检索结果-内蒙古大学图书馆

Enhancing Device-Free Gesture Recognition Capability of Mobile Communication Signals

IEEE Transactions on Communications 2025年

作者： Wu, Jingmiao He, Weijie Sun, Kai Huang, Wei Zhang, Haijun Leung, Victor C. M. Inner Mongolia University School of Electronic Information Engineering Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal Processing Hohhot010021 China University of Science and Technology at Beijing Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services Beijing100083 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada

Device-free gesture recognition using mobile communication signals is a convenient and efficient technology with broad application prospects in smart homes and human-computer interaction. It utilizes the effect of gestures on surrounding signals to achieve gesture recognition. The cell-specific reference signals (CRS) information can be used to achieve the task in close-range training scenarios. However, when gestures are performed at long-range or in non-training scenarios, the recognition performance will significantly degrade. To enhance device-free gesture recognition capability in arbitrary scenarios, we propose the signal quality enhancement algorithm and the gesture spectrogram construction method to solve this problem. Specifically, we superimpose the CRS information from multiple carriers to improve the gesture signal-to-noise ratio and increase the gesture sensing range. Then, we extract the gesture dynamic components from the CRS information and construct gesture spectrograms to represent scenario-independent gesture motion patterns. Using the gesture spectrogram features, we design a deep network to accomplish the gesture recognition task. We built a prototype system on a software-defined radio platform. Experimental results show that our proposed method can effectively increase the gesture sensing range from 30m² to 228m² and achieve an average recognition accuracy of 82.5% for five types of gestures in arbitrary scenarios. © 1972-2012 IEEE.

关键词： Gesture recognition

来源：评论

学校读者我要写书评

暂无评论

TPFIANet: Three path feature progressive interactive attention learning network for medical image segmentation

引用

Knowledge-Based systems 2025年 323卷

作者： Yawu Zhao Shudong Wang Yande Ren Jiehuan Wang Shaoqiang Wang Sibo Qiao Tiyao Liu Shanchen Pang Shandong Key Laboratory of Intelligent Oil & Gas Industrial Software Qingdao Institute of Software College of Computer Science and Technology China University of Petroleum Qingdao Shandong China Department of Medical Imaging Center Affiliated Hospital of Qingdao University Qingdao Shandong China Department of Medical Imaging Affiliated Hospital of Jining Medical University Jining Shandong China School of Information and Control Engineering Qingdao University of Technology Qingdao Shandong China School of Software Tiangong University Tianjin China

In the field of medical image segmentation, medical image segmentation methods with high accuracy and generalization capabilities are crucial for driving personalized healthcare solutions and enhancing patient experience. To address the inherent challenges of difficulty in acquiring complex structural features and weak generalization ability in medical image segmentation, we propose a three-path spatial learning (TPSL) module, which takes advantage of convolutional neural networks (CNNs) to skillfully learn specific details at different scales to acquire better feature representations, and then, we propose a progressive feature cross-fusion (PFCF) module, which aims to dynamically learn feature information under different levels in the encoder, which enhances the feature representation. Finally, we propose the feature interactive attention fusion (FIAF) module, which mixes features from different scales and channels, adaptively learns feature weights and enhances the connection between channel and local spatial information. Based on the above modules, we design a three path feature progressive interactive attention learning network (TPFIANet), which captures image features at different levels and scales. We demonstrate the segmentation performance of TPFIANet on three public datasets and three self-organized datasets. Notably, our TPFIANet also demonstrates amiable segmentation performance on datasets of different modalities while maintaining a lighter architecture.

关键词： Feature interactive attention fusion Medical image segmentation Progressive feature cross-fusion Three-path spatial learning

来源：评论

学校读者我要写书评

暂无评论

Multi-scale feature fusion for breast tumor grading using dual-adaptive attention mechanisms

引用

Pattern Recognition 2026年 169卷

作者： Israr Hussain Zhihui Lai Heng Kong Fazil Hussain College of Computer Science and Software Engineering Shenzhen University Shenzhen 518060 China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen 518060 China Department of Thyroid and Breast Surgery BaoAn Central Hospital of Shenzhen Shenzhen 518102 China Department of Medicine Provincial Head Quarter (PHQ) Hospital Gilgit 15711 Pakistan

Breast cancer is the most common malignant tumor in women worldwide. Early detection and timely treatment are crucial for improving survival rates and ensuring effective treatment planning. While existing methods primarily focus on classifying benign versus malignant tumors, accurate tumor grading remains underexplored. The scarcity of high-quality annotated datasets for advanced tumor grades, combined with their inherent similarity, limits model robustness and precise grading. To address these challenges, we propose a novel framework for breast tumor grading diagnosis that leverages multi-scale feature fusion with dual-adaptive attention mechanisms. This framework enhances grading performance by capturing both local and global information. It integrates information across multiple scales, improves feature representation, and enables the detection of subtle differences between grades. The framework consists of three primary modules: deep hybrid feature extraction, multi-scale feature fusion, and dual-adaptive attention mechanisms. Together, these modules enhance feature representation, capture salient information, and highlight discriminative features, ultimately improving grading accuracy. In addition, we constructed two distinct image datasets consisting of 17,058 ultrasound images and 1571 MRI images for breast tumor grading. Experimental results demonstrated the effectiveness of our framework, achieving a test accuracy of 0.89, a macro-average F1-score of 0.82, and a micro-average precision of 0.93, outperforming existing state-of-the-art methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Impasse Surface of Differential-Algebraic Power System Models: An Interpretation Based on Admittance Matrices

arXiv

引用

arXiv 2020年

作者： Song, Yue Hill, David J. Liu, Tao Zhang, Xinran The State Key Laboratory of Intelligent Autonomous Systems and Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong The Department of Electrical and Computer Systems Engineering Monash University Melbourne Australia The School of Automation Science and Electrical Engineering Beihang University Beijing China

The impasse surface is an important concept in the differential-algebraic equation (DAE) model of power systems, which is associated with short-term voltage collapse. This paper establishes a necessary condition for a system trajectory hitting the impasse surface. The condition is in terms of admittance matrices regarding the power network, generators and loads, which specifies the pattern of interaction between those system components that can induce voltage collapse. It applies to generic DAE models featuring high-order synchronous generators, static loads, induction motor loads and lossy power networks. We also identify a class of static load parameters that prevent power systems from hitting the impasse surface;this proves a conjecture made by Hiskens that has been unsolved for decades. Moreover, the obtained results lead to an early indicator of voltage collapse and a novel viewpoint that inductive compensation to the power network has a positive effect on preventing short-term voltage collapse, which are verified via numerical simulations. Copyright © 2020, The Authors. All rights reserved.

关键词： Differential equations

来源：评论

学校读者我要写书评

暂无评论

Green IoT using UAVs in B5G networks: A review of applications and strategies

arXiv

引用

arXiv 2021年

作者： Alsamhi, Saeed H. Afghah, Fatemeh Sahal, Radhya Hawbani, Ammar Al-Qaness, A.A. Lee, B. Guizani, Mohsen Software Research Institute Athlone Institute of Technology Athlone Ireland IBB University Ibb Yemen School of Informatics Computing and Cyber Systems Northern Arizona University United States Hudaidah University Hudaida Yemen School of Computer Science and Technology University of Science and Technology of China Hefei China State Key Laboratory for Information Engineering in Surveying Mapping and Remote Sensing Wuhan University China Department of Computer Science and Engineering Qatar University Qatar

Recently, Unmanned Aerial Vehicles (UAVs) present a promising advanced technology that can enhance people life quality and smartness of cities dramatically and increase overall economic efficiency. UAVs have attained a significant interest in supporting many applications such as surveillance, agriculture, communication, transportation, pollution monitoring, disaster management, public safety, healthcare, and environmental preservation. Industry 4.0 applications are conceived of intelligent things that can automatically and collaboratively improve beyond 5G (B5G). Therefore, the Internet of Things (IoT) is required to ensure collaboration between the vast multitude of things efficiently anywhere in real-world applications that are monitored in real-time. However, many IoT devices consume a significant amount of energy when transmitting the collected data from surrounding environments. Due to a drone's capability to fly closer to IoT, UAV technology plays a vital role in greening IoT by transmitting collected data to achieve a sustainable, reliable, eco-friendly Industry 4.0. This survey presents an overview of the techniques and strategies proposed recently to achieve green IoT using UAVs infrastructure for a reliable and sustainable smart world. This survey is different from other attempts in terms of concept, focus, and discussion. Finally, various use cases, challenges, and opportunities regarding green IoT using UAVs are presented. © 2021, CC BY.

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Correction to: Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing

引用

Journal of Cloud Computing 2025年第1期14卷 1-1页

作者： Zhou, Jincheng Lilhore, Umesh Kumar M, Poongodi Hai, Tao Simaiya, Sarita Abang Jawawi, Dayang Norhayati Alsekait, Deema Mohammed Ahuja, Sachin Biamba, Cresantus Hamdi, Mounir School of Computer and Information and Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Qiannan Normal University for Nationalities Duyun China Department of Computer Science and Engineering Chandigarh University Mohali India College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar School of Computing Faculty of Engineering Universiti Teknologi Malaysia (UTM) Johor Malaysia Department of Computer Science and Information Technology Princess Nourah Bint Abdul Rahman University Applied College Riyadh Saudi Arabia Department of Culture Studies Religious Studies and Educational Sciences University of Gävle Gävle Sweden

来源：评论

学校读者我要写书评

暂无评论

Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers

引用

Informatics in Medicine Unlocked 2023年 42卷

作者： Azim, Sayed Mehedi Sabab, Noor Hossain Nuri Noshadi, Iman Alinejad-Rokny, Hamid Sharma, Alok Shatabda, Swakkhar Dehzangi, Iman Center for Computational and Integrative Biology Rutgers University Camden 08102 NJ United States Department of Computer Science and Engineering United International University Plot 2 United City Madani Avenue BaddaDhaka 1212 Bangladesh Department of Bioengineering University of California Riverside 92507 CA United States BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering The University of New South Wales (UNSW Sydney) Sydney NSW 2052 Australia UNSW Data Science Hub UNSW Sydney Sydney NSW 2052 Australia Health Data Analytics Program AI-enabled Processes Research Centre Macquarie University Sydney 2109 Australia Institute for Integrated and Intelligent Systems Griffith University Brisbane Australia Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama 230-0045 Japan Department of Computer Science Rutgers University Camden 08102 NJ United States

The use of therapeutic peptides for the treatment of cancer has received tremendous attention in recent years. Anticancer peptides (ACPs) are considered new anticancer drugs which have several advantages over chemistry-based drugs including high specificity, strong tumor penetration capacity, and low toxicity level for normal cells. Due to the rise of experimentally verified bioactive peptides, several in silico approaches became imperative for the investigation of the characteristics of ACPs. In this paper, we proposed a new machine learning tool named iACP-RF that uses a combination of several sequence-based features and an ensemble of three heterogeneously trained Random Forest classifiers to accurately predict anticancer peptides. Experimental results show that our proposed model achieves an accuracy of 75.9% which outperforms other state-of-the-art methods by a significant margin. We also achieve 0.52, 75.6%, and 76.2% in terms of Matthews Correlation Coefficient (MCC), Sensitivity, and Specificity, respectively. iACP-RF as a standalone tool and its source code are publicly available at: https://***/MLBC-lab/iACP-RF. © 2023 The Authors

关键词： Anticancer peptides Ensemble learning Feature extraction Heterogeneous classifiers Machine learning Random Forest

来源：评论

学校读者我要写书评

暂无评论

CARDIOCARE: An integrated platform for the management of elderly multimorbid patients with breast cancer therapy induced cardiac toxicity

CARDIOCARE: An integrated platform for the management of eld...

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： G. Karanasiou L. Koumakis S. Sfakianakis G. Manikis G. Kalliatakis A. Antoniades L. Lakkas D. Mauri C. Cipolla K. Mazzocco A. Papakonstantinou G. Filippatos A. Constantinidou B. Šeruga C. Conti A. Bucur E. Pacella K. Marias M. Tsiknakis D.I. Fotiadis Unit of Medical Technology and Intelligent Information Systems University of Ioannina Ioannina Greece Foundation for Research and Technology - Hellas Institute of Computer Science Heraklion Crete Greece Computational Bio-Medicine Laboratory Institute of Computer Science Foundation for Research and Technology – Hellas Heraklion Greece Stremble Ventures Ltd Limassol Cyprus 2nd Department of Cardiology School of Medicine University of Ioannina Department of Medical Oncology University of Ioannina Greece Cardiology Division European Institute of Oncology Milan Italy Department for Breast Cancer Endocrine Tumors and Sarcoma Theme Cancer Karolinska University Hospital and the Department of Oncology-Pathology Karolinska Institute Stockholm Sweden Department of Cardiology National and Kapodistrian University of Athens School of Medicine Attikon University Hospital Athens Greece Bank of Cyprus Oncology Centre Bank of Cyprus Oncology Centre Nicosia Cyprus Department of Medical Oncology Institute of Oncology Ljubljana Ljubljana Slovenia Istituto di Management Sanitario S.r.l Milano Italy Philips Research Europe Eindhoven Netherlands European Society of Cardiology Brussels Belgium Department of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Crete Greece Medical Technology and Intelligent Information Systems University of Ioannina Ioannina Greece Biomedical Research Institute Foundation for Research and Technology – Hellas University Campus of Ioannina Greece

Breast cancer (BC) remains the most diagnosed cancer in women, accounting for 12% of new annual cancer cases in Europe and worldwide. Advances in surgery, radiotherapy and systemic treatment have resulted in improved clinical outcomes and increased survival rates in recent years. However, BC therapy-related cardiotoxicity, may severely impact short- and long-term quality of life and survival. This study presents the CARDIOCARE platform and its main components, which by integrating patient-specific data from different categories, data from patient-oriented eHealth applications and wearable devices, and by employing advanced data mining and machine learning approaches, provides the healthcare professionals with a valuable tool for effectively managing BC patients and preventing or alleviating treatment induced *** Relevance— Through the adoption of CARDIOCARE platform healthcare professionals are able to stratify patients for their risk for cardiotoxicity and timely apply adequate interventions to prevent its onset.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Technical debt and agile software development practices and processes: An industry practitioner survey

arXiv

引用

arXiv 2021年

作者： Holvitie, Johannes Licorish, Sherlock A. Spínola, Rodrigo O. Hyrynsalmi, Sami MacDonell, Stephen G. Mendes, Thiago S. Buchan, Jim Leppänen, Ville Turku Centre for Computer Science Software Development Laboratory Turku Finland University of Turku Department of Information Technology Turku Finland University of Otago Department of Information Science Otago Dunedin New Zealand Salvador University Graduate Program in Systems and Computer Bahia Salvador Brazil Federal University of Bahia Fraunhofer Project Center for Software and System Engineering Salvador Brazil Tampere University of Technology Pori Campus Pori Finland Federal Institute of Bahia Information Technology Department Bahia Santo Amaro Brazil Auckland University of Technology School of Engineering Computer and Mathematical Sciences Auckland New Zealand

Context: Contemporary software development is typically conducted in dynamic, resource-scarce environments that are prone to the accumulation of technical debt. While this general phenomenon is acknowledged, what remains unknown is how technical debt specifically manifests in and affects software processes, and how the software development techniques employed accommodate or mitigate the presence of this debt. Objectives: We sought to draw on practitioner insights and experiences in order to classify the effects of agile method use on technical debt management, given the popularity and perceived success of agile methods. We explore the breadth of practitioners' knowledge about technical debt;how technical debt is manifested across the software process;and the perceived effects of common agile software development practices and processes on technical debt. In doing so, we address a research gap in technical debt knowledge and provide novel and actionable managerial recommendations. Method: We designed, tested and executed a multi-national survey questionnaire to address our objectives, receiving 184 responses from practitioners in Brazil, Finland, and New Zealand. Results: Our findings indicate that: 1) Practitioners are aware of technical debt, although, there was under utilization of the concept, 2) Technical debt commonly resides in legacy systems, however, concrete instances of technical debt are hard to conceptualize which makes it problematic to manage, 3) Queried agile practices and processes help to reduce technical debt;in particular, techniques that verify and maintain the structure and clarity of implemented artifacts (e.g., Coding standards and Refactoring) positively affect technical debt management. Conclusions: The fact that technical debt instances tend to have characteristics in common means that a systematic approach to its management is feasible. However, notwithstanding the positive effects of some agile practices on technical debt management, comp

关键词： Legacy systems

来源：评论

学校读者我要写书评

暂无评论

Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions

arXiv

引用

arXiv 2022年

作者： Chen, Jiayang Hu, Zhihang Sun, Siqi Tan, Qingxiong Wang, Yixuan Yu, Qinze Zong, Licheng Hong, Liang Xiao, Jin Shen, Tao King, Irwin Li, Yu Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Research Institute of Intelligent Complex Systems Fudan University Shanghai China Shanghai AI Laboratory Shanghai China Harbin Institute of Technology China University of Electronic Science and Technology of China China Institute for Medical Engineering and Science Massachusetts Institute of Technology CambridgeMA United States Wyss Institute for Biologically Inspired Engineering Harvard University BostonMA United States Broad Institute of MIT and Harvard CambridgeMA United States Zelixir Biotech Shanghai China The CUHK Shenzhen Research Institute Hi-Tech Park Nanshan Shenzhen China

Non-coding RNA structure and function are essential to understanding various biological processes, such as cell signaling, gene expression, and post-transcriptional regulations. These are all among the core problems in the RNA field. With the rapid growth of sequencing technology, we have accumulated a massive amount of unannotated RNA sequences. On the other hand, expensive experimental observatory results in only limited numbers of annotated data and 3D structures. Hence, it is still challenging to design computational methods for predicting their structures and functions. The lack of annotated data and systematic study causes inferior performance. To resolve the issue, we propose a novel RNA foundation model (RNA-FM) to take advantage of all the 23 million non-coding RNA sequences through self-supervised learning. Within this approach, we discover that the pre-trained RNA-FM could infer sequential and evolutionary information of non-coding RNAs without using any labels. Furthermore, we demonstrate RNA-FM's effectiveness by applying it to the downstream secondary/3D structure prediction, SARS-CoV-2 genome structure and evolution prediction, protein-RNA binding preference modeling, and gene expression regulation modeling. The comprehensive experiments show that the proposed method improves the RNA structural and functional modelling results significantly and consistently. Despite only being trained with unlabelled data, RNA-FM can serve as the foundational model for the field. © 2022, CC BY-NC-ND.

关键词： RNA

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：