Reviewerly/exHarmony huggingface dataset:
Hierarchical Pooling Based Extreme Learning Machine for Image Classification

In this paper, a Hierarchical Pooling based Extreme Learning Machine (HPELM) is proposed for image classification. Extreme Learning Machine based on Local Receptive Fields (ELM-LRF) has been proved to be powerful for image classification. However, ELM-LRF is a shallow network and the features extracted by ELM-LRF is low-level. To obtain better results, one need to enlarge the dimension of the hidden features. This paper extends the concept of deep learning to ELM-LRF. Random convolutional nodes and hierarchical pooling structures are constructed for capturing high level semantic features. HPELM has the ability of feature extraction and classification. It improves the classification performance of ELM-LRF without increasing the number of the neuron in the last hidden layer. Experiments on the MNIST and NORB datasets demonstrate the attractive performance of HPELM even compared with the state-of-the-art algorithms.
Putting Artificial Intelligence to Work: The Operator Decision Aid

Advances in artificial intelligence and data analytics have unlocked new opportunities for progress in critical areas within the maritime domain. Over the past year, the U.S. Navy has initiated an Operator Decision Aid pilot project to apply rules-based navigation algorithms developed by the U.S. Defense Advanced Research Projects Agency (DARPA) and Office of Naval Research (ONR) to provide real-time recommendations to watch-standing teams on the Bridge and in the Combat Information Center. Recognizing the complexity inherent in the employment of artificial intelligence-based solutions, this paper will apply a multifactor framework developed by Crawford and Pollack (2004) to evaluate influential aspects of the project required to drive change, embrace complexity, and institute a culture of learning.
Author Correction: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
OPOSISI BINER DALAM INTERAKSIONISME SIMBOLIK PADA CERITA PENDEK “TENTANG PEREMPUAN (TPT)” KARYA BENNY ARNAS

This article discusses about the short story of TPT by Benny Arnas. It uses the concept of symbolic definition of George Herbert Mead’s perspective of symbolic interactions involving mind, self, and society. The definition of the symbol, in this case, must be the same among participants. If there is any difference, it would potentially raise conflicts and the dissimilarity of the symbol definition would be described. The method used in this data analysis is descriptive-analysis. The result shows that there is binary opposition towards symbol meaning in the interaction among participants. It reveals that there is a conceptual conflict about the characters’ point of view on the same symbols.
SELF-REGULATED LEARNING IMPLEMENTED BY THE STUDENTS OF VOCATIONAL HIGH SCHOOL

This study aimed at identifying whether the students of vocational high school in Buleleng sub-district have implemented self-regulated learning or not. Besides, analyzing the mostly implemented aspects of self-regulated learning was the other purpose of this study. The subject of this study were 405 students of vocational high schools in Buleleng sub-district. There were SMKN 2 Singaraja, SMKN 3 Singaraja, and SMK Triatmajaya Singaraja. Descriptive qualitative was used as the design of this study. Some instruments were used, such as questionnaire, observation checklist, and interview guide. The result of this study showed that self-regulated learning has been implemented by 75% vocational high schools students. Besides, there are three aspects which mostly implemented by students of vocational high school, they are self-control, self-judgment, and self-reaction based on Zimmerman cyclical phase theory
APLIKASI DELIVERY ORDER MAKANAN DAN MINUMAN BERBASIS WEB PADA RESTORAN MANG KABAYAN

The utilization of smartphone technology in various aspects has now been felt, without exception reaching restaurants that want to use technology for the satisfaction of customers and the benefits of restaurants. Humans in general want everything to be easily done, as well as restaurant customers who want to order menus easily in the sense that it is not complicated and does not take a long time. It's easy to order the menu in question without having to queue and without waiting for the waiter to be busy with other customers. Restaurant customers can also take time to order orders according to their needs so they are not disturbed by the presence of a waiter who is waiting for the order. The preparation of this study uses two research methods, namely, data collection methods and software development methods, namely using the waterfall method. To overcome the problems that the authors describe, a web-based application is made to make it easier for restaurants and customers to order food. With the use of media websites that have been published can facilitate food ordering in real time.
ENGLISH TEACHING INSTRUCTION FOR NON-ENGLISH LEARNERS

The quality of educational institutions is influenced by teaching and learning process that is students and lecturers.Novalita (2006) state that to learn a language the learners need more than just once or twice, but they need many time to understand the language, the real meaning of the language, the structure of the language, and so on.There is no good strategies in teaching process, but suitable strategy which is can be used in the teaching process.Therefore, every teacher or lecturer should master many strategies in the teaching and learning process.Some strategies can be applied to some students or learners, but it can't be applied to all of students or learners.he goal of this study is to observe how the teacher implements English teaching instruction at English language center (PKPBI).Besides that, what are the material used and the way how teacher evaluates and also how do the learners perceive the English teaching instruction at English language center (PKPBI) of Maulana Malik Ibrahim state Islamic university of Malang.This study was a qualitative research because this study is a case study which focuses on teaching process.The data collections used in this study were observation, interview, and documentation.In order to analyze the data collected in the research project and answer the core questions of the study, it was used the grounded theory.The researcher found that the contents of the material used was reading section characterized by provision of an English reading text on mathematic-content-related area followed by writing exercises.The teacher implement English teaching instruction with the aim of answering the question, it can be concluded that for the beginning of teaching, there were a big amount of mistakes with the guidance and no explicit implementation of grammatical aspects during the lessons, because the teacher intents to present language items as in a regular language course.The balance between content and language was not easy to manage either, because in some situations the teacher tends to focus more in language or in content.The teacher evaluate by her choice of evaluation.She felt confused and scared at the beginning of the experience.About perceiving of the learners, the researcher concluded that the students feel challenging with the process of teaching and learning in the class, they also interesting with because they can continued applied what they learn.
Improving the Quality of Stego Image Using Prediction Error and Histogram Modification

The transmitted information on the internet are prone to security concerns.To overcome this issue, some security methods have been developed in the last few decades.One of the reliable techniques to secure data is called data hiding.This method can be used in various multimedia data, like image, video, text, and audio.Histogram shifting (HS) is a reliable data hiding method used in digital images.It can preserve the similarity of the stego and original image; although, the amount of the protected data depends on the frequency of the most amount pixel in the original image.To solve this problem, we combine HS with prediction error (PE).By using the histogram generated by PE, the size of data that can be embedded increases.In the embedding phase, we do not shift the histogram, different from the existing methods.It is to maintain its original form as high as possible.Moreover, each PE value can contain more data.Based on the experimental result, the average increase in PSNR is 24.8075 dB for general images and 21.5625dB for medical images; while the average improvement of SSIM is 0.026823 and 0.022863 for general and medical images, respectively.
Data Mining untuk Nasabah Bank Telemarketing Menggunakan kombinasi Algoritm Naïve Bayes Dan Algoritma Genetik

The strategy used for telemarketing by conducting promotional media, this strategy is a marketing method used by banks, in offering products to customers, banks, one of the products that will be offered is time deposits, the bank has difficulty in knowing the obstacles experienced by customers in making a decision to make deposits against the bank, so that later it will have the effect of a financial crisis at the bank. Telemarketing banks must have targets for customers, where customers have the potential to join one of the bank's products, namely deposits by looking at existing customer data.With the existing problems will be overcome by the datamining technique that will be used for this research is the Naïve Bayes algorithm and genetic algorithm which aims to predict the Telemarketing customers' sources sourced from public UCI Repsitory data so that the bank offers a product to the customer right at the target. Naïve Bayes test with experimental results of 86.71% accuracy while cross validation testing using Genetic algorithm produces high accuracy 90.27%, Root proves the prediction of time series data Naïve Bayes method and Genetics produces an accuracy of 90.27%, so it can be concluded that using the Naive Bayes algorithm and Genetics can optimize in predicting Telemarketing client decisions right in the deposit offer.
THE IMPLEMENTATION OF KNOW-WANT-LEARN (K-W-L) STRATEGY IN TEACHING READING AT ELEVENTH GRADE OF SMA NEGERI 3 SINGARAJA

This study aimed at describing the implementation of Know-Want-Learn (K-W-L) strategy used by one of the English teachers in SMA Negeri 3, Singaraja, Bali. In this study, the subjects of the study were the students of SMA Negeri 3 Singaraja especially the eleventh grade, and, an English teacher. The present study employed qualitative design. The methods of data collection were classroom observation and, questionnaire. The findings showed that there were 3 stages of the implementation of Know-Want-Learn (K-W-L) strategy in SMA Negeri 3 Singaraja namely pre-teaching, whilst-teaching and post-teaching. There were several activities from each stage. In pre-teaching, teachers prepare teaching materials and also media to implement K-W-L strategies. In whilst-teaching, in this stage the teacher implements steps from K-W-L. The result of the questionnaire, showed that Know-Want-Learn (K-W-L) strategy is one of the brilliant alternative strategy that could be used by teacher, because KWL (Know, Want, Learn) developed some ideas about the text before reading the whole text, and focus on finding the important points of the text. It means before the student starts to read the text, they need to use their prior knowledge and continue to set their want or interest of the text.
Credit Card Fraud Detection Using Random Forest and Local Outlier Factor

With the evolution of new technology, the use of credit cards has augmented. As credit card becomes the trendiest style of payment for online payment as well as manual payment, the numbers of credit card frauds are increasing day by day. It is necessary to curb the credit card frauds as it causes huge amount of financial loss. Many modern techniques based on Artificial Intelligence, Data mining, Machine Learning, Sequence Alignment, Genetic programming, etc are available that can be used in detecting the fraudulent transactions. We have used machine learning based algorithms. Machine Learning is a subset of Artificial Intelligence. It is a scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using any explicit instructions, relying on patterns and inference instead. Machine learning is the technology in which we train the machine by using various algorithms and make the machine capable enough to take its own decisions. Machine Learning consists of many algorithms that can be used in fraud detection such asRandom Forest, Local Outlier Fraction, Isolation Forest, Naïve Bayes, K-nearest Neighbour, Hidden Markov Model, Neural Networks, etc that can be used in fraud detection.In this paper we have done comparative study of Random Forest algorithm and Local Outlier Factor.
The Effects of Simulation-Based Learning Using Virtual Reality in Nursing Student: A Meta-Analysis

Purpose: This study is a meta-analysis to assess the effect of simulation-based learning using virtual reality (VR) on knowledge, affective, and performance domain outcomes of learning in nursing students.
PECULIARITIES OF VARIOUS TYPES OF CIVIC IDENTITY

Aim. The aim of the research is to determine the psychological peculiarities of citizens with various types of civic identity.&#x0D; Methods. 190 Ukrainian citizens were interviewed about their relations with parents (or guardians) in the childhood , features of family upbringing, priority values of the parents' family, experience of interpersonal relationships with peers, participation in school/student activities, lifestyle, etc. The following psycho-diagnostic techniques were also used: questionnaire "Level and Type of Civic Identity" (Petrovska, 2018); "World Assumptions Scale" (Janoff-Bulman, adapted by Padun &amp; Kotelnikova, 2008); "Portrait Values Questionnaire" (Schwartz, adapted by Semkiv, 2013); "Interpersonal Trust Scale" (Rotter, adapted by Dostovalov, 2000); questionnaire "Level of Social Frustration" (Vasserman, 2004); "Social Activity Scale" (Lewicka, adapted by Cholij, 2010).&#x0D; Results. The typology of citizens ("devoted", "moderate", "disappointed", "indifferent" and "alienated") was created in accordance with the specificity of the formation of civic identity components (cognitive, value, affective, behavioral). Significance (value)/insignificance, positive/negative attitude towards belonging to the state and community of citizens and forms of activity/inactivity in relation to the state and citizens made up the basis of the classification. Also, psychological peculiarities of citizens with foregoing types of civic identity were determined.&#x0D; Conclusions. The main factors in the formation of a certain type of civic identity are basic beliefs (in particular, the justice of the world, the ability to control the events of one's life and self-value); civic behavioral patterns of reference persons (including civic attitudes of reference persons); social integration and social acceptance (experience of interpersonal relationships with peers); subjectness activity (defending own position, wide range of interests, initiative, active participation in many events); value-semantic orientations (in particular, universalism, self-regulation, safety, tradition); prosocial focus (focus of activity on socially useful affairs); social trust; the fact of meeting the needs of physical and social existence in the state (level of social frustration); experience of interaction with the state in the form of its various agencies.
A DESCRIPTIVE STUDY OF THE TEACHER’S TECHNIQUE ON CONTROLLING THE STUDENTS’ MISBEHAVIOR IN SMPN 1 SUKASADA

Students in this era were already being in touch a lot by technology. This is one of the reasons why students in this era were called as digital native students. The purpose of this research was to know the impact of using digital game to improve the digital native students’ English learning. Sample of this research were 25 elementary school students that chosen using lottery and they divided into 5 groups based on the digital local story game that they would play. Pre-test, post-test and interview were conducted to measure the improvement of students’ English learning. The result of the pre-test and post-test showed the significance difference in the students’ score. The result of the study showed that digital games can improve digital native students’ English skill.
Novel Framework for Proposed Intelligent Examination System

Objectives: Developing a computer-based system for examinations is the substitute for the current examination system based on paper.In recent days, the E-learning has become more popular because of its adaptability, integrity and user friendliness.In terms of the paper-based examinations, major challenge is the proctoring techniques used.In this paper, a novel method to avoid the presence of a proctor throughout the examination is proposed by an intelligencebasedexamination system.Methods: The system is designed with different complexity levels among the questions and also it acts as a tool for assessing the understanding of a student from the teaching materials.This method is proposed to improve the E-learning using intelligent question banks and examination system.Findings: This system can be timesaving and more efficient with an adequate level of security.The proposed methodology can be classified into two main phases such as the design of question bank along with its database, the design of the Artificial Intelligence based system for examination and its evaluation in order to improve the e-learning.Applications/Improvements: Future works in this system can be improved with the addition of theory-based questions and the integration of biometric based systems for enhancing the level of security.
Blind Image Quality Assessment Based on the Use of Saliency Maps and a Multivariate Gaussian Distribution

With the widespread use of image processing technologies, objective image quality metrics are a fundamental and challenging problem. In this paper, we present a new No-Reference Image Quality Assessment (NR-IQA) algorithm based on visual attention modeling and a multivariate Gaussian distribution to predict the final quality score from the extracted features. Computational modeling of visual attention is performed to compute saliency maps at three resolution levels. At each level, distortions of the input image are extracted and weighted by the saliency maps in order to highlight degradations of visually attracting regions. The generated features are used by a probabilistic model to predict the final quality score. Experimental results demonstrate the effectiveness of the metric and show better performance when compared to well known NR-IQA algorithms.
Xeggora: Exploiting Immune-to-Evidence Symmetries with Full Aggregation in Statistical Relational Models

We present improvements in maximum a-posteriori inference for Markov Logic, a widely used SRL formalism. Inferring the most probable world for Markov Logic is NP-hard in general. Several approaches, including Cutting Plane Aggregation (CPA), perform inference through translation to Integer Linear Programs. Aggregation exploits context-specific symmetries independently of evidence and reduces the size of the program. We illustrate much more symmetries occurring in long ground clauses that are ignored by CPA and can be exploited by higher-order aggregations. We propose Full-Constraint-Aggregation, a superior algorithm to CPA which exploits the ignored symmetries via a lifted translation method and some constraint relaxations. RDBMS and heuristic techniques are involved to improve the overall performance. We introduce Xeggora as an evolutionary extension of RockIt, the query engine that uses CPA. Xeggora evaluation on real-world benchmarks shows progress in efficiency compared to RockIt especially for models with long formulas.
APLIKASI PENGOLAHAN DATA PUSKESMAS (PUSAT KESEHATAN MASYARAKAT) DESA MARGODADI KAB. TULANG BAWANG BARAT

Health care community is one of the social facilities that uses the developing information technology. The development of this information technology can be seen on the development of clinics and hospitals because they have developed the computerized systems. The access to the contents of the data is done by computerizing so that it will facilitate the data processing, saving time, effort and costs. The method used in this research was through Waterfall. This Waterfall method consisted of communication, planning, modeling, construction, deployment. The data collecting techniques used in this research were interview, observation and literature study. The implementation of this method was by the system analysis, the context diagram, the DFD, and the table relationships. To design and create this application used Netbeans 7.1.2, Java programming languages, MySql databases, and Xampp Webserver, The implementation of this application for the data management of the community health center in the Margodadi Village was able to help the data recording, the data processing, and the report making done by the staffs so that the administrators were able to search the data in this application. Keywords: Information System; Community Health Service Margodadi; Waterfall
PERANCANGAN APLIKASI PENJUALAN RETAIL BERBASIS DEKSTOP PADA CV. HAMBALI KOPERPU

CV. Hambali Koperpu is a business in the field of drinking water, the existing sales system is still conventional, namely buying and selling transactions to the manufacture of transaction reports and customer data still using the book media recorded in each transaction, besides that it also often causes some problems due to files that lost With the use of computer technology that is using a special program created at CV. Hambali is a desktop application for Drinking Water Retail Sales Program and is designed using Microsoft Visual Basic 6.0 programming language and MySQL database as a data base server, with this application facilitating business activities in CV.Hambali and minimize errors that may arise in conventional systems.The transaction process to making reports and customer data can be resolved properly so that it resolves the problems that exist in the CV.Hambali Koperpu.
Comparative Study: Implementing Numbered Heads Together and Team Games Tournament to Enhance Students' Knowledge on Passive and Active Voice Construction

This study intends to find out what is the initial knowledge of the students before they were treated using Numbered Heads Together (NHT) and Team Games Tournament (TGT), ascertain of the significant difference between these two teaching strategies, and to know the responses of the students after they taught using Numbered Heads Together and Team Games Tournament are the aims of this research. This is a quantitative study with comparative design to know the students' knowledge of active and passive construction test. The research instrument of this study is pre-and-posttest. This study was conducted among seventh-grade students at SMPN 10 Cimahi. The results of this study showed that the initial score for both respondents is quite similar to the score for NHT group is 59.07 and for TGT group is 58.33. It is also known that there is a significant difference in students' knowledge on active and passive voice construction between students who are taught with Numbered Heads Together and those who are taught with Team Games Tournament showed by the result of the mean differences from both groups are 0.005 &lt; 0.05. The questionnaire's result also supports that both teaching strategies are eligible to be applied in teaching active and passive voice construction with the score for NHT class is 64.83% and for the TGT class is 63.34%, it can be categorized as "Good". It implies that the implementation of Numbered Heads Together and Team Games Tournament enhances student's knowledge of active and passive&#x0D;