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A Review of Healthcare Recommendation systems Using Several Categories of Filtering and Machine Learning-Based Methods 3

A Review of Healthcare Recommendation Systems Using Several ...

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3rd ieee International Conference on computing, Communication, and intelligent systems, ICCCIS 2022

作者： Kumar, Pardeep Kumar, Ankit Baba Mastnath University Asthal Bohar Rohtak India

ISBN: (纸本)9781665462006

Health-care Recommendation systems (RSs) is a famous application of AI (artificial intelligence) that involves the investigators worldwide. Several ML methods are utilized to develop health-care RSs. Selecting the best ML method to give customers a service/product is an interesting task in health-care RSs. Currently, it is observed in the buying pattern of individuals from in-shop to online the outcome in accessibility of OI (online information) which is exponentially improved day by day. In shopping scenarios, these RSs must be capable of advising reliable solutions to the customers. The medical health-care RSs have to manage a large quantity of data by cleaning the reliable data depending on the data analysis, generated on the user behaviour made by the customers during their online terms. RSs can suggest suitable items to customers based on their interests and existing favourites, leading to improved sales. This paper described the overview of health-care RS, phases of RSs such as IC (information collection), learning, and recommender or predictor. This paper presents an overview of three main methods used to construct health-care RSs that are content-based, collaborative filtering (CF)-based and hybrid (HB)-based filtering methods and discuss several ML-based methods used in health-care RSs with their performance comparison. The ML-based methods include;MFM (matrix factorization model), CNN, MLP, SVD, etc. © 2022 ieee.

关键词： Health care

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Brain Tumor Detection Using U-Net and 3D CNN Architecture 3

Brain Tumor Detection Using U-Net and 3D CNN Architecture

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3rd ieee International Conference on computing, Communication, and intelligent systems, ICCCIS 2022

作者： Ghanshala, Anshul Chauhan, Aakarshan Diwakar, Manoj Sharma, Sachin The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9781665462006

Magnetic resonance imaging (MRI) data must be manually segmented by medical specialists, which takes a lot of time. Automating this procedure is a challenging task because tumor tissues often resemble normal tissues and can seem quite differently in different people. Modern imaging technology like MRI provides detailed information on the human body's soft tissue architecture. Several techniques can be used to identify and separate a brain tumor from surrounding tissue in MRI scans. During the presentation of these 3D detection and segmentation techniques, it is underlined the importance of emphasizing the advantages and disadvantages of these strategies for brain tumor identification and segmentation. The description of numerous techniques for segmenting and detecting MRI images. In this paper, we propose a unique architecture that combines a 3D Convolutional Neural Network (CNN) and a U-Net for the detection of brain tumours. Our study produces superior outcomes than comparable existing methods, according to comparison analysis. © 2022 ieee.

关键词： Magnetic resonance imaging

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Resilient 3D Object Recognition using GR-Net in Sparse Point Clouds 3

Resilient 3D Object Recognition using GR-Net in Sparse Point...

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3rd International Conference on intelligent systems, advanced computing, and Communication, ISACC 2025

作者： Ghadekar, Premanand Dhame, Pratik Dixit, Soham Patil, Arpit Sanjekar, Rushikesh Shinde, Siddhesh Vishwakarma Institute of Technology Department of Information Technology Maharashtra Pune India

ISBN: (纸本)9798331523893

Recognizing three-dimensional (3 Dimensonal) objects is crucial for several uses for computer vision like service robots, self-driving cars and surveillance drones to navigate effectively in complex environments. However, existing classification techniques struggle with challenges such as varying resolutions, noisy data, and diverse object poses. Previous studies have highlighted the limitations of point cloud-based methods in handling sparsity, rotation, and positional variance. In this study, we concurrently address these difficulties with a unique technique to 3D object categorization. Our method leverages the graph structure of point clouds and employs a to develop a strong latent representation of 3D objects using a neural network. This representation achieves invariance to rotation, positional shift, and scaling while remaining resilient to point sparsity. Our technique outperforms existing approaches, as evidenced by experimental findings on the ModelNet40 dataset, which show a 45.0% and 38.1% gain in classification accuracy when employing sparse point clouds, respectively, over existing models. © 2025 ieee.

关键词： Object detection

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Implementation of Lightweight PRNG on PLC for Industrial Control systems 3

Implementation of Lightweight PRNG on PLC for Industrial Con...

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3rd International Conference on intelligent Cybernetics Technology and Applications, ICICyTA 2023

作者： Sama, Andi Gaol, Ford Lumban Harso Supangkat, Suhono Ranti, Benny Binus Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Institute of Technology Bandung Faculty of Digital Communication and Hotel & Tourism Bandung Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9798350394559

The Information Technology/Operational Technology convergence towards Industry 4.0 opens the opportunity to leverage recent advancements in Information Technology for Operational Technology, such as Cloud, Internet of Things, and Artificial Intelligence. Meanwhile, cyber-attacks are increasing for Operational Technology. The security aspect in Operational Technology systems has traditionally been a low priority, in contrast with speed. This introduces challenges as Industrial Control systems such as Programmable Logic Controller in Operational Technology have been traditionally optimized for speed rather than security due to limited computing power. As computations need to be as efficient as possible, security in Operational Technology has yet to be managed as robustly as in Information Technology. Operational Technology communication protocols for securing data transfer, for example, have no or just a few security capabilities, even for basic authentication and encryption. Common security algorithms rely on random numbers. However, Random Number Generator is not usually part of standard functions in Programmable Logic Controllers, the core control component in Industrial Control systems. In Industrial Control systems, the Random Number Generator is mostly implemented as a software-based Pseudo Random Number Generator. This paper shows how to apply a Pseudo Random Number Generator in a Siemens Compact PLC S7-1200 using a modified lightweight XORshift algorithm. The XORshift algorithm can generate better randomness than the system's clock-based implementation in the Siemens Library of Generic Functions. © 2023 ieee.

关键词： Internet of things

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An Integration Of Wireless Communications And Artificial Intelligence For Autonomous Vehicles 3

An Integration Of Wireless Communications And Artificial Int...

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3rd International Conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Raghuram, Kadambari Altarawni, Ibrahim Vijayalakshmi, K. Kumar, Ajay Jadeja, Abhijeetsinh Chandra, Pankaj Jntuk Department of Computer Science and Engineering Andhra Pradesh Kakinada India Aqaba University of Technology Applied Computing and Artificial Intelligent Department Aqaba Jordan Ramapuram Campus Srmist India INurture Education Solution Pvt. Ltd It Academics Delhi India Sankalchand Patel University Faculty of Computer Science Shri C.J. Patel College of Computer Studies India Guru Ghasi das Viswavidyalaya Dept of Information Technology Chattisgarh Bilaspur India

ISBN: (纸本)9798350399264

The pinnacle of transportation is the development of autonomous driving, which, with the help of CAVs and related traffic management systems, can eventually lead to congestion- and accident-free driving. This vision has as of late prodded extraordinary examination interest in fields including IoV, LTE-V2X, and 5G. In any case, the huge volume of traffic information that CAVs produce makes issues for both the current organizations and the approaching 5G correspondence organizations. For outside network innovations, the VMBS fills in as both a client hub and an edge processing hub. For CAVs, it fills in as a base station and a data caching hub, melding correspondence and calculation. People offer both the VMBS-empowered handset and figuring for CAVs as well as the VMBS-helped wireless innovation for other wireless gadgets to achieve this. It is underlined and addressed that there are a number of research obstacles and open questions. Last but not least, the results of the simulation show that the planned VMBS-CCNA may significantly enhance throughput, latency, and the average amount of links. © 2023 ieee.

关键词： Autonomous vehicles

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Secure and Lightweight data Sharing Mechanism for Medical IoT 3

Secure and Lightweight Data Sharing Mechanism for Medical Io...

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3rd International Conference on intelligent computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Yakkala, Tarun Sai Kumar Modekurty, Sri Krishna Boggarapu, Neeraj Mandal, Amit Kr Srm University Ap Department of Computer Science and Engineering Amaravathi India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

The healthcare sector has engaged in substantial research in terms of technological advancement to provide patients with efficient and secure services. With the adaption of the internet of things (IoT) in the healthcare domain, remote patients are now able to share their health records with medical experts at distant locations, leading to more efficient and less expensive services. Given that data sharing over the internet entails the patients' privacy, therefore, it is necessary to ensure that data is transmitted securely so that an adversary cannot tamper with it. Again, as IoT devices are resource-constrained, therefore, it is very important to transmit the data in a lighter format. This paper presents a mechanism for the communication of data or images over the network in a secure and lighter format. The proposed mechanism is implemented on Modified Chebyshev Polynomial and suitable data and image compression techniques with minimum distortion. © 2022 ieee.

关键词： Internet of things

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Reliability of Smart-Wearables using PSO-GA Optimized Algorithm in Terms of data Analysis 3

Reliability of Smart-Wearables using PSO-GA Optimized Algori...

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3rd International Conference on intelligent computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Sivakumar, Jananya Quadir, Md Abdul Vigneswaran, T. Punitha, K. Sivaraman, Arun Kumar Vellore Institute of Technology School of Computer Science and Engineering Tamil Nadu Chennai600127 India Vellore Institute of Technology School of Electronics Engineering Tamil Nadu Chennai600127 India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Rapid advancement in the smart-wearable industry has increased the importance of modeling the relationship between the raw data captured by the devices and the useful information obtained by analyzing using a metaheuristic approach. In this paper, a new model to cater to the user-end experience based on the PSO-GA optimized ANFIS approach is proposed. PSO-GA consists of alternating phases of Genetic Algorithm and Particle Swarm Optimization. The proposed model aims at minimizing the function, under dynamic changes while in constant interaction of the fitness-tracker with the human body. © 2022 ieee.

关键词： Genetic algorithms

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A Statistical Technique to Construct data-Driven Decision Rules Based on Prediction Intervals of Nonlinear Regressions 3

A Statistical Technique to Construct Data-Driven Decision Ru...

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3rd ieee International Conference on System Analysis and intelligent computing, SAIC 2022

作者： Prykhodko, Sergiy Prykhodko, Natalia Admiral Makarov National University of Shipbuilding Department of Software of Automated Systems Mykolaiv Ukraine Admiral Makarov National University of Shipbuilding Finance Department Mykolaiv Ukraine

ISBN: (数字)9798350396744

ISBN: (纸本)9798350396744

A statistical technique to build data-driven decision rules based on prediction intervals of nonlinear regressions created using multivariate normalizing transformations is proposed. In the general case, the proposed technique is iterative since there may be outliers in the process of building the decision-making rule based on prediction intervals of nonlinear regression. To construct nonlinear regressions and their prediction intervals we use the appropriate techniques based on multivariate normalizing transformations that take into account the correlation between dependent and independent variables. We give examples of constructing data-driven decision rules based on prediction intervals of nonlinear regression with two predictors created using the Johnson three-variate normalizing transformation for the SB family for three-dimensional non-Gaussian data from 33 auto companies, 32 of which were from the S&P 500 Index in 2020. The above rules are constructed to make a decision in which stocks it is better to invest in. We have found that as of December 2020, the shares of two auto companies were overvalued, and the shares of one, on the contrary, were undervalued, so the shares of this company could be bought. © 2022 ieee.

关键词： Decision making

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Beam Hopping Technique For Indian data Traffic 3

Beam Hopping Technique For Indian Data Traffic

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3rd ieee International Conference on computing, Communication, and intelligent systems, ICCCIS 2022

作者： Reddy, Pasala Bharath Kumar Reddy, Gottimukula Praveen Tabassum, Farhana Bhawsar, Yogesh Kumar Ahmad, Imteyaz Khoral, Jasvinder Singh Space Infrastructure - Geo Platform U R Rao Satellite Centre Indian Space Research Organization Bengaluru India

ISBN: (纸本)9781665462006

Current trend in space technology involves satellites that can provide variable Effective Isotropic Radiated Power (EIRP), variable bandwidth and flexible coverage area. With an inclination towards mass optimisation and to fully utilise the available resources on board by reusing them efficiently, a technique called beam hopping with spot beam technology has gained traction. In this paper, the feasibility of a beam hopping satellite for India along with its merits and demerits over conventional High Throughput Satellite (HTS) are discussed. Maximum advantage of beam hopping is obtained if the beams are hopped as per real time user demand which requires constant co-ordination between the satellite, ground station & the user. This requires dynamic resource allocation, thereby increasing the ground complexity manifold. In this paper, rather than dynamic hopping, probable data rate demand in various parts of India is analysed, a suitable probability distribution for the demand rate is identified and a beam hopping scheme is proposed to obtain near optimal throughput. Further, a comparative analysis of Beam Hopping HTS (BH HTS) is carried out with standard HTS to establish the effectiveness of beam hopping. © 2022 ieee.

关键词： Satellites

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Research on intelligent Training System of Athletes Assisted by Computer and Cloud computing 3

Research on Intelligent Training System of Athletes Assisted...

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3rd International Conference on Computers, Information Processing and advanced Education, CIPAE 2022

作者： Xie, Yu Liu, Lu Chengdu University of Information Technology Department of Physical Education Chengdu China Chengdu University of Information Technology Chengdu China

ISBN: (纸本)9781665468121

Collection work is the key to the training level of athletes in the process of track and field sports training. This paper applies the idea of multi-sensor to information fusion technology. In this paper, the critical indicators of athletes are collected through multiple sensors and cameras. The former is to use wavelet transform to realize the feature extraction of human surface EMG signals. Then this paper uses the artificial neural network method to identify the key features to get the preliminary track and field evaluation results. The research found that this method can measure the training rotation angle, motion characteristic data trajectory, speed, acceleration, and other indicators in real-time and accurately determine the difference. The motion acquisition technology proposed in this paper can correct bad habits and improve the training level. © 2022 ieee.

关键词： Wavelet transforms

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