检索结果-内蒙古大学图书馆

International Conference on Pattern Analysis and Intelligent Systems (PAIS)

作者： Ahmed Arbaoui Sahraoui Abdelatif Makhlouf Derdour Dept. of Computer Science Laboratory of Mathematics Informatics and Systems (LAMIS) Echahid Cheikh Larbi Tebessi University Tebessa Algeria Dept. of Computer Science LAMIS Laboratory Echahid Cheikh Larbi Tebessi University Tebessa Algeria Dept. of Mathematics and Computer Science LIAOA Laboratory University Of Larbi Ben M’Hidi Oum El Bouaghi Algeria

ISBN: (数字)9798350350265

ISBN: (纸本)9798350350272

The implementation of network slicing services, designed to fulfill the diverse requirements of each Vehicle-to-Everything (V2X) use case, has significantly facilitated the expansion of the Internet of Vehicles (IoV). Three critical communication needs for the V2X ecosystem are ensured by network slicing: ultra-low latency and high reliability, enhanced mobile broadband, and massive machine-type communication (mMTC) support. In addition, network scalability, high mobility, and large density are taken into account. It is noteworthy that the utilization of network slicing technology has evolved beyond its fundamental objectives. In this context, the application of network cutting technology extends its objectives to encompass aspects beyond the essential requirements. This review aims to scrutinize and categorize scientific research endeavors within this domain, according to the specific objectives underlying the adoption of network slicing technology in the IoV ecosystem.

关键词： Reviews Network slicing Scalability Ecosystems Security Resource management Reliability

来源：评论

学校读者我要写书评

暂无评论

Prediction of Stroke Risk Within 7-Years Follow Up Using Machine Learning Models

Prediction of Stroke Risk Within 7-Years Follow Up Using Mac...

引用

2023 IEEE EMBS Special Topic Conference on Data science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Tsarapatsani, Konstantina-Helen Sakellarios, Antonis Tsakanikas, Vasilis D. Rudolf, Henrik Trampisch, Hans J. Pezoulas, Vasileios C. Matsopoulos, George K. Fotiadis, Dimitrios I. University of Ioannina Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering IoanninaGR 45110 Greece Biomedical Research Institute Greece Institute for Biostatistics and Informatics in Medicine and Ageing Research University Medical Center Rostock Germany Ruhr University Bochum Department of Medical Informatics Biometry and Epidemiology Bochum Germany National Technical University of Athens School of Electrical and Computer Engineering Athens Greece

ISBN: (纸本)9798350383386

A stroke, also known as brain attack, occurs when blood supply to your brain is interrupted. Primary prevention relies on prompt prediction of a stroke. While currently there are several clinical risk scores, machine learning (ML) models seems to be more suitable tools for accurate prediction of stroke events. Therefore, this work focuses on the prediction of stroke within 7 years follow-up in patients who have not suffered from a stroke or TIA event at baseline. LightGBM (LGBM), Extreme Grading Boosting (XGBoost), Support Vector Machine (SVM) and Decision Tree were employed in the getABI dataset, which includes 5,897 participants. The performance of models was calculated by Accuracy (ACC), Sensitivity (SENS), Specificity (SPE) and area under the receiver operating characteristic curve (AUC) of each model. According to the comparison analysis's results, LGBM has been shown to be the most trustworthy algorithm, with accuracy 68 %. Moreover, sex, age, status of peripheral artery disease (PAD), history of myocardial infarction, angina pectoris, amputation and diabetes and pulse status of different arteries can be used as a simple and cost-effective way to predict *** Relevance: A fatal medical emergency, stroke may be anticipated using artificial intelligence, and the sooner it is predicted, the more cerebrovascular disease occurrences can be avoided. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Time Frequency Analysis of EMG Signal for Gesture Recognition using Fine-grained Features

arXiv

引用

arXiv 2025年

作者： Aarotale, Parshuram N. Rattani, Ajita Wichita State University Dept. of Biomedical Engineering WichitaKS67220 United States University of North Texas Dept. of Computer Science and Engineering DentonTX United States

Electromyography (EMG)–based hand-gesture recognition converts forearm muscle activity into control commands for prosthetics, rehabilitation, and human–computer interaction. This paper proposes a novel approach to EMG-based hand gesture recognition that uses fine-grained classification and presents XMANet, which unifies low-level local and high-level semantic cues through cross-layer mutual-attention among shallow-to-deep CNN experts. Using stacked spectrograms and scalograms derived from the Short-Time Fourier Transform (STFT) and Wavelet Transform (WT), we benchmark XMANet against ResNet50, DenseNet-121, MobileNetV3, and EfficientNetB0. Experimental results on the Grabmyo dataset indicate that, using STFT, the proposed XMANet model outperforms the baseline ResNet50, EfficientNetB0, MobileNetV3, and DenseNet121 models with improvement of approximately 1.72%, 4.38%, 5.10%, and 2.53%, respectively. When employing the WT approach, improvements of around 1.57%, 1.88%, 1.46%, and 2.05% are observed over the same baselines. Similarly, on the FORS EMG dataset, the XMANet(ResNet50) model using STFT shows an improvement of about 5.04% over the baseline ResNet50. In comparison, the XMANet(DenseNet121) and XMANet(MobileNetV3) models yield enhancements of approximately 4.11% and 2.81%, respectively. Moreover, when using WT, the proposed XMANet achieves gains of around 4.26%, 9.36%, 5.72%, and 6.09% over the baseline ResNet50, DenseNet121, MobileNetV3, and EfficientNetB0 models, respectively. These results confirm that XMANet consistently improves performance across various architectures and signal processing techniques, demonstrating the strong potential of fine-grained features for accurate and robust EMG classification. © 2025, CC BY-NC-ND.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Attention model-based and multi-organism driven gene recognition from text: application to a microbial biofilm organism set.

Attention model-based and multi-organism driven gene recogni...

引用

2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Bomgni, Alain Bertrand Fotseu, Ernest Basile Fotseu Wambo, Daril Raoul Kengne Sani, Rajesh K. Lushbough, Carol Zohim, Etienne Gnimpieba University of South Dakota Dept. of Biomedical Engineering Vermillion United States University of Dschang Dept. of Computer Science Dschang Cameroon SD School of Mines and Technology Dept. of Chem. and Bio. Engineering Rapid city United States

ISBN: (纸本)9781665468190

Nowadays, online databases such as PUBMED and PMC are experiencing an explosion of publications in the field of biomedical sciences. With so much information available online, one of the biggest challenges is managing all that raw, unstructured data and making it machine-readable. Name entity recognition is nowadays a prerequisite for data identification and extraction in biosciences. One of the areas that allows automatic extraction of information from biomedical literature today is Name Entity Recognition. Indeed, it makes it possible to simplify the workflow analysis and automatic extraction of name entities, thus improving the various existing models. There is in the literature a lot of tools for this purpose, but they are unable to extract microbial genes accurately. Moreover, current goal standard corpora such as BIOCREATIVE I to IV have limited representation of microbial knowledge. In this paper, we proposed a new method to recognize biofilm gene mentions from free text. This method relies on a context-specific dictionary to annotate a consistent corpus necessary to train an efficient recognition model. Indeed, this method provides a new workflow for dataset collection generation for microbial biofilm gene. Trained on a set of biofilm organisms our method achieves a score of up to 94%, outperforming state-of-the-art frameworks. © 2022 IEEE.

关键词： Extraction

来源：评论

学校读者我要写书评

暂无评论

Microaneurysm Detection for Early DR Diagnosis Using Advanced Image Processing and a Lightweight Feature Pyramid Network

Microaneurysm Detection for Early DR Diagnosis Using Advance...

引用

International Conference on Advancements in Computational sciences (ICACS)

作者： Muhammad Zeeshan Tahir Muhammad Nasir Tufail Muhammad Sanyuan Zhang Muhammad Ahsan Qureshi Dept. of Computer Science and Technology Zhejiang University Hangzhou Zhejiang China School of Biomedical Engineering University of Science and Technology of China Hefei Anhui China Department of Computer Science Air University Islamabad Pakistan

ISBN: (数字)9798331533038

ISBN: (纸本)9798331533045

Diabetic Retinopathy (DR) is a diabetes-related condition that can lead to vision loss and even permanent blindness. The growing number of diabetic patients combined with a shortage of ophthalmologists underscores the need for automated screening tools to enable early detection. Microaneurysms (MAs), the earliest signs of DR, yet identifying them in fundus images is challenging because of their tint size and subtle features. Furthermore, low contrast, noise, and lighting variations in fundus images, including glare and shadows, add complexity to the detection process. To address these challenges, we applied image enhancement techniques such as green channel extraction, gamma correction, and median filtering to improve image quality. Additionally, to boost the performance of the MA detection model, we integrated a lightweight Feature Pyramid Network (FPN) with a pre-trained ResNet34 backbone, allowing for multiscale feature capture. Our method was evaluated on the E-ophtha dataset, achieving a sensitivity of 0.601, precision of 0.697 and F1 score of 0.651. The experimental findings indicate that the proposed method surpasses current approaches.

关键词： Image quality Diabetic retinopathy Sensitivity Filtering Noise Lighting Blindness Feature extraction Complexity theory Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Animated Virtual Therapist in Virtual Reality Environment for People with Parkinson's Disease

Animated Virtual Therapist in Virtual Reality Environment fo...

引用

IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Wenting Li Ruth Agada Jie Yan Biomedical Engineering Dept. Washington University St. Louis USA Department of Computer Science Bowie State University Bowie USA

ISBN: (数字)9798331521578

ISBN: (纸本)9798331521585

This study investigates the effectiveness of virtual rehabilitation using a 3D animated virtual therapist delivering the LSVT-BIG program for people with Parkinson's disease (PwPD). Integrating an animated virtual therapist in a VR environment aims to overcome accessibility barriers, especially for individuals in remote areas. This VR-enhanced system provides immersive experiences, real-time feedback, and posture correction through computer vision, along with progress-tracking via personalized reports. This approach offers potential improvements in accessibility, engagement, and motivation, which may contribute to enhanced quality of life for individuals with Parkinson's disease.

关键词： computer vision Three-dimensional displays Authoring systems Parkinson's disease Medical treatment Virtual reality Real-time systems Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Coreference as an indicator of context scope in multimodal narrative

arXiv

引用

arXiv 2025年

作者： Ilinykh, Nikolai Lappin, Shalom Sayeed, Asad Loáiciga, Sharid Dept. of Philosophy Linguistics Theory of Science University of Gothenburg Sweden School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Dept. of Informatics King’s College London United Kingdom

We demonstrate that large multimodal language models differ substantially from humans in the distribution of coreferential expressions in a visual storytelling task. We introduce a number of metrics to quantify the characteristics of coreferential patterns in both human- and machine-written texts. Humans distribute coreferential expressions in a way that maintains consistency across texts and images, interleaving references to different entities in a highly varied way. Machines are less able to track mixed references, despite achieving perceived improvements in generation quality. © 2025, CC BY-NC-SA.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Beyond Wake Words: Advancing Smart Speaker Protection with Continuous Authentication and Local Profiles

Beyond Wake Words: Advancing Smart Speaker Protection with C...

引用

International Conference on computer Communications and Networks (ICCCN)

作者： Luca Hernández Acosta Andreas Reinhardt Tobias Müller Delphine Reinhardt Computer Security and Privacy (CSP) Institute of Computer Science University of Göttingen Göttingen Germany Dept. of Informatics TU Clausthal Clausthal-Zellerfeld Germany

ISBN: (数字)9798350384611

ISBN: (纸本)9798350348439

Voice assistants, as provided by smart speakers, have become ubiquitous. Current authentication methods in these systems, however, rely on wake words, posing a risk due to the susceptibility to replay attacks. Additionally, user data stored on servers could expose sensitive information. This study suggests an approach to improve user authentication and profile management in smart speakers, reducing risks tied to external data processing and storage. We propose a two-fold solution for continuous user authentication and local user profiles. This approach prevents unauthorized access to sensitive data and grants users access to their local recordings. Our method differs from current practices in two ways: (1) It authenticates users based on complete voice commands, reducing the risk of replayed wake word attacks, and (2) it operates locally, avoiding the transfer of sensitive data to external servers. We offer a proof-of-concept with Alexa Voice Service (AVS) integration and a thorough evaluation using voice datasets and a study with 17 participants. We tested our approach under various conditions, including accents, background noise, and muffled speech. Legitimate users are identified with 93% precision, 95% recall, 94% F1-score, and 99% accuracy, while illegitimate users are recognized with 99% accuracy across these metrics.

关键词： Measurement Accuracy Authentication Personal voice assistants User experience Delays Speaker recognition

来源：评论

学校读者我要写书评

暂无评论

Quality Assurance for LLM-RAG Systems: Empirical Insights from Tourism Application Testing 18

Quality Assurance for LLM-RAG Systems: Empirical Insights fr...

引用

18th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025

作者： Ahmed, Bestoun S. Baader, Ludwig Otto Bayram, Firas Jagstedt, Siri Magnusson, Peter Karlstad University Sweden & American University of Bahrain Dept. Mathematics and Computer Science Bahrain Ludwig Maximilian University Munich Dept. Mathematics Informatics and Statistics Munich Germany Karlstad University Dept. Mathematics and Computer Science Karlstad Sweden Karlstad University CTF Service Research Center Karlstad Sweden

ISBN: (纸本)9798331534677

This paper presents a comprehensive framework for testing and evaluating quality characteristics of Large Language Model (LLM) systems enhanced with Retrieval-Augmented Generation (RAG) in tourism applications. Through systematic empirical evaluation of three different LLM variants across multiple parameter configurations, we demonstrate the effectiveness of our testing methodology in assessing both functional correctness and extra-functional properties. Our framework implements 17 distinct metrics that encompass syntactic analysis, semantic evaluation, and behavioral evaluation through LLM judges. The study reveals significant information about how different architectural choices and parameter configurations affect system performance, particularly highlighting the impact of temperature and top-p parameters on response quality. The tests were carried out on a tourism recommendation system for the Varmland region in Sweden, utilizing standard and RAG-enhanced configurations. The results indicate that the newer LLM versions show modest improvements in performance metrics, though the differences are more pronounced in response length and complexity rather than in semantic quality. The research contributes practical insights for implementing robust testing practices in LLM-RAG systems, providing valuable guidance to organizations deploying these architectures in production environments. © 2025 IEEE.

关键词： Software quality

来源：评论

学校读者我要写书评

暂无评论

Quality Assurance for LLM-RAG Systems: Empirical Insights from Tourism Application Testing

Quality Assurance for LLM-RAG Systems: Empirical Insights fr...

引用

IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW

作者： Bestoun S. Ahmed Ludwig Otto Baader Firas Bayram Siri Jagstedt Peter Magnusson Dept. Mathematics and Computer Science Karlstad University Sweden & American University of Bahrain Bahrain Dept. Mathematics Informatics and Statistics Ludwig Maximilian University Munich Munich Germany Dept. Mathematics and Computer Science Karlstad University Karlstad Sweden CTF Service Research Center Karlstad University Karlstad Sweden

ISBN: (数字)9798331534677

ISBN: (纸本)9798331534684

关键词： System testing Quality assurance Temperature Systematics Large language models System performance Semantics Retrieval augmented generation Standards organizations Syntactics

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：