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19th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2023

作者： Liu, Chunhui Bai, Yanhui Wu, Jing Chifeng University School of Educational Science Chifeng024001 China Chifeng University School of Mathematics and Computer Science Chifeng024001 China Mathematics Teaching and Research Group No.4 Middle School of Chifeng Chifeng024001 China

ISBN: (纸本)9798350304398

In this paper, sublattices problem of lattices is studied by using the method and principle of hesitant fuzzy sets. The concept of hesitant fuzzy sublattices of lattices is introduced and its properties are investigated. The relationship between hesitant fuzzy sublattices and sublattices is given. It is proved that hesitant fuzzy intersection and direct product of some hesitant fuzzy sublattices, homomorphism image and inverse image of a hesitant fuzzy sublattice are also hesitant fuzzy sublattice. At the same time, a condition which makes hesitant fuzzy union of some hesitant fuzzy sublattices to be a hesitant fuzzy sublattice is obtained. © 2023 IEEE.

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The Main Factors of Enem: A Literature and Microdata Perspective

The Main Factors of Enem: A Literature and Microdata Perspec...

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Frontiers in Education (FIE) Conference

作者： Jacinto José Franco Fernanda Luzia de A. Miranda Jacques Duilio Brancher Lirian Keli dos Santos Computer Science IFMT Barra do Garças MT Brazil Teaching IFMT Barra do Garças MT Brazil Computer Science Londrina State University Londrina Brazil

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This is a Research Full Paper. Enem is a test applied annually since 1998 in Brazil with the purpose of evaluating high school students. The data from the tests are made available in Comma-separated values (CSV) files by Inep, enabling analysis to be carried out on more than 102 million records, combining factors and levels with a wealth of detail from a social and educational point of view. This is one of the most consistent databases in the world and yet there is no article that aims to establish, from the literature, the most frequent factors, relating the factors evidenced with data mining to interactions. From this discovery, it was possible to create unique visualizations of the last 25 years, exploring interactions between factors and levels, which enabled the discovery of new knowledge. To guide this study, a bibliographic search was carried out of all the articles returned in the Google Scholar search, making it possible to identify the most referenced factors. With this information, data was pre-processed using the Pareto principle (80/20), calculating averages and establishing grade levels and income levels in order to normalize the data, since the tests have varied in difficulty over the years and there have been significant changes in the economy since the first version of the exam. As for student performance, the financial investments made at primary and secondary level are enough to provide an indication to establish assumptions and, for this reason, family income is strongly related to educational opportunities and all the main factors. The best primary and secondary education institutions are federal and private schools. Skin color exerts some influence, but does not interfere significantly when one has advantageous financial conditions. The results highlight the importance of thinking about Brazil's poorest population, because as well as being socially vulnerable and disadvantaged, their performance is below what can be achieved.

关键词： Machine learning algorithms Image color analysis Reviews Databases Education Color Position measurement Skin Internet Investment

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Gamified Networked Learning Environments in Higher Education: A Study on Student Engagement and Value Creation in computer science 18

Gamified Networked Learning Environments in Higher Education...

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18th European Conference on Games Based Learning, ECGBL 2024

作者： Soleymani, Ali Aerts, Taico De Laat, Maarten Specht, Marcus Centre for Education and Learning EWI TU Delft Delft Netherlands Computer Science and Engineering Teaching Team EWI TU Delft Delft Netherlands Centre for Change and Complexity in Learning University of South Australia Adelaide Australia

ISBN: (纸本)9781917204194

In the rapidly evolving domain of computer science education, fostering deep engagement and sustained motivation among students remains a challenge. This study introduces the Answers platform, a pioneering online learning environment developed at TU Delft. This research aims to reimagine the learning experience for Bachelor and Master of science Students in computer science by integrating gamification elements grounded in Wenger's value creation framework. Our paper explores two critical research questions: the perception of learners towards gamified learning experiences and the impact of the Answers' system on value creation and motivation. We incorporated points, badges, and leaderboards in a semester-long intervention to enrich the learning landscape. The Value Creation Questionnaire (VCQ) results indicated that the platform effectively created potential and applied value, significantly enhancing students' learning practices and motivation. However, its impact on fostering social connections could have been more pronounced. The platform also moderately influenced students' ability to impact their world and shift perspectives. The Intrinsic Motivation Inventory (IMI) revealed that students generally enjoyed using the platform but felt it did not significantly enhance feelings of connectedness. This paper contributes to the body of knowledge by demonstrating the efficacy of gamification in computer science education and offering insights into the design of engaging online learning platforms. By bridging theoretical frameworks with practical application, the Answers platform exemplifies the potential of gamified environments to revolutionize educational practices in the digital age. © 2024 Dechema e.V.. All rights reserved.

关键词： Students

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Adaptive Density Peak Algorithm Based on K-nearest Neighbors with Pre-screening Strategy 6th

Adaptive Density Peak Algorithm Based on K-nearest Neighbors...

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6th Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2019

作者： Zhao, Long Liang, Yong-quan Fan, Jian-cong College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China Provincial Key Lab for Information Technology of Wisdom Mining of Shandong Province Shandong University of Science and Technology Qingdao China Provincial Experimental Teaching Demonstration Center of Computer Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9789811650352

Clustering by fast search and find of density peaks (DPC) is a new kind of clustering algorithm based on density and distance, which can obtain arbitrary shape of the clusters efficiently. It chooses the cluster centers based on the high value of density and distance. However, in the process of calculating density and distance, the wrong selection of cutoff distance will lead to the clustering performance because initial cluster centers are not selected correctly. In addition, the allocation strategy of one-step is not robust and easy to cause subsequent assignment errors. To overcome these defects, the density peak algorithm based on K-nearest neighbors with pre-screening strategy (PADPC) is proposed in this paper which can effectively increase the robustness of the original algorithm and achieve better experimental results. Experiments on classic datasets show the proposed clustering algorithm outperforms other competitive clustering algorithm greatly. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Clustering algorithms

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Chinese Text Emotional Analysis Based on Bi-LSTM Model Fusing Emotional Features 6th

Chinese Text Emotional Analysis Based on Bi-LSTM Model Fusin...

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6th Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2019

作者： Li, Hao Fan, Jian-cong College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China Provincial Key Lab for Information Technology of Wisdom Mining of Shandong Province Shandong University of Science and Technology Qingdao China Provincial Experimental Teaching Demonstration Center of Computer Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9789811650352

With the development of neural network, the method based on neural network is widely used in affective analysis. This model can get better results than the traditional machine-based learning method. However, it ignores a large number of existing emotional knowledge, such as emotional lexicon. In order to solve the problem, this paper proposes a features construction method based on emotional lexicon, and incorporates features into Bi-LSTM. The experimental results show that the improved Bi-LSTM can obtain higher F1 score. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

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Covid severity prediction: Who cares about the data quality?

Covid severity prediction: Who cares about the data quality?

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2022 International Conference on Frontiers of Information Technology, FIT 2022

作者： Nae, Teodora Krabbe, Johannes Bukhsh, Faiza Allah Jayasinghe Arachchige, Jeewanie Ahmed, Faizan University of Twente Faculty of Electrical Engineering Mathematics and Computer Science Enschede Netherlands Medische Spectrum Twente Enschede Netherlands University of Ruhuna Department of Computer Science Matara Sri Lanka University of Twente Formal Methods and Tools Group Enschede Netherlands

ISBN: (纸本)9798350345933

COVID-19 is an ongoing pandemic disrupting daily life and overwhelming the healthcare infrastructure. Since the outburst of the pandemic, researchers have used various techniques to predict many aspects of the disease, including mortality rate and severity. The reproducibility of this research is challenging due to varying methodologies used to collect data, data quality, vague description of methodological approach to training prediction models, over-relying on data imputation, and over-fitting. This paper focuses on these challenges and provides a short yet comprehensive review of research on COVID mortality and severity prediction. The emphasis is on the reproducibility of the results and data quality issues. To further elaborate on the issue, we report the development of severity prediction models using two data sets. CRISP-DM is used as a methodological approach. We analyze and criticize the quality of the used data sets and how they affect the performance and limitations of the trained models. We conclude this paper with comments on data quality issues, the importance of reproducibility, and suggestions to improve reproducibility. © 2022 IEEE.

关键词： COVID-19

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Automated Spam Review Detection Using Hybrid Deep Learning on Arabic Opinions

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computer Systems science & Engineering 2023年第9期46卷 2947-2961页

作者： IbrahimM.Alwayle Badriyya B.Al-onazi Mohamed K.Nour Khaled M.Alalayah Khadija M.Alaidarous Ibrahim Abdulrab Ahmed Amal S.Mehanna Abdelwahed Motwakel Department of Computer Science College of Science and ArtsSharurahNajran UniversitySaudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Computer Department Applied CollegeNajran UniversityNajran66462Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Online reviews regarding purchasing services or products offered are the main source of users’*** gain fame or profit,generally,spam reviews are written to demote or promote certain targeted products or *** practice is called review *** the last few years,various techniques have been recommended to solve the problem of spam *** spam detection study focuses on English reviews,with a lesser interest in other *** review detection in Arabic online sources is an innovative topic despite the vast amount of data ***,this study develops an Automated Spam Review Detection using optimal Stacked Gated Recurrent Unit(SRD-OSGRU)on Arabic Opinion *** presented SRD-OSGRU model mainly intends to classify Arabic reviews into two classes:spam and ***,the presented SRD-OSGRU model follows different levels of data preprocessing to convert the actual review data into a compatible ***,unigram and bigram feature extractors are *** SGRU model is employed in this study to identify and classify Arabic spam *** the trial-and-error adjustment of hyperparameters is a tedious process,a white shark optimizer(WSO)is utilized,boosting the detection efficiency of the SGRU *** experimental validation of the SRD-OSGRU model is assessed under two datasets,namely DOSC *** extensive comparison study pointed out the enhanced performance of the SRD-OSGRU model over other recent approaches.

关键词： Arabic text spam reviews machine learning deep learning white shark optimizer

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Humanoid Robot control system based on human pose detection 3

Humanoid Robot control system based on human pose detection

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3rd International Conference on Control and Intelligent Robotics, ICCIR 2023

作者： Wen, Jinghao Feng, Xuran Zhang, Qirui Yuan, Hongye Peng, Xi School of Computer Central China Normal University Hubei Wuhan430000 China Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning China Higher Education Institutions of Hubei Province Experimental Teaching Model Center of Basic Computer Science China

ISBN: (纸本)9781510671867

With the rapid progress of science and technology, an increasing number of robots are used in society. Compared with multi-legged crawling robots, humanoid robots have gained more flexibility and reliability with a structure similar to the human body, and have been widely used. Therefore, the proper pose control of the humanoid robot is particularly critical. This paper proposes and designs a humanoid robot control system based on human pose detection. The system detects the posture image of the human body by using the OpenPose method, and then uses the space vector method to calculate the rotation angle information of the human body joints. After being processed, the information is sent to the steering gear controller by the Raspberry Pi. After the controller solves and processes the signal, the pose of the robot is controlled by driving the steering gear. © 2023 SPIE.

关键词： Human computer interaction

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Metasystems in the Strategic Management of the Region

Metasystems in the Strategic Management of the Region

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International Conference on Management of Large-Scale System Development (MLSD)

作者： Alexander Solomatin Department of Mathematical Methods of Regional Programming Federal Research Center “Computer Science and Control” of RAS Moscow Russia

ISBN: (数字)9798350375718

ISBN: (纸本)9798350375725

Instead of the traditional “system-environment” pair for objects of the regional economy, it is proposed to consider metasystems - these objects together with all interacting objects of the microenvironment. Each object is considered as a point in the multidimensional space of characteristics. Objects are visualized to reflect their development and interaction with other objects.

关键词： Visualization Reflection Large-scale systems

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SP-DSTS-MIMO Scheme-Aided H.266 for Reliable High Data Rate Mobile Video Communication

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computers, Materials & Continua 2023年第1期74卷 995-1010页

作者： Khadem Ullah Nasru Minallah Durre Nayab Ishtiaque Ahmed Jaroslav Frnda Jan Nedoma Department of Computer Systems Engineering University of Engineering and Technology PeshawarPeshawar25000Pakistan National Centre in Big Data and Cloud Computing University of Engineering and Technology Peshawar(NCBC-UETP)Peshawar25000Pakistan Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and CommunicationsUniversity of Zilina01026ZilinaSlovakia Department of Telecommunications Faculty of Electrical Engineering and Computer ScienceVSB-Technical University of OstravaOstrava-PorubaCzech Republic

With the ever growth of Internet users,video applications,and massive data traffic across the network,there is a higher need for reliable bandwidth-efficient multimedia *** Video Coding(VVC/H.266)is finalized in September 2020 providing significantly greater compression efficiency compared to Highest Efficient Video Coding(HEVC)while providing versatile effective use for Ultra-High Definition(HD)*** article analyzes the quality performance of convolutional codes,turbo codes and self-concatenated convolutional(SCC)codes based on performance metrics for reliable future video *** advent of turbo codes was a significant achievement ever in the era of wireless communication approaching nearly the Shannon *** codes are operated by the deployment of an interleaver between two Recursive Systematic Convolutional(RSC)encoders in a parallel *** RSC encoders may be operating on the same or different architectures and code *** proposed work utilizes the latest source compression standards H.266 and H.265 encoded standards and Sphere Packing modulation aided differential Space Time Spreading(SP-DSTS)for video transmission in order to provide bandwidth-efficient wireless video ***,simulation results show that turbo codes defeat convolutional codes with an averaged E_(b)/N_(0) gain of 1.5 dB while convolutional codes outperformcompared to SCC codes with an E_(b)/N_(0) gain of 3.5 dBatBit ErrorRate(BER)of 10−*** Peak Signal to Noise Ratio(PSNR)results of convolutional codes with the latest source coding standard of H.266 is plotted against convolutional codes with H.265 and it was concluded H.266 outperform with about 6 dB PSNR gain at E_(b)/N_(0) value of 4.5 dB.

关键词： H.265 RSC turbo codes SCC SP-DSTS BP-CNN BER PSNR

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