检索结果-内蒙古大学图书馆

5th International Conference on Advancements in Computing, ICAC 2023

作者： Perera, K.A.Y. Mandawela, M.K.C.N. Nilumika, H.L.G. Rasanjana, A.H.P. Mahaadikara, M.M.D.J.T. Hettiarachchi, Sathira Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350358131

Rubber cultivation plays a vital role in the global economy as a primary natural rubber source necessitates efficient plantation management for sustainability and latex quality. This paper introduces an integrated mobile app that enhances rubber plantation management through real-time monitoring of tapping, disease identification via image processing, weed detection, and latex quality assessment. Addressing these challenges becomes pivotal to improving latex quality, minimizing waste, and promoting sustainable practices in the rubber industry. In conclusion, the proposed mobile application serves as a prospective solution for estate owners, utilizing selected algorithms to tackle these challenges effectively. © 2023 IEEE.

关键词： Sustainable development

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Domain Adaptation for Action Recognition via Self-Ensembling and Conditional Embedding Alignment 24

Unsupervised Domain Adaptation for Action Recognition via Se...

引用

24th IEEE International Conference on Data Mining, ICDM 2024

作者： Ghosh, Indrajeet Chugh, Garvit Md Faridee, Abu Zaher Roy, Nirmalya University of Maryland Department of Information Systems Baltimore County United States Indian Institute of Technology Department of Computer Science and Engineering Jodhpur India Amazon United States

ISBN: (纸本)9798331506681

Recent advancements in deep learning-based wearable human action recognition (wHAR) have improved the capture and classification of complex motions, but adoption remains limited due to the lack of expert annotations and domain discrepancies from user variations. Limited annotations hinder the model's ability to generalize to out-of-distribution samples. While data augmentation can improve generalizability, unsupervised augmentation techniques must be applied carefully to avoid introducing noise. Unsupervised domain adaptation (UDA) addresses domain discrepancies by aligning conditional distributions with labeled target samples, but vanilla pseudo-labeling can lead to error propagation. To address these challenges, we propose μDAR, a novel joint optimization architecture comprised of three functions: (i) consistency regularizer between augmented samples to improve model classification generalizability, (ii) temporal ensemble for robust pseudo-label generation and (iii) conditional distribution alignment to improve domain generalizability. The temporal ensemble works by aggregating predictions from past epochs to smooth out noisy pseudo-label predictions, which are then used in the conditional distribution alignment module to minimize kernel-based class-wise conditional maximum mean discrepancy (kCMMD) between the source and target feature space to learn a domain invariant embedding. The consistency-regularized augmentations ensure that multiple augmentations of the same sample share the same labels;this results in (a) strong generalization with limited source domain samples and (b) consistent pseudo-label generation in target samples. The novel integration of these three modules in μDAR results in a range of 4-12% average macro-F1 score improvement over six state-of-the-art UDA methods in four benchmark wHAR datasets. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Baby Bump: A Monitoring System for Pregnant Mothers and Babies 9

Baby Bump: A Monitoring System for Pregnant Mothers and Babi...

引用

9th IEEE International Conference for Convergence in technology, I2CT 2024

作者： Balasooriya, Dhanuka Perera, Sasini Wijendra, Dinuka R. Rathnayaka, Sahani Kishan, Rajendra Rajendran, Karthiga Thirukumar, Markandu Sri Lankan Institute of Information Technology Department of Computer Systems And Software Engineering Malabe Sri Lanka Teaching Hospital Department of Obstetrics & Gynaecology Batticaloa Sri Lanka

ISBN: (纸本)9798350394474

In contemporary times, nations like Sri Lanka are actively enhancing their efforts to improve the life expectancy of their citizens, with a strong focus on public health. The relationship between health and life expectancy is pivotal. Poor health conditions tend to diminish life expectancy, while robust health measures tend to extend it. Within the context of health, birth and death events are of paramount importance. Birth represents the genesis of life, enabling individuals to contribute to future generations and the overall population's expansion. It's the cornerstone of life on our planet. However, modern times have witnessed challenges in pregnancy and childbirth, with some infants not surviving the prenatal period or being born with health complications. Consequently, there is a pressing need to present a solution that can contribute to the betterment of maternal and infant health, ultimately augmenting Sri Lanka's life expectancy. The proposed solution is the development of a mobile application, encompassing features such as a Nutrition Predictor, Medicine Effect Predictor, AI chatbot, and Baby Status Predictor. This innovative application aims to address the complex issues surrounding pregnancy and childbirth, with the overarching goal of improving the nation's life expectancy. © 2024 IEEE.

关键词： Nutrition

来源：评论

学校读者我要写书评

暂无评论

Optimized Resource Allocation for IoT-D2D Communication Using WSN

引用

computer systems Science & engineering 2023年第5期45卷 1789-1804页

作者： S.Arun Mozhi Selvi Roobaea Alroobaea Saeed Rubaiee Abdulkader S.Hanbazazah Department of Computer Science and Engineering Holy Cross Engineering CollegeVagaikulam628851Tamil NaduIndia Department of Computer Sceience College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21974Saudi Arabia Department of Industrial and Systems Engineering College of EngineeringUniversity of JeddahJeddah21959Saudi Arabia

The need for a strong system to access radio resources demands a change in operating frequency in wireless networks as a part of Radio Resource Management(RRM).In the fifth-generation(5G)wireless networks,the capacity of the system is expected to be enhanced by Device-to-Device(D2D)*** cooperation and Resources Allocation(RA)in the development of Internet of Things(IoT)enabled 5G wireless networks are investigated in this *** radio RA methods for D2D communication while not affecting any Mobile Users’(MU)communication is the main challenge of this *** performance goals such as practising equality in the rates of user data,increasing Network Throughput(NT),and reducing End-to-End Delay(EED)are achieved by *** study undertaken on optimising performance for various wireless networks is focused on in this research *** a polynomialtime Proportional Fair Resource Allocation Method(PFRAM),which considers the MU’s rate requirements,is the prime objective of this *** Resource Allocation Method(RAM)can be used by the proposed method for MU,and the time and differing location channel conditions are the factors to be adapted *** more than one resource block is allowed by our PFRAM to a D2D *** automatic maintenance of battery-less IoT wireless devices’energy level is done potentially using an Extensible Energy Management System(EEMS).Finally,the device’s Node Transmission Power(NTP)can be managed using an Energy-Saving Algorithm(ESA)designed in this work for Node Uplink Data Transmission(NUDT).The trade-off between the Packet Loss Rate(PLR)and NTP is balanced by the *** cost of NUDT’s average Energy Consumption(EC)is reduced by locating the optical *** order to free much bandwidth for wireless information,NUDT conserves the harvested energy for minimising Radio Frequency(RF)Energy Transmission(ET).MATLAB simulations are used to assess the proposed *** IoT device’s NTP is managed using

关键词： IoT energy transmission WSN mobility resource allocation

来源：评论

学校读者我要写书评

暂无评论

Care3D: An Active 3D Object Detection Dataset of Real Robotic-Care Environments

Care3D: An Active 3D Object Detection Dataset of Real Roboti...

引用

2023 IEEE International Symposium on Multimedia, ISM 2023

作者： Adam, Michael G. Eger, Sebastian Piccolrovazzi, Martin Iskandar, Maged Vogel, Joern Dietrich, Alexander Bien, Seongjien Skerlj, Jon Naceri, Abdeldjallil Steinbach, Eckehard Albu-Schaeffer, Alin Haddadin, Sami Burgard, Wolfram Technical University of Munich Media Technology Department of Computer Engineering School of Computation Information and Technology Munich Germany Wessling Germany Robotics and Systems Intelligence Department of Computer Engineering School of Computation Information and Technology Technical University of Munich Munich Germany University of Technology Nuremberg Engineering Department Nuremberg Germany

ISBN: (纸本)9798350395761

As labor shortage increases in the health sector, the demand for assistive robotics grows. However, the needed test data to develop those robots is scarce, especially for the application of active 3D object detection, where no real data exists at all. This short paper counters this by introducing such an annotated dataset of real environments. The captured environments represent areas which are already in use in the field of robotic health care research. We further provide ground truth data within one room, for assessing SLAM algorithms running directly on a health care robot. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Enhancing Wireless Sensor Network Efficiency through Al-Biruni Earth Radius Optimization

引用

computers, Materials & Continua 2024年第6期79卷 3549-3568页

作者： Reem Ibrahim Alkanhel Doaa Sami Khafaga Ahmed Mohamed Zaki Marwa M.Eid Abdyalaziz A.Al-Mooneam Abdelhameed Ibrahim S.K.Towfek Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science and Intelligent Systems Research Center BlacksburgVirginia24060USA Delta Higher Institute for Engineering and Technology Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Artificial Intelligence and Computational Intelligence Research Center MeridenConnecticut06450USA School of ICT Faculty of EngineeringDesign and Information&Communications Technology(EDICT)Bahrain PolytechnicP.O.Box 33349Isa TownBahrain

The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial *** the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network *** infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node *** work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and *** using the ARIMA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and *** implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network *** compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world *** the most efficient in the optimization process,Biruni displays the lowest error rate at *** two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific *** to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be *** delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.

关键词： Wireless sensor networks optimization ARIMA model BER algorithm metaheuristic algorithms

来源：评论

学校读者我要写书评

暂无评论

Mutual information oriented deep skill chaining for multi‐agent reinforcement learning

引用

CAAI Transactions on Intelligence technology 2024年第4期9卷 1014-1030页

作者： Zaipeng Xie Cheng Ji Chentai Qiao WenZhan Song Zewen Li Yufeng Zhang Yujing Zhang Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai UniversityNanjingChina College of Computer and Information Hohai UniversityNanjingChina Center for Cyber‐Physical Systems University of GeorgiaAthensGeorgiaUSA Information Networking Institute Carnegie Mellon UniversityPittsburghPennsylvaniaUSA Department of Electrical and Systems Engineering University of PennsylvaniaPhiladelphiaPennsylvaniaUSA

Multi‐agent reinforcement learning relies on reward signals to guide the policy networks of individual ***,in high‐dimensional continuous spaces,the non‐stationary environment can provide outdated experiences that hinder convergence,resulting in ineffective training performance for multi‐agent *** tackle this issue,a novel reinforcement learning scheme,Mutual information Oriented Deep Skill Chaining(MioDSC),is proposed that generates an optimised cooperative policy by incorporating intrinsic rewards based on mutual information to improve exploration *** rewards encourage agents to diversify their learning process by engaging in actions that increase the mutual information between their actions and the environment *** addition,MioDSC can generate cooperative policies using the options framework,allowing agents to learn and reuse complex action sequences and accelerating the convergence speed of multi‐agent *** was evaluated in the multi‐agent particle environment and the StarCraft multi‐agent challenge at varying difficulty *** experimental results demonstrate that MioDSC outperforms state‐of‐the‐art methods and is robust across various multi‐agent system tasks with high stability.

关键词： artificial intelligence techniques decision making intelligent multi‐agent systems

来源：评论

学校读者我要写书评

暂无评论

Semantic association rules for data interestingness using domain ontology

引用

International Journal of Metadata, Semantics and Ontologies 2022年第1期16卷 47-67页

作者： Abhilash, C.B. Mahesh, Kavi Department of Computer Science and Engineering Indian Institute of Information Technology Dharwad Karnataka Dharwad India Department of Data Science and Intelligent Systems Indian Institute of Information Technology Dharwad Karnataka Dharwad India

The COVID-19 pandemic is a major public health crisis threatening people’s health, well-being, freedom to travel and the global economy. Understanding COVID-19 symptoms for determining the severity of cases is critical. This study aimed to discover interesting facts from the COVID-19 data set considering symptoms, medicines and comorbidity. For data mining research, the semantic web raises new possibilities. Resource Description Framework (RDF) triple format is commonly used to express semantic web data. Association Rule Mining (ARM) is one of the most effective methods of detecting frequent patterns. However, finding potential rules is a difficult task. We propose an improved method that uses ontology with ARM for finding semantic-rich rules from COVID-19 data sets. The outcomes are semantic association rules that are potentially beneficial for decision-makers. We compare our results with one of the most recent approaches in this field to demonstrate the importance of ontology-based methods. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Intelligent Smart Grid Stability Predictive Model for Cyber-Physical Energy systems

引用

computer systems Science & engineering 2023年第2期44卷 1219-1231页

作者： Ashit Kumar Dutta Manal Al Faraj Yasser Albagory Mohammad zeid M Alzamil Abdul Rahaman Wahab Sait Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Kingdom of Saudi Arabia Department of Archives and Communication King Faisal UniversityAl AhsaHofuf31982Kingdom of Saudi Arabia

A cyber physical energy system(CPES)involves a combination of pro-cessing,network,and physical *** smart grid plays a vital role in the CPES model where information technology(IT)can be related to the physical *** the same time,the machine learning(ML)modelsﬁnd useful for the smart grids integrated into the CPES for effective decision ***,the smart grids using ML and deep learning(DL)models are anticipated to lessen the requirement of placing many power plants for electricity *** this aspect,this study designs optimal multi-head attention based bidirectional long short term memory(OMHA-MBLSTM)technique for smart grid stability predic-tion in *** proposed OMHA-MBLSTM technique involves three subpro-cesses such as pre-processing,prediction,and hyperparameter *** OMHA-MBLSTM technique employs min-max normalization as a pre-proces-sing ***,the MBLSTM model is applied for the prediction of stability level of the smart grids in *** the same time,the moth swarm algorithm(MHA)is utilized for optimally modifying the hyperparameters involved in the MBLSTM *** ensure the enhanced outcomes of the OMHA-MBLSTM technique,a series of simulations were carried out and the results are inspected under several *** experimental results pointed out the better outcomes of the OMHA-MBLSTM technique over the recent models.

关键词： Stability prediction smart grid cyber physical energy systems deep learning data analytics moth swarm algorithm

来源：评论

学校读者我要写书评

暂无评论

Analyzing and Mitigating Common Vulnerabilities in Smart Contracts in Web3 Ecosystem: A Comprehensive Study 2

Analyzing and Mitigating Common Vulnerabilities in Smart Con...

引用

2nd IEEE International Conference on Data, Decision and systems, ICDDS 2023

作者： Hegadi, Rajendra Akella, Syam Sankar Karthik Reddy, Koushik Kumar Pavan, C. Indian Institute of Information Technology Dharwad Department of Data Science and Intelligent Systems Karnataka India Indian Institute of Information Technology Dharwad Department of Computer Science and Engineering Karnataka India

ISBN: (纸本)9798350314168

As we enter a new era of decentralized applications and blockchain technology, the issue of Web3 security becomes crucial and requires immediate attention. Given the growing popularity of using smart contracts in web3, it is vital to ensure the protection of digital assets and user data online. This paper aims to examine the different security risks associated with smart contracts in web3 and propose measures to mitigate them. This research article delves into the identification, causes, and potential mitigation steps for common vulnerabilities found in smart contracts in web3. Specifically, we focus on six major vulnerabilities: overflow and underflow, access control vulnerabilities, re-entrancy attacks, price manipulation attacks, signature reply attacks and self-destruct attacks. By comprehensively discussing these vulnerabilities and offering mitigation strategies, this research aims to disseminate the security vulnerabilities in smart contracts in Web3 ecosystem and provides a path way for adoption of blockchain technology. © 2023 IEEE.

关键词： Smart contract

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：