Reviewerly/exHarmony huggingface dataset:
KOMPARASI MODEL JIGSAW DENGAN TWO STAY TWO STRAY TERHADAP HASIL BELAJAR

This study aims to determine the differences in the Jigsaw type cooperative learning model with the Two Stay Two Stray type on the learning outcomes of the XI Grade Automatic Control System Expertise in the Engineering and Air Conditioning Technique Program at SMK Negeri 3 Pariaman. This type of research is an experiment in the form of Time Series Design that is used in class XI TPTU A with two learning models namely, Jigsaw model and Two Stay Two Stray model. The results showed the average value of the Jigsaw model was 81.67 and the average value of the Two Stay Two Stray model was 76.46. Obtained t test results with significance 0.05 which obtained tcount&gt; t table (3,568&gt; 2,013) which means that Ho is rejected and Ha is accepted. Then it can be concluded that there is a difference between the Jigsaw type cooperative learning model with the Two Stay Two Stray type on the learning outcomes of the XI Grade Automatic Control System Expertise in the Engineering and Air Conditioning Technique Program at SMK Negeri 3 Pariaman. Keywords: Comparison, Jigsaw, Two Stay Two Stray, Learning Outcomes
Hierarchical Freespace Planning for Navigation in Unfamiliar Worlds

Autonomous navigation in a large, complex space requires a spatial model, but the construction of a detailed map is costly. This paper demonstrates how two kinds of exploration support an alternative to metric mapping, one that facilitates robust hierarchical path planning. High-level exploration builds a global spatial model whose connectivity supports an effective, efficient, freespace planner, while low-level, target-driven exploration addresses areas where the global model lacks knowledge. Empirical results demonstrate successful and efficient travel in three challenging worlds.
ORGANIZATION AND METHODS OF RESEARCH AND EXPERIMENTAL WORK ON TRAINING OF PRIMARY SCHOOL TEACHERS IN PEDAGOGICAL COLLEAGUES FOR INTEGRATED TEACHING OF STUDENTS

The article reveals the peculiarities of the organization and methods of research and experimental work on the preparation of primary school teachers in pedagogical colleges for integrated student learning. The purpose of the article is to describe the general methodology of the pedagogical experiment and present the generalized results of experimental work. Achieving the goal involved the use of the following methods: empirical – observation, questionnaires, testing, interviews, the method of expert assessment to determine the state of readiness of future primary school teachers for integrated learning of students; pedagogical experiment to test the effectiveness of the implementation of pedagogical conditions and models of the studied process. Diagnosis of the readiness of future primary school teachers for integrated learning of students involved conducting research and experimental research in several stages: ascertaining, formative, control. To assess the levels of readiness of future primary school teachers for integrated learning, a system of criteria and indicators has been developed taking into account the structure of students’ preparing for professional activity and its result: in the context of our study − readiness of college students − future primary school teachers for integrated learning. The use of a set of methods and techniques of diagnosis allowed to determine the initial level of readiness of future primary school teachers for integrated student learning; to confirm the effectiveness of the implementation of the developed model and pedagogical conditions for the preparing of primary school teachers in pedagogical colleges for integrated student learning. The obtained results of the pedagogical experiment made it possible to develop methodological recommendations for teachers of pedagogical colleges on the introduction of pedagogical conditions and models of training future primary school teachers in pedagogical colleges for integrated student learning.
Isolation Graph Kernel

A recent Wasserstein Weisfeiler-Lehman (WWL) Graph Kernel has a distinctive feature: Representing the distribution of Weisfeiler-Lehman (WL)-embedded node vectors of a graph in a histogram that enables a dissimilarity measurement of two graphs using Wasserstein distance. It has been shown to produce better classification accuracy than other graph kernels which do not employ such distribution and Wasserstein distance. This paper introduces an alternative called Isolation Graph Kernel (IGK) that measures the similarity between two attributed graphs. IGK is unique in two aspects among existing graph kernels. First, it is the first graph kernel which employs a distributional kernel in the framework of kernel mean embedding. This avoids the need to use the computationally expensive Wasserstein distance.Second, it is the first graph kernel that incorporates the distribution of attributed nodes (ignoring the edges) in a dataset of graphs. We reveal that this distributional information, extracted in the form of a feature map of Isolation Kernel, is crucial in building an efficient and effective graph kernel. We show that IGK is better than WWL in terms of classification accuracy, and it runs orders of magnitude faster in large datasets when used in the context of SVM classification.
Evaluation of Automated Image Descriptions for Visually Impaired Students

Illustrations are widely used in education, and sometimes, alternatives are not available for visually impaired students. Therefore, those students would benefit greatly from an automatic illustration description system, but only if those descriptions were complete, correct, and easily understandable using a screenreader. In this paper, we report on a study for the assessment of automated image descriptions. We interviewed experts to establish evaluation criteria, which we then used to create an evaluation questionnaire for sighted non-expert raters, and description templates. We used this questionnaire to evaluate the quality of descriptions which could be generated with a template-based automatic image describer. We present evidence that these templates have the potential to generate useful descriptions, and that the questionnaire identifies problems with description templates.
A Smart Monitoring Berbasis Internet of Things (IoT) Suhu dan Kelembaban pada Kandang Ayam Broiler

This study aims to design and build Internet of Things-based smart monitoring of temperature and humidity in broiler chicken coops in Talang Kemiling Pagar Alam that can facilitate and help breeders. This research is monitoring temperature and humidity which still uses the farmer's body itself as a temperature and humidity sensing tool, so that farmers do not know what the actual temperature and humidity are in the chicken coop. Therefore it is necessary to make a tool that can monitor temperature and humidity conditions in broiler chicken coops by utilizing the existing internet network using temperature and humidity sensors, namely DHT11, 1 channel relay for lamp control, and NODEMCU ESP8266 as a microcontroller that processes and transmits data from sensors. to the telegram server via the internet network, the telegram application on an android smartphone is used as an interface for monitoring temperature and humidity in broiler chicken coops remotely. This research uses the Rapid Application Development (RAD) system development method. The stages taken are Requirement Planning, Design Workshop, Build The System and Implementation. To obtain data in this study, researchers conducted data collection techniques including observation, interviews and literature study. The results expected from this study are the tools produced can help and facilitate breeders in raising broiler chickens.
Passive learning of Timed Automata from logs (Student Abstract)

We propose a novel algorithm to passively learn deterministic Timed Automata from events sequences associated with the delay occurring between them. This algorithm produces models that are more specific than State-of-the-Art algorithms and that has a better identification of the temporal constraints applying on the systems.
Generalized Planning as Heuristic Search

Although heuristic search is one of the most successful approaches to classical planning, this planning paradigm does not apply straightforwardly to Generalized Planning (GP). Planning as heuristic search traditionally addresses the computation of sequential plans by searching in a grounded state-space. On the other hand, GP aims at computing algorithm-like plans that can branch and loop, and that generalize to a (possibly infinite) set of planning instances. This paper adapts the {\em planning as heuristic search} paradigm to the particularities of GP and presents the first native heuristic search approach to GP. First, the paper defines a novel GP solution space that is independent of the number of planning instances in a GP problem, and the size of these instances. Second, the paper defines several evaluation and heuristic functions, that do not require grounding, for guiding a combinatorial search in the GP solution space, making it possible to handle state variables with large numerical domains (e.g. integers). Lastly, the paper defines an algorithm for GP called Best-First Generalized Planning (BFGP), that implements a best-first search in the solution space guided by our evaluation/heuristic functions.
Main elements modeling of the educational process in the conditions of digitalization

The article deals with the issues of improving the efficiency of the educational process in higher education institutions by introducing it into the educational process. The formation of the digital economy is a global trend that dates back to the late 90s of the twentieth century, when for the first time global communication networks formed the market for digital products and services. From chain stores, contactless payment systems and remote communication, the world has moved to virtual reality and the digital sector of the economy in the context of digitalization, it is the basis for subsequent decisions. The resulting concept should be gradually implemented in various types of management of an educational organization with the widest possible use of IT services. The emerging multi-user environment involves the interaction of participants in the educational process: system administrators, teachers, students, involved persons (consultants) in a single network with an accessible interface. The network nature of the organization makes it possible to ensure the self-improvement of the proposed system and bring it to the level of artificial evolution, which will avoid the need for constant modernization and the inevitable delays and errors associated with the adoption and debugging of the upgraded system. The evolutionary scenario allows to improve the system in the process of its operation without the need to change the generations of services, retrain employees, making do with minimal support and maintenance. The effectiveness of the proposed system is ensured by the modern educational motto of digital development “improvement at work”.
Probing the nature of an island constraint with a parsed corpus: A case study on the Coordinate Structure Constraint in Japanese

This paper presents a case study of the use of the NINJAL Parsed Corpus of Modern Japanese (NPCMJ) for syntactic research. NPCMJ is the first phrase structure-based treebank for Japanese that is specifically designed for application in linguistic (in addition to NLP) research. After discussing some basic methodological issues pertaining to the use of treebanks for theoretical linguistics research, we introduce our case study on the status of the Coordinate Structure Constraint (CSC) in Japanese, showing that NPCMJ enables us to easily retrieve examples that support one of the key claims of Kubota and Lee (2015): that the CSC should be viewed as a pragmatic, rather than a syntactic constraint. The corpus-based study we conducted moreover revealed a previously unnoticed tendency that was highly relevant for further clarifying the principles governing the empirical data in question. We conclude the paper by briefly discussing some further methodological issues brought up by our case study pertaining to the relationship between linguistic research and corpus development.
A Study of Social Learning for 8th – grade Students on Studying English at SMP Muhammadiyah 12 GKB

Social learning is an essential learning as a part of activities to change the behavior through public action. This study investigates a study of social learning for 8th grade on studying English at SMP Muhammadiyah 12 GKB. To guide students learning, the teacher serves the activity through modelling so that teacher must have known the students’ need before going to the class. It includes observational learning for the students in which affected their attention process, retention process, motor reproduction process, and also reinforcement process. It adopted theory of bandura toward social learning. The subject research is 32 students at 8th&#x0D; grade, it uses descriptive qualitative research during the observation and interview. The result of study described the transcript of conversation that involved in the classroom activity. Therefore this study aims to show social learning for 8th grade students on studying English at SMP Muhammadiyah 12 GKB
Development of Interactive Multimedia Using Powerpoint Applications Combined With Ispring Suite Application

This study aims to develop interactive multimedia learning based on android using the combined PowerPoint application with the iSpring Suite application in financial accounting for class XI SMKN 1 Tembilahan.This type of research is development research with the ADDIE model.The test subjects were all students of class XI AK 1 SMKN 1 Tembilahan totaling 32 people.Types of data consist of primary data and secondary data.Data collection instruments using observation and questionnaires.Data analysis techniques used validation analysis by material experts and media experts and practicality by students.The results of the study state that the feasibility of android-based multimedia with financial accounting subjects, bank reconciliation material based on material expert judgment, gets a validity level of 80%, valid category.The feasibility of Android-based multimedia with financial accounting subjects and bank reconciliation material based on the media expert's assessment received a validity level of 84%, very valid category.Based on this assessment, Android-based multimedia is valid for use as learning multimedia for class XI AK 1 SMKN 1 Tembilahan.The feasibility of Android-based learning multimedia gets a practicality level of 82%, the category is very practical to use.Based on the results of this study, it is suggested that schools and teachers can take advantage of this multimedia as online learning during the corona virus pandemic.
RANCANG BANGUN MEDIA PEMBELAJARAN INTERAKTIF BERBASIS MACROMEDIA PADA MATA PELAJARAN SIMULASI DIGITAL

Digital Simulation is a basic subject of expertise in curricula in 2013. This Digital Simulation Learning is more directed at the activities of knowledge and skills for all students to shape their creativity by networking information with other parties who function to improve their knowledge and skills. In this research discusses the design of interactive learning media based on Macromedia on digital simulation subjects at 1 Baktiya Vocational School. In this design use the classic tutorial model. The software used to create media is Macromedia Adobe Director 11.5 and other supporting applications. The existence of pretest in the media as a measure of students' knowledge of the material being studied. Based on the results of the validity test the media obtained an average score of 0.83 so that the media is worthy of use. It is hoped that this media can become an example for designing interactive media, so that students are motivated while learning, and the achievement of learning objectives. Keywords: Designer, Interactive Learning Media, Adobe Director.
THE IMPLEMENTATION OF WEEKLY QUIZZES ON STUDENTS’ GRAMMAR ACHIEVMENT IN MAN 1 MAKASSAR

Based on the research findings and discussion in the previous chapter, it can be concluded that the use of weekly quizzes improves the grammar achievement of the eleventh year students of MAN 1 Makassar in academic year 2017/2018. It can beseen from the significant difference score between pretest and posttest after giving the treatment.
RELEVANCE IMPROVEMENT METHODS OF TEACHING EDUCATIONAL PROGRAMS THROUGH VIRTUAL TECHNOLOGIES

Informatization of the system of science and education is becoming relevant today. Virtual technologies expand the scope of computer technologies in General and make a great contribution to the development of science and education.This field is studied by Kazakh and many foreign scientists. The article reflects the relevance of improving the teaching methods of the educational program through virtual technologies in the training of computer science teachers. The relationship between modern systems and virtual technologies used in education is determined. Methods of teaching the educational program,forms of their representation and virtual technologies used in the virtualization of the educational environment, as well as tools necessary for the organization of teaching methods of the educational program are proposed. The advantages of teaching educational programs in a virtual educational environment using virtual technologies and the new role of the teacher in a virtual educational environment are described. The advantages of training in educational programs in a virtual educational environment through virtual technologies are presented.
Do It Once: An Embarrassingly Simple Joint Matching Approach to Response Selection

Existing matching models for response selection adopt the independent matching (IM) approach.To complete a prediction, they have to perform N independent matches, where N is the number of response options.In this paper, we explore a joint matching (JM) approach which performs matching only once regardless of the number of options.The JM approach does not change the structure of matching component but only modifies its input and output format.It also enables a cheap but effective data augmentation method.Extensive experiments on the MuTual dataset demonstrate that, even with the simplest formulation, JM outperforms IM approach by a large margin and reduces training time by over half.
MIXED PROBABILITY MODELS FOR ALEATORIC UNCERTAINTY ESTIMATION IN THE CONTEXT OF DENSE STEREO MATCHING

Abstract. The ability to identify erroneous depth estimates is of fundamental interest. Information regarding the aleatoric uncertainty of depth estimates can be, for example, used to support the process of depth reconstruction itself. Consequently, various methods for the estimation of aleatoric uncertainty in the context of dense stereo matching have been presented in recent years, with deep learning-based approaches being particularly popular. Among these deep learning-based methods, probabilistic strategies are increasingly attracting interest, because the estimated uncertainty can be quantified in pixels or in metric units due to the consideration of real error distributions. However, existing probabilistic methods usually assume a unimodal distribution to describe the error distribution while simply neglecting cases in real-world scenarios that could violate this assumption. To overcome this limitation, we propose two novel mixed probability models consisting of Laplacian and Uniform distributions for the task of aleatoric uncertainty estimation. In this way, we explicitly address commonly challenging regions in the context of dense stereo matching and outlier measurements, respectively. To allow a fair comparison, we adapt a common neural network architecture to investigate the effects of the different uncertainty models. In an extensive evaluation using two datasets and two common dense stereo matching methods, the proposed methods demonstrate state-of-the-art accuracy.
THEORETICAL-METHODOLOGICAL ANALYSIS OF THE PROBLEM OF THINKING IN PSYCHOLOGICAL SCIENCE

The theoretical and methodological analysis of the problem of thinking in psychological science is proposed.The classification of thinking forms and their subspecies is presented.The theoretical analysis of well-known scientists concerning the characteristics of the thinking essence and functions of the cerebral hemispheres in the framework of information processing is presented.The scheme of anatomical and psychophysiological system of thinking is offered.Understanding is revealed as a result of human thinking, as a complex analytical and synthetic activity of the brain, aimed at revealing the inner essence of objects, processes and representations of objective, surrounding reality.Consideration of forms of thinking and their varieties, especially conclusions, characterized in the presentation of information and communication technologies in the educational process of preschool institutions, which was noted in the prospects for further research.
Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning

Model-based reinforcement learning (RL) is more sample efficient than model-free RL by using imaginary trajectories generated by the learned dynamics model. When the model is inaccurate or biased, imaginary trajectories may be deleterious for training the action-value and policy functions. To alleviate such problem, this paper proposes to adaptively reweight the imaginary transitions, so as to reduce the negative effects of poorly generated trajectories. More specifically, we evaluate the effect of an imaginary transition by calculating the change of the loss computed on the real samples when we use the transition to train the action-value and policy functions. Based on this evaluation criterion, we construct the idea of reweighting each imaginary transition by a well-designed meta-gradient algorithm. Extensive experimental results demonstrate that our method outperforms state-of-the-art model-based and model-free RL algorithms on multiple tasks. Visualization of our changing weights further validates the necessity of utilizing reweight scheme.
Accuracy Analysis of Predictive Value in Transaction Data of Service Company Using Combination of K-Means Clustering and Time Series Methods

Profit decline is a frightening problem for service companies. The solution to prevent this is by analyzing data transactions using data mining and forecasting. K-Means used to cluster the level of car damage based on the number of panels repaired and the duration of repaired. The results of K-Means used as material for analysis the best time-series method for transaction data. The methods analyzed include the moving average, single exponential smoothing, double exponential smoothing, and winter's method. Single exponential smoothing is the most suitable forecasting method with transaction data. Based on the MAPE value obtained for minor damage of 12.58%, forecasting for moderate damage of 16.83%, forecasting for major damage of 17.31%, and forecasting for overall data of 8.0975%. It concluded that single exponential smoothing can apply with K-Means clustering and the company can use it to make strategies to prepare the number of workers and production materials required.