Reviewerly/exHarmony huggingface dataset:
The synthesis of control system to synchronize ship generator assemblies

This paper considers the construction of principles and the synthesis of a system of effective control over the processes of synchronization of generator sets (GSs) that form a part of the distributed MP-control systems for complex ship technical systems and complexes (STS and C). The tasks of synchronization have been set, the process and database models have been built, the system configurations have been defined. Based on the use of resultant functions, we have determined stages in solving the tasks of control over the frequency adjustment synchronization in a hierarchical sequence. The performance analysis of the STS and C control elements has been carried out; the use of the integrated optimization criteria and dual management principles has been proposed. Practical techniques to manage the GS synchronization have been given. We have solved the problem of high-speed control over the frequency of synchronized objects based on the principles of adjustment. That has made it possible to determine in advance the moments of GS enabling under the deterministic and stochastic statement of the synchronization task. The results of the experimental study into the GS synchronization processes are given; the effectiveness of the proposed GS control has been proven. The principles underlying the construction of procedures to control the GS composition when using the methods of "rigid" and "flexible" thresholds have made it possible to define the optimization criteria and implement a control law that satisfied the condition for an extremum, which is an indicator of the feasibility of the set goal and takes into consideration the limitations of control influences. We managed to design a system in the class of adaptive control systems by the appropriate decomposition of the system's elements by splitting a synchronization task into the task on performance and the task on control under the required conditions. The given examples of the processes where the synchronization failed while using standard synchronizer control algorithms, as well as processes of successful GS synchronization when applying the proposed synchronizer dual control algorithms, have confirmed the reliability of the main scientific results reported here.
Quantum computing and quantum information storage

This themed collection includes a selection of articles on quantum computing and quantum information storage.
Entangled and correlated photon mixed strategy for social decision making

Abstract Collective decision making is important for maximizing total benefits while preserving equality among individuals in the competitive multi-armed bandit (CMAB) problem, wherein multiple players try to gain higher rewards from multiple slot machines. The CMAB problem represents an essential aspect of applications such as resource management in social infrastructure. In a previous study, we theoretically and experimentally demonstrated that entangled photons can physically resolve the difficulty of the CMAB problem. This decision-making strategy completely avoids decision conflicts while ensuring equality. However, decision conflicts can sometimes be beneficial if they yield greater rewards than non-conflicting decisions, indicating that greedy actions may provide positive effects depending on the given environment. In this study, we demonstrate a mixed strategy of entangled- and correlated-photon-based decision-making so that total rewards can be enhanced when compared to the entangled-photon-only decision strategy. We show that an optimal mixture of entangled- and correlated-photon-based strategies exists depending on the dynamics of the reward environment as well as the difficulty of the given problem. This study paves the way for utilizing both quantum and classical aspects of photons in a mixed manner for decision making and provides yet another example of the supremacy of mixed strategies known in game theory, especially in evolutionary game theory.
Research and Application of Combined Algorithm Based on Sustainable Computing and Artificial Intelligence

The Internet is a popular form of information technology development in the new century, and it organizes and analyzes big data by taking effective measures to find useful information. With manpower, it is obviously not enough to be in such a huge information system, so the emergence of sustainable computing and artificial intelligence has become the core of large-scale data processing at this stage. This paper studies the application of the combined algorithm based on sustainable computing and artificial intelligence. In this paper, a new combined intelligent search algorithm is proposed by combining sustainable computing with artificial intelligence. The combination algorithm firstly analyzes the value from the aspects of ecological environment and economic benefits and studies the overall evaluation of sustainable development ability. Secondly, the energy analysis method is used to establish a reasonable comprehensive ecosystem and evaluate its impact on the sustainable development of environment and economy. Finally, the impact of resource consumption, wind speed detection, waste discharge, and utilization of renewable resources in a certain area is analyzed by simulation. Through the experimental results, on the one hand, it is proved that the data obtained by the combined algorithm are more accurate than the single algorithm; on the other hand, the combined algorithm can be further sublimated and widely used for other data detection. The combination algorithm proposed in this paper can effectively detect the required data and has high applicability.
THE USE OF DESCRIBING PICTURE STRATEGY TO IMPROVE SECONDARY STUDENTS’ SPEAKING SKILL

Describing picture strategy is one of the techniques that can be used to improve students' speaking skills. Speaking skill is one of the subjects that difficult to be mastered by young learners. This study was conducted in SMA Al Azhar 3 Bandar Lampung at first-grade students. With qualitative data, the result showed that describing a picture strategy can improve students' speaking skills. This finding is in line with the previous research finding that describing pictures can help students to improve students’ speaking skills. Nevertheless, there are some problems gained in using describing picture strategy. Many students could not apply grammar correctly when they speak by using the strategy. The students are difficult to understand English when their friends speak English using describing the picture.
New equidistribution of set-valued statistics on permutations

We construct bijections to show that two pairs of multiple set-valued statistics of permutations are equidistributed on symmetric groups. This extends a recent result of Sokal and the second author valid for integer-valued statistics as well as a previous result of Foata and Han for bivariable set-valued statistics.
Competence of the research and education center: definition, list and structure

Introduction. The article substantiates the need to introduce the concept of "REC competencies", associated with the emergence of a new type of partnership of education, science and business – world-class research and educational centers. The emergence of new positions within the REC and their dynamic changes also pose the task of continuous work with competencies. The article presents an analysis of the methodological results of the work of the competence group within the framework of the strategic sessions of the scientific and educational center of the Nizhny Novgorod region, research and approaches to the definition of competencies. Materials and Methods. Systematic and activity-based approaches were used as the methodological basis of the study. To solve the tasks set by the authors of the work, general scientific, psychological, pedagogical and practical methods of scientific research were used. Theoretical and empirical research methods were used: analysis, synthesis, generalization, comparison, comparison, scientific theorization. For the analysis, the materials collected by the working group "Competencies" within the framework of the strategic sessions of the REC of the Nizhny Novgorod region were used. Results. The article defines the concept of "REC competence", for the formulation of which an activity-based approach was used. The types of REC competencies are identified-meta-competencies (for the key activities of the research and educational center: research, innovation, entrepreneurship, engineering and technology, education) and cross-cutting competencies, the presence of which is necessary and sufficient for the REC project team in order to close the entrepreneurial contour of the project and make it successful on the world market. The structure of REC competence is defined, including motivational, cognitive, operational and vector components. The structure of cross-cutting competencies is described. Discussion and Conclusion. It is concluded that the description of the structure of end-to-end REC competencies can be used to improve the competencies of professionals involved in the creation and promotion of world-class projects in the REC structure. The conditions that must be provided to achieve the designated goals are defined.
Intonation Characteristics of Singing Based on Artificial Intelligence Technology and Its Application in Song-on-Demand Scoring System

With the continuous progress of my country’s cultural industry, how to apply artificial intelligence technology to song on demand has become an issue of concern. This research mainly discusses the research of singing intonation characteristics based on artificial intelligence technology and its application in song-on-demand scoring system. This paper uses the combination of ant colony algorithm and DTW algorithm to measure the similarity between speech signals with the average distortion distance, so as to expect accurate recognition results. The design of the song-on-demand scoring function module uses a combination of MVC mode and command mode based on artificial intelligence technology. The view component in the MVC mode is mainly used to display the content that the user needs to sing and realize the interaction with the user. The singer selects a song to start playing, and the scoring terminal device queries the music library server for song information according to the song number, then starts playing the song through the FTP file sharing service according to the audio file path in the song information, and at the same time displays the song on the display according to the timeline Show song and pitch information. The singer sings according to the screen prompts. The microphone collects the voice signal and transmits it to the scoring terminal. After the scoring algorithm is calculated, the result is fed back to the screen in real time. The singer can view his singing status in real time and make corresponding adjustments to obtain a higher score. After the singing, the scoring terminal will display the final result on the screen to inform the user and upload the singing record to the server for recording. In the tested on-demand retrieval engine, the average hit rate of the top 3 has reached more than 90% under various humming methods, basically maintaining the high hit rate characteristics of the original retrieval engine. The system designed in this research helps to effectively improve the singing level.
EFFECTS OF BLOCKCHAIN TECHNOLOGY ON PERFORMANCE OF FINANCIAL MARKETS IN KENYA

Purpose: The study sought to establish the effects of blockchain technology on the performance of financial markets in Kenya.&#x0D; Methodology: The study adopted an explanatory research design. The study target population was drawn from the commercial banks located in Nairobi County, Kenya. The study targeted 84 bank managers in the IT and finance department of the 42 commercial banks in Kenya. Thus the target population of the study was 84 financial market managers selected. The study population was grouped into simple identifiable group called strata and adopted a stratified simple random sampling technique with inclusion of commercial banks. A sample size of a sample size of 50 respondents was arrived at. Data was collected using a structured questionnaire. The data collected was cleaned and coded, quantified and analyzed quantitatively. Quantitative data were analyzed using SPSS 24 where descriptive and inferential statistics were used to capture the data in order to understand the pattern and nature of relationships. Results were presented using tables.&#x0D; Findings: The study findings showed that the correlation analysis showed that the adoption of blockchain technology had a positive and significant correlation to government policy R = 0.240. Adoption of blockchain technology had a positive and significant correlation to internet infrastructure by R = 0.293. Adoption of blockchain technology had a positive and significant correlation to transaction cost at R = 0.583. Lastly, adoption of blockchain technology had a positive and significant correlation to risk analysis at R = 0.507.&#x0D; Unique contribution to theory, practice and policy: The study recommended that there should be policy review on issues relating to risk analysis so as to curb illegal money transfers and enhance performance of financial markets in Kenya. The study recommends for a thorough scrutiny by the government and ensures such issues are keenly analyzed to help bring peace and stability in the world. The aspect of having good internet connectivity is beneficial to the nation in that access to proper information will be available and it enables many users to have wide access to services as well as creation of employment. There is need to conduct a study on stability of blockchain technologies use and their impact to the economic growth. The study incorporated Technology Acceptance Model and Innovation Diffusion Theory to link the study topic to the concepts
Corruption, Government Effectiveness and Human Development in Sub-Saharan Africa

Aside economic factors causing low human development which have been extensively studied in literature, the implications of high level of corruption and weak governance prevalent in sub- Saharan African (SSA) countries have not been explored. The study assessed the effects of corruption, government effectiveness and their joint effect on human development in SSA. Data collected on thirty-seven (37) countries within the period of 2005 to 2018 were analyzed using system Generalized Method of Moment which was most suitable for the dataset. Results indicated that lagged human development index (P&lt;0.01), government effectiveness (P&lt;0.05), economic growth rate (P&lt;0.1) and government health spending (P&lt;0.1) had significant positive effect on human development while corruption and its interaction with government effectiveness did not. The results of Arrelano-Bond test of first order autocorrelation and second order autocorrelation of error term as well as the Sargan test and Hansen J test for validity of instrumental variables confirmed the validity of the model. The robustness of the estimation was established as the coefficient of the lagged dependent variable fell between the values in the fixed effect and pooled ordinary least square regression. The study recommended retraining and reorientation of government employees towards the mindset of effective service delivery and strong political will to achieve it, diversification of SSA economies alongside other growth stimulating policies such as reduced lending interest rate on loans meant for the real sector, improvement in the ease of doing business, improved funding of the health sector and proper monitoring of activities in the public service by concerned agencies to curb corruption where it is present.
A common parametrization for finite mode Gaussian states, their symmetries, and associated contractions with some applications

Let Γ(H) be the boson Fock space over a finite dimensional Hilbert space H. It is shown that every Gaussian symmetry admits a Klauder–Bargmann integral representation in terms of coherent states. Furthermore, Gaussian states, Gaussian symmetries, and second quantization contractions belong to a weakly closed self-adjoint semigroup E2(H) of bounded operators in Γ(H). This yields a common parametrization for these operators. It is shown that the new parametrization for Gaussian states is a fruitful alternative to the customary parametrization by position–momentum mean vectors and covariance matrices. This leads to a rich harvest of corollaries: (i) every Gaussian state ρ admits a factorization ρ=Z1†Z1, where Z1 is an element of E2(H) and has the form Z1=cΓ(P)exp∑r=1nλrar+∑r,s=1nαrsaras on the dense linear manifold generated by all exponential vectors, where c is a positive scalar, Γ(P) is the second quantization of a positive contractive operator P in H, ar, 1 ≤ r ≤ n, are the annihilation operators corresponding to the n different modes in Γ(H), λr∈C, and [αrs] is a symmetric matrix in Mn(C); (ii) an explicit particle basis expansion of an arbitrary mean zero pure Gaussian state vector along with a density matrix formula for a general Gaussian state in terms of its E2(H)-parameters; (iii) a class of examples of pure n-mode Gaussian states that are completely entangled; (iv) tomography of an unknown Gaussian state in Γ(Cn) by the estimation of its E2(Cn) parameters using O(n2) measurements with a finite number of outcomes.
Gradient-Sensitive Optimization for Convolutional Neural Networks

Convolutional neural networks (CNNs) are effective models for image classification and recognition. Gradient descent optimization (GD) is the basic algorithm for CNN model optimization. Since GD appeared, a series of improved algorithms have been derived. Among these algorithms, adaptive moment estimation (Adam) has been widely recognized. However, local changes are ignored in Adam to some extent. In this paper, we introduce an adaptive learning rate factor based on current and recent gradients. According to this factor, we can dynamically adjust the learning rate of each independent parameter to adaptively adjust the global convergence process. We use the factor to adjust the learning rate for each parameter. The convergence of the proposed algorithm is proven by using the regret bound approach of the online learning framework. In the experimental section, comparisons are conducted between the proposed algorithm and other existing algorithms, such as AdaGrad, RMSprop, Adam, diffGrad, and AdaHMG, on test functions and the MNIST dataset. The results show that Adam and RMSprop combined with our algorithm can not only find the global minimum faster in the experiment using the test function but also have a better convergence curve and higher test set accuracy in experiments using datasets. Our algorithm is a supplement to the existing gradient descent algorithms, which can be combined with many other existing gradient descent algorithms to improve the efficiency of iteration, speed up the convergence of the cost function, and improve the final recognition rate.
Professional Training Is An Incentive For Moral And Aesthetic Education

Each profession has its own characteristics, and the profession of a music teacher has its own secrets and requirements. The uniqueness of the professional competencies of the future teacher is reflected in the fact that they are aimed at enriching the inner world of students in the music sphere with spiritual values and content that are reflected in the works of musical art. Professional spiritual competences reflect the specificity and spiritual nature of the practice of musical pedagogy. Their formation is one of the most pressing problems inherent in the modern system of music education, and is a prerequisite for determining the effectiveness of the professional activity of a music teacher and his educational work with children.
On the Identification and Prediction of Stalling Events to Improve QoE in Video Streaming

Monitoring the Quality of user Experience is a challenge for video streaming services. Models for Quality of User Experience (QoE) evaluation such as the ITU-T Rec. P.1203 are very promising. Among the input data that they require are the occurrence and duration of stalling events. A stalling even5 is an interruption in the playback of multimedia content, and its negative impact on QoE is immense. Given the idiosyncrasy of this type of event, to count it and its duration is a complex task to be automated, i.e., without the participation of the user who visualizes the events or without direct access to the final device. In this work, we propose two methods to overcome these limitations in video streaming using the DASH framework. The first method is intended to detect stalling events. For simplicity, it is based on the behavior of the transport layer data and is able to classify an IP packet as belonging (or not) to a stalling event. The second method aims to predict if the next IP packet of a multimedia stream will belong to a stalling event (or not), using a recurrent neural network with a variant of the Long Short–Term Memory (LSTM). Our results show that the detection model is able to spot the occurrence of a stalling event before being experienced by the user, and the prediction model is able to forecast if the next packet will belong to a stalling event with an error rate of 10.83%, achieving an F1 score of 0.923.
Learning History Using Augmented Reality

Subject of history is one of the subject that must be passed in the SPM examination. Subjet of history is very important in our life as a guides and teaches us in how to progress and advance not making the same mistakes. We also must have deep knowledge about history of homeland so we can appreciate them and also make them all our idols. However, learning about history of homeland warrior can be challenging, especially for student who think that learning about history is boring and some student are less aware of the importance of studying history. For help teacher to teach and also attract student in learn about history, we are try to use Augmented Reality for make learning session fun. The research aims to design an application for learning history of homeland using Augmented Reality.
Game Technologies As An Innovative Type Of Student-Centered Education

The article examines the role and importance of the use of gaming technologies in the upbringing of preschoolers and one of the types of personality-oriented learning in the formation of their knowledge, skills and abilities.