Reviewerly/exHarmony huggingface dataset:
Weighing the contribution of object identity vs configuration information in convolutional neural network scene representation

Visual perception involves extracting the specific identities of the objects comprising the scene in conjunction with their configuration (spatial layout of objects). How a visual information processing system weights these two types of information during scene processing, however, has never been examined. Convolutional neural networks (CNNs) are one class of visual information processing system, and recent developments have demonstrated their ability to accurately classify both object images and scene images. To understand the relative contribution of object identity and configuration information in CNN scene representation, we examined four CNN architectures (Alexnet, Resnet18, Resnet50, Densenet161) trained on either an object identification task or a scene recognition task. Each CNN was run on 20 sets of indoor scene images (e.g., a room with furniture). For each set, we created four images obtained by crossing two object sets (e.g., different pieces of furniture) in two different configurations. For a given CNN layer, we obtained the activations for each image in a set and then calculated the relative strength of object identity and configuration representation by measuring (1) the Euclidean distance for two images sharing the same configuration but different objects and (2) the Euclidean distance for two images sharing the same objects but different configurations. Object identity dominance is then measured as [(1)-(2)]/[(1)+(2)], with a value of 1 indicating an object-dependent representation that disregards their configuration, and -1 indicating a configuration-dependent representation that disregards the objects in it. All the CNNs revealed a statistically significant (p < .05) preference for configuration representations in early layers. In later layers, however, object representations dominated (p < .05). The same results hold regardless of whether a CNN was trained in the object or scene recognition task. These results provide significant insights regarding how object identity and configuration may contribute to scene representation in a CNN.
Eye movements reveal event understanding in visual narratives

What guides eye movements while viewing visual narratives? More specifically, do comprehension processes influence attentional selection when reading wordless picture stories? According to the Scene Perception & Event Comprehension Theory (SPECT) there are front-end processes, such as attentional selection, that occur during single eye fixations, and back-end processes, such as building an event model, that occur in working memory and long-term memory. Here we have investigated how attentional selection may be influenced by event models while people view visual narratives. Prior research has shown that as more situational changes occur in a visual narrative (e.g., space, time, characters, goals and sub-goals), viewers are more likely to perceive an event boundary (i.e., beginning of an event) (Magliano et al., 2011). Other research has shown that viewing times increase at event boundaries (Hard, Recchia & Tversky, 2011; Smith, Newberry & Bailey, 2019). In an eye-tracking study using the “Boy, Dog, Frog” picture stories, we replicated the findings that spatiotemporal and character changes produced higher event segmentation. We also replicated the findings that viewing time was longer at event boundaries. We then extended those findings to eye movements. We asked whether the longer viewing times at event boundaries, when more event indices changed, were due to longer fixations (i.e., increased processing load), or more fixations (i.e., more search for information). Longer viewing times were strongly associated with more fixations, not longer fixations, supporting the search hypothesis. Both viewing times and the number of fixations were found to be significantly predicted by spatiotemporal changes, character changes, and the beginning of superordinate goals. Further analyses will assess whether these additional fixations are simply allocated to the new and salient content in an image, or if they are also specifically directed towards the contents necessary to make inferences about the characters’ goals in the narrative.
Methods for Evaluating Depth Perception in a Large-Screen Immersive Display

We perform an experiment on distance perception in a large-screen display immersive virtual environment. Large-screen displays typically make direct blind walking tasks impossible, despite them being a popular distance response measure in the real world and in head-mounted displays. We use a movable large-screen display to compare direct blind walking and indirect triangulated pointing with monoscopic viewing. We find that participants judged distances to be 89.4% ± 28.7% and 108.5% ± 44.9% of their actual distances in the direct blind walking and triangulated pointing conditions, respectively. However, we find no statistically significant difference between these approaches. This work adds to the limited number of research studies on egocentric distance judgments with a large display wall for distances of 3-5 meters. It is the first, to our knowledge, to perform direct blind walking with a large display.
SOM-Based Visualization of Potential Technical Solutions with Fuzzy Bag-of-Words Utilizing Multi-view Information

SOM-based visualization is a promising approach for revealing potential technical solutions varied in patent documents. In this paper, we try to improve the quality of visual representation by constructing Fuzzy Bag-of-Words (FBoW) matrices through utilization of multi-view information. F-term is the special theme code given by the examiners of Japan Patent Office (JPO) for Japanese patent documents and is expected to be a potential candidate of second-view information. Document $$\times $$ F-term co-occurrence information is utilized for improving the quality of FBoW representation such that semantical similarities among words are measured by considering F-term semantics. The advantage of utilizing F-term semantics in constructing FBoW is demonstrated through analysis of patent document data.
Research on the Cultivation Strategies of Oral Ability in Computer-Assisted College English Teaching

In recent years, with the widespread use and promotion of English, college English teaching methods are undergoing tremendous changes. The cultivation of college English oral expression ability has received more and more attention. However, in the actual teaching process, the cultivation of college English oral ability is still weak, and the teaching effect is not good. In view of the current situation of college oral English training and the problems existing in the process of computer-assisted college English teaching, this paper puts forward the corresponding strategies of computer-assisted oral English teaching, which will provide a new direction for future research on computer-assisted oral English training.
The Classification of Magic SET Squares

Abstract A magic SET square is a 3 by 3 table of SET cards such that each row, column, diagonal, and anti-diagonal is a set. We allow the following transformations of the square: shuffling features, shuffling values within the features, rotations and reflections of the square. Under these transformations, there are 21 types of magic SET squares. We calculate the number of squares of each type. In addition, we discuss a game of SET tic-tac-toe.
How much time do you have? Introducing a multi-duration saliency model

What jumps out in a single glance of an image is different than what you might notice after closer inspection. Despite this, current computational models of visual saliency predict human gaze patterns at an arbitrary, fixed viewing duration (one image: one saliency map). This offers a limited view of the rich interactions between image content and gaze, and obscures the fact that different image content might be salient at different time points. In this paper we propose to capture gaze as a series of snapshots (one image: multiple saliency maps). Rather than aggregating individual scanpaths, we directly generate population-level saliency heatmaps for multiple viewing durations. Towards this goal, we turn to CodeCharts UI, a cost-effective interface for crowdsourcing gaze data without requiring an eye tracker. This interface provides precise control over timing, which allows us to gather attention patterns at different viewing durations. We collect the CodeCharts1K dataset with attention data for 0.5, 3, and 5 seconds of free-viewing on images from action, memorability, and out-of-context datasets. We find that gaze locations differ significantly across the three viewing durations but are consistent across participants within a duration, leading to multiple distinct heatmaps per image. Using insights from our analysis of human gaze data, we develop a temporally-aware deep learning model of saliency that simultaneously trains on data from multiple viewing durations. Our computational model achieves competitive performance on the LSUN 2017 Saliency Prediction Challenge when tested at the same viewing duration used for collecting the ground-truth human data. Importantly, our model also simultaneously produces predictions at multiple viewing durations. We discuss how knowing what is salient over different viewing windows can be used for image cropping, compression, and captioning applications.
DESIGNING A WEB RESOURCE FOR STUDYING THE ARDUINO PLATFORM AS A MEANS OF GENERATING THE PROFESSIONAL COMPETENCE OF FUTURE ENGINEERS-PROGRAMMERS WITH A HIGHER EDUCATION LEVEL “MASTER”

In the context of computerization of higher education institutions, the use of electronic resources, in particular sites for educational purposes, electronic textbooks, video collections, is aimed at increasing the level of professional training of students. As electronic educational resources are an integral part of the learning process, they have an educational and methodological purpose and serve to provide educational activities for students. They are considered one’s of the key elements of the informative and educational environment. One of them is educational web resources. Using modern web technologies, the education system and, as well, further computerization can be significantly improved. This process is irreversible and compulsory. Сonsidering this, the educational web resources are the best way for improving the educational level of contemporary teachers. The article is devoted to the design of an educational web resource for the study of the platform for Arduino's amateur design as a computer tool for the formation of professional competence of students of specialty 122 “Computer Science”, 121 “Software Engineering” at the level of higher education “Master”. The simulation of this web resource focuses on the systematization of knowledge and the development of practical design skills in the Arduino hardware computing platform when studying undergraduates of the disciplines “Quality Management of Electronic Educational Resources” and “Information Management Technologies”. In the process of designig, students determine the purpose and tasks of learning through electronic educational resources, analyze the existing analogs of the Arduino study sites, distinguish the main groups of requirements, design information architecture, present a precedent diagram for the roles specific to the website for educational purposes. The application of this topic in the educational process of the Kherson State University is aimed at developing professional competences for future programmers through the active introduction of new educational technologies, the use of opportunities for the information space, and the partnership between the teacher and the student.
Rethinking boundary extension as a universal phenomenon of visual memory

Boundary extension—a memory distortion in which observers misremember a scene as containing visual information beyond its edges—is widely regarded as a universal effect in visual memory, reflecting our brain’s automatic extrapolation of scene information. However, most studies of boundary extension exclusively focus on a narrow stimulus set of object-oriented images. In this study, we test 2000 participants on a recognition-based boundary transformation paradigm across a naturalistic set of images, consisting of 500 object-oriented images and 500 scene-oriented images. While the object-oriented images replicate previous boundary extension findings, the scene-oriented images show equal proportions of both boundary extension and the opposite effect of boundary contraction. The direction of boundary transformation is highly predictable from simple image properties: images with fewer, central, close and large objects tend to cause extension, while images with more, dispersed, distant, small objects cause contraction. Finally, these boundary transformation scores are highly consistent across paradigms (both rapid recognition and recall drawings), including a perceptual task with minimal memory load in which participants draw copies of images while viewing them with no time limit. Collectively, these results put into question boundary extension as a universal scene memory phenomenon, given that we observe boundary contraction for the most scene-like images, and that these effects occur even during minimal memory conditions. These findings also suggest alternate image-property-based accounts of scene transformation in the brain. Crucially, these results highlight the importance of revisiting already accepted psychological phenomena and the necessity to always consider broad, representative samples and images when making global inferences about the brain.
Covid-19: perspectives and initiatives in older adults health context in Brazil/ Covid-19: perspectivas e iniciativas no contexto da saúde do idoso no Brasil

Abstract This article provides information about COVID-19, contextualizing the national and international scenario, with an emphasis on the health of the elderly. Perspectives and initiatives for this risk group are presented, reinforcing the need to consider the aging process and not just age as the main marker in the approach of this population.
Size matters – larger images are unintentionally better remembered

We are constantly exposed to many images, and although we do not actively try to remember or encode them, some of them are remembered. It has been suggested that such non-intentional memory is influenced by the depth of processing, but it is yet unclear what precisely defines the depth of processing for visual images. Here we reasoned that bigger images may entail deeper level of processing and may thus be remembered better than smaller ones. We ran a series of five studies (n= 91, each person participated in only one study) where each study started with an exposure experiment followed by a memory assessment experiment. To mimic non-intentional memory, in the exposure experiment participants were only instructed to freely view the images without being informed about any proceeding task. In this experiment they were exposed to hundreds of photographs of different categories and different sizes (3x3 to 24x24 vis. deg.). Following this, in the memory assessment experiment, each participant was shown a set of images of intermediate size (~8x8 vis. deg.), only half of them presented earlier, and for each image was asked to report if she/he recall seeing it earlier or not. We found that across experiments, larger images were incidentally remembered better, and this was true regardless of order effects, image set, or spatial resolution. While it is clear that multiple factors affect image memorability during incidental exposure, here we found that the physical dimension of image size seems to play an important role in this process.
An Autoethnography on the Professional Development of a Novice Elementary School Teacher

이 연구의 목적은 한 초임교사의 교육대학원에서의 학습경험을 자문화기술지로 서술함으로써 재교육기관에서의 교사교육을 통한 전문성 발달과 그 의미를 해석하는 데 있다. 첫째, 연구자로서의 나는 교육대학원에서의 학습경험을 통해 새로운 교육적 경험을 하고, 교육자로서의 정체성을 형성할 수 있었다. 둘째, 나는 교육대학원에서의 학습경험을 통해 학교교육에 대한 가치 변화를 경험하였고, 초등학교 초임교사로서의 정체성과 역할을 성찰하였다. 셋째, 연구자로서의 나에게 교육대학원의 교사 재교육은 전문적 자본 발달의 장(場)이었다. 이와 같은 연구결과에 기초한 결론은 다음과 같다. 첫째, 교육대학원은 현장교사들이 교육대학원에서 전문적 자본을 개발 및 확장할 수 있도록 학습공동체를 지원할 필요가 있다. 둘째, 교육대학원은 현장교사들이 ‘학위 취득을 위한 시간 때우기’에 머물지 않게 교사 재교육의 목적과 기능에 충실한 교육과정과 수업을 마련해야 할 것이다. 셋째, 교육대학원은 단위학교나 지역교육청의 인적 및 물적 자원을 공유하여 교육과정과 수업에서의 학문성과 현장전문성을 보다 심화해야 할 것이다.The purpose of this paper is to interpret the professional development of a novice elementary school teacher and its meaning by describing the experience of a researcher at a graduate school of education through autoethnography. The specific results and conclusions are as follows. Firstly, a researcher was a novice teacher in elementary school and was able to develop educational experience and identity as an educator through learning experience at graduate school of education. Secondly, the researcher adopted changing value of school education through the experience of learning at the graduate school of education, and reflected on my identity and role as a novice teacher. Thirdly, for the researcher as a novice teacher, the graduate school of education was a place for professional capital development. Based on these findings, the following conclusions were made Firstly, the graduate school of education need to support professional learning communities so that school teachers can develop and expand professional capital at graduate school of education. Secondly, the graduate school of education should develop curriculums and courses that are faithful to the purpose and function of teacher education. Also, graduate school of education needs to expand and deepen the academic knowledge and expertise of the education program by actively sharing the human and material resources of the school and regional office of education.
Implementasi Metode Background Subtraction Pada Citra Area Parkir Sebagai Upaya Untuk Membangun Citra Satuan Ruang Parkir Virtual

AbstrakMencari tempat parkir kosong membutuhkan waktu yang cukup lama di area parkir yang luas.untukmencari tempat parkir kosong membutuhkan waktu yang cukup lama. Untuk mengatasi hal tersebut dalampenelitian ini maka akan digunakan pendeteksian tempat parkir kosong menggunakan metode backgroundsubtraction.Background subtraction merupakan proses pendeteksian objek dengan membedakan antara objekdengan latar yang terdapat dalam suatu citra. Selanjutnya background subtraction melalui prosesthresholding untuk menarik batas latar menjadi hitam dan objek menjadi warna putih, sehingga akan adaperbedaan antara objek dan latar. Dimana pada proses pendeteksian menggunakan maket dari tempatparkir dengan perbandingan 1 : 60.Dengan melakukan pengujian dengan menggunakan metode background subtraction dipengaruhi olehcahaya, semakin besar intensitas cahaya maka semakin bagus juga kualitas pendeteksiannya. Untukmendeteksi juga membutuhkan nilai threshold yang tepat diperoleh dari niliai histogram frame awal.Sehingga pada proses pendeteksian di penelitian ini menggunakan nilai thershold 40 dengan intensitascahaya 944 lux, agar mendapatkan persentase ketepatan pendeteksian 100%. Dalam penggunaan metodeini harus menggunakan intensitas cahaya yang konstan agar tidak terjadi kesalahan dalam prosespendeteksian.Kata Kunci: background subtraction,thresholding,camera,cell parkir, latar, objek.AbstractFinding an empty parking lot takes a long time in a large parking area. To overcome this problemin this study, the detection of empty parking spaces will be used using the background subtractionmethod.Background subtraction is the process of detecting objects by distinguishing between objectsand backgrounds in an image. Furthermore, background subtraction goes through a thresholding processto draw the background border to black and the object to white, so that there will be a difference betweenthe object and the background. Where in the detection process using a mockup from the parking lot witha ratio of 1: 60.By conducting tests using the background subtraction method influenced by light, the greaterthe light intensity, the better the detection quality. To detect it also requires the exact threshold valueobtained from the initial frame histogram values. So that the detection process in this study uses athershold value of 40 with a light intensity of 944 lux, in order to get a percentage of 100% detectionaccuracy. In the use of this method must use a constant light intensity so that errors do not occur in thedetection process.Keywords: background subtraction, thresholding, camera, parking cell, background, object.
VIRTUAL CAMPUS TOUR (STUDENT PERCEPTION OF UNIVERSITY VIRTUAL ENVIRONMENT)

The primary purpose of this research is to empirically evaluate whether students show a positive response to the virtual campus tour. This application is designed using a website and virtual reality. This virtual tour allows users to navigate and listen to background sounds and narration. Besides, users can read brief information about each department in the Faculty. Each panorama contains a hotspot that allows users to explore further in the vicinity. All images are combined using 3DVista Virtual Tour software to produce 3600 effects. Usability tests are carried out to get the user's response to the virtual campus tour, to improve the prototype, and to measure the level of user convenience and satisfaction. Measurement of student responses is done using questionnaires and interviews. Student response questionnaire was given to 71 respondents. The virtual campus tour received a positive response, and all respondents agreed that this virtual reality application could attract users to promote the campus..
A principled approach to the detection of camouflaged objects

Camouflage must be appreciated as an extraordinary feat of evolution, but any detection of such camouflaged objects by predator and prey is also an impressive feat of visual systems. Many historical studies of camouflage have focused on descriptive compilations or heuristic applications. Our goal instead is to understand camouflage detection in the framework of controlled psychophysical experiments, and to develop a principled theory based on task-relevant stimulus statistics and known biological vision mechanisms. Moreover, unlike most object detection questions in computer science and psychology that utilize multiple cues, we focus on the particularly hard scenario where the camouflaging object exactly mimics the luminance, contrast, color and texture of its background. What then is the available information, and how does the visual system exploit it? We recognize that most of the information here resides at the object-background edge. We define measures to quantify the total magnitude and spatial distribution of this edge information, calculate them at multiple spatial scales in accordance with known early visual computations, and develop a method to condense these correlated cues into fewer dimensions. We also describe a whitening procedure that decorrelates the texture and losslessly gathers the distributed cues into a narrow object boundary. In parallel, we characterize human psychophysical detection performance on stimuli with pink noise texture (which is well-studied and shares properties of natural scenes, hence provides a principled starting point), then extend to more naturalistic textures. We find that the edge measure that we have developed predicts detection performance smoothly, allowing us to extract detection thresholds across differing conditions of luminance, contrast, target size and stimulus duration. We apply these findings to identify the best location for an object to hide against a background, and evaluate the effectiveness of different textures for camouflage.