Reviewerly/exHarmony huggingface dataset:
From Understanding Genetic Drift to a Smart-Restart Mechanism for Estimation-of-Distribution Algorithms

Estimation-of-distribution algorithms (EDAs) are optimization algorithms that learn a distribution on the search space from which good solutions can be sampled easily. A key parameter of most EDAs is the sample size (population size). If the population size is too small, the update of the probabilistic model builds on few samples, leading to the undesired effect of genetic drift. Too large population sizes avoid genetic drift, but slow down the process. Building on a recent quantitative analysis of how the population size leads to genetic drift, we design a smart-restart mechanism for EDAs. By stopping runs when the risk for genetic drift is high, it automatically runs the EDA in good parameter regimes. Via a mathematical runtime analysis, we prove a general performance guarantee for this smart-restart scheme. This in particular shows that in many situations where the optimal (problem-specific) parameter values are known, the restart scheme automatically finds these, leading to the asymptotically optimal performance. We also conduct an extensive experimental analysis. On four classic benchmark problems, we clearly observe the critical influence of the population size on the performance, and we find that the smart-restart scheme leads to a performance close to the one obtainable with optimal parameter values. Our results also show that previous theory-based suggestions for the optimal population size can be far from the optimal ones, leading to a performance clearly inferior to the one obtained via the smart-restart scheme. We also conduct experiments with PBIL (cross-entropy algorithm) on two combinatorial optimization problems from the literature, the max-cut problem and the bipartition problem. Again, we observe that the smart-restart mechanism finds much better values for the population size than those suggested in the literature, leading to a much better performance.
Factor Analysis and Regression Prediction Model of Swimmers’ Performance Structure Based on Mixed Genetic Neural Network

With the development of economy, people put forward higher demands on material life and spiritual life, and sports have become an indispensable part of daily life. Ten km freestyle, although it has been started late, is loved by people all over the world, and it is getting more and more attention in the world of competitive sports. Through the theoretical research of 10 km freestyle, it can be seen that most of the research on this project is focused on the training, selection of materials, and how to improve the technique of crossing obstacles or pools, while the research on the performance of 10 km freestyle is limited to the analysis of the development trend of the performance and no research on the prediction of the actual performance, which to some extent restricts the scientific development of 10 km freestyle. The efficiency of a suitable learning is a factor that influences whether the training and learning of a BP neural network is stable or not. It can also directly determine the choice of weights. When the learning rate is chosen to be large, it increases the speed of learning and makes the stability of the network change. This has limited the scientific development of 10 km freestyle to a certain extent, and it is also a good entry point for the research of 10 km freestyle. BP neural network is one of the most widely used neural network models, which can be used for classification, clustering, prediction, and other related problems. In this study, we propose a comprehensive evaluation method of 10 km freestyle performance based on BP neural network and try to establish a neural network evaluation model by combining the athletes’ physiological and biochemical indexes and sports performance. In this study, the normalized index values are used as the network input, and the athletes’ performance in 10 km freestyle is used as the network output to predict the athletes’ performance in 10 km freestyle. This study provides a theoretical basis for adjusting the condition of 10 km freestyle athletes and improving their performance. Optimize the reasonable allocation of resources between coaches and athletes, and increase the opportunities for coaches and athletes to communicate and learn from outside.
FEATURES OF PROFESSIONAL BURNOUT IN THE TEACHERS-CHOREOGRAPHERS

The article is devoted to the features of professional burnout of choreographers, whose work is associated with intense physical and emotional stress, which combines the functions of a teacher, a choreographer and a tutor.The authors consider the burning out as a three-component system that includes psycho-emotional exhaustion, depersonalization and reduction of professional achievements.The peculiarities of the choreographers' pedagogical activity were considered which are related to their characteristics that contribute to the formation of the professional burnout phenomenon.The peculiarities of the three main structural components of the choreographer profession are analysed, which affect the level of neuropsychiatric violation, such as pedagogical activity, pedagogical communication, and personal qualities of a teacher-choreographer.The role of the global pandemic Covid-19, the distance learning, and high demands relating to the personality of the teacherchoreographer was separately considered, which could also be a prerequisite for professional burnout.This is because conducting distance lessons often takes more time, effort and energy from the teachers.It can be more stressful, due to lower involvement and return from students than in regular classes.The article is highlighted certain stressful features of pedagogical communication in the activities of a teacher-choreographer.It is also, noted the idea that the state of chronic emotional stress can lead to deformation of the emotional sphere of the teacher, a form of which is professional burnout.A rather high level of mental burnout in teachers was revealed, in the structure of which the leading role is played by the component of professional motivation; high level of neuroticism; high level of the inconsistency of significant values with the possibility of their implementation in professional activities; an average level of skills development and abilities of self-regulation; quite favourable socio-psychological climate and satisfactory nature Журнал «Перспективи та інновації науки» (Серія «Педагогіка», Серія «Психологія», Серія «Медицина») № 7(12) 2022 47 of the organization of teachers' professional activities.The main determinants that cause the emergence of occupational burnout have been identified and systematized, which include internal individual psychological and external socio-psychological factors.The authors prove the importance of the syndrome of professional burnout in choreographers, which is because their activities are related to the education, upbringing and development of children, the formation of the comprehensive and harmonious development of youth, and their abilities to achieve the highest values of society: human happiness, goodness, beauty and spiritual rebirth.
Performance of Contrast Adjustment in Face Recognition with Training Image under Various Lighting Conditions

The lighting factor has a very significant effect on facial recognition performance. To reduce the effect of this lighting factor, at the pre-processing stage the researchers used contrast adjustments to the image to improve facial recognition performance. The histogram equalization technique is generally used for contrast adjustment because of its excellent performance to normalize image illumination which is affected by lighting conditions. In this research, empirical experiments were carried out to determine the effect of contrast adjustment using histogram equalization on face recognition in more detail. This research aims to answer the question whether this technique can be used in all image lighting conditions or not. The Robust Regression method is used in this research to recognize faces, which in many cases have very good performance due to lighting factors. Experiments using images in the AR Face Database related to lighting factors. The testing process is carried out by comparing the results of face recognition using the histogram equalization technique in the pre-processing phase and face recognition without pre-processing in each lighting condition. The experimental results show that the use of the histogram equalization technique in pre-processing gives a better face recognition performance effect in low, medium and high lighting conditions. But in very high (extreme) lighting conditions, the use of the histogram equalization technique in pre-processing turns out to have a worse facial recognition performance effect, with an average accuracy of 93.17%, whereas without pre-processing it produces an average accuracy of 94 , 67%.
Machine learning Applications of Data Security and Privacy A Systemic Review

&lt;p&gt;&lt;em&gt;With the present day trends in technology, greater and more human beings rely on their non-public devices to preserve their sensitive information. Concurrently, the environment in which these devices are linked have grown to develop to be higher dynamic and complex. This opens the communicate of if the modern authentication techniques being used in these devices are reliable adequate to hold these user’s files safe. This paper examines the wonderful purchaser authentication schemes proposed to make larger the safety of great devices. This article is wreck up into two one of a variety avenues discussing authentication schemes that use each be- havioral biometrics or bodily layer authentication. This survey will discuss about every the advantages and challenges that show up with the accuracy, usability, and widespread safety of computing machine getting to recognize techniques in these authentication systems. This article pursuits to beautify in addition look up in this challenge by means of exhibiting the extra than a few existing day authentication models, their schematics, and their results.&lt;/em&gt;&lt;/p&gt;
Improved data clustering using multi-trial vector-based differential evolution with Gaussian crossover

&lt;p&gt;Many algorithms have been proposed to solve the clustering problem. However, most of them lack a proper strategy to maintain a good balance between exploration and exploitation to prevent premature convergence. Multi-Trial Vector-based Differential Evolution (MTDE) is an improved differential evolution (DE) algorithm that is done by combining three strategies and distributing the population between these strategies to avoid getting stuck at a local optimum. In addition, it records inferior solutions to share information about visited regions with solutions of the next generations. In this paper, an Improved version of the Multi-Trial Vector-based Differential Evolution (IMTDE) algorithm is proposed and adapted for clustering data. The purpose here is to enhance the balance between the exploration and exploitation mechanisms in MTDE by employing Gaussian crossover and modifying the sub-population distribution between the strategies. To evaluate the performance of the proposed clustering, 19 datasets with different dimensions, shapes, and sizes were employed. The obtained results of IMTDE demonstrate improvement in MTDE performance by an average of 12%. Our comparative study with state-of-the-art algorithms demonstrates the superiority of IMTDE in most of these datasets because of the effective search strategies and the sharing of previous experiences in generating more promising solutions. Source code is available on Github: https://github.com/parhamhadikhani/IMTDE-Clustering.&lt;br&gt; &lt;/p&gt;
ASSESSING STUDENTS' CONSECUTIVE INTERPRETING QUALITY (A CASE STUDY IN ENGLISH LITERATURE STUDY PROGRAM)

This research aims to assess the quality of students’ consecutive interpreting in terms accuracy, fluency, and acceptability in English Literature study program, Faculty of Adab and Humanities, UIN Sunan Gunung Djati Bandung. This research uses qualitative case study method with the results that shows 153 data from 10 students that have interpreted the messages consecutively. In terms of accuracy, there are 137 (89.56%) data were transferred accurately, 11 (7.18%) data were transferred less accurately, and 5 (3.26) data were transferred inaccurately. In terms of fluency, there are 125 (81.69%) data were transferred fluently, 25 (16.33%) data were transferred less fluently, and 3 (1.98%) data were not transferred fluently. Meanwhile, in terms of acceptability there are 128 (83.66%) data were transferred acceptable, 20 (13.07%) data were transferred less acceptable, and 5 (3.27%) data were transferred not acceptable. This research shows students are having considerable skill in interpreting the messages from source language into the target language consecutively.&#x0D; Keyword: Accuracy, Fluency, Acceptability
Facilitating EFL Students’ Development of Speaking Skills through Cue Card Media

This paper aims to investigate the use of Cue Card Media to facilitate the improvement in the English speaking competence through storytelling based on the recount text at the grade 10 students of SMK 1 public vocational high school using Cue Card Media. This Classroom Action Research employed four main stages by Kemmis and McTaggart’s (2014) model, including planning, action, observation, and reflection. The present proposed CAR study was undertaken at the SMK 1 public vocational high school Gorontalo as the site for this study, with the grade ten students majoring the program stream of travel business or Usaha Perjalanan Wisata (henceforth UPW) being the subject of this study. The data in this research were collected by using several instruments, to include checklist observation, questionnaire, and speaking test. Further, the analysis reports of this CAR study relied heavily upon the qualitative interpretation, whilst quantitative served to strengthen the qualitative data interpretations. The results found that the application of the Cue Card successfully enhanced students’ speaking skills by 26.28% statistically, with 55.56% in the first cycle and 81.84% in the second cycle. Following the open-ended survey questionnaires, it appeared that due to the efficacy of Cue Cards, these attractive speaking media benefitted students when it comes to speaking performance activities, yet the drawbacks of Cue Card learning media in speaking were also recognized. Discussions as to how Cue Cards may develop the practice of speaking instruction were also provided. This study adds to the growing pool of literature on the Cue Card implementation in the teaching of speaking skills in English.
The focus system in Hadiyya

Abstract This study identifies, analyses and describes the devices and functions of focus in information structuring in Hadiyya, a Highland East Cushitic language. Data, which were collected from native speakers, were dealt with based on the theory of Functional Grammar (Dik 1997). For focalization, the language uses morphological, lexical and syntactic means. The latter involves word-order change and cleft construction (including pseudo-cleft). Comparatively, the morphological mechanism is the most dynamic and frequent in use while the lexical means is limited both in the number of items employed and in frequency of occurrence.
Design of the Wearable Gadget for Motion Controlling of Electrical Standing Wheelchair for Disable People

Design of the Wearable Gadget for Motion Controlling of Electrical Standing Wheelchair for Disable People
The Effect of Reciprocal Teaching Strategy on the Fourth ‎Preparatory School Students’ Reading Comprehension ‎Performance and Retention

There are two aims in the present study. The first is to find out the effect of reciprocal teaching strategy on reading comprehension performance of EFL preparatory school students. The second is to check out the effect of the same strategy on Students’ retention of the reading texts. This study is limited to the fourth scientific preparatory school students in the city of Ramadi during the first course of the academic year 2019-2020. Two hypotheses are set. The first assumed that there is no significant difference between the mean score of the experimental group and the mean score of the control group in the post reading comprehension performance test at the level (0.05) of significance. The second hypothesis states that there is no significant difference in the mean scores of the reading retention test between the experimental group and the control at the (0.05) level. The selected sample includes 72 students who have been selected randomly. The sample is distributed over two groups (36 for the experimental group) and (36 for the control group) after equalizing. The experimental group is taught reading comprehension material according to reciprocal teaching method. The researcher depends on a reading comprehension test to be the main instruments for collecting data and has been exposed to jury members. After the final applications of both tests, results concerning the first hypothesis show that there is a significant difference in the mean scores of the performance test between control and experimental group in favour of the experimental group. Also, the results about the second hypothesis reveal that there is a significant difference in the mean scores of the reading retention test of the experimental group upon the control group. Finally, conclusions and recommendations are set.
SYNTAX

SYNTAX questions technological idealism in an age of ecological disruption and data-driven exploitation. The collaboration includes a series of eight animated, graphic scores designed to guide the two composers through a generative narrative of improvised sound.
THE USE OF CLOUD SERVICES AND EDUCATIONAL PLATFORMS IN THE LEARNING PROCESS OF PEDAGOGICAL UNIVERSITY

The article analyzes the educational platforms, cloud technologies and web services most commonly used by future teachers. The opinion of prospective teachers about the opportunities provided by educational platforms, interactive learning technologies, web services for the teacher in the context of e-learning is given. The author presents the results of the survey of Altai State Pedagogical University students on the features of the use of modern educational technologies, cloud services and electronic educational content in the educational process. The article focuses on the needs of future teachers in mastering e-learning technologies, in particular, the use of educational platforms and electronic educational content in the modern digital educational environment.
Calculation and Function of Composition Proportion in Photography Based on Digital Information Technology

In order to take better pictures, a method of composition proportion in photography based on digital information technology is proposed. Feature extraction is carried out from the captured pictures, and the modular customized design of digital information technology is adopted. The research is carried out in the two fields of image blur and approximate repeated image de redundancy. An improved image blur algorithm based on bag of words (bag of words) kernel function is proposed. The experimental results show that the coarse matching time is the time spent in matching a query image with thousands of images in the database, and the fine matching time is the time spent in matching a query image with eight candidate images with orb. The total query time is about 0.7 seconds, while it takes about 500 seconds to match thousands of images only with orb algorithm. In general, we combine coarse matching and fine matching, which can balance the accuracy and speed well. It is proved that the digital information technology proposed in this paper has a good effect in the calculation and function of composition proportion in photography.
Wi-Fi And Bluetooth Contact Tracing Without User Intervention

A custom Wi-Fi and Bluetooth contact tracing system is created to find detailed paths of infected individuals without any user intervention. The system tracks smartphones, but it does not require smartphone applications, connecting to the routers, or any other extraneous devices on the users. A custom Turtlebot3 is used for site surveying, where it simulates mobile device movement and packet transmission. Transmit power, receive power, and round trip time are collected by a custom ESP32C3 router. MAC randomization is defeated to identify unique smartphones. Subsequently, the wireless parameters above are converted to signal path loss and time of flight. Bidirectional long short term memory takes the wireless parameters and predicts the detailed paths of the users within 1 m. Public health authorities can use the contact tracing website to find the detailed paths of the suspected cases using the smartphone models and initial positions of confirm cases. The system can also track indirect contact transmissions originating from surfaces and droplets due to having absolute positions of users.
Quantum algorithm for learning secret strings and its experimental demonstration

In this paper, we consider the secret-string-learning problem in the teacher-student setting: the teacher has a secret string $s\in {\{0,1\}^{n}}$, and the student wants to learn the secret $s$ by question-answer interactions with the teacher, where at each time, the student can ask the teacher with a pair $(x, q) \in {\{0,1\}^{n}}\times\{0,1,\cdots, n-1\}$ and the teacher returns a bit given by the oracle $f_{s}(x,q)$ that indicates whether the length of the longest common prefix of $s$ and $x$ is greater than $q$ or not. Our contributions are as follows. (i) We prove that any classical deterministic algorithm needs at least $n$ queries to the oracle $f_{s}$ to learn the $n$-bit secret string $s$ in both the worst case and the average case, and also present an optimal classical deterministic algorithm learning any $s$ using $n$ queries. (ii) We obtain a quantum algorithm learning the $n$-bit secret string $s$ with certainty using $\left\lceil n/2\right\rceil$ queries to the oracle $f_s$, thus proving a double speedup over classical counterparts. (iii) Experimental demonstrations of our quantum algorithm on the IBM cloud quantum computer are presented, with average success probabilities of $85.3\%$ and $82.5\%$ for all cases with $n=2$ and $n=3$ , respectively.
Automated Construction Payment Using Blockchain-Enabled Smart Contracts and Building Information Modelling

The potential of blockchain in the construction sector has been recognized in existing literature, as well as its capacity to be integrated into construction projects to automate financial transactions for increased transparency, security, and control. Permissioned blockchain, according to existing research, can be utilized to create a business network among project participants due to its features being compatible with the nature of the construction sector. This article lays out a framework for introducing permissioned blockchain technology, notably Hyperledger fabric, into the construction delivery process. The suggested framework comprises explicit procedures that show how to develop a network during the pre-construction, construction, and closeout stages. The suggested framework also displays the flow of financial transactions across the envisaged financial system. Because of the capabilities of Building Information Modelling/Management (BIM) and cost planning. As a result, the framework determines the data needed to enter the blockchain financial system from 4D/5D BIM. The benefits of employing blockchain in the construction business were emphasized in a systematic literature review, which also selected the best blockchain platform. The framework can also be used by academics and industry practitioners to recognise the architecture of smart contracts (chaincode) in the construction sector, such as formulating endorsement and validation policies. Finally, the findings of this article will be used to develop a proof-of-concept prototype that will be used to test and confirm the suggested conceptual framework's applicability using a real-world case study.