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IEEE Potentials 2004年第1期23卷 24-27页

作者： Doom, Travis Raymer, Michael Krane, Dan IEEE Wright State University United States Department of Computer Science and Engineering Graduate Faculty in Biomedical Sciences Dayton OH United States WSU Biomedical Sciences Ph.D. Program Forensic Bioinformatics Inc. United States Bioinformatics Research Group Computer Science Department Wright State University United States

No abstract available

关键词： Bioinformatics Biology computing Biological information theory data analysis Computational biology Proteins Biochemistry Sequences Genomics Large-scale systems

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Aspect-based Sentiment Analysis for Improving Online Learning program Based on Student Feedback 6

Aspect-based Sentiment Analysis for Improving Online Learnin...

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6th IEEE International Conference on Cybernetics and Computational Intelligence, CyberneticsCom 2022

作者： Heryadi, Yaya Wijanarko, Bambang Dwi Murad, Dina Fitria Tho, Cuk Hashimoto, Kiyota Binus Graduate Program-Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Binus Online Learning Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Binus Online Learning Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Phuket83120 Thailand

ISBN: (数字)9781665497428

ISBN: (纸本)9781665497428

This paper presents an empiric results of aspectbased sentiment analysis in education to extract and classify opinions, sentiments, evaluations, attitudes, and emotions from newly graduates of an online learning program. As part of continuous education monitoring system, the sentiment analysis process produces valuable input to leverage service quality of online learning program. In this study, the aspect-based sentiment analysis is implemented to analyze a set of feedbacks from 162 newly graduate from Binus Online program majoring in Accounting, Management, Information System, and computer science. The important qualitative results of this study are confirmation that the main benefits of online learning from student perspective are mainly: the knowledge they gained from the program, learning guidance, reliable student team to work on thesis, quality of education support system, and learning happiness. © 2022 IEEE.

关键词： Sentiment analysis

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Critical (P5, dart) -Free Graphs 16th

Critical (P5, dart) -Free Graphs

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16th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2023

作者： Xia, Wen Jooken, Jorik Goedgebeur, Jan Huang, Shenwei College of Computer Science Nankai University Tianjin300071 China Tianjin Key Laboratory of Network and Data Security Technology Nankai University Tianjin300071 China Department of Computer Science KU Leuven Campus Kulak-Kortrijk Kortrijk8500 Belgium Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent9000 Belgium

ISBN: (纸本)9783031496134

Given two graphs H1 and H2, a graph is (H1, H2) -free if it contains no induced subgraph isomorphic to H1 nor H2. A dart is the graph obtained from a diamond by adding a new vertex and making it adjacent to exactly one vertex with degree 3 in the diamond. In this paper, we show that there are finitely many k-vertex-critical (P5, dart) -free graphs for k≥ 1. To prove these results, we use induction on k and perform a careful structural analysis via Strong Perfect Graph Theorem combined with the pigeonhole principle based on the properties of vertex-critical graphs. Moreover, for k∈ { 5, 6, 7 } we characterize all k-vertex-critical (P5, dart) -free graphs using a computer generation algorithm. Our results imply the existence of a polynomial-time certifying algorithm to decide the k-colorability of (P5, dart) -free graphs for k≥ 1 where the certificate is either a k-coloring or a (k+ 1 ) -vertex-critical induced subgraph. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Polynomial approximation

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Feedback GAN (FBGAN) for DNA: A novel feedback-loop architecture for optimizing protein functions

arXiv

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arXiv 2018年

作者： Gupta, Anvita Zou, James Department of Biomedical Data Science Department of Computer Science Stanford University

Generative Adversarial Networks (GANs) represent an attractive and novel approach to generate realistic data, such as genes, proteins, or drugs, in synthetic biology. Here, we apply GANs to generate synthetic DNA sequences encoding for proteins of variable length. We propose a novel feedback-loop architecture, called Feedback GAN (FBGAN) to optimize the synthetic gene sequences for desired properties using an external function analyzer. The proposed architecture also has the advantage that the analyzer need not be differentiable. We apply the feedback-loop mechanism to two examples: 1) generating synthetic genes coding for antimicrobial peptides, and 2) optimizing synthetic genes for the secondary structure of their resulting peptides. A suite of metrics demonstrate that the GAN generated proteins have desirable biophysical properties. The FBGAN architecture can also be used to optimize GAN-generated datapoints for useful properties in domains beyond genomics. Copyright © 2018, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Towards training-free refinement for semantic indexing of visual media 22nd

Towards training-free refinement for semantic indexing of vi...

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22nd International Conference on MultiMedia Modeling, MMM 2016

作者： Wang, Peng Sun, Lifeng Yang, Shiqang Smeaton, Alan F. National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China Insight Centre for Data Analytics Dublin City University Glasnevin Dublin 9 Ireland

ISBN: (纸本)9783319276700

Indexing of visual media based on content analysis has now moved beyond using individual concept detectors and there is now a focus on combining concepts or post-processing the outputs of individual concept detection. Due to the limitations and availability of training corpora which are usually sparsely and imprecisely labeled, training-based refinement methods for semantic indexing of visual media suffer in correctly capturing relationships between concepts, including co-occurrence and ontological relationships. In contrast to training-dependent methods which dominate this field, this paper presents a training-free refinement (TFR) algorithm for enhancing semantic indexing of visual media based purely on concept detection results, making the refinement of initial concept detections based on semantic enhancement, practical and flexible. This is achieved using global and temporal neighbourhood information inferred from the original concept detections in terms of weighted nonnegative matrix factorization and neighbourhood-based graph propagation, respectively. Any available ontological concept relationships can also be integrated into this model as an additional source of external a priori knowledge. Experiments on two datasets demonstrate the efficacy of the proposed TFR solution. © Springer International Publishing Switzerland 2016.

关键词： Matrix algebra

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Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning 41

Catapults in SGD: spikes in the training loss and their impa...

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41st International Conference on Machine Learning, ICML 2024

作者： Zhu, Libin Liu, Chaoyue Radhakrishnan, Adityanarayanan Belkin, Mikhail Department of Computer Science UCSD United States Halicioğlu Data Science Institute UCSD United States Harvard University United States Broad Institute of MIT and Harvard United States

In this paper, we first present an explanation regarding the common occurrence of spikes in the training loss when neural networks are trained with stochastic gradient descent (SGD).We provide evidence that the spikes in the training loss of SGD are "catapults", an optimization phenomenon originally observed in GD with large learning rates in (Lewkowycz et al., 2020).We empirically show that these catapults occur in a low-dimensional subspace spanned by the top eigenvectors of the tangent kernel, for both GD and ***, we posit an explanation for how catapults lead to better generalization by demonstrating that catapults promote feature learning by increasing alignment with the Average Gradient Outer Product (AGOP) of the true ***, we demonstrate that a smaller batch size in SGD induces a larger number of catapults, thereby improving AGOP alignment and test performance. Copyright 2024 by the author(s)

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Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study

JMIR Aging

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JMIR Aging 2025年 8卷 e69504页

作者： Socrates, Vimig Wright, Donald S. Huang, Thomas Fereydooni, Soraya Dien, Christine Chi, Ling Albano, Jesse Patterson, Brian Kanaparthy, Naga Sasidhar Wright, Catherine X. Loza, Andrew Chartash, David Iscoe, Mark Taylor, Richard Andrew Department of Biomedical Informatics and Data Science School of Medicine Yale University New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States Department of Emergency Medicine School of Medicine Yale University New Haven CT United States VA Connecticut Healthcare System US Department of Veterans Affairs West Haven CT United States Department of Pharmacy Yale New Haven Hospital New Haven CT United States BerbeeWalsh Department of Emergency Medicine University of Wisconsin–Madison Madison WI United States Section of Cardiovascular Medicine Department of Internal Medicine Yale School of Medicine New Haven CT United States School of Medicine University College Dublin Dublin Ireland Department of Biostatistics School of Public Health Yale University New Haven CT United States

Background: Polypharmacy, the concurrent use of multiple medications, is prevalent among older adults and associated with increased risks for adverse drug events including falls. Deprescribing, the systematic process of discontinuing potentially inappropriate medications, aims to mitigate these risks. However, the practical application of deprescribing criteria in emergency settings remains limited due to time constraints and criteria complexity. Objective: This study aims to evaluate the performance of a large language model (LLM)–based pipeline in identifying deprescribing opportunities for older emergency department (ED) patients with polypharmacy, using 3 different sets of criteria: Beers, Screening Tool of Older People’s Prescriptions, and Geriatric Emergency Medication Safety Recommendations. The study further evaluates LLM confidence calibration and its ability to improve recommendation performance. Methods: We conducted a retrospective cohort study of older adults presenting to an ED in a large academic medical center in the Northeast United States from January 2022 to March 2022. A random sample of 100 patients (712 total oral medications) was selected for detailed analysis. The LLM pipeline consisted of two steps: (1) filtering high-yield deprescribing criteria based on patients’ medication lists, and (2) applying these criteria using both structured and unstructured patient data to recommend deprescribing. Model performance was assessed by comparing model recommendations to those of trained medical students, with discrepancies adjudicated by board-certified ED physicians. Selective prediction, a method that allows a model to abstain from low-confidence predictions to improve overall reliability, was applied to assess the model’s confidence and decision-making thresholds. Results: The LLM was significantly more effective in identifying deprescribing criteria (positive predictive value: 0.83;negative predictive value: 0.93;McNemar test for paired proportion

关键词： calibration deprescribing emergency medicine geriatrics large language models natural language processing potentially inappropriate medication list

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Hummingbird-Optimizer and Otsu/ Kapur-Assisted Segmentation of Foot Ulcer 1st

Hummingbird-Optimizer and Otsu/ Kapur-Assisted Segmentation ...

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1st International Conference on data Engineering and Machine Intelligence, ICDEMI 2023

作者： Mohan, Ramya Kadry, Seifedine Department of Computer Science and Engineering Division of Research and Innovation Saveetha School of Engineering SIMATS Chennai602105 India Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Department of Applied Data Science Noroff University College Kristiansand4612 Norway Ajman University Ajman346 United Arab Emirates

ISBN: (纸本)9789819776153

In addition to traditional approaches, several computerized techniques have been developed to enhance the results. The automation in the medical domain considerably reduced the burden and improved disease diagnosis, treatment planning, and implementation. With the advent of automation, the medical domain has greatly reduced the burden of diagnosing diseases, developing treatment plans, and implementing them. This research aims to develop image-processing assisted detection of Diabetic Foot Ulcer (DF) from digital photographs. Digital photographs are used to assist in diagnosing Diabetic Foot Ulcer (DF). As part of the developed tool, (i) images are collected and resized, (ii) Otsu/Kapur and Hummingbird-optimizer thresholding is supported, (iii) level-set segmentation is used to extract the DF region, and (iv) the developed scheme is compared with the binary mask and its performance is verified. A total of 300 images are examined in this work, and MATLAB software is used to conduct the experiments. Comparing Otsu + LS with Kapur + LS, the overall result achieved with Kapur’s enhanced image is better than that of Otsu + LS. Authentic clinical DF images can be used to verify the proposed scheme in the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： MATLAB

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Towards an integrated risk analysis security framework according to a systematic analysis of existing proposals

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Frontiers of computer science 2024年第3期18卷 199-216页

作者： Antonio SANTOS-OLMO Luis Enrique SÁNCHEZ David G.ROSADO Manuel A.SERRANO Carlos BLANCO Haralambos MOURATIDIS Eduardo FERNÁNDEZ-MEDINA GSyA Research Group University of Castilla-La ManchaCiudad Real 13071Spain Institute for Analytics and Data Science University of EssexColchester CO43SQUK Alarcos Research Group University of Castilla-La ManchaCiudad Real 13071Spain ISTR Research group Department of Computer Science and ElectronicsUniversity of CantabriaSantander 39005Spain

The information society depends increasingly on risk assessment and management systems as means to adequately protect its key information *** availability of these systems is now vital for the protection and evolution of ***,several factors have led to an increasing need for more accurate risk analysis *** are:the speed at which technologies evolve,their global impact and the growing requirement for companies to *** analysis processes must consequently adapt to these new circumstances and new technological *** objective of this paper is,therefore,to present the results of an exhaustive analysis of the techniques and methods offered by the scientific community with the aim of identifying their main weaknesses and providing a new risk assessment and management *** analysis was carried out using the systematic review protocol and found that these proposals do not fully meet these new *** paper also presents a summary of MARISMA,the risk analysis and management framework designed by our research *** basis of our framework is the main existing risk standards and proposals,and it seeks to address the weaknesses found in these *** is in a process of continuous improvement,as is being applied by customers in several European and American *** consists of a risk data management module,a methodology for its systematic application and a tool that automates the process.

关键词： information security management security system security risk assessment and management

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Hybrid Cryptography on Wireless Sensor Network: A Systematic Literature Review 3

Hybrid Cryptography on Wireless Sensor Network: A Systematic...

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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Gandara, R. Benny Wang, Gunawan Utama, Ditdit Nugeraha Mereu Buana University Master Program of Electrical Engineering Jakarta Indonesia Information Systems Management Department Bina Nusantara University BINUS Graduate Program-Master of Information Systems Management Jakarta11480 Indonesia Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

Wireless technology gradual growth in the latest years has facilitated it to bridge its applications operated extensively in many types of industry. Wireless sensor network (WSN) technology brings several benefits over traditional wired technology by reason of the lower cost, immense flexibility escalation, and scalability which is able to be obtained from the old-style one. However, in its application WSN still experience some constraints on resource limitations in the form: processor, memory and energy, and any more challenges that related to availability, reliability and security. Based on its benefits, limitation, and challenges, and also three systematic stages, the review study was performed. The result of study was portrayed in this paper. It is regarding investigation result of hybrid cryptography (HC, as one of defense methods) realized for WSN to methodically increase the security level and decrease the resources usage. The result concluded that HC was proven in escalating the security defense level and downgrading the resources use on WSN compared to symmetric and asymmetric algorithms. © 2018 IEEE.

关键词： Wireless sensor networks

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