Reviewerly/exHarmony huggingface dataset:
Tile-Based Wireless Streaming of 360-Degree Video With Rate Adaptation Using Viewport Estimation

This paper presents tile-based wireless streaming of 360-degree videos with rate adaptation using viewport estimation. We propose a probabilistic model for viewport location to design importance weights of tiles. Based on the tile weights, we improve the streaming performance by dynamically adjusting quantization parameters and forward error correction rates across tiles.
CHANGES IN THE FEDERAL STATE STANDARDS OF GENERAL EDUCATION IN THE LIGHT OF THE THEORY OF DEVELOPING EDUCATION

This research discusses the possible risks associated with the possible discrediting of the activity-based approach to learning, due to the specification of the requirements for subject results for each academic subject, implemented in the new Federal State Educational Standard, with the uncertainty of the “system-activity approach” concept content. Recognizing the timeliness and the need to specify the requirements for substantive results for each academic subject, the authors note that this innovation in the methodological plan revives the illusion of the possibility of returning to Zunov’s approach (the formation theory for a certain set of knowledge, skills and abilities), which is detrimental to the modern school. In this regard, it is important for teachers to decide on the methodological basis of pedagogical activity that corresponds to the target idea of the latest standards. The article examines the reasons that require a return to the methodological foundations of the activity approach in the light of V.V. Davidov’s theory of developing education, an essential understanding of this phenomenon is offered. The main reasons include 1) the need to form, develop and improve the student’s mechanism of goal-setting; 2) the need to derive the content of the concepts being mastered in educational activities by the students themselves; 3) the development expediency of meta-subject educational within the framework of the particular academic subject assimilation; 4) proven implementation effectiveness of the task method in teaching; 5) the expediency of a radical transition to a dialogic form of education in the jointly distributed students’and teachers’activities.
SELF-DETERMINATION AS A STARTING POINT IN THE DESIGN OF INTRA-SCHOOL CHANGES

The study deals with the issues of the development of an educational organization in combination with the development of the individualities of the subjects of educational activity. There are conditions conducive to the most effective implementation of this activity. The project approach contributes to the harmonization of the interests and aspirations of the individual, directing them to the needs of the development of the team. Such long-term projects are being implemented on the basis of the supporting educational institution of Lyceum No. 590 in St. Petersburg. For members of the teaching staff, it is necessary to create conditions conducive to their professional and personal self-determination.
Klasifikasi Sekolah dalam Penerimaan Mahasiswa Baru Vokasi IPB Jalur USMI Menggunakan Metode CART

The selection of new student admissions for the IPB vocational school consists of several routes, one of which is the USMI route. In order to improve its performance, it is necessary to evaluate the USMI new student admission system. Previously, research with the same objective had been carried out using the clustering method. The study resulted in three clusters in which schools were differentiated based on commitment and quality. This study aims to create a classification model of the clusters obtained using the CART method. Classification and Regression Tree (CART) is a nonparametric classification technique that produces a single decision tree. The CART method can involve mixed-type data. The classification model generated from the 2019 data yields an accuracy of 98.52%. However, the results of 2019 model evaluation with the 2020 data are still not good enough to predict with an accuracy of 57.22%, so the 2020 data is re-clustered and produces three clusters. Furthermore, the classification model was remade with 2020 data, resulting in an accuracy of 97.47%. However, the results of the 2020 model evaluation with the 2021 data are still not good enough to predict with an accuracy of 44.34%, so the clustering in the previous year cannot be used for predictions of the following year's data. The grouping of schools for USMI applicants needs to be done by grouping schools every year.
Artistic education and evaluation in the nonformal educational system of the Republic of Moldova

In the Republic of Moldova, music and arts education takes place both in general education (primary and secondary) and in nonformal arts education. In the perimeter of this article, we aim to address the aspects of evaluating individual and group artistic activities, evaluating student performance, elements and stages of the evaluation process, steps that can improve evaluation activities.
Teachers’ perceptions of key competencies:the results of an opinion poll

The article shows the results of an on-line opinion survey on teachers of different specialties who work both in rural and urban areas, and brings into light their generally positive perception regarding the necessity of re-orientating education towards shaping key-competences during teaching. The purpose of the survey was to measure the teachers’ perceptions and attitudes with a view to making use of a wide range of different aspects related to this issue that is going to happen in the educational process.
Construction of some new quantum codes

In this paper, we consider <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R=\mathbb{F}_{q}[u, v]/ &lt; u^{2}-u, v^{2}-v, uv - vu &gt;$</tex> which is a finite non-chain ring, where <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$q$</tex> is an odd prime power and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$u^{2}=u, v^{2}=v, uv=vu$</tex> . We construct new quantum codes from <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\alpha+\beta u+\gamma v+\delta uv)$</tex> - constacyclic codes over <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R$</tex> . We give the structure of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\alpha+\beta u+\gamma v+\delta uv)$</tex> - constacyclic codes over <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R$</tex> and obtain self-orthogonal codes over <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbb{F}_{q}$</tex> by Gray map.
Incremental deep learning training approach for lesion detection and classification in mammograms

Recently, Deep Convolutional Neural Networks (DCNNs) have opened their ways into various medical image processing practices such as Computer-Aided Diagnosis (CAD) systems. Despite significant developments in CAD systems based on deep models, designing an efficient model, as well as a training strategy to cope with the shortage of medical images have yet to be addressed. To address current challenges, this paper presents a model including a hybrid DCNN, which takes advantage of various feature maps of different deep models and an incremental training algorithm. Also, a weighting Test Time Augmentation strategy is presented. Besides, the proposed work develops the Mask-RCNN to not only detect mass and calcification in mammography images, but also to classify normal images. Moreover, this work aims to benefit from a radiology specialist to compare with the performance of the proposed method. Illustrating the region of interest to explain how the model makes decisions is the other aim of the study to cover existing challenges among the stateof-the-art research works. The wide range of conducted quantitative and qualitative experiments suggest that the proposed method can classify breast X-ray images of the INbreast dataset to normal, mass, and calcification.
Theoretical basis of the development of the communicative competence of a teacher in an institution of higher education

The article analyzes the current state of research on the problem of communicative competence of the lexicographer in the scientific literature, and on this basis, the initial theoretical foundations of the research are formulated; based on a theoretical analysis of the essence, content and main characteristics of communicative competence, the main methods, techniques, tools and technologies necessary for the formation of a teacher's communicative competence were clarified; Pedagogical conditions are defined, which ensure the effectiveness of the development of communicative competence of future teachers in the process of self-control and self-improvement; the psychological conditions for the development of the future teacher's communicative competence in the process of self-control and self-improvement were investigated.
Quantum steering and its applications in quantum information

The concept of quantum steering was originally introduced by Schrödinger to describe the "spooky action-at-a-distance" effect noted in the Einstein-Podolsky-Rosen (EPR) paradox, whereby local measurements performed on one party apparently adjust (steer) the state of another distant party. In this talk, I will give an introduction about the advances of the EPR steering and its advantage as quantum resource. Then I will present our efforts on characterizing bipartite and multipartite steering and developing its unique applications in quantum information processing. I will give an overview of our recent developments on quantum steering and its applications in quantum information. I will share our view about the current challenges, opportunities and the future directions for this topic.
Preface: The 3rd International Conference on Science Education (ICoSEd)

First Page
All-optical modulation based on the phase-change materials combined with chains of silicon nanoantennas

Chalcogenide phase-change materials are showing promise for the development of non-volatile memory and neuro-inspired computing technologies. One of the key issues in these devices is the energy consumption for the write (crystallization) and erase (amorphization) process. In this work, we propose to combine a PCM with a subwavelength chain of silicon nanoantennas with variable sizes following a parabolic profile. In comparison with a common slab waveguide, it was numerically demonstrated that the nanoparticle chain requires 24 times less energy for the writing and 42 times less energy for erasing process due to slow- light behavior near the photonic band-gap edge, which enhances local electromagnetic fields in the structure. Achieved results could be used for neuromorphic silicon photonics applications.
Block-Streaming Service Loading Optimization of Android Dalvik Executable File for Cloud-End Collaboration

In recent years, dynamic loading technologies of Android applications have emerged in an endless stream. At present, the existing Android application loading method is to load the entire Android Dalvik Executable (DEX) file for cloud-end collaboration, and there is a problem of finer-grained loading optimization in the loading process. Based on the analysis of Android DEX file in this paper, a formal model of each class is established by using the analysis result of this file, analyzes the user's behavior, and tries to ensure that the class to be used in high probability is loaded into memory first, and a block-streaming service loading optimization model of Android DEX file is put forward. The validity of the model is verified by quantitative analysis of Android DEX file. Trying to load the whole Dalvik Executable file and the classes needed by the application separately, recording and comparing the storage space and loading time overhead. In order to avoid the uncertain factors of the network environment, the above files have been tested and recorded several times. The result shows that the time and storage space for loading the whole DEX file are far greater than the sum of the classes required by the application. With this model, the fine-grained formal analysis of Android DEX file can be performed, which is of great significance for exploring the loading method of application block flow service.
Non-linear Filters to Aid Detection of Glioblastoma in CT and MRI Brain Images

Noise is an unavoidable source of distortion in CT and MRI images, caused by a variety of factors such as imaging machine limitations, poor image resolution, patient condition, and inexperienced imaging professionals. The poor visual quality of acquired images leads to incorrect tumour detection, leading in differential diagnosis. As a result, denoising is a required computer-aided process after image acquisition to reduce noise while retaining significant information. Non-linear Filters are well-known tools for reducing noise in images while preserving structural information. A detailed examination of non-linear filters is conducted, with an emphasis on the selection of filter parameters with varying noise variance and their impact on image quality. The experiment is carried out on over 100 CT and MRI images containing Glioblastoma. The Non-Local Means filter is effective for both CT and MRI images, which are later on fused to enhance the detection. PSNR of 45dB and 38dB are obtained for CT and MRI images, respectively. The filter achieves an SSIM of 0.99 for images corrupted by Gaussian noise and Rician noise of varying noise variance.
RNG Entropy Enrichment to Improve Cybersecurity in IoT and Cloud Services

Compliance with cybersecurity demands is a necessity for the harmlessness and certainty of IoT devices and applications, infrastructures, and the protection of confidential data. The quality of cryptographic security in cloud services is key to IoT security. A variety of vital IoT applications rely on random numbers. The random number generators (RNG) used in many IoT devices have a serious fundamental weakness that challenges the security of the encryption keys they generate for communications. In this regard, the topics of cryptography and sufficiently robust random number creation, which are the basis of any encryption system, are of particular interest. This study seeks to answer a question which has been worrying many researchers long ago, namely how predictable and vulnerable an RNG is in a computer system that provides IoT cloud services. The quality of an array of random numbers was investigated by simulations. The consideration of the presented results concludes that due to the inefficiency in the random numbers and the established breaking of cryptographic defense, the IoT-based cloud service can happen to be a victim of various types of hacker attacks. The ways to improve the quality of the generator, both software and hardware, are indicated.
Automatic Modulation Recognition using Convolutional Neural Networks

Automatic modulation classification (AMC), an intermediate step between signal detection and modulation, is an active research area in wireless communication. AMC methodologies utilize the time varying temporal characteristics of complexed in-phase (I) and quadrature (Q) signal to identify the modulation type correctly and automatically. In this work, majority voting based convolution neural network (CNN) is used to recognize modulation scheme. To learn inherent properties more accurately and reduce complexity of the neural network, the signal length is reduced from 128 points to 64. In this regard, a sliding widow of length 64 is used to divide each signal into 5 sub-signals. Instantaneous amplitude (a) and phase (θ) are additionally used as input to the network. Finally, modulation scheme of the signal is decided based on majority voting and is calculated by argument maximum of sub-signal mean. Experiments show that majority voting increases the classification accuracy on publicly available dataset.
Kesiapan Pustakawan Berkolaborasi dengan Profesi Lainnya Mendukung Peningkatan Kapasitas dan Kesejahteraan Masyarakat Pertanian

Indonesian Center for Agricultural Library and Technology Dissemination is known as PUSTAKA has made a breakthrough by providing social inclusion services. The inclusion activity is carried out through collaboration between librarians and other professions. This study aims to determine the readiness of librarians to collaborate with other professions, the barriers to collaboration, and the abilities that librarians must possess to collaborate. The method in this study is a qualitative approach with a case study method. The subject of this study is the librarian at PUSTAKA. We found that: 1) librarians had collaborated with extension workers and felt the benefits of this collaboration; 2) obstacles faced are misscommunication, lack of capital, limited land, and lack of time. These obstacles can be overcome by proper communication and cooperation with other related parties. The collaboration between librarians and other profession is relevant to the dissemination of agricultural innovations. The librarian's skills related to cooperation include communication skills, problem solving skills, adaptability, and emotional intelligence. Based on the results of the study, it can be concluded that librarians and library managers are ready to collaborate with other professions. In future studies, it is necessary to review the librarian within the Ministry of Agriculture along with the models of cooperation that have been implemented.
STUDY OF THE PROBLEM OF PERSONALITY SELF-DEVELOPMENT ON THE PATH TO “LIVING” KNOWLEDGE

The defining positions of social transformations are currently innovations related to the intellectualization and informatization of public space. Today, there is a necessary need in society for people who have professional and significant qualities, intellectual abilities, and what is equally important is the readiness to carry out life in conditions of instability, dynamism, nonlinearity and uncertainty. The actual task of the pedagogical community in this regard is not only to convey to the students the necessary minimum of ready (formal) knowledge, but also to form the ability to transform the initial (formalized) cognitive structure into a new, personally significant, “living” typology of knowledge. “Living” knowledge in the study is defined as personal knowledge, extremely reliable, effective, design-life, professionally significant, cognitive-creative, capable of generating new information, new ideas, new knowledge. It has been established that the general scientific metaphor of “living” knowledge meets the tendency of the self-development of the individual and is due to the socio-cultural realities of the emerging “society of knowledge.” The phenomenon of “living” knowledge is inextricably linked with the cognitive structures of the personality, it is a characteristic feature of the cognitive, personal attitude to the activities of transforming the world and itself.
Be Creative - Secure the Future

In the 21st century, it is essential to develop new learning approaches and innovative learning materials that enable students to acquire competencies for living and working in an environment of the Fourth Industrial Revolution. Critical and algorithmic thinking, creative problem solving, teamwork, and social communication must be developed systematically. Learning methods that were acceptable to students in the last century are nowadays largely inadequate because they are based on memorizing and reproducing facts, already widely available on the Internet. Modern research into how the human brain works indicates that learning through play, projects, research, experience, etc., is far more in tune with how the human brain works. In short, every student must acquire comprehensive life competencies during their education, i.e., they must develop the ability to actively participate in society, manage their own lives and careers and start value-adding initiatives.
Advanced Neural Networks

In this chapter, we will look at some of the advanced concepts and models in deep learning. Image segmentation and object localization and detection are some of the key areas that have garnered a lot of importance lately. Image segmentation plays a crucial role in detecting diseases and abnormalities through the processing of medical images. At the same time, it is equally crucial in industries such as aviation, manufacturing, and other domains to detect anomalies such as cracks or other unwanted conditions in machinery. Alternately, images of the night sky can be segmented to detect previously unknown galaxies, stars, and planets. Object detection and localization has profound use in places requiring constant automated monitoring of activities, such as in shopping malls, local stores, industrial plants, and so on. Also, it can be used to count objects and people in an area of interest and estimate various densities, such as traffic conditions at various signals. We will begin this chapter by going through a few of the traditional methods of image segmentation so that we can appreciate how neural networks are different from their traditional counterparts. Then, we will look at object-detection and localization techniques, followed by generative adversarial networks, which have gained lot of popularity recently because of their use and potential as a generative model to create synthetic data. This synthetic data can be used for training and inference in case there is not much data available or the data is expensive to procure. Alternatively, generative models can be used for style transfer from one domain to another.
Technologies for developing inclusive readiness of families based on a competent approach

In this article, based on a competent approach, various interactive methods for the development of inclusive readiness of families, determinants of methodological support of the process of formation of inclusive readiness of pedagogues are given.
Organization and innovative management of the processes of preparing students of the preschool educational direction for professional and creative activities

The educator of the XXI century must possess pedagogical skills, a keen mind, pedagogical psychological knowledge, deep knowledge of his work and high thinking, political literacy, a wide range of flash, and thoughtfulness due to the current state of the world, the development of technology, and the ICT in science day by day. Teachers who work in preschool educational institutions should be well-versed in the best ways to organize educational materials, the theory of unstable personalities, and the enrichment of existing knowledge with new concepts. This article offers input on how preschool education is organized and how innovative management is used to get pupils ready for work-related and creative activities.
Preparing future teachers for the formation of chemical technological concepts in students scientific methodological foundations

Modernization of higher educational institutions and the educational process within them, improvement of the system for training pedagogical specialists’ quality and oversight, equipping future educators with cutting-edge professional knowledge, skills, and abilities, and the development of ac'meological motivation in relation to professional activity within them are all seen as crucial steps in the process of developing such training. Input is offered, as well as feedback on the scientific methodological underpinnings of preparing future teachers to help pupils develop chemical technology concepts.