Reviewerly/exHarmony huggingface dataset:
The forecast of solar activity in the 25th and 26th cycles using Excel 2016

Climate variations have a significant impact on the development of life processes on Earth. The Sun is the main source of energy in the climate system of our planet. Therefore, for climate prediction, it is important to predict variations in solar activity. When forecasting, the analysis of time series allows, assuming that the trend does not change, to show what should happen in the absence of external interventions. Using the database on the change in the average annual values of the Wolf numbers W(t) from 1700, we in Excel 2016 determined the general trend of changes, and from spectral analysis using the Fourier transform were determined fluctuations around the trend with periods of about 11, 22, 50–60 and 100–111 years old. From the analysis of data W(t) for the years 1700–2018 we calculated the forecast for the change in the Wolf numbers for 2019–2045; and from the data about the activity index in 1913-2018 the forecast of solar activity (SA) for 2019–2040 was calculated. Considering the differences in historical trends for the previous, respectively, 318 and 105 years, in both cases, the forecast for the 25th and 26th cycles of the SA showed less intensity at maximums than the same indicators even for the low-active cycle 24. We note that the use for the forecast only the data for the 1900s, having the greatest activity in the last 300 years, give predictive values 10–15% more than when to add to the historical data observations from 1700. Such addition of data on SA for the previous 200 years, when carrying out forecast calculations, lowers the general forecast trend of changes in Wolf numbers for 2019–2040 in the maxima of the 25th and 26th cycles by 10–15%. This conclusion confirms need to use for predictive calculations as long as possible set of observational data, when the length of the series significantly exceeds the forecast period. It is possible to substantiate the conclusion that the next few 11-year CA cycles should be even less intense than the 24th which ends now. That is, in the coming decades, we can expect a decrease in SA to the extent that was observed, for example, at the end of the 17th century. Therefore, it is possible that at the absence of anthropogenic factors, we are waiting for the next minor ice age. And in the coming years, the trend of increasing the average annual temperature may change to the trend of its decrease.
Meningkatkan Self-Esteem Siswa Melalui Model Pembelajaran Learning Cycle 7E Berdasarkan Kemampuan Awal Matematis

This research is a quasi-experimental research. The purpose of the study was to present a picture of the increase in self-esteem of students who obtained the 7E learning cycle learning model compared to students who obtained conventional learning based on student KAM. This research was conducted at a Junior High School in Serang Regency, Banten Province. Data collection techniques in research is through pretest and posttest. Data analysis was performed through a self-esteem scale score with the Mann-Whitney U test. The results showed that the increase in self-esteem of students who obtained the 7E learning cycle learning model was better than that of students who obtained conventional learning models in the medium KAM category. Whereas in the low and high KAM categories there is no difference in the increase in self-esteem of students who get the 7E learning cycle compared to students who get conventional learning.
Determining the Structure of Project Competence of Future Bachelors of Social Work

In the general structure of competence, the components of theoretical knowledge, transformative activity, moral and spiritual values and self-organization are considered, and two marginal levels are distinguished: a higher level of competence and a minimum acceptable level of competence.Taking into account the specific professional activity of future bachelors of social work, the structure of project competence is detailed as follows.In the theoretical knowledge component, the marginal levels differ in the limited knowledge at the minimum permissible level only by the management aspect, and the cross-sectoral understanding of the concepts of "project" and "project management" -at the highest level of competence.The transformative activities for the highest level of competence include methods for substantiating contradictions, to which the project is directed, determining the ideal end result, formulating a realistic project goal, decomposing the project, executing the project, introspection, as well as methods of managing teamwork.For minimal competence, only certain project management methods are foreseen, in particular, excluding teamwork management methods.In the component of moral and spiritual values, it is obligatory for both levels to act on the basis of the value attitude to the client of social work as a subject of self-government.As part of self-organization component, we consider projects developed by students as means of self-organization of their further transformative professional activity, but a higher level of competence (as opposed to minimum competence) involves taking into account the activities of other students and environmental events.
Ticket Payment Information System On The Sea Beach Light Using Simple Additive Weighting Method

&lt;p&gt;The Sea Beach Cahaya is one of the rising beach attractions in Kendal Regency, Central Java. In general, the tourism object of The Sea Pantai Cahaya still does not use many computer systems in their daily lives. As with tourism ticket purchases and also entrance tickets, vehicles that still use ticket paper as proof of payment, it is often disrupted if it is still fussing with the queue conditions and questions by visitors. On the other hand, report data collection is still considered slow.&lt;/p&gt;&lt;p&gt;One way to overcome the above problems is to make a ticket payment system that is computerized using the SAW (Simple Additive Weighting) method, replace paper tickets with a card model and also use the network to shorten report generation.&lt;/p&gt;
The manifestation of higher creative capacities and their psychodiagnostics in children of primary school

The article presents the results of a study of manifestations of higher creative capacities related to the creation of real creative products in a free situation of psychodiagnostics in children of 8-9 years old, in comparison with methods for diagnosing creativity and intelligence, which require strict regulation of respondents’ activity. The data obtained showed the absence of a relationship betweenexpert assessments of the real creative achievements of children and indicators of psychometric creativity and psychometric intelligence.
Using Sentinel-2B Imagery to Estimate the Eutrophication Level of Linh Dam Lake, Hoang Mai District, Hanoi

The successfully launched of Sentinel-2B (S2B) satellite into orbit created the recording frequency on Earth every 5 days with the simulated operating of Sentinel 2A satellite, and provided a high resolution (10m). This study aims to assess the effective application of S2B satellite on water environmental monitoring by using Secchi Disk Depth (SD) and surface water reflectance data, which was collected at the same time of the acquiring local scenes from S2B to establish SD estimated equation of Lake Linh Dam. Result showed that an accurate estimation model for SD in Lake Linh Dam by an exponential function of band 3 versus band 4 ratio (R2 = 0.86, RMSE=1.7). Resultant maps of SD distribution over the lake in 2018 and 2019 show that the water quality in Lake Linh Dam reached from the high eutrophication to super eutrophication level. This result is consistent with previous studies on eutrophication state of Lake Linh Dam, confirming the potential application of S2B image for water quality research in Hanoi lakes.&#x0D;
KENOTOMY, Creativity Face to Face with Artificial Intelligence

Artificial Intelligence wins an increasing capacity for undertaking more efficiently repetitive jobs and routine based tasks, using highly accurate logic-adaptive and deductive algorithms, replacing successfully the humans for these occupations.Facing this new reality the ultimate asset of mankind became the Creative Thinking.Enhancing and fostering the Creative Thinking should be a major duty especially along the educational process. Whatever the domain of study might be, the ability of generating fresh ideas and disruptive concepts will be sooner than expected the winning trump, or even the only reason for employing a human operator.What is Kenotomy?Kenotomy is Creativity focused education, leading students toward a seminal thinking mode, by developing their genuine imagination talent and enabling them with the skills for shifting approaches, encouraging unusual thinking pathways, archetypal perspective and serendipity, facilitating conceptualizing and recognizing the potential of ideas.Kenotomy is based on the integrative understanding of the creative mental processes and uses an adequate methodology for addressing them, triggering the ideation process.Kenotomy builds up creative minds, whatever the major of the students might be.How does Kenotomy work?Kenotomy differentiates two types of Creativity: the Reactive and the Intrinsic one and describes the dedicated ways for initiating them specifically.First of all Kenotomy relieves the acquired and inherent inhibitions, releasing and stimulating the inborn speculative talent and enhances the ideation ability, overcoming the empiric myopia by high abstracting skills and the routine saturation by a fresh apex-perspective. As a project centered education Kenotomy develops individual disruptive thinking as well as the group synergetic resonance with spectacular outcome: original problem solutions and unexpected, seminal concepts.
The study of the frames of Mandelbrot sets of polynomials of the second degree as a means of developing the originality of students' thinking

The article presents a methodology for studying the frames of Mandelbrot sets of polynomials of the second degree of a complex variable, based on the integration of analytical methods, mathematical programming and the use of computer graphics. A connection is established between the frames of the first and second orders of Mandelbrot sets of functions and with the curves – cardioid, lemniscate and circle. Algorithms for constructing the frames of the Mandelbrot sets of the functions under consideration in the MathCad mathematical package are presented. The task is to describe 3-order frames (where) of the Mandelbrot sets of functions and, which correspond to the existence of attracting fixed points of period 3. It is shown that the establishment of associative relations between classes of various mathematical objects (polynomials of a complex variable, curves, Mandelbrot sets) contributes to the development of original thinking and creative potential of students.
Motion-Based Occlusion-Aware Pixel Graph Network for Video Object Segmentation

This paper proposes a dual-channel based Graph Convolutional Network (GCN) for the Video Object Segmentation (VOS) task. The main contribution lies in formulating two pixel graphs based on the raw RGB and optical flow features. Both spatial and temporal features are learned independently, making the network robust to various challenging scenarios in real-world videos. Additionally, a motion orientation-based aggregator scheme efficiently captures long-range dependencies among objects. This not only deals with the complex issue of modelling velocity differences among multiple objects moving in various directions, but also adapts to change of appearance of objects due to pose and scale deformations. Also, an occlusion-aware attention mechanism has been employed to facilitate accurate segmentation under scenarios where multiple objects have temporal discontinuity in their appearance due to occlusion. Performance analysis on DAVIS-2016 and DAVIS-2017 datasets show the effectiveness of our proposed method in foreground segmentation of objects in videos over the existing state-of-the-art techniques. Control experiments using CamVid dataset show the generalising capability of the model for scene segmentation.
PENGARUH PENGGUNAAN APLIKASI SPARCOL VIDEOSRIBE TERHADAP KEMAMPUAN MENYIMAK SISWA

The Effect of Using the Sparcol Videoscribe Application on Students' Listening Abilities. The purpose of this study was to determine the effect of using the Sparcol videosribe application on the ability to listen to Grade VII students of SMP Negeri 1 Baranti, Sidenreng Rappang Regency. This research is a quasi-experimental study with a population of 57 people and using a total sample. The data in this study were collected through documentation and test techniques. Data were analyzed with descriptive statistical techniques namely mean. The results showed that the use of the Sparcol Videoscribe affected of listening ability of Grade VII students SMP Negeri 1 Baranti, Sidenreng Rappang Regency. This can be seen from the average value of the experimental group which is higher than the average value of the control group namely Mx = 83,44&gt; My = 75. Therefore, it is concluded that there is an influence of the use of the Sparcol Videosribe application to the listening ability of Grade VII students SMP Negeri 1 Baranti, Sidenreng Rappang Regency, 2018/2019.
Deep Learning Stereo Matching Algorithm using Siamese Network

Autonomous vehicle has become a very hot topic for researchers in recent years. One of the important sensors used in these vehicles is Stereo Cameras/Vision. Stereo vision systems are used to estimate the depth from the two cameras installed on robots or vehicles. This method can deliver the 3D position of all objects captured in the scene at a lower cost and higher density compared to LIDAR. Recently, neural net-works are vastly investigated and used in image processing problems and deep learning networks which has surpassed traditional computer vision methods specially in object recognition. In this paper, we propose to use a GPU with a new Siamese deep learning method to speed up the stereo matching algorithm. In this work, we use a high end Nvidia DGX workstation to train and test our algorithm and compare the results with normal GPUs and CPUs. Based on numerical evaluation, the Nvidia DGX can train a neural network with higher input image resolution approximately 8 times faster than a normal GPU and 40 times faster than a Core i7 8 Cores CPU. Since it has the ability to train on a higher resolution the network can be trained in more iteration and results in higher accuracy.
Preliminary Study on the Internet Sensation Analysis of New Energy Vehicles Policy

Abstract With the strong support of the government, new energy vehicles are developing rapidly. However, in the information age of networked and comprehensive application of the internet, the internet sensation have a positive or negative impact on the development of the new energy vehicle industry. Quantitative analysis of the internet sensation will help to propose suggestions and the countermeasures to adapt to the development of this industry. This paper applies the LDA topic model, machine learning and volume analysis of SVM classification algorithm to analyse the information obtained from the network information source of the new energy vehicle policy. The results show that government, enterprises and consumers are the main actors in the cultivation of new energy vehicles industry. While the government continues to stimulate the enthusiasm of enterprises for the construction of new energy vehicle infrastructure, it should reduce public concerns about financial subsidies and stimulate consumers. The enthusiasm of buying drives the sustainable development of the market. In order to reduce the deviation of government policy implementation, it is necessary to timely and directly use the internet as an information exchange platform for immediate and convenient communication advantages, to pay attention to and monitor the network public opinion of the new energy vehicle industry, and to reflect on lyric topics such as infrastructure and application promotion, as well as real-time tracking and understanding of the problems reflected in lyric topics such as infrastructure and application promotion, and actively adjusting the policy methods that are adapted to them, so that as a policy maker, it can fully stimulate the enthusiasm of enterprises and consumers and maximize the public interest.
Environment Mapping Algorithm Using Semantic Description and Constrained Delaunay Triangulation

The article discusses the issue of creating an environment’s map with semantic division of areas. This simplifies some aspects of mobile robot control and permits the robot to carry out tasks issued in a human-understandable form. The article presents an innovative algorithm for mapping the environment by a mobile robot. Its novelty stems from the use of a semantic description of the world and Delaunay triangulation method with constraints. This description is used to segment the map of the environment and to reduce redundant information. The developed algorithm is based on the idea of extending the borders of the already discovered areas; they are expanded as the new data are collected from the environment. These data contain information about the location of semantic types in the explored space and is used to update the areas during analysis of the environment’s map. The beforementioned triangulation method is used in that process. The performance of the proposed algorithm is tested in simulation studies. The obtained results show a good computational efficiency of the method, which is crucial in the problem of environment exploration by mobile robots with limited computational resources.
Elliptical Constructions in Estonian UD Treebank

This contribution is about the annotation of sentences with verbal predicate ellipsis in the Estonian Universal Dependencies (UD) treebank.The main aim of the UD initiative is to develop a cross-linguistically consistent treebank annotation scheme and build a multilingual treebank collection.There are more than 70 treebanks in over 100 languages in UD treebank collection version 2.2.However, the UD annotation scheme is constantly improved and amended and so the annotation of the treebanks is also changing from version to version.Our article studies a problematic issue in representing syntactic structureclauses with predicate verb ellipsis.UD syntactic annotation scheme is based on dependency syntax and as the dependency structure is verb-centered, predicate verb ellipsis causes more annotation problems than other types of ellipsis.We focus on such constructions (referred to in English often as gapping and stripping) in Estonian and their annotation in Estonian UD treebank versions 1 and 2.2.
Projection of Productive Subject Teacher of Construction Technology and Property in 2019–2023

2016 and the implementation of the 2013 National Curriculum for the revision of the national level Vocational High School in the new academic year 2017/2018, then a productive teacher expertise placement arrangement in accordance with the competence there is on the spectrum.This study aimed to describe the projected needs of Productive Subject Teacher of Construction Technology and Property in year 2019 -2023, so that the known picture of needs.This study is a pragmatic approach
A DETAIL INVESTIGATION ON THE MEDICAL DATABASES BY IMPLEMENTING VARIOUS METHODS

Outlier detection is presented in detail in chapter 1.The finding of outliers for high dimensional datasets is a challenging data mining task. Different perspectives can be used to define the notion of outliers. Hawkins et al., 2002, defines an outlier as “an observation which deviates so much from other observations as to create suspicions that it was generated by a different mechanism”. While 'Barnett and Lewis, 1994' define it as “An outlier is an observation (or subset of observations) which appears to be inconsistent with the remainder of that dataset”.
Mapping of Landslide Hazard Distribution in Alo Watershed Gorontalo Regency

Landslide occurrence can be influenced by physical factors and human activities. Thus, research related to the provision of information about landslide distribution in Alo watershed is needed as a basis in enhancing community preparedness in dealing with disasters. The method used in this study is the scoring method based on the Minister of Public Works Regulation No.22 / PRT / M / 2017 which is processed through a geographical information system through the overlay of all physical parameters. The result shows that the Alo watershed area is divided into three vulnerability categories. "Low" category covers 7171.8 ha, "medium" category covers 12008.7 ha, and "high" category covers 5039.5 ha out of 24.221 ha the total area of Alo watershed. Information provided in this research is expected to be able to help the local government in making policies in managing the Alo watershed area and enhancing the understanding of the local community in Alo watershed in dealing with disasters.
A Methodology for Validation of a Distributed Cloud Reservation Model

This work presents a methodology for planning and validation of cloud-based distributed systems, considering a number of bottlenecks. The proposed methodology considers the computational model, the data traffic model, the analytical model, and the simulation model. The validated model is specialized to process an online reservation system. The goal is to analyze the performance of three bottlenecks considering critical resources such as a server, disk-file and disk-channel system. Specifically, we aim to use validation to further determine processor utilization and message delay. The proposed model and simulation tool may be used not only to plan and dimensioning of the system but also to guide the management of the distributed system in critical situations that can be anticipated. The general results are important to the validation of such systems. They showed that the effective verification and validation may be relevant to the adequate resource usage of the system.
Reconhecimento de Grafos Fino de Precedência

The class of k-thin graphs have recently been introduced generalizing interval graphs. The complexity of the recognition of k-thin is open, even for fixed k 1. We introduce a subclass of the k-thin graphs, called precedence k-thin graphs, presenting an efficient recognition algorithm based on PQ trees.
Complex event representation in a typed feature structure implementation of Role and Reference Grammar

is typologically general, semantically-driven syntactic framework.A major focus of RRG is a fine-grained typology of form-to-meaning mapping, emphasizing the syntactic and semantic structure of complex event descriptions.I introduce a constraint-based typed feature structure variant of RRG which exploits RRG's semantically-motivated syntactic backbone: the Layered Structure of the Clause (LSC).Each layer in the LSC is represented as a subtype of sign, and the unique combination of syntactic and semantic properties possessed by each layer is captured by a set of constraints on the appropriate sign subtype.Sentences are incrementally built up from predicates (represented semantically as event frames) to propositions using constructions to pass and combine information through the different layers (and juncture types) in the LSC.An English fragment of this constraint-based RRG is implemented using the Attribute Logic Engine (Carpenter, 1992).