检索结果-内蒙古大学图书馆

2nd International Conference on computing and Data Analytics, ICCDA 2024

作者： Sheeja Kumari, V. Wilfred Blessing, N.R. Palarimath, Suresh Gunasekaran, Hemalatha Poorana Senthilkumar, S. Sutherlin Subitha, G. Saveetha School of Engineering Simats University Department of Computational Intelligence Chennai600 025 India College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Oman Dr. N. G. P Arts and Science College Department of Computer Applications Tamil Nadu Coimbatore India Stella Mary's College of Engineering Department of Computer Science and Engineering Tamil Nadu Kanyakumari India

ISBN: (纸本)9798331542573

This study introduces a novel approach to brain image segmentation by enhancing the VGG16 architecture. Neuroanatomical mapping is a critical aspect of understanding brain structures, and our research focuses on refining the VGG16 model to achieve more accurate segmentation results. We address the intricacies of brain image analysis, optimizing the architecture for the nuanced structures inherent in neuroimaging data. Our enhanced VGG16 model is thoroughly evaluated across diverse datasets, demonstrating superior performance compared to state-of-the-art segmentation methods. The framework proves robust and efficient in accurately delineating complex brain regions. We also delve into the interpretability of the segmentation results, shedding light on the learned features that contribute to the model's efficacy. The significance of our work extends beyond improved segmentation, offering valuable insights into the interpretability of deep learning models in neuroimaging. This research contributes to the broader field of biomedical image analysis and holds promise for applications in neuroscience and medical diagnostics. The proposed enhanced VGG16 framework emerges as a potent tool for advancing our understanding of brain structures and enhancing the capabilities of neuroimaging technologies. © 2024 IEEE.

关键词： Brain mapping

来源：评论

学校读者我要写书评

暂无评论

IoT-Based Water Quality Monitoring and Detection System 1

引用

2nd International Conference on Emerging Trends in Expert Applications and Security, ICETEAS 2023

作者： Kanchana, M. Gopirajan, P.V. Sureshkumar, K. Sudharsanan, R. Suganthi, N. Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chennai603203 India Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Kattankulathur Campus Chennai603203 India Department of Information Technology Saveetha Engineering College Chennai602105 India Department of Information Technology SRM Institute of Science and Technology Ramapuram Chennai600089 India Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai600089 India

ISBN: (数字)9789819919093

ISBN: (纸本)9789819919086

This paper suggests Internet of things (IoT) and Arduino-based tele-water quality monitoring systems integrated with the web application. The most critical component of the Wireless Sensor Network includes a microcontroller for processing the circuit's sensor data, a communication system between and within node communication, and a few other sensors such as pH, Microbial Fuel Cell (MFC), humidity, and temperature. All data is collected at the Arduino (data which is sensed by the sensors) by using remote monitoring and Internet of things technology (ESP8622MOD). The real-time data is transmitted, and that data is displayed by sending through the cloud in a human interface format on a server device (pc/mobile) by the web or mobile applications. The main objective is to get a water monitoring system with high mobility (the ability to check water more freely, the ability to check wherever required), high frequency, and low power (as it is compatible, we can take and check quickly). Therefore, our main objective is that our system will immensely help people with small water reservoirs, water mines, and villagers/ framers with fields to become conscious/aware of polluted water and stop contaminating the water. The deciding parameters of water, whether toxic or drinkable, are decided by the potential level of hydrogen value. If the hydrogen value is less than five, it is acidic, and if the hydrogen value is above 7.5, then it is primary. The MFC sensor, if the analogy sensor, senses any electricity from the cathode and anode ends (0–200 indicates acidic water, 200–300 is normal water, and above 300 is essential to water);by this water, we decide whether water toxic in nature and temperature and humidity also plays a role in determining the quality, it can result in an effect on the level of O2. Also, the capacity of organisms to resist certain pollutants, so different conditions should have different water temperatures. © 2023, The Author(s), under exclusive license to Spr

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Approach for Handling Imbalanced Students' Performance Data 15

Machine Learning Approach for Handling Imbalanced Students' ...

引用

15th International Conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2024

作者： Sujatha, E. Divya, S. Sakthivelan, R.G. Gopirajan, P.V. Thandalam Chennai India Chennai India Department of Computer Science and Engineering Gopalan College of Engineering and Management Bengaluru India Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Kattankulathur campus Chennai India

ISBN: (纸本)9798331300579

Imbalanced student performance data in educational institutions is crucial for any machine learning prediction model. It affects the efficiency of classifiers and challenges the sampling methods for having a more significant number of features. The proposed model was designed to predict the student's performance by comparing the results with popular similar models. The Kaggle dataset having 386 rows and 33 columns of student data, was used in this study. In addition, the Portugal database was considered for experimental analysis, containing 394 students and 19 attributes. It proves that the Random Forest classifier yields the highest accuracy at 84.15% in handling imbalanced datasets. The results show that the SVM-SMOTE is higher accuracy as, 94.76%, than the other sampling methods in predicting the student's performance with various features. © Grenze Scientific Society, 2024.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

AMSFuse:Adaptive Multi-Scale Feature Fusion Network for Diabetic Retinopathy Classification

引用

Computers, Materials & Continua 2025年第3期82卷 5153-5167页

作者： Chengzhang Zhu Ahmed Alasri Tao Xu Yalong Xiao Abdulrahman Noman Raeed Alsabri Xuanchu Duan Monir Abdullah School of Computer Science and Engineering Central South UniversityChangsha410083China School of Humanities Central South UniversityChangsha410083China Department of Human Anatomy and Histology & Embryology Basic Medical SciencesChangsha Health Vocational CollegeChangsha410100China Glaucoma Institute Changsha Aier Eye HospitalChangsha410000China Department of Computer Science and Artificial Intelligence College of Computing and Information TechnologyUniversity of BishaBisha67714Saudi Arabia

Globally,diabetic retinopathy(DR)is the primary cause of blindness,affecting millions of people *** widespread impact underscores the critical need for reliable and precise diagnostic techniques to ensure prompt diagnosis and effective *** learning-based automated diagnosis for diabetic retinopathy can facilitate early detection and ***,traditional deep learning models that focus on local views often learn feature representations that are less discriminative at the semantic *** the other hand,models that focus on global semantic-level information might overlook critical,subtle local pathological *** address this issue,we propose an adaptive multi-scale feature fusion network called(AMSFuse),which can adaptively combine multi-scale global and local features without compromising their individual ***,our model incorporates global features for extracting high-level contextual information from retinal ***,local features capture fine-grained details,such as microaneurysms,hemorrhages,and exudates,which are critical for DR *** global and local features are adaptively fused using a fusion block,followed by an Integrated Attention Mechanism(IAM)that refines the fused features by emphasizing relevant regions,thereby enhancing classification accuracy for DR *** model achieves 86.3%accuracy on the APTOS dataset and 96.6%RFMiD,both of which are comparable to state-of-the-art methods.

关键词： Diabetic retinopathy multi-scale feature fusion global features local features integrated attention mechanism retinal images

来源：评论

学校读者我要写书评

暂无评论

Chaotic Grey Wolf Optimization for Energy-Efficient Clustering and Routing in Wireless Sensor Networks 2

Chaotic Grey Wolf Optimization for Energy-Efficient Clusteri...

引用

2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Almusawi, Muntather Ravindran, Gobinath Parameshachari, B.D. Bhasker, B. Lavanya, N.L. The Islamic University Najaf Iraq SR University Department of Civil Engineering Telangana Warangal India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India REVA University School of Computing and Information Technology Bengaluru India Sapthagiri College of Engineering Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350317558

Wireless Sensor Networks (WSNs), the imperative challenge of energy efficiency takes center stage. This paper delves into inventive methodologies to combat energy depletion in sensor nodes, introducing the Chaotic Grey Wolf Optimization Algorithm (CGWOA) for optimal Cluster Head (CH) selection in WSNs. An evolution strategy and a mutation operation operator, CGWOA aims to amplify energy efficiency, scalability, and minimize network overhead through streamlined clustering. The outcomes underscore CGWOA's potential as a solution for advancing energy-efficient clustering and routing in WSNs, particularly in optimizing CH selection. The ensuing numerical validation underscores CGWOA's revealing an energy consumption of 1100 J, a throughput ratio of 69,785 kbps, 4900 active nodes, and a network lifetime extension to 8021. This comparative analysis shows the emphasis on problems to overcome existing methods like Particle Swarm Optimization for Energy-Efficient Clustering (PSO-EEC), Adaptive Hybrid Clustering Scheme with Grey Wolf Optimization (AHCS-GWO), Hybrid Optimization for Cluster Head Selection (HOCK). © 2024 IEEE.

关键词： Cluster head Clustering Energy consumption Network Lifetime Wireless senor network

来源：评论

学校读者我要写书评

暂无评论

Efficient Certificateless Authenticated Key Agreement for Blockchain-Enabled Internet of Medical Things

引用

Computers, Materials & Continua 2023年第4期75卷 2043-2059页

作者： Chaoyang Li Yanbu Guo Mianxiong Dong Gang Xu Xiu-Bo Chen Jian Li Kaoru Ota College of Software Engineering Zhengzhou University of Light IndustryZhengzhou450002China Department of Sciences and Informatics Muroran Institution of TechnologyMuroran050-8585Japan School of Computing Science and Technology North China University of TechnologyBeijing100144China Information Security Centre State Key Laboratory of Networking and Switching TechnologyBeijing University of Post and TelecommunicationsBeijing100876China

Internet of Medical Things(IoMT)plays an essential role in collecting and managing personal medical *** recent years,blockchain technology has put power in traditional IoMT systems for data sharing between different medical institutions and improved the utilization of medical ***,some problems in the information transfer process between wireless medical devices and mobile medical apps,such as information leakage and privacy *** paper first designs a cross-device key agreement model for blockchain-enabled *** model can establish a key agreement mechanism for secure medical data ***,a certificateless authenticated key agreement(KA)protocol has been proposed to strengthen the information transfer security in the cross-device key agreement *** proposed KA protocol only requires one exchange of messages between the two parties,which can improve the protocol execution ***,any unauthorized tampering of the transmitted signed message sent by the sender can be detected by the receiver,so this can guarantee the success of the establishment of a session key between the strange *** blockchain ledger can ensure that the medical data cannot be tampered with,and the certificateless mechanism can weaken the key escrow ***,the security proof and performance analysis are given,which show that the proposed model and KA protocol are more secure and efficient than other schemes in similar literature.

关键词： Certificateless key agreement authentication blockchain internet of medical things

来源：评论

学校读者我要写书评

暂无评论

Generative Positive-Unlabeled Classification for Hunting Small Open Reading Frames

Generative Positive-Unlabeled Classification for Hunting Sma...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Chen, Jie Liao, Wenbin Wen, Du Li, Jianqiang Wang, Fangzhong Shenzhen University College of Computer Science and Software Engineering China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology China Tianjin University Laboratory of Synthetic Microbiology School of Chemical Engineering & Technology China

ISBN: (纸本)9798350337488

The annotation of Open Reading Frames (ORFs) is a crucial step in gene annotation, as it precisely delineates the specific regions of expressed genes. However, small Open Reading Frames (smORFs), in comparison to ORFs, are shorter in length, exhibit lower expression abundance, and are more challenging to predict. Particularly in the presence of noise in prokaryotic data and limited availability of positive sample data, the difficulty of prediction is amplified. Therefore, it is necessary to study smORF prediction methods. However, current machine learning models use limited data for modeling and overlook the existence of undiscovered positive samples within the negative samples. Additionally, they do not incorporate prior knowledge that can be calibrated to enhance the 3-nt periodicity. This work utilizes a multimodal VAE for data dimensionality reduction and employs a GAN to generate latent vectors for data augmentation. It incorporates PU learning to leverage unknown samples and combines Riboseq data from experiments with and without antibiotic treatment. Additionally, an adversarial training mechanism is employed to enhance the model's robustness. © 2023 IEEE.

关键词： Class Imbalance Data Generation Gene Annotation Positive-Unlabeled Learning

来源：评论

学校读者我要写书评

暂无评论

A Comparison of Cloud Security Mechanisms 2

A Comparison of Cloud Security Mechanisms

引用

2nd International Conference on Automation, computing and Renewable Systems, ICACRS 2023

作者： Saravanan, D. Maragatharajan, M. Nirmala, E. Naveen, P. Francis Saviour Devaraj, A. School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh Kothrikalan India Department of Electrical and Electronics Engnieering KPR Institute of Engineering and Technology Tamil Nadu Coimbatore India Department of IT College of Computing & Information Sciences University of Technology and Applied Sciences Ibri Oman

ISBN: (纸本)9798350340235

Cloud computing is a broad term that can be understood differently depending on the context. Its primary goal is to reduce capital expenses on infrastructure, operating systems, deployment, and storage. The National Institute of Standards and technology (NIST) defines cloud computing as on-demand network access to a shared pool of computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. Cloud computing operates using virtualization and parallel computing principles and provides services like IaaS, PaaS, SaaS, and NaaS. The cloud is classified into public, private, hybrid, and community clouds, each with its own unique features. The major issue of cloud computing is to transfer the data with security breaches. Various security systems are available to protect the data security in the cloud. This research study has discussed some security models like Advanced encryption standard algorithm, Biometric model, Elliptic-curve cryptography with Diffie-Hellman algorithm and a new technique vector-matrix based encryption algorithm. The execution time for these algorithms were compared and results were discussed. © 2023 IEEE.

关键词： Advanced encryption standard algorithm Biometric model Cloud security Decryption Diffie-Hellman algorithm Elliptic-curve cryptography Hybrid cloud vector-matrix based encryption algorithm

来源：评论

学校读者我要写书评

暂无评论

A Comparative Analysis of Joomla, Drupal, Wordpress and ***: Exploring Features, Performance, and Suitability

A Comparative Analysis of Joomla, Drupal, Wordpress and ***:...

引用

2023 IEEE Asia-Pacific Conference on Computer Science and Data engineering, CSDE 2023

作者： Prasad, Ashwin Ashika Sharma, Neeraj Anand Kumar, Anal School of Science and Technology The University of Fiji Department of Computer Science and Mathematics Fiji College of Engineering Science and Technology Fiji National University Department of Computing Sciences and Information System Fiji

ISBN: (纸本)9798350341072

In the dynamic landscape of web development, the judicious choice of platform and structure plays a pivotal role. This comprehensive study conducts a thorough comparison of four prominent web development technologies: ***, Joomla, Drupal, and WordPress. With a primary focus on scrutinizing features, performance, and overall suitability, the research aims to provide valuable insights for developers, businesses, and decision-makers. By objectively evaluating the merits and limitations of each technology, this study seeks to empower stakeholders with essential knowledge, enabling them to make informed decisions at the onset of web development projects. © 2023 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Exploring Machine Learning Applications and Future Prospects in Drug Discovery 10

Exploring Machine Learning Applications and Future Prospects...

引用

10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Prabhu, M. Ramkumar Nancy, P. Rosaline, R.Anto Arockia Pandian, A. Pasumpon Devipriya, A. Arunagiri, Bhuvaneswari Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Electronics and Communication Engineering Tamil Nadu Chennai India Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Campus Chengalpattu India Care College of Engineering Department of Computer Science and Engineering Trichy India Adhiparasakthi Engineering College Department of Technology Tamil Nadu Melmaruvathur India

ISBN: (纸本)9798350353068

This study aims to provide a wide-ranging investigation of the ML-based drug discovery approach by discussing ML methods, results, and outcomes at the drug development process. The methodology covers the steps of data acquisition and preprocessing, feature engineering and selection, model selection and optimization, virtual screening of drugs, prediction of response to drugs, toxicity prediction, integration of multi-omics data, and validation and deployment of an ML model. The study shows superiority of ML-driven methods in terms of speeding up the candidate selection process, prediction of drug target relationships, toxicity prognosis, and integration of multiple molecular datasets for the discovery of new therapeutic targets and biomarkers. While the models might perform seriously in metrics and such, without the model interpretability, generalization, and ethics, there comes necessity to research more and to work together with various experts. A talk is given where a clear link between accurate delivering results, ethical management and regulations as well as a fully transparent reporting as can be done is given for responsible and fair ML technology development in drug discovery is made. If we cast our eye on the future, constant improvements and capital increases in ML based methods are set to achieve a fundamental breakthrough in drug development and individualized medicine and thus ultimately turn patients lives upside down for the better also global scale. © 2024 IEEE.

关键词： Forecasting

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：