Reviewerly/exHarmony huggingface dataset:
Blended learning as a modern educational technology for integrating the learning process in education institutions

Digital technologies increase the impact on society, economy and education every day. Schools gradually penetrate the technologies of virtuality and complemented reality; teachers must be prepared not only for their understanding, but also for their use. Currently, mixed learning becomes more popular in educational institutions, but not all teachers understand the essence of this concept. A generalized analysis of domestic scholars has shown that the notion of "mixed learning" relates to such concepts as "learning process", "learning system", "educational technology", "educational methodology", "combination of methods", "modernization tool", etc. On the basis of the analysis of literature on the concept of "mixed learning" in foreign and domestic researchers, the author presents her own definition, discloses the main components of mixed learning and its benefits in organizing educational activities in institutions of general secondary education; a scheme of combining traditional and e-learning in a mixed one is prepared. Digital technologies have a significant impact on the nature, the form of training, the kind of activity of students, allow the implementation of fundamentally new forms and methods of learning, and, as a consequence, increase the efficiency of educational process in a digital society. Before higher education there is the task of training specialists who can use a computer for the organization of interactive training and testing, video conferencing, participation in telecommunication projects, webinars, forums, etc. It is noted that modern teacher has to develop independently educational content in text, video, multimedia and hypermedia format, to use digital and educational resources, to set up educational content management systems and to organize training with the use of the Internet and its services.
Pengembangan Lembar Kerja Peserta Didik (LKPD) pada Materi Teks Fabel Berbasis Saintifik untuk Siswa SMP Kelas VIII

The purpose of this study was to describe the needs of students and teachers for learning to write scientific-based fable text, produce teaching materials on Student Worksheet (LKPD) on scientific-based Fable Text material, and describe the results of expert validation of the developed LKPD. This research is a development study using a modification of the development model of Dick, Carey, and Carey and Jolly &amp; Bolitho. The subjects of this study were students of class VIII and Indonesian Language Teachers. Data collection techniques are done using a questionnaire and documentation. The feasibility of the developed teaching material is known from the results of validation by three experts on the 4 components of teaching material, namely the component of material eligibility, language component, presentation component and graphic. Based on the results of expert validation, LKPD on the fable text material developed is categorized as good or suitable to be used as a textbook companion teaching material. In the content / material component, LKPD outlines one Basic Competency (KD) in each activity. Each activity is in accordance with the steps of the scientific approach that is equipped with worksheets and assessment rubrics so as to facilitate students and teachers in the learning and assessment process. In the language component, LKPD uses simple and effective language, and is equipped with a glossary to make it easier for students to understand new vocabulary. In the presentation and graphic components, LKPD uses larger types and font sizes, and attractive designs with illustrations of colored images.
Application of e-handout with Schoology-based PhET simulations to improve students’ visual representation ability on optical material

Abstract This research is pre-experimental and has a purpose to improve students’ visual representation ability through the application of e-handouts with schoology-based PhET simulations on optical material. Sub material taken is lenses and optical devices. One group pre-test post-test was designed in this research with samples were selected by the technique of cluster random sampling. XI MIA 3 class was sample as the implementation class and XI MIA 5 was sample as a modeling class at SMA Negeri 1 Sleman, Yogyakarta. The samples consist of 55 students. The essay test of eligibility results by expert judgment was used in this research. The research result is the application of e-handouts with Schoology-based PhET simulations can improve students’ visual representation ability and include in the medium category for both classes.
Study of Memory Effect in a Fuzzy EOQ Model with No Shortage

The feature of the fractional order derivative and fractional order integration is one of the important tools to realize the beauty of the fractional calculus.Fractional order derivative and integration has a long history like classical calculus but its users are much less compared to the classical calculus.The purpose of this paper is to study an inventory model with linear type demand rate under the fuzzy environment.This paper also wants to introduce the memory effect property of fractional order derivative which can help to setup the model more authentic.Two advantages have been included to the model (i) memory effect,(ii) fuzzy environment.Here, the fractional order model is defuzzyfied using (i) signed distance method,(ii) graded mean integration method.Fuzzification can close to the reality with incorporating uncertainty behavior of some economic parameters of the inventory system and fractional order can explain the memory phenomena.For this problem due to illustrate defuzzification, set up cost, holding cost per unit, per unit cost are assumed as triangular fuzzy numbers.Fractional order derivative and integration are applied to develop the whole work.It is known that fractional calculus is a valuable tool to describe memory phenomena.Fractional order is established as the index of the memory.In this paper, depending on strength of memory, memory phenomena considered in two steps(i) long memory,(ii) short memory.The proposed fuzzy models and technique lastly have been illustrated.Results of two defuzzyfications are compared with graphical presentations.This present studies can help to moderate the classical fuzzy inventory model.From the numerical studied it is observed that in long memory effect, profit is good compared to the low memory effect or memory less system.
LE-HGR: A Lightweight and Efficient RGB-Based Online Gesture Recognition Network for Embedded AR Devices

Online hand gesture recognition (HGR) techniques are essential in augmented reality (AR) applications for enabling natural human-to-computer interaction and communication. In recent years, the consumer market for low-cost AR devices has been rapidly growing, while the technology maturity in this domain is still limited. Those devices are typical of low prices, limited memory, and resource-constrained computational units, which makes online HGR a challenging problem. To tackle this problem, we propose a lightweight and computationally efficient HGR framework, namely LE-HGR, to enable real-time gesture recognition on embedded devices with low computing power. We also show that the proposed method is of high accuracy and robustness, which is able to reach high-end performance in a variety of complicated interaction environments. To achieve our goal, we first propose a cascaded multi-task convolutional neural network (CNN) to simultaneously predict probabilities of hand detection and regress hand keypoint locations online. We show that, with the proposed cascaded architecture design, false-positive estimates can be largely eliminated. Additionally, an associated mapping approach is introduced to track the hand trace via the predicted locations, which addresses the interference of multi-handedness. Subsequently, we propose a trace sequence neural network (TraceSeqNN) to recognize the hand gesture by exploiting the motion features of the tracked trace. Finally, we provide a variety of experimental results to show that the proposed framework is able to achieve state-of-the-art accuracy with significantly reduced computational cost, which are the key properties for enabling real-time applications in low-cost commercial devices such as mobile devices and AR/VR headsets.
Activation and Spreading Sequence for Spreading Activation Policy Selection Method in Transfer Reinforcement Learning

This paper proposes an automatic policy selection method using spreading activation theory based on psychological theory for transfer learning in reinforcement learning.Intelligent robot systems have recently been studied for practical applications such as home robot, communication robot, and warehouse robot.Learning algorithms are key to building useful robot systems important.For example, a robot can explore for optimal policy with trial and error using reinforcement learning.Moreover, transfer learning enables reuse of prior policy and is effective for environment adaptability.However, humans determine applicable methods in transfer learning.Policy selection method has been proposed for transfer learning in reinforcement learning using spreading activation model proposed in cognitive psychology.In this paper, novel activation function and spreading sequence is discussed for spreading policy selection method.Further computer simulations are used to examine the effectiveness of the proposed method for automatic policy selection in simplified shortest-path problem.
A Survey on Various Shadow Detection and Removal Methods

Shadows plays an inevitable part in an image and also the major source of hindrance in Computer Vision analysis. Shadow detection is the performance enhancement process that increases the accuracy of the Computer Vision algorithms like Object Tracking, Object Recognition, Image Segmentation, Surveillance, Scene Analysis, Stereo, Tracking, etc. Shadows limit the stability of these algorithms, and hence detecting shadows and its elimination are profound pre-processing techniques for improving execution of Vision algorithms efficiently. To label the challenges under various environmental conditions, researches have been carried out to develop various algorithms and techniques for shadow detection. This paper objective is to bring comparative analysis of shadow detection techniques with their pros and cons.
Multiquery Motion Planning in Uncertain Spaces: Incremental Adaptive Randomized Roadmaps

Abstract Sampling-based motion planning is a powerful tool in solving the motion planning problem for a variety of different robotic platforms. As its application domains grow, more complicated planning problems arise that challenge the functionality of these planners. One of the main challenges in the implementation of a sampling-based planner is its weak performance when reacting to uncertainty in robot motion, obstacles motion, and sensing noise. In this paper, a multi-query sampling-based planner is presented based on the optimal probabilistic roadmaps algorithm that employs a hybrid sample classification and graph adjustment strategy to handle diverse types of planning uncertainty such as sensing noise, unknown static and dynamic obstacles and an inaccurate environment map in a discrete-time system. The proposed method starts by storing the collision-free generated samples in a matrix-grid structure. Using the resulting grid structure makes it computationally cheap to search and find samples in a specific region. As soon as the robot senses an obstacle during the execution of the initial plan, the occupied grid cells are detected, relevant samples are selected, and in-collision vertices are removed within the vision range of the robot. Furthermore, a second layer of nodes connected to the current direct neighbors are checked against collision, which gives the planner more time to react to uncertainty before getting too close to an obstacle. The simulation results for problems with various sources of uncertainty show a significant improvement compared with similar algorithms in terms of the failure rate, the processing time and the minimum distance from obstacles. The planner is also successfully implemented and tested on a TurtleBot in four different scenarios with uncertainty.
The Dynamics of a Spherical Robot of Combined Type by Periodic Control Actions

This paper presents the results of the study of the dynamics of a real spherical robot of combined type in the case of control using small periodic oscillations.The spherical robot is set in motion by controlled change of the position of the center of mass and by generating variable gyrostatic momentum.We demonstrate how to use small periodic controls for stabilization of the spherical robot during motion.The results of numerical simulation are obtained for various initial conditions and control parameters that ensure a change in the position of the center of mass and a variation of gyrostatic momentum.The problem of the motion of a spherical robot of combined type on a surface that performs flat periodic oscillations is also considered.The results of numerical simulation are obtained for different initial conditions, control actions and parameters of oscillations.
TECHNIQUE OF TEACHING DESIGN AND DEVELOPMENT OF DATABASES TO FUTURE INFORMATION TECHNOLOGY EXPERTS

Statement of the problem. The article analyzes and formulates the problems of training in the field of database design and development in preparing students in the field of applied informatics. The article focuses on the problem of learning related with insufficient attention paid directly to the database design process. The purpose of the article is to develop methods for teaching future specialists, first of all, teaching the database design process, step by step mastering the discipline from acquiring basic knowledge and skills in the field of databases to developing a working prototype of an information system, the core of which is a database. Research methodology. The research methodology consists of the analysis and synthesis of research works of foreign and Russian scientists recognized by the scientific community, and the experience of teaching students in designing databases in the field of applied computer science. Research results. The proposed methodology assumes two-stage training with practical work between the stages, which allows, at the beginning of the second stage, to interactively conduct training in the analysis of the subject area and conceptual database design with specific examples of real enterprises and organizations. The results of applying this methodology confirm its effectiveness both in terms of acquiring knowledge, skills and abilities, as well as motivating students to professional activities, forming a holistic picture of the design process, and understanding the practical value of the acquired knowledge. Conclusions. The author’s method of teaching the course “Databases” proposed in the article is based on multi-stage interactive training, in which students return to the same design issues more than once, but at different levels of depth of knowledge. The advantage of the proposed method is the completeness of the scope of the design process until the final software product is obtained.
Scientific Journals in the post-Soviet States: The Place in the National and International Information Space

Introduction. The objective of the paper is to analyze scientific journals published in the post-Soviet states, as well as to identify the role of scientific journals in the information and analytical support for the adoption and implementation of decisions related to the management of scientific activities and socio- economic processes in countries and regions. Analysis of scientific journals based on a set of indicators will make it possible to identify the place of these publications in the national and international information space. Materials and Methods. The authors have analyzed available information about scientific journals published in the post-Soviet states and indexed by Scopus and Web of Science as well as information about such journals given on the website of the Higher Attestation Commission of Russia, data from the website of the Russian Science Citation Index and information from the official websites of the journals and from other sources. To obtain quantitative indicators related to the journals, standard means of search engines provided by the abovementioned resources were used. Data on the population of the countries and the number of researchers in them were taken from official statistics. Results. Data about the number of journals published in the post-Soviet states and indexed by Scopus, Web of Science and the Russian Science Citation Index, as well as those included in the list of the Higher Attestation Commission of Russia have been analyzed. Information on the publication activities of authors from the post-Soviet states has been evaluated as absolute and relative indicators. A number of common features of the editorial policies and practical activities of the considered journals have been identified as well as their approaches to the use of publication languages, to the issue of translated editions, to the formation of editorial boards and to the involvement of national and foreign authors. Discussion and Conclusion. Electronic repositories of scientific information play a crucial role in the formation of international and national scientific spaces. The materials presented in this article may be useful for coping with research tasks related to scientific periodicals as well as to support decision-making by heads of scientific units, editorial and publishing complexes.
Multivariable nonlinear predictive control of a clinker sintering system at different working states by combining artificial neural network and autoregressive exogenous

The clinker sintering system is widely controlled manually in the factory, and there is a large divergence between a linearized control model and the nonlinear rotary kiln system, so the controlled variables cannot be calculated accurately. To accommodate the multivariable and nonlinear features of cement clinker sintering systems, steady-state model and dynamic models are established using extreme learning machine and autoregressive exogenous models. The steady-state model is used to describe steady-state nonlinear relations, and the dynamic model is used to describe the dynamic characteristics of the sintering system. By obtaining the system gains based on the steady-state model, the parameters of the dynamic model are rectified online to conform to the system gain. Thus, a dynamic model named extreme learning machine-autoregressive exogenous is proposed, which can describe the nonlinear dynamic features of a sintering system. The results show that, compared with the autoregressive exogenous model, the extreme learning machine-autoregressive exogenous model has good control performance on the multivariable and nonlinear system and can reduce computing resource requirements during the online running. In addition, fluctuations of NO x and O 2 concentrations decreases, again demonstrating good control performance of an actual clinker sintering system using the extreme learning machine-autoregressive exogenous model.
Identifying new roles for academic libraries in supporting data-intensive research

Reacting to the appearance of data-intensive research prompts academic libraries to become service providers for scholars, who work with research data. Although this is an imperative for libraries worldwide, due to the differences between countries and institutions, the level of readiness to engage in related activities differs from country to country. While some of the related tasks are fairly novel, others heavily build on librarians’ traditional, well-known skills. To identify these tasks, as well as making an inventory of the required skills and abilities, this paper, based on a non-exhaustive review of the recent literature, presents both theoretical and practical issues. It is demonstrated that the most obvious directions of the service development in academic libraries to support data-intensive science are research data management, data curation, data literacy education for users, and data literacy education for librarians.
Residual Attention Net for Superior Cross-Domain Time Sequence Modeling

We present a novel architecture, residual attention net (RAN), which merges a sequence architecture, universal transformer, and a computer vision architecture, residual net, with a high-way architecture for cross-domain sequence modeling. The architecture aims at addressing the long dependency issue often faced by recurrent-neural-net-based structures. This paper serves as a proof-of-concept for a new architecture, with RAN aiming at providing the model a higher level understanding of sequence patterns. To our best knowledge, we are the first to propose such an architecture. Out of the standard 85 UCR data sets, we have achieved 35 state-of-the-art results with 10 results matching current state-of-the-art results without further model fine-tuning. The results indicate that such architecture is promising in complex, long-sequence modeling and may have vast, cross-domain applications.
SqORAM: Read-Optimized Sequential Write-Only Oblivious RAM

Abstract Oblivious RAMs (ORAMs) allow a client to access data from an untrusted storage device without revealing the access patterns. Typically, the ORAM adversary can observe both read and write accesses. Write-only ORAMs target a more practical, multi-snapshot adversary only monitoring client writes – typical for plausible deniability and censorship-resilient systems. This allows write-only ORAMs to achieve significantly-better asymptotic performance. However, these apparent gains do not materialize in real deployments primarily due to the random data placement strategies used to break correlations between logical and physical names-paces, a required property for write access privacy. Random access performs poorly on both rotational disks and SSDs (often increasing wear significantly, and interfering with wear-leveling mechanisms). In this work, we introduce SqORAM, a new locality-preserving write-only ORAM that preserves write access privacy without requiring random data access. Data blocks close to each other in the logical domain land in close proximity on the physical media. Importantly, SqORAM maintains this data locality property over time, significantly increasing read throughput. A full Linux kernel-level implementation of SqORAM is 100x faster than non locality-preserving solutions for standard workloads and is 60-100% faster than the state-of-the-art for typical file system workloads.
A Probabilistic Proof of a Recursion Formula for Sums of Powers

A probabilistic proof of a recursion formula for sums of powers is given by using some properties of expectations.
Detecting and Analyzing Year 2038 Problem Bugs in User-Level Applications

The year 2038 problem is a well-known year problem that might cause severe damage to many existing software systems. However, no current tool can detect the bugs since it requires the understandings of the problem unique encoding semantics. In this paper, we analyze real-world applications and raise the alarm over the fact that the Year 2038 problem is a real threat. We target all of the C based projects uploaded on GitHub in the years 2012 to 2018 (32,921 in total), between the dates July 1 to July 10. Our analysis shows that 7.35% of the compiled projects have bugs. Some of the bugs trigger undefined behavior and are dangerous enough to crash the software systems. Our bug fixing patches sent to six projects have been confirmed and approved, including large-scale, real-world projects such as the Amazon Web Service support tools and the Linux Test Project.