Collaboration in the 21st century: The theory, assessment, and teaching of collaborative problem solving

in Computers in Human Behavior (2020)

Neural correlates of perceptual color inferences as revealed by #thedress

in Journal of Vision (2020), 20(3(7)),

Color constancy involves disambiguating the spectral characteristics of lights and surfaces, for example to distinguish red in white light from white in red light. Solving this problem appears especially ... [more ▼]

Color constancy involves disambiguating the spectral characteristics of lights and surfaces, for example to distinguish red in white light from white in red light. Solving this problem appears especially challenging for bluish tints, which may be attributed more often to shading, and this bias may underlie the individual differences in whether people described the widely publicized image of #thedress as blue-black or white-gold. To probe these higher-level color inferences, we examined neural correlates of the blue-bias, using frequency-tagging and high-density electroencephalography to monitor responses to 3-Hz alternations between different color versions of #thedress. Specifically, we compared relative neural responses to the original “blue” dress image alternated with the complementary “yellow” image (formed by inverting the chromatic contrast of each pixel). This image pair produced a large modulation of the electroencephalography amplitude at the alternation frequency, consistent with a perceived contrast difference between the blue and yellow images. Furthermore, decoding topographical differences in the blue-yellow asymmetries over occipitoparietal channels predicted blue-black and white-gold observers with over 80% accuracy. The blue-yellow asymmetry was stronger than for a “red” versus “green” pair matched for the same component differences in L versus M or S versus LM chromatic contrast as the blue-yellow pair and thus cannot be accounted for by asymmetries within either precortical cardinal mechanism. Instead, the results may point to neural correlates of a higher-level perceptual representation of surface colors. [less ▲]

A Welfare Evaluation of Green Urban Areas

E-print/Working paper (2020)

Urban green areas cover more than 6% of urban land in Europe. This paper quan-tifies the impact of urban green areas on city structures for more than 300 Europeancities. It discusses the economic effects ... [more ▼]

Urban green areas cover more than 6% of urban land in Europe. This paper quan-tifies the impact of urban green areas on city structures for more than 300 Europeancities. It discusses the economic effects of the local amenity produced by green urbanareas using an urban economics model with various set of preferences. It estimatesthose models using data on detailed residential land uses, green urban areas and popu-lation density. It finally assesses the economic effects of reducing urban green areas incounterfactual exercises where cities are closed and open to migration and green urbanland is converted to residential plots or not. By this strategy, the economic assess-ment accounts for the general equilibrium effects through endogenous land prices andresidential space and location choices. It shows that the gross benefits of urban greenareas are substantial. A uniform removal of half of the urban green areas is equivalentto 6-9% reduction of household annual income. However, the conversion of those areasto residential plots brings a net gain of approximately 4% [less ▲]

How big is big? How fast is fast? A Hands-On Tutorial on Mathematics of Computation

Book published by Amazon (2020)

The assessment of collaborative problem solving in PISA 2015: An investigation of the validity of the PISA 2015 CPS tasks

in Computers and Education (2020)

Flipping Geometric Triangulations on Hyperbolic Surfaces

in symposium on computational geometry (SoCG) (2020)

We consider geometric triangulations of surfaces, i.e., triangulations whose edges can be realized by disjoint locally geodesic segments. We prove that the flip graph of geometric triangulations with ... [more ▼]

We consider geometric triangulations of surfaces, i.e., triangulations whose edges can be realized by disjoint locally geodesic segments. We prove that the flip graph of geometric triangulations with fixed vertices of a flat torus or a closed hyperbolic surface is connected. We give upper bounds on the number of edge flips that are necessary to transform any geometric triangulation on such a surface into a Delaunay triangulation. [less ▲]

All-or-none face categorization in the human brain

in NeuroImage (2020)

Visual categorization is integral for our interaction with the natural environment. In this process, similar selective responses are produced to a class of variable visual inputs. Whether categorization ... [more ▼]

Visual categorization is integral for our interaction with the natural environment. In this process, similar selective responses are produced to a class of variable visual inputs. Whether categorization is supported by partial (graded) or absolute (all-or-none) neural responses in high-level human brain regions is largely unknown. We address this issue with a novel frequency-sweep paradigm probing the evolution of face categorization responses between the minimal and optimal stimulus presentation times. In a first experiment, natural images of variable non-face objects were progressively swept from 120 to 3 ​Hz (8.33–333 ​ms duration) in rapid serial visual presentation sequences. Widely variable face exemplars appeared every 1 ​s, enabling an implicit frequency-tagged face-categorization electroencephalographic (EEG) response at 1 ​Hz. Face-categorization activity emerged with stimulus durations as brief as 17 ​ms (17–83 ​ms across individual participants) but was significant with 33 ​ms durations at the group level. The face categorization response amplitude increased until 83 ​ms stimulus duration (12 ​Hz), implying graded categorization responses. In a second EEG experiment, faces appeared non-periodically throughout such sequences at fixed presentation rates, while participants explicitly categorized faces. A strong correlation between response amplitude and behavioral accuracy across frequency rates suggested that dilution from missed categorizations, rather than a decreased response to each face stimulus, accounted for the graded categorization responses as found in Experiment 1. This was supported by (1) the absence of neural responses to faces that participants failed to categorize explicitly in Experiment 2 and (2) equivalent amplitudes and spatio-temporal signatures of neural responses to behaviorally categorized faces across presentation rates. Overall, these observations provide original evidence that high-level visual categorization of faces, starting at about 100 ​ms following stimulus onset in the human brain, is variable across observers tested under tight temporal constraints, but occurs in an all-or-none fashion. [less ▲]

Reducing overfitting and improving generalization in training convolutional neural network under limited sample sizes in image recognition

in 5th International Conference on Information Technology, Bangsaen 21-22 October 2020 (2020)

Member, Management Board, European Banking Center Network

Diverse speeches and writings (2020)

SYMBOL LEVEL PRECODING TECHNIQUES FOR HARDWARE AND POWER EFFICIENT WIRELESS TRANSCEIVERS

Doctoral thesis (2020)

Large-scale antennas are crucial for next generation wireless communication systems as they improve spectral efficiency, reliability and coverage compared to the traditional ones that are employing ... [more ▼]

Large-scale antennas are crucial for next generation wireless communication systems as they improve spectral efficiency, reliability and coverage compared to the traditional ones that are employing antenna arrays of few elements. However, the large number of antenna elements leads to a big increase in power consumption of conventional fully digital transceivers due to the one Radio Frequency (RF) chain / per antenna element requirement. The RF chains include a number of different components among which are the Digital-to-Analog Converters (DACs)/Analog-to-Digital Converters (ADCs) that their power consumption increases exponential with the resolution they support. Motivated by this, in this thesis, a number of different architectures are proposed with the view to reduce the power consumption and the hardware complexity of the transceiver. In order to optimize the transmission of data through them, corresponding symbol level precoding (SLP) techniques were developed for the proposed architectures. SLP is a technique that mitigates multi-user interference (MUI) by designing the transmitted signals using the Channel State Information and the information-bearing symbols. The cases of both frequency flat and frequency selective channels were considered. First, three different power efficient transmitter designs for transmission over frequency flat channels and their respective SLP schemes are considered. The considered systems tackle the high hardware complexity and power consumption of existing SLP techniques by reducing or completely eliminating fully digital RF chains. The precoding design is formulated as a constrained least squares problem and efficient algorithmic solutions are developed via the Coordinate Descent method. Next, the case of frequency selective channels is considered. To this end, Constant Envelope precoding in a Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing system (CE MIMO-OFDM) is considered. In CE MIMO-OFDM the transmitted signals for each antenna are designed to have constant amplitude regardless of the channel realization and the information symbols that must be conveyed to the users. This facilitates the use of power-efficient components, such as phase shifters and non-linear power amplifiers. The precoding problem is firstly formulated as a least-squares problem with a unit-modulus constraint and solved using an algorithm based on the coordinate descent (CCD) optimization framework and then, after reformulating the problem into an unconstrained non-linear least squares problem, a more computationally efficient solution using the Gauss-Newton algorithm is presented. Then, CE MIMO-OFDM is considered for a system with low resolution DACs. The precoding design problem is formulated as a mixed discrete- continuous least-squares optimization one which is NP-hard. An efficient low complexity solution is developed based also on the CCD optimization framework. Finally, a precoding scheme is presented for OFDM transmission in MIMO systems based on one-bit DACs and ADCs at the transmitter’s and the receiver’s end, respectively, as a way to reduce the total power consumption. The objective of the precoding design is to mitigate the effects of one-bit quantization and the problem is formulated and then is split into two NP hard least squares optimization problems. Algorithmic solutions are developed for the solution of the latter problems, based on the CCD framework. [less ▲]