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electrical, computer and Energy Technologies (ICECET), International Conference on

作者： Akeem. A. Azeez Biniyam Mezgebo Rodrigo França Sherif S. Sherif Biomedical Engineering Graduate Program University of Manitoba Winnipeg Canada Dept. of Electrical andComputer Engineering University of Manitoba Winnipeg Canada Dept. of Restorative Dentistry University of Manitoba Winnipeg Canada Dept. of Electrical and Computer Engineering University of Manitoba Winnipeg Canada

This paper presents an optical coherence tomography (OCT) system in conjunction with a novel image reconstruction technique employed for in vitro imaging of human teeth. The primary goal is to enhance the signal-to-noise ratio (SNR) in the obtained images. The study entails a comparative analysis between the conventional Fast Fourier Transform (FFT) OCT image reconstruction method and a newly introduced scaled nonuniform discrete Fourier transform (NDFT) approach. The findings reveal that the NDFT method consistently delivers superior results in terms of peak signal-to-noise ratio (PSNR) and overall image quality, even when dealing with redundant and nonuniform frequency domain samples. In light of these results, this paper concludes that integrating NDFT into OCT procedures has the potential to significantly enhance the quality of image reconstructions, thereby fostering its broader application in the field of dental imaging.

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Stunting Classification in Toddlers: Implementation and Evaluation of the Decision Tree Algorithm

Stunting Classification in Toddlers: Implementation and Eval...

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Information Technology and Computing (ICITCOM), International Conference on

作者： Debby Alita Imam Ahmad Rhaishudin Jafar Rumandan Moh Erkamim Widyasmoro Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Islamic Education Management Study Program Institut Agama Islam Negeri Ambon Ambon Indonesia Smart City Information Systems Study Program Universitas Tunas Pembangunan Surakarta Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350379839

ISBN: (纸本)9798350379846

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data.

关键词： Pediatrics Accuracy Computational modeling Prevention and mitigation Data models Classification algorithms Decision trees Data mining Information technology Diseases

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A multimodal integrative approach to model transcriptional addiction of thyroid cancer on RUNX2

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Cancer Communications 2022年第9期42卷 892-896页

作者： Emanuele Vitale Elisabetta Sauta Mila Gugnoni Federica Torricelli Veronica Manicardi Alessia Ciarrocchi Laboratory of Translational Research Azienda Unità Sanitaria Locale-IRCCS di Reggio EmiliaReggio Emilia 42123Italy Clinical and Experimental Medicine PhD Program University of Modena and Reggio EmiliaModena 41121Italy Department of Electrical Computer and Biomedical EngineeringUniversity of PaviaPavia 27100Italy

Dear Editor Aberrant gene expression sustains massive proliferation and stress adaptation under the regulation of oncogenic transcription factors(TFs)whose binding across the genome orchestrates in space and time *** dependency defines the addiction of cancer cells to TFs on top of the regulatory hierarchy governing cancer dysregulated programs[1].These factors and their dependent mechanisms are an attractive and unexplored reservoir of potential targets for new anticancer ***,while the transcriptional landscape of many cancer-supportive TFs has been revealed,this information remains purely descriptive and confined to in vitro *** foster transferability,new approaches that integrate clinical data into the transcriptional networks are needed.

关键词： addiction modal reservoir

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Extending Cislunar Communication Network Reach Using Reconfigurable Intelligent Surfaces

arXiv

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arXiv 2024年

作者： Huroon, Aamer Mohamed Donmez, Baris Huang, Yu-Chih Kurt, Gunes Karabulut Wang, Li-Chun EECS International Graduate Program National Yang Ming Chiao Tung University Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Taiwan Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan Dept. of Electrical Engineering Polytechnique Montréal Montréal Canada

This study introduces a novel approach to enhance communication networks in the cislunar space by leveraging Reconfigurable Intelligent Surfaces (RIS). Using the ability of RIS to dynamically control electromagnetic waves, this paper tackles the challenges of signal attenuation, directivity, and divergence in cislunar missions, primarily caused by immense distances and that Earth-based station transmitters do not always face the Moon. A new optimization problem is formulated, whose objective is to maximize the received signal-to-noise ratio (SNR) for Earth-to-Moon communications. We derive a closed-form solution to the problem of determining the optimal RIS phase shift configuration based on the effective area of the RIS. Through extensive simulations, this paper demonstrates how optimal adjustments in RIS phase shifts can significantly enhance signal integrity, hinting at the substantial potential of RIS technology to revolutionize long-distance cislunar communication. Copyright © 2024, The Authors. All rights reserved.

关键词： Moon

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Safety Helmet Detection Using Deep Learning: Implementation and Comparative Study Using YOLOv5, YOLOv6, and YOLOv7

Safety Helmet Detection Using Deep Learning: Implementation ...

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Green Energy, Computing and Sustainable Technology (GECOST), International Conference on

作者： Nigel Dale Then Yung W. K. Wong Filbert H. Juwono Zee Ang Sim Dept. of Electrical and Computer Engineering Curtin University Malaysia Miri Malaysia Computer Science Program University of Southampton Malaysia Johor Malaysia

ISBN: (纸本)9781665486644

The safety of construction site personnel is highly dependent on the adherence of personal protective equipment (PPE) wearing. Safety helmet monitoring has become a popular topic in recent years as a result of the success in the field of image processing. Deep learning (DL) is widely used in object detection tasks due to its ability to create features based on raw data. Constant improvements in the DL models have led to numerous successful outcomes in the implementation of safety helmet detection tasks. The performance of different DL algorithms from previous studies will be assessed and studied in this review paper. The YOLOv5s (small) model, YOLOv6s (small) model, and the YOLOv7 model will be trained and evaluated in this paper.

关键词： Personal protective equipment Deep learning Head Computational modeling Object detection Feature extraction Safety

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A Voice-Assisted Approach for Vehicular Data Querying from Automotive IoT-Based Databases

A Voice-Assisted Approach for Vehicular Data Querying from A...

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International Workshop on Secure Internet of Things (SIoT)

作者： Matheus Andrade Esther Wanderley Mariana Azevedo Thaís Medeiros Marianne Silva Ivanovitch Silva Daniel G. Costa Postgraduate Program in Electrical and Computer Engineering (PPgEEC) Federal University of Rio Grande do Norte - Natal Brazil INEGI Faculty of Enzineering University of Porto Porto Portugal

The automotive industry's transformative conver-gence of cutting-edge technologies, such as the Internet of Things (loT), electronic voice assistants, and custom APls, have paved the way for a remarkable array of opportunities to enhance vehicle security while revolutionizing user-car interactions. Actually, when leveraging loT sensors of multiple types and configurations, their produced, collected, and stored real-time data may offer in-depth and comprehensive insights into vehicle information, opening many possibilities when loT-generated databases are created. In this context, the primary goal of this paper is to create a new approach based on the popular Amazon Alexa voice assistant, which would allow facilitated queries of vehicular data from cloud-based databases. For that, a new Alexa service (skill) is created, as well as a custom API, allowing easy access to different types of data previously retrieved from vehicular sensors and properly stored. Doing so, the implemented skill indirectly processes data from loT sensors through the custom API, enabling users to access vital vehicular information using intuitive voice commands, remotely. A case study in a real scenario is conducted to validate and confirm the feasibility of real-time vehicle information access, showcasing the benefits of the proposed approach when combined with other solutions in a macro vehicular-centric loT ecosystem.

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Diabetic Retinopathy Detection: Improving Accuracy Using Multiple Transfer Learning Features from Pre-trained Deep Learning Networks

Diabetic Retinopathy Detection: Improving Accuracy Using Mul...

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Green Energy, Computing and Sustainable Technology (GECOST), International Conference on

作者： Kelvin Ka Yung Tiong W. K. Wong Filbert H. Juwono I. M. Chew Dept. of Electrical and Computer Engineering Curtin University Malaysis Miri Malaysia Computer Science Program University of Southampton Malaysia Nusajaya Malaysia

ISBN: (纸本)9781665486644

Diabetic Retinopathy (DR) is a type of complications caused by diabetes. Patients with DR may experience worsening vision, blindness, and eye pain. To effectively address this disorder, DR must be identified and classified according to its severity. Therefore, automated diagnosis of fundus lesions is of great interest for DR early detection. The development of deep learning technology has provided a strong foundation for effective implementation of the automated detection system. In particular, transfer learning techniques have greatly benefited the research community to reduce computation and reuse trained features. In this paper, the outputs from the ”average pooling” and ”fully connected” layers are used as the features to the Support Vector Machine (SVM) classifier with Error Correction Output Code (ECOC). The proposed method outperforms the fine-tuned pre-trained networks in predicting the severity classes with an accuracy of 80.1%. This means that multiple features extracted from the pre-trained networks contribute to a better recognition process.

关键词： Support vector machines Deep learning Training Retinopathy Pain Transfer learning Blindness

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Unbiased Parameter Estimation for Partially Observed Diffusions

arXiv

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arXiv 2023年

作者： Awadelkarim, Elsiddig Jasra, Ajay Ruzayqat, Hamza Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this article we consider the estimation of static parameters for partially observed diffusion process with discrete-time observations over a fixed time interval. In particular, we assume that one must time-discretize the partially observed diffusion process and work with the model with bias and consider maximizing the resulting log-likelihood. Using a novel double randomization scheme, based upon Markovian stochastic approximation we develop a new method to unbiasedly estimate the static parameters, that is, to obtain the maximum likelihood estimator with no time discretization bias. Under assumptions we prove that our estimator is unbiased and investigate the method in several numerical examples, showing that it can empirically out-perform existing unbiased *** Codes 60J22, 62M05, 65C40, 62M20 © 2023, CC BY.

关键词： Parameter estimation

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Plasmonic BICs as Biosensors with Better Detectivity

Plasmonic BICs as Biosensors with Better Detectivity

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Conference on Lasers and Electro-Optics (CLEO)

作者： Zhichao Li Ciril S. Prasad Xielin Wang Gururaj V. Naik Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Department of Electrical and Computer Engineering Rice University Houston TX USA

Plasmonic sensors exhibit high sensitivity due to enhanced local fields. But, their detectivity is poor because of their poor Q-factors. Using a plasmonic BIC, we experimentally demonstrate enhanced Q-factors in a pla... 详细信息

ISBN: (纸本)9781957171258

关键词： Absorption spectroscopy Field enhancement Optical sensing Plasmonic sensors Q factor Sensor performance

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Unified Variational Approach Description of Ground-State Phases of the Two-Dimensional Electron Gas

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Physical Review Letters 2024年第26期133卷 266504-266504页

作者： Conor Smith Yixiao Chen (陈一潇) Ryan Levy Yubo Yang (杨煜波) Miguel A. Morales Shiwei Zhang Center for Computational Quantum Physics Flatiron Institute New York New York 10010 USA Department of Electrical and Computer Engineering University of New Mexico Albuquerque New Mexico 87131 USA Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

The two-dimensional electron gas (2DEG) is a fundamental model, which is drawing increasing interest because of recent advances in experimental and theoretical studies of 2D materials. Current understanding of the ground state of the 2DEG relies on quantum Monte Carlo calculations, based on variational comparisons of different Ansätze for different phases. We use a single variational ansatz, a general backflow-type wave function using a message-passing neural quantum state architecture, for a unified description across the entire density range. The variational optimization consistently leads to lower ground-state energies than previous best results. Transition into a Wigner crystal (WC) phase occurs automatically at rs=37±1, a density lower than currently believed. Between the liquid and WC phases, the same ansatz and variational search strongly suggest the existence of intermediate states in a broad range of densities, with enhanced short-range nematic spin correlations.

关键词： Wave functions

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