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SSRN 2023年

作者： Dong, Wen Yang, Xin Zhang, Ning Chen, Pei Sun, Jianghao Harnly, James M. Zhang, Mengliang Department of Chemistry Middle Tennessee State University MurfreesboroTN37132 United States Department of Computer Science Middle Tennessee State University MurfreesboroTN37132 United States Department of Mathematics and Computer Science Fisk University NashvilleTN37208 United States Methods and Application of Food Composition Laboratory Beltsville Human Nutrition Research Center Agricultural Research Service United States Department of Agriculture BeltsvilleMD20705 United States

The effects of anthocyanin’s substitution groups on the UV-Vis molar absorptivity were examined by analyzing a group of 31 anthocyanidin/anthocyanin reference standards with ultra-high performance liquid chromatography-diode array detector (UHPLC-DAD). The hydroxylation and glycosylation on aglycones caused absorbance maxima shift and molar absorptivity change, which was dependent on the substitution position. Such molar absorptivity variation was often neglected in anthocyanin quantitation, resulting in significant analytical errors. A simple yet comprehensive strategy based on the molar relative response factors (MRRFs) and a single master reference calibration (i.e., cyanidin-3-glucoside) was proposed to compensate for the quantitative errors. MRRFs of 617 anthocyanins/anthocyanidins were calculated and the information is freely available at https://***/anthocyanin/. The strategy was applied to analyzing anthocyanins in red cabbage, blueberry, and strawberry samples. The results indicate this approach provides an effective, inexpensive, and accurate method for quantitative analysis of many anthocyanins in food materials without using individual reference standards. © 2023, The Authors. All rights reserved.

关键词： Anthocyanins

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Alteration of Cortical Somatosensory Feedback in Post-Stroke Movement Control 46

Alteration of Cortical Somatosensory Feedback in Post-Stroke...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Peng, Rita Huan-Ting Parmar, Nishaal Williamson, Jordan N. Sirpal, Parikshat Mulyana, Beni E. Rajabtabar Darvish, Mahmood Sung, Joohwan Sidorov, Evgeny V. Yang, Yuan Department of Bioengineering Grainger College of Engineering University of Illinois Urbana-Champaign UrbanaIL United States Clinical Imaging Research Center Stephenson Family Clinical Research Institute Carle Foundation Hospital UrbanaIL United States Department of Electrical and Computer Engineering University of Oklahoma TulsaOK74135 United States Department of Neurology University of Oklahoma Health Sciences Center Oklahoma CityOK73104 United States Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign UrbanaIL United States Department of Physical Therapy and Human Movement Sciences Northwestern University ChicagoIL United States

ISBN: (纸本)9798350371499

Sensory feedback is of vital importance in motor control, yet is rarely studied in diseases which frequently result in motor deficiency, such as hemiparetic stroke. This study employs the laterality index (LI) of somatosensory evoked potentials (SEPs) to investigate whether sensory feedback is altered in hemiparetic stroke during movements of the paretic arm, with a hemispheric shift from the lesioned hemisphere toward contralesional hemisphere. Through experimental design involving the isometric lifting of the paretic arms during tactile finger stimulation and the analysis of LI in SEPs P50 and N100, we found: 1) increased contralesional sensory activity in stroke participants when they are receiving sensory input in their paretic hand for both P50 and N100 and 2) the contralesional N100 activity is enhanced when stroke participants are performing an isometric arm lifting task. These results indicate a timedependent shifting of sensory feedback from the sensorimotor areas in the lesioned side to the contralesional side of the stroke brain. © 2024 IEEE.

关键词： Sensory feedback

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Blockchain Approach for Implementing Access Control In IOT

Blockchain Approach for Implementing Access Control In IOT

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Artificial Intelligence and Smart Communication (AISC), International Conference on

作者： Jeidy Panduro-Ramirez Melanie Lourens Anita Gehlot Devesh Pratap Singh Yashpal Singh Deepak J. Salunke Universidad Tecnológica del Perú Perú Department of Human Resources Management Durban University of Technology Berea Durban South Africa Uttaranchal Institute of Technology Uttaranchal University Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Computer Science and Engineering Jain Deemed to be University Bengaluru Karnataka India Department of Information Technology Pravara Rural Engineering College Loni SavitribaiPhule Pune University Pune Maharashtra India

Block chain is now attracting a lot of interest from scientists and experts for a variety of reasons, including wireless communication decentralization, remote access, digital security, and confidentiality. Although peer-to-peer networking, confidentiality, improved storage, and extra security are all advantages of crypto currencies, its irreversible nature is the primary factor in its top ranking. Block chain may be utilized as a crucial technique to do away with the need for a trustworthy third person in networks that are linked to one another because of how it is dispersed. The most well-known block chains that may be used for installation are Public block chain Fiber, IBM Bit coin, Eth, Eris, R3 Corda, and multichain. The abovementioned review study presents and evaluates the current proof - of - stake security methods for distribution chain, medicine, and IoT access controls. The thorough analysis of applications of block chain will function as the most recent state-of-the-art for academics to conduct cutting-edge research in the pursuit of block chain - based across diverse disciplines.

关键词： Access control Wireless communication Privacy Clustering algorithms Vehicular ad hoc networks Optical fiber networks Blockchains

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A model for structuring UML class diagrams to support non-visual interpretation and navigation 20

A model for structuring UML class diagrams to support non-vi...

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20th British computer Society Conference on human-computer interaction: Engage, HCI 2006

作者： Metatla, Oussama Bryan-Kinns, Nick Stockman, Tony Interaction Media and Communication Group Department of Computer Science Queen Mary University of London E1 4NS United Kingdom

Accessing textual information non-visually can be performed directly using Braille translators or text-to-speech engines. Problems arise when faced with graphically represented information, such as a diagram. For blind and visually impaired people, screen-readers are the most commonly used tools for accessing on-screen information, but they typically fail to deliver graphical information in appropriate and flexible ways. As a result, diagrammatic representations are inaccessible for such a population of users. We present the design of an experiment exploring a task-oriented approach for integrating speech and non-speech sounds to support the interpretation and navigation of conceptually relevant information encoded in a diagram. © BCS HCI Group Conference: Engage, HCI *** right reserved.

关键词： human computer interaction

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One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks

arXiv

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arXiv 2021年

作者： Senge, Manuel Igamberdiev, Timour Habernal, Ivan Trustworthy Human Language Technologies Department of Computer Science Technical University of Darmstadt Germany

Preserving privacy in contemporary NLP models allows us to work with sensitive data, but unfortunately comes at a price. We know that stricter privacy guarantees in differentially-private stochastic gradient descent (DP-SGD) generally degrade model performance. However, previous research on the efficiency of DP-SGD in NLP is inconclusive or even counter-intuitive. In this short paper, we provide an extensive analysis of different privacy preserving strategies on seven downstream datasets in five different 'typical' NLP tasks with varying complexity using modern neural models based on BERT and XtremeDistil architectures. We show that unlike standard non-private approaches to solving NLP tasks, where bigger is usually better, privacy-preserving strategies do not exhibit a winning pattern, and each task and privacy regime requires a special treatment to achieve adequate performance. © 2021, CC BY-SA.

关键词： Natural language processing systems

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Rapid convergence: The outcomes of making ppe during a healthcare crisis

arXiv

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arXiv 2021年

作者： Mack, Kelly Hofmann, Megan Lakshmi, Udaya Cao, Jerry Auradkar, Nayha Arriaga, Rosa I. Hudson, Scott E. Mankoff, Jennifer Paul G. Allen School of Computer Science University of Washington SeattleWA United States Human Computer Interaction Institute Carnegie Mellon University PittsburghPA United States School of Interactive Computing Georgia Institute of Technology AtlantaGA United States Paul G. Allen School of Computer Science University of Washington SeattleWA United States Human Computer Interaction Institute Carnegie Mellon University PittsburghPA United States Paul G. Allen School of Computer Science University of Washington SeattleWA United States

The NIH 3D Print Exchange is a public and open source repository for primarily 3D printable medical device designs with contributions from expert-amateur makers, engineers from industry and academia, and clinicians. In response to the COVID-19 pandemic, a collection was formed to foster submissions of low-cost, local manufacture of personal protective equipment (Personal Protective Equipment (PPE)). We systematically evaluated the 623 submissions in this collection to understand: what makers contributed, how they were made, who made them, and key characteristics of their designs. Our analysis reveals an immediate design convergence to derivatives of a few initial designs affiliated with NIH partners (e.g., universities, the Veteran’s Health Administration, America Makes) and major for-profit groups (e.g., Prusa). The NIH worked to review safe and effective designs but was quickly overloaded by derivative works. We found that the vast majority were never reviewed (81.3%) while 10.4% of those reviewed were deemed safe for clinical (5.6%) or community use (4.8%). Our work contributes insights into: the outcomes of distributed, community-based, medical making;features the community accepted as "safe" making;and how platforms can support regulated maker activities in high-risk domains (e.g., healthcare). © 2021, CC BY.

关键词： Health care

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Multi-view Contrastive Multiple Knowledge Graph Embedding for Knowledge Completion

Multi-view Contrastive Multiple Knowledge Graph Embedding fo...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Mori Kurokawa Kei Yonekawa Shuichiro Haruta Tatsuya Konishi Hideki Asoh Chihiro Ono Masafumi Hagiwara Human-Centered AI Laboratories KDDI Research Inc Fujimino-shi Saitama Japan Department of Information and Computer Science Keio University Yokohama Kanagawa Japan

Knowledge graphs (KGs) are useful information sources to make machine learning efficient with human knowledge. Since KGs are often incomplete, KG completion has become an important problem to complete missing facts in KGs. Whereas most of the KG completion methods are conducted on a single KG, multiple KGs can be effective to enrich embedding space for KG completion. However, most of the recent studies have concentrated on entity alignment prediction and ignored KG-invariant semantics in multiple KGs that can improve the completion performance. In this paper, we propose a new multiple KG embedding method composed of intra-KG and inter-KG regularization to introduce KG-invariant semantics into KG embedding space using aligned entities between related KGs. The intra-KG regularization adjusts local distance between aligned and not-aligned entities using contrastive loss, while the inter-KG regularization globally correlates aligned entity embeddings between KGs using multi-view loss. Our experimental results demonstrate that our proposed method combining both regularization terms largely outperforms existing baselines in the KG completion task.

关键词： Semantics Knowledge graphs Machine learning Benchmark testing Task analysis

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Learning what to do by simulating the past

arXiv

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arXiv 2021年

作者： Lindner, David Shah, Rohin Abbeel, Pieter Dragan, Anca Department of Computer Science ETH Zurich Center for Human-Compatible AI UC Berkeley

Since reward functions are hard to specify, recent work has focused on learning policies from human feedback. However, such approaches are impeded by the expense of acquiring such feedback. Recent work proposed that agents have access to a source of information that is effectively free: in any environment that humans have acted in, the state will already be optimized for human preferences, and thus an agent can extract information about what humans want from the state (Shah et al., 2019). Such learning is possible in principle, but requires simulating all possible past trajectories that could have led to the observed state. This is feasible in gridworlds, but how do we scale it to complex tasks? In this work, we show that by combining a learned feature encoder with learned inverse models, we can enable agents to simulate human actions backwards in time to infer what they must have done. The resulting algorithm is able to reproduce a specific skill in MuJoCo environments given a single state sampled from the optimal policy for that skill. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

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A Detailed Review and Study of Implementation of Security System Design for Machine Learning-Based Software Systems: Issues And Challenges

A Detailed Review and Study of Implementation of Security Sy...

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Advance Computing and Innovative Technologies in Engineering (ICACITE), International Conference on

作者： Melanie Lourens Vikas Tripathi Joel Alanya-Beltran Shaik Vaseem Akram Bandi Bhaskar Firos A Department of Human Resources Management Durban University of Technology Berea Durban South Africa Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Universidad Tecnológica del Perú Perú Uttaranchal Institute of Technology Uttaranchal University School of CS& AI SR University Warangal Telangana Department of Computer Science and Engineering Rajiv Gandhi University (A Central University) Doimukh Arunachal Pradesh India

The rapidly growing technology specially in the field of software, Machine Learning (ML) has played an important role in a range of tasks, including voice, video, and computer vision. It is currently being utilised in software systems to automate the crucial processes more and more. Machine learning-based modern software systems (MLBSS) are currently difficult to build safely, which will severely limit the uses in security and safety-critical domains. Recently, majority of articles are published and still research work is going on the safety problems for ML and Deep Learning (DL), which place a strong prominence on the models and data both, adversaries’ threats have been taken into consideration. In this paper, we address the prospect that system bugs or external adversarial assaults might lead to security vulnerabilities for machine learning-based software systems, and we propose that safe development techniques ought to be applied throughout the whole lifecycle. We conclude by providing a thorough study of the security for MLBSS, which includes a comprehensive analysis based on a review of the structure of three distinctive features in terms of security issues. The entire state-of-the-art for MLBSS secure development is also provided.

关键词：

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A Numerical real time web tracking and scrapping strategy applied to analysing covid-19 datasets 7

A Numerical real time web tracking and scrapping strategy ap...

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7th Annual International Conference on Network and Information Systems for computers, ICNISC 2021

作者： Ez-Zahout, Abderrahmane Chakouk, Said Mitouilli, Salwa El Bouni, Mohamed Amine Mohammed v University in Rabat Faculty of Sciences Computer Sciences Department Morocco Mohammed v University in Rabat Faculty of Letters and Human Sciences Communication Department Morocco Al Akhawayn University in Ifrane School of Science and Engineering Morocco

ISBN: (纸本)9781665402323

With the huge amount of data collected from the web, it is hard to manually analyze and extract useful incites from tables, matrices, or rows of data. Therefore, we need a way to represent these data (maps or graphs) to analyze/interpret them. Data visualization makes it easier to identify trends, patterns, and outliers with large datasets. Data Analytics is used to analyze raw data to make conclusions about the information. In this paper, we tackled web scrapping strategies to get COVID-19 data from the web, and then we went through some data analysis and exploration using EDA. © 2021 IEEE.

关键词： Data visualization

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