Reviewerly/exHarmony huggingface dataset:
A generic diffusion-based approach for 3D human pose prediction in the wild

Predicting 3D human poses in real-world scenarios, also known as human pose forecasting, is inevitably subject to noisy inputs arising from inaccurate 3D pose estimations and occlusions. To address these challenges, we propose a diffusion-based approach that can predict given noisy observations. We frame the prediction task as a denoising problem, where both observation and prediction are considered as a single sequence containing missing elements (whether in the observation or prediction horizon). All missing elements are treated as noise and denoised with our conditional diffusion model. To better handle long-term forecasting horizon, we present a temporal cascaded diffusion model. We demonstrate the benefits of our approach on four publicly available datasets (Human3.6M, HumanEva-I, AMASS, and 3DPW), outperforming the state-of-the-art. Additionally, we show that our framework is generic enough to improve any 3D pose prediction model as a pre-processing step to repair their inputs and a post-processing step to refine their outputs. The code is available online: \url{https://github.com/vita-epfl/DePOSit}.
The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes

Convolutional neural networks were the standard for solving many computer vision tasks until recently, when Transformers of MLP-based architectures have started to show competitive performance. These architectures typically have a vast number of weights and need to be trained on massive datasets; hence, they are not suitable for their use in low-data regimes. In this work, we propose a simple yet effective framework to improve generalization from small amounts of data. We augment modern CNNs with fully-connected (FC) layers and show the massive impact this architectural change has in low-data regimes. We further present an online joint knowledge-distillation method to utilize the extra FC layers at train time but avoid them during test time. This allows us to improve the generalization of a CNN-based model without any increase in the number of weights at test time. We perform classification experiments for a large range of network backbones and several standard datasets on supervised learning and active learning. Our experiments significantly outperform the networks without fully-connected layers, reaching a relative improvement of up to $16\%$ validation accuracy in the supervised setting without adding any extra parameters during inference.
Mask classification using deep learning methods

During the COVID-19 pandemic, wearing gauze masks was proven to prevent people from infection. In public areas like shopping malls or schools need a way to supervise people wearing masks. This research aims to provide managers of public areas with an idea to solve this problem by GoogLeNet which is a type of convolutional neural network algorithm. Especially in crowded public areas, people should wear masks whether for their health or the health of others. These areas, such as stations and shopping malls, can only supervise people wearing masks at the entrance, but it is difficult to supervise people wearing masks inside buildings. As a result, many people will take off their masks or incorrectly wear them indoors due to heat. In this case, we consider how to intercept everyone's avatars in the video on closed-circuit television. Use neural network training algorithms to monitor everyone's mask-wearing situation. And promptly warn people who wear masks incorrectly or who do not wear masks.
Distributed Arithmetic RNS-based FIR Filter Design using Pipelining and Retiming Methods for High-Speed DSP Systems

Abstract This work presents a way to increase the throughput and energy efficiency of finite impulse response (FIR) filters through the efficient application of retiming and two-level pipelining. It is a challenge to increase the filter's throughput and energy efficiency while reducing latency and hardware complexity. The operations of addition and multiplication are divided using two-level pipelining. The break addition procedure is retimed. The architecture of m-tap filter (4-tap, 8-tap, 16-tap, 32-tap, and 64-tap) with n-bit input word length (4-bit, 8-bit, 16-bit, and 32-bit) Pipelined Retiming delay generation Filters (PRF), were designed. The proposed distributed arithmetic-based FIR Filter with pipelining has produced the least delay of 2.564ns for 4-tap with 8-bit input, and the maximum delay of 56.040ns for 64-tap with 32-bit word length. The proposed distributed arithmetic-based FIR Filter with retiming method has produced the least delay of 0.687ns for 4-tap with 8-bit input, and the maximum delay of 4.535ns for 64-tap with 32-bit word length. When compared with the pipelining method, the delay has been decreased by 73.20% for 4-tap with 8-bit input and 91.90% for 64-tap with 32-bit word length.
Distributed Fusion Estimation for the Measurements with Bounded Disturbances

Abstract The information fusion problem is studied for multi-sensor systems in the presence of bounded disturbances. In this paper, a distributed fusion estimation algorithm is proposed based on the set-membership theory, which obtains the overall estimates based on multi-ellipsoids intersection. A parameter adaptive adjustment scheme is derived to guarantee the performance of the algorithm. The feedback mechanism is also introduced to enhance the estimation procedure. Through theoretical analysis and simulation, the performance of the proposed algorithm is analyzed, and some interesting properties of the proposed algorithm are proved. Results show that the proposed algorithm improves the point estimation accuracy. Compared with the algorithm without feedback, the one with feedback has better local estimation. Meanwhile, the effectiveness of the proposed algorithm in improving state estimation accuracy has been proved by the simulation results.
Effect of the Use of Graphic Media on the Learning Outcomes of Indonesian Language Subjects Instructional Text Material of Class IV Students MI Almunazomah Caringin District, Bogor Regency

Background: The use of media in the learning process can facilitate the process of communication or delivery of messages from teachers to students. Students can clearly understand the instruction meaning or message that the teacher conveys.&#x0D; Purpose: This study aims to determine the learning outcomes of students using graphic media and the effect of using graphic media on student learning outcomes in Indonesian subjects for class IV instructional texts at MI Almunazomah, Caringin District, Bogor Regency.&#x0D; Design and methods: This research is an experimental research. The subjects of this study were all fourth-grade students, totalling 20 people. The test instrument used to determine student learning outcomes is a multiple choice test in the form of pre-test and post-test.&#x0D; Results: The results of this study indicate that the experimental group taught using graphic media obtained an average pre-test average value post-test of 77 with a standard deviation of 16.36. Changes in learning outcomes are 42 by using graphic media. While the mean value of the pre-test in the control group was 37 with a standard deviation of 13.37 and the average value of the post-test was 52 with a standard deviation of 14.76. Changes in learning outcomes are 15 without using graphic media. Based on the hypothesis testing criteria at = 0.05, t observe = 3.59 and t table = 2.10 so that t observe &gt; t table or 3.59 &gt; 2.19 then Ha is accepted and Ho is rejected. It can be concluded that there is a significant effect of the use of graphic media on the learning outcomes of fourth grade students in the Indonesian subject of instructional text material at MI Almunazomah, Caringin District, Bogor Regency.
A Network-Theoretical Perspective on Oscillator-Based Ising Machines

The standard van Neumann computer excels at many things. However, it can be very inefficient in solving optimization problems with a large solution space. For that reason, a novel analog approach, the oscillator-based Ising machine, has been proposed as a better alternative for dealing with such problems. In this work, we review the concept of oscillator-based Ising machines. In particular, we address how optimization problems can be mapped onto such machines when the QUBO formulation is given. Furthermore, we provide an ideal circuit that can be used in combination with the wave digital concept for real-time simulated annealing. The functionality of this circuit is explained on the basis of a Lyapunov stability analysis. The latter also provides an answer for the question: when has the Ising machine solved a mapped problem? At the end, we provide emulation results demonstrating the correlation between functionality and stability of the discussed machine. These results show that mapping a problem onto an Ising machine effectively maps the solution of the problem onto an equilibrium of the phase space.
Virtual education, an engine to increase learning in the pandemic

The objective of this article is to know how virtual education intervenes in the learning process of students in Technical Secondary School No. 4 vs. General Secondary School No. 11 during the pandemic. The research that was carried out is of a comparative and differential type since two populations will be analyzed in order to know the learning process in virtual education; it is also of a preliminary nature since it will only have one moment in the validation of the external data. The instrument had 83 variables on a decimal ratio scale and 6 general data items. The statistical treatment was based on five levels in order to obtain validity and confidence in the information. The main results of the research highlight that carrying out a practice of the topics seen enhances the learning process in the subjects. The research concludes that the most suitable education for men is the virtual one since they generate a greater type of interrelationships, abilities, skills, communication and social situations that favor a quality education. It is proposed to carry out a course focused on virtual education to learn about technological tools.
Bibliometric Mapping Analysis of Scientific Publications in Chemistry Field on Cerium Oxide Nanoparticles Using Vosviewer

This study aims to look at the advancement of scientific publications related to cerium oxide nanoparticles through a bibliometric approach using qualitative methods with descriptive statistics on literature studies on scientific articles. Two types of software are used: Publish or Perish and VOSviewer. Publish or Perish is used as a source to search for various relevant articles through the Google Scholar database, using the keyword "Cerium Oxide Nanoparticle," and obtained 997 articles from 2012 to 2022. The results show that 2012 and 2013 were fairly constant, increasing from 2014 to 2016, fluctuating from 2017 to 2020, and decreasing in 2021 and 2022. Data from Publish or Perish is inputted into VOSviewer to visualize and analyze mapping trends related to cerium oxide nanoparticles, obtaining 7 clusters of 189 items. The popularity of the terms used in scientific publications related to cerium oxide nanoparticles during the last three years has become less trending. This study concludes that there are still opportunities for future researchers to develop or even make discoveries related to cerium oxide nanoparticles.
STEAM conceptions, competencies and attitudes in higher education: a pilot study

The rapid development of the STEAM disciplines (science, technology, engineering, art and mathematics) has allowed education based on this approach to be considered as a key and essential component for 21st century education, where students are required to have a range of science and technology skills, skills and knowledge, in addition to providing them with a range of tools to cope with the various situations that arise, many of them complex and challenging; the objective of this paper is to show the preliminary results of a pilot study that was carried out to validate two instruments that were designed in order to evaluate the competences and attitudes in STEAM education of students and university teachers. To meet this objective, four stages were implemented that included the following moments: Phase 1. Estimation of the distribution of data, Phase 2. Pilot study, Phase 3. Estimation of reliability and internal consistency. Phase 4. Preliminary results. The main results show favorable indicators in understanding, relevance and satisfaction of the items and an adequate internal consistency around the values of reliability and validity.
The Recitation Method Development in Online Learning for Reading Comprehension Students in the English Literature Study Program

In Universitas Negeri Medan, there are 6 assignments for each subjects to be accomplished in each semester, namely Routine Tasks, Critical Book Reviews, Critical Journal Reviews, Mini Research, Engineering Ideas and Projects. In doing all these tasks, of course, reading has important role. A good reading gives accurate data and information in accomplishing all tasks. To avoid a very boring reading and provide challenges, develop a good learning methods is a must. The aims of the study is to investigate how the recitation learning methods developed for the reading comprehension of the students. The data obtained through the observation, questionnaires, and interviews to know the competence of students in reading comprehension. Adopting research development method that refers to the development of model, this development research data is qualitative and quantitative data. The objective of this research is to develop recitation methods in online learning for reading comprehension skills of the students of English Literature Study Program in Universitas Negeri Medan. The results of this study are expected to be able to give contribution to the students who take Reading Subject and also to the lecturers who teach Reading Subject to be more efficient and effective in using appropriate learning methods in Reading Subject.
Generalization of the issues with implementing inclusive education in Ukraine empirical findings from sociological research experience

The focus of the paper is on the ongoing issues with the inclusion approach in the educational system. The authors make an effort to study legal documents governing inclusive education, the accessibility of medical and educational facilities, and the willingness of the teaching profession to engage with students who have special educational requirements. the empirical foundation created by a variety of empirical data gathered through traditional document analysis, parent and teacher interviews, and other means. The examination of the research's findings enables us to draw the conclusion that informants are well aware of the challenges facing inclusive education in the present. They are linked to the majority of school buildings' lack of architectural accessibility, teachers' inadequate professional preparation, experience interacting with kids who have various types and degrees of diseases, and the society's inadequate level of readiness to understand the concept of integration.
Kajian Emisi Gas Rumah Kaca (GRK) dari Perkembangan Teknologi Elektrifikasi Baterai Ponsel Pintar

Batteries as an energy source are no longer a newly recognized technology and their use has been a part of life for many years. Since 1800 AD the battery was invented by Alessandro Volta, an Italian physicist, the battery has undergone various developments ranging from form, function of use, to of course the amount of electric power or now known as MAH. Although the benefits of batteries are undeniable, it is the same as the phrase "There is no ivory that is not cracked", batteries also have the power to harm (bad) especially for the environment, including the contribution of carbon that produces Greenhouse Gas (GHG) emissions as one of the the cause of global warming (Global warming) which triggers climate change (Climate Change).&#x0D; To find out, a quantitative study was carried out by calculating the energy conversion of smartphone batteries using the carbone conversion principle in the IPCC formulation. The result shows that the use of smartphone batteries in the last decade has experienced a rapid increase starting from 25,179,840 tons of Co2 in 2011, in 2022 soaring to 302,158,080 tons of Co2. This shows a significant increase in GHG carbon emissions from the development and use of smartphone batteries, this figure accumulatively becomes a fairly large burden on the environment.
Effects of Focus on Forms and Focus on Form Instruction on Middle-Aged and Elderly Learners’ English Grammar Acquisition

Kyungmi Choi, Daria Soon-Young Seog, and Incheol Choi. 2022. Studies in Modern Grammar 115, 119-137. Effects of Focus on Forms and Focus on Form Instruction on Middle-Aged and Elderly Learners’ English Grammar Acquisition.&#x0D; This study, to find an effective way for older adult learners to acquire English, aims to investigate the extent instruction needs to be intentional or explicit.&#x0D; Traditionally, the issue was dealt with in terms of the effect of two instructional approaches—focus on forms (FonFs) and focus on form (FonF). The results of the grammaticality judgment test with audio stimuli show that FonFs instruction is a more appropriate method for middle-aged and elderly groups’ acquisition of grammatical knowledge than FonF instruction. In addition, it suggests that even among older adult learners, age still matters. That is, “the younger, the better” applies to adult learners of age 40 and above.
Resonant Actualization of Cultural Codes as a Determinant of Mental and Social Transformations (Part 1)

The unification of cultural codes forms the basic set of code symbols (image+sense), which are the basis for recognition, orientation, social cooperation, and response to external appeals. The result of unification is a stable system of deterministic goal-setting and behavioral equivalents. Cultural codes, as a derivative of upbringing, education, and cultural landscape, are the result of spatiotemporal transformation (from fields of reception to displacement from consciousness and compression) of organized information constructs - "dominants" encoded in the form of electro/magnetic patterns. "Dominant" in this message is a generalized definition of organized, hierarchical constructs (packages) of information carriers, forced out of the conscious levels of the psyche and continuing to circulate in closed, reverberant neural circuits. The "dominants" forced out of consciousness circulate through recurrent neural circuits, the activity of which is reduced to several stable states, performing the functions of information retention. The electrical and magnetic parameters of the repressed "dominants" are the basic potential of frequency resonance upon presentation of a perceptual/cognitive construct that is close in frequency parameters - a "code key" at the entrance to the psyche system. The basic principle of information exchange is the formation of the initial resonance potential: the arsenal of "dominants," the concentration of information in frequency electro-magnetic patterns. The interaction of the "information universe" with the arsenal of "dominants" is a resonant process of frequency coincidence of the patterns of the "code key" and the "dominant" displaced from consciousness, which results in actualization, the appearance of an object of resonance in the field of voluntary attention, in consciousness. The updated "dominant," as a "resonant operator," determines the dynamics of the system as a whole for the period of relevance. The phase transition in the socio/cultural environment is the result of changes in the hidden meanings of social frames. The dynamics of the perception of the transformation of frames under changing (appearing new) hidden meanings ["habituation"&gt;"acceptability"&gt;"acceptability”] determines the growth of the frustration potential associated with acquired needs. The transformation of basic cultural codes rebuilds the mechanism of reproduction of the ethnocultural matrix and congruent social structures.
Group-Aware Threshold Adaptation for Fair Classification

The fairness in machine learning is getting increasing attention, as its applications in different fields continue to expand and diversify. To mitigate the discriminated model behaviors between different demographic groups, we introduce a novel post-processing method to optimize over multiple fairness constraints through group-aware threshold adaptation. We propose to learn adaptive classification thresholds for each demographic group by optimizing the confusion matrix estimated from the probability distribution of a classification model output. As we only need an estimated probability distribution of model output instead of the classification model structure, our post-processing model can be applied to a wide range of classification models and improve fairness in a model-agnostic manner and ensure privacy. This even allows us to post-process existing fairness methods to further improve the trade-off between accuracy and fairness. Moreover, our model has low computational cost. We provide rigorous theoretical analysis on the convergence of our optimization algorithm and the trade-off between accuracy and fairness of our method. Our method theoretically enables a better upper bound in near optimality than existing method under same condition. Experimental results demonstrate that our method outperforms state-of-the-art methods and obtains the result that is closest to the theoretical accuracy-fairness trade-off boundary.
The Dual of a Tidal Force in the D1D5 CFT

It was demonstrated that a string probe falling radially within a superstratum geometry would experience tidal forces. These tidal forces were shown to excite the string by converting its kinetic energy into stringy excitations. Using the AdS/CFT correspondence we seek to understand this behavior from the perspective of the dual D1D5 CFT. To study this process we turn on an interaction of the theory which is described by a deformation operator. We start with an initial state which is dual to a graviton probe moving within the superstratum geometry. We then use two deformation operators to compute transition amplitudes between this state and a final state that corresponds to stringy excitations. We show that this amplitude grows as $t^2$ with $t$ being the amount of time for which the deformation operators are turned on. We argue that this process in the CFT is suggestive of the tidal effects experienced by the probe propagating within the dual superstratum geometry.