Reviewerly/exHarmony huggingface dataset:
COMPUTER NETWORK IMPLEMENTATION TO PREDICT FIRM PERFORMANCE

Keeping the iPhone at the center of our discussion, one wonders what would happen to Apple if some other company comes up with an even better range of high-end Smartphones and eventually beats Apple at their own game. Consequently, Apple can start by opening up their store so that some of its services are available on other platforms as well. This will popularize their services among those who cannot afford the expensive iPhones. The net effect of this move would be a greater amount of upcoming customized applications globally, which would boost sales even for the iPhones. Secondly, Apple should consider approaching other reliable companies to manufacture phones running on the iOS platform. Ask why Androids are popular, then you'll meet people who will buy a Samsung Galaxy Note 10 for well over 100 USD yet still run the same operating system as her friend who owns an Oppo F9 worth only 40 USD. This kind of price flexibility without losing out on brand superiority is what Apple needs in order to appeal to many users. Many people perceive Apple products as superior and reliable, and so would easily prefer a phone running on iOS at say 30 USD (even if not an iPhone) compared to an Android phone at the same price. Meanwhile, the firm can sustain its success by utilizing innovation. So far, we have seen how the price of a basic iPhone has increased over the years, with a notable corresponding increase in demand. We were able to single out a doubling in research and development expenses and comfortably attribute this prioritization of resources to the emergence of appealing devices that kept customers eager to buy no matter the price. This, therefore, means that further investment in research and innovation is the key to success.
SMS GATEWAY-BASED EARLY FLOOD DETECTION WARNING SYSTEM DESIGN

Natural disasters that are familiar and often occur around the world, including our country Indonesia one of which is flooding, and not infrequently this also often occurs at night and when the home occupier is not in a place that usually often causes material losses and not infrequently also causes fatalities. This study aims to implement a prototype system that allows to know the possibility of flooding before water enters the area or area of people's homes by using alerts in the form of alarm sounds or sms messages. Which is where this flood-cutting early warning prototype system will use Arduino as a microcontroller that will thoroughly control the ultrasonic sensor as a water level detector and buzzer sensor as a sounder or alarm when the water level has reached a certain limit, Where sms will be directly sent by the SENSOR SIM800L to the citizen's mobile phone or contact number that has been adjusted by the system. So the final result of this small study is that a prototype system of early warning of SMS Gateway-based flood detection will be very helpful for residents to know how the water level will be when entering people's homes.
Concept and Implementation of Online Game-Based Learning Approach in Distance Learning

&lt;p&gt;&lt;em&gt;Education is an endeless learning process either formally or nonformally. To achieve student’s goal, they must develop their potential. This potential can be achieve through learning that is education. In this pandemic situation, student’s doing online learning. But students don’t have any meaningfull learning in this activities. Students have been enamored in online games. The purpose of this study is to describe 1. Online game-based learning approach, 2. Implementation of a online game-based learning in distance learning. The result of this study are: (1) Online game-based learning is a learning approach based on software.; (2) the implementation of the online game-based learning approach in distance learning is combining data collection, system analysis, coding, implementation, and maintenance. The conclusion of this study are online game-based learning is an educational system where teacher can apply an online game for cognitive interest and learning motivation that students need.&lt;/em&gt;&lt;/p&gt;
Change of Critical Thinking Disposition by Applying Learning Portfolio Completion

This study was a similar experimental study that analyzed the effect by applying the learning portfolio completion. The study period lasted from October 1, 2019 to November 20, 2019. A total of 47 people participated in the study, and the effectiveness of the program was analyzed with the SPSS 18.0 program for critical thinking disposition. The statistical analysis method was frequency analysis and paired t-test. As a result of the analysis, the critical thinking disposition increased significantly in the application of the learning portfolio completion (Truth-seeking MD= -0.05, p <0.01), Openmindness MD= 0.11, p <0.001), Analyticity MD= 0.76, p <0.001), Systematicity MD= -.25, p <0.001), Self-confidence MD= -0.54, p <0.001), Inquisitiveness MD= 0.29, p <0.001), Maturity MD= -.0.33, p <0.001). In conclusion, the teaching method applied with the learning portfolio completion actually helped nursing students learn nursing students learn based on critical thinking. Based on these result, further research using learning portfolio is to be done and more systematic and practical application of learning portfolio completion to nursing students. This study would be used as a basic data for the study guideline development for learners.
Wavelet regression for compositional data

Regression for compositional data has so far been largely considered only from a parametric point of view. Recently, some work adapted non-parametric regression to nonEuclidean manifolds. For example, Di Marzio et al. (2013) pursue the circular case, and Di Marzio et al. (2014) the spherical one. In a recent article, Di Marzio, Panzera and Venieri (2015) extended this to nonparametric situations, introducing local constant and local linear smoothing for regression with compositional data. Also, Barientos et al. (2015) propose a Bayesian nonparametric procedure for density estimation for data in a d-dimensional simplex. In our analysis, we extend the work of Di Marzio, Panzera and Venieri to locally adaptive estimators, in particular discrete and continuous wavelets. We rely on the work of Dey and Wang (2004), modeling the priors on triangles by use of wavelets constructed specifically for triangles. We transfer their methodology of deriving father and motherwavelets using a sequential approach to orthogonalization to derive the motherwavelets. Our new estimator is derived for three cases: simplicial-real; simplicial-simplicial; and real-simplicial regression and is based on Bayesian approach using wavelet type priors. We present a detailed statistical elaboration and analysis, simulation results to compare the performance with some existing parametric estimators for compositional data regression, and an application to the results to two case studies from economics– inference for inequality indices and international trade.
IMPLEMENTING CO-CREATION IN DEVELOPING A MOBILE APP FOR COMMUNITY ENGAGEMENT IN HIGHER EDUCATION INSTITUTIONS: PROTOTYPE DEVELOPMENT

IMPLEMENTING CO-CREATION IN DEVELOPING A MOBILE APP FOR COMMUNITY ENGAGEMENT IN HIGHER EDUCATION INSTITUTIONS: PROTOTYPE DEVELOPMENT
THE PANDEMIC-DRIVEN DIGITAL DIVIDEND IN TEACHING: (IN)TANGIBLE ASSETS OR MYTHS?

H. Woellik1, O. Burukina2 1Carinthia University of Applied Sciences (AUSTRIA) 2University of Vaasa (FINLAND)
Blockchain Based Network Access Control (NAC) Management Solution and Architecture

There are many advantages of managing services and products in the cyber security sector through a central system, but this can sometimes be a disadvantage. The adequacy of a cyber security product running on a virtual server is limited by the capacity of the virtual server. It is ideal for cyber security products to operate in a distributed structure so that they can work with redundancy and more reliably. One of these products, the network access control management solution, is a product that checks whether the devices are reliable and includes or blocks them in the network. In this study, the model and architecture of a network access control (NAC) management solution has been revealed by choosing blockchain technology because it has a distributed structure, uses cryptography and hash algorithms, and can be processed with smart contracts.
MOBILE APPLICATIONS - AN EFFECTIVE AND EFFICIENT TOOL FOR DEVELOPING READING SKILLS

T. Kvatchadze1, L. Tavdgiridze1, I. Didmanidze1, D. Aburjania2, K. Tskhvaradze1 1Batumi Shota Rustaveli State University (GEORGIA) 2Batumi Public School (GEORGIA)
Multiple Mutation Strategy of Adaptive Differential Evolution Algorithm Research

In order to solve the problems of premature convergence and search stagnation in differential evolution algorithm, a multi-mutation strategy adaptive differential evolution (MSADE) algorithm was proposed. A multi-mutation strategy selection mechanism based on learning factors is used to select the Gaussian mutation strategy, DE/ Current-to-Best/1 and DE/Best/2 mutation strategy adaptively with the iteration of the algorithm, so as to ensure the rapid convergence of the algorithm while effectively jumping out of the local extreme point, and improve the optimization precision of the algorithm. The experimental results of six standard test functions show that the improved algorithm can effectively solve the problems of precocity and local optimum.
THE IMPACT OF INTEGRATED AUGMENTED REALITY AND REAL ENVIRONMENTAL CONTEXTS ON THE EXPLORATION AND KNOWLEDGE OF 5-6-YEAR-OLD CHILDREN

These days, there has been an increasing focus on research into the application of augmented reality (AR - hereinafter) technologies in preschool education. Different studies reveal how technology affordances including AR increase the educational opportunities of preschool children: toys with AR function, flashcard media promote engagement into learning activities, motivation, collaboration (Yilmaz, 2015, Utami, Rukiyah, Andika, & Sumarni, 2020), interactive platforms, virtual models change the teaching and learning process (Cascalesa, Lagunab, Pérez-Lópezc, Peronac, & Contero, 2012), develop a child’s cognitive and metacognitive processes (Wang, Kinzie, McGuire, & Pan, 2009), help learning natural science in classes, school laboratories, online spaces environments (Song & Wen, 2018). Much less attention is paid to the problem on how to integrate AR technology affordances and real environment objects while creating effective educational contexts that promote experiential, self-directed, inquiry-based educational process of preschool children.The aim of our research is to reveal the impact of educational contexts integrating AR technology affordances and real environment objects to promote exploration and deepen the knowledge of 5-6 year old children. The experiment was performed to determine what kind of exploration is encouraged and what knowledge is promoted in the child by: a) the AR tool iSandbox (experimental group - EG hereinafter) and games in a natural sandbox (control group - CG hereinafter); b) integrated educational contexts with AR and real objects (EG) and educational contexts with real objects (CG).Data collection methods: The observation (video recordings), the interview with the child, the questionnaire to assess the acquired knowledge of children. Data analysis method: a descriptive quantitative analysis.The results of the research revealed that children achieve best educational results when integrated educational contexts are created, which include the possibilities of AR tools and real environment affordances. These educational contexts enable children's self-directed, inquiry-based development of their knowledge.
What You Need to Know About Optical Circuit Reconfigurations in Datacenter Networks

Increasing demand for flexibility in datacenter networks has ledresearchers to propose various designs of adaptable topologies usingoptical circuit switching.However, reconfigurations interrupt data transmissions that can diminishthe benefit of adapting physical networks. The state-of-the-art lacks detailed models of end-to-end reconfigurationcharacteristics of involved networking components like end-host NICs andswitches. The measurements of five commercially available programmable NICs andswitches demonstrate that end-to-end reconfiguration delays indeed exhibitvariability across devices and settings. The results suggest, however, that their behavior can be modeled, whichopens new opportunities for scheduling algorithms.
Computational Analysis of Argumentation Strategies

The computational analysis of argumentation strategies is substantial for many downstream applications. It is required for nearly all kinds of text synthesis, writing assistance, and dialogue-management tools. While various tasks have been tackled in the area of computational argumentation, such as argumentation mining and quality assessment, the task of the computational analysis of argumentation strategies in texts has so far been overlooked.This thesis principally approaches the analysis of the strategies manifested in the persuasive argumentative discourses that aim for persuasion as well as in the deliberative argumentative discourses that aim for consensus. To this end, the thesis presents a novel view of argumentation strategies for the above two goals. Based on this view, new models for pragmatic and stylistic argument attributes are proposed, new methods for the identification of the modelled attributes have been developed, and a new set of strategy principles in texts according to the identified attributes is presented and explored.Overall, the thesis contributes to the theory, data, method, and evaluation aspects of the analysis of argumentation strategies. The models, methods, and principles developed and explored in this thesis can be regarded as essential for promoting the applications mentioned above, among others.
Relevance Weighted LDA for Linear Dimensionality Reduction

When taking care of an example characterization issue, it is entirely expected to apply a highlight extraction technique as a pre-handling strategy, not only to diminish the calculation multifaceted nature, however, possibly also to get better classification execution by reducing insignificant and repetitive data in the information. The linear discriminant analysis (LDA) is one of the most traditional linear dimensionalities decrease techniques. This paper fuses the between class connections as significance loads into the estimation of the by and large inside class dissipate framework in request to improve the presentation of the fundamental LDA technique and a portion of its improved variations. Authors exhibit that in a few explicit circumstances the standard multi-class LDA nearly totally fails to locate a discriminative subspace if the proposed pertinence loads are not consolidated. So as to appraise the pertinence loads of individual inside class scatter matrices, authors propose a few techniques for which one utilizes the advancement systems.
English Pedagogy for Student with Emotional and Behavioral Disorders In An Inclusive School

Inclusive school is a public school that the student with special needs can be educated together with normal students. Expanding the potential that they have through the appropriate teaching strategies is crucial to implement, especially for the student with EBD. The student with EBD is a student that has aggressive behavior and substantial negative influence in the learning process. In accordance to that, the researcher wants to investigate (1) the teaching strategies used by the English teacher for the student with Emotional and Behavioral Disorders (EBD), (2) the implementation of teaching strategies used by the English teacher for the student with Emotional and Behavioral Disorders (EBD). Using qualitative method, the research involves one English teacher of SD Satu Atap Sumbersari 1 Malang Inclusive School. The instruments used were observation and interview. The current research revealed that there were three strategies used by the English teacher at SD Satu Atap Sumbersari 1 Malang Inclusive School. First, the teacher shows the interest towards students’ progress through communication to the student with EBD. Second, giving the student an understanding to have control for everything occurring in their life by giving the student with EBD punishment when break the rules. Third, conducting class activities relevant to students’ interest with alternative activities made by the English teacher.
Multi-Scale Feature and Metric Learning for Relation Extraction

Existing methods in relation extraction have leveraged the lexical features in the word sequence and the syntactic features in the parse tree. Though effective, the lexical features extracted from the successive word sequence may introduce some noise that has little or no meaningful content. Meanwhile, the syntactic features are usually encoded via graph convolutional networks which have restricted receptive field. To address the above limitations, we propose a multi-scale feature and metric learning framework for relation extraction. Specifically, we first develop a multi-scale convolutional neural network to aggregate the non-successive mainstays in the lexical sequence. We also design a multi-scale graph convolutional network which can increase the receptive field towards specific syntactic roles. Moreover, we present a multi-scale metric learning paradigm to exploit both the feature-level relation between lexical and syntactic features and the sample-level relation between instances with the same or different classes. We conduct extensive experiments on three real world datasets for various types of relation extraction tasks. The results demonstrate that our model significantly outperforms the state-of-the-art approaches.
An Analysis of Early Reading Ability of Class 1 in Elementary School

This study aimed at describing students’ ability of early reading in SD Negeri 3 Ubud. This is a qualitative descriptive research. The samples were all of class I in total of 22 students comprising of 11 males and 11 females. The data were collected by using observation sheet and test of early reading ability. The data were analyzed by using Likert scale. The research finding showed that students’ ability of early reading of class I in SD Negeri 3 Ubud was categorized as good (B) with 85% percentage.&#x0D;
hub at SemEval-2021 Task 5: Toxic Span Detection Based on Word-Level Classification

This article introduces the system description of the hub team, which explains the related work and experimental results of our team's participation in SemEval 2021 Task 5: Toxic Spans Detection.The data for this shared task comes from some posts on the Internet.The task goal is to identify the toxic content contained in these text data.We need to find the span of the toxic text in the text data as accurately as possible.In the same post, the toxic text may be one paragraph or multiple paragraphs.Our team uses a classification scheme based on word-level to accomplish this task.The system we used to submit the results is ALBERT+BILSTM+CRF.The result evaluation index of the task submission is the F1 score, and the final score of the prediction result of the test set submitted by our team is 0.6640226029.
DISTRIBUTION OF DROUGHT IN THE WATERSHED JENEBERANG UPSTREAM, SOUTH SULAWESI

In the dry season, there is a significant decrease in the intensity of rainfall which will have an impact on a prolonged drought. This can result in a significant decrease in water discharge which affects the quantity of water available. The impact of the long drought was felt, such as dry rice fields, cracked soil, 33.188 ha of agricultural land experienced crop failure in 2019, water needs were only met 35% and many others. This study aims to see the distribution of drought levels in the Jeneberang upstream watershed by using Remote Sensing data and geographic information systems. The focus of this research location covers all the upstream areas of the Jeneberang watershed, starting from the Bili-Bili dam towards the upstream watershed. Remote Sensing and Geographic Information System (GIS) data can be used to detect areas of potential drought. Remote Sensing data can be used to identify the characteristics of the water content and the percentage of potential latent heat on the surface of the earth using the NDLI (Normalized Difference Latent Heat Index) transformation. The results of the NDLI transformation on the image produce very diverse values, so the values ​​are grouped using the Natural Breaks method. The results of the latent heat index transformation produce spectral values ​​between -0.0817 to 0.0829. The results are then divided into 5 classes with very low, low, moderate, high, and very high categories. In the Jeneberang upstream watershed, the widest potential for drought is in the low category with a percentage of 55.92% spread over 9 sub-districts in the Gowa Regency.
Subjective evaluation of traditional and learning-based image coding methods

We conduct a subjective experiment to compare the performance of traditional image coding methods and learning-based image coding methods. HEVC and VVC, the state-of-the-art traditional coding methods, are used as the representative traditional methods. The learning-based methods used contain not only CNN-based methods, but also a GAN-based method, all of which are advanced or typical. Single Stimuli (SS), which is also called Absolute Category Rating (ACR), is adopted as the methodology of the experiment to obtain perceptual quality of images. Additionally, we utilize some typical and frequently used objective quality metrics to evaluate the coding methods in the experiment as comparison. The experiment shows that CNN-based and GAN-based methods can perform better than traditional methods in low bit-rates. In high bit-rates, however, it is hard to verify whether CNN-based methods are superior to traditional methods. Because the GAN method does not provide models with high target bit-rates, we cannot exactly tell the performance of the GAN method in high bit-rates. Furthermore, some popular objective quality metrics have not shown the ability well to measure quality of images generated by learning-based coding methods, especially the GAN-based one.
Educational Process in Higher Education Institutions in the Context of the COVID-19 Pandemic

In 2020, almost all nations face a pandemic of COVID-19 coronavirus infection, including Russia. This virus has affected all spheres of social life, not excluding the field of education, and has required radical changes. The COVID-19 pandemic has given a strong impetus to the transition to a new education format, so students in higher education institutions have moved to a distance-learning format. With the transition to a new format, educational institutions had to face many difficulties, mainly the lack of experience and practice of mass introduction of remote access technologies to provide and receive educational services. At the same time, tremendous work has been carried out in Russia to amend the existing legislation on education, improve methods of regulating and controlling the educational process and the quality of education