Reviewerly/exHarmony huggingface dataset:
Enhancing Students’ Public Sector Accounting Learning by Using Augmented Reality

Public sector accounting is regarded as a critical component of accounting students' foundational skills that should be mastering.Basically, in terms of transaction recording, public sector accounting differs significantly from finance or managerial accounting.So it is important to give an interactive learning media to students so that they can master the basics of public sector accounting easier.Many real cases from any institution (government, worship place, hospital, school or university, and any other non-profit organization) can be utilized as examples in class to improve learning effectiveness.To pursuing all of that, the researcher use an augmented reality (AR) technology in this study.AR technology that has been developed in this research will figure out 2D explanation with animation by targeting a marker with the mobile camera to improve the learning experience.The application itself (AR) contain of 5 material and 2 assessment.Augmented reality will create objects that features the real environment and enable learners to interact with it through these objects.To confirm the effectiveness of this technology, 50 students studying public sector accounting was recruited as participants in this project to validate the effectiveness of this technique.The 50 students were divided into 2 groups, which were experimental group and control group.Then their ARassisted learning outcomes was quantified using Blooms cognitive degrees, which indicate the degree of achievement at various stages of learning.The results found that the students in the experimental group approved greater knowledge significantly on fundamental concepts of non-profit accounting features and transaction recording on financial statements using AR than students in the control group.The research found that when compared to traditional methods learning, augmented reality-based 2D animation be possible significantly raise students higher-degree cognitive abilities, approving them to more effectively accomplishing fundamental concepts in non-profit accounting characteristics and financial statement recording transactions.
A Case Study of English Reading Teaching in Higher Vocational Schools Under the Context of “Internet Plus”

The global pandemic outbreak in the past two years has propelled the fast development of modern education technology, and the deep integration of "Internet Plus" new technology and education industry has brought about innovations and reforms to language teaching and learning.This study, taking the first-year vocational school students as subjects and their English reading teaching and learning as a case, tentatively examined the application of PBL strategy under the internet plus environment to provide practical implications for foreign language teaching.Quantitative and qualitative research methods were adopted to investigate the factors influencing individual exploration and joint interactions in the process of task completion.The results indicated that the PBL-based teaching practice: (1) motivated the participants' autonomous learning with well-designed tasks; (2) improved the participants' language proficiency by exposing them to English environment and supervising their learning process; (3) contributed to the elevation of the participants' communicative competency through collaborative discussions and interactions; (4) enhanced the participants' self-confidence in English learning with online presentations and positive feedbacks from the teacher and their peers.
A Qualitative Study of Classroom Management Efficiency of High School English Class

High school classroom management constitutes a very important part in classroom teaching.It challenges a teacher's management ability, influences his/her teaching quality, and affects the mental and physical development of his/her students.Contemporary studies show that a student-centered model is advocated in classroom management, which aims to stimulate students' subjective initiative, arouse their enthusiasm of study and, promote their overall development.To this end, many researchers put forward strategies to improve the quality of classroom management such as rearranging the layout of the tables and chairs in the classroom, enriching teachers' theoretical knowledge about classroom management, and so on.This paper conducted a qualitative study by interviewing an excellent and experienced high school English teacher.It attempts to discover some valuable strategies of classroom management and thus provide insights for other high school English teachers.
A Study on the Blended Learning Based on Multimedia Platforms

With the increased penetration of mobile devices and the internet across China, the benefits of technology integration in learning have been widely reported.This paper explores the performance of a blended learning model based on multimedia platforms and constructivist theory on College Students' English learning.For this study, 107 students were split into an Experiment Class receiving the blended model of teaching and a Control class which received traditional teaching.The blended model split the teaching process into before class, during class and after class modules, which utilizes multimedia resources and multimedia platforms.The effectiveness of the teaching was analyzed using the results from an English reading attainment test at the start and end of a semester of learning.This study found that the blended learning model based performed better than the traditional learning model, with students showing an average score increase of 2.475 points over the semester compared to 0.208 for students receiving the traditional teaching method.
Enhancing Learning Outcomes of Undergraduates with Cloud-Based Textbook in Higher Education

Learning Outcomes have been attracting more and more attention from higher education.Many scholars have adopted related learning theories and cognitive theories to improve teaching and learning.But few studies on enhancing learning outcomes with textbooks are available so far.Our research aims to discuss improving the learning outcomes of undergraduates with cloud-based textbooks in higher education.We designed a book for the C programming language as an instance of a cloud-based book.The contribution of this research is that we present a novel approach to enhancing students learning outcomes in higher education by integrating the advantages of E-textbooks and the practice of learning theories into a cloud-based textbook.Our research helps teachers to understand the characteristics of cloud-based textbooks.The application encourages instructors to design or use cloud-based textbooks to improve learning outcomes.
Whole Process and Integration Talent Training Mode for Electromechanical Students

In order to improve the quality of talent training for students majoring in mechanical and electrical engineering, whole process and integration talent training mode in mechanical and electrical engineering is proposed.Discuss the main contents of the mode through the establishment of expert steering committee, practical teaching system, practice bases inside and outside the school, collaborative training between schools and enterprises, and double qualified teachers, the school enterprise cooperation forum and innovation and entrepreneurship education.Several years' practices prove that the talent training effect of the mode is remarkable.The employment quality of students has been improved, the team of teachers has been improved, and lots of school enterprise cooperation platforms have been constructed.
Design of Smart Campus Security Management and Control Platform Based on Big Data Technology

As the traditional campus network security defense means fail to cope with the smart campus security threats under the current background of big data, a design scheme of smart campus security management and control platform based on big data technology was proposed.In the scheme, the smart campus system was layered and classified for the design of security protection mechanism and the granular protection management of the smart campus security was realized.Big data technology was used to build a smart security brain, which solved the problem of disorder data and the difficulty in data association and succeeded in data fusion storage on the smart campus.The intelligent operation and management platform provided an all-around awareness of the security situation of the smart campus so that the risk prediction, security warning, security disposal, and intelligent linkage for protection and reinforcement were achieved.The simulated attack test and security risk assessment showed a significant boost in the smart campus security defense capability and an obvious drop in the security risk level after the deployment of the smart campus security platform.Besides, the smart campus security alert and self-disposal ability were also improved dramatically after the practical application analysis.
Data Showcases: the Data Journal in a Multimodal World

&#x0D; As an experiment, the Research Data Journal for the Humanities and Social Sciences (RDJ) has temporarily extended the usual format of the online journal with so-called â€˜showcasesâ€™, separate web pages containing a quick introduction to a dataset, embedded multimedia, interactive components, and facilities to directly preview and explore the dataset described. The aim was to create a coherent hyper document with content communicated via different media (multimodality) and provide space for new forms of scientific publication such as executable papers (e.g. Jupyter notebooks). This paper discusses the objectives, technical implementations, and the need for innovation in data publishing considering the advanced possibilities of today's digital modes of communication. The data showcases experiment proved to be a useful starting point for an exploration of related developments within and outside the humanities and social sciences. It turns out that small-scale experiments are relatively easy to perform thanks to the easy availability of digital technology. However, real innovation in publishing affects organization and infrastructure and requires the joint effort of publishers, editors, data repositories, and authors. It implies a thorough update of the concept of publication and adaptation of the production process. This paper also pays attention to these obstacles to taking new paths.
The Current Situation and Enlightenment of “Simulation Game” Application in Architecture and Planning Education in Europe and America

The article firstly elaborates on the current learning situation of contemporary university students and defines and classifies the concept of simulation games.Then it summarizes the development status of two types of games in university education in Europe and America, analyzes the influence and lessons of simulation games on architecture and planning education, and finally points out the practical problems and future directions that need to be solved in the process of developing gamification education in China.
Research on Hybrid Teaching of Computer Composition Principle Based on Engineering Education Certification

The paper analyzes the current teaching situation of the course "Computer Composition Principles" from the perspective of "student-centered, outputoriented and continuous improvement", and designs the "1-3-2-1" hybrid teaching organization model based on the engineering education accreditation.The organization mode is based on the digital course resources of Super Star MOOC, interactive communication on the online platform, and problem-oriented teaching activities.This model is conducive to cultivating students' independent learning ability, enabling them to deepen their understanding and mastery of the computer composition course, adopting diversified assessment and strengthening process control, so as to improve teaching quality and achieve the course teaching objectives.
The Influences of Embodied Experience on Social Presence of Chinese University Students’ Online Learning

Online courses have brought about the separation of time and space.In previous study, social presence of online learning have been extracted, with the in-depth analysis of learners' participation neglected.This study explored the influences embodied experience on social presence in Chinese university students' online learning, considering how to use embodied experiences to affect communication efficiency.It is practical to connect embodied cognition with telepresence, focus on social presence, and improve learning efficiency with effective embodied experience.In-depth interviews are utilized to find out opinions of every participant, so as to investigate how embodied experience determines communication efficiency through a more focused approach.Finally, the conclusion that embodied experience amplifies social presence was drawn.
DEFINITION OF REASON OF VILLAGE ANAKLIA FLOODING

In the presented article the reason of the village Anaklia territory, the site of the planned construction of a deep-sea commercial port� flooding is discussed. It should be noted that the village mainly is located on the sandy shore of the river mouth of river Enguri. In calm, but rainy weather, precipitation practically freely penetrates through the sandy soil without leaving any water holes and flooded land areas after the rain. However, on March 24-25, 2021, in rainy weather and stormy seas, the village was partially inundated by rainy water, due to which the first floors of residential buildings and hotels were flooded, and significant damage was caused to residents of such places. Therefore, this extraordinary case aroused a certain interest in order to develop a preventive measure to exclude a possible recurrence of the noted phenomenon. In our case during the storm, the top of the wave crest was elevated over the mean sea level to 3.5 meters, caused partial blockage of river Enguri runoff, due to which the water level in the river arose and seeped into the sandy layer to the ground. In article, the quantitative data of the theoretical calculations of the wave parameters that led to the development of this phenomenon are presented.
SPaReL: A Semantic Parsing Relation Linking Method for Knowledge Base Question Answering

Relation linking is an essential module of knowledge base question answering systems. To overcome the ambiguity of natural language and lack of training data, existing relation linking systems employ varieties of heuristics or aggregations of multiple systems. However, the current state-of-the-art methods heavily rely on the surface text and do not achieve optimal results. Since the semantic parsing structure of the question is a rich source of relation information that can strongly promote relation linking performance, we propose a two-stage Semantic Parsing Relation Linking system: SPaReL, which leverages semantic parsing using abstract meaning representation (AMR) to predict relations. The first stage employs a cross-encoder model that concatenates each candidate relation with a question semantic parsing slot to reduce the influence of irrelevant candidate relations on the prediction performance of the relation linking model. The second stage integrates the sentence information and the slot processed by the semantic parser, uses a dual-encoder model to link the remaining high-relevance candidate relations to predict the relation with the highest score. Our system achieves state-of-the-art results on four KBQA datasets, LC-QuAD 1.0, LC-QuAD 2.0, QALD-7 and QALD-9.
μ-Bench: Real-world Micro Benchmarking for SPARQL Query Processing over Knowledge Graphs

Real-world SPARQL querying benchmarks, which make use of the real-world RDF datasets and/or SPARQL queries, are the key element in testing the performance of different RDF Knowledge graph management systems in real-world settings. Over the last years, various real-world SPARQL querying benchmarks have been proposed. Although useful for general purpose SPARQL benchmarking, they do not allow generating microbenchmarks, i.e., small customized benchmarks according to the user specified criteria for a specific use case. These microbenchmarks are important to perform component-based testing, hence pinpoint pros and cons of the systems at micro level. We propose μ-Bench, a microbenchmarking framework for SPARQL query processing over RDF knowledge graphs. The framework makes use of the real-world (collected from query logs of public SPARQL endpoints) SPARQL queries to generate customized benchmarks according to the user defined criteria. The framework utilizes various clustering algorithms to select diverse benchmarks from the given input query log. We generated various microbenchmarks and evaluated state-of-the-art knowledge graph engines. The evaluation results show that specialized microbenchmarking is crucial for identifying the limitations of the various SPARQL query processing engines and other corresponding components.
Knowledge-Enhanced Visual Question Answering with Multi-modal Joint Guidance

Visual Question Answering (VQA) can facilitate social convenience, which needs to study complex joint reasoning in the visual and language over external knowledge. Recently, Knowledge-Based VQA has attracted the attention of researchers. There are many sources of external knowledge, including visual, textual, and commonsense knowledge, which can effectively improve the reasoning ability of the VQA model. However, introducing different knowledge sources increases the probability of retrieving irrelevant facts and generating noise and further impacts the model’s performance. Existing approaches use contrast and prompt learning, visual matrices, density retrieval, etc., to address the noise but bring complex processes. Furthermore, the knowledge representation in these approaches is limited to specific knowledge forms, such as the triple of the knowledge graphs. To address the challenges, we propose a multi-modal joint-guided (MMJG) external knowledge introduction method. The method is to select more relevant external knowledge to the current question through the attention of multi-modal information. Unlike any existing method, our approach learns an adaptive selection module to select external knowledge that is more relevant to the question. Our approach is not specific to a particular knowledge form. The comparison and ablation experiments on the benchmark dataset show that our method achieves better results and demonstrates that our method is more effective.
A Closer Look at Probability Calibration of Knowledge Graph Embedding

When the estimated probabilities do not match the relative frequencies, we say these estimated probabilities are uncalibrated [39], which may cause incorrect decision making, and is particularly undesired in high-stakes tasks [45]. Knowledge Graph embedding models are reported to produce uncalibrated probabilities [36], e.g., for all the triples predicted with probability 0.9, the percentage of them being truly correct triples is not . In this article, we take a closer look at this problem. First, we confirmed the issue that typical KG Embedding models are uncalibrated. Then, we show how off-the-shelf calibration techniques can be used to mitigate this issue, among which binning-based calibration produces more calibrated probabilities. We also investigated the possible reasons for the uncalibrated probabilities and found that the expit transform, the way used to convert embedding scores into probabilities, is ineffective in most cases.
Extracting ISA Relations of Concepts from Books via Weakly Supervised Learning

Relation extraction is an important task in natural language processing. In recent years, researchers have gradually discovered that relation extraction can be used for teaching and learning assessment. Among various dependencies, the ISA is a relation that accounts for a relatively large proportion and is of great significance for many related tasks. However, there is currently little research on the ISA relation extraction between cross-chapter concepts for few-shot in textbooks. In this paper, we propose a distant supervised few-shot relation extraction model based on example construction and self-attention optimization. We use the example construction method in contrastive learning to expand the samples and self-attention mechanism to weight the sentences in the sentence bag to extract the relations of the concepts. Experimental results show that the model we constructed performs better than the previous methods.
Improving Empathetic Dialogue Generation with Semantics Decoupling

Empathetic dialogue generation is dedicated to generating responses to empathize with users by perceiving and understanding context emotions and dialogue situations. Existing works typically emphasize that an empathetic response needs to express suitable emotion through perceiving context emotion but ignore the equal need to express informative content in response by understanding the dialogue situation. To this end, we propose a novel empathetic dialogue generation model abbreviated as EmpDGM, which is extended based on the Transformer by a semantics decoupler and empathetic generator. Specifically, the semantics decoupler can effectively decouple emotion semantics and content semantics in the input sequence using adversarial training and multi-task learning meanwhile ensuring the obtained content semantics is complete. And the empathetic generator introduces a gated fusion mechanism to fuse content semantics and context emotion embedding in a balanced manner throughout the whole generation process, which overcomes generally incorporating context emotion embedding as part of initial embedding in the generation module leading the insufficient emotion expression. We conduct automatic evaluation and manual evaluation on the benchmark dataset EMPATHETICDIALOGUES of empathetic dialogue generation. Experimental results reveal that our EmpDGM outperforms advanced baselines in both emotion perceptivity and content quality and generates more informative and affective responses.
Exploration of Architectural Design in the Co-construction Mode of User and Designer in the Metaverse Environment

After entering the era of metaverse, the breakthrough development of blockchain, high-speed interconnection and VR and other technologies have a certain impact on human production methods and life needs, and also bring a new way of expression and approach to the field of architecture. In this paper, the theory of architectural self-organization is used as the base point to explore the possibility of user-designer co-construction mode in virtual architectural design and construction, mainly analyzing the characteristics of the Internet creation mode and the co-construction system under the architectural self-organization mode, providing inspiration and new ideas for the future design of the metaverse user space immersion experience.
Application of Data Analysis by Python Technology in a Sea Fog Process

Python is characterized by a relatively easy-to-learn syntax, a large number of standard libraries and third-party database support, and good compatibility. It has been applied to theoretical research, practical cases, and also has the advantage of a wide variety of toolsets. Python has penetrated into scientific computing, big data processing, data analysis and other professions and fields. In this paper, we requested and downloaded ERA5 reanalysis data by script, and read ERA5 reanalysis data grid point data by Python Xarray toolkit, processed data time dimension and space dimension to read meteorological data into formatted array, and used Metpy to calculate meteorological equation on data. After that, the meteorological and marine data of a high impact sea fog process from February 9th to 14th, 2020 were analyzed and projected onto the map and plotted by Matplotlib and Cartopy, and the product batch 2D mapping was efficiently parallel optimized to study the formation mechanism of sea fog in Liaodong Bay and improve the forecast and warning level of sea fog.