Reviewerly/exHarmony huggingface dataset:
Constructions and Necessities of Some Permutation Polynomials over Finite Fields

Let <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <msub> <mrow> <mi mathvariant="double-struck">F</mi> </mrow> <mrow> <mi>q</mi> </mrow> </msub> </math> denote the finite field with <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <mi>q</mi> </math> elements. Permutation polynomials over finite fields have important applications in many areas of science and engineering such as coding theory, cryptography, and combinatorial design. The study of permutation polynomials has a long history, and many results are obtained in recent years. In this paper, we obtain some further results about the permutation properties of permutation polynomials. Some new classes of permutation polynomials are constructed, and the necessities of some permutation polynomials are studied.
Construction of an Improved English Teaching Model Based on Cellular Automata

In order to improve the effect of college English teaching reform, this paper puts cellular automata English into English teaching simulation and uses the cellular automata model to study the behavior of complex teaching systems. Moreover, this article uses the method of man-machine combination to establish the corresponding dynamic evolution model and design the local evolution rules of the complex system to simulate the English teaching process, including the movement of students and teachers, the interaction of the teaching process, the development of teaching activities, and the processing of teaching resources. In addition, this paper constructs the functional structure of the system and conducts system verification through experimental research. The experimental research results show that the English classroom teaching evaluation system based on the cellular automaton proposed in this article is very effective, and it has a certain role in promoting English teaching.
Revisiting Local Descriptors via Frequent Pattern Mining for Fine-Grained Image Retrieval

Fine-grained image retrieval aims at searching relevant images among fine-grained classes given a query. The main difficulty of this task derives from the small interclass distinction and the large intraclass variance of fine-grained images, posing severe challenges to the methods that only resort to global or local features. In this paper, we propose a novel fine-grained image retrieval method, where global–local aware feature representation is learned. Specifically, the global feature is extracted by selecting the most relevant deep descriptors. Meanwhile, we explore the intrinsic relationship of different parts via the frequent pattern mining, thus obtaining the representative local feature. Further, an aggregation feature that learns global–local aware feature representation is designed. Consequently, the discriminative ability among different fine-grained classes is enhanced. We evaluate the proposed method on five popular fine-grained datasets. Extensive experimental results demonstrate that the performance of fine-grained image retrieval is improved with the proposed global–local aware representation.
Summary and Outlook

With the tremendous success of deep learning in recent years, the field of data science has undergone unprecedented changes that can be considered a “revolution”. Despite the great successes of deep learning in various areas, there is a tremendous lack of rigorous mathematical foundations which enable us to understand why deep learning methods perform well.
Steganographic Data Hiding in QR Codes

In the era of technological development, data transfer over internet is playing vital role in communication. Now a days use of internet became common and it is necessary to secure the transmission of data in the form of protecting information systems from unauthorized access, use, disruption, modification, recording or destruction. There various methods available for data security, like cryptography and steganography. Steganography is the technique in which data gets hide behind any other information and it becomes difficult for unauthorized user to detect it. QR code is the trademark for a type of matrix barcode consisting of the black square modules arranged in a square grid on a white background. Any imaging devices such as camera, scanner are used for reading the code. In this article we are discussing different technologies that can be used for steganography along with steganography using QR codes.
Education Communication in the English Learning Process

This research was conducted with the aim of analyzing instructional communication between teachers and students in learning English and the obstacles faced by teachers and students in achieving learning communication objectives located at SMPN 25 Solok Selatan. This research uses qualitative research. Determination of informants by means of purposive sampling, research data obtained through in-depth interviews, observation, and documentation. Data processing techniques using the model of Miles and Huberman analysis and data validity with triangulation. The results showed that in the learning or instructional communication process: (1) communicators were still dominated by teachers while many students were still passive; (2) messages are arranged and designed by teachers based on the applicable curriculum taking into account the different backgrounds of students; (3) the method used is the lecture, demonstration, discussion, and question and answer method; and (4) feedback in the communication process is done directly by students both verbally and nonverbally. Barriers that occur in the learning communication process include the use of language by communicators that are less understood by students, the limited media used and the lack of motivation of students in learning English.
Solar radiation modelling and measurement techniques in Lafia Zone, Nasarawa state, Nigeria

The number of solar radiations measuring stations in Nigeria has been observed not to effectively describe the necessary variability; as such prediction models are necessary for estimation of solar radiation values using readily available meteorological variables. In this study, solar radiation parameters were determined for Lafia zone, Nasarawa State, Nigeria. Twelve (12) location were carefully selected to avoid sunshine and wind obstruction using a systematic random sampling technique. Three-hour daily measurement (12.00 pm to 2.00 pm) was done on three 12V, 5W solar panels using a pyranometer and the output was estimated using the Angstrom-Prescott Regression Equation. The continuity in the assembled system was measured using an Avometer. The result revealed that solar radiation intensity was found to range from 165.5 W/m2 to 298.6W/m2 with the mean value of 241.24 W/m2.The highest global solar radiation value of 29.8MJ/m2was observed in April while the lowest value of 16.5MJ/m2was observed in August. The extraterrestrial solar radiation was found to range from 9.06 MJ/m2 in August to 26.60 MJ/m2 in February with average value of 20.96MJ/m2. The atmospheric transmission coefficient over the year is found to range from 0.7 in July and September to 1.4 in December. The obtained atmospheric transmission coefficient determined for the year (2019) is a good indication for solar radiation application in Lafia geo-political zone, Nasarawa State. The performance of the developed model is observed to imply that it can be used to predict global solar radiation for Lafia zone in Nasarawa State.
THE CONCEPT OF SCHOOL TRAINING AND UPBRINGING IN THE CONTEXT OF LIFE-LONG EDUCATION

The article deals with the problems of ensuring the continuous development of a student in the system of general secondary education. The authors see the solution to this problem in the substantiation and practical implementation of the competence-contextual concept of training and education. The theoretical and methodological core of the proposed concept is an integral combination of: 1) the ideas of lifelong education as a process of building the potential of an individual moving along its steps; 2) a competency-based approach that sets the requirements for the results of training and education; 3) the theory of contextual education, creatively adapted to the conditions of a comprehensive school. The relationships between the theoretical provisions of the competence-contextual concept of training and education are described. The necessity of using the “educational competence” invariant as a cognitive mechanism for the formation of competency-based education outcomes in high school, as well as at subsequent levels of lifelong education, is substantiated. The essence of the educational activity of schoolchildren of a competence-contextual type using educational competence, and the teacher’s activities to organize their activities are disclosed. The results of the analysis of the possibility of known pedagogical and psychological-pedagogical theories to become the basis for the implementation of the proposed concept are presented. It is concluded that the theory of contextual education, which has become widespread as the basis of competence education at the levels of professional and additional professional education, can serve as such a basis. The main provisions and principles of contextual education are adapted by the authors of the article to the conditions of a general education school and are used as the basis for the development of a competence-contextual model of teaching and upbringing in a general education school as a link of lifelong education, consisting of four interrelated components: target, content, organizational-procedural and reflective. The effectiveness of this model was tested for 10 years in a pedagogical experiment conducted in 12 secondary schools of the Samara region.
TOWARDS OPEN-SET SEMANTIC SEGMENTATION OF AERIAL IMAGES

Abstract. Classical and more recently deep computer vision methods are optimized for visible spectrum images, commonly encoded in grayscale or RGB colorspaces acquired from smartphones or cameras. A more uncommon source of images exploited in the remote sensing field are satellite and aerial images. However the development of pattern recognition approaches for these data is relatively recent, mainly due to the limited availability of this type of images, as until recently they were used exclusively for military purposes. Access to aerial imagery, including spectral information, has been increasing mainly due to the low cost of drones, cheapening of imaging satellite launch costs, and novel public datasets. Usually remote sensing applications employ computer vision techniques strictly modeled for classification tasks in closed set scenarios. However, real-world tasks rarely fit into closed set contexts, frequently presenting previously unknown classes, characterizing them as open set scenarios. Focusing on this problem, this is the first paper to study and develop semantic segmentation techniques for open set scenarios applied to remote sensing images. The main contributions of this paper are: 1) a discussion of related works in open set semantic segmentation, showing evidence that these techniques can be adapted for open set remote sensing tasks; 2) the development and evaluation of a novel approach for open set semantic segmentation. Our method yielded competitive results when compared to closed set methods for the same dataset.
Peer review declaration

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review : Single-blind • Conference submission management system : ConfTool • Number of submissions received : 420 • Number of submissions sent for review : 420 • Number of submissions accepted : 248 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100) : 59% • Average number of reviews per paper : 2-3 • Total number of reviewers involved : 125 • Any additional info on review process : Step 1. Each submission will be reviewed by two/three professional experts in the related subject area. Step 2. Review Reports received from the reviewers will be judged by one of the editors. Step 3. If there are large discrepancy between two reviewers, the editor can assign a new reviewer or judge at his/her own. Step 4. The Review Reports will be sent to authors to modify the manuscript accordingly. Step 5. Authors will be required to revise their papers according to the points raised. Step 6. Revised version will be evaluated by one of the editors for the incorporation of the points raised by the reviewers. If all reviewers’ comments have been addressed, the paper will be accepted for publication. • Contact persons for queries : Name : Carsten Rode, Menghao Qin Affiliation: Technical University of Denmark Email : car@byg.dtu.dk , menqin@byg.dtu.dk
Research on the Effectiveness of Application of Tabletop Games in English Vocabulary Learning at Elementary School

The purpose of this research is to explore the impact of "tabletop games integrated into English teaching" on the effectiveness of English vocabulary learning and learning attitudes of third-grade students.The research method used is the quasi-experiment.The subjects are two normal classes of students in the third grade of an elementary school in Tainan.They were divided into two groups, experimental group and control group.All of them were allowed to review the English vocabulary learned in the English classroom after school over the research period.The experimental group played tabletop games to review English vocabulary, and the control group used traditional writing and recitation method to review English vocabulary.The test tools include the English vocabulary tests before and after the experiment and feedback questionnaires.Statistical methods such as descriptive statistics, analysis of covariance, independent samples t-test, and paired samples t-test were used for data analysis.The research results included: (1) Both groups of students have made significant progress in "listening comprehension of English vocabulary"; (2) Both groups have made significant progress in "spelling" ability and the average progress the students in the experimental group have made was greater than the students in the control group did; (3) The students in the experimental group as a whole expressed a middle-to-high degree of satisfaction with "tabletop games integrated into English teaching" and have had a positive attitude to it.Finally, specific suggestions were made based on the research results for reference by teachers, schools, and education-related administrative units.
Reinforcement Learning Agent for a Flight Simulation Video Game

This paper is a case study analysis of the viability of using machine learning methods for skilled NPC agents in production level video games and how they compare to their hand-coded counterparts.The implementation and experiments were made in a simple OpenGL game about flying an aircraft through a set of checkpoints without crashing.Our conclusion is that current machine learning methods are not feasible for building the NPC agent, because, while they simplify the agent's design, they exponentially complicate the testing and debugging processes without offering an improved ability for the NPC.
Mentoring As A Resource For Professional Development Of Teachers

In the context of growing uncertainty in the implementation of systematic reforms and transformations in the field of education, the problem of attracting young teachers to school is becoming urgent. The main idea of the article is the authors' statement that various formats of modern mentoring in the pedagogical environment are promising for securing young teachers in the profession. Mentoring contributes to the translation of the value-semantic attitudes of the teaching profession from experienced teachers to young people, affects the adaptation of university graduates in an educational organization. The purpose of the study is, based on the study of foreign and domestic theory and practice of education, to characterize the main trends in the development of mentoring activities. Methodology, methods and techniques are as follows. A comparative analysis of foreign and domestic literature on positive mentoring practices, a survey of teachers are aimed to identify attitudes to the problem of mentoring, the forms of its organization. The results are systematized main approaches that exist in European countries to the development of mentoring programs. There are analyzed data of the TALIS-2013 survey on mentoring in Germany, Finland, Hungary, Portugal, Montenegro, etc. We characterized the conditions that affect the effective development of mentoring activities: state participation in the development of mentoring programs; the presence of a system of moral incentives for mentors; training of mentors in the system of additional education; monitoring and self-assessment of educational deficits and their replenishment in the mentoring dyad; stable internal motivation for mentoring activities.
A FOUNDATION FOR RETHINKING: ON COLLECTED WORKS BY ANDREY PLATONOV

[Review:] Platonov A. P. Sochineniia. T. 4. 1928-1932: V 2 kn. / Gl. red. N. V. Kornienko; red. toma N. I. Duzhina; Kn. 1. Povesti / Podg. teksta i komm. N. I. Duzhinoi i N. V. Umriukhinoi. M.: IMLI, 2020. 653 s.; Kn. 2. Rasskazy. P’esy. Stsenarii. Stat’i / Podg. teksta i komm. E. V. Antonovoi, B. Dooge, N. I. Duzhinoi, R. E. Klement’eva, N. V. Kornienko, D. S. Moskovskoi, M. V. Osipenko (Bo-go molovoi), E. A. Rozhentsevoi, N. V. Umriukhinoi. M.: IMLI, 2020. 841 s.
Application of the C4.5 Algorithm to Predict the Types of Disease in Pigs Based on Android

Many Indonesian people, especially in Bali, make pigs as livestock. Pig livestock are susceptible to various types of diseases and there have been many cases of pig deaths due to diseases that cause losses to breeders. Therefore, the author wants to create an Android-based application that can predict the type of disease in pigs by applying the C4.5 Algorithm. The C4.5 algorithm is an algorithm for classifying data in order to obtain a rule that is used to predict something. In this study, 50 training data sets were used with 8 types of diseases in pigs and 31 symptoms of disease. which is then inputted into the system so that the data is processed so that the system in the form of an Android application can predict the type of disease in pigs. In the testing process, it was carried out by testing 15 test data sets and producing an accuracy value that is 86.7%. In testing the application features built using the Kotlin programming language and the SQLite database, it has been running as expected.
Image Caption Generation Using CNN-LSTM Based Approach

The Picture Caption Generator automatically represents the content of an image, which is a key problem in artificial intelligence that links computer vision with natural language processing (NLP). There is a growing necessity for context-based natural language image descriptions. Recent advances in
DEVELOPING DIVISITE (DISCOVERY LISTENING WEBSITE) TO FACILITATE STUDENTS’ LEARNING IN LISTENING SUBJECT

This research aimed to develop DIVISITE (Discovery Listening Website) and facilitate students’ learning of the listening subject. The design of this research was educational R&amp;D. The subjects of this study were the second-semester English Department students of STKIP PGRI Trenggalek for the academic year 2020/2021. The research procedure included needs analysis, studying education theories, developing the educational product, validating the product to experts, and field-testing. By using the website and combining it with the three stages in the Discovery Listening technique, it increased students' learning motivation and comprehension toward listening material. It was seen from the results of pre-motivation which obtained a score of 1051 (almost disagree). This implied that respondents rarely planned listening learning activities. Then, the results of the post-motivation questionnaire obtained a score of 1810 (almost agree). Thus, there was an increase related to students' learning motivation in listening by using the Discovery Listening Website. In conclusion, this research successfully developed DIVISITE (Discovery Listening Website) and facilitated students’ learning in listening. Furthermore, this research was able to achieve the research objectives, namely DIVISITE (Discovery Listening Website), to facilitate students learning in the listening subject.
IRIS: Learning the Underlying Information of Scientific Research Interests Using Heterogeneous Network Representation

Understanding scientific research fields and finding potential relations between seemingly distinct fields can help researchers rapidly grasp their most interested topics with expertises. In this study, we construct a heterogeneous network which contains authors, keywords, papers and institutions, and built an "Integrated Research Interest Space (IRIS)" which can represent both author and keyword nodes. Similar keywords in the sense of research interest and research manner can obvious aggregate together. Authors that are interested in different keywords distributed in different IRIS areas, with strongly associated with research objectives and methodologies of the keywords.The average similarities between authors and their real used keywords is significantly higher than that of randomly chosen author-keyword pairs.Based on these observations, we propose a simple algorithm which attempts to recommend potential interested keywords for researchers, and got meaningful results.Our study may also give useful hints for understanding research interests and discovering potential cross disciplines.
High security object integrity and manipulation of conceal information by hiding partition technique

In the current period, because of the far reaching accessibility of the Internet, it is incredibly simple for individuals to convey and share interactive media substance with one another.Nonetheless, simultaneously, secure exchange of individual and protected material has turned into a basic issue.Thusly, secure method for information move are the most dire need of the time.Steganography is the science and specialty of shielding the restricted information from an unapproved access.The steganographic approaches hide restricted information into a cover record of type sound, video, text or potentially image.The genuine test in steganography is to accomplish high strength and limit without dealing on the subtlety of the cover document.In this article, a proficient steganography strategy is proposed for the exchange of privileged information in computerized images utilizing number hypothesis.For this reason, the proposed technique addresses the cover image utilizing the Fibonacci grouping.The portrayal of an image in the Fibonacci succession permits expanding the bit planes from 8-bit to 12-bit planes.The test aftereffects of the proposed strategy in examination with other existing steganographic strategies display that our technique accomplishes high installing of privileged information as well as gives top caliber of stego images as far as pinnacle signal-to-clamor proportion (PSNR).Besides, the power of the technique is likewise assessed within the sight of salt and pepper clamor assault on the cover images.