Reviewerly/exHarmony huggingface dataset:
Cubo Kids: a Proposal for an Educational Application with Augmented Reality

Mobile devices have been playing an important role in changing how people have access to information. The use of mobile devices for educational purposes has been growing every day and, along with that, we can see how much Augmented Reality can contribute to the development of applications in this area. This work presents a case study carried out in Early Childhood Education classes, in a school in the city of Mossoró/ RN, RN, Brazil, using the Cubo Kids application, which was developed with Augmented Reality technology, in order to expand the possibilities of teaching and learning. The research allowed us to observe that the application can bring great possibilities to the teaching of children at all levels of Early Childhood Education.
PHONOLOGICAL CHANGE PROCESSES OF ENGLISH AND INDONESIAN

Phonological change is a language phenomenon that occurs because language users change the distribution of phonemes in a language. The aims of this study are to explain the phonological processes that occur in English and Indonesian and to explain the differences in phonological forms between English and Indonesian. The method used in this study is a contrasting-descriptive method by comparing two languages, namely English and Indonesian. The data were taken from the speech of students taking Indonesian and English courses at the University of Bengkulu, totaling 40 students in the first semester. The results show that five types of phonological change processes occurred in English and Indonesian, namely assimilation, metathesis, epenthesis, epithesis, and deletion. The phonological change in English often occurred when two vowel phonemes meet, such as /ea/ shift to /e/, or /i/, phoneme /y/ shift to /i/. Phoneme /e/ was pronounced when two vowel phonemes meet, such as /s/ and /n/ becomes /sen/. Phoneme /g/ is pronounced multiply when it meets the sound/ng/. Phoneme /u/ is pronounced when it meets phoneme /o/ + a consonant. Phoneme /h/ is unpronounced when it meets a vowel phoneme or more vowel phonemes in the words. Meanwhile, phonological changes in Indonesian often occurred from consonant phonemes to other consonant phonemes that have almost the same sound such as phoneme /z/ shift to /s/ and /j/. Phoneme /k/ was pronounced after phoneme /u/ and phoneme /h/ is pronounced after phoneme /a/at the end of words. Phoneme /y/ was pronounced between phonemes /i/ and /a/. Phoneme /h/ was unpronounced when it meets phonemes /a/, /i/, and /u/ in words. In conclusion, the process of phonological change that occurs in English and Indonesian is due to the influence of adjacent phoneme sounds that resemble nearby sounds.
A convergence proof for local mode filtering

In this paper, we present a convergence proof for an iterative procedure of local mode filtering. We formulate the local mode filtering as a quadratic optimization problem based on the Legendre transform of convex function, from which two closed-form expressions at each iteration step are derived for variables to be optimized. Those analytical solutions ensure that the value of objective function increases monotonically with the progress of the iterative procedure. We also show experimental results using a grayscale image, which support our theoretical results practically.
A Hub-based Graph Management for Efficient Repetition Path Traversing

Graph database (GDB) is one of the best approaches for enabling efficient management of relationships in the graph. It retains the shape of the graph to retrieve the required nodes through their interconnections. GDBs have an attractive characteristic called index-free adjacency, enabling users to traverse one edge at a fixed computing cost for vast and complex graph data. However, it is quite likely that GDBs cannot avoid reaching already-scanned nodes from different start nodes by repeatedly traversing edges that have a specific relationship type. This is because GDBs cannot consider the node degrees of each node in a graph. Consequently, when a GDB reaches a hub, the number of nodes that need to be arrived at by traversing different edges increases depending on the hub's adjacent nodes. Therefore, an inefficient process increases the cost of extracting a sub-graph in conventional GDBs. Accordingly, in this paper, we propose an efficient approach to repeatedly traversing edges belonging to a specific relationship type by distinguishing between hub s and other nodes. In particular, our approach manages repetition path s from each hub in addition to a list of the adjacent node in a conventional GDB; this GDB aims to enable us to manage a real-world network effectively.
Teaching IT Specialists with the Help of Online Learning

Purpose: The purpose of the chapter is to analyze mobile learning for improving students’ English proficiency using personal electronic devices and to assess English language teaching and learning supported by electronic media and tools. Design/methodology/approach: The authors determine the definition of mobile learning, the classification of devices, the advantages and disadvantages of mobile learning. They consider mobile learning to be an advanced educational technology both in a classroom and for extracurricular lessons for Higher School students of technical specialties. The educational standards of Higher School require solving the problem of future specialists’ professional communicative skills development and the authors analyze the ability of mobile learning to meet this task because digital electronic revolution keeps us connected with almost everyone around the world and makes necessary information available anywhere, at any time. Mobile learning can be applied inside and outside the classroom using personal mobile devices. Mobile education extends the boundaries of the traditional pedagogical methods with the effective integration of technology creating a favorable learning environment. Findings: It deserves attention that the paper is written completely on the results obtained by the authors during their practical work. They created and tested the exercises with mobile learning applying on the base of “Moodle mobile” which helps teachers to meet the requirements of the constantly changing modern society demands for the professional education development. The exercises selection and systematization gives teachers an opportunity to apply them in their everyday work. They analyzed mobile teaching methods as an advanced educational technology, gave a scientific review of the mobile education benefits and its drawbacks and suggested the recommendations on the new online practice which is used in the educational environment of technical Higher Schools. The authors underlined the disadvantage that there are some teachers who have not got enough skills to work with personal electronic devices. As for students, they feel free to use them for mobile learning because it enables them to improve their English proficiency. Originality/value: Using the tasks and exercises on the base of “Moodle mobile” during the lessons, the authors really confirmed the original concept of the new mobile learning teaching methods applying in the educational activity of technical Higher Schools’ students. The authors assessed the authenticity of the practically obtained results, offered practical recommendations for the mobile learning teaching methods, and proved the necessity to integrate the mobile devices into Higher Schools’ educational programs for educational technologies modernization with the purpose to improve the English language fluency level of the future specialists.
Remote driving technology based on 5G

Abstract Relying on the 5G development wave, this project realizes human-vehicle interaction in the simulated cockpit in an innovative way, and remotely controls vehicle-like robots (unmanned vehicles). It aims to build a vehicle remote control system with a lower cost and a more stable way, and develop a remote driving robot based on 5G communication for distribution, disinfection or more precise tasks.
Development of an IoT seismograph

Earthquakes have troubled mankind for thousands of years, mainly due to the extensive and significant disasters they can cause. The effects of a strong earthquake can be devastating; both in terms of building infrastructure and in terms of human losses. Earthquake effects can also be divided into direct, such as the collapse of a building, and indirect, such as causing fires from liquid/gaseous fuel leaks. Given the significant damage that occurs at regular intervals in various parts of the world due to an earthquake and especially in seismogenic areas, it is necessary to monitor seismic activity and have the possibility of warning of possible hazards. This paper focuses on the development of a low-cost seismograph with IoT capability. The seismograph can operate either as standalone, protecting the building that has been installed or it can operate as a node of a greater system protecting a greater area.
Gamifying the “unspoken”: Designing to Resolve Myths on Contraceptives among the Himba people of Namibia.

In this paper, we highlight our experiences of co-designing e-health technology solutions with the Himba people of northern Namibia. Using a user-centered and participatory design approach, we found out that there are various health information challenges faced by the people, many of which can be attributed to misconception and myths. We report on the design process used to develop a prototype of a HopScotch Game to help in passing correct information and dispelling myths and misconceptions. We also discuss the problems we faced in the process as well as the methodology used and give recommendations for future interventions
Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model

The Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) has been used widely as a natural Bayesian nonparametric extension of the classical Hidden Markov Model for learning from sequential and time-series data. A sticky extension of the HDP-HMM has been proposed to strengthen the self-persistence probability in the HDP-HMM. However, the sticky HDP-HMM entangles the strength of the self-persistence prior and transition prior together, limiting its expressiveness. Here, we propose a more general model: the disentangled sticky HDP-HMM (DS-HDP-HMM). We develop novel Gibbs sampling algorithms for efficient inference in this model. We show that the disentangled sticky HDP-HMM outperforms the sticky HDP-HMM and HDP-HMM on both synthetic and real data, and apply the new approach to analyze neural data and segment behavioral video data.
Texture Based Material Classification Using Gabor Filter

The image can be classified using various feature extraction techniques. Problem defined material class using properties of texture. The novel approach of this paper is to extract features of an image using the Gabor filter. Authors defined the method which combines Color, Luminance and Texture features. Texture features extracted by calculating the phase and magnitude of the Gabor Filtered image. The classification is carried out using KNN classifier with four different distance measures. Compare the statistics of the result under different distances types used in experiments.
Application of Electronic Operation Ticket for Intelligent Maintenance of Power Grid via Hololens

This paper presents a successful case called “electronic operation ticket” applying Mixed Reality (MR) device HoloLens for intelligent maintenance of high-voltage power grid. Information visualization is proposed with typical AR environment/model settings and the identification/tracking technologies. Experimental results show that the maintenance of power grid using electric operating tickets could improve the accuracy and safety options in dangerous environments, especially for those wrong options must be forbidden, and operator wearing HoloLens can easily follow the options listed in the electronic tickets robustly.
Actual Problems of Using Digital Technologies in Russian Higher Education

The article deals with the introduction of digital technologies in such an important social sphere of the economy as education. The purpose of the research is to analyze the prospects for their use as a result of changes in the need for a new type of specialists for the digital economy. It is proved that a radical and abrupt rejection of traditional methods of education as a source of knowledge in the next few years is hardly possible, since it is necessary to create economic, legal, social, material, and psychological foundations for their implementation. This will be largely due to the academic mobility of teachers and students, changes in the labor market, increased technical support for the educational process, and other processes. The research methodology consists in using system approach, cause-and-effect, economic-statistical, abstract-logical, and comparative analysis. The informational basis of the study in the framework of this article is the legal acts on the digital economy, statistical data, and electronic resources. The problems of introducing certain digitalization tools into the higher education system are identified however, based on resources, a generalizing conclusion is made that they are not dominant and do not eliminate the existing traditions of classical University education, while at the same time providing a more dynamic development of the educational services market. Estimates of the prospects for applying certain elements of digitalization in domestic education are presented. Recommendations are given for building models of interaction between the state, business, scientific and educational institutions, ensuring the availability of new quality educational services. The authors also proposed the basics of the conceptual model of digitalization of an educational institution, including new technologies, artificial intelligence in educational and scientific activities, marketing communications and digital interaction within the university, digital marketing, and competitive research projects.
A Cognitive System Process Approach: ELT Pedagogy for a Hybrid Communication Model

A majority of Western instructional approaches promote active learning instructional strategies influencing learners to think critically and creatively, thereby inculcating higher-order thinking skills. Cognitivism or Cognitive theory, an area of study associated with thinking skills, tries to understand the process that happens in the minds of learners that includes language learning and its use. As opposed to the behaviourist notion that language is learnt automatically by repetition and re-enforcement, the cognitive approach looks at it as a conscious and controlled thinking process that involves understanding and reasoning. With the advent of Artificial Intelligence and IoT [Internet of things], the day is not far when human beings will transcend known channels of interface to respond to machines, and communicate through a voice-enabled interface. This article is a study on the need to re-orient second language pedagogy to accommodate this futuristic reality and design a framework to promote better language acquisition.
Less Is More: Rejecting Unreliable Reviews for Product Question Answering

Promptly and accurately answering questions on products is important for e-commerce applications. Manually answering product questions (e.g. on community question answering platforms) results in slow response and does not scale. Recent studies show that product reviews are a good source for real-time, automatic product question answering (PQA). In the literature, PQA is formulated as a retrieval problem with the goal to search for the most relevant reviews to answer a given product question. In this paper, we focus on the issue of answerability and answer reliability for PQA using reviews. Our investigation is based on the intuition that many questions may not be answerable with a finite set of reviews. When a question is not answerable, a system should return nil answers rather than providing a list of irrelevant reviews, which can have significant negative impact on user experience. Moreover, for answerable questions, only the most relevant reviews that answer the question should be included in the result. We propose a conformal prediction based framework to improve the reliability of PQA systems, where we reject unreliable answers so that the returned results are more concise and accurate at answering the product question, including returning nil answers for unanswerable questions. Experiments on a widely used Amazon dataset show encouraging results of our proposed framework. More broadly, our results demonstrate a novel and effective application of conformal methods to a retrieval task.
Persona Modelling via Correlation and Regression Analysis in CCI Gamification

Segmentation plays an important aspect in persona modelling. Numerous researches directed to discover better choices to improve the accuracy of the segmentation process so that the narrative writing will produce the best persona model. Modelling persona that suit the different children behaviors, goals and attitudes towards the use of gamification in Children Computer Interaction (CCI) might be difficult. Interviews and observations conducted during the data collection phase before show that children have different expectations when playing games and their emotions and attitudes change when asked the same questions repeatedly and sometimes, they are not sure of the answer. Thus, this paper aims to discuss the relationship between cognitive and physical development with social/emotional development using correlation and regression analysis.
Bitcoin: An Investment Management Tool-Comparison between risk and average returns of different financial assets with BTC

The paper provides a detailed understanding about what exactly Bitcoin (BTC) is. It also answers the question about where and how to use bitcoin as a consumer. The paper elaborates about how bitcoin can be earned and generated along with an ease to understand explanation about its technology. The objective of the paper is to identify whether BTC is still a feasible asset to make an investment in as compared with other existing securities and assets for both short term and long-term investors in the global market. The purpose is to figure out if bitcoin has potential in 2020 and coming years and will it yield high returns even after it has seen a price drop in 2019. Bitcoin became popular when its price peaked to almost $20000 in 2017. Global investors not only look at BTC in short term speculative prospective but also as a long-term investment asset hence it is called as the Digital Gold. BTC is also considered to be highly volatile in nature which is why studying the risk factor involved in investing in it becomes very important. Both mean variance approach and correlation approaches are used to evaluate the risk involved in BTC as an asset and comparison is made with other popular global assets to see if investing in Bitcoin is an ideal option or not.
A Siamese Network Tracking Algorithm Based on Hierarchical Attention Mechanism

Abstract A siamese network tracking algorithm based on hierarchical attention mechanism is proposed in this paper. In order to obtain more robust target tracking results, different layer features are fused effectively. In the process of extracting features, attention mechanism is used to recalibrate the feature map, and AdaBoost algorithm is used to weight the target feature map, which improves the reliability of the response map. Besides, the Inception module is also introduced which not only increases the width of the network and the adaptability of the siamese network to the scale, but also reduces the parameters and improves the speed of network training. Experimental results show that this method can effectively solve the impact of background clutter and improve the accuracy of tracking.
A Stochastic Approach to Identify POS in Iraqi National Song using N-Iterative HMM using Agile Approach

Abstract This research article conveys the use of an agile approach for building an N-iterative HMM model for POST (Part of Speech Tagging) analysis. The agile model is a phenomenon or approach which has vast application. The implementation of such an iterative model is discussed in this paper. Most effectively, the information is conveyed with the help of the exact word we use during the communication. The sentence may not be a complete sentence or grammatically correct sentence, but the purpose of communication is served without any hurdle. Ages witnessing the evolution of the language earlier medium was sign language that might not contain any language communication rules that can be completed. Now complete language with so many tools and API is available, but the way preferred for the processing is the same (logically). The designed iterations lead to improved quality validation by using the word by word score calculation. The experiment is conducted to complete Part of Speech Tagging (POST) for Iraqi National Song (data set of translated Iraqi national song), and the stochastic approach used for completing the tagging is Iterative Hidden Markov Model. The results of the experiments convey the positive impact of the iterative approach over accuracy.
Research on Information Fusion Technology of Multi-Safety Information in Civil Aviation

The fuzzy reasoning and evidence theory were applied to the research of civil aviation safety information fusion in this paper. In the aspect of single event information fusion, the case simulation of "severe weather" event and "runway invasion" event was studied by using fuzzy reasoning and Matlab language programming simulation, which showed the feasibility of information fusion by using fuzzy reasoning. In the aspect of multi event information fusion, the research of the paper used the evidence theory to simulate the "bad weather" event and "runway intrusion" event, which explained the feasibility of the information fusion using the evidence theory.
Research on Agricultural Product Supply Chain Based on Internet of Things and Blockchain Technology

Regarding the problem of low customer satisfaction of agricultural products, difficulties in managing agricultural product supply chains, and low trust in the business entities of each link in the agricultural product supply chain, the efficiency of the agricultural product supply chain is not high. Based on the advantages of blockchain technology, the agricultural product supply chain is optimized and reconstructed. The operation mechanism of agricultural product supply chain under blockchain technology, and the development path of agricultural product supply chain under current blockchain technology is analyzed.
Study of water release that is absorbed by super absorbent polymer in disposable baby diapers

Super Absorbent Polymer (SAP) was the main component in disposable baby diapers. The functions of SAP were to absorb and to hold the liquid in disposable baby diapers. After the water was be absorbed by SAP, it was difficult to be released back into the environment. One of the way to release the water absorbed by SAP was conducted by addition of hygroscopic salt into the SAP. This research was conducted to determine the optimum addition of hygroscopic salt in saturated SAP and then to measure the water that can be released form SAP. The kind of hygroscopic salt sodium chloride (NaCl) and calcium carbonate (CaCO3). The variable of this experiment were quantity of the salt, duration time, and mixing rate. The analysis of this experiment was conducted using Design of Expert (DoE) 6.0.10 program to get the optimum quantity of the water that can be released from SAP. Based on the data, the high of quantity water can be released from SAP after it was added with sodium chloride. The optimum of quantity released water was 386.108 mL with the addition of 11.45 g NaCl and the mixing rate was 98.31 rpm for 29.91 minutes.