Reviewerly/exHarmony huggingface dataset:
Physics laboratory work using cloud technologies

The article describes the structure and content of the physics textbook «Laboratory work using cloud technologies» for students of vocational higher education institutions. The importance of modernizing the educational process in physics in general and approaches to conducting laboratory work in particular using the methods of modern information and communication and cloud technologies are analyzed. The importance and advantages of digitization of the educational process in physics through the use of cloud services, virtual laboratory works, simulators, mobile applications, flash animations, etc. are substantiated. The theoretical and practical blocks of the manual are described in detail. The theoretical unit is represented by three sections and is filled with didactic and methodical materials that contain recommendations, advice and rules for organizing, preparing and conducting a physical experiment. The practical unit of the manual is represented by one section «Laboratory works», which presents instructions for seven laboratory works. A feature of such works is the use of virtual laboratories, simulators, and cloud environments for testing physical laws, researching physical phenomena, and determining physical quantities. The article provides an example of instructions for laboratory work «Determining the index of refraction of light at the boundary of separation of two media». The research presented in this experiment is carried out using the «Refraction of Light» physical simulator of the website Phet.colorado.edu - the website of the University of Colorado. The process of measuring the refractive index of light at the boundary between two media is described in detail and step by step. The order of performing some tasks is illustrated by the corresponding screen images of the «Refraction of Light» physics simulator. The materials for surveying and monitoring the educational achievements of students are given, among which three directions of questions and tasks are singled out for the didactic purpose: to check the assimilation of knowledge, to check the formation of skills and abilities, to check the formation of beliefs. This manual has been tested in groups of students of the humanitarian profile of institutions of vocational pre-higher education. At the All-Ukrainian competition «Pedagogical OSCAR – 2023», the manual won the 2nd place in the nomination «Innovative approaches to the organization of practical training of students of vocational pre-university education».
Preparation of future science teachers for cognitive visualization of the educational process

The issue of designing a qualitative educational environment for the formation of a flexible personality in the light of global world changes has been actualized in the article. Its main essential characteristic is the ability to adapt to the changing conditions of the modern natural and social environment. We consider the visualization of the educational process as a means of improving the quality of educational services, forming a holistic perception of the environment that combines logical and visual thinking. According to the purpose of the article, based on the analysis of existing visualization techniques and their expert evaluation, the most effective ones for mastering the content of natural sciences disciplines as well as professional and methodological training of future natural sciences teachers have been identified and substantiated. The significance of visualization techniques for the educational environment has been determined by the method of expert evaluation according to the criterion of «didactic quality». Its indicators are: the possibility to use information educational environment of the higher education institution on the base of existing material and technical support; importance for creating a positive emotional background for teaching; importance for organizing interactive pedagogical interaction of participants in the educational process; accessibility for perception of educational information; expediency of use in the future natural sciences teachers professional training; easy to use both for teachers and students. The five most effective visualization techniques for ensuring a holistic perception of knowledge by combining logical and imaginative thinking (scribing, mind map, infographics, timeline, tag cloud) have been identified by ranking. The effectiveness of the scribing technique and its influence on the formation of indicators of the fully assimilated knowledge quality such as depth and awareness has been experimentally proved.
SIMULАTIОN АND АNАLYSIS ОF SPIKING NЕURАL MЕMBRАNЕ СОMPUTING MОDЕLS BАSЕD ОN RЕWRITING TIMЕD HYBRID PЕTRI NЕTS WITH АNTI-TОKЕNS

In this pаpеr wе prеsеnt thе rеwriting timеd hybrid Pеtri nеts (RTHPNs) еnhаnсhеd with pоsitivе аnd nеgаtivе plасе саpасity, guаrd funсtiоns fоr trаnsitiоns аnd rеwriting rulеs, mаrking-dеpеndеnt саrdinаlity rеvеrsiblе аrсs аnd аnti-tоkеns. Thе RTHPN mоdеl аllоws its struсturе аnd/оr аttributеs tо сhаngе аt run-timе dеpеnding оn its сurrеnt stаtе аnd/оr thе оссurrеnсе оf sоmе еvеnts. Аlsо, wе dеsсribе аn аpprоасh tо simulаtiоn аnd fоrmаl vеrifiсаtiоn bеhаviоur prоpеrtiеs оf spiking nеurаl mеmbrаnе соmputing (SNMС) mоdеls using pаrtiсulаr RTHPNs thаt is suppоrtеd by upgrаdеd VPNP Tооl. Thе usе оf RTHPNs in simulаtiоn аnd аnаlysis оf аn еxtеndеd SNMС mоdеl is illustrаtеd thrоugh еxаmplеs prоving thаt suсh аpprоасh prеsеrvеs fаithfully its bеhаviоurs.
Implementation of Random Search Algorithm with FSSRS (Fixed Step Size Random Search) for Applicating the Patrol System Based on Mobile Computing

Environmental security is very influential for the sustainability of human life. In order for environmental security to remain in a safe condition, a system is needed that can control the environment, such as patrolling at every point to ensure that the environmental conditions are safe. However, it is felt that this is not enough if the patrol system is not assisted by tools or systems that are digitalized and integrated with community service officers, such as firefighters, ambulances, and police, and are easy for officers to use when conducting patrols. So, it is necessary to schedule patrols to several points with different routes for each activity so that it is not easily read by unwanted parties in terms of crime. In order for the system to obtain patrol scheduling in a timely and efficient manner, an appropriate and efficient algorithm is needed, the algorithm is random search with FSSRS (Fixed Step Size Random Search) which can suggest random and precise patrol scheduling. From the results of training using four iterations, namely 50, 100, 150, and 200, the best value was produced in the 200th iteration. Data was taken from the results of a case study survey with eight patrol points using coordinates at each point. So, it can be concluded that the FSSRS algorithm is effectively used to randomize patrol points and can be implemented in the application patrol system.
PASS: Exploiting Post-Activation Sparsity in Streaming Architectures for CNN Acceleration

With the ever-growing popularity of Artificial Intelligence, there is an increasing demand for more performant and efficient underlying hardware. Convolutional Neural Networks (CNN) are a workload of particular importance, which achieve high accuracy in computer vision applications. Inside CNNs, a significant number of the post-activation values are zero, resulting in many redundant computations. Recent works have explored this post-activation sparsity on instruction-based CNN accelerators but not on streaming CNN accelerators, despite the fact that streaming architectures are considered the leading design methodology in terms of performance. In this paper, we highlight the challenges associated with exploiting post-activation sparsity for performance gains in streaming CNN accelerators, and demonstrate our approach to address them. Using a set of modern CNN benchmarks, our streaming sparse accelerators achieve 1.41 x to 1.93 x efficiency (GOP/sDSP) compared to state-of-the-art instruction-based sparse accelerators.
Unlocking the Secrets of Gesture-based Communication: A Feature Extraction Technique for Accurate Recognition of Human Activities in Socially Assistive Scenarios

Gesture-based communication is a crucial aspect of assistive technology, especially for the elderly and disabled who intend to communicate some source of information. The ability to accurately detect and recognize human activities is important for an assistive task. This work aims at the need for feature extraction to accurately predict human activities in socially assistive scenarios. A total of 20 classes of day-to-day human activities were recognized using Mediapipe as well as OpenPose and simultaneously compared to collect key points from the dataset. Spatio-temporal feature extraction was performed, recovering the missing key points that were originally undetected by the human pose estimation model. In order to classify the activities a Long Short-Term Memory (LSTM) based classifier is utilized to classify the sequential information of an activity. An accuracy score of 58% was obtained on experimental validation which indicates the essence of the feature extraction technique in presence of undetected key points in skeletal-based human pose estimation.
Comparing Psychophysiological Responses to Vicarious Pain Experience Elicited by Videos Featuring either Humans or Avatars

The present study adds to the ongoing debate surrounding emotional responses to vicarious pain experienced towards humans and avatars. Empirical data on this topic has yielded controversial results: some studies report the same emotional responses towards humans and avatars experiencing pain, while others suggest different reactions. Our research strengthens the case for similarity. We investigated heart rate variability (HRV) and electrodermal activity (EDA)—physiological markers of emotion—in 23 adults from Estonia as they viewed videos depicting vicarious pain featuring either humans or avatars. We found no significant differences in HRV and EDA responses between the two conditions. These outcomes hint at the potential for avatars to mirror human-like responses, offering crucial insights for the broader use and design of avatars in various applications.
Two Theories of Predictive Cognition

Nowadays, representations are all the more often conceived as probability distri­butions. Although many authors continue to adhere to “conceptual” and “proposi­tional” idioms, meanwhile, there are cognitive theories that can explain the tran­scend of mental operations beyond the narrow framework of associations and reflexive learning to conceptual cognition. The article discusses two concepts based on the understanding of cognitions as probabilistic predictions: the theory of pre­dictive processing (PP) and the theory of functional systems (FS). The PP-theory relies heavily on the concepts of computation and representation. However, repre­sentations are considered here as sub-symbolic, and, accordingly, computations are understood as probabilistic (Bayesian) inference. The FS-theory believes that a cognitive system anticipates parameters of the expected result and strives to maintain a certain level of metabolism, as well as to minimize the degrees of freedom of the system. As it is shown, we don’t have sufficient reasons to con­sider both theories equivalent. They are located at different levels of the Marr’s scheme, use different mathematics, and, probably, are not equally falsifiable. Based on these considerations, it can be assumed that the explanations and pre­dictions of these two theories will differ.
The Problem of Time in the Works of P.P. Gaidenko

The question of time can be attributed as one of the most important in the works of P.P. Gaidenko. Almost from the very beginning of her philosophical activity it was constantly in the center of her attention. The article briefly traces the main milestones in her consideration of the problem of time – from a dissertation on the philosophy of Heidegger (1963) to a generalizing book “Time. Duration. Eternity. The Problem of Time in European Philosophy and Science” (2006), which sums up many years of Piama Pavlovna’s research on this topic. Here the names of three great Greek thinkers – Plato, Aristotle and Plotinus – appear as symbols of various approaches to understanding time. For a long time, it de­termined the lines of further theoretical research. In the book the internal seman­tic echoes that permeate the entire text are very important. Piama P. Gaidenko shows how some models of the interpretation of time, proposed in Antiquity and then in medieval philosophy, are reproduced in various forms in subsequent eras and testify to the complex interaction of philosophical traditions as well as to a change in ways of thinking. The main lines of research outlined in the book clearly show both continuity and differences in approaches to the philosophical understanding of time in different periods. The book expresses not only the phi­losophical, but also the personal position of Piama P. Gaidenko, which was clearly manifested in the interpretation of the question of the relationship be­tween time and eternity. In this sense, of particular interest is the critique of the characteristic tendency of the philosophy of process, which is reflected in the denial of eternity or understanding it simply as infinite time.
Pneumonia Classification Based on GLCM Features Extraction using K-Nearest Neighbor

&lt;p class="Abstract"&gt;Pneumonia has been detected using Machine learning. The stages in this study began with preprocessing in 4 stages: resizing, cropping, filtering using a high pass filter, and Adaptive Histogram Equalization. The feature extraction process continued with 22 Gray Level Co-occurrence Matrix (GLCM) features and classification using K-Nearest Neighbor (KNN). The image used was 150 data sets for training on the classification of 3 classes with a ratio of 50:50:50 while training on two classes was 50 bacterial pneumonia and 50 viral pneumonia. The most optimal training data accuracy results were obtained using the angle direction on the GLCM, namely 135o with the KNN classification (k = 3). For the classification of two classes Using 40 data sets, an accuracy of 91% was obtained, while testing for three classes with 60 data sets was 83.3%.&lt;/p&gt;
The Segmented Storage System in Digital Oscilloscope

High-speed acquisition systems have improved the analysis of the acquired signals in digital oscilloscopes, but how to efficiently store, process and display the very large sample sequences? It has become an urgent challenge. In this paper, a new segmented storage system and processing architecture is designed. This system sequentially captures and stores the time domain waveforms near the trigger point, significantly increases the trigger rate and waveform capture rate; and transmitting a fixed amount of data in 3D pictures after 3D mapping processing in FPGA to improve data transmission efficiency. In the verification based on 1Gpts/ch storage resources, the maximum waveform capture rate is increased to 7 100 000wfm/s, and the system dead time ratio is 43.86%.
Open science for all: Implementing the UNESCO Recommendation on Open Science for an equitable and just transition to open science

Open science is a growing movement toward making science a global public good. Open practices are emerging as a way of transitioning rapidly to more accessible, transparent, and inclusive science to ensure that it also serves the broader society. In recognition of the transformative potential of open science to reduce existing inequalities in science, technology, and innovation, countries worked together within the United Nations Educational, Scientific and Cultural Organization (UNESCO) to map out a path to open scholarship. The 2021 UNESCO Recommendation on Open Science provides an international normative instrument that can direct shared progress toward more open and equitable scholarly systems, grounded in shared values and principles. As countries begin implementing the Recommendation, librarians and information professionals have a key role to play in creating solutions and strengthening processes for open scholarship.
Improving Adversarial Robustness Against Universal Patch Attacks Through Feature Norm Suppressing

Universal adversarial patch attacks, which are readily implemented, have been validated to be able to fool real-world deep convolutional neural networks (CNNs), posing a serious threat to practical computer vision systems based on CNNs. Unfortunately, current defending approaches are severely understudied facing the following problems. Patch detection-based methods suffer from dramatic performance drops against white-box or adaptive attacks since they rely heavily on empirical clues. Methods based on adversarial training or certified defense are difficult to be scaled up to large-scale datasets or complex practical networks due to prohibitively high computational overhead or over strong assumptions on the network structure. In this article, we focus on two cases of widely adopted universal adversarial patch attacks, namely the universal targeted attack on image classifiers and the universal vanishing attack on object detectors. We find that, for popular CNNs, the attacking success of the adversarial patch relies on feature vectors centered at the patch location with large norm in classifiers and large channel-aware norm (CA-Norm) in detectors, and further present a mathematical explanation for this phenomenon. Based on this, we propose a simple but effective defending method using the feature norm suppressing (FNS) layer, which can renormalize the feature norm by nonincreasing functions. As a differentiable module, FNS can be adaptively inserted in various CNN architectures to achieve multistage suppression of the generation of large norm feature vectors. Moreover, FNS is efficient with no trainable parameters and very low computational overhead. We evaluate our proposed defending method across multiple CNN architectures and datasets against the strong adaptive white-box attacks in both visual classification and detection tasks. In both tasks, FNS significantly outperforms previous defending methods on adversarial robustness with a relatively low influence on the performance of benign images. Code is available at https://github.com/jschenthu/FNS.
Securing Dual-Channel Audio Communication With a Two-Dimensional Infinite Collapse and Logistic Map

To provide robust security measures for audio data during transmission, this paper has developed a novel dual-channel audio encryption scheme based on chaos theory. Specifically, a new 2D chaotic system called two-dimensional Infinite Collapse with Logistic Map (2D-ICLM) is designed in this paper. Compared to traditional 2D chaotic systems, the 2D-ICLM exhibits a larger parameter space, complexity, and richness, along with high unpredictability and randomness. These characteristics provide potential advantages and applications in the field of encryption. In the proposed encryption scheme, audio information serves as input to a hash function, which generates the initial values and parameters for the 2D-ICLM, producing the keystream for the cryptographic system. Considering the correlation between the two channels of audio information, the information from the left and right channels is fused to create a new audio signal for encryption. Scrambling and diffusion processes are performed synchronously in the encryption algorithm, with the ciphertext information from the left channel utilized in the encryption of the right channel audio. The experimental results prove the effectiveness of the suggested audio encryption technique, effectively countering various conventional attack methods and showcasing its robust security features. The correlation of adjacent elements of ciphertext audio is 0.0013, the NSCR and UACI is around 0.9960 and 0.3345, and the efficiency is 0.0003s/KB.
Exploring the Effectiveness of Teachers' Blogs as Self-Supervision

Recently, as non-face-to-face classes have been activated due to the influence of COVID-19, teachers' SNS-based activities such as blogs and YouTube have become very active. Teachers produce and share various materials in the online space, such as their educational activities, administrative works, and philosophy about education. Noting that these activities will contribute to the improvement of teachers' expertise, the researcher tried to clarify through examples how blogs operated by teachers enhance teachers' expertise from the perspective of supervision. In this study, through interviews with five teachers operating blogs on educational activities, it was confirmed that teacher blogs have some function as a portfolio that records teachers' career, and are gaining the effect of self-supervision of developing expertise on their own. By analyzing related literature and synthesizing interview results, the functions of teacher blogs are classified into record preservation, self-reflection, and data sharing, and reinterpreted from the perspective of self-supervision. In conclusion, teacher blogs should be recognized as a category of self-supervision because they contribute to enhancing teachers' professionalism, and schools and offices of education suggested that teachers should work on ways to further develop their supervision culture.
The Implementation of Mobile Technology in The Process of Reporting Disasters and Events

Telecommunications have an important role in facilitating communication and information exchange, especially in emergency situations such as natural disasters and unexpected community events. Implementing mobile technology is a promising solution to improve the response and handling of in-kind problems. Mobile technology allows the public to quickly report incidents of disaster or security issues through applications or short message services. The implementation of mobile technology facilitates real-time communication between the community and Babinsa. The public can send reports quickly, convey important information, and share photos or videos as evidence of events. Babinsa, on the other hand, can respond more efficiently to these reports and take necessary actions based on the information received. Apart from that, mobile technology also supports two-way communication between Babinsa and the community. The public can also get the latest information about emergencies, efforts handling, or evacuation via app or direct message notification. Thus, the implementation of mobile technology can make a significant contribution to improving communication, response, and handling of disasters and community events.
Barbara Strozzi e Ferrante Pallavicino: il punto su una (non) storia d’amore

The current biography of Ferrante Pallavicino mentions his unhappy falling in love with Barbara Strozzi, daughter of Giulio Strozzi, the founder of the Accademia degli Unisoni. Evidence of this falling in love is said to be a letter that Ferrante dedicated to a certain Barbara B., a woman who rejected a lover's offers of love. This contribution demonstrates, through the words of Pallavicino himself, that the letter is part of a collection of exemplary letters written in accordance with certain situations, and that the dedicatee of the letter to Barbara B. is not Strozzi.