检索结果-内蒙古大学图书馆

A Comprehensive Survey on Tiny Machine Learning for Human Behavior Analysis

IEEE Internet of Things Journal 2025年

作者： Lamaakal, Ismail Essahraui, Siham Maleh, Yassine Makkaoui, Khalid El Ouahbi, Ibrahim Bouami, Mouncef Filali El-Latif, Ahmed A. Abd Almousa, May Peng, Jialiang Sultan Moulay Slimane University Laboratory LaSTI ENSAK Khouribga Morocco Prince Sultan University EIAS Data Science Lab College of Computer and Information Sciences Center of Excellence in Quantum and Intelligent Computing Riyadh11586 Saudi Arabia Menoufia University Faculty of Science Department of Mathematics and Computer Science Shebin El-Koom32511 Egypt Princess Nourah Bint Abdulrahman University College of Computer and Information Sciences Information Technology Department Riyadh Saudi Arabia Heilongjiang University School of Data Science and Technology Harbin150080 China Nanyang Technological University School of Computer Science and Engineering Nanyang Avenue Singapore639798 Singapore

The integration of Tiny Machine Learning (TinyML) with Human Behavior Analysis (HBA) represents a significant advancement in the field of Artificial Intelligence (AI), enabling real-time, efficient, and privacy-preserving analysis on resource-constrained devices. This paper provides the first comprehensive survey exploring this integration, presenting a detailed overview of TinyML, including its definitions, key concepts and advantages. The survey proposes a systematic taxonomy of TinyML applications in HBA, categorizing state-of-the-art implementations based on their use cases and specific methodologies. Furthermore, the challenges and limitations of integrating TinyML in HBA are thoroughly discussed, including technical constraints, data quality issues, and ethical considerations. Finally, future research directions and open issues are outlined, emphasizing the potential advancements and emerging trends in this field. This survey serves as a foundational resource, guiding researchers and practitioners in harnessing the capabilities of TinyML to advance HBA. © 2014 IEEE.

关键词： Embedded systems

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Decision-Making Approach for Better Selection of Blockchain Platform for Health Insurance Frauds Detection with Smart Contracts: Development and Performance Evaluation

引用

Procedia computer science 2023年 220卷 470-477页

作者： Rima Kaafarani Leila Ismail Oussama Zahwe ICCS-Lab Computer Science Department American University of Culture and Education 1507 Beirut Lebanon Cloud Computing and Distributed Systems (CLOUDS) Laboratory School of Computing and Information Systems The University of Melbourne Melbourne Australia Intelligent Distributed Computing and Systems (INDUCE) Laboratory Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University Abu Dhabi United Arab Emirates National Water and Energy Center United Arab Emirates University Abu Dhabi United Arab Emirates

Blockchain technology has piqued the interest of businesses of all types, while consistently improving and adapting to business requirements. Several blockchain platforms have emerged, making it challenging to select a suitable one for a specific type of business. This paper presents a classification of over one hundred blockchain platforms. We develop smart contracts for detecting healthcare insurance frauds using the top two blockchain platforms selected based on our proposed decision-making map approach which selects the top suitable platforms for healthcare insurance frauds detection application. Our classification shows that the largest percentage of platforms can be used for all types of application domains, the second biggest percentage for financial services, and a small number is to develop applications in specific domains. Our decision-making map and performance evaluations reveal that Hyperledger Fabric surpassed Neo in all metrics for detecting healthcare insurance frauds.

关键词： Blockchain Decision-Map Health Insurance Frauds Detection Hyperledger Fabric Neo Smart Contract Smart Healthcare

来源：评论

学校读者我要写书评

暂无评论

Toward multi-target self-organizing pursuit in a partially observable Markov game

arXiv

引用

arXiv 2022年

作者： Sun, Lijun Chang, Yu-Cheng Lyu, Chao Shi, Ye Shi, Yuhui Lin, Chin-Teng Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology China Centre for Artificial Intelligence CIBCI Lab Faculty of Engineering and Information Technology University of Technology Sydney Australia College of Computer and Information Science Southwest University China School of Information Science and Technology ShanghaiTech University China

The multiple-target self-organizing pursuit (SOP) problem has wide applications and has been considered a challenging self-organization game for distributed systems, in which intelligent agents cooperatively pursue multiple dynamic targets with partial observations. This work proposes a framework for decentralized multi-agent systems to improve the implicit coordination capabilities in search and pursuit. We model a self-organizing system as a partially observable Markov game (POMG) featured by large-scale, decentralization, partial observation, and noncommunication. The proposed distributed algorithm-fuzzy self-organizing cooperative coevolution (FSC2) is then leveraged to resolve the three challenges in multi-target SOP: distributed self-organizing search (SOS), distributed task allocation, and distributed single-target pursuit. FSC2 includes a coordinated multi-agent deep reinforcement learning (MARL) method that enables homogeneous agents to learn natural SOS patterns. Additionally, we propose a fuzzy-based distributed task allocation method, which locally decomposes multi-target SOP into several single-target pursuit problems. The cooperative coevolution principle is employed to coordinate distributed pursuers for each single-target pursuit problem. Therefore, the uncertainties of inherent partial observation and distributed decision-making in the POMG can be alleviated. The experimental results demonstrate that by decomposing the SOP task, FSC2 achieves superior performance compared with other implicit coordination policies fully trained by general MARL algorithms. The scalability of FSC2 is proved that up to 2048 FSC2 agents perform efficient multi-target SOP with almost 100% capture rates. Empirical analyses and ablation studies verify the interpretability, rationality, and effectiveness of component algorithms in FSC2. Copyright © 2022, The Authors. All rights reserved.

关键词： intelligent agents

来源：评论

学校读者我要写书评

暂无评论

Multi-Objective Multi-Verse Optimizer for Multi-Product Partial U-Shaped Disassembly Line Balancing Problem 18

Multi-Objective Multi-Verse Optimizer for Multi-Product Part...

引用

18th IEEE International Conference on Networking, Sensing and Control, ICNSC 2021

作者： Zhang, Shancheng Guo, Laide Guo, Xiwang Liu, Shixin Qi, Liang Qin, Shujin Tang, Ying Zhao, Ziyan Liaoning Petrochemical University College of Computer and Communication Engineering Fushun113001 China Northeastern University College of Information Science and Engineering Shenyang110819 China Shandong University of Science and Technology Department of Computer Intelligent Sci. Tech Qingdao266590 China Shangqiu Normal University College of Economics and Management Shangqiu476000 China Rowan University Electrical and Computer Engineering GlassboroNJ United States

ISBN: (纸本)9781665440486

The development of industry and technology promotes the acceleration of product replacement, and generate a large number of end-of-life products. Meanwhile, robots also play a significant role in disassembly. This paper proposes a scheme to solve a U-shaped disassembly line balancing problem with robots. A mathematical model for maximizing profits and minimizing carbon emissions is established. Then, the paper proposes an improved Multi-Objective Multi-Verse Optimizer (MOMVO) to solve the problem. Taking the disassembly of ballpoint pen and hammer drill as examples, our method is compared with Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), and Multi-Objective Cellular Genetic Algorithm (MOCGA). Comparison indexes include Inverted Generational Distance+ (IGD+) and hypervolume epsilon metric. The experimental results show that the MOMVO algorithm performs better than others on the U-shaped and robotic disassembly line. © 2021 IEEE.

关键词： Robotics

来源：评论

学校读者我要写书评

暂无评论

System Network Analytics: Evolution and Stable Rules of a State Series

arXiv

引用

arXiv 2022年

作者： Chaturvedi, Animesh Tiwari, Aruna Spyratos, Nicolas Data Science and Intelligent Systems Indian Institute of Information Technology Dharwad Karnataka Dharwad India Computer Science and Engineering Indian Institute of Technology Indore Indore India Computer Science Department LISN Lab University of Paris-Saclay Paris France

System Evolution Analytics on a system that evolves is a challenge because it makes a State Series SS = {S1, S2… SN} (i.e., a set of states ordered by time) with several inter-connected entities changing over time. We present stability characteristics of interesting evolution rules occurring in multiple states. We defined an evolution rule with its stability as the fraction of states in which the rule is interesting. Extensively, we defined stable rule as the evolution rule having stability that exceeds a given threshold minimum stability (minStab). We also defined persistence metric, a quantitative measure of persistent entity-connections. We explain this with an approach and algorithm for System Network Analytics (SysNet-Analytics), which uses minStab to retrieve Network Evolution Rules (NERs) and Stable NERs (SNERs). The retrieved information is used to calculate a proposed System Network Persistence (SNP) metric. This work is automated as a SysNet-Analytics Tool to demonstrate application on real world systems including: software system, natural-language system, retail market system, and IMDb system. We quantified stability and persistence of entity-connections in a system state series. This results in evolution information, which helps in system evolution analytics based on knowledge discovery and data mining. © 2022, CC BY.

关键词： Stability

来源：评论

学校读者我要写书评

暂无评论

EEG-based Emotion Recognition on Unstable Patterns over Time

EEG-based Emotion Recognition on Unstable Patterns over Time

引用

International Conference on Digital Home (ICDH)

作者： Guopei Wu Sheng Qin Yuling Luo Qiang Fu Jin Zeng Su Yang Junxiu Liu Guangxi Key Lab of Brain-inspired Computing and Intelligent Chips School of Electronic and Information Engineering Guangxi Normal University Guilin China Education Department of Guangxi Zhuang Autonomous Region Key Laboratory of Nonlinear Circuits and Optical Communications (Guangxi Normal University) Guilin China Department of Computer Science Swansea University UK

ISBN: (数字)9798331509873

ISBN: (纸本)9798331509880

In brain-computer interface (BCI) systems, users' emotion can be recognized by using electroencephalography (EEG) data. Recent researches proposed different methods for feature extraction and EEG-based emotion classification. However, EEG data collected over time is not always stable and accuracies of emotion recognition are found not robust. In this paper, a novel EEG emotion recognition system is proposed by combining ReliefF for extracting features, and Long Short-Term Memory Network coupled with Support Vector Machine for classification. A public EEG emotion dataset of SEED which contains three different recordings of EEG data is used in the experiments. It is shown that the proposed network is effective for mitigating the phenomenon of unstable accuracies, and achieves higher emotion classification accuracies compared to other approaches using the same dataset.

关键词： Support vector machines Emotion recognition Accuracy Feature extraction Electroencephalography Brain-computer interfaces Recording Classification algorithms Long short term memory Biological neural networks

来源：评论

学校读者我要写书评

暂无评论

Contextualized embeddings based transformer encoder for sentence similarity modeling in answer selection task 12

Contextualized embeddings based transformer encoder for sent...

引用

12th International Conference on Language Resources and Evaluation, LREC 2020

作者： Tahmid Rahman Laskar, Md. Huang, Jimmy Hoque, Enamul Department of Electrical Engineering and Computer Science York University TorontoON Canada School of Information Technology York University TorontoON Canada Information Retrieval and Knowledge Management Research Lab York University TorontoON Canada

ISBN: (纸本)9791095546344

Word embeddings that consider context have attracted great attention for various natural language processing tasks in recent years. In this paper, we utilize contextualized word embeddings with the transformer encoder for sentence similarity modeling in the answer selection task. We present two different approaches (feature-based and fine-tuning-based) for answer selection. In the feature-based approach, we utilize two types of contextualized embeddings, namely the Embeddings from Language Models (ELMo) and the Bidirectional Encoder Representations from Transformers (BERT) and integrate each of them with the transformer encoder. We find that integrating these contextual embeddings with the transformer encoder is effective to improve the performance of sentence similarity modeling. In the second approach, we fine-tune two pre-trained transformer encoder models for the answer selection task. Based on our experiments on six datasets, we find that the fine-tuning approach outperforms the feature-based approach on all of them. Among our fine-tuning-based models, the Robustly Optimized BERT Pretraining Approach (RoBERTa) model results in new state-of-the-art performance across five datasets. © European Language Resources Association (ELRA), licensed under CC-BY-NC

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Identifying Appropriate Probability Density Function for Wind Speed Profiles of Two Coastal Cities in Pakistan for Better Wind Power Assessment

Identifying Appropriate Probability Density Function for Win...

引用

Emerging Trends in Electrical, Control, and Telecommunication engineering (ETECTE), International Conference on

作者： Ghulam Abbas Arshad Ali Muhammad Zubair Zohaib Mushtaq Umar Farooq Irfan A. Khan Department of Electrical Engineering The University of Lahore Lahore Pakistan Faculty of Computer and Information Systems Islamic University of Madinah Madinah Saudi Arabia College of Engineering and Technology University of Doha for Science and Technology Doha Qatar Department of Electrical Electronics and Computer Systems University of Sargodha Sargodha Pakistan Intelligent Systems Lab & Automation Facility (ISLAF) IEECE University of the Punjab Lahore Pakistan Clean and Resilient Energy Systems (CARES) Lab Texas A&M University Galveston TX USA

ISBN: (数字)9798331504861

ISBN: (纸本)9798331504878

To assess the wind power potential of a specific wind site, a suitable distribution function that best suits the wind data needs to be known. In this study, we employ four probability density functions (PDFs), namely Weibull, Rayleigh, Log-Normal, and Gamma, on wind speed data obtained from two coastal cities in Pakistan, Gwadar and Karachi, to check which one is the best suited. Cities along the coastline of Pakistan offer greater wind speeds and, thus, greater wind power potential. The maximum likelihood technique is used to estimate the parameters of the density distributions. Three statistical measures-Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R 2 )-are used to assess the goodness of fit for every distribution. These measures give a complete picture of every distribution's correctness in terms of reflecting the recorded wind speed patterns. Numerical results reveal that the Weibull distribution fits well with the wind speeds of the two coastal cities compared to the other three probability distributions, providing insightful analysis for the evaluation of wind resources and possible local energy generation. The MATlab environment is used to compare the distributions and validate the effectiveness of the proposed methodology.

关键词： Wind energy generation Electric potential Wind energy Wind speed Urban areas Sea measurements Wind power generation Probability density function Probability distribution Weibull distribution

来源：评论

学校读者我要写书评

暂无评论

Query Focused Abstractive Summarization via Incorporating Query Relevance and Transfer Learning with Transformer Models 33rd

Query Focused Abstractive Summarization via Incorporating Qu...

引用

33rd Canadian Conference on Artificial Intelligence, Canadian AI 2020

作者： Laskar, Md Tahmid Rahman Hoque, Enamul Huang, Jimmy Department of Electrical Engineering and Computer Science York University Toronto Canada School of Information Technology York University Toronto Canada Information Retrieval and Knowledge Management Research Lab York University Toronto Canada

ISBN: (纸本)9783030473570

In the Query Focused Abstractive Summarization (QFAS) task, the goal is to generate abstractive summaries from the source document that are relevant to the given query. In this paper, we propose a new transfer learning technique by utilizing the pre-trained transformer architecture for the QFAS task in the Debatepedia dataset. We find that the Diversity Driven Attention model (DDA), which was the first model applied on this dataset, only performs well when the dataset is augmented by creating more training instances. In contrast, without requiring any in-domain data augmentation, our proposed approach outperforms the DDA model as well as sets a new state-of-the-art result. © Springer Nature Switzerland AG 2020.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

Mesenchymal stem cells loaded on 3D-printed gradient poly(e-caprolactone)/methacrylated alginate composite scaffolds for cartilage tissue engineering

引用

Regenerative Biomaterials 2021年第3期8卷 70-83页

作者： Yanyan Cao Peng Cheng Shengbo Sang Chuan Xiang Yang An Xiaochun Wei Zhizhong Shen Yixia Zhang Pengcui Li Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education MicroNano System Research CenterCollege of Information and ComputerTaiyuan University of TechnologyTaiyuan 030024China College of Information Science and Engineering Hebei North UniversityZhangjiakou 075000China Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair Department of OrthopedicsThe Second Hospital of Shanxi Medical UniversityTaiyuan 030001China Department of Plastic Surgery Peking University Third HospitalBeijing 100191China Department of Biomedical Engineering College of Biomedical EngineeringTaiyuan University of TechnologyTaiyuan 030024China

Cartilage has limited self-repair ability due to its avascular,alymphatic and aneural *** combination of three-dimensional(3D)printing and tissue engineering provides an up-and-coming approach to address this ***,we designed and fabricated a tri-layered(superficial layer(SL),middle layer(ML)and deep layer(DL))stratified scaffold,inspired by the architecture of collagen fibers in native cartilage *** scaffold was composed of 3D printed depth-dependent gradient poly(e-caprolactone)(PCL)impregnated with methacrylated alginate(ALMA),and its morphological analysis and mechanical properties were *** prove the feasibility of the composite scaffolds for cartilage regeneration,the viability,proliferation,collagen deposition and chondrogenic differentiation of embedded rat bone marrow mesenchymal stem cells(BMSCs)in the scaffolds were assessed by Live/dead assay,CCK-8,DNA content,cell morphology,immunofluorescence and real-time reverse transcription polymerase chain ***-loaded gradient PCL/ALMA scaffolds showed excellent cell survival,cell proliferation,cell morphology,collagen II deposition and hopeful chondrogenic differentiation compared with three individual-layer ***,our study demonstrates the potential use of the gradient PCL/ALMA construct for enhanced cartilage tissue engineering.

关键词： three-dimensional printing cartilage tissue engineering PCL methacrylated alginate bone marrow mesenchymal stem cells

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：