检索结果-内蒙古大学图书馆

An oceanographic data collection scheme using hybrid optimization for leakage detection during oil mining in mobility assisted UWSN

引用

Multimedia Tools and Applications 2024年第42期83卷 89723-89741页

作者： Choudhary, Monika Goyal, Nitin Gupta, Deepali Sharma, Bhanu Sharma, Nonita Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Seth Jai Parkash Mukandlal Institute of Engineering and Technology Haryana Radaur India Department of Computer Science and Engineering School of Engineering and Technology Central University of Haryana Haryana Mahendragarh India Department of Information Technology Indira Gandhi Delhi Technical University for Women Delhi India Immersive and Interactive Technology Lab Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

Data acquisition is the process of collecting, measuring and analysing information using standardised, validated techniques for application-specific tasks. In mobility-assisted underwater wireless sensor networks (UWSNs), where nodes are not fixed due to water current of 3 m/sec, data collection becomes an arduous task. There are few works that provide a mobile sink with optimised data transmission path planning and scheduling. These systems do not transmit the data fast enough to provide real-time data transmission as these methods do not consider the buffer occupancy rate and latency in data acquisition. In this paper, a stimulating transmission path planning technique for mobile sinks using the hybrid Grey Wolf Optimizer Whale Optimization Algorithm (GWOWOA) is proposed. In contrast to other optimization techniques, this hybrid technique includes a number of update processes such as random position update, prey search by the Grey Wolf Optimizer (GWO) and prey search by the Whale Optimization Algorithm (WOA). In this paper, the fitness function is calculated in terms of distance to the mobile sink, buffer occupancy rate, energy level and data acquisition latency. The use of these variables makes the proposed technique innovative. To prove the efficiency of the proposed system, GWOWOA is compared with existing systems. The simulation results show that the proposed system increases the residual energy and accuracy of the collected data and minimises the delay. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Data acquisition

来源：评论

学校读者我要写书评

暂无评论

A Perspective to Cloud Computing in Healthcare Sector 2

A Perspective to Cloud Computing in Healthcare Sector

引用

2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Himanshu Punhani, Akash Srm Institute of Science and Technology Delhi-NCR Campus Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798350371055

The medical services industry is on the cusp of another period driven by the union of distributed computing, man-made consciousness (simulated intelligence), and the Ayushman Bharat Wellbeing Record (ABHA) card drive. Distributed computing offers adaptability, adaptability, and cost-viability for medical care information the executives, while man-made intelligence holds enormous potential for customized medication, prescient investigation, and constant demonstrative help. The ABHA card, as the public computerized wellbeing identifier, gives a bound together stage to getting to and overseeing individual wellbeing records. This examination paper proposes an extensive structure for coordinating distributed computing, man-made intelligence, and ABHA to accomplish customized medical care. The paper will dig into the execution of this structure, tending to be specialized difficulties, information security contemplations, and moral ramifications. It will likewise investigate the possible effect of this methodology on working on tolerant results, decreasing medical services costs, and upgrading patient fulfilment. © 2024 IEEE.

关键词： ABHA ABHA Card AI Cloud Computing Data management Healthcare Security

来源：评论

学校读者我要写书评

暂无评论

Story Generation Using GAN, RNN and LSTM 1

引用

13th International Advanced Computing Conference, IACC 2023

作者： Shrouti, Devika Bayas, Ameysingh Joshi, Nirgoon Misal, Mrinank Mahajan, Smita Gite, Shilpa Computer Science and Engineering Department Symbiosis Institute of Technology Pune India Artificial Intelligence and Machine Learning Department Symbiosis Institute of Technology Pune India

ISBN: (数字)9783031567001

ISBN: (纸本)9783031566998

This paper explores the domain of story generation and presents a novel approach that uses Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory (LSTM) networks. The objective is to generate realistic and engaging stories for children. The traditional language models are proficient in maintaining grammatical consistency but often fail to establish long-term coherence. This study addresses and explores the individual performances and capabilities of 3 distinct text generation models based on GAN, RNN & LSTM respectively. The project employed three individual models and trained them on the same dataset and the evaluation was conducted using METEOR scores, accuracy, and loss metrics. To address this, our study introduces the use of GANs to enhance the quality of synthetic text. The MaskGAN model gave the highest accuracy and decent output on the trained dataset followed by the RNN and LSTM models. This paper is a significant step forward for story generation, highlights the unique contributions of GANs, RNNs, and LSTMs, amplifies the consistency and quality of independently generated narratives, and provides a foundation for future comparative analyses. MaskGAN achieved the highest accuracy and excelled in generating realistic and high-quality narratives followed by RNNs which exhibited decent accuracy but faced challenges with longer narratives, while the beam search-enhanced LSTM improved narrative quality offering a promising solution for coherent story generation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Cutting-Edge AI-Driven Higher Educational and Career Advisory Platform

Cutting-Edge AI-Driven Higher Educational and Career Advisor...

引用

2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Dewasurendra, S.V. Udunuwara, U.K.C. Wanniarachchi, T.T. Panditharathne, P.D.R.L. Thelijjagoda, Samantha Dissanayaka, Kapila Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798331543617

Sri Lankan students, especially those from rural and low-income backgrounds, face significant challenges in accessing higher education, including university applications, career planning, and financial aid. This research introduces an AI-powered platform designed to provide personalized assistance through university course recommendations, career guidance, financial aid information, and AI-generated mock aptitude tests. The platform employs Graph Neural Networks (GNNs) for course recommendations, Recurrent Neural Networks (RNNs) for career guidance, and a Retrieval-Augmented Generation (RAG) model for financial aid navigation. Additionally, AI-driven algorithms with Optical Character Recognition (OCR) technology support exam preparation. Data from students and universities informed model training, and evaluations showed high accuracy and user satisfaction across components. Results indicated that the platform effectively aligns educational resources with students' academic and career goals, promoting greater educational accessibility and support for underserved Sri Lankan students. © 2024 IEEE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

An Ensemble based Fraudulent Blockchain Account Detection System 2024

An Ensemble based Fraudulent Blockchain Account Detection Sy...

引用

16th International Conference on Contemporary Computing, IC3 2024

作者： Ralli, Rishabh Jugran, Gargi Gaurav, Mayank Goyal, Mukta Department of Computer Science & Engineering Jaypee Institute of Information Technology U.P Noida India

ISBN: (纸本)9798400709722

This paper addresses the issue of fraud in blockchain transactions, which can significantly undermine trust and financial stability within blockchain networks. By leveraging advanced ensemble learning techniques, it aims to detect and prevent fraudulent activities effectively. The analysis focuses on blockchain networks, utilizing a combination of sophisticated machine learning algorithms such as Support Vector Machine (SVM), random forests, Tabnet, XGBoost, and the deep learning model MLP. These algorithms meticulously analyze transaction data for unusual patterns indicating fraud. The ensemble approach distinguishes between legitimate and fraudulent accounts by accurately analyzing transaction patterns. Notably, the ensemble model achieved a testing accuracy of 93.6%, thereby aiming to reduce the potential financial and reputational risks associated with fraud in blockchain transactions. © 2024 Copyright held by the owner/author(s).

关键词： Fraudulent transactions

来源：评论

学校读者我要写书评

暂无评论

Optimum Sizing and Pricing for Multigrids using Deep Learning Techniques 2

Optimum Sizing and Pricing for Multigrids using Deep Learnin...

引用

2nd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Minocha, Sachin Taneja, Neeti Galgotias University Department of Computer Science and Engineering Greater Noida India Noida Institute of Engineering and Technology Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350347456

Due to the clean, effective, but reliable power they supply, substations have growing in popularity. Substations required tankers power in order to use the saved fuel during emergencies or peak loads. Given that dc microgrid will be dominant energy resource with in coming, the battery should be geared toward producing power. Batteries are utilized throughout the day, especially during rush hour and emergency situations. There are various battery types, including batteries, lion capacitors, etc. New systems like hybrid cars and other devices are constrained by the difficult challenge of considered as the ability capacity for microgrids. To acquire the best battery design for micro - grid, it is critical to understand several various properties such as standby time, energy efficiency, and total independence. A proven method for integrating and optimizing various energy sources and characteristics for the long battery sizing is blended time varying (MILP). Inside this effort, a brand-new Style. For instance, datasets are presented. To determine the ideal battery, computational approach called Support Vector Machine (SVM) based CNN is employed. The suggested machines learning-based Typical's response to feature selection techniques is assessed. The effectiveness of the top six feature selection algorithms is examined. The test data show that the approach performs better when types of filters are used. © 2023 IEEE.

关键词： Costs

来源：评论

学校读者我要写书评

暂无评论

Genetic-Chicken Swarm Algorithm for Minimizing Energy in Wireless Sensor Network

引用

computer Systems Science & engineering 2023年第2期44卷 1451-1466页

作者： A.Jameer Basha S.Aswini S.Aarthini Yunyoung Nam Mohamed Abouhawwash Department of Computer Science and Engineering Hindusthan Institute of TechnologyCoimbatore641032India Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of ComputationalMathematics Science and Engineering(CMSE) Michigan State University East LansingMI48824USA.

Wireless Sensor Network(WSN)technology is the real-time applica-tion that is growing rapidly as the result of smart *** power is one of the most signiﬁcant resources in *** enhancing a power factor,the clustering techniques are *** the forward of data in WSN,more power is *** the existing system,it works with Load Balanced Cluster-ing Method(LBCM)and provides the lifespan of the network with scalability and *** the existing system,it does not deal with end-to-end delay and deliv-ery of *** overcoming these issues in WSN,the proposed Genetic Algo-rithm based on Chicken Swarm Optimization(GA-CSO)with Load Balanced Clustering Method(LBCM)is *** Algorithm generates chromosomes in an arbitrary method then the chromosomes values are calculated using Fitness *** Swarm Optimization(CSO)helps to solve the complex opti-mization ***,it consists of chickens,hens,and *** divides the chicken into *** Balanced Clustering Method(LBCM)maintains the energy during communication among the sensor nodes and also it balances the load in the *** proposed GA-CSO with LBCM improves the life-span of the ***,it minimizes the energy consumption and also bal-ances the load over the *** proposed method outperforms by using the following metrics such as energy efﬁciency,ratio of packet delivery,throughput of the network,lifetime of the sensor ***,the evaluation result shows the energy efﬁciency that has achieved 83.56%and the delivery ratio of the packet has reached 99.12%.Also,it has attained linear standard deviation and reduced the end-to-end delay as 97.32 ms.

关键词： Energy efﬁciency sensor nodes chicken swarm optimization load balanced clustering method wireless sensor network cluster heads load-balancing ﬁtness function

来源：评论

学校读者我要写书评

暂无评论

A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When?

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1429-1442页

作者： Bharati, Subrato Mondal, M. Rubaiyat Hossain Podder, Prajoy Bangladesh University of Engineering and Technology Institute of Information and Communication Technology Dhaka1205 Bangladesh Concordia University Department of Electrical and Computer Engineering MontrealQCH3G 1M8 Canada

Artificial intelligence (AI) models are increasingly finding applications in the field of medicine. Concerns have been raised about the explainability of the decisions that are made by these AI models. In this article, we give a systematic analysis of explainable artificial intelligence (XAI), with a primary focus on models that are currently being used in the field of healthcare. The literature search is conducted following the preferred reporting items for systematic reviews and meta-analyses standards for relevant work published from 1 January 2012 to 2 February 2022. The review analyzes the prevailing trends in XAI and lays out the major directions in which research is headed. We investigate the why, how, and when of the uses of these XAI models and their implications. We present a comprehensive examination of XAI methodologies as well as an explanation of how a trustworthy AI can be derived from describing AI models for healthcare fields. The discussion of this work will contribute to the formalization of the XAI field. © 2020 IEEE.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

Ontology-based video retrieval using modified classification technique by learning in smart surveillance applications

引用

International Journal of Cognitive Computing in engineering 2023年第1期4卷 55-64页

作者： Sathiyaprasad, B. Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Jeppiaar Nagar Rajive Gandhi Salai Chennai600 119 India

With the rapid advancements in communication and multimedia computing technology, multimedia information, particularly video data, has recently become disproportionately accessible. Video is widely used in a variety of applications, making efficient management and retrieval of the expanding volume of video data critical. To manage such tasks, include automated recognition of the image queries in video retrieval with a reduced degree of system memory usage, spot detection, maintenance time, identification of exact duplicate videos, and so on. This research determination demonstrates the Modified R-Ratio with Viola-Jones Classification Method (MRVJCM) with the relevance of developing techniques and algorithms for automatic recognition of image queries. The R-Ratio Viola–Jones framework has two distinguishable feature maintenance processes, such as Feature Selection and Integration and Feature Cascading. These two distinct features are applied to the motion features (texture, emotions, elements, and shape) within the three features. The proposed techniques and their relevant algorithms are used to retrieve the most accurate videos and to assure the mathematical operation of video retrieval in the operation of the comparable protected system. As a result, the proposed MRVJCM achieves 98% of accuracy, 93% of precision, 92% of recall, and 42% of RMSE. © 2023

关键词： Ontology

来源：评论

学校读者我要写书评

暂无评论

Optimization of quality of service using ECEBA protocol in wireless body area network

引用

International Journal of Information technology (Singapore) 2023年第2期15卷 595-610页

作者： Pawar, Renuka Sahebrao Kalbande, Dhananjay Ramrao Computer Engineering Department Sardar Patel Institute of Technology Andheri (West) Mumbai 400058 India

Smart healthcare using IoT is the Internet of Healthcare Things (IoHT) that consists of smart monitoring of health remotely by forming the wireless body area networks (WBANs). Each WBAN node having body sensors will collect the periodic medical information of patients and sent to actuators or access points where the medical decision is taken in a multi-hop manner. The IoHT deployment suffers from the two challenges such as cost-effective link establishment and effective access control policies. This paper proposed the novel edge layer protocol called Enhanced Cost-effective and Energy Efficient Based Access control policies (ECEBA). The goal of cost-effective algorithms is to improve the quality of service. The proposed solution is using the lightweight elliptical curve cryptography (ECC) to achieve medial data security and medical user privacy preservation. The ECEBA protocol is implemented and evaluated using NS2. The simulation results prove the efficiency of the proposed protocol over existing methods. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's institute of computer Applications and Management.

关键词： Access control policies Cost-effective Elliptical curve cryptography Energy-efficiency Internet of healthcare things Routing protocol

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：