Reviewerly/exHarmony huggingface dataset:
The Politics of the Knowledge Economy and the Rise of Populism

This chapter considers the “second-order” effects of the transition to the knowledge economy. This means the set of preferences, beliefs, and party allegiances that are crystallizing as a consequence of the political-economic realities brought about by the knowledge economy. Chapter 3 considered “first-order” effects—immediate policy responses reflecting existing political coalitions—and showed that these responses were relatively limited and in most countries, failed to offer much compensation for those who lost out in the collapse of the Fordist economy. This chapter argues that this failure has created the political conditions for the rise of populism. Populism refers to a set of preferences and beliefs that rejects established parties and elites, that sees established politicians as gaming the system to their own advantage, and that at the same time sees the poor as undeserving of government support.
Earthquake Disasters and Government Committees

After major devastating earthquakes, the Japanese government has set up committees to promote seismological research and to reduce future earthquake damage. Two committees have made efforts to assess possible precursors for large earthquakes with particular emphasis in Tokai region, but such short-term deterministic prediction is now considered difficult in the seismological community. The Headquarters of Earthquake Research Promotion, established after the 1995 Kobe earthquake, promoted to expand the geophysical observation network, made long-term and probabilistic forecast of earthquakes on active faults and subductions zones, predicted strong ground motion from such earthquakes, and made national seismic hazard maps including probabilistic estimation of ground motion. Such long-term forecast and ground motion prediction was made before the 2016 Kumamoto earthquake, but the results were not fully utilized by local governments or the general public to prepare for potential earthquake. The Central Disaster Management Council estimated the maximum possible earthquakes along the Nankai Trough and beneath the Tokyo metropolitan area, assessed the human, building and economic losses from such earthquakes, and made policies to reduce such damage.
Leading the New Normal by “Four Comprehensives” in Innovation and Entrepreneurship Education at Institutions of Higher Learning

The strategic blueprint of â€œfour comprehensivesâ€ centrally embodies the strategic thought of the Party Central Committee for the governance of China since the 18th National Congress of the Communist Party of China. It is an important guideline for behavior for quickening construction of an innovative type country and promoting steady growth of economy to clearly understand the inexorable trend of reform in innovation and entrepreneurship education at institutions of higher learning, and lead the new normal in innovation and entrepreneurship education in institutions of higher learning under the instruction of â€œfour comprehensivesâ€.
CaRT: Framework for Semantic Query Correction and Relaxation

With the emergence of the resource description framework (RDF) graphs, the SPARQL query processing on the large-scale RDF graph has become a more challenging problem. However, the efficiency of SPARQL query is difficult to reach and there are several issues that may arise. In our work, we address the problem of the no answer query. Many approaches are proposed to deal with this problem. These approaches used in generally relaxation methods to help user in finding alternative answers when their queries fail or do not return the expected answers. However, the majority of the proposed works don’t detect and show to the user the cause of failure. This paper presents a Correct-and-Relax Triples (CaRT) framework designed to facilitate the exploitation of large knowledge base. Our framework proposes a new relaxation method that detects and corrects only the failed triples of a failed SPARQL query. We conducted comprehensive experiments on a benchmark RDF dataset and demonstrated the performance of our approach by improving the efficiency of the SPRQL query.
Standard Plenoptic Camera Calibration for a Range of Zoom and Focus Levels

Plenoptic cameras have a complex optical geometry combining a main lens, a microlens array and an image sensor to capture the radiance of the light rays in the scene in its spatial and directional dimensions. As conventional cameras, changing the zoom and focus settings originate different parameters to describe the cameras, and consequently a new calibration is needed. Current calibration procedures for these cameras require the acquisition of a dataset with a calibration pattern for the specific zoom and focus settings. Complementarily, standard plenoptic cameras (SPCs) provide metadata parameters with the acquired images that are not considered on the calibration procedures. In this work, we establish the relationships between the camera model parameters of a SPC obtained by calibration and the metadata parameters provided by the camera manufacturer. These relationships are used to obtain an estimate of the camera model parameters for a given zoom and focus setting without having to acquire a calibration dataset. Experiments show that the parameters estimated by acquiring a calibration dataset and applying a calibration procedure are similar to the parameters obtained based on the metadata.
Your Online and Offline Presence

Job satisfaction is an important topic for software developers. Some developers just want to earn more money. Others want better job security or better working conditions. Other developers want to leave a heritage by affecting the lives of many people and building something they are really proud of.
Learning and visual attention across neurodevel-opmental conditions: Using Multiple Object-Tracking as a descriptor of visual attention

While most studies in Multiple Object-Tracking (MOT) have focused on understanding the mechanisms of visual tracking, recent work has suggested that MOT can be used to characterize individual differences in attention resource capacity (Tullo, et al., 2018). In the current study, we investigated whether repeated practice on an adaptive MOT task could explain the interplay between attention resource capacity and learning in relation to individuals diagnosed with neurodevelopmental conditions. Specifically, we investigated whether MOT performance would differ across neurodevelopmental conditions that are either defined by deficits in attention (e.g., ADHD), or exhibit clinically significant difficulties in attention among other deficiencies (e.g., Autism). We asked whether intelligence, our proxy for cognitive capability, and/or diagnostic profile (i.e., autism, ADHD, Intellectual Disability [ID], and Learning Disability [LD]) predicted learning on daily MOT performance across 15 sessions. Children and adolescents (N=106; Mage=13.51) with a diagnosis of either autism (n=32), ADHD (n=35), or ID/LD (n=39) visually tracked 3 of 8 spheres for 8 seconds. Task difficulty adapted to the participant’s capability on a trial-by-trial basis. Performance was defined as the average speed in cm/s, where participants correctly tracked all target items. Results indicated that MOT performance mapped onto a logarithmic function, which resembled a typical learning curve at R2=0.87. Performance improved by 105% from the first to last day of testing. Moreover, day-one performance was predicted by intelligence: R2=0.28, and the rate of change in performance (i.e., learning) differed across diagnostic groups. Children and adolescents with autism (MsD1-1=1.11) demonstrated a greater standardized change than those with ADHD (MsD1-15=0.54) or ID/LD (MsD1-15=0.52). These differences highlight variability in learning capability and attention resource capacity, which vary by diagnosis and higher-level cognitive ability, such as fluid reasoning intelligence. Overall, these findings emphasize the promise and utility of MOT to define both attentional and learning capabilities across individuals.
Component processes of Visual Search: Insights from neuroscience

I will discuss cognitive and neural mechanisms that contribute to VS, how these mechanisms are organized in real time, and how they change across the lifespan. These component processes include the ability to activate representations of search targets (attentional templates), the guidance of attention towards target objects, as well as the subsequent attentional selection of these objects and their encoding into working memory. The efficiency of VS performance changes considerably across the life span. I will discuss findings from search experiment with children, adults, and the elderly, in order to understand which component processes of VS show the most pronounced changes with age. I will focus on the time course of target template activation processes, differences between space-based and feature-based attentional guidance, and the speed with which attention is allocated to search targets.
Statistical learning enables implicit subadditive predictions

The visual system readily detects statistical relationships where multiple cues jointly predict a specific outcome (e.g., two co-authors publishing a paper, or two co-founders starting a company). What is less known is how the visual system generates predictions when only a single cue is present, after learning that the two cues were previously jointly associated with an outcome. Here we examine three hypotheses: (1) complete inheritance hypothesis where the single cue predicts 100% of the outcome previously associated with the two cues, (2) proportional inheritance hypothesis where the single cue predicts 50% of the outcome, and (3) subadditive hypothesis where the single cue predicts more than 50% but less than 100% of the outcome, consistent with support theory (Tversky & Koehler, 1994). To test these hypotheses, we used a statistical learning paradigm where participants were exposed to two objects (e.g., red and blue squares) that were followed by a circle with a specific size. After exposure, participants viewed a single object (e.g., a red square) at a time and were asked to estimate the circle size that was associated with the object. Afterwards, participants recalled the size of the circle that followed the two objects during exposure. We found that the estimated size associated with the single object was significantly smaller than the recalled size associated with the two objects, but significantly larger than 50% of the recalled size (Experiment 1), or larger than 33% of the recalled size in case of three objects (Experiment 2). This confirms the subadditive hypothesis. Importantly, no participants were consciously aware of the association between the objects and the circle size. The results reveal a new consequence of statistical learning on visual inferences: when multiple objects predict a specific outcome, the single object is implicitly expected to predict an outcome in a subadditive fashion.
How to create objects with your mind: From object-based attention to attention-based objects

A curious thing can happen when you stare at a regular gridlike pattern — e.g. a piece of graph paper, or the tiles on a bathroom floor. Although such patterns contain no structure, you may often begin to see structure anyway (e.g. a block ‘+’ shape). This phenomenon appears to be based on attention to relevant squares of the grid, and previous (older, underappreciated) research demonstrated that these squares do indeed accrue attentional benefits, such as faster probe detection. We will call this phenomenon scaffolded attention, because of how the grid provides a scaffold for selection.(Note that you cannot see these same shapes when staring at a blank page.) Here we asked whether this form of attention actually creates bona fide object representations that go on to enjoy object-specific effects. In essence, whereas previous work explored many cues to ‘object-based attention’ (e.g. involving continuity and closure), these current studies ask whether attention can be object-based even with no cues to objecthood at all. In several experiments (each with a direct replication), observers viewed 3×3 grids, and attended to particular squares until they could effectively see shapes such as two vertical (or horizontal) lines, or a block-letter H (or I). As they engaged in this form of scaffolded attention, two probes appeared, and observers simply reported whether they were the same or different. Remarkably, this produced a traditional ‘same-object advantage’: performance was enhanced for probes presented on the same (purely imagined) object, compared to equidistant probes presented on different objects — while equating for spatial factors. Thus, attention to the relevant squares effectively groups them, forming object representations out of thin (scaffolded) air. In other words, this demonstrates an unexpected inversion of the typical relationship between objects and attention: there is not only object-based attention, but also attention-based objects.
The fixation-related N400 during natural scene viewing: Investigating the foveal vs. extrafoveal processing of object semantics

In vision science, a topic of great interest and controversy is the processing of objects that are (in)consistent with the overall meaning of the scene in which they occur. Two interrelated questions are at the core of this debate. First, how much time is needed to determine the meanings and identities of objects in a scene, and second, whether foveal vision is required to access object-scene semantics. Results from eye-movement studies have been mixed, ranging from rapid processing of semantic information in peripheral vision to a lack of evidence for extrafoveal semantic processing. Here, we aimed at contributing to this debate by co-registering eye-movements and EEG during unconstrained viewing of naturalistic scenes. Participants inspected photographs of real-world scenes (e.g. a bathroom) in which the consistency of a target object (e.g. toothpaste vs. flashlight) was systematically manipulated in preparation of a later change detection task. The EEG was analyzed using linear deconvolution modelling to examine the fixation-related brain potentials (FRPs) evoked by the first fixation on the target object (t), the preceding fixation (t-1), as well as all other non-target fixations on the scene. The eye-movement data showed that inconsistent objects were prioritized over consistent objects (looked at earlier) and were more effortful to process (looked at longer). The FRPs demonstrated that the frontocentral N400 effect for scenes generalizes from steady-fixation paradigms to natural viewing. Crucially, this fixation-related N400 initiated during the pre-target fixation t-1 and continued throughout fixation t, which suggests that the extraction of object semantics already began in extrafoveal vision. However, there was no significant effect of consistency on the probability of immediate target fixation and on the ERP aligned to scene onset, which suggests that object-scene semantics was not immediately accessed. Taken together, these results emphasize the usefulness of combined EEG/eye-movement recordings for understanding high-level scene processing.
High-Dimensional Quantum Communication Using Space Encoding

Quantum communication (QC) represents a key enabler for many quantum applications. However, low information rates and short propagation distances, limit the development of this field and its practical applications. High-dimensional (Hi-D) QC can address these challenges enhancing the information rate and the systems error tolerance. We report our recent results on Hi-D quantum communication where we prove the capability of preparing, manipulating, transmitting and measuring Hi-D quantum states through multi-core and multimode fiber.
The Issues Related on Semantics of Construction in Korean Linguistics

This study aims to compensates Jeong & Jeong(2019) which reviews the literature of Korean linguistics having done under the name of Construction Grammar. There were some issues in the literature, related on semantics of construction.<BR>First, when verbs are used in constructions that are incompatible with their original meaning, there were discussions that the construction can modify the verb’s meaning, and that the verb choose the construction after the verb’s meaning changes. We discussed that it is not uncommon for a construction to dominate and to control the meaning of a verb, and we cannot only consider the possibility of a verb’s choosing a construction after the meaning changes first.<BR>Second, when there are several constructions of same form, the problem can be raised that which of them can be seen in the relation of polysemy. In this paper, according to Nam(2005) on the homonymy and polysemy of lexical elements, discussed that the constructions that share the ‘same conceptual properties’ can be understood as the constructions in the relation of polysemy.
Modeling attention during visual search with hierarchical Bayesian inference

The Bayesian brain hypothesis (Knill & Pouget, 2004) suggests that the visual cortex infers properties of a visual scene by computing conditional probabilities of underlying causes given a particular image. Within this framework, top-down spatial and feature-based attention have been modeled as feedback of prior probabilities over locations and features, respectively (Rao, 2004; Chikkerur et al., 2010). The present study investigated whether, given an image and top-down priors, the posterior probability of a feature map could be used to guide simulated eye movements in a computational model performing a visual search task. A two-layer hierarchical generative model (Lee et al., 2009) was trained on images of handwritten digits (MNIST; LeCun et al., 1998) using unsupervised learning. In this model, activity in the first layer represents the conditional probability of features (e.g., oriented lines), given the image, while feedback from the second layer represents the prior over first-layer features. In order to simulate eye movements, the model selected locations within the image based on the maximum posterior probability of the first-layer feature map, given the image and second-layer feedback. The model was tested using a visual search task for a digit (approximately 20×20 pixels) placed among non-digit distractors in a 60×60 pixel search array. For each trial, the model selected the most probable location of a single target digit placed randomly in the search array. In order to quantify the accuracy of the model, correct trials were defined as selecting a location within 10 pixels of the target center. Across 10,000 trials, the model was able to correctly locate the target on 70% of trials (chance: 11%). These results suggest that a visual system conforming to the Bayesian brain hypothesis could accurately perform visual search by using Bayes’ rule to combine bottom-up sensory information with top-down priors.
Innovative Use of Open Educational Resources in the Higher Education Libraries

Advancement in Science and Technology has made a tremendous impact on library and information centers. It has changed the traditional libraries and information centers into digital libraries, and library services are oriented towards ICT. As an outcome, e-resources are becoming more common among the libraries of higher educational institutions. They have gradually replaced the traditional print resources. Unfortunately, most of the libraries in the higher education sector except reputed institutions are facing a financial crunch situation. These institutions due to the limitation in the budget, find it hard to fulfill the information requirements of its users in the electronic environment. The cost of subscription to electronic resources goes beyond the purchasing capacity of the parent institution. Funding agencies at the institutions adopt consortia-based approach rather than individual institutional funding. In this context, open education resources fulfill the information requirements of the higher education institution. This chapter analyzes these open educational resources.
EXPERIENCE OF USING THE ROBBO ROBOTIC KIT IN STUDENTS' PROJECT ACTIVITY

The article discusses the advantages of the ROBBO kit, which includes the constructor ROBBO Laboratory and the children's IoT solution ROBBO Roboplatform over other robotic solutions used in the educational process. An example of a project for the group use of the ROBBO Laboratory and the ROBBO Roboplatform is given.
Teacher education and popular culture: proverbs about the climate and weather

This research was funded by CIEd – Research Centre on Education, projects UID/CED/1661/2013 and UID/CED/1661/2016, Institute of Education, University of Minho, through national funds of FCT/MCTES-PT, and by FCT through the research fellowship Reference SFRH/BD/120532/2016.
Re-re-considering Yarbus: Predicting observer “taskiness” from eye movement patterns

Greene, Liu and Wolfe reported a negative result for identifying task using eye movements (2012). Others have challenged this finding, often by substituting dynamic for static features (Boisvert & Bruce, 2016). We propose instead mapping eye movements onto a latent dynamic manifold with connected, overlapping regions of related task effects. This manifold’s structure is defined using features extracted from a variational auto-encoder trained on multi-dimensional time-series of values for two different salience maps at observer fixation locations (GBVS: Harel et al., 2007; modified semantic similarity: Rose & Bex, 2018). This approach helps reconcile Greene’s findings with others’ by treating eye movement as less “task driven” than “tasky”: affected by current task while remaining influenced by those performed in the past. We therefore hypothesized that observers’ sequential performance of different tasks–as in Greene and colleagues’ study–may deflect behavior across manifold regions, decreasing classifiability. Performing the same task should result in more regular trajectories within a manifold, increasing classifiability. We tested this hypothesis on three data-sets first by comparing classification accuracy per task/trial using twenty-five manifold features and a SVM classifier. Second, we compared sequential determinism and entropy in trial-to-trial sequences of feature distances to separating hyperplanes using multidimensional recurrence quantification analysis (Wallot, 2016). For two sets (Koehler et al.,2014; Borji&Itti, 2014,Expt.2), subjects always performed the same task. In the third (created in-lab), tasks were randomized across trials. Classification performance was significantly above chance and equivalent to that reported elsewhere for random order studies (Borji & Itti, 2014:24.2%, ours:24.6%, chance:14.2%; Boisvert & Bruce,2016:53.4%; ours:51%, chance:33.3%) but not the third (ours:39.5%, chance:33.3%). Determinism was also significantly higher and entropy significantly lower for the random task order experiment than for the others (Kruskal-Wallis, p< 0.001). Our method therefore both retains high discrete classification peformance while connecting task effects to other efforts concerning serial dependencies (Fischer & Whitney,2014).