Reviewerly/exHarmony huggingface dataset:
Application of Internet of Things Big Data in Early Waring Management of Enterprise Human Resource Crisis

As a new management concept, human resource has stepped on the stage of society.As an important force to promote the healthy development of enterprises, it has been paid attention to by various industries.The lack of early warning mechanism is an important factor leading to human resource crisis.The effective measure to prevent human resource crisis is to carry out early warning of human resource crisis.This paper analyzes the main problems of human resource management in China's enterprises, discusses its early warning management system, analyzes its difficulties and advantages, and puts forward effective countermeasures combined with computer technology, so as to promote the sound function and efficient operation of enterprise human resource management system.
Study and Analysis of COVID-19 Impacts on the Performance of College Students and Courses

The COVID-19 pandemic has transformed every domain of the world including the education.The main objective of this research is to analyse and study the impacts of COVID-19 pandemic on the performance of the students and courses.The analysis is performed based on three category of teaching mode namely face to face, face to face combined with online and completely online.The appropriate statistical tool, testing of hypothesis using ANOVA table is applied for this research work.Three salient factors of this analysis is to compare the students' performance based on the different mode of teaching for all target students, course wise impact of teaching and students who have come across all the 3 modes of teaching.Analysis of student's performance is imperative at this stage, since this helps to bring out fruitful outcome with respect to education.
PSYCHOLOGICAL AND PEDAGOGICAL ASPECTS IN THE ACTIVITY OF PENITENTIARY SERVICE

This article is dedicated to the main problems of psychological and pedagogical activity of penitentiary service.The topic of studying the psychological state of corrections officers became relevant and interesting for this study.The aim was to reveal the main problems of psycho-emotional state faced by officers and to investigate the main factors influencing psychological stability and the consequences of not overcoming them in the performance of official duties of penitentiary staff.The norms of professional ethics that require officers of penitentiary servicde are described.The main psychological problems that may stand in the way of effective performance of official activities are identified and the specifics of each of them are revealed.During the writing of this work, the materials of outstanding domestic and foreign researchers in the field of psychology and pedagogy were taken as materials.The main problems of violation of the psycho-emotional state of the staff that occur in atypical conditions are analyzed.The article examines and reveals the main factors such as psychological adaptation, unwillingness to perform professional duties under the influence of stressors, negative psycho-emotional states, loss of psycho-emotional balance and resilience in extreme conditions and their impact on personnel activity with convicts.The results of the study revealed the consequences of overcoming negative psycho-emotional factors and their impact on the further effectiveness of pedagogical activities of penitentiary officers.Negative effects such as emotional burnout, occupational deformity and post-traumatic growth have been reported.This issue should be researched and studied in further research, because the current conditions of our state make it extremely relevant.Problems of psychological states of employees and their impact on the effectiveness of pedagogical activities of officers deserve wider consideration both in theoretical and practical terms.
High School Architecture in Times of Blended-Learning System

A blended learning system is a group of contemporary learning methods that began in the early 2000s.However, its existence turns out to be essential during the pandemics.When a conventional learning system offers only 1 learning method: conventional face-to-face meeting, a blended learning system gives 4 varied and technologyfriendly methods: offline synchronous, offline synchronous, online asynchronous, and offline asynchronous.The way we plan high school buildings indeed change to make place for the paradigm shift.This research discusses the differences among learning spaces both in conventional and blended learning methods through a participatory approach.The research methods are as follows; 1) The Architecture of Blended Learning System; 2) Security, Authority, Control, and Trust; 3) Interaction and Empathy; 4) The Future of High School Design.Conclusion and finding of this research are rooms in blended learning systems offer themselves flexible and versatile spaces and act as effective and efficient discussion places, especially for 11 to 18-year-old students.
Mining Hidden Partitions of Voice Utterances using Fuzzy Clustering for Generalized Voice Spoofing Countermeasures

The high level of usability achieved by voice biometrics compared to other biometric authentication modalities has promoted the widespread use of automatic speaker verification (ASV) systems as authentication tools for several services in various domains.Despite their satisfactory performance, ASV systems are vulnerable to malicious voice spoofing attacks.Hence, voice spoofing countermeasures have emerged as essential solutions to stop such harmful attacks and protect ASV systems as well as users' confidentiality.Typically, these countermeasures classify utterances into genuine and spoofing categories.In this research, we propose two voice spoofing countermeasures that mainly aim to improve the generalization of supervised learning models.This goal is achieved through the adaptive handling of the high variance of both utterance classes, i.e., genuine and spoofing classes.The proposed spoofing countermeasure addresses the poor generalization problem by identifying the hidden structure of each utterance category prior to the classification task.Specifically, fuzzy clustering algorithms were deployed to mine the hidden partitions of utterance classes.The conducted experiments showed that the proposed approach outperforms the state-of-theart approaches in the ASVspoof 2017 dataset, with a testing EER equal to 1.07%.
Observer-Based Fault Estimation for Discrete T-S Fuzzy Systems

In this paper, the problem of fault estimation (FE) for discrete T-S fuzzy system is considered. An observer-based fault estimator is designed by applying the extended state method and the error dynamic system is asymptotically stable and the disturbances’ effect meets the $$H_\infty $$ performance. Sufficient conditions and observer gains for the FE problem are shown. An example shows the feasibility of the proposed FE scheme.
Innovating under Uncertainty: The Patent-Eligibility of Artificial Intelligence after Alice Corp. v. CLS Bank International

Artificial intelligence-related inventions raise complex questions of how to define the boundaries around patentable subject matter. In the United States, many claim that the recent doctrinal developments by the Supreme Court have led to incoherence and excessive uncertainty within the innovation community. In response, policymakers and stakeholders have suggested legislative amendments to address these concerns. We first review these developments, and subsequently use the patent examination record to empirically test the claims of increased uncertainty. We find that, although uncertainty did spike following the Supreme Court’s holding in Alice, it quickly returned to levels comparable to its historic norm. This has implications both for those advocating for legislative changes to the law of eligible subject matter, as well as other jurisdictions considering adopting a test similar to that applied in Alice.
UNIVERSITY 3.0: METHODOLOGICAL APPROACHES TO THE MANAGEMENT OF SCIENTIFIC AND INNOVATIVE DEVELOPMENT

This article is connected with the questions of effective preobrazovaniya of high school students in deystvuyushchie centers of peredovoy science and innovative predprinimatelstva in the framework of the concept of "University 3.0". Formation of the system of management of scientific and innovative development of universities, which will allow to find resources and methods of effective reproduction of scientific and innovative potential.
Using dependency parsing for few-shot learning in distributional semantics

In this work, we explore the novel idea of employing dependency parsing information in the context of few-shot learning, the task of learning the meaning of a rare word based on a limited amount of context sentences.Firstly, we use dependency-based word embedding models as background spaces for few-shot learning.Secondly, we introduce two few-shot learning methods which enhance the additive baseline model by using dependencies.
Media and Interactivity as a Factor in the Professional Development of a Pedagogue in the Modern Computer Educational Environment

This work is devoted to analysis of the contemporary state of the educational milieu and the new qualities of the pedagogue-musician providing relevance in the pedagogical space for him. We relate media and interactivity to such qualities. These conceptions are highlighted in the article, and accentuation is made of the commonality of systems and methods of receiving informational competence on the part of the pedagogue-musician who received any level of education. The authors of the present research work analyze their own experience in the system of distanced education Moodle and Moodle Music from the point of view of actualizing educational technologies. The new technologies integrate to a greater degree into the system of traditional education. Upscaling the overall culture of the media-informational content and communication of a new type, the swiftest inclusion of pedagogues into this process is viewed as a source of transformation and optimization of a new value oriented content which is necessary to be formed by professional musicians. Mention is made of the impossibility of the entire substitution of the personal pedagogical communication with the pupil, moreover, for musicians, where the emphasis is traditionally made on individual lessons. But, wherever it is possible, it is important not to deny the realities of our time and to become involved in the mastery of contemporary informational and computer-music technologies, to adapt to contemporary realities, to upscale their level of media-informational culture and their auditorium, to diminish the gap between innovations based on broad usage of new informational educational technologies, on the one hand, and traditional music pedagogy, on the other hand.
Exploring the Influence of Computer-Mediated Environments and Social Aspects on Self-Resentation in Virtual Spaces

With the advent of the digital age, virtual spaces become people's indispensable living sphere and social networking sites become the salient vehicle for people to present themselves.To figure out key factors influencing individual behaviors in the new context, this paper uses a comprehensive view to examine how CMEs (computer-mediated environments), gender, and culture exert influence on virtual self-presentation.As a review of prior findings, this paper presents factors of virtual aspects and social aspects simultaneously, thus providing a new perspective to understand the influential mechanisms on virtual self-presentation, which may facilitate future research.This study synthesizes 19 articles from 1999 to 2020 related to the keywords on Google Scholar.The results manifest there is an association between CMEs and social aspects, the two of which exert influence on virtual self-presentation comprehensively.
Interactive Word Completion for Plains Cree

The composition of richly-inflected words in morphologically complex languages can be a challenge for language learners developing literacy.Accordingly, Lane and Bird (2020) proposed a finite state approach which maps prefixes in a language to a set of possible completions up to the next morpheme boundary, for the incremental building of complex words.In this work, we develop an approach to morph-based auto-completion based on a finite state morphological analyzer of Plains Cree (nêhiyawêwin), showing the portability of the concept to a much larger, more complete morphological transducer.Additionally, we propose and compare various novel ranking strategies on the morph auto-complete output.The best weighting scheme ranks the target completion in the top 10 results in 64.9% of queries, and in the top 50 in 73.9% of queries.
Development of an Online-Based Administration Service Management Information System at SMP Negeri 1 Datuk Lima Puluh Batu Bara Regency

The implementation of the Administrative Service Management Information System at SMP Negeri 1 Datuk Lima Puluh is one of the efforts to improve education services.The theoretical basis in this study is a theory related to Information System Management.The purpose of this research is to provide a means for students' parents to use information and communication technology at SMP Negeri 1 Datuk Lima Puluh.The next goal is to find out what products and services are needed by SMP Negeri 1 Datuk Lima Puluh and parents of students in developing E-Service Applications.The method used in this study is the Research and Development (R&D) method but is limited to the model development stage, while the approach used is a descriptive qualitative approach.From the development of the model, this research resulted in a Management Information System application product at SMP Negeri 1 Datuk Lima Puluh Batu Bara Regency.After the system test, the E-Service Application runs well.From the research that has been carried out, it was found that the information system used by the school is still conventional.While in the management of administrative services already using computers but the input is still manual, therefore we need a computer-based application program that can be accessed 24 hours and based online, so as to increase efficiency, transparency, positive responses and services to students, teachers, employees and parents.
Research on Translation Corpus Building with the Assistance of AI

The quality of machine translation depends on the corpus available for it to learn from.With the development of AI, the translation corpus is now the key to realize Intelligent translation and scenario-based translation.The data on the Internet, data of the enterprise, user-generated data, machine-generated data, all of which can be the sources of AI-Assisted translation corpus data.Types of these data are diversified.There are term data, text data, unstructured data, and knowledge graph.AI-Assisted translation corpus construction can collect data in the following four modes: open-source data based on the third-party, corpus-sharing mode based on crowdsourcing translation, self-learning mode based on machine, collaborative mode based on human-machine cooperation.In the future, corpus-based translation teaching will be an important part of intelligent translation.
An Efficient Productive Feature Selection and Document Clustering (PFS-DocC) Model for Document Clustering

In mining, document clustering pretends to diminish the document size by constructing the clustering model which is extremely essential in various web-based applications.Over the past few decades, various mining approaches are analysed and evaluated to enhance the process of document clustering to attain better results; however, in most cases, the documents are messed up and degrade the performance by reducing the level of accuracy.The data instances need to be organized and a productive summary have to be generated for all clusters.The summary or the description of the document should demonstrate the information to the users' devoid of any further analysis and helps in easier scanning of associated clusters.It is performed by identifying the relevant and most influencing features to generate the cluster.This work provides a novel approach known as Productive Feature Selection and Document Clustering (PFS-DocC) model.Initially, the productive features are selected from the input dataset DUC2004 which is a benchmark dataset.Next, the document clustering model is attempted for single and multiple clusters where the generated output has to be more extractive, generic, and clustering model.This model provides more appropriate and suitable summaries which is well-suited for web-based applications.The experimentation is carried out in online available benchmark dataset and the evaluation shows that the proposed PFS-DocC model gives superior outcomes with higher ROUGE score.
Joint Modeling of Emoji Position and Its Label for Better Understanding in Social Media

In social media, the frequent use of small images, called emojis, in posts has played a key role in recent communications. However, less attention has been paid to their positions in the given texts although users are known to carefully choose and place emojis that match their post. Exploring the position of emojis in texts is expected to enhance our understanding of the relationship between emojis and texts. In this paper, we propose a novel task of inserting an emoji at a position in a given tweet. We extend an emoji label prediction method considering the information of emoji positions, by jointly learning the emoji position in a tweet to predict the emoji label. Additional information on emoji position can improve the performance of emoji prediction. Human evaluations validate the existence of a suitable emoji position in a tweet. The proposed task makes tweets fancier and more natural. In addition, the emoji position can further improve the performance of irony detection compared to emoji label prediction. We also report the experimental results for the modified dataset, due to the problem of the original dataset for the first shared task to predict an emoji label in SemEval 2018.
Fuzzy Tsukamoto Implementation to Detect Physiological Condition on IoT-Based e-Learning Users

Science and technology advancement drives humans to adapt to the digital world. IT development is proven to positively affect the education area through the concept of electronic learning (e-learning). This is especially true during the COVID-19 pandemic where traditional classrooms teaching was transferred to e-learning. This technological development demands individuals to adapt to the advancement. Despite its benefits, technological advancement may affect the physical condition of e-learning users. When the e-learning users fail to adjust, they might have physical condition problems that cause depression. Therefore, we propose an Internet of Things (IoT)-based system to detect the physiological conditions of e-learning users. By implementing Fuzzy Tsukamoto as artificial intelligence on IoT technology, we can identify the physiological condition of e-learning users such as relaxed, calm, anxious, and stressed conditions. Structurally, the proposed system consists of three stages: 1) Sensor data acquisition, 2) Physiological condition detection using Fuzzy Tsukamoto, 3) Display the output directly to the website. We evaluate the effectiveness of the proposed system in the task of detecting the physiological condition of the ten e-learning users. Based on experimental results, the proposed system presents 84.01% of accuracy. This result indicates that the proposed system is able to reliably detect physiological conditions on IoT-based e-learning users. By detecting psychological conditions, e-learning is expected to become an adaptive learning system so that it can adapt to the characteristics of each user.
Construction of College Students’ English Autonomous Platform based on Virtual Cloud Terminal System

Aiming at the low initiative of students in traditional offline teaching and online MOOC teaching in programming course teaching, this paper analyzes the function of virtual English platform, summarizes the experience of using virtual English platform, constructs hybrid classroom teaching based on virtual English platform, and studies the advantages of virtual English platform in hybrid classroom teaching.Taking Python language as an example, this paper first introduces the functions and uses of virtual English platform, and combined with my own teaching experience, puts forward a hybrid classroom teaching method combined with virtual English platform, analyzes the role of virtual English platform in hybrid classroom teaching, and puts forward the prospect of teaching methods of programming course in the future.
Kaolinitic clays as a potential source of dioxins in the Noosa River catchment, Queensland, Australia

Environmental context Dioxins have been found along the east coast of Australia in agricultural areas where there is no obvious source of dioxins. These dioxins have an unusual signature that does not match common industrial sources, but it has been suggested that they may be associated with pesticide use. This study found a strong correlation between dioxins with this unique signature and the amount of a kaolinitic clay in the sediments sampled. Abstract The presence, concentrations and profiles of 2,3,7,8-substituted polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) in sediment were investigated in this study with the aim of determining whether dioxin-like compounds were present and, if found, a likely source could be deduced. The sampled catchment lies within an area of high conservation value. Sediments from seven lake sites were sampled as possible sinks for any contamination from historical pesticide use. PCDD/Fs were measured in all the lake sediments. The 2,3,7,8-substituted congener profile was dominated by octachlorodibenzo-p-dioxin (OCDD) with furans at or below the limit of detection, a profile that has been associated with kaolinitic clays from around the world. A strong and significant correlation was found between the total dioxin concentration and the percentage of kaolinitic clay in the sediments. The lack of furans in the 2,3,7,8-substituted PCDD/F profile indicates pesticides or pentachlorophenol (PCP) are unlikely to be the source in the catchment. Further, the concentration of total dioxins and OCDD tended to be higher than those measured outside the study area, even though, overall, the study area is likely to have had less pesticide use than the other intensive agricultural areas previously studied. The results presented in this paper indicate that caution should taken when attributing the presence of dioxins in soil and sediment to anthropogenic sources.
AUTOBIOGRAPHY OF I. S. SHMELEV

This article is devoted to the publication of I. S. Shmelevʼs autobiography from the collection of S. A. Vengerov (Manuscript Department, Pushkinskiy Dom), a detailed answer to a standard ques-tionnaire, written specifi cally for the occasion. While working on the text, Shmelev used the materials previously prepared for other purposes. The research led to important clarifi cations in the dating and purpose of his autobiography published in 1973, from the Shmelev Archive at the Research Department of Manuscripts, Russian State Library.