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2nd International Conference on electrical, Communication and computer engineering, ICECCE 2020

作者： Kim, Myoung Jin Park, Taewoo Lee, Soochahn Jung, Ho Yup Yun, Il Dong Hankuk University of Foreign Studies Dept. Computer and Electronic System Yongin Korea Republic of Geumgang University Division of Public Policy Nonsan Korea Republic of School of Electrical Engineering Kookmin University Seoul Korea Republic of Chosun Niveristy Dept. Compter Engineering Gwangju Korea Republic of

ISBN: (数字)9781728171166

ISBN: (纸本)9781728171166

In this paper, we propose an efficient and effective semi-automatic segmentation framework for knee cartilage in longitudinal MR images. The proposed method provides a seamless and efficient combination of initial automatic segmentation and interactive segmentation. The main idea is to generate and transfer the seeds, rather than the labels, of the manual segmentation results of the initial image, to segment sequential images. Here, segmentation seeds are defined as sample voxels that are highly likely to be either the organ of interest or background. Similar to user annotations by scribbles, seeds can be used to determine labels for remaining voxels. Compared to methods that transfer segmentation labels, the proposed method is able to reduce the amount of required user annotations, since it does not require the user to identify and correct erroneous regions in the transferred segmentation labels, while still providing a robust initial segmentation based on transferred initial seeds. We evaluate the effectiveness of the proposed framework by measuring the interaction time of the user to segment the cartilage within the images. We compare the results with previous methods and show that the proposed method reduces the required interaction time. © 2020 IEEE.

关键词： Cartilage

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Synchronization within synchronization: transients and intermittency in ecological networks

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National Science Review 2021年第10期8卷 23-32页

作者： Huawei Fan Ling-Wei Kong Xingang Wang Alan Hastings Ying-Cheng Lai School of Physics and Information Technology Shaanxi Normal University School of Electrical Computer and Energy Engineering Arizona State University Department of Environmental Science and Policy University of California Santa Fe Institute Department of Physics Arizona State University

Transients are fundamental to ecological systems with significant implications to management,conservation and biological control. We uncover a type of transient synchronization behavior in spatial ecological networks whose local dynamics are of the chaotic, predator–prey type. In the parameter regime where there is phase synchronization among all the patches, complete synchronization(i.e. synchronization in both phase and amplitude) can arise in certain pairs of patches as determined by the network symmetry—henceforth the phenomenon of ‘synchronization within synchronization.' Distinct patterns of complete synchronization coexist but, due to intrinsic instability or noise, each pattern is a transient and there is random, intermittent switching among the patterns in the course of time evolution. The probability distribution of the transient time is found to follow an algebraic scaling law with a divergent average transient lifetime. Based on symmetry considerations, we develop a stability analysis to understand these phenomena. The general principle of symmetry can also be exploited to explain previously discovered,counterintuitive synchronization behaviors in ecological networks.

关键词： ecological networks cluster synchronization phase synchronization transient chaos network symmetry

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Selective HuBERT: Self-Supervised Pre-Training for Target Speaker in Clean and Mixture Speech

arXiv

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arXiv 2023年

作者： Lin, Jingru Ge, Meng Wang, Wupeng Li, Haizhou Feng, Mengling Department of Electrical and Computer and Engineering National University of Singapore Singapore119077 Singapore Saw Swee Hock School of Public Health National University of Singapore Singapore117549 Singapore Shenzhen Research Institute of Big Data School of Data Science The Chinese University of Hong Kong Shenzhen518172 China

Self-supervised pre-trained speech models were shown effective for various downstream speech processing tasks. Since they are mainly pre-trained to map input speech to pseudo-labels, the resulting representations are only effective for the type of pre-train data used, either clean or mixture speech. With the idea of selective auditory attention, we propose a novel pre-training solution called Selective-HuBERT, or SHuBERT, which learns the selective extraction of target speech representations from either clean or mixture speech. Specifically, SHuBERT is trained to predict pseudo labels of a target speaker, conditioned on an enrolled speech from the target speaker. By doing so, SHuBERT is expected to selectively attend to the target speaker in a complex acoustic environment, thus benefiting various downstream tasks. We further introduce a dual-path training strategy and use the cross-correlation constraint between the two branches to encourage the model to generate noise-invariant representation. Experiments on SUPERB benchmark and LibriMix dataset demonstrate the universality and noise-robustness of SHuBERT. Furthermore, we find that our high-quality representation can be easily integrated with conventional supervised learning methods to achieve significant performance, even under extremely low-resource labeled data. Copyright © 2023, The Authors. All rights reserved.

关键词： Extraction

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Can Personalized Medicine Coexist with Health Equity? Examining the Cost Barrier and Ethical Implications

arXiv

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arXiv 2024年

作者： Francisco, Kishi Kobe Yee Apuhin, Andrane Estelle Carnicer Tan, Myles Joshua Toledo Byers, Mickael Cavanaugh Maravilla, Nicholle Mae Amor Tan Karim, Hezerul Abdul AlDahoul, Nouar Biology Program College of Arts and Science University of St. La Salle Negros Occidental Bacolod City Philippines Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Department of Epidemiology College of Public Health & Health Professions College of Medicine University of Florida GainesvilleFL United States Department of Natural Sciences College of Arts and Science University of St. La Salle Negros Occidental Bacolod City Philippines Department of Chemical Engineering College of Engineering and Technology University of St. La Salle Negros Occidental Bacolod City Philippines Department of Electronics Engineering College of Engineering and Technology University of St. La Salle Negros Occidental Bacolod City Philippines Yo-Vivo Corporation Negros Occidental Bacolod City Philippines Department of Civil and Coastal Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Faculty of Engineering Multimedia University Selangor Cyberjaya Malaysia Department of Computer Science Division of Science New York University Abu Dhabi Saadiyat Marina District Abu Dhabi United Arab Emirates

Personalized medicine (PM) promises to transform healthcare by providingtreatments tailored to individual genetic, environmental, and lifestylefactors. However, its high costs and infrastructure demands raise concernsabout exacerbating health disparities, especially between high-income countries(HICs) and low- and middle-income countries (LMICs). While HICs benefit fromadvanced PM applications through AI and genomics, LMICs often lack theresources necessary to adopt these innovations, leading to a wideninghealthcare divide. This paper explores the financial and ethical challenges ofPM implementation, with a focus on ensuring equitable access. It proposesstrategies for global collaboration, infrastructure development, and ethicalframeworks to support LMICs in adopting PM, aiming to prevent furtherdisparities in healthcare accessibility and outcomes. © 2024, CC BY.

关键词： Personalized medicine

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Cost and impact of weak medium term policies in the electricity system in Western North America

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Electricity Journal 2021年第3期34卷 106925-106925页

作者： Hidalgo-Gonzalez, Patricia L. Johnston, Josiah Kammen, Daniel M. Energy and Resources Group University of California BerkeleyCA United States Electrical Engineering and Computer Sciences University of California BerkeleyCA United States Mechanical and Aerospace Engineering University of California San DiegoCA United States The Goldman School of Public Policy University of California BerkeleyCA United States

We study the cost and lock in of carbon intensive technologies due to weak medium-term policies. We use SWITCH WECC—a power system capacity expansion optimization model with high temporal and geographical resolution. We test three carbon cap scenarios. For each scenario, we optimize the power system for a medium timeframe (2030) and a long timeframe (2050). In the medium timeframe optimizations, by 2030 coal replaces gas power. This occurs because the long optimization foresees the stronger carbon cap in 2050. Therefore, it is optimal to transition towards cleaner technologies as early as 2030. The medium-term optimization has higher costs in 2040 and 2050 compared to the long optimization. Therefore, to minimize total costs to reduce emissions by 80 % in 2050, we should optimize until 2050 or have stronger carbon cap policies by 2030 (such as 26 % carbon emissions reductions from 1990 levels by 2030 across the WECC). © 2021 Elsevier Inc.

关键词： Carbon

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Design and Implementation of a Smart Human Posture Monitoring Device Using a Wearable Vest

Design and Implementation of a Smart Human Posture Monitorin...

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International Conference on Advances in Biomedical engineering (ICABME)

作者： Roy Abi Zeid Daou Elio Geha Youssef Aoun Ali Hayek Josef Boercsoek Jose Javier Serrano Olmedo Biomedical Engineering department Furn El Chebbak Université La Sagesse Beirut Lebanon Education and Research Center MART Learning Chananir Lebanon Biomedical Technologies Department Faculty of Public Health Lebanese German University Jounieh Lebanon Department Lippstadt 2 Hardware Engineering Marker Allee 76-78 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 Tecnologia Biomedica Universidad Politecnica de Madrid Spain

Chronic back pain can present a serious health concern, with symptoms that can significantly affect an individual's well-being, mobility, and overall quality of life over an extended period. While chronic back pain may manifest suddenly in some cases, it often develops gradually and persists for weeks, and in untreated cases, it can linger for years. Hence, the utilization of assistive devices such as wearable posture-monitoring vests can offer valuable assistance and guidance to users. This research paper is dedicated to the development of a system for detecting, diagnosing, and correcting poor posture, specifically leaning posture. The vest is designed to provide users with visual, auditory, and tactile cues to help them address this issue, thereby reducing the risk associated with leaning. Additionally, an integrated electrical box has been designed to consolidate all components directly onto the main board in a secure enclosure. This box also displays the daily count of instances where the user has leaned. This system is characterized by its electrical safety, portability, compactness, comfort, and affordability. A comprehensive analysis of the system's performance has been conducted with a meticulous evaluation of accuracy. Each component of the system has undergone successful testing, and the system as a whole is currently in the testing phase. The results of these tests have indicated a lack of faulty errors and have demonstrated outstanding accuracy and detection rates. Over 100 individuals of varying ages, genders, and BMI categories were involved in testing, with each person wearing the device for an average of six hours. The accuracy rate achieved was 98.85%, with an average of 54.35 instances of poor posture detected per participant.

关键词：

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Whose tweets are surveilled for the police: An audit of a social-media monitoring tool via log files

arXiv

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arXiv 2020年

作者： Borradaile, Glencora Burkhardt, Brett LeClerc, Alexandria School of Electrical Engineering and Computer Science Oregon State University School of Public Policy Oregon State University

Social media monitoring by law enforcement is becoming commonplace, but little is known about what software packages for it do. Through public records requests, we obtained log files from the Corvallis (Oregon) Police Department's use of social media monitoring software called DigitalStakeout. These log files include the results of proprietary searches by DigitalStakeout that were running over a period of 13 months and include 7240 social media posts. In this paper, we focus on the Tweets logged in this data and consider the racial and ethnic identity (through manual coding) of the users that are therein flagged by DigitalStakeout. We observe differences in the demographics of the users whose Tweets are flagged by DigitalStakeout compared to the demographics of the Twitter users in the region, however, our sample size is too small to determine significance. Further, the demographics of the Twitter users in the region do not seem to reflect that of the residents of the region, with an apparent higher representation of Black and Hispanic people. We also reconstruct the keywords related to a Narcotics report set up by DigitalStakeout for the Corvallis Police Department and find that these keywords flag Tweets unrelated to narcotics or flag Tweets related to marijuana, a drug that is legal for recreational use in Oregon. Almost all of the keywords have a common meaning unrelated to narcotics (e.g. broken, snow, hop, high) that call into question the utility that such a keyword based search could have to law enforcement. As social media monitoring is increasingly used for law enforcement purposes, racial biases in surveillance may contribute to existing racial disparities in law enforcement practices. We are hopeful that log files obtainable through public records request will shed light on the operation of these surveillance tools. There are challenges in auditing these tools: public records requests may go unfulfilled even if the data is available, social media platfor

关键词： Law enforcement

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Characterizing Sociolinguistic Variation in the Competing Vaccination Communities 1

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13th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2020

作者： Memon, Shahan Ali Tyagi, Aman Mortensen, David R. Carley, Kathleen M. School of Computer Science Carnegie Mellon University PittsburghPA15213 United States Engineering and Public Policy Carnegie Mellon University PittsburghPA15213 United States

ISBN: (数字)9783030612559

ISBN: (纸本)9783030612542

public health practitioners and policy makers grapple with the challenge of devising effective message-based interventions for debunking public health misinformation in cyber communities. Framing and personalization of the message is one of the key features for devising a persuasive messaging strategy. For an effective health communication, it is imperative to focus on preference-based framing where the preferences of the target sub-community are taken into consideration. To achieve that, it is important to understand and hence characterize the target sub-communities in terms of their social interactions. In the context of health-related misinformation, vaccination remains to be the most prevalent topic of discord. Hence, in this paper, we conduct a sociolinguistic analysis of the two competing vaccination communities on Twitter: pro-vaxxers or individuals who believe in the effectiveness of vaccinations, and anti-vaxxers or individuals who are opposed to vaccinations. Our data analysis show significant linguistic variation between the two communities in terms of their usage of linguistic intensifiers, pronouns, and uncertainty words. Our network-level analysis show significant differences between the two communities in terms of their network density, echo-chamberness, and the EI index. We hypothesize that these sociolinguistic differences can be used as proxies to characterize and understand these communities to devise better message interventions. © 2020, Springer Nature Switzerland AG.

关键词： Linguistics

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RO-YOLOv9 Vehicle and Pedestrian Detection Algorithm

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computer engineering and Applications 2025年第11期61卷 144-155页

作者： Liao, Yanhua Wan, Xuejun Zhao, Zhouzhou Pan, Wenlin School of Electrical and Information Engineering Yunnan Minzu University Kunming650500 China Science and Technology Information Brigade Yuxi Public Security Bureau Yunnan Yuxi653100 China School of Mathematics and Computer Science Yunnan Minzu University Kunming650500 China

Aiming at the low detection accuracy, false detection and missed detection problems caused by small or occluded vehicle and pedestrian targets in road traffic environments, a road target detection algorithm RO-YOLOv9 is proposed. Firstly, the small target detection layer is added to enhance the algorithm’s feature learning ability for small targets. Secondly, the bidirectional and adaptive scale fusion feature pyramid network (BiASF-FPN) structure is designed to optimize multi-scale feature fusion and ensure that the algorithm effectively captures detailed information from small to large scale targets. Thirdly, the OR-RepN4 module is proposed to simplify the complex algorithm structure and improve the inference speed through the re-parameterization strategy. Finally, the shape neighborhood weighted decomposition (Shape-NWD) loss function is used to focus on the shape and size of the bounding box, and the normalized Gaussian Wasserstein distance smoothing regression is used to achieve cross-scale invariance and reduce the detection error of small-scale and occluded targets. The experimental results show that under the optimized SODA10M and BDD100K datasets, the mAP@ 0.5 (mean average precision) of RO-YOLOv9 algorithm reaches 68.1% and 56.8%, respectively, which is 5.6 percentage points and 4.4 percentage points higher than that of the YLOLOv9 algorithm, and the detection frame rates reach 55.3 and 54.2 frames per second, respectively, achieving a balance between detection accuracy and detection speed. © 2025 Journal of computer engineering and Applications Beijing Co., Ltd.;Science Press. All rights reserved.

关键词： Boolean functions

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Prioritizing Strategies for Building the Resilience of public Health Systems to Disasters Across Multiple Communities and Countries

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International Journal of Disaster Risk Science 2024年第1期15卷 1-17页

作者： Benjamin J.Ryan Mayumi Kako Shelby Garner Rok Fink Ismail Tayfur Jonathan Abrahams Sanjaya Bhatia Adriana Campelo Matthew Fendt Alicia Fontenot Nahuel Arenas Garcia Tim Hatch Ryoma Kayano LaShonda Malrey‑Horne Makiko MacDermot Md Moshiur Rahman Chaverle Noel Shuhei Nomura Jeremy P.Novak Maria Opazo Kendell Oliver Luciana Peters Sohel Rahman PerihanŞimşek Andrew Stricklin Raymond Swienton Bryan W.Brooks Frist College of Medicine Belmont UniversityNashvilleTN 37212USA Department of Environmental Science Environmental Health Science ProgramCollege of Arts and SciencesBaylor UniversityWacoTX 76798USA Division of Nursing Science School of Biomedical and Health SciencesHiroshima UniversityHiroshima 734-8553Japan Gordon E.Inman College of Health Sciences and Nursing Belmont UniversityNashvilleTN 37212USA Faculty of Health Sciences University of Ljubljana1000 LjubljanaSlovenia Department of Emergency Medicine University of Health Sciences34668 IstanbulTurkey Monash University Accident Research Center MelbourneVIC 3800Australia Global Education and Training Institute United Nations Ofce for Disaster Risk ReductionIncheon 22004Republic of Korea Regional Ofce for the Americas and Caribbean United Nations Ofce for Disaster Risk ReductionPanama City 0843-03441Panama Engineering and Computer Science Baylor UniversityWacoTX 76798USA Department of Public Health Robbins College of Health and Human SciencesBaylor UniversityWacoTX 76798USA Alabama Department of Public Health MontgomeryAL 36092USA World Health Organization Centre for Health Development(WHO Kobe Centre) Kobe 651-0073Japan Waco-McLennan County Public Health District WacoTX 76707USA Department of Health Policy and Management School of MedicineKeio UniversityTokyo 160-8582Japan Department of Global Health Policy Graduate School of MedicineThe University of TokyoTokyo 113-0033Japan Tokyo Foundation for Policy Research Tokyo 106-6234Japan Global Development College BrisbaneQLD 4000Australia Municipality of Pudahuel 13124 PudahuelChile City Hall of Porto Alegre Porto Alegre 90010-170Brazil Ministry of Health and Family Welfare Government of the People’s Republic of BangladeshDhaka 1000Bangladesh Department of Emergency Aid and Disaster Management Trabzon University61335 TrabzonTurkey Department of Emergency Medicine UT SouthwesternDallasTX 75390USA

The COVID-19 pandemic highlighted the urgent need to strengthen public health *** response,the United Nations Disaster Risk Reduction(UNDRR) public Health System Resilience Scorecard(Scorecard) was applied in workshops across multiple *** aim of our research was to explore the workshop findings to develop priority strategies for strengthening public health system *** conducted a workshop from 14 to 16 March 2023,at the UNDRR Global Education and Training Institute in Incheon,Republic of Korea.A sequential modified Delphi method was utilized to develop a set of prioritized resilience *** were drawn from 70 strategies identified from 13 distinct workshops in eight *** two surveys,23 strategies were *** received ratings of "High" or Very High" from89% of *** related to the inclusion of public health risks in emergency plans,integrating multidisciplinary teams into public health,enabling local transport mechanisms,and improving the ability to manage an influx of *** Scorecard provides an adaptable framework to identify and prioritize strategies for strengthening public health system *** leveraging this methodology,our study demonstrated how resilience strategies could inform disaster risk reduction funding,policies,and actions.

关键词： Health system resilience public policy Resilience scorecard Workshops

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