Information distribution within musical segments

In the research on word recognition, it has been shown that word beginnings have higher information content for word identification than word endings; this asymmetric information distribution within words has been argued to be due to the communicative pressure to allow words in speech to be recognized as early as possible. Through entropy analysis using two representative datasets from Wikifonia and the Essen folksong corpus respectively, here we show that musical segments also have higher information content (i.e., higher entropy) in segment beginnings than endings. Nevertheless, this asymmetry was not as dramatic as that found within words, and the highest information content was observed in the middle of the segments (i.e., an inverted-U pattern). This effect may be because the first and last notes of a musical segment tend to be tonally stable, with more flexibility in the first note for providing the initial context. The asymmetric information distribution within words has been shown to be an important factor accounting for various asymmetric effects in word reading, such as the left-biased preferred viewing location and optimal viewing position effects. Similarly, the asymmetric information distribution within musical segments is a potential factor that can modulate music reading behavior and should not be overlooked.published_or_final_versio

Eye movement pattern in face recognition is associated with cognitive decline in the elderly

Conference Theme: Mind, Technology, and SocietyThe present study investigated the relationship between eye movement pattern in face recognition and cognitive perform-ance during natural aging through modeling and comparing eye movement of young (18-24 years) and older (65-81 years) adults using Hidden Markov Model (HMM) based approach. Young adults recognized faces better than older adults, particularly when measured by the false alarm rate. Older adults’ recognition performance, on the other hand, correlated with their cognitive status assessed by the Montreal Cognitive Assessment (MoCA). Eye movement analysis with HMM revealed two different strategies, namely “analytic” and “holistic”. Participants using the analytic strategy had better recognition performance (particularly in the false alarm rate) than those using the holistic strategy. Significantly more young adults adopted the analytic strategy; whereas more older adults adopted the holistic strategy. Interestingly, older adults with lower cognitive status were associated with higher likelihood of using the holistic strategy. These results suggest an association between holistic eye movement patterns and cognitive decline in the elderly.postprin

Hidden Markov modeling of eye movements with image information leads to better discovery of regions of interest

Conference Theme: Integrating Psychological, Philosophical, Linguistic, Computational and Neural PerspectivesPoster Session 2: no. 56Hidden Markov models (HMM) can describe the spatial and temporal characteristics of eye-tracking recordings in cognitive tasks. Here, we introduce a new HMM approach. We developed HMMs based on fixation locations and we also used image information as an input feature. We demonstrate the benefits of the newly proposed model in a face recognition study wherein an HMM was developed for every subject. Discovery of regions of interest on facial stimuli is improved compared to earlier approaches. Moreover, clustering of the newly developed HMMs lead to very distinct groups. The newly developed approach also allows reconstructing image information at fixation.postprin

Hidden Markov model analysis reveals better eye movement strategies in face recognition

Conference Theme: Mind, Technology, and SocietyHere we explored eye movement strategies that lead to better performance in face recognition with hidden Markov models (HMMs). Participants performed a standard face recognition memory task with eye movements recorded. The durations and locations of the fixations were analyzed using HMMs for both the study and the test phases. Results showed that in the study phase, the participants who looked more often at the eyes and shifted between different regions on the face with long fixation durations had better performances. The test phase analyses revealed that an efficient, short first orienting fixation followed by a more analytic pattern focusing mainly on the eyes led to better performances. These strategies could not be revealed by analysis methods that do not take individual differences in both temporal and spatial dimensions of eye movements into account, demonstrating the power of the HMM approach.postprin

Scanpath modeling and classification with Hidden Markov Models

How people look at visual information reveals fundamental information about them; their interests and their states of mind. Previous studies showed that scanpath, i.e., the sequence of eye movements made by an observer exploring a visual stimulus, can be used to infer observer-related (e.g., task at hand) and stimuli-related (e.g., image semantic category) information. However, eye movements are complex signals and many of these studies rely on limited gaze descriptors and bespoke datasets. Here, we provide a turnkey method for scanpath modeling and classification. This method relies on variational hidden Markov models (HMMs) and discriminant analysis (DA). HMMs encapsulate the dynamic and individualistic dimensions of gaze behavior, allowing DA to capture systematic patterns diagnostic of a given class of observers and/or stimuli. We test our approach on two very different datasets. Firstly, we use fixations recorded while viewing 800 static natural scene images, and infer an observer-related characteristic: the task at hand. We achieve an average of 55.9% correct classification rate (chance = 33%). We show that correct classification rates positively correlate with the number of salient regions present in the stimuli. Secondly, we use eye positions recorded while viewing 15 conversational videos, and infer a stimulus-related characteristic: the presence or absence of original soundtrack. We achieve an average 81.2% correct classification rate (chance = 50%). HMMs allow to integrate bottom-up, top-down, and oculomotor influences into a single model of gaze behavior. This synergistic approach between behavior and machine learning will open new avenues for simple quantification of gazing behavior. We release SMAC with HMM, a Matlab toolbox freely available to the community under an open-source license agreement.published_or_final_versio

Calculations of the refractive index of AlGaN/GaN quantum well

We have calculated the refractive index of a AlxGa1-xN/GaN square quantum well (QW). The imaginary part of the dielectric function has been obtained by summing up the contributions of the dominant interband transitions, excitonic contributions, and the continuum contribution, obtained by weighting the well's and the barrier's continuum contributions. In the calculation of the contribution of the conduction-valence band bound-state effect without electron-hole interaction, conduction bands are assumed to be parabolic and valence bands have been calculated using Chuang's model [Phys. Rev. B 54, 2491 (1996)], but with Chan's basis expansion method [J. Phys. C 19, L125 (1986)] instead of finite-difference scheme. Excitonic contribution has been described with an expression derived by the density-matrix approach at the subband edge without the influence of band mixing. The continuum contributions have been described with the modified Adachi's model. The effects of the aluminum mole fraction x and the width of the well on the refractive index are analyzed and discussed.published_or_final_versio

Analytic eye movement patterns in face recognition are associated with better performance and more top-down control of visual attention: an fMRI study

Conference Theme: Integrating Psychological, Philosophical, Linguistic, Computational and Neural PerspectivesPoster Session 3: no. 57Recent research has revealed two different eye movement patterns during face recognition: holistic and analytic. The present study investigated the neural correlates of these two patterns through functional magnetic resonance imaging (fMRI). A more holistic pattern was associated with more activation in the face-selective perceptual areas, including the occipital face area and fusiform face area. In contrast, participants using a more analytic pattern demonstrated more activation in areas important for top-down control of visual attention, including the frontal eye field and intraparietal sulcus. In addition, participants using the analytic patterns had better recognition performance than those showing holistic patterns. These results suggest that analytic eye movement patterns are associated with more engagement of top-down control of visual attention, which may consequently enhance recognition performance.postprin

J-Class Abelian Semigroups of Matrices on C^n and Hypercyclicity

We give a characterization of hypercyclic finitely generated abelian semigroups of matrices on C^n using the extended limit sets (the J-sets). Moreover we construct for any n\geq 2 an abelian semigroup G of GL(n;C) generated by n + 1 diagonal matrices which is locally hypercyclic but not hypercyclic and such that JG(e_k) = C^n for every k = 1; : : : ; n, where (e_1; : : : ; e_n) is the canonical basis of C^n. This gives a negative answer to a question raised by Costakis and Manoussos.Comment: 10 page

A Generalized Loss Function for Crowd Counting and Localization

Previous work [40] shows that a better density map representation can improve the performance of crowd counting. In this paper, we investigate learning the density map representation through an unbalanced optimal transport problem, and propose a generalized loss function to learn density maps for crowd counting and localization. We prove that pixel-wise L2 loss and Bayesian loss [29] are special cases and suboptimal solutions to our proposed loss function. A perspective-guided transport cost function is further proposed to better handle the perspective transformation in crowd images. Since the predicted density will be pushed toward annotation positions, the density map prediction will be sparse and can naturally be used for localization. Finally, the proposed loss outperforms other losses on four large-scale datasets for counting, and achieves the best localization performance on NWPU-Crowd and UCF-QNRF

Phthalocyanine based Schottky solar cells

Phthalocyanine (Pc) materials are commonly used in organic solar cells. Four different phthalocyanines, nickel phthalocyanine (NiPc), copper phthalocyanine (CuPc), iron phthalocyanine (FePc), and cobalt phthalocyanine (CoPc) have been investigated for organic solar cell applications. The devices consisted of indium tin oxide (ITO) coated glass substrate, Pc layer, and aluminum (Al) electrode. It has been found that ITO/CuPc/Al Schottky cell exhibits the best performance. To investigate the influence of the active layer thickness on the cell performance, cells with several different thicknesses were fabricated and optimal value was found. Schottky cell exhibits optimal performance with one ohmic and one barrier contact. However, it is suspected that ITO/CuPc contact is not ohmic. Therefore, we have investigated various ITO surface treatments for improving the performance of CuPc based Schottky solar cell. We have found that cell on ITO treated with HCl and UV-ozone exhibits the best performance. AM1 power conversion efficiency can be improved by 30% compared to cell made with untreated ITO substrate. To improve power conversion efficiency, double or multilayer structure are required, and it is expected that suitable ITO treatments for those devices will further improve their performance by improving the contact between ITO and phthalocyanine layer.published_or_final_versio