Reviewerly/exHarmony huggingface dataset:
Chunking is not all-or-none: hierarchical representations preserve perceptual detail within chunks

Objects are not stored as unitary representations: memory representations are hierarchically structured in that objects structure memory, but features within objects are mostly independent (Fougnie et al. 2013). Yet prominent chunk learning theories still treat learned chunks as all-or-none bound representations (e.g., in visual memory, “content-free labels”, Huang & Awh, 2018). Here we suggest that as in the case of objects themselves, chunks that combine objects are also hierarchically structured, with preserved information about their contents in addition to the chunk ‘pointer’. We tested this in two ways: In Experiment 1 and 2, we had participants learn new ‘chunks’ using the color-pair paradigm of Brady et al. (2009), in which colors frequently co-occur next to each other in a working memory paradigm (e.g., orange frequently co-occurs with green). However, unlike previous work where the colors were identical on every trial, the colors in these experiments varied in luminance: so although green frequently occurred with orange, the particular green and orange on each trial were unique. We found that (1) learning significantly improved capacity over the experiment; (2) after learning, knowledge about the 2 colors was correlated, showing some binding; and yet (3) participants did not simply encode abstractions (“irish flag colors”), but had preserved knowledge of trial-specific color information as well. In Experiment 3, we relied on existing chunks. Participants were instructed to remember known words (e.g., “GO”) or unknown letter pairs (e.g., “SP”), with letter fonts varying from trial to trial. The presence of pre-existing word chunks helped not only in knowing the letters but also improved knowledge of the fonts -- which contradicts predictions made by a content-free labels account. Overall we find evidence that memory should be considered hierarchical: Chunks, like objects, serve as cues to access specific information within them, rather than serving as all-or-none abstractions.
Strategy instruction boosts visual search optimality but such improvements transfer poorly to similar tasks

When searching for a target in the visual scene, such as for your red car, performance depends on the strategy chosen (e.g., searching for red things vs. things with wheels), and research has revealed widespread suboptimality of strategy. Explicit strategy instruction can improve choice, but can the improvement generalize across separate tasks that retain similar strategy components?
Facial Feature Removal for Anonymization of Neurological Image Data

Abstract Interdisciplinary exchange of medical datasets between clinicians and engineers is essential for clinical research. Due to the Data Protection Act, which preserves the rights of patients, full anonymization is necessary before any exchange can take place. Due to the continuous improvement of image quality of tomographic datasets, anonymization of patient-specific information is not sufficient. In this work, we present a prototype that allows to reliably obscure the facial features of patient data, thus enabling anonymization of neurological datasets in image space.
The stuff of natural scenes: probing human property judgments of textures, materials, and other amorphous scene components with convolutional neural networks

Scenes are composed not only of discrete objects with defined shapes but also complex visual “stuff” in the form of amorphous textures and patterns (e.g., grass, bricks, smoke). Many behaviorally relevant properties of scenes can be quickly recognized based solely on the stuff they contain—e.g., hotness of fire, hardness of concrete, fragility of glass. Though much work has explored how the human visual system represents individual objects, less is known about how we process the amorphous stuff that makes up most of the visual environment. Furthermore, an open question is to determine what classes of computational models can account for the human ability to rapidly detect a rich set of high-level properties from a brief glance at a patch of visual stuff. To address these questions, we developed a dataset of 500 high-quality images from 50 categories of textures encountered in real-world environments, and we collected annotations of readily identifiable qualitative properties of these images (e.g., material properties, haptic properties, semantic attributes). In preliminary investigations, we sought to determine whether computational models trained for object recognition also yield representations that are useful for predicting the qualitative properties of visual stuff. Our findings show that while many perceptual and haptic properties (e.g., bumpiness) are equally well-predicted by both supervised and untrained convolutional neural networks, high-level semantic attributes (e.g., naturalness) were much better predicted by supervised models. Nonetheless, all models failed to reach the noise ceiling for the majority of the property annotations, demonstrating that further work is needed to account for the richness of human stuff perception. Our dataset will provide a critical benchmark for computational models and will be useful for follow-up studies that seek to understand how humans recognize the many qualitative properties of the stuff in their visual surroundings.
A Novel Color Image Encryption Scheme Based on Chaotic Sequence and DNA Mutation Principle

Based on the simplified three-dimensional fractional unified chaotic system and the principle of DNA mutation, this paper proposes a color image encryption method to further improve the security of image information transmission.On the other hand, the pseudorandom sequence generated by the 3D score simplified unified chaotic system uses the DNA mutation principle algorithm to scramble the color image and expand the pixel value.Finally, the security of the proposed cryptographic algorithm is analyzed using key space, correlation, information entropy, etc. Numerical simulation results show that the algorithm has good security.The results of this paper provide a theoretical basis for the unification of the chaotic system applying the principle of fractional simplification and DNA mutation to image security.
Cyberbullying en posgrado

espanolEn el contexto de la cultura digital que atraviesan las Instituciones de Educacion Superior, se estan generando nuevas practicas violentas a traves de las redes sociales.Este articulo explora el caso del cyberbullying en el posgrado, se analizan las representaciones sociales de los estudiantes y sus reco-mendaciones para enfrentarlo. EnglishIn the context of digital culture new violent practices are appearing in social networks used by higher education institutions. This article explores the case of the cyberbullying in graduate pro-grams, analyzing the social representations that students have about this phenomenon and their suggestions to deal with it.
The Influence of The Use of The Chemical Ludo Educational game On Environmental Pollution Material On The Learning Outcomes of Class VII Junior High School Student

This research is motivated by the availability of the Ludo chemistry educational game on environmental pollution material where the research has not yet reached the stage of knowing the effect of its use on learning outcomes. This study aims to determine the effect of the use of the chemical Ludo educational game on environmental pollution material on the learning outcomes of seventh grade students of SMPN 34 Padang. The type of research used is a quasi-experimental design with a non-equivalent control group design. The population in this study were seventh grade students of SMPN 34 Padang. The sample selected using purposive sampling technique was class VII7 as the experimental class and class VII8 as the control class. The data analysis technique used is the independent t-test (t-test) obtained from the posttest.  The results of the study showed that an increase in understanding of learning outcomes occurred in the experimental class compared to the control class. This can be seen from the posttest average result of the experimental class, which is 80, while the average result of the control class is 71.72. Based on the percentage of mastery learning the experimental class got 78.6% while the control class got 55.2%. This is in accordance with the results of the test (t), namely tcount 2.3102 > ttable 2.00404 at the real level = 0.05 with dk = 55 and probability t0.95. This concludes that there is a significant effect on the use of the Ludo Chemistry educational game on student learning outcomes on environmental pollution at SMPN 34 Padang. Keywords— influence, chemical ludo, environmental pollution, learning outcomes
A Genre Analysis of Korean Hotels’Responses to Negative Reviews

This study investigates the issue of how top hotels in Seoul respond to customers’complaints in website by exploring their responses to negative reviews through genre analysis for the purpose of making contribution to hotels and English teaching. The purposes of this study are to identify (1) moves’proper application to the selected texts in comparison with Thumvichit & Gampper(2019) move structure, (2) moves and steps of RNRs and their occurrence frequency by covering a communicative function, and (3) the correlation between moves/steps and formulaic sequences(4-gram clusters) of RNRs and to help English for Specific Purposes writing class. The results showed that (1) the types and the order of application of the move applied in the RNR text were classified into six types, (2) moves/steps were categorized into obligatory, conventional, and optional ones according to the frequency, and (3) there was also a significant difference in the recurrent word combination and frequency of each move/step.
Teaching the Teams

Understandably, nearly all Agile approaches are designed with the implicit assumption that dependency management is hard, and, in fact, too expensive to manage, plan for, or predict. As a consequence, Agile processes which grudgingly acknowledge dependencies work very hard to remove them, minimize them, or pretend that they do not exist.
Electroweak Probes Experimental Overview: TimeEvolution of Electroweak Measurements

Electroweak probes of high energy nuclear collisions play a unique role in the study of QCD matter -they grant access to information about the collision without themselves undergoing QCD interactions.This provides a probe of the initial state through QGP evolution.Indeed, studies of electroweak probes have played a role of forming and answering key questions of high energy nuclear collisions in the last decades.In this article, a selection of the recent results of electroweak measurements discussed at the Hard Probes 2020 conference are presented.
Elliptic Curve Cryptography

In this chapter, we briefly motivate the use of asymmetric cryptography based on ECC systems for applications in resource-constrained devices like flash memory controllers. We review applications and fundamentals of elliptic curve cryptography, the corresponding one-way function, i.e. the so-called PM, as well as associated group laws. Furthermore, we summarize methods that reduce the computational complexity and speed up the calculation of the point multiplication.
The effect of proximity and continuity on amodal completion

Due to the influence of COVID-19, the experiment was conducted online in laboratory training. This study examined the effects of proximity and continuity on amodal completion. This study focused on the effects of proximity and continuity as conditions under which two bars touched the top and bottom sides of a large rectangle were perceived to be connected as one bar behind the rectangle (6.0cm high, 12.0cm width). Actually, the perceived length was different for each participant. The position of the upper bar is fixed at 3.0 cm from the left side of the rectangle, and at 30 degrees. Five conditions were set for the angle and position of the lower bar based on the position and angle of the upper bar. The two bars were spatially closest to each other in the 0.0 cm condition. When the angle of the lower bar was 0.0 degrees, it was the same angle as the upper bar. The contact point of the lower bar with the rectangle was aligned with the upper bar in the 9.0 cm condition. 127 university students participated in this experiment. Some participants observed with their laptops and some with their smartphones. There was no difference in results by their devices. Each participant observed only one angular condition. The order in which the position conditions were presented was different for each angle condition. We classified the participants' descriptions into three categories whether the two bars appear to be connected as a single bar, to be separated into two bars, or to appear to be a single figure as a whole. 85% of participants reported a single bar in the 9.0 cm and 0.0 degrees condition. In terms of Gestalt grouping, it was tended to perceive them together in good continuity, not in proximity.
Reduction of Noise in Restoration of Images Using Mean and Median Filtering Techniques

Abstract: The purpose of this paper is to present a study of digital technology approaches to image restoration. This process of image restoration is crucial in many areas such as satellite imaging, astronomical image &amp; medical imaging where degraded images need to be repaired Personal images captured by various digital cameras can easily be manipulated by a variety of dedicated image processing algorithms [2]. Image restoration can be described as an important part of image processing technique. Image restoration has proved to be an active field of research in the present days. The basic objective is to enhance the quality of an image by removing defects and make it look pleasing [2]. In this paper, an image restoration algorithm based on the mean and median calculation of a pixel has been implemented. We focused on a certain iterative process to carry out restoration. The algorithm has been tested on different images with different percentage of salt and pepper noise. The improved PSNR and MSE values has been obtained. Keywords: De-Noising, Image Filtering, Mean Filter &amp; Median Filter, Salt and Pepper Noise, Denoising Techniques, Image Restoration.
Application of Cisco Packet Tracer Software in Computer Networking Experiment Teaching

This paper is based on Cisco Packet Tracer software, combined with its specific concepts, the basic characteristics are analyzed, based on the related structure of current computer networking experiments, build a basic network training platform, based on topological structure simulation, network equipment settings and testing, targeted analysis is carried out, it can further solve the defects in the current computer network teaching, lay the foundation for the improvement of students’ comprehensive ability.
Land Rights Documentation and Verification System Using Blockchain Technology

Land verification usually describes systems through which matters concerning land ownership, possession, or other rights are often recorded (usually with workplace or department) to provide title proof, facilitate transactions, and stop illegal settlement. The data recorded and, so, the security given will change reliably with the purview. The strategy of formally and legitimately recording through arriving or built property rights or title certificates freely appears a politician's record of proprietorship of the rights inalienable through that proprietorship. On the off chance that we specify the arrive confirmation framework utilizing blockchain innovation, it by implication implies arrive enrollment with blockchain innovation. We cannot utilize blockchain technology to confirm land registration data in the event that we do not keep it within the blockchain framework. So during this paper, we will briefly discuss the present land registration system, the challenges in our traditional approach, and, eventually, how we will solve those challenges through the utilization of blockchain technology. Finally, we will compare which technology of blockchain public or private is best suited for the utilization case.
Applications of Eulerian Graph for Mathematical and Real Situation

Graph Theory is an important topic of discrete mathematics and computer science having applications in modeling a variety of real life situations in many disciplines. This article is intended for the attention of young researchers and provides an introductory discussion of some well known application problems in which role of eulerian graph and eulerian circuit is significant. In this paper, we have made an attempt to use the eulerian graph to solve the mathematical and real life situations.
Improving students anecdot writing ability through genius learning strategies and discussion methods

The purpose of this study was to improve the ability of class X IPS 1 SMA Negeri 4 OKU through genius learning strategies and lecture methods. Research data collection techniques using observation, documentation and tests. The research data analysis technique used a descriptive writing test through direct learning and observation models to see student learning activity. Based on the results of the study, it can be concluded that there is an increase in the ability to write anecdotes through genius learning strategies and lecture methods in class X IPA 1 SMA Negeri 4 OKU. In cycle 1, an average value of 66.68 was obtained, students who achieved completeness were 22 students or the percentage of completeness was 61.11%. In cycle 2 the average value is 69.28%. Students who achieved completeness were 29 students or the average persetanse completeness was 80.56%. Furthermore, in cycle 3 the average value is 76.81. Students who achieved completeness were 34 students or the percentage of student completeness was 94.44%.
In the 1960s and 1970s, Missionary Eleanor van Lierop's Welfare Project for Women in Need and the Establishment of Aeranwon : Based on 『Lord of the Dance』

Missionary Eleanor van Lierop is the founder of Aeranwon, which was established to help prostitutes who have increased rapidly after the Korean War. Based on her Christian perception of women, she tried to overcome the prejudice of Korean society that 'a woman who is once into prostitution cannot be recovered'. She also urged the need for welfare for prostitutes. Through the establishment of the first single mother protection facility in Korea, she was the first to take the lead in respecting the fetus' life and protecting the motherhood of the single mother. Her activities have led to the interests and alliances of various institutions in welfare work for women in need. The values of Aeranwon's founding spirit, such as respect for the life of the fetus, protection of motherhood, and preservation of family, are in line with the social ethics pursued by Korean Christianity. In the end, the establishment and growth of Aeranwon contributed to sharing the value of Christianity in Korean society and led to changes in government policies. This can be seen as a case in which Christianity has established itself as a new standard of the view of women replacing Confucianism. Because of this, it has historical significance in the history of the Korean church.
Large-scale quantum photonics for computing and communications

Recent advances in materials, control, and nanofabrication now open the prospect for scalable quantum technologies based on solid-state quantum systems. In particular, photonic integrated circuits (PICs) now allow routing photons with high precision and low loss, and solid-state artificial atoms provide high-quality spin-photon interfaces. The first part of this talk will review progress towards quantum memory-integrated PICs for quantum networks and modular quantum computers. The second part of the talk will consider new directions for processing classical and quantum information in deep learning neural networks architectures.
New enhancements to the DeepGaze models for a better understanding of human scanpaths

The family of DeepGaze models comprises deep learning based computational models of freeviewing overt attention. DeepGaze II predicts freeviewing fixation locations (Kümmerer et al, ICCV 2017) and DeepGaze III (Kümmerer at al, CCN 2019) predicts freeviewing sequences of fixations. The models encode image information using deep features from pretrained deep neural networks to compute a spatial saliency map, which, in case of DeepGaze III, is then combined with information about the scanpath history to predict the next fixation. Both models have set the state of the art in their respective tasks in the last years. Here, we improve the performance of both models substantially. We replace the backbone deep neural network VGG-19 with better performing networks such as DenseNet. We also improve the architecture of the model and the training procedure. This results in a substantial performance improvement for both DeepGaze II and DeepGaze III and sets a new state of the art for freeviewing fixation prediction and freeviewing scanpath prediction across all commonly used metrics. We further use the improved DeepGaze III model to better understand human scanpaths. For example, we quantify the effects of scene content and scanpath history on human scanpaths. We find that, on the MIT1003 dataset, scene content has a substantially larger effect on fixation selection than scanpath history and that there are only very subtle but measurable interactions between scene content and scanpath history that go beyond a scalar saliency measure. Furthermore, we are able to disentangle the central fixation bias into contributions that are driven by image content, by the initial central fixation, and by a remaining effect that cannot be explained from these two sources. Taken together, the improved DeepGaze models allow us to analyze human scanpaths in ways that are not possible without high-performing deep learning models.
Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge

This competition concerns educational diagnostic questions, which are pedagogically effective, multiple-choice questions (MCQs) whose distractors embody misconceptions. With a large and ever-increasing number of such questions, it becomes overwhelming for teachers to know which questions are the best ones to use for their students. We thus seek to answer the following question: how can we use data on hundreds of millions of answers to MCQs to drive automatic personalized learning in large-scale learning scenarios where manual personalization is infeasible? Success in using MCQ data at scale helps build more intelligent, personalized learning platforms that ultimately improve the quality of education en masse. To this end, we introduce a new, large-scale, real-world dataset and formulate 4 data mining tasks on MCQs that mimic real learning scenarios and target various aspects of the above question in a competition setting at NeurIPS 2020. We report on our NeurIPS competition in which nearly 400 teams submitted approximately 4000 submissions, with encouragingly diverse and effective approaches to each of our tasks.