Reviewerly/exHarmony huggingface dataset:
A Prompt-Based UIE Framework

Information extraction is the automated retrieval of specific information related to a selected topic from a body of unstructured text. Generally, many NLP tasks can be categorized as information extraction tasks, such as named entity extraction (NER), relation extraction (RE), event extraction (EE), etc. To dealing with different IE tasks of different situation, we propose a prompt-based universal information extraction framework which is friendly to both research and industry scenarios.
Research on Data Analysis of English Translation Trends Based on Artificial Intelligence Technology

With the rapid development of mankind and economic society in the world today, global cooperation among countries in the world has continued to deepen, the demand for English translation in human society has increased rapidly, and the advancement of artificial intelligence technology has also been advancing. The quality of English translation has been proposed new requirements. This article aims to study the trend analysis of English translation of artificial intelligence big data. Based on the analysis of the advantages of machine translation and the development trend of translation technology, in order to understand the application of artificial intelligence technology to students, this article uses a questionnaire survey investigate the students in three classes of English majors in a college and make relevant suggestions by analyzing the data obtained. The survey results show that machine translation based on artificial intelligence technology is more favored by students, but the problem of mechanization of machine translation also restricts students’ application.
Key areas for professional development of teaching staff in the field of digital technologies

The fact that the level of digital competencies of teaching staff directly affects the development of the digital economy in Russia makes the research relevant. The requirements (trends) of modern society show the need for training qualified personnel in the field of digital competencies. The article presents an approach to identifying key digital competencies and proposes activities (ideas, forms of training) aimed at their development while training pedagogical personnel in the framework of continuous professional education offered by Krasnoyarsk Regional Institute for Advanced Studies and Professional Retraining of Educators.
Research on Blended Teaching Mode under the Background of "Internet plus": Application based on Chaoxing Learning Pass Platform

Under the background of "Internet plus", the way of information dissemination and resource acquisition has changed greatly. The development of network technology makes it more convenient for students to obtain online learning resources, and the use of computer-assisted teaching can better promote the deep integration of education technology and classroom teaching. Based on the application of Chaoxing Learning Pass Platform and the support of computer technology for education teaching under the background of "Internet plus", this paper explores the construction of blended teaching mode in the context of educational information, which is useful for promoting the deep integration of modern education informationization and traditional classroom teaching and providing useful reference for curriculum reform in higher education.
Exam Marks Summation App Using Tesseract OCR in Python

There are no tools to auto grade subjective questions and no auto summations app to date. As a result, examiners need to mark subjective answer scripts manually and they might overlook some marks while summing up subjective answer scripts scores obtained by students. Therefore, this study aims to develop an exam mark summation app to ease miscalculation problems. Tesseract OCR was implemented in this Marks Summation App as a platform to scan the multi-page handwritten marks using pen tip above a 0.5mm size in red, blue, and black to recognise the marks wrote by the examiners. The captured marks images will be uploaded to server for image processing by promptly executing the python script in the server. The extraction of numbers from the processed image will sum up the scores to determine each candidate's final score. It is recommendable to scan the original materials to produce more accurate accuracy. Out of 118 numbers from 21 testing samples, 88 numbers are correctly recognised, whereas 30 are not recognised correctly. Thus, the accuracy of the developed exam mark summation app is 74.58%. The app's performance is more superior than car plate recognition result in the field. In the future, we hope to increase the app’s recognition accuracy by exploring deep learning in recognizing handwritten numbers.
Survival Probability Assessment using Machine Learning Algorithms

As the largest passenger ship at that time, the sinking of the Titanic was a tragedy, many people died here. Of course, some people escaped successfully. What kind of people are more likely to survive this disaster? In this paper, we aim to predict which characteristic will affect the survive probability. First, we made statistics on the passenger in the accident and analyzed the characteristics of the survivors. The Decision Tree (DT) and K-Nearest Neighbor (KNN) algorithms were used to achieve. At last, the decision tree with cleaning data has higher accuracy, thus characterizing the survivor population. The Decision Tree with data preprocessing achieves the accuracy of 0.81716, which validate the effectiveness of the proposed method.
WORLDSKILLS STANDARDS IN PREPARING BACHELORS OF TEACHER EDUCATION: DEMONSTRATION EXAM AS PART OF THE FINAL CERTIFICATION

Introduction. The paper presents an analysis of the demonstration exam as a practice-oriented means of final control of individual educational results of future primary and basic school teachers. The research substantiates the hypothesis that the demonstration exam meets modern requirements for the forms of final state certification, which is implemented within the competence approach. The focus of the study is on resolving organizational and content-related issues concerned with the introduction of demonstration exam in the state final certification of the educational process of university. Materials and methods. The methods employed in the study are: analysis of normative, scientific, psychological-and-pedagogical methodological literature on the implementation of conditions for the demonstration exam; and a survey of all exam participants. Results of the study. Based on the experience of conducting a demonstration exam for the final-year Bachelor’s degree students, the advantages of this method of assessing the level of competencies gained versus conventional ones are analyzed. Conclusion. The paper has presented the conditions formulated for the introduction of the demonstration exam in the educational process of university.
Research on Hadoop Platform Big Data Software System Based on Forest Random Search Algorithm

With the advent of the Internet age, the generation and collection of Internet data are developing explosively. Using financial institution big data capture software system to process and store relevant data has become a normal choice for many commercial and research institutions. Financial institution big data capture software system can simplify users’ specific operations for information transmission and information calculation, and improve users’ use efficiency and accuracy. In the process of research, this paper uses forest random search algorithm, java graphical interface and Hadoop platform for design and research. After testing, when the server is Intel atomd510, the system optimization module of big data capture software of financial institutions is optimized on Hadoop cluster, and the system task execution time becomes shorter, which is more than 5% shorter than the original data time. The optimization is effective.
Empowering the visually-challenged scholars at Nehru Memorial Museum and Library: A case study

Nehru Memorial Museum and Library (NMML) is the largest repository in the India related to private paper collections of prominent individuals & social and any political organizations actively participated in the struggle for India's freedom. This is an organisation of advanced study in the area of modern and contemporary history. The NMML has one of the largest archives and library in India for documenting information resources relating to the Indian freedom struggle & modern and contemporary Indian history. The NMML has a well equipped centre for visually challenged readers. This centre is being used by the readers effectively. In this paper need of the visually impaired reader has been highlighted. The facilities available in the library have been well described.
EFFICIENCY OF EDUCATIONAL SERVICES IN HIGHER EDUCATION: SCIENTIFIC AND METHODOLOGICAL APPROACHES

The paper discusses key methodological approaches to the formation of conceptual questions in the field of efficiency of educational services in higher education from the standpoint of different stakeholders.
Error Analysis in Using Inflectional Morphemes Students’ Recount Text of English Students

Based on the explanation above, the researcher decides to conduct a research on inflectional morphemes errors in the recount text written by third semester students, this research is expected to identify of errors in using inflectional morphemes. So the researcher comes to the title “Error Analysis in Using Inflectional Morphemes Students’ Recount Text of English Students”. Based on definition above the researcher used a qualitative research because the researcher want to find out the types of errors in using inflectional morpheme in writing recount text of English students. The researcher taken one group of three groups of that English Department with consists of 30 students in a group. The study applied descriptive qualitative settled in collecting the case study that used to gain detail information concerning students’ error on inflectional morpheme in writing recount text. Based on the students writing recount text composition there are 106 errors. Based on the data, the writer classified the errors that occur into some categories as well: Addition, Omission, Misformation, and Misordering. The result of this research indicates that there are a number of errors made by third semester students of UHKBPNP English students in writing recount text using inflectional morpheme. Based on research finding, the researcher was concluded: “There are four types of errors commonly made by the students’ recount text using inflectional morpheme namely error of addition, omission, misformation, and misordering.
Performing a Bake-Off

In this final chapter of the book, we will compare our anomaly detector service to the Azure Cognitive Services Anomaly Detector service. Importantly, the intent of this chapter is not to prove conclusively which is better; it is instead an opportunity to see how two services stack up and see if our service is competitive with a commercially available option. We will begin by laying out the parameters of comparison. Then, we will perform the bake-off, comparing how the two services handle the same datasets. Finally, we will close with a few thoughts on how we can improve our anomaly detection engine.
Utilizing Social Media Retweeting for Improving Event Participant Prediction

Events have become a common way for activity organization in many digital platforms. Event participant prediction is an important problem when planning future events for these platforms. Previous works have found that cold-start recommendation techniques can be used to solve the problem effectively. However, for many starting platforms, training data they own is limited, and may not be sufficient to learn accurate recommendation models. On the other hand, social media retweeting is a kind of event participant data that can be obtained easily. In this paper, we propose to utilize social media retweeting to help improve event participant prediction models. Our approach uses an entity-connect knowledge graph to bridge the social media and the target domain, assuming that event descriptions in the target domain are written in the same language as social media tweets. Experimental evaluation with real-world event participation datasets shows that adding social media retweeting data with our approach does steadily improve prediction accuracy in the target domain.
Introduction

It is crucial to facilitate the rapid development of industries like security surveillance, medical applications, and distance education by fully utilizing and deeply excavating the immense amount of visual signals with advanced image processing technologies. In the past twenty years, significant image processing techniques have aroused a wide range of attention from the relevant researchers in the areas of multimedia signal processing, pattern recognition and intelligent systems, automatic detection technology, and so on. During a series of processes from visual signal acquisition and generation to reception, visual signals will be inevitably affected, leading to a decrease in image quality and further suppressing the accuracy of subsequent object detection and recognition algorithms. Thus, image quality assessment (QA) is commonly regarded as the foundation of image processing techniques. In this chapter, the basic theories of image QA are firstly outlined, from the classification of image QA, namely subjective assessment and objective assessment, to the classification of objective image QA, namely full-reference assessment, reduced-reference assessment, and no-reference assessment in terms of whether undistorted reference images are available or not. Then the research background, characteristics of images, and frontier technologies of various kinds of image QA in hot research fields like screen content images, 3D-synthesized images, sonar images, enhanced images, light-field images, virtual reality images, and super-resolution images are concisely analyzed.
REST with Jakarta EE REST API

The REpresentational State Transfer or REST architecture is a stateless, HTTP-based communication standard for modern applications. Originally proposed by Dr. Roy Fielding in his PhD thesis, it is the de facto means of enabling simple, stateless, predictable, fast, and representation-based communication between applications written in different languages and frameworks. An application written in the Django framework in Python can have REST resources that are consumed by another application written in Java with Jakarta EE. Similarly, a Jakarta EE application can create resources that can be consumed by a C# application.
Improving BERT Pre-training with Hard Negative Pairs

In this paper, we ran various experiments on BERT's pre-training tasks and observed their impact on a language model's success on different downstream tasks such as masked word prediction, sentiment analysis, named entity recognition and text classification. Also, an improvement method called Hard Negative Pairs (HNP) is suggested to increase the success of the Same Sentence Prediction (SSP) task. The goal of HNP is to pick negative pairs that are more similar to the original sentence. After that, two additional improvements for SSP are proposed. One of these methods aims to create shorter sequences while the other one's main goal is selecting a splitting point other than the middle of the sentence. Experiments were performed for these three different suggestions and their different combinations. The results show that the SSP model that uses HNP and smaller sequence generation methods has an improvement over the original SSP. The longest trained model on 1 GB data gets closer results to the BERTurk, even though BERTurk trained with 35 times more data.
Desktop Publishing, Illustration, Painting, and 3D Modeling Software

Imagine the local printshop quotes twice the amount you envisioned spending on the marketing materials you plan to use to announce your grand opening. Having marketing materials such as brochures, business cards, and flyers designed (the expensive part of the process) and printed can cut into the budget. As a business owner, wouldn’t it be nice to have the means to create your own marketing materials without breaking the bank? This chapter looks at a two free desktop publishing solutions that can aid in creating your own marketing materials (such as postcards, brochures, and newsletters). If you don’t need (or want) to go the route of Adobe InDesign, Microsoft Publisher, or QuarkXpress, these solutions can be perfect for small businesses with tight marketing budgets.
Real-time TLD Target Tracking Algorithm Based on Improved Kernel Correlation Filtering for Maritime Targets

Aiming at the problem that the traditional KCF algorithm cannot adapt to the long-term target tracking in a complex offshore environment, TLD is a combination of track detection learning module tracking algorithms, which can carry out long-term target tracking, but its real-time performance needs to be improved. Based on the framework of the TLD target tracking algorithm, the tracking module adopts the improved multi-feature fusion and scale adaptive KCF algorithm, adaptive Kalman filter algorithm is used to predict the target position of the detection module, and the detection area is reduced. The detection speed of the algorithm is improved, and the detection results of occlusion detection and position estimation are used to modify the tracking results. In order to improve the accuracy of the tracker, an improved filtering template updating strategy is proposed. To improve the accuracy of the tracker, a new filtering template updating strategy is proposed. Then the accuracy and success rate of the proposed algorithm are verified on OTB50 dataset. Finally, a practical tracking experiment is carried out. By comparing the improved algorithm with KCF algorithm and DSST algorithm, the effectiveness of the proposed algorithm in complex Marine environment is verified.
Software Defects Prediction Model with Self Improved Optimization

Software systems have significantly grown and increased its complexity to unprecedented levels. Because of these characteristics, preventing software faults is extremely difficult. Therefore, automatic forecasting of errors is required, and it might assist developers deploy with limited resources more efficiently. Different methods on identifying and correcting these flaws at low cost were offered, which, significantly improves the effectiveness of the techniques. This work includes 4 steps to offer a new SDP model. The input data is preprocessed and from that, the “statistical features, raw features, higher order statistical features and proposed MI and entropy features” are extracted. Then, feature selection is done and appropriate features are elected via chi-square scheme. The elected features are detected via LSTM and DBN to predict the defects. The weights of LSTM and DBN are optimized by Opposite Behavior Learning Integrated SDO (OBLI-SDO) algorithm. Finally, examination is done to prove the betterment of OBLI-SDO.
TEKNO YÖNETİM ALT YAPISININ GİZİLGÜCÜ OLAN BULUT BİLİŞİM YÖNETİM SİSTEMİNE DETERMİNİST BİR YAKLAŞIM

The concept of cloud computing refers to a new approach that has begun to be applied to the provision and use of information services. In other words, they are internet-based information services whose resources can be shared between users. Dec. Thanks to this system, it is possible to collect information from different databases into a single base without difficulty. Nowadays, people are quickly keeping up with technology, practicality, speed, etc. as such, he enters into searches. Considering the advantages that this approach can provide to companies and the potential for change that it will bring about, it is thought that it can be an important innovation. Therefore, the article primarily discusses the development of the concept of cloud computing and explains and classifies its current applications, and examples. In addition, the advantages and disadvantages should be taken into account, and how useful it will be in the field of business should be considered. The study conducted a literature review of qualitative research methods and made an overview of the Cloud Computing System, examined the application areas identified by previous studies, and provided information about the current situation.
Person Re-Identification for Suppressing Background Interference

To alleviate the problem of background interference in the person re-identification (Re-ID) field, the paper proposes a novel Re-ID method with background suppression ability. First, it analyzes the implicit relationship between foreground and background in the multi-camera surveillance scene according the experiments. Second, a background suppression network is designed, which is composed of foreground sub network, background sub network and noise suppression module. By the noise suppression loss function, the ability of person feature extraction is enhanced, while the background noise is suppressed. The experimentation results on Market1501 and DukeMTMC-reID datasets show that the proposed method has lower computation complexity, and it boosts the recognition performance and improves the transferable ability.
Modern innovative technologies in education and their application

For a skillful and conscious choice from the existing bank of pedagogical technologies, precisely those that will achieve optimal results in training and education, it is necessary to understand the essential characteristics of the modern interpretation of the concept of “pedagogical technology”.
Satisfaction Rate with Virtual Education Programs during COVID-19 Pandemic and Its Relationship with Their Academic Performance among Nursing Students

Satisfaction Rate with Virtual Education Programs during COVID-19 Pandemic and Its Relationship with Their Academic Performance among Nursing Students
Easing the use of smart contracts through model-based engineering

Despite the interest in blockchain technology and smart contracts, their complexity is a problem that slows down their adoption. Due to its potential, institutions from very diverse fields are exploring the possibilities offered by the application of this technology, encountering a recurring problem: the high learning curve of the design and creation of smart contracts, both for professionals in the areas of business, as well as for developers unfamiliar with this technology. In this work, after analyzing the current situation regarding the existence of tools or solutions for the definition of smart contracts, a proposal is presented based on the application of techniques and principles of Model Driven Engineering, which will ostensibly improve the levels of usability of existing solutions.
A DISCOURSE ANALYSIS OF FIGURATIVE LANGUAGE USED IN THE LECTURE OF USTAD ABDUL SOMAD LC.MA.

The research is aimed to analyze a discourse of figurative languages used in the lecture of Ustad Abdul Somad, LC.MA. (UAS) which is held in Pasaman District, West Sumatera province.The research is qualitatively descriptive approached. In conducting the research, the data are collected by using documentation technique. The data are categorized by referring to Perrine’s category namely personification, metaphor, hyperbole and paradox. The Data are transcript from Indonesian language into English language. To analyze the data, the research uses discourse analysis and descriptive method. The findings of the research are 98 expressions of figurative languages found in the lecture of UAS for 70 minutes namely 34.6 % the expressions of paradox, 25.5% the expressions of hyperbole, 20.4% the expression of metaphor and 19.3 % the expression of personification. These figures are analyzed by using the context of the utterances.