Reviewerly/exHarmony huggingface dataset:
Autonomous Vehicles Roundup Strategy by Reinforcement Learning with Prediction Trajectory

Autonomous vehicles are increasingly applied on many situations, but their autonomous decision-making ability needs to be improved. Multi-Agent Deep Deterministic Policy Gradient(MADDPG) adopts the method of centralized evaluation and decentralized execution, so that the autonomous vehicle can obtain the whole-field status information and make decisions through the companion information. In the process of autonomous vehicle training, we introduce artificial potential field, action guidance and other methods to alleviate the problem of sparse rewards. At the same time, we add a repulsion function to consider the relationship between team vehicles. Extended Kalman Filter(EKF) is also applied to predict the autonomous vehicle trajectory, changing the training network state input information. At the same time, secondary correction of the predicted autonomous vehicle trajectory is made to change the prediction range with the training time, and improve the training convergence speed while the speed of opposite agents increases. Simulation experiments show that the convergence speed and win rate of MADDPG algorithm based on trajectory prediction and artificial potential field is significantly improved, and it also has strong adaptability to various task scenarios.
Medir a qualidade da escrita em Português L2 a densidade de ideias

The paper proposes to look at idea density as a measure of lexical richness and precision in L2 Portuguese. Idea density (Kemper et al. 2001; Snowdon et al. 1999) is a measure of lexical richness and precision that has been associated with grammatical complexity in a study about the quality of L1 writing at different stages of life. Nevertheless, we argue that the same analysis methodology can be useful in the evaluation of L2 Portuguese writing. Thus, we propose the analysis of a writing task, a synthesis, written by a group of adult learners of advanced L2 Portuguese based on the same method used by Snowdon et al. (1999). The results show that idea density found in the written texts is not very high, which may be due to a lack of motivation for writing, as well as to lack of familiarity with the written register.
An Appraisal System Based Discourse Analysis on China-Hungary Anti-epidemic Reports

As the official media, China Daily's attitude in foreign reports is highly consistent with the government's foreign policy.Based on the theories of CDA and PDA, this paper analyzes the attitude resources in the reports of China and Hungary fighting against the epidemic.The results demonstrate that the affect resources take the largest proportion in China Daily's China-Hungary anti-epidemic reports.Almost all attitude resources are positive and mainly expressed in the implicit form (invoked).More appraisers are among others rather than the author of the report.The appraised are primarily others instead of the appraiser oneself.This evaluation mode ensures the objectivity of the report and helps to win the trust and support of readers.
A CMOS Compatible Bistable Resistively-coupled Ising Machine-BRIM

Ising machines and other nature-based computing platforms have recently become attractive due to their potential of outperforming conventional computers when solving problems that involve a large number of competing alternatives, such as combinatorial optimizations. In this paper, a newly proposed resistively-coupled Ising machine with bistable nodes (BRIM) is designed and simulated in a 45nm CMOS process. The performance of the proposed machine is evaluated based on its capability of solving the Max-cut graph problem. A spin-fix annealing technique is applied to help escape local minima and improve the solution quality. Simulation result shows that this technique effectively increases the probability of finding the Max-cut solution by 50.5% and reduces the solution error to 1.73 on average.
Pengaruh Metode PQRST Berbantuan Media Puzzle Kalimat Terhadap Keterampilan Membaca Pemahaman

This research aims to determine the effect of the PQRST method assisted by Sentence Puzzle Media on Reading Comprehension Skills for Grade 4 Students at SDN Banyakan, Mertoyudan District, Magelang District.The research design design uses a Pre-Experimental with the type of One Group Pretest-Posttest Design. Samples taken as many as 25 students through saturated sampling technique. The data collection method used in this research is the performance test. The validity test of intrumen by expert and using with SPSS 24.0 for windows like that reliability test. Prerequisite analysis test consist end from normality test, while data analysis used parametric statistical techniques, namely the Paired Sample T-test with the help of SPSS 24.0 for windows.The results showed the reading comprehension skills of the fourth grade students of SDN Banyakan before using the PQRST method assisted by sentence puzzle media (Pre test), the highest reading comprehension skills were 66, while the lowest was 13 with the average student being 41.20. The results of reading comprehension skills after using the PQRST method with sentence puzzle media (Post test) obtained the highest score of 87, the lowest score of 40 with the average reading comprehension skills of students was 62.76. Based on the results of the study showed that the PQRST method assisted by sentence puzzle media had a significant effect on reading comprehension skills of fourth grade students of SDN Banyakan. This is indicated by the tcount value of 16.800 with a sig = 0.00 (p &lt;0.05).
A Method to Estimate COVID-19 Contamination Risk Based on Social Distancing and Face Mask Detection Using Convolutional Neural Networks

We present a method for evaluating COVID-19 contamination risk based on social distancing between individuals and face mask usage. Our method employs images captured by surveillance cameras as input to a system that computes a health risk indicator in real time. This system can handle real-world situations, performing detections in large public spaces, such as squares and streets, as well as other potentially crowded areas like restaurants and shopping centers. Our system uses the number of people with and without masks and their proximity to evaluate the risk of COVID-19 contamination. We employed deep neural networks to detect people with and without masks, and we used computer vision to measure the distance between them. Both cases presented challenges, including distinguishing face masks at wildly different distances and positions concerning the camera, occlusions, shape variance, etc. We have built and made public a face mask detection dataset (44,402 faces) with images that include these challenging scenarios and used them to train our deep neural networks. Our best deep neural network architecture achieved 91.41% precision, 82.88% accuracy, and 89.88% recall on face mask detection.
Rider Re-identification Based on Pyramid Attention

In recent years, object re-identification (ReID) based on deep learning has made great progress, and research in this field mainly focuses on person and vehicle. However, the researchers ignore an important target: riders. Electric bikes are an essential part of modern transportation scenarios, so identifying riders and monitoring their behavior on a large scale is critical to public safety management. To bridge the research gap of rider ReID, this paper proposes a pyramid attention network (PANet), which utilizes the pyramid structure to capture multi-scale clues and discovers key regional features from fine to coarse. PANet first learns fine-grained attention in local small regions, then gradually aggregates local regions to expand the scope of attention exploration, and finally conducts global coarse-grained attention learning. We implement two different dimensional attention computations in the pyramid attention network: spatial attention and channel attention. Experiments on BPReID and MoRe datasets demonstrate the effectiveness of this network design, which can achieve better performance with limited computational overhead.
A Distributed SAT-Based Framework for Closed Frequent Itemset Mining

Frequent Itemset Mining is an essential part of data mining. SAT-based approaches that extract frequent itemsets in big data encounter significant challenges when computing power and storage capacity are limited. This paper proposes an efficient distributed SAT-based framework for the Closed Frequent Itemset Mining problem (CFIM) which minimizes communications throughout the distributed architecture and reduces bottlenecks due to shared memory. Moreover, it enhances scalability and fault tolerance. This approach makes use of a Computation-Distributed Paradigm to efficiently enumerate the set of all closed itemsets, by reducing the processing time. To the best of our knowledge, this paper presents the first attempt towards a distributed SAT-based approach for CFIM. An extensive empirical evaluation on various real-word datasets shows the efficiency of the approach.
Towards Design Patterns for Production Security

In Production System Engineering (PSE), domain experts aim at effectively and efficiently analyzing and mitigating information security risks to product and process qualities for manufacturing. However, traditional security standards do not connect security analysis to the value stream of the production system nor to production quality requirements. This paper aims at facilitating security analysis for production quality already in the design phase of PSE. In this paper, we (i) identify the connection between security and production quality, and (ii) introduce the Production Security Network (PSN) to efficiently derive reusable security requirements and design patterns for PSE. We evaluate the PSN with threat scenarios in a feasibility study. The study results indicate that the PSN satisfies the requirements for systematic security analysis. The design patterns provide a good foundation for improving the communication of domain experts by connecting security and quality concerns.
PELATIHAN MEMBUAT MEDIA PEMBELAJARAN MULTIMEDIA BAGI GURU-GURU DI SD MUHAMMADIYAH IV KOTA PADANG

SD Muhammadiyah IV Padang City is an educational institution located at Jln Sawahan No.103, Simpang Haru, Kec. East Padang, Padang City Prov. West Sumatra. Teaching and learning activities at SD Muhammadiyah IV Padang City have used Curriculum 13. The problem with partners raised in this community service program is the lack of maximum knowledge of teachers about Curriculum 13 at partner schools. Constraints that are often experienced by partners are in learning tools, especially in the models and learning media used. In addition, the lack of teacher knowledge by combining Curriculum 13 with learning media. In relation to the main problems that have been mentioned, this program will offer solutions that are expected to solve partner problems.The method used is a participatory approach, which is an approach that is oriented to efforts to increase the participation of teachers directly in making multimedia learning media. The participatory approach in essence can be interpreted as an effort or way to involve teachers in learning activities which include three stages, namely the program planning stage, program implementation and program assessment.The result of this community service program is that partners will have multimedia learning media. In addition, another result is an increase in learning tools in accordance with Curriculum 13. And schools (principals and teachers) can use the media in their respective classes. The results of this service will be published in an accredited national journal. The rest will be teaching materials for MI/SD Social Studies courses at PGMI FAI UMSB Keywords –Media, Learning, Multimedia, Approach, Participatory
12th International Conference on Educational Studies and Applied Linguistics

To be able to use the target language sentence structure efficiently, a speaker needs to learn and have a very large number of words (Nation, 2013). Research shows that understanding the meaning of a word is not sufficient, rather, it involves more than just its meaning; such as spelling, and grammatical behavior (Pigada &amp; Schmitt, 2006). Vocabulary acquisition requires effective methods. One of the methods of learning vocabulary is learning the process of word formation in the target language. This research aims at investigating and exploring one of the productive word-formation processes in the English language which is conversion or zero-derivation in which the grammatical category of a word is changed without adding any affixes. For instance, every day, I walk(V) to the park near my house, or, every day, I take a walk(N) with my dog. The results will have several pedagogical implications for researchers, teachers, and learners. Based on the presented data in the current study, it can be concluded that zero-morph can be considered one of the productive word-formation processes, and pedagogical implications are discussed in the discussion section.
The Correlation between Task Commitment and Students’ EFL Learning Achievement

This research aims to prove whether there is a correlation between task commitment and students’ EFL Learning achievement on reading comprehension of the second-semester students of the Indonesian Language and Literature Education Study Program. This study used eleven questionnaire items of task commitment and learning achievement tests on giving and responding opinions. The sample of this research was 30 out of 165 students. Based on the calculation results using rser correlation, the correlation value of this study was 0.129. The correlation value was very low (almost uncorrelated) according to the interpretation table of the r value. A conclusion can be drawn that the task commitment, as one of the students’ internal factors, did not affect the students’ learning achievement.
A Method for Image Steganography based on NICE Model

We present a method for Image Steganography. Our method redesign and trains a NICE (Non-linear Independent Component Estimation) model on an image dataset. Then we can obtain a bijective function of dataset image distribution to simple data distribution via the model. Using this module, we can simply synthesize stego images from secret information, and the stego images can also perform lossless message extraction in the reverse direction. Unlike traditional methods, our method is more secure and has a large embedding capacity. Experiments show the feasibility of our method. The security and embedding capacity of the method are analyzed.
HE-SNE: Heterogeneous Event Sequence-based Streaming Network Embedding for Dynamic Behaviors

Large amounts of user behavior data provide opportunities for user behavior modeling and have great potential in many downstream applications such as advertising and anomaly detection. Compared with traditional methods, embedding-based methods are used more often recently because of their efficiency and scalability. These methods build a “behavior-entity” bipartite graph and learn static embeddings for nodes in the graph. However, behavior patterns in the real world could not be static because entity properties such as user interests usually evolve along with time. In this paper, we formulate user behaviors as a temporal event sequence and propose a stream network embedding approach to capture the evolving nature of user behaviors. Representation of each event is built and used to update the embeddings of nodes. Two contextual behavior modeling tasks are studied for dynamic user behaviors, and experimental results with real-world data demonstrate the effectiveness of our proposed approach over several competitive baselines.
DESIGN OF LEARNING TASKS IN HISTORY DEVELOPING PERSONAL RESULTS WITHIN THE FRAMEWORK OF UPDATED FSES

The issue of achieving the results of mastering the basic educational programs is of particular relevance in the context of the practical implementation of the updated Federal State Educational Standards in the primary school. The article deals with learning tasks in history that form a group of personal results in different types of lessons in grades 6–10. The training tasks proposed by us cover all spheres of the development of personal results (patriotic education, civic education, spiritual and moral sphere, understanding of the value of scientific knowledge, aesthetic education, formation of a value attitude to life and health, labour and environmental education, adaptation to the changing conditions of social and natural environment) named in the Exemplary Work Program on History, have a variety of forms, and in some cases are directly related to the local history of Transbaikalia and the Pskov land. The article notes the significant educational potential of the discipline “History” for the formation of the internal position of students. Being in-cluded in a variety of activities in history lessons, students gain experience in exploring life meanings, understanding values, orientation in moral standards, which means they can develop their own existential attitude towards the world around them (nature, society) and themselves.
Creation of students' self-assessment forms using information technologies

This paper introduces a complex software solution developed to support self-assessment of students at primary and high schools. Different templates are created using an application, which allows generating any kind of self-assessment form. Then, the templates are used in a web application, which offers a simple graphical user interface for practical usage of the forms. Hereby, we explain the process of software development and discuss its basic functionalities.
The Phonological Influences on Non-Native Phonetic Change

Introduction: Studies of cross-language perception at the segmental level generally find that adults have great difficulty understanding the contrast of non-native consonants and/or vowels. Non-original phonotactics are often generated by type accuracy and error. Purpose: This article examines the effect of phonology on non-native phonetic changes. Methods: This research is a qualitative research with a literature review study method from the latest research. The collected data were analyzed by in-depth analysis. Results: Based on the results of data analysis, it shows that non-native speakers are not as accurate in the production of different illegal sequences. These findings also imply that linguistic experiences with native tones need not facilitate non-native phonetic changes. However, non-native phonetics change if there is habituation and construction in the right way. Conclusion: It can be concluded that non-native English still has problems in proper English articulation. Given the importance of phonetic accuracy in expressing spoken messages, foreign speakers must pay close attention to this matter and fix it by encouraging, involving and involving them every time to practice.
Peningkatan Hasil Belajar Siswa Melalui Metode Pembelajaran Student Facilitator And Explaining Pada Siswa Kelas VIIA SMP Negeri 4 Barebbo Kecamatan Barebbo Kabupaten Bone

Abstrack. The main problem in this study is how to apply the Student Facilitator And Explaining learning method to improve learning outcomes for opportunities in class VIIa of SMP Negeri 4 Barebbo, Barebbo District, Bone Regency. This study aims to improve learning outcomes with the Student Facilitator And Explaining learning method in class VIIa of SMP Negeri 4 Barebbo, Barebbo District, Bone Regency. The research procedure includes planning, implementing actions, observing and reflecting. The subjects in this study were 18th grade students of SMP Negeri 4 Barebbo, Barebbo, Bone Regency, consisting of 6 boys and 12 girls. The results showed that in the first cycle the average value obtained was 66.38 while in the second cycle the average value obtained was 81.3. Changes in attitudes, attendance, activity, self-confidence and seriousness of students participating in teaching and learning activities also showed an increase. This can be seen from the results of observations during the learning process. Based on the results of the research above, it can be concluded that the learning outcomes of Class VIIa students of SMP Negeri 4 Barebbo, Barebbo District, Bone Regency through the application of the Student Facilitator And Explaining learning method have increased.
Decision Support System untuk Menentukan Lokasi Cabang Baru Muhri Fashion Menggunakan Penggabungan TOPSIS dan SAW

Business is a commercial field of business that is in great demand. One of them is a business in the field of fashion or fashion. Fashion or fashion is something that is in demand by the wider community with an attraction to the way, pattern, and even decoration in the form of clothing, levis, trousers, and other fashions. The owner of the Haji Muhri shop is one of the people who are interested in doing business in the fashion world. The shop owner will set up a new store branch in the East Kotawaringin area, Central Kalimantan. The researcher offers owners to use a combination of the Simple Additive Weighting (SAW) method and the Technique For Order Preference By Similarity To Ideal Solution (TOPSIS), as a decision support system. Decision support system is a system that has the ability to perform an analysis of the decision-making model. Decision support system (DSS) is also a system with alternative processes that have a specific purpose, meaning that this system can be used in situations that are even very rare. The combination of methods between SAW and TOPSIS serves to produce an optimal decision based on alternatives and predetermined criteria. This study uses 7 locations as alternatives and 9 criteria. In this study, the alternative locations chosen were Mentawa Baru Hulu, Mentawa Baru Hilir, Ketapang, Sawahan, Baamang Hulu, Baamang Tengah, and Baamang Hilir, which resulted in Mentawa Baru Hilir with a value of 0.751 or 75.1% as the highest value from the location. other calculations that have been made to be the best alternative for the location of the new branch of the Haji Muhri Fashion Store
DIGITALIZATION OF EDUCATION IN THE PANDEMIC CONDITIONS (GERMAN EXPERIENCE)

The article examines the features of digitalization of education in Germany during the coronavirus pandemic, as well as the questions that will be answered by education specialists, teachers, parents and students themselves in the post-AIDS period.
DEVELOPMENT OF METACOGNITIVE ABILITIES OF FUTURE TEACHERS IN THE PROCESS OF GUIDING RESEARCH ACTIVITIES OF YOUNGER STUDENTS

The article contains a description of the process of development of metacognitive abilities of future teachers in the process of managing the research activities of younger students. The purpose of the study is to empirically test the effectiveness of a set of methodological techniques used by university teachers in the classroom according to the method of managing the teaching and research activities of younger students by future elementary school teachers
Improvement and Application of Discrete State Transition Algorithm

Discrete state transition algorithm relies on the initial solution and can easily fall into the local optimum. This paper proposes an improved discrete state transition algorithm (CDSTA) for the above problem. Firstly, the genetic algorithm is used to initialize to obtain the initial solution with high quality and quickly approximate the optimal value. Secondly, the optimal recovery strategy reduces the number of iterations to accelerate the algorithm's convergence rate. Finally, the chaotic perturbation strategy is introduced. When the algorithm falls into the stagnation state, a chaotic sequence is generated by Tent mapping to get rid of the local extremum. Two single-peaked and three multi-peaked functions are used to experiment with the improved algorithm, and the performance is compared and analyzed with other algorithms. The results show that the improved algorithm's solution accuracy and convergence rate are better than other comparative algorithms. The application of the improved algorithm to the traveling salesman problem demon-strates that CDSTA has good practical engineering application potential.