Miracle-dz/UniFAR-FTUs huggingface dataset:
Social learning and online discussion: is twitter a wise crowd?

Technologists, interested in demonstrating the value of data analytics products to the field of public policy, argue that analysis of social media sites can provide insights about policy perspectives among the wider public. At its core are assumptions that diverse groups can provide wise answers to social queries, and that governments can utilize crowd-sourcing as a deliberative tool to improve policy decision-making. The use of data analytics for social networking sites like Twitter could inform policymaking if it could identify areas of potential agreement among a diverse group of individuals. This paper uses the De Groot learning model to test the capacity of online crowds to come to consensus about social problems. Using this model, and the Idle No More social movement as a case, this paper examines the degree that Twitter is a "wise" crowd in terms of its structure, meaning it is capable of sustaining an inclusive exchange of information over time. The paper finds that structurally, the Twitter network is the sort that can converge on a topic, however the larger the discussion, the more the network structure will be centralized, meaning small groups can dominate the messaging. However, influential actors change over time, suggesting that network structure may not matter as much as information flows across influential events.
Speed for the Elite, Consistency for the Masses: Differentiating Eventual Consistency in Large-Scale Distributed Systems

Eventual consistency is a consistency model that emphasizes liveness over safety, it is often used for its ability to scale as distributed systems grow larger. Eventual consistency tends to be uniformly applied to an entire system, but we argue that there is a growing demand for differentiated eventual consistency requirements. We address this demand with UPS, a novel consistency mechanism that offers differentiated eventual consistency and delivery speed by working in pair with a two-phase epidemic broadcast protocol. We propose a closed-form analysis of our approach's delivery speed, and we evaluate our complete mechanism experimentally on a simulated network of one million nodes. To measure the consistency trade-off, we formally define a novel and scalable consistency metric that operates at runtime. In our simulations, UPS divides by more than 4 the inconsistencies experienced by a majority of the nodes, while reducing the average latency incurred by a small fraction of the nodes from 6 rounds down to 3 rounds.
"Hidden observer" phenomena in hypnosis: an experimental creation?

Spanos and Hewitt (1980) have recently argued, on the basis of an experiment they report, that Hilgard's "hidden observer" phenomenon is pure laboratory artifact. This report reviews their claim and concludes on the following grounds that their experiment does not warrant so sweeping a conclusion: (a) Spanos and Hewitt have posed the issue as fact versus fiction and do not appear to be aware of a third alternative, namely, that the hidden observer effect is a phenomenon encountered in hypnosis that may be influenced both by demand characteristics and by the social-psychological context. (b) They appear to obtain the effect 100% of the time, unlike Hilgard, who has emphasized the phenomenon's differential incidence. (c) In contrast to Hilgard, who furnishes abundant verbal reports of his subjects' phenomenal experience as buttressing evidence for the "genuineness" of the effect in subjects who report having it, Spanos and Hewitt do not. (d) Two major procedural aspects of their experiment are discussed. Either or both may have inadvertently influenced the outcome of their experiment in the direction of their hypothesis that the responses of subjects are entirely the product of experimenter-induced expectations.
Representability of Pairing Relation Algebras Depends on your Ontology

We consider classes of relation algebras expanded with new operations based on the formation of ordered pairs. Examples for such algebras are pairing (or projection) algebras of algebraic logic and fork algebras of computer science. It is proved in Sain{N emeti 36] that there is nòstrong' representation theorem for all abstract pairing algebras in most set theories including ZFC as well as most non-well-founded set theories. Such a `strong' representation theorem would state that every abstract pairing algebra is isomorphic to a set relation algebra having projection elements which are deened with the help of the real (set theoretic) pairing function. Here we show that, by choosing an appropriate (non-well-founded) set theory as our metatheory, pairing algebras and fork algebras admit such`strong' representation theorems.
Mutual information based similarity measure for Collaborative Filtering

Collaborative Filtering(CF) is one of the most successful recommender systems. The most critical step in CF is similarity computation. In CF, similarity is used for neighbor search. In addition, it will be used as a weighted coefficient during the prediction step. Typically, three different similarity measures are used: cosine based similarity, Pearson correlation coefficient based similarity and adjusted cosine based similarity. However, as these methods are based on linear correlations, they are also limited. Indeed the linear correlation only takes into account the linear part of the correlation. This paper introduces a new similarity measure based on mutual information to avoid the above limitation. The experiments, done on MovieLens data sets, show that this new method outperforms traditional similarity measures under the nonlinear correlation circumstance.
Robotic Wheelchair Control Considering user Comfort - Modeling and Experimental Evaluation

This paper analyzes the comfort of wheelchair users when a sliding-mode trajectory-tracking controller is used. The transmission of the horizontal (fore-and-aft) vibration to the head-neck complex (HNC) in the seated human body may cause unacceptable discomfort and motion sickness. A double-inverted pendulum model with two degrees of freedom is considered as a model for the HNC. The user comfort is examined not only in the time domain (using the fourth power vibration dose value), but also in the frequency domain (using the cross-spectral density method). For measuring the acceleration of the wheelchair, along the trajectory, an inertial measurement unit was used.
Non-Negative Matrix Factorization for Note Onset Detection of Audio Signals

A novel approach using non-negative matrix factorization (NMF) for onset detection of musical notes from audio signals is presented. Unlike most commonly used conventional approaches, the proposed method exploits a new detection function constructed from the linear temporal bases that are obtained from a non-negative matrix decomposition of musical spectra. Both first-order difference and psychoacoustically motivated relative difference functions of the temporal profile are considered. As the approach works directly on input data, no prior knowledge or statistical information is thereby required. A practical issue of the choice of the factorization rank is also examined experimentally. Numerical examples are provided to show the performance of the proposed method.
Cloud-assisted individual l1-pca face recognition using wavelet-domain compressed images

Face recognition has been an active research field for a long time, and recently new challenges have arisen in designing cloud-assisted face recognition algorithms. In a cloud assisted face recognition system, mobile devices acquire the data images; then, in order to unbind the cloud face recognition algorithm from the particular features extracted at the mobile device, the images are encoded and uploladed into the cloud. In this framework, it is important to understand and control the effect of the image compression stage performed at the mobile device on the performances of the face recognition algorithms realized within the cloud. Here, we analyze the impact of wavelet domain image compression on the Individual Adaptive (IA) L1-PCA subspace computation and assess the performance of a classifier operating on data characterized by increasing compactness and accordingly decreasing accuracy.
International Conference on Information Systems ( ICIS ) 2009 Communication and Performance across Time Zones : A Laboratory Experiment

We often hear that global knowledge work teams are affected by time zone differences, but most research in geographically dispersed collaboration has focused on the effects of distance and has treated time zones as a secondary factor. The experimental study we describe here is part of a larger research program aimed at understanding how technical teams coordinate their work across time zones and which factors influence performance. In this study we investigate how time zone differences affect team performance in a laboratory setting. The study is composed of three phases corresponding to different task type manipulations – simple, complex and equivocal task. In each of the study phases, dyadic teams were randomly assigned into 4 time zone (i.e., work time overlap) conditions: full overlap, 2/3 overlap, 1/3 overlap and no overlap. Teams performed a map drawing task simulating the assembly of software components. We completed data collection for 131 dyad teams. In each phase we collected the following data: team performance (speed and accuracy), exit survey, and chat log capture. In this paper we describe our research design, briefly discuss our preliminary results from analysis of data from Phase 1, and describe our expectations and next steps for the full study. In Phase 1 we found that time separation has a negative effect on accuracy. We also found that a small amount of time separation has a negative effect on production speed but, surprisingly, speed actually increases with further increases in time separation – a “U” shaped curve. Our chat log text analysis also revealed differences in communication patterns across time zone conditions, which helps explain the unanticipated results. To evaluate if the simplicity of our task influenced our results in Phase 1 we manipulated the task in Phase 2 (added complexity) and Phase 3 (more equivocal). Expected results and implications from these subsequent phases are discussed at the end.
Identifying the characteristics of usability that encourage prolonged use of an Activity Monitor

Together with the use of rapid prototyping techniques and efforts to reduce the production cost, wearable and mobile electronic devices are brought to the market faster than ever, with less time spent on actual usability testing of these devices for prolonged use. Due to this, the usability lifespan of such electronic devices has reduced significantly where consumers might be moving or upgrading on to using newer electronic devices more often than they really need to. Therefore, this paper focuses on identifying key characteristics of usability that may encourage prolonged use of an activity monitoring device. Also, to observe and record any user acceptance and/or usability issues that may arise from using an activity monitor over a prolonged period.
The Evolution of Optical Depth in the Lyα Forest: Evidence Against Reionization at z~6

We examine the evolution of the IGM Lyα optical depth distribution using the transmitted flux probability distribution function (PDF) in a high-resolution sample of 55 QSOs spanning absorption redshifts 1.7 < z < 5.8. The data are compared to two theoretical τ distributions: a model distribution based on the density distribution of Miralda-Escudé et al. (2000; MHR00) and a lognormal distribution. Assuming a spatially uniform UV background and an isothermal IGM, as was done in previous works where transmitted flux statistics have been used to infer an end to cosmic reionization at z ~ 6, the MHR00 model fails to reproduce the observed flux PDFs at redshifts where the optical depth distribution is well sampled unless large continuum corrections are applied. A lognormal τ distribution, in contrast, fits the data well at all redshifts with only minor continuum adjustments. Extrapolating the evolution of the lognormal distribution at z < 5.4 predicts the observed upturn in the Lyα and Lyβ effective optical depths at z > 5.7, while simultaneously reproducing the mean transmitted flux down to z = 1.6. In this empirical sense, the evolution of the Lyα forest at z ~ 6 is consistent with observed trends at lower redshift. If the evolution of the forest at z ≲ 5 reflects a slowly evolving density field, temperature, and UV background, then no sudden change in the IGM, such as one due to late reionization, appears necessary to explain the disappearance of transmitted flux at z ~ 6. If the MHR00 density distribution is correct, then a nonuniform UV background and/or IGM temperature may be required to produce the correct distribution of optical depths. We find that an inverse temperature-density relation for the MHR00 model significantly improves the PDF fits, but with a large scatter in the equation-of-state index.
Single image superresolution using sparsity and dictionary learning in wavelet domain

Recently sparse representation is proven to be very successful for image processing applications. This paper proposes a superresolution approach that utilizes the decorrelating and sparsifying property of discrete wavelet transform, with the signal-fitting capability of sparse representation over learned dictionaries. Two dictionaries are learned (using K-SVD algorithm) for each wavelet subband: one for the low resolution one for the high resolution images. In the training set, noisy variants of the high a resolution image obtained by interpolating its low resolution counter-part, are intentionally included. A patch based approach is employed and different patch sizes are studied. The sparse representation coefficients for the respective low and high resolution images are assumed to be the same. Experiments are conducted using the Kodak24-image set. The proposed algorithm is proven to be competitive with the leading super-resolution techniques both visually and quantitatively. With a patch size of 11×11 the proposed method is 0.89 dB better than the method proposed by Elad et.al. and 2.19 dB better than bicubic interpolation.
Vectorizing for Wider Vector Units in a HW/SW Co-designed Environment

SIMD accelerators provide an energy efficient way of improving the computational power in modern microprocessors. Due to their hardware simplicity, these accelerators have evolved in terms of width from 64-bit vectors in Intel's MMX to 512-bit wide vector units in Intel's Xeon Phi. Although SIMD accelerators are simple in terms of hardware design, code generation for them has always been a challenge. This paper explores the scalability of SIMD accelerators from the code generation point of view. We explore the potential problems in vectorization at higher vector lengths. Furthermore, we propose Variable Length Vectorization and Selective Writing in a HW/SW co-designed environment to get around these problems. We evaluate our proposals using a set of SPECFP2006 and Physics bench applications. Our experimental results show an average dynamic instruction elimination of 33% and 40% and an average speed up of 15% and 10% for SPECFP2006 and Physics bench respectively, for 512-bit vector length, over the scalar baseline code.
Semi-Cosmopolitan Transnational Students: The Identity Work of Transnational Students at an Elite Dominican School

ABSTRACT The Dominican Republic has a substantial history of transnational movement to the US that affects more than one generation of transnationals, whose lives, as described by Smith (1994), are ‘neither “here” nor “there” but at one both “here” and “there”’(p. 17). While the Dominican transnational narrative has often been described as transnationalism from below (Smith and Guarnizo, 1998), the following case studies of transnational, but relatively privileged, youth require rethinking that framework. Participants describe a semi-cosmopolitan identity that has been shaped by their comparative experiences in more than one locale.
Targeting of the 5-HT1A Serotonin Receptor to Neuronal Dendrites Is Mediated by Yif1B

The 5-HT1A receptor (5-HT1AR) is the most extensively characterized serotonin (5-HT) receptor mainly because of its involvement in the mode of action of antidepressants. The 5-HT1AR is confined to the somatodendritic domain of central neurons, where it mediates serotonin-evoked hyperpolarization. Our previous studies underlined the role of the short 5-HT1AR C-terminal domain in receptor targeting to dendrites. We used this 17 aa region as bait in a yeast two-hybrid screen, and identified, for the first time, an intracellular protein interacting with the 5-HT1AR. This protein is homologous to the yeast Yif1p, previously implicated in vesicular trafficking between the endoplasmic reticulum (ER) and the Golgi apparatus, but not yet characterized in mammals. We confirmed 5-HT1AR–Yif1B interaction by glutathione S-transferase pull-down experiments using rat brain extracts and transfected cell lines. Yif1B is highly expressed in the brain, and specifically in raphe 5-HT1AR-expressing neurons. Colocalization of Yif1B and 5-HT1AR was observed in small vesicles involved in transient intracellular trafficking. Last, inhibition of endogenous expression of Yif1B in primary neuron cultures by small interfering RNA specifically prevented the addressing of 5-HT1AR to distal portions of the dendrites, without affecting other receptors, such as sst2A, P2X2, and 5-HT3A receptors. Together, our results provide strong evidence that Yif1B is a member of the ER/Golgi trafficking machinery, which plays a key role in specific targeting of 5-HT1AR to the neuronal dendrites. This finding opens up new pathways for the study of 5-HT1AR regulation by partner proteins and for the development of novel antidepressant drugs.
STEAM: A Smart Temperature and Energy Aware Multicore Controller

Recent empirical studies have shown that multicore scaling is fast becoming power limited, and consequently, an increasing fraction of a multicore processor has to be under clocked or powered off. Therefore, in addition to fundamental innovations in architecture, compilers and parallelization of application programs, there is a need to develop practical and effective dynamic energy management (DEM) techniques for multicore processors. Existing DEM techniques mainly target reducing processor power consumption and temperature, and only few of them have addressed improving energy efficiency for multicore systems. With energy efficiency taking a center stage in all aspects of computing, the focus of the DEM needs to be on finding practical methods to maximize processor efficiency. Towards this, this article presents STEAM -- an optimal closed-loop DEM controller designed for multicore processors. The objective is to maximize energy efficiency by dynamic voltage and frequency scaling (DVFS). Energy efficiency is defined as the ratio of performance to power consumption or performance-per-watt (PPW). This is the same as the number of instructions executed per Joule. The PPW metric is actually replaced by PαPW (performanceα-per-Watt), which allows for controlling the importance of performance versus power consumption by varying α. The proposed controller was implemented on a Linux system and tested with the Intel Sandy Bridge processor. There are three power management schemes called governors, available with Intel platforms. They are referred to as (1) Powersave (lowest power consumption), (2) Performance (achieves highest performance), and (3) Ondemand. Our simple and lightweight controller when executing SPEC CPU2006, PARSEC, and MiBench benchmarks have achieved an average of 18% improvement in energy efficiency (MIPS/Watt) over these ACPI policies. Moreover, STEAM also demonstrated an excellent prediction of core temperatures and power consumption, and the ability to control the core temperatures within 3ˆC of the specified maximum. Finally, the overhead of the STEAM implementation (in terms of CPU resources) is less than 0.25%. The entire implementation is self-contained and can be installed on any processor with very little prior knowledge of the processor.
Continuous Vehicle Detection and Tracking for Non-overlapping Multi-camera Surveillance System

Vehicle detection and tracking has always been a significant research on traffic surveillance video. However, multi-camera object tracking consists of a non-overlapping video surveillance network, which makes vehicle re-identification a challenging problem. In this paper, we proposed a novel method for continuous vehicle detection and tracking in multi-camera campus surveillance videos. The method contains two main parts: One is auto vehicle detection and tracking by using background modeling combining with RCNN (Region Convolutional Neural Networks). The other one is multi-camera vehicle re-identification, which collaborates vehicle visual attributes and spatio-temporal information. The experiment results demonstrate that the proposed approach performs with high efficiency and accuracy, which can also be employed to optimize the trajectories of vehicles in multi-camera surveillance videos.
Gmd Report 40 Resource Prediction and Admission Control for Interactive Video Browsing Scenarios Using Application Semantics

Highly interactive multimedia applications, like browsing in video databases, generate strongly varying loads on the media server during the presentation of media data. Existing admission control approaches for limiting the number of concurrent users and thus guaranteeing acceptable service quality are only suited for applications with uniform load characteristics like video-ondemand. We propose an approach to admission control that is based on the stochastical model of Continuous Time Markov Chains, which allows to describe the different presentation states occurring in the interactive access to the multimedia database. The model is derived from semantic information on the forthcoming browsing session, in particular, it considers the relevance of the videos to the user. In this way a more precise prediction on resource usage can be given for achieving the two goals of Quality of Service (QoS) and good server utilization. The admission control mechanism is part of a multimedia database architecture for supporting efficient browsing in large video collections.
Accuracy of the Bronchoalveolar Lavage Enzyme-Linked Immunospot Assay for the Diagnosis of Pulmonary Tuberculosis

AbstractAssessing of local immune response may improve the accuracy of pulmonary tuberculosis (PTB) diagnosis. Many studies have investigated diagnosing PTB based on enzyme-linked immunospot (ELISPOT) assay of bronchoalveolar lavage (BAL) fluid, but the results have been inconclusive. We meta-analyzed the available evidences on overall diagnostic performance of ELISPOT assay of BAL fluid for diagnosing PTB.A systematic literature search was performed using PubMed, Embase, Wangfang, Weipu, and CNKI. Data were pooled on sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). Overall test performance was summarized using summary receiver operating characteristic curves and the area under the curve (AUC). Deeks test was used to test for potential publication bias.Seven publications with 814 subjects met our inclusion criteria and were included in this meta-analysis. The following pooled estimates for diagnostic parameters were obtained: sensitivity, 0.90 (95% CI: 0.85–0.94); specificity, 0.80 (95% CI: 0.77–0.84); PLR, 5.08 (95% CI: 2.70–9.57); NLR, 0.13 (95% CI: 0.06–0.28); DOR, 49.12 (95% CI: 12.97–186.00); and AUC, 0.96. No publication bias was identified.The available evidence suggests that ELISPOT assay of BAL fluid is a useful rapid diagnostic test for PTB. The results of this assay should be interpreted in parallel with clinical findings and the results of conventional tests.