检索结果-内蒙古大学图书馆

An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

引用

computers, Materials & Continua 2024年第5期79卷 2565-2583页

作者： Syed Ayaz Ali Shah Aamir Shahzad Musaed Alhussein Chuan Meng Goh Khursheed Aurangzeb Tong Boon Tang Muhammad Awais Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad CampusAbbottabad22060Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Faculty of Information and Communication Technology University Tunku Abdul RehmanKampar CampusKampar31900Malaysia Centre for Intelligent Signal and Imaging Research University Teknologi PETRONASBandar Seri IskandarPerak32610Malaysia School of Computing Sciences University of East AngliaNorwichNR47TJUK

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood *** task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different ***,the speed of the retinal vessel segmentation system is of utmost *** the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the *** address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical *** algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)*** experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE ***,our algorithmexhibits competitive performance with state-of-the-art ***,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE *** is worth noting that these results were achieved using Matlab scripts containing multiple *** suggests that the processing time can be further reduced by replacing loops with *** the proposed algorithm can be deployed in real time *** summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

关键词： Line detector vessel detection localization mathematical morphology image processing

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Approach for Analysis and Characterization of COVID-19

引用

computers, Materials & Continua 2022年第1期70卷 451-468页

作者： Indrajeet Kumar Sultan S.Alshamrani Abhishek Kumar Jyoti Rawat Kamred Udham Singh Mamoon Rashid Ahmed Saeed AlGhamdi School of Computing Graphic Era Hill UniversityDehradun(UK)India Department of Information Technology College of Computer and Information TechnologyTaif UniversityTaif21944Saudi Arabia School of Computer Science&IT JAIN(to be Deemed University)BangaloreIndia School of Computing Dehradun Institute of TechnologyUttarakhandIndia Department of Computer Engineering Faculty of Science and TechnologyVishwakarma UniversityPuneIndia Department of Computer Engineering College of Computer and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Early diagnosis of a pandemic disease like COVID-19 can help deal with a dire situation and help radiologists and other experts manage human resources more *** a recent pandemic,laboratories perform diagnostics manually,which requires a lot of time and expertise of the laboratorial technicians to yield accurate ***,the cost of kits is high,and well-equipped labs are needed to perform this ***,other means of diagnosis is highly *** is one of the existing methods that finds its use in the diagnosis of *** radiography observes change in Computed Tomography(CT)chest images of patients,developing a deep learning-based method to extract graphical features which are used for automated diagnosis of the disease ahead of laboratory-based *** proposed work suggests an Artificial Intelligence(AI)based technique for rapid diagnosis of COVID-19 from given volumetric chest CT images of patients by extracting its visual features and then using these features in the deep learning *** proposed convolutional neural network aims to classify the infectious and non-infectious SARS-COV2 *** proposed network utilizes 746 chests scanned CT images of 349 images belonging to COVID-19 positive cases,while 397 belong to negative cases of *** experiment resulted in an accuracy of 98.4%,sensitivity of 98.5%,specificity of 98.3%,precision of 97.1%,and F1-score of 97.8%.The additional parameters of classification error,mean absolute error(MAE),root-mean-square error(RMSE),and Matthew’s correlation coefficient(MCC)are used to evaluate our proposed *** obtained result shows the outstanding performance for the classification of infectious and non-infectious for COVID-19 cases.

关键词： Coronavirus covid-19 respiratory infection computed tomography deep neural network

来源：评论

学校读者我要写书评

暂无评论

Simulating a Finite-State Markov Chain for Rayleigh Block-Fading Channel based on its Mathematical Model, and Practical Representation 25

Simulating a Finite-State Markov Chain for Rayleigh Block-Fa...

引用

25th International Arab Conference on Information Technology, ACIT 2024

作者： Attar, Hani Ababneh, Jafar Al-Hihi, Mohammad Rachini, Ali Solyman, Ahmed Zarqa University Faculty of Engineering Zarqa Jordan University of Business and Technology College of Engineering Jeddah21448 Saudi Arabia Zarqa University Faculty of Information Technology Cyber Security Department Zarqa Jordan Erlangen Germany Department of Computer Science and Information Technology Jounieh Lebanon Glasgow Caledonian University School of Computing Engineering and Built Environment Glasgow United Kingdom

ISBN: (纸本)9798331540012

In the proposed paper, simulating the Finite State Markov Chain (FSMC) to be implemented as Rayleigh Block-fading channel. Indeed, FSMC is regarded as a practical fading channel because of its random choice for future transmission probability. Accordingly, this paper introduces the FSMC technology with the theoretical limits and equations;moreover, the uplink and downlink Rayleigh Block-fading channel scenarios are also investigated and supported by the simulation set-up. The results for the Rayleigh fading channel for the Long-Term Evaluation-Advanced network were obtained as an example of the channel's attitude. The findings demonstrate that FSMC provides such reliable results and is suitable for use as a practical fading channel, particularly in terms of burst error behavior. © 2024 IEEE.

关键词： Markov chains

来源：评论

学校读者我要写书评

暂无评论

Metaverse with Mobile Twin Edge computing: Empowering Optimal Efficiency and Accuracy

Metaverse with Mobile Twin Edge Computing: Empowering Optima...

引用

2024 International Conference on engineering and computing, ICECT 2024

作者： Bibi, Asma Noor, Umara Rashid, Zahid International Islamic University Faculty of Computing and Information Technology Department of Software Engineering Islamabad Pakistan Kohsar University Department of Computer Science Murree Pakistan Technology Management Economics and Policy Program College of Engineering Seoul National University Seoul08826 Korea Republic of

ISBN: (纸本)9798350349719

The concept of Digital Twin has been widely used by researchers to represent physical entities in computer-generated reality in the metaverse. In this research, a novel concept of 'Mobile Twin' is coined. Mobile Twin serves as a replica of a mobile device in the virtual environment enabling communication. The purpose of introducing Mobile Twin in the metaverse is to bring mobility and benefits similar to tangible mobile devices while eliminating the need for individual energy sources, storage limitations, resource usage, and efficiency. The true benefits of a mobile twin can be achieved with an architecture where computing nodes are decentralized, data processing is near the network's edge with faster response times and reduced latency. For this purpose, the mobile twin-based applications of metaverse are built over edge computing-based network architecture. This idea introduced the aspect of 'Revolutionary Ultra-low latency (RULL)' in the metaverse. © 2024 IEEE.

关键词： Electric power utilization

来源：评论

学校读者我要写书评

暂无评论

Reversible Watermarking Method with Low Distortion for the Secure Transmission of Medical Images

引用

computer Modeling in engineering & Sciences 2022年第3期130卷 1309-1324页

作者： Rizwan Taj Feng Tao Shahzada Khurram Ateeq Ur Rehman Syed Kamran Haider Akber Abid Gardezi Saima Kanwal School of Computer and Communication Lanzhou University of TechnologyLanzhouChina Faculty of Computing The Islamia University of BahawalpurBahawalpurPakistan Department of Electrical Engineering Government College UniversityLahorePakistan College of Internet of Things Engineering Hohai UniversityChangzhouChina Department of Computer Science COMSATS University IslamabadIslamabadPakistan

In telemedicine,the realization of reversible watermarking through information security is an emerging research ***,adding watermarks hinders the distribution of pixels in the cover image because it creates distortions(which lead to an increase in the detection probability).In this article,we introduce a reversible watermarking method that can transmit medical images with minimal distortion and high *** proposed method selects two adjacent gray pixels whose least significant bit(LSB)is different from the relevant message bit and then calculates the distortion *** use the LSB pairing method to embed the secret matrix of patient record into the cover image and exchange pixel *** results show that the designed method is robust to different attacks and has a high PSNR(peak signal-to-noise ratio)*** MRI image quality and imperceptibility are verified by embedding a secret matrix of up to 262,688 bits to achieve an average PSNR of 51.657 *** addition,the proposed algorithm is tested against the latest technology on standard images,and it is found that the average PSNR of our proposed reversible watermarking technology is higher(i.e.,51.71 dB).Numerical results show that the algorithm can be extended to normal images and medical images.

关键词： LSB reversible watermarking medical images security data distortion

来源：评论

学校读者我要写书评

暂无评论

Personalized Care for Multiple Sclerosis with IoT Wearables and Deep Learning

Personalized Care for Multiple Sclerosis with IoT Wearables ...

引用

2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Vetriselvi, D. Sampathrajan, Rajeshkumar Deepa, A. Sujatha, V. Deepa, P. Pandi Murugan, S. Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai India McKinsey & Company Fort WorthTX United States Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai India Department of Electronics and Communication Engineering Shree Sathyam College of Engineering and Technology Tamil Nadu Salem India Department of Artificial Intelligence and Data Science Agni College of Technology Tamil Nadu Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798350374933

This research work presents a new method for improving individualized treatment for patients with Multiple Sclerosis (MS) by combining Internet of Things (IoT) wearables with deep learning (DL) methods, namely Long Short-Term Memory (LSTM) networks. MS is a long-term autoimmune disorder that affects the central nervous system. It is marked by unexpected episodes of worsening symptoms and periods of improvement, highlighting the need for tailored therapy. The widespread use of IoT devices presents unique possibilities for the ongoing monitoring of many physiological and activity measurements important to the development and symptoms of MS. Using LSTM networks, which are very proficient in analyzing temporal sequences, create a prediction model that may anticipate exacerbations of MS symptoms and customize therapies appropriately. Through the analysis of longitudinal data obtained from IoT devices, our model acquires knowledge about unique patterns of illness development and treatment response. This knowledge allows us to create customized care plans for individuals. These paths include proactive activities such as adjusting medication, making lifestyle changes, and seeking early medical advice. The goal is to reduce the worsening of symptoms, improve the quality of life, and optimize treatment results for individuals with MS. The proposed method shows potential for transforming the treatment of MS by offering proactive and patient-centered therapy adaptable to individual requirements and the dynamics of the illness. © 2024 IEEE.

关键词： Patient treatment

来源：评论

学校读者我要写书评

暂无评论

Towards new realities: Implications of personalized online layers in our daily lives

引用

i-com 2024年第2期23卷 221-229页

作者： Herder, Eelco Stojko, Laura Strecker, Jannis Neumayr, Thomas Yigitbas, Enes Augstein, Mirjam Department of Information and Computing Sciences Utrecht University Utrecht Netherlands Department of Computer Science University of the Bundeswehr Munich Neubiberg Germany Institute of Computer Science University of St. Gallen St. Gallen Switzerland Research Group Personalized Environments and Collaborative Systems University of Applied Sciences Upper Austria Hagenberg Austria Faculty of Electrical Engineering Computer Science and Mathematics Paderborn University Paderborn Germany

We are currently in a period of upheaval, as many new technologies are emerging that open up new possibilities to shape our everyday lives. Particularly, within the field of Personalized Human-computer Interaction we observe high potential, but also challenges. In this article, we explore how an increasing amount of online services and tools not only further facilitates our lives, but also shapes our lives and how we perceive our environments. For this purpose, we adopt the metaphor of personalized 'online layers' and show how these layers are and will be interwoven with the lives that we live in the 'human layer' of the real world. © 2024 the author(s), published by De Gruyter, Berlin/Boston.

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

Dijkstra's Algorithm with Bellman-Ford for Shortest Path Discovery in Big Data 2

Dijkstra's Algorithm with Bellman-Ford for Shortest Path Dis...

引用

2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Karthikeyan, M. Sekar, Satheeshkumar Basha, H. Anwer Epsiba, P. Ganesh, E.N. Meenakshi, B. Srm Institute of Science and Technology School of Computing Faculty of Engineering and Technology Department of Computing Technologies Kattankulathur Tamil Nadu Chennai India Mphasis Corporation ChandlerAZ United States Saveetha College of Liberal Arts & Sciences Simats University Department of Computer Science Tamil Nadu Chennai India Sri Indu College of Engineering and Technology Department of Electronics and Communication Engineering Telangana Hyderabad India Department of Electronics and Communication Engineering Avadi Tamil Nadu Chennai India Sri Sairam Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350368413

Many applications, from logistics to social networks, rely on quickly navigating the shortest pathways inside large-scale graphs. For shortest route finding in huge data settings, this study aims to compare Dijkstra's method with the Bellman-Ford algorithm. Applying these methods to large datasets will allow us to compare their speed, accuracy, and scalability. Graph density and negative weight cycles are two of the intrinsic properties of big data settings that will be used to determine which method is most suited to each. Optimal algorithm selection for given data situations is guided by insights into each algorithm's operational strengths and shortcomings, which are revealed via rigorous testing and performance metrics analysis. This comparison helps real-world applications of each method and provides valuable information for future advancements in large data processing shortest route calculation algorithms. In a study comparing Dijkstra's Algorithm and Bellman-Ford using the RandomGraph1 dataset, the results showed that for nodes 100-500, the former's ms value ranged from 5.2 to 52.3 and the latter's ms value ranged from 6.8 to 68.9. Similarly, for nodes 100-500, the MB value range for Dijkstra's Algorithm was 10.2-46.7 and for Bellman-Ford, it was 14.8-71.9. Data from a different SparseGraph1 dataset reveals that, for values between 100 and 500, Dijkstra's Algorithm has a percentage range of 98.5 to 99.8, while for Bellman-Ford, it varies from 97.2 to 99.3. © 2024 IEEE.

关键词： Graph algorithms

来源：评论

学校读者我要写书评

暂无评论

Metaheuristic Optimization Through Deep Learning Classification of COVID-19 in Chest X-Ray Images

引用

computers, Materials & Continua 2022年第11期73卷 4193-4210页

作者： Nagwan Abdel Samee El-Sayed M.El-Kenawy Ghada Atteia Mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Noha E.El-Attar Tarek Gaber Adam Slowik Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura 35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura 35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityEgypt School of Science Engineeringand EnvironmentUniversity of SalfordUK Faculty of Computers and Informatics Suez Canal UniversityIsmailia41522Egypt Koszalin University of Technology Poland Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

As corona virus disease(COVID-19)is still an ongoing global outbreak,countries around the world continue to take precautions and measures to control the spread of the *** of the excessive number of infected patients and the resulting deficiency of testing kits in hospitals,a rapid,reliable,and automatic detection of COVID-19 is in extreme need to curb the number of *** analyzing the COVID-19 chest X-ray images,a novel metaheuristic approach is proposed based on hybrid dipper throated and particle swarm *** lung region was segmented from the original chest X-ray images and augmented using various transformation ***,the augmented images were fed into the VGG19 deep network for feature *** the other hand,a feature selection method is proposed to select the most significant features that can boost the classification ***,the selected features were input into an optimized neural network for *** neural network is optimized using the proposed hybrid *** experimental results showed that the proposed method achieved 99.88%accuracy,outperforming the existing COVID-19 detection *** addition,a deep statistical analysis is performed to study the performance and stability of the proposed *** results confirm the effectiveness and superiority of the proposed approach.

关键词： Covid-19 feature selection dipper throated optimization particle swarm optimization deep learning

来源：评论

学校读者我要写书评

暂无评论

Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm

引用

computers, Materials & Continua 2023年第8期76卷 2261-2279页

作者： Ayman Khallel Al-Ani Shams Ul Arfeen Laghari Hariprasath Manoharan Shitharth Selvarajan Mueen Uddin Cybersecurity Research Group Faculty of Computing and InformaticsUniversity Malaysia SabahJalan UMSKota KinabaluSabah88400Malaysia National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaGelugorPenang11800Malaysia Department of Electronics and Communication Engineering Panimalar Engineering CollegePoonamalleeChennai600123TamilnaduIndia Department of Computer Science&Engineering Kebri Dehar UniversityKebri Dehar250Ethiopia College of Computing and Information Technology University of Doha for Science and TechnologyDoha24449Qatar

In this paper,the application of transportation systems in realtime traffic conditions is evaluated with data handling *** proposed method is designed in such a way as to detect the number of loads that are present in a vehicle where functionality tasks are computed in the *** to the existing approach,the design model in the proposed method is made by dividing the computing areas into several cluster regions,thereby reducing the complex monitoring system where control errors are ***,a route management technique is combined with Artificial Intelligence(AI)algorithm to transmit the data to appropriate central ***,the combined objective case studies are examined as minimization and maximization criteria,thus increasing the efficiency of the proposed ***,four scenarios are chosen to investigate the projected design’s *** all simulated metrics,the proposed approach provides better operational outcomes for an average percentage of 97,thereby reducing the amount of traffic in real-time conditions.

关键词： Transportation Artificial Intelligence(AI) data-driven Internet of Things(IoT)

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：