Miracle-dz/UniFAR-FTUs huggingface dataset:
The two disciplines problem – ‘it’s like Déjà vu all over again!’

For decades, assessment has constituted one of the most controversial issues in education with respect to matters of theory, design, implementation and educational policy. Many of the arguments surround what we assess, how we assess, and the ways in which information derived from assessments is used to shape educational practice. In 2001, a report was issued by the US. National Research Council entitled ‘Knowing What Students Know: The Science and Design of Educational Assessment’ (Pellegrino, Chudowsky, & Glaser, 2001). The goal was to evaluate the state of research and theory on educational assessment and establish the scientific foundations for their design and use. As argued in that volume, many of the debates that surround educational assessment emanate from a failure to understand its fundamental nature, including the ways in which theories and models (a) of learning and knowing and (b) of measurement and statistical inference interact with and influence processes of assessment design, use and interpretation. The current lead article by Baird, Andrich, Hopfenbeck, and Stobart (2017) highlights many of the same issues and concerns and asks that we give greater attention to the connection between theories of learning and educational assessments. Given the many and far ranging aspects of the Baird et al. piece, I have chosen to focus my commentary on their core issue – the relationship between assessment and learning – but come at some answers in a related but different way. I fundamentally agree with their premise that ‘if assessment is to serve the learning goals of education, then this discussion of the relationship between assessment and learning should be developed further and be at the forefront of high-stakes, large-scale educational assessments’. However, I believe discussion of that relationship transcends and encompasses the design and use of educational assessments across multiple levels of educational practice and policy. In what follows, I focus first on the fundamental nature of educational assessment and its connection to theories, models and data on learning. I then turn to discussion of contemporary views of learning in the form of learning progressions as they relate to assessment development. In the third part of my commentary I consider the continuum spanned by the classroom to international large-scale assessments in the context of levels and timescales of assessment. I then consider some implications of a focus on learning for the design and use of assessments at the two
Lifetime optimization of sensor-cloud systems

Sensor-Cloud is an emerging technology and popular paradigm of choice in systems development for various real-life applications. It consists in integrating wireless sensor networks with cloud computing environment. In fact, the cloud provides new opportunities of massive data storage, processing and analysing that wireless sensor networks can not offer. Despite the fact that the cloud have helped to overcome many wireless sensor networks limitations, there are other challenging issues that need to be addressed. The major problem that can significantly affect Sensor-Cloud performance is the short lifetime due to limited energy supply of sensors and sometimes some sinks. In this work, we propose a Sensor-Cloud Optimization problem (SCL-OPT) that maximizes lifetime as well as increases energy efficiency of sensors and sinks layers.
OFF-THE-SHELF CLOSE-RANGE PHOTOGRAMMETRIC SOFTWARE FOR CULTURAL HERITAGE DOCUMENTATION AT STONEHENGE

This paper is a summary of a student internship with English Heritage's Photogrammetric Unit. During this placement affordable solutions for heritage close-range photogrammetric measurement were examined. Topcon's Image Surveying Station PI-3000 photogrammetric software was used on a project to record carvings found on one of the stones at Stonehenge. Analysis of this carving (and others) is essential in order to understand Stonehenge's history as well as to help to conserve its condition. An original survey of this carving was carried out in 1967 (Atkinson, 1968) providing context against which this survey using PI-3000 could be compared to in the future. In preparation for this work a comparison of camera calibration techniques (using PI-3000 and PhotoModeler) was carried out. Creating a 3D model using the photogrammetric method based on a bundle adjustment requires knowledge of camera calibration parameters. Photogrammetric camera calibration parameters allow for the recovery of the central perspective bundle. They can be determined during a self calibration process if using appropriate software. It was decided to assess the camera calibration provided by PI-3000. Therefore, to test the software, a Canon IXUS 900Ti was calibrated using PI-3000 and PhotoModeler. The paper presents the results of these calibrations and compares the two software packages. PI-3000 was then used to document a single carving found on inner face of the 53 rd stone of Stonehenge. The outcome could be compared with the survey performed in 1967. Around ten images were collected with a calibrated Cannon A640 camera. Scale was introduced to the scene using a ruler laid against the stone. PI-3000 was then used to produce a meshed surface of the carving. Results will be presented. The paper concludes that off-the-shelf photogrammetric equipment and software could be utilized in commercial projects to provide heritage recording. However, principles of close range photogrammetry still needed to be understood in order to produce high quality results.
Clinical investigations of receptive and expressive musical functions after stroke

There is a long tradition of investigating various disorders of musical abilities after stroke. These impairments, associated with acquired amusia, can be highly selective, affecting only music perception (i.e., receptive abilities/functions) or expression (music production abilities), and some patients report that these may dramatically influence their emotional state. The aim of this study was to systematically test both the melodic and rhythmic domains of music perception and expression in left- and right-sided stroke patients compared to healthy subjects. Music perception was assessed using rhythmic and melodic discrimination tasks, while tests of expressive function involved the vocal or instrumental reproduction of rhythms and melodies. Our approach revealed deficits in receptive and expressive functions in stroke patients, mediated by musical expertise. Those patients who had experienced a short period of musical training in childhood and adolescence performed better in the receptive and expressive subtests compared to those without any previous musical training. While discrimination of specific musical patterns was unimpaired after a left-sided stroke, patients with a right-sided stroke had worse results for fine melodic and rhythmic analysis. In terms of expressive testing, the most consistent results were obtained from a test that required patients to reproduce sung melodies. This implies that the means of investigating production abilities can impact the identification of deficits.
Eurographics/ Ieee-vgtc Symposium on Visualization (2006) Affiliation Dynamics with an Application to Movie-actor Biographies

We propose a visualization approach for dynamic affiliation networks in which events are characterized by a set of descriptors. It uses a radial ripple metaphor to display the passing of time and conveys relations among the different constituents through appropriate layout. Our method is particularly suitable when assuming an egocentric perspective, and we illustrate it on movie-actor biographies.
Unsupervised learning of sub-millisecond temporal coded sequence by a network of \ coincidence detector " neurons

In this paper, we examine unsupervised learning for sequence of sub-millisecond temporal coded information in a network of neurons, which are assumed to have high temporal resolution. The learning scheme is based on a spatially and temporally local one, i.e., unsupervised Hebbian learning. The input sequence is temporal information that needs an accuracy on the order of sub-milliseconds. Through the learning, segregation of the synaptic connections occurs to form systematic structures in the network. Namely, the network develops in a self-organizing manner. The trained network works like an \associative memory" of the learned sequence, namely, the network responds when a newly input sequence is similar to the learned sequence. Consequently, the assembly of neurons is able to learn and distinguish an input sequence that carries information on the order of sub-milliseconds, although the spike emission intervals of the neurons are on the order of milliseconds.
On improved scheme for digital circuit rewiring and application on further improving FPGA technology mapping

The digital circuit rewiring technique has been shown to be one of the most powerful logic transformation methods being able to further improve some already excellent results on many EDA problems. In this work a new hybrid rewiring approach that can enjoy advantages from both ATPG-based and graph-based rewiring is proposed. Our hybrid approach utilizes structural characteristics and ATPG technique to perform quick alternative wires identification inside circuits. Experimental results suggest that our hybrid engine is able to achieve about 50% of alternative wires coverage when compared with ATPG-based rewiring engine with 4% of runtime only. For some problems only requiring a good-enough and very quick solution, this new rewiring technique may serve as a useful alternative.
Parallel encoding of sensory history and behavioral preference during Caenorhabditis elegans olfactory learning

Sensory experience modifies behavior through both associative and non-associative learning. In Caenorhabditis elegans, pairing odor with food deprivation results in aversive olfactory learning, and pairing odor with food results in appetitive learning. Aversive learning requires nuclear translocation of the cGMP-dependent protein kinase EGL-4 in AWC olfactory neurons and an insulin signal from AIA interneurons. Here we show that the activity of neurons including AIA is acutely required during aversive, but not appetitive, learning. The AIA circuit and AGE-1, an insulin-regulated PI3 kinase, signal to AWC to drive nuclear enrichment of EGL-4 during conditioning. Odor exposure shifts the AWC dynamic range to higher odor concentrations regardless of food pairing or the AIA circuit, whereas AWC coupling to motor circuits is oppositely regulated by aversive and appetitive learning. These results suggest that non-associative sensory adaptation in AWC encodes odor history, while associative behavioral preference is encoded by altered AWC synaptic activity. DOI: http://dx.doi. org/10.7554/eLife.14000. 001
Segmenting Glioma in Multi-Modal Images using a Generative Model for Brain Lesion Segmentation

In this paper, we evaluate a fully automated method for channel-specific tumor segmentation in multi-dimensional images proposed by us in [1]. The method represents a tumor appearance model for multi-dimensional sequences that provides channel-specific segmentation of the tumor. Its generative model shares information about the spatial location of the lesion among channels while making full use of the highly specific multi-modal signal of the healthy tissue classes for segmenting normal tissues in the brain. In addition to tissue types, the model includes a latent variable for each voxel encoding the probability of observing tumor at that voxel, based on the ideas from [2, 3]. This extends the general “EM segmention” algorithm for situations when specific spatial structures cannot be described sufficiently through population priors. Different from [1], we now use a simplified EM algorithm for estimating the tissue state that also allows us to enforce additional constraints for segmenting lesions that are either hyperor hypo-intense with respect to other tissues visible in the same image.
Real-Time Bid Prediction using Thompson Sampling-Based Expert Selection

We study online meta-learners for real-time bid prediction that predict by selecting a single best predictor among several subordinate prediction algorithms, here called "experts". These predictors belong to the family of context-dependent past performance estimators that make a prediction only when the instance to be predicted falls within their areas of expertise. Within the advertising ecosystem, it is very common for the contextual information to be incomplete, hence, it is natural for some of the experts to abstain from making predictions on some of the instances. Experts' areas of expertise can overlap, which makes their predictions less suitable for merging; as such, they lend themselves better to the problem of best expert selection. In addition, their performance varies over time, which gives the expert selection problem a non-stochastic, adversarial flavor. In this paper we propose to use probability sampling (via Thompson Sampling) as a meta-learning algorithm that samples from the pool of experts for the purpose of bid prediction. We show performance results from the comparison of our approach to multiple state-of-the-art algorithms using exploration scavenging on a log file of over 300 million ad impressions, as well as comparison to a baseline rule-based model using production traffic from a leading DSP platform.
Confidence intervals by the profile likelihood method , with applications in veterinary epidemiology

The commonly used Wald-type confidence intervals are based on the approximately normal distribution of parameter estimates valid in many “nice” estimation settings. However, one may come across “difficult” situations where the procedure works poorly or breaks down. In this paper, we review an alternative method based on the likelihood function, illustrating by 2 examples its use and the computations involved.
Illumination Characteristics of Mobility Lights

The authors measured the light-distribution patterns and the decay in light output of three mobility lights that visually impaired persons can use for night travel: the Wide-Angle Mobility Light (WAML), the Streamlight, and the Mag-Lite. The WAML had a wide beam with a medium-bright central region. The beam of the Streamlight had the brightest central region and a moderately wide surround of lower illumination. The Mag-Lite had the narrowest light distribution about a bright central spot. Both the Streamlight and the Mag-Lite maintained near-maximum brightness before undergoing rapid decay, while the WAML showed a gradual decay changing from near-maximum brightness to near extinction in almost a linear fashion 40 to 80 minutes after being turned on.
A mechanism for flexible dynamic trait replacement

Dynamic trait replacement is a programming language feature for changing the objects' behavior at runtime by replacing some of the objects' methods. In previous work on dynamic trait replacement for JAVA-like languages, the object's methods that may be replaced must correspond exactly to a named trait used in the object's class definition. In this paper we propose the notion of replaceable: a programming language feature that decouples trait replacement operation code and class declaration code, thus making it possible refactoring classes and/or performing unanticipated trait replacement operations without invalidating existing code.
The face of quality in crowdsourcing relevance labels: demographics, personality and labeling accuracy

Information retrieval systems require human contributed relevance labels for their training and evaluation. Increasingly such labels are collected under the anonymous, uncontrolled conditions of crowdsourcing, leading to varied output quality. While a range of quality assurance and control techniques have now been developed to reduce noise during or after task completion, little is known about the workers themselves and possible relationships between workers' characteristics and the quality of their work. In this paper, we ask how do the relatively well or poorly-performing crowds, working under specific task conditions, actually look like in terms of worker characteristics, such as demographics or personality traits. Our findings show that the face of a crowd is in fact indicative of the quality of their work.
Simultaneous Clustering and Tracklet Linking for Multi-face Tracking in Videos

We describe a novel method that simultaneously clusters and associates short sequences of detected faces (termed as face track lets) in videos. The rationale of our method is that face track let clustering and linking are related problems that can benefit from the solutions of each other. Our method is based on a hidden Markov random field model that represents the joint dependencies of cluster labels and track let linking associations. We provide an efficient algorithm based on constrained clustering and optimal matching for the simultaneous inference of cluster labels and track let associations. We demonstrate significant improvements on the state-of-the-art results in face tracking and clustering performances on several video datasets.
High-Resolution H I Mapping of NGC 4038/39 (“The Antennae”) and Its Tidal Dwarf Galaxy Candidates

We present new VLA C + D array H I observations and optical and near-infrared imaging of the well-known interacting system NGC 4038/39, "The Antennae. " At low spatial resolution (∼40″), the radio data reach a limiting column density of ∼1019 cm-2 (2.5 σ), providing significantly deeper mapping of the tidal features than afforded by earlier H I maps. At relatively high spatial resolution (∼10″), the radio data reveal a wealth of gaseous substructure both within the main bodies of the galaxies and along the tidal tails. In agreement with previous H I studies, we find that the northern tail has H I along its outer length but none along its base. We suggest that the H I at the base of this tail has been ionized by massive stars in the disk of NGC 4038. The gas in the southern tail has a bifurcated structure, with one filament lying along the optical tail and another running parallel to it but with no optical counterpart. The two filaments join just before the location of several star-forming regions near the end of the tail. The H I velocity field at the end of the tail is dominated by strong velocity gradients, which suggests that at this location the tail is bending away from us. We delineate and examine two regions within the tail previously identified as possible sites of a so-called tidal dwarf galaxy condensing out of the expanding tidal material. The tail velocity gradients mask any clear kinematic signature of a self-gravitating condensation in this region. A dynamical analysis suggests that there is not enough mass in gas alone for either of these regions to be self-gravitating. Conversely, if they are bound they require a significant contribution to their dynamical mass from evolved stars or dark matter. Even if there are no distinct dynamical tidal entities, it is clear that there is a unique concentration of gas, stars, and star-forming regions within the southern tail: the H I channel maps show clear evidence for a significant condensation near the tail star-forming regions, with the single-channel H I column densities higher than anywhere else in the system, including within the main disks. Finally, the data reveal H I emission associated with the edge-on "superthin" Scd galaxy ESO 572-G045, which lies just beyond the southern tidal tail of The Antennae, showing it to be a companion system.
Development Labs: University Knowledge Production and Global Poverty

Abstract:In 2012, the United States Agency for International Development allocated $137 million to fund seven universities to create development labs to advance social/economic progress and reduce poverty. International economic development has become a booming field and industry but is also highly contested. The function of the university as a development strategy has great potential but can also be subject to criticism. This qualitative study included a visit to all seven universities and generated findings related to a development lab model and mentality, including: the importance of failure, knowledge co-creation, and the role of the academy in constructing culture.
An Off-Line Variable-Size Bin Packing for EDF

This paper presents a bin-packing algorithm for the allocation of tasks to identical processors. For this purpose, we consider the case of independent periodic real-time tasks scheduled under EDF, whose deadlines may not be equal to periods. The presented bin-packing algorithm combines the feasibility condition of Devi [5] with the First Fit binpacking heuristic. The result is an off-line variable-size bin packing which might deliver better results, as shown with an example, than the First Fit Decreasing heuristic on the base of the density condition. Finally, we discuss some interesting issues that rise in relation to the presented algorithm.
Traffic Advisories Based on Route Prediction

Traffic advisories can be delivered to assist travelers in avoiding congested areas and reaching their destinations in a timely manner. Instead of relying on a user to manually enter travel routes and times, we propose a prototype application that learns from the user's travel history and automatically predicts the user's destinations and routes. Traffic flow information is then accessed to determine whether congestions will occur along the predicted routes to warrant the delivery of a traffic advisory alert. User acceptance and trust are evaluated in a field study.
Demand-Driven Path-Sensitive Program Slicing

A reduced-thickness backlighter for an autostereoscopic display is disclosed having a lightguide and at least one light source parallel to an edge of the lightguide so as to be substantially coplanar with the lightguide. The lightguide is provided with a first surface which has a plurality of reflective linear regions, such as elongated grooves or glossy lines, parallel to the illuminated edge of the lightguide. Preferably the lightguide further has a second surface which has a plurality of lenticular lenses for reimaging the reflected light from the linear regions into a series of thin vertical lines outside the guide. Because of the reduced thickness of the backlighter system, autostereoscopic viewing is enabled in applications requiring thin backlighter systems. In addition to taking up less space, the reduced-thickness backlighter uses less lamps and less power. For accommodating 2-D applications, a 2-D diffuser plate or a 2-D lightguide parallel to the 3-D backlighter is disclosed for switching back and forth between 3-D viewing and 2-D viewing.