Reviewerly/exHarmony huggingface dataset:
e-IATROS — A Virtual Medical Doctor and Its Dialogue Systems: Features, Emotion, Learning

The current incremental need for immediate responses (real-time) on many medical emergencies is necessity for an advanced society. In many cases, people who are living in rural areas need a critical, for their healthy, commuting time to a Medical Center (Hospital). In addition, human physicians have limited capability for offering their services to large number of emergencies or medical cases. Thus, there is a need for the medical technologies to take the advantage of the advanced IT and Engineering for the design and development of Virtual Doctor Diagnoses Systems to facilitate such needs. This paper presents the components needed for the development of such an intelligent system, called e-IATROS, and its Virtual Doctor (VDr) dialogue systems. The e-IATROS system has the potential to simultaneously talk to a large number of human patients without humans to detect that they are talking to a computer based system. This is a necessary feature for convincing human patients to trust the machine and express their issues. To do so, the e-IATROS has to use the voice of the actual human doctor for each human patient. Each VDr dialogue system mainly interacts with a patient extracting non-measurable and measurable symptoms to contribute to the generation of possible prognosis. The e-IATROS system is presented with its capabilities recognizing the patient emotion and learning through the process.
The use of online course as part of blended leaning technology in teaching foreign languages at non-linguistic university

The study looks into the issues of enhancing the proficiency of independent work of sophomores on developing their foreign language communicative competency by means of implementing an online course as part of blended learning technology. The authors investigated the question of students’ perception and their attitude regarding online learning and its effectiveness in the process of preparation for standardized testing in English at the National Research University Higher School of Economics. The paper depicts didactic and psychological potential of blended learning and describes the stages and results of the training experiment.
Design of Heterogeneous Data SQL Access Scheme Based on PostgreSQL

Big Data Services Platform has important applications in the power distribution system. Grid operation will generate a large amount of measurement data, this type of data is generally stored in NOSQL database, and the data cannot be obtained through SQL statement. In order to maximize the value of the data, the paper needs to develop the SQL engine based on PostgresSQL Foreign Data Wrapper (Postgres_fdw). By analyzing the features of PostgreSQL and the shortcomings of the existing Universal Measurement Data Access Interface (UAPI), paper uses hierarchical strategy, and develops SQL engine based on Postgres_fdw, and to realize the function of the big data platform to obtain measurement data by using SQL, an external table space estimation scheme and SQL analysis scheme for measurement data has been proposed. Field functions and performance tests were performed to verify the effectiveness of the engine.
Feasibility Study of a New Security Verification Process Based on Face Recognition Technology at Airport

Abstract In order to optimize the mode of manual security identity verification at security checkpoints in the domestic airports in China, this paper proposes a new security identity verification process based on face recognition technology. This paper also presents the carried out practical tests on the feasibility and effectiveness of the proposed process. The new process includes two important steps: self-service centralized verification and automatic face recheck of passengers. The test results show that the process is effective and cost efficient. The technology significantly reduces the rate of human error, dramatically relieves the workload of the security staff and shorten the passenger’s time spending at identity check in the airport.
Vector representations of graphs and distinguishing quantum product states with one-way LOCC

Distinguishing sets of quantum states shared by two parties using only local operations and classical communication measurements is a fundamental topic in quantum communication and quantum information theory. We introduce a graph-theoretic approach, based on the theory of vector representations of graphs, to the core problem of distinguishing product states with one-way LOCC. We establish a number of results that show how distinguishing such states can be framed in terms of properties of the underlying graphs associated with a set of vector product states. We also present a number of illustrative examples.
Local JPEG Grid Detector via Blocking Artifacts, a Forgery Detection Tool

Image JPEG compression leaves blocking artifact traces.This paper describes an algorithm that exploits those traces to locally recover the grid embedded in the image by the JPEG compression.The algorithm returns a list of grids associated with different parts of the image.The method uses Chen and Hsu's cross-difference to reveal the artifacts.Then, an a contrario validation step according to Desolneux, Moisan and Morel's theory delivers for each detected grid a Number of False Alarms (NFA) which tells how unlikely it is that the detection is due to chance.The only parameter is the step size of the windows used, which represents the exhaustiveness of the method.The application to image forgery detection is twofold: first, the presence of discrepant JPEG grids with low NFA is a strong forgery cue; second, knowledge of the grid is anyway required for further JPEG forensic analysis.
Using the Proteus virtual environment to train future IT professionals

Based on literature review it was established that the use of augmented reality as an innovative technology of student training occurs in following directions: 3D image rendering; recognition and marking of real objects; interaction of a virtual object with a person in real time. The main advantages of using AR and VR in the educational process are highlighted: clarity, ability to simulate processes and phenomena, integration of educational disciplines, building an open education system, increasing motivation for learning, etc. It has been found that in the field of physical process modelling the Proteus Physics Laboratory is a popular example of augmented reality. Using the Proteus environment allows to visualize the functioning of the functional nodes of the computing system at the micro level. This is especially important for programming systems with limited resources, such as microcontrollers in the process of training future IT professionals. Experiment took place at Borys Grinchenko Kyiv University and Sumy State Pedagogical University named after A. S. Makarenko with students majoring in Computer Science (field of knowledge is Secondary Education (Informatics)). It was found that computer modelling has a positive effect on mastering the basics of microelectronics. The ways of further scientific researches for grounding, development and experimental verification of forms, methods and augmented reality, and can be used in the professional training of future IT specialists are outlined in the article.
Towards Ubiquitous Learning of Balinese-to-Latin Script Transliteration as Part of Balinese Language Education

As part of the Balinese culture in Indonesia, the Balinese script has rarely been used today.Its Balinese-to-Latin script transliteration knowledge is also affected by that condition and has caused concern over the threat of extinction.This study is aimed to preserve that knowledge through a technological approach by collaboration between Information Technology and Balinese Language discipline.This research analyzed the ubiquitous learning aspect of Balinese-to-Latin script transliteration as part of Balinese Language education, which is a mandatory local subject from basic to high school in Bali Province.This analysis was conducted on the Balinese Glyph Recognition (BalineseGR) web application that was developed as a technology product of Universitas Pendidikan Ganesha (Undiksha), Indonesia.Balinese is a sort of Optical Character Recognition (OCR) web application that receives a Balinese script image and outputs Latin text.It was considered as the first Balinese-to-Latin script transliteration web application using JavaScript for the algorithm.Recently, its initial development has covered transliteration knowledge of eighteen Balinese script's basic syllables (Akśara Wreşāstra) only.Since ubiquitous learning is supported by mobile computer through a wireless network, and it is aimed to provide learners with content and interaction anytime and anywhere, BalineseGR web application has several aspects to concern about (1) its counterpart mobile application development where image input not only from a file but also more useful directly from a camera, and (2) richer knowledge content, including a transliteration of the vowels (Akśara Suara), additional basic syllables (Akśara Şwalalita), sound killers (Pangangge Tengenan), numerals, punctuations, ligatures, and miscellaneous glyph.
Digital Library: An Innovation in Infrastructure in Learning and Development amongst Students

Web distributed network system made extension for inquire about in the territory of data framework and its related fields. Advanced Library, one of the latest improvements in Library and Information Science, which help its client to look for data through internet browser. Computerized Library is sorted out grouping of data, with its bolstered administrations and a spot where the data is kept in advanced arrangement and can be recovered over a system. Since most recent multi decade specialists are concentrating on the clients of Digital Library to grow progressively proficient and viable framework to offer quality assistance to clients. The point of this paper is to furnish writing on Digital Library as for its clients that might be useful for future research. The paper examines about the users driven methodology with regards to Digital Library.
Benchmarking UAQ Solvers

The User Authorization Query (UAQ) Problem is key for RBAC systems that aim to offer permission level user-system interaction, where the system automatically determines the roles to activate in order to enable the requested permissions. Finding a solution to a UAQ problem amounts to determining an optimum set of roles to activate in a given session so to obtain some permissions while satisfying a collection of authorization constraints, most notably Dynamic Mutually-Exclusive Roles (DMER) constraints. Although the UAQ Problem is NP-hard, a number of techniques to solve the UAQ problem have been put forward along with encouraging, albeit inconclusive, experimental results. We propose a methodology for designing parametric benchmarks for the UAQ problem and make a novel suite of parametric benchmarks publicly available that allows for the systematic assessment of UAQ solvers over a number of relevant dimensions. By running three prominent UAQ solvers against our benchmarks, we provide a very comprehensive analysis showing (i) the shortcomings of currently available benchmarks, (ii) the adequacy of the proposed methodology and (iii) that the reduction to PMaxSAT is currently the most effective approach to tackling the UAQ problem.
Probabilistic Tsunami Heights Model using Bayesian Machine Learning

Song, M.-J. and Cho, Y.-S., 2020. Probabilistic tsunami heights model with Bayesian machine learning. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1291–1296. Coconut Creek (Florida), ISSN 0749-0208.Tsunamis, which are long-period oceanic waves, are known as catastrophic disasters and can cause large losses of human life, as well as property damage. To date, tsunami research has focused on developing numerical models to predict accurate tsunami heights and run-up heights, because hydraulic experiments are associated with high costs for laboratory installation and maintenance. Recently, artificial intelligence (AI) has been progressed, demonstrating enhanced performances in science and engineering fields. This study explored the use of AI to estimate maximum tsunami heights. Bayesian machine learning, a neural network method, was employed, and numerical simulation was performed for historical and probable maximum tsunami events.
Lossless Hybrid Coding technique based on Quasi Fractal &amp; Oscillation Concept Method for Medical Image Compression

The Image compression is the most important entity in various fields. Image compression plays vital role in many applications. Out of which biomedical is one of the challenging applications. In medical research, everyday there is fast development and advancement. Medical researchers are thinking about digital storage of data hence medical image compression has a crucial role in hospitals. Here Morphological filter &amp; adaptive threshold are used for refinement and used Quasi Fractal &amp; Oscillation concept for developing new hybrid algorithm. Oscillation concept is lossy image compression technique hence applied on Non-ROI. Quasi fractal is lossless image compression technique applied on ROI. The experimental results shows that better CR with acceptable PSNR has been achieved using hybrid technique based on Morphological band pass filter and Adaptive thresholding for ROI. Here, innovative hybrid technique gives the CR 24.61 which improves a lot than hybrid method using BTC-SPIHT is 5.65. Especially PSNR is also retained and bit improved i.e. 33.51. This hybrid technique gives better quality of an image.
What Are People Asking About COVID-19? A Question Classification Dataset

We present COVID-Q, a set of 1,690 questions about COVID-19 from 13 sources, which we annotate into 15 question categories and 207 question clusters. The most common questions in our dataset asked about transmission, prevention, and societal effects of COVID, and we found that many questions that appeared in multiple sources were not answered by any FAQ websites of reputable organizations such as the CDC and FDA. We post our dataset publicly at https://github.com/JerryWeiAI/COVID-Q. For classifying questions into 15 categories, a BERT baseline scored 58.1% accuracy when trained on 20 examples per category, and for a question clustering task, a BERT + triplet loss baseline achieved 49.5% accuracy. We hope COVID-Q can help either for direct use in developing applied systems or as a domain-specific resource for model evaluation.
Development of Student Interest in Scientific Research: Experience and Problems of a Regional University

The research featured the problem of attracting university students to scientific research. The article focuses on the experience of the Department of Management, Penza State University of Architecture and Construction. The authors used a survey method to analyze opinions of more than 400 students from regional universities and more than 30 highly qualified experts in the related field. The research objective was to assess the willingness of students to participate in research and to develop useful recommendations on how to organize research activities in various student communities. The present study will be of interest to university students, academics, higher education governing bodies, and scientists that deal with studentship issues.
Effects of Flow Circulations on the Sediment Dynamics in the Deep-water Navigation Channel of the Yangtze River Estuary

Xu, H.-J,; Huang, Z.; Bai, Y., and Bai, Y.-C., 2020. Effects of flow circulations on the sediment dynamics in the Deep-water Navigation Channel of the Yangtze River Estuary. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 723a-727a. Coconut Creek (Florida), ISSN 0749-0208.In this paper, a two-dimensional model is established to estimate the hydro-sediment dynamics in the Deepwater Navigation Channel of the Yangtze River Estuary by calculating the flow field and sediment deposition. The results show that the circulation is mainly caused by shear stress of the flow in the main channel during the maximum flood and ebb tides and that at these times, the circulations are small and close to the groyne roots. At the slack tides, the water level gradient is an indispensable factor, and the circulations are relatively larger and located in the center of the groyne fields. The spatiotemporal characteristics of the sediment dynamics are considered closely related to the flow circulations. Specifically, the flow circulations inhibit the scouring of the groyne fields because these circulations form areas with low flow velocities and an enclosed environment that prevents powerful flow of the deep-water channel into the groyne fields. The results will provide effective support for the safe operation of the Deep-water Navigation Channel in the Yangtze River Estuary.
A Survey: Virtual, Augmented and Mixed Reality in Education

In the upcoming era of technology Virtual Reality and Augmented Reality are not new eye catching technology but still it has some limitations to put a stop for actual enactment.It is true that the progress of new technologies has made it more beneficial to afford the hardware and software made available AR, VR and MR in the number of domains including education.The nature of technologies provides a number of opportunities.It may help from traditional allocation of separate lessons to take care of pastoral responsibility to learning concepts.These technologies fulfill the needs of learners in the technological century.It reinvents the door of education and makes the education field interactive using appropriate virtual settings.This discussion of this works includes the reinvention of education using AR, VR and MR technologies.Its modified way of education fills the needs of practical lessons.
Phonetic Spelling Algorithm Implementations for <i>R</i>

The phonics package provides several functions for indexing words by their English language pronunciation. Over nearly one hundred years, many different algorithms have been developed to support word and name indexing. From Soundex, developed in the early 20th century and predating the digital computer, through to modern digital phonetic algorithms like Phonex, the phonics package provides support for more than a dozen methods. Together, these provide phonetic algorithms appropriate for use in name indexing and name matching across a variety of English language use cases.
Using Formants to Compare Short and Long Vowels in Modern Standard Arabic

This study was concerned with the short vowels in modern standard Arabic words with Consonant Vowel-Consonant Vowel-Consonant Vowel (CVCVCV) structure, and the long vowels in words with Consonant Vowel Vowel-Consonant (CVVC).Even though there has been a dispute on the precise number of Arabic vowels that exist between language studies, this study used the opinion that the Arabic language has three vowels; the elongation of each vowel gave the other three because this is the opinion of classical Arabic linguists which is the source of the Modern Standard Arabic (MSA).Studies said that the first and second formant values (F1, F2) can represent the vowels.In this study, the formants were measured using LPC (Linear Predictive Coding), verifying the measurement to see if the measured follows the pattern of formants measurements of the other studies, and the formants were used to investigate the relationship between short and long vowels.Furthermore, the study figured out if the dialect of speakers can affect the values of formants, even if the spoken language is MSA, some statistical measurements were calculated to evaluate the relationship.
Directions for Explainable Knowledge-Enabled Systems.

Interest in the field of Explainable Artificial Intelligence has been growing for decades and has accelerated recently. As Artificial Intelligence models have become more complex, and often more opaque, with the incorporation of complex machine learning techniques, explainability has become more critical. Recently, researchers have been investigating and tackling explainability with a user-centric focus, looking for explanations to consider trustworthiness, comprehensibility, explicit provenance, and context-awareness. In this chapter, we leverage our survey of explanation literature in Artificial Intelligence and closely related fields and use these past efforts to generate a set of explanation types that we feel reflect the expanded needs of explanation for today's artificial intelligence applications. We define each type and provide an example question that would motivate the need for this style of explanation. We believe this set of explanation types will help future system designers in their generation and prioritization of requirements and further help generate explanations that are better aligned to users' and situational needs.
Temporally Forward Nonlinear Scale Space for High Frame Rate and Ultra-Low Delay A-KAZE Matching System

High frame rate and ultra-low delay are the most essential requirements for building excellent human-machine-interaction systems. As a state-of-the-art local keypoint detection and feature extraction algorithm, A-KAZE shows high accuracy and robustness. Nonlinear scale space is one of the most important modules in A-KAZE, but it not only has at least one frame delay and but also is not hardware friendly. This paper proposes a hardware oriented nonlinear scale space for high frame rate and ultra-low delay A-KAZE matching system. In the proposed matching system, one part of nonlinear scale space is temporally forward and calculated in the previous frame (proposal #1), so that the processing delay is reduced to be less than 1 ms. To improve the matching accuracy affected by proposal #1, pre-adjustment of nonlinear scale (proposal #2) is proposed. Previous two frames are used to do motion estimation to predict the motion vector between previous frame and current frame. For further improvement of matching accuracy, pixel-level pre-adjustment (proposal #3) is proposed. The pre-adjustment changes from block-level to pixel-level, each pixel is assigned an unique motion vector. Experimental results prove that the proposed matching system shows average matching accuracy higher than 95% which is 5.88% higher than the existing high frame rate and ultra-low delay matching system. As for hardware performance, the proposed matching system processes VGA videos (640×480 pixels/frame) at the speed of 784 frame/second (fps) with a delay of 0.978 ms/frame.
Review of dynamic three-dimensional surface imaging based on fringe projection

The dynamic three-dimensional(3D) surface imaging technology based on fringe projection was summarized and the characteristics of typical strategies were analyzed. Firstly, the basic principle of the technique was introduced, including the basic structure of the system, the principle of 3D surface imaging, and the two typical phase extraction methods, phase shifting method and Fourier transform method. Secondly, the dynamic imaging scheme including high speed projection scheme and dynamic 3D surface imaging method using relatively low speed camera was introduced. Thirdly, the absolute phase acquisition methods in dynamic 3D image were introduced, mainly analog and digital coding and area statistical coding, were introduced. Finally, the methods of accurate dynamic phase measurement were introduced.
On a method of synthesis of correlation-immune Boolean functions

Abstract An efficient recursive method for synthesis of correlation-immune Boolean functions is proposed. At the first stage, this method uses minimal correlation-immune functions. A classification of 6-variable minimal correlation-immune functions under the Jevons group is put forward. New results on minimal correlation-immune functions are given.