Reviewerly/exHarmony huggingface dataset:
Act3D: 3D Feature Field Transformers for Multi-Task Robotic Manipulation

3D perceptual representations are well suited for robot manipulation as they easily encode occlusions and simplify spatial reasoning. Many manipulation tasks require high spatial precision in end-effector pose prediction, which typically demands high-resolution 3D feature grids that are computationally expensive to process. As a result, most manipulation policies operate directly in 2D, foregoing 3D inductive biases. In this paper, we introduce Act3D, a manipulation policy transformer that represents the robot's workspace using a 3D feature field with adaptive resolutions dependent on the task at hand. The model lifts 2D pre-trained features to 3D using sensed depth, and attends to them to compute features for sampled 3D points. It samples 3D point grids in a coarse to fine manner, featurizes them using relative-position attention, and selects where to focus the next round of point sampling. In this way, it efficiently computes 3D action maps of high spatial resolution. Act3D sets a new state-of-the-art in RL-Bench, an established manipulation benchmark, where it achieves 10% absolute improvement over the previous SOTA 2D multi-view policy on 74 RLBench tasks and 22% absolute improvement with 3x less compute over the previous SOTA 3D policy. We quantify the importance of relative spatial attention, large-scale vision-language pre-trained 2D backbones, and weight tying across coarse-to-fine attentions in ablative experiments. Code and videos are available on our project website: https://act3d.github.io/.
Tailoring quantum error correction to spin qubits

Spin qubits in semiconductor structures bring the promise of large-scale 2D integration, with the possibility to incorporate the control electronics on the same chip. In order to perform error correction on this platform, the characteristic features of spin qubits need to be accounted for. E.g., qubit readout involves an additional qubit which necessitates careful reconsideration of the qubit layout. The noise affecting spin qubits has further peculiarities such as the strong bias towards dephasing. In this work we consider state-of-the-art error correction codes that require only nearest-neighbour connectivity and are amenable to fast decoding via minimum-weight perfect matching. Compared to the surface code, the XZZX code, the reduced-connectivity surface code, the XYZ$^2$ matching code, and the Floquet code all bring different advantages in terms of error threshold, connectivity, or logical qubit encoding. We present the spin-qubit layout required for each of these error correction codes, accounting for reference qubits required for spin readout. The performance of these codes is studied under circuit-level noise accounting for distinct error rates for gates, readout and qubit decoherence during idling stages.
Exploration and Exploitation of Unlabeled Data for Open-Set Semi-Supervised Learning

In this paper, we address a complex but practical scenario in semi-supervised learning (SSL) named open-set SSL, where unlabeled data contain both in-distribution (ID) and out-of-distribution (OOD) samples. Unlike previous methods that only consider ID samples to be useful and aim to filter out OOD ones completely during training, we argue that the exploration and exploitation of both ID and OOD samples can benefit SSL. To support our claim, i) we propose a prototype-based clustering and identification algorithm that explores the inherent similarity and difference among samples at feature level and effectively cluster them around several predefined ID and OOD prototypes, thereby enhancing feature learning and facilitating ID/OOD identification; ii) we propose an importance-based sampling method that exploits the difference in importance of each ID and OOD sample to SSL, thereby reducing the sampling bias and improving the training. Our proposed method achieves state-of-the-art in several challenging benchmarks, and improves upon existing SSL methods even when ID samples are totally absent in unlabeled data.
Wasserstein Loss for Semantic Editing in the Latent Space of GANs

The latent space of GANs contains rich semantics reflecting the training data. Different methods propose to learn edits in latent space corresponding to semantic attributes, thus allowing to modify generated images. Most supervised methods rely on the guidance of classifiers to produce such edits. However, classifiers can lead to out-of-distribution regions and be fooled by adversarial samples. We propose an alternative formulation based on the Wasserstein loss that avoids such problems, while maintaining performance on-par with classifier-based approaches. We demonstrate the effectiveness of our method on two datasets (digits and faces) using StyleGAN2.
PENGEMBANGAN MEDIA PEMBELAJARAN BERBASIS PLOTAGON PADA MATA PELAJARAN BAHASA INDONESIA UNTUK SISWA KELAS IV SD NEGERI LUBUK KUMBUNG

This study aims to make a plotagon-based learning video media for fourth grade students of SD Negeri Lubuk Kumbung Musi Rawas which is valid and practical. Rawas age with a sample of 10 students for the small group test. The type of development used is the type of development of the 4D model (four-D model). The data collection technique used a validation questionnaire of linguists, material experts and practicality questionnaires for teachers and students. Based on the results of research and development, several conclusions can be drawn as follows: 1) Based on the results of the validation, it is known that the plotagon-based learning video is categorized as good with a validity percentage of 86,26 so it is categorized as valid. 2) The practicality of plotagon-based learning videos in individual trials or one to one involving 10 students is categorized as very good with a percentage of 91.33%. Based on the test results, it is known that the student responses are categorized as good, which means that the plotagon-based learning videos are practical or easy to use.&#x0D; Keywords: learning video, plotagon
NOTES ON GRATITUDE IN LANGUAGE TEACHING IN MEXICO

During the pandemic, many educational paradigms were put to the test, others were modified and, in this new stage of knowledge, the training of university students has required new strategies.Emotional needs suddenly appear to limit and/or hinder the learning dynamics, behavior during classes can sometimes even indicate a learning simulation.Due to different circumstances, teachers have to resort to different areas of knowledge to integrate them into everyday activities so that learning a second language is no longer a challenge, and transforms that challenge into brief, simple, everyday activities and possible from there.In this investigation, it was possible to demonstrate the work carried out by students at `` Universidad Veracruz`` who take English courses.Recording the progress of these students in the linguistic process could be easy, however, the factor was incorporated into this: Gratitude and through writing a diary we can show a) their linguistic advances and b) the increase in their inputs and the maturation of their writings.
Joint Semi-Supervised and Active Learning via 3D Consistency for 3D Object Detection

Autonomous driving powered by deep learning requires large-scale, high-quality training data from diverse driving environments to operate effectively worldwide. However, collecting and annotating such data is costly and time-consuming. To address this challenge, active learning methods have been explored to select the most informative data samples for training. Nevertheless, most existing methods focus on 2D tasks and do not fully exploit the value of unlabeled data. In this paper, we propose a semi-supervised active learning approach for 3D object detection tasks that leverages the potential of collected data and reduces annotation costs. Our method considers the 3D consistency of bounding box predictions in both semi-supervised and active learning processes, thereby improving the performance of point cloud-based 3D object detection models. Our framework specifically utilizes self-supervision to decrease bounding box uncertainties. Moreover, it selects objects that are either occluded or distant and still exhibit high uncertainty for annotation even after semi-supervised training has decreased their uncertainty. Experiments on the KITTI dataset demonstrate that our semi-supervised active learning approach selects objects with high measurement uncertainties and enhances the model's ability to detect occluded objects. Our approach improves the baseline by more than 60% (+17.12 mAP) when using only 1500 annotated frames.
Design Of Android Base School Information Media Application Case Study Of Qomariah Educational Institution

Currently the world of technology and information is developing very quickly, including school information systems. The school information system is one of the information media that can be accessed by all elements of the school including teachers and students so that they can relate to each other in terms of teaching and learning activities and information that can be quickly disseminated to all students, so that students do not need to come to school. in this technological era from young to old all use smartphones to facilitate communication but PKBM Qomariah does not yet have the right information media. So an Android-based school information system application was made using Android studio. Android applications make it easier for teachers and students because they can be accessed on various smartphones. All teachers and students mostly have smartphones. With this application, teachers and students can get information from schools easily. The research method used is descriptive method by conducting observations, literature studies, and interviews. While the method used in making software is waterfall which consists of several stages, namely requirements definition, system and software design, implementation and unit testing, system integration and testing, Operation and Maintenance.
PELAKSANAAN GERAKAN LITERASI BAC PELAKSANAAN GERAKAN LITERASI BACA- TULIS DISEKOLAH DASAR NEGERI 022 MUARA MAHAT BARU

This study aims to see what literacy programs are implemented in elementary schools. Schools and teachers foster literacy through the GLS (School Literacy Movement) program. This study aims to see the extent to which literacy literacy programs are implemented in elementary schools. This type of research is a qualitative research with a descriptive approach. The instruments used in this study were interview guides, observations, and documentation. Interviews were conducted with class 1 homeroom teachers where this research was conducted at SDN 022 Muara Mahat Baru. The results of the research show that the program implemented at this school is (1) reading for fifteen minutes (2) reading corner (3) reading in the library or the teacher bringing a reading basket to class which can be done depending on when the teacher applies it. And in implementing literacy programs we need to carry out three stages, namely habituation, development, and learning.
Attitudes of special education teachers towards using augmented reality technology in teaching students with learning disabilities in Riyadh.

The primary aim of this study was to examine the views of special education teachers towards the integration of augmented reality technology in teaching students with learning disabilities in Riyadh.The researchers adopted an analytical descriptive approach and administered a questionnaire to 79 participants through social media platforms.The findings of the research indicated that special education teachers possess moderate attitudes towards the use of augmented reality technology, with an overall average score of 3.507 and a standard deviation of 1.006.The study's authors suggested a few recommendations, such as the necessity to encourage the adoption of augmented reality technology in all educational institutions in Saudi Arabia by offering teacher training programs.Furthermore, further investigation is required to evaluate the impact of augmented reality technology on the academic success of students and the teaching efficacy of educators, particularly those with learning disabilities, to ensure that its implementation is optimized.
K-CAE: Image Classification Using Convolutional AutoEncoder Pre-Training and K-means Clustering

The work presented in this paper is in the general framework of classification using deep learning and, more precisely, that of convolutional Autoencoder.In particular, this last proposes an alternative for the processing of high-dimensional data, to facilitate their classification.In this paper, we propose the incorporation of convolutional autoencoders as a general unsupervised learning data dimension reduction method for creating robust and compressed feature representations for better storage and transmission to the classification process to improve K-means performance on image classification tasks.The experimental results on three image databases, MNIST, Fashion-MNIST, and CIFAR-10, show that the proposed method significantly outperforms deep clustering models in terms of clustering quality.Povzetek
Development of Interactive Multimedia Based on Explanation Text Materials Using Adobe Animate

This research is a research and development research on interactive multimedia-based explanatory text that aims to determine the validation, practicality and effectiveness of the product developed. Development of Interactive Multimedia -Based Explanation Text Materials Using the Procedure for Developing ADDIE Model. The ADDIE development model has 5 steps, namely: Analyze, Design, Development, Implementation, and Evaluation (Evaluation). The results showed that effectiveness was obtained based on increased student learning outcomes after pretest and posttest with N-Gain of 0.65 'medium' criteria. In the completed student pretest as many as 7 out of 25 students after using a posttest product and students who completed 22 out of 25 students. Mastery learning with a percentage value of 88% with the 'very good' category. It can be concluded that student learning outcomes increase after using the teaching material for interactive and effective multimedia -based explanatory texts.
Pengaruh asap rokok elektrik terhadap kekasaran komposit nanohibrid dan bulkfill (Laporan Penelitian)

Background: Nanohybrid and nanohybrid bulkfill are two type of modified composites that were made to have low shrinkage level. These composites can have increased surface roughness after electric cigarette smoke exposure. Objective: To determine the difference of electric cigarette smoke exposure effect on surface roughness of nanohybrid and nanohybrid bulkfill composite. Method: 14 samples of nanohybrid and nanohybrid bulkfill composite were exposed to electric cigarette smoke for 7 days with 20 cycles of 10 blows for 4 second with 20 second pause for each blows, surface roughness for each samples were measured on day 0, day 3, day 5 and day 7. Samples were incubated for ± 24 hours with a temperature of 37°C. Result: Average surface roughness increase of nanohybrid bulkfill is higher compared to nanohybrid on every measurements. Mann-Whitney test showed there are no significant surface roughness difference between nanohybrid and nanohybrid composite on every measurements. Conclusion: Average surface roughness increase of nanohybrid bulkfill is higher than nanohybrid composite. There was no significant difference of surface roughness between the two group of nanohybrid and nanohybrid bulkfill composite.
Path of Trust: An Off-Chain Performance Enhancement Algorithm for Public Blockchains

Blockchain technology is one among the latest innovations in computing industry. Blockchains have gathered widespread interest in the industry due to their potential as secure data storage. Despite the potential benefits of blockchains, there are several limitations which hinders mass deployment, one of these limitations being low throughput. Low throughput has limited blockchain adoption in large scale applications such as banking or mobile payments. This study addresses this limitation through development of a performance enhancement algorithm called Path of Trust (PoT). PoT uses off-chain stratergy in which transactions meeting certain criteria bypass the main chain and sent direct to the recipient. The PoT algorithm was incorporated into a blockchain wallet that was developed as a mobile app. Experiments were run to verify the performance of the developed solution. Based on the experiments performed, the performance of the blockchain based on the developed solution was improved when compared to the original blockchain. With PoT algorithm running, the average transaction processing time was 12.81 secs per transaction compared to 18.52 secs when PoT was not running.
Corporate Social Responsibility (CSR) Effect on Teaching and Learning: Evidence from an Emerging Economy

This study examined the concept of Corporate Social Responsibility (CSR) and the effect of CSR initiatives on teaching and learning from teachers, students, and heads' perspectives. The study relied on in-depth interviews and focus-group discussions to obtain data. The participating schools were selected through a stratified sampling technique, with the individual respondents purposively sampled. Interviews and discussions were tape-recorded and subsequently transcribed, sorted to identify central and recurrent themes in the data. The study showed that corporate bodies have contributed immensely to the teaching and learning processes through improved school infrastructural facilities. It also found that CSR activities have enhanced teaching and learning processes. Thus, resulting in improved quality of teaching delivery, students' academic performance and beneficiary schools' societal status. The findings, however, focused mainly on the perspectives of teachers, students, and heads of schools. The findings are expected to maximize the effective deployment of CSR resources in education service and infrastructure provision in less-developed countries. The results are expected to engender further debate among corporations and other relevant stakeholders on the need for concerted efforts in tackling the school infrastructure deficit prevalent in less-developed nations. This study is one of its kinds on the effect of CSR initiatives on teaching and learning from direct beneficiaries' perspectives within the African context. This study also provides evidence of the need for a deliberate effort to encourage private-sector investment in school infrastructure.&#x0D; Keywords: Corporate Social Responsibility, Education financing, Emerging Economy, Teaching and Learning
Prediction and Formation of Creative Youth as a Class: Genetic-Modeling and Genetic-Creative Approaches

The article reveals the methodological problems of the study on the youth creative class formation.the purpose of the research is to carry out forecasting and formation of creative youth as a class in modern social and psychological conditions in line with the genetic­modeling and genetic­creative approaches.In accordance with the purpose, the main tasks are defined: the analysis of the demands made to young people in modern socio­psychological conditions; to find out the most adequate method of studying the personality of today and to determine its basic principles.research methods. A complex of scientific research methods was used to implement the key tasks: theoretical analysis, generalization, comparison, sys-tematization, theoretical modeling, and scientific interpretation.research results. It is established that the image of an ideal reference fi­gure, identification with which acts as an intermediate but important moment of life affirmation of a personality, constitutes a separate research problem in the modern psychology of life crises and the development of strategies for overcom-ing them. It is found out that the great potential of psychological science lies in its applied application for the purpose of overcoming the problems of the life crisis of a personality, in the disclosure of mechanisms of free internal dialogue of personal “Me” with different hypostases of self, in the disclosure of one’s own potential of subjectivity.It is shown that the genetic and creative method procedurally practically coincides with the process of counseling and therapy. This opens up the possibi­lity of scientific analysis of the data obtained in this process. It is established that this method helps to study the very process of psychological practice, making it the subject of scientific research. The main principles of the genetic and creative method were developed and defined, namely, the principle of development, the principle of experience, the principle of freedom, the principle of interaction, the principle of uncertainty and indeterminism, the principle of therapeutic effect.conlusions. The problem of scientific analysis of “grasping” the flow of a complexly structured entity, which is a personality, is analyzed, in particu-lar, the possibilities and limitations of nomothetic and ideographic methods, the problems of reductionism, the question of the constituting principle of the personality are highlighted. It is shown that the genetic­modeling method and the genetic­creative method are remained the most adequate methods of per-sonality research; the basic principles of use are explained. New aspects of re-search on personality development and self­affirmation in modern conditions are revealed
Improving the Role of Students in Teaching Campus Leraning 4 Introduction of Numbers in Mandarin Language in Students of SMP Gadjah Madan Medan

Language is a distinctive sign that distinguishes humans from other creatures and is used as a communication interaction. Language can differ from one country to another and from one tribe to another. Language shows the nation and the people who live in it, language can show how strong and how independent a nation is and how classy a nation is in its time. The objectives of implementing this Community Service activity are 1. To increase awareness of students at Gadjah Mada Middle School in Medan, 2. To provide students with an understanding of basic learning of numbers in Mandarin, 3. To provide moral and material support for students in blending in with the community various tribes and ethnicities., 4. Instill One Family World Values ​​through Information and Communication Technology. The target of this community service is Gadjah Mada Middle School students consisting of class VII, VIII and class IX. This Community Service activity is a visit and socialization with the theme Increasing the Role of Students in the Teaching Campus 4 Introduction to Numbers in Mandarin for Students of SMP Gadjah Madan Medan. The outputs generated from this Community Service are documentation about socialization and learning for students and reports as proof of community service that are published in the Community Service Journal institution.
ANALISIS LITERASI DIGITAL GURU MATEMATIKA MTSN 1 KUTAI KARTANEGARA

This study aims to determine the digital literacy of MTsN 1 Kutai Kartanegara mathematics teachers in preparing questions in mathematics learning. This research is a descriptive qualitative research. The subjects of this research are mathematics teachers including VII, VIII, and IX grade teachers at the school. The object of this research is the digital literacy of mathematics teachers. Data were collected through questionnaires, interviews, and documentation. Data analysis in this study was carried out using three stages, which are data reduction, data presentation, and conclusion drawing. The results showed that the digital literacy of mathematics teachers at MTsN 1 Kutai Kartanegara was categorized as capable in preparing questions in mathematics learning. In terms of teacher capabilities, they are capable in aspects of internet searching, content evaluation, and knowledge assembly. Although, in the aspect of hypertextual navigation they are still less capable