Reviewerly/exHarmony huggingface dataset:
On equivalence of cyclic and dihedral zero-divisor codes having nilpotents of nilpotency degree two as generators

Abstract Zero-divisor codes are codes constructed using group rings where their generators are zero-divisors. Generally, zero-divisor codes can be equivalent despite their associated groups are non-isomorphic, leading to the proposed conjecture “Every dihedral zero-divisor code has an equivalent form of cyclic zero-divisor code”. This paper is devoted to study equivalence of zero-divisor codes in $$F_2G$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>F</mml:mi> <mml:mn>2</mml:mn> </mml:msub> <mml:mi>G</mml:mi> </mml:mrow> </mml:math> having generators from the 2-nilradical of $$F_2G$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>F</mml:mi> <mml:mn>2</mml:mn> </mml:msub> <mml:mi>G</mml:mi> </mml:mrow> </mml:math> , consisting of all nilpotents of nilpotency degree 2 of $$F_2G$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>F</mml:mi> <mml:mn>2</mml:mn> </mml:msub> <mml:mi>G</mml:mi> </mml:mrow> </mml:math> . Essentially, algebraic structures of 2-nilradicals are first studied in general for both commutative and non-commutative $$F_2G$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>F</mml:mi> <mml:mn>2</mml:mn> </mml:msub> <mml:mi>G</mml:mi> </mml:mrow> </mml:math> before specialized into the case when G is cyclic and dihedral. Then, results are used to study the conjecture above in the cases where the codes generators are from their respective 2-nilradicals.
Effectiveness of Augmented Reality (AR) on Students’ Achievement and Motivation in Learning Science

This study aimed to determine the impact of an augmented reality (AR) application, NutricARd, on students’ achievement and motivation. The mixed-methods research seeks to ascertain the influence of AR-NutricARd learning cards on the motivation and achievement of form 2 science students. There were 50 participants in this study. The NutricARd applications, which had undergone rigorous design and development research, were employed for the treatment group. Each of the control and experimental groups had 25 participants. The control group used existing AR features in textbooks provided by the Malaysia Ministry of Education. The study revealed that there is a significant difference in achievement between the treatment and control groups. Pre-tests and post-tests, as well as a procedure for semi-structured interviews, were employed as research tools in this study. The paired t-test results showed that there was also a significant difference in students’ motivation. The semi-structured interview showed that AR-NutricARd has the capabilities and intriguing aspects that encourage students to engage with the science subject. The findings of the study also showed that there is a significant relationship between motivation and achievement. Thus, a higher motivation implies increased student achievement.
Leonov’s Universe

The St. Petersburg digest of selected works by Professor Valery P. Leonov published in specialized editions in the period of 1972–2020 is reviewed. The digest was published in St. Petersburg. The works for the digest were selected by Valery Leonov himself. “The Selected Works” comprise his papers, interviews and communications and reflect the dynamics of Leonov’s scholarly interests and preferences in library and information segment. The digest is divided into eight subject sections: 1) Bibliology: new aspects of theory; 2) Library science as a fundamental science; 3) Bibliographic information and the problems of its surrogation; 4) Library and bibliographic processes as a social phenomenon; 5) Bibliography: in search of a new paradigm; 6) The concept of the exact bibliography science; 7) Biography of the Library of the Academy of Sciences: an experiment; 8) The International Association of Bibliophiles and the Library of Russian Academy of Sciences. The special section of the digest is dedicated to Leonov’s teachers, colleagues and friends. In the epilogue, the readers will learn about several episodes of Leonov’s biography. The book is supplemented with the detailed name index. The digest will be of interest to the wide library and information professional community.
Convolutional neural networks based weapon detection: a comparative study

Lately, one of the most common illegal activities include the use of shooting weapons. In such dangerous situations, there is a dire need of preventive measures that can automatically detect such munitions. This paper presents the use of computer vision and deep learning to detect weapons like guns, revolvers and pistols. Convolutional Neural Networks can be efficiently used for object detection. In this paper, precisely, two Convolutional Neural Network (CNN) architectures - Faster R-CNN with VGG16 and YOLOv3, have been used, to carry out the detection of such weapons. The pre-trained neural networks were fed with images of guns from the Internet Movie Firearms Database (IMFDB) which is a benchmark gun database. For negative case images, MS COCO dataset was used. The goal of this paper is to present and compare performance of the two models to bring about gun detection in any given scenario. The results of YOLOv3 outperforms Faster R-CNN with VGG16. The ultimate aim of this paper is to detect guns in an image accurately which in turn can aid crime investigation.
Universal Real-Time Strategy Game in Unreal Engine

Abstract: In the rapid growing field of game development and game design, the RTS genre of games continues to attract substantial number of gamers. RTS genre games not only provide entertainment for gamers but also the ability to yest and grow their real time application of tactical and logical decision-making skills. RTS games are lately very popular but a brief number of games are available with similar concepts. This reputation in the story line of the available games makes the long-term game play less desirable. The project intents to develop a spin-off RTS game with major emphasis on level design, gameplay mechanics, user interface development and resource management. Keywords: Unreal Engine, Blender, Gaea, Mesh, the Home Line.
Formalizing Creativity: Academic Writing in Early College Years

The transition from high school to college can easily be deemed to be one of the biggest changes in a student’s life. However, due to its dramatic nature, one may fail to fully consider the intricacies of this change. In college, the criteria for evaluating students’ academic standing shifts from simple examinations to a blend of assignments and exams. Multiple assignments need the students to write authentic pieces of academic writing. This perspective article aims at providing a conceptual description, and analysis, of academic writing during early college years. We evaluate the structure and components of various stages in academic writing. The outcomes of the paper provide a thorough analysis of dichotomies that exist in students’ experiences using two models of literacy: The Autonomous Model, and The Ideological Model. To further reemphasize how crucial early college years are, a contrast has been made between what academic writing is and should be in high school; and what academic writing is in college. This contrast is exemplified using the Central Board of Secondary Education, which is India’s primary board for education. This article also explores the academic and cognitive dimensions of academic writing. Taking the current status quo and the recent transformation of the academic world into consideration, the outcome also highlights the challenges and limitations posed by the COVID-19 pandemic and provides recommendations to tackle the same. The article also introduces and appraises the idea of students in today’s world, who majorly identify as “digital natives.” It subsequently analyses how this identity impacts their academic life in a pandemic-struck online system of education. A brief yet elaborate account of the Indian context, and its structural realities were the key focus while making inferences. Finally, the article presents limitations and challenges faced by students in three ways, reiterating the contrast between high school and college in terms of academic instruction, briefly analyzing the social environment in college along with its possible implications, and commenting upon the ambiguity in academic expectations.
Sentiment Analysis using Transformer Based Pre-Trained Models for the Hindi Language

India has one of the largest user bases for Internet-based services. In 2021, India had 624 million internet users, the second largest in the world<sup>1</sup><sup>1</sup>https://datareportal.com/reports/digital-2021-india. With so many internet users, each generating lots of textual data, having tools to analyze the data can be very helpful to a wide variety of people including researchers, marketers, and product managers. Research regarding Sentiment Analysis in English is plentiful, but we need a different method to perform the same in Hindi, one of the most popular languages of the Indian subcontinent. In this paper, we use Transformer-based pre-trained models on Hindi Sentiment Analysis tasks. The sentiment analysis task is done on a dataset that has Hindi text and its corresponding sentiment as Positive, Negative, and Neutral. The Hindi text contains sentences collected from various sites. The sentences primarily contain product and movie reviews. The sentiment analysis is done using five different transformer-based models, out of which a few have been trained for multiple languages while the others have been fine-tuned specifically for the Hindi language. We also compare the performance of a few different multilingual models on sentiment analysis tasks. Out of all the models compared, we get the best accuracy of 82&#x0025; from the Hindi Microsoft Multilingual-MiniLM-L12-H384 model.
Use of Pear Deck as an Interactive Tool in Teaching Reading Comprehension During the New Normal

Good English language proficiency is given attention by the Malaysian government in line with the global challenge where the use of ICT is emphasized.Through the introduction of the Malaysian Education Blueprint 2013-2025, the government is keen on ensuring every child is proficient in English.With the on-going battle against COVID-19 pandemic, online learning has become inevitable.However, students get demotivated when it comes to remote classes, especially in English lessons.As such, this research investigated students' perceptions of the use of Pear Deck during the pandemic.This action research used a pre and post-test and employed a semi-structured interview where 20 Form Three students of average proficiency in an urban area school in Penang were purposely selected which provided needed data that was then analysed accordingly using SPSS for quantitative data and a thematic analysis in analysing qualitative data.Based on the discussion of data, it is revealed that active learning pedagogy practices are important factors in improving students' success and they have a good perception towards the use of Pear Deck in reading activities during the pandemic.It is hoped that this study can encourage teachers in trying out Pear Deck in their ESL classroom for more engaging activities for the students.
A Review Paper on Cloud Computing

The word "cloud computing" comes from the record that the data being obtained is generally traced down in some way in the cloud or a virtual area. Cloud service providers enable clients to store documents and apps on remote servers and then access them via the Internet. In this paper, I have given a brief analysis of cloud computing by reviewing more than 20 articles on cloud computing. The outcome of this review distinguishes the face of the IT industries earlier than and after cloud computing.
Pedagogical Technologies for the Development of Students' Professional Competence

The main purpose of the article is to study the basic provisions of the use of pedagogical technologies for the development of students' professional competence. Improving the training of specialists requires finding effective ways to form students' systemic ideas about the object of their professional activity, the skills and abilities of its research, organization and management. One of the most pressing problems in the field of professional training is the formation of various aspects of the professional culture of specialists, which are an expression of the maturity and development of the entire system of socially significant qualities, is productively implemented in individual activities and is inextricably linked with their personal culture. During their studies at the university, students should receive comprehensive pedagogical training, a sincere interest in creative search and the formation of pedagogical professionalism. As a result of the study, the main trends, aspects and prospects of the use of pedagogical technologies for the development of students' professional competence were revealed
A secure multi-party computation protocol without CRS supporting multi-bit encryption

To solve the problems in the existing fully homomorphic encryption (FHE)-based secure multi-party computation (SMC) protocols such as low efficiency, the FHE scheme that supports multi-bit encryption was modified during the generation of the public key so that the users could generate their public keys independently without the common random string (CRS) matrix. Further, a multi-bit Gentry-Sahai-Waters scheme (MGSW) scheme without CRS was constructed. The modified LinkAlgo algorithm was adopted to expand the single-key ciphertext into the multi-key ciphertext and simplify the way of generating the expanded ciphertext. In this way, a multi-key FHE (MFHE) scheme was achieved based on the MGSW scheme. Finally, a three-round SMC protocol without CRS was constructed using the MFHE scheme and the decisional learning with errors (DLWE) assumption, which was secure in the semi-malicious model. Compared to the existing protocols, the protocol proposed herein can support multi-bit encryption and is found with smaller ciphertext size and lower storage overhead and generate the expanded ciphertext in a simpler way. Overall performance is better than existing protocols.
Computation by Convective Logic Gates and Thermal Communication

We demonstrate a novel computational architecture based on fluid convection logic gates and heat flux-mediated information flows. Our previous work demonstrated that Boolean logic operations can be performed by thermally driven convection flows. In this work, we use numerical simulations to demonstrate a different , but universal Boolean logic operation (NOR), performed by simpler convective gates. The gates in the present work do not rely on obstacle flows or periodic boundary conditions, a significant improvement in terms of experimental realizability. Conductive heat transfer links can be used to connect the convective gates, and we demonstrate this with the example of binary half addition. These simulated circuits could be constructed in an experimental setting with modern, 2-dimensional fluidics equipment, such as a thin layer of fluid between acrylic plates. The presented approach thus introduces a new realm of unconventional, thermal fluid-based computation.
Mutual information estimation for graph convolutional neural networks

Measuring model performance is a key issue for deep learning practitioners. However, we often lack the ability to explain why a specific architecture attains superior predictive accuracy for a given data set. Often, validation accuracy is used as a performance heuristic quantifying how well a network generalizes to unseen data, but it does not capture anything about the information flow in the model. Mutual information can be used as a measure of the quality of internal representations in deep learning models, and the information plane may provide insights into whether the model exploits the available information in the data. The information plane has previously been explored for fully connected neural networks and convolutional architectures. We present an architecture-agnostic method for tracking a network's internal representations during training, which are then used to create the mutual information plane. The method is exemplified for graph-based neural networks fitted on citation data. We compare how the inductive bias introduced in graph-based architectures changes the mutual information plane relative to a fully connected neural network.
A Substitution-Box Structure Based on Solar Panel Data

The demonstration that the nonlinearity criterion of substitution box (s-box) structures based on the random selection principle can be improved through post-processing techniques has created a new research area. The necessity of obtaining sbox structures that can be given as input to these post-processing algorithms has emerged. In this study, a study was carried out on how to obtain sbox structures based on solar panel data. The cryptological properties of the obtained sbox structures were tested using five basic evaluation metrics and compared with similar studies in the literature. The successful results indicated that these outputs may have various practical applications in the future.
New dual method for elastica regularization

The Euler's elastica energy regularizer has been widely used in image processing and computer vision tasks. However, finding a fast and simple solver for the term remains challenging. In this paper, we propose a new dual method to simplify the solution. Classical fast solutions transform the complex optimization problem into simpler subproblems, but introduce many parameters and split operators in the process. Hence, we propose a new dual algorithm to maintain the constraint exactly, while using only one dual parameter to transform the problem into its alternate optimization form. The proposed dual method can be easily applied to level-set-based segmentation models that contain the Euler's elastic term. Lastly, we demonstrate the performance of the proposed method on both synthetic and real images in tasks image processing tasks, i.e. denoising, inpainting, and segmentation, as well as compare to the Augmented Lagrangian method (ALM) on the aforementioned tasks.
Analysis of CART and Random Forest on Statistics Student Status at Universitas Terbuka

CART and Random Forest are part of machine learning which is an essential part of the purpose of this research. CART is used to determine student status indicators, and Random Forest improves classification accuracy results. Based on the results of CART, three parameters can affect student status, namely the year of initial registration, number of rolls, and credits. Meanwhile, based on the classification accuracy results, RF can improve the accuracy performance on student status data with a difference in the percentage of CART by 1.44% in training data and testing data by 2.24%.
A Study of the Determinants of General Education at Four-Year Universities

This study aims to explore the determinants of the students’ outcomes of general education. For this purpose, this study measured the outcomes of general education using four sub-areas with the “The Evaluation Tool for Students’ Outcomes in General Education” and investigated the priorities and interactions among the factors by entering independent variables related to general education, such as taking the general education curriculum, the satisfaction with general education, self-regulated learning, and the happiness in decision tree analysis. The analysis data were collected by random sampling from students at four-year universities nationwide and through an online survey, and data from a total of 671 students’ responses were analyzed. The main results of the decision tree analysis are as follows. First, the most important determinant of the outcomes of overall general education, humanistic value establishment, and creative problem-solving ability performance is ‘learning management’ or ‘self-regulated learning’. Second, the most important determinant of the outcomes of the pursuit of scientific value is whether the students took ‘Natural Sciences’ classes. Third, the most important determinant of the outcomes of knowledge was convergence ability. Fourth, there were differences between the determinants of the outcomes of general education (overall) and those of the four sub-areas. Effective measures for improving the outcomes of general education were proposed according to the research results.
BLANK APPS, THEIR USAGE IN NATURAL HISTORY SUBJECTS AND THEIR EFFECT ON STUDENTS ON 2ND STAGE OF ELEMENTARY SCHOOLS

Are online quiz apps in education as effective as it might seem at a first glance?Using blanks apps has become very widespread lately, mostly because of the Co-Vid-19 pandemic and the need for distance learning.These apps make it possible for the children to exercise the curriculum with the help of quizzes and other interactive formats and to get immediate feedback.These applications usually have attractive looks, playful forms and are very user friendly, both for the teachers as well as for the students.But what is their real impact on pupils?Do they really help children to speed up the fixation of the curriculum or to improve their studying results?Do they increase children's interests for the subject?We are looking for answers to these questions in the following research study with the help of analyzing expert articles and a questionnaire targeted to children on 2nd stage of elementary schools.
Adaptive Chaotic Maps in Cryptography Applications

Chaotic cryptography is a promising area for the safe and fast transmission, processing, and storage of data. However, many developed chaos-based cryptographic primitives do not meet the size and composition of the keyspace and computational complexity. Another common problem of such algorithms is dynamic degradation caused by computer simulation with finite data representation and rounding of results of arithmetic operations. The known approaches to solving these problems are not universal, and it is difficult to extend them to many chaotic systems. This chapter describes discrete maps with adaptive symmetry, making it possible to overcome several disadvantages of existing chaos-based cryptographic algorithms simultaneously. The property of adaptive symmetry allows stretching, compressing, and rotating the phase space of such maps without significantly changing the bifurcation properties. Therefore, the synthesis of one-way piecewise functions based on adaptive maps with different symmetry coefficients supposes flexible control of the keyspace size and avoidance of dynamic degradation due to the embedded technique of perturbing the chaotic trajectory.
The Number of Solutions of Certain Equations over Finite Fields

Let s be a positive integer, p be an odd prime, [see formula in PDF], and let [see formula in PDF] be a finite field of q elements. Let [see formula in PDF] be the number of solutions of the following equations: [see formula in PDF][see formula in PDF] over the finite field [see formula in PDF], with [see formula in PDF][see formula in PDF][see formula in PDF] and [see formula in PDF][see formula in PDF] are positive integers. In this paper, we find formulas for [see formula in PDF] when there is a positive integer l such that dD |([see formula in PDF]) , where [see formula in PDF][see formula in PDF][see formula in PDF][see formula in PDF][see formula in PDF][see formula in PDF][see formula in PDF][see formula in PDF] And we determine [see formula in PDF] explicitly under certain cases. This extends Markoff-Hurwitz-type equations over finite field.