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Effi-CNN: real-time vision-based system for interpretation of sign language using CNN and transfer learning

Multimedia Tools and Applications 2025年第6期84卷 3137-3159页

作者： Pranav Katarya, Rahul Big Data Analytics and Web Intelligence Laboratory Computer Science & Engineering Department Delhi Technological University New Delhi India

The deaf and mute population has difficulty conveying their thoughts and ideas to others. Sign language is their most expressive mode of communication, but the general public is callow of sign language;therefore, the mute and deaf have difficulty communicating with others. A system that can correctly translate sign language motions to speech and vice versa in real time is required to overcome this communication barrier. Effi-CNN, a vision-based Sign Language Recognition (SLR) system employing transfer learning with EfficientNetB2, is proposed in this paper. We have also developed a system covering sign gestures to text in real time. Our approach was evaluated on eight publicly available datasets, including the Massey University gesture dataset, the ArSL2018 dataset, the MNIST-ASL dataset, and others. When comparing our results to state-of-the-art algorithms, the experimental findings showed that our proposed work is more successful than existing models. Our proposed model delivered an accuracy of 99.90 on MNIST dataset. The results show that our Effi-CNN surpasses most currently existing solutions and can categorize many gestures with a low error rate. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Process capability monitoring and change-point analysis for S-type quality characteristic

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Quality Technology and Quantitative Management 2024年第2期21卷 237-256页

作者： Liao, Mou-Yuan Wu, Chien-Wei School of Economics and Management Huzhou College Huzhou China Department of Data Science and Big Data Analytics Providence University Taichung Taiwan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan

Among various quality assurance activities, process capability indices (PCIs) are recognized as the most effective tools to quantify and evaluate process performance. The one-sided capability index (Formula presented.) can adequately measure the process capability for processes with a smaller-is-better (S-type) quality characteristic. While focusing on the index (Formula presented.), this study constructs a capability control chart to monitor the short-term capability based on the exponentially weighted moving average (EWMA). Simulations have shown that the EWMA capability control chart is adaptive regarding average run length. Further, this study applies change-point analysis to determine whether and when the short-term capability-level changes. Using these two proposed methods, engineers can realize a variety of short-term process capabilities in good time and implement control measures efficiently against a poor long-term process capability. © 2023 International Chinese Association of Quantitative Management.

关键词： Control charts

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Fine-Tuned BERT Model for Hate Speech Detection in Political Discourse 22

Fine-Tuned BERT Model for Hate Speech Detection in Political...

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22nd International Conference on ICT and Knowledge Engineering, ICT and KE 2024

作者： Nwaiwu, Steve Jongsawat, Nipat Tungkasthan, Anucha Thaloey, Jarinya RMUTT Data and Information Science Faculty of Science and Technology Pathum Thani Thailand RMUTT Big Data Analytics and Management Faculty of Science and Technology Pathum Thani Thailand

ISBN: (纸本)9798350391411

This research tackles the challenge of detecting hate speech and offensive content in political discussions on social media. By employing natural language processing (NLP) techniques, the study aims to contribute to creating healthier online communities. The researchers started with a manually labeled dataset of Reddit comments centered on political discourse. To address the common issue of class imbalance in classification tasks, they used an oversampling strategy to ensure equal representation of each class. Additionally, they applied data augmentation, specifically synonym replacement, to increase the diversity of the training data, which helps improve the model's generalization. For text preprocessing, the Bidirectional Encoder Represen- tations from Transformers (BERT) tokenizer was used. This tokenizer converts text into subwords, which is especially useful for handling out-of-vocabulary terms. The model used in this study is a fine-tuned version of BERT base, trained with specific hyperparameters: a learning rate of 5e-5, a batch size of 24, and a weight decay of 0.01. Training was carried out over seven epochs using the Hugging Face Transformers library and NVIDIA Tesla P100 GPUs available on Kaggle. The model's performance was assessed using 5-fold cross- validation, resulting in impressive metrics: an average accuracy of 99.34 percent, precision of 99.36 percent, recall of 99.34 percent, F1-score of 99.34 percent, and an ROC-AUC score of 99.96 percent. These results highlight the model's effectiveness in identifying hate speech and offensive content across different data splits. Compared to earlier research, this approach shows significant improvement in performance metrics. It demonstrates the potential of combining BERT with data augmentation and oversampling techniques for detecting hate speech in political discourse on Reddit. This study lays the groundwork for future research into real-time detection systems and cross-lingual models. © 2024 IEEE.

关键词： Natural language processing systems

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Primordial magnetic non-Gaussianity with generic vacua and detection prospects in CMB spectral distortions

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Physical Review D 2024年第4期110卷 043511-043511页

作者： Arko Bhaumik Supratik Pal Physics and Applied Mathematics Unit Technology Innovation Hub on Data Science Big Data Analytics and Data Curation

Assuming a slow-roll inflationary model where conformal invariance of the Maxwell action is broken via a nonminimal kinetic coupling term, we investigate the non-Gaussian three-point cross-correlation function between the primordial curvature perturbation and the primordial magnetic field, under a fairly general choice of initial vacua for both the scalar and the gauge field sectors. Among the possible triangular configurations of the resulting cross-bispectrum, we find that the squeezed limit leads to local-type non-Gaussianity allowing a product form decomposition in terms of the scalar and magnetic power spectra, which is a generic result independent of any specific choice of the initial states. We subsequently explore its detection prospects in the cosmic microwave background (CMB) via correlations between prerecombination μ-type spectral distortions and temperature anisotropies, sourced by such a primordial cross-correlation. Our analysis with several proposed next-generation CMB missions forecasts a low value of the signal-to-noise ratio (SNR) for the μT spectrum if both the vacua are assumed to be pure Bunch-Davies. On the contrary, the SNR may be enhanced significantly for non-Bunch-Davies initial states for the magnetic sector within allowed bounds from current CMB data.

关键词： Cosmic microwave background Inflation Primordial magnetic fields

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Semantic grounding of LLMs using knowledge graphs for query reformulation in medical information retrieval

Semantic grounding of LLMs using knowledge graphs for query ...

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2024 IEEE International Conference on big data, bigdata 2024

作者： Tommasel, Antonela Assent, Ira Isistan CONICET-UNCPBA Argentina Aarhus University Department of Computer Science Denmark Digit Aarhus University Centre for Digitalisation Big Data and Data Analytics Denmark

ISBN: (纸本)9798350362480

The widespread adoption of electronic health records has generated a vast amount of patient-related data, mostly presented in the form of unstructured text, which could be used for document retrieval. However, querying these texts in full could present challenges due to their unstructured and lengthy nature, as they may contain noise or irrelevant terms that can interfere with the retrieval process. Recently, large language models (LLMs) have revolutionized natural language processing tasks. However, despite their promising capabilities, their use in the medical domain has raised concerns due to their lack of understanding, hallucinations, and reliance on outdated knowledge. To address these concerns, we evaluate a Retrieval Augmented Generation (RAG) approach that integrates medical knowledge graphs with LLMs to support query refinement in medical document retrieval tasks. Our initial findings from experiments using two benchmark TREC datasets demonstrate that knowledge graphs can effectively ground LLMs in the medical domain. © 2024 IEEE.

关键词： Knowledge graph

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On the Convergence of Prey Predator Algorithm

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International Journal of Applied and Computational Mathematics 2024年第2期10卷 1-23页

作者： Tilahun, Surafel Luleseged Department of Mathematics HPC and Big Data Analytics Center of Excellence Addis Ababa Science and Technology University Addis Ababa 16417 Ethiopia

Unlike their success in solving complex and difficult problems, there is a lack of proper mathematical analysis and discussion of metaheuristic algorithms. Even though some researches are done on these aspects, the gap is still wide and different researchers outlined that more needs to be done to understand and analyse the search behaviour mathematically in order to move towards explainable AI. Convergence analysis is one of the issues researchers are trying to address. In this paper, a discussion on the convergence of prey predator algorithm will be presented. It is a swarm based algorithm which shows promising results. Furthermore, some initial researches show that it is a generalized algorithm where some well known algorithms fall as its special case. Hence, its analysis can be customized and used for other algorithms as well. Based on mathematical arguments, this paper discusses the convergence analysis of the algorithm to a near optimal solution with appropriate implementation, i.e. appropriate parameter setting. Prey predator algorithm is shown to be an ϵ-convergent algorithm that means there is a non infinity iteration number to get at least epsilon less quality from an optimal solution. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2024.

关键词： Convergence Metaheuristic Prey predator algorithm Swarm intelligence

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Seeing Through the Lies: A Vision Transformer-Based Solution 3rd

Seeing Through the Lies: A Vision Transformer-Based Solution

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3rd International Conference on Artificial-Business analytics, Quantum and Machine Learning: Trends, Perspectives, and Prospects, Com-IT-Con 2023

作者： Rasool, Aale Katarya, Rahul Big Data Analytics and Web Intelligence Laboratory Department of Computer Science Delhi Technological University New Delhi India

ISBN: (纸本)9789819725076

Deepfake technology has become increasingly sophisticated and poses a growing threat to society, as it can be used to create convincing fake videos for malicious purposes. Therefore, detecting deepfakes has become crucial to ensure the authenticity of visual content. This paper proposes a novel deepfake detection approach that utilizes InceptionResNetV2 for feature extraction and Vision Transformer (ViT) with Nyström Attention mechanism for classification. Our model achieves high accuracy, AUC, precision, and recall on the CelebDFv2 dataset and outperforms state-of-the-art techniques like EfficientNet, XceptionNet, and ResNet. We also perform evaluations on the CelebDFv1 and DFDC datasets. Furthermore, we conduct a comprehensive literature survey to highlight the existing research in deepfake detection. We provide a roadmap for future work in this field, highlighting potential research directions that can further improve the effectiveness and applicability of deepfake detection models. The proposed model shows great potential for real-world applications, and the suggested future work can help to address some of the remaining challenges in this area. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Face recognition

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Recommendation fairness and where to find it: An empirical study on fairness of user recommender systems

Recommendation fairness and where to find it: An empirical s...

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2023 IEEE International Conference on big data, bigdata 2023

作者： Tommasel, Antonela Assent, Ira Aarhus University Department of Computer Science Digit Aarhus University Centre for Digitalisation Big Data and Data Analytics Denmark Isistan CONICET-UNCPBA Argentina

ISBN: (纸本)9798350324457

Recommender systems play a crucial role in how users consume information and establish new social relations. However, different factors (such as the data collection process, the designed recommendation model, or even the interpretation of findings) could make recommenders (unintendedly) prone to biases, favouring certain user groups or items, thus resulting in unfair outcomes. Recommenders also face fairness criticism for inducing filter bubbles, echo chambers, and, more generally, facilitating opinion manipulation. In this work, we study the impact of user recommender systems on fairness. To this end, we carry out a user recommendation task on a politically polarized Twitter data collection. Then, we evaluate how the different politically aligned user groups experience recommendation quality. Finally, we explore causal models to identify data and model-related features that could affect the fairness of recommender outcomes. Our study shows that political alignment is associated with the unfairness of recommenders affecting not only the relevance of recommendations, but also their diversity and the resulting interaction patterns. © 2023 IEEE.

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Efficiency-optimized 6G:A virtual network resource orchestration strategy by enhanced particle swarm optimization

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Digital Communications and Networks 2024年第5期10卷 1221-1233页

作者： Sai Zou Junrui Wu Haisheng Yu Wenyong Wang Lisheng Huang Wei Ni Yan Liu College of Big Data and Information Engineering Guizhou UniversityGuiyangChina Prospective Technology Lab of the China Future Internet Engineering Center BeijingChina College of Computer Science and Engineering University of Electronic Science and TechnologyChengduChina International Institute for Next Generation Internet Macao University of Science and TechnologyMacaoChina Data61 Business Unit CSIROAustralia

The future Sixth-Generation (6G) wireless systems are expected to encounter emerging services with diverserequirements. In this paper, 6G network resource orchestration is optimized to support customized networkslicing of services, and place network functions generated by heterogeneous devices into available *** is a combinatorial optimization problem that is solved by developing a Particle Swarm Optimization (PSO)based scheduling strategy with enhanced inertia weight, particle variation, and nonlinear learning factor, therebybalancing the local and global solutions and improving the convergence speed to globally near-optimal *** show that the method improves the convergence speed and the utilization of network resourcescompared with other variants of PSO.

关键词： Virtualization Network function orchestration Network resource virtualized orchestration (NRVO) Particle swarm optimization(PSO)

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Influencing Factors of Healthy Aging Risk Assessed Using Biomarkers:A Life Course Perspective

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China CDC weekly 2024年第11期6卷 219-224,I0014-I0017页

作者： Cedric Zhang Bo Lua Yajie Gao Jinming Li Xingqi Cao Xinwei Lyu Yinuo Tu Shuyi Jin Zuyun Liu Center for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Healththe Key Laboratory of Intelligent Preventive Medicine of Zhejiang ProvinceZhejiang University School of MedicineHangzhou CityZhejiang ProvinceChina Institute of Epidemiology and Health Care University College LondonLondonUK College of Chemical and Biological Engineering Zhejiang UniversityHangzhou CityZhejiang ProvinceChina

Assessing individual risks of healthy aging using biomarkers and identifying associated factors have become important areas of *** this study,we conducted a literature review of relevant publications between 2018 and 2023 in both Chinese and English *** studies have predominantly used single biomarkers,such as C-reactive protein,or focused on specific life course stages and factors such as socioeconomic status,mental health,educational levels,and unhealthy *** summarizing the progress in this field,our study provides valuable insights and future directions for promoting healthy aging from a life course perspective.

关键词： such insight directions

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