Reviewerly/exHarmony huggingface dataset:
The development and application of an AI chatbot-based phatic communion teaching model for elementary school students

The purpose of this study is to develop a phatic communion teaching model using AI chatbots and find out its effect in elementary school. Phatic communion is vital in that it has a social function. The experimental classes were conducted with 18 students in the 5th grade. The results are as follows: First, the teaching model aimed to nurture the learners’ phatic communion speaking skills by having them chat with AI chatbots. The model included explicit teaching methods for the concept of phatic communion. Second, in building the AI chatbot, the language perspective and the method perspective were both brought into consideration. Third, several features were found in conversations between the chatbot and learners. Learners made expressions of empathy at their own will using forms of phatic communion. The diversity of expressions was also confirmed. The learners responded that they felt connected to the chatbot and showed their willingness to continue using phatic communion. The study had some limitations. It was challenging to allow a free conversation between the chatbot and learner because the chatbot was built based on a script. Additionally, learners with low levels of English had difficulty learning phatic communion with this model. It is hoped that various teaching methods for phatic communion will be developed after additional research and sharing ideas with other teachers.
Research on College English Independent Learning System Based on Constructive Teaching

Under the development trend of economic globalization, the trade exchanges between countries become more and more close, and the social development puts forward higher requirements for college students' English level. In order to adapt to the new social environment and meet the requirements of the country and society for talent cultivation in the new era, the education department of Our country proposes to speed up the pace of college English education innovation and make rational use of modern educational technology.
How Monero Works

Disruptive technology means that we keep the benefits of the existing things and enjoy the new tech's advantages. Let’s take electric cars as an example. They provide all the benefits of traditional gasoline cars – they can drive, have a somewhat comparable price, and are still as safe and convenient as the best “dirty” cars. But on top of that, electric cars are “green” and less noisy. If we follow this logic, which can be observed with any other innovative technology, the new payment systems based on crypto must provide all the benefits of the traditional banking system and plastic cards, even before we get decentralization, universal access, and other new features.
Introduction

This chapter starts with the decline of trust found in contemporary academic literature and media. It notes how distrust became cliché in the lives of people. The coronavirus pandemic has reignited the attention on the importance of trust. Numerous policy responses to the pandemic were framed under the context of trust. Thus, the decline of trust has been identified as a fundamental threat to democracy. The dimensions of multi-level governance raised issues on building trust in line with networked governance and the varying capacity of governance to retain and build trust. The chapter highlights its research design under the context of transparency as a necessary condition to build trust.
Languaging, Body and Translation in Giulio Angioni’s Una Ignota Compagnia (1992)

Giulio Angioni’s novel <italic>Una ignota compagnia</italic>, first published in 1992, is discussed in Chapter III paying particular attention to the centrality that the use of various languages, and the mixing of them, acquires in the text. Even if the novel is certainly one of the first texts to appear in Italy to address the issue of what was starting to be perceived as Italian society becoming multicultural, it has not been the object of particularly sustained critical attention. Nonetheless <italic>Una ignota compagnia</italic> constitutes one of Angioni’s most ambitious texts, able as it is to confront the changes induced by globalization while engaging at the same time with diverse experiences of Sardinian emigration.
AN ANALYSIS ON STUDENTS’ WRITING MOTIVATION AT SMKN 1 BANGKINANG

Low writing motivation is a result of students' lack of interest in writing, their lack of writing vocabulary, and their inability to develop their ideas into written form. There are two types of student motivations: those that come from within the student, known as intrinsic motivation, and those that come from the outside, known as extrinsic motivation. The purpose of this study is to evaluate the writing motivation of students at SMKN 1 Bangkinang Kota. The sample for this study consisted of 36 students in the tenth grade who were majoring in computer and network engineering, with 19 male and 17 female students making up the total. This study employs a quantitative design because it is a suitable method for gathering statistical information to address research questions. The findings demonstrated that SMKN 1 Bangkinang students in the tenth grade had better intrinsic motivation to study English, particularly writing. This is demonstrated by the average intrinsic motivation score (3.76) which is greater than the average extrinsic motivation score (3.31). In other words, they write because they want to be proficient writers.
Using the PESTEL Model to Analyze the Impact of the Normalized Epidemic on Enshi's Tourism Industry

Since the normalization of epidemic prevention and control, with the joint efforts of various departments at all levels, the overall situation of epidemic prevention and control in Enshi has been stable.In May 2022, the Ministry of Culture and Tourism issued a "circuit breaker" mechanism for inter-provincial tourism; in June 2022, the Hubei Provincial Department of Culture and Tourism issued documents related to the resumption of inter-provincial tourism, bringing hope for the recovery of Enshi's tourism industry.In this context, this paper will use the PESTEL model to analyze the macro environment of Enshi's tourism industry from the six aspects of politics, economy, social culture, technology, environment and law, explore the current situation of Enshi's tourism development, and put forward feasible development suggestions. Research BackgroundEnshi Prefecture is located in the southwest of Hubei Province.It is the youngest autonomous prefecture in the Republic and the only ethnic minority autonomous prefecture in Hubei Province.Because of its unique topography, climatic environment, hydrological environment and natural resources, Enshi has great advantages in developing tourism.Li Mingshu (2019) believes that with the improvement of traffic conditions, tourism has developed into the pillar industry, green industry and engine industry with the greatest potential and the strongest vitality in Enshi Prefecture.Wang Liang (2020) believes that the development of Enshi's tourism industry, the construction of ecological environment and the quality of life of residents are important factors to promote the level of tourism urbanization in Enshi Prefecture [1].Pi Pengcheng (2021) found that the sustainable development of forest health tourism in Enshi Prefecture has advantages > opportunities > disadvantages > threats [2].However, from the end of 2019 to 2020, due to the rapid spread of the epidemic and strict epidemic prevention measures, Enshi's tourism industry was almost at a standstill [3]; it was only after the transition to the normalized prevention and control stage that Enshi's tourism industry began to pick up. The basic situation of Enshi tourismAfter inquiring about the data in the statistical bulletin of the Enshi State Bureau of Statistics, a table of relevant data on Enshi's tourism industry from 2017 to 2021 (five years) was formed (Table 1).The table shows that Enshi has more than 30 A-level scenic spots, including 4A-level and above.
TEACHING ENGLISH WITH SPEAKING FOR TOURISM MODULE (STM) BASED ON FOLKTALE IN LARIKE VILLAGE

English in vocational learning is given more attention to the English culture (source culture) rather than local culture (target culture). Furthermore, the demand of English speaking in tourism is increasing significantly and this leads to design a new of teaching material based on local culture. This study aims to design teaching material based on local culture known as folktale in Larike village, Ambon. Maluku. This study obviously used research and development (R&amp;D) by following the ADDIE model (Analysis, Design, Development, Implementation and Evaluation). The first results obviously shown that destination and tourist information got the highest percentage (80%). Tradition was the next rank with percentage (65%) followed by shopping and sightseeing (36%). In addition, the language functions that they need the most is asking for and giving information with percentage (60,8%). Then, it also clearly obtained describing an object in the second rank with percentage (54,1%) and asking for and giving directions with percentage (45,2%). In the development stage, speaking for Tourism Module (STM) based on folktale were eligible based on the experts and students’ validation with average score of holistic Aiken index respectively 0,876 (valid) and 0.795 (valid). The second result of Speaking for Tourism Module (STM) based on folktale on small-scale implementation with scored 81.74% and large-scale trials obtained a score of 85%. In conclusion, based on the value obtained, Speaking for Tourism Module (STM) based on folktale was feasible (very valid) to be implemented to the students in Larike village.
Path Planning Method Based on Multi-direction Improved A-Star Algorithm

In the process of path planning, the traditional A* algorithm has some disadvantages, such as fewer directions to choose, only two distances between adjacent nodes, non-smooth path, and non-shortest path. In order to address these problems, this paper proposes the multi-direction improved A* algorithm. In this algorithm, there are multiple selection directions when selecting the next node, and the number of optional moving costs is increased. The algorithm not only expands the searchable neighborhood, but also shorts the total length of the path by means of path feature points. The effectiveness of the proposed algorithm is verified by simulation in two different environments: the orderly environment and chaotic environment. The simulation results show that the path planned by the improved A* algorithm not only requires the shortest simulation time, but also can reduce the total length of the path, and the number of inflection points is less. The multi-directional characteristics of the proposed method can also be reflected in the final planned path.
A Comprehensive Solution for Handling Security Issues with Seaport IoT Systems

In the current epoch, the Internet of Things (IoT) can be reflected as an important technological revolution related to evolution of smart cities, smart homes, IoT-controlled factories, and IoT for logistics in seaports implementations. With the existence of smart sensing systems in seaports becoming a reality today, different sectors in seaports are working toward a programmed mode. Some of the eye-opening projects related to smart seaports in the IoT era can be found all over the globe. In many of these new architecture implementations, even though the rapid development of IoT enables us to inspire new research works, the challenges in IoT also grow equally in terms of security. Encryption plays a key role in safeguarding IoT hardware and the data from various sensors. The proposed work focuses on reality study on various security issues emerging in the usage of IoT in seaports and suggestions for handling the security issues. Highly secure algorithms need developed in IoT encryption level standards are discussed here. Conclusions regarding the extension of future research prospects in the IoT systems and high-level security in seaports are guided in the final segment of the paper.
Evaluating Deep Learning Algorithms for Natural Language Processing

Natural language processing (NLP) is generally referred to as the utilization of natural languages such as text and speech through software. The NLP is studied for more than 50 years approximately. Deep learning (DL) is one of the subdomains of machine learning, which is motivated by functions of the human brain, also known as artificial neural network (ANN). DL is performed well on several problem areas, where the output and inputs are taken as analog. Also, deep learning achieves the best performance in the domain of NLP through the approaches. The approaches need additional data, however, not have as much linguistic expertise for operating and training. There are a large number of hype claims in the region of deep learning techniques. But, away from the hype, the deep learning techniques obtain better outcomes. In this paper, the information linked with the DL algorithm is analyzed based on the NLP approach. The concept behind the network implementation and feature learning is described clearly. Finally, the outline of various DL approaches is made concerning result validation from preceding models and points out the influence of deep learning models on NLP.
Implementation of Data Mining with Naive Bayes Algorithm for Eligibility Classification of Basic Food Aid Recipients

One of the primary issues that the government of a nation concentrates on is poverty. The provision of precise and focused data on poverty is a crucial component of the Poverty Reduction Strategy. One technique for classifying data is Naïve Bayes. The aid manager will subsequently use the categorization findings to inform judgments about categorizing and determining who should get basic food assistance. Predictions for those who get basic food assistance fall into two categories: eligible and ineligible. Sample data from the hamlet of XYZ used as the basis for the forecast. In this study, a web-based application is used to construct and assess the Naïve Bayes method. The accuracy for 135 training data, 40 test data, and seven characteristics employed generates 86 percent accuracy, 85 percent recall, and 88 percent precision according to the assessment findings using the confusion matrix.
Improving the Ability of Persons Identification in a Video Files Based on Hybrid Intelligence Techniques

With the advancement in technology, the importance of person recognition in photographs or videos has grown due to its usefulness in the search for wanted persons and criminal identification using various theories and algorithms and various non-hybrid and hybrid techniques to identify the person through the face, and its features have been developed. The paper proposed a hybrid algorithm to improve the performance of person identification in video files. The system works through several steps: first, face detection using Viola–Jones algorithm; second, feature extraction by algorithm local binary pattern (LBP); final, person identification by hybrid proposed algorithm (HPBFF) by hybrid between backpropagation neural network and firefly algorithm. The results show that the system was able to identify and monitor the person with a high classification accuracy rate of 98.4%, compared to 94.7% for the approach without the hybrid. The results of the tests revealed that the system is robust and has a high recognition rate, making it suitable for use in mobile and compact identification and authentication.
Contrast Limited Brightness Preserving Dynamic Fuzzy Histogram Equalization Technique for Enhancement of Steady State Tokamak Plasma Images

Fusion energy can be obtained by combining deuterium and tritium in the nuclear fusion reactor. Measurement and analysis of the hot plasma obtained during fusion is essential for fusion energy studies. Image processing is one of the non-invasive methods used to measure the plasma parameters. In this work a novel image processing technique, Contrast Limited Brightness Preserving Dynamic Fuzzy Histogram Equalization (CLBPDFHE), is proposed to enhance the contrast of the plasma in order to measure the plasma parameters to work on plasma confinement for a long time. Performance metrics obtained from simulation results show that the contrast of plasma is improved in the CLBPDFHE technique compared to conventional Histogram Equalization (HE) techniques.
Artificial Neural Network-Based Tic-Tac-Toe Game

The tic-tac-toe is a game for two players in which the three-row, three-column square block is filled with a cross (X) or a circle (O). A changeover will occur between the participants in the game, allowing each player shall make a choice. Reward points are awarded, if one of the players has marked the same markers as the other like horizontally, vertically, or diagonally. The goal of this research is to train an artificial neural network (ANN) how to play the tedious game of tic-tac-toe using a series of mathematical combinations of the sequences that the system would play if the rules were followed. We developed the most effective technique in the game of tic-tac-toe. The performance measures of the ANN classifier are calculated, the results of the experiment revealed that ANN can improve accuracy, and it might be utilized in other board games like Go and chess.
A METHOD FOR HANDLING CLOUD COMPUTING USING INTERNET CRAWLERS AND DATA MINING

The internet becomes a crucial component of organisation.The massive usage data produced by user and Internet interaction can be collected and used as knowledge for a variety of applications.As internet browsing becomes a more common activity for more people worldwide, business and research communities are paying more attention to the analysis of web site regularities and patterns in user navigation.When it comes to quantity, complexity, semantics, distribution, and processing costs, cloud computing, internet-based computing, cognitive informatics, and computational intelligence represent extraordinarily huge scales of data.Even more information has been gathered about Internet and mobile device users.To enable the capability to make sense of and optimize the use of such large amounts of online data for extracting knowledge and decision-making, we need new tools for such a massive online data mining.It has been demonstrated that visualisation is a useful technique for gaining understanding about cloud computing.Visualization-based data discovery tools are centred on the front end of cloud computing to let organisations more easily and thoroughly explore the data, while technologies like Apache Hadoop and others are developing to solve back-end challenges like storage and processing.
The evolution of the code during review: an investigation on review changes

Code review is a software engineering practice in which reviewers manually inspect the code written by a fellow developer and propose any change that is deemed necessary or useful. The main goal of code review is to improve the quality of the code under review. Despite the widespread use of code review, only a few studies focused on the investigation of its outcomes, for example, investigating the code changes that happen to the code under review. The goal of this paper is to expand our knowledge on the outcome of code review while re-evaluating results from previous work. To this aim, we analyze changes that happened during the review process, which we define as review changes. Considering three popular open-source software projects, we investigate the types of review changes (based on existing taxonomies) and what triggers them; also, we study which code factors in a code review are most related to the number of review changes. Our results show that the majority of changes relate to evolvability concerns, with a strong prevalence of documentation and structure changes at type-level. Furthermore, differently from past work, we found that the majority of review changes are not triggered by reviewers' comments. Finally, we find that the number of review changes in a code review is related to the size of the initial patch as well as the new lines of code that it adds. However, other factors, such as lines deleted or the author of the review patchset, do not always show an empirically supported relationship with the number of changes.
Speech Act of Demand by the Community of Speaking on the Buying Transaction of Sand Mining on the River Banks in the Sungai Sariak Region, Padang Pariaman Regency

Speech Act is communication activity which contains the intent to be conveyed when speaking (the illocutionary power of an utterance) and the effect the speaker wants to achieve (perlocutionary speech). In the sale and purchase of sand mining on the banks of the Sariak River, Padang Pariaman Regency, there is a speech act between the miner and the buyer of the sand. The researcher wants to reveal the lexicon and meaning in speech acts as linguistic documentation and the richness of the lexicon. The purpose of this research is to develop linguistics in a sociopragmatic perspective. The theory used in this study is the theory of speech acts in sociopragmatic science. In this study the author uses a qualitative approach. The researcher found the syntactic aspect in the form of words and sentences. The syntactic form found is in the form of nouns that turn into adverbs due to changes in meaning in speech acts based on the context. Then find the sentence mode in the speech act of request by using declarative and interrogative sentences/questions, and using terms and language that are in accordance with the social context of interaction and culture of the community, so that efficient communication is achieved.
An image registration technology for fault detection of EMU underbody

In order to efficiently match and use the monitoring information obtained by the EMU fault detection robot, image registration technology can play a role. Facing the operation site of EMU fault detection robot, based on the original image data information of vehicle bottom fault collected by EMU fault detection robot, this paper carries out gamma transform and windowing preprocessing on the vehicle bottom image of EMU, puts forward the image registration algorithm of vehicle bottom fault detection of EMU based on Fourier transform, and gives the specific operation process of this algorithm. The experimental verification and comparative analysis show that compared with the image registration technology of EMU underbody fault detection based on Fourier transform, the image registration technology of EMU underbody fault detection based on conventional affine transform has obvious advantages, high effectiveness, strong robustness, accuracy and reliability, and can complete the high-precision, stable and reliable matching of images in a reasonable time, which meets the requirements of field practical application. The research of this paper provides theoretical support and technical basis for the intelligent identification of vehicle bottom fault defects of EMU, and has a good application prospect.
AUTOMATED MULTI-DOMAIN ENGINEERING DESIGN THROUGH LINEAR GRAPHS AND GENETIC PROGRAMMING, 160-170.

This paper proposes a methodology of integrating the linear graph(LG) approach with genetic programming (GP) for generating anautomated multi-domain engineering design approach by using thein-house developed LG MATLAB toolbox and the GP toolbox inMATLAB.