Reviewerly/exHarmony huggingface dataset:
Index graphs of finite permutation groups

Let &lt;em&gt;G&lt;/em&gt; be a subgroup of &lt;em&gt;S&lt;/em&gt;&lt;sub&gt;n&lt;/sub&gt;. For &lt;em&gt;x ∈ G&lt;/em&gt;, the index of &lt;em&gt;x&lt;/em&gt; in &lt;em&gt;G&lt;/em&gt; is denoted by &lt;em&gt;ind x&lt;/em&gt; is the minimal number of 2-cycles needed to express &lt;em&gt;x&lt;/em&gt; as a product. In this paper, we define a new kind of graph on &lt;em&gt;G&lt;/em&gt;, namely the index graph and denoted by &lt;em&gt;Γ&lt;/em&gt;&lt;sup&gt;ind&lt;/sup&gt;&lt;em&gt;(G)&lt;/em&gt;. Its vertex set the set of all conjugacy classes of &lt;em&gt;G&lt;/em&gt; and two distinct vertices &lt;em&gt;x ∈ C&lt;/em&gt;&lt;sub&gt;x&lt;/sub&gt; and &lt;em&gt;y ∈ C&lt;/em&gt;&lt;sub&gt;y&lt;/sub&gt; are adjacent if &lt;em&gt;Gcd(ind x, ind y) 6 ≠ 1&lt;/em&gt;. We study some properties of this graph for the symmetric groups &lt;em&gt;S&lt;/em&gt;&lt;sub&gt;n&lt;/sub&gt;, the alternating group &lt;em&gt;A&lt;/em&gt;&lt;sub&gt;n&lt;/sub&gt;, the cyclic group &lt;em&gt;C&lt;/em&gt;&lt;sub&gt;n&lt;/sub&gt;, the dihedral group &lt;em&gt;D&lt;/em&gt;&lt;sub&gt;2n&lt;/sub&gt; and the generalized quaternain group &lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;4n&lt;/sub&gt;. In particular, we are interested in the connectedness of them.
Pengelolaan Tinggalan Arkeologi: Kegiatan Pelestarian Sebagai Daya Tarik Wisata

Indonesia is one of the largest archipelagic countries in the world, one of which is rich in cultural diversity in the form of values, ideas, behaviors, and cultural heritage materials from the past to the present. Cultural diversity, such as archaeological remains, which is an asset for recording the development of historical and cultural values forming the identity of the Indonesian nation's civilization, has developed massively as a tourist attraction that can generate income. As a result, it have impact on increasing economic exploitation of archaeological remains by the government, local government, industry, and society. Which inturn often consciously or not causes problems besides causing degradation of historical and cultural values, as well as the existence of these archaeological remains. For this reason, the diversity of archaeological remains as a national asset is important to managed and preserved sustainably through a sustainable tourism development approach. Scientific articles that aim to provide ideas or concept solutions are like library research carried out through qualitative descriptive analysis methods by relying on the availability of secondary data and information relevant to the topic, both in print and electronic form, from various sources. Hopefully, this article can be input into the process of solving problems and making decisions needed by the government in formulating policies for managing archaeological remains in a sustainable and integrated manner to strengthen conservation efforts for the benefit of the people's welfare.
THE INFLUENCE OF PARENTAL GUIDANCE AND LEARNING MOTIVATION ON STUDENT MATHEMATICS LEARNING OUTCOMES BASED ON STUDENT EMOTIONAL INTELLIGENCE

The emotional intelligence of students is an essential aspect in achieving learning results, particularly in mathematics. This study intends to identify the impact of parental supervision and learning motivation on mathematics learning outcomes at Wahid Hasyim 8 Waru Middle School in terms of high, medium, and low emotional intelligence. This research utilizes quantitative research methods by doing ex-post facto. In collecting data, the researcher uses surveys and documentation. The questionnaire instrument contains three questionnaires, including a parent guidance questionnaire, a learning motivation questionnaire, and an emotional intelligence assessment. While documentation is used to collect statistics on student learning outcomes, it also serves as a means of communication between instructors and students. The results of hypothesis testing from the results of parental guidance and learning motivation on student learning outcomes are reviewed in terms of high emotional intelligence with an F count of 40,661 and an F sig of 0.024, moderate emotional intelligence with an F value of 5.288, and an F count of 0.010, and emotional intelligence with an F value of 7.073 and an F sig of 0.049. The association between mathematical learning results, parental supervision, and learning motivation in terms of emotional intelligence might be described as good and significant.
Designing 3D Animated Games as Learning Media For Lontara (Edulontara) Based on Android

At this time it is known that many children, especially students, have played games, both through computers and mobile phones. Students think that games can fill their spare time. The use of media that involves technology can affect student achievement and motivation, one of which is game play. The background of the research is that learning in schools still uses learning methods that use guidebook media, which causes a lack of interest and attention from students to take part in ongoing learning, for that it is necessary to develop an educational game that can be used as a medium of learning and can motivate students to be interested in study. The purpose of making 3D animation game applications for learning lontara script is so that students can easily understand and be interested in learning lontara script. The system development method used is waterfall starting from data collection, system analysis, application design, system testing and implementation. Black-box testing method that focuses on the functional requirements of the software. The programming language used is the Visual C programming language. With the application of the 3D animation game for learning the Lontara script, it is hoped that it can provide information and help students understand and be interested in learning the Lontara script.
Recycling Ablution Water (Wudu’) Using Membrane Water Treatment: A Study from Fiqh Halal Perspective

Water conservation is essential in Islam. The reuse of water for ablution through the process of water treatment is one way of water conservation. However, discussions and debates occurred because the source of water used for the treatment is categorized as musta’mal, which is pure but not purified and may contain mutanajjis water. This article proposes a model of treatment and purification of ablution water in mosques or surau using membrane water treatment for water reuse. This article uses a qualitative method focusing on document analysis regarding fiqh books, articles and guidelines related to water treatment technology. According to the fiqh and science, this study found that water treatment for treating used ablution water using membrane water filter is pure and clean.
RetroMAE v2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models

To better support retrieval applications such as web search and question answering, growing effort is made to develop retrieval-oriented language models. Most of the existing works focus on improving the semantic representation capability for the contextualized embedding of [CLS] token. However, recent study shows that the ordinary tokens besides [CLS] may provide extra information, which helps to produce a better representation effect. As such, it's necessary to extend the current methods where all contextualized embeddings can be jointly pre-trained for the retrieval tasks. With this motivation, we propose a new pre-training method: duplex masked auto-encoder, a.k.a. DupMAE, which targets on improving the semantic representation capacity for the contextualized embeddings of both [CLS] and ordinary tokens. It introduces two decoding tasks: one is to reconstruct the original input sentence based on the [CLS] embedding, the other one is to minimize the bag-of-words loss (BoW) about the input sentence based on the entire ordinary tokens' embeddings. The two decoding losses are added up to train a unified encoding model. The embeddings from [CLS] and ordinary tokens, after dimension reduction and aggregation, are concatenated as one unified semantic representation for the input. DupMAE is simple but empirically competitive: with a small decoding cost, it substantially contributes to the model's representation capability and transferability, where remarkable improvements are achieved on MS MARCO and BEIR benchmarks.
MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers

Pre-trained Language Models (LMs) have become an integral part of Natural Language Processing (NLP) in recent years, due to their superior performance in downstream applications. In spite of this resounding success, the usability of LMs is constrained by computational and time complexity, along with their increasing size; an issue that has been referred to as `overparameterisation'. Different strategies have been proposed in the literature to alleviate these problems, with the aim to create effective compact models that nearly match the performance of their bloated counterparts with negligible performance losses. One of the most popular techniques in this area of research is model distillation. Another potent but underutilised technique is cross-layer parameter sharing. In this work, we combine these two strategies and present MiniALBERT, a technique for converting the knowledge of fully parameterised LMs (such as BERT) into a compact recursive student. In addition, we investigate the application of bottleneck adapters for layer-wise adaptation of our recursive student, and also explore the efficacy of adapter tuning for fine-tuning of compact models. We test our proposed models on a number of general and biomedical NLP tasks to demonstrate their viability and compare them with the state-of-the-art and other existing compact models. All the codes used in the experiments are available at https://github.com/nlpie-research/MiniALBERT. Our pre-trained compact models can be accessed from https://huggingface.co/nlpie.
Validating Streaming JSON Documents with Learned VPAs

We present a new streaming algorithm to validate JSON documents against a set of constraints given as a JSON schema. Among the possible values a JSON document can hold, objects are unordered collections of key-value pairs while arrays are ordered collections of values. We prove that there always exists a visibly pushdown automaton (VPA) that accepts the same set of JSON documents as a JSON schema. Leveraging this result, our approach relies on learning a VPA for the provided schema. As the learned VPA assumes a fixed order on the key-value pairs of the objects, we abstract its transitions in a special kind of graph, and propose an efficient streaming algorithm using the VPA and its graph to decide whether a JSON document is valid for the schema. We evaluate the implementation of our algorithm on a number of random JSON documents, and compare it to the classical validation algorithm.
KEEFEKTIFAN PENERAPAN BIG BOOK BERBASIS ETNOPEDAGOGIK DALAM PEMBELAJARAN MEMBACA PERMULAAN DI KELAS I SEKOLAH DASAR

This research big book is motivated by the lack of use of teaching materials, the low reading skills of students as well as a lack of interest in reading. The purpose of this study was to determine the effect of applying big books ethnopedagogic-basedto students' early reading and to introduce students to the cultural behavior of Javanese society that students must possess. This research method is quantitative using a one group pretest posttest design. The population of this research is the first grade students of SDN Cipete Utara 15 Pagi, totaling 41 students. The sampling technique used is using saturated sampling. The sample in this study were all first grade students at SDN Cipete Utara 15 Pagi. Data collection techniques used are observation, interviews, and questionnaires. The data analysis technique is Paired Sample T-Test with the help of SPSS 25.0 Software. The results of the pretest- posttest that the initial reading score was 69.07 increased to 80.31. Based on the results of the different test, there are differences before and after the implementation of the big book based on ethnopedagogics with a significance value of 0.00 (&lt; 0.05). So it was concluded that there was an big book ethnopedagogic- basedinfluence on the early reading skills of first graders.
PENGARUH MEDIA POP UP BOOK BERBASIS LITERASI DIGITAL UNTUK MENINGKATKAN KETERAMPILAN BERBICARA SISWA KELAS RENDAH DI SEKOLAH DASAR

Speaking is one of the important skills that must be mastered by students, but teachers still have difficulty in teaching this skill to students. As a result, students' speaking skills are low. This study aimed to analize the effectiveness of digital literacy-based pop up book media in improving the speaking skills of lower grade students in elementary school. The method used was quantitative with a pretest-posttest design. The results showed that there were differences in students' speaking skills before and after using the media. This was indicated by the increase in the speaking ability of low-grade students after the use of digital literacy-based pop up book media.
The Use of Digital Technologies in the Educational Space to Improve the Effectiveness of Communication in the “Student-Teacher” Model

Currently, the use of digital technologies in the educational process is an urgent direction in the professional training of specialists of the higher professional education institutions. The use of digital technologies in the educational process allows to improve the quality of training, significantly increase the level of competitiveness of future specialists in the labor market, in many ways helps to create interactive conditions in the classroom. Digital technologies started to be used in the educational process during the pandemic of 2020–21, when distance learning was used as the main way of obtaining education. The article substantiates the necessity of the digital technologies’ application in organizations of the higher professional education system, considers four levels of changes in teaching practices using the technologies and suggests the use of “Virtual Reality (VR)” technology and concludes about the essence of digital transformation of education.
Study of the Damage and Fracture Processes of Heterogeneous Rocks Based on Fft Method - a Comparison of Computer Generation and Image Reconstruction Models

Studying the influence of microstructure on rock damage and fracture processes is of great practical engineering importance for evaluating the mechanical properties of surrounding rocks in complex geological engineering environments.Â To incorporate rock microstructures into numerical models, computer generation (e.g., molecular dynamics, MD) or image reconstruction methods (e.g., digital image processing, DIP) are frequently adopted, but the differences, advantages and disadvantages regarding the two methods in simulating damage and fracture processes in heterogeneous rocks have not been discussed and analyzed yet. In this study, the MD model was first optimized on the basis of the previous work, and the "Realistic grain size based microstructure model generation program" was developed by combining the estimated mineral grain sizes from microscopic images, and then the DIP model was established by using the image reconstruction method. On this basis, a numerical method based on Fast Fourier transform (FFT), which is self-developed, is used to simulate the failure process of heterogeneous rocks under different confining pressures. First, a series of macro-microscopic experiments were used to obtain the basic mechanical properties of the Dingziwan Granite (DG). Then, generated examples of improved MD and DIP models are given, with carefully calibrated microscopic parameters using macro-microscopic experiments. Third, the macroscopic mechanical behavior of DG under different confining pressures was predicted using two models. Finally, the differences between the two models are compared quantitatively. Results indicate that both micromechanical models established in this study can reasonably predict the main characteristics of macromechanical behavior of heterogeneous rocks, but the two models have different mechanical responses to varying scales due to the local stress concentration phenomenon. The improved MD model can efficiently study the influence of rock heterogeneity on its macroscopic mechanical behavior, while the DIP model can highly reproduce the types of microcracks (intragranular, transgranular and grain boundary cracks) and the transition of brittle-ductile failure pattern of rocks.
Egocentric Hand-object Interaction Detection

In this paper, we propose a method to jointly determine the status of hand-object interaction. This is crucial for egocentric human activity understanding and interaction. From a computer vision perspective, we believe that determining whether a hand is interacting with an object depends on whether there is an interactive hand pose and whether the hand is touching the object. Thus, we extract the hand pose, hand-object masks to jointly determine the interaction status. In order to solve the problem of hand pose estimation due to in-hand object occlusion, we use a multi-cam system to capture hand pose data from multiple perspectives. We evaluate and compare our method with the most recent work from Shan et al. \cite{Shan20} on selected images from EPIC-KITCHENS \cite{damen2018scaling} dataset and achieve $89\%$ accuracy on HOI (hand-object interaction) detection which is comparative to Shan's ($92\%$). However, for real-time performance, our method can run over $\textbf{30}$ FPS which is much more efficient than Shan's ($\textbf{1}\sim\textbf{2}$ FPS). A demo can be found from https://www.youtube.com/watch?v=XVj3zBuynmQ
Region Proposal Network Pre-Training Helps Label-Efficient Object Detection

Self-supervised pre-training, based on the pretext task of instance discrimination, has fueled the recent advance in label-efficient object detection. However, existing studies focus on pre-training only a feature extractor network to learn transferable representations for downstream detection tasks. This leads to the necessity of training multiple detection-specific modules from scratch in the fine-tuning phase. We argue that the region proposal network (RPN), a common detection-specific module, can additionally be pre-trained towards reducing the localization error of multi-stage detectors. In this work, we propose a simple pretext task that provides an effective pre-training for the RPN, towards efficiently improving downstream object detection performance. We evaluate the efficacy of our approach on benchmark object detection tasks and additional downstream tasks, including instance segmentation and few-shot detection. In comparison with multi-stage detectors without RPN pre-training, our approach is able to consistently improve downstream task performance, with largest gains found in label-scarce settings.
UniRel: Unified Representation and Interaction for Joint Relational Triple Extraction

Relational triple extraction is challenging for its difficulty in capturing rich correlations between entities and relations. Existing works suffer from 1) heterogeneous representations of entities and relations, and 2) heterogeneous modeling of entity-entity interactions and entity-relation interactions. Therefore, the rich correlations are not fully exploited by existing works. In this paper, we propose UniRel to address these challenges. Specifically, we unify the representations of entities and relations by jointly encoding them within a concatenated natural language sequence, and unify the modeling of interactions with a proposed Interaction Map, which is built upon the off-the-shelf self-attention mechanism within any Transformer block. With comprehensive experiments on two popular relational triple extraction datasets, we demonstrate that UniRel is more effective and computationally efficient. The source code is available at https://github.com/wtangdev/UniRel.
Learning Reward Functions for Robotic Manipulation by Observing Humans

Observing a human demonstrator manipulate objects provides a rich, scalable and inexpensive source of data for learning robotic policies. However, transferring skills from human videos to a robotic manipulator poses several challenges, not least a difference in action and observation spaces. In this work, we use unlabeled videos of humans solving a wide range of manipulation tasks to learn a task-agnostic reward function for robotic manipulation policies. Thanks to the diversity of this training data, the learned reward function sufficiently generalizes to image observations from a previously unseen robot embodiment and environment to provide a meaningful prior for directed exploration in reinforcement learning. We propose two methods for scoring states relative to a goal image: through direct temporal regression, and through distances in an embedding space obtained with time-contrastive learning. By conditioning the function on a goal image, we are able to reuse one model across a variety of tasks. Unlike prior work on leveraging human videos to teach robots, our method, Human Offline Learned Distances (HOLD) requires neither a priori data from the robot environment, nor a set of task-specific human demonstrations, nor a predefined notion of correspondence across morphologies, yet it is able to accelerate training of several manipulation tasks on a simulated robot arm compared to using only a sparse reward obtained from task completion.
Training of Pre-Service Teachers of Computer Science in Computer Graphics

The article is devoted to the issue of teaching computer graphics to students of computer science at pedagogical universities, which is related to the development of information and communication technologies and modern trends in education.Based on a survey conducted with the participation of the authors of more than 250 representatives of IT companies and computer science teachers, it has been determined what life competences should be formed by teachers in students within computer science classes according to the requirements of the labour market, which sections of computer graphics are promising for student learning and therefore important for training of pre-service teachers of computer science.The content of computer graphics training for pre-service teachers of computer science at five pedagogical universities of Ukraine is analysed, the system of computer graphics training for pre-service teachers of computer science at the National Pedagogical Dragomanov University is described.Besides, the structure is presented and the need for the introduction of a specially developed electronic training course for distance learning of pre-service teachers of computer science is defined.It is determined which components of the information and digital competence of pre-service teachers of computer science the course in computer graphics should be aimed at.It is noted that this course contributes to the formation of important informationdigital and professional competences, which are necessary for a modern specialist in the field of computer graphics as well as for a pre-service computer science teacher.The teachers who took part in the survey emphasised that they lacked qualification in dealing with such methodological issues as active methods of teaching computer science (51.1%), the cognitive-research method (44.8%), the educational project method (41.6%) etc.