检索结果-内蒙古大学图书馆

5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Palarimath, Suresh Maran, Pyingkodi Wilfred Blessing, N.R. Cibi, A. Kavitha, S.J. Steffi, S. College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Oman Kongu Engineering College Department of Computer Application Erode India College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman Virtusa Consulting Service Private Limited Data & Analytics Visualizaation - Delivery Chennai India Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Computer Science and Engineering Chennai India

ISBN: (纸本)9798331518097

Digital twins are a relatively new concept that have lately garnered interest in the industrial sector. Digital twins are virtual models that mirror actual products. In this research, we suggest using the technology of digital twins to the field of healthcare in order to enhance clinical decision support and to provide more individualized treatment for patients. When artificial intelligence (AI) is combined with digital twins, healthcare professionals are able to more effectively analyze large volumes of varied data and increase their ability to make diagnostic and therapeutic decisions. In this research, we provide a conceptual framework for leveraging digital twins and AI to solve existing limits in cancer care, notably endometrial cancer therapy. This research study mainly focuses on cancer care, and more specifically on endometrial cancer treatment. In addition, we analyze the possible challenges and opportunities that may arise throughout the process of integrating this technology in healthcare settings. Our overarching objective is to improve the standard of treatment as well as the clinical results for people who have cancer. © 2024 IEEE.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Vapor growth of V‑doped MoS_(2)monolayers with enhanced B‑exciton emission and broad spectral response

引用

Frontiers of Optoelectronics 2023年第4期16卷 109-120页

作者： Biyuan Zheng Xingxia Sun Weihao Zheng Chenguang Zhu Chao Ma Anlian Pan Dong Li Shengman Li Key Laboratory for Micro-Nano Physics and Technology of Hunan Province State Key Laboratory of Chemo/Biosensing and ChemometricsHunan Institute of Optoelectronic IntegrationCollege of Materials Science and EngineeringHunan UniversityChangsha 410082China College of Advanced Interdisciplinary Studies and Hunan Provincial Key Laboratory of Novel Nano Optoelectronic Information Materials and Devices National University of Defense TechnologyChangsha 410073China Wuhan National Laboratory for Optoelectronics(WNLO) Huazhong University of Science and Technology(HUST)Wuhan 430074China

Dynamically engineering the optical and electrical properties in two-dimensional(2D)materials is of great signifcance for designing the related functions and *** introduction of foreign-atoms has previously been proven to be a feasible way to tune the band structure and related properties of 3D materials;however,this approach still remains to be explored in 2D ***,we systematically demonstrate the growth of vanadium-doped molybdenum disulfde(V-doped MoS_(2))monolayers via an alkali metal-assisted chemical vapor deposition *** transmission electron microscopy demonstrated that V atoms substituted the Mo atoms and became uniformly distributed in the MoS_(2)*** was also confrmed by Raman and X-ray photoelectron ***-dependent photoluminescence spectra clearly revealed the enhanced B-exciton emission characteristics in the V-doped MoS_(2)monolayers(with low doping concentration).Most importantly,through temperature-dependent study,we observed efcient valley scattering of the B-exciton,greatly enhancing its emission *** transport experiments indicated that typical p-type conduction gradually arisen and was enhanced with increasing V composition in the V-doped MoS_(2),where a clear n-type behavior transited frst to ambipolar and then to lightly p-type charge carrier *** addition,visible to infrared wide-band photodetectors based on V-doped MoS_(2)monolayers(with low doping concentration)were *** V-doped MoS_(2)monolayers with distinct B-exciton emission,enhanced p-type conduction and broad spectral response can provide new platforms for probing new physics and ofer novel materials for optoelectronic applications.

关键词： Atomic substitution.V-doped MoS_(2) Distinct B-exciton Broad spectral response

来源：评论

学校读者我要写书评

暂无评论

Next – Gen Driver Monitoring System

Next – Gen Driver Monitoring System

引用

Global Power, Energy and Communication Conference (GPECOM)

作者： Suganiya Murugan Harish Krishnadas S Abiishek G Pradeep Kumar S Rubini B Department of Computing Technologies SRM Institute of Science and Technology Chennai India Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India Department of Electrical and Electronics Engineering Vels Institute of Science Technology and Advanced Studies Chennai India

ISBN: (数字)9798350351088

ISBN: (纸本)9798350351095

the Next Gen Driver Monitoring System utilizes advanced techniques to enhance road safety by detecting driver drowsiness, nodding, and blink patterns. Integrating cutting-edge technology, the system analyzes facial landmarks and eye movements in real-time through sophisticated algorithms. Through the fusion of computer vision and advanced algorithms, it accurately identifies signs of driver fatigue and distraction, providing timely alerts to mitigate potential risks on the road. This research delves into the design, implementation, and evaluation of the system, demonstrating its effectiveness in reducing accidents caused by drowsy or inattentive driving. The Next Gen Driver Monitoring System represents a significant advancement in automotive safety technology, ushering in safer driving experiences.

关键词： Computer vision Vehicle safety Fatigue Road safety Real-time systems Monitoring Vehicles

来源：评论

学校读者我要写书评

暂无评论

Optimization Model for Machine Learning Based Intrusion Detection System (OML-IDS) in Mobile-Edge Computing 4

Optimization Model for Machine Learning Based Intrusion Dete...

引用

4th International Conference on Emerging Trends in Networks and Computer Communications, ETNCC 2024

作者： Kiruthiga, R. Jeyalaksshmi, S. Vanitha, V. Khan, Abdul Azeem Pal, Souvik Kumar, Rahul SRM Institute of Science & Technology Department of Computer Applications Kattankulathur Chennai India Depart. of IT Vels Institute of Science Technology & Advanced Studies Chennai India Sri Sankara Arts and Science College Department of Computer Applications Kanchipuram India Faculty of Islamic Technology Brunei Sister Nivedita University Department of CS and Engineering Kolkata India Lovely Professional University Division of Research and Development Phagwara144411 India KKR and KSR Institute of Technology and Sciences Andhra Pradesh Guntur India

ISBN: (纸本)9798350353266

The Internet of Things (IoT) and 5G communications now primarily use mobile edge computing (MEC). The fundamental concept behind MEC is the deployment of a hierarchy of edge servers with more computational power to handle the computing duties that are being offloaded by low-end IoT edge devices. Some of the security risks in MEC pertain to the application layer, the network layer, the data, and the node. Out main aim is to protect MEC from different cyber-attacks and continuous monitoring of digital assets. The network layer security for MEC is protected by intrusion detection systems (IDSs). We need an updated IDS system capable of detecting modern cyber-attacks as well as monitoring the devices. Thus, this paper proposes an optimization model for MEC settings that functions in conjunction with an OML-IDS, a machine learning-based intrusion detection system. To begin identifying attack patterns in a MEC environment, this model first develops an optimization-based feature selection strategy for selecting an ideal subset of characteristics. For the purpose of intrusion categorization and detection, a hybrid ML algorithm is also used. Enhancing the offloading latency, synchronization time, and turnaround time is necessary if you want to be able to recognize assaults in real time. © 2024 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

Designing a Heuristic Based Hybrid CNN with Attention Mechanism for the Effective Classification of Fish Species

Designing a Heuristic Based Hybrid CNN with Attention Mechan...

引用

International Conference on Inventive Research in Computing Applications (ICIRCA)

作者： M. Bhanumathi B. Arthi Department of Computer Science and Engineering SRM Institute of Science and Technology Department of Computer Science and Engineering Vels Institute of Science Technology & Advanced Studies(VISTAS) Department of Computer Science and Engineering Faculty of Engineering and Technology College of Engineering and Technology SRM Institute of Science and Technology

In recent days, the population of fish species is enormously increased. The measurement of the total population of the fish species is also a complex task. The population of fishes can be easily identified by its classification of variants. But, the categorization of fishes is an annoying task for marine ecologists and biologists. The fishery activities can be easily managed by calculating the total population and size. Several methods are developed for classifying the fish species, but they take more computational time and manpower. These limitations are overthrown by automatic methods. The automatic method monitors the activities of fish and their path. The major advantages of this automatic System are to reduce labor requirement and time. This research study suggests a new fish species categorization model with the help of a Hybrid Convolution Neural Network(CNN) with an Attention Mechanism (HCNN-AM). In the initial phase, the images are aggregated from the standard benchmark dataset. Then, the images are forwarded to the hybrid CNN with an attention mechanism for effectively classifying the fish species, in which the attributes are optimized with the aid of a hybrid Fitness-based Hybrid Rat Swarm with Billiards-inspired Optimization (FH-RSBO). Therefore, the planned method is an efficient substitute for strenuous and time-consuming methods of physical recognition by marine experts. Thus, it becomes the most advantageous task to monitor the fish biodiversity in their natural habitats.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Comparison of COVID-19 Detection using Deep Learning Methods

A Comparison of COVID-19 Detection using Deep Learning Metho...

引用

Electronics and Renewable Systems (ICEARS), International Conference on

作者： S. Pradeep Kumar Suganiya Murugan B. Rubini Electrical and Electronics Engineering Vels Institute of Science Technology and Advanced Studies Chennai Department of Computing Technologies SRM Institute of Science and Technology Chennai

The recognition of covid-19 is major confront in today’s world, specified as sudden increase in spreading of the disease. Hence, identifying this infection in earlier phase facilitates medicinal fields such as doctors, nurses and lab reporters. This article introduces a novel deep learning technique especially Convolutional Neural Network (CNN) by analyzing features in chest input images. Moreover, this proposed Convolutional Neural Network detects the covid-19 disease under several layers and finally performs binary classification that categorizes input images into covid 19 and non-covid patients. Finally, comparisons had made among all models to predict which model diagnose the disease accurately. To evaluate the overall model performance in detection and classification of covid disease, metrics criterias precision, recall and F1-score are evaluated. Validation analysis were completed for quantify the outcomes via performance measures for each model. This proposed comparison attains maximum accuracy of 100% along with least loss as 0.04 that might diminish human inaccuracy in identification procedure.

关键词： COVID-19 Deep learning Training Renewable energy sources Neural networks Predictive models Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Copper-comprising nanocrystals as well-defined electrocatalysts to advance electrochemical CO_(2) reduction

引用

Journal of Energy Chemistry 2021年第11期30卷 71-102,I0002页

作者： Jianfeng Huang Tianyi Yang Ke Zhao Shuangqun Chen Qin Huang Yu Han Multi-scale Porous Materials Center Institute of Advanced Interdisciplinary StudiesSchool of Chemistry and Chemical EngineeringChongqing UniversityChongqing 400044ChinaAdvanced Membranes and Porous Materials CenterKing Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia

In the continuous development of electrochemical CO_(2) reduction (ECR), Cu-based electrocatalysts have received great attention, due to their unique ability to produce high value-added multicarbon products. Of particular interest are various Cu-comprising nanocrystals, not only because they usually show better catalytic properties than bulk materials, but also because their well-defined structures and highly tunable compositions facilitate in-depth mechanistic studies. This review aims to summarize the latest developments of electrocatalysts for ECR, with a focus on systems using Cu-comprising nanocrystals. We first give a general introduction to the field of ECR, covering the significance of this process, reaction mechanisms, catalyst evaluation criteria, and electrolytic cell configurations. Next, we discuss Cu-comprising nanocrystals developed for ECR by categorizing them into four groups: monometallic copper, copper-containing bimetals/multimetals, copper compounds, and copper–metal oxide hybrids;among these groups, we choose representative examples for detailed discussion on the synthetic methods, structural and compositional reaction sensitivities, and catalyst evolution during ECR. In the last section, we outline the challenges in this field from the fundamental and applicative aspects, and give perspectives on the expansion of catalyst varieties, the identification and preservation of active sites, and the exploration of industrially relevant operations for these nanocrystals. We hope the insights provided in this review will inspire the design and development of next-generation catalysts for ECR.

关键词： Copper Nanocrystals Electrocatalysts Carbon-dioxide reduction Restructuring

来源：评论

学校读者我要写书评

暂无评论

Automated Detection of Breast Cancer using Artificial Intelligence Systems

Automated Detection of Breast Cancer using Artificial Intell...

引用

Artificial Intelligence and Knowledge Discovery in Concurrent engineering (ICECONF), International Conference on

作者： Bethanney Janney J Aishvariya Shivani. S Sindu Divakaran S. Krishnakumar Hemalatha R J P. Grace Kanmani prince Department of Biomedical Engineering Sathyabama Institute of Science and Technology Chennai India Departmentof Biomedical Engineering VELS Institute of Science Technology and Advanced Studies(VISTAS) Chennai India

The second leading cause of death for women worldwide remains breast cancer. In particular as they age, all women have a higher risk of acquiring breast cancer. Populations range in their incidence of various forms of breast cancer, and they also differ in their risks of developing breast cancer in general. Hence, it is crucial to determine the degree of the malignancy as soon as possible. Artificial intelligence may be able to classify breast cancer with competence levels on par with those of a doctor. This paper proposes the detection of breast cancer through a deep learning algorithm-based approach that involves segmentation, feature extraction, and grading. A soft computing technique is developed to categorize tumours as benign or malignant using breast histopathology images. To determine the exact grades of breast cancer, the initiation technique uses K-mean clustering-based segmentation, feature extraction, and classification. The segmented region yielded attributes such as correlation, homogeneity, contrast, LBPs (local binary patterns), and energy coefficients. In order to establish which network is better at recognizing the diagnosis of breast malignancy, the Artificial neural network classifier, deep learning architectures of AlexNet and GoogLeNet are contrasted. The AlexNet classification methodology produces accurate solutions than other methods by obtaining 100% accuracy. The proposed enhanced segmentation and classification techniques may help the automated diagnosis system to reduce the number of erroneous diagnoses and increase prediction performance. It could therefore aid clinicians in obtaining an additional opinion and in the early detection of diseases.

关键词： Deep learning Image segmentation Histopathology Artificial neural networks Medical services Feature extraction Breast cancer

来源：评论

学校读者我要写书评

暂无评论

Influence of Heat on Fractionalized Nanofluid with Magnetic Field

引用

International Journal of Applied and Computational Mathematics 2025年第1期11卷 1-15页

作者： Ramzan, Muhammad Amir, Muhammad Abbas, Shajar Nazar, Mudassar Jan, Rashid Al Agha, Afnan AL Garalleh, Hakim Centre for Advanced Studies in Pure and Applied Mathematics Bahauddin Zakariya University Multan Pakistan Department of Civil Engineering College of Engineering Institute of Energy Infrastructure (IEI) Universiti Tenaga National (UNITEN) Putrajaya Campus Jalan IKRAM-UNITEN Selangor Kajang 43000 Malaysia Mathematics Research Center Near East University TRNC Nicosia 99138 Turkey Department of Mathematical Science College of Engineering Universty of Business and Technology Jeddah 21361 Saudi Arabia

Numerous researchers have been drawn to the rheology of non-Newtonian fluids because of their diverse uses in the engineering and manufacturing fields, such as lubrication, plastic processing, and mining. Additionally, the characteristics of magnetohydrodynamics non-Newtonian fluids permit its widespread application in computer hard drives, loudspeakers, magnetic resonance imaging, the administration of magnetic medicines, and magnetic hyperthermia. The novelty of present study is the use of fourier’s and fick’s laws. The current work is focused on the analysis of heat and mass transfer in a magnetohydrodynamics Maxwell nanofluid flows across an inclined vertical plate because of these possible uses. The values of angle of inclination is chosen in the range 0 to π3. From Table 1, the values of nanoparticles lies in the range of 0.012–0.18. Using suitable non-dimensional variables, ordinary differential equations are created from the modeling equations, and the Laplace transform method is used to solve these equations. Semi-analytical solutions for temperature, concentration, Bio-Convection, and velocity are found after employing the Laplace transform approach to address the issue. The study highlights several key outcomes likes velocity of fluid is increased with increasing values of Gr but decreased with increasing values of Pr, M, and maxwell parameter. The effect of increasing values of parameters R, L1, and N1 are seen to suppress the concentration profile. The bioconvection concentration profile increases with Φ but reduced with increasing values of L2. Furthermore, the comparison between ordinary and fractionalized maxwell fluid has been drawn. The application of the unsteady flow of nanofluid over a plate with the CPC operator has the potential to impact a wide range of solar energy-related technologies and innovations, leading to increased efficiency, sustainability, and the advancement of renewable energy solutions. © The Author(s), under exclusive licence

关键词： Chemical reaction CPC derivative Free convection Magnetic field Maxwell fluid

来源：评论

学校读者我要写书评

暂无评论

General strategy for evaluating the d-band center shift and ethanol oxidation reaction pathway towards Pt-based electrocatalysts

引用

Science China Chemistry 2023年第1期66卷 279-288页

作者： Jin-Hong Zheng Guang Li Jun-Ming Zhang Ningyan Cheng Li-Fei Ji Jian Yang Jialin Zhang Bin-Wei Zhang Yan-Xia Jiang Shi-Gang Sun State Key Laboratory of Physical Chemistry of Solid Surfaces Department of ChemistryCollege of Chemistry and Chemical EngineeringXiamen UniversityXiamen 361005China School of Chemistry and Chemical Engineering Chongqing UniversityChongqing 401331China Center of Advanced Energy Technology and Electrochemistry Institute of Advanced Interdisciplinary StudiesChongqing UniversityChongqing 400044China Key Laboratory of Magnetic Molecules&Magnetic Information Materials Ministry of Education School of Chemical and Material ScienceShanxi Normal UniversityTaiyuan 030031China Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of EducationInstitutes of Physical Science and Information TechnologyAnhui UniversityHefei 230039China

The catalytic performance of Pt-based catalysts depends sensitively on their d-band ***,there are still huge challenges to evaluate their d-band centers from experimental technologies,and modulate them to analyze their selectivity in ethanol oxidation reaction(EOR).Here,Pt1Au1alloy supported on the commercial carbon material(Pt_(1)Au_(1)/C)is employed as a typical example to investigate its d-band center shift of surface Pt,and as electrocatalysts to study its selectivity towards ***,a highly reliable in situ Fourier-transform infrared spectroscopy CO-probe strategy is developed to characterize the d-band center shift of surface *** modified electronic effect and site effect of Pt_(1)Au_(1)/C dictated the adsorption configuration of intermediate species and the OH species coverage,thereby influencing its *** importantly,we developed a universal cyclic voltammetry peak differentiation fitting method as an electrochemical analysis technique to investigate CO_(2)selectivity,which is potentially extendable to other Pt-based electrocatalysts.

关键词： PtAu in situ FTIRS d-band center ethanol oxidation reaction CV peak differentiation fitting method

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：