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International Conference on ent computing and Control Systems (ICICCS)

作者： Sweadha. M M. Selvi Dept. of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

The Smart Medical Box is a sophisticated IoT-driven solution designed to enhance medication adherence by utilizing computer vision and machine learning. The system automates the identification and extraction of essential information from medication labels, ensuring precision in dosage reminders and reducing human error. It incorporates a high-resolution camera, an OCR engine, and an Arduino-based microcontroller to enable seamless image processing and real-time analysis. With an intuitive interface and GPS-enabled location services, users can efficiently manage their medication schedules while accessing nearby pharmacies when needed. This research focuses on designing and implementing a scalable and cost-effective system that improves medication compliance and minimizes health risks associated with missed or incorrect dosages. By integrating advanced image processing techniques and AI-driven recognition algorithms, the Smart Medical Box ensures high accuracy in identifying medications. Additionally, features such as automated alerts, real-time monitoring, and pharmacy locator tools enhance the system's usability and accessibility. This innovation is particularly beneficial for elderly individuals and patients with chronic conditions, offering a simplified and automated approach to medication tracking. Performance evaluations of the system indicate a significant improvement in medication adherence, a high recognition accuracy rate, and positive user feedback. Future enhancements, including AI-based OCR, voice assistance, and mobile application connectivity, are expected to further improve functionality and ease of use. This paper presents the conceptualization, development, and testing of the Smart Medical Box, highlighting its potential to revolutionize personal healthcare management by providing an intelligent, efficient, and user-friendly solution.

关键词： Accuracy Image recognition Microcontrollers optical character recognition Medical services Real-time systems Usability Older adults Biomedical imaging Global Positioning System

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A Feature Extraction Method for Arabic Offline Handwritten Recognition System Using Naïve Bayes Classifier

A Feature Extraction Method for Arabic Offline Handwritten R...

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2021 International Conference on computing and Communications Applications and Technologies, I3CAT 2021

作者： Abdalkafor, Ahmed Subhi Alheeti, Khattab M. Ali Al-Jobouri, Laith University of Anbar Career Development Center Ramadi Iraq University of Anbar College of Computer Sciences and Information Technology Computer Networking Systems Department Ramadi Iraq Abertay University School of Design and Informatics United Kingdom

ISBN: (纸本)9781665424417

Handwriting recognition in the Arabic language is considered one of the most challenging problems and the accuracies in recognizing still need more enhancements due to the Arabic character's nature, cursive writing, style, and size of writing in contrast to working with other languages. In this paper, we propose a system for Arabic Offline Handwritten Character Recognition based on Naïve Bayes classifier (NB). Extraction features preceded by divided the image of character into three horizontal and vertical zones and 3x3 zones in one and two dimensions respectively, then classified by Naïve Bayes. The performance of the system proposes evaluated by using the benchmark CENPARMI database reached up to 97.05% accuracy rate. Experimental results confirm a high enhancement inaccuracy rate in comparison with other Arabic optical Character Recognition systems. © 2021 IEEE.

关键词： Starters

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Efficient and economical smart healthcare application based on quantum optical neural network

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optical and Quantum Electronics 2024年第3期56卷 445-445页

作者： Zhou, Tianyi Anuradha, T. Mahendra, S.J. Webber, Julian L. Mehbodniya, Abolfazl Wang, Jinsong Subrahmanyam, Kodukula School of Artificial Intelligence (School of Future Technology) Nanjing University of Information Science and Technology Nanjing China Department of Information Technology Velagapudi Ramakrishna Siddhartha Engineering College AP Kanuru Vijayawada India Department of Medical Electronics M S Ramaiah Institute of Technology Bengaluru India Department of Electronics and Communication Engineering Kuwait College of Science and Technology (KCST) Doha Area 7 Ring Road Kuwait City Kuwait Case School of Engineering Case Western Reserve University Cleveland Cleveland 44106 OH United States Department of CSE Koneru Lakshmaih Education Foundation Andhrapradesh Vaddeswaram Guntur India

In recent years, AI and quantum technologies have received a great deal of interest from a wide range of fields. This research introduces a novel methodology for creating AI systems that are both interpretable and clever, making them ideal for use in safe, trustworthy healthcare environments. In order to handle and analyse large healthcare datasets while maintaining privacy and security, our technology employs quantum optical neural networks (QONN). We place a premium on gathering useful healthcare data while strictly protecting individual privacy. The collected data undergoes meticulous cleaning and preprocessing, including normalization procedures to eliminate noise, outliers, and irrelevant information. The core of our approach involves the construction of a neural network utilizing both optical and quantum computing techniques. Key components of QONNs comprise qubits, optical elements, and conventional neural network layers. The training of the QONN is executed using pre-evaluated healthcare data, optimizing its performance through advanced techniques such as Improved Genetic Algorithms (IGA). Furthermore, we establish an AI system that employs explicit skill-based approaches. To achieve this, interpretability algorithms, saliency maps, and attention mechanisms may be essential tools. A critical aspect of this study involves a comprehensive evaluation of the AI system's performance. This evaluation includes soliciting feedback from qualified medical experts and implementing necessary enhancements and adjustments to augment its functionality and rectify any shortcomings. To assess the effectiveness of the constructed AI system, we conduct an analysis of pertinent metrics. We compare the system's results with those obtained using various healthcare analytics methods to ascertain its efficacy. This rigorous evaluation ensures that the AI system is not only functional but also a valuable asset in the realm of healthcare analytics and decision-making. © 2024, The Aut

关键词： Artificial intelligence (AI) Healthcare datasets Improved genetic algorithms (IGA) optical components Quantum optical neural networks (QONN)

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Webcam-Based OCR System with Text-to-Speech Conversion

Webcam-Based OCR System with Text-to-Speech Conversion

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Sustainable Communication Networks and Application (ICSCNA), International Conference on

作者： Rekha R Nair Tina Babu Kishore S Poornima J Madduru Sambasivudu Manchikalapudi Bhargavi Department of Computer Science and Engineering Alliance School of Advanced Computing Alliance University Bengaluru India Department of Computer Applications Nitte Institute of Professional Education Nitte(Deemed to be University) Mangalore India Department of Information Science and Engineering Brindavan College of Engineering Bengaluru India Department of Computer Science and Engineering Malla Reddy College of Engineering and Technology Hyderabad India

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530020

The project develops an OCR system that converts webcam-captured text to speech, featuring user registration for personalized experiences. Key components include image capture via webcam, text extraction using OCR, database storage, and text-to-speech conversion. The system employs Python, OpenCV for image processing, Tesseract for OCR, and Google Text-to-Speech for audio output. Main objectives are to streamline text digitization and assist visually impaired users. The modular design allows for future enhancements like language translation. Comprehensive testing ensures reliability and effectiveness. The system demonstrates an efficient solution for converting printed text to digital and audio formats, with applications in document digitization, education, and accessibility services. It reduces manual effort in text digitization and improves access to written information for visually impaired individuals, showcasing potential across various fields.

关键词： Translation Webcams Scalability optical character recognition User interfaces Streaming media Real-time systems Text to speech Reliability Testing

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Automatic Parking System Using Deep Learning and Internet of Things

Automatic Parking System Using Deep Learning and Internet of...

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Emerging Systems and Intelligent computing (ESIC), International Conference on

作者： Saddi Jyothi M. Rami Reddy Chinthalapudi Siva Vara Prasad Nimmagadda Rishita Toka Shyam Satya Vara Prasad Shaik Irfan Ali Department of Information Technology Lakireddy Bali Reddy College of Engineering Mylavaram Andhra Pradesh India Freshman Engineering Department Lakireddy Bali Reddy College of Engineering Mylavaram Andhra Pradesh India

To address the labour - intensive requirements of traditional parking lot operations, we have developed an automated system for access control, occupancy tracking, and revenue processing. The proposed system employs computer vision and deep learning techniques to autonomously handle parking lot ingress and egress while reducing operating costs. Vehicles entering and exiting the automated parking facility will be detected using infrared sensors interfaced to a Raspberry Pi microcomputer. License plate images will be captured by a Pi camera module and processed in real-time using an optical character recognition (OCR) algorithm based on a convolutional recurrent neural network architecture optimized for number plate recognition. Human access control can be handled in parallel by leveraging object detection models like Faster R-CNN or YOLO to differentiate pedestrian from vehicle ingress. The onboard occupancy tracking functionality will alleviate the need for manual counting of available spaces. Additionally, real-time parking availability stats will be published to a monitoring website allowing customers to view open slots prior to arrival. Lot capacity constraints can be configured to automatically disable entrance gates when maximum capacity is reached. The system’s sensor fusion and computer vision capabilities eliminate tedious manual tallying and oversight required by legacy parking systems. By autonomously controlling access gates, tracking and publishing occupancy stats, and extracting revenue data from license plates, the proposed automated parking lot system aims to reduce operating costs while creating a scalable solution applicable to facilities ranging from apartment complexes to large shopping malls. The use of a low-cost, open-source development platform promotes maintainability while allowing for customized enhancements.

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Progress in 6G technology: A Short Review

Progress in 6G Technology: A Short Review

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International Conference of Computer and Informatics Engineering (IC2IE)

作者： Muhammad Irfan Maulana Muhammad Suryanegara Dept. of Electrical Engineering Faculty of Technology Universitas Indonesia Depok Indonesia

With the ITU's approval of the new draft proposal recommendations within the IMT Framework document for the period beyond 2030, research has recognized that 6G mobile technology incorporates numerous enhancements in usage scenarios and capabilities. This paper presents a short review of the progress of 6G technological advancement, including its use cases, key performance indicators, innovations in network support technology, and several potential spectrum options. The review is developed based on primary literature, including the relevant ITU document that encompasses IMT 2030 usage scenarios (as of June 2023). In this paper, we try to define progress in research for new services related to 6G use cases. A simulation is conducted to offer an overview of the theoretical 6G capacity. The simulation for theoretical 6G capacity is based on the bandwidth of spectrum candidates between 100 MHz and 1000 MHz. For network support, we identify some requirements to support 6G networks, such as integrated access and backbone, integrated space and terrestrial networks, free-space optical networks, distributed cloud computing, and artificial intelligence. Finally, the paper will also delve into discussing the implications and challenges expected during the 6G implementation phase, including the fulfillment of the key performance indicator objectives and the key value indicator, which is divided into two main components: the first is growth, and the second is sustainability and efficiency domains.

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Engineering single-molecule fluorescence withasymmetric nano-antennas

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Light(Science & Applications) 2021年第5期10卷 858-866页

作者： Wenqi Zhao Xiaochaoran Tian Zhening Fang Shiyi Xiao Meng Qiu Qiong He Wei Feng Fuyou Li Yuanbo Zhang Lei Zhou Yan-Wen Tan State Key Laboratory of Surface Physics and Department of Physics Fudan UniversityShanghai 200433China Shanghai Institute for Advanced Communication and Data Science Shanghai UniversityShanghai 200444China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced CommunicationShanghai UniversityShanghai 200444China Department of Chemistry and State Key Laboratory of Molecular Engineering of Polymers Fudan UniversityShanghai 200433China Institute for Nanoelectronic Devices and Quantum Computing Fudan UniversityShanghai 200433China Collaborative Innovation Center of Advanced Microstructures Nanjing 210093China Multiscale Research Institute of Complex Systems Fudan UniversityShanghai 200433China

As a powerful tool for studying molecular dynamics in bioscience,single-molecule fluorescence detection providesdynamical information buried in ensemble *** in the near-infrared(NIR)is particularly usefulbecause it offers higher signal-to-noise ratio and increased penetration depth in tissue compared with *** low quantum yield of most NIR fluorophores,however,makes the detection of single-moleculefluorescence ***,we use asymmetric plasmonic nano-antenna to enhance the fluorescence intensity ofAlEE1000,a typical NIR dye,by a factor up to *** asymmetric nano-antenna achieve such an enhancement mainlyby increasing the quantum yield(to~80%)rather than the local field,which degrades the molecules'*** coupled-mode-theory analysis reveals that the enhancements stem from resonance-matching between antennaand molecule and,more importantly,from optimizing the coupling between the near-and far-ield modes withdesigner asymmetric *** work provides a universal scheme for engineering single-molecule fluorescence inthe near-infrared regime.

关键词： stability. asymmetric quantum

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enhancements of Model and Method in Lithography Hotspot Identification

Enhancements of Model and Method in Lithography Hotspot Iden...

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Design, Automation and Test in Europe Conference and Exhibition (DATE)

作者： Huang, Xuanyu Zhang, Rui Huang, Yu Wang, Peiyao Li, Mei Tsinghua Univ Ctr Nano & Micro Mech Dept Mech Engn Beijing Peoples R China HiSilicon Technol Co Ltd Shenzhen Peoples R China

ISBN: (纸本)9783981926354

The manufacturing of integrated circuits (ICs) has been continuously improved through the advancement of fabrication technology nodes. However the lithography hotspots (HSs) caused by optical diffraction problems seriously affect the yield and reliability of ICs. Although lithography simulation can accurately capture the HSs through physically simulating the lithography process, it requires a lot of computing resources, which usually takes > 100 CPU .h/mm(2) [1]. Due to the image recognition nature, the state-of-the-art HS identification algorithms based on deep learning have obvious advantages in reducing run time comparing to the traditional algorithms. However, its accuracy still needs to be enhanced since there are many false alarms of non-hotspots (NHSs) and escapes of the real HSs, which makes it difficult to be a signoff technique. In this paper, we propose two enhancements in HS identification. First, a hybrid deep learning model is proposed in lithography HS identification, which includes a CNN model to combine physical features. Second, an ensemble learning method is proposed based on multiple sub-models. The proposed enhanced model and method can achieve high HS identification accuracy on the benchmarks 1-4 of the ICCAD 2012 dataset with recall> 98.8%. In addition, it can achieve even 100% recall on the benchmark 1 and benchmark 3 while maintaining the precision at a high level with 53.6% and 87.1%, respectively. Moreover, for the first time it can achieve not only 100% recall on benchmark 5, but also high precision of 61.8%, which is much higher than any published deep learning methods for HSs identification, as far as we know. The proposed model and methodology can be applied in industrial IC designs due to its effectiveness and efficiency.

关键词： lithography hotspot ensemble learning deep learning convolutional neural network

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An optical microcavity and nanoantenna hybrid resonator

An optical microcavity and nanoantenna hybrid resonator

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作者： B Ferrando University of Amsterdam

学位级别：硕士

We have computationally examined the LDOS landscape of a hybrid optical microresonator composed of a Fabry-Perot cavity and a 75 nm gold nanocube antenna. We then develop a wide spectrum of understanding about the individual components: from the nanocube on a mirror scenario to the Fabry-Perot cavity alone. We computationally reach full tunability of the plasmonic resonance and study its induced polarity with quasi-normal modes for the nanocube-on-amirror conguration, while for the cavity we create a map of the transmission and re ection spectrum. We nally show asymmetric hybrid resonance lineshapes reminiscent of Fano interference phenomena which exceed LDOS enhancement values for each component when alone by 1/3, at over 15000. We construct a bottom-up assembly method to construct a sample and we then characterize it with dark eld microscopy, confocal microscopy, nanoparticle enhanced nonlinear emission and nanoparticle enhanced Raman experiments. We conclude that the Fabry-Perot-nanocube hybrid resonator holds the potential for monster LDOS enhancements, with direct implications in the strive for room temperature cavity QED, high delty single photon sources for quantum computing and sensor and detector technology.

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Waveguide-integrated silicon T centres

arXiv

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arXiv 2022年

作者： DeAbreu, A. Bowness, C. Alizadeh, A. Chartrand, C. Brunelle, N.A. MacQuarrie, E.R. Lee-Hone, N.R. Ruether, M. Kazemi, M. Kurkjian, A.T.K. Roorda, S. Abrosimov, N.V. Pohl, H.-J. Thewalt, M.L.W. Higginbottom, Daniel B. Simmons, S. Department of Physics Simon Fraser University BurnabyBCV5A 1S6 Canada Photonic Inc. CoquitlamBC Canada Département de physique Université de Montréal MontréalQCH3C 3J7 Canada Leibniz-Institut für Kristallzüchtung Berlin12489 Germany VITCON Projectconsult GmbH Jena07745 Germany

The performance of modular, networked quantum technologies will be strongly dependent upon the quality of their quantum light-matter interconnects. Solid-state colour centres, and in particular T centres in silicon, offer competitive technological and commercial advantages as the basis for quantum networking technologies and distributed quantum computing. These newly rediscovered silicon defects offer direct telecommunications-band photonic emission, long-lived electron and nuclear spin qubits, and proven native integration into industry-standard, CMOS-compatible, silicon-on-insulator (SOI) photonic chips at scale. Here we demonstrate further levels of integration by characterizing T centre spin ensembles in single-mode waveguides in SOI. In addition to measuring long spin T1 times, we report on the integrated centres’ optical properties. We find that the narrow homogeneous linewidth of these waveguide-integrated emitters is already sufficiently low to predict the future success of remote spin-entangling protocols with only modest cavity Purcell enhancements. We show that further improvements may still be possible by measuring nearly lifetime-limited homogeneous linewidths in isotopically pure bulk crystals. In each case the measured linewidths are more than an order of magnitude lower than previously reported and further support the view that high-performance, large-scale distributed quantum technologies based upon T centres in silicon may be attainable in the near term. Copyright © 2022, The Authors. All rights reserved.

关键词： Silicon on insulator technology

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