Reviewerly/exHarmony huggingface dataset:
Average-case complexity of the Euclidean algorithm with a fixed polynomial over a finite field

Abstract We analyse the behaviour of the Euclidean algorithm applied to pairs ( g , f ) of univariate nonconstant polynomials over a finite field $\mathbb{F}_{q}$ of q elements when the highest degree polynomial g is fixed. Considering all the elements f of fixed degree, we establish asymptotically optimal bounds in terms of q for the number of elements f that are relatively prime with g and for the average degree of $\gcd(g,f)$ . We also exhibit asymptotically optimal bounds for the average-case complexity of the Euclidean algorithm applied to pairs ( g , f ) as above.
Blockchain as a Complementary Technology for the Internet of Things: A Survey

Blockchain is a new technology resulting from a continuous research on consensus mechanisms to ensure the integrity of a distributed shared replica. It represents a data structure built on a hash function and distributed among the various participants according to previously agreed consensus rules. This work aims to carry out a comprehensive survey of the consensus mechanism that forms the heart of blockchain technology and its suitability for the Internet of Things. It begins by explaining blockchain technology from a historical and technical point of view before approaching the different philosophical approaches within the consensus mechanism, their disadvantage, and their suitability for the IoT sector.
Design of Bathroom Floor Drain Cover Based on Universal Design Concepts

This article is based on the concept of universal design, with family life as the background, through observation and simulation experiments, and using video shooting to record and decompose the process of different people using the existing floor drain cover. After the participants cleaned the floor drain cover, let them score based on the seven principles of universal design. After that, generate personas was set up, and user behavior trajectories were drawn in detail based on the video to analyze the pain points of different people in the family environment using floor drain covers, and put forward the improved design scheme. Finally, the improved scheme was modeled and verified.
POV Display and Interaction Methods extending Smartphone

Persistence of Vision (POV) display uses a technique that presents an after-image that occurs when rhythmic blinking LEDs are moved swiftly. It is a cost-effective and simple method used to turn a large surface into a display. In addition, a characteristic visual expression, such as one floating in the air, can be produced. This technique is widely used because of its advantages, however, it has the limitation of poor interactivity. In this study, a system in which a smartphone can be used as a POV display by mounting a rotation mechanism and installing original applications is suggested. Furthermore, examples of the application and the possibility of interaction methods using this system are presented, including the concept, implementation, experimental results, and implications.
Didactic Adaptation with ICT’s Preliminary Educational Proposal

First, a collection of information from the educational system of Ecuador corresponding to basic general education was carried out, from this document the information on the general and specific objectives of the subjects from first to sixth in which “Caso Mile..” is found is derived, with which we aim to a single subject that is Language and Literature that according to the ministerial report works in 5 blocks that are detailed in the graph, all this at the macro level of curricular concretion, going to the meso curricular level, there is already the annual curricular planning with its evaluation criteria and evaluation indicator going down to the micro level where you can already see the planning of the didactic unit and within this it is necessary that through a IDCA (Individual Diagnosis of Curricular Adaptation) adaptation planning can be considered. Now the IDCA is enriched with the information obtained from the reports presented annually by “Caso Mile..”, so we have the most relevant things explained in the table from the second year to the fifth and it is studying the sixth. Then the proposal of didactic adaptation with ICTs is launched, where reviewing the ministerial objectives the minimum achievements of scope, an initial evaluation must be carried out using the resources that currently have to cope with the teaching of “Mile.. Case” and with these results propose the use of Ramps and adaptations if necessary of hardware and software to strengthen your skills. The problem that was seen when reviewing the history is that the reports have little or no curricular adaptations, the maximum is to do fewer repetitions and achieve the minimum achievements in the subjects, the potential we have in this case is that we work at the therapy level At the pedagogical level, there is speech therapy, occupational therapy and physical therapy that can be fed to exercise the adaptation of specialized hardware and software.
Foreign language communication as the basis for the professional training of future engineers at the university

This article is devoted to the problem of the formation of foreign language communication among university students of technical specialties. The approaches of Russian researchers to the definition of the concepts of "foreign language communication", "competence of foreign language communication", "professional foreign language communication" are considered.
Pacific Fleet Special-Purpose Underwater Rescue Party (EPRON): Shch-Class Submarine Rescue Operations as Contribution to Strengthening Defence Potential of the Soviet Far East in the 1930s

The research objective is as follows: to analyse Shch-class submarine rescue operations conducted by the Special-Purpose Underwater Rescue Party (EPRON) in the Pacific Ocean as a contribution to strengthening the defence potential of the Soviet Far East in the 1930s. Scientific originality of the study involves a comprehensive analysis of the EPRON activity in the Pacific Border district in the mentioned period. As a result, it is proved that the Red Banner Special-Purpose Underwater Rescue Party contributed greatly to the Pacific fleet provision, played an important role in improving rescue services in the Pacific region. The EPRON performed a wide range of underwater works, conducted emergency operations to rescue Shch-class submarines.
Ratio control and fault handling of aero-naval traction systems using neural network theory

In this paper, a new ratio control solution has been developed. The main goal of the developed solutions is to solve the ratio control problem of the aero-naval traction systems based on the structure of two blend stations. As well as, fault diagnoses and handling algorithm for the deficiency or loss of any propeller in aero-naval traction systems have been implemented, to ensure the ratio control of both outputs against the reference changing and disturbances. The proposed solutions include designing a centralized algorithm using neural network-based control. As well as two solutions proposed for configuring the blend station blocks, the first depends on the master-slave technique and the second depends on the adaptive blend factors. All software algorithms are implemented in LabVIEW software and tested in real-time.
Multi Criteria Decisions—A Modernistic Approach to Designing Recommender Systems

Recommender systems (RS) are the most widely used technique to suggest the users their likings based on the ratings and ranking given by another set of users from the same community. These recommendations are based on mostly a single-criterion rating or the average of overall ratings. These overall ratings avoid the implementation of fine grain analysis of the users’ behavior. The performance of any recommender system can be highly improvised by implementing the multi criteria recommender systems (MCRSs). In MCRSs, more feature reviews are taken into consideration in the algorithm making the recommendation process more efficient. Any comment given by the user online has a rich set of words that specify his preferences also known as review elements. There are many methods to extract these review elements, most widely used are Sentiment Analysis or Text Mining Methods. The recommender systems are more efficient if these review elements are incorporated in the algorithm. The major problems of RS like cold start problems and sparsity problems can be minimized substantially using this technique. The main aim of this paper is not only to understand these review items better, but explore methodologies of incorporating these elements into the RS to develop an efficient recommender system. It also explains how these elements can be incorporated in the recommender algorithms to enhance the RSs performance. This paper also presents the future trends to design efficient recommender systems using multi criteria decisions systems.
Fingertips Detection With Nearest-Neighbor Pose Particles From a Single RGB Image

Vision-based detection of fingertips is useful for freehand Human-Computer Interaction (HCI)—especially in virtual, augmented, and mixed reality—to have a seamless experience. The estimation of fingertips position in an RGB image involves overcoming various challenges like occlusion, appearance ambiguities, etc. The general approach relies on a two-stage pipeline involving hand location and detection of fingertips for a single hand. This paper presents an effective single-stage Convolutional Neural Network (CNN) for the detection of fingertips of both hands. We use a set of reference points, referred to as pose particles, and train a CNN model end-to-end to find the N-nearest particles in the proximity of each fingertip. Moreover, the same CNN model is used to compute the position vector’s components with reference to these N-nearest neighbors. Finally, a fingertip position is estimated by computing the centroid of all the points given by these position vectors. With the proposed approach, it is possible to estimate the fingertips position for single or double hands. Moreover, there is no requirement for prior hand localization. We demonstrated the feasibility and effectiveness of the proposed methodology by performing experiments on three different datasets.
Research on the Value of the Construction of Intelligent Sports Park for Perfecting Public Sports Service System

This article revolves around the contents of the 19th National Congress of the Communist Party and General Secretary Xi Jinping on sports power, national fitness, social conflicts, sports public service system, artificial intelligence, etc., and analyzes and summarizes the successful experiences of domestic intelligent sports parks. Therefore, the value of the intelligent sports park in improving the public service system is summarized.
Variable Fragments Evolution in Differential Evolution

The crossover operator plays an important role in Differential Evolution. However, the choice of proper crossover operator and corresponding parameters is dependent on the features of the problems. It is not easy for practitioners to choose the right crossover operator and associated parameter value. In the newly proposed method, a novel evolution scheme called Variable Fragments Evolution was presented. During the evolution, the roughly fixed fragments of genes of all individuals were selected in a population for directional variation. Variable Fragments Evolution was compared with commonly used binomial crossover. Experimental results show that Variable Fragments Evolution exhibits better performance than the binomial crossover. Thus it can serve as an alternative evolution scheme for Differential Evolution.
An association rule based recommender system for learning materials recommendation

The classic learning environments are based on the "one size fits all" approach, that is to propose the same contents to all learners without considering their preferences and abilities. This work aims to develop a learning environment that provides personalized contents to learners. For this, a new association rule based recommendation approach (A_RS) is proposed and integrated into this environment. A_RS recommends learning materials taking into account learners' preferences, prior knowledge and memory capacity.
Design and Implementation of Handwritten Digit Recognition Using Deep Convolution Neural Networks

MNIST dataset is a huge collection of handwritten digit images along with proper annotations and labeling. With the dramatic advent of deep learning and underlying models, recognition of handwritten digits is heavily targeted in the literature. Convolutional neural network (CNN) is a most successful model in the field of computer vision. Due to its automatic feature extraction capability, CNNs are widely adopted for these kinds of recognition and detection tasks. In this work, we employ CNN for the handwritten digit recognition task using MNIST dataset and our proposed architectures achieves a remarkable accuracy. Moreover, we also present the future research direction in this handwritten digit recognition task.
Locally Recoverable Codes correcting many erasures over small fields

Abstract We define linear codes which are s -Locally Recoverable Codes (or s -LRC), i.e. codes which are LRC in s ways, the case $$s=1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>s</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math> roughly corresponding to the classical case of LRC codes. We use them to describe codes which correct many erasures, although they have small minimum distance. Any letter of a received word may be corrected using s different local codes. We use the Segre embedding of s local codes and then a linear projection.
Recommender System for Resolving the Cold Start Challenges Using Classification

Recommender Systems are quite popular and very useful for predictions of various products to consumers by providing recommendations. It deals with the definite type of items and produces the recommendations that are personalized to deliver effective and valuable suggestions to the consumer. The cold-start problem is one of the challenges in recommender systems. The cold-start situation arrives when products added to the collection have either no experiences, or very little. This causes a challenge for collaborative filtering algorithms mainly because they rely on the interactions of the item to make recommendations. In general, it is much harder to ask new user about their personal information (users don’t want to answer too many questions). But it is easier to ask a lot of information about a new item (people who add it are interested in filling in this information to make their products recommended to the customers). The proposed system delivers the recommendation of new items to existing users with high consistency and precision.
Development of Machine Learning Model Using Least Square-Support Vector Machine, Differential Evolution and Back Propagation Neural Network to Detect Breast Cancer

Recently death rate among women increases due to Breast Cancer. Breast Cancer diagnosis system has been implemented with the help of Different Machine learning algorithms. Out of those, in our present work, we have used DE, LSSVM, and BPNN algorithms for developing Machine learning models. Here the training dataset is taken from UCI repository. In this system, we compare results of LS-SVM and backpropagation neural networks to generate accurate results at an early stage. Early detection increases the chances of treatment which helps to save women Life. It will be helpful to medical field because it avoids loss of data.
Analyzing Emotions in Conceptual Models Verification Tasks performed in Online Contests

Emotion research in the area of software engineering has gained significant attention. Mostly this research has been focused on understanding the role of emotions in software programming carried out within collaborative software development environments. With the purpose of providing more evidence on emotion research in the early stages of the software life cycle, in this paper, we report the results of a live study conducted in competitive conditions. The main objective of the study is to analyze the emotions expressed by competitors when performing verification tasks with the support of CoSTest, a model-driven testing tool. Our results show that participants tend to experience more positive emotions (e.g., attentive, alert, active) than negative emotions (upset, hostile, afraid) when verification tasks are performed in an online contest.
Island model in ActoDatA

In this paper, we make a first assessment of the performance of ActoDatA, a novel actor-based software library for distributed data analysis and machine learning in Java that we have recently developed. To do so we have implemented an evolutionary machine learning application based on a distributed island model. The model implementation is compared to an equivalent implementation in ECJ, a popular general-purpose evolutionary computation library that provides support for distributed computing.
Identifying Reliable Recommenders in Users’ Collaborating Filtering and Social Neighbourhoods

Recommender systems increasingly use information sourced from social networks to improve the quality of their recommendations. However, both recommender systems and social networks exhibit phenomena under which information for certain users or items is limited, such as the cold start and the grey sheep phenomena in collaborative filtering systems and the isolated users in social networks. In the context of a social network-aware collaborative filtering, where the collaborating filtering- and social network--based neighbourhoods are of varying density and utility for recommendation formulation, the ability to identify the most reliable recommenders from each neighbourhood for each user and appropriately combine the information associated with them in the recommendation computation process can significantly improve the quality and accuracy of the recommendations offered. In this chapter, we report on our extensions on earlier works in this area which comprise of (1) the development of an algorithm for discovering the most reliable recommenders of a social network recommender system and (2) the development and evaluation of a new collaborative filtering algorithm that synthesizes the opinions of a user’s identified recommenders to generate successful recommendations for the particular user. The proposed algorithm introduces significant gains in rating prediction accuracy (4.9% on average, in terms of prediction MAE reduction and 4.2% on average, in terms of prediction RMSE reduction) and outperforms other algorithms. The proposed algorithm, by design, utilizes only basic information from the collaborative filtering domain (user–item ratings) and the social network domain (user relationships); therefore, it can be easily applied to any social network recommender system dataset.
Optimal recombination and adaptive restarts improve GA performance on the asymmetric TSP

We propose a new genetic algorithm (GA) with optimal recombination and adaptive restarts for the asymmetric travelling salesman problem (ATSP). The optimal recombination problem (ORP) is solved in a crossover operator based on a new exact algorithm that solves the ATSP on cubic digraphs. We use an adaptive restart rule based on the Schnabel census estimate. A computational experiment on the known benchmark instances shows that the proposed algorithm yields results competitive to those of state-of-the-art algorithms for the ATSP and confirms that the ORP may be used successfully in genetic algorithms.
Automatic Adaptive Sequencing in a Webgame

Intelligent tutoring systems can improve student outcomes, but developing such systems typically requires significant expertise or prior data of students using the system. In this work we propose a new approach for automatically adaptively sequencing practice activities for an individual student. Our approach builds on progress for automatically constructing curriculum graphs and advancing a student through a graph using a multi-armed bandit algorithm. These approaches have relatively few hyperparameters and are designed to work well given limited or no prior data. We evaluate our method, which can be applied to a diverse range of domains, in our online game for basic Korean language learning and found promising initial results. Compared to an expert-designed fixed ordering, our adaptive algorithm had a statistically significant positive effect on a learning efficiency metric defined using in game performance.
Variances of Surface Area Estimators Based on Pixel Configuration Counts

Abstract The surface area of a set which is only observed as a binary pixel image is often estimated by a weighted sum of pixel configurations counts. In this paper we examine these estimators in a design based setting—we assume that the observed set is shifted uniformly randomly. Bounds for the difference between the essential supremum and the essential infimum of such an estimator are derived, which imply that the variance is in $$O(t^2)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>O</mml:mi> <mml:mo>(</mml:mo> <mml:msup> <mml:mi>t</mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> as the lattice distance t tends to zero. In particular, it is asymptotically neglectable compared to the bias. A simulation study shows that the theoretically derived convergence order is optimal in general, but further improvements are possible in special cases.
Continuity of Traditions in the Context of the History of One Department: Lev Gerasimovich Filatov and Alexander Petrovich Lebedev

Introduction. The relevance of the topic is related to the preservation of the significant role of the individual in the development of education. The head of the department, as one of the key structural divisions of the higher educational institution, has played an important role in the implementation of the scientific and pedagogical tasks of the university and the reproduction of teaching staff. Materials and Methods. The methodological basis of the research is the socio-cultural perspective of the study of the life activity of educational actors, which involves taking into account the social, cultural, spiritual and moral factors of the formation of the personality of a higher school teacher and studying the impact of this personality on the development of education. The study is historical and biographical in nature, contains elements of the direction of social history. Results. The scientific and pedagogical path of the two heads of the Department of the History of the Motherland (until 1991 – the history of the Communist Party of the Soviet Union) is also shown in the context of the development of the department as a structural unit of the university, the higher school in the republic. The socio-cultural conditions for the formation of personal and professional qualities of two teachers, scientists, heads of the department, their role in the development of one of the most important structural divisions of the university are revealed. Discussion and Conclusions. Continuity of personnel, preservation of traditions, and transfer of experience are important for all spheres of society, and especially for the sphere of science and education. On the example of the activity of the personalities of the two heads of the department, the implementation of the continuity of managerial, methodological, pedagogical principles of teaching and management of the structural unit of the university is illustrated.