Reviewerly/exHarmony huggingface dataset:
Opinion mining using combinational approach for different domains

An increase in use of web produces large content of information about products. Online reviews are used to make decision by peoples. Opinion mining is vast research area in which different types of reviews are analyzed. Several issues are existing in this area. Domain adaptation is emerging issue in opinion mining. Labling of data for every domain is time consuming and costly task. Hence the need arises for model that train one domain and applied it on other domain reducing cost aswell as time. This is called domain adaptation which is addressed in this paper. Using maximum entropy and clustering technique source domains data is trained. Trained data from source domain is applied on target data to labeling purpose A result shows moderate accuracy for 5 fold cross validation and combination of source domains for Blitzer et al (2007) multi domain product dataset.
CoRE: Non-Linear 3D Sampling for Robust 360° Video Streaming

CoRE is an approach for streaming 360° videos based on a non-linear sampling of the equirectangular video cube. CoRE is robust to view prediction errors.
Blockchain in Collection of Data for Cardio Vascular Disease (CVD)

Cardio Vascular Disease (CVD) is fast growing as an epidemic in the world. World Health Organization(WHO) in its latest survey observes that 31% of the total population affected now could rise considerably in the near future. The figures could be much alarming in the developing countries like India, where there are no historical track records of medical condition of the population. It's only the death of the patient and his postmortem data that is reveling these enormous numbers. The research started with the building of the model using machine learning to predict the risk of CVDs. The very fact that there exists no such data that could be used for prediction in our country is alarming. This motivated us to build a data acquisition model. This model would support our unsupervised learning. Once the data is ready it could be used for further study
Penanganan Kemiskinan Melalui Implementasi Blended Learning dalam Meningkatkan Kompetensi Pendamping pada Pelaksanaan Pertemuan Peningkatan Kemampuan Keluarga (P2K2)/Family Development Session/FDS (Studi Kasus di Kabupaten Bandung Provinsi Jawa Barat)

Handling poverty has been carried out through various policies and mechanisms, one of which is through the  Program Keluarga Harapan (PKH) . In order to achieve its goals, a social assistant is assigned to shelter Keluarga Penerima Manfaat (KPM) through Pertemuan Peningkatan Kemampuan Keluarga (P2K2). It turns out that many assistants underperformed in delivering the P2K2 presentaion. This is due to lack of knowledge of the module, underultizing learning aids and methods, lack of self-confidence and lack of effective communication which could result in stagnation to KPM. In order to improve its competence, P2K2 Training was carried out in blended learning. Qualitative research methods were chosen in this study with in-depth data collection, observation and documentation studies. The technique of checking the validity of qualitative data used data triangulation, and methods with a qualitative data analysis process.The results of this study indicate that the process of implementing blended learning includes learning online for 10 days equipped with discussion forums and chat forums. PKH social assistants felt that they gained additional knowledge of how to deliver all modules after attending blended learning. The increase of skills was also felt by the assistants offline because there were simulations in each session and practice in field learning. The informant's goal was to carry out P2K2 because it was beneficial for KPM so that their welfare would improve. The informants' self-confidence also improves because the informants felt that they were improving. The informant's ability to control and to mitigate negativity is better because the informant realizes that P2K2 must be carried out pleasantly because, Informant’s felt that verbal and non-verbal communication skills were improving by paraphrasing and maximizing eye contact, gestures, body language and facial expressions. Keywords: handling poverty, blanded learning, P2K2
Suitability study of certain features and classifiers for Bharatanatyam double-hand mudra images

Bharatanatyam, a traditional Indian classical dance, requires a study under the supervision of experts. At present, there is a scarcity of experts in this fine art, which requires leveraging of technology to make it self-pursuable. This paper presents a three-stage methodology for classification of double-hand mudra images of Bharatanatyam, wherein contours of mudras are obtained first, cell features are extracted that include number of vertical and horizontal intersections of grid lines with the contours of the mudras, mudra type and Hu-moments, second and classified using three classifiers, namely, rule based, artificial neural network and k-nearest neighbour, third. A comparative study of classifiers is given for their suitability. The proposed method finds many applications such as e-learning of mudras and proper postures leading to self-learning of Bharatanatyam dance, and online commentary during concerts.
EFFECTIVE COMMUNICATION AS A MEANS OF SOLVING INTER-PERSONAL CONFLICTS IN THE PEDAGOGICAL ENVIRONMENT

effectIVe cOMMunIcatIOn as a Means Of sOlVIngInter-PersOnal cOnflIcts In the PeDagOgIcal enVIrOnMent summary.In today's world, where communication is an integral part of daily life, it is simply necessary to have all the means of communications to prevent conflicts.The accelerated pace of today requires most people to be at the workplace most of the time.Thus, the ability to communicate with co-workers, to effectively and without any problems perform tasks given by the administration is an essential component of the competencies of the 21st century specialist, including an educator.The article deals with the meaning of the terms "communication", "conflict", examines the genesis of their origin, as well as the psychological features of the participants in the conflict.The author asserts that it is almost impossible to avoid conflicts between staff members.It is necessary to anticipate them by taking preventive measures.To do this it is necessary to carefully observe interpersonal communication between staff members, in order to timely identify increased anxiety, aggressiveness and bias.The study emphasizes that effective communication is the best way to resolve a workplace conflict.Communication is considered to be successful if both verbal and non-verbal means are used.For effective communication it is necessary to take into account the psychological features of the interlocutors.The article emphasizes that a conflict in a team is not always destructive.Sometimes it happens on the contrary, thanks to it the tension is weakened, stability in the relations between the members of the team appears.Trying to use the effective communication to relieve tension in the team, it is not necessary to criticize the interlocutor sharply, to seek a compromise for the conflicting parties, to try to objectively analyze the situation so that none of the opponents remain offended, to choose such words and speech constructions, so that no one feels humiliated.The author emphasizes that in order to eliminate conflict situations in the pedagogical team, it is necessary to rationally organize the work of higher educational institution, to create a favorable social and psychological climate, to constructively resolve interpersonal disputes through effective communication.
TRAINING OF TEACHERS AS A FORM OF DEVELOPMENT OF PROFESSIONAL COMPETENCE IN THE CONDITIONS OF PRESCHOOL EDUCATIONAL ORGANIZATION

Statement of the problem. The article updates the problem of demand for practical-oriented forms of development of professional competences of teachers and search for conditions of their introduction into pre-school educational organizations in the process of professional development of teachers and improvement of their qualifications. The purpose of the article is to reveal the essence of the internship and technology of its realization as a form of development of professional competence of teachers in conditions of pre-school educational organization and justification of its developing potential. The methodology of the research is founded on major provisions of competence-based, system-activity approaches, regulatory requirements of the professional standard of the teacher, analysis of innovative experience reflected in the research works of scientists on the development of professional competence of teachers of the pre-school education system. Research results. The paper analyzes work on the essence of the internship and the technology of its implementation in the process of professional development of teachers. In the course of the study, the author defined the notion of «internship», on the basis of which the internship technology for teachers was developed and introduced into practice. The developed technology includes five interrelated and consistently implemented stages, allowing teachers to master the demanded professional competence in a pre-school educational organization. Conclusion. Implementation of the internship technology developed and presented in the article allows the development of professional competence of teachers in a pre-school educational organization. This form can be used in the activities of vocational education institutions to improve the competence-based training of educational system specialists.
Development of OCR Mobile Application Including Miss-recognized Proofreading System Using Database Search Algorithm

In this paper, we introduce miss-recognition proofreading algorithm for optical character recognition(OCR) based on database search method, implement the algorithm as an Android application, and verify its operation. We consider the proposed algorithm to have robustness against miss-recognition by searching the database partially using the character recognition results. The proposed algorithm selects several characters randomly take out of OCR results, search the database which is prepared in advance for several times using selected characters, and decide the character string with the highest number of search as the proofreading results. And then, we implement this algorithm as the Android OCR application. This application consists of five components as follows. (1) Image input (2) Pre-processing (cropping, denoising, and binarization) (3) Character recognition (using Tesseract-OCR software developed by Google and Hewlett Packard) (4) Correct miss-recognition (using the proposed algorithm), (5) Texts output In this research, we present the recognition accuracy when we use the proposed algorithm and not use. Although it depends on the recognition accuracy of the OCR itself, our results reveal that the recognition rate is improved by the proposed method.
A First Step in the Translation of Alloy to Coq

Alloy is both a formal language and a tool for software modeling. The language is basically first order relational logic. The analyzer is based on instance finding: it tries to refute assertions and if it succeeds it reports a counterexample. It works by translating Alloy models and instance finding into SAT problems. If no instance is found it does not mean the assertion is satisfied. Alloy relies on the small scope hypothesis: examining all small cases is likely to produce interesting counterexamples. This is very valuable when developing a system. However, Alloy cannot show their absence. In this paper, we propose an approach where Alloy can be used as a first step, and then using a tool we develop, Alloy models can be translated to Coq code to be proved correct interactively.
Principles of organization the methodological activities of preschool teachers on a basis active approach

Л. В. Алексєєнко-Лемовськакандидат педагогічних наук, доцент, професор кафедри педагогіки і психології дошкільної освіти Національного педагогічного університету імені М. П. Драгоманова conditions, the availability of free time for the teacher's creative activity; efficiency, flexibility, mobility and an individual approach requiring, the creative nature of methodological work, the creation of a methodological work system in a preschool institution; continuing teachers' self-education, qualified assistance provision both in theoretical and in practical matters; improving teaching effectiveness.
Predicting dynamical systems with echo state networks with different topology

The prediction of complex nonlinear dynamical systems with the help of machine learning techniques has become increasingly popular. In particular, the so-called echo state networks (ESN) turned out to be a very promising approach especially for the reproduction of the long-term properties of the system. The heart of ESN is a network of nodes that is fed with input data and is connected with an output layer. So far only random Erdos-Renyi networks are used. However, there is a variety of conceivable other network topologies that may have an influence on the results. As a first step, we statistically analyze the quality of prediction - both the exact short term prediction as well as the reproduction of the long-term properties of the system as estimated by the correlation dimension and largest Lyapunov exponent for random, small world and scale-free networks. Using the Lorenz and the Rossler system we find significant variations of the results. The longterm prediction is worse for the scale-free network, where the differences between the network types are more pronounced in the Rossler system. Random and scale-free networks perform similar in both cases with slight advantages for the small world network. Our results suggest that the network topology has significant influence on the performance of ESN. Studying the results for different networks in detail also gives new insights about the complexity of the underlying dynamical system.
PENGGUNAAN STRATEGI VISUALISASI DALAM PEMBELAJARAN MEMBACA PEMAHAMAN BAHASA INGGRIS BERBASIS KARAKTER PADA SISWA SMP

Reading English text is not an easy matter, especially for junior high school students. They demanded to comprehend the idea in the texts. So, this article discusses about the strategy for the junior high school students which is interesting and easy to be implemented. This article also describes reading comprehension with character-based by integrating reading comprehension activities with character education. Strategy used here is visualization strategy that involves the students’ prior knowledge to makes mental image that will help them comprehend the text. They will have to sketch it down so the images become clear. The teacher will supervise students while presenting themselves with good character so that they become role models for their students. This strategy will involve interaction between teacher and students.
Translation of Children’s Picture Book

Children’s story books serve not only as a medium of verbal communication but also as that of non-verbal one. Messages conveyed through children’s story books will not be attracting to children if not accompanied by their non-verbal forms, such as pictures and symbols. Therefore every story book should be able to influence the child psychologically through pictures or symbols. This in turn affects the process of translating children’s storybook texts, including in determining translation techniques. This study examines the technique of translating Balinese children’s story books from English into Indonesian. This study was conducted with a qualitative research design. The results of the study show that the translation of Balinese children’s textbooks is mostly done literally using simple language. The writing children’s story books emphasizes the presentation of non-verbal forms of communication to foster and maintain their interest in reading. The writing and translation of children’s story texts is based on consideration of their psychological aspects so that the translator avoids the use of complicated words.
Direct sum testing - the general case.

A function $f:[n_1]\times\dots\times[n_d]\to\mathbb{F}_2$ is a direct sum if it is of the form $f\left(a_1,\dots,a_d\right) = f_1(a_1)\oplus\dots \oplus f_d (a_d),$ for some $d$ functions $f_i:[n_i]\to\mathbb{F}_2$ for all $i=1,\dots, d$, and where $n_1,\dots,n_d\in\mathbb{N}$. We present a $4$-query test which distinguishes between direct sums and functions that are far from them. The test relies on the BLR linearity test (Blum, Luby, Rubinfeld, 1993) and on an agreement test which slightly generalizes the direct product test (Dinur, Steurer, 2014). In multiplicative $\pm 1$ notation, our result reads as follows. A $d$-dimensional tensor with $\pm 1$ entries is called a tensor product if it is a tensor product of $d$ vectors with $\pm 1$ entries, or equivalently, if it is of rank $1$. The presented tests can be read as tests for distinguishing between tensor products and tensors that are far from being tensor products. We also present a different test, which queries the function at most $(d+2)$ times, but is easier to analyze.
Fraud Detection in MeDInsu using Machine Learning Algorithms - A Web Application

Extortion is no matter how you look at it and costly to the social protection assurance structure. Coercion incorporates intentional guile or double dealing expected to achieve an unapproved advantage. It is shocking in light of the way that the event of medical coverage extortion keeps growing every year. With a particular ultimate objective to recognize and sidestep the blackmail, information mining methodology are associated. This fuses some preliminary learning of human administrations structure and its beguiling practices, assessment of the traits of social protection assurance data. Information mining which is disengaged into two learning methodologies viz., administered and solo is used to recognize beguiling cases. Regardless, since all of the above methods has its own specific course of action of central focuses and disadvantages, by joining the advantages of both the frameworks, a novel cross breed approach for distinguishing tricky cases in therapeutic inclusion industry is proposed.
PREDIKSI KEGAGALAN SISWA DALAM DATA MINING DENGAN MENGGUNAKAN METODE NAÏVE BAYES

In an effort to improve the quality of a nation, there is no other way except through improving the quality of education. The success and failure of students' classes in the study determined many factors that influence it. The results of this study are using the naive bayes data mining method which is used to predict student failures in their studies as well as influential factors including failure, traveltime, internet, romantic, freetime, go-out, health, and absence. Naive Bayes algorithm is an algorithm that can be used to predict using probability theory with a high degree of accuracy. Naive Bayes algorithm testing uses WEKA tool which produces an accuracy of 77.22 from 395 datasets. This algorithm is used to predict student class failures
Analisis Pembelajaran Matematika pada Materi Perpangkatan dengan Model Pembelajaran Multiple Intelligences

&lt;p&gt;Penelitian ini bertujuan untuk: (1) Mengetahui aktivitas siswa selama mengikuti proses pembelajaran matematika dengan menggunakan model pembelajaran &lt;em&gt;Multiple Intelligences&lt;/em&gt;. (2) Mengetahui persepsi siswa terhadap pembelajaran matematika dengan menggunakan model pembelajaran &lt;em&gt;Multiple Intelligences&lt;/em&gt;. (3) Mengetahui hasil belajar siswa baik secara individu maupun secara klasikal dalam pembelajaran matematika dengan menggunakan model pembelajaran &lt;em&gt;Multiple Intelligences&lt;/em&gt;. Penelitian ini menggunakan penelitian deskriptif dengan pendekatan kualitatif. Teknik pengumpulan data yang dipergunakan dalam penelitian ini adalah angket dan pengamatan. Dari hasil ketuntasan belajar secara individual didapatkan prosentase ketuntasan secara klasikal yaitu 77,2 %, sehingga model pembelajaran &lt;em&gt;Multiple Intelligences&lt;/em&gt; merupakan teori belajar yang dipandang sebagai penggunaan berbagai teori, prinsip, metode, strategi dan taktik belajar dalam menciptakan situasi belajar yang menyenangkan guna memperoleh hasil belajar yang sesuai dengan yang diinginkan.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;This study aims to: (1) Determine student activities during the mathematics learning process by using Multiple Intelligences learning models. (2) Knowing students' perceptions of mathematics learning by using Multiple Intelligences learning models. (3) Determine student learning outcomes both individually and classically in mathematics learning by using Multiple Intelligences learning models. This research uses descriptive research with a qualitative approach. Data collection techniques used in this study were questionnaires and observations. From the results of individual learning completeness obtained the classical mastery percentage is 77.2%, so the Multiple Intelligences learning model is a learning theory that is seen as the use of various theories, principles, methods, strategies and learning tactics in creating enjoyable learning situations in order to obtain learning outcomes in accordance with what is desired.&lt;/p&gt;
Learning Probabilities: Towards a Logic of Statistical Learning.

We propose a new model for forming beliefs and learning about unknown probabilities (such as the probability of picking a red marble from a bag with an unknown distribution of coloured marbles). The most widespread model for such situations of 'radical uncertainty' is in terms of imprecise probabilities, i.e. representing the agent's knowledge as a set of probability measures. We add to this model a plausibility map, associating to each measure a plausibility number, as a way to go beyond what is known with certainty and represent the agent's beliefs about probability. There are a number of standard examples: Shannon Entropy, Centre of Mass etc. We then consider learning of two types of information: (1) learning by repeated sampling from the unknown distribution (e.g. picking marbles from the bag); and (2) learning higher-order information about the distribution (in the shape of linear inequalities, e.g. we are told there are more red marbles than green marbles). The first changes only the plausibility map (via a 'plausibilistic' version of Bayes' Rule), but leaves the given set of measures unchanged; the second shrinks the set of measures, without changing their plausibility. Beliefs are defined as in Belief Revision Theory, in terms of truth in the most plausible worlds. But our belief change does not comply with standard AGM axioms, since the revision induced by (1) is of a non-AGM type. This is essential, as it allows our agents to learn the true probability: we prove that the beliefs obtained by repeated sampling converge almost surely to the correct belief (in the true probability). We end by sketching the contours of a dynamic doxastic logic for statistical learning.
An Approach to Improve the Detection rate using Sampling of Imbalanced Data

Synthetic Minority Over-sampling Technique (SMOTE) works by creating synthetic observations based upon the existing minority observations. In this research KDD Cup99 dataset is used. Through SMOTE we tried to increase the rare classes (U2R and R2L).The random forest was used to create the model in the Cost Sensitive Classifier.The tests were performed on many percentage ratios of rare classes.Results were better than the existing one.