Reviewerly/exHarmony huggingface dataset:
Essence of Upbringing Process and the Competence Approach in Training

Research relevance: understanding of teaching concept related to main function of а teacher in teaching and educating students. In the learning process, teacher should pay special attention to students’ cognitive activity development and try to use it more in learning process, using innovative technologies and interactive methods. Research objectives: consider issues from the concept of teaching, “learning” and “competence” and their essence, to reveal the importance of the competence-based approach in teaching. Research materials and methods: article analyzes essence of learning process and authors give their point of view. Research results: educational process essence and importance of learning based on modern competencies revealed. Conclusions: learning competence includes set of a student’s educational achievements, expressed by level of basic and subject competence at a certain stage in educational process.
3D Depth Camera Based Face Mask Recognition Using Spatial and Frequency Features

A novel method for face mask recognition is demonstrated using spatial and frequency features from the captured 3D information by depth camera. Mask types can be further classified, and the average recognition accuracy is 82.11%.
Automatic Face Mask Detection Using a Hide and Seek Algorithm

The coronavirus has affected millions around the world and has inevitably brought about a necessity to wear face masks in official and public places to take the first step in keeping one’s self safe. To monitor personnel and public areas and prevent the spread of the disease we present a scalable and deployable face mask detection system in a real time setting using a novel hide and seek algorithm. Our model, based on openCV library and dlib environment utilizes the facial landmarks where in the algorithm detects face masks through the presence and absence of facial markers. We call this process as seeking and hiding. We overcome present issues of high computational cost of deep learning models and low inference speeds of general detection paradigms. We also validate our algorithm on several aspects which affect the accuracy of other models such as image and face orientation, type of face masks and more. As our model requires no data for model training, we eliminate the highly sensitive issue of acquiring facial data and bias. Our model achieves 98.79\(\%\) precision and 94.81\(\%\) recall.
Errors in Degree Symbols and Descriptors

Investigation titled "Association of Antibiotic Treatment With Outcomes in Patients Hospitalized for an Asthma Exacerbation Treated With Systemic Corticosteroids," 2 published online in the March 2019 issue of JAMA Internal Medicine, a quiz answer option has been updated.In Question 4, option C has been changed to "Lower risk of treatment failure."The quiz has been updated online.
Few-Shot Learning Based on Convolutional Denoising Auto-encoder Relational Network

In this paper, we introduce the embedded learning idea in the learning model to design a few-shot learning algorithm based on convolution denoising auto-encoder relational network. The purpose is to solve the problem of high cost and small amount of data during the spacecraft’s orbit operation. By building the end-to-end relationship network and learning relationships between each sample, we can diagnose the fault of the spacecraft thermal control system effectively with few samples. The experimental results show that the classification algorithm in this paper has a significant improvement in accuracy compared with traditional deep learning methods, and avoid overfitting problem effectively.
Peer review declaration

The review processes in the 6 th ICSBE 2021 were conducted using own system named conference management system (CMC), which was done by expert referees from the professional (national and international referees) and close scientific background. All the accepted papers passed two round review processed by two different reviewers, where each of them did not know. Followings are detail peer review information. • Type of peer review: Double-blind Peer review was conducted by double blind type with both of author and reviewers do not each other. And, in the paper, the author did not write the name and affiliation in the review processes. Review processes were done by two round reviews: 1 st round: review and comments by two reviewers, and 2 nd round: reviewers checked any revision from author based on the comments. • Conference submission management system : The 6 th ICSBE used conference management system (CMC) to deal various tasks including submitting your paper, receiving the results of paper review, submitting the final (camera-ready) version of your paper, registering as participant (as a presenter or an observer) in the Conference, receiving invoice to be paid prior to the Conference, uploading your proof of payment and receiving the receipt of your payment, receiving unique QR-code for on-site registration, receiving certificate of participation in an electronic form. Following is the link of CMC system: https://icsbe.tsipil-uii.ac.id/otentifikasi/ • Number of submissions received : We received 81 papers • Number of submissions sent for review : Number paper for review is 76 papers • Number of submissions accepted : Number paper accepted is 50 papers. • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100) : Acceptance rate is 66%. • Average number of reviews per paper : Each paper was two round reviews. • Total number of reviewers involved : Total number reviewers involved were 44 people including national and international reviewers. • Any additional info on review process : In the review process, the authors have to provide the revision report using revision report template. The paper rejection will be taken in following conditions: 1) Not using English, 2) revision is not performed based on reviewer comments, 3) not fit the IOP template, 4) papers double submitted, and 5) return revision paper out of deadline. • Contact person for queries : Name : Dewi Wulandari, S.Hut., M.Agr., Ph.D Affiliation : Universitas Islam Indonesia Email : dewi.wulandari@uii.ac.id
Evaluating and Improving OCR Efficiency

The purpose of this research is to establish a method for OCR quality evaluation in different archival situations and stages of document ingest process. The conducted experiments explain the importance of OCR optimization using the example of Croatian typewritten materials. Furthermore, the paper discusses the importance of unique, or distinct, words in document retrieval.
EXPERT ASSESSMENT OF TECHNICAL PREPAREDNESS INDICATORS OF QUALIFIED GRECO-ROMAN WRESTLERS AT THE STAGE OF SPECIALIZED BASIC TRAINING

Purpose: to determine the quality of technical actions of qualified Greco-Roman wrestlers at the stage of specialized basic training.Material and methods: method of expert evaluation; methods of mathematical statistics. Results:The results of the study showed that the experts evaluated the technical actions in standing position, which were performed by qualified wrestlers of the experimental group before the pedagogical experiment, not higher than 3.65 points.After the pedagogical experiment, four technical actions received average scores above four points: turn down -4.27 points, hip throw -4.15, dumping -4.13 and pushing out of the mat -4.00 points, respectively.It indicates a significant improvement in the quality of technical actions by the wrestlers of the experimental group (p <0.01).In the athletes of the control group, when performing technical actions in standing position, the expert assessment did not exceed 3.98 points (turn down).The experts rated the quality of technical actions in the referee's position by the wrestlers of the experimental group with higher scores than at the beginning of the pedagogical experiment, where the best score was 3.78 points (holding in the referee's position).After conducting a pedagogical experiment, for technical actions: turn-over with body-hold, back belt throw and holding in the referee's position, the athletes of the experimental group received average scores of 4.45, 4.05 and 4.32 points, respectively.It indicates a significant improvement in the quality of technical actions by the wrestlers of the experimental group (p <0.01).The wrestlers of the control group also increased their indicators of expert evaluation, but significantly less than the athletes of the experimental group (the highest score -3.98).Conclusions: It was found that according to the indicators of expert assessment on a 5-point scale after the pedagogical experiment, the quality of the performance of all technical actions among the wrestlers of the experimental and control groups increased.However, the increase in the indicators of values is higher among the athletes of the experimental group.When performing technical actions in a standing position, the wrestlers of the experimental group improved their results in the range from 13.69% to 23.64%; control group athletes -from 6.61% to 9.37%.When performing technical actions in the referee's position, the athletes of the experimental group increased their indices in the range from 13.44% to 27.50%; control group athletes -from 2.22% to 9.54%.It indicates a significant improvement in the quality of technical actions performance by the wrestlers of the experimental group (p <0.01) in comparison with the athletes of the control group.Key words: expert assessment of technical preparedness of Greco-Roman style wrestlers; holds in the standing position; holds in the referee's position; stage of specialized basic training.
Access to Archives and ICARUS Digital Platforms: Data Protection in Theory and Practice

Access to archival material is a complex issue, wider than archival profession and related to legal, administrative and political factors, and increasingly to the IT sector as well. This area is fundamentally regulated by archival legislation, but due to the existence of other relevant regulations with different accessibility approaches, archive regulations and procedures need to be systematically harmonized with current regulations, leading to numerous open issues in the practical work of the archives. In this paper the author presents a European legal framework on the use of information and data protection relating to archival material in the digital environment, and analyses its practical implications through the example of ICARUS's international digital archive platforms.
Spatially variant biases considered self-supervised depth estimation based on laparoscopic videos

Depth estimation is an essential tool in obtaining depth information for robotic surgery and augmented reality technology in the current laparoscopic surgery robot system. Since there is a lack of ground-truth for depth values and laparoscope motions during operation, depth estimation networks have difficulties in predicting depth maps from laparoscopic images under the supervised strategy. It is challenging to generate the correct depth maps for the different environments from abdominal images. To tackle these problems, we propose a novel monocular self-supervised depth estimation network with sparse nest architecture. We design a non-local block to capture broader and deeper context features that can further enhance the scene-variant generalisation capacity of the network for the differences in datasets. Moreover, we introduce an improved multi-mask feature in the loss function to tackle the classical occlusion problem based on the time-series information from stereo videos. We also use heteroscedastic aleatoric uncertainty to reduce the effect of noisy data for depth estimation. We compared our proposed method with other existing methods for different scenes in datasets. The experimental results show that the proposed model outperformed the state-of-the-art models qualitatively and quantitatively.
A Perspective from Information Theory

With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an online resource, this textbook is an invaluable tool for the upper undergraduate and graduate student.
Ethics and Engineering Design

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Deep Learning Algorithm Aids Breast Cancer Detection by Mammography

Abstract Using deep learning, a method to detect breast cancer from DM and DBT mammograms was developed.
Removing the Blurring from X-Ray Image Using BM3D Technique

The x-ray image quality of normal patient is needed to enhance to diagnose accurately. For this reason, block-matching 3D (BM3D) technique is chosen for denoising the x-ray images. The currently the best BM3D denoising system utilizes a white Gaussian noise (WGN) design. The similar 2D x-ray image is converted to 3D data arrays by grouping to improve the sparsity and it is called grouping. Collaborative filtering is a unique method for dealing with these three-dimensional groups. The collaborative filtering reduces noise, demonstrating even the details of image shared by grouped blocks while preserving the crucial unique characteristics from every individual block. After that, the shifted blocks are replaced with new positions. As these blocks coincide, we get a variety of special predictions with each pixel, which we have to combine. The Wiener filtering process is implemented in the transform coefficients to a post-thresholding signal in the present BM3D algorithm for improved noise removal. Wiener filtering of transform domain co-efficient is used based on the properties of x-ray images in terms of PSNR and SNR value. The hard thresholding system is used in previous step to denoise the x-ray image in the utter lack of a ground-truth signal. The performance of BM3D technique is compared with wavelet transform to evaluate image quality.
Jonassen model in the development of integrative projects

Instructional design has been integrated not only in processes for the generation of didactic materials oriented to education but also in other types of projects oriented to industry, the health sector, commerce, etc., where planning is reflected of solving a problem that involves a process of teaching or learning knowledge. This article presents the process of developing a mobile application using as a basis the implementation of the Jonassen Instructional Design model. Being a constructivist model, the reader will be able to observe how diverse knowledge of various methodologies are integrated, such as the Snowflake that is well structured and focuses on planning and creating novels, and the OOHDM that is oriented to the development of web applications using elements of hypermedia, so that in the end you get a useful and versatile mobile application that you can download freely from the Google Play Store.
Paths to Distance Learning at A University and its Application

The results of a 2019 sociological survey conducted on a nationwide structured Abstract sample of extramural students (2019) and graduates (2000–2018) of Higher Edu cational Institutions (HEIs) are used to reveal cultural, socio-economic, territorial origin of extramural students and graduates and identify the types of their educational strategies as well work experience and status at the enrollment stage. We analyze their movements within the socio-occupational hierarchy as a result of obtaining that education. Extramural students differ from full-timers in that they feature a more de mocratic socioeconomic composition and possess a different amount of educational resources at the enrollment stage. These differences are presented in the form of four educational trajectories, which correlate with indicators of origin on a scale from “weaker” to “stronger”. “Advantages / disadvantages” of the educational trajectories and status at the enrollment stage, affect the degree of success in the application of distance education in the labor market in accordance with the level of qualifications and specialties of the diploma. Extramural students / graduates are formed from two streams: those who enter the HEIs immediately after secondary education and those who come with work experience. The latter get a higher return on the labor market from distance education.
A License Plate Super-resolution Algorithm based on Dictionary Learning and Neural Network

A license plate super-resolution algorithm was proposed based on dictionary learning and neural network. Firstly, a high-resolution dictionary was built for each number on license plate. Secondly, the dictionary was applied to each blurry number image respectively to fill in the missing feature information. Then, the images with features filled were input into the neural network to perform the feature extraction, pixel shuffle and other operations. After that, the final super-resolved image was obtained. Experimental results showed that proposed algorithm outperformed existing super-resolution algorithms like Bicubic, SRCNN, SRGAN and VDSR as applied to blurry license plate images, and greatly improved the recognition rate.
Improving the Accuracy of Walking Context Recognition Using Step Rate

Demand for recognition of purchasing behavior has been increasing due to the expectation that it would be profitable in marketing. A method of recognizing purchase behavior involves classifying customer behaviors into three states: "moving", "searching" (for a product) and "observing" (i.e., examining the label, etc.) on the basis of acceleration and angular velocity data obtained from the sensor of a smartphone. The method can recognize a user’s purchasing behavior without relying on external infrastructure such as cameras or radio frequency identifiers (RFIDs). However, its recognition accuracy is low; it falls below 30 percent especially in the searching state. In this study, we focus on the fact that the number of steps per time (step rate) is different in each state. That is, the customer’s step rate becomes slower as states change from moving to observing, as it is harder to examine products while on the move. In addition, we propose a two-stage classifier based on the differences in walking motion. Through these features and the classifier, we aim to improve the accuracy of behavior recognition. For an evaluation, we asked subjects to freely walk and shop for products in a supermarket and took movies of them. We compared the classification accuracies of three types of feature: base features, step-rate features, and the total feature combining the first two types. Our evaluation indicated the accuracy score of the step-rate features improved by 12.7% and that of the total feature improved by 18.2% relative to using the base features. In addition, a two-step classifier using the total features improve the accuracy score by 2.3% compared with the one-stage classifiers. By further subdividing purchase behaviors into ones such as "crouching motion", we can further improve accuracy and also recognize purchase behaviors in more detail.
Two-Rebit Entanglement: Theory and Experiment

We characterize entanglement over real and complex, composite quantum systems. Methods are formulated and applied to simultaneously certify inseparability and separability for two rebits and two qubits, respectively.
Contemporary Intercultural Educational Programs for Ethnographic and Historical Museum

This article presents the main dimensions of the intercultural educational environment, systematized in the framework of research on contemporary intercultural educational programs for ethnographic and historical museums. In this context, the results of a study of the opinion of teachers on the need and importance of the implementation of intercultural educational programs for ethnographic and historical museums have been interpreted.
Use Cases

Over the course of this book, we have drilled into various aspects of blockchains as well as use cases to help us focus on those aspects. In this chapter, we will take a step up and view the array of possibilities of use cases that were executed in various industries for various purposes. As we walk through this journey of use cases and the experience of building and executing some, the reader is required to refer back over the initial chapters to correlate the elements of blockchain and to map the appropriate tools, architectures, consensus, and so on. If a particular use case uses a particular stack, one can always challenge with better protocols and architectures to yield better throughputs and performances.
Model Checking Quantum Markov Chains

This chapter develops model-checking techniques for a much larger class of quantum systems modelled as quantum Markov chains or more generally, quantum Markov decision processes. The differences between quantum automata and quantum Markov systems require us to develop algorithms for the latter that are fundamentally different from those for the former.
System to Crawl Web and Forum for Medical Data

Medical Practitioners are those who require to have updated information of drugs, diseases, diagnosis and combinations of prescriptions. Internet is the rich source of information. The first attempt of every person is to search internet for his queries. But the relevant information searching and identifying the relevancy and accuracy of huge data is still a challenge. This paper focuses on data retrieval related to medical field. Forum crawler and web crawler will perform crawling of data from forums and web respectively. This system can be used by doctors as well as pharmacists to search medical related information as per their need.