Reviewerly/exHarmony huggingface dataset:
Binary Stripe Unwrapping Based on Mean-speed Walk and Local Median Correction for Rapid High-resolution Structured-light Range Imaging

Aim: Structured light is frequently selected for efficient and accurate depth imaging, and single-frame-based methods have been presented for real-time sensing or imaging dynamic objects. However, many existing single-frame-based methods do not provide sufficient range resolution. Even those capable of sufficient range resolution mostly result in insufficient signal-to-noise ratio or depend on spatially windowed uniqueness, where a larger window makes the identification trickier. Method: This paper presents a novel method for rapid structured-light range sensing using a binary color stripe pattern. For accurate and reliable depth acquisition, we identify projected stripes by our stripe segmentation and unwrapping algorithms. For robust stripe detection, the color-stripe segmentation algorithm performs image upsizing, motion blurring, and color balancing. The binary stripe unwrapping algorithm consists of mean-speed walk unrolling, row-wise unrolling, and local median correction, and resolves the high-frequency color-stripe redundancy efficiently and reliably. objective: We provide a novel method for rapid structured-light range sensing using a binary color stripe pattern. Result: Experimental results show the effectiveness and reliability of the presented method. Conclusion: Even using an entry-level phone camera under a low-cost DLP projector produces high-accuracy results.
An analysis of the test characteristics of the nationwide middle school English listening tests: Based on speech rate and Coh-Metrix analyses

The purpose of the current study is to compare and contrast the two standardized middle school English listening tests; the National test and the Seoul test. To compare the test characteristics of the 20 items for each test, the speech rate as well as 9 linguistic features selected from Coh-Metrix (a web-based text-analysis tool) were analyzed. Coh-Metrix measures were analyzed under the following categories: basic counts, lexical complexity, syntactic complexity, and discourse coherence. 60 middle school students participated in this study to compare the test results and the overall difficulty. To calculate the speech rate (WPM), Praat and MS Excel were used, and Coh-Metrix was used to compare the aforementioned linguistic measures of each listening test. The test results revealed that the average score of the National type was higher than that of the Seoul test. The analysis on the speech rate demonstrated that the average speech rate of both test types belonged to ‘Moderately Slow’ based on the standard speech rate classification (Pimsleur, Hancock, &amp; Furey, 1977); however, the speech rate of the Seoul test was found to be significantly higher. Most of the linguistic features analyzed were about the similar measures. Pedagogical implications will be discussed.
The effects of the learning variables and self-regulated learning strategy affecting academic achievement of a general English online course

This study analyzed the effects of the learning variables and self-regulated learning strategy affecting college learners' achievement in an online general English course. For the study, three learning variables and four self-regulated learning strategies were selected: checking the bulletin board, learning progress, the total number of times students accessed the LMS, cognitive strategy, metacognitive strategy, behavior strategy, and motivational strategy. 106 Korean college students participated in the course. Their data were collected employing the Learning Management System and a self-regulated learning strategy questionnaire. The results were analyzed with the independent T-test and multiple regression analysis. First for the learning variables, checking the bulletin board, the total number of the times students accessed the LMS were closely correlated with their academic achievement. Second, motivational strategy and behavior strategy were closely correlated with their academic achievement. Third, motivational strategy and behavior strategy significantly affected their academic achievement. Fourth, for the high and low groups of motivational strategy and behavior strategy, the data showed a significant mean difference in the variables of checking the bulletin board and the total number of times students accessed the LMS. Some implications and discussions for analyzing learning variables and self-regulated learning strategy affecting academic achievement are illustrated.
Warping Patterns

Chapter Goal: Review how to create patterns and then enter the pattern through the Swatches panel to distort it further. Also, work with the new feature, Object > Repeating Shapes.
Working with Type Paths

Chapter Goal: Work with type on paths and see how you can distort the lettering and the text path going around a vector logo.
Ellipse Detection Combining Region Detection and Arc Filtering

Ellipse detection is a hot issue in the field of computer vision, and how to detect ellipses quickly and accurately, especially small ellipses with low resolution, is the main challenge of this problem. First, ellipses data sets of different sizes are constructed, and the region detection method in deep learning is introduced into the ellipse detection process. Furthermore, a two-stage arc filtering strategy is proposed based on quadratic curve constraints, which can effectively detect nested ellipses and reduce the number of missed and false positive detections. Finally, the bicubic interpolation method is employed to enlarge the area for small ellipses detection. The experimental results demonstrate the proposed method has a significant improvement in detection accuracy with competitive speed. Especially, on the small ellipse data set, the detection accuracy of the proposed method is more than two times of the traditional arc-based methods.
Introduction: “disruptive…” or (just) “emerging” technologies?

When we talk about “disruptive technologies”, what exactly do we mean? According to the Cambridge Dictionary, a disruptive technology is a new technology that completely changes the way things are done. Even though we cannot be certain which technologies will accomplish this in the future, the public has over the past years broadly accepted “disruptive technologies” as a term which refers to blockchain, the Internet of Things, artificial intelligence, virtual reality, drones, 3D printing and other cutting-edge technologies, which are the subject of this Study Report.
Translation Quality Regarding Low-Resource, Custom Machine Translations: A Fine-Grained Comparative Study on Turkish-to-English Statistical and Neural Machine Translation Systems

Corpus-based machine translation (MT) has been the main approach to developing and implementing MT systems in both academia and the industry over the last three decades. In this field, the type and size of the corpus used for training MT engines have presented problems for both statistical MT (SMT) systems as well as neural MT (NMT) systems, being the two dominant corpusbased approaches. Moreover, language pairs such as Turkish-English have been understudied within this framework. This article aims to evaluate the translation quality in Turkish-to-English custom MT systems that have been trained on different corpus sizes and types. Two NMT engines and two SMT engines were trained on the KantanMT platform using two different training corpus types with either only domain-specific cardiology corpus or this corpus plus a mixed-domain corpus. The study conducted both automatic evaluations with metrics including BLEU, F-Measure and TER, as well as a comprehensive human evaluation with metrics including fluency, A/B test, and adequacy. Lastly, the study realized a separate, subjective terminology evaluation in order to investigate how differently MT systems handle terminology, as this is a crucial aspect for specific-domain text types such as cardiology. While the automatic evaluation results suggest the SMT engines to perform better than NMT engines, all human evaluators rated the mixed-domain NMT engine as the highest performing one. However, the terminology evaluation task demonstrated SMT to still be able to perform better and to commit less terminology errors, despite the industry and academia shifting toward NMT engines.
System of Automatic Recognition of Video Text Amazigh based on the Random Forest

In this paper; we introduce a system of automatic recognition of Video Text Amazigh based on the Random Forest. After doing some pretreatments on the video and picture, the text is segmented into lines and then into characters. In the stage of characteristics extraction, we are representing the input data into the vector of primitives. These characteristics are linked to pixels’ densities and they are extracted on binary pictures. In the classification stage, we examine four classification methods with two different classifiers types namely the convolutional neural network (CNN) and the Random Forest method. We carried out the experiments with a database containing 3300 samples collected from different writers. The experimental results show that our proposed OCR system is very efficient and provides good recognition accuracy rate of handwriting characters images acquired via Video camera phone.
SPECIFICITY OF TEACHING UKRAINIAN PHRASEOLOGY IN GROUPS OF STUDENTS OF NON-TECHNICAL SPECIALTIES

The article deals with the problems of specificity of teaching Ukrainian phraseology in groups of students of non-technical specialties.The article considers the specific features of the presentation of Ukrainian phraseology in classes of Ukrainian as a foreign language in order to form a professionally oriented linguistic competence.Theoretical positions are demonstrated by the example of teaching foreign students of architectural specialties studying the history of culture and fine arts.To study the problem of presentation of phraseology is important not only in terms of theoretical solution of the problem, but also in practical terms, namely the study of a foreign language.The use of phraseological units causes difficulties in learning the language by foreign students because phraseological units that function in the language as separate formations, integral in meaning, stable in their composition.The meaning of FU is always related to the meaning of a free phrase of the same syllable, which is a criterion for classifying some phraseological phenomena.For more successful teaching of phraseology, it is necessary to identify the most effective methods and techniques that can be used by the teacher in studying various topics of the course.The article analyzes the importance of the presentation of phraseological units in a foreign audience.
The Problem of Technology and Technologization of Modern Processes Through the Prism of Martin Heidegger’s Methodology

In this article, on the basis of the philosophical method of Martin Heidegger (1889–1976), an attempt is made to show how the distance separating the world of philosophy from the world of high technology can be overcome. The purpose of the study is to extrapolate Heidegger’s way of thinking onto the modern processes of technologization and digitalization as well as to demonstrate how Heideggerian philosophy can be used in practice today. Thus, we need to take a step back and reconsider Heidegger’s attempts to develop a new way of questioning and thinking. This article is relevant due to the increasing technologization and digitalization of all spheres of human life, including education, culture and philosophy. To identify the weaknesses and shortcomings of the concept of digitalization, it is contrasted with the Heideggerian critique of technological thinking in general and its digital component in particular. The paper demonstrates the way to bridge the gap between technology and the true being of humans. Further, the article considers the evolution of Heidegger’s analysis and attitude to technology during the development of his philosophical thought: from analysing Dasein (human existence as being) in the early period to shifting the focus to language, poetry and language of poets in the later period. In Heidegger’s philosophy, such poetry is the poetry of Friedrich Hölderlin (1770–1843). The concept of Machenschaft (machination) as a justification of the manufacturability of the processes of human life is considered. The main signs of machination are presented: transformation of the social sphere into a huge mechanism – “machine” – controlled by technology; digitalization as an equalization of individuals; recognition of the omnipotence of technologies implemented as “programmes of action”. In the era of machination, a person cannot yet recognize himself as a machine and considers himself a living being with his own experiences. It is concluded that philosophy should take on a leading role in determining and critically evaluating the new human worldview on a global scale.
Exploration of PET and HDPE Plastic Waste into the Art Creating of Lampshade with Geometric Shape

Nowadays, waste has become a problem faced by people worldwide, especially in Indonesia. Wastes that are difficult to process, like plastics, can disturb environmental aesthetics, environmental cleanliness, and health. They have a power that is difficult to decipher, so the researcher applied several methods to them. Through an experimental process, this research designed the products of lighting elements for cafés made of plastic bottles in the types of PET and HDPE. Several phases in the testing process must be carried out to convert the wastes. First, data collection was then continued by the experiment process to produce design synthesis. In the design process, the researcher conducted waste collection, sorting, milling, washing, forming, and finishing processes. This research involved 3 sites for case studies, namely Blimbing Village TPS, Robbries Gallery as a place to search for data on waste processing processes, and Akarating Café as a theme and also as a place to look for observation data. The experimental process yielded lights used in a cafe having a hexagon shape with 2 different color accents and having different placements, such as hanging on the roof and sticking on the wall.
A Generalized Poisson-Pseudo Maximum Likelihood Estimator

We propose a Generalized Poisson-Pseudo Maximum Likelihood (G-PPML) estimator that relaxes the PPML estimator’s assumption that the dependent variable’s conditional variance is proportional to its conditional mean. Instead, we employ an iterated Generalized Method of Moments (iGMM) to estimate the conditional variance of the dependent variable directly from the data, thus encompassing the standard estimators in international trade literature (i.e., PPML, Gamma-PML, and OLS) as special cases. With conditional variance estimates, GPPML generates coefficient estimates that are more efficient and robust to the underlying data generating process. After establishing the consistency and the asymptotic properties of the G-PPML estimator, we use Monte Carlo simulations to demonstrate that G-PPML shows decent finite-sample performance regardless of the underlying assumption about the conditional variance. Estimations of a canonical gravity model with trade data reinforce the properties of G-PPML and validate the practical importance of our methods.
The Feasibility of Developing Learning Media Based-Leactora Inspire at English Course

The study aimed to determine learning media based-Lectora Inspire feasibility at English course.The ADDIE model is being used in this research and development.The feasibility results of learning media based-Lectora Inspire in English courses meet the very valid criteria with the results from material/content experts reaching a validity level of 85% and media product design experts reaching a validity level of 87,5%.
Are We Cyborgs?

This chapter addresses the possibilities of a pedagogical shift in higher education based upon a thoughtful integration of learning technologies and a rich pedagogical interaction. The lockdown provided the opportunity to deepen our understanding about the relationship between subjects and technology, bringing up classical utopian and dystopian views. At this point, we are living in a hybrid world, with a fusional relationship with digital devices. As for education, it is clear that remote and blended learning delivery modes were not a temporary fashion. The authors discuss a set of principles that seem relevant to current and future remote and blended methodologies: (1) technology means freedom not slavery and it can serve a slow pedagogy, (2) communication is no longer a pure anthropocentric concept, and (3) a symbiotic and dialogical relationship between student and lecturer is not a thing from the past. With such principles in mind, they share their personal vision applied to the redesign of a module of semiotics concerning creative writing.
Research on Course Reform Based on Computer Big Data and Virtual Reality Technology

This article designs a Korean online speech recognition system for the Korean language teaching reform. Based on the computer big data perspective, we use the Mel frequency cepstral coefficient (MFCC) and some inherent characteristics of the speech signal to perform cestrum analysis. The experimental results show that for the speech recognition of isolated words with small vocabulary of non-specific people in Korean, the Cepstral Coefficient (MFCC) algorithm based on Mel frequency has a higher recognition rate than the hidden Markov method.
The effectiveness of using e-book based on multimodal representation and technological and pedagogical content knowledge (TPACK) to improve ICT literacy of physics teacher

This study aims to determine the effectiveness of using the Physics teacher's guide e-book based on multimodal representation and Technological Pedagogical and Content Knowledge (TPACK) to improving teachers’ ICT literacy. Given the important role of technology in the learning process, especially in the current Covid-19 pandemic era. The research method used was an experiment with a non-equivalent control group design. This study involved 61 in-service physics teachers and 40 pre-service teachers as participants who were taken by purposive sampling. The instruments used include ICT literacy test questions on the knowledge aspect, and a four-scale questionnaire. Physics teacher guide e-book used in this study is in the form of an e-Pub which can display simulation and animation videos that can be accessed by teachers in offline conditions. The analysis of ICT literacy data was carried out by IBM SPSS.20 software. The results showed that the Physics teacher guide e-book was effective in increasing teachers' ICT literacy. This product has a greater impact on the increase in literacy compared to the teacher's commonly used books. In addition, the results of the questionnaire data analysis showed that the teacher's response stated that they strongly agreed with the Physics teacher guide e-book that was developed to improve ICT literacy.
Communities of Practice in the Academic Library: Strategies for Implementation

"Communities of Practice in the Academic Library: Strategies for Implementation." Technical Services Quarterly, 40(1), pp. 39–40
Information Security of UN Sustainable Development Goals Implementation

The Goals and Targets of the 2030 Agenda for Sustainable Development are a roadmap for countries in their pursuit of prosperity.The Agenda defines the principal areas of the signatory countries' activity to build a society of prosperity regarding the level of social stability increasing in situations of uncertainty, risks, and crises.Global threats and conflicts and related humanitarian crises threaten to undo much of the development progress achieved in recent decades.For the second year, we have not seen progress in achieving the Sustainable Development Goals.The article examines the results of information support of the UN Sustainable Development Goals at the level of scientific publications posted in the ERA (Education Research Abstracts) database in 2015-2022.The results of the data analysis showed an uneven interest in the SDGs on the part of the scientific community and the representation of specific SDGs in scientific publications.In particular, in 2015, SDG 2, SDG 6, and SDG 7 were the «outsiders» in terms of representation in scientific publications.The difference between the lowest (260 -SDG 2) and the largest (26 305 -SDG 4) number of publications in 2015 is almost 102 times.In 2022, this difference was 80.At the same time, the analysis of publication activity, starting from 2015, shows the most significant increase in the number of publications until 2022, specifically for SDG 2 and SDG 6, due to their relevance in the context of global processes.
The Application of Data Mining Algorithm in the Legal Protection of Personal Data

Although big data has brought great convenience to human life, the crime of network user data interests is becoming more and more important. There are growing calls for legal protection of personal data. The purpose of this paper is to study the application of legal protection of human data based on data mining algorithms. The principle and process of data mining and Apriori algorithm are analyzed, and then several classification standards of privacy-preserving algorithms oriented to data mining are introduced. From the perspective of legal protection, the role of legal protection of personal data is introduced in detail. The process of privacy protection algorithm in frequent pattern mining is clearly analyzed. On this basis, the noise addition method is introduced into standard mining protection privacy protection, and the noise data and the amount of noise data are described in detail. When the things in the original data set When the number is 20, the execution time is 1052. This method can effectively improve the effectiveness of the frequent pattern mining privacy algorithm.
An Improved Particle Swarm Optimization Approach for Solving the Engineering Problems

In this paper, a new efficient approach for improving the PSO’s performance of particle swarm optimization algorithm, namely NEA-PSO, is presented. By introducing a new strategy of velocity updating. This proposed algorithm focuses on expanding the search area around the local best and global best exploited at each iteration. Thus, in the new algorithm, the progress of position updating of each individual particle in the swarm will move a longer step in comparison with the original PSO. Based on this strategy movement, the convergence rate in the proposed algorithm will be enhanced. Moreover, because of the more flexibility of exploring new search spaces, the accuracy in the NEA-PSO is also perfected. To verify the effectiveness and reliability of the NEA-PSO algorithm, the first five benchmark test functions are used as an example to demonstrate the effectiveness of the proposed algorithm. Then, NEA-PSO is applied to solve a particular engineering problem. The obtained results show that the NEA-PSO algorithm registers high reliability, and it can be seen as an alternative to the original PSO algorithm in solving optimization problems.