Reviewerly/exHarmony huggingface dataset:
The Influence of Modern Electronic Media on the Teaching Content of Traditional Design

Objectives: At present, most of the researches on differentiated teaching focus on the theoretical research of differentiated instruction, the demonstration of necessity of differentiated instruction, the implementation process of differential teaching, and the implementation of differentiated teaching. Methods: at present, most of the researches on differentiated teaching focus on the theoretical research of differentiated instruction, the demonstration of necessity of differentiated instruction, the implementation process of differential teaching, and the implementation of differentiated teaching. Results: This paper took computer design course as an example, mainly from three aspects: the simple Bias classification algorithm, the student’s difference performance and the difference teaching. Based on the related theories, a student classification method based on Naive Bayes algorithm was proposed. Conclusion: This paper took computer design course as an example, mainly from three aspects: the simple Bias classification algorithm, the student’s difference performance and the difference teaching. Based on the related theories, a student classification method based on Naive Bayes algorithm was proposed.
Comparison of BEKK GARCH and MEWMA Methods on IDX Composite and Exchange Rate Volatility

At the beginning of 2020, the world was busy with a new virus namely COVID-19. In Indonesia, COVID-19 virus was first identified on March 2nd, 2020. This global pandemic made several impacts. One of the impact is on Country's Economy that can be seen in the decline of IDX Composite and the weakening of US Dollar exchange rate to Rupiah. The movement of IDX Composite and US Dollar exchange rate to Rupiah often increases and decreases every day. This condition can be caused by volatility due to fluctuation. There are several methods to cover the volatility of multivariate data, one of them can be approached using Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) model. In addition to the GARCH model, there is another approach that can also be used to cover volatility data, that is Multivariate Exponential Weighted Moving Average (MEWMA) model. Based on the analysis results of the three training data, it was found that the RMSE of the BEKK GARCH method was greater than the RMSE of the MEWMA method and VAR(2)-MEWMA that be used on the three training data had the consistently volatility predict of IDX Composite return and US Dollar exchange rate to Rupiah return. MEWMA method can be said to have a better predictive ability, so VAR(2)-MEWMA is used to model IDX Composite return data and US Dollar exchange rate to Rupiah return data from November 2019 to August 2021 and is used to predict the volatility of the next month on September 2021. MEWMA model’s ability is quite good in predicting volatility of IDX Composite return data and US Dollar exchange rate to Rupiah return data.
Learn to build cross-platform mobile apps using the ionic framework

In this workshop, participants will learn about the Ionic framework (https://ionicframework.com) that can be used to quickly develop native apps for both Android and iOS using one code base, writte...
Allocation of multi-dimensional distance learning resource based on MOOC data

In order to overcome the problems of allocation balance and low allocation efficiency in traditional distance teaching resource allocation methods, the paper proposes a multi-dimensional distance learning resource allocation method based on MOOC data. This method establishes a network model of MOOC resources, analyses the structure of the MOOC remote teaching platform, and collects MOOC data and learning resource information in layers on the basis of the model. Based on the data collection results, clustering of data resources can be achieved from multiple dimensions. Finally, by calculating the allocation of learning resources, a balanced allocation of multi-dimensional distance learning resources is achieved. Experimental results show that, compared with the traditional learning resource allocation method, the proposed method has a maximum allocation balance of 93% and a resource allocation efficiency of 96.2%.
Learning from Home Satisfaction for Graduate Biology Students in the COVID-19 Era

The study aims to assess the level of satisfaction for Biology master’s students understudying in online learning mode henceforth learning from home at Yogyakarta State University. A structured questionnaire was employed to view student satisfaction around 7 dimensions namely; resource availability and well-operating tools, instructor support & interaction, lesson quality and quality of delivery, assessment mechanism, teaching method, learning environment, and satisfaction. Of 49 students was surveyed and asked to answer questions relating to learning from home experience and the level of their satisfaction. Out of which participants over 80% were females and around 19% males where the major part of them belonged to 21-30 years of age. Data were analyzed using SPSS software and item’s reliability was found higher (over 0.75) that substantiated the reliability of the questionnaire used. Based on calculating the mean and SD, data reveal that students are highly satisfied by the learning from home system. Findings suggest that the implementation of the learning from home program was a very great idea during this dire disease era as the majority of the students supported the initiative. However, the study discovered also that the quality and distribution of internet connectivity, non-updated devices for some students was the main challenge that might be rending online learning more ineffective.
Main Didactic Aspects Related to the Applying of STEM Technology in Science Education

STEM technology is an innovative educational technology. It refers to development of the students’ intellectual abilities, to constructive and cognitive-researching activity and to technical work. There are presented basic didactic aspects, connected with the applying of the STEM technology in Science education. The emphasis is put on practical tasks with problematic character. They allow 21st century competencies to be formed, such as creativity, communication skills, teamwork and critical thinking. Organization of the educational process, educational work forms and teacher’s new pedagogical role are also presented. Educational simulations and robots are looked at as didactic means of putting the STEM technology into practice while studying Science, in particular Physics.
Automata for Dynamic Answer Set Solving: Preliminary Report.

We explore different ways of implementing temporal constraints expressed in an extension of Answer Set Programming (ASP) with language constructs from dynamic logic. Foremost, we investigate how automata can be used for enforcing such constraints. The idea is to transform a dynamic constraint into an automaton expressed in terms of a logic program that enforces the satisfaction of the original constraint. What makes this approach attractive is its independence of time stamps and the potential to detect unsatisfiability. On the one hand, we elaborate upon a transformation of dynamic formulas into alternating automata that relies on meta-programming in ASP. This is the first application of reification applied to theory expressions in gringo. On the other hand, we propose two transformations of dynamic formulas into monadic second-order formulas. These can then be used by off-the-shelf tools to construct the corresponding automata. We contrast both approaches empirically with the one of the temporal ASP solver telingo that directly maps dynamic constraints to logic programs. Since this preliminary study is restricted to dynamic formulas in integrity constraints, its implementations and (empirical) results readily apply to conventional linear dynamic logic, too.
Software Reusability Development through NFL Approach for Identifying Security Based Innerrelationships of Affecting Factors: A Recent Study

This paper has proposing the neural based fuzzy framework based approach to estimate the reusable components which are directly and indirectly involve the security and privacy to improve the quality of the software system. This approach has considered the twenty effecting factors and fifty three attribute matrices. It has formed with three stages of execution scenarios. The first stage has executed with eleven effecting factors and eighteen attribute matrices for identification of supporting software reusability components, the second stage has executed with four effecting factors and thirty five attribute matrices for identification of sub- internal relationships in terms of security-privacy, and the third stage has executed with eight effecting factors and six attribute matrices for identification of sub of sub-internal relationships in terms of security risk estimation. In component based software reusability development process, the software developers have to choose the best components which are self adaptive future to overcome the functional errors, framework mismatches, violation of user level privacy issues and data leakage feasibilities. The software developers can build high quality software applications by taking the consideration of the reusable components which are more suitable to provide high level data security and privacy. This analytical finding proposes a fuzzy logic model to evaluate the most feasible effecting factors that influence the enterprise level data security-privacy practices at real time environment.
Analysis of Vocaburary and Grammar Items in the Spanish I Section of the CSAT(College Scholastic Ability Test)

In this study, the Spanish I Section of the CSAT, which was conducted for 10 years from 2011 to 2020, was the subject of analysis. In particular, in-depth analysis was conducted on the vocabulary and grammar areas where the majority of high-difficulty questions were concentrated. In vocabulary area analysis, 10 questions related to idioms and 8 questions related to multisense words in the vocabulary area for 10 years can be said to increase the difficulty of the vocabulary area. In idiomatic expressions, the more difficult a combination of words had an unfamiliar meaning, the higher the difficulty level, and in polysemic words, when asked for the meaning of the rear rank, the difficulty was higher. In the analysis of the grammar area, we tried to grasp the tendency of the grammar elements that were repeatedly asked, and tried to understand how the difficulty level was increased, focusing on the questions with high difficulty. There were a number of grammatical elements that were repeatedly asked, and most of the high-difficulty questions asked for a grammatically correct or wrong grammatical judgment, and combined response questions were used. It can be understood as a high-level measure to increase the difficulty with the correct answer rate in mind, but while increasing the difficulty, the educational ripple effect of the CSAT and the evaluation of language use should be considered.
Hubungan Motivasi dan Hasil Belajar Terhadap Pembelajaran Matematika di Sekolah Dasar 02 Taeh Bukik

The aim of this research was to find out the significant relationship between learning motivation and learning outcomes in mathematics learning. This study consists of two variables, namely variable X and variable Y. In this study variable X is learning motivation and variable Y is learning outcomes. The type of research used in research is quantitative. The research method used in this study was the correlation study and the population in this study is the fourth-grade students of SDN 02 Taeh Bukik and the sample used in this study was 12th-grade students. The sampling technique used in this study was probability sampling, namely simple random sampling. Data collection techniques used in this study were tests and questionnaires. Data analysis techniques used by researchers to analyze data or determine the assessment of the relationship of motivation variables with student learning outcomes in mathematics using correlation was the product-moment. The result of this study indicated that there was a significant relationship between motivation and learning outcomes on students' mathematics learning at grade IV SDN O2 Taeh Bukit.
The SYSTEM IDENTIFICATION OF FRIEND AND ENEMY USING NIGHT VISION CAMERA ON BATTLE ROBOT (CQB) USING PATTERN RECOGNITION METHOD

Abstract – Indonesian Army has the main task of protecting against enemy attacks, which include forest battles as well as urban battles. The obstacle faced today is that in the process of urban warfare operations, infiltration and hostage rescue in buildings are still less efficient and optimal. The robot is designed with a system that can identify friends and foes using a Night Vision camera and the Pattern Recognition method. Pattern recognition is a symbolic grouping automatically that is done by a computer to find out objects or patterns. The results of the Night vision camera test are able to detect human objects with a maximum distance of 6 meters. This night vision scope has a fairly large accuracy rate of 83%. And light intensity has an influence on the identification process because if the light intensity is more than 200 lux then the system is not able to identify the object.
Educación remota y pandemia: experiencias de padres de familia

The paper presents an analysis of the experiences of parents and emergency remote education, implemented by the Ministry of Public Education (SEP), due to the COVID-19 pandemic. It is a phenomenological investigation, supported by the semi-structured interview, which outlines the use of ICT, through platforms and digital resources, and the process of appropriation by parents in virtual environments; its objective is to investigate what are the challenges they have faced in this period, in order to redefine this information. The work is presented in three sections: in the first, the problem is contextualized; the second presents the theoretical references and instruments used; and the third, the review, systematization and interpretation of the data obtained. The research shows the heterogeneity of the educational environment in public schools, the little recognition of the teaching work, the functions of parents and a task for which they were not prepared. This conjuncture reveals the urgency of reworking the educational model and adapting it to the context, as well as creating educational policies, whose central axes are in the permanent updating, in the immediate attention of deficiencies and needs of the educational actors, and in providing connectivity and literacy digital to all of them.
Automatic detection of cell nuclei from H&E-stained based Marker-Controlled Segmented Histopathological Images

A computer-aided diagnosis system is the most important step for implementing an automated cell nuclei segmentation using cancer cells. Breast cancer is one of the world's major public health issues affecting women. It has two states: benign and malignant. Benign states are slow to develop, rarely spread to other parts of the body, and have well-defined borders. Malignant state, on the other hand, has a tendency to grow faster and is life threatening. Histopathological Images (HIs) are the gold standard for evaluating certain types of tumors for cancer diagnosis. Image segmentation techniques aim to identify and extract foreground objects in an image, resulting in individual segments. Image segmentation is fundamentally different from one type of image to the next because each has its own context and different geometrical properties, posing a challenge in designing a generic algorithmic procedure. In this paper, an effort is made to compare and study the efficiency of colour image segmentation using Fuzzy C-Means Clustering, segmentation using K-Means Clustering, Watershed Segmentation using Gradient, and proposed H&E Stained based Marker-Controlled towards tumor detection segmentation. The analysis concluded that the performance of Watershed Segmentation using Marker-Controlled produced better results than other techniques.
The Impact of Leadership Styles on Employees’ Commitment within Dubai Government Entities: Mediating Effects of Communication

Employee commitment is the essential element especially for the government entities success where employees are not willing to perform and this situation motivates the research to examine employee commitment of the government entities in Dubai. Thus, this study investigated the relationship between leadership styles and employees’ commitment and communication among Dubai government entities. This study also assess the impact of communication on the relationship between leadership styles and employees’ commitment at the Dubai Immigration Department (DID). This study has followed the quantitative methods of data collection and also used the smart-PLS for analysis. The findings revealed that transformational and transactional styles have positive effects on employees’ commitment to DID. Findings also revealed that there is a significant relationship between transformational and transactional styles and communication. A positive effect is also discovered to exist between communication and employees’ commitment. Communication mediates transformational and transactional styles and employee commitment. The original contribution to knowledge is the mediating role communication plays in DID in relation to employees’ commitment. These findings helped to determine the appropriate recommendations for policy and practice in the UAE, as well as suggestions for future research.
LibGuides: Effective Meetings: Increase Productivity, Collaboration, and Innovation: Effective Meetings

If you want to improve your skills to lead effective meetings and be a valuable contributor to meetings, then join us for this workshop.
A Deeper Comparison of Go and Java

This chapter drills down on the earlier introduction of Go vs. Java. It describes in greater detail the significant differences between Java and Go.
The generic structures of the editorials of the Jakarta Post published in August 2020

This study focuses on the analyze the generic structures and language features the editorials of the Jakarta Post to classify the type of exposition text and to know the appropriateness of being teaching material examples in studying a kind of text types. As the subject, six of editorials of the Jakarta Post published in August, 2020 were chosen randomly. The object is the generic structures of the editorials. Then, documentation is used as a technique of data collection to be analyzed and classified by using a book entitled “Text Types” by Mark and Kathryn, and a book entitled “English for Social Purpose” by Jenny Hammond to determine the appropriateness to be teaching material of genre. The results showed each editorial of the Jakarta Post consist of three generic structures, (1) thesis that introduces the topic, (2) series of arguments, (3) Summing up or recommendation as a conclusion that restate editorial writer’s point of view. Based on the features of the generic structures the two editorials belong to Hortatory Text and the rest belong to Analytic Text. All of the editorials also contain four features of a good argument, (1) clearly expressing point of view, (2) using reasons to support the argument, (3) using evidence to prove the argument, (4) showing cause and effect (conclusion) and appropriate to be teaching material.&#x0D; Keywords: Genres; generic structures; editorials; the Jakarta Post. &#x0D;
Going into the Future

In this chapter some likely key future additions to the Go language will be introduced. We will then summarize what we have learned about Go with a presentation of a substantial capstone program, both in Go and Java.
Klasifikasi Penyakit Diabetes Menggunakan Metode CFS dan ROS dengan Algoritma J48 Berbasis Adaboost

Diabetes was a disease that occurs due to high blood-glucose levels. Researchers tried to prevent complications from developing by using data mining techniques. One of the techniques used in data mining was classification. The purpose of this study improves the accuracy of the classification of diabetes for a better and optimal result. The method in this study is Correlation Feature Selection (CFS) as attribute selection, Random Over Sampling to handle unbalanced data and AdaBoost to improve the performance of the J48 algorithm so the result obtained best. Based on the result of this study, showed that Correlation Feature Selection for attribute selection and Random Over Sampling to handle imbalance's class with the Adaboost-based J48 algorithm proved can increase the results of the diabetes classification with an accuracy of 92.3%. For the further research recommended to apply other methods so that the accuracy results obtained are more optimal for comparison.
A Survey on The Use of Social Media as a Medium in Learning Writing Skills

This study aimed to investigate the use of social media as a medium in learning writing skills. The subjects of this survey study were 124 second-year students of the English Study Program, Faculty of Teachers Training and Education, Universitas Riau (2019 batch) selected using the total sampling technique. There were 85 out 124 students who completed the questionnaire. Data were analyzed using descriptive statistics in the form of frequencies and percentages. This study showed that the kinds of social media that are commonly used in learning writing are Twitter, YouTube, Instagram, WhatsApp, and Facebook. Some specific writing skills learned through social media claimed by the respondents included learning new vocabulary, grammatical structure, correct spelling, paragraph development, correct capitalization, correct punctuation, unified ideas, and coherent ideas. Respondents also reported that they used social media for several purposes: adding references and information, taking as learning resources, developing creativity, collecting assignments, conducting online discussion, exchanging learning materials with classmates, and sending material in learning writing skills. It can be concluded social media has been part of significant alternative learning media used by students to improve their writing skills.
Long short-term memory networks for bed position classification

This paper describes an approach of 2 stacked layers of Long Short-Term Memory for bed position classification. The sensor panel data is collected from 2 types of sensors under the 30Hz sampling rate, i.e. piezoelectric and pressure sensors. The data is classified into 5 classes and those data are normalized with min-max scaling on a fixed range between 0 and 1. The model is experimented using window sliding technique for preprocessing dataset with changing the number of hidden nodes in 128, 80 and 50 nodes of the model. The overall accuracy is 94.74% which can be comparable with the previous work.