Miracle-dz/UniFAR-FTUs huggingface dataset:
Normalized cuts clustering with prior knowledge and a pre-clustering stage

Clustering is of interest in cases when data are not labeled enough and a prior training stage is unfeasible. In particular, spectral clustering based on graph partitioning is of interest to solve problems with highly non-linearly separa- ble classes. However, spectral methods, such as the well-known normalized cuts, involve the computation of eigenvectors that is a highly time-consuming task in case of large data. In this work, we propose an alternative to solve the normalized cuts problem for clustering, achieving same results as conventional spectral meth- ods but spending less processing time. Our method consists of a heuristic search to find the best cluster binary indicator matrix, in such a way that each pair of nodes with greater similarity value are first grouped and the remaining nodes are clustered following a heuristic algorithm to search into the similarity-based representation space. The proposed method is tested over a public domain image data set. Results show that our method reaches comparable results with a lower computational cost.
When You're Lost for Words: Faceted Search with Autocompletion

In this paper, we show how the autocompletion data structure of [2] can be used to answer faceted-search queries eciently. Specically , we have built a fully-functional browserbased search engine that can index collections with arbitrary category information and that, after each keystroke from the user, computes and displays the following information: (i) words or phrases that begin with the last query word and would lead to good hits; (ii) the most relevant categories for those hits; (iii) any category names that match the query as typed so far; (iv) the most relevant hits for the query as typed so far. By appropriately rewriting the faceted-search queries as autocompletion queries according to [2], we obtain very fast query processing times, improving those obtained by standard approaches by an order of magnitude. On 11,685 scientic articles from the DBLP collection, with their full text and categorized by author, conference, and year, the average query processing time is about 25 milliseconds, on a single machine and with the index on disk. For the 2,172,832 articles of the latest dump of the English Wikipedia, with their full text and categorized by Wikipedia’s own category labels, we achieve an average query processing time of about 350 milliseconds.
Deduction as Stochastic Simulation

Abstract : Many theorists argue that deduction is based on the construction of mental models or simulations of descriptions. Individuals tend to reason intuitively from a single mental model, but on occasion they make a deliberate search for alternative models. Previous computer implementations of the theory were deterministic, but evidence from empirical studies suggested that a stochastic algorithm would have greater predictive power. We present such a system for inferences from assertions with single quantifiers, such as ? All the agents are lawyers? This system implements constraints on the size of model, the sorts of individual it represents, and on the likelihood of a search for alternative models. We show that the system yields quantitative predictions at a fine-grained level, and that they fit the data from two experiments better than previous accounts.
Color Reduction in an Authenticate Live 3D Point Cloud Video Streaming System

In this paper, an authenticate live 3D point cloud video streaming system is presented, using a low cost 3D sensor camera, the Microsoft Kinect. The proposed system is implemented on a client-server network infrastructure. The live 3D video is captured from the Kinect RGB-D sensor, then a 3D point cloud is generated and processed. Filtering and compression are used to handle the spatial and temporal redundancies. A color histogram based conditional filter is designed to reduce the color information for each frame based on the mean and standard deviation. In addition to the designed filter, a statistical outlier removal filter is used. A certificate-based authentication is used where the client will verify the identity of the server during the handshake process. The processed 3D point cloud video is live streamed over a TCP/IP protocol to the client. The system is evaluated in terms of: compression ratio, total bytes per points, peak signal to noise ratio (PSNR), and Structural Similarity (SSIM) index. The experimental results demonstrate that the proposed video streaming system have a best case with SSIM 0.859, PSNR of 26.6 dB and with average compression ratio of 8.42 while the best average compression ratio case is about 15.43 with PSNR 18.5128 dB of and SSIM 0.7936.
Risk v. Overreaction and Migration

I provide empirical evidence in support of the conjecture that many observed market anomalies are simply a manifestation of the market’s process of searching for equilibrium. Therefore, these anomalies should be fully explained by risk pricing, if only we knew how to correctly measure risk in a out of equilibrium state. I focus on the Intangible Returns anomaly, as defined by Daniel and Titman (2006) and show that it is a manifestation of the evolution of the HML risk factor, which the market suffers during the observed period.
Saliency detection via the spatial layout of image

Recently many saliency detection algorithms tend to employ some priors, like center prior and boundary prior, which will bring some errors hard to decrease during the follow-up works. Salient object regions are considered as the regions with uniqueness, compactness and tiny boundary connectivity. Based on this idea, a new saliency region detection is proposed. In this paper, we adopt boundary connectivity and color spatial distribution, which have been proved to be more reasonable, as saliency cues. To improve the quality of saliency estimations, we optimize the results with an efficient principled framework. Besides, for getting pixel-wise saliency values, we employ graph-cuts algorithm to make up for the errors brought by segmenting the image into superpixels. Experiment results on five public datasets state clearly our method is efficient, and the comparisons with six state-of-the-art algorithms further prove the accuracy and robustness of the proposed algorithm.
The influence of online reviews to online hotel booking intentions [Summary]

Purpose – This study aims to investigate the impacts of online review and source features upon travelers’ online hotel booking intentions. Design/methodology/approach – This study developed a research model and empirically examined the model by collecting data from business travelers in the Mainland China. Factor analysis was adopted to identify features of online reviews content and source attribute. Regression analysis was used to examine impacts of these attributes upon travelers’ online booking intention. Findings – Six features of online reviews content and one source attribute were identified, namely, usefulness, reviewer expertise, timeliness, volume, valence (negative and positive) and comprehensiveness. Regression analysis results testified positive causal relationships between usefulness, reviewer expertise, timeliness, volume and comprehensiveness and respondents’ online booking intentions. A significantly negative relation between negative online reviews and online booking intentions was ident.
A stochastic algorithm finding $p$-means on the circle

A stochastic algorithm is proposed, finding some elements from the set of intrinsic $p$-mean(s) associated to a probability measure $\nu$ on a compact Riemannian manifold and to $p\in[1,\infty)$. It is fed sequentially with independent random variables $(Y_n)_{n\in \mathbb{N}}$ distributed according to $\nu$, which is often the only available knowledge of $\nu$. Furthermore, the algorithm is easy to implement, because it evolves like a Brownian motion between the random times when it jumps in direction of one of the $Y_n$, $n\in\mathbb{N}$. Its principle is based on simulated annealing and homogenization, so that temperature and approximations schemes must be tuned up (plus a regularizing scheme if $\nu$ does not admit a H\"{o}lderian density). The analysis of the convergence is restricted to the case where the state space is a circle. In its principle, the proof relies on the investigation of the evolution of a time-inhomogeneous $\mathbb{L}^2$ functional and on the corresponding spectral gap estimates due to Holley, Kusuoka and Stroock. But it requires new estimates on the discrepancies between the unknown instantaneous invariant measures and some convenient Gibbs measures.
Quality and comparison of antenatal care in public and private providers in the United Republic of Tanzania.

OBJECTIVE To compare the quality of public and private first-tier antenatal care services in Dar es Salaam, United Republic of Tanzania, using defined criteria. METHODS Structural attributes of quality were assessed through a checklist, and process attributes, including interpersonal and technical aspects, through observation and exit interviews. A total of 16 health care providers, and 166 women in the public and 188 in the private sector, were selected by systematic random sampling for inclusion in the study. Quality was measured against national standards, and an overall score calculated for the different aspects to permit comparison. FINDINGS The results showed that both public and private providers were reasonably good with regard to the structural and interpersonal aspects of quality of care. However, both were poor when it came to technical aspects of quality. For example, guidelines for dispensing prophylactic drugs against anaemia or malaria were not respected, and diagnostic examinations for the assessment of gestation, anaemia, malaria or urine infection were frequently not performed. In all aspects, private providers were significantly better than public ones. CONCLUSION Approaches to improving quality of care should emerge progressively as a result of regular quality assessments. Changes should be introduced using an incremental approach addressing few improvements at a time, while ensuring participation in, and ownership of, every aspect of the strategy by health personnel, health planners and managers and also the community.
Improved design of two and four-group decodable STBCs with larger diversity product for eight transmit antennas

Recently, full rate and full diversity two-group (2Gp) and four-group (4Gp) decodable space-time block codes (STBC) derived from quasi-orthogonal STBC (QSTBC) and designed under diversity product maximization criterion have been proposed. In this paper, we derive an upper bound of diversity product for those STBCs and discover that the diversity product of the current 2Gp-QSTBC and 4Gp-QSTBC has the potential to approach the upper bound for 8 transmit antennas. To this end, we propose an improved design of 2Gp and 4Gp STBC with increased diversity product for 8 transmit antennas by allowing sufficient number of dimensions for constellation rotation. The diversity product of the proposed two-group decodable STBC achieves the derived upper bound.
Soroban: Attributing Latency in Virtualized Environments

Applications executing on a hypervisor or in a container experience a lack of performance isolation from other services executing on shared resources. Latency-sensitive applications executing in the cloud therefore have highly-variable response times, yet attributing the additional latency caused by virtualization overheads on individual requests is an unsolved problem. We present Soroban, a framework for attributing latency to either the cloud provider or their customer. Soroban allows developers to instrument applications, such as web servers to determine, for each request, how much of the latency is due to the cloud provider, and how much is due to the consumer's application or service. With this support Soroban enables cloud-providers to provision based on acceptable-latencies, adopt fine-grained charging levels that reflect latency demands of users and attribute performance anomalies to either the cloud provider or their consumer. We apply Soroban to a HTTP server and show that it identifies when the cause of latency is due to a provider-induced activity, such as underprovisioning a host, or due to the software run by the customer.
An Efficient Method to Identify the Most Frequent Item Sets Using Database Count Algorithm and Effective Aco Algorithm in a Peer to Peer Network

— A peer-to-peer (P2P) network is one that does not have fixed clients and servers but a number of peer nodes that function as both clients and servers to the other nodes in the network. Association Rule Mining can be used for discovering hidden relationship between items stored in various nodes in the network . By given a user-specified threshold, also known as minimum support, the mining of association rules can discover the complete set of frequent patterns. In this paper, a Database count algorithm is used to mine the local frequent item sets and then generate the global frequent item sets from a Peer to peer network. Then the global item sets are optimized by using the Effective Ant colony Optimization algorithm to generate the most frequent item sets.
Application of a Learning-Companion Robot in Learning Environments

In this paper, a learning-companion robot based on a Pleo (a dinosaur-robot) is introduced. The learning-companion robot is equipped with a low-cost Web camera, a computer, and an attention monitoring algorithm so that it can not only monitor a learnerpsilas attention status but also detect whether the learner is too close to a computer screen during an on-line learning activity. The motivation of the development of the learning-companion robot is to alleviate parentspsila supervision burdens when they can not personally accompany their children to engage in some learning activities or playing computer games.
Free Acoustic and Language Models for Large Vocabulary Continuous Speech Recognition in Swedish

This paper presents results for large vocabulary continuous speech recognition (LVCSR) in Swedish. We trained acoustic models on the public domain NST Swedish corpus and made them freely available to the community. The training procedure corresponds to the reference recogniser (RefRec) developed for the SpeechDat databases during the COST249 action. We describe the modifications we made to the procedure in order to train on the NST database, and the language models we created based on the N-gram data available at the Norwegian Language Council. Our tests include medium vocabulary isolated word recognition and LVCSR. Because no previous results are available for LVCSR in Swedish, we use as baseline the performance of the SpeechDat models on the same tasks. We also compare our best results to the ones obtained in similar conditions on resource rich languages such as American English. We tested the acoustic models with HTK and Julius and plan to make them available in CMU Sphinx format as well in the near future. We believe that the free availability of these resources will boost research in speech and language technology in Swedish, even in research groups that do not have resources to develop ASR systems.
Cost-Sensitive Analysis in Multiple Time Series Prediction

In this paper we propose a new methodology for Cost-Benefit analysis in a multiple time series prediction problem. The proposed model is evaluated in a real world application based on a network of wireless sensors distributed in energy production plants in a region. These sensors generate multiple time series data representing energy production. To build the prediction model for total energy production in the region we have used three common forecasting techniques, Support Vector Machines (SVMs), Multilayer Perceptron (MLP), and Multiple Regression (MR). For training and testing of the models we have used the data from year 2002 to 2004. We analyzed the quality of total energy prediction with different subsets of sensors. We build our cost-benefit model for the prediction process as a function of sensors in a distributed network and estimated the optimum number of sensors that will balance the expenses of the system with the prediction accuracy.
Problemas emocionais e de comportamento e rendimento escolar em adolescentes

This is a transversal correlational and comparative study, with a quantitative approach, which evaluated the relation between emotional and behavioral problems and school performance of adolescents considering their evaluation, of their relatives and teachers’. Participated 70 adolescents, as well as their main caregivers, an equal number, and 21 teachers. The adolescents answered to Youth Self Report (YSR), the families to Child Behavior Checklist (CBCL), and the teachers to Teacher´s Report Form (TRF). The school performance was evaluated from the grades of Portuguese and Math subjects. The results showed that attention problems, as well as externalizing symptoms were the scales most associated with low school performance. Therefore, it is important to consider the emotional and behavioral problems in the school context, from the perspective of multiple informants, in view of their association with adolescent academic performance.
Mass limits for the progenitor star of supernova 2001du and other Type II-P supernovae

The supernova SN 2001 du was discovered in the galaxy NGC 1365 at a distance of 19 ′ 2 Mpc, and is a core-collapse event of Type II-P. Images of this galaxy, of moderate depth, have been taken with the Hubble Space Telescope approximately 6.6 yr before discovery and include the supernova position on the WFPC2 field of view. We have observed the supernova with the WFPC2 to allow accurate differential astrometry of SN 2001du on the pre-explosion frames. As a core-collapse event it is expected that the progenitor was a massive, luminous star. There is a marginal detection (3σ) of a source close to the supernova position on the pre-discovery V-band frame, but it is not precisely coincident and we do not believe it to be a robust detection of a point source. We conclude that there is no stellar progenitor at the supernova position and derive sensitivity limits of the pre-discovery images that provide an upper mass limit for the progenitor star. We estimate that the progenitor had a mass of less than 15 M O . We revisit two other nearby Type II-P supernovae that have high-quality pre-explosion images, and refine the upper mass limits for the progenitor stars. Using a new distance determination for SN 1999gi from the expanding photosphere method, we revise the upper mass limit to 12 M O . We present new HST images of the site of SN 1999em, which validate the use of lower spatial resolution ground-based images in the progenitor studies and use a new Cepheid distance to the galaxy to measure an upper mass limit of 15 M O . for that progenitor. Finally we compile all the direct information available for the progenitors of eight nearby core-collapse supernovae and compare their mass estimates. These are compared with the latest stellar evolutionary models of pre-supernova evolution which have attempted to relate metallicity and mass to the supernovae type. Although this is statistically limited at present, reasonable agreement is already found for the lower-mass events (generally the Il-P), but some discrepancies appear at higher masses.
Implications of Graphic Cigarette Warning Labels on Smoking Behavior: An International Perspective

Graphic warning labels (GWLs) have been developed as a representative non-price policy to block such marketing. This study investigated the current state and effect of the global introduction of GWLs and examines the future tasks related to GWLs. We systematically reviewed literatures on GWL and a tobacco control strategy in the past fifteen years. The policy of enforcing GWLs has spread globally based on the Framework Convention on Tobacco Control. GWLs are more effective than text warnings and are implemented in over 70 countries. The policy has showed the impact of GWLs as a preventive effect on adolescents’ smoking, inducement of smoking cessation, reduction in the amount of tobacco smoked, and reduction in smoking rates. The success of an anti-smoking policy can manifests itself as an effect of individual policies, the rise of tobacco prices, and the introduction of GWLs.
Situated Language Understanding with Human-like and Visualization-Based Transparency

Communication with robots is challenging, partly due to their differences from humans and the consequent discrepancy in people’s mental model of what robots can see, hear, or understand. Transparency mechanisms aim to mitigate this challenge by providing users with information about the robot’s internal processes. While most research in human-robot interaction aim towards natural transparency using human-like verbal and non-verbal behaviors, our work advocates for the use of visualization-based transparency. In this paper, we first present an end-to-end system that infers task commands that refer to objects or surfaces in everyday human environments, using Bayesian inference to combine scene understanding, pointing detection, and speech recognition. We characterize capabilities of this system through systematic tests with a corpus collected from people (N=5). Then we design human-like and visualizationbased transparency mechanisms and evaluate them in a user study (N=20). The study demonstrates the effects of visualizations on the accuracy of people’s mental models, as well as their effectiveness and efficiency in communicating task commands.
Electrical Advantages of Dendritic Spines

Many neurons receive excitatory glutamatergic input almost exclusively onto dendritic spines. In the absence of spines, the amplitudes and kinetics of excitatory postsynaptic potentials (EPSPs) at the site of synaptic input are highly variable and depend on dendritic location. We hypothesized that dendritic spines standardize the local geometry at the site of synaptic input, thereby reducing location-dependent variability of local EPSP properties. We tested this hypothesis using computational models of simplified and morphologically realistic spiny neurons that allow direct comparison of EPSPs generated on spine heads with EPSPs generated on dendritic shafts at the same dendritic locations. In all morphologies tested, spines greatly reduced location-dependent variability of local EPSP amplitude and kinetics, while having minimal impact on EPSPs measured at the soma. Spine-dependent standardization of local EPSP properties persisted across a range of physiologically relevant spine neck resistances, and in models with variable neck resistances. By reducing the variability of local EPSPs, spines standardized synaptic activation of NMDA receptors and voltage-gated calcium channels. Furthermore, spines enhanced activation of NMDA receptors and facilitated the generation of NMDA spikes and axonal action potentials in response to synaptic input. Finally, we show that dynamic regulation of spine neck geometry can preserve local EPSP properties following plasticity-driven changes in synaptic strength, but is inefficient in modifying the amplitude of EPSPs in other cellular compartments. These observations suggest that one function of dendritic spines is to standardize local EPSP properties throughout the dendritic tree, thereby allowing neurons to use similar voltage-sensitive postsynaptic mechanisms at all dendritic locations.