检索结果-内蒙古大学图书馆

Global and Diverse Ensemble model for regression

Neurocomputing 2025年 647卷

作者： Durán-Rosal, Antonio M. Ashley, Thomas Pérez-Rodríguez, Javier Fernández-Navarro, Francisco Department of Quantitative Methods Universidad Loyola Andalucía Spain Department of Computer Science and Numerical Analysis University of Córdoba Spain Department of Computer Languages and Computer Science University of Málaga Spain

Diversity is a fundamental component in ensemble methods, crucial for enhancing the overall performance and robustness of predictive models. In bagging and boosting, diversity is implicitly generated through the data sampling process. In stacking, diversity is introduced by incorporating heterogeneous machine learning models as base learners, and an error function is created to focus on minimizing the meta-learner's overall errors. Some models promote diversity directly within the error function;however, they often prioritize generating competitive and diverse individual learners, neglecting the necessity of creating an ensemble that is collectively accurate, as seen in stacking, whilst ensuring diversity among its members. Motivated by this point, two ensemble models are proposed in this manuscript, named Global and Diverse Ensemble methods. These models incorporate implicit diversity through data, diversity in the heterogeneity of base learners, and an error function designed to produce a competitive overall ensemble with diverse individuals. The two diversity proposals included in the models are negative correlation and squared Pearson correlation. In both cases, the error function incorporates the minimization of the ensemble's overall error (global error measure) in addition to promoting diversity. The proposed methods have been rigorously tested on 45 publicly available regression datasets using shallow base learners, as well as on 7 additional datasets using deep base learners, yielding very promising results. These findings underscore the importance of integrating these diversity-promoting elements and minimizing the global errors of the ensemble, rather than focusing solely on the errors of individual base learners, in the design of ensemble methods. © 2025 The Authors

关键词： Linear regression

来源：评论

学校读者我要写书评

暂无评论

Chaotic Elephant Herd Optimization with Machine Learning for Arabic Hate Speech Detection

引用

Intelligent Automation & Soft Computing 2024年第3期39卷 567-583页

作者： Badriyya B.Al-onazi Jaber S.Alzahrani Najm Alotaibi Hussain Alshahrani Mohamed Ahmed Elfaki Radwa Marzouk Heba Mohsen Abdelwahed Motwakel Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Prince Saud AlFaisal Institute for Diplomatic Studies Riyadh12735Saudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqra11911Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in Egypt New CairoNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipAl-Kharj16278Saudi Arabia

In recent years,the usage of social networking sites has considerably increased in the Arab *** has empowered individuals to express their opinions,especially in ***,various organizations that operate in the Arab countries have embraced social media in their day-to-day business activities at different *** is attributed to business owners’understanding of social media’s importance for business ***,the Arabic morphology is too complicated to understand due to the availability of nearly 10,000 roots and more than 900 patterns that act as the basis for verbs and *** speech over online social networking sites turns out to be a worldwide issue that reduces the cohesion of civil *** this background,the current study develops a Chaotic Elephant Herd Optimization with Machine Learning for Hate Speech Detection(CEHOML-HSD)model in the context of the Arabic *** presented CEHOML-HSD model majorly concentrates on identifying and categorising the Arabic text into hate speech and *** attain this,the CEHOML-HSD model follows different sub-processes as discussed *** the initial stage,the CEHOML-HSD model undergoes data pre-processing with the help of the TF-IDF ***,the Support Vector Machine(SVM)model is utilized to detect and classify the hate speech texts made in the Arabic ***,the CEHO approach is employed for fine-tuning the parameters involved in *** CEHO approach is developed by combining the chaotic functions with the classical EHO *** design of the CEHO algorithm for parameter tuning shows the novelty of the work.A widespread experimental analysis was executed to validate the enhanced performance of the proposed CEHOML-HSD *** comparative study outcomes established the supremacy of the proposed CEHOML-HSD model over other approaches.

关键词： Arabic language machine learning elephant herd optimization TF-IDF vectorizer hate speech detection

来源：评论

学校读者我要写书评

暂无评论

MODELING OF ENHANCED FRACTAL CHEETAH OPTIMIZER WITH DEEP LEARNING FOR INTEGRATED ARABIC DIALECT IDENTIFICATION

引用

Fractals 2025年第2期33卷

作者： Alahmari, Saad Al-Shathry, Najla I. Eltahir, Majdy M. Alruwais, Nuha Sayed, Ahmed Abdelbagi, Sitelbanat Department of Computer Science Applied College Northern Border University Arar91431 Saudi Arabia Department of Language Preparation Arabic Language Teaching Institute Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Information Systems Applied College Mahayil King Khalid University Abha Saudi Arabia Department of Computer Science and Engineering College of Applied Studies and Community Services King Saud University Saudi Arabia P.O. Box 22459 Riyadh11495 Saudi Arabia Research Center Future University in Egypt New Cairo11835 Egypt Department of Computer and Self Development Preparatory Year Deanship Prince Sattam bin Abdulaziz University AlKharj Saudi Arabia

The Arabic language has different variants that can roughly be classified into three major types, namely Modern Standard Arabic (MSA), Dialectal Arabic (DA), and Classical Arabic (CA). There are slight variations between CA and MSA regarding pronunciation, syntax, and terminology. On the other hand, DA is quite different from MSA and CA in that it reflects the country of origin, or at least the geographic location of the speaker if the mobility factor is considered. Deep learning demonstrated its effectiveness in DA detection tasks, leveraging neural network models such as transformer models, Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs). Researchers have established models that automatically discriminate between Arabic dialects by processing contextual information, linguistic features, and phonetic patterns embedded in large datasets. Using Deep Learning (DL) in Arabic dialect detection contributes in various complex systems to the development of natural language processing. It assists in addressing the problems related to a wide variety of Arabic dialects, which facilitate applications including machine translation, speech recognition, and sentimental analysis tailored to regional linguistic variation. This study suggests an Enhanced Fractal Cheetah Optimization Algorithm with Deep Learning for Integrated Arabic Dialect Identification (ECOADL-IADI) technique. The ECOADL-IADI technique mainly intends to classify the variations of the Arabic language into multiple classes. At the preliminary level, the ECOADL-IADI technique performs preprocessing of Arabic text. Next, the BERT word embedding process is carried out. The ECOADL-IADI technique applies a Bidirectional Recurrent Neural Network (BiRNN) model for Arabic dialect identification. Lastly, the ECOA-based hyperparameter selection process improves the classifier outcomes of the BiRNN model. A wide range of experiments were conducted to examine the detection results of the ECODL-IADI t

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

6-regular partitions: New combinatorial properties, congruences, and linear inequalities

arXiv

引用

arXiv 2023年

作者： Ballantine, Cristina Merca, Mircea Department of Mathematics and Computer Science College of the Holy Cross WorcesterMA01610 United States Department of Mathematical Methods and Models Fundamental Sciences Applied in Engineering Research Center University Politehnica of Bucharest BucharestRO-060042 Romania

We consider the number of the 6-regular partitions of n, b6(n), and give infinite families of congruences modulo 3 (in arithmetic progression) for b6(n). We also consider the number of the partitions of n into distinct parts not congruent to ±2 modulo 6, Q2(n), and investigate connections between b6(n) and Q2(n) providing new combinatorial interpretations for these partition functions. In this context, we discover new infinite families of linear inequalities involving Euler's partition function p(n). Infinite families of linear inequalities involving the 6-regular partition function b6(n) and the distinct partition function Q2(n) are proposed as open *** Codes 11P81, 11P82, 05A19, 05A20 © 2023, CC BY.

关键词： Combinatorial mathematics

来源：评论

学校读者我要写书评

暂无评论

Prototype for the Model-Based Assets and Liabilities Management Support System

Prototype for the Model-Based Assets and Liabilities Managem...

引用

International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Aleksandra Zhukova Anna Flerova Maxim Tarasenko Alexey Chernov Ruslan Gabbasov Department of Mathematical Modelling of Economic Systems Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russia Department of Mathematical Modelling of Economic Systems FRC CSC RAS Moscow Russia Laboratory of Numerical Methods of Applied Structural Optimization MIPT Moscow Russia

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This paper presents the prototype of the instrument that supports the control of assets and liabilities by a bank using the mathematical computations. The specifics of the approach lies in the application of the recent advances in the control theory to provide the strategic analysis for various planning horizons and scenarios of external and internal factors.

关键词： Instruments Computational modeling Prototypes Mathematical models Planning Control theory Information technology

来源：评论

学校读者我要写书评

暂无评论

Enhancing Password Security: Analyzing Password Management Practices Among IT Students

Enhancing Password Security: Analyzing Password Management P...

引用

International IEEE Conference and Workshop: Óbuda on Electrical and Power Engineering (CANDO-EPE)

作者： Anita Mihalovicsne Kollar Jozsef Katona Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Electronics and Communication Systems Kando Kalman Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemet Hungary Department of Applied Quantitative Methods Faculty of Finance and Accountancy Budapest Business University Budapest Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

Today, with the digital world in its full swing, strong password management is key to protecting sensitive information from both internal and external threats. The current research explores the passwords managing behavior of the IT students at the University of Dunaujvaros. A survey made in May 2024 questioned 68 students, 59 males and 9 females, about behaviors such as using passwords with complexity, not repeating them for multiple accounts or machines, changing them regularly, and which applications they use for password management. The findings have depicted that, as a whole, students appear to be moderately sensitive about the password security instructions. Nonetheless, most continue to indulge in unsafe practices, including easily remembered or weak passwords and infrequent password changes. Furthermore, approximately half of the responders use password management applications, indicating room for significant improvement in the future. The results suggest that intervention and special education measures should be taken to enhance the practice of password security among future IT experts. This research has good potential to contribute toward strategies designed for people behaving safely in password management, and hence promote a secure digital environment.

关键词： Surveys Continuing education Power engineering Correlation Engineering profession Education Passwords Complexity theory Security Protection

来源：评论

学校读者我要写书评

暂无评论

Model for Analysis of High-Frequency Modulated Random Signals 13

Model for Analysis of High-Frequency Modulated Random Signal...

引用

13th International Conference on Advanced computer Information Technologies, ACIT 2023

作者： Javorskyj, Ihor Yuzefovych, Roman Lychak, Oleh Semenov, Pavlo Sliepko, Roman Romanyshyn, Yulia Karpenko Physico-mechanical Institute of NAS of Ukraine Department of Methods and Facilities for Acquisition and Processing Diagnostic Signals Lviv Ukraine Bydgoszcz University of Science and Technology Institute of Telecommunication and Computer Sciences Bydgoszcz Poland Lviv Polytechnic National University Department of Applied Mathematics Lviv Ukraine Odesa National Maritime University Department of Hoisting and Transport Machines and Engineering of Port Technological Equipment Odesa Ukraine Ivano-Frankivsk National Technical University of Oil and Gas Department of Records Management and Information Activity Ivano-Frankivsk Ukraine

The use of the Hilbert transform for the analysis of periodically non-stationary random signals (PNRSs), whose carrier harmonics are modulated by jointly stationary high-frequency random processes is discussed. A representation of the signal in the form of a superposition of high-frequency components is obtained and it is shown that these components are jointly periodically non-stationary random processes. The properties of the band-pass filtered signals are examined, and it is shown that band-pass filtering can reduce both the number of signal variance cyclic harmonics and their amplitudes. We show that it is possible to extract the quadratures of narrow-band high-frequency modulation processes using the Hilbert transform. © 2023 IEEE.

关键词： Random processes

来源：评论

学校读者我要写书评

暂无评论

THE BLESSING OF RANDOMNESS: SDE BEATS ODE IN GENERAL DIFFUSION-BASED IMAGE EDITING

arXiv

引用

arXiv 2023年

作者： Nie, Shen Guo, Hanzhong Allan Lu, Cheng Zhou, Yuhao Zheng, Chenyu Li, Chongxuan Gaoling School of Artificial Intelligence Renmin University of China Beijing China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

We present a unified probabilistic formulation for diffusion-based image editing, where a latent variable is edited in a task-specific manner and generally deviates from the corresponding marginal distribution induced by the original stochastic or ordinary differential equation (SDE or ODE). Instead, it defines a corresponding SDE or ODE for editing. In the formulation, we prove that the Kullback-Leibler divergence between the marginal distributions of the two SDEs gradually decreases while that for the ODEs remains as the time approaches zero, which shows the promise of SDE in image editing. Inspired by it, we provide the SDE counterparts for widely used ODE baselines in various tasks including inpainting and image-to-image translation, where SDE shows a consistent and substantial improvement. Moreover, we propose SDE-Drag - a simple yet effective method built upon the SDE formulation for point-based content dragging. We build a challenging benchmark (termed DragBench) with open-set natural, art, and AI-generated images for evaluation. A user study on DragBench indicates that SDE-Drag significantly outperforms our ODE baseline, existing diffusion-based methods, and the renowned DragGAN. Our results demonstrate the superiority and versatility of SDE in image editing and push the boundary of diffusion-based editing methods. See the project page https://***/SDE-Drag-demo/for the code and DragBench dataset. Copyright © 2023, The Authors. All rights reserved.

关键词： Diffusion

来源：评论

学校读者我要写书评

暂无评论

Multimodal Variational Autoencoder for Low-cost Cardiac Hemodynamics Instability Detection

arXiv

引用

arXiv 2024年

作者： Suvon, Mohammod N.I. Tripathi, Prasun C. Fan, Wenrui Zhou, Shuo Liu, Xianyuan Alabed, Samer Osmani, Venet Swift, Andrew J. Chen, Chen Lu, Haiping Department of Computer Science University of Sheffield Sheffield United Kingdom Centre for Machine Intelligence University of Sheffield Sheffield United Kingdom Department of Infection Immunity and Cardiovascular Disease University of Sheffield Sheffield United Kingdom Department of Clinical Radiology Sheffield Teaching Hospitals Sheffield United Kingdom INSIGNEO Institute for in Silico Medicine University of Sheffield Sheffield United Kingdom Information School University of Sheffield Sheffield United Kingdom Department of Computer Science IITRAM Gujarat India Department of Engineering Science University of Oxford Oxford United Kingdom Department of Computing Imperial College London London United Kingdom

Recent advancements in non-invasive detection of cardiac hemodynamic instability (CHDI) primarily focus on applying machine learning techniques to a single data modality, e.g. cardiac magnetic resonance imaging (MRI). Despite their potential, these approaches often fall short especially when the size of labeled patient data is limited, a common challenge in the medical domain. Furthermore, only a few studies have explored multimodal methods to study CHDI, which mostly rely on costly modalities such as cardiac MRI and echocardiogram. In response to these limitations, we propose a novel multimodal variational autoencoder (CardioVAEX,G) to integrate low-cost chest X-ray (CXR) and electrocardiogram (ECG) modalities with pre-training on a large unlabeled dataset. Specifically, CardioVAEX,G introduces a novel tristream pre-training strategy to learn both shared and modality-specific features, thus enabling fine-tuning with both unimodal and multimodal datasets. We pre-train CardioVAEX,G on a large, unlabeled dataset of 50, 982 subjects from a subset of MIMIC database and then fine-tune the pre-trained model on a labeled dataset of 795 subjects from the ASPIRE registry. Comprehensive evaluations against existing methods show that CardioVAEX,G offers promising performance (AUROC = 0.79 and Accuracy = 0.77), representing a significant step forward in non-invasive prediction of CHDI. Our model also excels in producing fine interpretations of predictions directly associated with clinical features, thereby supporting clinical decision-making. Copyright © 2024, The Authors. All rights reserved.

关键词： Large datasets

来源：评论

学校读者我要写书评

暂无评论

Student Perceptions of AI-Enhanced Adaptive Learning Systems: A Pilot Survey

Student Perceptions of AI-Enhanced Adaptive Learning Systems...

引用

International IEEE Conference and Workshop: Óbuda on Electrical and Power Engineering (CANDO-EPE)

作者： Klara Ida Katonane Gyonyoru Jozsef Katona Department of Organizational Development and Communication Science Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemet Hungary Department of Applied Quantitative Methods Faculty of Finance and Accountancy Budapest Business University Budapest Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

Artificial Intelligence (AI) significantly enhances adaptive learning by personalizing and tailoring instruction to individual student needs. AI analyzes data in real-time to create personalized learning paths based on students' strengths, weaknesses, and preferences, which keeps students engaged and motivated. A major benefit of AI in adaptive learning is the provision of real-time feedback and assessment, allowing students to correct mistakes promptly and understand concepts more thoroughly. AI-based intelligent tutoring systems are primarily intended to simulate personalized tutoring processes that guide students in complex problem-solving and answering questions. It is convenient in teaching mathematics, sciences, and languages. AI also supports inclusive education, dealing with diversified learning requirements and styles, such as those of learners with disabilities. For the teacher, AI acts as a reflector of student performance so that one can intervene early and make adjustments in the method of instruction by creating effective learning environments. AI technology is a field in constant development and harbors the potential to change the face of adaptive learning, bringing an upswing in educational outcomes. This article will summarize the advantages and features that merit improvement of the AI-embedded adaptive learning systems with student feedback.

关键词： Surveys Adaptive learning Power engineering Data security Real-time systems Mathematics Problem-solving Artificial intelligence Faces

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：