检索结果-内蒙古大学图书馆

Patient-centric information management in blockchain and interplanetary storage

Journal of Ambient Intelligence and Humanized Computing 2025年第1期16卷 85-96页

作者： Dewangan, Narendra Chandrakar, Preeti Department of Computer Science and Engineering National Institute of Technology Raipur G.E. Road Chhattisgarh Raipur492010 India

In the healthcare sector, the protection of patient information is an essential factor in terms of secrecy and privacy. This information is very useful for industrial and research purposes. Electronic medical records (EMR) hold data related to patients and their treatments. According to GDPR (general data protection regulation), patient information should be anonymous. There should not be any disclosure of patients private information during data transfer. For hiding patients private information, encryption is required. For developing countries, the treatment cost is also a matter for health services. Blockchain technology provides facilities like distributed and immutable data storage and peer-to-peer data transfer. We need cheaper blockchain-based solutions for the healthcare sector. IPFS provides a secure way to store the content of the files in a decentralized manner by using the Merkle tree. By using IPFS with blockchain, we can counter the use of fake medical records or the forge of EMR. In this paper, the interplanetary file system (IPFS) is used to store EMR in compliance with GDPR. We work on the treatment cycle of patients with a blockchain-maintained hospital and doctor. Our proposed system enhances the security and transparency of patients’ treatment information. We compared our proposed system with previously developed systems and provided analytical results in terms of security, privacy, and cost. We implemented our proposed system on a Python-customized blockchain with a customized consensus algorithm. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Number Plate Recognition Using OpenCV 6

Number Plate Recognition Using OpenCV

引用

6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Roopa Chandrika, R. Vanitha, K. Thahaseen, Aafiya Chandramma, R. Neerugatti, Vikram Mahesh, T.R. Faculty of Engineering Department of Computer Science and Engineering Coimbatore India Al-Ameen Engineering College Department of Computer Science and Engineering Erode India Bangalore India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350306613

The advancement of automated number plate recognition (ANPR) systems has garnered noteworthy attention in recent times owing to their diverse applications across multiple domains, including traffic management, parking management, and law enforcement. This paper presents an innovative ANPR method using OpenCV, an open-source computer vision library. Developing ANPR systems is a great fit for OpenCV since it offers a flexible platform for image processing and computer vision tasks. The suggested method effectively detects and recognizes number plates from images and video streams by utilizing OpenCV's capabilities for feature extraction, image preprocessing, and machine learning. Character segmentation, optical character recognitlon (OCR), and licence plate localization are important stages in the process. The ANPR system's accuracy and effectiveness are increased by using these strategies. A variety of real-world datasets, including different lighting conditions, camera angles, and vehicle types, are used in extensive experiments to assess the system's performance. The outcomes show how well the OpenCV-based ANPR system performs in tasks requiring license plate recognition, attaining high accuracy and resilience. Additionally, covered in the paper are possible uses for the ANPR system in security systems, vehicle tracking, and traffic monitoring. To make sure the system is workable in a variety of situations, scalability and real-time implementation are also taken into account. © 2024 IEEE.

关键词： machine learning number plate OpenCV recognition

来源：评论

学校读者我要写书评

暂无评论

Automated Disease Detection and Classification in Jackfruit Leaves: An Efficient Deep Learning-Based Approach 3rd

Automated Disease Detection and Classification in Jackfrui...

引用

3rd International Conference on Trends in Electronics and Health Informatics, TEHI 2023

作者： Saha, Dip Kumar Mahmud Joy, Md. Ashif Reza, Md. Rokonuzzaman Shovon, Reduanul Bari Department of Computer Science and Engineering American International University-Bangladesh Kuratoli Bangladesh Department of Computer Science and Engineering United International University Dhaka Bangladesh Department of Computer Science and Engineering The International University of Scholars Dhaka Bangladesh Department of Computer Science and Engineering Military Institute of Science and Technology Dhaka Bangladesh

ISBN: (纸本)9789819739363

Jackfruit is the national fruit of Bangladesh, and one of the most consumed fruits in India, Sri Lanka, Philippines, Indonesia, Malaysia, Australia, and many more countries. The every year due to diseases jackfruit production stays lower than the expectation. The early identification of these diseases is crucial for agricultural productivity, and our research showcases the effectiveness of deep learning techniques in addressing this issue. This study introduces an innovative approach to detect and classify two common jackfruit leaf diseases, algal spot and black spot, combining the YOLOv8 object detection model and the EfficientNetB7 pre-trained deep convolutional neural network model. The models trained on 6,360 images of those two diseases and our methodology achieved an accuracy of 99.9% on training and 99.5% on testing. This work represents a valuable contribution to agriculture, emphasizing the synergy between cutting-edge technology and age-old challenges, with the potential to positively impact the agricultural industry and global food security. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Citrus fruits

来源：评论

学校读者我要写书评

暂无评论

Integrating the Internet of Things to Protect Electric Vehicle Control Systems from Cyber Attacks

引用

IAENG International Journal of Applied Mathematics 2024年第3期54卷 433-440页

作者： Bhukya, Baddu Naik Venkataiah, V. Kuchibhatla, S. Mani Koteswari, S. Kumari, R.V.S. Lakshmi Raju, Yallapragada Ravi Department of Electrical and Electronics Engineering Prasad V. Potluri Siddhartha Institute of Technology Andhra Pradesh Vijayawada India Department of Computer Science Engineering CMR College of Engineering & Technology Telangana Hyderabad India Department of Electrical and Electronics Engineering ACE Engineering College Telangana Hyderabad India Department of Electronics and Communication Engineering Pragati Engineering College Kakinada India Andhra Pradesh Surampalem India Department of Electrical and Electronics Engineering Gayatri Vidya Parishad College of Engineering for Women Andhra Pradesh Visakhapatnam India Department of Computer Science and Technology Madanapalle Institute of Technology and Science Andhra Pradesh India

The Internet of Things (IoT) facilitates the delivery of intelligent services by sensing, gathering, processing, and exchanging data from millions of linked smart devices. The Internet of Things (IoT), which is based on communication infrastructure, provides real-time cyber-physical device monitoring, control, and sensing, such as electric autos. Traditional communication infrastructure's vulnerability to cyberattacks hampered IoT's capacity to investigate these potential applications. This study proposes an algorithm for monitoring and controlling electric vehicles through the Internet of Things communication network to prevent fake data injection attacks. A state-space model depicts a fully autonomous electric car equipped with a vision system. Intelligent sensors and actuators from the Internet of Things are utilized to monitor and change system conditions, compensating for the large distance between the electric car and the control center. Sensing data is delivered from the vehicle to the central command center via an insecure, attack-prone communication path. The mean square error approach is used to derive states in the most effective state estimation system for comprehending and showing autos. A semi-definite programming approach is used to create an optimal control algorithm to manage the vehicle states. The simulation results show how precisely and successfully the proposed algorithms can foresee and regulate a vehicle's state. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Blockchain and Deep Learning-Based Decentralized Anomaly Detection Framework for VANET 18

Blockchain and Deep Learning-Based Decentralized Anomaly Det...

引用

18th IEEE International Conference on Vehicular Electronics and Safety, ICVES 2024

作者： Jetani, Harshil Patel, Janam Mahida, Nikunjkumar Patel, Man Gupta, Rajesh Tanwar, Sudeep Gupta, Ankur Institute of Technology Nirma University Department of Computer Science and Engineering Gujarat 382481 India Model Institute of Engineering and Technology Department of Computer Science and Engineering J and K India

ISBN: (纸本)9798350387278

The automotive industry is increasing exponentially day by day providing a safer and efficient experience to the consumers. Intelligent Transportation Systems (ITS) has become more crucial with the increasing number of vehicles. Moreover, there is a growing demand for intelligent services like efficient traffic monitoring in vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) communication environments. Vehicular Ad-hoc Network (VANET) represents the demanding and vibrant environment for securing the interaction between the vehicle, RSUs, and pedestrians through the Controller area network (CAN). RF jamming Attacks can be integrated through wireless mediums. The paper presents an improvement in securing VANETs through the combination of Blockchain technology (BT) with Deep learning (DL). In DL-based model, RNN is utilized for detecting and classifying malicious activities. BT ensures secure transactions and automated trust-less interactions using smart contracts. Thus, the non-attack data classified by DL layer is communicated using BT. IPFS is used for storing the information to enhance the scalability while mitigating the maintenance cost of BT. The accuracy achieved by the RNN model during evaluation was 97%. Multiple models were evaluated over metrics like accuracy, precision, recall, F1-score, and ROC-AUC curve. © 2024 IEEE.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Ranking of Documents Through Smart Crawler 3rd

Ranking of Documents Through Smart Crawler

引用

3rd International Semantic Intelligence Conference, ISIC 2023

作者： Dange, Amol S. Swamy, B. Manjunath Shinde, Ashwini B. Department of Computer Science & Engineering Annasaheb Dange College of Engineering & Technology Maharashtra Ashta India Department of Computer Science & Engineering Don Bosco Institute of Technology Bangalore India

ISBN: (纸本)9789819773558

With the exponential boom in information storage on the internet these days, search engines like Google are of extreme significance. The critical issue of a search engine, ranking models are techniques utilized in engines like Google to find relevant pages and rank them in lowering order of relevance. The offline gathering of those papers is important for offering the consumer with more accurate and pertinent findings. Earlier when an end-user issues a question, crawling is the system of retrieving documents from the web. With the internet’s ongoing expansion, the quantity of files that need to be crawled has grown surprisingly. It's crucial to wisely rank the files that want to be crawled in each iteration for any academic or mid-degree organization because the resources for non-stop crawling are constant. Algorithms are created to deal with the crawling pipeline already in the area while bringing the blessings of ranking. These algorithms ought to be quick and effective to save you from turning into a pipeline bottleneck. The proposed method uses the Hamming distance algorithm application. Also, this method incorporates parallel processing by using Kafka in between subtasks. Primarily, based on the Hamming Distance algorithm software, the quest engine is designed for, an effective smart crawler is created that ranks the page that needs to be downloaded in each new release. Evaluating with different present methods, the implemented Hamming Distance technique achieves an excessive accuracy of 99.8%. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Hamming distance

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis for Speech Recognition Using DeepSpeech

Comparative Analysis for Speech Recognition Using DeepSpeech

引用

2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Singh, Chanpreet Singh, Aryan Upreti, Himanshu Bhatt, Shobha Sharma, Kirti Netaji Subhas University of Technology Department of Computer Science and Engineering Delhi India Netaji Subhas University of Technology Department of Computer Science Engineering Delhi India

ISBN: (纸本)9798350378092

The presented work aims to implement speech recognition systems for Hindi and English using advanced deep learning. Enhancing ASR technologies is crucial for improving digital communication's accessibility and efficiency across different linguistic contexts, which is pivotal for fostering broader adoption of technology in multilingual environments. The experiments were conducted using speech corpora such as LJSpeech(English Language) and OpenSLR(Hindi Language). The novelty of this research lies in the tailored adaptation of hybrid deep learning architectures, combining the strengths of Convolutional Neural Networks (CNNs) for feature extraction and Recurrent Neural Networks (RNNs) for sequence learning, specifically configured for the acoustic properties of English and Hindi. These architectures are integrated using connectionist temporal classification to enhance transcription precision without the need for linguistic pre-segmentation. The research findings provide evidence that the implemented hybrid deep learning architectures significantly enhance the performance of ASR systems. By specifically addressing the unique challenges posed by Hindi languages, the models demonstrate improved accuracy in transcription, particularly in environments with varied acoustic properties. The system obtained a minimum WER of 21.89. This approach showcases how advanced neural network configurations can adapt to complex linguistic features, thus reducing the Word Error Rate and improving the overall reliability of speech recognition systems in real-world applications. © 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

Improved Load-Balanced Clustering for Energy-Aware Routing(ILBC-EAR)in WSNs

引用

computer Systems science & engineering 2023年第1期44卷 99-112页

作者： D.Loganathan M.Balasubramani R.Sabitha S.Karthik Department of Electronics and Communication Engineering Info Institute of EngineeringCoimbatore641107India Department of Computer Science and Engineering SNS College of TechnologyCoimbatore641035India

Sensors are considered as important elements of electronic *** many applications and service,Wireless Sensor Networks(WSNs)are involved in significant data sharing that are delivered to the sink node in energy efficient man-ner using multi-hop ***,the major challenge in WSN is the nodes are having limited battery resources,it is important to monitor the consumption rate of energy is very much ***,reducing energy con-sumption can increase the network lifetime in effective *** that,clustering methods are widely used for optimizing the rate of energy consumption among the sensor *** that concern,this paper involves in deriving a novel model called Improved Load-Balanced Clustering for Energy-Aware Routing(ILBC-EAR),which mainly concentrates on optimal energy utilization with load-balanced process among cluster heads and member *** providing equal rate of energy consumption among nodes,the dimensions of framed clusters are ***,the model develops a Finest Routing Scheme based on Load-Balanced Clustering to transmit the sensed information to the sink or base *** evaluation results depict that the derived energy aware model attains higher rate of life time than other works and also achieves balanced energy rate among head ***,the model also provides higher throughput and minimal delay in delivering data packets.

关键词： Wireless sensor networks energy consumption load balanced clustering finest routing

来源：评论

学校读者我要写书评

暂无评论

An Unsupervised Writer Identification Based on Generating Clusterable Embeddings

引用

computer Systems science & engineering 2023年第8期46卷 2059-2073页

作者： M.F.Mridha Zabir Mohammad Muhammad Mohsin Kabir Aklima Akter Lima Sujoy Chandra Das Md Rashedul Islam Yutaka Watanobe Department of Computer Science and Engineering American International University BangladeshDhaka1229Bangladesh Department of Computer Science&Engineering Bangladesh University of Business&TechnologyDhaka1216Bangladesh Department of Computer Science and Engineering University of Asia PacificDhaka1216Bangladesh Department of Computer Science and Engineering University of AizuAizu-Wakamatsu965-8580Japan

The writer identification system identifies individuals based on their handwriting is a frequent topic in biometric authentication and verification *** to its importance,numerous studies have been conducted in various *** have established several learning methods for writer identification including supervised and unsupervised ***,supervised methods require a large amount of annotation data,which is impossible in most *** the other hand,unsupervised writer identification methods may be limited and dependent on feature extraction that cannot provide the proper objectives to the architecture and be *** paper introduces an unsupervised writer identification system that analyzes the data and recognizes the writer based on the inter-feature relations of the data to resolve the uncertainty of the features.A pairwise architecturebased Autoembedder was applied to generate clusterable embeddings for handwritten text ***,the trained baseline architecture generates the embedding of the data image,and the K-means algorithm is used to distinguish the embedding of individual *** proposed model utilized the IAM dataset for the experiment as it is inconsistent with contributions from the authors but is easily accessible for writer identification *** addition,traditional evaluation metrics are used in the proposed ***,the proposed model is compared with a few unsupervised models,and it outperformed the state-of-the-art deep convolutional architectures in recognizing writers based on unlabeled data.

关键词： Writer identification pairwise architecture clusterable embeddings convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

A Bi-directional Gated Recurrent Unit and Long Short-Term Memory based Fake Profile Identification System 1

A Bi-directional Gated Recurrent Unit and Long Short-Term Me...

引用

1st International Conference on Software, Systems and Information technology, SSITCON 2024

作者： Geetha, B. Sushmitha, Boggarapu Ilanchezhian, P. Alabdeli, Haider Ahila, R. Saveetha College of Liberal Arts and Sciences Simats Department of Computer Science Chennai India Avn Institute of Engineering and Technology Hyderabad Department of Computer Science and Engineering India Sona College of Technology Salem Department of Information Technology India College of Technical Engineering the Islamic University Department of Computers Techniques Engineering Najaf Iraq New Prince Shri Bhavani College of Engineering and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350352931

Nowadays, fake profiles are programmatically created online individualities that mislead and influence others, which are done by frequently using stolen photos, fraudulent information, or fictional particulars. Hence, these fake profiles are used for malicious activities such as phishing, social engineering, catfishing, and scattering misinformation. The expansion of fake profiles is increased with triggering more damage than any other cyber-attacks. The solution has been recommended in various ways to detect fake profiles, but the existing models have more overfitting problems. To overcome these issues, a combined model of Bi-directional Gated Recurrent Unit (BiGRU) and Long Short-Term Memory (LSTM) algorithms is proposed. Initially, data preprocessing is done on TwiBot-20 dataset with Natural Language Processing (NLP) and tokenization to remove unnecessary characters. Next, a word embedding technique name called GloVe is used to extract the optimal features, Finally, from the extracted features, the proposed BiGRU-LSTM model gives a precise rate in detecting and classifying fake profiles as human and bot generated. The proposed BiGRU-LSTM gives better results than the other compared existing methods Convolutional Neural Network (CNN) in terms of accuracy, precision, recall, and f1 score of 99.73 %, 98.23 %, 99.56 %, and 99.63 %respectively. © 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

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：