Reviewerly/exHarmony huggingface dataset:
A Rapid Combined Model for Automatic Generating Web UI Codes

Encoder-Decoder network is usually applied to image caption to automatically generate descriptive text for a picture. Web user interface (Web UI) is a special type of image and is usually described by HTML (hypertext marked language). Consequently, it becomes possible to use the encoder-decoder network to generate the corresponding code from a screenshot of Web UI. The basic structure of the decoder is RNN, LSTM, GRU, or other recurrent neural networks. However, this kind of decoder needs a long training time, so it increases the time complexity of training and prediction. The HTML language is a typically structured language to describe the Web UI, but it is hard to express the timing characteristics of the word sequence and the complex context. To resolve these problems efficiently, a rapid combined model RCM (rapid combined model) is designed in this paper. The basic structure of the RCM is an encoder-decoder network. The word embedding matrix and visual model are included in the encoder. The word embedding matrix uses fully connected units. Compared with LSTM, the accuracy of the word embedding matrix is basically unchanged, but the training and prediction speed have been significantly improved. In the visual model, the pretrained InceptionV3 network is used to generate the image vector, which not only improves the quality of the recognition of the Web UI interface image but also reduces the training time of the RCM significantly. In the decoder, the word embedding vector and the image vector are integrated together and input into the prediction model for word prediction.
Stabilizer rank and higher-order Fourier analysis

We establish a link between stabilizer states, stabilizer rank, and higher-order Fourier analysis – a still-developing area of mathematics that grew out of Gowers's celebrated Fourier-analytic proof of Szemerédi's theorem \cite{gowers1998new}. We observe that <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>n</mml:mi></mml:math>-qudit stabilizer states are so-called nonclassical quadratic phase functions (defined on affine subspaces of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msubsup><mml:mrow class="MJX-TeXAtom-ORD"><mml:mi mathvariant="double-struck">F</mml:mi></mml:mrow><mml:mi>p</mml:mi><mml:mi>n</mml:mi></mml:msubsup></mml:math> where <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>p</mml:mi></mml:math> is the dimension of the qudit) which are fundamental objects in higher-order Fourier analysis. This allows us to import tools from this theory to analyze the stabilizer rank of quantum states. Quite recently, in \cite{peleg2021lower} it was shown that the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>n</mml:mi></mml:math>-qubit magic state has stabilizer rank <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi mathvariant="normal">&amp;#x03A9;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mi>n</mml:mi><mml:mo stretchy="false">)</mml:mo></mml:math>. Here we show that the qudit analog of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>n</mml:mi></mml:math>-qubit magic state has stabilizer rank <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi mathvariant="normal">&amp;#x03A9;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mi>n</mml:mi><mml:mo stretchy="false">)</mml:mo></mml:math>, generalizing their result to qudits of any prime dimension. Our proof techniques use explicitly tools from higher-order Fourier analysis. We believe this example motivates the further exploration of applications of higher-order Fourier analysis in quantum information theory.
A Case-Based Reasoning for Detection Coronavirus (Covid-19) Using Cosine Similarity

Case-based reasoning is a new approach that can be used to diagnose disease in addition to using expert systems or other approaches, which are part of artificial intelligence.Case-based reasoning can diagnose diseases based on visible or perceived clinical symptoms.This study tries to build case-based reasoning for early detection of COVID-19 by looking at the characteristics of clinical symptoms seen in a person using the Cosine Similarity method.Cosine similarity is a method to find level of similarity between two cases.The detection process is carried out by entering a new case containing symptoms into the system, then system will perform a similarity calculation process between the old case and the new case.The results show case-based reasoning for early detection of COVID-19 using the Cosine Similarity method can detect a similarity level of 80%.
Written and Spoken Language in Igbo Cultural Milieu: A Philosophical Approach

Aristotle in his De Interpretatione sketches how words are related to things through the mind. It is the spoken word that brings to light the secret intentions of the human heart. Hence the Igbo people usually say that the spoken word is the human mind made visible. In our contemporary society, the effects of many related spoken word problems are often misconstrued as either attacks from the malevolent spirits or as the machinations of the evil people. The spoken words can create as well as destroy. There is, therefore, a serious need to create the awareness and enlightenment in this regard to the grassroots. This work will, therefore, attempts to bring out the concept of the spoken language in Igbo cultural milieu, as a phenomenon to a philosophical scrutiny and, hence to provide the much needed literature in the field. Hence, the work intends to bring some enlightenment concerning the Igbo concept of the spoken words. This enlightenment will as well create awareness on the effectiveness and efficaciousness of the spoken words both in the positive and the negative dimensions, as well as the reason Igbo-African prefer spoken words to the written words. The researcher primarily uses philosophic techniques as a method to achieve the purpose of the study.
THE MEDIATING EFFECT OF COOPERATIVE LEARNING APPLICATION ON THE RELATIONSHIP BETWEEN SOCIAL MEDIA USAGE AND LANGUAGE PROFICIENCY OF STUDENTS

Language proficiency is the ability to use language for a variety of communicative purposes. Users with a good command of the language are considered to have a good command of it because they can grasp it without difficulty, communicate a wide range of ideas clearly in speech and writing, and comfortably engage with other speakers (Renandya et al. 618). Thus, educators agree that proficiency in the English language is the basis for success in academic pursuits. Subsequently, Trice reported that international students were isolated from local students and faculty members because of their poor English language skills.
Blockchain-based model to track and verify official certificates

Document verification is a complicated domain with a variety of difficult and time-consuming methods to validate. Customized verification and authentication processes may be required for various sorts of papers, such as financial papers, government papers, transaction papers, educational credentials, and so on. A huge problem today we are facing is the number of fake certificates that are in circulation, this problem is quite predominant. This has become a new business for a long time. Hardworking people with genuine degrees/certificates have been suffering and they get rejected in the job market because of the lack of identification to differentiate between the original and the fake certificate. At times people are getting jobs through fake certificates and this becomes very dangerous. The scenario calls for a new system that can verify and authenticate certificates, their issuers, and their holders in a way that is much more efficient, simple, and intuitive to use, and efficiently mitigates widespread credential fraud. To combat the counterfeiting of academic certificates, our blockchain approach combines a verified distributed ledger with a cryptographic mechanism. Our Blockchain technology will also provide a standard sharing platform for storing and accessing documents, reducing overall verification time and allowing companies to quickly monitor and access real papers. Our system that helps to identify original certificates will help the hard-earned people to get their jobs in their desired organizations and all the fake circulation of certificates will be stopped because the system identifies the genuine true certificates.
Intensional Semantics for Syllogistics: what Leibniz and Vasiliev Have in Common

This article deals with an alternative interpretation of syllogistics, different from the classical (extensional) one: an intensional one, in which subject and predicate are not associated with a set of individuals (the extension of the concept) but a set of attributes (the content of the concept). The authors of the paper draw attention to the fact that this approach was first proposed by Leibniz in works on logical calculus, which for a long time remained in the shadow of his other philosophical works. Currently, the intensional approach is gaining more and more popularity due to the development of non-classical logics, and the article will present several existing intensional formal syllogistic semantics. The paper will also consider another historical approach to syllogistics, associated with the name of the Russian logician Nikolai Vasiliev, who is not only one of the founders of non-classical (non-Aristotelian logic) but also of a different intensional interpretation of such logic. The authors, along with the already known formalizations of Vasiliev’s ideas, present two new systems. One of them is a reconstruction of one type of imaginary logic with statements of three qualities: affirmative and two types of negative statements (with absolute and ordinary negation). The second system is the one that is adequate to semantics, in which instead of the four classical ones, only three types of statements are presented (two particular statements are replaced by one - accidental), and their significance is determined through the relation of the classical logical entailment. Both of them are interpreted intensionally. The intensional approach in logic and, in particular, in syllogistics allows us to expand the class of accepted principles (which occurs due to the expansion of the class of correct moods of syllogisms).
LRGAN: A computational lightweight image inpainting neural network

<p indent="0mm">Currently, most image inpainting approaches focus on improving the quality of inpainted images while ignoring the requirement for a low-end platform. In this work, we propose a lightweight group convolution module in place of vanilla convolution. This module, named lightweight attention-based group convolution (LABGC), uses a depth-wise convolution to achieve multi-scale image inpainting. Meanwhile, to alleviate the information constraint between channels, we propose a cycle channel attention mechanism. Then in our proposed LRGAN inpainting network, we use LABGC. We use parallel discriminators in the overall network design to ensure local and non-local consistency. Experiments show that our model is as accurate as state-of-the-art approaches in terms of speed and FLOPs.
PROBLEMS OF ESTABLISHMENT OF DISTANCE LEARNING IN UKRAINE

The article deals with the stages of formation of distance learning in Ukraine from the standpoint of ensuring education continuity in cases of emergency. The legal framework for establishment of distance learning has been analyzed. The development of a child’s creative and intellectual abilities through open and free use of all educational resources and programs, including those available on the Internet, has been revealed as the main task of distance learning. The advantages of distance learning for pupils of secondary schools have been determined. They consist in intensive updating of knowledge acquired from the world information resources, expansion of the field of a teacher’s activities (regardless of the location of all subjects of the educational process) as well as development of cognitive interests, contribution to the formation of students’ professional orientation and mastering the methods of scientific research. Questionnaires have been developed to determine the attitude of the Ukrainian students and their parents to distance learning as an alternative to full-time education during a pandemic. A sociological study of the organization of distance learning at schools was conducted and the data on the problems and challenges faced by pupils and their parents during online learning were collected. The following conclusion has been made: due to bigger amount of free time and less busy schedule, studying at home turned to be comfortable for pupils, while for their parents, first of all, the advantage of distance learning dealt with saving time on the way to / from school. The biggest problems were the difficulty to study without teachers’ explanations and help and the lack of live communication.The main factors of distance learning have been identified: in particular, the flexibility of place, time, pace and trajectory of learning. The article outlines the prospects for use of distance learning elements in the development of the Ukrainian school system in the future.
Deep CNN Model for Non-Screen Content and Screen Content Image Quality Assessment

In the current world, user experience in various platforms matters a lot for different organizations. But providing a better experience can be challenging if the multimedia content on online platforms is having different kinds of distortions which impact the overall experience of the user. There can be various reasons behind distortions such as compression or minimal lighting condition while taking photos. In this work, a deep CNN-based Non-Screen Content and Screen Content NR-IQA framework is proposed which solves this issue in a more effective way. The framework is known as DNSSCIQ. Two different architectures are proposed based upon the input image type whether the input is a screen content or non-screen content image. This work attempts to solve this by evaluating the quality of such images.
LAGRANGE INTERPOLATION FOR NATURAL COLOUR IMAGE DEMOSAICING

The quality of the digital image of the camera is determined by the colour demosaicing. The size and cost of the camera is reduced by a single sensor to capture the image which uses a Bayer Colour Filter Array (CFA). The captured image by the camera is the CFA image and the missing components of Red (R), Green (G), and Blue (B). The proposed system uses Lagrange interpolation in both directions to find the missing components of G. To get the whole G image, Inter Channel Correlation (ICC) is utilized. Then Colour different interpolation is employed for the reconstruction of R and B image. A fine-tuning step is designed to improve the quality. Natural images which are obtained from Kodak and IMAX are used for performance analysis. The qualities of the reconstructed images are validated in terms of Peak Signal to Noise Ratio (PSNR).&nbsp; The comparative analysis with the state-of-the-art approaches in the literature shows that the Lagrange interpolation provides better quality than others.
Logica Dominans vs. Logica Serviens

Logic is usually presented as a tool of rational inquiry; however, many logicians in fact treat logic so that it does not serve us, but rather governs us – as rational beings we are subordinated to the logical laws we aspire to disclose. We denote the view that logic primarily serves us as logica serviens, while denoting the thesis that it primarily governs our reasoning as logica dominans. We argue that treating logic as logica dominans is misguided, for it leads to the idea of a “genuine” logic within a “genuine” language. Instead of this, we offer a naturalistic picture, according to which the only languages that exist are the natural languages and the artificial languages logicians have built. There is, we argue, no language beyond these, especially none that would be a wholesome vehicle of reasoning like the natural languages and yet be transparently rigorous like the artificial ones. Logic is a matter of using the artificial languages as idealized models of the natural ones, whereby we pinpoint the laws of logic by means of zooming in on a reflective equilibrium.
Research on the Immersive Classroom Teaching Mode of Colleges and Universities Based on Virtual Reality

In order to improve the teaching effect of colleges and universities and eliminate the disadvantage Figures of the traditional teaching mode, this paper applies virtual reality technology to the immersive teaching mode of colleges and universities and uses four-dimensional light field parameterization to describe the acquisition process and reproduction process of integrated imaging. Moreover, this paper studies the propagation characteristics of the light field during the reproduction of the integrated imaging system and establishes an evaluation method for the 3D scene reproduction capability of the integrated imaging system using light field parameters. In addition, this paper analyzes the problem of parameter matching between the acquisition end and the display end in the current integrated imaging system and does a detailed study on the method of light field conversion and gives the interpolation method of the light field image. Finally, this paper constructs an immersive teaching system for colleges and universities based on virtual reality and verifies the performance of the system through experimental research. From the experimental research results, it can be seen that the immersive classroom teaching model in colleges and universities based on virtual reality proposed in this paper has good teaching effects.
Dyslexia, Self-efficacy, and Language Instruction in Foreign Language Learning -- A Mixed Quantitive-qualitative Study

The aim of the research is to investigate the interdependence between dyslexia, self-efficacy, and foreign language instruction. The author of the study applied a mixed-method: quantitative and qualitative. The quantitative data were collected through self-efficacy questionnaires filled out by dyslexic and non-dyslexic students, and the qualitative data were collected during a case study conducted with a dyslexic student. The research findings in the first quantitative part of the study reveal that self-efficacy in dyslexic students is substantially lower than in non-dyslexic students. According to the results of the second mixed, quantitative - qualitative part of the study encompassing a case study, foreign language instruction has an impact on dyslexic students’ self-efficacy and appropriate language instruction rises self-efficacy in students with dyslexia.
An improved K-Nearest neighbour with grasshopper optimization algorithm for imputation of missing data

K-nearest neighbors (KNN) has been extensively used as imputation algorithm to substitute missing data with plausible values. One of the successes of KNN imputation is the ability to measure the missing data simulated from its nearest neighbors robustly. However, despite the favorable points, KNN still imposes undesirable circumstances. KNN suffers from high time complexity, choosing the right k, and different functions. Thus, this paper proposes a novel method for imputation of missing data, named KNNGOA, which optimized the KNN imputation technique based on the grasshopper optimization algorithm. Our GOA is designed to find the best value of k and optimize the imputed value from KNN that maximizes the imputation accuracy. Experimental evaluation for different types of datasets collected from UCI, with various rates of missing values ranging from 10%, 30%, and 50%. Our proposed algorithm has achieved promising results from the experiment conducted, which outperformed other methods, especially in terms of accuracy.
Geography and math teachers in distance learning education amid COVID-19 pandemic in Albania

The Coronavirus 2019 pandemic (COVID-19) brought a rapid change in the professional routine of in-service teachers worldwide. The study presents an assessment of challenges of online distance learning where a sample group of 155 geography and mathematics teachers, in pre-university system in Albania were involved during the first periods of the COVID-19 pandemic. The research found that lack of prior preparation has significantly affected the selection and usage of platforms, suitable for distance learning. Teachers face more difficulties in cartographic, graphic and symbolic semantic and less in verbal one. At the beginning of the pandemic, teaching was done mostly through WhatsApp and further on with the RTSH TV channels, followed by Google Classroom and Zoom. Teachers have fulfilled the needs for technological training through cooperation with colleagues and self-training and through various tutorials. The study emphasizes that teachers need professional development especially in software systems and online teaching methodologies.
A General Profile of Artificial Intelligence Adoption in Banking Sector

Artificial Intelligence (AI) is rapidly transforming the global financial services industry. The new digitalization model is powered by artificial intelligence technology, and AI has the potential to disrupt and refine the existing financial services industry. The increasing amount of data in banking has revealed the need for fast and reliable service. Banks are financial service organizations that have used AI effectively in recent years. This paper reveals the general profile of artificial intelligence adoption by banks. Based on the evidence from all 17 banks operating in the Afyonkarahisar province of Turkey, it is concluded that AI technologies are applied in almost every area of the banking sector to improve the overall service offered. Moreover, the use of AI is evaluated as a potential that provides ease of use and reduces costs. As for the operations in future, the participants think AI will provide high levels of benefit to banks in their financial services in the incoming years. Given no similar study, this study appears to provide an original contribution to the literature regarding the use of AI in banking services within the Turkish context.
IMPROVING STUDENTS’ READING COMPREHENSION OF DESCRIPTIVE TEXT BY USING TEACHER’S SCAFFOLDING

This classroom action research aimed to improve student’s reading comprehension of descriptive text by using the teacher’s scaffolding, especially in the aspect of vocabulary, finding the detailed information and main idea, determining pronoun reference, and using correct language features. This research was conducted in three cycles, with 32 students of the VII E class in SMP Negeri 03 Sungai Raya as the subject. The collected data were qualitative and quantitative data. The qualitative data were gathered from the observation checklist and field notes, and the quantitative data were collected from the reading test. The findings showed that the use of teacher’s scaffolding in teaching reading comprehension text was encouraged students to determine the language features and pronoun reference, completing the detailed information and main idea and, increasing students’ vocabulary. The students became more active, enthusiastic, motivated and, confident in the reading comprehension class. The students enjoyed reading descriptive text and followed the learning activities. Based on the quantitative data, the students’ score of cycle 1 was 65,59, increased to 78,84 in the second cycle and 83 in the third cycle.