Reviewerly/exHarmony huggingface dataset:
Peningkatan Kompetensi Guru dalam Menyusun Rencana Pelaksanaan Pembelajaran Kurikulum 2013 Melalui Pendampingan di Gugus Sirih Gading UPT Dinas Pendidikan Pemuda dan Olahraga Kecamatan Kandangan

The results of kindergarten teacher supervision were found in teaching teachers not yet making plans for daily activities, so learning activities did not run effectively. For this reason, action guidance is needed for the teacher to increase his competence in preparing the daily activity plan. The purpose of this study was to determine the improvement of kindergarten teacher competencies in preparing daily activities plans through ongoing guidance through mentoring in the Sirih Gading Cluster UPT Department of Youth and Sports Education Kandangan District Academic Year 2017/2018. The subjects of this study were all kindergarten teachers in the Sirih Gading UPT Cluster of the Department of Education, Youth and Sports, Kandangan District, totaling 18 teachers. With this school action research, it is expected that 75% of kindergarten teachers are able to plan their daily activities properly. The action is carried out with two cycles each cycle there are three meetings consisting of four stages, namely: planning, implementation, observation and reflection. The results of the action from cycle I to cycle II increased aspects of the competence of kindergarten teachers in preparing daily activities properly and correctly in the Sirih Gading Cluster UPT Department of Youth and Sports Education in Kandangan District 2018 in cycle I there were 6 teachers or 33% increased to 15 teachers or 85%. While its activity increased from 65% in the first cycle to 90% in the second cycle. Thus it can be concluded that through mentoring can improve the competence of kindergarten teachers in preparing daily activities plans in the Sirih Gading Cluster UPT Department of Youth and Sports Education in Kandangan District. Based on the research findings, suggestions can be made so that: (1) Teachers before carrying out learning to plan their daily activities properly and correctly, so that teaching and learning activities take place smoothly, effectively and efficiently and learning objectives are achieved. (2) Kindergarten Supervisors are advised to carry out ongoing guidance in preparing daily activity plans, so that Kindergarten teachers are able to prepare plans for day activities properly and correctly and Kindergarten Supervisors are advised to conduct further research on the skills of Kindergarten teachers in carrying out learning to find other aspects that are not yet revealed.
Task-agnostic Temporally Consistent Facial Video Editing

Recent research has witnessed the advances in facial image editing tasks. For video editing, however, previous methods either simply apply transformations frame by frame or utilize multiple frames in a concatenated or iterative fashion, which leads to noticeable visual flickers. In addition, these methods are confined to dealing with one specific task at a time without any extensibility. In this paper, we propose a task-agnostic temporally consistent facial video editing framework. Based on a 3D reconstruction model, our framework is designed to handle several editing tasks in a more unified and disentangled manner. The core design includes a dynamic training sample selection mechanism and a novel 3D temporal loss constraint that fully exploits both image and video datasets and enforces temporal consistency. Compared with the state-of-the-art facial image editing methods, our framework generates video portraits that are more photo-realistic and temporally smooth.
COMBINATION OF WATER SAVING TECHNOLOGYAND ORGANIC FERTILIZER FOR CH4 MITIGATIONIN RICE PADDY CULTIVATION

Climate change as one of the global warming impacts is a phenomenon of the increasingtemperature of the earth that takes place globally from year to year. Global warming occurs as the result of thegreenhouse effect, the increased emissions of gases such as carbon dioxide (CO2), methane (CH4), nitrous oxide(N2O), and chlorofluorocarbons (CFC) that trap the solar energy in the earth atmosphere. Paddy rice cultivationis the biggest contributor to CH4 gas emissions produced through anaerobic decomposition of organic materialin the flooded irrigation system and through nitrous oxide gas generated from the volatilization of nitrogen as aresult of intensive administration of inorganic fertilizers. This paper deals with irrigation technology, paddyfield cultivation, and emissions. The study used a Randomized Block Design as the environmental design andsplit-plot as the treatment design. The main plot was Water-saving Technology (A) consisting of three levels,which were Surface (Flooded) Irrigation of 5cm (A1), Intermittent Irrigation (A2), and Saturated WaterConditions (A3). The subplot was a dosage of an organic fertilizer made from local raw material, fermentedwater hyacinth (bokashi) (P) consisting of 3 levels, which were 800 kg/ha (P1), 1,000 kg/ha (P2), and 1,200kg/ha (P3). The results showed that the highest CH4 emissions were obtained from the flooded irrigationtreatment combined with organic fertilization of 1,200 kg/ha. There were no differences in terms of productionin all treatment combinations. The differences in production only occurred in the average treatment of irrigation,in which the highest production occurred in the flooded irrigation treatment.
Different Levitation Systems Observed in Big Basin UFOs, EMEC and Anti Maxwell Effect and Free Energy.

In Quantum FFF Theory, there are different levitation systems possible observed in Big Basin UFOs. Two systems (1,2) are assumed to use a new physics magnetic field effect called “Anti Maxwell Dip” effect dependent of the conductor diameter around each current in a wire without an equal reaction force. According to Quantum FFF Theory. The third system (EMEC) is a new physics centrifugal effect based on Electron Muon conversion in a torus shape, also without reaction force. (3) 1e, The Dual different diameter electric conductor based solenoidal or Dual Diameter Solenoidal Effect (DDSE) B=0 effect and Lorentz levitation effect. 2e, The Triple Different Diameter Electric wire Lorentz levitation effect. (TDDE) 3e, The EMEC : Electron- Muon-Electron Conversion centrifugal effect.
NP Reasoning in the Monotone $$\mu $$-Calculus

Satisfiability checking for monotone modal logic is known to be (only) NP-complete. We show that this remains true when the logic is extended with alternation-free fixpoint operators as well as the universal modality; the resulting logic – the alternation-free monotone $$\mu $$ -calculus with the universal modality – contains both concurrent propositional dynamic logic (CPDL) and the alternation-free fragment of game logic as fragments. We obtain our result from a characterization of satisfiability by means of Büchi games with polynomially many Eloise nodes.
Recent Developments in Monster-Oriented Semantics

In his “Demonstratives”, David Kaplan discussed certain nonintensional operators called monsters. The operators, unlike ordinary ones, change the reference of indexicals by shifting the parameter of context. Although Kaplan denied monsters at least in English on the ground of both the doctrine of direct reference and the principle of compositionality, many monstrous phenomena of singular terms have been confirmed by some semanticists lately, which seems to urge Kaplanian semantics to be revised. In this survey article, we offer a survey of recent developments in the semantics of indexicals, variables, and proper names by focusing on monsters, and give some suggestions about direct reference, monsters, and compositionality.
Interference-based universal decoupling and swapping for multimode bosonic systems

Beam-splitter operations are widely used to process information encoded in bosonic modes. In hybrid quantum systems, however, it might be challenging to implement a reliable beam-splitter operation between two distinct bosonic modes. Without beam-splitters, some basic operations such as decoupling modes and swapping states between modes can become highly non-trivial or not feasible at all. In this work, we develop novel interference-based protocols for decoupling and swapping selected modes of a multimode bosonic system without requiring beam-splitters. Specifically, for a given generic coupler characterized by a Gaussian unitary process, we show how to decouple a single mode or swap any pair of modes with a constant depth sequence of operations, while maintaining the coupling for the remaining system. These protocols require only multiple uses of the given coupler, interleaved with single-mode Gaussian unitary operations, and thus enable efficient construction of operations crucial to quantum information science, such as high-fidelity quantum transduction. Our results are directly derived from fundamental physical properties of bosonic systems and are therefore broadly applicable to various existing platforms.
Reading Education for the Improvement of Middle School Students' Reading Proficiency

This study aims to study the ways to improve reading skills of middle school students through suitable reading education. Modern society is information age, in which knowledge and information are overflowing. It is a society that requires the ability to select proper information and utilize it. Although various information is obtained through various media through the spread of computers and the development of the Internet through industrialization, reading ability is the fundamental ability for selecting and utilizing this information. As a result, this study focuses on reading education in order to improve the reading skills of middle school students. Reading ability refers to the ability to read and understand various passages and reading education can play an important role in improving reading ability. This paper presents a plan for making reading everyday habit through the method of reading education tailored to the interests and right level of middle school students. It also suggests a plan for proper reading education for improving reading ability of them. This research figures out that reading education is essential for middle school students to improve their reading skills. Various methods of reading education contributes developing creative and critical problem-solving skills.
Single Image Brightening via Multi-Scale Exposure Fusion with Hybrid Learning

A small ISO and a small exposure time are usually used to capture an image in the back or low light conditions which results in an image with negligible motion blur and small noise but look dark. In this paper, a single image brightening algorithm is introduced to brighten such an image. The proposed algorithm includes a unique hybrid learning framework to generate two virtual images with large exposure times. The virtual images are first generated via intensity mapping functions (IMFs) which are computed using camera response functions (CRFs) and this is a model-driven approach. Both the virtual images are then enhanced by using a data-driven approach, i.e. a residual convolutional neural network to approach the ground truth images. The model-driven approach and the data-driven one compensate each other in the proposed hybrid learning framework. The final brightened image is obtained by fusing the original image and two virtual images via a multi-scale exposure fusion algorithm with properly defined weights. Experimental results show that the proposed brightening algorithm outperforms existing algorithms in terms of the MEF-SSIM metric.
Muir, John Clark - Biographical entry - Index to the AMA archive

Muir, John Clark - Biographical entry - Index to the AMA archive - NAME is a biographical, bibliographical and archival database of SUBJECT with links to related articles and images. ADD MORE DESCRIPTION AS REQUIRED
A dimensão cultural da organização do conhecimento

The studies on the cultural dimension of the knowledge organization have been getting a prominent role in scientific communications, revealing their importance in the current academic context. The investigations in epistemic commu-nities can help in the study of this topic in evidence, identifying its main theoreticians and sources of information, in order to help the development of future researches. It was possible to identify a strong theoretical contribution in researchers working in Brazil, as well as prominent research sources in the ISKO context and periodicals such as Scire. As final contributions, it was possible to identify a community that contributes in a profitable way to the area and that can serve as a basis for the construction of new knowledge about the cultural aspects of the knowledge organization.
PrositNG - A Machine Learning Supported Disease Model Generation Software.

Decision models (DM), especially Markov Models, play an essential role in the economic evaluation of new medical interventions. The process of DM generation requires expert knowledge of the medical domain and is a time-consuming task. Therefore, the authors propose a new model generation software PrositNG that is connectable to database systems of real-world routine care data. The structure of the model is derived from the entries in a database system by the help of Machine Learning algorithms. The software was implemented with the programming language Java. Two data sources were successfully utilized to demonstrate the value of PrositNG. However, a good understanding of the local documentation routine and software is paramount to use real-world data for model generation.
Structure Of The Underground Water Monitoring Algorithm Based On Remote Sensing Of The Earth

The article presents the structure of the study of hydrogeological monitoring of groundwater based on remote sensing of the earth. In the article, a groundwater monitoring structure has been developed to study hydrogeological processes based on the modern ERDAS Imagine software environment. The ERDAS Imagine system allows you to directly view and process files of various vector and raster formats, as well as has extensive import and export capabilities for determining groundwater. The effectiveness of groundwater monitoring is to determine the wet layer of a given satellite image area.
Mood System in the Tourism Brochure of “Friendly Lombok”

Mood system can be found in every clause. This research was conducted to investigate the types of mood and their speech functions in the tourism brochure of “Friendly Lombok”. Qualitative descriptive research design was employed in conducting this research. The findings show that the mood system found in the tourism brochure of “Friendly Lombok” are declarative mood, interrogative mood, and imperative mood. In the brochure, the information and encouragement given by the author is delivered to the readers through the declarative mood.  The interrogative mood functions to demand questions and attract the readers’ attention.  The author’s authority to command and persuade the readers to take an action are expressed through the imperative mood. Based on the analysis, the declarative mood is the most common mood in the tourism brochure of “Friendly Lombok”.  It shows that the author of the brochure tends to state information and encouragement of tourism aspects in Lombok to the readers.
QuantityEr: An extensible and simple solution to obtain the amount of results of complex queries to GitHub

GitHub is a platform that provides hosting for software development version control using Git. It features an application programming interface to allow the software to interact with the platform. The enormous quantity of information Hosted in GitHub may be useful to make studies about the current presence of development tools in the open-source software development community. However, the search engine has restrictions that make it impossible to issue complex queries to the platform. In this report, it is described as an object-oriented and extensible solution, named QuantityEr, to obtain the number of search results of complex queries to GitHub by using the inclusion-exclusion principle. The mathematical definitions, as well as related concepts, are presented. The mathematical model is discussed. The application of general design and used development tools are presented. Also, the results of the execution examples are showed. It is concluded that the treated problem has been solved although more work may be done to improve the solution.
Building up Ontologies with Property Axioms from English Wikipedia

Large-scale ontologies have received much attention in various fields such as information retrieval, data integration, and question answering. However, since it is costly to construct and maintain large-scale ontologies manually, several ontology learning methods fromWikipedia have been proposed. YAGO and DBpedia are famous examples of large-scale ontologies automatically constructed from multilingualWikipedia. However, there is room to extract from Wikipedia many kinds of relationships that are not included in YAGO or DBpedia. Previously, we proposed a method for constructing large-scale ontologies named Japanese Wikipedia Ontology (JWO) from Japanese Wikipedia. Since JWO has been constructed using several methods that are different from the extracting methods of YAGO and DBpedia, it is possible to extract relationships that do not exist in YAGO or DBpedia by using these methods. However, some of the methods are Japanese language-dependent, and cannot be applied directly to English Wikipedia. In this paper, we propose methods for constructing large-scale ontologies named English Wikipedia Ontology (EWO) from English Wikipedia. To achieve this, we have modified the Japanese language-dependent methods of JWO and extended several methods for extracting property axioms. EWO includes Is-a relations (rdfs:subClassOf), classinstance relations (rdf:type), property relations and types, and synonyms (owl:sameAs). The property relations are triples: property domain (rdfs:domain), property range (rdfs:range), and property hypernymy-hyponymy relations (rdfs:subPropertyOf). The property types are object (owl:ObjectProperty), data (owl:DatatypeProperty), symmetric (owl:SymmetricProperty), transitive (owl:TransitiveProperty), functional (owl:FunctionalProperty), inverse functional (owl:InverseFunctionalProperty), asymmetric (owl:AsymmetricProperty), reflexive (owl:ReflexiveProperty) and irreflexive (owl:IrreflexiveProperty). To evaluate EWO, we compared it with existing ontologies constructed from English Wikipedia. Thus, we clarified the differences between the existing ontologies and EWO.
Schematic Method: A Creative Way to Teach Short Stories

This study employs a quasi-experimental design. The samples were 170 students from 3 intact classes, in three different schools and they were taught two short stories. The objectives of the study were to investigate whether the schematic method, the STAD method or the conventional method helps ELS students to improve their mean scores in answering questions related to themes, characterization, literary devises, and settings in the two short stories. The 56 students in Experimental Group 1 from school A were taught using the schematic method, the 57 students in Experimental Group 2 from school B were taught using the STAD method and the 57 students in the Control Group from school C were taught using the conventional method. The study was conducted for 8 weeks and the three groups were taught the same short stories (‘QWERTYUIOP’ and the ‘Fruitcake Special’), specifically in the areas of themes, characterization, use of literary devices and settings. Prior to the intervention, all the three groups were given the pre-test and at the end of the intervention they were given the post-test. The data obtained from the pre-test and post-test were analyzed using the SPSS Program version 24.0. The data was analyzed using one way ANOVA, Post-Hoc Pairwise Comparisons test and the ANCOVA test. The findings indicate that the schematic method helped to enhance students’ mean scores significantly for literary devices and settings compared with the Experimental Group 2 and the Control Group. These findings have crucial pedagogical, practical and theoretical implications.
A New Importance-Performance Analysis by Size-Insensitive Integrity-Based Fuzzy C-Means

In conventional Importance-Performance Analysis, lots of researchers assume that a given set of attributes is spread across four quadrants. The researcher uses the vertical axis and the horizontal axis on the drawing to optimally divide the quadrants. From the perspective of machine learning, a new Importance-Performance Analysis by Size-Insensitive Integrity-based Fuzzy C-Means is proposed. From the empirical results, the new IPA by Size-Insensitive Integrity-based Fuzzy C-Means is plain and simple, successful, and easy to know.
Learning Expectation of Label Distribution for Facial Age and Attractiveness Estimation

Facial attributes (\eg, age and attractiveness) estimation performance has been greatly improved by using convolutional neural networks. However, existing methods have an inconsistency between the training objectives and the evaluation metric, so they may be suboptimal. In addition, these methods always adopt image classification or face recognition models with a large amount of parameters, which carry expensive computation cost and storage overhead. In this paper, we firstly analyze the essential relationship between two state-of-the-art methods (Ranking-CNN and DLDL) and show that the Ranking method is in fact learning label distribution implicitly. This result thus firstly unifies two existing popular state-of-the-art methods into the DLDL framework. Second, in order to alleviate the inconsistency and reduce resource consumption, we design a lightweight network architecture and propose a unified framework which can jointly learn facial attribute distribution and regress attribute value. The effectiveness of our approach has been demonstrated on both facial age and attractiveness estimation tasks. Our method achieves new state-of-the-art results using the single model with 36$\times$ fewer parameters and 3$\times$ faster inference speed on facial age/attractiveness estimation. Moreover, our method can achieve comparable results as the state-of-the-art even though the number of parameters is further reduced to 0.9M (3.8MB disk storage).
Identifying Beneficial Learning Behaviors from Large-Scale Interaction Data

Understanding the effect of learning behavior is fundamental to improving learning outcomes. In this paper, we perform a behavioral analysis based on data from a large high-stakes exam preparation platform. By measuring the importance of a set of candidate learning behaviors in predicting final exam outcomes, we identify a suite of beneficial behaviors. In particular, we find that breadth (wide coverage of content per week) and intensity together with consistency (frequent and equal-length practice for a limited period) are most predictive of final exam success rate, among eleven studied behaviors.
Miller, D - Biographical entry - Index to the AMA archive

Miller, D - Biographical entry - Index to the AMA archive - NAME is a biographical, bibliographical and archival database of SUBJECT with links to related articles and images. ADD MORE DESCRIPTION AS REQUIRED