Reviewerly/exHarmony huggingface dataset:
Arabic Dialects System using Hidden Markov Models (HMMs)

The Arabic language has many different dialects and it must be recognized before using the automatic speech recognition (ASR). On the other hand, it is observed in all Arab countries that the standard Arabic language is widely written and used in an official speech, newspapers, public administration, and schools but it is not used in daily conversations instead the dialect is widely spoken in daily life and rarely written. In this paper, we examine the difficult task of properly identifying various Arabic dialects and propose a system developed to identify a set of four regional and modern standard Arabic speeches, based on speech recognition using Hidden Markov Models (HMMs) algorithms. HMMs have become a very popular way to build a speech recognition system. It is set as hidden states and possibilities of transition from one state to another. Due to the similarities and differences between the Arabic dialects, speeches collected from the ADI5 datasets were retrieved from the MGB-3 challenge source. We proposed an Arabic Dialect Identification System called "Building a System for Arabic Dialects Identification based on Speech Recognition using Hidden Markov Models (HMMs)" that takes Input as speech utterances and produces output as dialect being spoken. During the training phase, speech utterances from one or more dialects were analyzed to capture the important properties of audio signals in terms of time and frequency. During the testing phase, previously unseen test utterances were utilized to the system, and the system outputs the dialect associated with the model of dialect that most closely matches the test utterance. The proposed model of the system shows promising results of the model for each dialect match.
Optimized Implementation of Simpira on Microcontrollers for Secure Massive Learning

Internet of Things (IoT) technology, in which numerous devices cooperate, has a significant impact on existing industries, such as smart factories, smart cars, and smart cities. Massive learning and computing using data collected through the IoT are also being actively performed in these industries. Therefore, the security of low-end microcontrollers used in the Internet of Things should be highly considered due to their importance. Simpira Permutation is a Permutation design using the AES algorithm designed to run efficiently on 64-bit high-end processors. With the efficient implementation of Simpira algorithm, we can ensure secure massive learning in IoT devices without performance bottleneck. In nature, Simpira exploited the part of AES algorithm. The AES algorithm is the most widely used in the world, and Intel has developed hardware accelerated AES instruction set (AES-NI) to improve the performance of encryption. By using AES-NI modules, Simpira can be improved further on high-end devices. On the other hand, low-end processors do not support AES-NI modules. For this reason, an optimized implementation of efficient Simpira should be considered. In this paper, we present an optimized implementation of Simpira on 8-bit AVR microcontrollers and 32-bit RISC-V processors, which are low-end processors that do not support AES-NI features. There are three new techniques applied. First, Addroundkey is computed efficiently through pre-computation. Second, it takes advantage of the characteristics of round keys to omit some of the operations. Third, we omit unnecessary operations added to use AES-NI features. We have carried out performance evaluations on 8-bit ATmega128 microcontrollers and 32-bit RISC-V processors, which show up-to 5.76× and 37.01× better performance enhancements than the-state-of-art reference C codes for the Simpira, respectively.
Are these texts readable? An Analysis on the Readability Level of English Textbooks for Indonesian High Schools

Reading texts or passages from textbooks are commonly used as learning materials in the Indonesian EFL context. This leads to the emergence of readability or reading level analyses for EFL reading materials using conventional formulas which, unfortunately, were originally developed for either English as L1 or L2 context. Moreover, there are alternative readability formulas for EFL materials that are relatively newer yet still underused in the field. Hence, this current descriptive study aimed to address this gap by attempting to analyze the reading texts in three Senior High School English textbook series published by the Ministry of Education and Culture, using formulas measuring the readability level without grade-levelling and using simplified EFL reading materials. In this study, the two specific formulas employed to conduct the readability level analysis were Miyazaki EFL Readability Index and McAlpine EFLAW formula. The results showed that the overall Miyazaki EFL readability score of all reading texts in the 10th, 11th, 12th grade English textbooks was 50, categorized as having a “standard” difficulty. Meanwhile, based on the analysis using McAlpine EFLAW readability formula, the overall readability score was 20.86, which was considered as “very easy to understand”. Eventually, it could be concluded that the two formulas could be conveniently used to analyze the readability level of all the reading texts in the textbook series. Moreover, the texts could be deemed as of “suitable and understandable” level for the intended EFL students in Indonesia.&#x0D; &#x0D; &#x0D; Keywords:Readability; Texts; Textbooks; Miyazaki EFL formula; McAlpine EFLAW formula&#x0D;
Image to Caption Generator

Abstract: Image captioning aims to automatically generate a sentence description for an image. Our project model will take an image as input and generate an English sentence as output, describing the contents of the image. It has attractedmuch research attention in cognitive computing in the recent years. The task is rather complex, as the concepts of both computer vision andnatural language processing domains are combined together. We have developed a model using the concepts of a Convolutional Neural Network (CNN) and LongShort Term Memory (LSTM) model and build aworking model of Image caption generator by implementing CNN with LSTM.The CNN works as encoder to extract features from images and LSTM works as decoder to generates words describing image. After the captiongeneration phase, weuse BLEU Scoresto evaluate the efficiency of our model. Thus, our system helpsthe user to get descriptive caption for the given input image.
DEVELOPMENT OF MEDIA LITERACY OF THE FUTURE JOURNALISTS IN INSTITUTIONS OF HIGHER EDUCATION

The article emphasizes the need for media education as an integral component of the educational process, the expansion of its theoretical and practical potential, demand in modern society, taking into account the specifics of the information space of Ukraine, especially in times of a full-scale Russian-Ukrainian war. The level of media education research in the West and in Ukraine is described, various definitions of this concept in modern Ukrainian scientific researches are analyzed. The narrow and broad meaning of the term is considered: the component of training of secondary and higher education students in the first case and long-term social and educational activities without age restrictions. Attention is paid to the Concept of the introduction of media education in Ukraine and its implementation in the state in general and in institutions of higher education in particular. Critical thinking is characterized, the development of which is one of the main goals of media education. The statement that representatives of professions directly related to the media, as well as students of higher education majoring in Journalism should be engaged in media education at a professional level, has been presented and substantiated. The latter should develop media competence in a formal educational environment. Additionally, they can deepen existing media skills in the form of informal and informal education. The same applies to representatives of pedagogical professions, i.e., those through whom media education activities are carried out. Successful work in the field of most modern professions is practically unthinkable without developed abilities of continuous self-education throughout life, including media education. The place of the media education component in the process of obtaining professional higher education is determined. It can be integrated with traditional disciplines of the educational and professional program or introduced autonomously (disciplines chosen by students, optional courses, etc.). The stages of media education are characterized, as well as the criteria for the development of media competence of young people: conceptual, sensory, motivational, evaluative, creative. Key words: media education, media competence, critical thinking, higher education, journalism
The Smartphone Use of Learning English Among University Students in A State University in Semarang

Based on the finding and discussion above that the university students in a state university in Semarang used some applications and features of their smartphone to learn and sharpen their English ability such as hello English, speaky, youtube, spotify, and browser based on their needs. They are self-learner. They tend to cognitive needs because the five respondents used their smartphone to sharpen their English skills through features and applications on their smartphones. This is not only learn their English skills, but also they were able to gain information based on English which could support their English in the class.. The respondent 5 would look for information related to his English assignment that he doesn't know more about (smartphone functions as a supplement). While, the four other respondents who learn and sharpen their English skills deeper through applications provided by smartphones (smartphones function as a complement).
THE DEVELOPMENT OF COGNITIVE ACTIVITY OF STUDENTS IN THEORETICAL PHYSICS TEACHING

The article deals with the theoretical aspects and practical implementation of the author's methodical approach to the systematic support and development of students' cognitive activity in teaching theoretical physics at a pedagogical university as a determining factor in improving the quality of the educational process. The author noted that the problem of increasing of the level and quality of fundamental training of pre-service physics teachers in accordance with the requirements of state regulatory documents in modern educational conditions is urgent, complex and multifaceted. The author analyzed the main factors of formation of stable internal motivation of students for active educational and cognitive activities. In accordance with the didactic principle of fundamentality and professional orientation, methodological principles of personally oriented teaching of theoretical physics at a pedagogical university is proposed. The author highlighted methodological aspects of formation, support and development of cognitive activity of students in the teaching of theoretical physics based on the application of active methods, methods and forms of learning, which encourage them to active thinking activity as much as possible, form a culture of mental work and independent practical actions. The list of active methods includes: creation of problematic situations, discussion of physical paradoxes, implementation of the principle of historicism in education, mathematical modeling of researched objects and solving of interesting non-standard problems, drawing up reference summaries, structural-logical diagrams, comparative tables based on literary sources; the use of modern ICT training and program-pedagogical tools of various didactic purposes (demonstration, simulation, modeling, control, testing), the use of interactive technologies (educational discussions, round tables, work in large and small groups) and methodological techniques of the professional direction («Acquaintance» . students' mini-lecture, «The game of misunderstanding», «Say it easier», «Hyperlinks»). Fundamental importance is attached to the solution of the mentioned problem of the teacher's own motivation to work and professional self-improvement, because, as its known, a real teacher prepares his whole life for his best lesson. Key words: professional competence of the future physics teacher, theoretical physics, cognitive activity.
Formation of Transversal Competences of Future Economists in the Conditions of Digital Space

The article emphasizes the importance of economic education as a part of general education, in terms of market transformations and democratization of society. It is established that the concept of “transversal competence” is not sufficiently developed by European scientists. It is specified that transversal competence is a universal competence and a new format of an educator’s experience. The articles mention that Digital Skills is a composite transversal competence of educators. It is proposed to take into account the increase of digital skills in the formation of transformational competencies of educators in the digital space using various forms and methods of improving digital skills. Such methods as Web Quest and the use of such Internet applications: Simple Note, Flash card, Quick Math, Duo Lingo, Animation en volume pro, Puppet Pals, Pixton, Vialoguas, digital workspace, Pear Deck, Padlet, Kahoot, social networks, messengers and email.
Robotic Motion Planning in Dynamic Environments and its Applications

The fundamental problem of robot motion planning in a dynamic environment (RMPDE) is to find an optimal collision-free path from the start to the goal in a dynamic environment. Our literature survey of over 100 papers from the last four decades reveals that there are more than 30 models of RMPDE, and there is no benchmarking criterion to select one that is the best in a given situation. In this context, generating a regression-based model with 10 attributes is the first and foremost contribution of our research. Given a highly human-interactive environment like a cafeteria or a bus stand, the gross hidden Markov model has special importance for modeling a robot path. A variant of the growing hidden Markov model for a serving robot in a cafeteria is the second contribution of this paper. We simulated the behavior of GHMM in a cafeteria with static and dynamic obstacles (static obstacles were both convex and concave) and with three different arrangements of the tables and obstacles. Robots have been employed in mushroom harvesting. A novel proposition discussed in this paper is probabilistic road map planning for a robot that finds an optimum path for reaching the ripened mushrooms in a randomly planted mushroom farm and a dexterous hand to pluck the selected mushrooms by employing inverse kinematics. Further, two biologically inspired meta-heuristic algorithms, ant colony optimization, and firefly has been studied for their application to latex collection. The simulation results with this environment show that the firefly algorithm outperforms ant colony optimization in the general case. Finally, we have proposed a few pointers for future research in this domain. The compilation and comparison of various approaches to robot motion planning in highly dynamic environments, and the simulation of a few models for some typical scenarios, have been the contributions of this paper.
Educating Future Female Seafarers in the Maritime College from the Perspective of Masculinity

Recently, the Maritime Bureau and Seafarers Policy Division of the Ministry of Land, Infrastructure, Transport, and Tourism have been working to promote gender equality in the seafarer industry. Moreover, in 2017, the “Committee on the Promotion of Female Seafarers’ Activities from a Female Experts’ Perspective” was launched to discuss the issue. I participated in this committee as one of three academic experts. The committee has reported that the percentage of female seafarers in the Japanese shipping industry is only 2%, and less than 10% of shipping companies have shown a positive attitude toward the employment of female seafarers, indicating that the employment of female seafarers is not being promoted. The purpose of this study is to train female students in maritime colleges to be able to work as seafarers with leadership skills in the future using “masculinity” as a keyword.
Verifiable Data Search with Fine-Grained Authorization in Edge Computing

In the research of searchable encryption, fine-grained data authorization is a convenient way to manage the search rights for users. Recently, Liu et al. proposed a fine-grained searchable scheme with verification, which can control the search authorization and verify the results. In this paper, we first present a forgery attack against Liu et al.’s scheme and then propose a novel scheme of verifiable data search with fine-grained authorization in edge environment. Based on the key aggregate mechanism and Merkle hash tree, our proposed scheme not only achieves file-oriented search permission management but also implements the correctness and completeness verification of search results. In addition, with the assistance of edge server, resource-constrained users can easily perform the tasks of search and verification. Finally, we prove our scheme is secure based on the decision <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>l</mi> </math> -bilinear Diffie–Hellman exponent problem. The performance analysis and experiment results demonstrate that our proposed scheme has lower computation, communication, and storage costs contrast to the existing schemes.
GPU Based Similarity Metrics Computation and Machine Learning Approaches for String Similarity Evaluation in Large Datasets

Abstract The digital era brings up on one hand massive amounts of available data, and on the other hand the need of parallel computing architectures for efficient data processing. String similarity evaluation is a processing task applied on large data volumes, commonly performed by various applications such as search engines, bio-medical data analysis and even software tools for defending against viruses, spyware, or spam. String similarities are also evaluated in musical industry for matching playlist records with repertory records composed of song titles, performer artists and producers names, aiming to assure copyright protection of massmedia broadcast materials. Thus, the present paper proposes a GPU based approach for parallel implementation of the Jaro-Winkler string similarity metric computation. Further on, a thresholding-based algorithm is also implemented using GPU for matching records over large datasets. The global GPU RAM memory is used to store multiple string lines as raw data. In the case of a single string, its comparisons with the raw data are performed using the maximum number of available GPU threads and the stride operations. Moreover, based on the computed similarity metrics, an adaptive neural network approach guided by a novelty detection classifier together with a naive neural network implementation are proposed to increase the accuracy of the records matching procedure. Timing considerations and the computational complexity are detailed for the proposed approaches compared with state-of-the-art CPU and GPU approaches. A speed-up factor of 21.6 was obtained for the GPU based JaroWinkler implementation compared with the general purpose processor one, whereas improved accuracy for the records matching procedure was delivered using machine learning approaches.
The Effectiveness of E-Learning Platform in Higher Institutions: A Review on Language, Psychology, and Culture

The effectiveness of e-learning has some uniqueness and challenges in terms of obstacles faced, and its learning model. This research employs the observation method by observing both spoken and written data, survey, and interview. Data was obtained from 80 higher institutions students and 50 lecturers of four state-owned institutions, and four private institutions.The results show that the effective learning conducted through e-learning has met the expected standard. Through the learning process, the students were provided by motivational training, and educated with character building based on their religious belief. Moreover, the lecturers carried out their teaching process through WhatsApps Group, zoom meeting and/ or google meet applications, and provided the students with instructions and guidance. The instructions and guidances were particularly concerned on how to conduct the online classes with the camera on, comprehending the Semesterâ€™s Lesson Plan (SLP) for the whole semester, providing feedback on the materials, examples, video assignments, and weekly tasks given. Besides that the instructions and guidances were also specified for the students to seize the opportunities to present their tasks virtually. Likewise, the supports from the institutions are also needed concerning the committee for quality assurance in the implementation of E-learning, draft, attendance list, journal, contract of the course, motivational to the lectures in implementing E-learning, and video conference room (Vicon) as well.
BitextEdit: Automatic Bitext Editing for Improved Low-Resource Machine Translation

Mined bitexts can contain imperfect translations that yield unreliable training signals for Neural Machine Translation (NMT). While filtering such pairs out is known to improve final model quality, we argue that it is suboptimal in low-resource conditions where even mined data can be limited. In our work, we propose instead, to refine the mined bitexts via automatic editing: given a sentence in a language xf, and a possibly imperfect translation of it xe, our model generates a revised version xf' or xe' that yields a more equivalent translation pair (i.e., <xf, xe'> or <xf', xe>). We use a simple editing strategy by (1) mining potentially imperfect translations for each sentence in a given bitext, (2) learning a model to reconstruct the original translations and translate, in a multi-task fashion. Experiments demonstrate that our approach successfully improves the quality of CCMatrix mined bitext for 5 low-resource language-pairs and 10 translation directions by up to ~ 8 BLEU points, in most cases improving upon a competitive back-translation baseline.
Indonesian Tertiary Education Students’ Academic Writing Setbacks and Solutions

Writing is a crucial skill and tertiary education students face difficulties in academic writing. This paper aimed to identify the setbacks or difficulties and the solutions to the setbacks experienced by the Indonesian tertiary education students in academic writing. A survey was used as the method of this study. The data were collected through a questionnaire using a Google form distributed to 26 fifth-semester students taking the Academic Writing course in the English Language Education Study Program of Sanata Dharma University, Yogyakarta, Indonesia, for the academic year 2019/2020. The survey results showed that, in general, the students faced setbacks in, for example, parts of speech, tenses, spelling, prepositions, vocabulary, punctuation, cohesion, discourse markers, writing paragraphs with a clear focus, constructing clear and coherent academic essays, paraphrasing, in-text referencing, and compiling a correct reference list. Concerning academic writing solutions, the results showed that lecturers should be trained and equipped with various writing strategies, feedback on the strengths and weaknesses was vital, and the students needed to improve their organization of ideas, for example. Other solutions were better language skills, language elements, critical thinking skills, paraphrasing, and referencing. Implications of the findings are that students and lecturers would understand and identify common setbacks in academic writing and have opportunities to adopt the suggested solutions to academic writing difficulties.