Reviewerly/exHarmony huggingface dataset:
Innovative perception of literary education: Communication concept

The paper presents a communication concept of teaching with a focus on teaching Literary Education. In the article, we present in more detail a research survey involving a total of 16 humanities teachers, which examined the current state of communication between pupils and teachers: the data were obtained from an analysis of teaching videos that preceded the observation of teaching. The analysis of the video recordings was supplemented by interviews with the teachers who led the lessons and student questionnaires, which served as a tool for data triangulation. Based on the analysis of the results, the authors present a generally tuned model of good educational communication, in the center of which should be a balanced distribution of power forces (i.e. the role of the teacher and the position of students). The implementation of the communication concept in real teaching can lead to a deeper and more comprehensive interpretation of artistic narratives, it can develop the pupil´s personality and can enrich the teacher. The communication conception of teaching forms the starting point for an innovative conception of Literary Education, which builds on the thesis that text (artistic narrative) is in the center of literature teaching. It is the communication between the teacher, the pupil and the text that is the basis of creative literary expressivity, the gros of contemporary Literary Education according to the didactics of literature.
Tamil and Kannada Prosody - A Comparative Study

The old and ancient Tamil and Kannada literature is fully of poetic nature. Research oriented and related studies about prosody or meter is very less and rare. Amsha gana (asai) in Tamil is very wide and comprehensive and it has remained and kept its uniqueness by not getting influenced by other languages. So Kannada Scholers has opined that to understand the basic nature of Dravidian Prosody its necessary to learn about Tamil Prosody which is very essential. The present research article is about the study between Kannada and Tamil Prosodian literature and comparative study of Kannada and Tamil Amsha gana (Asai) Maathre (Ner and Nirai) has been dealt in this article with this comparative attempt of equivalent, diversity and difference between Kannada and Tamil prosody has been made in this study. These type of research studies helps to reconstruct the origin nature of (Proto Dravidian) Dravidian Prosody by and large.
Implementation of Genetic Algorithms and Momentum Backpropagation in Classification of Subtype Cells Acute Myeloid Leukimia

Acute Myeloid Leukimia (AML) is a type of cancer which attacks white blood cells from myeloid. AML subtypes M1, M2, and M3 are affected by the same type of cells called myeloblasts, so it needs more detailed analysis to classify.Momentum Backpropagation is used to classified. In its application, optimal selection of architecture, learning rate, and momentum is still done by random trial. This is one of the disadvantage of Momentum Backpropagation. This study uses a genetic algorithm (GA) as an optimization method to get the best architecture, learning rate, and momentum of artificial neural network. Genetic algorithms are one of the optimization techniques that emulate the process of biological evolution.The dataset used in this study is numerical feature data resulting from the segmentation of white blood cell images taken from previous studies which has been done by Nurcahya Pradana Taufik Prakisya. Based on these data, an evaluation of the Momentum Backpropagation process was conducted the selection parameter in a random trial with the genetic algorithm. Furthermore, the comparison of accuracy values was carried out as an alternative to the ANN learning method that was able to provide more accurate values with the data used in this study.The results showed that training and testing with genetic algorithm optimization of ANN parameters resulted in an average memorization accuracy of 83.38% and validation accuracy of 94.3%. Whereas in other ways, training and testing with momentum backpropagation random trial resulted in an average memorization accuracy of 76.09% and validation accuracy of 88.22%.
Educational Expenditure and Economic Welfare in Sub Saharan African Countries: Effects and transmission channels

This study sets out to evaluate how public educational expenditure affects economic welfare.Specifically, we investigated the effects and the transmission channels of public educational expenditure on economic welfare in 15 Sub Saharan African (SSA) countries from 2000-2017.We sourced data from the World Development Indicators, World Governing Indicators, the Freedom House and Polity IV data bases.We used the Panel Corrected Standard Errors Estimator (PCSE) in a static model framework to evaluate the direct effects of educational expenditure on economic welfare and the causal mediation analysis to assess the channels through which public educational expenditures affect economic welfare.Our results from the PCSE estimator revealed that the square of public educational expenditure, democracy, access to education, quality governance, trade openness and financial development positively and significantly affect economic welfare in SSA countries while educational expenditure has negative and significant direct effects.However, based on the causal mediation analysis, we found out that trade openness, governance, democracy and educational access positively and significantly mediated the negative effects of public educational expenditure on economic welfare in SSA.On the basis, we strongly recommend that governments should increase the sizes of public spending on education, improve on governance, improve on access to education and liberalise their economies.
Document Capturing Automation: Case Study

Capturing of new documents into the enterprise document repository involves some kind of (usually labour intensive) task of metadata attributing.Attributes include document types, folders, cases and others.This is, in fact, a classification process and may be addressed by Machine Learning based classification methods.The research presented in this paper aims to introduce a flexible framework for document capturing automation employing Machine Learning based document classification bots and providing an intuitive user interface featuring analysis of the document classification performance, creation of the domain specific rules, and configuration or the process parameters.The paper outlines important aspects of the frameworkchannels, rules, handling imbalanced data and continuous training.The prototype DOBO of the framework is presented and its performance evaluation results are discussed.
Cloud service security evaluation of smart grid using deep belief network

In this paper, we analyse key security problems in the scalable platform architecture of cloud service of smart grid. We also establish evaluating process according to the lack of evaluation mechanism. They evaluate security risks in 5 respects which are policy and organisational risks, general technical risks, SaaS risks, PaaS risks and IaaS risks. The evaluation model based on deep belief network (DBN) is proposed which is composed of multiple RBMs and a BP neural network. The RBMs are trained by greedy training algorithm, and then BP algorithm is used to fine-tuning. After case verification, it is found that the various errors (including mean absolute error (MAE), mean relative error (MRE), mean square error (MSE), maximum error and minimum error) of DBN model are the smallest compared BP and AE model. It avoids the problem that multilayer neural network is trapped in the local optimum.
Encryption and Compression Digital Video Files using Artificial Neural Networks and Genetic Algorithm

The research and studies of encryption and compression of digital files to the confidentiality and ease of dealing with networks and the Internet, by reducing the size of files transmitted through multimedia, and also used to increase the confidentiality of information transmitted.The purpose of the research is to encrypt and compress colored digital video files using artificial neural networks and genetic algorithm, The digital video file is entered into Audio Video Interleave (AVI) and cut into a set of frames, Each frame is then analyzed into the three color segments (red, green and blue) And an audio input from the Waveform Audio File Format (WAV) type (which represents the encryption key), the encoded frame was then inserted into the compression algorithm, A hybrid compression method was adopted which is considered as one of the solutions that reduces the size of the required data on the one hand and gives it a secret on the other, Where it was segmentation and clustering the encoded frames into a cluster of clusters (The optical pixels), which have been introduced into the artificial neural network (back propagation network), The genetic algorithm has been used to calculate the weight values of each cell of the network.The decryption and decompression is then performed, and by using a set of testing and comparison tools that showed that the results were consistent with the research requirements, and Matlab R2017b was used to implement research algorithms.
Characterization of human motion by the use of an accelerometer-based detection system

Human motion mode detection is of great value in evaluating motor ability. In this study, a method of human motion mode detection based on an acceleration sensor was characterized. A human motion mode detection system was designed using the standard deviation, peak, valley and peak-valley interval as characteristic values and a particle swarm optimization – support vector machine (PSO-SVM) algorithm as the detection method. The measurements of 10 subjects in static, walking and running stages were collected and evaluated. The experimental results showed that the static, walking and running detection accuracy values were 96%, 90% and 92% respectively, and the overall value was 94%. Using the same number of samples, the detection accuracy of SVM was 82.57%, while that of PSO-SVM was 93.1%, which had the highest reliability. This study demonstrates the validity of the human motion mode detection method based on an acceleration sensor which can accurately detect static state, walking and running, and the method is worth further promotion and application.
Pre-service English Teachers’ Use of Reinforcement Strategy in Microteaching

This article investigates the reinforcement strategies used by pre-service English teachers in a microteaching class. The researchers employed a case study. Twenty-two students participated in this research. Observation, interviews, and video recording were used to gather the data. The data were then organized, coded, interpreted. The findings revealed that four types of reinforcement were used by pre-service English teachers in microteaching, namely positive reinforcement (81.93%), negative reinforcement (17%), punishment (3.36%), and extinction (2.94%). Moreover, the pre-service English teachers delivered reinforcement strategy by using warmth and enthusiasm expressions of praise, avoiding the punishment, and using non-variety usage of positive reinforcement. In conclusion, pre-service English teachers mostly used positive reinforcements in their teaching practice. They delivered the reinforcement strategy by using warmth and enthusiasm expressions of praise, avoiding the punishment, and using non-variety usage of positive reinforcement.
The Development of Fantasy Teaching Materials by Using VAK (Visual Auditory Kinesthetic) on 7th Grade Students in SMP Negeri 1 Medan

This study aims to produce teaching materials by using VAK (Visual Auditory Kinestethic) on fantasy story material for 7th grade students of SMP Negeri 1 Medan. The research method used is Research and Development which refers to Borg and Gall model. The stages of development are the initial study phase, initial product development, and product trials. The results showed that the results of material validation included content eligibility with an average of 82% with a very good category, Eligibility for Presentation with an average of 87.5% with a very good category, and an assessment of language aspects with an average of 82.2% with a category very good. For the assessment of graphics by design experts obtained an average of 87% with the category "very good". Product trials are carried out in three stages: individual testing, small group trials, and limited field trials. Individual trials with an average of 86% with very good categories, small group trials with an average of 87.4% with very good categories, and limited field trials with an average of 88.3% with very good categories. The effectiveness of teaching materials is obtained through student learning outcomes in the pretest and posttest. Average score at pretest is 52 and at posttest is 76. This proves that the teaching material of fantasy story by using VAK (Visual Auditory Kinestethic) is feasible, easy, and effective for use in 7th grade students of SMP Negeri 1 Medan. This research has implications for Indonesian language learning process, which is teaching material by using VAK (Visual Auditory Kinestethic) which is developed to provide practical contributions, especially in the implementation of the learning process for teachers, teaching materials in the form of this module can be additional teaching materials to provide convenience in conveying fantasy story material taught, enriching and increasing students' knowledge about fantasy story so that learning will be more interesting and motivate students, trains students to learn independently.
Aesthetic Aspects of Acting Emotional Experiences in a Scene Role

The aim of this paper is to find out the aesthetic aspects of acting emotional experiences in a scenic role.Research methodology. Methods of analytical and synthetic processing of sources are used (in the study of phenomenological, psychological, special applied artistic literature on this subject); structural and functional and typolo-gical approaches (in revealing the psychological acting “entities” and their relationship in the process of acting emotional experience in the scenic role).Results. It is found out that emotional reactions that arise in the process of experiencing a role differ from life in connection with the fact of distinguishing the person of an actor from his playing, creative “hypostasis”. The analysis of features of the actor’s creative process is carried out. It is argued that getting more and more into the character is an obligatory and integral part of acting. It is found out that the “aesthetic component” of the actor’s activity essentially belongs to the contemplation of the actor of his own emotional reactions. It is observed that the actor’s emotional state is one that does not correlate neither with the state of the character of a role, nor with the person of the actor as a person.Novelty. The aesthetic component of the actor’s experience on stage and the creative process have been revealed.The practical significance. The main provisions and materials of the article can be applied by actors directly in creative work and teachers in the process of training the future actors. The conclusions can be used for further scientific research of various aspects of acting and stage art in general.
HOTEL RECOMMENDATION SYSTEM USING HYBRID TECHNIQUE

Recommendation systems are software techniques used for suggesting items in an automated fashion to users tailored their preferences. Collaborative filtering may be a set of technologies that predict which items during a set of information a specific customer will like supported the preferences of many people. The multi-user based CF will tend to provide accurate recommendations by considering the user preferences in multiple forms and several methods have been proposed and implemented for improving the accuracy of these systems. However, the problem of multi-user recommendations is still considered an optimization problem with single-user and overall rating . In addition, increasing the accuracy in predicting the appropriate items suggested to the user's preferences is one of the main challenges faced in these systems.
Pemberdayaan Perawat dalam Penerapan Nurse Early Warning System untuk Memantau Kondisi Pasien di Rumah Sakit

AbstractSevere adverse events such as cardiac arrest and death are often marked by abnormal vital signs a few hours before the event. Majene Regional General Hospital is the only hospital in the Majene Regency and is a reference center for all puskesmas in the Majene and surrounding districts. As a health service institution that organizes health services, it is closely related to the responsibility of providing emergency services. The Nurse Early Warning System (NEWS) is a development in emergency services for patients treated in hospitals, which serves as an early detection tool so that if there is a decrease in the patient's condition it can be known earlier can be handled more quickly. The purpose of this activity is to increase the knowledge and skills of nurses in the application of the nurse early warning system (NEWS) in monitoring the condition of patients in the care room. The implementation method starts from identifying the problem, delivering material about NEWS, demonstrating the assessment of the patient's condition and the nurse's independent practice in using NEWS. The evaluation results of this activity are the increase in knowledge and skills of nurses using NEWS in monitoring the condition of patients in the care room.
A Survey on Frequent Item sets Mining for Big Data

connects large-volume, complex, and increasing data sets with multiple independent sources. Nowadays, Data are speedily expanding in all science and engineering domains due to the rapid evolution of data, data storage, and the networking collection capabilities. Due to its variability, volume, and velocity, Big Data enjoys the ability of extracting constructive information from huge streams of data or datasets. Data mining includes exploring and analyzing big quantities of data in order to locate different molds for big data. Frequent item sets is one of the most important tasks for discovering useful and meaningful patterns from large collections of data. Mining of association rules from frequent patterns from big data mining is of interest for many industries, for it can provide guidance in decision making processes; such as cross marketing, market basket analysis, promotion assortment, ...etc. The techniques of discovering association rules from data have traditionally focused on identifying the relationship between items predicting some aspect of human behavior;  usually buying behavior. This paper provides a review on different techniques for mining frequent item sets.
METHODOLOGICAL ASPECTS OF DRAUGHTING TEACHING IN TECHNICAL VOCATIONAL EDUCATIONAL INSTITUTIONS

The article, in accordance with the State Standard of Education of branch “Technology”, states that the main purpose of this industry is the formation of technically and technologically educated personality, prepared for life and active work in a modern high-tech information society. Therefore, graphic knowledge and skills today are considered to be one of the factors contributing to the general cultural and professional development of person, his/her readiness for continuous professional growth throughout life.It was found that the study of draughting in vocational educational institutions is connected with mastering of cognition methods, scientific style of thinking, development of intuition and spatial imagination of future professionals; at the same time, it has a humanitarian orientation, is a kind of language of science and technology, forms the spiritual and intellectual sphere of personality.The authors of the article as the aim of scientific investigation define the characteristics of leading concepts (geometric, graphic, projectional, machine-building, systematic, constructional, etc.) and leading methodological aspects of draughting teaching in vocational educational institutions (development of concepts, draughting’s reading, use of manuals and screenplays, etc.).The conclusion of the study was to anticipate the need to create pedagogical conditions to ensure the draughting teaching in technical vocational educational institutions.
Expert System for Identifying Damages of Panasonic NS1000 PABX Devices with A* Pathfinding

Someone can be said to have the ability to handle damage to the Panasonic NS1000 PABX device and perform a configuration of at least 3 years or already have a certificate of competence and training. The problem to be investigated is the number of experts there is only one and can only identify 5 damage per day and 1 day there are 25 damage. PABX Panasonic NS1000 has 30 rules and 130 data symptoms of damage as its knowledge base. This Expert System is designed to identify damage to PABX Panasonic NS1000 mobile application-based applications using the A * (A star) pathfinding algorithm and the forward chaining method with the PHP (Jquery Mobile) programming language and the database using MySQL, as an application program used by PT. Mediatama Anugrah Citra to facilitate the process of troubleshooting and effective problem solving on target. The features in this expert system include the identification of problems, the identification process, up to the achievement of the goal state and solutions effectively, quickly and precisely, the user as the user or admin has its own login and access rights in identifying, entry and editing. In the programming case testing process it can be seen that the application of the A * Pathfinding algorithm with the heuristic function has proven ineffectively implemented in the expert system and the results of the UAT testing process, the respondents agree (above 91.23%) that overall the expert system helps the expert and can deduce damage to PABX devices correctly.
Optimized prediction of solar irradiation based on MPC and ELM neural network

Abstract Based on the characteristics of randomness and instability of solar radiation, this paper presents an optimal prediction algorithm of solar radiation based on Model Predictive Control (MPC) and Extreme Learning Machine (ELM). Firstly, the meteorological factors directly related to solar radiation are selected to determine the input attributes; secondly, the weather forecast and historical irradiance information at the current time are used as inputs, and the irradiance at the current time is used as the output to predict the solar irradiance; finally, the MPC rolling optimization idea is used to realize the optimal processing of solar radiation prediction data. The simulation results show that MPC-ELM algorithm has smaller simulation error than other algorithms, which shows that the algorithm has more advantages.
ANALISIS PENGGUNAAN FRAMEWORK WEBSITE JDIH KHUSUS PERATURAN KEMENTERIAN REPUBLIK INDONESIA

The development of website technology is currently very rapidly developing. In general, the use of websites in government agencies is not new and has become common in government agencies, one of which is in the realm of the ministry. The website is used for various purposes, ranging from information for the public to operational activities. Website about Jaringan Dokumentasi dan Informasi Hukum (JDIH) is a form of implementation of regulations that state that all things about law are public information, so the public must be able to access information related to legal products from the ministry. For this reason, we are trying to identify the framework of each Ministry’s JDIH website using Wappalyzer to analyze how the website distributes its legal products in terms of appearance and features. From this analysis, there is no standardization used on the Ministry's JDIH website.