Reviewerly/exHarmony huggingface dataset:
SMART: Emerging Activity Recognition with Limited Data for Multi-modal Wearable Sensing

Activity recognition using ubiquitous wearable devices (e.g., smartphones, smartwatches and sport bracelets) can be applied to many application domains such as healthcare, smart environments, assisted living, human-computer interaction, surveillance etc. Most existing activity recognition approaches require users to provide each activity a sufficient amount of annotations (labels) in order to achieve acceptable performance and therefore often fail to scale to a large number of activities by recognizing new (emerging) activities. To tackle this limitation, the systems requiring limited training data are much desired. However, existing activity recognition solutions on limited training data rely heavily on low-level activity or attribute extraction and therefore suffer from two major limitations: (1) failing to work well when activities are highly similar to each other, such as jogging, running, and jumping front and back, and (2) leading to overall system performance degradation on recognizing existing activities with sufficient training data. In this paper, we introduce SMART, a unified semi-supervised framework for recognizing highly similar emerging activities without sacrificing the performance on recognizing existing activities. Extensive experiments on real-world data showed that compared to the state of the art, SMART yielded superior performance on recognizing emerging activities, especially highly similar emerging activities, while providing comparable performance on recognizing existing activities.
COGNITIVE AND PERSONAL PREDICATORS OF SUCCESSFUL EDUCATION OF STUDENTS

The problem of predictors of the success of the teaching is one of the classical for any levels of education. It is known that the success of the teaching depends on cognitive and personal characteristics, and in the student age, the role of personal characteristics increases. However, the data on the correlation of cognitive and personal characteristics as predictors of the success of the teaching are highly contradictory and need to be clarified. This work is devoted to the study of the correlation of cognitive and personal characteristics as predictors of the success of students' learning, taking into account their personality type.As methods of research, we chose: "Universal Intellectual Test" by NA Baturin and NA Kurgansky, a questionnaire for determining the type of personality - Type Indicator Myers-Briggs. As indicators of the success of the exercise, the overall ranking was used. For the processing of the results, the methods of mathematical statistics were used: the Spearman correlation analysis, the Mann-Whitney U test, the one-way variance analysis of Kruskall-Wallis for k independent samples. The sample consisted of 174 students of the Ural Federal University.The study showed that the predictors of the success of the teaching are, first of all, cognitive characteristics. Different personal characteristics are loosely associated with the success of the students' teaching. However, it is revealed that each type of personality in the learning process chooses its strategy for solving problems in connection with its intellectual characteristics. This points to different strategies for achieving success in teaching different types of personality.Based on the results of this study, recommendations have been developed and implemented to increase the success of students' studies in connection with their type of personality.
On Node Embedding of Uncertain Networks

Node embedding has recently shown state-of-the-art performance in various network analysis tasks. However, most of the existing node embedding methods do not consider the uncertainty of the input data, which is often the case in practice. This work offers an empirical evaluation of the typical node embedding methods when applied on uncertain networks. Precisely, we examine the performance of embedding vectors obtained by these methods in a set of downstream tasks. To this end, we employ a wide range of uncertain networks and traditional prepossessing techniques for dealing with uncertainty. Our findings suggest that the existing node embedding methods perform practically well on networks with uncertainty once the network data is appropriately prepossessed.
Speed control system in mobile robot based on Bezier curve trajectory

Abstract The development of robot technology is currently growing rapidly. Mobile robot is one robot with many applications in everyday life. One of the important things in the field of mobile robots is the problem of trajectories or trajectories, in this case how robots can track approved paths. In this study, the mobile robot control system has been tested to track tracks. The path used in this study is the third-order Bezier Order, with control points and end points of the predetermined pathway. Based on the results of simulation tests on the development of mobile robot trajectories, based on the results of simulation tests on mobile robots, it is found that the performance of the track tracking control system is very dependent on the placement of the Bezier curve control points or in other words the actual path formed by the robot is greatly influenced by the shape of the Bezier trajectory that was designed.
Automatic XML creation for Multisensorial Books

The use of human senses (i.e., sight, hearing, touch, taste, smell) provides us information about how to build a more concrete representation of the world. Multisensorial Media (MulSeMedia) is one of the innovations that can improve these representations of the physical world by improving the reader's Quality of Experience (QoE) in digital books (e-books). Multisensorial Books is the new e-book reading platform that combines traditional multimedia elements with MulSeMedia components to enhance the QoE of the user in the reading/learning task. However, to create new stories for Multisensorial Books, previous works use manual XML annotations, which can be very laborious. Also, the previous works do not provide controls of multisensorial effects intensities. In this scenario, this work proposes contributions, such as the automatic annotations of multisensorial media using the XML model and the construction of a sensory word lexicon to control the intensity of the effects during the reading of Multisensorial Books.
Mission Planning for Shepherding a Swarm of Uninhabited Aerial Vehicles

Uninhabited aerial vehicles (UAVs) are widely used in many areas for completing complex missions such as tracking targets, search and rescue, farming (shepherding in the traditional sense) and mapping. Mission planning for shepherding a UAV swarm is advantageous for Human-Swarm Teaming. While most research on shepherding see the shepherd as a simple reactive agent, a smart shepherd in a complex environment will need to consider many dimensions and sub-decisions to successfully guide a swarm through complex environment and towards a goal. In this chapter, we review and offer formal definitions for the sub-problems required for a shepherd to complete a mission successfully. The swarm mission planning system needs to have decision modules capable of solving four main problems: task decomposition, task assignment, path planning and trajectory generation. These sub-problems are coupled differently depending on the scenario. This chapter defines these sub-problems in their general form and gives UAV swarm shepherding problem as a specific application. A brief review of the widely used algorithms for tackling these problems and the state of art of mission planning are also given in this chapter.
Methods for pattern detection based on colour and size features in video streams

Abstract Detecting pattern in images plays a huge role in the field of computer vision. The article summarizes methods for detecting patterns by their properties, such as colours, shapes in images. And with video, the detection of patterns is also based on their movement. Human face recognition problem is also mentioned in the application of MTCNN network architecture and reconfiguring FaceNet to suit actual requirements. Test results are given and recommendations with data and program operating conditions are provided for the reference.
A Conference Publishing System Based on Academic Social Network

Scholars and researchers participate in various academic conferences to share the latest research results and academic ideas. As more and more conferences are held, conference organizers need to promote their conference by setting up conference website. Therefore, conference organizers need a convenient and trusted tool to help them build a conference website. In addition, with the rapid growth of the Internet and the explosion of conference information, recommend conferences to scholars that interest them becomes important. For this consideration, we designed and implemented an academic conference publishing system, which can publish conference information quickly, implements multi-level management and recommends conferences that they are interested in for system users. In addition, by associating with SCHOLAT, our system presents conference members’ personal academic information and provide an online communication platform. We simulate the actual use environment to deploy and verify the system, and it is proved that the system has excellent performance in security, availability, authority and other aspects.
Fully Immersive Web-Based Collaborative Virtual Environment for Upper Limb Rehabilitation Purposes

Web-based collaborative virtual reality is emerging as platform-independent technology that permits developers to produce fully immersive and interactive virtual environments accessible through web-browsers. The use of collaborative virtual environments can be helpful in situations when therapists and patients are unable to meet personally. This work introduces an extension of the LIRKIS G-CVE system with web-based interfaces for remote management of the upper limb rehabilitation process. Concerning the quality and safety of web technologies., we consider distant virtual training to be efficient for ordinary people.
The Level of Digital and Communication Competencies of Students at Faculties of Civil Engineering in the Distance Learning Form

For education, 2020 became the year of distance learning and online communication in the teacher-student relationship, but also in the student-student relationship. This teaching system brings many challenges for both parties and the need to improve the communication and digital competencies of all involved. It also requires increased demands on the hardware and software provision of teaching on both sides of the teaching process. This article focuses on the issue and description of communication and digital skills needed for distance learning. The main goal of the research is to compare and map the communication and digital ICT competencies of faculty students with a construction focus during full-time and distance learning. The results of the research are analyzed in the article using methods of descriptive as well as analytical statistics.
Comparing Cybersecurity Information Exchange Models and Standards for the Common Secure Information Management Framework

Cyber threats have increased in spite of formal economic integration in the world. Decision-makers and authorities need to respond to the growing challenge of cyberthreats by increasing cooperation. Information is one of the main facilities when the objective is to prevent hybrid threats at EU level and between the western countries. The main purpose of the study is to find out separating and combining factors concerning existing cyber information sharing models and information management frameworks in western countries. The aim is also to find out crucial factors, which affect the utilization of a common Early Warning System for the ECHO stakeholders. The main findings are that unclear allocation of responsibilities in national government departments prevents authorities from fighting together against cyber and physical threats. Responsibilities for developing cybersecurity have been shared among too many developers. Operational work concerning cyber threat prevention between European public safety authorities should be more standardized, with more centralized information management system. When the purpose is to protect the critical infrastructure of society, public safety organizations in European Union member states need proactive features and continuous risk management in their information systems. The sharing of responsibilities for standardization concerning information management systems and cyber emergency procedures between authorities and international organizations is unclear.
A Sentiment Analysis Service Platform for Streamed Multilingual Tweets

Micro-blogging and social-media platforms are now prominent forums for disseminating information, opinions and commentaries. Among these, Twitter enjoys an in-excess of 330M base of users who continually produce and consume information snippets. Users collectively create a voluminous and multi-lingual corpus in a very broad range of topics on a daily basis. The discourse generated in the blogosphere is often of prime interest and importance to individuals, organizations, and companies. These actors would certainly like to periodically receive an overall assessment of demonstrated "sentiments" on specific issues by automatically classifying tweets expressed in different languages in conjunction with big-data analytics. In this paper, we propose a scalable service platform that employs multilingual sentiment analysis to classify streamed-tweets and yields analytics for selected topics in real-time. We discuss the main component of our Spark-enabled platform as we seek to offer an effective big-data service that can: 1) dynamically handle voluminous as well as high-rate tweettraffic through a multi-component application exploiting the latest software developments, 2) accurately identify messages originated by non-genuine user-accounts, and 3) utilize the Spark machine-learning library (MLib) to successfully classify streamed multi-lingual messages in real-time, using multiple potentially distributed executors. To empower our service platform, we have adopted training sets and developed sentiment analysis (SA) models for English, French, and Greek that help classify streamed tweetswith high accuracy. While experimenting with our distributed analytical platform, we establish both accurate and real-time classification for tweetsexpressed in the above European languages.
Design and Implementation of Multimedia Technology Assisted English Vocabulary Teaching Courseware for Industrial Engineering Major

Abstract With the popularity of computers, multimedia teaching came into being. Facts have proved that multimedia teaching has many advantages (e.g., information diversification, integration of various technologies, interaction of processing processes, etc.). However, as everyone knows, industrial engineering students are non-English majors and belong to science and engineering. Students’ English level lags behind English majors. In English learning, vocabulary memory is usually the biggest obstacle for students to learning English. Especially some synonyms, antonyms, pronunciations, and derived words are difficult to remember and easy to confuse. There are also many synonyms, whose breadth and depth are complex, and it is difficult for students to remember clearly. Therefore, this puts forward a new topic for industrial engineering English teachers, that is, how to make monotonous English vocabulary teaching interesting, vivid, and easy to remember while also improving students’ English performance and English learning ability. From the perspective of multimedia teaching, this article aims to find a more convenient, efficient, and practical method of teaching English vocabulary for industrial engineering majors, and make English vocabulary teaching courseware related to industrial engineering. From a practical point of view, the use of English multimedia in industrial engineering is promising. Through the comparison of experimental data, the specific role of multimedia teaching in English vocabulary teaching is discussed. Before the experiment, the results of the experimental class and the control class are very different. The English learning progress and academic performance of the experimental class are much better than those of the control class. The average score for gender differences is 1.2 points. There are significant differences in test results after the experiment. The average score difference is 4.71 points. The concentration of the experimental class is also better.
Reflections on Orlov

In 1928 Ivan Orlov published a remarkable paper which contains the first formulation of a relevant logic. The paper remained largely unknown to English-speakers until this discovery of relevant logic was shown by Kosta Doen in 1992. By that time the material on relevant logic was well known; however, there is more of interest in Orlov's paper than this: his remarks on intuitionism, the motivation for his construction, and its wider implications. This paper explains and reflects on these matters.
Prospects for the development of the library of a creative university

The modernization stages of arts academic library as suggested by the authors are highlighted: preliminary analysis of regulatory documents and the resource base of the scientific library of the Kemerovo State Institute of Culture, planning for collections development with for books and information resources, upgrade of library services, planning for modernization and technological deve-lopment, and designing library zones. The authors offer their recommendations on improvement of library information services within the context of distance educa-tion and modernizing the material and technical support of the library based on foresight technology and a sociological survey of students and the faculty. The students’ and faculty’s demands for advanced services and digital services through social media were revealed. The findings of the study support the idea of optimi-zation and modernization of the range of library services. For the students, the library not only provides information support, but also offers its facilities for communication, individual and team work, and relaxation. Within this context, the procurement cost estimates were prepared. The contest of students’ design pro-jects of library space zoning was organized.
Discrete-time estimation of switched stochastic polynomial systems and its application to reconstruction of induction motor variables

This paper presents a solution to the filtering problem for a class of stochastic discrete-time nonlinear polynomial systems with switching in the state equation over linear observations and its application to a mechatronic system. The switching in the state equation is performed between two different nonlinear functions according to a sequence of independent Bernoulli random variables that take the quantities of zero and one. The mean-square filtering solution is obtained for a general nonlinear discrete-time polynomial system and a finite-dimensional system of filtering equations is then obtained for a second degree polynomial system as a particular case. The mean-square estimates of polynomial state terms are expressed as functions of the estimate and covariance matrix. Finally, some numerical simulations are carried out to reconstruct the variable states given a vector output measurement for a linear system, a second degree polynomial system, and an induction motor model to show effectiveness of the proposed algorithm. The proposed method is compared with an extended Kalman filter-based algorithm for discrete-time switched nonlinear systems.
Problems with the use of forensic techniques in the judicial investigation of the authenticity of an electronic digital signature.

Abstract This article aims to study the tactical foundations of conducting a forensic study of the authenticity of an electronic digital signature and documents that raise doubts about their reliability. The methodological foundations of identification, classification and search studies of “electronic traces” and signatures of the transformation made on the basis of algorithms with imitation and use of the latest methods are given. To identify “electronic traces” the functions of using hardware and technical means for counterfeiting an electronic signature are specified and methods of establishing to determine the kind and type of a particular device on which the documented information was manipulated. There are considered sets of features that allow identifying parts and details of documents subjected to an unsanctioned modification, as well as a specific list of correctly formulated questions, which should be put to the expert in the decision on the appointment of an examination to determine signs of forgery.
Cbdc – A New Stage In Money Digitalization

CBDC (central bank digital currency) is a currency issued or approved by central banks or institutions authorized by the country concerned. At the time of writing, no such currency has been issued, but there is an active professional worldwide discussion of the possibilities, advantages, disadvantages, prospects of creating such money. The purpose of the report is to give a basic description of the potential CBDCs in the context of issuance and circulation of money, including among others accounting treatment. Comparison with cryptocurrencies is a focus too. As CBDC is still at project level, the opportunities presented are hypothetical and based on literature research. However, the importance of the problem requires informing the public and involvement of the academic community in the discussion.
Blockchain-Based Food Supply Chain Management

Blockchain is an emerging technology that is based on the concept of distributed ledgers. It allows for pervasive transactions among different parties and eliminates the need for third-party intermediaries. Several of blockchain's characteristics make it suitable for use in the agriculture sector. Some of the potential applications of blockchain include efficient management of the food supply chain and value-based payment mechanisms. The products of agriculture are usually the inputs for a multi-actor distributed supply chain, in which case the consumer is usually the final client. The food chain involves several actors including farmers, shipping companies, distributors, and groceries. This makes the entire system to be distributed with multiple actors playing different roles throughout the chain. This currently used system is inefficient and unreliable in various aspects. This project aims to leverage blockchain technology to solve and address discrepancies involved in food supply chains.
Handwritten Myanmar Character Recognition System using the Otsu’s Binarization Algorithm

Handwritten is a famous techniques involved in many recognition system in image processing and pattern recognition.In this paper, first step is pre-processing includes noise reduction, colour conversion and edge detection method to segment Handwritten Myanmar Characters from the image.Also, Open Source Tesseract OCR engine is used to recognize the segmented Handwritten Myanmar Characters.The recognition accuracy will highly depend on the good segmentation.Some of the handwritten recognition applications are criminal documentation, security method, image and Movie managing and medical science research on Myanmar character recognition is still in its early days with limited literature available till date.