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Eye Tracking System Using Convolutional Neural Network 5

Eye Tracking System Using Convolutional Neural Network

引用

5th International Conference on computer and Applications, ICCA 2023

作者： Iskandar, Shatha Jaara, Zahraa Ali, Mohamad Abou Sbeity, Fatima Kasem, Abdallah Hamawy, Lara Lebanese International University Department of Biomedical Engineering Lebanon University of the Basque Country Dept.of Computer Science & Artificial Intelligence Spain Lebanese University Dept. of Physics & Electronics Lebanon Notre Dame University Dept. of Electrical & Computer Engineering Lebanon

ISBN: (纸本)9798350303254

Several diseases and disabilities, including cerebral palsy (CP), cause patients to lose their ability to communicate easily with the outside world. In this paper we aim to detect the movement of the iris that can be used to move a wheelchair for CP patients, write sentences by simply looking at an interactive screen, or even by moving an artificial arm. Thus, the two-dimensional CNN model and the coding method, we proposed, tracks the eye movement, specifically the movement of the iris, using VGG image annotator software and a dataset of several people's eyes images A dataset of 500 images from several patients, where only the eyes were cropped and studied, was taken to train the model about eye movement and detection. The proposed model achieved a mean squared error drop of about 49,720 from the original we started with, which was 50,000. © 2023 IEEE.

关键词： Neural network models

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MedicaLog: Transforming Healthcare with AI-Powered Health Data Platform

MedicaLog: Transforming Healthcare with AI-Powered Health Da...

引用

2023 IEEE biomedical Circuits and Systems Conference, BioCAS 2023

作者： Isiksalan, Isil Worcester Polytechnic Institute Dept. of Electrical and Computer Engineering Worcester United States

ISBN: (纸本)9798350300260

In this paper, we present MedicaLog, a novel health data platform designed to tackle key challenges in contemporary healthcare. A significant global deficiency in shared health data repositories has impeded efficient health management, leaving nearly 3.5 billion individuals without basic health services. [1] MedicaLog employs exponential technologies like wearable electronics and IoT to continuously gather and process diverse health *** detail the primary challenges in the existing healthcare domain, underscoring the need for a tailored, proactive healthcare strategy. Our market analysis delves into the prospects and obstacles of this pioneering solution. The financial blueprint underscores MedicaLog's feasibility and its vast potential for *** main focus explores MedicaLog's evolution, embracing solution design and prototype creation. Our iterative innovation approach ensures a compelling user experience. The journey provides insights, emphasizing user engagement and AI-driven digital twin *** conclusion, MedicaLog proposes a groundbreaking, integrated, and patient-oriented healthcare paradigm. This paper outlines MedicaLog's development and its prospective role in reshaping global health. © 2023 IEEE.

关键词： exponential technologies healthcare innovation design

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Fast Image Quantization with Efficient Color Clustering 18

Fast Image Quantization with Efficient Color Clustering

引用

Colloidal Nanoparticles for biomedical Applications XVIII 2023

作者： Liu, Yingying Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

ISBN: (纸本)9781510658950

Color image quantization has been widely used as an important task in graphics manipulation and image processing. The key to color image quantization is to generate an efficient color palette. At present, there are many color image quantization methods that have been presented, which are fundamentally clustering-based algorithms. As an illustration, the K-means clustering algorithm is quite popular. However, the K-means algorithm has not been given sufficient focus in the field of color quantization due to its high computational effort caused by multiple iterations and its very susceptibility to initialization. This paper presented an efficient color clustering method to implement fast color quantization. This method mainly addresses the drawbacks of the conventional K-means clustering algorithm, which involves reducing the data samples and making use of triangular inequalities to accelerate the nearest neighbor search. The method mainly contains two stages. During the first phase, an initial palette is generated. In the second phase, quantized images are generated by a modified K-means method. Major modifications include data sampling and mean sorting, avoiding traversal of all cluster centers, and speeding up the time to search the palette. The experimental results illustrate that this presented method is quite competitive with previously presented color quantization algorithms both in the matter of efficiency and effectiveness. © 2023 SPIE.

关键词： Nearest neighbor search

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Chest Radiographs Enhancement with Contrast Limited Adaptive Histogram 17

Chest Radiographs Enhancement with Contrast Limited Adaptive...

引用

17th International Conference on Ubiquitous Information Management and Communication, IMCOM 2023

作者： Lee, Hyeri Choo, Hyunseung Le, Duc-Tai Bum, Junghyun Sungkyunkwan University Dept. of Electrical and Computer Engineering Suwon Korea Republic of College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9781665453486

Among all the image contrast enhancement methods, histogram equalization is the most widely used. However, conventional histogram equalization causes the entire image to be too bright, resulting in noise generation as a consequence of excessive brightness changes and information loss when the histogram is intensively distributed into a specific amount of brightness. The Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm is designed to address these limitations. To avoid overamplifying brightness variations, CLAHE clips the histogram of an input image to make it uniformly distributed. This study employs the CLAHE algorithm to improve contrast in chest radiographs, with the expected result that lung disease diagnosis will be more accurate. © 2023 IEEE.

关键词： Image reconstruction

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Federated Learning with Clustering-Based Participant Selection for IoT Applications

Federated Learning with Clustering-Based Participant Selecti...

引用

2022 IEEE International Conference on Big Data, Big Data 2022

作者： Wang, Kevin I-Kai Ye, Xiaozhou Sakurai, Kouichi The University of Auckland Dept. of Electrical Computer and Software Engineering Auckland New Zealand Kyushu University Dept. of Informatics Fukuoka Japan

ISBN: (纸本)9781665480451

Modern Internet of Things (IoT) systems are highly complex due to its mobile, ad-hoc and geographically distributed nature. Very often, an edge-cloud infrastructure is established to offer intelligent services in modern IoT systems. However, IoT edge devices are typically resource-constrained and can not perform sophisticated machine learning algorithm on board. Data sharing with a central server is a common approach of crowdsourcing, but also brings privacy and security concerns. The emerging federated learning offers a promising pathway to achieve an accurate model through distributed machine learning while ensuring data privacy. The existing federated learning process is not tailored to the mobile and adhoc nature of IoT systems where devices are of varying data and system qualities and may not be able to participate the entire training process. Therefore, in this paper, a new federated learning framework is proposed to support asynchronous model fusion with clustering-based participant selection. The proposed framework aims to accommodate the ad-hoc nature of IoT devices, and at the same time avoiding low quality or even malicious data from its participants to ensure model convergence and performance. © 2022 IEEE.

关键词： Internet of things

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An exact based approach for the Post Enrollment Course Timetabling Problem 26

An exact based approach for the Post Enrollment Course Timet...

引用

26th Pan-Hellenic Conference on informatics, PCI 2022

作者： Dimitsas, Angelos Nastos, Vasileios Gogos, Christos Valouxis, Christos Dept. of Informatics & Telecommunications University of Ioannina Arta Epirus Greece Dept. of Electrical & Computer Engineering University of Patras Rio Greece

ISBN: (纸本)9781450398541

Educational timetabling has long piqued the interest of the scheduling community. Since timetabling governs how universities operate daily, it has been vital in academia to put substantial effort into creating schedules of the highest caliber. To create schedules that satisfy all stakeholders, various approaches have been tried to solve educational timetabling problems, which are typically NP-Hard. Over the past 20 years, several scheduling contests have been held with a focus on issues related to educational operations. In this paper, we focus on the Post Enrollment Course Timetabling Problem and two datasets from the International Timetabling Competitions held in 2002 and 2007. We propose a local search procedure augmented by a base mathematical model and variations of this model that yields competitive results, within reasonable execution times, to some of the best-known solutions. © 2022 ACM.

关键词： Integer programming

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Modeling of Photovoltaic-Wind Hybrid Systems 3

Modeling of Photovoltaic-Wind Hybrid Systems

引用

3rd International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2022

作者： Isaied, Mohammad Tarabsheh, Anas Al Abu Dhabi University Dept. of Computer And Biomedical Engineering Abu Dhabi United Arab Emirates Abu Dhabi University Dept. Electrical Computer And Biomedical Engineering Abu Dhabi United Arab Emirates The Hashemite University Dept. Faculty of Engineering Electrical Engineering Zarqa Jordan

ISBN: (数字)9781665491495

ISBN: (纸本)9781665491495

This article proposes a model for photovoltaic-wind hybrid systems. The system under investigation comprises five PV modules attached to the blades of a vertical-axis wind turbine. The solar irradiation readings at each PV module are monitored at three different tilt angles: 90°(default), 50°, and 10°. These measurements are taken on many selected days at random times around noon. This paper calculates the solar irradiation received at each PV module and estimates the optimum tilt angle of the system. A simple clear sky model is used for the calculation, the input data of the model is the solar geometry, including location latitude, solar azimuth angle and solar elevation angle, no aerosol or atmospheric data is necessary. A comparison between measurement and calculated data is conducted, and the result shows that the optimum tilt angle is 50°. The mean absolute percentage error is computed between the measured and calculated values and shows that it ranges between 11% and 17% at a 90° tilt angle, and between 5% and 17.4% at a 50° tilt angle. © 2022 IEEE.

关键词： Wind power

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Localization of Dengue Virus Likelihood Using Image Processing Technique 6

Localization of Dengue Virus Likelihood Using Image Processi...

引用

6th IEEE International Conference on Emerging Smart Computing and informatics, ESCI 2024

作者： Hosen, Md. Mahbub Islam, Md. Rahatul Tabassum, Faria Tonni, Syeda Thamina Noor, Malik Mohammad Nafiur Rahman, Shahid Northern University of Bangladesh Dept. of Computer Science and Engineering Dhaka Bangladesh Kyushu Institute of Technology Dept. of Human Intelligence Systems Wakamatsu Kitakyushu Japan Bangladesh University of Engineering and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Bangladesh Advance Robotics Research Center Human Intelligence Lab Dhaka Bangladesh Canadian University of Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350306613

The Aedes mosquito, found in tropical areas, transmits, and causes dengue fever. The spread of the dengue fever virus from an infected Aedes mosquito bite typically takes between three and fifteen days to manifest itself clinically as dengue fever symptoms. Early and automated detection of this illness will reduce the occurrence of outbreaks and facilitate the digitization of the system. Our primary objective is to identify regions at high risk for dengue fever using limited image data through the utilization of sophisticated machine learning and image processing methods. This work showcases the application of transfer learning algorithms for the timely identification of regions at risk for dengue mosquito infestation, particularly in situations where obtaining early data on dengue outbreaks is challenging. The experiments included images of 2150 dengue-positive data sets and 1440 dengue-negative data sets. We used AI and image classifiers Yolo V4 Tin, Tensor Flow, Google Colab, etc. for the training data set, and the system makes predictions with a 99.63% accuracy rate. Our system has some unique attributes;it not only detects the percentage of dengue probability but also the specific dengue-prone location on the submitted image. © 2024 IEEE.

关键词： aedes mosquito dengue-prone image processing yolo v4 tiny

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An S-Matrix-Based Model of a Capacitive-Inductive Channel for Wireless Power and Data Transmission 30

An S-Matrix-Based Model of a Capacitive-Inductive Channel fo...

引用

30th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2023

作者： Liotta, Alessandro Moisello, Elisabetta Frattini, Giovanni Giannelli, Pietro Malcovati, Piero Bonizzoni, Edoardo University of Pavia Dept. of Electrical Computer and Biomedical Engineering Pavia Italy Analog Devices S.r.l. Vimercate Italy

ISBN: (纸本)9798350326499

This paper presents an S-matrix-based model for a capacitive-inductive structure, which serves as the channel for both power and data transmission in a wireless power transfer system. The power/data channel structure, consisting of two coil inductors, each surrounded with an open ring copper layer, allows simultaneous transmission of power and data while reducing power disturbances on the data transmission. An accurate modeling of the structure represents a significant challenge, as it is crucial for designing the integrated circuit that interfaces with it. To address this, a model based on S-matrix analysis is developed for the fabricated capacitive-inductive channel structure, using measurements as a basis. This model was subsequently compared to a discrete-circuit model through Cadence simulation. The results highlight that the S-matrix-based model provides a more precise representation of the structure, aligned with real behavior of the simultaneous wireless power and information transfer (SWPIT) system. © 2023 IEEE.

关键词： Data communication systems

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Detection of Attention Deficit Hyperactivity Disorder using Decision-level Fusion of Brain Connectivity Information Based on Deep Learning

Detection of Attention Deficit Hyperactivity Disorder using ...

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2023 Medical Technologies Congress, TIPTEKNO 2023

作者： Cura, Ozlem Karabiber Ciklacandir, Fatma Gunseli Akan, Aydin Atli, Sibel Kocaaslan Izmir Katip Celebi University Dept. of Biomedical Engineering Izmir Turkey Izmir Katip Celebi University Dept. of Computer Engineering Izmir Turkey Izmir University of Economics Dept. of Electrical and Electronics Eng. Izmir Turkey Izmir Katip Celebi University Faculty of Medicine Dept. of Biophysics Izmir Turkey

ISBN: (纸本)9798350328967

Attention Deficit Hyperactivity Disorder (ADHD) is a neurological disorder that often first appears in children. The condition is treated via behavioral studies, but there is no definitive technique to identify it. Electroencephalography (EEG) signals of ADHD patients are widely investigated to understand alterations in the brain. We offered EEG connectivity featured image creation to be used as input to CNN architectures in the proposed study. EEG data from 15 ADHD patients and 18 control participants are evaluated, and ADHD detection performance is shown, to demonstrate the efficacy of the suggested method. EEG connectivity featured images are obtained using six different connectivity features (magnitude square coherence, cross-power spectral density, correlation coefficient, covariance, cohentropy coefficient, and correntrophy coefficient). Deep features are extracted for each image subset using EEG connectivity-featured images to train ResNet-50. The effectiveness of the suggested strategy for detecting ADHD is assessed using the DT, LR, and SVM classifiers and decision-level fusion. According to experimental results, employing EEG connectivity featured images as input to ResNet-50 architecture, and decision-level fusion offers important advantages in identifying ADHD. © 2023 IEEE.

关键词： Electroencephalography

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