检索结果-内蒙古大学图书馆

IEEE International Conference on computer communication and the Internet (ICCCI)

作者： Tuaniai Archevapanich Woranidtha Krungseanmuang Vasutorn Chaowalittawin Posathip Sathaporn Punyisa Chaowalittawin Boonchana Purahong Department of Electronics and Communication Engineering Faculty of Engineering and Architecture Rajamagala University of Technology Suvarnabhumi Nonthaburi Thailand Department of Robotics and Computational Intelligent Systems School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Indusstrail Physics School of Science Bangkok Thailand Department of Computer Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9798350351767

ISBN: (纸本)9798350351774

This paper presents an innovative approach to identifying defects in alloy wheel production by integrating image processing techniques with a mobile application platform. The system receives X-ray alloy images from the factory via mobile phone, processes them using image processing techniques to enhance clarity and readiness for defect detection, and then transmits the processed images to a Django framework via a uniform resource locator (URL). Subsequently, the system detects defects in the images, encodes them in Base64 format, and sends them to the mobile application through an API (Application Program Interface) for display on the user interface. This well-designed system architecture offers manufacturers a comprehensive solution to ensure product quality, reduce costs, and enhance customer satisfaction.

关键词： Uniform resource locators Image processing Metals Wheels systems architecture User interfaces Mobile applications

来源：评论

学校读者我要写书评

暂无评论

Expeditious Diagnosis of Cerebral Aneurysm on MR Brain Angiogram Images Utilizing Soft Computing Techniques

Expeditious Diagnosis of Cerebral Aneurysm on MR Brain Angio...

引用

International Conference on Inventive Computation Technologies (ICICT)

作者： Anjaneya L. H K. Maheswari N. Revathi Siva. K. P Manzoore Elahi M. Soudagar Joshuva Arockia Dhanraj Department of Electrical and Electronics Engineering Bapuji Institute of Engineering and Technology Davangere Karnataka India Department of Computer Science and Engineering CMR Technical Campus Kandlakoya Hyderabad Telangana India Department of Electronics and Communication Engineering Panimalar Engineering College Chennai Tamil Nadu India Department of Computer Science and Business Systems Sri Eshwar College of Engineering Coimbatore Tamil Nadu India Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Techinical Sciences Chennai Tamil Nadu India Department of Mechatronics Engineering Centre for Automation and Robotics (ANRO) Hindustan Institute of Technology and Science Padur Chennai Tamil Nadu India

ISBN: (数字)9798350359299

ISBN: (纸本)9798350359305

It is always a challenging task for radiologists to detect Cerebral Aneurysms (CA). Unenhanced magnetic resonance angiography (MRA) has become a popular screening tool because of its non-invasiveness, lack of contrast, and ionizing radiation. Because of its screening role, MRA requires a high recognition rate. This paper presents Machine Learning (ML) methods for detecting CA in MRA data. MRA scans of normal and aneurysms are collected and evaluated. This research study is divided into two sections: segmentation and classification. First, K-Means Clustering (KMC) is used for aneurysm segmentation from MR images. Second, image classification is done. For that, the appropriate features are retrieved using feature extraction and selection. Then Gray Level Run Length Matrix (GLRLM) is used for feature extraction and the Genetic Algorithm (GA) for feature selection. The GLRLM and GA features are provided independently to the ML models for training and testing. The ML models used in the research work are Artificial Neural Networks (ANN) and Modified Fuzzy C-Means (MFCM). The metrics are employed to evaluate the GLRM and GA features with ANN and MFCM. The combination of GA features with ANN produces the best results when compared to other combinations. The GA with ANN obtains an outstanding 98.33% accuracy, 100% specificity and precision, 96.67% sensitivity, and 98.31% F1 score.

关键词： Training Image segmentation Sensitivity Artificial neural networks Aneurysm Feature extraction Reliability

来源：评论

学校读者我要写书评

暂无评论

GUEST EDITORIAL

引用

China communications 2021年第12期 4-7页

作者： Yingchang Liang Yue Gao Liang Xiao Yulong Zou Guoru Ding the University of Electronic Science and Technology of China the Center for Intelligent Networking and Communications the Artificial Intelligence Research Institute the School of Computer Science and Electronic Engineering Institute for Communication Systems University of Surrey Engineering and Physical Sciences Research Council the IEEE Com Soc Wireless Communication Technical Committee the Department of Information and Communication Engineering Xiamen University the NUPT the College of Communications Engineering PLA Army Engineering University

To meet the rapid growth of mobile communications services, the continuously upgraded wireless networks significantly increase the demand for radio spectrum ***, the spectrum supply is limited, thus triggering the spectrum demand-supply ***, dynamic spectrum sharing emerges as a promising paradigm of enhancing spectrum usage, which has been widely recognized and adopted in commercial wireless standards,

关键词：

来源：评论

学校读者我要写书评

暂无评论

Planning Algorithm for Scientific Workflows: A Cost-Aware and Makespan Approach Based on Locust-Inspired Algorithm

SSRN

引用

SSRN 2023年

作者： Ala’anzy, Mohammed Alaa Othman, Mohamed Hanapi, Zurina Mohd Mohamed, Nader Ahmad, Zulfiqar Almaty040900 Kazakhstan Department of Communication Technology and Networks Universiti Putra Malaysia UPM Selangor D.E. Serdang43400 Malaysia Universiti Putra Malaysia UPM Selangor D.E. Serdang43400 Malaysia Department of Computer Science and Information Systems Pennsylvania Western University California PA15419 United States Department of Computer Science and Information Technology Hazara University Mansehra21300 Pakistan

Job scheduling of scientific workflows in cloud computing is an NP-hard optimisation problem. Efficiently scheduling the tasks in a workflow remains a challenging and open research problem that needs to be addressed. Scientific workflows are data-intensive;whereas, high powered computational resources are needed for handling them. Therefore, cloud computing is an impressive paradigm to handle such massive amounts of data effectively on a pay-as-you-use basis. In cloud computing, cost and execution time limitations are increasingly becoming significant concerns. The challenges of rising cost and time are particularly tough for scientific workflows since they need complex data processing through the communication network. In this paper, we propose a novel planning algorithm based on a locust-inspired algorithm for scientific workflow in a cloud environment for heterogeneous systems. This algorithm aims to optimise the scheduling and execution of tasks in such a way that it can be applied to a wide range of systems, with the goal of minimising overall costs and maximising efficiency. The proposed algorithm generates a task list based on the locust-inspired positioning of the tasks whereas the task list will consist the priority and balance tasks. This task list is used to submit tasks to the heterogeneous virtual machines, taking into account the queue list and the earliest finish times in order to optimise the scheduling of the tasks. Moreover, the child-parent tasks and the link latency are also considered in the scheduling of the tasks. In light to this, the makespan and financial costs have improved in accordance with this method, which has successfully demonstrated its effectiveness. The proposed algorithm is assessed using real-world dataset of data-exhaustive workflows and compared to state-of-the-art algorithms. The performance evaluation result demonstrates that our proposed algorithm could effectively reduce the cost and the makespan of the most of the invest

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

Precise Identification of Anomalies in Brats MR Brain Images using Metaheuristic Optimization Techniques

Precise Identification of Anomalies in Brats MR Brain Images...

引用

International Conference on Inventive Computation Technologies (ICICT)

作者： S. Rosaline K. Maheswari B. Dhanasakkaravarthi Vaishali M Sathish Kannan Nandakumar Selvaraju Department of Electronics and Communication Engineering R.M.K. Engineering College Kavaraipettai Thiruvallur Tamil Nadu India Department of Computer Science and Engineering CMR Technical Campus Kandlakoya Hyderabad Telangana India Department of Mechanical Engineering Agni College of Technology Thazhambur. Chennai Tamil Nadu India Department of Computer Science and Business Systems Sri Eshwar College of Engineering Coimbatore Tamil Nadu India Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Techinical Sciences Chennai Tamil Nadu India Department of Automobile Engineering Hindustan Institute of Technology and Science Padur Chennai Tamil Nadu India

ISBN: (数字)9798350359299

ISBN: (纸本)9798350359305

A condition known as an anomaly occurs when some brain features behave improperly and cause either minor or significant harm to brain cells. Brain tumors, vascular malformations, and inflammatory lesions are among the most well-known abnormalities. A variety of Machine Learning (ML) and Deep Learning (DL) methods are employed in the analysis and detection of brain irregularities. The use of metaheuristic optimization is one such method. Three optimization processes have been chosen for this investigation. The study examines and documents anomaly detection efficiency. A public dataset comprising brain scan images from disparate institutions is employed in the research to analyze the effectiveness of the detection procedure. The three algorithms used are Sequential Minimal Optimization (SMO), Krill Herd Optimization (KHO), and Particle Swarm Optimization (PSO). The three algorithms are fed the preprocessed images for training and testing. From the simulation result, it is established that the KHO algorithm is the best method for identifying brain abnormalities. The KHO achieved an accuracy of 0.96, whereas the competitive model like PSO scored an accuracy value of 0.93 and SMO attained 0.95. The KHO method is quite accurate in detecting the presence of any kind of abnormality.

关键词： Training Magnetic resonance imaging Simulation Metaheuristics Software algorithms Medical services Software

来源：评论

学校读者我要写书评

暂无评论

AI-Driven Yoga Evolution for Advancing Mindfulness and Well-Being Through Cloud-Connected Practices

AI-Driven Yoga Evolution for Advancing Mindfulness and Well-...

引用

Smart Technologies for Sustainable Development Goals (ICSTSDG), International Conference on

作者： Chitra Sabapathy Ranganathan T. Senthil Kumar E. Sivanantham Aarthy. S.T S. Murugan M. Nalini Mphasis Corporation Chandler Arizona USA School of Information Technology and Engineering VIT University Vellore Tamil Nadu India Department of Electronics and Communication Engineering Rajalakshmi Institute of Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Computer Science and Business Systems S.A. Engineering College (Autonomous) Chennai Tamil Nadu India

ISBN: (数字)9798331516284

ISBN: (纸本)9798331516291

Yoga, a conventional practice focused on mindfulness and overall well-being, is significantly changing with Artificial Intelligence (AI) and cloud computing technology. This research examines the potential synergies between AI and yoga to improve mindfulness practices and foster overall wellness in the era of digital technology. AI algorithms produce personalized yoga routines that adapt to individual requirements, talents, and objectives. The routines are constantly improved using feedback from users and physiological data gathered from wearable devices, promoting a personalized and adaptable approach to practicing yoga. The cloud connection allows effortless access to an extensive collection of yoga materials, such as instructional videos, guided meditations, and community support networks. Using AI-powered data analytics, individuals may get valuable information about their development, assess their current yoga practice, identify problem areas, and obtain personalised recommendations for improvement. The conventional practice of yoga is updated and made more attainable, enabling people to develop mindfulness, cope with stress, and improve their general well-being in a progressively connected society.

关键词： Cloud computing Technological innovation Data analysis Human factors Real-time systems Artificial intelligence Wearable devices Biomedical monitoring Sustainable development Videos

来源：评论

学校读者我要写书评

暂无评论

Integrated Sensing and communications Towards Proactive Beamforming in mmWave V2I via Multi-Modal Feature Fusion (MMFF)

arXiv

引用

arXiv 2023年

作者： Zhang, Haotian Gao, Shijian Cheng, Xiang Yang, Liuqing State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China Guangzhou511400 China Guangzhou511400 China Department of Electronic and Computer Engineering the Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Hong Kong

The future of vehicular communication networks relies on mmWave massive multi-input-multi-output antenna arrays for intensive data transfer and massive vehicle access. However, reliable vehicle-to-infrastructure links require exact alignment between the narrow beams, which traditionally involves excessive signaling overhead. To address this issue, we propose a novel proactive beamforming scheme that integrates multi-modal sensing and communications via Multi-Modal Feature Fusion Network (MMFF-Net), which is composed of multiple neural network components with distinct functions. Unlike existing methods that rely solely on communication processing, our approach obtains comprehensive environmental features to improve beam alignment accuracy. We verify our scheme on the Vision-Wireless (ViWi) dataset, which we enriched with realistic vehicle drifting behavior. Our proposed MMFF-Net achieves more accurate and stable angle prediction, which in turn increases the achievable rates and reduces the communication system outage probability. Even in complex dynamic scenarios with adverse environment conditions, robust prediction results can be guaranteed, demonstrating the feasibility and practicality of the proposed proactive beamforming approach. Copyright © 2023, The Authors. All rights reserved.

关键词： Beamforming

来源：评论

学校读者我要写书评

暂无评论

ASSESSING THE ROBUSTNESS OF CRITICAL BEHAVIOR IN STOCHASTIC CELLULAR AUTOMATA

arXiv

引用

arXiv 2022年

作者： Pontes-Filho, Sidney Lind, Pedro Nichele, Stefano Department of Computer Science Oslo Metropolitan University Oslo Norway Department of Computer Science Norwegian University of Science and Technology Trondheim Norway AI Lab - OsloMet Artificial Intelligence Lab Oslo Norway NordSTAR Nordic Center for Sustainable and Trustworthy AI Research Oslo Norway Department of Holistic Systems Simula Metropolitan Centre for Digital Engineering Oslo Norway Department of Computer Science and Communication Østfold University College Halden Norway

There is evidence that biological systems, such as the brain, work at a critical regime robust to noise, and are therefore able to remain in it under perturbations. In this work, we address the question of robustness of critical systems to noise. In particular, we investigate the robustness of stochastic cellular automata (CAs) at criticality. A stochastic CA is one of the simplest stochastic models showing criticality. The transition state of stochastic CA is defined through a set of probabilities. We systematically perturb the probabilities of an optimal stochastic CA known to produce critical behavior, and we report that such a CA is able to remain in a critical regime up to a certain degree of noise. We present the results using error metrics of the resulting power-law fitting, such as Kolmogorov-Smirnov statistic and Kullback-Leibler divergence. We discuss the implication of our results in regards to future realization of brain-inspired artificial intelligence *** Codes 68T01 © 2022, CC BY.

关键词： Stochastic models

来源：评论

学校读者我要写书评

暂无评论

Nodes Number Estimation based on ML for Multi-operator Unlicensed Band Sharing to Extend Indoor Connectivity

Nodes Number Estimation based on ML for Multi-operator Unlic...

引用

IEEE Conference on Wireless communications and Networking

作者： Oluwatobi Baiyekusi Haeyoung Lee Klaus Moessner Department of Computer & Information Sciences University of Strathclyde Glasgow UK School of Physics Engineering and Computer Science University of Hertfordshire Hatfield UK 5GIC & 6GIC Institute for Communication Systems (ICS) University of Surrey Guildford UK Faculty of Electronics and Information Technology University of Technology Chemnitz Germany

Due to ever-increasing data and resource-hungry applications, the need for new spectrum by mobile networks keeps increasing. Unlicensed spectrum is still expected to play a crucial part in meeting the capacity demand for future mobile networks. But if this will be a reality, fair coexistence attained via practical and efficient channel access procedures would be necessary. In designing such channel access schemes, awareness of the number of nodes contending for the channel resource will be required. This paper investigates a node number estimation approach using channel idle time and analysed via machine learning (ML) techniques. When multiple nodes access the same unlicensed channel, varying idle times can be associated with a statistical distribution. In this paper, a statistical distribution of the idle-time slots over the channel is used to characterise and analyse the channel contention based on the number of nodes. Three ML model-based approaches are evaluated and the results confirm the proposed solution’s viability but also reveal the best-performing ML technique of the three, for the task of node number estimations.

关键词： Radio frequency Maximum likelihood estimation Statistical distributions Channel estimation Machine learning Predictive models Data models

来源：评论

学校读者我要写书评

暂无评论

Analog parallel processor for broadband multifunctional integrated system based on silicon photonic platform

引用

Light(science & Applications) 2025年第3期14卷 746-756页

作者： Na Qian Defu Zhou Haowen Shu Ming Zhang Xingjun Wang Daoxin Dai Xiao Deng Weiwen Zou State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghaiChina State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBejingChina State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and EngineeringInternational Research Center for Advanced PhotonicsZhejiang UniversityHangzhouChina

Sharing the hardware platform between diverse information systems to establish full cooperation among different functionalities has attracted substantial ***,broadband multifunctional integrated systems with large operating frequency ranges are challenging due to the bandwidth and computing speed restrictions of electronic ***,we report an analog parallel processor(APP)based on the silicon photonic platform that directly discretizes and parallelizes the broadband signal in the analog *** APP first discretizes the signal with the optical frequency comb and then adopts optical dynamic phase interference to reassign the analog signal into 2N parallel *** photonic analog parallelism,data rate and data volume in each sequence are simultaneously compressed,which mitigates the requirement on each parallel computing ***,the fusion of the outputs from each computing core is equivalent to directly processing broadband *** the proof-of-concept experiment,two-channel analog parallel processing of broadband radar signals and high-speed communication signals is implemented on the single photonic integrated *** bandwidth of broadband radar signal is 6 GHz and the range resolution of 2.69 cm is *** wireless communication rate of 8 Gbit/s is also *** the bandwidth and speed limitations of the single-computing core along with further exploring the multichannel potential of this architecture,we anticipate that the proposed APP will accelerate the development of powerful optoelectronic processors as critical support for applications such as satellite networks and intelligent driving.

关键词： analog parallel processor sharing hardware platform multifunctional integrated systems establish full cooperation different functionalities analog parallel processor app based silicon photonic platform electronic circuitryherewe broadband signal

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：