Reviewerly/exHarmony huggingface dataset:
Innovations in the Professional Activity of Teachers as a Leading Reference Point of Work of Institutions of Higher Pedagogical Education

The article reveals the current problem of preparing future teachers to work in conditions of modernization of the education system, the rapid introduction of various innovations in professional teaching activities. Innovation in education is considered as an approach and method that provides a planned qualitative change of professional relations in educational institutions in the direction of strengthening the innovative potential of the educational environment to solve the problem of training future professionals to work in the informatization of educational space, implementation of inclusive approach and non-discrimination and other innovation challenges. The innovative component of the functions of modern school teachers is revealed and characterized, which become extremely multiple and, in addition to the traditional didactic, provide consultative, diagnostic, correctional and developmental, organizational and methodological, medical and social and others. Based on the study of the experience of training future teachers in free economic education and the results of the survey of higher education and teachers, it is established that special attention in the educational process should be paid to modernizing the content of education and improving training technologies for future professionals. It is proved that such methods and techniques are effective in teaching pedagogical disciplines, in which the applicants themselves take an active part in learning, gaining innovative professional experience.
Obscuration Resistant Method For Unmanned Air Vehicle Object Tracking

The target occlusion problem is a difficult problem for Unmanned Air Vehicle (UAV) object tracking, especially when there exists similar object interference, which is very likely to cause model drift. To solve this problem, in this paper we propose a novel anti-occlusion strategy: modeling the interfering target in advance and repositioning the target by finding the best match when the target is obscured. In addition, to accurately determine whether the target is occluded and model the interference target at the right time, we also propose judgment conditions for target occlusion and interference target modeling. Experiments demonstrate that the proposed anti-occlusion algorithm has good robustness and accuracy on both Object Tracking Benchmark (OTB100) and UAV Tracking Benchmark (UAV123).
Lower Eocene shale, south-west Aswan, Egypt: Remote sensing analysis, geological investigations and innovative utilization of Ca-bentonite

The Sinn El-Kaddab plateau, south-west Aswan, Egypt is topped by the Lower Eocene Dungul Formation, which comprises the Nagb Dungul Limestone Member, being underlain by the Abu Ghurra Shale Member (Ca-bentonite). Remote sensing techniques were employed to discriminate the different geological formations of the area. Mineralogy and chemical composition of Ca-bentonite were highlighted. It is composed mostly of silt and clay fraction enriched in montmorillonite, which has high absorptive capacity and water holding power. Geochemically, it contains appreciable concentrations of iron, manganese, potassium, zinc and nickel. Based on its physical and chemical properties, it has been tested in cultivation of pure sandy soil for retaining water around the roots of the plant for as long as possible and to enrich the fertility of the soil. The Egyptian common beans (Paulista var.) were selected to follow the effect of the investigated Ca-bentonite on vegetative growth and seed yield as well as its role in rationalizing the required irrigation water. It proved high efficiency in increasing the productivity of the plant and in rationalizing the irrigation water to about 50%. The vegetative growth increased by about 58 %, as well as the seed crop including seed index, number of seed/per pod and seed germination. The considered Ca-bentonite is a good source for improving the physical properties of sandy soils as well as increasing their fertility. Its role in rationalizing the required irrigation water in cultivation of sandy lands is vital and of prime importance.
Graph Convolution Network Considering Edge Node Feature Aggregation

As the level of power grid intelligence continues to enhance, the identification of power grid topology becomes more and more important. Generating embedded vectors of power grid topology is an important method to identify power grid topology. At present, in the field of embedded expression of graph nodes and semi-supervised learning, graph convolutional networks (GCN) have been widely used. But the typical GCN model performs poorly in the classification performance of graph edge nodes. In order to improve the classification performance of graph edge nodes, this paper proposes a graph convolutional network considering edge nodes feature aggregation (Enfa-GCN). The Enfa-GCN model realizes feature aggregation of graph edge nodes by marking the missing key features of graph edge nodes. This paper conducts a large number of experiments on three benchmark data sets to evaluate the Enfa-GCN model. Compared with the most advanced models, Enfa-GCN has advantages in graph edge node classification and overall graph node classification performance. Among them, Enfa-GCN is 1.42%, 0.44%, and 0.87% higher than GCN on the Cora, Citeseer, and Pubmed data sets, respectively. It shows that the Enfa-GCN model has a significant effect in improving the classification performance of graph edge nodes and the classification performance of whole graph nodes.
Design of Novel Media Communication Platform Based on the Combination of Audio and Short Video Signal

This manuscript studies the design of novel media communication platform based on the combination of audio and short video signal. As an application framework, website can integrate data resources, network resources and application systems to serve users in the form of information management platform and unified user interface. Online news dissemination has high-speed, multimedia, interactivity, database and other performance advantages in information dissemination that traditional media have never had. This paper proposes the novel framework combining the audio and short video signal processing to design the efficient data processing unit. The application scenarios are then validated through testing.
A Gesticulation Superintend Arm with Arduino IDE

In today's era where technological advancement is at its peak, the need for sophisticated and ergonomic machinery is rapidly increasing. With the growing involvement of robots in several fields and the automation of factories, it can be inferred that robotics is the future. Through this paper, robotic arm that can be controlled with the means of human hand gestures is proposed. To achieve this, an accelerometer and a gyro sensor module are used. These modules each have three axes, making them appropriate for sensing hand deflection. To make reliable data, the values obtained are processed using mathematical coMPUtations, scaled, and filtered. This data is utilized to control the arm's movement Because all of the processing happens at the same time, the robotic arm's movement is synchronized with the human arm's motions. The Arduino IDE platform was used to create this robotic arm. Finally, the findings are examined.
Improvement and Development of Educational Activities of the School in Working with Migrant Students

The purpose of the study is to identify ways to improve the educational activities of the modern school, in which migrant schoolchildren are taught together with Russian students. The paper conducts a detailed analysis of the current state of school education that includes migrant students and identifies the main issues associated with the organisation of the educational process. Based on the data obtained, the key areas requiring development are identified and new ways of improving the organisation of the educational process in these areas are proposed. Scientific novelty lies in presenting new ways to improve the level of organisation of the educational process that includes migrant students both in the field of methodological support and in the sphere of workload distribution and the system of teachers’ remuneration. As a result of the study, the following solutions have been proposed as priority innovations: to develop a universal methodological handbook for schools on the optimal organisation of the educational process that includes migrant students; to create an all-Russian electronic school register to display academic paths of migrant schoolchildren; to prepare several sets of all-Russian bilingual electronic textbooks in all subjects of the school curriculum; for schools and universities to develop jointly electronic interactive courses in Russian as a Foreign Language, taking into account students’ age particularities; to create a system for assessing additional time spent by teachers on the adaptation of the educational process and a more rational redistribution of workload among pedagogical staff; to elaborate principles for calculating incentive allowances to reflect the high level of competence of teachers who work in classes where migrant students are taught together with Russian schoolchildren.
Region Proposal-Based Convolutional Neural Network for Missing Child Detection

Object identification has exploded alongside the remarkable progression of Convolutional Neural Network and its variations since 2012. Identification of objects in a field of computer vision has significantly increased especially to face and human subjects. Subsequently, computer vision has also addressed a global challenge on certain systems such as missing child detection in the last decade. However, there are certain challenges and limitations in the detection of children in the crowd only with face detection. Thus this paper proposes a Regional proposal based Convolutional Neural Network system that addresses the global challenges using three add-on features along with face. The real time dataset has been collected and the experimentations are conducted to validate the significance of the proposed system.
Construction of College English Data Resources and Change of Teacher Positioning Using QoS Constraints

Cultivating students' autonomous learning abilities has become a research hotspot in CE (College English) reform, and the new CE autonomous learning teaching mode with students at the center also requires teachers to change traditional teaching ideas. The traditional teaching mode and teacher orientation have changed dramatically as a result of the new situation of CE teaching reform. The design and implementation of a CE data resource base based on a web database demonstrates that these technologies provide people with greater convenience and practicality. A GA (Genetic Algorithm) based on a QoS (Quality of Service) constraint is proposed on this basis. This algorithm can find a suitable resource node in the computing resources for each subtask that meets the constraint conditions and assign it to the corresponding task. Information-based education has become a powerful driving force for educational revolution, with computer technology and network information technology making English classroom teaching richer, more flexible in form, rich in content, and searchable in data.
How to Effectively Reduce Failure Analysis Time?

Abstract Debugging is one of the most expensive and challenging phases in the software development life-cycle. One important cost factor in the debugging process is the time required to analyze failures and find underlying faults. Two types of techniques that can help developers to reduce this analysis time are Failure Clustering and Automated Fault Localization. Although there is a plethora of these techniques in the literature, there are still some gaps that prevent their operationalization in real-world contexts. Besides, the abundance of these techniques confuses the developers in selecting a suitable method for their specific domain. In order to help developers in reducing analysis time, we propose methodologies and techniques that can be used standalone or in a form of a tool-chain. Utilizing this tool-chain, developers (1) know which data they need for further analysis, (2) are able to group failures based on their root causes, and (3) are able to find more information about the root causes of each failing group. Our tool-chain was initially developed based on state-of-the-art failure diagnosis techniques. We implemented and evaluated existing techniques. We built on and improved them where the results were promising and proposed new solutions where needed. The overarching goal of this study has been the applicability of techniques in practice.
Salience-simplification strategy for markedness of causal subordinators: “Because” and “since” in argumentative essays

Previous studies have discriminated between different causal subordinators by assessing their lexico-semantics, clausal positioning, and the potential for separating punctuation marks. Distinguishing between the subordinators "because" and "since" in argumentative essays, this study adds to this line of research by a) exploring more contextual factors around these two causal markers, b) incorporating the effective factors in multifactorial models to measure their weights in discriminating between these two causal markers, and c) examining the different weights borne by individual factors from the perspective of markedness correspondence strategies. We retrieved 976 causal complex sentences (488 for each subordinator) from student argumentative essays and applied conditional inference tree models to these data. The results revealed that six factors were effective in discriminating between causal subordinators. The semantic factor clausal relationship indicated preferred clausal relationships introduced by "because" and "since," while five syntactic factors demonstrated form correspondence to the markedness of the subordinators. Furthermore, conditional inference tree models revealed the factors' relative weights in discriminating between "because" and "since," suggesting that writers adopt the salience-simplification strategy to match the markedness of the subordinators in argumentative essays.
Ability to generate output series for Hysteresis Reservoir Computing

Hysteresis reservoir computing generates a variety of output series by changing the parameters of the elements. In this paper, we show that hysteresis reservoir computing has improved its learning ability by changing the parameters, and can represent specific series data.
An Agglomerative Hierarchical Clustering Framework for Improving the Ensemble Clustering Process

Agglomerative Hierarchical Clustering (AHC) is a general type of Hierarchical Clustering (HC) that forms clusters from the “bottom-up.” This paper focuses on the development of AHC methods based on ensemble-based approaches. Accordingly, we develop an AHC framework based on clusters clustering along with an innovative similarity criterion that performs clustering through ensemble approaches. The proposed algorithm consists of three main steps. In the first step, a group of single AHC methods are combined to detect relationships between samples and as well as the formation of initial clusters. The similarity of the samples is calculated using an innovative similarity criterion based on the clusters created. In the second step, all the initial clusters created by different methods are re-clustered to form hyper-clusters. After clusters clustering, each sample is assigned to a hyper-cluster with maximum similarity to create the final clusters in the third step. The comprehensive experimental study has been performed to evaluate the performance of the proposed algorithm based on several benchmark datasets from the UCI machine learning repository. The results clearly show that the proposed ensemble AHC-based framework performs better than the state-of-the-art methods.
Sharing Health Records in Senegal Using Blockchain

Electronic Health Records offer real advantages for accessing and storing patient health information, which can improve the management of patient care. However, the attractive features of electronic records (accessibility, portability, and portability of patient health information) also present privacy risks. Organizations need to share person-specific health data without disclosing the privacy of their subjects.
The framework design of question generation based on knowledge graph

This paper proposes a systemic design framework GTQG (Graph Transformer Question Generator), which generates questions based on the combination of knowledge graph and graph neural network. We use graph Transformer to capture semantic relations, and incorporate into multi-dimensional external information such as question types and external question libraries to present knowledge graph. Thus, a series of questions can be generated based on an n-hop subgraph. In the application of educational scenarios, our approach GTQG serves for questioning teaching help improve students' reasoning and logic skills in text reading practice.
<scp>VR‐Based</scp> improvement of aerobics teaching quality

Currently, most of students do not pay much attention to aerobics. Affected by various factors, students' participation in aerobics learning is low and lack of interest. However, regular aerobics exercise can enhance physical fitness and improve physical and mental health. Compared with other sports, aerobics is not so boring, and the exercise effect is excellent. The introduction of virtual reality (VR) technology in aerobics teaching not only makes up for the deficiency of traditional aerobics teaching, but also brings students a great sense of novelty, and teachers' teaching efficiency and students' learning efficiency will be significantly improved. The empirical variogram‐based 360° aerobics teaching video coding unit (CU) partition algorithm is proposed to improve coding efficiency and provide real visual experience. Experiments show that the proposed algorithm performs well in BD‐Rate and Quality of Experience (QoE), so that students can adjust movements according to the standard aerobics movements, which will greatly improve the efficiency of aerobics teaching.
User Experience (UX) Librarianship and Health Sciences Libraries (HSLs)

This article provides the results of an investigation into how health sciences librarians with user experience (UX) duties describe their roles and initiatives. Through an online survey, 40 respondents provided details on institutional demographics, work plans, participant recruitment, and data collection. Four interviews were also conducted. This investigation provides perspectives on UX within the health sciences library (HSL) environment including barriers and successes. It is hoped that the results of this article will influence research into timely and efficient UX initiatives within HSLs and provide librarians, staff, and administrators the information they need to support decision making.
Extensions of Karger’s Algorithm: Why They Fail in Theory and How They Are Useful in Practice

The minimum graph cut and minimum s-t-cut problems are important primitives in the modeling of combinatorial problems in computer science, including in computer vision and machine learning. Some of the most efficient algorithms for finding global minimum cuts are randomized algorithms based on Karger’s groundbreaking contraction algorithm. Here, we study whether Karger’s algorithm can be successfully generalized to other cut problems. We first prove that a wide class of natural generalizations of Karger’s algorithm cannot efficiently solve the s-t-mincut or the normalized cut problem to optimality. However, we then present a simple new algorithm for seeded segmentation / graph-based semi-supervised learning that is closely based on Karger’s original algorithm, showing that for these problems, extensions of Karger’s algorithm can be useful. The new algorithm has linear asymptotic runtime and yields a potential that can be interpreted as the posterior probability of a sample belonging to a given seed / class. We clarify its relation to the random walker algorithm / harmonic energy minimization in terms of distributions over spanning forests. On classical problems from seeded image segmentation and graph-based semi-supervised learning on image data, the method performs at least as well as the random walker / harmonic energy minimization / Gaussian processes.
Leakage-Resilient $$\mathsf {IBE}$$/$$\mathsf {ABE}$$ with Optimal Leakage Rates from Lattices

We derive the first adaptively secure $$\mathsf {IBE}$$ and $$\mathsf {ABE}$$ for t-CNF, and selectively secure $$\mathsf {ABE}$$ for general circuits from lattices, with $$1-o(1)$$ leakage rates, in the both relative leakage model and bounded retrieval model ( $$\mathsf {BRM}$$ ). To achieve this, we first identify a new fine-grained security notion for $$\mathsf {ABE}$$ – partially adaptive/selective security, and instantiate this notion from $$\mathsf {LWE}$$ . Then, by using this notion, we design a new key compressing mechanism for identity-based/attributed-based weak hash proof system ( $$\mathsf {IB}$$ / $$\mathsf {AB}$$ - $$\mathsf {wHPS}$$ ) for various policy classes, achieving (1) succinct secret keys and (2) adaptive/selective security matching the existing non-leakage resilient lattice-based designs. Using the existing connection between weak hash proof system and leakage resilient encryption, the succinct-key $$\mathsf {IB}$$ / $$\mathsf {AB}$$ - $$\mathsf {wHPS}$$ can yield the desired leakage resilient $$\mathsf {IBE}$$ / $$\mathsf {ABE}$$ schemes with the optimal leakage rates in the relative leakage model. Finally, by further improving the prior analysis of the compatible locally computable extractors, we can achieve the optimal leakage rates in the $$\mathsf {BRM}$$ .
A relation calculus for reasoning about t-probing security

Abstract In the context of side-channel attacks against cryptographic circuits, t -probing security characterizes the amount of information derivable about sensitive values (e.g., keys) by observing t output/internal values. Non-interference is a useful mathematical tool used by researchers to assess the probing security of a circuit which employs Boolean masking to protect itself from attacks. However, reasoning about non-interference still requires either difficult ratiocination or complex automatic tools. In this work, we propose a novel point of view to reason about non-interference, by exploiting the Walsh transform of a Boolean function. To this end, we introduce a calculus for mechanically reasoning about the shares of a variable and show that this formalism provides a lean algebraic explanation of known compositional patterns allowing for the discovery of new ones. Eventually, we show how this formalism can be applied to study the probing security of known cryptographic gadgets.