters. Our analysis of values in tweets reveals that a) different types of values exist in tweets and there are significant differences between values embedded in tweets (independent of brands), b) brands differ in the values they embed within the tweets and c) the presence of certain values stimulates user interests more than others (e.g. through retweeting or liking a tweet). The paper discusses these results in detail along with the implications of the results for marketing practice.
Fusion Strategies for Robust Speech Recognition and Keyword Spotting for Channel- and Noise-Degraded Speech

Recognizing speech under high levels of channel and/or noise degradation is challenging. Current state-of-the-art automatic speech recognition systems are sensitive to changing acoustic conditions, which can cause significant performance degradation. Noise-robust acoustic features can improve speech recognition performance under varying background conditions, where it is usually observed that robust modeling techniques and multiple system fusion can help to improve the performance even further. This work investigates a wide array of robust acoustic features that have been previously used to successfully improve speech recognition robustness. We use these features to train individual acoustic models, and we analyze their individual performance. We investigate and report results for simple feature combination, feature-map combination at the output of convolutional layers, and fusion of deep neural nets at the senone posterior level. We report results for speech recognition on a large-vocabulary, noiseand channel-degraded Levantine Arabic speech corpus distributed through the Defense Advance Research Projects Agency (DARPA) Robust Automatic Speech Transcription (RATS) program. In addition, we report keyword spotting results to demonstrate the effect of robust features and multiple levels of information fusion.
Breast pumps as an incentive for breastfeeding: a mixed methods study of acceptability

Abstract Increasing breastfeeding rates would improve maternal and child health, but multiple barriers to breastfeeding persist. Breast pump provision has been used as an incentive for breastfeeding, although effectiveness is unclear. Women's use of breast pumps is increasing and a high proportion of mothers express breastmilk. No research has yet reported women's and health professionals' perspectives on breast pumps as an incentive for breastfeeding. In the Benefits of Incentives for Breastfeeding and Smoking cessation in pregnancy (BIBS) study, mixed methods research explored women's and professionals' views of breast pumps as an incentive for breastfeeding. A survey of health professionals across Scotland and North West England measured agreement with ‘a breast pump costing around £40 provided for free on the NHS’ as an incentive strategy. Qualitative interviews and focus groups were conducted in two UK regions with a total of 68 participants (pregnant women, new mothers, and their significant others and health professionals) and thematic analysis undertaken. The survey of 497 health professionals found net agreement of 67.8% (337/497) with the breast pump incentive strategy, with no predictors of agreement shown by a multiple ordered logistic regression model. Qualitative research found interrelated themes of the ‘appeal and value of breast pumps’, ‘sharing the load’, ‘perceived benefits’, ‘perceived risks’ and issues related to ‘timing’. Qualitative participants expressed mixed views on the acceptability of breast pumps as an incentive for breastfeeding. Understanding the mechanisms of action for pump type, timing and additional support required for effectiveness is required to underpin trials of breast pump provision as an incentive for improving breastfeeding outcomes. © 2016 The Authors. Maternal & Child Nutrition published by John Wiley & Sons Ltd.
Computing Mel-frequency cepstral coefficients on the power spectrum

We present a method to derive Mel-frequency cepstral coefficients directly from the power spectrum of a speech signal. We show that omitting the filterbank in signal analysis does not affect the word error rate. The presented approach simplifies the speech recognizers front end by merging subsequent signal analysis steps into a single one. It avoids possible interpolation and discretization problems and results in a compact implementation. We show that frequency warping schemes like vocal tract normalization can be integrated easily in our concept without additional computational efforts. Recognition test results obtained with the RWTH large vocabulary speech recognition system are presented for two different corpora: The German VerbMobil II dev99 corpus, and the English North American Business News 94 20k development corpus.
Edaphic and light conditions of sympatric plant morphotypes in western Amazonia

Abstract Here I present a dataset of edaphic and light conditions associated with the occurrence of sympatric morphotypes of Geonoma macrostachys (Arecaceae/Palmae), a candidate case study from Amazonia hypothesized to have evolved under ecological speciation. Transects were established in three lowland rainforests in Peru, and the abundance of each local morphotype of this species was recorded in a total area of 4.95 hectares. Composite soil samples and hemispherical photographs were taken along the transects were the species occurred to obtain information on soil nutrients, soil texture, and indirect measurements of light availability. The raw and summary tables disclose the characteristics of each study site and habitats within them, which could be useful to soil scientists, ecologists, and conservationists engaged in similar research activities or meta-analyses in Amazonia.
Efficient quantum algorithms for computing class groups and solving the principal ideal problem in arbitrary degree number fields

This paper gives polynomial time quantum algorithms for computing the ideal class group (CGP) under the Generalized Riemann Hypothesis and solving the principal ideal problem (PIP) in number fields of arbitrary degree. These are are fundamental problems in number theory and they are connected to many unproven conjectures in both analytic and algebraic number theory. Previously the best known algorithms by Hallgren [20] only allowed to solve these problems in quantum polynomial time for number fields of constant degree. In a recent breakthrough, Eisentrager et al. [11] showed how to compute the unit group in arbitrary fields, thus opening the way to the resolution of CGP and PIP in the general case. For example, Biasse and Song [3] pointed out how to directly apply this result to solve PIP in classes of cyclotomic fields of arbitrary degree. The methods we introduce in this paper run in quantum polynomial time in arbitrary classes of number fields. They can be applied to solve other problems in computational number theory as well including computing the ray class group and solving relative norm equations. They are also useful for ongoing cryptanalysis of cryptographic schemes based on ideal lattices [5, 10]. Our algorithms generalize the quantum algorithm for computing the (ordinary) unit group [11]. We first show that CGP and PIP reduce naturally to the computation of S-unit groups, which is another fundamental problem in number theory. Then we show an efficient quantum reduction from computing S-units to the continuous hidden subgroup problem introduced in [11]. This step is our main technical contribution, which involves careful analysis of the metrical properties of lattices to prove the correctness of the reduction. In addition, we show how to convert the output into an exact compact representation, which is convenient for further algebraic manipulations.
Capacidad organizacional en la implementación de sistemas computarizados. Casos: Propilven y LUZ FM 102.9

Este articulo presenta los resultados de dos estudios de caso en Venezuela: En el primero, se estudio el proceso de implementacion del Sistema de Control Distribuido (SCD) en la empresa de resinas Propilven,S.A. y, en el segundo, la implementacion del Sistema de Audio Digital (SAD) en la emisora radial LUZ FM 102.9. El objetivo del estudio es analizar la capacidad organizacional (CO) a lo largo del proceso de implementacion, y su rol en la creacion de competencias para el uso efectivo de las tecnologias mencionadas. La estrategia metodologica implico: definir el corpus del estudio; extraer de cada caso los resultados referidos a la relacion planteada en el objetivo; sistematizar la data; analisis de resultados y elaboracion de conclusiones. Los casos muestran como en estas empresas no se crearon las competencias para el uso efectivo de la tecnologia, al no producirse una integracion efectiva de la nueva tecnologia a los procesos internos de la empresa. La investigacion da soporte a la teoria acerca de la importancia de ciertas rutinas organizacionales para la integracion efectiva de nuevos conocimientos al interior de la firma. La implementacion de sistemas computarizados debe entenderse como un proceso de desarrollo de competencias organizacionales el cual abarca: 1) el proceso de construir la base de conocimiento, 2) el proceso de adquirir conocimiento complementario y 3) el proceso de integrar conocimiento basico y complementario. Se concluye que el proceso de integrar conocimiento basico y complementario en la implementacion de tecnologias requiere el despliegue de un conjunto de rutinas organizacionales claramente estructuradas para alinear sistemas tecnicos, destrezas, estrategia y mercado.
Robust Nonlinear Predictive Controller for Permanent-Magnet Synchronous Motors With an Optimized Cost Function

A robust nonlinear predictive controller for permanent-magnet synchronous motors is proposed. The nonlinear predictive control law is formulated by optimizing a novel cost function. A key feature of the proposed control is that it does not require the knowledge of the external perturbation and parameter uncertainties to enhance the robustness. A zero steady-state error is guaranteed by an integral action of the controller. The stability of the closed-loop system is ensured by convergence of the output-tracking error to the origin. The proposed control strategy is verified via simulation and experiment. High performance with respect to speed tracking and current control of the motor has been demonstrated.
GeT Move : An Efficient and Unifying Spatio-Temporal Pattern Mining System for Moving Objects

Recent improvements in positioning technology has led to a much wider availability of massive moving object data. A crucial task is to find the moving objects that travel together. Usually, these object sets are called spatio-temporal patterns. Analyzing such data has been applied in many real world applications, e.g., in ecological study, vehicle control, mobile communication management, etc. However, few data mining tools are available for flexible and scalable analysis of massive scale moving object data. The main reason is that there is no a unifying approach to manage the patterns while many different kinds of spatio-temporal patterns have been proposed in recent years. Each approach only focuses on mining a specific kind of pattern. Our system, GeT Move, is designed to extract and manage different spatio-temporal patterns concurrently. A user-friendly interface is provided to facilitate interactive exploration of mining results. Since GeT Move is tested on many kinds of real data sets, it will benefit users to carry out versatile analysis on these kinds of data by exhibiting different kinds of patterns at the same time.
Qualitative social research: a risky business when it comes to collecting ‘sensitive’ data

Qualitative researchers are compelled to use their personal judgements before, during and after interviews, particularly when their interview subjects are drawn from vulnerable groups. This paper discusses the dilemmas qualitative researchers encounter when collecting data that is ethically ‘sensitive’; and situates the discussion in the realm of the Australian Occupational Health & Safety (OH&S) legislative requirement of ‘duty of care’ using the Rapidly Degenerative Neurological Diseases Pilot Program in Western Australia as the case example. The paper is focussed upon the practicalities and ethical concerns of the researchers conducting qualitative data collections. The discussion seeks to provide practical reflections on lessons learned and suggestions for self-care practice for researchers in the field and calls for policies that instruct and protect them.
Online Kernel-Based Classification Using Adaptive Projection Algorithms

The goal of this paper is to derive a novel online algorithm for classification in reproducing kernel hilbert spaces (RKHS) by exploiting projection-based adaptive filtering tools. The paper brings powerful convex analytic and set theoretic estimation arguments in machine learning by revisiting the standard kernel-based classification as the problem of finding a point which belongs to a closed halfspace (a special closed convex set) in an RKHS. In this way, classification in an online setting, where data arrive sequentially, is viewed as the problem of finding a point (classifier) in the nonempty intersection of an infinite sequence of closed halfspaces in the RKHS. Convex analysis is also used to introduce sparsification arguments in the design by imposing an additional simple convex constraint on the norm of the classifier. An algorithmic solution to the resulting optimization problem, where new convex constraints are added every time instant, is given by the recently introduced adaptive projected subgradient method (APSM), which generalizes a number of well-known projection-based adaptive filtering algorithms such as the classical normalized least mean squares (NLMS) and the affine projection algorithm (APA). Under mild conditions, the generated sequence of estimates enjoys monotone approximation, strong convergence, asymptotic optimality, and a characterization of the limit point. Further, we show that the additional convex constraint on the norm of the classifier naturally leads to an online sparsification of the resulting kernel series expansion. We validate the proposed design by considering the adaptive equalization problem of a nonlinear channel, and by comparing it with classical as well as with recently developed stochastic gradient descent techniques.
Assessing the impact of wind variability on the long-term operation of a hydro-dominated system

Hydro-dominated systems are characterized by uncertainty on the inflows to the reservoirs. Driven by both technological advances and environmental awareness, the share of renewables in the energy production mix has been increasing over the past decades. However, due to their intermittent nature, the integration of renewables entails additional uncertainty, which may negatively impact the operation of the system if the overall risk is not properly appraised. This work analyzes the impact of short-term wind variability on the long-term operation of a hydro-dominated power system based upon two risk measure approaches, namely (i) chance constrained programming, and (ii) conditional value-at-risk. Both approaches are formulated under the framework of stochastic dual dynamic programming. The proposals are tested on a portion of the Colombian power system, in the presence of wind energy and storage units.