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Prospects of Solar Cell Technology from Silicon to Carbon Nanotube 9

Prospects of Solar Cell Technology from Silicon to Carbon Na...

9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

作者： Shabir, Aamar Cao, Jing Fouad, Emadelden Ullah, Muhammad Florida Polytechnic University Dept. of Electrical and Computer Engineering Lakeland United States C. Leon King High School IB Program Tampa United States Florida Polytechnic University Dept. of Engineering Physics Lakeland United States

ISBN: (数字)9781728184425

ISBN: (纸本)9781728184425

Solar cell is becoming one of the vibrant power generations among all the renewable energy resources and demanding the most attention of researchers to achieve the goal of increasing stability and efficiencies. To reinforce the advancement of the solar cell, carbon nanotubes (CNTs) have come out as a highly potential candidate due to the reasons of chirality, mean free path, conductivity, current density, etc. The CNT has a unique size, structure, and attractive characteristics which enable the bold concept of getting maximum power from a solar cell. The recent availability of the CNT in quantities and formats amenable opens a new window to improve the efficiency of the solar cell. This paper will present a prospect of the recent research about CNTs and their contribution as a potential material in solar cell technology. © 2022 IEEE.

关键词： Carbon nanotubes

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CLINICAL DETERIORATION PREDICTION IN BRAZILIAN HOSPITALS BASED ON ARTIFICIAL NEURAL NETWORKS AND TREE DECISION MODELS 15

CLINICAL DETERIORATION PREDICTION IN BRAZILIAN HOSPITALS BAS...

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15th International Conference on ICT, Society and Human Beings, ICT 2022, 19th International Conference on Web Based Communities and Social Media, WBC 2022 and 14th International Conference on e-Health, EH 2022 - Held at the 16th Multi Conference on computer Science and Information Systems, MCCSIS 2022

作者： Yazdanpanah, Hamed Silva, Augusto C.M. Guedes, Murilo Morales, Hugo M.P. dos Coelho, Leandro S. Moro, Fernando G. Department of Research Robô Laura PR Curitiba Brazil Department of Computer Science University of São Paulo SP São Paulo Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana PR Curitiba Brazil Electrical Engineering Graduate Program Federal University of Parana PR Curitiba Brazil

ISBN: (纸本)9789898704405

Early recognition of clinical deterioration (CD) has vital importance in patients’ survival from exacerbation or death. Electronic health records (EHRs) data have been widely employed in Early Warning Scores (EWS) to measure CD risk in hospitalized patients. Recently, EHRs data have been utilized in Machine Learning (ML) models to predict mortality and CD. The ML models have shown superior performance in CD prediction compared to EWS. Since EHRs data are structured and tabular, conventional ML models are generally applied to them, and less effort is put into evaluating the artificial neural network’s performance on EHRs data. Thus, in this article, an extremely boosted neural network (XBNet) is used to predict CD, and its performance is compared to eXtreme Gradient Boosting (XGBoost) and random forest (RF) models. For this purpose, 103,105 samples from thirteen Brazilian hospitals are used to generate the models. Moreover, the principal component analysis (PCA) is employed to verify whether it can improve the adopted models’ performance. The performance of ML models and Modified Early Warning Score (MEWS), an EWS candidate, are evaluated in CD prediction regarding the accuracy, precision, recall, F1-score, and geometric mean (G-mean) metrics in a 10-fold cross-validation approach. According to the experiments, the XGBoost model obtained the best results in predicting CD among Brazilian hospitals’ data. © 2022 15th International Conference on ICT, Society and Human Beings, ICT 2022, 19th International Conference on Web Based Communities and Social Media, WBC 2022 and 14th International Conference on e-Health, EH 2022 - Held at the 16th Multi Conference on computer Science and Information Systems, MCCSIS 2022. All rights reserved.

关键词： Neural networks

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Application of 3D Printing and Design in Healthcare: A Focus on Undergraduate Research to Attract Students to Bioengineering and Related Disciplines

Application of 3D Printing and Design in Healthcare: A Focus...

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Frontiers in Education (FIE) Conference

作者： Cindy M. Zelada-Quiroz Brian L. Reyes-Santiago Eduardo I. Ortiz-Rivera Bio-Engineering Graduate Program University of Puerto Rico at Mayagüez Mayagüez PR Department of Computer Science and Engineering University of Puerto Rico at Mayagüez Mayagüez PR Department of Electrical and Computer Engineering University of Puerto Rico at Mayagüez Mayagüez PR

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This research-to-practice paper describes developing and analyzing state-of-the-art smart boots created by combining CAD technology and advanced 3D printing techniques to attract students in bio-engineering and related fields. The primary objective of this innovative immobilization boot is to expedite fracture recovery phases through an ergonomic design to ensure optimal patient comfort during its use. Technological solutions are crucial in aiding the rehabilitation process for fractures caused by falls, heavy lifting, or rotational trauma. However, cost and comfort-related issues persist, underscoring the need for alternative approaches. This research addresses these challenges and delves into the broader implications of fracture treatment, catalyzing future projects and investigations in bioengineering. Additionally, this study serves as an educational tool that sparks the interest of high school and engineering students, promoting multidisciplinary collaboration in innovation. By involving students in specialized courses covering 3D design, human bone anatomy, biology, and materials science, this initiative empowers them to deepen their knowledge and develop new technologies to address bone injury problems. Material analyses include evaluating the type of material depending on the fracture site, such as PLA for printing and cotton and silicone gel for the midsection between the splint and the body. This research aims to advance our understanding of the type of fracture, the methods associated with their treatment, and tissue repair processes during bone callus formation. To summarize, this multidisciplinary approach drives advancements in bio-engineering and related fields, aiming to enhance patient outcomes and inspire students to pursue further research in bio-engineering and related fields. As part of this endeavor, a list of university-level courses based on the experience of the University of Puerto Rico at Mayaguez (UPRM), such as biology, bio-materials, 3D

关键词： Technological innovation Materials science and technology Three-dimensional displays Tissue engineering Medical services Three-dimensional printing Bones Mechanical factors Manufacturing Sparks

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Trajectory Learning and Demonstration of a Robot Manipulator Based-on Sensor Fusion from a Hand-held Tool

Trajectory Learning and Demonstration of a Robot Manipulator...

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International Automatic Control Conference

作者： Kai-Tai Song Szu-Chen Ou Institute of Electrical and Control Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Yang Ming Chiao Tung University Hsinchu Taiwan ROC Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan ROC

ISBN: (数字)9798350354904

ISBN: (纸本)9798350354911

This paper presents a programming system for a robot manipulator using a hand-held demonstration tool. In this system, a user holds the self-designed tool to demonstrate a desired motion path, and the robot arm replicates the learned trajectory. The path-demonstration tool, including optical tags (OT) and an IMU, is designed to collect trajectory data from hand motion. Sensor data fusion allows the system to track accurately the demonstrated trajectory. A calibration procedure is proposed to transform the trajectory from tool’s coordinate system to robot’s coordinate system. A cubic spline-based trajectory planning method is proposed to ensure smooth reproduction of the learned trajectory in both time and space. Experimental results show that the robot is able to replicate squared and curved trajectories collected from the path-demonstration tool. The average position error is within 2.435 mm in XYZ directions and the average orientation error is within 0.65 degrees.

关键词： Trajectory planning Tracking Robot kinematics Transforms Sensor fusion programming Robot sensing systems Manipulators Trajectory Splines (mathematics)

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Investigating the effect of cerebral atrophy on brain deformation using subject-specific models

Investigating the effect of cerebral atrophy on brain deform...

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Medical Imaging 2023: Biomedical Applications in Molecular, Structural, and Functional Imaging

作者： Hong, Allen Carass, Aaron Zuo, Lianrui Prince, Jerry L. Alshareef, Ahmed Department of Biomedical Engineering The College of New Jersey EwingNJ08618 United States Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States Laboratory of Behavioral Neuroscience National Institute on Aging National Institutes of Health BaltimoreMD20892 United States Biomedical Engineering Program University of South Carolina ColumbiaSC29208 United States

ISBN: (纸本)9781510660410

Traumatic brain injuries (TBIs) are a major health risk that increases with age. Natural brain aging results in cerebral atrophy and the enlargement of the ventricular regions. The objective of this study is to investigate the effect of cerebral atrophy on brain biomechanics with subject-specific models to determine the risk of traumatic brain injury (TBI). Utilizing subjects from a longitudinal study of aging in healthy volunteers, we created subject-specific brain models of a small cohort with progressive age-related cerebral atrophy. We then simulate concussive loading conditions to study changes in brain deformation, a correlate to risk of TBI. The results display differing trends with increasing ventricle volume, with some subjects exhibiting increases and others showing decreasing strain. Additional subject simulations are needed to clarify these the causes of these trends. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Health risks

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MAMMOS: MApping Multiple human MOtion with Scene understanding and natural interactions

MAMMOS: MApping Multiple human MOtion with Scene understandi...

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International Conference on computer Vision Workshops (ICCV Workshops)

作者： Donggeun Lim Cheongi Jeong Young Min Kim Dept. of Electrical and Computer Engineering Seoul National University Samsung Research Interdisciplinary Program in Artificial Intelligence and INMC Seoul National University

We present MAMMOS, an automated framework that generates the motions of multiple humans that naturally interact with each other in a given 3D scene. Many practical VR scenarios require creating dynamic human characters in harmony with the surrounding environment and other people. However, it is hard for an artist to manually generate multiple character motions tailored to the given 3D scene structure, or gather sufficient data to train an automated system that jointly considers the entangled requirements. MAMMOS is a hierarchical framework that successfully handles spatio-temporal constraints and generates high-quality motions. Given a simple tuple of action labels of the desired motion sequence, MAMMOS first places anchors in time and location for characters that avoid collisions yet enable necessary interactions. Then we generate the timelines of individual collision-free paths within the scene and connect them to perform diverse and natural motions. To the best of our knowledge, we are the first to generate long-horizon motion sequences of multiple humans with realistic interactions such that we can automatically populate the 3D scenes.

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Delayed Muscle Activity in Stroke Survivors with Upper-Limb Hemiparesis

Delayed Muscle Activity in Stroke Survivors with Upper-Limb ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Danielle R. Lopez Caleb J. Thomson Fredi R. Mino Steven R. Edgely Patrick P. Maitre Marta M. Iversen Jacob A. George Interdepartmental Neuroscience Program University of Utah Salt Lake City UT USA Department of Biomedical Engineering University of Utah Department of Electrical and Computer Engineering University of Utah Department of Physical Medicine and Rehabilitation University of Utah Departments of Electrical and Computer Engineering and Physical Medicine and Rehabilitation University of Utah

Stroke is the leading cause of disability worldwide, and nearly 80% of stroke survivors suffer from upper-limb hemiparesis. Myoelectric exoskeletons can restore dexterity and independence to stroke survivors with upper-limb hemiparesis. However, the ability of patients to dexterously control myoelectric exoskeletons is limited by an incomplete understanding of the electromyographic (EMG) hallmarks of hemiparesis, such as muscle weakness and spasticity. Here we show that stroke survivors with upper-limb hemiparesis suffer from delayed voluntary muscle contraction and delayed muscle relaxation. We quantified the time constants of EMG activity associated with initiating and terminating voluntary hand grasps and extensions for both the paretic and non-paretic hands of stroke survivors. We found that the initiation and termination time constants were greater on the paretic side for both hand grasps and hand extensions. Notably, the initiation time constant during hand extension was approximately three times longer for the paretic hand than for the contralateral non-paretic hand (0.618 vs 0.189 s). We also show a positive correlation between the initiation and termination time constants and clinical scores on the Modified Ashworth Scale. The difficulty stroke survivors have in efficiently modulating their EMG presents a challenge for appropriate control of assistive myoelectric devices, such as exoskeletons. This work constitutes an important step towards understanding EMG differences after stroke and how to accommodate these EMG differences in assistive myoelectric devices. Real-time quantitative biofeedback of EMG time constants may also have broad implications for guiding rehabilitation and monitoring patient *** Relevance— After a stroke, muscle activity changes, and these changes make it difficult to use muscle activity to drive assistive and rehabilitative technologies. We identified slower muscle contraction and muscle relaxation as a key difference i

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Digital Phenotype Representation by Statistical, Information Theory, Data-Driven Approach with Digital Health Data

Digital Phenotype Representation by Statistical, Information...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Binh Nguyen Michael Nigro Alice Rueda Venkat Bhat Sri Krishnan Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan Univerity Toronto ON Interventional Psychiatry Program St. Michael’s Hospital Toronto

Digital phenotyping (DP) is a multidisciplinary field of science that quantifies the individual level phenotype through active and passive data. Although DP is a multidisciplinary field, there lacks a technical and a systematic approach to representing DP. This work proposes the development of digital phenotype profile (DPP) to represent a user’s physical and behavioural health baseline through systematic investigations with an emphasis on robustness and explainability. To achieve this, a Statistical, Information Theory, and Data-driven (SID) pipeline will develop the foundation of the DPP. SID evaluates the non-linearity of the signal to offer inference for domain-specific feature extraction, evaluates the information theory to rank the DPP parameters, and imputes missing data for robust analysis, respectively. SID was applied to a 24-hr Multi-Level dataset and was able to represent individual DPPs. The respective DPPs were visualized and clusters of awake and asleep were used for individual specific modelling.

关键词： Systematics Pipelines Data visualization Signal processing Feature extraction Robustness Acoustics

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On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection

arXiv

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arXiv 2023年

作者： Park, Sangha Mok, Jisoo Jung, Dahuin Lee, Saehyung Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

Successful detection of Out-of-Distribution (OoD) data is becoming increasingly important to ensure safe deployment of neural networks. One of the main challenges in OoD detection is that neural networks output overconfident predictions on OoD data, make it difficult to determine OoD-ness of data solely based on their predictions. Outlier exposure addresses this issue by introducing an additional loss that encourages low-confidence predictions on OoD data during training. While outlier exposure has shown promising potential in improving OoD detection performance, all previous studies on outlier exposure have been limited to utilizing visual outliers. Drawing inspiration from the recent advancements in vision-language pre-training, this paper venture out to the uncharted territory of textual outlier exposure. First, we uncover the benefits of using textual outliers by replacing real or virtual outliers in the image-domain with textual equivalents. Then, we propose various ways of generating preferable textual outliers. Our extensive experiments demonstrate that generated textual outliers achieve competitive performance on large-scale OoD and hard OoD benchmarks. Furthermore, we conduct empirical analyses of textual outliers to provide primary criteria for designing advantageous textual outliers: near-distribution, descriptiveness, and inclusion of visual semantics. © 2023, CC BY-NC-SA.

关键词： Forecasting

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An autonomous robotic system for collecting garbage over small water bodies

An autonomous robotic system for collecting garbage over sma...

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作者： Syed Nouman Hasany Saniya Shah Zaidi Syed Ahmad Sohail Muhammad Farhan Electrical Engineering Program Habib University Computer Science Program Habib University Electrical and Computer Engineering Program Habib University

Water pollution is a grave problem requiring utmost attention as it directly affects marine *** freshwater ecosystem,for example,lakes and ponds,a major chunk of water garbage is plastic floating on the surface of water which is labor intensive to collect *** this paper,we present a novel autonomous robotic system capable of navigating small water bodies and is equipped with computer vision that helps it to detect the *** detection is followed by focusing on an area of interest to determine whether the garbage lies in the scope of robot for ***,if WiFi communication is available,the robot has the provision of tracking the detected garbage to determine its *** design of garbage collection unit of the robot ensures the garbage does not move outward once *** robot is tested in two different pools and with plastic bottles as main type of *** results manifest the high degree of control of its locomotion as well as of detection and collection of the *** deep neural network based detector onboard the robot can be retrained after self-collection of appropriate data to detect other types of garbage as well.

关键词： An autonomous robotic system for collecting garbage over small water bodies

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