Reviewerly/exHarmony huggingface dataset:
Effect of The Volume of Banana Fiber As A Polymer Composite Amplifier With Polyester Resin Matrix On The Sound Absorption of Acoustic Materials

Research has been carried out on the banana fiber effect as a polymer composite amplifier with polyester resin matrix on the sound absorption of acoustic materials. Sound Absorber material is made with a variation in the volume of banana fiber that is different from polyester resin. The volume of banana fiber and polyester resin used is 15% Fiber: 85% Polyester Resin, 20% Fiber: 80% Polyester Resin, 25% Fiber: 25% Fiber: 75% Resin Polyester, 30% Fiber: 70% Polyester Resin, 35% Fiber: 65% Polyester Resin. So when made composite then the amount of banana fiber used and polyester resin is 100%. Research methods are carried out in the collection of banana fiber, composite manufacturing and testing of sound absorption properties using impedance tubes. The testing of coefficient sound reflection and also sound absorbance coefficient testing is done using sound level meter and signal generator by reference to principle the method of tube impedance via approach to the acoustic box. The banana fiber composite result and polyester resin are able to reflect the sound of highest which is 0.44 in a frequency 500 Hz with fiber 15%. While lowest sound reflection coefficient is 0.06 at a frequency of 8000 Hz and fiber 35%. While in the test the highest value absorbance coefficient that absorbs sound is = 0.94 at fiber volume 35%, and frequency 8000 Hz, while the lowest sound coefficient is 0.56 in fiber 15% and frequency 500 HZ
R-UNet++: A Local Segmentation Network for the Classification of Oracle Bone Materials

The rejoining of oracle bone (OB) fragments with the same material is a significant topic in the field of oracle bone inscriptions research. Facing to the challenges of OB materials classification, a classification framework based on R-UNet++ is proposed. R-UNet++ draws on the dense convolution block link in UNet++, and on this basis introduces the improved strategies by attention module, bilinear upsampling method and residual unit, which effectively inhibits the noise response generated by multi-scale feature fusion and enhances the fine- grained segmentation capability in final. In this classification framework, first, R-UNet++ is able to accurately divide the difference information between classes. Then, ResNet50 is adopted to further extract features from images segmented by R-UNet++ and completes the OB materials classification task. With the real OB dataset, segmentation and classification experimental results show that R-UNet++ has strong ability to accomplish the exact segmentation task. Compared with other state-of-the-art classification networks, the classification accuracy has a higher improvement, which fully verifies the feasibility and efficiency of proposed classification framework.
SOCIAL INTELLIGENCE AND ACADEMIC PERFORMANCE OF STUDENTS

The article discusses the relationship between academic performance of students and the level of development of social intelligence. Based on theoretical and practical developments of Russian and foreign scientists, the notion of social intelligence and its structure is investigated. The results of an empirical study of the relationship between intersessional academic performance and the development of social intelligence are presented.
Teeth attention mechanism image classification based on lightweight network

In order to solve the problem that embedding attention mechanism module into lightweight convolutional neural network will increase the number of parameters and FLOPs with less accuracy improvement, a Teeth Attention Module (TAM) based on lightweight network was proposed. The feature map is enhanced from two aspects of channel attention and spatial attention. In the channel attention module, local channel interaction is carried out from height and width without dimensionality reduction through one-dimensional convolution, and it is divided into MP-ECAM and AP-ECAM according to pooling mode. In the spatial attention module, the average value and maximum value of each pixel point in the feature map are calculated according to the dimensions to construct ESAM. Finally, TAM is constructed in a channel-space-channel manner. TAM was embedded into the lightweight networks MobileNetV2, ShuffleNetV2 and EfficientNetV1 respectively, and the experiment was carried out on CIFAR-10 image classification datasets. Compared with Squeeze and Excitation Module (SE), Convolutional Block Attention Module (CBAM) and Efficient Channel Attention Module (ECA), this module can achieve higher accuracy with less increase of the number of parameters and FLOPs.
Building of the collection of industrial sci-tech library of a new type

The relevancy of the topiс arises from the demands by librarians and organizations’ managers and by transformation of industrial sci-tech libraries. Acquisitions to the collections must meet information needs of the employees. The examples of developments and procedures to acquire printed materials to the collections as well as to select appropriate computerized library systems are provided.
Analytic Velocity Obstacle for Efficient Collision Avoidance

Abstract Velocity obstacle is one of popular reactive navigation algorithms for path planning of autonomous agents. The collision-free property can be guaranteed if the agent is able to choose a velocity outside the velocity obstacle region under the assumption that obstacles maintain a constant velocity within the control cycle time of the agent. To date, selection of the optimal velocity relies on either sampling or optimization approaches. The sampling approach can maintain the same amount of computation cost but may miss feasible solutions under collision risks with insufficient number of samples. The optimization approach such as the linear programming demands for convexity of the constraints in the velocity space which may not be satisfied considering non-holonomic agents. In addition, the algorithm has varying computation demand depending on the navigation situation. This paper proposes an analytic approach for choosing a candidate velocity rather than relying on the sampling or optimization approaches. The analytic approach can significantly reduce computation cost without sacrificing the performance. Agents with both holonomic and non-holonomic constraints are considered to demonstrate the performance and efficiency of the proposed approach. Extensive comparison studies with static, non-reactive, and reactive moving obstacles demonstrate that the analytical velocity obstacle is computationally much more efficient than the optimization based approach and performs better than the sampling based approach1.
Effects of Depth of Field on Focus Using a Virtual Reality Escape Room

Depth of Field (DOF) is an effect that can be found in every single optical camera. Nowadays DOF is a common effect even for virtual cameras and it is used for more realistic rendering. In this work, an Escape Room is constructed and it is equipped with a post-process DOF effect to help the players navigate through the game. The DOF is independent from the player’s vision direction. It is designed to highlight the objects that are important to progress towards the end of the game and not the ones the player is looking at. It is desired to shift the attention of the user subconsciously and make him move more efficiently. If an object becomes important during the game it gets highlighted too and if one is no longer useful the DOF stops focusing on it. Finally, an experiment took place to test if the DOF is making the players navigate more effectively inside the game, and check for possible side effects, like frustration and motion sickness. The analysis results suggest that the DOF can be used as a hint system.
THE STRUCTURE OF PROFESSIONAL COMPETENCE OF A TEACHER

In this article, the professional competence of a teacher is considered as a set of generalized knowledge, skills and abilities that ensure the implementation of the content of state educational standards. The most common skill is the ability to think and act pedagogically, closely related to the ability to subject facts and phenomena to theoretical analysis. Ideally, the full compliance of the teacher with the requirements of the qualification characteristic means the formation of the ability to think and act pedagogically integrating the whole set of pedagogical skills. Regardless of the level of generality of the pedagogical task, the completed cycle of its solution is reduced to the triad "think — act — think" and coincides with the components of pedagogical activity and their corresponding skills. As a result, the model of professional competence of a teacher acts as a unity of his theoretical and practical readiness.
Metropolis Algorithm

General aspects of the Markov Chain Monte Carlo algorithms, which we learned in the previous chapter, may have left you confused. To really understand the subject, we need concrete examples and implementations. In this chapter, we introduce the Metropolis algorithm [1, 2], which is the most famous version of MCMC, and use it to demonstrate how actual simulations are done.
Heterologous Image Registration Based on DartNet53 Deep Neural Network

Heterologous image matching is a popular academic topic in the world. Its commonly used data carriers are infrared and visible light images. Deep learning is machine learning applied to deep neural networks. As a technology emerging in recent years, it has been widely used in speech recognition, image processing and other fields and achieved good results. The main direction of this topic is the detection and matching of heterogeneous images based on deep learning. Different from traditional methods, this subject adopts darknet53, a light-weight and high-speed neural network, so as to achieve the purpose of optimizing the detection and matching effect and prove it through experiments. Today, deep learning and multi-disciplinary cross-matching have become a hot topic among hot topics. The application of low-cost, high-efficiency artificial intelligence networks in multi-scenario environments has become a consensus pursued by the scientific community.
Gender, Firm Performance, and FDI supply-purchase Spillovers in Emerging Markets

The paper measures the gender premium (or penalty) in productivity and innovation of firms in 32 emerging economies. We estimate whether the gender status of firms' ownership in FDI recipient countries matters for the size of knowledge spillovers from linkages between local firms and Multinational Enterprises (MNEs). Furthermore, we explore whether the gender ownership structure of Multinational Enterprises (MNEs) is also vital for spillovers between MNEs and local firms. Our results show that female-owned firms (both local and MNEs) are on average less productive and innovative. Although domestic firms benefit from supplying inputs to MNEs in terms of Total Factor Productivity (TFP) and innovation, a gender handicap cancels out these gains potentially. Female gendered MNEs also impose a similar penalty on knowledge spillovers. As a policy implication, the paper highlights the importance of mitigating gender discrimination for improving productivity and absorptive capacity of local firms in the emerging world.
Further Resources

We’d love it if this book were the only thing you needed to read about web application security. Unfortunately, it is not, and the reason is that things change. New technologies come out, introducing new vulnerabilities. New versions of software are released, with new bugs creating threats. And hackers are always on the lookout for vulnerabilities that haven’t been discovered yet.
Cluster Analysis of Students' Consumption Behavior Based on K-means++ Algorithm

The clustering effect quality of the classical Kmeans algorithm is very sensitive to the initialization of the clustering center. When different initial clustering centers are selected for clustering modeling, the obtained clustering effect is quite different. In order to obtain more stable clustering results, this paper uses the improved distributed K-means + + algorithm based on the K-means algorithm to cluster the consumption behavior of students' behavior data. The students are clustered into three categories, and the characteristics of the three groups of the clustering results are compared and analyzed. The experimental results show that it is feasible to use clustering eigenvalues such as consumption intensity and consumption frequency to assist school funding departments to carry out targeted poverty alleviation work. At the same time, it provides a solution for finding “hidden poor students” and finding “fake poor students”.
A Virtual Reality (VR) Apparel Design Exhibition: Exploring Students’ Experiences During the COVID-19 Pandemic

<span style="font-size:12.0pt;line-height:115%;font-family:&quot;Times New Roman&quot;,serif;mso-fareast-font-family:Calibri;mso-ansi-language:EN-US;mso-fareast-language:EN-US;mso-bidi-language:AR-SA">This study aimed to explore a) students’ experiences of showcasing their apparel design work through a VR design exhibition and b) students’ experiences of viewing a VR design exhibition during the pandemic.&nbsp;</span><span style="font-size:12.0pt;line-height:115%;font-family:&quot;Times New Roman&quot;,serif;mso-fareast-font-family:Calibri;mso-ansi-language:EN-US;mso-fareast-language:EN-US;mso-bidi-language:AR-SA">In this study, both designers’ and viewers’ experiences of a 3D VR design exhibition created using Mozilla Hubs was examined. Through the 3Denvironment, viewers were able to “walk around” a gallery to view apparel designs, posters, and videos and to “interact with each other” in the gallery room (e.g., using the chat function and a personal avatar).&nbsp;</span><span style="font-size:12.0pt;line-height:115%;font-family:&quot;Times New Roman&quot;,serif;mso-fareast-font-family:AdvOT1ef757c0;color:black;mso-ansi-language:EN-US;mso-fareast-language:EN-US;mso-bidi-language:AR-SA">The presentation of this study includes visual examples of a VR apparel design exhibition and effective strategies for disseminating students’ apparel artifacts through a 3D virtual platform.&nbsp;</span>
Leveraging Machine Learning to Predict Volcanic Eruptions by Function Neural Networks

When it comes to volcanic eruption surveillance, techniques that rely on seismic analysis of data tend to use automatic methods that ignore the fact that volcanic formations are varied and flexible. Sophisticated procedures for data categorization and assessment, evaluation, investigation and interpretation are needed to identify small variations in seismic sequences linked with volcanic instability. Machine Learning (ML) and Deep Learning (DL) technologies are continually being devised to better machine extraction and processing of valuable data. The proposed study has employed Radial Basis Function Neural Networks (RBFNN) to predict volcanic eruptions in Indonesia. Further, the proposed RBFNN model is compared with other Neural Network (NN) models and it was observed that RBFNN has outperformed all other models in terms of accuracy.
Partneship is a constant of vitality Ivan Prokopenka`s and Grigory Skovorody`s

The study of the professional work of Ivan Prokopenko and Grigory Skovoroda under the conditions of martial law in Ukraine will contribute to the establishment of partnership in the organization of the educational process, and the improvement of the quality of professional training. The purpose of the article is to reveal the essence and ways of implementing partnership on the example of the life and professional activity of Ivan Prokopenko and Grigory Skovoroda. To achieve the goal, comparative historical methods were used – to reveal the key points of understanding of partnership by teachers. The methods of analysis, synthesis and generalization of historical facts are used to substantiate the ideas of partnership pedagogy. The retrospective method was used for creative interpretation of the results of the conducted research.In the article, the author revealed the idea of partnership based on synergistic and systemic approaches. Cultural relevance and the principle of historicism made it possible to characterize partnership as a dynamic phenomenon that is determined by social factors. The article emphasizes that the idea of "equal to equal" democracy is important in partner interaction, unconditional equality in the right to express one's position, respect for another point of view, trust and goodwill in communication and interaction are recognized. The value of tacit knowledge and experience, mutual demand is also recognized.In the article, the author substantiated that Grigory Skovoroda set an example of socially significant partnership and humanity in the Kharkiv Collegium, private teaching. The main positions of Grigory Skovoroda's pedagogical partnership are highlighted: personal dialogue in forms of educational interaction; friendly conversation, correspondence in extracurricular time to encourage self-discovery, self-immersion, self-analysis; simulation of life situations, choice situations with a projection for success.Value orientations of partnership pedagogy according to Ivan Prokopenko: respect, benevolence, trust, dialogue and distributed leadership. He approved the partnership in all forms of educational, educational, professional and research work at G.S. Skovoroda Kharkiv National Pedagogical University on the basis of the philosophy of the heart, humane pedagogy. The article states that in his activities, Ivan Prokopenko used the principles of trust and openness in professional communications, respect and recognition of the self-worth of each individual. He successfully applied the practice of distributed leadership, in all horizons of connections and activities of the university.Common aspects of the pedagogical partnership of Ivan Prokopenko and Grigory Skovoroda: careful attitude to the student, understanding of the self-worth of a person, cordocentric living of success and failure.As a promising direction for further research, we offer a comparison of the ideas of partnership in the work of Confucius and modern practices of partnership in educational institutions of Ukraine and China.
Non-Facial Video Spatiotemporal Forensic Analysis Using Deep Learning Techniques

Digital content manipulation software is working as a boon for people to edit recorded video or audio content. To prevent the unethical use of such readily available altering tools, digital multimedia forensics is becoming increasingly important. Hence, this study aims to identify whether the video and audio of the given digital content are fake or real. For temporal video forgery detection, the convolutional 3D layers are used to build a model which can identify temporal forgeries with an average accuracy of 85% on the validation dataset. Also, the identification of audio forgery, using a ResNet-34 pre-trained model and the transfer learning approach, has been achieved. The proposed model achieves an accuracy of 99% with 0.3% validation loss on the validation part of the logical access dataset, which is better than earlier models in the range of 90-95% accuracy on the validation set.
Content Features of Local History Resources of Libraries in the South of Ukraine

Due to the comprehensive use of information and communication technologies, there are changes in the information needs of local history content. The current audience’s readership demand encourages the expansion of information support, digitalisation of information, and an increase in local history content in the electronic segment. The aim of the article is to analyse the content of local history resources of libraries in the south of Ukraine and highlight the features of its formation to satisfy the readers’ needs. The research methodology includes the content monitoring of official websites, electronic libraries, and libraries’ weblogs of Mykolaiv, Kherson, and Odesa regions, as well as the review and analytical method of studying the existing theoretical heritage on the research topic. The scientific novelty is to highlight the features of the formation and diversity of content of electronic local history information resources with a focus on satisfying readers’ requests since users of local history documents have recently shown an increased interest in documents on the latest data carriers. Сonclusions define the role of local history electronic resources of libraries in the south of Ukraine in the region’s information space, as well as further prospects for their genesis and development. It is emphasised that one of the priority areas of local history activities of libraries in the formation of regional identity is the joint activity of library institutions with cultural, educational, research, archival institutions, community initiatives, and organisations. It is noted that the intensive development of digital library projects in combination with the study of local history information needs opens up additional ways to implement the tasks of libraries to ensure wide access of users to unique local history content resources and play an extremely important role in the information space of the region. The article offers suggestions for improving the digital content of local history in combination with the study of local history information needs.
Media Educational Technologies in Teaching Schoolchildren and Students in the Age of Digital Transformation

Currently, media education is being actively introduced into Russian schools and universities.The process of media education is presented as an integral system in the context of representation of meaningful constructs.The results of the study allow us to state that in the era of digital transformation, media educational technologies are able to act as an effective tool in the professional activities of a teacher of a general education or higher educational institution.This fact is due to a combination of conditions, among which we have identified the following: intensive development of digital technologies; increasing media exposure to the younger generation; expansion of the area of implementation of media education technologies.As our practical experience has shown, the use of the above technologies of media education in the process of analyzing media texts in a school, student audience will allow not only to comprehensively study media works, but to form one's own point of view about it, develop analytical skills and critical autonomy of the individual, which will help increase the level of media literacy.The authors provide a set of effective media education technologies that are integrated in the education of schoolchildren/students; the results of this integration are presented.
Cryptanalysis of a Code-Based Identification Scheme Presented in CANS 2018

NIST recently published the first four winning algorithms from the post-quantum cryptography (PQC) standardization process that has been ongoing since 2017. The four algorithms selected are a key establishment algorithm called CRYSTALS-Kyber and three digital signature algorithms called CRYSTALS-Dilithium, FALCON, and SPHINCS+. The first two of these signature schemes are based on structured lattices and the last is a hash-based signature scheme. These future standards will be the default options for post-quantum algorithm selection in most security products. To diversify post-quantum signature standards, NIST has issued a call for submissions for signature schemes that have short signatures and fast verification before June 1, 2023. Code-based signatures schemes are promising candidates for this additional process. In this paper, we first show that the rank-based Veron’s identification scheme proposed in [6] in CANS 2018 reveals information in the response step. Second, we perform an attack on the support of the error to find the secret in this scheme. Finally, we propose a secure zero-knowledge identification protocol with rank settings and a code-based signature scheme with fast verification.