Reviewerly/exHarmony huggingface dataset:
Regularization by Denoising for Inverse Problems in Imaging

In this work, a generalized scheme of regularization of inverse problems is considered, where a priori knowledge about the smoothness of the solution is given by means of some self-adjoint operator in the solution space. The formulation of the problem is considered, namely, in addition to the main inverse problem, an additional problem is defined, in which the solution is the right-hand side of the equation. Thus, for the regularization of the main inverse problem, an additional inverse problem is used, which brings information about the smoothness of the solution to the initial problem. This formulation of the problem makes it possible to use operators of high complexity for regularization of inverse problems, which is an urgent need in modern machine learning problems, in particular, in image processing problems. The paper examines the approximation error of the solution of the initial problem using an additional problem.
Theatre in the Age of Digital Technologies

The paper studies the functioning of modern theater in regard to the use of digital technologies. New digital technologies affect the development of theater as an art form, with unique forms of performances, new theatrical specialties, specific technologies of stage creativity, and theatrical work appearing. Currently, the technification of theatre stage design, a process of mutual influence ofscience and art, goes along with the aestheticization of theatre equipment. The concept of the virtual and interactive theatre was also clarified due to the influence of digital culture. In this context, introduction of new technologies in theatre is associated with the changes in the stage design imagery linked to the change in worldview, with the development ofsocio-aesthetic features of the clash of different eras, the enhancement of the theatre technical equipment, which contributes to the emergence of new genre precedents in theatre. At the same time, digital technologies in modern stage design made it possible to form a new culture of scenography, adding a diverse, spatial composition, special effects, hyperrealism or expressionistic blur to the space of the stage. Digital culture and its new technologies contribute to the globalization of the perception of theatrical art, including online broadcasts of performances, where new technologies radically influence the dynamics of the artistic process and serve as a source of diversity in the existing forms of theatrical discourse and its artistic practice.
THE VOCABULARY MASTERY OF THE SEVENTH GRADE STUDENTS OF SMP NEGERI 4 BAUBAU BY USING ANIMATION VIDEO

The problem statement of this research was does the use of animation video improve the vocabulary mastery of seventh grade students of SMP Negeri 4 Baubau. The objective of this research was to find out whether or not the use of animation video improve the vocabulary mastery of seventh grade students of SMP Negeri 4 Baubau. The type of the research was a quantitative research with applying quasi- experimental method. The population was the seventh grade students of SMP Negeri 4 Baubau as many as 325 students. The sample was taken using cluster random sampling amounted 58 students. The data collection was carried out by using an instrument that was test. The data obtained were analyzed by descriptive statistics and inferential statistics. Based on the results of data analysis, it can be concluded that there is a significant effect of the application of animation video on the vocabulary mastery of seventh grade students at SMP Negeri 4 Baubau. The t-test results show that the probability value (t-count) is 2.295 and sig (2-tailed) is 0.025 which is less than 0.05 so that the alternative hypothesis (Ha) is accepted and the null hypothesis (HO) is rejected. It means, there is a significant effect before and after the application of animation video, as well as the average value of pre-test and post-test experimental class 51.55 to 80.76. as well as the control class 55.24 to 70.28.
AN ANALYSIS OF STUDENTS’ ATTITUDE IN LEARNING ENGLISH AT ELEVENTH GRADE OF SMA NEGERI 2 GU

The problem in this study was how were the students’ attitude in learning English at eleventh grade of SMA Negeri 2 Gu? This study aimed at determining and identifying students’ attitude in learning English in the eleventh grade of SMA Negeri 2 Gu. The design of this study was a descriptive qualitative. Subjects of the research were fifteen students of eleventh grade at SMA Negeri 2 Gu. Techniquies of data collection in this study were questionnaire and interviw. Techniques of data analysis used were data reduction, data display and conclusion. The result showed thwt te students had positive attitude in learning English, which consisted of aspect of cognitive attitude, aspect of affective attitude and aspect of behavior attitude. In all aspects students’ attitude were in the good category. Based on three aspects of attitudes, the most dominant aspect of attitude was the affective attitude aspect.
Hyperrealism Of Shaken Consciousness

The article analyzes the transformation of the artistic consciousness of the majority of Ukrainian artists in the conditions of Putin’s war in Ukraine. It is traced how the barbarism of the orcs gave rise to psychological and creative resistance in the artistic environment. The logic in the grotesque-reductive series of works by V. Kravets is analyzed. The method of the artist’s work with the wide use of meaningful metaphors is shown. As a critic of the brutality and barbarism of the enemy army, the author of the drawings makes the body-lower sphere a generalizing image of the “all-Russian body”. It is shown that the characters of the series are monsters, their images are essentially excrement. This grotesque realism is so demeaning — hyperrealism, figurative recoding in the drawings of V. Kravets connects his method to the concept of the “tragic carnival” of German expressionism of the 1930s–1950s. Irony and sarcasm bordering on the terrible illustrate the relevance of a series of drawings, depicting existence on the shaky border between “life and death”. Laughter in the artist’s works changes from plus to minus.
READING ANXIETY AND ITS EFFECT TOWARDS READING COMPREHENSION ON GRADE EIGHT STUDENTS OF SMP NEGERI 1 BAUBAU

Problem statement of this research was whether there are any significant correlation of reading anxiety towards reading comprehension on grade eight students of SMP Negeri 1 Baubau. Objective of the research was to find out whether there was the correlation reading anxiety towards reading comprehension on grade eight students of SMP Negeri 1 Baubau. The data collection in this research was carried out using a research instrument in the form of a questionnaire to determine the student’s reading anxiety and a test to determine student’s reading comprehension. The data obtained were analysis by descriptive statistical analysis and inferential statistical analysis. The results of this research showed that the correlation coefficient value of students reading anxiety towards students reading comprehension was 0.037 with a significant level of 0.798. Because the sig.(2-tailled) &gt; 0.05 the hypothesis H0 is accepted and H1 was rejected. It means that there was not any significant and correlation classroom reading anxiety towards reading comprehension on grade eight students of SMP Negeri 1 Baubau.
Assessment of the Gambian Police Force on Crime Prevention and Control

The study assessed the Gambia Police Force (GPF) on Crime Prevention and Control in the Greater Banjul Area of The Gambia from 2017 to 2019. The study used both primary and secondary data. Primary data were collected using questionnaires and interview guides. The targeted population for this study was serving members of The Gambia Police Force (GPF), and 254 members were sampled out of 700 populations using the Taro Yamane formula. The distribution of the sample size was based on convenient sampling in terms of accessing major police stations and police posts. In the course of the fieldwork, 254 copies of the questionnaire were administered with the aim of retrieving the required number meant for the study. The study used descriptive and inferential statistical tools to analyse the data. Three interviews were conducted with officials from GAF, NAATIP, and WANEP who are knowledgeable on the subject of investigation. The selection and distribution of the numbers of respondents were purposively interviewed. The findings of the study revealed that the GPF used outdated gadgets and human intelligence as methods and approaches in responding to crime prevention and control in the country. The study also revealed that GPF faced certain operational limitations in using modern security tools. This was due to inadequate exposure in terms of training and the challenge of the apolitical among the ranks and files of the GPF. The study identified copious challenges facing GPF which is a general issue in most African countries based on the extant literature. The challenge of funding; corruption; political interference; indiscipline; non-compliance and reporting of some citizens and so on, have constituted some level of hindrances to the GPF on crime prevention and control in The Gambia. This paper evaluates the effectiveness of the methods and approaches used by the GPF on crime prevention and control; and assess the challenges facing the GPF on crime prevention and control in the Gambia (GBA).
Second-Order Statistics for STBC Classification Over Amplify-and-Forward Cooperative Systems

The space-time block code (STBC) classification has recently been recognized as a prominent fundamental tool for the development of smart communication systems, which are applied in both the defense and private sectors.The use of multiple antennas at the transmitter introduces a new dimension of difficulty to the signal classification task since it is essential to make judgments about the number and arrangement of broadcast antennas.The reported research has only addressed STBC classification over noncooperative environments, with no solutions offered for cooperative transmissions.A comprehensive STBC classification algorithm for amplify-and-forward cooperative transmissions is proposed in this investigation.The classification procedure is predicated on analytical formulas established for the time-domain features of the STBC signals.There are two phases involved in implementing the offered algorithm into practice.The first stage includes estimating the correlation functions of the incoming signals across two different time periods using second-order statistics, and a false alarm oriented assessment is utilized in the second stage to produce a judgment.The proposed algorithm's many benefits involve not necessitating any previous information about the modulation form, channel characteristics, signal-to-noise ratio (SNR), or the start of STBC blocks.Simulation experiments demonstrate that the proposed algorithm can give adequate classification performance in the presence of transmission imperfections even at relatively low SNR levels.
VISITOR GUIDE APPLICATION AT MUSEUM WITH AUGMENTED REALITY ANDROID-BASED

Study this aim as a spatial introduction media on each the floor of the museum and the collections of the Regional Museum of Deli Serdang Pada Visitors Android based . Study this conducted at the Regional Museum of Deli Serdang, which is located at Jalan Negara, Petapahan Sports , Arts and Culture Area , Lubuk Pakam , Deli Serdang, North Sumatra 20517. In research this writer use Research and Development (R&amp;D) methods . Study it also uses Rapid Application Development (RAD) as methodology development application . In conclusion this that the Visitor Guide Application (VGA) with technology Augemented Reality at the Regional Museum of Deli Serdang based on Android has built use Unity 3d apps , Blender and Vuforia with attractive appearance and user friendly. Augmented reality technology can used as tool guide because capable displays 3d object on each collection . The Visitor Guide Application (VGA) is also used as an introduction to spatial planning in each area the floor of the museum and collections in the Deli Serdang Regional Museum visitors Android based . Application this aim for make it easy visitors and the museum in the introduction process collections at the Regional Museum of Deli Serdang.
Training on The Utilization of Mendeley and Similarity in Increasing The Quality of Students’ Academic Work

Undergraduate students (S1) who complete their studies are required to be able to write not only a final project in the form of a thesis, but also a scientific pa-per in the form of scientific articles. However, the issue is that students view writing research reports as a very tiresome task, whether it's making quota-tions, creating lists, or many prefer a fast flow such as copy paste. As a result, this training activity is predicted to be beneficial for students in terms of writ-ing research results and the outcomes of their studies in the form of scientific papers, as well as enhancing the quality of scientific articles for students, par-ticularly in the field of education. The instructional approach is a combination of lecture, question and answer, simulation, and practice.
Guidance for Students in The Development of Learning Media to Increase Learning Outcomes

Overcoming the problem of low student learning outcomes is very important for the development of learning media so that students get good learning outcomes. Therefore, this study aims to determine the development of learning media to improve social studies learning outcomes. The population in this study were all students of class V as many as 22 students. The total value of the learning media development test on student learning outcomes is 0.81, in accordance with the findings of this study that the impact index value obtained is positive. The development of learning media has a significant effect on student learning outcomes. The development of learning media is considered successful if it is able to actively involve students in the learning process physically, mentally, and socially, as well as increase students' self-confidence.
Tumada Peak Drinking Water Supply System Plan (SPAM) Tumada Village is Located in The Kapontori District of The Buton Regency

The community service program's objective is to apply technical knowledge, particularly civil engineering, to the village government and the local population. So they may appreciate the critical nature of discussion and consultation over image design during the Planning for Drinking Water Supply System (SPAM) phase prior to construction. The program's implementation is supposed to result in a design that is responsive to the needs and conditions of the surrounding environment. To accomplish this, effective design concepts and mentorship methods are employed to provide consulting services to the village administration and community, ensuring that the program's objectives are realized. The final results acquired include the design and budget for the Puncak Tumada Drinking Water Supply System (SPAM) in Tumada Village, Kapontori District, Buton Regency.
Audio Visual Media Learning Guidance using Wondershare Filmora as Elementary School Teacher Professional Development in Batupoaro District Baubau City

The field of Information Technology which is the basis of learning, in this case the basis of the Teacher Working Group is obliged to share about video editing procedures with Filmora. In addition, the existence of a Teacher Working Group organization in Batupoaro District is also a strong reason to help schools that have not yet received an understanding of the Wondershare Filmora software. The method used in this service activity is in the form of socialization and practice. Through training and guidance, it is hoped that the Teacher Working Group in Batupoaro District can make Wondershare Filmora software as a good learning medium to be applied in elementary schools. The results of this service activity are marked by increased knowledge, understanding and skills of the Teacher Working Group Batupoaro Cluster 2 Baubau City has: 1) a better understanding of multimedia, especially in terms of video editing, 2 becomes more aware of applicable information technology, 3) become more aware of the Wondershare Filmora software application in daily learning classes, 4) become more confident when entering the community with the knowledge they have
Agnostic PAC Learning of k-juntas Using L2-Polynomial Regression

Many conventional learning algorithms rely on loss functions other than the natural 0-1 loss for computational efficiency and theoretical tractability. Among them are approaches based on absolute loss (L1 regression) and square loss (L2 regression). The first is proved to be an \textit{agnostic} PAC learner for various important concept classes such as \textit{juntas}, and \textit{half-spaces}. On the other hand, the second is preferable because of its computational efficiency, which is linear in the sample size. However, PAC learnability is still unknown as guarantees have been proved only under distributional restrictions. The question of whether L2 regression is an agnostic PAC learner for 0-1 loss has been open since 1993 and yet has to be answered. This paper resolves this problem for the junta class on the Boolean cube -- proving agnostic PAC learning of k-juntas using L2 polynomial regression. Moreover, we present a new PAC learning algorithm based on the Boolean Fourier expansion with lower computational complexity. Fourier-based algorithms, such as Linial et al. (1993), have been used under distributional restrictions, such as uniform distribution. We show that with an appropriate change, one can apply those algorithms in agnostic settings without any distributional assumption. We prove our results by connecting the PAC learning with 0-1 loss to the minimum mean square estimation (MMSE) problem. We derive an elegant upper bound on the 0-1 loss in terms of the MMSE error and show that the sign of the MMSE is a PAC learner for any concept class containing it.
Structural Similarity: When to Use Deep Generative Models on Imbalanced Image Dataset Augmentation

Improving the performance on an imbalanced training set is one of the main challenges in nowadays Machine Learning. One way to augment and thus re-balance the image dataset is through existing deep generative models, like class-conditional Generative Adversarial Networks (cGAN) or Diffusion Models by synthesizing images on each of the tail-class. Our experiments on imbalanced image dataset classification show that, the validation accuracy improvement with such re-balancing method is related to the image similarity between different classes. Thus, to quantify this image dataset class similarity, we propose a measurement called Super-Sub Class Structural Similarity (SSIM-supSubCls) based on Structural Similarity (SSIM). A deep generative model data augmentation classification (GM-augCls) pipeline is also provided to verify this metric correlates with the accuracy enhancement. We further quantify the relationship between them, discovering that the accuracy improvement decays exponentially with respect to SSIM-supSubCls values.
Topological Generality and Spectral Dimensionality in the Earth Mineral Dust Source Investigation (EMIT) using Joint Characterization and the Spectral Mixture Residual

NASA's Earth Surface Mineral Dust Source Investigation (EMIT) mission seeks to use spaceborne imaging spectroscopy (hyperspectral imaging) to map the mineralogy of arid dust source regions. Here we apply recent developments in Joint Characterization (JC) and the spectral Mixture Residual (MR) to explore the information content of data from this novel mission. Specifically, for a mosaic of 20 spectrally diverse scenes we find: 1) a generalized three-endmember (Substrate, Vegetation, Dark; SVD) spectral mixture model is capable of capturing the preponderance (99% in 3 dimensions) of spectral variance with low misfit (99% of pixels with RMSE < 3.7%); 2) manifold learning (UMAP) is capable of identifying spatially coherent, physically interpretable clustering relationships in the spectral feature space; 3) UMAP yields results that are at least as informative when applied to the MR as when applied to raw reflectance; 4) SVD fraction information usefully contextualizes UMAP clustering relationships, and vice-versa (JC); and 5) when EMIT data are convolved to spectral response functions of multispectral instruments (Sentinel-2, Landsat 8/9, Planet SuperDove), SVD fractions correlate strongly across sensors but UMAP clustering relationships for the EMIT hyperspectral feature space are far more informative than for simulated multispectral sensors. Implications are discussed for both the utility of EMIT data in the near-term, and for the potential of high SNR spaceborne imaging spectroscopy more generally, to transform the future of optical remote sensing in the years and decades to come.
X-Pruner: eXplainable Pruning for Vision Transformers

Recently vision transformer models have become prominent models for a range of tasks. These models, however, usually suffer from intensive computational costs and heavy memory requirements, making them impractical for deployment on edge platforms. Recent studies have proposed to prune transformers in an unexplainable manner, which overlook the relationship between internal units of the model and the target class, thereby leading to inferior performance. To alleviate this problem, we propose a novel explainable pruning framework dubbed X-Pruner, which is designed by considering the explainability of the pruning criterion. Specifically, to measure each prunable unit's contribution to predicting each target class, a novel explainability-aware mask is proposed and learned in an end-to-end manner. Then, to preserve the most informative units and learn the layer-wise pruning rate, we adaptively search the layer-wise threshold that differentiates between unpruned and pruned units based on their explainability-aware mask values. To verify and evaluate our method, we apply the X-Pruner on representative transformer models including the DeiT and Swin Transformer. Comprehensive simulation results demonstrate that the proposed X-Pruner outperforms the state-of-the-art black-box methods with significantly reduced computational costs and slight performance degradation.
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Data pruning aims to obtain lossless performances with less overall cost. A common approach is to filter out samples that make less contribution to the training. This could lead to gradient expectation bias compared to the original data. To solve this problem, we propose \textbf{InfoBatch}, a novel framework aiming to achieve lossless training acceleration by unbiased dynamic data pruning. Specifically, InfoBatch randomly prunes a portion of less informative samples based on the loss distribution and rescales the gradients of the remaining samples to approximate the original gradient. As a plug-and-play and architecture-agnostic framework, InfoBatch consistently obtains lossless training results on classification, semantic segmentation, vision pertaining, and instruction fine-tuning tasks. On CIFAR10/100, ImageNet-1K, and ADE20K, InfoBatch losslessly saves 40\% overall cost. For pertaining MAE and diffusion model, InfoBatch can respectively save 24.8\% and 27\% cost. For LLaMA instruction fine-tuning, InfoBatch is also able to save 20\% cost and is compatible with coreset selection methods. The code is publicly available at \href{https://github.com/henryqin1997/InfoBatch}{github.com/NUS-HPC-AI-Lab/InfoBatch}.