检索结果-内蒙古大学图书馆

N th layer Hierarchical Bidirectional LSTM sign language Interpretation for Hearing Impaired person

Procedia computer science 2025年 258卷 3175-3183页

作者： Harapriya kar Viswanathan P Computer Science and Engineering Vellore Institute of Technology Vellore and 632014 India

Multidimensional investigation into sign language interpreting systems improves recognition effectiveness while tackling the complexities and difficulties that the deaf and mute community faces. However, current models failed to validate accurate signed gestures and lacked expedited prediction analysis. The integration of Bidirectional LSTM models, while leveraging extensive temporal data, often resulted in the amplification of compounding errors in spatiotemporal analysis. To address this issue, we propose an N th layer Bidirectional LSTM (NHBLSTM) to solve compounding errors within a multidimensional sign language interpretation. NHBLSTM employs a co-attention prediction mechanism that refines sequential input at multiple levels, allowing for precise evaluation of dynamic data flow and minimizing errors. The model’s hierarchical bidirectional structure within the N th layer reduces training epochs, while its multi-tiered design enhances the validation of diverse gestures, leading to faster and more accurate predictions. Through experimental comparison with LSTM models, the NHBLSTM approach demonstrated a significant improvement, achieving 99% accuracy, and offering a robust solution for sign language interpretation, particularly benefiting individuals with hearing impairments.

关键词： Sign language Hearing Impaired LSTM BLSTM HBLSTM RNN

来源：评论

学校读者我要写书评

暂无评论

Energy and Bandwidth Based Link Stability Routing Algorithm for IoT

引用

computers, Materials & Continua 2022年第2期70卷 3875-3890页

作者： D.Kothandaraman A.Balasundaram R.Dhanalakshmi Arun Kumar Sivaraman S.Ashokkumar Rajiv Vincent M.Rajesh School of Computer Science and Artificial Intelligence SR UniversityWarangalTSIndia School of Computer Science and Engineering Center for Cyber Physical SystemsVellore Institute of Technology(VIT)ChennaiIndia Department of Computer Science and Engineering KCG College of TechnologyChennaiIndia School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiIndia Department of Computer Science and Engineering Saveetha School of EngineeringSIMATSChennaiIndia

Internet of Things(IoT)is becoming popular nowadays for collecting and sharing the data from the nodes and among the nodes using internet ***,some of the nodes in IoT are mobile and dynamic in *** maintaining the link among the nodes,efficient bandwidth of the links among the mobile nodes with increased life time is a big challenge in IoT as it integrates mobile nodes with static nodes for data *** such networks,many routing-problems arise due to difficulties in energy and bandwidth based quality of *** to the mobility and finite nature of the nodes,transmission links between intermediary nodes may fail frequently,thus affecting the routing-performance of the network and the accessibility of the *** existing protocols do not focus on the transmission links and energy,bandwidth and link stability of the nodes,but node links are significant factors for enhancing the quality of the *** stability helps us to define whether the node is within or out of a coverage *** paper proposed an Optimal Energy and bandwidth based Link Stability Routing(OEBLS)algorithm,to improve the link stable route with minimized error rate and *** this paper,the optimal route from the source to the sink is determined based on the energy and bandwidth,link stability *** the existing routes,the sink node will choose the optimal route which is having less link stability *** stable link is determined by evaluating link stability value using distance and ***-energy of the node is estimated using the current energy and the consumed *** energy is estimated using transmitted power and the received *** bandwidth in the link is estimated using the idle time and channel capacity with the consideration of probability of collision.

关键词： Link stability internet of things optimal energy optimal bandwidth residual energy

来源：评论

学校读者我要写书评

暂无评论

ASSESSING THE ACCURACY AND ETHICAL IMPLICATIONS OF AUTOMATED CRIMINAL DETECTION USING A DEEP LEARNING APPROACH

ASSESSING THE ACCURACY AND ETHICAL IMPLICATIONS OF AUTOMATED...

引用

2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Jagadeesan, S. Sujigarasharma, K. Manjula, R. Vetriselvi, T. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Department of IOT School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9798350305708

This study examines the accuracy and ethical implications of using convolutional neural networks (CNN) for automated crime detection. A CNN model was trained on a dataset of criminal mugshots to identify potential criminal behaviour based on facial features. This study analyzed the performance of the model and achieved a high accuracy rate in identifying criminals. However, the ethical implications of automated criminal detection are also explored, including bias, privacy and human rights violations. The findings of this study highlight the need for caution and ethical considerations when implementing automated crime detection technologies. It is important to ensure that such technologies are not used to violate the rights of individuals or perpetuate societal biases. © 2023 IEEE.

关键词： CNN Criminal detection Face detection Machine learning

来源：评论

学校读者我要写书评

暂无评论

Smart contract token-based privacy-preserving access control system for industrial Internet of Things

引用

Digital Communications and Networks 2023年第2期9卷 337-346页

作者： Weizheng Wang Huakun Huang Zhimeng Yin Thippa Reddy Gadekallu Mamoun Alazab Chunhua Su Department of Computer Science City University of Hong KongHong Kong SAR999077China Division of Computer Science University of AizuFukushima965-8580Japan School of Information Technology and Engineering Vellore Institute of TechnologyTamil NaduIndia College of Engineering IT and EnvironmentCharles Darwin UniversityAustralia School of Computer Science and Cyber Engineering Guangzhou UniversityChina

Due to mobile Internet technology's rapid popularization,the Industrial Internet of Things(IIoT)can be seen everywhere in our daily *** IIoT brings us much convenience,a series of security and scalability issues related to permission operations rise to the surface during device ***,at present,a reliable and dynamic access control management system for IIoT is in urgent *** till now,numerous access control architectures have been proposed for ***,owing to centralized models and heterogeneous devices,security and scalability requirements still cannot be *** this paper,we offer a smart contract token-based solution for decentralized access control in IIoT ***,there are three smart contracts in our system,including the Token Issue Contract(TIC),User Register Contract(URC),and Manage Contract(MC).These three contracts collaboratively supervise and manage various events in IIoT *** also utilize the lightweight and post-quantum encryption algorithm-Nth-degree Truncated Polynomial Ring Units(NTRU)to preserve user privacy during the registration ***,to evaluate our proposed architecture's performance,we build a prototype platform that connects to the local ***,experiment results show that our scheme has achieved secure and dynamic access control for the IIoT system compared with related research.

关键词： Blockchain Privacy preservation Smart contract Industrial IoT

来源：评论

学校读者我要写书评

暂无评论

Breast Cancer Prediction Using Artificial Intelligence technology 4

Breast Cancer Prediction Using Artificial Intelligence Techn...

引用

4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Akila, V. Christaline, J. Anita Srm Institute of Science and Technology Vadapalani Dept. of Electronics and Communication Engineering Chennai India Vellore Institute of Technology School of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350343670

The aim of the project is to compare the performance of four different machine learning algorithms for breast cancer prediction such as decision tree, logistic regression, XG boost, and CAT boost. We used a dataset of patient medical records containing various clinical factors to train and test the algorithms. Accurate diagnosis and early detection are essential for enhancing patient outcomes. Data mining is a prominent tool in the healthcare industry for processing massive amounts of data. To examine massive amounts of complicated medical data, researchers use a variety of data mining and machine learning approaches. The use of these strategies can help medical practitioners forecast the onset of breast cancer. © 2024 IEEE.

关键词： Algorithms Breast cancer Data mining Machine Learning

来源：评论

学校读者我要写书评

暂无评论

Assessing the Feasibility and Scalability of Using Spark for Identifying Tip Burn Diseases in Strawberry Leaves 2nd

Assessing the Feasibility and Scalability of Using Spark for...

引用

2nd International Conference on Advances in Data-driven Computing and Intelligent Systems, ADCIS 2023

作者： Prathyuma, V. Hareesh Teja, S. Suganeshwari, G. Divya, S. School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai600127 India Centre for Advanced Data Science Vellore Institute of Technology Tamil Nadu Chennai6000127 India

ISBN: (纸本)9789819995233

Tip burn is a common calcium deficiency symptom found in strawberry leaves, which can deform, fold over, and discolor the tips or edges of budding leaves. To help farmers detect diseases early and manage their crops more effectively, this work aims to build a solution that employs image processing and machine learning techniques to detect tip burn in strawberry leaves on a farm. The proposed work utilizes a dataset of 1431 images of ‘diseased’ and ‘healthy’ strawberry leaves. A Random Forest classifier, which is an ensemble learning model built on decision trees, CNN, or convolutional neural networks, and VGG-16, a transfer learning-based approach were all fitted in the PySpark environment to assess the feasibility and scalability of using Spark for distributed computing. The results indicate the deep learning approaches outperformed the traditional machine learning approach in accuracy and execution speed, making them a promising tool for identifying tip burn diseases in strawberry leaves. Overall, this work provides farmers with a fast, feasible, and reliable method for detecting tip burn, aiding in crop management, and reducing crop loss. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Optimal feature extraction and classification-oriented medical insurance prediction model: machine learning integrated with the internet of things

引用

International Journal of computers and Applications 2022年第3期44卷 278-290页

作者： Chowdhury, Subrata Mayilvahanan, P. Govindaraj, Ramya School of Computer Science Vels Institute of Science Technology & Advanced Studies TN Chennai India School of Information Technology and Engineering Vellore Institute of Technology TN Vellore India

This paper plans to develop an effective machine learning system integrated with the Internet of Things (IoT) to predict the health insurance amount. IoT in healthcare enables interoperability, machine-to-machine communication, information exchange, and data movement that make healthcare service delivery effective. The model includes three phases (a) Feature Extraction, and (b) Weighted Feature Extraction, and (c) Prediction. The feature extraction process computes two statistical measures: First Order Statistics like mean, median, standard deviation, the maximum value of entire data, and minimum value of entire data, and Second-Order Statistics like Kurtosis, skewness, correlation, and entropy. The prediction process deploys a renowned machine learning algorithm called Neural Network (NN). As the main contribution, the weighted feature vector is developed here, where the weight optimally tuned by Modified Whale Optimization Algorithm (WOA). Also, the contribution relies on NN, where the training algorithm replaced with the same modified WOA for weight update. The modified WOA developed here is termed as Fitness dependent Randomized Whale Optimization Algorithm (FR-WOA). At last, the valuable experimental analysis using three datasets confirms the efficient performance of the suggested model. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Dynamic Modeling and Quantum-Enhanced Forecasting of Multi-Seasonal Energy Prices in Simulated Microgrid Environments

引用

IEEE Access 2025年 13卷 90362-90388页

作者： Dash, Ritesh Sinha, Anupa Jyotheeswara Reddy, K. Dhanamjayulu, C. Kamwa, Innocent Kalinga University Research Scholar Computer Science Engineering Raipur India Kalinga University Computer Science Engineering Raipur India REVA University School of Electrical and Electronics Engineering Bangalore India Vellore Institute of Technology School of Electrical Engineering Vellore632014 India Laval University Department of Electrical Engineering and Computer Engineering Quebec G1V 0A6 Canada

The study address the challenge of forecasting per unit energy prices in a microgrid environment consisting of solar and hydro power resources under multi-seasonal *** deep learning techniques such as LSTM,GRU and ESN often struggle with non-linear dependencies and volatility in energy market. To overcome these we propose a hybrid framework incorporating Adiabatic Quantum Computing (AQC) for electricity price forecasting. The proposed AQC model encodes-32 system and market related variables into quantum states and applies adiabatic evolution to derive optimized price prediction. Simulation results using real microgrid data set-up based on HIL shows that AQC reduces forecasting error by 17.03% compared to LSTM, 14.29% to GRU and 13.88% to ESN over 24-hrs and 48-hrs horizons. The enhanced accuracy and robustness of the quantum assisted model demonstrates its potential for next generation energy market forecasting and decisions making *** entire framework is tested using a synthetic microgrid dataset designed to emulate real-world seasonal and operational dynamics. While this enables controlled validation of the models, the generalizability of the results to real world deployment requires further empirical evaluations on physical microgrid data set. © 2013 IEEE.

关键词： Qubits

来源：评论

学校读者我要写书评

暂无评论

Opposition based sunflower optimization algorithm using cloud computing environments

引用

Materials Today: Proceedings 2022年 62卷 4896-4902页

作者： Chandrashekar, Chirag Krishnadoss, Pradeep School of Computer Science and Engineering Vellore Institute of Technology Chennai 600 127 India

computer!! The one everyone uses almost every day in this busy world, a device capable of handling tasks from simple addition to complex tasks like launching rockets, but to sustain these tasks, and be a part of the huge networks like the internet and serve as an integrated part of IoT (internet of things) many different devices like cloud computing, servers are developed which can handle the request and return the appropriate response to the device. However, IoT device face certain issues among which the obtainability of on-going energy heads in one of the biggest issue and reason of this is because of the enormous amount of information that is created by using IoT devices and handling this information is one of the biggest constraints. To reduce these issues, many different schedulers were introduced like the optimized schedule task requests which enhances system productivity and performance, and the task scheduler whose objective is to divide tasks based on the available resources so the it reduces make span and time consumption. Hence to improve cloud computing many different meta-heuristics systems for task scheduling were introduced, but their throughput was far from the optimal state and needed upgrading. Keeping that in mind, this paper proposes an Opposition based sunflower optimization (OSFO) algorithm for enhancing the throughput of already available task schedulers in terms of cost, energy and makespan. © 2022

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Privacy Preservation in Social Network Data using Evolutionary Model

引用

Materials Today: Proceedings 2022年 62卷 4732-4737页

作者： Srivatsan, S. Maheswari, N. School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai India

Social Networks have seen an exponential increase in their user activity. The corresponding user data can be extremely valuable, for improving user experience, identifying trends to make business decisions, and analyzing local and global user behavior. There are concerns over how this data is handled, largely because there are no stringent measures to regulate its handling. Anonymizing user data is vital to ensure the re-identification risk is minimum while retaining as much possible useful information from it. This work proposes a novel method to anonymize user data and ensure it satisfies the three privacy constraints of K-Anonymity (KA), L-Diversity (LD), and T-Closeness (TC), while also keeping information loss from anonymization techniques to the minimum. This dual objective problem is solved through a minimization approach. © 2022

关键词： Behavioral research

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：