Reviewerly/exHarmony huggingface dataset:
A Text Classification Method Based Automobile Data Management

The state grid has a large number of assets, the physical part of these assets involves many categories, such as power equipment, real estate, vehicles and so on. The state grid needs to record and manage these assets, which involves the process of storing equipment and assets with specific IDs. However, because the type of equipment and assets are not uniformly coded across provinces, and various text descriptions vary from one to another, making this management and recording process is very difficult and complex. FastText is a text-based classifier, its N-gram model can read the sequential information between words and is faster than most other models, so we decide to use FastText to solve this problem, that is, through the classification of text to record various equipment and assets. It is suitable for the need for automatic identification of equipment and assets in this project. The purpose of this method is to ensure the correct correspondence with the type of equipment and assets according to the standard rules of technical object types of the state grid. FastText has a good classification accuracy, and so far, the method has achieved good results in the automotive category.
Research on Domain Emotion Dictionary Construction Method based on Improved SO-PMI Algorithm

The analysis of netizens' emotional tendency after emergencies is an important means for the government to understand netizens' mentality and guide public opinion. Constructing a scientific and reasonable domain emotion dictionary is an important part of accurate emotion analysis of Internet users. Currently, there are few sentiment dictionaries in the field of college education. This article proposes an improved SO-PMI method for constructing emotional dictionaries in the field of college education. Use TF-IDF to sort the importance of emotional seed words, modify the field importance of the SO-PMI extended word set, and a basic emotional dictionary formed by combining Dalian Polytechnic and HowNet emotional dictionary, and finally formed an emotional dictionary in the field of college education. According to the judgment of interrogative sentences and exclamation sentences, the calculation rules of sentiment intensity of sentences are revised. The experimental results show that this method has achieved good results on the actual Weibo comment data set.
LABORATORY PRACTICAL AID AS A TOOL TO REALIZE PRACTICE-ORIENTED APPROACH IN TEACHING PHYSICS AT HIGHER SCHOOL

The article deals with the problem of realizing the content of physical education, which is related to the fact that the knowledge being formed remains unclaimed, completely divorced from the need to apply it in reality. The essence of the introduction of laboratory and practical aids into the educational process of studying physics is revealed. One of the examples of a practical task introduced into the educational process to implement this aid is given. It is concluded that laboratory practical aid facilitates the realization of practice orientation principle in the curriculum, increase of the indicators of performance and formation of general professional competences of student’s personality.
Vehicles Detection Based on Improved YOLOv3

Real-time detection of road vehicles is a hot research topic in the field of computer vision. Aiming at the problems of low detection accuracy and slow speed in road vehicles detection algorithms, a road vehicles target detection method based on improved YOLOv3 is proposed in this paper. Firstly, by embedding the Convolutional Block Attention Module (CBAM) in the feature layer after the fusion of low-level features and high-level features, the ability of the neural network to obtain effective information is improved. Secondly, the adaptive multi-scale anchor frame size is determined based on the K-means clustering algorithm, which is beneficial to improve the detection ability of large, medium and small vehicles targets. Finally, the DIoU loss function is introduced to improve the ability to recognize occluded targets. The experimental results show that the average accuracy of the proposed method on the standard data set KITTI reaches 94.36%, which is 2.2% higher than the traditional YOLOv3, and the detection speed reaches 52.0f/s, in other words, the model can still maintain a better real-time detection speed when detection accuracy is improved.
THE TRANSITION TO ONLINE LEARNING AS A NEW STAGE IN THE DEVELOPMENT OF HIGHER EDUCATION: SOCIAL BENEFITS AND RISKS THROUGH THE PRISM OF ASSESSMENTS OF KEY PARTICIPANTS IN THE EDUCATIONAL PROCESS

The article presents the results of the first stage of monitoring current trends in the educational space, determined by pandemic circumstances. The purpose of this stage was to comprehend the process of transformation of education, characterized by the strengthening of the role of information technology, as well as to form an idea of ​​the satisfaction of students and teachers with the quality of online learning. The research included two directions. The “office” part made it possible to conduct a comparative analysis of higher education models in the pre-pandemic and current period. The field studies included both quantitative and qualitative measurements. In the first case, a survey of students of higher educational institutions was conducted, in the second - structured interviews with representatives of the teaching community.
Topological and Optimal Design of Grasping Manipulator for Obstacle Crossing Vehicle with Foldable Operating Arm

Aiming at the new demand for movable operating manipulators using on the spacecraft surface and lunar surface, an obstacle crossing vehicle with a foldable large workspace arm and a grasping manipulator is carried out. Firstly, the topological structures of the moveable vehicle is demonstrated in detailed by using the physical models of each part. Then, the forward position analysis of the manipulator is carried out, and the end pose of the manipulator is calculated. The correctness of the kinematic analysis of manipulator is verified by comparing theoretical result from MATLAB toll box with the simulation result obtained by SolidWorks. Finally, the kinematics performance evaluation index of the manipulator is defined, and is kinematic optimization is completed.
Stable and Diverse: A Unified Approach for Computerized Adaptive Testing

Computerized Adaptive Testing (CAT), aiming to provide personalized tests for each examinee, is an emerging task in the intelligent education field. A CAT system selects questions step by step according to the knowledge states of each examinee, which are estimated by Cognitive Diagnosis Models (CDM). Most existing methods depend on the performance of a single CDM, which is often unstable. Besides, they may select similar questions to generate a test, which to some extent ignores the diversity of selected questions. To this end, in this paper, we propose a novel framework, namely Ensembled Computerized Adaptive Testing (EnCAT). Specifically, EnCAT comprises two components, ensemble part and explore part. In the ensemble part, we ensemble multiple CDMs to determine whether a question is informative, which ensures the stability of CAT process. Then, in the explore part, we learn the question representation from the question content and design a mechanism to quantify the similarity of different questions, which avoids the selection of similar questions and is free of expensive human labeling. Finally, extensive experiments are conducted on a real-world dataset, where the experimental results demonstrate the effectiveness of our proposed EnCAT framework with good performance.
Low-Cost Smart Cart with Nutritional Information

In this work, an architecture and solution for the acquisition of products and navigation in grocery stores using a smart cart are proposed. The cart also can provide nutritional information of certain products. This SMART cart was named as billing, navigation, and nutrition (BNN) cart highlighting the advantages of improved quality of services provided by retailers to augment the consumer value. Thus, BNN cart provides smart billing of products, easy navigation inside the shop for identification of products, and nutrient information display, which will be a more wanted choice in the upcoming days and thereby providing a great customer experience.
NON-TRADITIONAL TECHNOLOGIES AND WAYS OF CULTIVATING PATRIOTISM, CIVIC CONSCIOUSNESS AND RESPECT OF HUMAN RIGHTS IN CADET CLASSES

The problem of cultivating patriotism and personal civic consciousness is updated. The features of the concepts of “civic consciousness” and “patriotism” are emphasized. Opinions of researchers on the essence of these concepts and respondents (cadets) enquiry results on the essence of patriotism and the practice oriented program of cultivating patriotism and civic consciousness in cadet classes “I-we-citizen” are presented. The principles of education and program realization are shown. Technologies of deliberation, workshops, project learning, health saving, cognitive creative actions technology of I.P. Ivanov, reflective and game technologies were singled out as most efficient.
THE IMPORTANCE OF CYBER PROFESSIONALISM OF A TEACHER IN THE DIGITAL TRANSFORMATION OF CAREER GUIDANCE WORK

The article considers the importance of a teacher's cyber-professional competence in the context of the digital transformation of career guidance. To identify the relevance of the article, a multivariate analysis of the functioning of the existing career guidance system in general secondary education was carried out. According to the survey results, traditional career guidance tools for high school students are much more popular than digital ones. This situation does not meet the modern needs of high school students in the field of career guidance and shows that teachers and psychologists are not ready to demonstrate it with the help of digital tools. Therefore, the article concludes that a cybercompetent teacher in a digital education environment should be able to meet the needs of students in the field of professionally oriented support for professional self-determination in the field of IT, STEM, STEAM and STREAM professions
IEEE VR 2022 Message from the Journal Paper Chairs and Guest Editors

In this special issue of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IEEE Transactions on Visualization and Computer Graphics</i> (TVCG), we are pleased to present a subset of papers from the 29th IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2022), held virtually March 12-16, 2022, in Christchurch, New Zealand.
Vision-Based Human Attention Modelling

This chapter is primarily concerned with human attention modelling, specifically the human driver. Previous related studies have typically focused on a single side without providing a comprehensive understanding. As a result, this chapter introduces a context-aware human driver attention estimation framework that combines scene visual saliency information and appearance-based driver state to provide a more accurate estimation. It has been validated in a VR-based experimental platform. Currently, the implicit and explicit of the human cognitive state and the contextual scenario still ill-defined, and we hope the related research can investigate it further.
Support Point Sets for Improving Contactless Interaction in Geometric Learning for Hand Pose Estimation

Estimation of the hand pose of a surgeon is becoming more and more important in the context of computer assisted surgery. Previous point cloud-based neural network methods for this task usually estimate offset fields to infer the 3D joint positions. Occlusions of important hand parts and inconsistencies in the point clouds, e.g. caused by uneven exposure from the depth sensor, pose a challenge to these methods. We propose to simplify the optimization problem by only estimating a weight for each point of the cloud, such that the inferred joint position is given as the weighted sum over the input points. To better capture the directional information, we define a support point set that expands the convex hull of the hand point set and enter the union of both sets as input to our network. We propose a hierarchical graph CNN, whose graph structure enables optimal information flow between the two point sets. With a mean joint error of 9.43 mm, our approach outperforms most comparable state-of-the-art methods with an average reduction by 19%, while also reducing the computational complexity.
Implementación de una Red Neuronal Convolucional para la clasificación de ruido sísmico y señales sísmicas

This article develops a detection methodology of seismic events based on Convolutional Neural Network in order to improve the processing of huge rawdata of seismograms. This is a trained model by using 45 thousand signals between seismic event and noise, databases of the Geophysical Institute of Peru (IGP) and STEAD (Stanford Earthquake Dataset), for testing we use 15 thousand instances, I obtain a promising results, the confusion matrix, 99.18% of success and an accuracy of 99.69%. This method shows better performance that STA/LTA classical algorithm with less false-positives in 20% of 1000, it could improve the real time monitoring.
Immersive Experience Framework: A Delphi Approach

The concept of immersion has been widely used for the design and evaluation of user experiences. Augmented, virtual and mixed reality environments have further sparked the discussion of immersive user experiences and underlying requirements. However, a clear definition and agreement on design criteria of immersive experiences remains debated, creating challenges to advancing our understanding of immersive experiences and how these can be designed. Based on a multidisciplinary Delphi approach, this study provides a uniform definition of immersive experiences and identifies key criteria for the design and staging thereof. Thematic analysis revealed five key themes - transition into/out of the environment, in-experience user control, environment design, user context relatedness, and user openness and motivation, that emphasize the coherency in the user-environment interaction in the immersive experience. The study proposes an immersive experience framework as a guideline for industry practitioners, outlining key design criteria for four distinct facilitators of immersive experiences – systems, spatial, empathic/social, and narrative/sequential immersion. Further research is proposed using the immersive experience framework to investigate the hierarchy of user senses to optimize experiences that blend physical and digital environments and to study triggered desired and undesired effects on user attitude and behavior.
Teaching Chinese as a foreign language under the background of the Internet

The Internet era has become more dependent on interaction under the Internet, and with the expansion of China's international comprehensive strength, the boom in learning Chinese has gained momentum, making the threshold for learning Chinese lower and lower for learners from all walks of life. Due to the impact of the epidemic, the main position of teaching Chinese as a foreign language at home and abroad has also shifted from offline to online. The characteristics of Chinese classes for foreigners in the Internet context are very different from those of traditional Chinese classes for foreigners, mainly in terms of course length, teacher composition, teaching methods, classroom organization and management, and teaching media. In this paper, we first analyze the articles related to teaching Chinese as a foreign language classroom, online teaching classroom, and overseas online Chinese classroom research by using the visual analysis of China Knowledge Network, and then analyze the characteristics of online Chinese teaching by observing the popular Chinese teaching videos on foreign websites, and the similarities and differences among the existing online teaching models, and suggest improvements for future development.
Emergence of quasiperiodic regimes in a neutral delay model of flute-like instruments: Influence of the detuning between resonance frequencies

&lt;p style='text-indent:20px;'&gt;Musical instruments display a wealth of dynamics, from equilibria (where no sound is produced) to a wide diversity of periodic and non-periodic sound regimes. We focus here on two types of flute-like instruments, namely a recorder and a pre-hispanic Chilean flute. A recent experimental study showed that they both produce quasiperiodic sound regimes which are avoided or played on purpose depending on the instrument. We investigate the generic model of sound production in flute-like musical instruments, a system of neutral delay-differential equations. Using time-domain simulations, we show that it produces stable quasiperiodic oscillations in good agreement with experimental observations. A numerical bifurcation analysis is performed, where both the delay time (related to a control parameter) and the detuning between the resonance frequencies of the instrument – a key parameter for instrument makers – are considered as bifurcation parameters. This demonstrates that the large detuning that is characteristic of prehispanic Chilean flutes plays a crucial role in the emergence of stable quasiperiodic oscillations.&lt;/p&gt;
A NEW TECHNIQUE FOR COMPRESSION AND STORAGE OF IMAGES

During the past decades we have been observing a permanent increase in image data, leading to huge repositories.[1]. This paper focuses on image compression and storage. We define methods to improve the efficiency and effectiveness of image compression. Image compression refers to represent an image with as few bits as possible while preserving the level of quality and intelligibility required for a particular application. The present work aims to develop an efficient algorithm for compression and storage of two-tone image. In this paper, an efficient coding technique is proposed and termed as line- skipping coding for two-tone image. The technique exploits 2-D correlation present in the image. This new algorithm is devised to reduce fifty to seventy five percentage of memory storage.
FORMATION OF SENSORY-ECOLOGICAL REPRESENTATIONS AMONG MODERN PRESCHOOLERS

We consider the conceptual and methodological aspects of sensory-ecological representations formation of modern preschoolers. We define sensory-ecological representations as the cognitive basis for the development of a holistic attitude to the sensory-perceived world, which is a system of images, views that reflect the expressive features of objects that determine the nature of sensory perception. The concrete scientific level of work is provided by: the theory and practice of environmental education, the purpose of which is the formation of the ecological culture of the younger generation (first of all, the ecological consciousness of the individual); theories of developmental learning; modern theories and concepts of sensory education of preschool children. The dialogue of children and nature on a sensory basis is a primary condition for the formation of sensory-ecological representations of preschoolers. The interaction of preschoolers with representatives of flora and fauna, which cause a positive emotional reaction, is necessary. The purposeful pedagogical process of forming sensory-ecological representations of preschoolers was designed and implemented in the form of the cognitive and creative project “Rainbow Week”. SWOT-analysis shows beneficial and negative impacts of realized pedagogical process. The conclusion is made about the importance of the formation of sensory-ecological representations in the context of the formation of sensory-ecological culture of students. The results of the study can be used by educators of preschool educational organizations, teachers-psychologists to develop methodological materials and recommendations.
Lexical Semantic Analysis to support Ontology Maintenance Modeling of FMEA

For text-based documents, word representations and meaning extraction play essential roles in knowledge modeling and presentation. A maintenance procedure comprises consecutive logical arguments for determining step-by-step cause-effect events, ideally resulting in mitigative tasks. Therefore, the context and meaning representation when mimicking the purpose of a maintenance procedure are highly dependent on the word sense, syntax-semantic interface, and semantic features of the argument. This paper proposes an event-based ontology approach for supporting a failure-mode-effect analysis (FMEA), based on a lexical semantic analysis and on identifying the meaning(s) of contextual text. Our approach constructs a straightforward lexical semantic approach for analyzing the semantic and syntactic features of the contextual structures of maintenance reports, so as to facilitate translation and interpretation for knowledge-based reasoning in the format of an FMEA. Then, the knowledge is converted into a computer-understandable representation with less heterogeneity and ambiguity. The methodology enables users to obtain a representation format that maximizes shareability and accessibility, allowing for multi-purpose usage. First, it maps the argument structure into a causal event structure, in which an event is represented as a group of highly frequent contextual features or words logically linked together to shape structured arguments. Then, Dowty and Van Valin's decomposition model is employed in the format of [Event-State-Activity-Accomplishment-Result] to determine the syntax-sematic interface(s) and linking rules in the causal chain. In addition, Van Valin's model is used to differentiate between active and causative accomplishments for punctual/non-punctual changes of states in the causal chain. Finally, the metadata and/or hypernyms of causal events are represented, to accommodate ontology modeling for semantic extraction and cause-effect interpretation. We show how easily the result is converted to a computer-understandable document using Web Ontology Language & Resource Description Framework (W3C), thereby enriching interoperability and data exchange, explicit wording, multidimensional word representation, and contextual meaning extraction in machine processing.