Reviewerly/exHarmony huggingface dataset:
Digital resources of the American Library Association for green and sustainable libraries

The experience of Russian libraries in educating ecological (ecological information) culture is widely discussed in domestic professional media. However, in Russia we feel the lack of information on relevant activities of foreign libraries and/or library associations. The authors offer their analysis of digital resources in sustainable development, green movement and ecological education of the population as provided by the American Library Association (ALA) and presented on ALA website. The resources comprise information on the efforts of ALA structural units related to organization of sustainable development activities at libraries; ALA politics and guiding materials; the interactive blog on libraries’ supporting sustainable communities; the catalog of new books in the “American Libraries” series within the subject scope “Sustainable development at the libraries”, and key international documents on sustainable development. The concept of three components of sustainable development of the society – Economy, Ecology and Equity – aka Three E, which ALA considers to be fundamental for sustainable libraries, is analyzed. Based on their analysis, the authors suggest that libraries will design and realize their own projects unifying all Three E. They conclude that further studies of the efforts of foreign libraries and/or library associations in ecological education and development of ecological (ecological information) culture, and, in particular, the study of relevant digital (electronic) resources are vitally important for Russian libraries and library science, including commencing digital (electronic) library science.Ecology and studying the related experience of libraries are among the major lines of activities of the Russian National Public Library for Science and Technology (RNPLS&amp;T). The paper is prepared within the framework of the State Order № 075-01300-20-00.
A Video-Based Method for Vehicle Counting Based on Motion and Color Features

The vehicle detection and counting plays a crucial role in traffic control. With the development of intelligent transportation system (ITS), vehicle counting based on traffic video shows great importance and huge advantages compared with traditional technologies. However, the complexity and accuracy of many algorithms are often difficult to get a good balance. At the same time, the motion and color features of the vehicle are sometimes not fully utilized. Based on these, a video-based method for vehicle counting based on motion and color features was proposed. The vehicle will be detected based on motion and color features both to improve the accuracy of detection, and the counting information will be converted from detection information based on a horizontal line. The results show that the proposed method is effective on different videos.
RNA genetic algorithm based on octopus learning mechanism

Genetic algorithms are often easy to fall into local optimum, Inspired by octopus RNA gene editing ability and learning ability, this paper proposed an RNA genetic algorithm based on octopus learning mechanism (LRNA-GA), which uses a single RNA chain to represent the individuals of the population, Imitating the octopus's A-to-G RNA editing method to replace traditional gene mutations, using behavioral learning to design the RNA chain, and determining the possibility of RNA editing by evaluating the RNA chain, so as to quickly jump out of the local optimal solution. The effectiveness of LRNA-GA is tested through typical benchmark functions, and it has fast search capabilities and high accuracy.
Fairy Tales World Specifics in the Perception of a Child

The article shows the child’s perception of the phenomenon of a fairy tale. Research relevance: The world in a fabulous way amazingly changes the thinking of the child, teaches him life and perceptual perception of the surrounding reality. Research materials and methods: in this work authors used methods of analysis of works based on experimental research and statements of scientists’ psychologists such as Jean Piaget, Buhler, L. S. Vygotsky, A. M. Gorky, V. A. Sukhomlinsky and others on the influence of fairy tales on the children thinking. Analysis of such concepts as the world of fairy tales, artifactism and fantasy. Research objectives: consideration of the psychological perception of art by children, analysis of the child’s perception of the relationship between the forces of science and magic in the mind. Research results: identifying ideas about educational teaching of children based on multifaceted interests such as pursuit of observation, ensuring artistic value of scenes and focus on thinking. Conclusions: the ability to recognize human interests, which are very important in the process of forming a child’s creative activity.
Decision-Making under Group Commitment

Coordination is essential for establishing and sustaining teamwork. Agents in a team must agree on their tasks and plans, and thus, group decision-making techniques are necessary to reach agreements in teams. For instance, to agree on a joint task, the agents can provide their preferences for the alternative tasks, and the best alternative could be selected by majority. Previous works assumed that agents only provide their preferences for the alternatives. However, when selecting a joint task for teamwork, it is essential to consider not only the preferences of the agents, but also the probability of the agents being able to execute the task if it is selected. In this paper, we propose a novel model, the decIsion-MAking under Group commItmeNt modEl (IMAGINE), for computing the optimal decision for a team considering several parameters. Each agent provides: (1) the utility of each alternative for the team, (2) the associated cost for the agent by executing the alternative, and (3) the probability that the agent will be able to execute the alternative task. The IMAGINE gathers these data from the agents, as well as the requisite quorum for each alternative task, which is the minimum number of agents required to complete the task successfully. Given this information, the IMAGINE determines the optimal decision for the group. We evaluated the IMAGINE by comparing it to a baseline method that does not consider the quorum requirement. We show that the IMAGINE generally comes up with a better decision than the baseline method and that the higher the quorum, the better the decisions the IMAGINE makes are.
Locality Sensitive Hashing Based Clustering for Large Scale Documents

Nowadays, the size of data continues to increase more rapidly day by day. Considering this situation, large-scale processing has become a very important issue in document clustering, due to its capability to organize large numbers of documents as few meaningful and consistent clusters. In this study, a dataset consisting of 390 English textbooks with a total size of 7.61 GB, has been used for the clustering task. Locality sensitive hashing and k-shingles methods have been used to obtain clusters with high quality. Clusters have been evaluated using cluster validity indices. According to the experimental results, high-quality clusters have been obtained, with 0.88 and 0.79 for Silhouette and Davies–Bouldin scores, respectively.
Scenario-Based Customer Service VR Training System Using Second Language

Since a training system using VR can reproduce an actual training environment, training systems have been studied in commercial fields such as medical care and construction. This immersive experience in a virtual space can have a great effect on learning a second language. In this paper, we propose an immersive learning system that learns phrases used in the customer service industry in the customer service experience. We asked the subjects to experience the system, measured the effects of learning, and evaluated the system. Evaluating the learning effect of phrases used in customer service English on 8 students, all student achieved good learning results. Besides, to evaluate the usability of the system, the VR system was evaluated by performing SSQ to measure VR sickness shows this system doesn't cause virtual sickness, SUS to measure usability shows this system evaluation is higher than average system, and IPQ to measure presence in an immersive space shows this system gives average virtual reality experience.
Economic Benefit Evaluation System of Higher Education

In order to overcome the unscientific and complexity of the economic benefit evaluation of higher education, this paper puts forward a new economic benefit evaluation system of higher education. The system combines three dimensions to include common evaluation indicators, namely, the educated, universities and society. Based on this, the system also combines advanced science and technology, such as computer technology, artificial intelligence technology and cloud computing technology, which can realize data collection, data mining and data storage. The experimental results show that the system can improve the objectivity and rationality of the economic benefit evaluation of higher education.
Evaluation of Classical Data Structures in the Java Collections Framework

The performance of software applications for computer networking, Web services, and cloud computing, with respect to speed, scalability, fault tolerance, and quality of service, is critical. Designing software involves the appropriate choice of data structures, because their performance with respect to space (memory utilization for data storage) and time (execution speed of operations) play significant roles in determining the performance of the software. This paper evaluates the performance of Java Collections implementation of classical data structures and how it scales with increase in data size. The effects of memory allocation, heap memory size, and garbage collection on performance are discussed. Also, this paper identifies areas for improvement in the implementation of the classical data structures and discusses their asymptotic analysis.
Increasing The Ability To Recognize Number Symbols Through The Activities Of Playing Snakes And Stairs For Children Of Group A In Tk Aisyiyah Busthanul Athfal 6 Candi

This research is motivated by the lack of ability of group A children in Kindergarten Aisyiyah Busthanul Athfal 6 Candi in recognizing the symbol of numbers. Based on a preliminary study in Kindergarten Aisyiyah Busthanul Athfal 6 Temple found that 70.59% of 17 Kindergarten A children were still wrong in recognizing good symbols when asked to say by sorting number cards, dancing lines according to the number of drawings, counting many marbles and pasting numbers right. These problems are caused by the introduction of non-matching number symbols, and non-concrete learning media (using worksheets). The solution provided is the introduction of the number symbol by playing snakes and ladders with steps to recognize the symbol number. This research is a classroom action research (CAR) that uses Kemmis and Mc. Taggart. The subject of the action was the children of group A "Kindergarten Aisyiyah Busthanul Athfal 6 Candi, totaling 17 children, each with 13 boys and 4 girls. In this study using three stages, namely pre cycle, cycle I, and cycle II. The results of this study that have been carried out to improve the ability to recognize child group A symbols in Aisyiyah Busthanul Athfal 6 Kindergarten Temple show that the ability to recognize child number symbols from pre-cycle, cycle I, and cycle II has increased. In the pre-cycle completeness the overall value of group A was 29.41%, the first cycle completeness the overall value of group A was 52.94%, and in the second cycle the completeness value of group A was 82.35%. This proves that there is an increase in the ability to recognize child number symbols after a study using a snake ladder game in learning material.
Where the Bugs are: A Quasi-replication Study of the Effect of Inheritance Depth and Width in Java Systems

The role of inheritance in the OO paradigm and its inherent complexity has caused conflicting results in the software engineering community. In a seminal empirical study, Basili et al., suggest that, based on a critique of the Chidamber and Kemerer OO metrics suite, a class located deeper in an inheritance hierarchy will introduce more bugs because it inherits a large number of definitions from its ancestors. Equally, classes with a large number of children (i.e., descendants) are difficult to modify and usually require more testing because the class potentially affects all of its children. In this paper, we use a large data set containing bug and inheritance data from eleven Java systems (seven open-source and four commercial) to explore these two research questions. We explore whether it is the case that a class deeper in the hierarchy is more buggy because of its deep position. Equally, we explore whether there is a positive relationship between the number of children and bugs, if classes with large numbers of children are indeed more difficult to modify. Results showed no specific trend for classes deeper in the hierarchy to be more buggy vis-a-vis shallower classes; the four commercial systems actually showed a negative relationship. The majority of classes across the hierarchy were also found to have no children and those classes included the most buggy.
Simulation of Young’s Double Slit Interference Experiment Based on MATLAB

Due to the high requirements of optical experimental equipment for double slit interference experiment, it is difficult for the laboratory to obtain the theoretical results of the experiment. In this paper, MATLAB software is used to simulate the experimental phenomenon of Young's double slit interference, and the corresponding color interference pattern and light intensity curve can be obtained by inputting different monochromatic light experimental parameters. At the same time, the interference fringes of seven colors of visible light are simulated, and the simulation diagram of the influence of wavelength on the interference fringe spacing is obtained. Finally, the simulation of Young's double slit interference experiment phenomenon is realized, so as to facilitate the teaching and research of optical experiments such as double slit interference.
ICDAR 2021 Competition on Script Identification in the Wild

The paper presents a summary of the 1st Competition on Script Identification in the Wild (SIW 2021) organised in conjunction with 16th International Conference on Document Analysis and Recognition (ICDAR 2021). The goal of SIW is to evaluate the limits of script identification approaches through a large scale in the wild database including 13 scripts (MDIW-13 dataset) and two different scenarios (handwritten and printed). The competition includes the evaluation over three different tasks depending of the nature of the data used for training and testing. Nineteen research groups registered for SIW 2021, out of which 6 teams from both academia and industry took part in the final round and submitted a total of 166 algorithms for scoring. Submissions included a wide variety of deep-learning solutions as well as approaches based on standard image processing techniques. The performance achieved by the participants prove the elevate accuracy of deep learning methods in comparison with traditional statistical approaches. The best approach obtained classification accuracies of 99% in all three tasks with experiments over more than 50K test samples. The results suggest that there is still room for improvements, specially over handwritten samples and specific scripts.
Terminology/Keyphrase Extraction for Creation of Book Indexes in Polish

The paper addresses the problem of automatic identification of phrases to be included in back-of-book indexes. We analyzed books in Polish and English published with subject indexes compiled by their authors. We checked what kinds of phrases are placed in those indexes and how often they actually occur in the corresponding books. In the experiments, we use existing terminology and keyphrase extraction tools. For Polish, the first tool is better than the second one, but for English texts, the results are inconclusive.
Cascaded Coarse-to-fine Network with Hybrid Loss for Eyeball Segmentation in CT Image

Eyeball segmentation in computed tomography (CT) images is the basis of computer-assisted diagnosis and surgery navigation system for eye diseases. Fully automatic eyeball segmentation is challenging due to the blurry boundaries, low contrast, and small proportion the eyeball occupied. We propose a framework based on cascaded coarse-to-fine network, combined with hybrid loss function for eyeball segmentation in CT images. The application of refinement module optimizes the coarse segmentation result. The hybrid loss function composed of CE, IoU, and SSIM simultaneously supervises the region and boundaries of the segmentation. Experiments on 4590 2D head CT images show that our method can effectively maintain the eyeball structure with clear boundaries and reduce the false-positive prediction in noneyeball regions.
Novel four-step phase shifting algorithm based on the products of sines and cosines

Wrapped phase extraction is an essential process for the retrieval of absolute phase and even the computation of object height information in fringe projection profilometry. Over the past few decades, tremendous efforts have been devoted to developing various techniques for computing wrapped phase. By comparison, four-step phase-shifting techniques play an important vehicle for obtaining the wrapped phase of 3D objects. At present, a variety of four-step phase-shifting algorithms show the comprehensive mathematical deduction and their theories are very clear. Analysis from the perspective of theoretical integrity, however, the phase-shifting techniques lack the exploration of arbitrary phase shift. In view of this, inspired by the prosthaphaeresis in trigonometric, we present a novel four-step phase-shifting algorithm. The proposed method includes 16 kinds of four-step phase-shifting fringe combination and corresponding calculation formula of wrapped phase, which are deduced with two frames fringe images of sines and two ones of cosines. Furthermore, simulations and experiments have been carried out to reveal the influence law of variable phase shift on the performance of these approaches.
An Information Technology Resource Management Model for Learners

Information and communication technology has a recognised role. In order to achieve reform and development in all areas, especially in education, it is necessary to keep progressing and develop learning to have the knowledge and ability to apply information and communication technology to use in educational institution administration. It allows the management to plan or set goals in doing work for the best benefit. The objectives of this study were to 1) study information technology resource management, and 2) propose guidelines for information technology resource management in learning management for learners under the Office of the Basic Education Commission. This study involved mixed-methods research. The samples used in this study comprised school administrators, teachers, students and the school committee of educational institutions under the Office of the Basic Education Commission, consisting of the Eastern Economic Corridor (EEC) area, which is a trade and investment promotion zone that is important for the development of the country's competitiveness. The results of the study showed that the guidelines for information technology resource management in learning management for learners in educational institutions under the Office of the Basic Education Commission should be promoted in 4 areas including human resource management, budget management, material and educational information technology equipment management, and general management. As a result, the resource management will be more successful. This affects the appropriate formulation of policies for related departments to promote the management of information technology in the study of learners.
Graphical representation and hierarchical decomposition mechanism for vertex-cover solution space

In this paper, solution space organization of minimum vertex-cover problem is deeply investigated using the K\"{o}nig-Eg\'{e}rvary (KE) graph and theorem, in which a hierarchical decomposition mechanism named KE-layer structure of general graphs is proposed to reveal the complexity of vertex-cover. An algorithm to verify the KE graph is given by the solution space expression of vertex-cover, and the relation between multi-layer KE graphs and maximal matching is illustrated and proved. Furthermore, a framework to calculate the KE-layer number and approximate the minimal vertex-cover is provided, with different strategies of switching nodes and counting energy. The phase transition phenomenon between different KE-layers are studied with the transition points located, and searching of vertex-cover got by this strategy presents comparable advantage against several other methods. The graphical representation and hierarchical decomposition provide a new perspective to illustrate the intrinsic complexity for large-scale graphs/systems recognition.
Efficient and Bias-aware Recommendation with Two-side Relevance for Implicit Feedback

Today’s wide-spread recommendation is usually constructed based on implicit data such as click for easy collection but whether the no clicked data is negative feedback or unobserved positive feedback confuses the model construction. As a response, Relevance Matrix Factorization (Rel-MF) is recently proposed to tackle this problem as well as the missing-not-at-random (MNAR) problem ignored by previous studies. However, Rel-MF meets three problems: limited assumption (LA), negative square loss (NSL) and indiscriminate no click data (INCD). In this paper, we first get rid of Rel-MF’s limited assumption and establish a more general theory by incorporating a defined transformation function which captures the relevance level to our two-side relevance ideal loss, containing Rel-MF’s theory. To resolve the INCD problem and NSL problem, we introduce an adjusting variable and perform normalization, respectively, which is called Naive Solution with Normalization for Rel-MF (NRel-MF). But we then analytically discover that the clipped function proposed by Rel-MF meets the high variance problem. To overcome it, we design a power clipped function and further propose Improved Solution with Power Function for Rel-MF (PRel-MF). Besides, we also explore propensity score estimation from user and hybrid perspectives in contrast to Rel-MF’s sole item perspective. Finally, we also consider and address the computational problem caused by the Rel-MF’s non-sampling strategy. Empirical results verify the effectiveness of our solutions from both performance even in rare items and loss decrease. In broader perspective experiment, decent performance is seen in item perspective with fewer recommended items while in user perspective with more recommended items and hybrid perspective outperforms them in more situations.