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arXiv 2024年

作者： Belaustegui, Ian Xul Arango, Marcela Ordorica Rossi-Pool, Roman Leonard, Naomi Ehrich Franci, Alessio Department of Mechanical and Aerospace Engineering Princeton University United States Instituto de Fisiología Celular - Neurociencias Centro de Ciencias de la Complejidad Universidad Nacional Autónoma de México Mexico Department of Electrical Engineering and Computer Science University of Liege WEL Research Institute Wavre Belgium

An important problem in many areas of science is that of recovering interaction networks from simultaneous time-series of many interacting dynamical processes. A common approach is to use the elements of the correlation matrix or its inverse as proxies of the interaction strengths, but the reconstructed networks are necessarily undirected. Transfer entropy methods have been proposed to reconstruct directed networks but the reconstructed network lacks information about interaction strengths. We propose a network reconstruction method that inherits the best of the two approaches by reconstructing a directed weighted network from noisy data under the assumption that the network is sparse and the dynamics are governed by a linear (or weakly-nonlinear) stochastic dynamical system. The two steps of our method are i) constructing an (infinite) family of candidate networks by solving the covariance matrix Lyapunov equation for the state matrix and ii) using L1-regularization to select a sparse solution. We further show how to use prior information on the (non)existence of a few directed edges to drastically improve the quality of the reconstruction. © 2024, CC BY-SA.

关键词： Covariance matrix

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COVID-19 Vaccine and Booster Shots Compatibility Analyzer using CMOS-based Monochrome Encoding

COVID-19 Vaccine and Booster Shots Compatibility Analyzer us...

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International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)

作者： Ken Sammuel I. Camacho Megan Victoria Hillary Y. Chua-Unsu Ryan Rhay P. Vicerra Ronnie Concepcion Raouf N.G. Naguib Department of Manufacturing Engineering and Management De La Salle University Manila Philippines School of Mathematics Computer Science and Engineering Liverpool Hope University Liverpool United Kingdom

The continuous increase in COVID-19 positive cases in the Philippines might further weaken the local healthcare system. As such, an efficient system must be implemented to further improve the immunization efforts of the country. In this paper, a contactless digital electronic device is proposed to assess the vaccine and booster brand compatibility. Using Logisim 2.7.1, the logic diagrams were designed and simulated with the help of truth tables and Boolean functions. Moreover, the finalized logic circuit design was converted into its equivalent complementary metal-oxide semiconductor (CMOS) and stick diagrams to help contextualize how the integrated circuits will be designed. Results have shown that the proposed device was able to accept three inputs of the top three COVID-19 vaccine brands (Sinovac, AstraZeneca, and Pfizer) and assess the compatibility of heterologous vaccinations. With the successful results of the circuit, it can be concluded that this low-power device can be used to manufacture a physical prototype for use in booster vaccination sites.

关键词： COVID-19 Logic circuits Prototypes Personal digital devices Encoding Software Vaccines

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Machine Learning on Stroke Risk Prediction Systems as Complementary Technology for Neurologists: A Critical Review

Machine Learning on Stroke Risk Prediction Systems as Comple...

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International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)

作者： Chrischell Lucas Kathrina Clarisse Padrique Mariah Christa lansangan Maria Jena Isabel Gusi Marian Lubag Ronnie Concepcion Sandy lauguico Ryan Rhay Vicerra Raouf N. G. Naguib Department of Manufacturing Engineering and Management De La Salle University Manila Philippines School of Mathematics Computer Science and Engineering Liverpool Hope University Liverpool United Kingdom

Stroke is considered the second-leading cause of death all over the world. Due to the risks entangled with stroke, the need to identity its early signs and symptoms is vital in preventing it. By recognizing the modifiable and non-modifiable risk factors related to stroke, numerous systems are developed through a machine learning (ML) approach. Ergo, utilizing stroke-risk prediction systems could prevent its occurrence and minimize fatality. This literature review focuses on assessing the current models and systems available. Numerous studies stick to utilizing traditional machine learning algorithms although the machine learning pipelines of the reviewed studies are mostly in question due to the lack of performing data pre-processing techniques. On the other hand, there are several studies which develop new machine learning algorithms based on traditional algorithms to perform more specific predictions. There has also been a perceived increase in studies wherein graphical user interface (GUI) is integrated in the process of presenting the results of a prediction system and this trend helps deliver the established systems to be used in the healthcare industry. Although that seems to be the end goal, implementation of machine learning algorithms still can be improved by setting guidelines and reporting standards to increase the acceptability and face validity of the algorithms’ predictions. Factor assessment is also key in addressing issues surrounding the transparency of machine learning by showing how risk factors have contributed to the prediction. Overall, further study and continued research on its reliability and dependability may aid in the forward trajectory of modern diagnosis.

关键词： Industries Machine learning algorithms Machine learning Medical services Predictive models Prediction algorithms Market research

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Penrose’s eight-conic theorem via Penrose’s eight-quadric theorem

arXiv

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arXiv 2024年

作者： Arnold, Russell Chern, Albert Eide, Morten Gunn, Charles Neukirchner, Thomas Penrose, Roger Mathematical Section Goetheanum Dornach Switzerland Department of Computer Science and Engineering University of California San Diego La Jolla United States Jevnaker Norway Falkensee Germany Free Waldorf School Karlsruhe Germany Mathematical Institute University of Oxford United Kingdom

This article proves the following theorem, first enunciated by Roger Penrose about 70 years ago but never published: In P2, if conics are assigned to seven of the vertices of a combinatorial cube such that (i) conics connected by an edge are in double contact, and (ii) the chords of contact associated to a cube face meet in a common point, then there exists an eighth conic such that the completed cube satisfies (i) and (ii). The theorem turns out to be a remarkable generalization of many well-known theorems of projective geometry – Pappus, Desargues, Pascal, Brianchon, Monge, and Poncelet are the best-known ones. This archetypal principle provides a unifying framework in which the myriad specializations of the theorem and their interrelationships can be grasped as an organic whole, enriching the field of projective geometry and opening new vistas for research. The article begins with a series of motivational examples. It then gives a geometric proof assuming that the conics are regular, followed by an algebraic one that removes this restriction. The geometric proof is obtained as a slice of an analogous theorem for quadrics in P3;the algebraic one is based on the determinants of a special matrix associated to the configuration of *** Codes 00A05 © 2024, CC BY-NC-ND.

关键词： Geometry

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Simultaneous Information and Energy Transmission with Short Packets and Finite Constellations

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IEEE Transactions on Communications 2025年

作者： Zuhra, Sadaf ul Perlaza, Samir M. Poor, H. Vincent Skoglund, Mikael Princeton University Department of Electrical and Computer Engineering PrincetonNJ08540 United States INRIA Centre Inria d’Université Côte d’Azur 2004 Route des Lucioles Sophia Antipolis06902 France Laboratoire de Mathématiques GAATI Université de la Polynésie Française French Polynesia KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Malvinas Väg 10 Stockholm11428 Sweden

This paper characterizes the trade-offs between information and energy transmission over an additive white Gaussian noise channel in the finite block-length regime with finite channel input symbols. These trade-offs are characterized in the form of inequalities involving the information transmission rate, energy transmission rate, decoding error probability (DEP) and energy outage probability (EOP) for a given finite block-length code. The first set of results identify a set of necessary conditions that a given code must satisfy for simultaneous information and energy transmission. Following this, a novel method for constructing a family of codes that can satisfy a target information rate, energy rate, DEP and EOP is proposed. Finally, achievability results identify the set of tuples of information rate, energy rate, DEP and EOP that can be simultaneously achieved by the constructed family of codes. © 1972-2012 IEEE.

关键词： Gaussian noise (electronic)

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Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

arXiv

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arXiv 2024年

作者： Liu, Jian Sun, Wei Yang, Hui Zeng, Zhiwen Liu, Chongpei Zheng, Jin Liu, Xingyu Rahmani, Hossein Sebe, Nicu Mian, Ajmal The National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China The School of Architecture and Art Central South University Changsha410082 China The Department of Automation Tsinghua University Beijing100084 China The School of Computing and Communications Lancaster University LA1 4YW United Kingdom The Department of Information Engineering and Computer Science University of Trento Trento38123 Italy The Department of Computer Science The University of Western Australia WA6009 Australia

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features. Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects. A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing. To fill this gap, we discuss the recent advances in deep learning-based object pose estimation, covering all three formulations of the problem, i.e., instance-level, category-level, and unseen object pose estimation. Our survey also covers multiple input data modalities, degrees-of-freedom of output poses, object properties, and downstream tasks, providing the readers with a holistic understanding of this field. Additionally, it discusses training paradigms of different domains, inference modes, application areas, evaluation metrics, and benchmark datasets, as well as reports the performance of current state-of-the-art methods on these benchmarks, thereby facilitating the readers in selecting the most suitable method for their application. Finally, the survey identifies key challenges, reviews the prevailing trends along with their pros and cons, and identifies promising directions for future research. We also keep tracing the latest works at Awesome-Object-Pose-Estimation. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Design and Implementation of a QoL Improvement System for Visually Impaired Patients

Design and Implementation of a QoL Improvement System for Vi...

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International Conference on Advances in Computational Tools for engineering Applications, ACTEA

作者： Roy Abi Zeid Daou Jad Beaino Johnny Hawat Ramy Ibrahim Ali Hayek Josef Boercsoek Jose Javier Serrano Olmedo Mechatronics department Faculty of Engineering Université La Sagesse Beirut Lebanon MART Learning Education and Research Center Chananir Lebanon Department Lippstadt 2 Hardware Engineering University of Applied Science Hamm-Lippstadt Hamm Department of Computer Architecture and System Programming Faculty of Electrical Engineering/Computer Science University of Kassel Germany Lab of Bioinstrumentation and Nanomedicine Centro de Tecnología Biomédica Universidad Politécnica de Madrid Spain

Visually impaired people encounter several challenges in their mobility and navigation. Their daily activities are obstructed due to their inability to adapt or recognize accurately their surroundings, especially outside their house which they are more familiar with. Thus, it becomes the main reason of accidents, falling off, getting lost in unknown areas, etc. Furthermore, one of the sensory systems that helps the body to process data about the external environment is the visual system. Blind people also lose touch with the outside world, develops poor motor habits, which results in postural problems as a result. This project will assist visually impaired people in their daily life and simplify normal tasks through a system combining two previously designed projects, “Smart Shoes for Blind and Visually Impaired People”, and “Human posture monitoring device”. The multifunctional system is developed with the goal of securing safe movements for visually impaired people as well as maintaining a good back posture by detecting leaning postures (LP). The purpose of the smart shoe is to identify obstacles and protect the user from unintended accidents. A compatible Android application has been developed to alert the user when there is an obstruction or when he is walking on a wet surface. Voice alarms will be used to acoustically alert the user. If the user collapses, a message with their position will be sent right away to a relative. On the other hand, the smart vest will identify the position of the user's back and alert him to maintain a straight posture through the same application as well. As the system is dealing with human health, some safety measurements would be taken into consideration to implement a safe electrical system in order to reduce error and to increase accuracy.

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Bee Identification Problem for DNA Strands

Bee Identification Problem for DNA Strands

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IEEE International Symposium on Information Theory

作者： Johan Chrisnata Han Mao Kiah Alexander Vardy Eitan Yaakobi School of Physical and Mathematical Sciences Nanyang Technological University Singapore Department of Computer Science Technion &#x2014 Israel Institute of Technology Haifa Israel Department of Electrical and Computer Engineering University of California San Diego La Jolla USA

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

Motivated by DNA-based applications, we generalize the bee identification problem proposed by Tandon et al. (2019). In this setup, we transmit all M codewords from a codebook over some channel and each codeword results in N noisy outputs. Then our task is to identify each codeword from the MN noisy ***, via a reduction to a minimum-cost flow problem on a related flow network ${\mathcal{G}_N}$, we show that the problem can be solved in O(M 3 ) time in the worst case. Next, we consider the deletion channel and study the expected number of edges in the network ${\mathcal{G}_N}$. Specifically, we obtain closed expressions for this quantity for certain codebooks and when the codebook comprises all binary words, we show that this quantity is sub-quadratic when the deletion probability is less than 1/2. This then implies that the expected running time for this codebook is o(M 3 ). For other codebooks, we develop methods to compute the expected number of edges efficiently. Finally, we adapt classical peeling-decoding techniques to reduce the number of nodes and edges in ${\mathcal{G}_N}$.

关键词： DNA Genetic communication Noise measurement Task analysis Manganese

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Weight Perception Analysis using Electroencephalographic Signals : Full/regular papers, CSCI-ISPC

Weight Perception Analysis using Electroencephalographic Sig...

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International Conference on Computational science and Computational Intelligence (CSCI)

作者： Murtaza Aslam Fozia Rajbdad Ö mer M. Soysal Electrical and Computer Engineering Department Louisiana State University Baton Rouge LA Computer Science Department Southeastern Louisiana University Hammond LA

Haptics is the study of coupling the human sense of touch and motion with computer systems. In this study, we analyze weight perception of the brain based on electroencephalographic signals, which is obtained using a pressure tactile as a stimulus. The state of weight perception is represented by the relative power of alpha and beta sub-bands of subjects. Independent Component Analysis is applied for post-processing. In the final stage, Linear Discriminant Analysis and Support Vector Machine techniques are utilized for classification of the brain signals as either holding a weight or being in a resting state. Our proposed method achieved satisfactory performance when Support Vector Machine with Radial Basis Function kernel classifier and relative power features, which are obtained from the alpha sub-band of four EEG channels, were used.

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Towards Real-Time Monitoring of Thermal Ablation Lesions in Liver Using Microwave Imaging

Towards Real-Time Monitoring of Thermal Ablation Lesions in ...

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Antennas and Propagation Society International Symposium

作者： Sunil Gaddam Poulami Samaddar Keerthy Gopalakrishnan Devanshi Damani Suganti Shivaram Shuvashis Dey Dipankar Mitra Sayan Roy Shivaram P. Arunachalam Dept. of Medicine Microwave Engineering & Imaging Lab (MEIL) Division of Gastroenterology and Hepatology Mayo Clinic Rochester MN USA Department of Cardiology Rochester MN USA Department of Pharmacology Mayo Clinic Rochester MN USA Dept. of Electrical and Computer Engineering North Dakota State University Fargo ND USA Dept. of Computer Science University of Wisconsin-La Crosse La Crosse WI USA Dept. of Electrical Engineering and Computer Science South Dakota Mines Rapid City SD USA Department of Radiology Mayo Clinic Rochester MN USA

Minimally invasive ablative therapies have been used extensively to treat hepatic tumors in patients where surgical resections are not needed. Besides electroporation, ablation therapies induce extreme temperatures, i.e., hypothermia or hyperthermia, to cause irreversible damage to the tissue cells. The lesion volume created as a result depends on the temperature gradient in the tissue. Accurate and sensitive temperature monitoring is critical to optimize the treatment and reduce the risk of complications and extrahepatic injury. This study presents an approach to assess the tissue temperatures non-invasively using microwave imaging (MWI). A cross-section of a liver phantom is used for microwave imaging electromagnetic simulation at 915 MHz. Dielectric properties of porcine liver tissue at 915 MHz and varying temperatures are gathered from the literature. Point sources placed around the phantom model act as transmitters and receivers. Distorted Born Iterative Method (DBIM) was used to reconstruct the relative permittivity that is mapped to the temperature field and compared. The mapped temperature field from the reconstructed dielectric parameters resembles the temperature field used to create the phantom model demonstrating the feasibility of using MWI for the non-invasive assessment of liver tissue temperatures for ablative therapies

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