Reviewerly/exHarmony huggingface dataset:
Anger and Voter Loyalty

This chapter shows that, when they are angry, voters are more likely to vote for their own party’s presidential candidate. This chapter further shows that, in an era of nationalized politics, anger toward the opposing party’s presidential candidate can lead to voter loyalty in subpresidential (e.g., House and Senate) elections. Moreover, I show that anger leads to a higher probability of a voter casting a straight-ticket ballot for his or her party. In sum, this chapter shows that an angry voter is a loyal voter.
MODERN TEACHING APPROACH: VIRTUAL REALITY AND 3D MODELING

Since the last few decades, virtual reality (VR) and augmented reality (AR) interfaces have shown the potential to enhance teaching and learning, by combining physical and virtual worlds and leveraging the advantages of both. Conservative techniques of content presentation (fixed video, audio, scripts) lack personalization and interaction. There is a need for MOOC to embrace advanced learning techniques to provide more engaging experience to its learners. Finally, we create internal avatar model while using in virtual reality (VR) and augmented reality (AR) interfaces.
Digital Accounting Algorithms

In the article, the authors explore some aspects of the organization of accounting processes in Russia. It is said that it is necessary to improve the existing accounting system in the country, as this requires the active development of digital technologies that widely cover the economy. The reorientation of the existing accounting system in the Russian Federation to the needs of the digital economy is possible through the widespread use of various digital accounting algorithms. The implementation of the proposed ideas can lead to a qualitative change in the organization of management and decision-making in all major areas.
English Education Innovation Model Based on Big Data

With the gradual acceleration of globalization, English, as the world's first language, is becoming more and more important in various fields. In China's education, English education mode is not very perfect. Therefore, we can combine the technical characteristics of the current era, grasp the technology of the times, use big data to find out the shortcomings of English education, and put forward appropriate solutions combined with the actual situation. This paper analyzes the advantages of big data technology applied to English teaching, analyzes and discusses the advantages of English education mode under the background of big data compared with the traditional education mode by taking two schools with the same category as the research object, and then the experiment shows that the former can improve the efficiency of the whole teaching work, and the students in the two schools can improve the efficiency of the whole teaching work In comparison, 37% of the participants in the experimental group were satisfied, 30% of them were very satisfied, while only 27% of the control group were satisfied. Therefore, the first mock exam is to introduce the innovation of English education mode in the context of big data. Based on this, the paper also makes some research and Discussion on the development of this model.
CAISY: Chatbot using Artificial Intelligence and Sequential Model with YAML Dataset

This paper presents a method for constructing a software robot “CAISY” for answering queries for any training set(domain). This has been achieved with the help of word embedding and Sequence 2 Sequence model using Long Short Term Memory neural networks. The proposed method can respond to test queries under a maximum of 5 seconds response time. The exciting feature of Caisy is it could be applied to any domain where the data is available for training the model. For the demonstration, this paper presents Caisy is taught for answering queries related to Normal Conversation. Caisy has been optimized by minimizing the loss value with the help of variation of hyperparameters.
QPA*: Design of a searching and path planning algorithm for intelligent agents in two dimensions

Searching algorithms and path planning algorithms are in a variety of applications, where the mobile robotics field is one of the most popular. QPA* algorithm attempts to perform this two strategies at the “same time”. The algorithm makes use of three strategies to generate a different solution to the exploration and path planning mainstream, using a “proposed version” of a modified A* (star) algorithm, the idea of the Potential Fields Algorithm (to deal with the collision avoidance) applied as a artificial binary field, and an exploration heuristic named “quadrant grid search”. The QPA* algorithm is designed to be applied in a search and rescue robot, where the problem of “localization” and “mapping” is consider to be independent of the exploring and path planning algorithm. The “exploration” part of QPA * is intended to overcome the main problem of path planning algorithms, that is the lack of a true “exploration factor” and preserve the efficiency of making a route using the path planning approach of A* algorithm. Finally, we test three different approximations (for the path planning part) in combination with the quadrant grid search, in order to identify the pros and cons of this design.
Reinforced Keyphrase Generation with BERT-based Sentence Scorer

Keyphrase generation is a crucial task that can effectively provide underlying support for numerous downstream natural language processing (NLP) tasks, e.g., information retrieval and document summarization. However, the existing generative or extractive methods neglect the fact that the sentences are not equally important to generate the keyphrases of the articles. Intuitively, some sentences are more representative than others to catch an article's central idea. To better select the representative sentences, we apply a BERT-based sentence scorer to estimate the importance of each sentence. Then, we design two strategies to more accurately generate the keyphrases by employing the learned importance score. In addition, to alleviate the inconsistency problem between the training and testing modes, we introduce a fine-grained token-level reinforcement learning (RL) reward based on prefix-matching to enhance the training procedure to boost the performance of our model. Empirical results on five datasets demonstrate that our model brings substantial improvements over the state-of-the-art methods.
Approach to Relevant Data Providing for the Pedagogical Design in Knowledge-Intensive Areas

This article is devoted to the issue of creating an information system for obtaining data necessary for the pedagogical design. The proposed system is implemented in the form of an application programming interface that provides data in a standardized form, which allows it to be used not only as an independent data source but also, for example, to be embedded in the information systems of universities. The proposed system provides the following standardized data: information on educational and professional standards, employers’ requirements, and key skills of applicants in accordance with the standards, events related to the professional sphere. Educational and professional standards are downloaded from open government sources. Data on employer requirements and key skills of the applicant is extracted from vacancies obtained using the hh.ru application programming interface in accordance with the standards. The data is processed using natural language processing technologies and cluster analysis. The text data is normalized using Porter's stemmer, a TF-IDF weight matrix is created and cluster analysis is performed using the DBSCAN algorithm in order to determine the most necessary and relevant skills in a particular professional field. An additional function is a selection of events related to the professional field. The data obtained make it possible to form the relevant content of the educational tasks of the workshops and adjust the implementation of the educational process to the needs of the labor market, which increases the relevance of the skills acquired during the program of study.
Nuclei Image Boundary Detection Based on Interval Type-2 Fuzzy Set and Bat Algorithm

In biological science, detection of nuclei in cell images is necessary for research and disease identification. The low light and varying illumination in the nuclei images make them highly uncertain to differentiate. As a result, the automatic boundary detection of the nuclei in cell images is a crucial task. Here, we propose a nuclei image boundary detection based on an interval type-2 fuzzy set(IT2FS). The IT2FS manages the uncertainties in the nuclei images and helps to detect accurate boundaries. The bat algorithm (BA) is exploited to generate the proper IT2FS build upon statistics of the image. The Kaggle 2018 dataset is used to measure the performance experimentally. Our method is found to be superior to the recently published methods on the standard dataset.
EPF-CLPA: An Efficient Pairing-Free Certificateless Public Auditing for Cloud-based CPS

Cloud based cyber physical system (CPS) enables individuals to store and share data collected from both cyberspace and the physical world. This leads to the proliferation of massive data at a user's local site. Since local storage systems can't store and maintain huge data, it is a wise and practical way to outsource such huge data to the cloud. Cloud storage provides scalable storage space to manage data economically and flexibly. However, the integrity of outsourced data is a critical challenge because user's lose control of their data once it's transferred to cloud servers. Several auditing schemes have been put forward based on public key infrastructure (PKI) or identity-based cryptography to verify data integrity. However, “the PKI-based schemes suffer from certificate management problem and identity-based schemes face the key escrow” problem. Therefore, to address these problems, certificateless public auditing schemes have been introduced on the basis of bilinear pairing, which incur high computation overhead, and thus it is not suitable for CPS. To reduce the computation overhead, in this paper, Using elliptic curve cryptography, we propose an efficient pairing-free certificateless public auditing scheme for cloud-based CPS. The proposed scheme is more secure against type I/II/III adversaries and efficient compared to other certificateless based schemes.
Information Technologies in Professional Training of Medical University Graduates: Modelling Standard Interaction with Outpatients and Treatment Process

The paper offers an architecture and a preliminary design of a special training computer program, which targets to improve analytical medical skills of graduate students. The article includes presenting computer programs for students to improve their medical skills. The program allows medical students to prepare for activities of outpatient clinics in practical health care: maintaining medical records, developing a diagnostic program, drawing up a treatment plan and monitoring a patient at home. Attention is paid to the discussion of the form of communication that can be used to transfer data between a patient and a doctor. The proposed interface is simple and includes crucial points from some other programs. The program can be applied for training a wide audience, from students to teachers.
The Application of Original Movies in English Listening and Speaking Teaching in Secondary Vocational Schools

Film is an important language carrier and cultural bridge. As an auxiliary teaching method, the appreciation of the original English film plays an important role in listening and oral English teaching in vocational schools. This article aims to improve the teaching level of middle vocational English by discussing the application of the original movie in middle vocational English listening and oral teaching. In this paper, a questionnaire survey and interviews were conducted with some students in A vocational school. After finishing analysis, it was found that 93.71% of the students believed that the original movie was simply to impart knowledge and skill training in the classroom, neglecting the communication between listening, speaking, reading and writing; 66.23% of students believe that the original film teaching method is conducive to improving their listening and speaking skills, and put forward the application strategy of the original film in listening and speaking teaching. The research in this article helps to promote the development of vocational English education.
A Vector Tracking Structure of FLL-Assisted PLL for GNSS Receiver

Satellite-based navigation applications have become one of the most common navigation methods in the world. The tracking of satellite navigation receiver in weak signal environments is challenging. To improve receiver tracking performance, a frequency locked loop (FLL) assisted phase locked loop (PLL) vector tracking structure for GNSS receiver is proposed in this paper. In the carrier loop, a carrier tracking algorithm of Kalman filter (KF)-based FLL-assisted PLL is used. In the code tracking loop, the pseudo-range information is fed back to the code numerically controlled oscillator (NCO) through vector tracking, and the code frequency of each tracking channel is adjusted to realize the information sharing of all channels. Experimental results show that, the FLL-assisted PLL vector tracking algorithm can quickly re-lock the satellite signal with good robustness after severe signal fading.
BP neural network model for comprehensive evaluation of rural financial ecological environment

For this reason, the key to solve the problem of rural financial development is to solve the problem of rural financial development. At present, the state has given important instructions to improve the rural financial ecological environment, but the relevant research on the evaluation of rural financial ecological environment in China is still insufficient. In view of this situation, this paper puts forward a BP neural network model for the comprehensive evaluation of rural financial ecological environment. First of all, this paper studies the relevant basic theory of financial ecology and ecological environment comprehensive evaluation. Through the research, this paper believes that the construction of rural financial ecological environment involves many factors, and each factor has a mutual influence. It is difficult to determine the influence of a single factor on the final result. Therefore, in view of this complex situation, this paper establishes a set of multi factor evaluation index systems including economy, policy, law, culture, etc. And these complex factors are trained by BP neural network. The training results were normalized to quantify the specific impact of each index on the rural financial ecological environment. Finally, in order to verify the actual evaluation effect of this model, a number of comparative experiments including validity verification, stability analysis, comparison and verification of different model error rates are carried out. Through the analysis of experimental data, we can see that the BP neural network evaluation model in this paper has good comprehensive performance and significantly improves the calculation accuracy compared with the traditional analytic hierarchy process.
A GNSS Loop Tracking Structure Based on Unscented Kalman Filter

In GNSS Vector Tracking (VT) receiver, the tracking loop information is used to update the navigation solution. Different from the traditional GNSS receiver, changes of phase and frequency in the tracking loop can affect navigation results directly. In order to improve the fluctuation of the carrier frequency, a GNSS loop tracking structure based on Unscented Kalman filter (UKF) is proposed in this paper. A frequency-locked loop system model is constructed, which includes the state and the measurement equations. The noise variance of each part is used to assist UKF to complete the carrier loop tracking. The experimental results show that the UKF-based tracking carrier algorithm can output stable pseudorange rate changes in weak signal environment. The carrier-to-noise ratio of UKF is higher than the traditional tracking method when the tracking loop lock successfully.
Human-to-Robotic Voice Conversion by Employing Wave Patterns Based on Gender and Emotions

Mutual conversion from one’s voice into another is one of the promising research fields in speech processing communities while working with human voice. Influenced by the rapid interest in this area in recent trends, we have developed a system to identify gender and emotions, e.g., sad, happy, angry, neutral, and fear from human voice. A separate repository containing wave patterns of all possible phonemes of male and female voice in different emotions has been developed by employing this system. Similarly, we have prepared another system to convert human voice into equivalent phonemes. On the other hand, like human voice wave repository, an additional repository containing wave patterns of robotic voice has also been developed. Finally, the phonemes of human voice are converted into their corresponding phonemes of equivalent robotic voice based on the matched wave patterns available in this mapped repository. The results have shown satisfactory performance in voice conversion.
통사-화용-운율 접합면에서의 한국어 문중 ‘-요’ 첨가에 대한 시론(試論)

Language and Information Society 41. This article has two main aims: One is to review some previous pioneering studies on the syntax-pragmatics interface. It starts with a review of Ross’s (1970) seminal work of the “performative” analysis and its recent revival at the syntax-pragmatics interface. The other purpose is to offer a challenging proposal of sentence-medial attachment of discourse marker -yo in Korean at the syntax-pragmatics-prosody interface. Based on the view that syntactically, sentence-final -yo is an exponent of the Speech Act Phrase for the addressee located above the matrix/highest CP (Yim 2013), and on the fact that prosodically, sentence-medial -yo forms an intonational phrase (Yim and Dobashi 2016), the article argues that sentence-medial -yo also is a spell-out of intra-clausal Speech Act Phrase.
Research on Furniture Design Based on Computer Software Technology

Abstract With the development of computer technology, there are more and more related software for various fields. This paper mainly studies the specific application of Solidworks parametric 3D design software and ANSYS software in home design.
Visualizing Evolving Trees

Evolving trees arise in many real-life scenarios from computer file systems and dynamic call graphs, to fake news propagation and disease spread. Most layout algorithms for static trees do not work well in an evolving setting (e.g., they are not designed to be stable between time steps). Dynamic graph layout algorithms are better suited to this task, although they often introduce unnecessary edge crossings. With this in mind we propose two methods for visualizing evolving trees that guarantee no edge crossings, while optimizing (1) desired edge length realization, (2) layout compactness, and (3) stability. We evaluate the two new methods, along with five prior approaches (three static and two dynamic), on real-world datasets using quantitative metrics: stress, desired edge length realization, layout compactness, stability, and running time. The new methods are fully functional and available on github. (This work was supported in part by NSF grants CCF-1740858, CCF-1712119, and DMS-1839274.)
KALIMAT PENOLAKAN DALAM BUKU TEKS SEJARAH INDONESIA KELAS XII SMA SWASTA MEGATAMA KOTA JAMBI

In the Indonesian History textbook, there are direct and indirect refusal sentences. It is said directly if the sentence conveyed can be understood as a refusal, such as a word  no  when it is uttered, then the sentence has described the refusal; if the sentence has an ambiguous or unclear meaning, then it is said as indirect refusal. This research aims to describe the sentence of refusal by using the word  no  or equivalent, reasons, conditions, suggestions or choices, and comments. The research was conducted by using a qualitative descriptive method. The data was collected by using the documentation technique. This research found five forms of refusal sentences include refusal by using the word  no  or equivalent, refusal by using reason, refusal by using terms, refusal by using proposals or choices, refusal by using comments. Thus, it can be concluded that an invitation, offer and request are not always fulfilled so that a refusal speech occurs, a refusal can be spoken based on the form so as not to be disappointed.
Classification of Human Postural Transition and Activity Recognition Using Smartphone Sensor Data

The global statistics on health monitoring show that 15% of humans in the world live with some kind of disability. One of the fundamental rights of such people is the existence of companion to supervise their day-to-day activities. Smartphones are beneficial for this purpose of monitoring human activity and provide means that give high accuracy while estimating activities. Sensors such as accelerometer and gyroscope available in any smartphone can be used to record basic activities like walking, sitting, standing, etc., with the ones that involve postural transitions for example sit-to-lie, stand-to-sit, etc. This paper proposes a methodology in order to overcome the difficulty that lies in recognition of such activities with transitions using filtering, windowing and outlier detection. The results of the proposed methodology show that logistic regression classifier provides the highest accuracy of 96.16%. The analysis and approach outperform in comparison with the previous works of the researchers.
DISTANCE EDUCATION: A «NEW TREND» OR THE REQUIREMENT OF THE INFORMATION WORLD

The authors of the article presented vision of the existing concept in Russia of creating and developing a single system of distance education. Recognizing the existence of distance learning as a need for the information age, the authors make a number of constructive proposals regarding the reorganization of the educational process and the selforganization of a person as the main actor, as well as the creation of a single information and educational space.
Combating the COVID-19 Hate and Racism Speech on Social Media

The spread of COVID-19 worldwide has been associated with hate and racism speech on social media which sometimes encourages violence and bullying in the different communities. Some officials, public figures and even common people, including students, have been expressing hate, racism, negative, hostile, and intolerant attitudes towards certain groups of people based on their color, origin, race, religion or social/political stance. This study surveys students and instructors’ views of COVID-19 five months after the outbreak of the pandemic, and whether they consider it a punishment from God to certain countries or not. Based on the findings, it proposes the creation of an anti-hate Twitter page to teach students tolerance rather than negative sentiment associated with COVID-19.