Reviewerly/exHarmony huggingface dataset:
Deterministic Photon Storage and Readout in a Semimagnetic Quantum Dot–Cavity System Doped with a Single Mn Ion

Abstract Light trapping is a crucial mechanism for synchronization in optical communication. Especially on the level of single photons, control of the exact emission time is desirable. In this paper, a single‐photon buffering device composed of a quantum dot doped with a single Mn atom in a cavity is theoretically proposed. A method to detain a single cavity photon as an excitation of the dot is presented. The storage scheme is based on bright to dark exciton conversion performed with an off‐resonant external optical field and mediated via a spin‐flip with the magnetic ion. The induced Stark shift brings both exciton states to resonance and results in an excitation transfer to the optically inactive one. The stored photon can be read out on demand in the same manner by repopulating the bright state, which has a short lifetime. The results indicate the possibility to suspend a photon for almost two orders of magnitude longer than the lifetime of the bright exciton.
Integration of biosensor to a window-based control system for user emotion detection to static and dynamic visual contents of webpages

Purpose Basic capturing of emotion on user experience of web applications and browsing is important in many ways. Quite often, online user experience is studied via tangible measures such as task completion time, surveys and comprehensive tests from which data attributes are generated. Prediction of users’ emotion and behaviour in some of these cases depends mostly on task completion time and number of clicks per given time interval. However, such approaches are generally subjective and rely heavily on distributional assumptions making the results prone to recording errors. This paper aims to propose a novel method – a window dynamic control system – that addresses the foregoing issues. Design/methodology/approach Primary data were obtained from laboratory experiments during which 44 volunteers had their synchronized physiological readings – skin conductance response, skin temperature, eye movement behaviour and users activity attributes taken by biosensors. The window-based dynamic control system (PHYCOB I) is integrated to the biosensor which collects secondary data attributes from these synchronized physiological readings and uses them for two purposes: for detection of both optimal emotional responses and users’ stress levels. The method’s novelty derives from its ability to integrate physiological readings and eye movement records to identify hidden correlates on a webpage. Findings The results from the analyses show that the control system detects basic emotions and outperforms other conventional models in terms of both accuracy and reliability, when subjected to model comparison – that is, the average recoverable natural structures for the three models with respect to accuracy and reliability are more consistent within the window-based control system environment than with the conventional methods. Research limitations/implications Graphical simulation and an example scenario are only provided for the control’s system design. Originality/value The novelty of the proposed model is its strained resistance to overfitting and its ability to automatically assess user emotion while dealing with specific web contents. The procedure can be used to predict which contents of webpages cause stress-induced emotions to users.
Unsupervised domain adaptation with non-stochastic missing data

We consider unsupervised domain adaptation (UDA) for classification problems in the presence of missing data in the unlabelled target domain. More precisely, motivated by practical applications, we analyze situations where distribution shift exists between domains and where some components are systematically absent on the target domain without available supervision for imputing the missing target components. We propose a generative approach for imputation. Imputation is performed in a domain-invariant latent space and leverages indirect supervision from a complete source domain. We introduce a single model performing joint adaptation, imputation and classification which, under our assumptions, minimizes an upper bound of its target generalization error and performs well under various representative divergence families ( $$\mathscr {H}$$ -divergence, Optimal Transport). Moreover, we compare the target error of our adaptation-imputation framework and the “ideal” target error of a UDA classifier without missing target components. Our model is further improved with self-training, to bring the learned source and target class posterior distributions closer. We perform experiments on three families of datasets of different modalities: a classical digit classification benchmark, the Amazon product reviews dataset both commonly used in UDA and real-world digital advertising datasets. We show the benefits of jointly performing adaptation, classification and imputation on these datasets.
Fuzzy based Decision Support Model for Deciding the Students’ Academic Performance

— In the education domain, especially in higher education, a standard of performance assessment is determined by the grade point average (GPA). In its use in the evaluation process, GPA assessment standards have some shortcomings, such as focusing only on the improvement of the GPA value regardless of other factors that can affect an evaluation result, so that the GPA standard cannot be used as one and only one basic reference in determining the results of performance evaluation ideally. The study is a completed version of the previous one. The purpose of this study is to construct a decision support model (DSM) that can conduct performance assessment by considering various parameters that are considered to affect the academic performance results of students. The model was constructed by using three methods: fuzzy logic of Sugeno, conventional, and mathematical. This study uses quantitative data analysis because the data used is real data in the form of personal data and academic value data of students in the field. The predetermined methods were implemented in this study to calculate the academic performance value of students by considering various other parameters outside the GPA parameters. So that the assessment results will be more ideal and can strengthen the standard of GPA assessment in conducting the process of evaluating student performance. Also, finally, the verification and validation values of the model are represented.
Implementation of Fuzzy C-Means and K-Medoids in Grouping People's Welfare Indicators (Case Study in Riau Province in 2020)

Riau Province is one of the provinces that has social inequality in its society.This is due to the uneven distribution of development carried out in remote areas that are difficult for the government to access.Therefore, the researchers grouped districts in Riau Province with a low welfare index by clustering using Fuzzy C-Means and K-Medoids methods.Clustering is a method of grouping objects or events into groups based on their similarity values.Later, a comparison will be made between the Fuzzy C-Means and K-Medoids methods to get the best result on the Riau Province community welfare data in 2020.From the analysis that has been carried out, there is a grouping of data into 3 clusters for Fuzzy C-Means method and 2 clusters for K-Medoids.Based on the result of the variances comparison of the two methods, namely Fuzzy C-Means and K-Medoids, each of which has a variance of 0.375681 and 3.248903, it can be concluded that the best cluster method for this case is Fuzzy C-Means.Based on the results of clustering on districts/cities by Fuzzy C-Means method can be applied as a reference by related parties to improve the welfare of the people of the Riau province.
The Use of Thematic Progression in Writing: Hortatory Exposition Text at Second Grade Students of SMA Negeri 1 Elar

The objective of the research is to find out whether or not the use of Thematic Progression in Writing Hortatory Exposition text can improve the writing skill at the second grade students of SMA Negeri 1 Elar.This research employed pre-experimental method which one class was given pre-test, treatment and post-test.The population of this research was the second grade students of SMA Negeri 1 Elar.The total sample was 20 students and it used purpose sampling technique.The instrument was writing text in order to measure the students' writing skill in learning process by using Thematic Progression Writing Hortatory Exposition text.The result of the data showed that the implementation of Thematic Progression in Writing Exposition text was effective in improving the students' writing skill at SMA Negeri 1 Elar.In other words, the finding indicated that using Thematic Progression in Writing Exposition text technique in teaching writing was able to improve the students' writing skill.Based on the result of the data showed that there was a significant difference between the pre-test mean score (38.25) and post-test mean score (80.65).While the test value was higher than the t-table value (37.157>2.093)at the level of significant level 0.05 with the degree of freedom was 37. Based on the result of the data analysis, Thematic Progression in Writing Exposition text activity can improve the students' writing skill and it is an effective activity to make the students active in learning writing.It can be concluded that the use of thematic progression in writing hortatory exposition can be improved at SMA Negeri 1 Elar.
Transmission of coherent information at the onset of interactions

In this work, we investigate the parameters governing the rate at which a quantum channel arises at the onset of an interaction between two systems, $A$ and $B$. In particular, when system $A$ is pre-entangled with an ancilla, $\tilde{A}$, we quantify the early-time transmission of pre-existing entanglement by calculating the leading order change in coherent information of the complementary channel ($A\rightarrow B'$). We show that, when $A$ and $B$ are initially unentangled and $B$ is pure, there is no change in coherent information to first order, while the leading (second) order change is divergent. However, this divergence may be regulated by embedding the conventional notion of coherent information into what we call the family of $n$-coherent informations, defined using $n$-R\'enyi entropies. We find that the rate of change of the $n$-coherent information at the onset of the interaction is governed by a quantity, which we call the $n$-exposure, which captures the extent to which the initial coherent information of $A$ with $\tilde{A}$ is exposed to or `seen by' the interaction Hamiltonian between $A$ and $B$. We give examples in qubit systems and in the light-matter interaction.
CULTURE THROUGH THE PRISM OF EXPRESSIONIST TRADITIONS IN CINEMA ART OF THE XX-XXI CENTURIES (IMAGE OF GOLEM)

In this article, the author comes to the conclusion that the expressionist tradition in cinema quite adequately reflects the laws of the cultural development of society: creative figures throughout the twentieth and first 20 years of the twentyfirst century. periodically return to the Golem theme; his image remains relevant, since it embodies the idea of sometimes the only defense (from the outside) of a person helpless before the collisions of the surrounding world, which means that this latent fear of the world cannot be considered exclusively the property of the modernist worldview of the early twentieth century. Unshakable to this day, however, remains the moral law: in every film product, the Golem is subject to destruction as a godless substance, as an unsuccessful attempt by a person to stand on the same level with the Creator. At the same time, the image of the Golem in the history of cinematography is influenced by the historical situation and the constantly changing spiritual and aesthetic demands of the viewer associated with it. Mythological Golem in the XXXXI centuries. ceases to be slow and clumsy, and for its revival, neither an ecstatic mystical experience, nor a righteous man, nor a whole group of such (obviously, because in modern reality it is very problematic to find them): for more than 100 years in cinema, the mythical Golem from an earthen image, thanks to the director's vision, she gradually follows the path of her increasing "incarnation" and eventually turns into a fragile girl, now into an unhappy child.
Co-Evolutionary Paradigm of Ecological Education for Sustainable Development: Methodological Basis

Throughout the history of its development, environmental education has been viewed as a priority area in the modernization of all educational systems in the face of aggravated environmental problems. A comparative analysis of the change in environmental education paradigms made it possible to conclude that they evolved in accordance with the change in cognitive models and value-target guidelines: environmental education, environmental education and environmental education for sustainable development. On the basis of a generalization of philosophical, scientific, psychological and pedagogical research, the statement is substantiated that in the modern conditions of the global environmental crisis, the relevance and importance of developing the methodological foundations of environmental education based on a co-evolutionary strategy, which ensures the transition of mankind to the path of sustainable development, is obvious. The article reveals the methodological foundations of the co-evolutionary strategy of environmental education for sustainable development, which reflects the cognitive model, value co-evolutionary relations and the constructive coherent-creative orientation of nature-friendly activity. The co-evolutionary paradigm of environmental education for sustainable development, based on the ideas of synergy, reflects the picture of the world of a post-industrial society. The essence of co-evolutionary subject-activity, transdisciplinary, integrative and integrative-situational, cultural-ecological coherent-creative approaches is revealed. The conclusion is made about the semantic and value-worldview conjugation of these approaches, which ensures the integrity of the methodological foundations of the co-evolutionary paradigm of environmental education for sustainable development. The experience of the Nizhny Novgorod scientific school of environmental education in the implementation of the considered methodological approaches in environmental education for sustainable development is presented. The promising directions of research on this problem are formulated, related to the determination of the functional completeness of the methodological foundations and the development of methods for their implementation in educational practice. Keywords: co-evolutionary paradigm, environmental education for sustainable development, methodology
I-Voting System Based on Block Chain

The Blockchain based I-Voting uses a digital-currency analogy where in eligible voters can cast a ballot anonymously using a computing environment. BIV(Blockchain I-Voting) employs an encrypted key, smart biometrics and tamper proof real-time personal ID verification. Blockchain enable the creation of tamper-proof audit trails for voting. In this generation of Technology there is an effect way for casting vote through online(Digital Voting) to make a public electoral process faster, cheaper, and more easier. In this generation it is being a compelling one in modern society which removes a power barrier between the elected candidate and the voter.
Optimization and control of fuel cell thermal management system based on neural network

Aiming at the direct methanol fuel cell system is too complicated, difficult to model, and the thermal management system needs to be optimized. The article attempts to bypass the internal complexity of direct methanol fuel cell, based on experimental data, use neural networks to approximate arbitrarily complex non-linear functions ability to apply neural network identification methods to direct methanol fuel cell, a highly non-linear thermal management system optimization modelling. The paper uses 1000 sets of battery voltage and current density experimental data as training samples and uses an improved back propagation neural network to establish a battery voltage-current density dynamic response model at different temperatures. The simulation results show that this method is feasible, and the established model has high accuracy. It makes it possible to design the real-time controller of the direct methanol fuel cell and optimize the thermal energy manage?ment system?s efficiency.
Prospects for the application of active learning methods in modern education

The article examines the prospects for the application of active learning methods in modern education. The survey shows that the prospects for the application of active learning methods in modern education are conditioned by the influence of different factors. These factors can be divided into several groups: comprehensive organization of teaching, building adequate communication, the use of new learning technologies, organization of personality-oriented education and teamwork. The survey showed that there are real and potential barriers for teachers to use innovative teaching methods, but there is no serious paradox. There is no doubt that there is an intensive interest in the prospects and future of the application of active learning methods in modern education and their application in education. When choosing a teaching method, teachers' ability to use this method and local conditions should be considered.
Evaluation of classification performances of minimum spanning trees by 13 different metrics

Minimum Spanning Tree (MST) is a well-known clustering algorithm that provides a graphical tree representation of the objects in a data set by exploiting local information to link each pair of similar objects. The a-posteriori analysis of this tree in terms of nodes and edges provides the basis to derive simple classifiers, namely semi-supervised classification approaches based on the minimum spanning tree approach. In this work, we propose different metrics to evaluate the MST ability to group objects of the same a-priori known classes. The classification capability of the proposed approach, using 13 different distance measures, was compared with that of classical supervised classification approaches such as N-Nearest Neighbour (N3), Binned Nearest Neighbour (BNN), Partial Least SquaresDiscriminant Analysis (PLS-DA), K-Nearest Neighbour (KNN), exponentially weighted K-Nearest Neighbour (wKNN) and Support Vector Machine with radial functions (SVMRBF) on 31 data sets. The proposed approach resulted to be competitive and comparable with the considered classical supervised classification methods. Finally, we analysed the role of the 13 different measures in terms of performance and percentage of not-assigned objects.
The Use of Android Game to Improve Impaired Hearing Student Vocabulary Mastery

In general, problems that occur in the actual are the discovery of instruments that have not been tested for problem solving abilities. The aim of this research is to reveal the content validity and interrater reliability of the instrument for evaluating the problem solving abilities that have been prepared. The research method is used a quantitative description by 3 expert judgments, they are experts in research and evaluation, mathematics education experts, and mathematics teachers. The instrument was developed in the form of an expert observation sheet with 3 aspects of assessment, they are the aspect of content eligibility, construction aspects, and language aspects, which of each aspect has 4 categories, which are very relevant, relevant, quite relevant, and highly irrelevant. Data were analyzed using the Aiken's V formula to determine the level of instrument validity and to determine the level of consistency / constancy between assessors using Instraclass Correlation Coefficient (ICC) analysis with the help of SPSS version 23.0. the results of analysis of the content validity of all items valued above 0.3 which means that all aspects assessed by experts are valid. Interrater reliability test using ICC obtained a value of 0.516, which means that all aspects of the instrument for evaluating problem solving abilities that have been rated have a level of consistency. Thus, the instrument of problem-solving ability that has been tested for validity and reliability can be used by educators to determine the level of students' problem solving abilities appropriately
CNN-based Text-independent Automatic Speaker Identification Using Short Utterances

With the widespread use of voice-controlling services and devices, the research for developing robust and fast systems for automatic speaker identification had accelerated. In this paper, we present a Convolutional Neural Network (CNN) architecture for text-independent automatic speaker identification. The primary purpose is to identify a speaker, among many others, using a short speech segment. Most of the current researches focus on deep CNNs, which were initially designed for computer vision tasks. Besides, most of the existing speaker identification methods require audio samples longer than 3 seconds in the query phase for achieving a high accuracy. We created a CNN architecture appropriate for voice and speech-related classification tasks. We propose an optimum model that achieves 99.5% accuracy on LibriSpeech and 90% accuracy on VoxCeleb 1 dataset using only 1-second test utterances in our experiments.
Security and imperceptibility improving of image steganography using pixel allocation and random function techniques

Information security is one of the main aspects of processes and methodologies in the technical age of information and communication. The security of information should be a key priority in the secret exchange of information between two parties. In order to ensure the security of information, there are some strategies that are used, and they include steganography and cryptography. An effective digital image-steganographic method based on odd/even pixel allocation and random function to increase the security and imperceptibility has been improved. This lately developed outline has been verified for increasing the security and imperceptibility to determine the existent problems. Huffman coding has been used to modify secret data prior embedding stage; this modified equivalent secret data that prevent the secret data from attackers to increase the secret data capacities. The main objective of our scheme is to boost the peak-signal-to-noise-ratio (PSNR) of the stego cover and stop against any attack. The size of the secret data also increases. The results confirm good PSNR values in addition of these findings confirmed the proposed method eligibility.