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检索条件"任意字段=Conference on Algorithms, Devices, and Systems for Optical Information Processing"

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AI-Driven Personalized Skincare Recommendations

AI-Driven Personalized Skincare Recommendations

引用

Electronics and Renewable systems (ICEARS), International conference on

作者： Iyyanar Perumal Kalaivani P Naveenkumar A Saran V Sriram K Suruthi N Department of Information Technology Sona College of Technology Salem India Department of CSE Kongu Engineering College Perundurai India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

This study investigates the utilization of artificial intelligence (AI) to transform skincare product recommendations and the formulation of individualized routines through the analysis of user inputs and characteristics. The system utilizes data including skin type, acne count, oiliness level, and UV exposure, using KNearest Neighbors (KNN) for personalized product suggestions. Natural Language processing (NLP) approaches are utilized to develop tailored 7-day skincare regimen recommendations by examining product and user problems, converting unstructured data into actionable insights. Moreover, deep learning algorithms are employed for real-time image-based assessments of skin conditions, facilitating precise acne diagnosis and oiliness evaluation. The system integrates visual data with textual analysis, continually adapting through user feedback to improve accuracy and relevance. This article highlights the capacity of AI-driven methods to automate routine generation and provide tailored product recommendations, fostering innovation in the cosmetics sector through a thorough, data-oriented strategy.

关键词： Deep learning Visualization Accuracy Transforms Nearest neighbor methods Skin Natural language processing Real-time systems Artificial intelligence Wearable devices

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Adaptive Interference Cancellation in MIMO information Transmission systems

Adaptive Interference Cancellation in MIMO Information Trans...

引用

Digital Signal processing and its Applications (DSPA), International conference on

作者： Yuri Parshin Thuan Nguyen Radio devices department RSREU Ryazan State Radio Engineering University Ryazan Russia Federation

In this paper, the application of adaptive spatial interference compensation in MIMO systems is considered when using adaptive processing of the steepest descent according to the MMSE criterion. Application of a compensator using the steepest descent algorithm for interference cancellation in two cases: when the correlation matrix is known and when the correlation matrix is unknown. It is shown that during adaptation, the values of the weighting coefficients increase to the optimal value and the computational experiment confirmed cancellation interference of the MIMO receiver when using adaptive processing of the steepest descent according to the criterion of the minimum mean square of the error, especially for strong interference.

关键词： Adaptive systems Interference cancellation Correlation Computer simulation Signal processing algorithms Receivers Mean square error methods

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An Improved IoT Device Fingerprinting via Enhanced Feature Selection

An Improved IoT Device Fingerprinting via Enhanced Feature S...

引用

International conference on Signal processing and Communication systems, ICSPCS

作者： Mariam Munsif Mir Mohammad Awrangjeb Wee Lum Tan Ali Zia School of Information and Communication Technology Griffith University Nathan QLD Australia Machine Learning & Artificial Intelligence - Future Science Platforms CSIRO Canberra ACT Australia

ISBN: (数字)9798350389630

ISBN: (纸本)9798350389647

In the context of the Internet of Things (IoT), device fingerprinting involves identifying or classifying devices based on their unique intrinsic behavioural properties found in the network traffic data, which can be vast in amount and contain redundant information. Therefore, feature selection from the available network data is crucial for device fingerprinting. Feature sets selected by the existing fingerprinting methods are domain-adapted, specific to the datasets in which the methods are tested. They do not perform well in cross-domain scenarios when tested against other datasets. In this paper, we propose a novel feature set for an improved device fingerprinting method, which performs better than the existing methods. Genetic algorithm and voting mechanisms are utilised to obtain the feature set, and the stratified sampling method is used to ensure unbiased data for training ML models. We compare the performance of the proposed feature set to various existing methods using three benchmark IoT network traffic datasets. Our results show that the new feature set successfully identified IoT devices with 98.4% accuracy under a testing time of 0.02 seconds.

关键词： Performance evaluation Training Accuracy Signal processing algorithms Telecommunication traffic Fingerprint recognition Feature extraction Internet of Things Object recognition Security

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Dynamic optical Model for Time-Based Enhancement of Augmented Reality Environments

Dynamic Optical Model for Time-Based Enhancement of Augmente...

引用

IEEE Annual Computing and Communication Workshop and conference (CCWC)

作者： Qi Zhang School of Information Technology Illinois State University Normal Illinois United States

ISBN: (数字)9798331507695

ISBN: (纸本)9798331507701

Dynamic lighting is essential for creating realistic day-night cycles and enhancing augmented reality (AR) experiences. In this paper, we introduce a dynamic optical model that simulates the natural progression of light from sunrise to sunset and into nighttime, bringing environments to life. Our model leverages six photographic images as backgrounds for AR scenes and incorporates advanced rendering techniques to generate textured models and geometries. These textures are enhanced using novel image processing methods to improve contrast and visibility, particularly in low-light conditions. Our algorithm ensures a seamless blend between virtual elements and the natural world by matching AR lighting conditions with the real environment. The environment's light transitions dynamically, from daylight brightness to ambient nighttime light, with the sun acting as the primary light source, rotating around the virtual world to simulate realistic lighting and shading effects. This texture-sampling-based lighting algorithm adapts to real-time conditions, interactively adjusting the lighting to enhance AR elements, highlight critical information, and create immersive, believable experiences in virtual simulations and AR applications.

关键词： Visualization Adaptation models Computational modeling Heuristic algorithms Lighting Virtual environments Rendering (computer graphics) optical imaging Real-time systems optical sensors

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Improving Accuracy of Pseudo-LiDAR for 3D Object Detection by Accurate Depth Estimation 6

Improving Accuracy of Pseudo-LiDAR for 3D Object Detection b...

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6th IEEE International conference on Knowledge Innovation and Invention, ICKII 2023

作者： Peng, Tao Kim, Byeongwoo University of Ulsan Department of Electrical Electronic and Computer Engineering Ulsan Korea Republic of

ISBN: (纸本)9798350323535

With the advancement of autonomous driving technology, traditional 2D object detection approaches no longer fulfill the Safety of The Intended Functionality (SOTIF) standards. LiDAR sensors are efficient in giving precise point cloud information for accurate and reliable 3D object detection. Alternative sensors also are researched by researchers if they have lower costs but are limited in environmental circumstances. Notably, pseudo-LiDAR-based monocular 3D object detection has emerged as a viable option, as it generates a depth map from an RGB picture before translating it into a point cloud for 3D object detection. However, because the majority of depth estimation algorithms do not account for the loss of boundary information during feature extraction processing, depth artifacts occur in the periphery of objects in the depth map. These artifacts introduce long-tail problems in pseudo-LiDAR data, undermining the accuracy of 3D object detection. Therefore, we suggested a depth estimation method using Laplacian pyramid-based depth residuals to correctly capture object depth bounds. This improved the estimate and revised the depth map, which was converted into pseudo-LiDAR point cloud data. The pseudo-LiDAR was then used to recognize 3D objects. The proposed method, in particular, significantly mitigated the common border Long-tail problems in pseudo-LiDAR data, hence improving the precision of 3D object detection. Experiment validations demonstrated the method's efficiency and enhanced performance to improve the reliability of autonomous driving systems. © 2023 IEEE.

关键词： optical radar

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On Using the Raspberry Pi Camera to Receive 8-PAM Signals in optical Camera Communication

On Using the Raspberry Pi Camera to Receive 8-PAM Signals in...

引用

International Symposium on Communication systems, Networks and Digital Signal processing, CNSDSP

作者： Miguel Rêgo Vicente Matus Othman Younus Alexis A. Dowhuszko Zabih Ghassemlooy Mónica Figueiredo Pedro Fonseca Luis Nero Alves Department of Electronics Telecommunications and Informatics University of Aveiro Aveiro Portugal Instituto de Telecomunicações Aveiro Portugal Institute for Technological Development and Innovation in Communications Universidad de Las Palmas de Gran Canaria Las Palmas Faculty of Engineering and Environment Northumbria University Newcastle upon Tyne U.K. Department of Information and Communications Engineering Aalto University Espoo Finland School of Technology and Management Polytechnic of Leiria Leiria Portugal

ISBN: (数字)9798350348743

ISBN: (纸本)9798350348750

optical Camera Communication (OCC) has emerged as a way of implementing optical Wireless Communication (OWC) without the need of adding an additional interface to smart devices equipped with cameras, and is suitable for applications in Internet of Things (IoT), secure communications, indoor positioning and electromagnetic interference sensitive scenarios. Given the fact that a camera consists of an array of photodetectors connected to analog-to-digital converters, we can leverage this fact to implement not only binary signal reception, but also a multi-level Pulse Amplitude Modulation (PAM) receiver. In this paper, we explore the usage of the Raspberry Pi Camera V2.1 as a receiver for implementing 8-PAM OCC, focusing on the technical characteristics of this camera and identifying the limitations that arise from its low cost. A decoder algorithm is proposed, aimed at circumventing the identified limitations with signal processing solutions. The proposed algorithm was experimentally validated in an indoor scenario and a Symbol Error Rate (SER) was measured for up to 1.8m, remaining under 1.3%.

关键词： Signal processing algorithms Symbols Cameras Amplitude modulation optical receivers Adaptive optics optical sensors

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Human Activity Recognition using Signal processing and Classical ML algorithms 7

Human Activity Recognition using Signal Processing and Class...

引用

7th IEEE International conference for Convergence in Technology, I2CT 2022

作者： Samant, Tapaswini Banerjee, Shobhan Rath, Manas Kumar Swain, Tanmaya Kalinga Institute of Industrial Technology School of Electronics Engineering Bhubaneswar India Birla Institute of Technology and Science - Pilani Rajasthan India

ISBN: (纸本)9781665421683

For many of the modern-day applications, human beings are being tracked based on their activity all throughout a given period. The applications may be in surveillance systems, health care, human interaction, marketing, etc. This has become a specific field of study altogether and people are extensively working on this field to find better solutions to the given real-world problems. The data is being collected through devices such as smartwatches (Fitbits, Apple Watch, etc.) or smartphones and is further used to analyze the activity of the human by whom the device is being used. Here we have used the data from UCI Machine Learning Repository which gives us the information acquired from 30 peoples' smartphones. We have gyroscope and accelerometer data upon which appropriate signal processing techniques have been applied to generate features. Then these features are fed to various classical ML and ensemble models, and we perform a comparative analysis by looking into their specifics and accuracies. © 2022 IEEE.

关键词： Smartphones

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Secure Transmission for Movable Antennas Empowered Cell-Free Symbiotic Radio Communications

Secure Transmission for Movable Antennas Empowered Cell-Free...

引用

International conference on Wireless Communications and Signal processing (WCSP)

作者： Jiayu Guan Bin Lyu Yan Liu Feng Tian Nanjing University of Posts and Telecommunications Nanjing China Jiangsu Engineering Research Center of Novel Optical Fiber Technology and Communication Network Suzhou China Tongji University Shanghai China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

In this paper, a novel movable antenna (MA) empowered secure transmission scheme is designed for cell-free symbiotic radio (SR) systems in the presence of an eavesdropper (Eve). Specifically, multiple distributed access points (APs) equipped with MAs collaboratively transmit confidential information to the primary user (PU), in the meanwhile the backscatter device (BD) transmits its own information to the secondary user (SU) by reflecting incident signals from the APs. The MAs deployed at the APs can adjust their positions flexibly to improve channel conditions between the APs and the PU/SU/BD and suppress the eavesdropping from the Eve on confidential information at the PU. Under this setup, we maximize the secrecy rate of primary transmission through jointly optimizing the APs' transmission beamforming vectors and the positions of the MAs, while adhering to the quality of service constraints at the SU. To address the challenges caused by the non-convexity and find a near-optimal solution, an alternating optimization (AO) framework is proposed, utilizing the successive convex approximation method, the semi-definite relaxation technology and a genetic algorithm modified particle swarm optimization (GA-PSO) algorithm. Numerical results demonstrate the secrecy rate enhancement provided by utilizing the MAs and show the impact of the GA-PSO algorithm for improving the solving accuracy.

关键词： Symbiosis Wireless communication Accuracy Transmitting antennas Signal processing algorithms Quality of service Approximation algorithms Vectors Optimization Radio communication

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Towards IoT Context Data Analysis and Classification

Towards IoT Context Data Analysis and Classification

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International Multidisciplinary information Technology and Engineering conference (IMITEC)

作者： Vivian Bandason Khulumani Sibanda Nyashadzashe Tamuka Department of Computer Science University of Fort Hare Alice Eastern Cape South Africa Department of Applied Informatics Walter Sisulu University East London Eastern Cape South Africa

ISBN: (数字)9798350387988

ISBN: (纸本)9798350387995

The capability of generating and acquiring data has never been as pronounced as today since the advent of information Technology in the early 19th century. Big Data is a growing trend where data processing has grown so much that it is beyond the ability of commonly used software tools to capture, manage, and analyse this data. The most fundamental challenge for the Big Data applications is to explore the large volumes of data and extract useful knowledge. Another recent development furthering the accumulation of data is the Internet of Things - wherein the amount of “things” housing different sensors has multiplied. The Internet of Things (IoT) is built on sensors and actuators, which send out large quantities of data about their state and the environment. Data processing techniques can be utilized to extract relevant insights from this treasure of data and information that is generated in IoT environments. This research investigates how sensor data from user devices can be used to determine context information about a user. As far as the classification of daily human activities (such as walking, eating, driving and sleeping) is concerned, several studies have proposed traditional computer vision methods. Unlike traditional computer vision methods, which pose mobility limitations, computational complexity, and privacy issues, our approach leverages mobile sensor data for real-time activity recognition. Three classification algorithms which are the K-Nearest Neighbours (KNN), Decision Trees, and Support Vector Machines (SVM) were evaluated based on their accuracy in classifying human activities. Findings revealed that the KNN was superior to other algorithms in providing a promising approach for context-aware systems in IoT environments. This study highlights the potential of Machine Learning and sensor data in enhancing user-centric applications through improved context-awareness.

关键词： Support vector machines Computer vision Nearest neighbor methods Market research Real-time systems Sensors Classification algorithms Internet of Things information technology Software tools

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Age of information Aware Task Allocation for Crowd Sensing: A Pricing-Matching Approach

Age of Information Aware Task Allocation for Crowd Sensing: ...

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IEEE conference on Vehicular Technology (VTC)

作者： Wenqian Zhou Xuying Zhou Ning Jin Jingyi Xu Wei Wang Chau Yuen College of Information Engineering China Jiliang University Hangzhou P.R. China Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking College of Information Science and Electronic Engineering Zhejiang University Hangzhou P.R. China School of Electrical and Electronics Engineering Nanyang Technological University Singapore

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

Fueled by the increasing of smart mobile devices, the growth of crowd sensing tasks is explosive, where the Network Service Provider (NSP) relies on the sensing users (mobile devices) to sense and transmit fresh information. information freshness is captured by the Age of information (AoI) metric, which is a critical factor for real-time crowd sensing tasks. Considering the individual rationality of sensing users, it is challenged to design an AoI-aware task allocation since freshness means resource consumption. In this paper, an AoI-based dynamic pricing-matching approach is proposed to motivate sensing users to participate in tasks and also complete the task allocation. The problem is modeled as a many-to-many matching with the aim of improving the social welfare. Indeed, the differentiated AoI caused by various service priorities of sensing users should take into consideration. Toward this end, we divide sensing users into sub-users and derive the closed form of their corresponding AoI. Lastly, the proposed matching algorithm is validated to achieves a stable matching with dynamic prices and ensures the individual rationality. Simulation results demonstrate the proposed matching algorithm can achieve a significantly better social welfare than existing algorithms.

关键词： Measurement Vehicular and wireless technologies Heuristic algorithms Simulation information age Mobile handsets Real-time systems

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