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Design and Implementation of Course Articulation Information System 1

5th International Conference on Innovative Computing, IC 2022

作者： Dai, Yanmei Xie, Yongsheng Fang, Jiajue Li, Shuwu Office of Academic Affairs Guangxi Science and Technology Normal University Guangxi Laibin545004 China Faculty of Mathematics and Computer Science Guangxi Science and Technology Normal University Guangxi Laibin545004 China Department of Teaching Quality Control and Evaluation Guangxi Science and Technology Normal University Guangxi Laibin545004 China

ISBN: (数字)9789811941320

ISBN: (纸本)9789811941313

The course articulation information system construction is required by the educational modernization and high-quality education. Given this, such a system was designed by following the principle of the main leader in charge, the people-oriented principle, the principle of authority consistency, the systematic and dynamic principle, the stability principle, and the principle of easy development and maintenance. Lenovo R4900d was selected as the physical platform, J2EE as the integrated development environment and NetBeans 8.0 as the development tool to develop and apply the course articulation information system. Next, the talent training programs, curriculum syllabuses and teaching plans of secondary vocational schools and undergraduate colleges were shared, inquired and analyzed, in an effort to solve the articulation information asymmetry between secondary vocational education and undergraduate education, provide information reference for teachers to improve their teaching and enhance the educational quality. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Curricula

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Hardware Data Prefetch for XiangShan Processor 7

Hardware Data Prefetch for XiangShan Processor

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7th International Conference on Integrated Circuits and Microsystems, ICICM 2022

作者： Zhu, Yuhan Zheng, Jiachun Ding, Shuyan Li, Lunbo Nanjing University of Science and Technology College of Computer Science and Engineering Nanjing China Beijing Institute of Open Source Chip Technical Research & Development Department Beijing China Nanjing University of Science and Technology Electric and Electronic Teaching and Experiment Center School of Electronic and Optical Nanjing China

ISBN: (纸本)9781665460439

XiangShan, a rising star of RISC-V-based processors proposed by Chinese Academy of science, is famous for its high performance and agile methodology. At present, the second-generation Yanqi Lake architecture of XiangShan has already reached the frequency of 2GHz at the 14nm process node, which ranks the first in the field of open-source RISC-V-based processors. One of the key approaches that contribute to its high performance is prefetch. A timely and accurate prefetcher can effectively eliminate cache misses and thus hide memory access latency. Aiming at the specific environment of XiangShan, out-of-order and parallel, a stride-based prefetcher for the L1DCache is achieved on the Yanqi Lake structure of XiangShan. Serious benchmarks from SPEC2006 were run on XiangShan, the result of which demonstrates that our prefetcher improves the performance of XiangShan by an average of 2.5% and up to 13.3%. © 2022 IEEE.

关键词： Lakes

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System Methodology of Data Analysis and Preprocessing for Solving Classification Problems

System Methodology of Data Analysis and Preprocessing for So...

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International computer sciences and Information Technologies (CSIT)

作者： Irina Kalinina Aleksandr Gozhyj Victoria Vysotska Eugene Malakhov Victor Gozhyj Iryna Tregubova Intelligent Information Systems Department Petro Mohyla Black Sea National University Mykolayiv Ukraine Department of Information Systems and Networks Institute of Computer Science and Information Technologies National University “Lviv Polytechnic” Lviv Ukraine Department of Mathematical Methods of Computer Systems of Odessa National Mechnikov University Odesa Ukraine Department of Computer Science State University of Intelligent Technologies and Telecommunications Odesa Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

The article describes and investigates the systematic methodology of data analysis and preprocessing for solving classification problems. The methodology combines the following groups of methods on the basis of a systemic approach: methods of processing data gaps, methods of processing anomalous values, methods of feature generation, methods of identifying nonlinearities and non-stationarity, and normalization methods. methods of character generation were studied. methods of feature selection and generation are divided into three main groups: filtering methods, wrapping methods, and embedded methods. Since feature selection plays a crucial role in machine learning, increasing model performance and reducing computational costs, the paper proposes a combined feature selection method that includes the step-by-step use of both filtering and wrapping methods. The method consists of five steps to efficiently select the most relevant features of a data set. It offers a better approach to feature selection. This results in improved model performance with fewer features and reduced computational cost. The creation of a red wine classification system was considered for the experimental verification of the system methodology of analysis and pre-processing of data. The Red Wine Quality dataset was used. The purpose of the classification is to identify factors associated with the risk of untimely delivery of previous orders to customers and information about recipients of goods. To solve the task of wine quality classification, simulations were carried out using various algorithms. The effectiveness of the system approach to solving problems of analysis and preprocessing of data to solve problems of classification was proved.

关键词： Data analysis Systematics Filtering Computational modeling Machine learning Feature extraction Computational efficiency Classification algorithms Wrapping Information technology

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The Development and Testing of a Model for Converting American Sign Language (ASL) Sentences Using Natural Language Processing Techniques

The Development and Testing of a Model for Converting Americ...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Alongkorn Kaewprom Aritat Suriyapattanapong Smith Sanmano Pokpong Songmuang Sivakorn Malakul Suksanareewittaya School Bangkok Thailand Streesmutprakan School Bangkok Thailand Chitrala School Bangkok Thailand Department of Computer Science Thammasat University Thailand The Institute for the Promotion of Teaching Science and Technology Bangkok Thailand

ISBN: (数字)9798350370096

ISBN: (纸本)9798350370102

This research addresses the global prevalence of people with hearing disabilities, recognizing the increasing numbers within this demographic. The communication challenges encountered by these individuals drive the development and evaluation of a language translation model. The primary goal is to design a model specifically tailored for translating sign language sentences into English, considering the unique word order in sign language. The study involves comparing eight models that utilize various techniques. Evaluation will be conducted through the bleu score, with 100 randomly selected sentences in each of the 10 rounds. Consistent inputs will be used across rounds to calculate the bleu score, offering a comprehensive assessment of model performance.

关键词： Measurement Sign language Technological innovation Social networking (online) Sociology Euclidean distance Natural language processing

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Designing a Model for Predicting Asthma in Adolescent Using Map Reduce and Federated Learning

Designing a Model for Predicting Asthma in Adolescent Using ...

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science, Engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Raphael Henshaw Ekpo Victor Chukwudi Osamor Ambrose A. Azeta Kayode Akindeji Adeyinka Elizabeth Orelaja Department of Computer and Information Sciences Covenant University Ota Ogun State Nigeria Department of Software Engineering Namibia University of Science and Technology Windhoek Namibia Department of Electrical Power Engineering Faculty of Engineering and The Built Environment Durban University of Technology South Africa Department of Computer Science and Quantitative Methods Clarksville Tennesse U.S.A

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

This study aims at designing Map Reduce and federated learning-based asthma prediction model for adolescent to provide answers to the problems associated with the existing asthma prediction model for adolescent. This study leveraged on two diverse datasets: the Nigerian Hospital Asthma dataset and the National Survey of Children Health dataset for benchmarking purposes. Symmetrical uncertainty and normalization interaction were employed for feature selection. The model was trained using Federated Artificial Intelligence (AI) Technology Enabler (FATE) and complemented with XGBoost model and one central server for federated algorithm averaging. The study was implemented with python programming language on Google Collaboratory environment. The results of the analysis showed considerable high accuracy of 0.98, precision (0.98%), recall (0.98%) and F1-socre (0.99%) for the asthmatic class and precision of 0.98%, recall of 0.98%, as well as F1-score of 0.99% for the non-asthmatic class. The implemented model was benchmark with the existing asthma prediction models in the literature. Simulated attack was also performed using implemented model with and without Map Reduce. This study concludes that the researchers’ model has the potentials to outperform some of the existing machine learning models on asthma prediction in adolescent, thereby facilitating collaborative sharing of the model with other hospitals, protect the patient information from leakage, meeting the criteria of healthcare data protection regulation as well as beneficial for enhancing the security of the dataset.

关键词： Surveys Pediatrics Hospitals Computational modeling Predictive models Benchmark testing Data models

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Investigating Preservice Secondary Teachers’ Understanding and Enactment of the Standards-Based Practices During Microteaching

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Journal for STEM Education Research 2024年第1期7卷 63-95页

作者： Menon, Deepika Cheng, Diana S. Ngugi, Rosetta W. Teaching Learning and Teacher Education Center for Science Mathematics and Computer Education University of Nebraska-Lincoln 840 N 14th Street Lincoln 68588-0233 NE United States Department of Mathematics Towson University 7800 York Road Towson 21252 MD United States Department of Physics Kennesaw State University 1000 Chastain Road Kennesaw 30144 GA United States

Reform efforts in K-12 science education have been gaining pace ever since the introduction of the Next Generation science Standards (NGSS). The new vision calls for reconsidering teacher preparation programs to prepare future teachers who are confident and competent in delivering NGSS-based instruction. This study investigated the development of 27 preservice secondary science and mathematics teachers’ (PSTs’) knowledge and skills as they understand, interpret, and implement the NGSS, particularly science and engineering practices (SEPs), within the context of microteaching during a STEM methods course. Primary data sources include 12 videos of 40-min-long microteaching lessons, self-reflections, semi-structured and focus-group interviews, and artifacts such as student-designed science lesson plans. This qualitative study utilizes deductive-inductive and thematic analysis approaches to analyze PSTs microteaching videos to understand how various SEPs were enacted and integrated within the science lessons. While the average duration of the occurrence of each SEP varied, SEP 1 (Asking questions) showed the least occurrence compared to other SEPs across lessons. Most PSTs reported a better understanding of the NGSS framework at the end of the semester and found it a useful tool for planning a science lesson. Implications for preservice secondary STEM teacher education programs are discussed. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Microteaching Next Generation science Standards Preservice teacher education science and engineering practices Secondary STEM teachers

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Economic and Mathematical Model of a Group of Gas Fields 14

Economic and Mathematical Model of a Group of Gas Fields

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14th International Conference Management of Large-Scale System Development, MLSD 2021

作者： Solomatin, A.N. Federal Research Center 'Computer Science and Control Russian Academy of Sciences Department of Mathematical Methods of Regional Programming Moscow Russia

ISBN: (纸本)9781665412308

Economic and mathematical model of a group of gas fields is considered allowing forming the group development strategies for the long-term perspective. An algorithm for calculating the dynamics of gas production by fields and methods for calculating numerous technical and economic indicators of gas production and transport are presented. In addition, information is provided about the software implementation and use of the developed mathematical apparatus. © 2021 IEEE.

关键词： Gas industry

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Are Existing Out-Of-Distribution Techniques Suitable for Network Intrusion Detection?

arXiv

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arXiv 2023年

作者： Corsini, Andrea Yang, Shanchieh Jay Department of Science and Methods for Engineering University of Modena and Reggio Emilia Modena Italy Department of Computer Engineering Rochester Institute of Technology Rochester United States

Machine learning (ML) has become increasingly popular in network intrusion detection. However, ML-based solutions always respond regardless of whether the input data reflects known patterns, a common issue across safety-critical applications. While several proposals exist for detecting Out-Of-Distribution (OOD) in other fields, it remains unclear whether these approaches can effectively identify new forms of intrusions for network security. New attacks, not necessarily affecting overall distributions, are not guaranteed to be clearly OOD as instead, images depicting new classes are in computer vision. In this work, we investigate whether existing OOD detectors from other fields allow the identification of unknown malicious traffic. We also explore whether more discriminative and semantically richer embedding spaces within models, such as those created with contrastive learning and multi-class tasks, benefit detection. Our investigation covers a set of six OOD techniques that employ different detection strategies. These techniques are applied to models trained in various ways and subsequently exposed to unknown malicious traffic from the same and different datasets (network environments). Our findings suggest that existing detectors can identify a consistent portion of new malicious traffic, and that improved embedding spaces enhance detection. We also demonstrate that simple combinations of certain detectors can identify almost 100% of malicious traffic in our tested scenarios. © 2023, CC BY.

关键词： Embeddings

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Economic analysis of one type of criminal activity 14

Economic analysis of one type of criminal activity

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14th International Conference Management of Large-Scale System Development, MLSD 2021

作者： Troyanovskiy, V.M. Federal Research Center 'Computer Science and Control' Russian Academy of Sciences Department of Mathematical Methods of Regional Programming Moscow Russia

ISBN: (纸本)9781665412308

This paper provides a formal analysis of the regularities of functioning and development of economic crimes. It was expedient to find out the conditions in which theft would not be worthwhile, i.e., supplement legal research with the economic analysis. The analysis results will help to find ways of rational crime counteraction and minimize the damage from it. © 2021 IEEE.

关键词： Economic analysis

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A framework for inclusive AI learning design for diverse learners

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computers and Education: Artificial Intelligence 2024年 6卷

作者： Song, Yukyeong Weisberg, Lauren R. Zhang, Shan Tian, Xiaoyi Boyer, Kristy Elizabeth Israel, Maya School of Teaching & Learning College of Education University of Florida GainesvilleFL32611 United States Department of Computer and Information Science and Engineering University of Florida GainesvilleFL32611 United States

As artificial intelligence (AI) becomes more prominent in children's lives, an increasing number of researchers and practitioners underscored the importance of integrating AI as learning content in K-12. Despite the recent efforts in developing AI curricula and guiding frameworks in AI education, the educational opportunities often do not provide equally engaging and inclusive learning experiences for all learners. To promote equality and equity in society and increase competitiveness in the AI workforce, it is essential to broaden participation in AI education. However, the framework that guides teachers and learning designers into inclusive learning design tailored for AI education is lacking. Universal Design for Learning (UDL) provides guidelines for making learning more inclusive across disciplines. Based on the principles of UDL, this paper proposes a framework to guide the design of inclusive AI learning. We conducted a systematic literature review to identify AI learning design-related articles and synthesized them into our proposed framework. Our new framework includes the core component of AI learning content (i.e., five big ideas), anchored by the three UDL principles (the "why," "what," and "how" of learning), and six praxes with pedagogical examples of AI education. Alongside this, we present an illustrative example of the application of our proposed framework in the context of a middle school AI summer camp. We hope this paper will guide researchers and practitioners in designing more inclusive AI learning experiences. © 2024 The Author(s)

关键词： Curricula

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