Miracle-dz/UniFAR-FTUs huggingface dataset:
“GROw”ing up: tweenagers' involvement in family decision making

Purpose – Practitioners in particular have noted that kids are growing older younger (KGOY) and academic research has in parallel shown that children are becoming more involved in the final stages of purchase decisions, albeit in a limited number of product categories studied. This paper aims to investigate this market.Design/methodology/approach – This quantitative and qualitative study examines the relatively under‐researched, but increasingly important, tweenager market across a number of product categories and the extent to which ten to 12 year olds are involved in the final stages of purchase decision making. Further to this, the paper considers whether a liberal versus traditional approach to decisions made within the family (gender role orientation (GRO)) affects the degree of involvement.Findings – The findings suggest that GRO is indeed a factor in family decision making but that the relationship is far from a simple one. The authors posit why perceptions of involvement are sometimes inconsistent.
An evaluation of the active labour market programmes in Sweden

The low unemployment rates traditionally enjoyed by Sweden have often been attributed to the country’s extensive system of active labour market programmes, which have thus often been regarded as a model for other countries to emulate. The paper investigates the presence of short- and long-term treatment effects on a number of outcomes, including employment and unemployment benefit collection. Special attention is devoted to subsequent outcomes experienced by former participants, in particular to their job attachment and their performance should they fall back into unemployment. Finally, the distinctive feature of the Swedish labour market policy, whereby participation in programmes renews eligibility to generous unemployment compensation, is investigated in relation to the incentives it is likely to create to keep cycling between compensated unemployment spells and programme participation. The approach used is propensity score matching, with some additional analyses trying to account for a partially unobserved outcome variable due to misclassification problems in the data. Joining a programme as opposed to waiting longer in open unemployment appears on average to have a positive dynamic effect on participants’ employment rates. The overall findings indicate however that the human capital-enhancing component of the programmes may not always be strong enough to outcompete the work disincentives provided by the system. Furthermore, even when cycling has been ruled out by focusing on individuals observed to exit their unemployment spell, programmes are found to have no effect on any of the outcomes considered.
Towards a Silent Speech Interface for Portuguese - Surface Electromyography and the Nasality Challenge

A Silent Speech Interface (SSI) aims at performing Automatic Speech Recognition (ASR) in the absence of an intelligible acoustic signal. It can be used as a human-computer interaction modality in high-backgroundnoise environments, such as living rooms, or in aiding speech-impaired individuals, increasing in prevalence with ageing. If this interaction modality is made available for users own native language, with adequate performance, and since it does not rely on acoustic information, it will be less susceptible to problems related to environmental noise, privacy, information disclosure and exclusion of speech impaired persons. To contribute to the existence of this promising modality for Portuguese, for which no SSI implementation is known, we are exploring and evaluating the potential of state-of-the-art approaches. One of the major challenges we face in SSI for European Portuguese is recognition of nasality, a core characteristic of this language Phonetics and Phonology. In this paper a silent speech recognition experiment based on Surface Electromyography is presented. Results confirmed recognition problems between minimal pairs of words that only differ on nasality of one of the phones, causing 50% of the total error and evidencing accuracy performance degradation, which correlates well with the exiting knowledge.
New technique for feature selection: Combination between elastic net and relief

One of the most advanced forms of industrial maintenance is predictive maintenance. Indeed, the present analysis of the behavior of a material helps to predict future behavior. The analysis is also used to predict the nature of the failure and to minimize the delay in the fault detection. So as the diagnosis of faults in rotating machines is an important subject in order to increase their productivity and reliability, the choice of features to be used for classification and diagnosis constitutes a crucial point. The use of all the possible features will cause an increase in the computational cost and it will even lead to the increase of the classification error because of the existence of redundant and non-significant features. In this context, we are interested in presenting different methods of feature selection and proposing a new approach that tends to select the best features among existing ones and perform the classification-identification using the selected features. The evaluation of the proposed technique is done using real signals from a rotating machine.
Event-detection in sensor fields by adaptive distributed computations

Consider a sensor-field deployed to detect intrusions into a security zone, with each sensor monitoring more than one site. We develop an efficient inference algorithm for determining, from the sensor readings, the most probable set of locations where intrusions have occurred. With N potential points of intrusion, there are 2 * *N subsets of points where intrusions could occur, and searching by direct enumeration is not a scalable method. We present an adaptive distributed algorithm that drastically reduces the computational effort by several orders of magnitude by partitioning the problem into virtual ‘computational domains’, where the domains are adapted to the actual sensor readings. The algorithm either finds a provably optimal global solution, or provides a bound on the deviation of the solution from optimality. Its effectiveness is demonstrated on two examples that model several hundred locations being monitored for intrusion, with the possibility of multiple simultaneous breaches. In effect, our distributed approach makes it feasible to solve much larger intrusion-detection problems than can be solved by a centralized algorithm.
Modeling aspects for power conversion locomotive transformers

This paper aims to present the currently mostly used models of such transformers as well as new models under study, in the frame of a long term agreement of our university with some of the known specialized industries. Two AC models based on two different philosophies are presented, as well as a third one describing the transformer used as inductance in DC mode. Typical cases are taken as examples to illustrate the application domain of these transformers.
Visual Scaffolding in Integrated Spatial and Nonspatial Analysis

Collaborative visual analytics that feature mixtures of spatial and nonspatial data occur across disciplines, and are particularly common in bioinformatics, neuroscience and geospatial analysis. In this work we analyze, from a human-centric perspective, data collected from the design and evaluation of three successful visual analysis tools, spanning seven case studies. We focus on the importance of the users’ background to the design process, and we discuss the importance of visual scaffolding to such collaborative, integrated spatial and nonspatial visual analysis tools. Scaffolding is a psychology concept which denotes the support given during a learning process. We further present evidence that spatial and nonspatial coordinated views can serve as a form of visual scaffolding for expert-level, collaborative visual analyses
Mapping perceived depth to regions of interest in stereoscopic images

The usable perceived depth range of a stereoscopic 3D display is limited by human factors considerations to a defined range around the screen plane. There is therefore a need in stereoscopic image creation to map depth from the scene to a target display without exceeding these limits. Recent image capture methods provide precise control over this depth mapping but map a single range of scene depth as a whole and are unable to give preferential stereoscopic representation to a particular region of interest in the scene. A new approach to stereoscopic image creation is described that allows a defined region of interest in scene depth to have an improved perceived depth representation compared to other regions of the scene. For example in a game this may be the region of depth around a game character, or in a scientific visualization the region around a particular feature of interest. To realize this approach we present a novel algorithm for stereoscopic image capture and describe an implementation for the widely used ray-tracing package POV-Ray. Results demonstrate how this approach provides content creators with improved control over perceived depth representation in stereoscopic images.
Fast and correct performance recovery of operating systems using a virtual machine monitor

Rebooting an operating system is a final but effective recovery technique. However, the system performance largely degrades just after the reboot due to the page cache being lost in the main memory. For fast performance recovery, we propose a new reboot mechanism called the warm-cache reboot. The warm-cache reboot preserves the page cache during the reboot and enables an operating system to restore it after the reboot, with the help of a virtual machine monitor (VMM). To perform correct recovery, the VMM guarantees that the reused page cache is consistent with the corresponding files on disks. We have implemented the warm-cache reboot mechanism in the Xen VMM and the Linux operating system. Our experimental results showed that the warm-cache reboot decreased performance degradation just after the reboot. In addition, we confirmed that the file cache corrupted by faults was not reused. The overheads for maintaining cache consistency were not usually large.
A Common Variant of Endothelial Nitric Oxide Synthase (Glu298Asp) Is an Independent Risk Factor for Carotid Atherosclerosis

Background and Purpose— Endothelium-derived NO is formed from l-arginine by endothelial NO synthase (eNOS) encoded by the NOS 3 gene on chromosome 7. Because several studies have indicated that NO plays a key role in the development of the atherosclerotic process, we investigated whether common variants in the eNOS gene are associated with an increased risk of plaque on carotid arteries. Methods— We studied 375 subjects attending the hypertension center of our institution to be screened for arterial hypertension. The examined subjects were classified according to the presence of carotid plaques (intima-media thickness ≥1.5 mm), and 2 intronic (CA and 27-bp repeats) polymorphisms and 1 exonic (Glu298Asp) polymorphism of the eNOS gene were explored. Results— Only the Glu298Asp polymorphism of eNOS was associated with the presence of carotid plaques (P <0.05). In particular, there was an excess of homozygotes for the Asp298 variant among subjects with carotid plaques, whereas the number of subjects who had the Glu298 allele in exon 7 of the eNOS gene was equally distributed in both study groups. Interestingly, the risk of having carotid plaques was increased ≈3 times in subjects who were homozygotic for the Asp298 variant compared with subjects who were homozygotic for the Glu298 variant and was independent of the other common risk factors (age, blood pressure, and smoking). Conclusions— Homozygosity for Asp298, a common variant of the eNOS gene, is an independent risk factor for carotid atherosclerosis in this study population.
The influence of Semantic Roles in QA: A comparative analysis

Los conjuntos de preguntas utilizados normalmente para evaluar los sistemas de busqueda de respuestas (BR) estan principalmente constituidos por preguntas cuyas respuestas son entidades nombradas (NE), por tanto, la mayoria de estos sistemas usan reconocedores de entidades para extraer las posibles respuestas. Ultimamente, el etiquetado de roles semanticos y su contribucion a la BR es un tema de especial interes. Sin embargo, los sistemas basados en NEs siempre funcionaran mejor que los basados en roles a la hora de extraer respuestas para preguntas cuya respuesta sea una NE. El objetivo de este articulo es evaluar ambos metodos para preguntas de lugar bajo las mismas condiciones, usando, no solo preguntas basadas en nombres propios sino tambien basadas en nombres comunes. Para ello se presentan tres propuestas diferentes de un modulo de extraccion de respuestas embebidas en un sistema de BR: una basada en entidades nombradas y dos basadas en roles semanticos. Los resultados obtenidos indican que mientras la propuesta de NE contesta mejor las preguntas basadas en nombres propios (+49,57% MRR), las propuestas de roles obtienen los mejores resultados en las preguntas basadas en nombres comunes (+223,48% MRR) siendo sus resultados de una precision mas alta para ambos tipos de preguntas.
Steady-State Analysis for Multiserver Queues Under Size Interval Task Assignment in the Quality-Driven Regime

We study the steady-state behavior of multiserver queues with general job size distributions under size interval task assignment SITA policies. Assuming Poisson arrivals and the existence of the αth moment of the job size distribution for some α > 1, we show that if the job arrival rate and the number of servers increase to infinity with the traffic intensity held fixed, the SITA policy parameterized by α minimizes in a large deviation sense the steady-state probability that the total number of jobs in the system is greater than or equal to the number of servers. The optimal large deviation decay rate can be arbitrarily close to the one for the corresponding probability in an infinite-server queue, which only depends on the system traffic intensity but not on any higher moments of the job size distribution. This supports in a many-server asymptotic framework the common wisdom that separating large jobs from small jobs protects system performance against job size variability.
Carrier independent localization techniques for GSM terminals

Exactly determining the geographical position of a telecommunication device is an open research challenge for the personal and mobile communications community. In this paper we explore the terminal localization problem in a GSM system, and we develop a set of carrier independent solutions. Specifically, we introduce four different techniques, all based on the 6-strongest cells traditionally used in the GSM standard. Through extensive simulations we show that our technique can achieve remarkable results without requiring any additional equipment in the core network or the mobile devices.
The Effects of Housing Assistance on Labor Supply: Evidence from a Voucher Lottery

This study estimates the effects of means-tested housing programs on labor supply using data from a randomized housing voucher wait-list lottery in Chicago. Evidence for the net effects of housing programs on labor supply is central to a wide range of policy decisions about how to provide housing assistance to the poor. Economic theory is ambiguous about the expected sign of any labor supply response. We find that among working-age, able-bodied adults, housing voucher use reduces quarterly labor force participation rates by 4 percentage points (6 percent of the control complier mean) and quarterly earnings by $285 (10 percent), and increases social program participation rates by 2 percentage points (16 percent of the control mean). These impacts are toward the lower end of the range of recent estimates from other studies of housing programs, but nonetheless do still imply that housing vouchers reduce labor supply.
Analyzing bandung public mood using Twitter data

Nowadays, the number of internet users in Indonesia is increasing rapidly. This condition leads to possibility to use and analyze the data gathered from the internet users to show the big picture of the specific condition in certain region. Currently, there are some research on analyzing public mood, such as happy, sad, anger, fear, and neutral. The analysis itself consists of mood classification and topic clustering. However, there is still difficulty to find the best combination of algorithm and feature in the mood classification and topic clustering. In this paper, we propose to compare several algorithms, namely preprocessing (url elimination, word normalization, and stop words elimination), attribute selection (CfsSubsetEval and ClassifierSubsetEval), classification algorithm (Naive Bayes Classifier and Support Vector Machine), and clustering algorithm (EM and simple k-means), to find the best results. Experiments have been done by using 949 tweets from Bandung data. The best classification result was 89.04%, achieved by the combination of using normalization in the preprocessing, CfsSubsetEval in the attribute selection and Naïve Bayes algorithm.
Using Multi-Instance Hierarchical Clustering Learning System to Predict Yeast Gene Function

Time-course gene expression datasets, which record continuous biological processes of genes, have recently been used to predict gene function. However, only few positive genes can be obtained from annotation databases, such as gene ontology (GO). To obtain more useful information and effectively predict gene function, gene annotations are clustered together to form a learnable and effective learning system. In this paper, we propose a novel multi-instance hierarchical clustering (MIHC) method to establish a learning system by clustering GO and compare this method with other learning system establishment methods. Multi-label support vector machine classifier and multi-label K-nearest neighbor classifier are used to verify these methods in four yeast time-course gene expression datasets. The MIHC method shows good performance, which serves as a guide to annotators or refines the annotation in detail.
ICT ’ s Approaches to HTD and Tracking at TDT 2004

This is ICT’s first year of participation in the TDT evaluation. We participate in two tasks: Hierarchical Topic Detection (HTD) and Tracking. The two systems are both based on vector-space model. We use the method of multi-layered clustering to produce directed acyclic graph (DAG) of topics and improve the performance using the technology of traditional detection task. We only implement a baseline system for the tracking task. Our preprocessor of text help reduce the tracking cost.
2 1 2 N ov 2 00 1 Resonant normal forms as constrained linear systems

We show that a nonlinear dynamical system in Poincaré-Dulac normal form (in R) can be seen as a constrained linear system; the constraints are given by the resonance conditions satisfied by the spectrum of (the linear part of) the system and identify a naturally invariant manifold for the flow of the “parent” linear system. The parent system is finite dimensional if the spectrum satisfies only a finite number of resonance conditions, as implied e.g. by the Poincaré condition. In this case our result can be used to integrate resonant normal forms, and sheds light on the geometry behind the classical integration method of Horn, Lyapounov and Dulac.
Admixed Phylogenetic Distribution of Drug Resistant Mycobacterium tuberculosis in Saudi Arabia

Background The phylogeographical structure of Mycobacterium tuberculosis is generally bimodal in low tuberculosis (TB) incidence countries, where genetic lineages of the isolates generally differ with little strain clustering between autochthonous and foreign-born TB patients. However, less is known on this structure in Saudi Arabia—the most important hub of human migration as it hosts a total population of expatriates and pilgrims from all over the world which is equal to that of its citizens. Methodology We explored the mycobacterial phylogenetic structure and strain molecular clustering in Saudi Arabia by genotyping 322 drug-resistant clinical isolates collected over a 12-month period in a national drug surveillance survey, using 24 locus-based MIRU-VNTR typing and spoligotyping. Principal Findings In contrast to the cosmopolitan population of the country, almost all the known phylogeographic lineages of M. tuberculosis complex (with noticeable exception of Mycobacterium africanum/West-African 1 and 2) were detected, with Delhi/CAS (21.1%), EAI (11.2%), Beijing (11.2%) and main branches of the Euro-American super-lineage such as Ghana (14.9%), Haarlem (10.6%) and Cameroon (7.8%) being represented. Statistically significant associations of strain lineages were observed with poly-drug resistance and multi drug resistance especially among previously treated cases (p value of < = 0.001 for both types of resistance), with relative over-representation of Beijing strains in the latter category. However, there was no significant difference among Saudi and non-Saudi TB patients regarding distribution of phylogenetic lineages (p = 0.311). Moreover, 59.5% (22/37) of the strain molecular clusters were shared between the Saudi born and immigrant TB patients. Conclusions Specific distribution of M. tuberculosis phylogeographic lineages is not observed between the autochthonous and foreign-born populations. These observations might reflect both socially favored ongoing TB transmission between the two population groups, and historically deep-rooted, prolonged contacts and trade relations of the peninsula with other world regions. More vigorous surveillance and strict adherence to tuberculosis control policies are urgently needed in the country.
Objective Assessment of an Ionic Footbath (IonCleanse): Testing Its Ability to Remove Potentially Toxic Elements from the Body

Ionic footbaths are often used in holistic health centres and spas to aid in detoxification; however, claims that these machines eliminate toxins from the body have not been rigorously evaluated. In this proof-of-principle study, we sought to measure the release of potentially toxic elements from ionic footbaths into distilled and tap water with and without feet. Water samples were collected and analyzed following 30-minute ionic footbath sessions without feet using both distilled (n = 1) and tap water (n = 6) and following four ionic footbaths using tap water (once/week for 4 weeks) in six healthy participants. Urine collection samples were analyzed at four points during the study. Hair samples were analyzed for element concentrations at baseline and study conclusion. Contrary to claims made for the machine, there does not appear to be any specific induction of toxic element release through the feet when running the machine according to specifications.