Reviewerly/exHarmony huggingface dataset:
Singing and Nervous System Regulation Based on Wireless Sensor Network Perception

In order to build an intelligent platform that can be applied to singing and nervous system adjustment, this paper optimizes the positioning and information processing algorithms for wireless sensor network perception. Moreover, this article combines binocular vision to realize the singer’s real-time positioning, combines the singer’s emotion recognition with the intelligent sensor system, and combines the emotion recognition with the adjustment of the nervous system, so that the singer can better control the intelligent platform. In addition, in order to solve the problem of multisensor information fusion, this paper improves the sensor fusion algorithm to make it suitable for the information fusion of vision sensors and information sensors. Finally, this paper designs the functional structure of the system, transmits data through wireless sensor networks, simulates human emotion models, and studies the process of singing and the adjustment of the nervous system. It can be seen from the experimental research results that the method proposed in this paper has a certain effect.
Improving the Diagnosis of Breast Cancer Using Regularized Logistic Regression with Adaptive Elastic Net

Early diagnosis of breast cancer helpsimprove the patient's chance of survival.Therefore, cancer classification and feature selection are important research topics in medicine and biology.Recently, the adaptive elastic net was used effectively for feature-based cancer classification, allowing simultaneous feature selection and feature coefficient estimation.The adaptive elastic net basically employed elastic net estimates as the initial weight.Nevertheless, the elastic net estimator is inconsistent and biased in selecting features.Therefore, the regularized logistic regression with the adaptive elastic net (RLRAEN) was used to handle the inconsistency problem by employing the adjusted variances of features as weights within the L 1 -regularization of the elastic net model.The proposed method was applied to the Wisconsin Breast Cancer dataset of the UCI repository and compared to the other existing penalized methods that were also applied to the same dataset.Based on the experimental study, the RLRAEN was more efficient in terms of feature selection and classification accuracy than the other competing methods.Therefore, it can be concluded that RLRAEN is a better method in breast cancer classification.
Anadolu University Open Education Faculty Students’ Opinions on the Use of Artificial Intelligence Based Systems and Applications

This study aims to examine to what extent are the students aware of the AI based systems used in language learning.The design of the study was determined as a quantitative research method.For this purpose, a web-based questionnaire was applied to 204 students with A1 and A2 English levels enrolled in the Open Education Faculty, and thus data were collected about the students' views on Artificial Intelligence-based systems that they use to improve their English speaking and writing skills.The data obtained from the students were analyzed using descriptive statistical procedures such as frequency and percentage analysis.The findings of the study revealed that many of the distance education students do not have an idea whether AI-based applications have an effect on improving their English 'speaking' skills.It also showed that most students who participated in this study had no idea whether these practices had an effect on improving their English 'writing' skills.In this context, the study proves that students are limitedly aware of Artificial Intelligence-based systems used while learning foreign languages, and therefore, more studies on the subject should be conducted and these systems should be introduced to students.
Using quantum communications for maritime signal flags

Quantum communications are becoming very quickly a reality. There are huge advancement made in the field of quantum internet. Recently, IBM has announced the first commercial quantum computer with 20 qubits. Given all the advancements in the field, in this paper we investigate how quantum technologies can be applied in maritime communications. In this paper we address the problem of international maritime flag signals. More exactly, we proposed some quantum communication schemes for international maritime signal flags. We are also study the efficiency and security boost that quantum communications give in this type of maritime communication.
Blockchain Technology and Its Potential Effects on Accounting: A Systematic Literature Review

With the growth of the business world, autonomous software programs such as MRP, ERP, and SAP have been used to synchronize different units and departments since the 1960s. There have been great technological developments in the last decades, such as Blockchain, the Internet of Things, artificial intelligence, and machine learning. The attention of the accounting world has also been on those technological developments, especially on Blockchain Technology. Accounting academics and professionals have been trying to understand how blockchain technology can affect accounting and what kind of changes might be brought about by that technology. Therefore, the purpose of this study is to make a systematic literature review in order to foresee the potential effects of blockchain on accounting. Selected keywords were searched for on the Scopus database. The results show that most of the studies in this area focus on technical issues and the development of software applications, and a small number of studies make a connection between blockchain and accounting. Although most of the authors are very optimistic about blockchain technology and claim that this technology may change the double-entry accounting system completely and radically, some have discrete approach and express critical views.
DOMAIN SPECIFIC AUTOMATED ESSAY SCORING USING CLOUD BASED NLP API

The paper presents a methodology and an application framework (PUAnalyzeThis) that makes use of MeaningCloud API to automatically extract entities, concepts, relations, etc. and calculate scores and grades based on their relevance to a preliminary created topics graph. These topic graphs are either to be created by the teacher or automatically generated by scanning a certain amount of sample texts in the subject area. A prototype has been developed and tested with essays in the field of Computational Linguistics for informatics students at the University of Plovdiv “Paisii Hilendarski”.
Attributes that may raise the occurrence of merge conflicts

Collaborative software development typically involves the use of branches. The changes made in different branches are usually merged, and direct and indirect conflicts may arise. Some studies are concerned with investigating ways to deal with merge conflicts and measuring the effort that this activity may require. However, the investigation of factors that may reduce the occurrence of conflicts needs more and deeper attention. This paper aims at identifying and analyzing attributes of past merges with and without conflicts to understand what may induce direct conflicts. We analyzed 182,273 merge scenarios from 80 projects written in eight different programming languages to find characteristics that increase the chances of a merge to have a conflict. We found that attributes such as the number of changed files, the number of commits, the number of changed lines, and the number of committers demonstrated to have the strongest influence in the occurrence of merge conflicts. Moreover, attributes in the branch that is being integrated seem to be more influential than the same attributes in the receiving branch. Additionally, we discovered positive correlations between the occurrence of conflicts and both the duration of the branch and the intersection of developers in both branches. Finally, we observed that PHP, JavaScript, and Java are more prone to conflicts.
Constructing co-presence through shared VR gameplay

This study analyzes how participants playing VR games construct co-presence and shared gameplay. The analysis focuses on in­stances of play where one person is wearing the VR equipment, and other participants are located nearby without the ability to directly interact with the game. We first show how the active player using the VR equipment draws on talk and embodied activity to signal their presence in the shared physical environment, while simul­taneously conducting actions in the virtual space, and thus creates spaces for the other participants to take part in gameplay. Second, we describe how other participants draw on the contextual config­urations of the moment in displaying co-presence and position themselves as active and consequential co-players. The analysis demonstrates how gameplay can be communicatively con­structed even in situations where the participants have differential rights and possibilities to act and influence the game.
Analysis of Efficient Implementation of Elliptic Curve Cryptography Architecture for Resource Constraint Application

Elliptic Curve Cryptography is gaining attraction in providing a high security level in data transmission with low cost, small key size and smaller hardware realization. High-speed implementation is a significant factor in ECC applications such as smart cards, network servers, wireless sensor based networks, Internet of Things and Radio Frequency Identification. These applications require low-cost and lightweight implementations. In the resource constrain application, lightweight cryptography has emerged as the desired one because of limited energy in devices and the scarce computational resources. Design options and a wide range of parameters affect the overall implementation of the ECC system. Implementation target device, coordinate system, underlying finite fields and modular arithmetic algorithms are key design parameters that impact the overall implementation outcome. A statistical study is conducted on a large collection of published work based on the design parameters. The basic question that arises is how to select the appropriate flexibility-efficiency tradeoff. The subjects of generator, versatile, reconfigurable, dedicated and general purpose scalar multipliers are addressed. A review of various algorithms to perform scalar multiplication on prime and binary fields has been done more effectively. The results of ECC implementation on different FPGA platform is compared and analyzed with the various performance parameters. Besides, a classification of the previous works in terms of flexibility, performance, scalability and cost effectiveness is presented.
Motivating Factors Influencing Online Learning Among University Students: A Study of a Private University in Malaysia

The purpose of this study is to examine the motivating factors that influence online learning among university students during the Covid-19 pandemic era. Due to sudden transformation from traditional face-to-face learning approach to remotely digital learning, some present studies revealed that students’ motivation in online learning is probably the most important factor that educators can target to improve learning. There are four chosen independent variables in this study which are student’s participation, role of instructors, online learning environment and technical infrastructure affect online learning. This research uses a survey method where 150 questionnaires are distributed online. Then, the collected data are tabulated to analyze the findings and results.
Low-angle estimation using frequency-agile refined maximum likelihood algorithm based on optimal fusion

Low elevation estimation, which has attracted wide attention due to the presence of specular multipath, is essential for tracking radars. Frequency agility not only has the advantage of strong anti-interference ability, but also can enhance the performance of tracking radars. A frequency-agile refined maximum likelihood (RML) algorithm based on optimal fusion is proposed. The algorithm constructs an optimization problem, which minimizes the mean square error (MSE) of angle estimation. Thereby, the optimal weight at different frequency points is obtained for fusing the angle estimation. Through theoretical analysis and simulation, the frequency-agile RML algorithm based on optimal fusion can improve the accuracy of angle estimation effectively.
Joint activities and development of the creative potential of the personality of the future specialist

Introduction. Achieving a qualitatively new state of society largely depends on the formation of the creative potential of young specialists capable of transforming, developing and implementing original solutions to professional and personal tasks, in connection with which the development of mechanisms for the formation of a professional capable of transforming the world and oneself seems to be very relevant. The authors propose to organize joint activities to solve creative problems in the form of a system of training sessions for the development of the creative potential of the personality of students. Materials and methods. The study involved 200 junior students of Volgograd universities, boys and girls aged 18-20 years, humanitarian and natural science areas of training. The main statistical calculations were performed using the analysis of nonparametric data using the chi-square test for the analysis of frequency differences, as well as using the statistical Mann-Whitney U test. The results of the study. Statistically significant significant differences were revealed according to the Mann-Whitney U-test (at p &lt;0.05) between the values of the scales of the experimental and control groups of students according to the following indicators: the index of verbal originality (p = 0.033); the index of verbal uniqueness (p = 0.026); the number of responses produced (p = 0.008); striving for creativity and creativity (p = 0.026), expert assessment of creative potential (p = 0.041). The diagnostic indicators allowed us to conclude that students in the humanitarian areas of training more often demonstrate a high level of originality and productivity of verbal constructions, they are characterized by the spontaneity inherent in a self-actualizing personality. Students of natural science areas of training are more often looking for new ways of thinking, they have a more pronounced desire for self-development. Conclusions. Purposeful, organized joint activities in the form of training aimed at the formation of knowledge, skills and abilities of collective solution of creative problems, has shown effectiveness in solving the problem of developing the creative potential of future specialists.
Las redes sociales y su influencia en el desarrollo de habilidades sociales de los adolescentes

El presente trabajo investigativo tiene como objetivo conocer la relación entre el uso de redes sociales y el desarrollo de habilidades sociales en los adolescentes, teniendo en cuenta que las redes sociales son los medios de comunicación más utilizados por los adolescentes y que las habilidades sociales son competencias que les ayudan a actuar de manera eficaz en las relaciones interpersonales, así como también prevenir circunstancias problemáticas que se presentan en esta etapa del ser humano. Para ello se ha aplicado dos instrumentos, uno relacionado al uso de las redes sociales y otro respecto a las habilidades sociales, en estudiantes de unidades educativas fiscales y particulares de la ciudad de Ambato-Ecuador. Mediante la prueba estadística de Spearman (valor de -0,208) se puede afirmar que en el grupo de estudio existe una relación inversa en el uso de redes sociales y las habilidades sociales.&#x0D; PALABRAS CLAVE: redes sociales, habilidades sociales, adolescentes, unidades educativas.&#x0D; Social networks and their influence on the development of social skills of adolescents&#x0D; ABSTRACT&#x0D; The present research work is to know the relationship between the use of social networks and the development of social skills in adolescents, taking into account that social networks are the means of communication most used by adolescents and social skills are competences that help them to act effectively in interpersonal relationships, as well as prevent problematic circumstances that arise in this stage of the human being. For this, two instruments have been applied, one related to the use of social networks and the other regarding social skills, in students from fiscal and private educational units in the city of Ambato-Ecuador. Using the Spearman statistical test (value of -0.208) it can be affirmed that in the study group there is an inverse relationship in the use of social networks and social skills.&#x0D; KEYWORDS: social networks, social skills, adolescents, educational units.
Probabilistic Rule Induction for Transparent CBR Under Uncertainty

CBR systems leverage past experiences to make decisions. Recently, the AI community has taken an interest in making CBR systems explainable. Logic-based frameworks make answers straightforward to explain. However, they struggle in the face of conflicting information, unlike probabilistic techniques. We show how probabilistic inductive logic programming (PILP) can be applied in CBR systems to make transparent decisions combining logic and probabilities. Then, we demonstrate how our approach can be applied in scenarios presenting uncertainty.
Continuous-Variable Quantum Key Distribution Based on Heralded Hybrid Linear Amplifier with a Local Local Oscillator

An improved continuous variable quantum key distribution (CVQKD) approach based on a heralded hybrid linear amplifier (HLA) is proposed in this study, which includes an ideal deterministic linear amplifier and a probabilistic noiseless linear amplifier. The CVQKD, which is based on an amplifier, enhances the signal-to-noise ratio and provides for fine control between high gain and strong noise reduction. We focus on the impact of two types of optical amplifiers on system performance: phase sensitive amplifiers (PSA) and phase insensitive amplifiers (PIA). The results indicate that employing amplifiers, local local oscillation-based CVQKD systems can enhance key rates and communication distances. In addition, the PIA-based CVQKD system has a broader application than the PSA-based system.
Comparing Performance of Supervised Learning Classifiers by Tuning the Hyperparameter on Face Recognition

In this era, face recognition technology is an important component that is widely used in various aspects of life, mostly for biometrics issues for personal identification. There are three main steps of a face recognition system: face detection, face embedding, and classification. Classification plays a vital role in making the system recognizes a face accurately. With the growing need for face recognition applications, the need for machine learning methods are required for accurate image classification is also increasing. One thing that can be done to increase the performance of the classifier is by tuning the hyperparameter. For this study, the evaluation performance of classification is conducted to obtain the best classifier among four different classifier algorithms (decision tree, SVM, random forest, and AdaBoost) for a specific dataset by tuning the hyperparameter. The best classifier is obtained by evaluating the performance of each classifier in terms of training time, accuracy, precision, recall, and F1-score. This study was using a dataset of 2267 facial data (128D vector space) derived from the face embedding process. The result showed that SVM is the best classifier with a training time of 0.5 s and the score for accuracy, precision, recall, and F1-score are about 98%.
ANN and SVM algorithm in Divorce Predictor

Classification is a technique used to predict group membership or label for data samples (instances). In order to predict the result, the classification algorithm processes the training set, which contains a set of attributes and corresponding results. One of these classification technique is implemented in order to predict divorce in Turkey. This research is executed by Yöntem, M. K. et al. in 2019. In this , M. K. concluded that the ANN algorithm combined with correlation-based feature selection has the best performance with an accuracy of 98.82% and Kappa value of 0.9765. Nevertheless, unlike any previous research, ANN is not considered very good in terms of the required training time. In several previous studies, it was also concluded that other classification algorithms, such as SVM, have better prediction accuracy compared to ANN. In this study, prediction accuracy and Kappa value between ANN and SVM algorithms are compared using the same dataset and feature selection as the research done by Yöntem, M. K., to ensure a fair comparison between both of the algorithms. The result obtained from comparing both algorithms is that the SVM algorithm performs better than ANN with an accuracy of 99.8235 and a Kappa value of 0.9964. The training time required by SVM is also better than the ANN training time.
Analysis of Teachers’ Challenges in Teaching Speaking Through Online Learning during Covid-19 Pandemic in SMAN 2 Abiansemal

ABSTRACT&#x0D; This research aims at at finding out 1) the challenges of the teachers in teaching speaking during online learning in SMAN 2 Abiansemal, 2) the teachers’ ways to cope with the challenges in teaching speaking during online learning in SMAN 2 Abiansemal and 3) the strengths and the weaknesses of the strategy used by the investigated teachers during online learning in teaching speaking. The subjecs of this research were three English teachers in SMAN 2 Abiansemal. To collect the data, two instruments were needed, observation sheet and interview guide. The obtained data were analyzed qualitative by using Interactively Data Analysis Model by Miles and Huberman (1994). This research discovers 1) 9 challenges in online learning, 2) 9 ways to cope the challenges, and 3) 9 weaknesses and strengths of the strategy.
The application of discussion method for improving the students' logical thinking skills

This study aims to: 1) describe the conditions of Indonesian language learning for class XI students at Vocational High School 1 of BYL; 2) describe and explain the events of Cycle I and Cycle 2 in Indonesian language learning when using on-the-spot learning using the discussion method; 3) describe and explain the effectiveness of Indonesian language learning with conventional methods and deep discussion methods. This study used a classroom action research design with four steps, namely, 1) planning: 2) implementation; 3) observation; 4) reflection. In the initial step (planning) the researcher pays attention to things that are strategic towards the implementation steps that are carried out, then the researcher takes action to do things that need to be done in the next process, namely by collaborating with colleagues who are partners to discuss and help with implementation of action research is carried out, as well as trying to condition the learning in the classroom carried out in the research. The results of this study indicate that: (1) students need to work and learn together to decide something that is difficult when faced; (2) learning in a happy condition creates a safe, comfortable, calm, and controlled atmosphere; (3) The results of the effectiveness test show that learning using the discussion method results in better achievement than learning using conventional methods.