检索结果-内蒙古大学图书馆

The β maps: Strong clustering and distribution results on the complex unit circle

Linear Algebra and Its Applications 2024年 688卷 59-77页

作者： Schiavoni-Piazza, Alec J.A. Meadon, David Serra-Capizzano, Stefano Department of Science and High Technology University of Insubria via Valleggio 11 Como22100 Italy Division of Scientific Computing Department of Information Technology University of Uppsala Lägerhyddsv. 1 Box 337 UppsalaSE-751 05 Sweden

In the current work, we study the eigenvalue distribution results of a class of non-normal matrix-sequences which may be viewed as a low rank perturbation, depending on a parameter β>1, of the basic Toeplitz matrix-sequence {Tn(eiθ)}n∈N, i2=−1. The latter of which has obviously all eigenvalues equal to zero for any matrix order n, while for the matrix-sequence under consideration we will show a strong clustering on the complex unit circle. A detailed discussion on the outliers is also provided. The problem appears mathematically innocent, but it is indeed quite challenging since all the classical machinery for deducing the eigenvalue clustering does not cover the considered case. In the derivations, we resort to a trick used for the spectral analysis of the Google matrix plus several tools from complex analysis. We only mention that the problem is not an academic curiosity and in fact stems from problems in dynamical systems and number theory. Additionally, we also provide numerical experiments in high precision, a distribution analysis in the Weyl sense concerning both eigenvalues and singular values is given, and more results are sketched for the limit case of β=1. © 2024 The Author(s)

关键词： Matrix algebra

来源：评论

学校读者我要写书评

暂无评论

Understanding Catchment Impacts: Enhanced Water Level Prediction with LSTM and Explainable AI 6

Understanding Catchment Impacts: Enhanced Water Level Predic...

引用

6th International Conference on Advancements in computing, ICAC 2024

作者： Wijayaraja, Jaliya L. Gamage, N.D.U. Pallegangoda, P.V.N.U. Priyashantha, Nalaka Weerasekara, W.B.M.R. Abeygunawardhana, Pradeep K.W. Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka Ministry of Defence Disaster Management Division Colombo Sri Lanka

ISBN: (纸本)9798331517878

Flooding is a significant global challenge, impacting millions annually and causing extensive damage to property and infrastructure. This growing threat is exacerbated by climate change and shifting monsoon patterns. Sri Lanka, with its complex geography of central mountains and extensive river basins, faces increasing flood risks due to these climatic changes. To address these pressing issues, the study introduces an LSTM-based approach integrated with explainable AI to enhance flood prediction capabilities. The methodology involves a systematic approach to data collection and structuring, including a context-based pre-processing method tailored to Sri Lanka's specific geographical characteristics. The research presents a comprehensive modeling approach for predicting water levels and incorporates explainable AI techniques to assess the impact of each catchment area on prediction outcomes, aiming to provide greater transparency in the prediction process and a clearer understanding of the model's decision-making. The model achieved a Mean Squared Error (MSE) of 0.000431 and a Root Mean Square Error (RMSE) of 0.0208, indicating relatively low prediction errors and suggesting that the predictions closely approximate the observed water levels. The study effectively assessed the impact of each catchment area and identified the Rathnapura catchment as the primary contributor to flooding in the targeted region of the Kalu Ganga River. This research is crucial for improving flood management strategies and mitigating the risks associated with flooding in vulnerable regions. © 2024 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

The Indian healthcare system turns to digital health: eSanjeevaniOPD as a national telemedicine service

引用

Journal of information technology Teaching Cases 2023年第1期13卷 67-76页

作者： Naithani, Charu Sood, Sanjay P Agrahari, Amit Information Technology & Systems Indian Institute of Management Lucknow India Health Informatics Division Centre for Development of Advanced Computing Mohali India

Healthcare infrastructure in the emerging economies is largely concentrated in their urban areas, and the burgeoning rural population is usually deprived of quality medical care. Telemedicine systems are expected to bridge this gap. This case study documents telemedicine’s significance and allows students to examine India’s national patient-to-doctor telemedicine service, eSanjeevaniOPD. The portal provides free and contactless consultation by a government doctor using video calls. COVID-19 hastened the adoption of eSanjeevaniOPD in the country, but its post-covid future would largely depend on feature innovation, architecture development, and digital strategies. With a total of three million teleconsultations in one year, eSanjeevaniOPD is one of the world’s largest digital healthcare delivery systems. This case provides insight into Indian health infrastructure, summarizes the journey of eSanjeevaniOPD, and raises questions on the digital transformation of the Indian healthcare delivery system. © Association for information technology Trust 2021.

关键词： COVID-19 pandemic Developing Economy Digital Health Digital Tranformation Healthcare Delivery System Indian Public Sector Teaching Case Telemedicine

来源：评论

学校读者我要写书评

暂无评论

TRANSMISSION SYSTEM MODEL IN THE TRACK-VEHICLE RELATIONSHIP BASED ON LONG TERM EVOLUTION technology

引用

Archives of Transport 2023年第2期66卷 89-108页

作者： Chrzan, Marcin Pirosz, Pawel Paś, Jacek Faculty of Transport Electrical Engineering and Information Technology Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland Faculty of Computing and Telecommunications Poznan University of Technology Poznań Poland Division Electronic Systems Exploitations Manager Military University of Technology Warszawa Poland

Because of degradations of the wired infrastructure connecting the element of railroad control systems, and related primarily to their destruction, the use of the radio transmission medium for independent management of railroad traffic control devices is increasingly being considered. An undoubted problem in implying such solutions is the security of transmission in such systems. It should be noted that security at a certain level of transmission is currently already offered by the radio transmission systems themselves, which has also been used in the GSM-R standard. The creation of a separate dedicated system for railroads involves huge expenditures for the design, testing, certification and, finally, construction and implementation of such technology. Therefore, in the opinion of the author of this dissertation, it is possible to use public open radio networks for the needs of railroads, which significantly reduces costs, since such a system is based on existing infrastructure. It is necessary to develop a way of transmitting information that meets the requirements of secure transmission in the sense of railroad traffic control systems. The task is to develop a general model for open radio transmission in traffic control systems based on the latest public radio standard, which is LTE, 5G or Future Railway Mobile Communications System (FRMCS). The article will present the concept of data transmission in the track – vehicle relationship with the use of LTE (Long Term Evolution) technology. It will show the concept of transmission based on the PNEN50159:2011 standard and the results of the tests conducted during control trips on the railway route. The main element that will be subject to the research will include the transmission safety and its delay. The impact of a type of transmission encryption on its delay will be estimated with the assumed blocks of data sent during the transmission. A probability distribution and density functions of the transmission delay pro

关键词： Radio transmission

来源：评论

学校读者我要写书评

暂无评论

Hybrid PLS-ML Authentication Scheme for V2I Communication Networks

Hybrid PLS-ML Authentication Scheme for V2I Communication Ne...

引用

2023 International Symposium on Networks, Computers and Communications, ISNCC 2023

作者： Amin, Hala Kaldari, Jawaher Mohamed, Nora Aman, Waqas Al-Kuwari, Saif College of Science and Engineering Division of Information and Computing Technology Hamad Bin Khalifa University Qatar Foundation Doha Qatar

ISBN: (纸本)9798350335590

Vehicular communication networks are rapidly emerging as vehicles become smarter. However, these networks are increasingly susceptible to various attacks. The situation is exacerbated by the rise in automated vehicles complicates, emphasizing the need for security and authentication measures to ensure safe and effective traffic management. In this paper, we propose a novel hybrid physical layer security (PLS)-machine learning (ML) authentication scheme by exploiting the position of the transmitter vehicle as a device fingerprint. We use a time-of-arrival (ToA) based localization mechanism where the ToA is estimated at roadside units (RSUs), and the coordinates of the transmitter vehicle are extracted at the base station (BS). Furthermore, to track the mobility of the moving legitimate vehicle, we use ML model trained on several system parameters. We try two ML models for this purpose, i.e., support vector regression and decision tree. To evaluate our scheme, we conduct binary hypothesis testing on the estimated positions with the help of the ground truths provided by the ML model, which classifies the transmitter node as legitimate or malicious. Moreover, we consider the probability of false alarm and the probability of missed detection as performance metrics resulting from the binary hypothesis testing, and mean absolute error (MAE), mean square error (MSE), and coefficient of determination R2 to further evaluate the ML models. We also compare our scheme with a baseline scheme that exploits angle of arrival at RSUs for authentication. We observe that our proposed position-based mechanism outperforms the baseline scheme significantly in terms of missed detections. © 2023 IEEE.

关键词： Transmitters

来源：评论

学校读者我要写书评

暂无评论

Advanced Convolutional Neural Networks for Detecting and Quantifying Infections in Coconut Tree Tissue Cultures 6

Advanced Convolutional Neural Networks for Detecting and Qua...

引用

6th International Conference on Advancements in computing, ICAC 2024

作者： Heenkenda, Anusha Chandeep Nadaraja, Sathisrajan Hettiarachchi, Raveesha Dias, Nethya Rathnayake, Samadhi Vidhanaarachchi, Samitha Vidhanaarachchi, Vijitha Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka Coconut Research Institute Tissue Culture Division Lunuwila Sri Lanka

ISBN: (纸本)9798331517878

Coconut tree cultivation is crucial for many tropical cultures, serving as a vital source of nutrition, income, and environmental stability. However, the traditional methods used in coconut tree tissue culture are not without challenges. Issues such as bacterial and fungal infections can significantly hamper the growth and productivity of coconut trees, limiting the effectiveness of tissue culture practices. These infections often go undetected in their early stages, making it difficult for farmers to take timely and effective action. This research proposes a novel approach to improving coconut tree tissue culture by integrating machine learning with agronomical expertise. Through advanced image analysis, the study enhances the identification and severity prediction of bacterial and fungal infections in tissue cultures. These insights lead to actionable recommendations for healthier trees and more efficient cultivation. Integrating technology with traditional expertise marks a significant advancement in addressing challenges faced by coconut farmers, offering a pathway to increased productivity, sustainability, and improved infection management, benefiting both farmers and the broader agricultural community. © 2024 IEEE.

关键词： Coconut tree tissue culture image analysis infection detection infection severity prediction YOLOv8-based Machine Learning

来源：评论

学校读者我要写书评

暂无评论

Integrating Deep Learning for Plant Growth Monitoring and Browning Disease Severity Identification in Coconut Tissue Culture 6

Integrating Deep Learning for Plant Growth Monitoring and Br...

引用

6th International Conference on Advancements in computing, ICAC 2024

作者： Rajapaksha, H.M.S.N. Thiwanka, W.A.D.A. Tissera, Wishalya Vidhanaarachchi, Samitha Kishara, Jenny Vidhanaarachchi, V.R.M. Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka Coconut Research Institute Tissue Culture Division Lunuwila Sri Lanka

ISBN: (纸本)9798331517878

The research aimed to address the inefficiencies and inaccuracies associated with manual plant growth measurement methods at the Coconut Research Institute (CRI). Deep learning algorithms were employed to automate the analysis of plant growth factors, including leaf size, leaf count, root length, and stem growth. Images of coconut tissue culture plants were collected and processed, followed by data augmentation to enhance model accuracy. The YOLOv8 model was utilized for the detection of flasks and the segmentation of leaves and stems. Through iterative training and augmentation, models with improved precision, recall, and Mean Average Precision (mAP) metrics were developed. The model, trained on an augmented dataset with 50 epochs, demonstrated significant improvements in segmentation tasks, achieving a precision of 0.925 and mAP50 of 0.884. For flask detection, a smaller dataset and pre-trained weights led to the selection of a model with a precision of 0.990 and mAP50 of 0.995. Root classification was performed using a YOLOv8 model, with the highest accuracy observed in the sharpened dataset (0.6977). Additionally, four CNN models were tested for browning disease classification, with InceptionV3 achieving the highest accuracy of 96%. The study demonstrates that deep learning models, particularly YOLOv8 and InceptionV3, are effective in automating plant growth monitoring and disease detection, significantly improving the accuracy and efficiency of data collection at the Coconut Research Institute in Sri Lanka(CRISL). The results provide a foundation for the broader application of these models in the agricultural domain, enhancing overall plant health management. © 2024 IEEE.

关键词： Plant diseases

来源：评论

学校读者我要写书评

暂无评论

Recurring Multi-layer Moving Window Approach to Forecast Day-ahead and Week-ahead Load Demand Considering Weather Conditions

引用

Journal of Modern Power Systems and Clean Energy 2022年第6期10卷 1552-1562页

作者： Dao H.Vu Kashem M.Muttaqi Ashish P.Agalgaonkar Arian Zahedmanesh Abdesselam Bouzerdoum School of Electrical Computer and Telecommunications EngineeringUniversity of WollongongWollongongAustralia Information and Computing Technology Division College of Science and EngineeringHamad Bin Khalifa UniversityDohaQatar IEEE

The incorporation of weather variables is crucial in developing an effective demand forecasting model because electricity demand is strongly influenced by weather *** dependence of demand on weather conditions may change with time during a ***,the time stamped weather information is *** this paper,a multi-layer moving window approach is proposed to incorporate the significant weather variables,which are selected using Pearson and Spearman correlation *** multi-layer moving window approach allows the layers to adjust their size to accommodate the weather variables based on their significance,which creates more flexibility and adaptability thereby improving the overall performance of the proposed ***,a recursive model is developed to forecast the demand in multi-step *** electricity demand data for the state of New South Wales,Australia are acquired from the Australian Energy Market Operator and the associated results are reported in the *** results show that the proposed approach with dynamic incorporation of weather variables is promising for day-ahead and week-ahead load demand forecasting.

关键词： Autoregressive(AR)model load forecasting multi-layer moving window Pearson correlation Spearman correlation

来源：评论

学校读者我要写书评

暂无评论

David and Goliath: Asymmetric Advantage in MIoT 6

David and Goliath: Asymmetric Advantage in MIoT

引用

6th International Conference on Advanced Communication Technologies and Networking, CommNet 2023

作者： Oligeri, Gabriele Sciancalepore, Savio Sadighian, Alireza Hamad Bin Khalifa University Qatar Foundation Division of Information and Computing Technology College of Science and Engineering Doha Qatar Eindhoven University of Technology Eindhoven Netherlands

ISBN: (纸本)9798350329391

Modern battlefields are experiencing an increased dependency on smart devices that can sense, process, and communicate data, also known as the Military Internet of Things (MIoT) architecture. While MIoT supports and enhances situation awareness, it opens up new cyber attacks that, when properly designed and deployed, can affect the safety of military *** this work, we discuss the trade-off between two opposite phenomena caused by the massive deployment of MIoT in modern battlefields: situational awareness and asymmetric advantage. We highlight how a resource-constrained adversary can resort to simple and effective tactics to deploy cyber attacks that can have either short-term effects or be detrimental to strategic military objectives. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Trajectory Optimization for UAV-based Communication Systems Powered by Energy Harvesting 100

Trajectory Optimization for UAV-based Communication Systems ...

引用

100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Arkoub, Mohammad Abou Hamdi, Rami Qaraqe, Marwa Hamad Bin Khalifa University Qatar Foundation Division of Information and Computing Technology College of Science and Engineering Doha Qatar Afg College The University of Aberdeen Doha Qatar

ISBN: (纸本)9798331517786

Unmanned aerial vehicles (UAV), also known as drones, is an aircraft without a human pilot onboard and controlled simultaneously by computers remotely. UAVs have been employed in different applications which include fire fighting, security, data coverage, and information transformation. UAVs represent a key technology for next-generation wireless networks that support internet of things (IoT) systems and smart cities. However, one of the bottlenecks of UAV communications systems is power consumption. Most of the UAV energy is consumed on the propulsion part which affects the ability of the UAV to transfer information. Energy harvesting can be incorporated into UAV systems to reduce network operating costs and carbon footprints. Hence, we formulate a trajectory optimization problem for UAV-based communications systems powered by energy harvesting. Then, we provide a solution based on convex optimization to tackle the UAV energy efficiency constraint. Indeed, this paper presents an energy-efficient scheme based on simultaneously powering a UAV with solar energy and optimizing the trajectory to increase the energy efficiency of the drone. This approach has not only been shown to increase the energy efficiency of the drone but also decrease the carbon footprints. Numerical simulations are done to show the efficiency of the proposed scheme. © 2024 IEEE.

关键词： Drones

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：