Reviewerly/exHarmony huggingface dataset:
Augmented reality technology as an object of study in the informatics course of basic school

The article discusses the feasibility of studying augmented reality technology in the informatics course of basic school and identifies the problem in determining approaches to such training. The purpose of this article is to reveal the possibility, as well as the positive impact of the development of such technology on improving the level of preparation of students for life in the information society. The analysis of scientific-methodical and educational-didactic literature in the field of augmented reality technology allowed to justify the necessity and possibility of studying and applying augmented reality technology in the informatics course of basic school. Summarizing and systematizing the experience of teaching schoolchildren augmented reality technology made it possible to define goals, tasks and planned results of the training, to adjust the content of teaching informatics in basic school, to determine the thematic content of the informatics course of basic school with didactic elements of augmented reality technology. Approbation of the research materials allowed to demonstrate the feasibility of the including of augmented reality technology in the informatics course of basic school. The results of the study are the methodological basis for the formation of the content of training and application of augmented reality technology in the informatics course of basic school, which allows you to teach this technology and apply it in the process of teaching informatics. The materials of the study can be useful to specialists in the field of informatics teaching methods and informatics teachers.
A Deep Matrix Factorization Method with Missing Not at Random Data for Social Recommendation

With the rapid development of online social networks, a mass of data mining techniques for integrating social relations into ordinary recommendation algorithms have emerged. Despite the extensive studies, social recommendation methods always assume that the data is missing at random (MAR), which is in the rare instance. What’s more, no existing work has taken into account both explicit ratings and non-preference implicit feedback when it comes to social recommendation. To tackle these challenges, in this paper, we propose a novel framework, deep social matrix factorization with missing not at random data (DSMF-MNAR). Firstly, on the premise that the data is not missing at random, we extend the popular Bayesian Personalized Ranking (BPR) model to complete the user-item rating matrix and user-user trust matrix. Secondly, with the two matrices as the input, we extend the Deep Matrix Factorization (DMF) model to incorporate the user-user trust relationship. Finally, we present a new loss function, in which we factor both explicit ratings and implicit feedback. Extensive experiments conducted on three real-world datasets demonstrate that our proposed method provides the best top-N recommendations, illustrating the benefits of the added model complexity.
Information support system for management decisions in the agricultural sector

Abstract There is a need in modern agriculture to automate many processes, including automation of taking decision or the providing of current information for taking decisions by responsible person. The aim of the project is to automate the control of the growth of crops or livestock with the help of various devices, such as sensors of various types, analyzing the microclimate of the site according to such characteristics as humidity, air temperature, ground, RFID - tags, GPS - module for analyzing the location of livestock on the farm and intelligent information system that processes the data coming from sensors. The emergence of smart agriculture (Internet of things in agriculture) will facilitate taking decision for owners and responsible persons. Decision making is also facilitated by the quality interface of the information system, which includes the characteristics of data from all types of devices. An additional factor complicating making decision is the ambiguity of the data, which in turn leads to some conflicts. A Petri nets-based model can be used to model and analyse risks. Analysing the model using Petri nets, it can be argued that it is a powerful modelling tool and can be useful in the agricultural sector for selecting the best element from the set, or modelling of data flows.
Development of Communicative-Rhetorical Competence of a Future Engineer at the Research University

The article focuses on the development of the communicative-rhetorical competence of a future engineer. This competence is considered to be a necessary condition for his development as a qualified specialist and a significant factor in his/her future professional activities. In the XXI century, in modern conditions, engineering and engineering duties should be inseparable from organizational and managerial activities. The solution of production problems and team work with diversified specialists are realized through communicative and rhetorical qualities of an engineer. He/ she should be ready for productive business communication and effective presentation of his/her position, as well as presentation of the results of work. Public speaking skills hence acquire particular importance for engineers along with communication skills. Communicative-rhetorical competence is the ability to carry out a conscious effective speech influence in the process of interpersonal, group and collective public communication, which measure up linguistic and cultural norms, and realizes the goals of communication through the use of various language levels. It is advisable to develop communicative-rhetorical competence of future engineers at the level of university training. The rationale for its effective development is proposed by creating a set of relevant pedagogical conditions: the introduction of an additional discipline “Rhetoric” or the modernization of an existing subject program with a similar focus; using of special educational technologies and methods for the development of communicative-rhetorical competence; advanced training of university teachers; creation by the university of appropriate conditions for active research and social activities of students; cooperation of educational institutions with large enterprises, companies and research centers. The pedagogical conditions should take into account the capabilities of a research university: the integrated nature of the learning process; using modern educational technologies in the process of learning; availability of a developed system of professional retraining and advanced training of teachers and other specialists. The authors worked out the recommendations for the selection and structuring of the material, as well as methods for developing the communicative and rhetorical competence of future engineers in a research university, and also identified problems that need further consideration, including the search for innovative techniques and methods.
Implementation and Design User Interface Layout Use Leap Motion Controller With Hand Gesture Recognition

Abstract Human Computer Interaction is the study how to design, evaluate, and implement computer systems interactive, the systems can make a dialogue with human. This research was designed and implementation leap motion used hand movements into digital models, which can be used to replace the function of the mouse or keyboard and can provide an alternative in the utilization of hand movements as interactions that the naturally between human and computers and allowing users to input gesture commands into an application in place of a mouse or keyboard. Human gesture recognition as technique interaction for deliver interpretation more natural and for communicating with computers. The aim of this research to find usability leap motion, how effectiveness of the Leap Motion controller for hand gesture recognition for solve important problems in human use of mouse or keyboard. Testing and implementation from this reseach focused are tracking, detection, dynamic, and statis gesture recognation. The result 6 gesture recognation double outward swipe, tap, swipe, clap, circular and fly control tap accuracy of gesture interrpretation data has obtained 87.62%. The uses the data for recognation model has obtain very good and testing with Leap Motion visualizer hand gesture recognation are often sensitive to poor resolution.
Photo Cropping via Deep Reinforcement Learning

The following topics are dealt with: learning (artificial intelligence); multi-agent systems; game theory; social networking (online); natural language processing; time series; financial data processing; neural nets; Markov processes; mobile robots.
Practical Significance of GA PartCC in Multi-Label Classification

Multi-label classification (MLC) can be defined as the objective of learning a classification model which has the capability to infer the accurate labels of new, previously unseen, objects where it is a likely situation that each object of the dataset may rightfully belong to multiple class labels. While single-label classification problems have been thoroughly researched, the same cannot be said for MLC. A gradually increasing number of problems are now being tackled as multi-label, allowing for richer and more accurate knowledge mining in real-world domains, such as medical diagnoses, social media, text classification, etc. Currently, there are two ways of solving MLC problems; Problem Transformation Approach and Algorithm Adaptation Method. Of the two, the former has in its domain Classifier Chains (CC) which is the most effective and popular method of solving MLC problems because of its simplicity in implementation. Unfortunately, CC is not favoured due to 2 drawbacks, [1] ordering of the labels for classification are randomly decided without a fixed logic or algorithm to it which results in varying accuracy, [2] all the labels, even those which may be redundant for a particular dataset are put into the chain despite the probability that some may be carrying irrelevant details. Through the research conducted for the purpose of this study, both challenges are tackled along with others detailed further on simultaneously using Genetic Algorithms (GA) over a Partial CC (PartCC) model, which is a modification over CC. A toxic comments dataset is used since its classification is a multi-label text classification problem with a highly imbalanced dataset. This paper aims to create a prototype model that is capable of detecting various types of toxicity like neutral, toxic, severe toxic, threats, obscenity, insults and identity hate. With the explosion of social media in the modern world and the resulting increasing phenomenon of social media hatred and bullying, there is a need for an advanced prototype model to predict the toxicity of each class of comments.
“I Need a Hug Right Now”: Affective Support Through Remote Touch Technology

Touch is a contextual medium for affective conveyance. It is difficult to assign specific meanings to each instance of touch in isolation. However, when engaged within context, touch becomes a powerful and indispensable means for humans to convey feelings of love, concern, and sympathy. This dissertation focuses on how remote touch functioning with other contextual channels like speech may help to intensify or modulate one's affective experiences.
IoT-Poly

The current shortage of cybersecurity personnel is exacerbated by the increase of damage caused by cyber-attacks, specially with the advent of the Internet of Things (IoT). Cybersecurity personnel face several challenges for acquiring the necessary abilities to address the attacks due to a lack of learners' motivation in security education and a general security fatigue. In this paper, we propose a cybersecurity game exercise tool, IoT-Poly, which focuses on areas that are hitherto unsupported by the existing game exercises. IoT-Poly aims to help cybersecurity personnel acquire the necessary skills to handle security issues that are related to the IoT through risk assessment and instructional design. We conducted three game exercise sessions using IoT-Poly to evaluate the reaction and the learning effect of the learners with the Kirkpatrick's four grades evaluation. We compared the results of learners' reactions of IoT-Poly with three other exercise tools by using the evaluation index of the educational game called MEEGA+. The results of IoT-Poly were rated as equal to or higher than the results of the other exercise tools in the ARCS motivation model. We evaluated the effects of learning by analyzing the results of the questionnaires asking the degree of understanding of the content of IoT-Poly, and the worksheets recorded during the sessions. The evaluation results showed that IoT-Poly is a useful tool for cybersecurity personnel to acquire the necessary abilities while keeping their learners' motivation high.
A rehabilitation system for monitoring torso movements using an inertial sensor

The paper presents the results of preliminary research carried out using the developed rehabilitation system. The system uses a single measurement module with a reduced architecture that enables to control the virtual or extended environment. The reduced architecture allows to minimize the dimensions of the electronic system. The measuring module is based on two main components - SoC Wi-Fi module and inertial sensor. The Digital Motion Processor included in inertial sensor allows for precise monitoring of the rehabilitative movement. The measuring module was placed on the exerciser's back so as to minimize the impact of chest movements during respiratory activities. Sensor data are transmitted to the server, which simultaneously registers them and displays the game.Gameplay is controlled by torso movements. During the tests, the sensor's behaviour on the exerciser's body was verified and its measurements were compared with an optoelectronic reference system.
Research on Failure Modes and Impact Analysis of Key Electronic Components

Abstract Analyze the failure mode of electronic components, find the type of stress that causes the failure of the energy meter, trace the key components that cause the fault, and complete the failure mode and impact analysis of key electronic components through failure detection means and failure analysis experiments. In order to develop a reliable product, it is necessary to understand the potential failure mechanism of the product. Modeling to describe the relevant failure modes can promote the development of product design principles. The research results of failure mechanism are not only conducive to improving the reliability manufacturing level of domestic electric energy meter, but also can save the maintenance and transformation cost of electric energy meter, and have very important practical significance for the construction of smart grid.
An On-Chain Method for Automatic Entitlement Management Using Blockchain Smart Contracts

Managing the entitlements for the compliant use of digital assets is a complex and labour-intensive task. As a consequence, implemented processes tend to be slow and inconsistent. Automated approaches have been proposed, including systems using distributed ledger technology (blockchains), but to date these require additional off-chain sub-systems to function. In this paper, we present the first approach to entitlement management that is entirely on-chain, i.e. the functionality for matching the digitally encoded rights of content owners (expressed in ODRL) and the request for use by a customer are checked for compliance in a smart contract. We describe the matching algorithm and our experimental implementation for the Ethereum platform.
Design security adaptation of communication spaces for the modern educational forms’ implementation in the educational buildings of universities

Abstract The architectural and design environment of educational buildings and their open areas are adapted in the operation course to the changing educational conditions, technologies and the way of the students’, as well as the expansion of educational, communication and recreational zones. The design tools used to distinguish, isolate and transform the zones to ensure the adaptation of communication spaces to the changes in the learning process and to saturate them with the additional functions are under the study. The researched design tools for localization of the additional functions’ zones in social spaces with free planning; the design means of isolation zones (zone boundary) to create the open, half-open and closed zones being able to control the degree of the zone’s isolation; the design filling of a zone (zone saturation). The criteria for the quality of the educational building extracurricular spaces environment are proposed: dynamism, which is caused by episodic events changes; transformations for compact zones; flexibility and rationality of the educational building spaces use by applying the combinatorial method. On the basis of the field surveys of the high school educational buildings and the study of Russian and foreign experience of their design the options and methods for greater involvement of educational communication spaces for learning and recreation are proposed in this study.
An Empirical Study of Test-Driven Development vs. Test-Last Development Using Eye Tracking

Test-Driven Development (TDD) is an iterative software development technique in which unit tests are defined before production code, while Test-Last Development (TLD) is a more traditional development technique in which unit tests are written after the features are implemented. There have been a number of empirical studies investigating the effects of TDD compared to other approaches in terms of software quality and productivity. However, there are few investigations in which the TDD effects are explored from the viewpoint of the developers’ experience. This paper presents an eye-tracking study carried out in order to measure visual attention during the coding and test tasks when developers are using TDD compared to TLD. Our preliminary findings pointed out a similar visual effort proportion in both techniques, but a difference regarding eye gaze behavior between them which needs to be confirmed.
CARNet: Densely Connected Capsules with Capsule-Wise Attention Routing

Convolutional neural networks (CNNs) have been proven to be effective for image recognition, which plays an important role in cyber security. In this paper, we focus on a promising neural network, capsule network, which aims at correcting the deficiencies of CNNs. Routing procedure between capsules, which serves as a key component in capsule networks, computes coupling coefficients with complicated steps iteratively. However, the expensive computational cost poses a bottleneck for extending capsule networks deeper and wider to approach higher performance on complex data. To address this limitation, we propose a novel routing algorithm named capsule-wise attention routing based on attention mechanism. With a successful reduction of computational cost in the routing procedure, we construct a deep capsule network architecture named CARNet. Our CARNets are proven experimentally to outperform other state-of-the-art capsule networks on SVHN and CIFAR-10 benchmarks while reducing the amount of parameters by 62% at most.
Utilizing Digital Media for Embedding Local Cultural Values: Vocational High Schools Context

Abstract Culture and language are truly inseparable. This study explored how teachers of Vocational High Schools (VHS) embedded local cultural values in their language learning by utilizing digital media. This was a small scale exploratory case study involving six participants comprising of three Indonesian language teachers, and three English teachers of Vocational High Schools in three different regencies of Central Java, Indonesia. The data were primary collected through interview and focus group discussion (FGD). To analyse the data, the interactive models of qualitative data analysis of Miles &amp; Huberman (2014) was employed. Evidences showed that teachers used texts or video materials containing local culture in form of (1) ideas: norms, moral, religious values; (2) activities: traditional ceremonies, and (3) artefacts: historical places, foods, or customs. Teachers reported that among of methods recommended in 2013 Curriculum implementation, Inquiry and Project-Based Learning became teachers’ preferences. Students’ projects in form of texts writing or video making of certain local culture were resulted from the learning. Teachers supported their learning by the use of various digital medias, such as internet, animated video or You tube, WhatsApp group. Whereas google classroom and quipper school were other forms of digital learning presented while students were on the job training program. Teachers- students were connected by the presentation of the materials and assignments. Overall, embedding local culture in language learning raised students’ interest, increased their participation as well as developed their’ local cultural awareness.
Image Quality Assessment, Denoising and Comparative Analysis using Filters for C-arm X-ray Images

C-arm is a fluoroscopy based medical imaging device, which has various operational parameters (dose levels, power applied and frame rate) that has some effect on the image quality. X-ray fluoroscopy exhibits various types of noise (quantum, Gaussian, speckle, photon, Poisson noise, etc.) that must be reduced in real time. Presence of noise degrades the image quality and thus decreases the performance of subsequent application. We have developed a method for statistical quality assessment and denoising technique for flat field detected C-arm X-ray image sequence. The analysis approach is tested on 84 x-ray image sequences acquired from homogeneous phantoms (PMMA) of different widths. Statistical parameters (mean, standard deviation and signal to noise ratio) are considered for generating noise profile. These generated noise profiles are used to study effect on noise due to different widths of phantom, dose levels, applied kV power, and frame rate considered for respective image sequence. Denoising of these image sequence is done using spatial domain filters. Conventional mean, Gaussian and median filters of different kernels are chosen for denoising of image sequence. Comparative results of different filter performance is also studied.
Toward a Common System Architecture for Knowledge Mapping

Development of applications in knowledge mapping requires a system architecture approach to be able to explain conceptual models that define structure, behaviour and view of the system. There are many system architectures that are made for knowledge mapping but are very diverse, and there are no general guidelines that help a scholar used as references in making them. Therefore this research proposes a universal architectural system that can be used to create a knowledge mapping system. With the literature study method and content analysis on the system architecture used in previous studies, this study proposes four layers which can generally conduct in creating architectural systems, namely: Acquisition layer, database layer, knowledge mapping process layer and user interface layer.
An Architecture for 2D Game Streaming Using Multi-Layer Object Coding

Advances in cloud computing have enabled systems where the game logic and rendering are processed on a server and streamed to a thin client. Meanwhile, there are still many challenges to provide games through the cloud without latency issues. This work proposes a novel technique to reduce encoding times and bandwidth usage on cloud gaming systems. We propose LACES (LAyer Caching gamE Streaming), an API that separates 2D game objects into multiple layers and allows the cloud server to encode and stream only modified parts of the frame. Using our technique, we managed to reduce the encoding size on the server by 99,79% and the average streaming size to the client by 96%, with no changes to the video quality or resolution and with no noticeable user input delay.