Reviewerly/exHarmony huggingface dataset:
Improving the social activity of students on the basis of pedagogical neology is a socio-pedagogical necessity

The article discusses the need for social activity of students on the basis of pedagogical neology. The development of creative social activity among young students is one of the most important tasks of the National Project “Education”. The social activity of young people is one of the significant components of the social development of students who are able to fully live in a new democratic society and be the most useful for it. The considered phenomenon of social activity in a detailed form allows specialists to understand and outline the right vectors for creating pedagogical conditions for the development of creative social activity of students.
KNOWLEDGE MANAGEMENT SYSTEM OF THE INDUSTRIAL PRODUCTION, SCIENTIFIC AND EDUCATIONAL COMPLEX AS A DIDACTIC TOOL FOR THE DEVELOPING PROFESSIONAL COMPETENCE OF AN ENGINEER

The relevance of the research is justified by the need for systematic collaboration between universities and production in the context of digitalization, since other technologies are proposed that change the learning process. The paper presents an analysis of the literature on the problem of creating a knowledge management system in the industrial and scientific educational complex, which shows the need to create an information infrastructure. The application of the knowledge management system in educational practice allows you to establish multi-level connections (interpersonal, intergroup, interorganizational) in the intellectual field of the industrial production, scientific and educational complex, as well as comprehensively solve didactic and educational tasks. The paper also attempts to reveal the essence of the concept of "didactic tools". Didactic tools should be considered as a set of interrelated tools intended for participants in the learning process, the use of which in educational practice contributes to the effective solution of certain didactic tasks. A working definition of the developed didactic tools is proposed – the knowledge management system of the industrial, scientific and educational complex: a set of interrelated and systematic processes and tools intended for the subjects of interaction in the intellectual field of the industrial, scientific and educational complex. It provides collection, formalization, examination, updating, accumulation, preservation, enrichment, reuse and dissemination of industry knowledge. The means allocated as part of the didactic tools are always systematically interconnected, although each of them can solve its own separate task. There are two major subsystems in the knowledge management system: a subsystem for managing separated knowledge, which are separated from the personality of their bearer and are presented in some symbolic form (text, hypertext, ontology), and a subsystem for managing personal knowledge that people carry (students, teachers, researchers, experts from industry). The subsystem of personal knowledge management is analyzed, it involves the use of pedagogical technologies of a personality-oriented nature, and the need for the forming a culture of working with knowledge, the presence of professionalism among instructors when using the knowledge management system of an educational organization is substantiated. The development of a knowledge management system for an industrial scientific, industrial, scientific and educational complex requires the solution of many diverse tasks that require the involvement of experts from different subject areas in the team of developers, which create the knowledge management system.
The quality of care with the use of information technology in the professional school Doutor José Alves da Silveira in Quixeramobim – Ceará

Over the years the quality of care in institutional organizations has been seen as a need for improvement and full improvement for citizens to enjoy the services provided with zeal, strife for efficiency and effectiveness, structuring elements for an administration focused not only on theories, but also on results. In this context, in order to reduce the impasses arising from the quality of care, the research question arose: What influence do information technologies have to boost the quality of care at the Professional School Doutor José Alves da Silveira? This article highlights the importance of the role of quality of care with the use of information technology at the Professional School Doutor José Alves da Silveira in Quixeramobim Ceará, with the objective of describing the processes related to quality management in care from the implementation of information technologies, analyzing the changes promoted in the quality of care from the accused speech of teachers and comparing the previous and current situation of the quality of care through the analysis of the data extracted in the above mentioned objectives. To meet the purposes of this study, the methods and techniques used were exploratory research with a qualitative approach, using the interview method and, research instrument, the questionnaire, with five open questions sent to twelve class directors through the google form. The participant observation method was also used, which aims to capture the meanings and subjective experiences of those who intervene in the process of social interaction. The interviewees were chosen for convenience and sampling using the saturation technique. The results collected were compared by the teachers' statements, perceiving the similarities in the answers. It is concluded that the quality of care combined with information technologies were satisfactory, in improving the services provided to users increasing the level of satisfaction and agility, in the way of perceiving the processes of technological innovation to make the organization an interactive space with more dialogue, interaction and agility in the flow of processes.
Exploration and Practice of Cultivating Students' Innovative Ability Based on MuRobotSys

With the continuous changes in modern undergraduate education, personnel training, and education methods, the significance of innovation ability in comprehensive quality training has become a normalized goal. The simulation platform's experimental learning can provide the foundation for the integrated teaching model's training of engineering project simulation ability as well as training of innovative ideas and divergent thinking. Therefore, the development and practice of engineering projects based on the simulation platform are common experimental methods in teaching. This article locates the innovative talent training concept of “high comprehensive quality and strong practical ability,” which is based on the MURobotSys simulation platform to carry out robot innovation teaching, put forward and practice the “Three-layers” teaching system, under the traction of innovative practical teaching and robot competition. Providing a complete, reasonable and efficient teaching system for the cultivation of students’ innovative ability has important significance and effect on the cultivation of students’ innovative ability.
Recognition of digital phase modulation signal in wireless communication

Digital modulation signal is an important field of wireless communication. With the continuous development of wireless communication technology, the recognition technology of digital signal is also advancing. In this paper, the recognition technology of digital phase-modulation signal is studied, and the received MPSK signal is converted into an isopotential horoscope through data processing. Based on deep learning theory, three deep learning models such as ResNet, VGG16 and Mobilenet are selected to carry out feature extraction and recognition of the isopotential constellation of MPSK signal, and the accuracy of recognition is compared.
The Challenge of Classification Confidence Estimation in Dynamically-Adaptive Neural Networks

An emerging trend to improve the power efficiency of neural network computations consists of dynamically adapting the network architecture or parameters to different inputs. In particular, many such dynamic network models are able to output ’easy’ samples at early exits if a certain confidence-based criterion is satisfied. Traditional methods to estimate inference confidence of a monitored neural network, or of intermediate predictions thereof, include the maximum element of the SoftMax output (score), or the difference between the largest and the second largest score values (score margin). Such methods only rely on a small and position-agnostic subset of the available information at the output of the monitored neural network classifier. For the first time, this paper reports on the lessons learned while trying to extrapolate confidence information from the whole distribution of the classifier outputs rather than from the top scores only. Our experimental campaign indicates that capturing specific patterns associated with misclassifications is nontrivial due to counterintuitive empirical evidence. Rather than disqualifying the approach, this paper calls for further fine-tuning to unfold its potential, and is a first step toward a systematic assessment of confidence-based criteria for dynamically-adaptive neural network computations.
Eye Movement and Visual Target Synchronization Level Detection Using Deep Learning

In recent years, deep learning has been widely used in the eye-tracking area. Eye-tracking has been studied to diagnose neurological and psychological diseases early since it is a simple, non-invasive, and objective proxy measurement of cognitive function. This project aims to develop a system to automatically track the synchronisation of eye movement data and its visual target. To achieve this goal, we employ a deep learning algorithm (Points-CNN and Head-CNN) to detect the eye centre location and classify the synchronisation level of the eye movement and visual target. Moreover, we modify the eyediap dataset to assist with our research objective. The video data in the eyediap dataset is used to track the eye movement trajectory, while the visual target movement data is used to extract the direction change window. The movement feature vectors are extracted from the eye movement data and the visual target movement data with the direction change window. Euclidean distance, Cosine similarity, and Jaccard similarity coefficient are used to assist the synchronization detection of the eye and visual target movement vector. In the synchronisation detection part, K-Nearest Neighbors, Support Vector Machine, Logistic Regression are investigated.
A Bayesian formulation for the optical monitoring of deformation process by digital image correlation

In this communication reference was made to the inverse problem of detecting displacement fields by optically monitoring through a single camera the in plane deformation process of a flat domain. A Bayesian, stochastic formulation was proposed for such Digital Image Correlation (2D DIC) problem, in the framework of a finite element discretization for the kinematic field. The focus was posed on a suitable observation or measurement equation ensuring identifiability of the state parameters, herein represented by the nodal displacements. The peculiar features of the DIC problem, severely ill posed, have led to adopt a vector measurement equation in implicit form: it was derived by prescribing stationarity of the L2 objective function, which quantifies the mismatch between a pair of digital images acquired at different time instants. Once such equation was specified, the residual vector and the sensitivity matrix, key ingredients of Bayesian approach, turned out to coincide with pseudo load vector and pseudo stiffness matrix governing the linear incremental problem (i.e. the Newton-Raphson iterations) for finite element DIC. Updating Bayesian equations provided current displacement estimates endowed with covariance matrices quantifying their degree of uncertainty, on the basis of previous estimates and of the new experimental information. Preliminary results were discussed, with reference to synthetic data.
Prior distributions-based data augmentation for object detection

To solve the problem of data hungry, data augmentation methods based on cut-and-paste that can explore the visual context are widely used.However, these methods either limit the expansion of the instances diversity of dataset or increase the computational burden.In this paper, we propose a novel data augmentation strategy based on prior distributions, which can be used to guide data augmentation for object detection.On one hand, the method can effectively capture the relationship between the foreground instance and the visual context.On the other hand, it can increase the instances diversity of the original dataset as much as possible.Experimental results show that the performance of the popular object detection model can be effectively improved by expanding the original dataset with our method.Compared with the baseline, our method improves by 0.8 percentage point on PASCAL VOC and 1.1 percentage points higher on cross-data test set.
Motion Planning for Autonomous Vehicles Based on Dynamic Bio-inspired Neural Network Model

Background: Nowadays, with the increase of the number of cars, traffic accidents occur frequently, improving the active safety of cars, and traffic safety has become an inevitable requirement of the development of intelligent transportation. Objective: Motion planning for autonomous driving is a challenging problem due to the uncertainty of the unknown complex environment. Conventional methods may fail in some cases on account of poor real-time performance and instability. The objective is to propose a motion planning method to plan a reasonable path autonomously for an autonomous vehicle in unknown environments and ensure obstacle avoidance. Methods: The solution is to use the improved Glasius Bio-inspired Neural Network (GBNN) to plan a feasible route for the autonomous vehicle, which adaptively changes the direction of movement according to the changes of neuron values. Neuron connection weight in the neural network is reasonably improved to increase the update rate of activity value, so that this model can more adapt to the changes of dynamic environment. Meanwhile, the planned trajectory is fitted to meet vehicle kinematics model. Results: Unstructured and structured roads are tested in static and dynamic environments, respectively. During the test, static obstacles and surrounding vehicles’ intentions are all generated randomly. In this way, the generated route can be optimal and adapt to the stochastic as well. Conclusion: Simulation results in unstructed road and structed road show the effectiveness of the proposed algorithm in autonomous motion planning. In addition, the performance of path length, smoothness and turning angle has been improved.
SUS Urdu based Evaluation of Websites of Higher Educational Institutes of Pakistan

An institute needs to grow day by day in all aspects like a large number of admissions, educational quality, innovations, etc. Educational marketing provides a variety of opportunities for an institute by getting the attention of students. The students seeking admission for higher education can check the official website to get the know-how of an institute as it’s the first authentic source of information. The website must be easy to use for students to get the latest information. In this study, the websites of University of Engineering and Technology, University of the Punjab, and University of education are evaluated through the SUS scale developed in the Urdu language. A total of 60 participants were engaged. The results show that the SUS score of these websites was in the “low marginal” range.
DPETAs: Detection and Prevention of Evil Twin Attacks on Wi-Fi Networks

Numerous types of threats could become vulnerable to Wi-Fi networks. In terms of preventing and reducing their effect on the networks, it has become an imperative activity of any user to understand the threats. Even after thoroughly encrypting them, the route between the attacker’s device and the victim’s device may even be vulnerable to security attacks on Wi-Fi networks. It has also been noted that there are current shortcomings on Wi-Fi security protocols and hardware modules that are available in the market. Any device connected to the network could be a possible primary interface for attackers. Wi-Fi networks that are available in the transmission range are vulnerable to threats. For instance, if an Access Point (AP) has no encrypted traffic while it is attached to a Wi-Fi network, an intruder may run a background check to launch the attack. And then, attackers could launch more possible attacks in the targeted network, in which the Evil Twin attack have become the most prominent. This Evil Twin attack in a Wi-Fi network is a unique outbreak mostly used by attackers to make intrusion or to establish an infection where the users are exploited to connect with a victim’s network through a nearby access point. So, there are more chance to get user’s credentials by the perpetrators. An intruder wisely introduces a fake access point that is equivalent to something looks like an original access point near the network premises in this case. So, an attacker is capable of compromising the network when a user unconsciously enters by using this fake access point. Attackers could also intercept the traffic and even the login credentials used after breaching insecure networks. This could enable monitoring the users and perhaps even manipulating the behavior patterns of an authorized network user smoother for attackers. The key consideration of this research paper is the identification and avoidance of the Evil Twin attack over any Wi-Fi networks. It is named as DPETAs to address the strategies that intruders use to extract identities and what users need to do to keep them out of the networks.
PENINGKATAN HASIL BELAJAR MELALUI MEDIA PERMAINAN GO GO EGG DI SEKOLAH DASAR

The purpose of this study is to improve student learning outcomes by using a game media called Go Go Egg. The game is adapted from a board game called Jumanji. The theme of this game is about introducing the diversity of Indonesian culture.The research method used is quasi-experimental with a one-group pretest-posttest research design. The subjects in this study were 19 fourth grade elementary school students. This research was conducted to see whether or not there was an increase in student learning outcomes before using the Go Go Egg game media and after using the Go Go Egg game media based on Indonesian cultural diversity. The data collection technique used was a written test in the form of multiple choice questions on the pretest and posttest with equivalent questions. The data analysis technique used in this research is the paired t-test.The results of the study of learning outcomes using the Go Go Egg game media an increase in the average value. The results at the pretest were 13.58 and increased at the posttest to 18.84. The conclusion from this study is that the Go Go Egg game can improve the learning outcomes of fourth grade elementary school students.
Underwater State Estimation using Bearings only Measurements with an Emphasis on Sonar

Surveillance in underwater is very important in naval defence system. This is done by using the acoustic/sound waves in underwater rather than optic/ electromagnetic waves as these are susceptible to high attenuation. The Sonar which uses the acoustic waves to detect and track the target is mounted/ placed on the observer ship/ submarine. The Sonar generate the bearing measurements. Sonar operates both in active and passive modes. Sonar operating in passive mode is generally preferred as there is less or no risk for the observer of being tracked by the target. In this research work, an overview of sonar operation is presented and the unscented Kalman filter algorithm is applied to track the target path using bearing measurements. The simulation results are presented obtained using Matlab. The UKF algorithm is evaluated using Monte-Carlo simulation.
Gradability in MTT-Semantics

In this paper, we look at the issue of gradability within formal semantics in modern type theories (MTT-semantics). Specifically, we look at both gradable adjectives and nouns, and show that the rich typing mechanisms afforded by MTT-semantics can give us a natural account of gradability. Gradable adjectives take indexed nouns as their arguments, while gradable nouns are $$\varSigma $$ -types where their first projection is a degree parameter. Furthermore, we provide a standard polymorphic measure function applicable to all gradable adjectives and nouns. We also look at multidimensional adjectives and use enumerated types to capture multidimensionality. We formalize our account in the Coq proof assistant and check its formal correctness. Lastly, we briefly describe a recent proposal of model gradability by means of subtype universes in MTTs that can potentially give a unifying treatment of gradability for both regular gradable adjectives, but also multidimensional ones.
Comparative Analysis of Highly Ranked BIS Degree Programs

Student centeredness in curriculum development has pedagogical benefits. Learning outcomes describe what competences will be possessed by students after graduating. Degree programs as well as labour market needs may be compared based on such competences. Developing or redesigning Business Information Systems (BIS) degree programs may utilize offers of competitor institutions as best practices. This was the case at a Hungarian university where the process of reforming the BIS program to meet changing market requirements included a review of peers. This paper presents both competitor and labour market analysis to create a baseline how programs offered by peer institutions ranked on Times Higher Education World University Rankings perform.
The Effect of Education Funding Sources on Increasing Student Learning Outcomes at Manado 7 State High School

This research aims to determine the source of education funding and the magnitude of the influence of these sources of educational funding on student learning outcomes. The expected benefits from this research include practical benefits, which can serve as a reference for readers and become a means for this research to explore economic education theories, and theoretical benefits as inputs for Education Office. This research used a descriptive method with correlational techniques, in which the data collected were analyzed with a correlation formula. The population was all students who received BKM (Bantuan Keluarga Miskin or Poor Family Assistance) scholarships, and the sample was taken from the entire population. The research results showed that students’ average potential was satisfactory, and education funding significantly influenced student achievement. Apart from the education funding factors, learning achievement is also determined by other factors, such as student perseverance.
Changing approaches and educational practices in engineering education in the context of the Covid-19 pandemic

The article describes the experience of the authors’ transition to distance learning during the COVID-19 pandemic using the example of the online course “Engineering Mechanics” hosted on the National Open Education Platform. The course consists of original digital content: lecture notes, a base of educational tasks (simulators), test and homework assignments, practical examples and demonstrations of video and other educational materials. A comparative study of the learning outcomes of Ural Federal University (UrFU) students obtained using mixed learning technology in 2019 and distance learning in a pandemic was carried out. The transition to distance learning showed that training using the online course “Engineering Mechanics” can be considered as an alternative to traditional training.