Reviewerly/exHarmony huggingface dataset:
A literature review on digital content management: trends and future challenges

Purpose The purpose of this study is to review the literature on digital content management (DCM) published between 2001 and 2021, as well as to provide insights and research directions for the future. Design/methodology/approach This study followed the systematic literature review framework PRISMA for reviewing existing literature on DCM. The PRISMA checklist helps the researcher in refining the reporting of the review paper. Data was collected from Scopus and Web of Science (WoS) databases. A total of 136 documents were selected for analysis from Scopus and WoS. Findings Based on current papers, this study attempted to discuss some key DCM trends and themes. Seven themes have been identified in the literature: virtual reality and its implications on DCM; personal DCM; microservices based DCM; model for DCM; DCM using Bluetooth Low Emergency technology; DCM software; and DCM codification. This study identifies influential authors, top contributing countries, top contributing institutions, most cited papers, most common title words and contributions by fields. Originality/value The findings of this study, as well as future research projects, open the path for more research and contributions to the field.
Application of Composite PSO Algorithm in Hybrid Electric Vehicle Control Optimization

The optimization of hybrid electric vehicle control strategy parameters has always been the concern subject of researchers. At present, matching and optimization methods for the control strategy parameters are still being explored. The optimization of HEV control strategy parameters is a multivariate multi-objective nonlinear programming problem. Most of the methods adopted by OEMs are still based on large numbers of calibration tests and data analysis, through a large number of repeated modification of control parameters to obtain a relatively good data as the best result. As a result, the work efficiency is low, the research and the development cycle times are long. According to the characteristics of the PSO algorithm and its composite algorithm, it is not easy to fall into the local optimal solution, and the convergence speed is fast and the work efficiency is significantly improved. This paper provides a composite PSO algorithm for multi-variable nonlinear programming problems. The algorithm is easy to obtain better global optimization results. Combined with practical application requirements, it has been used to guide the development of actual vehicle control systems.
AEB Target Selection Method Based on Sensor Fusion

This paper proposes an AEB target selection method based on sensor fusion which includes three modules: perception-data-fusion, trajectory-prediction and AEB-target-filtering three modules. Perception-data-fusion includes three sub modules: time-space-synchronization, data-association and target-tracking. Trajectory-prediction includes three sub modules: signal-filtering, mode-selection and trajectory-generation. AEB-target-filtering includes five sub modules: coordinate-transformation, collision-judgment, collision-time-calculation, initial-target-selection and target-filter. This paper also designs an offline testing method and tool. The result of offline test aiming at typical AEB application scenarios shows that the proposed method has high accuracy and robustness which can adapt to different driving conditions.
An Ontological Approach to Information Integration in Data Intensive Domains

The development and support of knowledge-based systems for experts in the field of social network analysis (SNA) is complicated because of the problems of viability maintenance that inevitably emerge in data intensive domains. Largely this is the case due to the properties of semi-structured objects and processes that are analyzed by data specialists using data mining techniques and others automated analytical tools. Firstly, new sources (e. g. online social networks, published databases) constantly become available for gathering, analyzing, and interpreting data. Thus, new sources should be modelled and embedded in existing data structures maintaining logical consistency. Secondly, new techniques and underlying algorithms are also constantly being developed. Therefore, analysis results should be integrated with source data, and metamodels that describe the integration should be adaptable and extensible. Thirdly, the dynamism of semi-structured objects entails constant changes in knowledge models produced by domain experts and knowledge engineers. Considering that the same data could be used by different domain experts it is crucial not only to support traceability of changes in models but also to ensure independence of expert interpretation of these models. The analysis of existing approaches to information integration shows lack of solutions implementing traceability of changes. This paper introduces a novel approach to information integration based on ontological and production knowledge models to fill this gap. A conceptual description of the approach and an underlying set-theoretical model are given. The main difference of the given approach from the existing ones is the uniformity to the integration of different kinds of ontologies as well as different versions of ontologies using rule-based model of ontological mappings, which is demonstrated by the example of solving the special case of the problem of identifying key users (so-called bridges) in social networks.
Design and Build 2D Android-based Adventure Game “Excuse Me”

Manners are a must for a child as basic education from an early age. Learning manners should be taught in childhood starting with an introduction to simple manners and manners. This encourages the idea to create a game that can be used as a tool in teaching etiquette for early childhood. Learning methods accompanied by play will make it easier for children to understand things easily. This educational game is entitled "excuse me" with a 2D adventure genre where a story is presented about a little boy who wants to return to his house after school, but on the way, he meets many obstacles. The little boy must pass through one after another in order to return to his home safely. This game has 5 levels and each level has different obstacles. The game framework development in this research uses the Unity 3D game engine to build android based games. The advantage of the "excuse me" game is that this game can be a more interactive and interesting learning method and can make players feel that etiquette is very important in everyday life and in the game. and the disadvantages of this game are that it cannot run on the iOS operating system, lacks levels, and has an unattractive interface. Responses from children aged 13 and over indicated that the media was "very interesting".
Twitter and the aphoristic (re)turn in thought, knowledge and education

Click to increase image sizeClick to decrease image size Disclosure statementNo potential conflict of interest was reported by the authors.
Linguistic laws in Catalan

In this work, we explore and review linguistic laws, in the case of Catalan, going from prelinguistic to higher linguistic levels and addressing both speech and writing. We show evidence supporting the theory that linguistic laws are universal patterns in human language that are more robust in the oral corpus than in writing. This reinforces the “physical hypothesis,” which argues that linguistic laws could have a physiological and biophysical origin, and they are reflected in written texts as a consequence of speech symbolization. However, future work is necessary to increase empirical evidence by deeply analyzing other language corpora, propose new cognitive and physical models that clarify the mathematical formulation of some statistical patterns, find more evidence to explain the relationship between prelinguistic and higher linguistic levels, and understand the results reported up to date from a global interdisciplinary perspective of language theory.
Avoiding Pragmatic Oddity: a bottom-up Defeasible Deontic Logic

Abstract This paper presents an extension of Defeasible Deontic Logic to deal with the Pragmatic Oddity problem. The logic applies three general principles: (i) the Pragmatic Oddity problem must be solved within a general logical treatment of contrary-to-duty (CTD) reasoning; (ii) non-monotonic methods must be adopted to handle CTD reasoning; (iii) logical models of CTD reasoning must be computationally feasible and, if possible, efficient. The proposed extension of Defeasible Deontic Logic elaborates a preliminary version of the model proposed by Governatori and Rotolo [15]. The previous solution was based on particular characteristics of the (constructive, top-down) proof theory of the logic. However, that method introduces some degree of non-determinism. To avoid the problem, we provide a bottom-up characterization of the logic. The new characterization offers insights for the efficient implementation of the logic and allows us to establish the computational complexity of the problem.
Precomputing reconfiguration strategies based on stochastic timed game automata

Many modern software systems continuously reconfigure themselves to (self-)adapt to ever-changing environmental contexts. Selecting presumably best-fitting next configurations is, however, very challenging, depending on functional and non-functional criteria like real-time constraints as well as inherently uncertain future contexts which makes greedy one-step decision heuristics ineffective. In addition, the computational overhead caused by reconfiguration planning at run-time should not outweigh its benefits. On the other hand, completely pre-planning reconfiguration decisions at design time is also infeasible due to the lack of knowledge about the context behavior. In this paper, we propose a game-theoretic setting for precomputing reconfiguration decisions under partially uncertain real-time behavior. We employ stochastic timed game automata as reconfiguration model to derive winning strategies which enable the first player (the system) to make fast look-ups for presumably best-fitting reconfiguration decisions satisfying the second player (the context). To cope with the high computational complexity of finding winning strategies, our tool implementation1 utilizes the statistical model-checker Uppaal Stratego to approximate near-optimal solutions. In our evaluation, we investigate efficiency/effectiveness trade-offs by considering a real-world example consisting of a reconfigurable robot support system for the construction of aircraft fuselages.
Reading Comprehension and Academic Writing: Results of the research project

This book corresponds to volume 3 of the EDUCATION FOR SUSTAINABLE DEVELOPMENT collection. It gathers contributions from teachers and instructors who work at educational institutions from primary to higher education in Ecuador and the United States and who participate in or are supporters of the Cooperation Network for Scientific Research on Reading Comprehension and Academic and Creative Writing REDLEA. The diverse topics presented to respond to the need to contribute to sustainable development processes from education. The contributions of the pedagogical innovations research group for sustainable development of the Eloy Alfaro Lay University of Manabí, Ecuador, and the brotherhood with the Kansas State University of the United States, for the execution of the Camino project are appreciated. This book contains sections that address academic reading and writing comprehension, socio-emotional education, inclusive education, and pedagogical innovations for sustainable development. We hope this work will contribute to the training process of new generations of teachers with diverse, inclusive, and progressive views.
Battlefield Target Intelligent Value Analysis Based on Real-Time Data

In the process of battlefield target identification and decision-making, it has the characteristics of real-time change of target parameter data and large amount of data. The previous target value analysis methods have large limitations. Considering the impact of real-time data driving on target value analysis and decision-making, the cloud model is used to target the target. The uncertain and fuzzy information in the real-time data is quantified to generate cloud membership; based on the data envelopment analysis (DEA) method, a relatively optimal efficiency decision-making tool, the value of the battlefield target is carried out. Sorting and decision making. Finally, a numerical example is analysed to verify the applicability and correctness of the model. The calculation example shows that the model can meet the timeliness of hitting targets in wartime, and it provides a practical mathematical tool for analysis of the value of battlefield targets.
Garbage sorting system based on improved single shot multibox detector

Garbage pollution is a very difficult problem in environmental governance. Due to the many sources of garbage pollution and a wide range of impacts, this problem is only slow to solve by human means. In order to improve the automation of garbage disposal, on the one hand, this paper proposes a garbage detection method based on CNN (convolutional neural network) using multi-layer feature processing. On the other hand, the detection algorithm is combined with an industrial robot to form a complete garbage sorting system. This paper uses the one-stage idea to first optimize the backbone structure to improve the extraction effect of shallow features. Then the attention module is introduced to make the network pay more attention to information that plays a key role in garbage detection. Finally, a multi-layer feature fusion method is used to combine the features of the shallow network with the features of the deep network to generate a fused feature map for use in target detection tasks. The experimental results show that the detection speed of the method proposed in this paper is 13.75% higher than that of SSD, and the garbage detection accuracy reaches 99.5%, which is better than the SSD detection algorithm. The garbage detection method proposed in this paper can quickly realize the precise positioning of garbage and complete automatic robot sorting.
Digital Animation and Augment Reality as a Way of Added Value to Artistic Exhibition

A public art exhibition aims to allow for the best possible appreciation of the works of the artist by the largest volume of potential audience. This article explores a strategy to maximize public interest and engagement using Digital Animation and Augmented Reality technology as a way of promoting a complementary look at the work of art in this context. The exhibition No Plan for Japan, consisting of six collections of original drawings by the Portuguese illustrator Ana Aragão was on display at the Museu do Oriente – Fundação do Oriente between November 5th, 2021 and February 14th, 2022. The artist drawings emerge from the utopia and fantasy of creating imaginary buildings that stand out for their great degree of detail and the sensation of life and movement they convey, through elements such as flags, fluttering cloths or even through the fragile balance of their foundations. Inspired by this implicit movement, a teacher from the undergraduate course in Video Games and Multimedia Applications at Universidade Lusófona do Porto, guided a group of four students in a joint project animating 18 illustrations selected from No Plan for Japan and, using the mobile application Artivive, integrated these animations in the exhibition space through Augmented Reality. This study intends to analyse the results of this collaborative project demonstrating the effectiveness of the proposed strategy in contributing to an increased and differentiated look at the exhibited artworks.
Breaches spotlight role of cybersecurity standards

Significance Several standards-setting organisations, including the International Organization for Standardization (ISO) and the National Institute of Standards and Technology (NIST), publish extensive catalogues of information security controls and cybersecurity standards. These increasingly guide organisational decision-making on security budgets and critical controls. However, they are at best a starting point for cybersecurity. Impacts International bodies will increasingly tailor their cybersecurity advice to serve resource-strapped small and medium-sized enterprises. Larger organisations will use standards to verify compliance with baseline expectations. Compliance with standards will not provide a meaningful assessment of whether data and networks are adequately protected.
The Technological Basis of Training Future Teachers of Agricultural Disciplines in Higher Education Institutions: Pedagogical Experience of Great Britain

The article aims to develop a comprehensive pedagogical model for training future teachers of agrarian disciplines in the context of implementing a three-level pedagogical technology for educational process management (EPM). The pedagogical experience of Great Britain is under review, which can be used to improve the technological process of forming the professional competence of teaching specialists.&#x0D; The research methodology was determined by a set of methodological approaches (system, activity, competence, technological, personal development) and was based on a pedagogical experiment that included ascertaining, formative and control stages.&#x0D; Results. The theoretical and methodological foundations of the introduction into the educational environment of the three-level pedagogical technology of educational process management in the conditions of training future teachers of agricultural disciplines in higher education institutions are analysed. An applied model of educational process management for the training of future teachers of agricultural disciplines is proposed on the example of the first (bachelor) level of education in the conditions of introducing a SMART-educational communicative environment.&#x0D; The structure of the readiness of future teachers of agricultural disciplines for professional activity (motivational-cognitive, practical-active, creative-developmental levels) is determined.&#x0D; The technological stages of the process of professional training of future teachers of agricultural disciplines in institutions of higher education in the context of the pedagogical experience of Great Britain (motivational-orientational, planning, cognitive-transformative, control-analytical, regulatory-developmental) are considered. The didactic methods, forms and means of the proposed pedagogical technology for managing the educational process are substantiated.&#x0D; Conclusions. The results of the experimental work demonstrate a significant increase in the quality indicators of the professional training of future teachers of agricultural disciplines in higher education institutions (motivation, creative activity, productivity) in the conditions of the implementation of the three-level pedagogical technology of the EPM.&#x0D; The implementation of a three-level pedagogical technology in the educational process management system allows for boosting students’ creative activity, increasing the level of their internal motivation, and deepening the level of independence and individualisation of learning, which eventually is determined by a high level of readiness for professional pedagogical activity.
A Comparison of Statistical Dependency and Functional Dependency between Attributes Based on Data

Chi-squared test is a standard statistical test to ascertain independence between categorical variables. So, it is recommended to do the test for the attributes in the datasets, and remove any redundant attributes before we supply the datasets to machine learning algorithms. But, if we have many attributes that are common in real-world datasets, it is not easy to choose two attributes to do the independence test. On the other hand, several automated algorithms to find functional dependencies based on data have been suggested. Because functional dependencies show many-to-one relationships between values of attributes, we could conjecture that there might be statistical dependence in the found functional dependencies. For us to overcome the problem of choosing appropriate attributes for statistical dependency tests, we may use some algorithms for automated functional dependency finding. We want to confirm that the found functional dependencies can show statistical dependence between attributes in real-world datasets. Experiments were performed for three different real-world datasets using SPSS to confirm the statistical dependence of functional dependencies that are found by an open-source tool called FDtool, where we can use FDtool for automated functional dependency discovery. The experiments confirmed that there exists statistical dependence in the found functional dependencies and showed improvements in decision trees after removing dependent attributes.
An Observational Study of Teacher’s Gestures in EFL Classroom

Verbal utterances and nonverbal utterances are acknowledged to be semantically and pragmatically coexpressive. Previous theories reveal that gestures are useful for teacher’s conceptual planning of messages and student’s comprehension and learning motivation. This study is carried out using an observational study and aimed to give insight into the use of gestures by EFL teacher during the teaching in the language classroom. An Islamic senior high school EFL teacher with a bilingual classroom become the participant of this study. A video recording is put on the back of the classroom aimed to capture the teacher’s gestures and the teacher and the students’ interaction, an audio recording is placed on the teacher’s front table, and the researcher is on the corner of the classroom to observe the teaching process synchronously. The data collected were transcribed then analysed using AS-Unit for recognizing the English utterances and the categorization of gestures was adopted from Wang and Loewen (2016). The finding elaboratively describes the use of gestures (i.e., iconics, metaphorics, deictics, beats, head movements, affect displays, kinetographs, and emblems) produced by the teacher in her classroom utterances. The finding shows that the gestures take a big part in supporting the teacher as speaker in teacher’s complex lexical retrieval. Also, the visual of the use gestures is provided. Therefore, the result of this study serves as a teaching reflection and can be employed as a model to provide language learning comprehensible input in the language classroom.
Reconstructing Bayesian networks on a quantum annealer

Bayesian networks are widely used probabilistic graphical models, whose structure is hard to learn starting from the generated data. O'Gorman et al. have proposed an algorithm to encode this task, i.e., the Bayesian network structure learning (BNSL), into a form that can be solved through quantum annealing, but they have not provided an experimental evaluation of it. In this paper, we present (i) an implementation in Python of O'Gorman's algorithm, (ii) a divide et impera approach that allows addressing BNSL problems of larger sizes in order to overcome the limitations imposed by the current architectures, and (iii) their empirical evaluation. Specifically, several problems with an increasing number of variables have been used in the experiments. The results have shown the effectiveness of O'Gorman's formulation for BNSL instances of small sizes, and the superiority of the divide et impera approach on the direct execution of O'Gorman's algorithm.