Reviewerly/exHarmony huggingface dataset:
Examples of Concepts Representations in the Main Content Lines of an Alternative Course of Mathematics in High School

The article considers an example of building a course for correcting knowledge in mathematics obtained in high school when moving to a university. The purpose of the experiment is to introduce students to the university course of mathematics with a parallel repetition of those sections of school mathematics that determine the success of mastering the university program. The developed course implements the following methodological approach — the creation of integral teaching materials that combine various representations of mathematical concepts. The integrity of such teaching materials is manifested in the use of connections between mathematics and theoretical informatics, the connections of various sections of mathematics with each other using a variety of computer tools available to schoolchildren. The possibilities of dynamical geometry are analyzed and discussed in detail when the concept of derivative is introduced.
Underwater distorted image restoration algorithm based on compressed sensing and centroid method

Imaging of static scenes under water is widely used in underwater detection technology. Aiming at the problem of severe distortion of underwater scene images caused by water surface fluctuations. An underwater distorted image restoration algorithm based on compressed sensing and centroid method is proposed. First, track the significant feature points between video frames to obtain the displacement trajectory of the feature points, then use the compressed sensing algorithm to reconstruct the motion vector field of the entire image to eliminate the periodic distortion of the image. Further, on this basis, the dense optical flow between the images is calculated to construct the centroid of the image sequence, thereby eliminating the randomness distortion that may exist in the image. The experimental results show that compared with the current mainstream restoration methods, the algorithm can ensure that the restored image has high definition while eliminating image distortion, and it performs well in some image quality evaluation indicators.
Multi-scale rotating target detection in high resolution remote sensing image based on improved YOLOv5

As the remote sensing image information rapidly becomes abundant, it is a challenge for the detection of tiny targets with dense distribution. Therefore, a multi-scale rotating object detection model based on the improved YOLOv5 is proposed in this paper. Firstly, because of adding a prediction feature layer to the network, the detection precision of tiny targets has substantially increased. Secondly, the loss between rotation anchors can be fitted at a high precision due to the compressed loss function aiming at the calculation of the IoU loss of rotation is proposed. Finally, a hybrid prior bounding box strategy is applied in the feature prediction layer to suit the targets to be detected in different sizes. Experiments conducted on the DOTA dataset indicates that this method significantly exceeded the original YOLOv5. It has extraordinary performances for the task of object detection in optical remote sensing image fields.
A superglue image registration algorithm based on adaptive dynamic attention mechanism

To improve image alignment quality, we propose a SuperGlue-based image alignment algorithm, which is an adaptive dynamic graph attention mechanism. The method first uses a deep learning method (SuperPoint) for feature point extraction to get the position, confidence, and encoding vectors of feature points. Next, a multilayer perceptron is used to embed the position, confidence, and encoding vectors together into a high-dimensional vector, and then the information of neighboring points is aggregated using an adaptive attention mechanism to make its node representation vector unique. Meanwhile, to avoid the performance impairment caused by full connectivity, the information range of aggregation is adaptively decayed according to the number of extracted feature points and the number of iterative layers. As the number of layers increases, the information is continuously passed, the graph is continuously updated, and finally the descriptors with unique properties are obtained. Finally, the matching results are obtained by solving the score matrix. The experimental results show that the image alignment quality of our method is improved over previous image alignment algorithms.
UAV-based panoramic scene recognition utilizing discrete spherical image features

Vision scheme based on the unmanned aerial vehicle (UAV) has gained widespread attention in recent years. Nevertheless, on account of the limited field-of-view of traditional images, it is difficult to apply to the fields that require comprehensive visual information. Therefore, a novel visual scheme based on the UAV platform with panoramic images is proposed in this paper, in which a platform consists of the panoramic cameras and the unmanned aerial vehicle are innovatively established and a scene recognition method based on discrete spherical image features are implemented. For the sake of reducing the distortion of panoramic image, we propose an icosahedron-based panoramic image representation for feature extraction, and then combined with the convolutional neural network and support vector machine, recognition task of the real image captured by the UAV platform are accomplished. Compared with the most widely used representation, namely the equirectangular projection, the proposed method can improve the recognition accuracy by 13.64% based on the Panoramic Scene dataset. Besides, our method can obtain a better performance even under the condition of large noise. Therefore, the proposed UAV-based panoramic scene recognition method can be applied to the fields that require comprehensive visual information effectively.
Privacy Protection for Cloud Based Online Transaction Using Steganography &amp; Visual Cryptography

In the present days, we are moving towards modern technologies of cashless transactions.Whenever we are doing online transactions, some data is produced.Day by day the production of data is increased to manage such data cloud computing is the best solution, it is based on pay as per use strategy, but while sharing the personal data in cloud environment security is important issue and this can be solved by using Steganography and visual cryptography.In this study, we are providing secure solution for the online transaction with the combination of steganography and visual cryptography by introducing new certified authority in between the customer and merchant.The certified authority prohibits the merchant to access and store the customer's confidential data.
The Moderating Effect of Career Adaptability in the Influence of University Students' Self-directed Learning Ability on Creative Convergence Competency

The purpose of this study is to verify the moderating effect of career adaptability in the effect of university students' self-directed learning ability on creative convergence competency. To achieve the purpose of this study, 172 university students were surveyed on self-directed learning ability, career adaptability, and creative convergence competency. The research method conducted multiple regression analysis to find out the effect of self-directed learning ability and career adaptability on creative convergence competency, and then used PROCESS Macro V3.5 Model 1 to verify the moderating effect of career adaptability, and Bootstrapping to analyze statistical significance. The results of the study are first, it was found that university students' self-directed learning ability and career adaptability had a significant effect on their creative convergence competency. Second, it was found that career adaptability controls the effect of self-directed learning ability on creative convergence competency. The results of this study suggest that educational efforts are needed not only to improve university students' creative convergence competency but also to help university students adapt well to the changing career environment.
An Efficient Unsupervised Approach for OCR Error Correction of Vietnamese OCR Text

Different types of OCR errors often occur in OCR texts due to the low quality of scanned document images or limitations in OCR software. In this paper, we propose a novel unsupervised approach for OCR error correction. Correction candidates for OCR errors are generated and explored in their neighborhoods using correction character edits controlled by an adapted hill-climbing algorithm. Correction characters are extracted from only original ground truth texts, which do not depend on OCR texts in training data. A weighted objective function used to score and rank correction candidates is heuristically tested to find optimal weight combinations. The proposed model is evaluated on an OCR text dataset originating from the Vietnamese handwritten database in the ICFHR 2018 Vietnamese online handwritten text recognition competition. The proposed model is also verified concerning its stability and complexity. The experimental results show that our model achieves competitive performance compared to the other models in the ICFHR 2018 competition.
Virtual and Augmented Reality for Building

Virtual reality and augmented reality have reached a technological maturity, allowing them to bring added value in many fields of activity [...]
THE STUDENTS’ DIFFICULTIES ON THE USE OF ADJECTIVE PHRASE IN WRITING ENGLISH TEXT

This study aimed at finding out: (1) What are the students’ difficulties on the use of adjective phrase in writing English text, (2) What are the factors that make students difficult in writing adjective phrase. The method of this research was descriptive quantitative method. Based on the results researcher found the students’ difficulties on the use adjective phrases those are intralingua error and interlingua error. Intralingua error consisted of 41 items or,87.23% students have difficulty in intralingua errors, while interlingua error consisted of 6 items or 12.76% students have difficulty in interlingua errors. Based on the types of adjective phrases, there were 12 items or 25.53% of students have difficulty using predicative adjectives and there were 35 items or 74.46% of students having difficulty using attributive adjectives. The factors that make difficult for students to write adjective phrases in writing are grammatical weaknesses, knowledge, understanding, lack of training and educational background. It can be concluded that there were two students’ difficulty on the use of adjective phrase and 4 factors that make students difficult to make adjective phrase.
Accounting Information System for Processing Zakat Funds at the North Sumatra National Amil Zakat Agency is Online Based

Zakat institutions are institutions that are in the midst of the public, so they are required to have transparency and accountability. In carrying out its activities as an amil, zakat processing organizations have principles that must be obeyed, including zakat processing organizations must have an accounting system and financial management. Audits, as well as publications. These three principles indicate that zakat fund management organizations must be transparent in carrying out their duties. This study aims to determine and examine the application of zakat accounting and accounting policies used by the national amil zakat agency. Provides an overview of the application of zakat accounting in the academic world. To solve this problem, the most effective solution is made, namely a web-based information system. In developing this application using the waterfall method. For the data flow method using UML (Unified Modeling Language) for data modeling using ERD (Entity Relationship Diagram) to describe the data model. With the development of this web-based information system, it aims to build a personal service process for institutions and facilitate the processing of zakat funds so that information regarding services and distribution is conveyed properly to institutions
Exploring the Influence of Absorptive Capacity on Innovation: An Empirical Study of Large Industrial Companies in Syria

This paper investigates the impact of absorptive capacity on exploratory innovation in large industrial companies in Syria. The study employs a sample of 278 managers, and utilizes multiple regression analysis for the investigation. The results reveal a significant positive relationship between absorptive capacity and exploratory innovation. These findings highlight the importance of absorptive capacity as a strategic tool for enhancing exploratory innovation, and offer valuable insights for managers and policy-makers in industries facing dynamic and complex environments.
Countermeasures for the development of industry-based university foundations in the new era

The report of the 20th National Congress of the Communist Party of China points out that education, science and technology, and talent are the basic and strategic support for the construction of a modern socialist country in all respects. It has pointed out the direction and development path for the development of universities as well as university foundations. Starting from the history, current situation and future development of university foundations, this paper proposes to fully understand the great significance of the new era and enhance the sense of mission in the work of university foundations; to deeply understand the connotation of the work and continuously deepen the understanding of the regularity of university foundations; to accurately grasp the development trend of the industry and continuously create a new situation for the development of university foundations. The industry-based university foundations should take the spirit of the 20th National Congress as the guide, combine the characteristics and discipline advantages of the university, focus on improving the quality of talent cultivation, scientific research and innovation level, and social service capacity, take multiple measures to comprehensively improve the governance capacity and contribute to the construction of a leading education country.
Computational Social Sciences Issues

This chapter defines a Discrete-Time and Continuous-Time Markov Chain Process aimed to identify the language used to write a text. This is a brief introduction to show the usefulness of both random walks in the recognition of a language, and how these methods can lead to deepen the recognition using other possible structural language. An example is established and solved from diphthongs of the English language
How Male Default Has Impeded Gender Equality through the Emojis

Living in a digital age, people conduct the majority of their communication online. Online communication is not only an outlet for expression but a vessel for different ways of expression. One such tool for expression is emojis. However, this type of online communication does not exclude the fact there is default male bias that before 2016 excluded women. The paper seeks to help readers understand the male bias and how it has impacted internet users, especially women. This paper investigates gender inequality in the form of digital communication. This research was conducted through reading other research papers and information regarding the history of emoji communication and making a recommendation for the next steps by compiling all existing data for emojis. It can be concluded that the idea of "male default" has been demonstrated in the design of emoji expression and has impeded the advancement of gender equality.
Service Quality Dimensions and Student Satisfaction during the Covid-19 Pandemic among Selected Higher Education Institutions in Manila, Philippines

Many private schools are greatly affected by the impact of the COVID-19 pandemic and as a result, many HEIs decided to shut down their school operations such as College of Holy Spirit Manila, Colegio de San Lorenzo, and Kalayaan College. Low student retention is the main reason for its permanent closure and based on the previous study, student satisfaction with service quality can increase customer loyalty for continuous patronage. The study assesses student satisfaction in the SQD using the Modified SERVQUAL Model among the selected HEIs in Manila, Philippines during the COVID-19 pandemic. The main objective of the study is to provide updated data information regarding student satisfaction to help both participating and non-participating schools continuously improve the service quality for students. The 366 survey respondents and 12 interview participants are 3rd years and 4th-year undergraduate students from the selected private HEIs in Manila, Philippines. The research design is descriptive research and used the mixed method technique to assess student satisfaction in the service quality dimensions for both academic and non-academic services. The homogeneous purposive sampling technique is used to select and recruit participants with shared characteristics such as the same year levels which are the 3rd year and 4th year undergraduate students who have more knowledge, experience, and exposure to the services of the university for both academic and non-academic services. Kruskal Wallis test and Mann Whitney are used for statistical data analysis and hypothesis testing. In the quantitative part of the study, the empathy dimension is the lowest SQD among selected HEIs in Manila. Therefore, it is recommended that university administrators establish a TQM service culture with an emphasis on genuine connection. In the thematic analysis, the reliability dimension with academic teaching ineffectiveness got the highest frequency among negative sub-themes. Therefore, it is recommended for academic heads to reconduct a faculty development program with an emphasis on advanced teaching effectiveness. Keywords: Service Quality Dimensions, Student Satisfaction, Higher Education Institutions, Mixed Methods, Philippines
Will Innovation, Training, and IT Support Moderate IT Investments in a Mandated Environment, Such as in a Covid-19 Era, to Create Value for Students in a Tertiary Educational Setting?

Objectives: To examine the creation of Value from IT investments for tertiary students.The focus was to use the complementary assets (Innovation, Training, and IT Support) as moderating variables for the relationship between IT investments and value creation in a mandated (Covid-19 setting) tertiary educational setting.Methods: One of the leading universities in Ghana was used as the object of study.A google form questionnaire was sent to the student body, and 508 responses were received.Smart PLS was used to analyze the responses.Findings: The results revealed that even though there was some level of interaction between the complementary assets (Innovation, training, IT Support) and IT investments, none of them had a significant effect on IT Value (Training > IT VALUE, p = 0.412; Innovation > IT VALUE, p = 0.371; IT Support > IT VALUE, p = 0.417).It was also revealed that IT investments was significantly correlated with IT Value (IT INVESTMENTS > IT VALUE, p = 0.000), confirming the insignificance of the moderators.In other words, the IT investments alone created value for the students.Novelty: The study is one of the early studies in IT value creation beyond IT investments in a mandated tertiary educational setting.In this study, it is evident that students in a mandated environment, such as in the case of Covid-19, where students are mandated to use the LMS and other IT infrastructure, will find their way out to create value for themselves once the IT infrastructure is in place; complementary assets may not be too necessary.
The emotional intelligence development of future English language teachers

This article presents a methodology for intelligence development based on the premise of emotive units at the lexical-phraseological level and the emotive content of professional-oriented texts. The methodology of emotional intelligence development for future English language teachers is based on the provisions of the emotional-conceptual approach which includes three stages of teaching: nomination, description and expression of emotions by means of a foreign language. Each stage involves four levels of teaching: presentation, practice, production and assessment. The content of emotional intelligence in ELT includes: subject, procedure and outcome components. Our significant achievements are qualitative and quantitative indicators of the general communicative and professional-communicative aspects of students’ emotional intelligence development. The purpose of the article is to create a scientifically-based methodology for the emotional intelligence development of future foreign language teachers in the process of professionally-oriented education. The objectives of the article are to: substantiate the structural-content and functional characteristics of emotional intelligence; create a methodology for emotional intelligence development in foreign language teachers and define qualitative and quantitative indicators of emotional intelligence development.
Debugging the Karmabug

Debugging the Karmabug For reasons I will not go through right now, I needed a new library for making synchronous HTTP requests in Node.js. I know what you are saying, “But that’s one of the seven deadly sins of JavaScript!” &lt;sup&gt;1&lt;/sup&gt; Well, just know I had my reasons, and I wanted to replace sync-request. Since I was already using the Fetch API with node-fetch in the async part of my library, I thought: why not build a sync-fetch, using node-fetch under the hood like sync-request uses (then-)request. Two days later, it was actually working, as far as I could tell.
KHiTE: Multilingual Speech Acquisition to Monolingual Text Translation

Objectives: To develop a system that accepts cross-lingual spoken reviews consisting of two to four languages, translate to target language text for Indic languages namely Kannada, Hindi, Telugu and/or English termed as cross lingual speech identification and text translation system.Methods: Hybridization of software engineering models are used in natural languages for pre-processing such as noise removal and speech splitting to obtain phonemes.Combinatorial models namely Hidden-Markov-Model, Artificial Neural Networks, Deep Neural Networks and Convulutional Neural Networks were deployed for direct and indirect speech mapping.Trained corpus consisting of thousand phonemes in the form of wave files for each language considered is named as KHiTEShabdanjali.The basic parameters cosidered for training dataset are pause, pitch, sampling frequency, threshold etc. Findings: The research has resulted in the development of mono-lingual and multi-lingual speech identification, tool for processing of cross-lingual speech and language identification, mono-lingual, bi-lingual, tri-lingual and quad-lingual speech to monolingual text translation for the four languages.It is a generic approach and can be used for other regional languages of India by training the corpus with the selected language.Novelty: Cross-lingual speech identification and text translation system helps users in e-shopping by reducing the time incurred in making a decision to purchase a product having enough features at an economical price, e-tutoring, e-farming activities, digitizing, defence etc.