Reviewerly/exHarmony huggingface dataset:
Experience of distance learning in modern Russia (philosophical and educational experiments)

This article is devoted to the issue of distance learning for students. This form of education has become common in Russia in conditions of high risk of the coronavirus infection COVID-19. However, there are concerns that distance learning will become a regular norm. Meanwhile, the consequences of this may be negative, since education and promotion of students’ moral growth will become essentially impossible. The entire education system will be reduced to informing students about certain disciplines. Thus, distance learning should not take the form of a daily norm in the education system. English version of the article is available at URL: https://panor.ru/articles/experience-of-distance-learning-in-modern-russia-philosophical-and-educational-experiments/70447.html
Few-shot deep model of waste classification based on model agnostic meta-learning

Waste classification based on deep neural networks is up against the dataset deficiency. However, that is too expensive and time-consuming for collecting and labeling waste samples. We proposed an improved ResNet-18 model based on Model Agnostic Meta-Learning (MAML) to improve classification accuracy with a few-shot waste classification dataset. the feature extraction part of the improved model includes a convolution layer and four residual blocks; the classification part of the improved model includes a max-pooling layer and three fully connected layers. Moreover, GroupNorm is adopted to reduce the impact of different feature distributions normalization on the classification accuracy. With initial parameters from the MAML training on the Mini-ImageNet dataset, the model improve accuracy only with one training iteration results on few waste samples. The experiments verified the effectiveness of our model on the Mini-ImageNet dataset and a few-shot waste classification dataset
ANALYSIS OF FAST ALGORITHM OF MATRIX-VECTOR MULTIPLICATION FOR THE BANK OF DIGITAL FILTERS

Algorithms of implementation of vector-matrix multiplication are presented, which are intended for application in banks (sets) of digital filters. These algorithms provide significant savings in computational costs over traditional algorithms. At the same time, reduction of computational complexity of algorithms is achieved without any performance loss of banks (sets) of digital filters. As the basis for the construction of algorithms proposed in the article, the previously known Winograd method of multiplication of real matrices and vectors and two versions of the method of type 3M for multiplication of complex matrices and vectors are used. Methods of combining these known methods of multiplying matrices and vectors for building digital filter banks (sets) are considered. The analysis of computing complexity of such ways which showed a possibility of reduction of computing complexity in comparison with a traditional algorithm of realization of bank (set) of digital filters approximately in 2.66 times – at realization on the processor without hardware multiplier is carried out; and by 1.33 times – at realization on the processor with the hardware multiplier. These indicators are markedly higher than those of known algorithms. Analysis of sensitivity of algorithms proposed in this article to rounding errors arising by digital signal processing was carried out. Based on this analysis, an algorithm is selected that has a computational complexity smaller than that of a traditional algorithm, but its sensitivity to rounding errors is the same as that of a traditional algorithm. Recommendations are given on its practical application in the development of a bank (set) of digital filters.
Verification of Composed Web Service Using Synthesized Nondeterministic Turing Model (SNTMM) With Multiple Tapes and Stacks

To verify the composed web services, a general view of what traits of a service need to be identified is still lacking. The existing verification model did not address any mechanism for getting alternative services if we failed to reach the desired service and partially concentrated on the reachability problem for a deterministic and non-deterministic system in sequential. This paper proposes a synthesised non-deterministic turing machine model (SNTMM) by combining the multistacked non-deterministic Turing machine (MSNTM) model and multitaped non-deterministic Turing machine (MTNTM) model to verify the composed web services for both deterministic and non-deterministic systems in parallel. The deceased transition and departed service marking algorithm have been proposed to address each participated service's reachability in composing service for all possible input in parallel. This article shows an example to demonstrate the meticulousness of the model. The experimental results show that the performance of the proposed model is measured efficiently.
Estimation of Global Solar Energy to Mitigate World Energy and Environmental Vulnerability

The present consumption level of the reserved fuel left on Earth that powers the world is depleting the limited fossil fuel level, while fossil fuel burning is causing deadly environmental vulnerability. Inevitably, alternative energy sources that are abundant and benign to the environment are needed to drive the modern world. The use of solar energy, which is renewable and abundant everywhere, in every sector of modern life is an interesting option for powering the modern world. Therefore, in this research, a calculative mechanism is conducted to estimate the global solar energy in order to present a clean and renewable energy system for the world. Interestingly, the calculated results show that the average energy density of sunlight irradiance energy on the surface of the Earth is 1,366 W/m2, which is determined by calculating the diameter of Earth as 10,000,000 meridians from the North Pole to the equator and the radius of Earth as 2/π × 107 m. Therefore, the net solar energy coming to Earth is calculated as 1,366 × (4/π) × 1014 ∼= 1.73 × 1017 W by computing a day consisting of 86,400 seconds and a year consisting of 365.2422 days, on average. The annual net solar irradiance reaching Earth is 1.73 × 1017 × 86,400 × 365.2422 ∼= 5.46 × 1024 J, which is equivalent to 5,460,000 EJ, which is 10,056 times higher than the annual net current energy demand on Earth. Simply put, the utilization of solar energy, which is clean and environmentally friendly, could be the primary source of energy to satisfy the net power demand of the entire world.
Using Social Signals to Predict Shoplifting: A Transparent Approach to a Sensitive Activity Analysis Problem

Retail shoplifting is one of the most prevalent forms of theft and has accounted for over one billion GBP in losses for UK retailers in 2018. An automated approach to detecting behaviours associated with shoplifting using surveillance footage could help reduce these losses. Until recently, most state-of-the-art vision-based approaches to this problem have relied heavily on the use of black box deep learning models. While these models have been shown to achieve very high accuracy, this lack of understanding on how decisions are made raises concerns about potential bias in the models. This limits the ability of retailers to implement these solutions, as several high-profile legal cases have recently ruled that evidence taken from these black box methods is inadmissible in court. There is an urgent need to develop models which can achieve high accuracy while providing the necessary transparency. One way to alleviate this problem is through the use of social signal processing to add a layer of understanding in the development of transparent models for this task. To this end, we present a social signal processing model for the problem of shoplifting prediction which has been trained and validated using a novel dataset of manually annotated shoplifting videos. The resulting model provides a high degree of understanding and achieves accuracy comparable with current state of the art black box methods.
PEDAGOGICAL CONDITIONS PROMOTING THE FORMATION OF SOCIAL EXPERIENCE OF STUDENTS DURING EXTRACURRICULAR ACTIVITIES

This work presents and analyzes the pedagogical conditions that have developed on the basis of the studied theoretical, scientific and pedagogical sources (M. K. Apetyan, N. M. Borytko, D. V. Grigoriev, N. V. Ippolitova, A. G. Ligostaev, Yu. A. Ryzhikova, N. S. Sterkhova, A. Fernham, P. Haven, etc.) of the analyzed author's work experience and contributes to the effectiveness and efficiency of the claimed research process. The pedagogical conditions that we have formulated are: taking into account the age and psychological characteristics of primary school students; the combination of various types of teacher's activities, which actualizes the extracurricular ac-tivities of schoolchildren; the use of a complex of forms, methods and techniques aimed at form-ing the social experience of younger schoolchildren and, of course, positively influencing the development of students ' ideas and knowledge about the world around them, necessary for its development and active communication (including in language) of the skills of pupils. This, in turn, helps to form their social experience in extracurricular activities. Thus, the current ap-proaches to the development of pedagogical conditions and the solution of scientific psycholog-ical and pedagogical problems are characterized. The author describes the program of extracurricular activities “Polyglot” (linguistic ori-entation), which is substantively tested by the author. The program is focused primarily on the formation of the social experience of younger students (grades 2–4) in extracurricular activities. The positions on the preferences of students when mastering the Program have been analyzed and the results achieved during the implementation of the Program have been determined: the necessary and sufficient conditions have been created for the formation of social experience; the level of motivation for learning English and the level of formation of the linguistic competence of students were increased, thanks to extracurricular activities. Significant research results are ranked.
Risk Management Analysis Of Information System Security Internet Management Applications Using Octave-S Method At The Service Of Archives And Library Of Sumedang Regency

The current information system is an important resource, has strategic value and has a very important role as competitiveness, main competence, and in the survival of an organization. The convenience, convenience and benefits promised in every development and implementation of an information system are also recognized as an effort to make or place the information system more vulnerable to potential threats. The risks that occur are damage to the server caused by a virus attack, data loss due to the absence of a database backup, connection lost to is user due to interference with the internet connection. The purpose of this study is to identify, analyze and manage risks that may occur in the Internet Management Application Information System (Kunang-kunang) in the Archives and Libraries Service of Sumedang Regency. Risk assessment uses the OCTAVE-S method. The final result of the ridiko management analysis is that the Internet Management Application Information System (Kunang-kunang) is at the Green level (Green) which means it meets the criteria that there are only a few risks in the system and 39 statements on the questionnaire are declared valid. From the results of the implementation of this analysis, recommendations are formulated to improve system security management in the Internet Management Application System.
Rancang Bangun Aplikasi Pencarian Toko Servis Resmi Komputer Di Kota Pekanbaru

The role of information technology is never separated in all aspects of people's daily lives. One of the technological developments that affect data recording at this time is the Global Positioning System (GPS). The Global Positioning System (GPS) is a satellite-based navigation system that provides information about the location on the earth's surface easily, quickly, cheaply, and the accuracy can be justified. Especially in the development of spatial information or better known as Geographic Information Systems. Utilization of geographic information systems in the field of technology, namely being able to find the location of official computer service stores in Pekanbaru City. An authorized computer service shop is a trusted place for repairing various computer equipment. Because the technicians in this shop have special experience in each of their skills. In general, people feel doubtful and afraid when they want to repair computers at service shops that do not necessarily have special skills. With this Geographic Information System, it can make it easier for users of official computer service store services. These conveniences include finding the location of an authorized computer service shop, with the technicians having special skills according to the user's wishes or finding the location of the nearest authorized computer service shop from the user's point location.
The Usage of Balanced Scorecard (BSC) in Evaluating the Performance of the University of Jordan/Aqaba Branch from the Academic Staff Perspective

The study aims to investigate the usage of Balanced Scorecard as a tool to evaluate the performance of the University of Jordan/Aqaba branch from the perspective of academic members. In order to achieve the objectives of the study and test hypotheses, the study relied on primary and secondary data, where the questionnaire was designed to reconnaissance the opinion of the sample of (65) members, the study was based on the analytical descriptive method and analysis of study variables and test hypotheses. One of the most important results of the study, the University is working to keep pace with scientific development through the development of academic programs and to ensure that the development of new programs according to scientific requirements, which has enabled the possibility of application of the performance of Balanced Scorecard, as noted, the cost of time courses at the university, which is obvious in the level of academic and administrative services submitted to the students that greatly increase the tuition fees for students in colleges, the university strives heavily on the development of their role and to highlight the reputation and efficiency among all Arab and international universities, and is working to develop a relationship with alumni and follow up on their situation, but it faces some difficulties due to the economic conditions that prevent without the possibility of absorption of graduates into the labor market. The most important recommendations of the study is that University has to work to intensify efforts to further develop and to elevate the Balanced Scorecard to the rank of international universities besides the university administration serving to check the tuition fees for students and work on the budget with the services provided to them taking into consideration the social situations, as well as to increase the voltage in the follow-up conditions of graduates and to work up creating jobs for them.
Satellite Image Compression Algorithm Based on the FFT

Image compression is minimizing the size in bytes of a graphics file without degrading the quality of the image to an unacceptable level, the reduction in file size allows more images to be stored in a given amount of disk or memory space, it also reduces the time required for images to be sent over the ground. This paper presents a new coding scheme for satellite images. In this study we apply the fast Fourier transform and the scalar quantization for standard LENA image and satellite image. The results obtained after the (SQ) phase are encoded using entropy encoding, after decompression, the results show that it is possible to achieve higher compression ratios, more than 78%, the results are discussed in the paper.
Occupancy Estimation from Thermal Images

We propose a non-intrusive, and privacy-preserving occupancy estimation system for smart environments. The proposed scheme uses thermal images to detect the number of people in a given area. The occupancy estimation model is designed using the concepts of intensity-based and motion-based human segmentation. The notion of difference catcher, connected component labeling, noise filter, and memory propagation are utilized to estimate the occupancy number. We use a real dataset to demonstrate the effectiveness of the proposed system.
It’s a Trap! How Cognitive Representations Inhibit Performance in Complex and Changing Environments

Organizations rely on simplified cognitive representations to make sense of the complex environment they participate in. These environments rarely stay stable – either by active attempts such as market entry or through incremental and disruptive changes in the environment itself, organizations are continuously pushed to adapt to new situations. Drawing on theories of organizational search and learning, cognitive sciences, and cognitive psychology, we explore how simplified cognitive representations facilitate and inhibit firm performance under uncertain circumstances, and how these effects differ over time in environments of differing degrees of complexity and similarity. Results of a computational simulation indicate that there is a trade-off in benefits provided by cognitive and experiential search, and that a ‘representation trap’ affects high and low performers differentially across different environments. In the initial landscape, the simplified cognitive representations adopted by low performers effectively trap them in inferior path-dependent trajectories, largely precluding the possibility of performance enhancement. However, the tables are turned when the population enters a different environment. Previous high performers experience difficulty in defending their advantage because their previously superior cognitive representations become an imprint that limits performance. We extend prior accounts of the cognition-oriented view in organizational search and learning by showing how simplified cognitive representations can inhibit performance and how they react to environmental change.
Observational Studies on Algorithms of Frequent Pattern Mining

Data mining is an extensive research area, as frequent pattern mining performs an effective role in many real-life applications. Frequent patterns are used in data mining with multiple algorithms that give different performances over different datasets. Often, the initial basic algorithms for pattern mining like Apriori, FP Growth, and Eclat are used. The cornerstone of this manifesto is to explore the major issues/challenges related to the algorithms used with the transaction Subdata of continuous mining of pattern.
Interpretation of Adam and Eve's Magic Squares 3x3 Talisman Using a Mathematical Approach

Indonesian society until now still believes and use talisman. One of wich that often used is Adam and Eve’s magic square 3x3 talisman. The Adam and Eve’s magic squares 3x3 talisman is the basic of making other talismans. This talisman is used for compassion, safety, treatment and other efficacy. This talisman is called Adam and Eve’s because mathematically the number of Adam’s name equal to 45 and Eve’s is equal to 15 which corresponds to the number of this talisman that is interpreted that Eve is made of Adam’s ribs. This talisman can also be taken from the beginning of the Surah in Quran is a combination of kaf ha ya ain shad and ha’ mim ain sin qaf with mathematical calculation can be obtained of talisman. If the Adam and Eve’s magic squares 3x3 talisman is consideret as a matrix then a mathematical operation can be done by calculating the characteristic roots or addition of eigen value with the results 15. This number corresponds to the sum of the columns, rows or diagonals of this talisman. By the same characteristics root value will provide the energy of harmony to the purpose of its manufacture.
Computation of the Exact Fisher Information Matrix of a Multiple Input Single Output Time Series Models

Klein, Mélard, and Zahaf (1998) have proposed the computation of the exact Fisher information matrix of a large class of Gaussian time series models called the single-input-single-output (SISO) model, includes dynamic regression with autocorrelated errors and the transfer function model, with autoregressive moving average errors. For computing the Fisher information matrix of a SISO model, they introduced an algorithm based on a combination of two computational procedures: recursions for the covariance matrix of the derivatives of the state vector with respect to the parameters and the fast Kalman filter recursions used in the evaluation of the likelihood function. In this paper, we propose a generalization of this method for computing the Fisher information matrix of a MISO model.
Synthesizing Human Faces Using Latent Space Factorization and Local Weights

We propose a 3D face generative model with local weights to increase the model’s variations and expressiveness. The proposed model allows partial manipulation of the face while still learning the whole face mesh. For this purpose, we address an effective way to extract local facial features from the entire data and explore a way to manipulate them during a holistic generation. First, we factorize the latent space of the whole face to the subspace indicating different parts of the face. In addition, local weights generated by non-negative matrix factorization are applied to the factorized latent space so that the decomposed part space is semantically meaningful. We experiment with our model and observe that effective facial part manipulation is possible, and that the model’s expressiveness is improved.
DIGITAL TRANSFORMATION OF THE HIGHER EDUCATION SYSTEM: TWO YEARS OF A PANDEMIC

The theoretical approaches to the main problems of digital transformation of the higher education system in the Russian Federation. In aspect of this point questions connected with a features of the technological support of the educational process, digital literacy and digital divide of participants in online education, methods of educational and scientific work, as well as features of psychological adaptation in the digital reality. The ways of using the accumulated educational experience in the post-pandemic world are proposed.
Hand Gesture Recognition Using Convolutional Neural Network and Diagonal Sum Algorithm

The research presents a computer-based vision application to identify hand gestures. A camera records a live video stream that is utilised to build an interface snapshot. For every five varieties of count-hand movements, the methodology is taught at least once (one, two, three, four, and five). After that, the system attempts to recognise a test gesture. The Convolutional Neural Network was used since its algorithm is self-developed and during the pre-processing stage it removed the backdrop for every training move. The image is turned into a binary image and the sums of the diagonal components of the picture are computed. This amount helps to distinguish and classify distinct hand movements. Data gloves or markers were used in prior systems to enter data into the system. When it comes to utilising the system, I have no such constraints. The user may intuitively move his/her hand in front of the camera.