Reviewerly/exHarmony huggingface dataset:
Comparing single-sitting versus modular text message surveys in Egypt

Survey researchers increasingly explore the use of text message surveys as a cost efficient data collection that can be applied in hard-to-reach populations where other survey modes suffer from undercoverage, e.g., in regions with low landline and/or internet penetration. However, not much is known about how to best administer text message surveys. We experimentally compare two designs of automated text message surveys in terms of response rate, nonresponse bias, substantial responses, and participation in a follow-up survey in Egypt. In the single-sitting design, respondents automatically received a new question once they reply to a question. In the modular design, respondents received a new question each day, regardless of whether they responded to the previous question. We invited 1,081 Egyptian parents of kindergarten children who own a mobile phone to participate. We found that, compared to the single-sitting group, the modular group achieved a higher number of answered questions but had fewer fully completed questionnaires. In addition, we found a difference between groups on substantive responses. We find no nonresponse bias in both groups and no difference in probability to respond to a follow-up survey. Our results will help researcher to make design decision about how to implement text message surveys.
Emergency Remote Education Amid COVID-19 Pandemic

The COVID-19 health emergency has created an unprecedented crisis in many areas. In education, it caused the suspension of face-to-face classes at all educational levels to prevent the spread of the virus and mitigate its impact. In extraordinary circumstances, such as those faced since 2020, the governments and the corresponding educational authorities found it necessary to apply strategies that would allow continuity to the learning processes remotely, causing a series of changes. The teacher, for example, required a transformation in his/her role as part of the social isolation demanded by the pandemic, for which it should be noted, he/she was not prepared; compelling him/her to act mainly as a mediator in the teaching-learning processes, and rely on the use of technology as an educational resource. Therefore, given the particularities of the current context and the conditions required for students to adapt themselves to the challenges to come, the education needs to be structured according to the four pillars raised by Jaques Delors at the end of the last century; but from a different approach; which will be addressed through the next chapter.
Disjunctive logic programs, answer sets, and the cut rule

Abstract In Minker and Rajasekar (J Log Program 9(1):45–74, 1990), Minker proposed a semantics for negation-free disjunctive logic programs that offers a natural generalisation of the fixed point semantics for definite logic programs. We show that this semantics can be further generalised for disjunctive logic programs with classical negation, in a constructive modal-theoretic framework where rules are built from claims and hypotheses , namely, formulas of the form $$\Box \varphi $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>□</mml:mo> <mml:mi>φ</mml:mi> </mml:mrow> </mml:math> and $$\Diamond \Box \varphi $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>◊</mml:mo> <mml:mo>□</mml:mo> <mml:mi>φ</mml:mi> </mml:mrow> </mml:math> where $$\varphi $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>φ</mml:mi> </mml:math> is a literal, respectively, yielding a “base semantics” for general disjunctive logic programs. Model-theoretically, this base semantics is expressed in terms of a classical notion of logical consequence. It has a complete proof procedure based on a general form of the cut rule. Usually, alternative semantics of logic programs amount to a particular interpretation of nonclassical negation as “failure to derive.” The counterpart in our framework is to complement the original program with a set of hypotheses required to satisfy specific conditions, and apply the base semantics to the resulting set. We demonstrate the approach for the answer set semantics. The proposed framework is purely classical in mainly three ways. First, it uses classical negation as unique form of negation. Second, it advocates the computation of logical consequences rather than of particular models. Third, it makes no reference to a notion of preferred or minimal interpretation.
MODELING THE APPLICATION OF AUGMENTED REALITY TECHNOLOGY IN THE EDUCATION PROCESS

Augmented reality technology (AR) is strengthening its position in our daily lives every year. The main goal of augmented reality technology is to digitize the world around us by adding additional information that is relevant and attractive to the consumer in a particular sector. Gadget stores are adding more and more fun and useful PR programs, while big companies and startups are coming up with new ideas on how to effectively apply augmented reality technology to business processes. Education is one of the areas where the application of PR technology is receiving increasing attention and funding. It is also anticipated that the penetration of this technology into education will only increase and the PR education industry will expand. The aim of this article is to analyze the impact of PR technology on the participants of the educational process and to form an application model in Lithuanian general education schools. The article examines the possibilities of applying augmented reality technology in the education sector, distinguishing the level of basic schools. The impact on the educational process and its participants is also analyzed and evaluated. Several research methods are used and combined in the work – the analysis of scientific literature is combined with classroom research to find out the already applied PR models at different levels of the education sector and the questionnaire survey method to assess the situation of PR technology use in Lithuanian basic schools. The results revealed that augmented reality technology is still poorly applied in Lithuania in the educational process, mostly due to human and financial resources. The analysis presented in the article can be useful for educational institutions wishing to implement smart technologies, which are also designed for an innovative teaching process.
Study on ATM with One-Time Password for a Safe and Smart Future

Abstract: Money is the most crucial thing to accomplish nowadays, whether you're buying something, travelling, or dealing with a medical problem. However, it is inconvenient when you need to carry a significant amount of cash in your pockets. ATMs can in useful in this situation. The bank has an ATM that can disburse cash to you wherever you are. An ATM is a simple way to make money; all you have to do is insert a card and enter a PIN, and the money is yours. But, if someone steals your card and you know your password, he will have complete access to your funds. This highlights the issue of present security and necessitates the search for anything new in the system that can give a second degree of protection. A one-time password (OTP) is a password that is used to verify user authentication for a single login to a system. The security of the Automatic Teller Machine (ATM) system is addressed in this research in a novel way. Keywords: OTP, ATM, PIN, security, system.
Features of Professional Well-being in a Situation of Uncertainty

The paper proposes to consider the issue of the professional well-being of future specialists in the world of uncertainty at the intersection of scientific areas -psychology and economics.It is quite difficult for a young person to be professionally successful; it is difficult to realise his potential in the modern world.His professional trajectory cannot develop linearly in a rapidly changing world.The human capital of an educational organisation in a situation of uncertainty is the key to the professional viability of future specialists.To activate the human capital of an educational organisation, it is necessary to have a teaching staff ready for new personal changes, focused on what a person will be like tomorrow.Research subject: professional viability in a situation of uncertainty.For the teacher's professional viability, it is necessary to consider the structure of the professional self-concept "I-changing", which contributes to the rapid entry into a new professional reality.The constituent elements of the "I-changing" include flexibility, adaptability, risk acceptance, acceptance of responsibility, independence, psychological activation, tolerance to uncertainty, indicators of subject orientations -the trans-situational locus of control, trans-situational variability, trans-situational mobility.The formation of the elements of self-changing is due to effective deep scenarios.
ACCURACY OF DETERMINATION OF LINEAR SPECTRAL FREQUENCIES

The article describes the basic idea of coding a speech signal by the method of linear prediction (Linear Predictive Coding – LPC), which consists in the fact that instead of the parameters of the speech signal, the encoded parameters of a certain filter are transmitted over the communication line, which is, in a sense, an equivalent of the human vocal tract, as well as parameters of the excitation signal of this filter: tone or noise. The essence of the parameters of the synthesizing filter – linear prediction coefficients (LP), calculated in the process of frame-by-frame adaptive filtering – is disclosed. The main advantages of these coefficients are stated, which consists in the ability to completely describe the state of the predictor filter, as well as the main disadvantages obtained as a result of numerous studies that prevent the direct transmission of LPCs over the communication channel due to their sensitivity to quantization errors. The necessity of searching for mathematically equivalent parameters f the reducing filter is substantiated. Alternative parameters of the LSP representation of the vocal tract model, called Linear Spectral Frequencies (LSP), are proposed, and are most often used in low-speed speech codecs at the present time. The main difficulty of the task of calculating the LSP directly from the LSP in real time is described, and it is also investigated that most of the analyzer’s processor time, as a rule, is spent on this task. It is proved that despite the high level of development of digital processors, the problem of calculating the parameters of the vocal tract model in real time remains one of the main difficulties in speech coding. That is why methods that reduce the complexity of this procedure are currently of significant interest. A new method for calculating the LSP and an algorithm based on it are proposed. Its main advantages over the existing ones are described. An assessment of the possible improvement in the quality of speech processing was made, due to the use of the developed method for calculating the LSP.
Uniqueness of optimal randomized algorithms for balanced AND-OR trees

In this paper, we investigate optimal randomized algorithms of balanced AND-OR tree evaluation, with regards to query complexity. For balanced AND-OR trees, previous studies have made a good progress on the uniqueness of eigen-distributions, i.e., optimal mixed strategies determining an input (Suzuki & Nakamura 2012, Peng et. al. 2016). However, it has been considered that the dual problem, the uniqueness of optimal randomized algorithms, is rather difficult, and a new approach has been needed. By introducing a group-theoretical methods, we show that the uniqueness does not hold and there are uncountably many optimal randomized algorithms.
Assessment of knowledge and practice of criminal intelligence and staff profiling for fraud prevention in Nigerian banks

The study was set to examine knowledge and practice of criminal intelligence and staff profiling for fraud prevention in Nigerian banks, the study adopted the mixed method research design of descriptive survey and key informant interview. Multistage sampling technique was used to select the sample population for the study a total of 324 respondents was sampled using the Taro Yamane formula for sample size determination. Questionnaire and key person’s interview were used as data collection instrument. The findings of the study conclude that bank staff is aware and knowledgeable of criminal intelligence and staff profiling as an effective tool for fraud prevention. Beyond the awareness, bank staff are also knowledgeable on the application of criminal intelligence and staff profiling, while they also agreed that the extent of application of criminal intelligence and staff profiling in the recruitment, placement and monitoring of staff is low. However, the study recommends that Senior management of banks should be given adequate training and this training should be regularly updated on criminal intelligence and monitoring, as well as staff profiling. This would facilitate a greater uptake of credible intelligence and the prevention of bank fraud and other criminal activities.
Peer review declaration

Abstract • Type of peer review: Open • Conference submission management system: Applications were accepted through an electronic system. Website https://topconferenc.ano-cntr.ru/ • Number of submissions received: 82 • Number of submissions sent for review: 82 • Number of submissions accepted: 82 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 96,47 • Average number of reviews per paper: 3 • Total number of reviewers involved: 38 • Any additional info on review process: • Contact person for queries: Kaplan Mikhail Alexandrovich E-mail: mishakaplan@yandex.ru / 79031927386@yandex.ru Tel.: +79031927386 Forum Scientific Secretary
Developing the Interactive e-Module Based on Integrated Learning for Primary School Students

In the 2013 curriculum subjects in primary schools were organized with themes, namely combining all subjects that reflect students’ everyday lives. However, the themes in the student’s book do not integrate one subject with the others and do not reflect the students real life. Therefore, it is hard for many primary school teachers in Padang to implement the integrated learning using the textbooks. This research aims to develop the interactive e-module based on the principles of integrated learning that can facilitate students in carrying out learning process, so it can improve students’ competency. The research and development of interactive e-module use four-D models that consist of four stages, namely define, design, develop and disseminate. The research subject was the interactive e-module based on integrated learning. The respondents of this research were 12 teachers and 70 Grade 5 students of three primary schools in Padang, West Sumatra, Indonesia. Data were collected using observation sheets, interview guides, questionnaires, and tests. There are three main results obtained from the research. First, according to expert judgment the interactive e-module is valid. Second, based on teacher and student's responses the module is very practical. Third, based on the student learning outcomes the interactive e-module is effective.
A Real-time Face Mask Detection and Social Distancing System for COVID-19 using Attention-InceptionV3 Model

One of the deadliest pandemics is now happening in the current world due to COVID-19. This contagious virus is spreading like wildfire around the whole world. To minimize the spreading of this virus, World Health Organization (WHO) has made protocols mandatory for wearing face masks and maintaining 6 feet physical distance. In this paper, we have developed a system that can detect the proper maintenance of that distance and people are properly using masks or not. We have used the customized attention-inceptionv3 model in this system for the identification of those two components. We have used two different datasets along with 10,800 images including both with and without Face Mask images. The training accuracy has been achieved 98% and validation accuracy 99.5%. The system can conduct a precision value of around 98.2% and the frame rate per second (FPS) was 25.0. So, with this system, we can identify high-risk areas with the highest possibility of the virus spreading zone. This may help authorities to take necessary steps to locate those risky areas and alert the local people to ensure proper precautions in no time.
A study on mode effects of National Assessment of Educational Achievement(NAEA)

This study was conducted using paper-based test (PBT) and computer-based test (CBT) data collected from the 2020 national level academic achievement evaluation for high school sophomores. First, according to the reliability analysis results, stable reliability indices were calculated for the two implementation methods in Korean, math, and English subjects. As a result of examining construct equivalence, it was found that the construct equivalence between the two modes in Korean and English subjects was suspected. In order to control the school-level characteristics, a multi-level model was applied to the schools where both PBT and CBT were implemented, and the regression coefficients of the random intercept model showing greater model-fit were interpreted from the analysis results. As a result, a clear mode effect was found in the type of construct item in Korean and English subjects, and the CBT score was significantly higher. Next, differences in mode effects for each subgroup such as gender, regional size, and school gender were analyzed. As a result, it was found that male students tend to score favorable on CBT in mathematics and English subjects, and female students
Improvement of Multi Frequency Heterodyne Phase Unwrapping in Extreme Environment

Multi-frequency heterodyne (MFH) phase unwrapping algorithm plays an important role in 3D surface measurement because of its high precision and anti-interference features. However, under extreme environments such as over-dark or over-bright or low signal-to-noise ratio (SNR), the phase unwrapping may fail due to the increase of phase error. In order to improve the robustness of algorithm, we proposed an improved MFH algorithm to reduce the error accumulation of synthetic phase in the process of MFH algorithm. We expanding synthetic phase using the rounding function to remove the error of the synthesis phase, and then scaling down expanded synthetic phase to obtain the synthetic phase in [0, 2π], which has higher accuracy than before. The simulation and experimental results show that, in the same conditions, our method is more robust than traditional MFH algorithms. The proposed method is applied to the surface measurement of relay components, and it can effectively avoid the failure of phase unwrapping in the actual measurement.
Features of Labor Behavior of Graduates of Postgraduate Studies in Russia

A scientific study results comparing the basic scales of the MMPI test of young professionals focused on working in the academic field with the average scales of successful scientists and university teachers are presented.The methodological basis of the study was the methodology based on the standard interpretation of the basic scales of the MMPI test.The results obtained give every reason to question the effectiveness of measures taken in Russia aimed at rejuvenating the labor potential of academic organisations, since, in most cases, the profiles of university graduates who intend to develop their career trajectory in the academic field, when compared with the profiles of successful scientists and teachers, have relatively significant differences.The nature of these differences may contribute in the very near future to the modification of labor activity in creative organisations into a model where the quality of office work and strict compliance with all labor regulations will be considered as an effective variant of the personnel management system.The creative nature of the staff's work will be assessed as an undesirable deviation from the established labor regulations.To eliminate such a negative trend, it is necessary to conduct a PR campaign within the state to increase the social prestige of scientific and pedagogical activities in academic organisations.This will make it possible to attract talented young specialists to graduate school and further assign them to academic organisations and could successfully engage in creative activities and not those university graduates who could not "get a job" in commercial organisations or state (municipal) institutions.
A Study on Prediction Skills and Reading Efficiency in College English Based on Optimized BP Networks

In this paper, an in-depth study and analysis of college English prediction skills and reading efficiency are conducted using an optimized BP network algorithm, which is designed separately, and the accuracy of scoring results is verified and the experimental results are analyzed using two datasets; finally, under the guidance of writing feedback theory and data visualization design criteria, a reasonable visualizable writing feedback is created. The learning and training of the BP neural network model revealed that there was significant information loss in the similar nearest-neighbor user dataset used for training, and there were instances where some items were rated by the target user but not by similar nearest-neighbor users. As a result, such data is useless in training, and the neural network loses a significant amount of useful information when learning. To address this issue, this paper proposes using the singular value decomposition technique for filling, which alleviates the sparsity of the filled matrix data and improves the accuracy of recommendations even more. Both scoring models constructed using 1D CNN and LSTM networks belong to the second class of models, and this type of “end-to-end” scoring model does not require feature engineering. Finally, using 650 spoken recordings and their corresponding manual scoring data, the model is trained and tested. The experimental results show that, with a smaller training dataset, the BP network model achieves a better overall scoring performance.
A HRI Framework Based on Eye Tracking

Existing human-robot interaction (HRI) technologies are not intuitive or effective enough for the disabled. Most of them can neither express their explicit intent (voice, posture, touch, etc.), nor communicate based on implicit intent. We propose a novel HRI framework for implicit intent reasoning based on eye tracking. The framework is designed for people with normal vision, and it will track and analyze their eye movements to infer their intents in a smart home environment. These intents are then sent to an assistive robot and guide the robot to accomplish specific tasks such as using keys to open the door. Two Experiments were carried out to validate the effectiveness of the framework. In the implicit intents classification task, the average classification accuracy of the two implicit intents (task-free visual browsing and task-oriented visual search) was 84.43% via the Support Vector Machine (SVM). In implicit intent reasoning task, Naive Bayesian (NB) networks were used to establish the intent knowledge base, reaching the highest accuracy of intent reasoning was 98%. These results proved that our framework could aid the elderly and the disabled to better adapt to the smart home environment in their daily life.
Design of asymptotically perfect linear photonic circuits

Conventional multiport interferometers based on MZI meshes suffer from component imperfections, which limit their scaling. We introduce two new designs that overcome this limitation: a 3-splitter MZI for generic errors and a broadband MZI+Crossing design for more realistic correlated errors. These architectures, motivated by the correspondence between SU(2) and the Riemann sphere, are more error tolerant than the standard MZI mesh and support progressive self-configuration. Numerical simulations reveal orders-of-magnitude error reductions compared to the standard MZI mesh; moreover, the mesh is asymptotically perfect: the matrix error decreases with mesh size.