Reviewerly/exHarmony huggingface dataset:
Comparative analysis of the topics of scientific publications in the field of artificial intelligence in international and Russian journals

Aim. To perform a comparative analysis of the topics and volumes of publication activity in the field of artificial intelligence (AI) of Russian authors in journals indexed in such databases as the Russian Science Citation Index (RSCI) and WoS/Scopus, in relation to the fields of AI technologies, scientific directions and organisations of the place of work. Tasks. To create a list of publications by authors with Russian affiliation in journals indexed in WoS/Scopus, including those categorised as Q1 and Q2 quartiles, as well as in the proceedings of A* level conferences, the topics of which are related to the AI sphere; to create a list of publications by Russian researchers devoted to the AI topics in journals indexed in RSCI, including those categorised as Q1; to carry out a comparative analysis of the topics and structure of publications by Russian authors in journals indexed in WoS/Scopus and RSCI in relation to the fields of AI technologies, groups of scientific specialties, and organisations of the authors’ place of work. Methods. The methodology of the study is based on expert analysis of publications in scientific journals indexed in WoS/Scopus, including Q1 and Q2 quartiles, in proceedings of A* level conferences, scientific journals indexed in RSCI for 2017–2021, the subject matter of which relates to the field of AI, based on selections from open databases of publications using libraries and packages for data processing and analysis. The criterion for attributing an article to the AI subject was the presence of word combinations from the fields of AI technologies and subtechnologies in the search fields “publication title” and (or) “Keywords”, “Abstract”. Results. Comparison of highly rated WoS/Scopus, Q1, Q2, A* and RINC K1 publications shows that among WoS/Scopus, Q1, Q2, A* publications “Machine learning: knowledge representation, ontology, interpretation, explanation” (32 %) and “Computer vision” (30 %) dominate. Among RINC Q1 publications, “Responsible Artificial Intelligence (ethics and philosophy, legal regulations, security)” (34 %), “Machine learning: knowledge representation, ontology, interpretation, explanation” (28 %) and “Intelligent analysis of data and processes, making sense of patterns” (13 %) dominate. Conclusions. The analysis of publication activity of Russian authors in relation to AI topics on the basis of comparison of scientific publications from WoS/Scopus and RINC databases can serve as an information basis for selection of AI competence centres and formation of lists of best practices in the field of AI.
CogNLG: Cognitive graph for KG‐to‐text generation

Abstract Knowledge graph (KG) has been fully considered in natural language generation (NLG) tasks. A KG can help models generate controllable text and achieve better performance. However, most existing related approaches still lack explainability and scalability in large‐scale knowledge reasoning. In this work, we propose a novel CogNLG framework for KG‐to‐text generation tasks. Our CogNLG is implemented based on the dual‐process theory in cognitive science. It consists of two systems: one system acts as the analytic system for knowledge extraction, and another is the perceptual system for text generation by using existing knowledge. During text generation, CogNLG provides a visible and explainable reasoning path. Our framework shows excellent performance on all datasets and achieves a BLEU score of 36.7, which increases by 6.7 compared to the best competitor.
Contextual topic discovery using unsupervised keyphrase extraction and hierarchical semantic graph model

Abstract Recent technological advancements have led to a significant increase in digital documents. A document’s key information is generally represented by the keyphrases that provide the abstract description contained therein. With traditional keyphrase techniques, however, it is difficult to identify relevant information based on context. Several studies in the literature have explored graph-based unsupervised keyphrase extraction techniques for automatic keyphrase extraction. However, there is only limited existing work that embeds contextual information for keyphrase extraction. To understand keyphrases, it is essential to grasp both the concept and the context of the document. Hence, a hybrid unsupervised keyphrase extraction technique is presented in this paper called ContextualRank, which embeds contextual information such as sentences and paragraphs that are relevant to keyphrases in the keyphrase extraction process. We propose a hierarchical topic modeling approach for topic discovery based on aggregating the extracted keyphrases from ContextualRank. Based on the evaluation on two short-text datasets and one long-text dataset, ContextualRank obtains remarkable improvements in performance over other baselines in the short-text datasets.
Cryptography

This chapter describes the basic techniques of cryptography as a tool to ensure confidentiality of data.
Risk

Unwanted events, such as attempts to breach the security policy of an IT system, may appear with very different frequencies and have very different consequences. Risk analysis is used to determine which possible events are the most serious, so that most effort should go into preventing them. This chapter explains the meaning of objective risk, and gives an introduction to the discipline of risk management – the ways in which risk can be reduced in an IT system by introducing countermeasures.
Preface

Second International Conference on Artificial Intelligence, Computational Electronics and Communication System (AICECS 2023) Welcome to AICECS 2023 Department of Electronics and Communication Engineering, Manipal Institute of Technology (MIT) in association with IEEE Student Branch Manipal (IEEE SBM) organized the second International Conference on Artificial Intelligence, Computational Electronics and Communication Systems (AICECS) 2023, on 16-17 February 2023 in MIT - Manipal campus. The conference received funding’s from SERB-DST, Govt. of India. List of Edited By, Inaugural Program, Track and sessions, Track 1: Artificial Intelligence, Track 2: Computational Electronics, Track 3: Communication Systems, session 1, Cultural Program and Banquet Dinner, Valedictory Program, About the Institute, Committees, All photos are available in this pdf.
Book Publishing in Barnaul in the Pre-Revolutionary Period

The social significance of book publishing is determined by the large role of print media in personal education, in the dissemination of knowledge and ideas. Therefore, the study of this sociocultural phenomenon is an important area of modern scientific research. The purpose of this article is to make a quantitative analysis of book publishing in Barnaul in the pre-revolutionary period. The quantitative indicators of book publishing in Barnaul town per year and in general for the pre-revolutionary period were calculated. The results obtained showed that from the XIX century to 1917 at least 210 titles were issued in Barnaul, with the exception of periodic ones. The most productive were 1899 and 1900, when 13 titles were issued in each. Printing houses that worked in the town in the pre-revolutionary period were identified. The share of each of them was determined by the number of titles printed in it. Thelargest part – 44.8 % – was published in the Main Directorate of the Altai Mining District. The publishing repertoire and the author’s corps were outlined. The latter was represented mainly by persons who worked in Altai District. Many authors were the members of the Society of lovers of Altai exploration. The main group of publishers was formed by local societies, that’s why their office documentation was a noticeable part of printed materials and determined the publishing repertoire of Barnaul printing houses.
Study on Interplay of tension, deformation, and ore formation

This study undertakes an in-depth exploration of the intricate relationship between gold mineralization in the Tamdytau area within Central Kyzylkum and the underlying tectonic tension and deformation processes. Additionally, the research delves into the interconnection between occurrences of gold ore deposits in Western Uzbekistan and the prevailing regional fault systems. Through thorough investigation, the study unveils compelling insights. The findings demonstrate that a substantial portion, approximately 34%, of the gold ore deposits in the region are geographically situated within zones closely aligned with regional ore-controlling faults that exhibit a predominant northwestern strike. This correlation underscores the significance of these structural features in influencing the distribution of gold mineralization. Furthermore, a detailed analysis of gold ore distribution within the Tamdytau region discloses a noteworthy trend: over 80% of the ore occurrences are strategically located within areas characterized by relatively low shear stress values and stress neutralization conditions. This observation highlights the crucial connection between the geological stress environment and the formation of gold-rich mineralization. These revelations underscore the profound role played by tectonic processes, particularly tension and deformation, in shaping the presence of gold mineralization within the study area. The intricate interplay between geological factors and mineralization patterns has far-reaching implications for the understanding of gold deposition mechanisms and the potential for uncovering valuable resources within this region.
Authorship in the Age of Artificial Intelligence: A Civil Law Approach

The emergence of automated processes in the creation of artistic works has become an undeniable reality. Thanks to applications that fall under what mainstream is calling “generative AI”, it is now possible to generate images from mere descriptions or to construct texts based on concise instructions (prompts). As a result, the issue of authorship of these creations has regained prominence in legal discourse. The present study therefore seeks to shed light on this very question.First, we will disregard the machine-centric perspective and instead adopt a human-centric approach. Accordingly, our analysis will focus on the automated execution process to determine whether a work can exhibit originality, i.e., the manifestation of free and creative choices made by a human author.Second, we will analyze the notion of "imprint of data" with the goal of establishing that the replication of certain patterns from pre-existing data does not prevent an individual from using artificial intelligence systems to create original works.Finally, we will turn our attention to determining the author of an original AI-generated work. In doing so, we will identify the primary candidates as the user and the developer, and then evaluate the circumstances under which each party might be considered appropriate for such attribution.
Exploring the influence of service employees' characteristics on their willingness to work with service robots

Purpose This research empirically investigates how service employees' ratings of technology readiness (TRI), negative attitudes towards robots (NARS), Big Five personality traits (BFI) and emotional demands (ED) affect their willingness to work with service robots (WTW). Design/methodology/approach One set of data is collected from 410 service employees expected to work with service robots in Study 1. Another set of field data is collected from 102 employees working with service robots in Study 2. Hierarchical regression is used to test hypotheses about the impact of technology readiness, negative attitudes towards robots and Big Five personality traits on WTW. Additionally, the interactions of emotional demands in the workplace are analysed. Findings TRI-optimism and TRI-insecurity significantly affect WTW in Study 2 but are nonsignificant in Study 1. The impacts of NARS-emotions in interaction with robots and NARS-interaction with robots situations on WTW are significant in Study 1 but nonsignificant in Study 2. Moreover, BFI-neuroticism negatively affected WTW in Study 1, while these effects were nonsignificant in Study 2. Finally, emotional demands significantly interact with three of eleven dimensions of IVs in Study 1, but all interactions are nonsignificant in Study 2. Practical implications This research provides a guiding framework for service companies to screen employees expected to cowork with service robots, to enhance newly hired employees' WTW and to improve existing employees' WTW. Originality/value Integrating the characteristics of service employees, service robots and jobs into a theoretical framework, this research is the first to empirically examine the effects of service employees' several critical characteristics (technology readiness, negative attitudes towards robots and Big Five personality) on WTW and the moderation of job characteristics (emotional demands).
[Source Apportionment and Potential Ecological Risk Assessment of Soil Heavy Metals in Typical Industrial and Mining Towns in North China].

To understand the status of heavy metals in soils of typical industrial and mining towns and quantitatively analyze the potential sources, the contents of seven heavy metals (Cd, As, Pb, Cr, Cu, Ni, and Zn) in 150 surface soils in Xuanhua District, Zhangjiakou City, Hebei Province were collected and examined. The geoaccumulation index and potential ecological risk index methods were used to evaluate the heavy metal pollution status and potential ecological risk. Principal component analysis (PCA) and the positive matrix factorization (PMF) model were used to comprehensively analyze the pollution sources of seven heavy metals, and geostatistics was used to identify the high contribution areas of potential sources. The results revealed that:① the average values of heavy metals in the study area ranged from 0.23-103.34 mg·kg-1, among which the average contents of Cd, Pb, Cu, and Zn were higher than the soil background value of Hebei Province. ② The results of the geoaccumulation and potential ecological risk indices demonstrated that the degree of pollution of the seven heavy metals was in the following order:Cd>Pb>Cu>Zn>Ni>As>Cr, the content of Cd in 16% sites was above a moderate pollution level, and the potential ecological risk of heavy metals in more than 95% sites was at a light risk level. ③ The main sources of accumulation of the seven heavy metals in the study area were combined sources of industry and traffic, natural sources, and agricultural sources, with their contribution rates of 33.1%, 48.7%, and 18.2%, respectively. Among them, Cd, Pb, Cu, and Zn were primarily affected by the combined sources of industry and transportation; Cr, Ni, and As were mainly affected by natural sources, whereas Cd and some As were affected by agricultural sources. The organic combination of PCA, PMF model, and geostatistical methods confirmed the results of each analysis, which increased the reliability of the analytical results of heavy metal sources.
An ECAPA-TDNN Based Network for Hand Gesture Recognition on Skeletal Data

Due to the high variety of sign languages, it is essential to present a model that could recognize the hand gesture recognition. The state-of-art model is mainly driven by convolution neural networks (known as CNN), and researches are on optimizing CNN architectures. The CNN networks are too large and require long time to train. To address these challenges, we developed a more accurate and robust ECAPA-TDNN structure for recognition. The ECAPA-TDNN is a structure of multiple one- dimensional neural networks with one-dimensional convolution, activation layers, and batch normalization. On the challenging SHREC 2017 3D Shape Retrieval Contest dataset, the ECAPA-TDNN achieved an accuracy of 92.9%, which is 2% higher than the state-of-the-art accuracy achieved by CNNs.
THE USE OF NINJA APPS GAME TO ENRICH THE STUDENT'S WORD STOCKS

This research was carried out to help the students' problems in the classroom. Based on the pre-observation students tended to be passive and unmotivated and engaged in the learning process. Besides, the students also had a poor vocabulary. The researchers then applied Ninja Apps Game to solve the problems. The objectives of this research were to improve the students' participation and motivation through the implementation of Ninja Apps Game. This research employed classroom action research on thirty-eight students of the non-English study program. To collect the data the researchers used observation, interview, and measurement techniques. The instrumentations used were an observation sheet, field note, test, and interview guidelines. The findings showed that Ninja Apps Game effectively improved the students' participation, motivation, and vocabulary mastery. The students were happy, relaxed, and enjoyed the implantation of Ninja Apps Game. The finding of this research brings a new perspective to the teaching and learning process, especially in teaching vocabulary. Ninja Apps Game provides some activities which reflect cooperation, competition, and also discipline in using time.
Word Embedding for Cross-lingual Natural Language Analysis

Word embedding, a distributed representation of natural language based on deep neural networks, has made significant breakthroughs in many natural language processing tasks and has gradually become a hot subject in research and application. Word embedding methods can capture more complex and valuable semantic information than existing methods. However, existing methods of word embedding often rely on large-scale annotation resources, which are often difficult to obtain, especially for resource-poor languages. In response to this problem, researchers have explored different research routes, such as unsupervised learning from untagged data, semi-supervised learning that integrates tagged and untagged data, or crowdsourcing. At the same time, many scholars have proposed to improve the analysis accuracy of target tasks by integrating the annotation resources of different languages and enabling knowledge from foreign languages to be transferred or merged with models. This paper discusses the development and prospects of word embedding.
Exploring Healthful Spatial Interface with Bodystorming: A Case Study from the Vertical Workspace Workshop

The wide spread of artificial intelligence and spatial computing is driving the emerging development of healthful spatial interface (HSI), which requires new paradigms for generating relevant designs. In this paper, we present a case study on exploring tools and methods for ideating HSI concepts based on bodystorming. Specifically, we set out a workshop utilizing office vitality as the research context to investigate interactive elements in a vertical space for individual workers. We developed a real-size vertical space mockup capsuled with some tools, as well as a co-creation workflow to support bodystorming activities of this workshop. Based on a pilot study with nine participants, we obtained some qualitative data to reflect on the effectiveness of our workshop in facilitating design ideations of HSIs. Moreover, we found the proposed approach helped us quickly explore how HSIs could be designed and vertically arranged for increased office vitality. We conclude with implications and discussions for future work.
Dragon Boat Simulation: An Immersive Experience Beyond Traditional Gaming

Immersive sports are emerging recently after the metaverse hype. This paper investigates an immersive setup that leverages virtual reality to recreate the kinetic and sensory nuances of dragon boating. We employ a body-centric approach to enable users to engage with authentic paddling actions, e.g., mobilising iron sticks on the boat with reasonably emulated water resistance. The virtual environments mirror real-world scenes, e.g., Pearl River (Guangdong). We employed multi-modal experiences to replicate the visuals and tactile, kinesthetic, and environmental intricacies of dragon boating. Our Dragon Boat simulator serves as a groundwork for redefining the boundaries of immersive sports training that bridges the gap between virtuality and the real world.
Mitigating inherent latency in off-device computer vision for spatial interfaces

Researchers commonly need to deploy specialised computer vision models on Mixed Reality devices, such as Microsoft HoloLens, to extract richer contextual information. This paper introduces an approach to alleviate the negative impacts of elevated latency caused by model inference time, network transactions, and photo capture during the use of external deep learning models. In contrast to previous methods that constrained user movements, our approach augments users’ environmental perception while preserving freedom of movement.
Demonstrating Proxemic Cursor Input for Touchless Displays

Touchless gesture interfaces often use cursor-based interactions, where widgets are targeted by a movable cursor and activated with a mid-air gesture. Proxemic cursor interactions are a novel alternative that facilitate faster selection without the need for direct targeting. We present an interactive demonstration exhibit that uses proxemic cursor interactions for input to a touchless public display.
PENGEMBANGAN MEDIA VIDEO ANIMASI MENGGUNAKAN POWTOON PADA TEMA DAERAH TEMPAT TINGGALKU SUBTEMA KEUNIKKAN DERAH TEMPAT TINGGALKU

This researchaims to detremine the development and fesibility of animated video media using Powtoon on the theme of the area where I live, sub-theme, the uniqueness of area where I live. This reserch uses an R&amp;D (Research and development) research approach using the ADDIE model, there are five stages of analysis, design, implementation, evaluation. The subject of this research were class IVA student at Ciawi 23 state elementary school, consisting of 26 students. This research was conducted in the even semester of the 2022/2023 academic year. In this research, the instruments used consisted of validation sheets from media experts, language experts, material experts, student response questionnaire results, and teacher response questionnaire results. This is proven by the media validation results which obtained a percentage of 88%, language experts obtained a precentage of 90%, and material experts obtained a precentage of 88%.