Reviewerly/exHarmony huggingface dataset:
Integration of Achieve 3000 Graded Reading Platform in College English Course Teaching

Reading, as an essential part of English learning, is directly related to the accumulation of vocabulary, construction of grammar framework, and recognition of oral pronunciation for English learners.Therefore, the country attaches great importance to cultivating English reading ability, and English reading scores account for many national large-scale exams.However, due to the varying levels of English teaching in various universities, the English proficiency of college students varies, and traditional English teaching methods are no longer suitable for the current situation.Graded reading has become a significant trend in college English curriculum teaching.The Lexile Framework for Reading is a widely used grading technique in the United States.The Lexile Framework uses numbers and the letter "L" to measure difficulty, with smaller numbers indicating lower reading difficulty and vice versa.This article introduces a reading grading system for teaching college English courses, utilizing the Achieve3000 (after this referred to as A3000) intelligent system based on the Lansi grading reading system.Through personalized reading and writing customization solutions, students' English reading literacy has been effectively improved, especially regarding vocabulary and reading knowledge storage.The teaching quality and level of English courses have also been improved accordingly.
Investigation on Artificial Intelligence Algorithms in Robot Object Recognition Systems under the Background of Big Data

With the development of artificial intelligence algorithms, the application of big data in various fields is becoming increasingly widespread, including computer vision, speech recognition, intelligent robots, etc.However, there are few applications for robot object recognition systems.This article would combine existing artificial intelligence technologies to study object recognition systems, and upgraded the robot object recognition system using convolutional neural network models and error back propagation models, respectively.Through experiments, it was found that convolutional neural networks could shorten the time to 0.8 seconds, while the error back propagation model could improve the recognition accuracy to 95%, with an average accuracy of 91.7%.The results indicated that the convolutional neural network model had a significant effect in shortening recognition time; while the error back propagation model was effective in improving recognition accuracy.
Utilizing Scientific Information Technology to Promote the Modernization of Physical Education in Rural Schools

Scientific information technology provides development space for the development of modern education, but also provides a driving force for the modernization of rural school physical education, but scientific information technology can't be simply imposed on the governance of rural school physical education, logical integration into the practical application of rural school physical education is to become an effective process to drive its operation, development and improvement.This paper adopts the research method of a literature and logical analysis, takes the scientific information technology to empower the modernization development of physical education in rural schools as the background and the integration trend of the modernization development of physical education in rural schools as the basis, and analyzes the integration relationship between scientific information technology and the modernization development of physical education in rural schools.This paper recognizes the problems of the modern development of physical education in rural schools enabled by information technology, and provides corresponding solutions.
Remodeling of Higher Vocational Foreign Language Classroom Discourse Ecology in the Context of Digital Transformation

In the context of digital transformation, the discourse ecology is reshaped through the reorganization and reconstruction of course design, teaching implementation, and evaluation of effects by teachers, to better promote high-quality classroom teaching reform.The paper proposes a construction strategy for the discourse ecology in higher vocational foreign language classrooms and analyzes how to use digital tools to build an efficient, lively, and diverse discourse ecology in the classroom through specific cases.Finally, multiple evaluation indicators for the construction of discourse ecology in the classroom are proposed, aiming to promote the in-depth development of ideological and political education in the curriculum.
The Predicaments and Solutions for K-12 English Teaching Reform under the Core Literacy Concept

This paper aims to investigate the application of the core literacy concept in K-12 English teaching, analyze the predicaments of English teaching reform under the core literacy concept, and propose corresponding solutions.The concept, characteristics, origins, and development of the core literacy concept are introduced.The impact of the core literacy concept on English teaching is analyzed, and the specific practice of the core literacy concept in English teaching is discussed.The predicaments of English teaching reform under the core literacy concept, including student factors, teacher factors, and systemic factors, are analyzed, and corresponding solutions are proposed.The research content and main viewpoints are summarized, and suggestions and prospects for English education are proposed.Through this research, it is hoped to promote the reform and innovation of English education and improve the core literacy level of students.
A Comparative Study of the Syntactic Complexity of English Writing for High School Students

Based on the self-built corpus and LOCNESS corpus, combined with L2 syntactic Complexity measurement index, SPSS, and other software are utilized to explore the commonality and difference in syntactic complexity between English language learners and native speakers with a large-scale corpus of compositions.Concluding the study, English language learners were significantly lower than native speakers in seven of these measures.Although there is not any statistically significant difference in the average length measure of T-unit, there is a large numerical difference.The results have a certain significance for teaching and learning in second language writing.
A Reflection on Teaching Grammar in Korean Language Teaching – From the Teachers’ Perspective

This study aims to examine Korean language teachers’ perceptions of teaching grammar and provide implications for KFL and teacher education. An online questionnaire survey was conducted, and 114 teachers participated in the study. The data were categorized into four areas through factor analysis and analyzed using t-tests, ANOVA tests, and frequency analysis. The study
SOC Software

Chapter 8 discusses the general software architectures for SOC and IOT software example for the design case study. This chapter is also a continuation of IOT solution being discussed in previous two chapters. It introduces software development life cycle (SDLC), different software architecture styles such as layered architecture and event driven software architecture, their selection for the solution and method to define software architecture around the chosen software architecture style is covered in detail. Software modeling by design space analysis for SOCs is also dealt with in this chapter. Approach to develop the IOT SOC software solution, is addressed in this chapter.
An Optical Neural Network Accelerator Based on A Dual Microring Modulator Array

We propose and demonstrate an integrated scalable optical neural network accelerator based on a dual microring modulator array, which can both implement matrix multiplication and convolutional operation and improve the computation density and speed.
Open-TransMind: A New Baseline and Benchmark for 1st Foundation Model Challenge of Intelligent Transportation

With the continuous improvement of computing power and deep learning algorithms in recent years, the foundation model has grown in popularity. Because of its powerful capabilities and excellent performance, this technology is being adopted and applied by an increasing number of industries. In the intelligent transportation industry, artificial intelligence faces the following typical challenges: few shots, poor generalization, and a lack of multi-modal techniques. Foundation model technology can significantly alleviate the aforementioned issues. To address these, we designed the 1st Foundation Model Challenge, with the goal of increasing the popularity of foundation model technology in traffic scenarios and promoting the rapid development of the intelligent transportation industry. The challenge is divided into two tracks: all-in-one and cross-modal image retrieval. Furthermore, we provide a new baseline and benchmark for the two tracks, called Open-TransMind. According to our knowledge, Open-TransMind is the first open-source transportation foundation model with multitask and multi-modal capabilities. Simultaneously, Open-TransMind can achieve state-of-the-art performance on detection, classification, and segmentation datasets of traffic scenarios. Our source code is available at https://github.com/Traffic-X/Open-TransMind.
SSGVS: Semantic Scene Graph-to-Video Synthesis

As a natural extension of the image synthesis task, video synthesis has attracted a lot of interest recently. Many image synthesis works utilize class labels or text as guidance. However, neither labels nor text can provide explicit temporal guidance, such as when an action starts or ends. To overcome this limitation, we introduce semantic video scene graphs as input for video synthesis, as they represent the spatial and temporal relationships between objects in the scene. Since video scene graphs are usually temporally discrete annotations, we propose a video scene graph (VSG) encoder that not only encodes the existing video scene graphs but also predicts the graph representations for unlabeled frames. The VSG encoder is pre-trained with different contrastive multi-modal losses. A semantic scene graph-to-video synthesis framework (SSGVS), based on the pre-trained VSG encoder, VQ-VAE, and auto-regressive Transformer, is proposed to synthesize a video given an initial scene image and a non-fixed number of semantic scene graphs. We evaluate SSGVS and other state-of-the-art video synthesis models on the Action Genome dataset and demonstrate the positive significance of video scene graphs in video synthesis. The source code is available at https://github.com/yrcong/SSGVS.
What Makes a Good Data Augmentation for Few-Shot Unsupervised Image Anomaly Detection?

Data augmentation is a promising technique for unsupervised anomaly detection in industrial applications, where the availability of positive samples is often limited due to factors such as commercial competition and sample collection difficulties. In this paper, how to effectively select and apply data augmentation methods for unsupervised anomaly detection is studied. The impact of various data augmentation methods on different anomaly detection algorithms is systematically investigated through experiments. The experimental results show that the performance of different industrial image anomaly detection (termed as IAD) algorithms is not significantly affected by the specific data augmentation method employed and that combining multiple data augmentation methods does not necessarily yield further improvements in the accuracy of anomaly detection, although it can achieve excellent results on specific methods. These findings provide useful guidance on selecting appropriate data augmentation methods for different requirements in IAD.
Ontological Method for the Modeling and Management of Building Component Construction Process Information

Knowledge of the construction process plays a decisive role in guiding construction and thus affects the quality of buildings. However, the integration and relevance of information in the traditional process file are poor, and it is easy to ignore the process changes caused by the differences when applying information directly. Therefore, this paper introduces an ontological method for the information modeling and management of the construction process. The proposed method uses machine readable language to integrate process knowledge in a structured way, thereby improving the relevance of information and promoting the reuse, sharing and retrieval of knowledge. At the same time, the semantic web rule language (SWRL) rules are used to model the relevant laws and regulations with reference to the construction product quality acceptance regulations and to correlate the construction process information so as to ensure the compliance of building products and the accuracy of process information. Finally, the feasibility of the method is verified via specific use cases on an ontology implementation platform.
Adversarial Coreset Selection for Efficient Robust Training

Abstract It has been shown that neural networks are vulnerable to adversarial attacks: adding well-crafted, imperceptible perturbations to their input can modify their output. Adversarial training is one of the most effective approaches to training robust models against such attacks. Unfortunately, this method is much slower than vanilla training of neural networks since it needs to construct adversarial examples for the entire training data at every iteration. By leveraging the theory of coreset selection, we show how selecting a small subset of training data provides a principled approach to reducing the time complexity of robust training. To this end, we first provide convergence guarantees for adversarial coreset selection. In particular, we show that the convergence bound is directly related to how well our coresets can approximate the gradient computed over the entire training data. Motivated by our theoretical analysis, we propose using this gradient approximation error as our adversarial coreset selection objective to reduce the training set size effectively. Once built, we run adversarial training over this subset of the training data. Unlike existing methods, our approach can be adapted to a wide variety of training objectives, including TRADES, $$\ell _p$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>ℓ</mml:mi> <mml:mi>p</mml:mi> </mml:msub> </mml:math> -PGD, and Perceptual Adversarial Training. We conduct extensive experiments to demonstrate that our approach speeds up adversarial training by 2–3 times while experiencing a slight degradation in the clean and robust accuracy.
INSLISLITE EVALUATION IN THE PROCESSING OF LIBRARY MATERIALS TOWARD USABILITY MODEL

An information system can ease the user in receiving information. The library needs to use effective and efficient service by using the information system. Processing of library materials is important to do to facilitate the search for information and expedite service activities. This research has a case study at the Bandar Lampung City Library and Archives Service which has used the INLISLite system since 2014. But until now they are still using INLISLite version 3.1. This study uses a qualitative descriptive method by conducting field research on the problems that occur, as well as interacting directly with librarians. INLISLite version 3.1 which is used displays several menus such as Back Office, Read on Place, Guest Book, Online Membership, Digital Collection Services, OPAC, Articles, Member Registration, Statistics, Surveys, Self-Returns, and Self Borrowing. The results first result from the study, librarians can process library materials on the Back Office menu. The second is there are no problems in the learnability and efficiency aspects because in this aspect the INLISLite system makes it very easy for librarians, but there are problems in the Memorability, Error, and Satisfaction aspects.
The review of scientific research conducted by libraries: What comes next?

The author reviews the two editions (2021, 2023) of the multi-authored monograph “Scientific research in libraries: Subject scope, organization, presentation of findings” [in Russian]. The monograph is prepared by three national libraries – the Russian State Library, the National Library of Russia and the Presidential Library named after B. N. Yeltsin. The first edition has already won a high a ppraisal in the professional scientific media. The author of the review shares the assessment, moreover, he emphasizes that the monograph testifies to the ability of the national libraries to collaborate without duplication, each relying on its background and historical traditions. At the same time, scientific gaps have now become more visible. It is important to involve scientific research conducted by other federal libraries, regardless their departmental subordination, as well as by the higher educational institutions training library professionals. The author points out the absence of the unified scientific policy of research studies, equally important for the library science, bibliography and book science, and the entire branch of book and library science. In particular, it is vitally important to define the relations between the concepts of “library science” and “general library science”; to articulate the concepts of “private library science”, “special library science”, and “electronic library science”; to identify the place of library science, bibliography and book studies in the system of sciences and thus to contribute to the state recognition of the value of our scientific disciplines; to bring the national standards in the field of library activity in line with the Federal Law “On Librarianship”; to specify the actual purpose of library work, to elaborate the criteria for library document value; to develop the theory and methodology for identifying information needs, etc. The publication of the monograph is an extraordinary event in our scientific community that expects such comprehensive publications for the future.
Research on Multi-Target Path Planning for UUV Based on Estimated Path Cost

The precision and efficiency of multi-target path planning are crucial factors influencing the performance of anti-mine operations using unmanned underwater vehicles (UUVs). Addressing the inadequacies in computation time and solution quality present in existing path planning algorithms, this study proposes a novel path cost estimation strategy based on neural networks. This strategy swiftly generates an accurate cost matrix, ensuring the attainment of high-quality traversal orders when utilized as input for the traveling salesman problem, thereby yielding a globally optimal path. Simulation experiments demonstrate that while maintaining high-quality solutions, the proposed strategy significantly enhances the computational efficiency of the algorithm. Furthermore, the practical application and effectiveness of the proposed algorithm have been demonstrated through an actual UUV prototype experiment in a lake environment.
Analysis of Jordanian Commercial Banks' Business Intelligence Systems and Their Emphasis on Entrepreneurship

The study aimed at identifying the reality use of business intelligence (BI) systems and to test their impact on entrepreneurial orientations of Jordanian commercial banks.The Study population consists of ( 13) Jordanian commercial banks in Amman, a Purposeful sample of (120) manager was taken which included (administrations managers, branches managers, departments managers).The number of questionnaires retrieved and valid for analysis were ( 102) at a rate of (85%) of distributed questionnaire.The researchers found that there is a statistically significant effect at the level (α ≤0.05) for the use of business intelligence systems (data collection and analysis, business performance management, competitive intelligence, adequacy of strategic techniques) in achieving entrepreneurial orientations of Jordanian commercial banks.So overall business intelligence systems dimensions (data collection and analysis, business performance management, competitive intelligence, adequacy of strategic techniques) have the ability to achieve entrepreneurial orientations of Jordanian commercial banks).
Factors influencing academic staff attitudes towards smart boards use in education process in Applied Science University in Jordan

This research aims to study Factors Influencing Academic Staff Attitudes Towards Smart Boards Use in Education Process in Applied Science University.Additionally, it seeks to examine the moderating role of the type of school.The research's independent variables consist of Factors (interaction, self-efficiency, course design, technical support, convenience and accessibility), while the dependent variable is Attitudes towards smart board.A quantitative method used The primary data was collected through academic staff university email and through whatsapp.A sample of (N=27) respondents, who are academic staff in Applied Science University.The result of this research confirms showed that there is a significant positive impact of the smart board on the attitudes of faculty members through positive interaction between them and students and educational materials.The result of interviews this research confirms that the smart board supports the process of interaction between the lecturer and the students in one hand, and on the other hand, it supports the process of interaction between students and educational materials.
Kirik the Novgorodian and Cosmological Riddles in Old Rus

The text of the “Teaching on Numbers” by the monk and mathematician Kirik the Novgorodian (the first half of the 12th century) was introduced into scientific circulation in the 1820s. Initially, this text was assessed as exclusively mathematical-calendar content. As the research unfolded, questions of a textual, historical-mathematical, philosophical, cultural and socio-psychological nature arose. Compared with similar writings of Kirik’s era, his calculations are recognized as accurate, and in methods of calculation on the abacus, he was 400 years ahead of his time. In addition to the “Teaching on Numbers”, the theological treatise penned by Kirik, “The Questions of Kirik”, has come down to our times, written in the form of a dialogue between a pastor and a bishop about the vital problems of service practice. Despite numerous articles and solid monographs on Kirik’s legacy, some postulates of the “Teaching”, as well as vocabulary features, remain undisclosed and mysterious. The first riddle concerns the scientific research and peculiarities of the reconstruction of the lists of Kirik’s treatises, which have come down to us only from the 16th century. A mere mystery concerns the fragment about circuits in the renewal of the elements, which, at first glance, has a natural philosophical content. The question arises: could Kirik, as a thoughtful scientist, simply rewrite these calculations from the prototype text familiar to him, the so-called “seven-thousanders”? Hypotheses are put forward of Platonic, Pythagorean, Gnostic influences on the essence of the fragment, but no supporting texts have been found. The article presents arguments in favor of the hypothesis of the influence of the mathematical teachings of the Pythagoreans on the prototype of the fragment about the renewal of the elements. The Pythagorean thesis about the structure of the corporeal cosmos according to the laws of beauty and harmony, which are based on the principle of commensurability, is clearly reflected in the mathematical calculations of the fragment. Kirik addressed his “Teaching” to lovers of numbers and he himself belonged to the circle of intellectuals. Modern studies of the Pythagorean tradition confirm the intercultural nature of the influence of the Pythagorean tradition on other ideological directions of thought. In Old Rus the tradition was supported by chroniclers and chronologists.