Reviewerly/exHarmony huggingface dataset:
PHYSICAL EDUCATION CLASSES AS A WAY OF FORMING VALUE ORIENTATIONS IN THE EDUCATIONAL SPACE OF SURGUT OIL AND GAS INSTITUTE

In the article, the author describes physical education classes within the framework of value orientations in the educational space of higher education. The study consisted in the development of an algorithm for the actions of a teacher in physical education and university leadership to improve the cultural component of physical education. Research base: Surgut Oil and Gas Institute, 1-3 year students became participants in the study. The author presented the results of a study on the attitude of students to physical education and sports, attitudes to health in the discourse of value orientations
LESSONS IN GRADE 11 MATHEMATICS USING GRAPHING CALCULATOR APPLICATIONS

Since mobile devices are becoming ubiquitous in today’s student generation and to replace bulky and costly handheld graphing calculators, this quasi-experimental study determined the effects of the lessons using graphing calculator applications in a Mathematics classroom. The study involved two intact classes of Grade 11 GAS students of San Jose National High School, Malilipot, Albay. The experimental group was taught lessons using graphing calculator applications with the integration of contextualized, inquiry-based, collaborative and interactive learning approaches. On the other hand, the control group received the same lessons but without the use of applications. The actual conduct of the lessons was video-recorded and observed by the teacher-observers to determine and analyze carefully the students’ notable behaviors. Further, the effects of the lessons in terms of students’ performance, mental effort, and interest were assessed by using teacher-made test, Paas Mental Effort Rating (PMER) scale, and Mathematics Interest Inventory, respectively. Students’ journal entries, teachers’ observation notes, and focus group discussions’ responses were used to triangulate the results. Qualitative and quantitative analyses showed that the lessons using graphing calculator applications supported student collaboration and facilitated better teacher-student interaction. It also allowed students to become comfortable when and how to use the applications, as well as making them active and participative during learning activities. It further enhanced students’ conceptual understanding and process skills, and increased their level of interest towards Mathematics. The use of the applications also afforded the minimizing of students’ extraneous cognitive load by investing lower mental effort in learning the lessons. To this extent, the use of graphing calculator applications in Mathematics lessons is needed for the betterment of learning the subject.
An Improved Pose Matching Method Based on Deep Learning

An improved pose matching method based on the combination of Mask-RCNN and correlation coefficient is proposed to improve the accuracy of pose matching in images. Firstly, the feature points of two-dimensional human pose joints in the test set are correctly identified and extracted by fine-tuned Convolutional Neural Networks. Then, the joint feature points extracted for the same target in the two images are not necessarily the corresponding feature point pairs, the correlation coefficient matching algorithm is used for correction. Compared with the traditional algorithm, this method eliminates the feature points outside the target segmentation area effectively, which reduces the mismatch and improves the matching accuracy. The experimental results verify the effectiveness of the method and the practicability of the system.
PENGARUH KREATIVITAS SISWA DALAM MODEL PEMBELAJARAN PROBLEM BASED LEARNING TERHADAP PRESTASI BELAJAR SISWA KELAS IV SDN KALISARI 01

The research focuses on the effect of students' creativity iniproblemibased learningilearning models onistudent achievementlin science subjects class IV SDN Kalisari 01.Theipurpose ofithis research is to determine the effect of student creativity in problemibasedilearningnlearning models on student achievement in science subjects class IV SDN Kalisari 01.This study uses aiquasiiexperimental design approach.This research takes the form of designnis nonequivalentncontrol groupndesign with two groups,namely thencontrol groupnand thenexperimental groupnusing 2 (two) data collectionntechniques, namely tests and non-tests.Basedionithe results of the study, there is an influence of Student Creativity in Problem Based Learning (PBL) Learning Modeliwith 66% results.That means students' creativity in PBL was good.Natural science learning achievement in grade IV students of SDN Kalisari 01 magnetic and
The Value of Hard Work Embodied in the Novel Mata dan Manusia Laut by Okky Madasari

This study aims at describing the character education values embodied in the novel Mata dan Manusia Laut by Okky Madasari. The novel is chosen due to the character values that can be a reflection of students to apply in daily life. As the object of the study is the stories of this novel which contains the character education values. This study is a descriptive qualitative research in which the data in this study are in the form of words. The data used in the form of a narrative dialogue between characters in the novel. The technique used is the content analysis method. For the data validity of this research uses theory triangulation, method triangulation, and data triangulation. The data analysis technique used is the analysis of the Flow model by Miles and Huberman (2012) through the stages of data reduction, data presentation, as well as withdrawal conclusions. The theory of character education values refers to the Thomas Lickona theory which consists of ten character education values. However, this study is more focused on the value of hard work. The results of this study show that regarding the character education values, novel Mata dan Manusia Laut by Okky Madasari gives examples as well as description especially for the value of hard work which contains eleven values quoted from the novel. Also, the novel Mata dan Manusia Laut by Okky Madasari is representative enough as literacy learning, especially for a novel containing character education.
SISTEM PENUNJANG KEPUTUSAN PEMILIHAN INDUK AYAM KUB TERBAIK DENGAN METODE FUZZY DAN VIKOR

Kampung Unggul Superior Chicken (KUB) is a native native chicken selection from the Animal Research Center (Balitnak). KUB chicken has the advantage of low incubation and high egg production, so it becomes a parent producer of many DOC (female line). Currently consumption of native chicken meat and eggs in the community from year to year has increased while its production has not been able to fully meet the needs of the community. Some of the problems in maintaining KUB hens are not optimal body weight, length of time in laying eggs and even a small amount of egg production quality from selected prospective broodies originating from KUB hens who have high productivity in laying eggs. to overcome these problems, an application system is needed, one of which is a decision support system application. This application can provide recommendations in the selection of the best KUB hens so that the hens can be maintained intensively so that the supply of chicken meat and eggs can meet the needs of the community. There are several methods that can be used to determine the selection of the best KUB Parent, including using the Vikor method. Vikor is used to overcome the problem of complex multi-criteria systems that focus on ranking and selection of an alternative, while to determine the weighting using the Fuzzy Method. The results of this study are in the form of an application system that can help breeders / enclosure technicians in determining the selection of the Best KUB Chicken Parent. The level of system accuracy using the Vikor and Fuzzy methods was obtained at 77.2% of the 9 test data used.
TO THE PROBLEM OF SOCIAL COMPETENCE RESEARCH AS CONDITIONS OF PARTNER INTERACTION PARTICIPANTS OF THE REFORM PROCESS

The problem of social competence as a condition for partnership interaction among participants in the process of educational innovation is presented in the article. The theoretical analysis of the phenomenon of social competence has been carried out. Social competence is seen as an integrative characteristic of the individual that determines effective social interaction, the effectiveness of socialization in the professional environment and in the world, where the important conditions for a productive solution to life's problems are social maturity, subjectivity and social intelligence. Empirically established differences in social competence among students of pedagogical specialties with a pronounced active positive and active negative attitude to educational innovations. It is revealed that students of pedagogical specialties with active negative attitude to educational innovations have less expressed social and psychological competence, compared to students of pedagogical specialties with active positive attitude to educational innovations. Empirically determined correlation features of social competence with terminal values and personal self-efficacy. Direct significant correlations were found between social-psychological competence and such terminal values: active social contacts, development of self, preservation of individuality, achievements, creativity, spiritual satisfaction. There are empirically significant direct correlations between social and psychological competence and psychological resilience. Psychological resilience is defined as a dynamic process aimed at maintaining a stable level of psychological and physical functioning in critical situations, the ability to overcome such situations without persistent disturbances, successfully adapting to adverse changes. Based on the correlation study on the correlation coefficient of Ch. Spearman, a direct significant correlation of social and psychological competence with personal self-efficacy and psychological resilience was established. The higher the students' pedagogical specialties are socio-psychological competence, the greater their psychological resilience is expressed, that is, the more they are able to maintain in a critical situation a stable level of psychological and physical functioning, to successfully adapt to difficult life circumstances.
REFLEXIVE INFLUENCE OF SOCIO-PSYCHOLOGICAL THEATRE IN PREVENTATIVE-CORRECTIONAL WORK OF SOCIAL WORKER

Innovative forms of work play an important role in bringing up a personality, one of them is creation and activity of social-psychological theatre, which forms actively social-psychological ideal, presenting it by certain images, with the help of which social-psychological ideas, moral norms, life values transform in personal experience of a human, temperamental gains of his character. Socio-pedagogical theatre (SPT), forum-theatre and playback theatre are effective in social educator’s prevention and correction work. Socio-pedagogical theatre represents effective methods of group correction, developmental and preventive work with teenagers, as aims at interactive group work. Taking in consideration the fact that socio-psychological theatre is one of interactive methods of social worker’s work, we can outline a few objectives which are realized in the process of its organization. Namely: forming and development of communication and interaction skills; active formation of socio-psychological ideal, which reveals itself in certain psychological images with the help of which socio-psychological ideas, moral norms, life values transform into personal experience; development of decentering (ability to overcome self-centering, ability to take into consideration other points of view); development of emotional (sensory) experience; prevention of personal deviations and social problems. The aim of SPT: pupils’ behavior correction from “risk groups”, help teenagers to adopt in society; healthy way skills formation; prevention of offences among pupils; struggle with negative influence in youth environment; active life position formation. We point out that with the help of reflection which accompanies theatrical performance its participant gains effective tools of self-correction of personal behavior stereotypes.
Development of web-based application in population administration system using scrum framework

The purposes of managing population data include increasing service effectiveness, ensuring data accuracy, ensuring identity and population documents that are single [9].To make this purpose to be realized, accurate and real-time data collection techniques are needed, as well as good data integration between population data managers at the central, provincial and city / district levels.
Product Line Configuration Meets Process Mining

Product line engineering is a new production paradigm that provides organizations a competitive edge by improving productivity and decreasing costs. The purpose with this new production paradigm is no longer to develop a single product but to develop a product family and to generate the products of the line through configuration processes. However, the potential benefits of product line engineering can be missed when dealing with large product lines because the configuration processes become error prone tasks. Consequently, guiding stakeholders during such complex configuration processes and recommending the best configuration alternatives until leading to a satisfying experience becomes a challenge. This paper focuses on enhancing product line configuration processes through process mining techniques. Therefore, user's actions of previous product line configurations are logged, mined and analyzed. We conducted a preliminary research to motivate the advantages of process mining in product line configuration and to explore what can process mining bring for configuration processes and how to use it to enhance configuration processes. Thus, guidance questions are sketched in order to position process mining as a solving tool for the configuration difficulties. Furthermore, we propose a reference architecture that considers process mining for configuring product lines.
Security Testing Tool for NoSQL Systems

NoSQL systems are becoming more popular due to their inherent advantages and solutions it provides to the limits of a relational database. However, despite its benefits, it comes with security challenges. In this paper, an input validation mechanism architecture is proposed for Mongo DB to detect and prevent NoSQL injection attacks, the mechanism employs a Deterministic Finite Automaton (DFA) approach to detect and prevent attacks on NoSQL systems. Furthermore, a security comparison of some NoSQL systems is provided based on recent literature. The security features compared are authentication, authorization, data encryption and input validation. The proposed mechanism will improve the security of Mongo DB system because invalid inputs requests will be detected and prevented from being processed.
Affordances na interação online de aprendizes de inglês na modalidade Educação a Distância

The main objective of this research was to describe the mechanisms for engagement with affordances that help to sustain written interpersonal interactions of students in online discussion forums of a virtual learning environment while they were learning English as a foreign language. The notion of affordance was discussed in this study according to three dimensions: (i) environmental, (ii) technological, and (iii) linguistic, associating a pragmatic theory to the latter (GREENO, 1994; VAN LIER, 2000; LAMY &amp; HAMPEL, 2007). The research findings showed that the environmental and technological affordances contributed to the construction of students’ presence as well as of a learning community. New forms of online interactions afforded new forms of language learning, especially by the movement of relexicalization and gap-filling.
Recognition of Eyelid Movement Using Electroencephalographic Signals

Eyelid movement patterns are a key factor in the detection of fatigue, and in this study, electroencephalography (EEG) was used to record the brainwave patterns associated with eyelid movement in subjects during various stages of fatigue.The three movements involved were no eyelid movement, closing the eye, and opening the eye.The collected signals were processed using the wavelet transform (WT) to break down the EEG signal and obtain the main features.The support vector machine (SVM) and back propagation neural network (BPNN) were used to determine eyelid movement conditions.
[Prediction and feature selection for fatal gastrointestinal bleeding recurrence in hospital via machine learning].

To propose a method of prediction for fatal gastrointestinal bleeding recurrence in hospital and a method of feature selection via machine learning models.728 digestive tract hemorrhage samples were extracted from the first aid database of PLA General Hospital, and 343 patients among them were diagnosed as fatal gastrointestinal bleeding recurrence in hospital. A total of 64 physiological or laboratory indicators were extracted and screened. Based on the ten-fold cross-validation, Logistic regression, AdaBoost and XGBoost were used for classification prediction and comparison. XGBoost was used to search sequence features, and the key indicators for predicting fatal gastrointestinal bleeding recurrence in hospital were screened out according to the importance of the indicators during training.Logistic regression, AdaBoost and XGBoost all get better F1.5 score under each feature input dimension, among which XGBoost had the best effect and the highest score, which was able to identify as many patients as possible who might have fatal gastrointestinal bleeding recurrence in hospital. Through XGBoost iteration results, the Top 30 indicators with high importance for predicting fatal gastrointestinal bleeding recurrence in hospital were ranked. The F1.5 scores of the first 12 key indicators peaked at iteration (0.893), including hemoglobin (Hb), calcium (CA), red blood cell count (RBC), mean platelet volume (MPV), mean erythrocyte hemoglobin concentration (MCH), systolic blood pressure (SBP), platelet count (PLT), magnesium (MG), lymphocyte (LYM), glucose (GLU, blood gas analysis), glucose (GLU, blood biochemistry) and diastolic blood pressure (DBP).Logistic regression, AdaBoost and XGBoost could achieve the purpose of early warning for predicting fatal gastrointestinal bleeding recurrence in hospital, and XGBoost is the most suitable. The 12 most important indicators were screened out by sequential forward selection.
Blind Deconvolution with Scale Ambiguity

Recent years have witnessed significant advances in single image deblurring due to the increasing popularity of electronic imaging equipment. Most existing blind image deblurring algorithms focus on designing distinctive image priors for blur kernel estimation, which usually play regularization roles in deconvolution formulation. However, little research effort has been devoted to the relative scale ambiguity between the latent image and the blur kernel. The well-known L 1 normalization constraint, i.e., fixing the sum of all the kernel weights to be one, is commonly selected to remove this ambiguity. In contrast to this arbitrary choice, we in this paper introduce the L p -norm normalization constraint on the blur kernel associated with a hyper-Laplacian prior. We show that the employed hyper-Laplacian regularizer can be transformed into a joint regularized prior based on a scale factor. We quantitatively show that the proper choice of p makes the joint prior sufficient to favor the sharp solutions over the trivial solutions (the blurred input and the delta kernel). This facilitates the kernel estimation within the conventional maximum a posterior (MAP) framework. We carry out numerical experiments on several synthesized datasets and find that the proposed method with p = 2 generates the highest average kernel similarity, the highest average PSNR and the lowest average error ratio. Based on these numerical results, we set p = 2 in our experiments. The evaluation on some real blurred images demonstrate that the results by the proposed methods are visually better than the state-of-the-art deblurring methods.
Temporal Domain Difference Based Secondary Background Modeling Algorithm

This paper proposes a temporal domain difference based secondary background modeling algorithm for surveillance video coding. The proposed algorithm has three key technical contributions as following. Firstly, the LDBCBR (Long Distance Block Composed Background Reference) algorithm is proposed, which exploits IBBS (interval of background blocks searching) to weaken the temporal correlation of the foreground. Secondly, both BCBR (Block Composed Background Reference) and LDBCBR are exploited at the same time to generate the temporary background reference frame. The secondary modeling algorithm utilizes the temporary background blocks generated by BCBR and LDBCBR to get the final background frame. Thirdly, monitor the background reference frame after it is generated is also important. We would update the background blocks immediately when it has a big change, shorten the modeling period of the areas where foreground moves frequently and check the stable background regularly. The proposed algorithm is implemented in the platform of IEEE1857 and the experimental results demonstrate that it has significant improvement in coding efficiency. In surveillance test sequences recommended by the China AVS (Advanced Audio Video Standard) working group, our method achieve BD-Rate gain by 6.81% and 27.30% comparing with BCBR and the baseline profile.
Electricity Consumption Forecasting Using Nonlinear Autoregressive with External (Exogeneous) Input Neural Network

Forecasting is prediction of future values based on historical data.Electricity consumption forecasting is crucial for utility company to plan for future power system generation.Even though there are previous works of electricity consumption forecasting using Artificial Neural Network (ANN), but most of their data is multivariate data.In this study, we have only univariate data of electricity consumption from January 2009 to December 2018 and wish to do a prediction for a year ahead.On top of that, our data consist of autoregressive component, hence Nonlinear Autoregressive with External (Exogeneous) Input (NARX) Neural Network Time Series from Matlab R2018b was used.It gives the mean absolute percentage error (MAPE) between actual and predicted electricity consumption of 1.38%.
Ergativity Case-Marking in Batak Toba Language

Batak Toba Language (BTL) is an accusative, ergative and split-S language. It is called accusative because BTL has an active diathesis basic construction. In the BTL, the active diathesis clause is morphologically marked on the verb (head marking) by adding the prefix /ma-/, /maN-/ or zero prefix (occurred in some verbs that can stand without affixes). BTL is categorized ergative, firstly, because in the basic S argument from the intransitive verbs in BTL can be semantically gets the most influence from the verb, and it is also applied as O of intransitive verbs. Secondly, By using treatment parameters S equal to O and different from A in nominal construction. BTL is also categorized as split-S language because the behavior is that the agent-like argument of intransitive verb (Sa) in transitive verbs can be nominalized with /par-/ affixes, while the patient-like arguments of other intransitive patients cannot be nominalized with /par-/ affixes