Reviewerly/exHarmony huggingface dataset:
Development of instructional materials based on mobile learning media (MLM) and its benefits

Abstract This study aims to develop a learning model based on Mobile Learning Media (MLM), test its effectiveness, and describe its benefits. MLM was developed for Computer Numerical Control (CNC) programming courses in vocational high schools. The effectiveness is tested by indicators of students’ higher-order thinking skills (HOTS). Advantages are explored based on their performance in learning. Recently, CNC programming lesson is known as a difficult subject because it requires critical and creative thinking skills. The research design was experimental with a pretest-posttest random control group pattern. Research respondents totaled 120 students with 60 students in the experimental class and 60 students in the control class. The research data includes data on the effectiveness of the model and student learning outcomes. Analysis of research data used descriptive statistical techniques and independent sample T-test with the help of SPSS 2.0 software. The results showed that the use of MLM was effective to improve teacher performance in teaching. MLM can facilitate students to develop HOTS. This is proved by the increase in student learning outcomes after the application of MLM. Based on the analysis of answers accompanied by reasons, students are able to show significant improvement in all critical and creative thinking processes.
Unmasking the impact of m-learning on medical undergraduates

Introduction: Newer m-learning devices have become an integral part of medical education. Documentation of impact of these m-learning devices on medical education is still conflicting. The objective of the study was to determine the impact of m-learning on medical undergraduates.Materials and Methods: After obtaining Institutional Ethics Committee approval, this descriptive type of cross-sectional study was carried out among first to fifth semester MBBS undergraduates at a tertiary care teaching hospital. A 31 item prevalidated questionnaire was distributed among respondents and responses were evaluated.Results: Two hundred and sixty-six completely filled responses were obtained. Male preponderance was seen. Most of the students spent 2–4 h on mobile phones. 54.51% students had knowledge regarding m-learning. 79.8 students had medical apps on their electronic portable devices. There has been an improvement in the communication skills among respondents due to m-learning. Some disadvantages were also documented in our study which includes distraction from studies and use of other applications.Conclusion: The awareness about change in the pattern of learning among medical students from “bench-side” to “web-site” is the need of the hour. Internet connectivity is the major area of concern to be looked upon for better m-learning.The following core competencies are addressed in this article: Medical knowledge, Practice-based learning, and Communication skills.
Review of the monograph: Stromov V.Y., Sysoyev P.V., Zavyalov V.V. Development of Scholars’ Research in a Classical University: Experience of the Derzhavin Tambov State University. Tambov, Publishing House “Derzhavinsky”, 2021, 130 p. ISBN 978-5-00078-439-6

The monograph under review presents a five-year experience of building and functioning of a model of organizing scholars’ research at the Derzhavin Tambov State University. The problem areas of the development of scholars’ research in a classical university indicated in the work are accompanied by proposals for overcoming them. The goals and objectives of the development of scholars’ research in a classical university are outlined. The level model and the main vectors of development of scholars’ research in a classical university, theoretical foundations for the development of the mentoring institute, goals and objectives of the development of the univer-sity-wide student research society are developed. A description of the most striking projects of student self-government in the research area “School of Competencies”, “Youth Entrepreneurship” and “I Want to Be a Post-Graduate Student” aimed at attracting students to research and innovation activities is given. This monograph is a practical guide for building an effective model for organizing scholars’ research in a classical university, contributing to the involvement of a larger number of students in research and innovative activities.
Accurate hierarchical stereo matching based on 3D plane labeling of superpixel for stereo images from rovers

An accurate hierarchical stereo matching method is proposed based on continuous 3D plane labeling of superpixel for rover’s stereo images. This method can infer the 3D plane label of each pixel combined with the slanted-patch matching strategy and coarse-to-fine constraints, which is especially suitable for large-scale scene matching with low-texture or textureless regions. At every level, the stereo matching method based on superpixel segmentation makes the iteration convergence faster and avoids huge redundant computations. In the coarse-to-fine matching scheme, we propose disparity constraint and 3D normal vector constraint between adjacent levels through which the disparity map and 3D normal vector map at a coarser level are used to restrict the search range of disparity and normal vector at a fine level. The experimental results with the Chang’e-3 rover dataset and the KITTI dataset show that the proposed stereo matching method is efficiently and accurately compared with the state-of-the-art 3D labeling algorithm, especially in low-texture or textureless regions. The computational efficiency of this method is about five to six times faster than the state-of-the-art 3D labeling method, and the accuracy is better.
Perceptual Image Hashing Using Surf for Tampered Image Detection

Photographs have become a part of everyone's life. It connects us to our past and is used as evidence in various fields like advertising, intelligence, journalism, science, etc. Today, photographs are replaced by digital images. Digital images are the collection of small bits of data, i.e., pixels, which are stored in computers. The problem with digital images is that they can tamper easily. Tampering is nothing but replacing the original content with some new content. Nowadays, digital images can be tampered effortlessly by using software like Photoshop, PhotoPlus, Corel Paint Shop. In this digital world, it is impossible to find out whether it is a real image or a tampered one. As a result, tampered image detection has become more important to verify digital image authenticity. In this paper, the techniques that are used to detect tampered images which are explained in detail, and also a new method known as perceptual image hashing using the speeded up robust features (SURF) technique is briefed.
Formation of Microclimate in Individual Parts of Public Premises

Abstract Human activity is of a collective and individual nature, since people often spend their working and free time in groups. Modern standards in the Russian Federation determine the parameters of the microclimate depersonalized and on average, the accepted parameters are suitable for 75 % of people, and 25 % would like to have a warmer or cooler ambient air temperature around them, which is associated with the peculiarities of each person’s metabolism. The creation of collective and individual engineering systems in the collective space of the building to the needs of a specific person will create a temperature at the workplace or in places of recreation of the person that will improve the quality of life and productivity, will reduce the incidence. The collective and individual nature of the engineering systems that form the microclimate in the premises will allow you to spend energy resources more economically. The parameters of human metabolism change over time during the working day, day, season and throughout life, which requires constant and periodic adjustment of the temperature regime in an individual space in a collective room.
Learning HDR illumination from LDR panorama images

For indoor scenes, the fourth-order spherical harmonic function is used to model the illumination, resulting in that 48 spherical harmonic coefficients are used to represent the whole scene. The illumination contained in the low dynamic range image is insufficient, so high dynamic range environment maps are adopted in this part, and the aim is to predict spherical harmonic coefficients of the corresponding high dynamic range image from the low dynamic range image. For this problem, the MSE loss function is used in this paper. Experiments verify the effectiveness of our method. The final visual results show that our method can predict accurate spherical harmonic coefficients, and the recovered luminance is realistic.
Geometric manipulation of a decoherence-free subspace in atomic ensembles

We consider an ensemble of atoms with $\Lambda$-type level structure trapped in a single-mode cavity, and propose a geometric scheme of coherent manipulation of quantum states on the subspace of zero-energy states within the quantum Zeno subspace of the system. We find that the particular subspace inherits the decoherence-free nature of the quantum Zeno subspace and features a symmetry-protected degeneracy, fulfilling all the conditions for a universal scheme of arbitrary unitary operations on it.
Systematic Assessment of Interactive Instructional Technologies in Higher Engineering Education

Given the diversity of interactive instructional systems targeting higher engineering education, a systematic assessment of such systems is desirable in order to offer an overview on the existing landscape. Following a Systematic Mapping protocol (search, extraction, selection, mapping/visualization and discussion), 294 studies have been selected from a publication interval between 2010–2019 and discussed according to venue characterization and field applicability distribution. The resulting analysis demonstrated the various forms of research under which studies are conducted (from Validation Research, Experience Papers to Opinion Papers and Solution Proposal), while offering a specific depiction on the interactive technologies (Augmented/Virtual/Mixed/Simulated Reality, Game-based strategies, Simulation environments, Conversational tools/other bots) used in educational processes (teaching, learning, training, tutoring, practicing, supporting). The current study demonstrates the overall applicability of the Systematic Assessment frameworks to in-depth characterization of such a landscape, providing the preliminaries for a further statistical analysis.
Сluster of design objects images in aesthetic and social, economic, and technological systems

Currently, there is no holistic concept of the creative possibilities of humanity and its civilizations, which confirms the relevance of this study. To create images of design objects – edged weapons, represented by visual-symbolic cognitive information dynamic systems (VKIDS) with locally stable structures (LUS) in the development of cognitive technologies of plastic arts and design, the methods of linguistic-combinatorial and tabular modelling were used. RESULTS: the morphogenesis of images of objects of design, represented by a cluster of bladed weapons and logotypes decor and marks of identification, as a result of cognitive technologies in the creation of SKIDS that provides a universal language of communication in relationships ontological and semiotic realities, which increases the growing importance of the plastic arts and design, focused on images of artefacts vintage and modern bladed weapons through the concepts of archetypes symbols and signs: system, taxonomy and classification.
To a сomparative characteristics of national models of higher education organization

The article examines national models of higher education organization. The analysis is based on the higher education systems of the USA, Germany, the Netherlands, China and Russia. The authors proposed a number of criteria for differentiating the principles of organizing the higher education system in different countries: classifying higher education as private (satisfied on the basis of private effective consumer demand) or collective (patronized) benefits, organizing financing of the higher education system, barriers (filters) for students «at the entrance» and «at the exit», the degree of commercialization of the activities of universities, the role of the academic community. On the basis of the conducted research, ideal-typical models of the organization of higher education that exist in developed and rapidly developing countries are distinguished: the market for private services, state paternalism, the market for merit goods, the quasi-market and the hybrid model. It is concluded that the low level of funding and the total commercialization of the activities of state universities give rise to many problems of Russian higher education, first of all, such as the decline in the quality of educational services and the prestige of this education itself.
The Obstacles of Software Process Improvement in Software House: A Systematic Literature Review and Empirical Study

Abstract A software house, that established in 2005 based in Indonesia, got 31 projects in 2019. By the end of year, Project Management Officer released documents to inform company’s project health. There are 14 projects confirmed late, 6 projects on time and 11 projects scheduled complete on the next year. That late projects cause serious problem like loses revenue and gets disrupted of company’s cash flow. Based on the root cause analysis, it found that no standardization of software development process in the company. Before designing the standardization to improve process, we need to analyze the obstacles that might be happened. Therefore, this study aims to identify the obstacles on software process improvement in software house. We performed a systematic literature review to determine the obstacles, then we do empirical research to 58 employees on company’s development department to sort the priority of obstacles in the company. From the systematic literature review, we found studies that relevant and there are 13 obstacles of software process improvement, then from the empirical research we got top three obstracles. We also proposed recommendations to solve that obstacles.
Research on Project-based Curriculum and “Mini-Class” Teaching Method

Project-based Curriculum teaching method is a new form of production of project instead of traditional teaching method, which integrates contents of project into the curriculum and enables students to complete production of project in the form of classes. “Mini-Class” is based on WeChat Subscription Number. Professional teacher of each course regularly pushes the core content of each lesson to their followers in the form of videos, pictures, text and other forms. The most important thing of “Mini-Class” is to realize barrier-free communication and interaction between teachers and students at any time and anywhere, and to truly realize the openness of e-learning.
Proof complexity of substructural logics

In this paper, we investigate the proof complexity of a wide range of substructural systems. For any proof system P at least as strong as Full Lambek calculus, FL, and polynomially simulated by the extended Frege system for some superintuitionistic logic of infinite branching, we present an exponential lower bound on the proof lengths. More precisely, we will provide a sequence of P-provable formulas {An}n=1∞ such that the length of the shortest P-proof for An is exponential in the length of An. The lower bound also extends to the number of proof lines (proof lengths) in any Frege system (extended Frege system) for a logic between FL and any superintuitionistic logic of infinite branching. As an example, Hilbert-style proof systems for any finitely axiomatizable extension of FL that are weaker than the intuitionistic logic, in particular the usual Hilbert-style proof systems for the logics FLS for the set of structural rules S⊆{e,i,o,c}, fall in this category. We will also prove a similar result for the proof systems and logics extending Visser's basic propositional calculus BPC and its logic BPC, respectively. Finally, in the classical substructural setting, we will establish an exponential lower bound on the number of proof lines in any proof system polynomially simulated by the cut-free version of CFLew.
Poster: Engineering Students’ Personality Traits and Their Accommodation in Higher Education Process

Although the prospects of engineering higher education have stayed in focus of a public debate for a number of years, this matter remains relevant for the modern society. Our research zooms in on identification of professionally relevant personality straits of current engineering students. The basic assumption underlying out research is the understanding that much depends on students’ readiness, willingness, motivation, and personal qualities. Therefore, an analysis of personality traits which are conducive to solving effectively professional challenges should be rather useful. Another important topic is development of such personality traits as a result of higher education in the process of following university courses.
Forecasting Non-Stationary Time Series with the Multiscale Autoregressive (MAR) Model Approach Using the Haar Wavelet Filter at the Rupiah Exchange Rate Against the Dollar

Abstract Time series data is a collection of a phenomenon that occurs based on a fixed or at the same time index. Time series phenomena often exhibit non-stationary behavior. One of the time series analyses for non-stationary data is the Multiscale Autoregressive Model (MAR). The MAR model chosen is a model that meets the assumptions of normality and white noise. The predictors used in MAR modeling are wavelet coefficients and scales which are the result of decomposition using Maximal Overlap Discrete Wavelet Transform (MODWT), MODWT functions to decompose data based on the level of each wavelet filter (family). The wavelet filters used in this study are Haar. In this study, the model generated from the data that was stationary first was more accurate than the data that was not stationary first.
Detecting Curve Text with Local Segmentation Network and Curve Connection

Curve text or arbitrary shape text is very common in real-world scenarios. In this paper, we propose a novel framework with the local segmentation network (LSN) followed by the curve connection to detect text in horizontal, oriented and curved forms. The LSN is composed of two elements, i.e., proposal generation to get the horizontal rectangle proposals with high overlap with text and text segmentation to find the arbitrary shape text region within proposals. The curve connection is then designed to connect the local mask to the detection results. We conduct experiments using the proposed framework on two real-world curve text detection datasets and demonstrate the effectiveness over previous approaches.
A Digital Voting System for the 21st Century

We present Terminus, a voting system based on blockchain technology. Terminus relies on technology solutions pioneered by Monero, a privacy-focused Blockchain, and on specifically designed operational procedures: this guarantees full anonymity of the vote and addresses several concerns of digital voting systems. Terminus was tested at an event of an Italian political movement, and will be used to carry out polls to drive some of the political decisions of this movement. We also introduce an evaluation framework for DLT voting systems, and use it to compare existing systems.
Optimized Quantum Parameter Estimation in Open Quantum Systems

Quantum parameter estimation has been long pursued in various physics areas, such as quantum optics, quantum information processing, gravitational wave detection, and so on. Generally, the quantum system dynamics is usually assumed to be fixed and the system is closed, the highest precision can be achieved by preparing the optimal probe state and performing the quantum measurement based on ideal basis that saturates the quantum Cramer-Rao inequality. However, how to extend this problem to a more general open quantum system is still an open question. In this paper, we apply the optimal control theory, Pontrygin optimal principle, to enhance the parameter estimation precision in open quantum systems. The control laws and the control algorithm are exactly presented. Simulation results demonstrated the efficiency of the optimal control laws.
Traffic Classification and Comparative Analysis with Machine Learning Algorithms in Software Defined Networks

In computer networks, diverse applications generate network traffic with different characteristics. Network traffic classification is significant to manage networks better, improve service quality and ensure security. Software-Defined Networks (SDN) provides flexible and adaptable techniques for traffic classification with its programmable structure. SDN flows naturally exhibit particular characteristics of network applications and protocols. Therefore, it can be said that SDN can present significant opportunities in traffic classification using machine learning. This study proposes a traffic classification approach using machine learning models in SDN. In this study, DNS, Telnet, Ping and Voice traffic flows were created on the SDN using the Distributed Internet Traffic Generator (D-ITG) tool. Twelve-attributes representing these traffic flows (the number of packets transmitted, average transmission time, the number of instantly transmitted packets, etc.) were determined, and over the SDN controller in the physical network, a real-time data set was created by collecting data depending on the attributes. Later, the performance of k Nearest Neighbor (k-NN), Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), Decision Tree (DT) and Naive Bayes (NB) machine learning models were tested for traffic classification on this data set. When the k-NN model was tested on this real-time data set, its classification accuracy was obtained as the maximum with 99.4%. Therefore this model has been determined as a machine learning giving the highest classification performance with the lowest cost flow attributes in traffic classification in SDN.
Improving Real-world Object Detection Using Balanced Loss

Training process is crucial to the success of object detectors. Real-world datasets often have skewed distributions, which results in imbalance issues during the training process, and thus affects the performance of detector. In this work, we propose a simple but effective framework towards balanced learning for object detection, in which two balanced loss functions are developed to alleviate the imbalance during training: balanced cross entropy loss and balanced classification regression loss, respectively for reducing the imbalance at positive-negative samples and objective level. Experiments on one pedestrian detection and one foreign particle inspection task show that, benefitted from the balanced loss design, the detection performance can be improved significantly.