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Smart Healthcare Solutions: Leveraging Internet of Things Technologies for Advanced computing, Communications and Applied Informatics 6

Smart Healthcare Solutions: Leveraging Internet of Things Te...

引用

6th Parul international conference on Engineering and technology, PICET 2024

作者： Apetorgbor, Mawuli Dulewale, Niraj Dhawale, Chitra Department of Science and Technology Datta Meghe Institute of Higher Education and Research Wardha India

ISBN: (纸本)9798350369748

Envision a future where healthcare evolves to cater to each individual's unique needs, a vision made feasible by the convergence of IoT and healthcare. The analysis delves into this transformative fusion, illustrating how IoT is reshaping computing, communication, and information management in the era of intelligent healthcare. We explore ground-breaking research and cutting-edge technologies, unveiling a plethora of applications ranging from remote patient monitoring to tailored treatment plans and streamlined hospital operations. Despite encountering challenges, we also scrutinize the vast potential of IoT to revolutionize healthcare delivery, empower patients, and ultimately, save lives. Embark with us on this journey into a connected healthcare landscape, where technology seamlessly integrates with medical practice to forge a healthier, more personalized world for all. © 2024 IEEE.

关键词： Electronic health record

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Differential Evolution Based on Estimation of Distribution for C-DCOP 3

Differential Evolution Based on Estimation of Distribution f...

引用

3rd international conference on Intelligent Communications and computing, ICC 2023

作者： Zhao, Qingchuan College of Computer Science and Engineering Chongqing University of Technology Chongqing China

ISBN: (纸本)9798350308327

Aiming at the shortcomings of the existing Continuous Distributed Constraint Optimization Problems (C-DCOP) solving algorithms, such as the weak search ability, the inability to guarantee convergence, and the solution quality to be improved, Differential Evolution based on Estimation of Distribution for C-DCOP (DEED) is proposed, and the elite strategy and the reservation strategy guarantee the the convergence of DEED, the solution quality is effectively improved by introducing the estimation of distribution, in addition, the adaptive crossover probability enhances the search ability. Finally, the experimental results on four types of benchmark problems show that compared with the state-of-the-art C-DCOP solving algorithms, DEED exhibits excellent performance in terms of solution quality. © 2023 IEEE.

关键词： Evolutionary algorithms

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DRQN-based Task Offloading in UAV-assisted Mobile Edge computing Environments with Hidden Channel Conditions 15

DRQN-based Task Offloading in UAV-assisted Mobile Edge Compu...

引用

15th international conference on Information and Communication technology convergence, ICTC 2024

作者： Song, Taewon Soonchunhyang University Department of Internet of Things Asan Korea Republic of

ISBN: (纸本)9798350364637

Mobile edge computing (MEC) with unmanned aerial vehicle (UAV) assistance offers promising solutions for reducing latency in 5G networks. However, uncertainty in task processing requirements poses challenges for efficient task of-floading. This paper introduces a deep recurrent Q-network (DRQN) based algorithm for task offloading in UAV-assisted MEC environments with hidden channel conditions. We for-mulate the problem as a partially observable Markov decision process (POMDP), where the UAV decides whether to process tasks locally or offload them to a cloud server without complete information about the channel state. Our approach leverages temporal dependencies in the environment to make informed decisions under uncertainty. Simulations demonstrate that our DRQN-based algorithm outperforms previous methods, including DQN-based, offload-only, and local-only strategies. This work contributes to the development of robust task offloading strategies for dynamic edge computing environments in 5G and beyond networks. © 2024 IEEE.

关键词： Markov processes

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Influence of implicit iterative method on convergence rate of SIMPLE algorithm

Influence of implicit iterative method on convergence rate o...

引用

2023 international conference on Cloud computing, Performance computing, and Deep Learning, CCPCDL 2023

作者： Li, Hangbo Beijing Institute of space launch Beijing100076 China

ISBN: (纸本)9781510666474

In the application of SIMPLE algorithm, the generation and solving of linear equations with sparse coefficient matrix appear. Gauss-Seidel and ILU iteration are commonly used to solve the problem. Combined with the common characteristics of LU-SGS time advance method and ILU iterative method, the numerical iterative solutions of sparse matrix linear equations are studied. An iterative LU-SGS algorithm for solving general sparse matrix is proposed. Using C++ as programming language, a special equation solving library is constructed by using three-point data storage structure of multi-dimensional column vector and sparse matrix dot product algorithm. Combined with SIMPLE algorithm based on pressure, the transient NS equation in static grid is simulated numerically. Compared with Gauss-Seidel iterative method, this algorithm has the advantages of accurate calculation and fast convergence, so it has certain application value and reference value. © 2023 SPIE.

关键词： Iterative methods

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Text-to-Speech and Speech-to-Text Models: A Systematic Examination of Diverse Approaches 9

Text-to-Speech and Speech-to-Text Models: A Systematic Exami...

引用

9th IEEE international conference for convergence in technology, I2CT 2024

作者： Sudhan, Surabhi Nair, Parvathy P. Thushara, M.G. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science And Applications Amritapuri India

ISBN: (纸本)9798350394474

The convergence of Text-to-Speech (TTS) and Speech-to-Text (STT) models has spearheaded an era of transformative advancements in natural language processing (NLP). This article discusses transformative advances in natural language processing (NLP). It presents a comprehensive survey that systematically examines specific STT and TTS models, such as rule-based systems and deep learning architectures, and explores their structures, methodologies, and applications. The paper classifies these models based on their underlying technologies, architectural approaches, training methods, and application domains, and provides a detailed overview of their development. It highlights industry successes and challenges, covering a range of application areas, from assistive technologies to virtual assistants and language translation. This research provides new perspectives to understand the current world of STT and TTS technologies, which will especially benefit researchers, developers, and industry players. By highlighting the empowering bridge between written and spoken language, the paper uniquely contributes to the ongoing dialogue in the field. It not only sheds light on the current state of STT and TTS technologies but also lays the groundwork for future innovations and advances that could change the way we interact with language. © 2024 IEEE.

关键词： Deep learning

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CAWA: Correlation-Based Adaptive Weight Adjustment via Effective Fields for Debiasing 13

CAWA: Correlation-Based Adaptive Weight Adjustment via Effec...

引用

Joint 13th international conference on Soft computing and Intelligent Systems and 25th international Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024

作者： Noh, Kyoungrae Kim, San Kim, Jaekwang Sungkyunkwan University Computer Science and Engineering Suwon Korea Republic of Sungkyunkwan University Convergence Program for Social Innovation Suwon Korea Republic of

ISBN: (纸本)9798350373332

In real-world image classification tasks, neural networks often encounter significant challenges due to unexpected or deceptive correlations and biases inherent in the dataset. These biases can emerge from disproportionate data distributions, causing models to generalize poorly to new, unseen data. Such data distribution issues are particularly problematic compared to more balanced datasets because they lead the model to rely on bias attributes rather than intrinsic attributes. Ideally, the model should classify based on intrinsic attributes, but due to the influence of bias attributes, frequent misclassification occurs. Such biases compromise the fairness and accuracy of the model, especially in critical scenarios such as medical diagnosis, autonomous driving, or criminal justice, where misclassification can have significant consequences. To address these challenges, we propose an innovative two-stage approach aimed at mitigating bias more effectively and efficiently. © 2024 IEEE.

关键词： Image classification

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FinTech Edge: Utility computing & Artificial Intelligence Technologies for Smart Financial Acquisition & Blockchain in the Financial Industries 7

FinTech Edge: Utility Computing & Artificial Intelligence Te...

引用

7th international conference on Contemporary computing and Informatics, IC3I 2024

作者： Singh, Sandeep Sarkar, Tiyas Mangla, Monika Rakhra, Manik Singh, Amanpreet Jairath, Kapil Lyallpur Khalsa College Department of Computer Science Punjab Jalandhar India Lovely Professional University School of Computer Science & Engineering Punjab Phagwara India Dwarkadas J Sanghvi College of Engineering Department of Information Technology Mumbai India Lovely Professional University School of Computer Science & Applications Punjab Phagwara India Trinity College Department Of Sciences Punjab Jalandhar India

ISBN: (纸本)9798350350067

The study ventures into the changing environment of blockchain, artificial intelligence (AI), and cloud computing as key components of financial technology (FinTech). This research examines how these technologies are transforming the financial system, with a focus on intelligent finance investment including blockchain's disruptive potential. It begins with a brief description of cloud computing, explaining how it promotes extensibility, formability & cost-efficiency inside financial Institutions. The focus then shifts to AI applications, including the impact of robot advisers, trading using algorithms as well as statistical research on the reinvention of investing processes. The tale probes further into complex architecture of blockchain technology, giving light on its ability to increase the security and openness of the financial system. It reveals linkages that open the path for novel methods and significant developments, emphasizing the convergence of cloud, AI & blockchain. As we explore these FinTech territories, the paper acknowledges the inherent obstacles and dangers while also providing thoughts on legislative and ethical implications. It examines emerging trends, predicting the long-term influence of novel innovations on the financial environment. © 2024 IEEE.

关键词： Decentralized finance

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Application of Improved Sparrow Neural Network Algorithm Based on Chaotic Mapping for Waste Quantity Prediction 2

Application of Improved Sparrow Neural Network Algorithm Bas...

引用

2nd international conference on Signal Processing and Intelligent computing, SPIC 2024

作者： Guo, Haifeng Li, Fuqiang Song, Liying Yao, Zhenglin Shenyang Ligong University College of Automation and Electrical Engineering Shenyang China Technology Limited Company Beijing China

ISBN: (纸本)9798350368888

To improve the accuracy of waste generation predictions, a method incorporating chaotic mapping into the Sparrow Search Algorithm (SSA) is proposed. This enhanced algorithm is then integrated with neural networks for more precise predictions. The SSA typically encounters issues like slow convergence and getting stuck in local optima during optimization. By introducing Tent and Sine chaotic maps, the algorithm's randomness and diversity are increased, enhancing the initial population quality. Neural network backpropagation is then used to update positions. Through comparative analysis of BP, SSA, and chaotic SSA neural networks, more accurate predictions of waste generation are achieved. © 2024 IEEE.

关键词： Mapping

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Scheduling the Tasks in Cloud computing using Adaptive Adjustment in Whale Optimization Algorithm 2

Scheduling the Tasks in Cloud Computing using Adaptive Adjus...

引用

2nd international conference on Data Science and Information System, ICDSIS 2024

作者： Pareek, Piyush Kumar Nithyashree, G.D. Rajashekhar, S.A. Zanke, Pankaj Navyashree, K.S. Nitte Meenakshi Institute Of Technology Artificial Intelligence And Machine Learning Bengaluru India East West Institute Of Technology Department Of Computer Science And Engineering Bengaluru India Sapiens International Corporation United States

ISBN: (纸本)9798350381665

One of the most popular infrastructures for employing virtual machines, also known as processing units, is cloud computing. Task scheduling is fundamental problems of cloud computing. A number of methods to handle the nondeterministic polynomial-time (NP)-complete optimisation issue of choosing the best scheduling criteria in cloud computing have been proposed by academics in the past. An effective optimisation approach is suggested in this research, based on the whale optimisation algorithm (WOA), to address the common problems of solution algorithms, which include poor global optimisation ability, ease of sliding into local optimisation, and sluggish convergence speed. We provide an adaptive adjustment method that may dynamically alter search behaviour during the whale optimisation algorithm's iterative operation. The technique described to further update the position of search individuals also uses the evolutionary approach of differential variation. The algorithm's exploration and development capacities are then balanced, and a restart approach is included to keep the system from entering local optimisation. The approach simultaneously resolves the work planning issue in the situation of rain cloud processing. When compared to other algorithms, this technique uses more resources and converges more quickly. Additionally, the evaluation function seeks for the optimal answers by taking the makespan, resource cost, and load balancing level into account. © 2024 IEEE.

关键词： Cloud computing

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Parameter Calibration of VISSIM Based on Genetic Algorithm 11

Parameter Calibration of VISSIM Based on Genetic Algorithm

引用

11th international conference on Information Systems and computing technology, ISCTech 2023

作者： Wang, Jing Chen, Dashan Pang, Maosheng Huang, Yuxuan Shanghai University of Technology School of Rail Transit Shanghai China

ISBN: (纸本)9798350342406

Traffic simulation models are widely used in traffic system management and optimization. Parameter calibration is an important step before using traffic simulation software. In this study, the simulation software VISSIM was taken as an example to study the calibration problem of traffic simulation model, and the method flow of parameter calibration was designed and realized by using genetic algorithm. In view of the problems of genetic algorithm, such as easy to fall into local optimal and slow convergence speed, the initial population and variation of the algorithm were improved, and the algorithm was realized by using MATLAB. By combining experimental data to calibrate it, the convergence iteration times of genetic algorithm before and after improvement are reduced by 37.5%, and the speed improvement effect is significant. Meanwhile, the simulation error of parameter index after calibration based on the improved genetic algorithm is controlled at about 20%, which verifies the effectiveness of the designed method. © 2023 IEEE.

关键词： Genetic algorithms

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