Reviewerly/exHarmony huggingface dataset:
Design and Implementation of Model Predictive Controller

The precise position control of a DC servo motor is a major concern in today's control theory.This work presents position following and forecast of DC servo engine utilizing an alternate control technique.Control technique is required to limit and diminish the consistent state error.A model predictive controller MPC is utilized to plan and actualize these prerequisites.Two sorts of controlling techniques are presented in this task.The Active Set Method (ASM), the inside point technique (IIP), and have been utilized as controlling strategies.This work distinguishes and depicts the plan decisions identified with a two sorts of controllers and judicious regulator for a DC servo motor.Execution of these regulators has been confirmed through reproduction utilizing MATLAB/SIMULINK programming.As indicated by the recreation results the Comparisons among ASM, IIP.The tuning strategy was increasingly proficient in improving the progression reaction attributes, for example, decreasing the rise time, settling time and most prominent overshoot in Position control of DC servo motor.
Improving Students’ Reading Comprehension by Using SRYPHOMAT at the Second Grade Students of SMP, Nur Karya Makassar

The objective of the research is to find out whether or not the use of SRYPHOMAT reading strategy can improve the reading comprehension at the second grade students of SMP Cipta Karya, Makassar.This research applied pre-experiment method which one class was given pre-test, treatment and post-test.The population of this research was the second grade students of SMP Cipta Karya Makassar.The total sample consisted of 32 students and it used purpose sampling technique.The instrument was reading comprehension text in order to measure the students reading skill in learning process by using SRYPHOMAT reading strategy.In other words, the finding indicated that by using SYPHOMAT reading strategy in teaching reading comprehension was able to improve the students' reading skill.Based on the results of the data showed that there was a significant difference of the students' achievement in reading, where the mean score of post-test was higher than the pre-test (67.18>35.78).The result of the data analysis, SYPHOMAT reading strategy can improve the students' reading skill and it is an affective activity to make the students active in learning reading comprehension.Based on the finding of the research it could be concluded that the use of SRYPHOMAT reading strategy improved the students' reading comprehension at the second grade of SMP Cipta Karya Makassar.
Pedagogical Causes Of School Failure

During school years, students succeed to face, in a higher or lower extent, the school requirements.School results influence the student's position in the class he/she is part of, in the circle of friends, in the family etc.In its turn, school is appreciated in the community according to the results of the students who are attending it.The unsatisfactory learning results obtained by certain students, reported to their real potential and to the school exigencies represent forms of school failure.The causes of school failure are manifold.There is a series of objective or subjective factors which favour school failure.School has the responsibility to identify these factors and to frame effective prevention and control strategies of school failure.The present paper highlights the pedagogical causes of school failure, analysed from three perspectives: the teachers, the parents of students who face learning difficulties and that of the students who register low school performance, reported to their potential.In this research, there were 135 interviewed people out of which: 45 teachers, 45 parents and 45 students.The paper has tried to identify the main pedagogical causes which determine the school failure and to present effective solutions for the prevention and control of school failure based on the proposals stated by the participants in the research.
Morphological Computing of Cognition and Intelligence, MORCOM 2021-Online Conference

The theme of the conference, &ldquo;Morphological Computing of Cognition and Intelligence&rdquo; (MORCOM 2021), focused on the unconventional forms of computing, which bring the promise of more efficient intelligent and cognitive computing. The present editorial, written by the organizers of the conference, reports the ideas and goals of MORCOM 2021 and provides an overview of the contributions.
An Analysis of English Schooling at College Quality Based on Modern Information Technology

The importance of learning English is increasing as China’s foreign exchanges become more frequent. China’s independent colleges have been steadily growing in recent years, with the main school’s main characteristic of cultivating applied talents, and teaching quality gradually improving. College English teaching is a practical application of college English education and instruction. The “sum of beliefs, recognized values, and technologies commonly accepted by the members of a specific community” is the world outlook and mode of behavior that a group of researchers engaged in a particular science adopts. Modern information technology has pervaded people’s work and lives since the dawn of the information age, and it is now widely used in a variety of fields. Teachers’ primary roles have shifted from disseminator of information, presenter of knowledge, transmitter of culture, and provider of correct answers in today’s learning environment supported by modern information technology to promoter of learning, organizer of activities, student helper, and interactive collaborator. This paper obtains some information useful to the development of teaching work based on the data mining algorithm used in the mining practice of the educational administration information management system. This information is useful for improving teaching quality, implementing the talent development program more effectively, mastering student skill development, and teachers’ teaching situations.
Effect of marketing communication and information sharing on performance of small and medium-sized enterprises (SMEs) in Thailand

The objective of this study is to examine the role of marketing communication and information sharing in firm performance. In this direction, the relationship between marketing communication, information sharing, customer retention, customization and firm performance is examined. A survey instrument was preferred in this study for data collection. A questionnaire was designed by using already revealed scale items related to the marketing communication, information sharing, customer retention, customization and firm performance in previous studies. 500 questionnaires were distributed among the employees of small and medium-sized enterprises (SMEs) in Thailand. Data were analyzed by using statistical tool; Partial Least Square (PLS). It is found that marketing communication has positive effect on customer retention which further lead to the firm performance. Additionally, information sharing has positive effect on customization which lead to the firm performance. Therefore, marketing communication and information sharing has central importance to promote SMEs performance.
A Research on Image Dehazing Technology for Image Enhancement

Image defogging is to study the method of image enhancement in foggy weather with low definition and lighter color.Image defogging technology aims to improve image contrast and scene clarity, and has broad application prospects in the fields of target recognition, traffic navigation, and remote sensing.Three defogging algorithms in image defogging technology are introduced based on the current research status: global histogram equalization, local histogram equalization, and Retinex algorithm.This article introduces the main steps of the three algorithms and discusses the advantages and disadvantages of each algorithm.Finally, the processing results of these three algorithms are compared and comprehensively evaluated.
Socio-Emotional Development Of Students In The Context Of The Covid-19 Pandemic

The work "Socio-emotional development of students in the context of the COVID-19 pandemic" is based on the application dimension, on how to capitalize on the relationship between the online educational environment and the socio-emotional development of high school students, but also to highlights the complex mechanism of the online learning process, which influences the development of empathy, tolerance in communication and interrelationships.This approach aims to present to teachers solutions and methods by which they can capitalize on digital learning and development, the link between the pandemic context and the socio-emotional development of students, with direct effects on the adaptation of preadolescents to the culture of global society, building a digital identity and a digital well-being.This study also took into account the growing awareness of educators about the need for interconnection and adaptation to the demands of today's society availability for cooperation and collaboration and active involvement in global teamwork and professional networks through constructive and reflective dialogue.Emphasis is also placed on the complex mechanism that exists between emotional development and learning, which are the solutions adopted by educators, but also viable strategies used in the work at the department both online and offline on dysfunctional emotional processing in middle school students.
Classification of Facial Expression Using Principal Component Analysis (PCA) Method and Support Vector Machine (SVM)

Classification is a process to assert an object into one of defined categories. This study examines the classification of recognition of student’s facial expression during digital learning –indifferent and serious expression. The dataset used was from a vocational school -SMK Muhammadiyah 2 Bantul. This study used the combination of algorithm: Principal Component Analysis (PCA) and Support Vector Machine (SVM) to increase the accuracy. This study aims at comparing the performance of combination of two algorithm: (PCA to SVM) and (PCA to k-NN). The result states that the combination of PCA-SVM algorithm is higher than the combination of PCA-k-NN algorithm with the average accuracy of 96% and 89%.
Cognitive-pragmatic programs theory intentional aspect: General provisions (Article 1)

The article offers a conceptual understanding of the intentional aspect of the original author's theory of cognitive-pragmatic programs (CPP). The article investigates the intentional parameters of the transition of the CPP generator (subject-source) to purposeful activity that is embraced as a “text” in the space of his cognitive consciousness. It is noted that in the context of the CPP theory, the concept of intentionality gets its own actualization. Intentionality is a specific orientation of the volitional and psychoemotional aspirations of the subject-source (generator of the CPP) / subject-interpreter. This orientation is realized as an intention that generates an intention and received the form of a signal. The concept of “signal” at the stage of the formation of the CPP acts as an externally manifested informative incentive to a certain (textual) activity. There is a zone of the potential transition of the intention into the signal with its subsequent realization in one or another semiotic form between the intention and the signal (the realized intention). The condition for this transition is a stimulus-impulse. Based on the specifics of the impulse-stimulus, the intention has three forms of realization, and as a result, three types of signal are possible: signal (–) — complete formal absence of a signal or complete discrepancy between the conceptual and semantic content of the signal and intention; signal (+/–) — partial compliance with intention; signal (+) — complete conceptual and semantic correspondence with intention. The specificity of the internal structure of the signal is genetically related to understanding the intentional state essence (model: I = S(p)). The CPP theory assumes S (psychological state) as the mental component of the signal S1(m), and Р is the conceptual-pragmatic («pre-ideological») component of the signal S1(c – p). Signal formula in the CPP theory context: S1 = S1(m) + S1(c – p). S1 is a conceptual and pragmatic materialization of the programmed mental-volitional aspirations of the subject-source. The general initial idea of “direction — motive — intention” leads to the conceptualization of the resultant system “intention — signal — discourse”.
P- and S-wave arrival picking and epicentral distance estimation of earthquakes using convolutional neural networks

&amp;lt;p&amp;gt;In recent years, machine learning techniques have been widely applied in seismological data processing such as seismic event detection, phase picking, location, magnitude estimation, and further data analysis for determining source mechanisms. Especially in earthquake location, deep learning methods are used to reduce location errors compared to conventional algorithms.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this study, we present a deep learning based epicentral distance estimation with two separate models using seismic data from two stations as input data. The first model is the P- and S-wave arrival time picking model and the second is the epicentral distance estimation model. Since the traditional epicentral distance estimation methods uses the difference in arrival times between P- and S-waves, the P- and S-wave arrival times were first predicted from three-component seismic data so that this information could be directly used as the next input data. This picking information is used as input data along with the station location in the epicentral distance estimation model to output the final epicentral distance. Since this method uses data from two stations, it has higher accuracy than epicentral distance estimation using data from a single station.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The P- and S-wave arrival time picking model was modified by referring to the ResUNet (Diakogiannis et al., 2020) structure to improve performance based on the seismic detection and phase picking model from the three-component acceleration data developed by Mousavi et al. (2020). This modified model performs feature extraction for P- and S-phase picking and includes a residual block and skip connection. The model for estimating the distance from the epicenter was constructed using a basic artificial neural network (ANN) architecture. As input data, a total of eight features were used by adding six combinations of the difference in arrival times of P-wave and S-wave in each component of the two stations and two values of the latitude and longitude difference between two stations. The ANN architecture consists of four hidden layers and the epicentral distances of the two stations are final output.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The STEAD data were used as training data and test data. The STEAD is a seismogram dataset recorded from about 450,000 global earthquakes, and among them, data with magnitudes greater than 2.5 and epicentral distances less than 400 km were selected and used. As a result of applying the trained model to the test data, the mean absolute error of the predicted epicentral distance was 6.5 km, which showed improved performance compared to the previous results. Also, since this method uses six time-differences as input data, it can provide more robust results even in the presence of random noise at the picked times.&amp;lt;/p&amp;gt;
ANALYSIS OF YUGRA STATE UNIVERSITY STUDENTS’ DIGITAL FOOTPRINT

The article deals with the search and analysis of Ugra State University students’ digital footprint. The concept of a student’s digital footprint and the potential of its application in the educational process are considered. The authors describe the process of searching for the digital footprint of Yugra State University students who major in “Software Engineering” and “Informatics and Computer Engineering”. The analysis and systematization of the obtained digital footprint data has been carried out. The approach to the study of the students’ digital footprint presented in the work can be applied in improving the quality of education and the prospects for using information technologies in higher education.
Grammatical Errors of English Descriptive Texts Written by Sixth Grade Students of Multi-Q Elementary School

The entitled of this study is "Grammatical Errors of English Descriptive Texts Written by Sixth Grade Students of Multi-Q Elementary School".This study aims at finding and describing the types of error found in students' descriptive texts.Descriptive text is one type of texts in writing that is usually used in the level of elementary school especially in sixth grade.To make a good written text, the students must be able to master and apply the structure correctly.But in fact, many students still face difficulties when they make English composition and cause grammatical errors in their writing.The theory used in this study is from Dulay about types of error.The data were analyzed qualitatively.The method that used in this research is observation method.The technique used to collect the data are divided into: asking permission to the headmaster of Multi-Q Elementary School, giving blank paper to the students to make descriptive text with a free topic, and collecting the texts are made by the students.The process of data analyzing were: the errors were found by reading every sentence carefully, find out the errors and classifying them according to the types of error.In this research, there are four types of errors namely: omission, addition, misformation, and misordering.
Classifying the difficulty levels of working memory tasks by using pupillary response

Knowing the difficulty of a given task is crucial for improving the learning outcomes. This paper studies the difficulty level classification of memorization tasks from pupillary response data. Developing a difficulty level classifier from pupil size features is challenging because of the inter-subject variability of pupil responses. Eye-tracking data used in this study was collected while students solved different memorization tasks divided as low-, medium-, and high-level. Statistical analysis shows that values of pupillometric features (as peak dilation, pupil diameter change, and suchlike) differ significantly for different difficulty levels. We used a wrapper method to select the pupillometric features that work the best for the most common classifiers; Support Vector Machine (SVM), Decision Tree (DT), Linear Discriminant Analysis (LDA), and Random Forest (RF). Despite the statistical difference, experiments showed that a random forest classifier trained with five features obtained the best F1-score (82%). This result is essential because it describes a method to evaluate the cognitive load of a subject performing a task using only pupil size features.
Adoption of Blockchain Technology Based Accounting Platform

Accounting has always been influenced by digital technology, although most of it has been replacing analogue instruments with digital versions. A blockchain is a digital ledger that is used to record transactions between different participants in a network. It is an internet-based, peer-to-peer distributed ledger that contains all transactions since its inception. Blockchain technology has the potential to revolutionize the world humanity implementing in the business based on the concept of transmitting valuable digital assets like bitcoin without the need of a third-party intermediary. Blockchain is considered as a type of database or a sort of digital ledger, which is widely used by many financial organizations. It's a distributed ledger which keeps records of immutable and verifiable data. This blockchain technology permits decentralized ledger transactions to be produced without the intervention of a third party. Because of its decentralization, networks have a high degree of protection. The aim of the study is to investigate various decisions making factors, affecting in adopting blockchain technology in the field of accounting. The result showed that secure and private, transparent and auditable, immutable, better transparency, reduce cost, transparency, real-time transaction, and flexible are most likely influencing factors in adoption of blockchain technology. The result indicates that the Quorum, Sap Hana, and Ethereum, platforms are most consistent and trusted platforms for block chain technology and the blockchain platforms are found most suitable, secured and stronger platform.&#x0D; &#x0D; Received: 25 October 2021 / Accepted: 2 February 2022 / Published: 5 March 2022
Designing Application Appropriateness for Augmented Reality with Requirement Integration from the User-Cursor Paradigm

Technological advances have increased the potential for wearable augmented reality (AR) devices. More applications are being ported for this platform with this development, and not all are suited for AR. After the initial novelty fades, users often find the application gimmicky and unwieldy, causing them to become incredulous towards AR’s potential. Developers need to ensure that the application emphasizes elements that are unique to AR for a successful port. This paper analyzes the human- cursor paradigm to derive a set of requirements and integrate them into an application. With this integration, an application that has no exclusive need of the AR platform can be redesigned to take advantage of AR’s capability making it more valuable to the user. This emphasis will promote targeted development of meaningful applications further expanding the augmented reality platform.
Move structures found in the final project abstracts written by Indonesians and Filipinos

This study was conducted to investigate the move structures of the final project report abstracts produced by the undergraduate students of the English Education Department (EED-UMK) Indonesia and by the Secondary Education undergraduate students of Central Bicol State University of Agriculture (CBSUA) Philippine. This study employed the content analysis method. Sample final project reports from EED-UMK and CBSUA were gathered and analyzed. The findings of this research revealed that the abstracts of EED-UMK and CBSUA used different move structures patterns. The majority of EED-UMK abstracts (80%) referred to Hyland's five move structures, which consisted of introduction, purpose, method, product, and conclusion (I-P-M-Pr-C). Meanwhile, one of the CBSUA abstracts (20%) applied Bathia�s four move structures consisting of purpose, method, result, and conclusion (P-M-R-C). The remaining of the EED UMK and CBSUA abstracts did not address either Bathia's or Hyland's styles. This study concludes that the two Universities have different style structures in writing the final report abstracts. This study suggests that students use the move structure style consistently in their abstracts.
Gamification Project in Japanese Higher Education for Spanish as a Foreign Language

This paper discusses and highlights the use of Information and Communication Technologies (ICT); more precisely showing gamification as a motivational generator element, in a Japanese university context, for teaching Spanish as a foreign language. The method: the investigative approach is a mixed method (quantitative and qualitative). This quasi-experimental and cross-cutting design study was applied to two student groups (experimental and control groups). The working hypothesis is that as a result of the implementation of gamification strategies and techniques to a course through LMS (Blended Learning) for teaching Spanish, motivation and academic performance will increase among students. In conclusion: one of the main goals of this article is to frame and enclose the main mechanics of gamification, and apply them into our daily teaching. According to the data obtained, it is therefore apparent that we achieve a higher commitment and better involvement from our students.