检索结果-内蒙古大学图书馆

IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Sherief Hashima Ehab Mahmoud Mohamed Kohei Hatano Eiji Takimoto Mostafa M. Fouda Zubair Md Fadlullah Computational Learning Theory Team Riken-AIP Fukuoka Japan College of Engineering Prince Sattam Bin Abdulaziz University Wadi Aldwaser Saudi Arabia Department of Informatics Kyushu University Fukuoka Japan Department of Electrical and Computer Engineering Idaho State University Pocatello ID USA Center for Advanced Energy Studies (CAES) Idaho Falls ID USA Department of Computer Science Western University London ON Canada

Recently emerging WiGig systems experience limited coverage and signal strength fluctuations due to strict line-of-sight (LoS) connectivity requirements. In this paper, we address these shortcomings of WiGig communication by exploiting two emerging technologies in tandem, namely the reconfigurable intelligent surface (RIS) and unmanned aerial vehicles (UAVs). In ultra-dense traffic sites (referred to as hotspots) where WiGig nodes or User Devices (UDs) experience complex propagation and non-line-of-sight (non-LoS) environment, we envision the deployment of a UAV-mounted RIS system to complement the WiGig base station (WGBS) to deliver services to the UDs. However, commercially available UAVs have limited energy (i.e., constrained flight time). Therefore, the trajectory of our considered UAV needs to be locally estimated to enable it to serve multiple hotspots while minimizing its energy consumption within the WGBS coverage boundaries. Since this tradeoff problem is computationally expensive for the resource-constrained UAV, we argue that sequential learning can be a lightweight yet effective solution to locally solve the problem with a low impact on the available energy on the UAV. We formally formulate this problem as a contextual multi-armed bandit (CMAB) game. Then, we develop the linear randomized upper confidence bound (Lin-RUCB) algorithm to solve the problem effectively. We regard the UAV as the bandit learner, which attempts to maximize its attainable rate (i.e., the reward) by serving distinct hotspots in its trajectory that we treat as the arms of the considered bandit. The context is defined as the hotspots’ locations provided using GPS (global positioning system) service and the reward history of each hotspot. Our proposal accounts for the energy expenditure of the UAV in moving from one hotspot to another within its battery charge lifetime. We evaluate the performance of our proposal via extensive simulations that exhibit the superiority of our proposed

关键词：

来源：评论

学校读者我要写书评

暂无评论

Classification of Primary and Secondary Brain Tumor Using Extreme Learning Machine

Classification of Primary and Secondary Brain Tumor Using Ex...

引用

2021 International Conference on Data Science, Artificial Intelligence, and Business Analytics, DATABIA 2021

作者： Rahmat, Romi Fadillah Maria Wijaya, Riyan Faza, Sharfina Nababan, Erna Budhiarti Nadi, Farhad Al-Khowarizmi Universitas Sumatera Utara Information Technology Department Medan Indonesia Universitas Sumatera Utara Information Technology Department Medan Indonesia Politeknik Negeri Medan Computer Engineering and Informatics Medan Indonesia Universiti Sains Malaysia School of Computer Science Penang Malaysia Universitas Muhammadiyah Sumatera Utara Department of Information Technology Medan Indonesia

ISBN: (纸本)9781665426800

Brain tumor is a growth of the abnormal tumor cells in the human brain. The brain tumor is classified into two types, namely primary tumor, which starts within the brain, and secondary tumor or known as a brain metastasis tumor. The primary tumors consist of various categories;however, the most common and terminal tumor is Glioblastoma. The difference between the metastasis tumor and the end-of-life phase glioblastoma will be complicated to distinguish if the origin of the tumor cannot be identified. The limitations in differentiating Glioblastoma and Metastasis from MRI images led to the clinical dilemma since both tumors require different further treatments. Therefore, we conducted research to assist and simplify the classification process to identify the primary and secondary brain tumors based on MRI digital image processing. In this study, we proposed a methodology such as Extreme Learning Machine for classification and Gray Level Co-Occurrence Matrix for the feature extraction. The total data used in this study was 100 MRI images with a proportion of 70:30 for training and testing data respectively. The system achieved an accuracy rate of 96.67% in classifying primary and secondary brain tumors. © 2021 IEEE.

关键词： Tumors

来源：评论

学校读者我要写书评

暂无评论

Factors Influencing Metabolite Profiles in Global Arabica Green Coffee Beans: Impact of Continent, Altitude, Post-Harvest Processing, and Variety

SSRN

引用

SSRN 2024年

作者： Kim, Jae-Seong Choi, Jaekue Park, Seong-Eun Kwak, Suryang Cho, Haechang Son, Hong-Seok Department of Biotechnology College of Life Sciences and Biotechnology Korea University Seoul02841 Korea Republic of Department of Computer Science and Engineering College of Informatics Korea University Seoul02841 Korea Republic of Department of Bio and Fermentation Convergence Technology Kookmin University Seoul02707 Korea Republic of Department of Physics College of Science Korea University Seoul02841 Korea Republic of

The metabolites of green coffee beans can be influenced by various factors, including species, variety, geographical origin, and post-harvest processing methods. We simultaneously analyzed 176 global green coffee beans (C. arabica) from various continents, altitudes, post-harvest processing methods, and varieties to comprehensively investigate the primary factors influencing coffee quality through machine learning analysis. Partial least squares-discriminant analysis (PLS-DA) revealed that coffee bean characteristics were differently affected by each factor, and the metabolites associated with the sub-variables in each factor were identified. According to the Random Forest model, the continent had the greatest effect on coffee metabolite profiles, followed by the post-harvest processing, altitude, and variety. Additionally, comprehensive heatmap visualizations, incorporating the four factors, are presented, which can be utilized as valuable information for manufacturing customized coffee beans aligned with consumer preferences. These findings provide comprehensive insights into the association between various factors affecting coffee quality and coffee metabolites. © 2024, The Authors. All rights reserved.

关键词： Metabolites

来源：评论

学校读者我要写书评

暂无评论

Modeling global solar radiation using ambient temperature

引用

Cleaner Energy Systems 2024年 7卷

作者： Ali, Mohamed A. Elsayed, Ashraf Elkabani, Islam Youssef, M. Elsayed Hassan, Gasser E. Computer Based Engineering Applications Department Informatics Research Institute City of Scientific Research and Technological Applications (SRTA-City) New Borg El-Arab City Alexandria 21934 Egypt Department of Mathematics and Computer Science Faculty of Science Alexandria University Alexandria Egypt Faculty of Industrial and Energy Technology Borg Al Arab Technological University Alexandria Egypt Faculty of Computer Science and Engineering AlAlamein International University El Alamein Egypt

Accurate information about solar radiation is regarded as the most important stage in determining the availability of solar energy. As well, it is considered the principal input for various applications of solar energy. Because solar radiation measurements are unavailable at many locations throughout the world, many solar radiation models have been developed to predict global solar radiation. In this regard, this study objects to develop accurate and quick Global Solar Radiation (GSR) models for new locations, which currently lack an accurate model. Additionally, assess the performance of a recently introduced model, one of the best temperature-based models for GSR estimation, in these five new sites. Moreover, the proposed model's generalization capacity is investigated over the whole zone, the Suez Canal Zone, and a comparative analysis of its performance is presented. Models’ estimation is compared to the observed values, and the most common performance indicators are obtained to assess models’ performance. The findings indicate that the developed models in this study can predict global solar radiation accurately. Where the Models’ performance, both the local and general models, are larger than 95 % at all sites except for the local one at Port Said City (coastal site), it is 91 %. Additionally, the developed models have good RMSE and MABE values which range from 0.8 to 1.8 (MJ/m² day⁻¹) and 0.7 to 1.7 (MJ/m² day⁻¹), successively. Besides, they have excellent performance with coefficient of determination (R²) values ranging from 0.95 to 0.98, whereas prior research's ranges are 0.884–0.895 for R² and 2.69–3.367 (MJ/m² day⁻¹) for RMSE. Therefore, the developed models in this study can be utilized for accurate GSR forecast, with their high applicability which may be achieved by combining them with various long- or short-term weather forecasting approaches, that are mostly used t

关键词： Egypt Empirical models Solar energy Solar radiation Suez canal

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of Charging Circuit for Energy Storage System in Multi-Input Non-Isolated Converter with High Gain

Design and Implementation of Charging Circuit for Energy Sto...

引用

IEEE International Conference on Intelligent engineering Systems (INES)

作者： Donya Taheri Ghazanfar Shahgholian Mohammad Mehdi Mirtalaei Amirhosein Mosavi Arman Fathollahi Annamaria Varkonyi-Koczy Department of Electrical Engineering Najafabad Branch Islamic Azad University Najafabad Iran Smart Microgrid Research Center Najafabad Branch Islamic Azad University Najafabad Iran John von Neumann Faculty of Informatics Budapest Hungary University of Public Service Budapest Hungary Department of Electrical and Computer Engineering Aarhus University Aarhus Denmark John von Neumann Faculty of Informatics Obuda University Budapest Hungary

In this study, the topology of a multi-input high-gain non-isolated power converter is suggested. Within this converter, techniques involving voltage multiplier cells and a coupling inductor are utilized. It is possible to use switches that have low voltage stress and, as a result, low conductivity by combining these two methodologies. For applications dealing with clean energy, like green electrical power for public hospitals and etc., that consider a specific type of energy storage system, this particular configuration is an excellent choice. First, the charging performance of the energy storage system is explained, and then, for the design of the multi-input non-isolated power converter with a high voltage gain, the configuration and functionality of the proposed converter are fully investigated. This is accomplished so that the multi-input non-isolated converter can have high voltage gain. The correct operation of the converter is demonstrated through the presentation of a detailed design method, and numerical outcomes are shown for a variety of modes in which the converter can operate effectively. Eventually, to guarantee that the simulation outcomes are accurate, an experimental prototype of the proposed converter has been produced in a laboratory, and the results of the simulation have been validated with those obtained in practice.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Iterative Collaboration Network Guided By Reconstruction Prior for Medical Image Super-Resolution

arXiv

引用

arXiv 2025年

作者： Kui, Xiaoyan Ji, Zexin Zou, Beiji Li, Yang Dai, Yulan Chen, Liming Vera, Pierre Ruan, Su School of Computer Science and Engineering Central South University Changsha410083 China Department of Nuclear Medicine Henri Becquerel Cancer Center Rouen France School of Informatics Hunan University of Chinese Medicine Changsha410208 China Department of Mathematics and Computer Science Ecole Centrale de Lyon Ecully69130 France University of Rouen-Normandy AIMS - QuantIF UR 4108 RouenF-76000 France

High-resolution medical images can provide more detailed information for better diagnosis. Conventional medical image super-resolution relies on a single task which first performs the extraction of the features and then upscaling based on the features. The features extracted may not be complete for super-resolution. Recent multi-task learning, including reconstruction and super-resolution, is a good solution to obtain additional relevant information. The interaction between the two tasks is often insufficient, which still leads to incomplete and less relevant deep features. To address above limitations, we propose an iterative collaboration network (ICONet) to improve communications between tasks by progressively incorporating reconstruction prior to the super-resolution learning procedure in an iterative collaboration way. It consists of a reconstruction branch, a super-resolution branch, and a SR-Rec fusion module. The reconstruction branch generates the artifact-free image as prior, which is followed by a super-resolution branch for prior knowledge-guided super-resolution. Unlike the widely-used convolutional neural networks for extracting local features and Transformers with quadratic computational complexity for modeling long-range dependencies, we develop a new residual spatial-channel feature learning (RSCFL) module of two branches to efficiently establish feature relationships in spatial and channel dimensions. Moreover, the designed SR-Rec fusion module fuses the reconstruction prior and super-resolution features with each other in an adaptive manner. Our ICONet is built with multistage models to iteratively upscale the low-resolution images using steps of 2× and simultaneously interact between two branches in multi-stage supervisions. Quantitative and qualitative experimental results on the benchmarking dataset show that our ICONet outperforms most state-of-the-art approaches. Copyright © 2025, The Authors. All rights reserved.

关键词： Multi-task learning

来源：评论

学校读者我要写书评

暂无评论

GraMDTA: Multimodal Graph Neural Networks for Predicting Drug-Target Associations

GraMDTA: Multimodal Graph Neural Networks for Predicting Dru...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jaswanth K. Yella Sudhir K. Ghandikota Anil G. Jegga Department of Electrical Engineering and Computer Science University of Cincinnati OH USA Division of Biomedical Informatics OH USA Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center OH USA Department of Pediatrics University of Cincinnati OH USA

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Identifying novel drug-target associations is vital for drug discovery. However, the screening of millions of small molecules for a selected target protein is challenging. Several computational approaches have been developed in the past using machine learning methods for computational drug-target association (DTA) prediction, which predominantly uses the structural data of drugs and proteins. Some of these approaches use knowledge graph networks and link prediction. To the best of our knowledge, there have been no approaches that use both structural learning, which offers molecular-based representations, and knowledge graph-based learning, which offers interaction-based representations, for DTA discovery. Based on the premise that multimodal sources of information acting complimentarily could improve the robustness of DTA predictions, we developed GraMDTA, a multimodal graph neural network that learns both structural and knowledge graph representations by utilizing multihead attention to fuse multimodal representations. We compared GraMDTA with other computational approaches for DTA prediction to demonstrate the power of multimodal fusion in the discovery of DTA.

关键词： Proteins Drugs Knowledge engineering Protein engineering Source coding Benchmark testing Sampling methods

来源：评论

学校读者我要写书评

暂无评论

A Hospital Healthcare Monitoring System Using Internet of Things Technologies 6

A Hospital Healthcare Monitoring System Using Internet of Th...

引用

6th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2021

作者： Karvounis, Evaggelos Vavva, Maria Giannakeas, Nikolaos Tzallas, Alexandros T. Smanis, Ioannis Tsipouras, Markos G. Department of Informatics and Telecommunication University of Ioannina Arta Greece Modihive Research and Development P.C. Thessaloniki Greece Dept. of Electrical and Computer Engineering Univ. of Western Macedonia Kozani Greece

ISBN: (纸本)9781665427425

In any hospital health care monitoring system, it is necessary to constantly monitor the patient's physiological parameters. Previous studies report that important parameters of any patient that have to be monitored in hospital are heart rate, respiratory rate, oxygen saturation, temperature, change in systolic blood pressure, motion, posture and its location. This work presents a monitoring system that has the capability to monitor in real-time the physiological parameters of the patient using a comfortable wearable device. A Wireless Sensor Network in collaboration with multiple wireless relay nodes, are responsible for collecting and sending the signals from the wireless sensors to the base station. The data is stored and processed using intelligent techniques in a cloud-based environment. Early warning alerts are automatically sent to the medical staff allowing them to intervene on time and earlier than when using manual vital sign observations. By grouping patients according to risk, medical experts can continuously monitor patients health status and quickly identify those that need their attention most. © 2021 IEEE

关键词： Hospitals

来源：评论

学校读者我要写书评

暂无评论

An optimization-based algorithm for simultaneous shaping of poles and zeros for non-collocated vibration suppression

引用

IFAC-PapersOnLine 2022年第16期55卷 394-399页

作者： Adrian Saldanha Haik Silm Wim Michiels Tomáš Vyhlídal Department of Computer Science KU Leuven Celestijnenlaan 200A 3001 Leuven Belgium Dept. Instrumentation and Control Engineering Faculty of Mechanical Engineering and Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6 Czechia

This article presents a control design method for simultaneous shaping of the poles and zeros of linear time-invariant systems, motivated by the application of non-collocated vibration suppression to flexible multi-body systems. An entire suppression of vibrations at a target mass for a given excitation frequencies can be recast into the problem of assigning zeros of the transfer function from the excitation force to the target mass' position. The design requirement of achieving sufficient damping in the closed loop system combined with suppressing vibrations at the target, leads to the minimization of the spectral abscissa function of the closed loop system as a function of the controller parameters, subject to zero location constraints. These constraints exhibit polynomial dependence on the controller parameters. We present two approaches to solve the optimization problem which are both based on constraint elimination followed by application of an algorithm for non-smooth unconstrained optimization. The design approach is applicable to delay-free models as well as time-delay models of retarded and neutral type. Simulations results illustrate its applicability to a spring-mass-damper system.

关键词： vibration suppression zero placement time-delay systems spectral optimization

来源：评论

学校读者我要写书评

暂无评论

Rostam: A Passwordless Web Single Sign-On Solution Mitigating Server Breaches and Integrating Credential Manager and Federated Identity Systems

SSRN

引用

SSRN 2023年

作者： Mahnamfar, Amin Bicakci, Kemal Uzunay, Yusuf Informatics Institute Istanbul Technical University Istanbul34467 Turkey Computer Engineering Department Istanbul Technical University Istanbul34467 Turkey Securify Information Technology and Security Training Consulting Inc. Ankara06378 Turkey

The challenge of achieving passwordless user authentication is real given the prevalence of web applications that keep asking passwords. Complicating this issue further, in an enterprise environment, a single sign-on (SSO) service is often maintained but not all applications can be integrated with it. We envision a passwordless future which provides a frictionless and trustworthy online experience for users by integrating credential management and federated identity systems. In this regard, our implementation ROSTAM offers a dashboard that presents all applications the user can access with a single click after a passwordless SSO. The security of web passwords on the credential manager is ensured with a Master Key, rather than a Master Password, so that encrypted passwords can remain secure even if stolen from the server. We propose and implement novel techniques for synchronization (pairing) and recovery of this Master Key. We compare our solution to previous work using different evaluation frameworks, demonstrating that our hybrid solution combines the benefits of credential management and federated identity systems. © 2023, The Authors. All rights reserved.

关键词： Authentication

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：