检索结果-内蒙古大学图书馆

2023 International Conference on Advancement in Computation and computer Technologies, InCACCT 2023

作者： Bavyaa, R. Raja Mohamed, S. Sathyanarayanan, K. Mithun, V. KIT-Kalaignarkarunanidhi Institute of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350396485

Over the years, the healthcare sector has found its boom and requirement increase under the category of donation. The only source of blood and blood components such as plasma and platelets for patients in need of the same is open-handed donors. The issue here is not lack of people willing to donate;rather, it is the difficulty in finding an ardent supporter or donor at the ideal moment. A necessity arises where one should gather several global health groups so that people could be connected during a crisis. A one stop facilitation towards healthcare donation is LIFELINE-A Centralized system for Donation of Blood, Plasma, Platelets and Human Organs. It is an extended web application to unify the needs of the healthcare world by merging in the donation of blood and its components along with specified organ transplant notification and organ donation volunteership. Although there are several applications for blood donation, the major drawback was figured out when issues raised to find out other donors like plasma during an instance of COVID. The main focus is to create a fully functional system that integrates all kinds of health-oriented donation with timely updated information thus by establish a direct connection between the donor and recipient irrespective of the odds of technology at both ends. Distinctive features like, notification specific to the locale range of the patient, exemption according to donor's donation interval, activity status of the donor, authenticity of information furnished, location tracking of the donor until the donor reaches the recipient and further other enhancements are being focused on. © 2023 IEEE.

关键词： Platelets

来源：评论

学校读者我要写书评

暂无评论

Adoption of Blockchain technology in Land Registry Systems 3

Adoption of Blockchain Technology in Land Registry Systems

引用

3rd International Conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Sah, Chandan Kumar Chandavarkar, B.R. National Institute of Technology Karnataka Department of Computer Science & Engineering Surathkal India

ISBN: (纸本)9798350300710

The adoption of blockchain technology in land registry systems has gained significant attention in recent years due to its potential to increase efficiency, transparency, and security. This paper provides an overview of the current state of land registry systems and the challenges they face, in-cluding issues related to fraud, corruption, and a lack of trust. Then it discusses how blockchain technology can address these challenges by providing a decentralized, tamper-proof, and transparent platform for recording land transactions. The paper also examines some of the existing blockchain-based land registry systems and their features, using approaches and methodologies, including the use of smart contracts and digital signatures. Finally, the paper discusses the potential benefits and limitations of adopting blockchain technology in land registry systems and provides recommendations for policymakers and stakeholders interested in implementing these systems. © 2023 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Automatic extraction of sequence diagram semantic information 5

Automatic extraction of sequence diagram semantic informatio...

引用

5th International Conference on Machine Learning, Big Data and Business Intelligence, MLBDBI 2023

作者： Wang, Kai Liu, Wei Mu, Yongan Gao, Sheng Wuhan Institute of Technology Department of Computer Science and Engineering Dcse Wuhan China

ISBN: (纸本)9798350359930

In the realm of software reuse, particular attention has been devoted to the reuse of software design. The UML (Unified Modeling Language) sequence diagram, serving as a dynamic representation, adeptly reflects the evolution and progression of a system. During the software verification phase, it proves instrumental in examining the correctness and consistency of the system. Consequently, the automatic identification and extraction of semantic elements within UML sequence diagrams have become imperative. To address this issue, a Sequence Diagram Extraction (SDE) method based on object detection and text extraction is proposed. This method employs grayscale processing coupled with morphological operations to preprocess distorted images, thereby reducing noise from the original images. The You Only Look Once-version 5 (YOLOv5) algorithm, a deep learning model, is applied to detect each role, object, control focus, and message on the image. Precise localization, segmentation, and cropping of each region are performed. The results are input into the EasyOCR(A text recognition model that has been trained many times) algorithm to execute accurate optical character recognition for every extracted block region. Finally, the detection outcomes undergo semantic merging to obtain comprehensive semantic information for the entire sequence diagram. The effectiveness of the proposed approach is validated through the application of the method to fifty different sequence diagrams, affirming its viability. © 2023 IEEE.

关键词： Software design

来源：评论

学校读者我要写书评

暂无评论

Enhanced capsule generative adversarial network with Blockchain fostered Intrusion Detection System for Enhancing Cyber security in Cloud 2

Enhanced capsule generative adversarial network with Blockch...

引用

2nd International Conference on Smart Technologies and Systems for Next Generation Computing, ICSTSN 2023

作者： Ravi Kanth, R. Prem Jacob, T.P. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350348002

Cloud computing (CC) is vulnerable to existing information technology attacks, since it extends and utilizes information technology infrastructure, applications and typical operating systems. In this manuscript, an Enhanced capsule generative adversarial network (ECGAN) with blockchain based Proof of authority consensus procedure fostered Intrusion detection (ID) system is proposed for enhancing cyber security in CC. The data are collected via NSL-KDD benchmark dataset. The input data is fed to proposed Z-Score Normalization process to eliminate the redundancy including missing values. The pre-processing output is fed to feature selection. During feature selection, extracting the optimum features on the basis of univariate ensemble feature selection (UEFS). Optimum features basis, the data are classified as normal and anomalous utilizing Enhanced capsule generative adversarial networks. Subsequently, blockchain based Proof of authority (POA) consensus process is proposed for improving the cyber security of the data in cloud computing environment. The proposed ECGAN-BC-POA-IDS method is executed in Python and the performance metrics are calculated. The proposed approach has attained 33.7%, 25.7%, 21.4% improved accuracy, 24.6%, 35.6%, 38.9% lower attack detection time, and 23.8%, 18.9%, 15.78% lower delay than the existing methods, like Artificial Neural Network (ANN) with blockchain framework, Integrated Architecture with Byzantine Fault Tolerance consensus, and Blockchain Random Neural Network (RNN-BC) respectively. © 2023 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Deep and Transfer Learning-based Research Article Recommendation System for Healthcare Services 2

Deep and Transfer Learning-based Research Article Recommenda...

引用

2nd International Conference on informatics, ICI 2023

作者： Trivedi, Chinmay Ramoliya, Fenil Gupta, Rajesh Kakkar, Riya Tanwar, Sudeep Agrawal, Smita Nirma University Institute of Technology Department of Computer Science and Engineering Ahmedabad India

ISBN: (纸本)9798350343830

To address the growing volume of confidential biomedical data in the healthcare sector, we propose an inventive Deep Learning (DL) approach for suggesting relevant articles, tailored specifically for the healthcare field. The proposed approach addresses the challenge of information curation by presenting a personalized assistant that aids both patients and medical professionals in navigating the extensive scholarly landscape. In situations where individuals face limitations in accessing healthcare services, such as remote or restricted circumstances, our approach demonstrates significant value in providing direct medical consultation. By acquiring insights into symptoms and potential diseases through medical articles, it provides a foundation for informed decision making. It harnesses advanced pre-Trained models including Bidirectional Encoder Representations from Transformers (BERT), Robustly Optimized BERT Pretraining Approach (RoBERTa), and eXtreme Learning Machine Network (XLNet). These models undergo rigorous training using diverse medical article datasets, extracting nuanced semantics through tokenization, embeddings, self-Attention mechanisms, and transformations. The system's reliability is enhanced by conducting a thorough assessment of optimizers, including Root Mean Square Propagation (RMSprop), AdamW, and Stochastic Gradient Descent (SGD). Finally, the proposed approach is evaluated against various matrices such as accuracy and loss curves, F1, recall, and precision comparison. © 2023 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Hybrid Marine Predators Optimization and Improved Particle Swarm Optimization-Based Optimal Cluster Routing in Wireless Sensor Networks(WSNs)

引用

China Communications 2022年第6期19卷 219-247页

作者： A.Balamurugan Sengathir Janakiraman M.Deva Priya A.Christy Jeba Malar Department of Computer Science&Engineering KPR Institute of Engineering and TechnologyCoimbatoreTamilnaduIndia Department of Information Technology CVR College of EngineeringHyderabadTelanganaIndia Department of Computer Science&Engineering Sri Eshwar College of EngineeringCoimbatoreTamilnaduIndia Department of Information Technology Sri Krishna College of TechnologyCoimbatoreTamilnaduIndia

Wireless Sensor Networks(WSNs)play an indispensable role in the lives of human beings in the fields of environment monitoring,manufacturing,education,agriculture etc.,However,the batteries in the sensor node under deployment in an unattended or remote area cannot be replaced because of their wireless *** this context,several researchers have contributed diversified number of cluster-based routing schemes that concentrate on the objective of extending node survival ***,there still exists a room for improvement in Cluster Head(CH)selection based on the integration of critical *** meta-heuristic methods that concentrate on guaranteeing both CH selection and data transmission for improving optimal network performance are *** this paper,a hybrid Marine Predators Optimization and Improved Particle Swarm Optimizationbased Optimal Cluster Routing(MPO-IPSO-OCR)is proposed for ensuring both efficient CH selection and data *** robust characteristic of MPOA is used in optimized CH selection,while improved PSO is used for determining the optimized route to ensure sink *** specific,a strategy of position update is included in the improved PSO for enhancing the global searching efficiency of *** high-speed ratio,unit speed rate and low speed rate strategy inherited by MPOA facilitate better exploitation by preventing solution from being struck into local optimality *** simulation investigation and statistical results confirm that the proposed MPOIPSO-OCR is capable of improving the energy stability by 21.28%,prolonging network lifetime by 18.62%and offering maximum throughput by 16.79%when compared to the benchmarked cluster-based routing schemes.

关键词： Marine Predators Optimization Algorithm(MPOA) Particle Swarm Optimization(PSO) Optimal Cluster-based Routing Cluster Head(CH)selection Wireless Sensor Networks(WSNs)

来源：评论

学校读者我要写书评

暂无评论

Harnessing the Power of CNN to Detect Late and Early Blight in Potato with Enhanced Accuracy 3

Harnessing the Power of CNN to Detect Late and Early Blight ...

引用

3rd International Conference for Advancement in technology, ICONAT 2024

作者： Tripathi, Kaustubh Taneja, Neeti Ahmed, Ibrar Soni, Dhruv Kumar Taneja, Ashu Noida Institute of Engineering and Technology Department of Computer Science and Engineering Uttar Pradesh Greater Noida India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350354171

Potatoes are a ubiquitous vegetable in every household. Potato planting has been widespread in India for the past decades. However, potato output is being impeded by diseases such as late blight and early blight [1], which result in higher production costs. The objective of this project is to develop a rapid disease detection procedure using deep learning techniques. The goal is to diagnose diseases in potato crops at an early stage, hence increasing potato production. The diagnosis will be done using digital methods. Our primary objective is to identify and diagnose potato diseases by utilizing leaf images that have been enhanced and trained using the Convolutional Neural Network (CNN) technique. This study provides a comprehensive explanation of image processing and deep learning algorithms used in automated systems to detect and classify potato leaf diseases. Image processing is the optimal choice for the detection and diagnosis of agricultural illnesses. This study involves the division of around 2100 images of healthy and afflicted potato leaves, which were obtained via Kaggle and other pre-prepared models. The program forecasts an accuracy of 97.27% when tested with 20% test and validation data and 80% training data. Our results demonstrate that we successfully completed all essential duties in detecting potato diseases. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Fake Account Detection on Social Media using Random Forest Classifier 7

Fake Account Detection on Social Media using Random Forest C...

引用

7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Nikhitha, Kancharla Venkata Bhavya, Karnati Nandini, D. Usha Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397253

As the growth of online social networks increases, everyone is associated and linked with social media. A massive amount of personal data is being attacked and stolen by cyber attackers. These fraudulent profiles also spread negative publicity, false news, and various malicious programs. One of the best ways is to detect these fake accounts, not only the best way but also it is the first step to stopping the negative news and false rumours. There are many efficient ways and techniques to detect these fake accounts. However, these techniques are based on or depend on the account features. The main aim of this research is to examine three machine learning algorithms i.e., random forest, logistic regression, and decision tree. The level of efficiency in the three mentioned methodologies are compared and the highest accuracy has been achieved for random forest classifier. © 2023 IEEE.

关键词： Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

Exposure on Semi-Supervised Regression with Generative Adversarial Networks

Exposure on Semi-Supervised Regression with Generative Adver...

引用

2023 International Conference on Data Science, Agents and Artificial Intelligence, ICDSAAI 2023

作者： Rajeswari, M. Shyamala, P. Chitra, P. Chennai Institute of Technology Department of Computer Science and Engineering Chennai Kundrathur India

ISBN: (纸本)9798350348910

Semi-supervised learning presents a challenge in preparing a classifier in a dataset that has few marked and many unlabelled models. The GAN architecture is expanded by the semi-supervised GAN model, which involves preparing a managed discriminator, an unaided discriminator, and a generator model simultaneously. The result is a managed grouping model that effectively sums up hidden models and a generator model that produces possible instances of pictures from the domain. The aim of research is to study semi-supervised learning problems using GANs for regression. The goal of reverse engineering is to predict the continuum of data given rather than simply splitting the work into a small number of different categories. In the case of autonomous driving, for example, it is very expensive to obtain a sufficient number of written standards covering all driving. In this particular case, we can use the semi-supervised learning method together with the basic structure design, such as the creation of negative networks. The proposed GAN-based semi-supervised writing strategies are centered around addressing the characterization issue. The problem of developing a semi-supervised method using GAN for regression tasks is still unresolved. Reg-GAN has been presented in two different architectures to address this issue. © 2023 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Efficient Fetal Health Monitoring and Classification with Machine Learning 7

Efficient Fetal Health Monitoring and Classification with Ma...

引用

7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Singh, Kabir Shyry, Prayla Franklin, Ramya G Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397253

The goal of the research on fetal health categorization using machine learning is to create a model that can precisely predict the condition of a fetus during pregnancy. This is crucial because prompt action following early identification of fetal health issues might enhance the pregnancy's outcome. This research study suggests classifying fetal health status using machine learning approaches based on ultrasound images and other clinical parameters. To train and test our model, we will gather a sizable dataset of ultrasound images and clinical characteristics from pregnant women. To categorize the state of fetal health, the proposed model will employ machine learning algorithms and image processing techniques. Our approach should categorize fetal health status with a high degree of accuracy, and it will help obstetricians and gynecologists provide better treatment for pregnant patients. © 2023 IEEE.

关键词： Genetic programming

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：