检索结果-内蒙古大学图书馆

8th International Conference on Web Intelligence, Mining and Semantics, WIMS 2018

作者： Bratić, Brankica Houle, Michael E. Kurbalija, Vladimir Oria, Vincent Radovanović, Miloš University of Novi Sad Faculty of Sciences Novi Sad Serbia National Institute of Informatics Tokyo Japan New Jersey Inst. of Technology Dept. of Computer Science NewarkNJ United States

ISBN: (纸本)9781450354899

K-nearest neighbor graphs (K-NNGs) are used in many data-mining and machine-learning algorithms. Naive construction of K-NNGs has a complexity of O(n2), which could be a problem for large-scale data sets. In order to achieve higher efficiency, many exact and approximate algorithms have been developed, including the NN-Descent algorithm of Dong, Charikar and Li. Empirical evidence suggests that the practical complexity of this algorithm is in Õ(n1.14), which is a significant improvement over brute force construction. However, NN-Descent has a major drawback — it produces good results only on data of low intrinsic dimensionality. This paper presents an experimental analysis of this behavior, and investigates possible solutions. We link the quality of performance of NN-Descent with the phenomenon of hubness, defined as the tendency of intrinsically high-dimensional data to contain hubs —points with high in-degrees in the K-NNG. We propose two approaches to alleviate the observed negative influence of hubs on NN-Descent performance. © 2018 Association for Computing Machinery.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

P10.12.A CDK12/CDK13 inhibition disrupts a transcriptional program critical for glioblastoma survival

引用

Neuro-Oncology 2022年第SUPPLEMENT_2期24卷 ii51–ii51页

作者： Lier, S Rein, I Lund, S Lång, A Lång, E Meyer, N Dutta, A Anand, S Nesse, G Johansen, R Klungland, A Rinholm, J Bøe, S Anand, A Pollard, S Lerdrup, M Pandey, D Institute of Basic Medical Sciences University of Oslo Oslo Norway Dept. of Microbiology Oslo University Hospital Oslo Norway Dept. of Radiation Biology Oslo University Hospital Oslo Norway Dept. of Computer Science and Engineering Indian Institute of Technology Guwahati Assam India Department of Informatics Systems and Communications University of Milano-Bicocca Milan Italy Dept. of Biosciences University of Oslo Oslo Norway MRC Centre for Regenerative Medicine SCRM Building University of Edinburgh Edinburgh United Kingdom Center for Chromosome Stability (CCS) Department of Cellular and Molecular Medicine University of Copenhagen Copenhagen Denmark

来源：评论

学校读者我要写书评

暂无评论

The role of cue enhancement and frequency fine-tuning in hearing impaired phone recognition

arXiv

引用

arXiv 2019年

作者： Abavisani, Ali Hasegawa-Johnson, Mark A. University of Illinois at Urbana-Champaign Dept. of Electrical and Computer Engineering Beckman Inst. 405 N Mathews Ave UrbanaIL61801 United States

A speech-based hearing test is designed to identify the susceptible error-prone phones for individual hearing impaired (HI) ear. Only robust tokens in the experiment noise levels had been chosen for the test. The noise-robustness of tokens is measured as SNR90 of the token, which is the signal to the speech-weighted noise ratio where a normal hearing (NH) listener would recognize the token with an accuracy of 90% on average. Two sets of tokens T1 and T2 having the same consonant-vowels but different talkers with distinct SNR90 had been presented with flat gain at listeners’ most comfortable level. We studied the effects of frequency fine-tuning of the primary cue by presenting tokens of the same consonant but different vowels with similar SNR90. Additionally, we investigated the role of changing the intensity of primary cue in HI phone recognition, by presenting tokens from both sets T1 and T2. On average, 92% of tokens are improved when we replaced the CV with the same CV but with a more robust talker. Additionally, using CVs with similar SNR90 , on average, tokens are improved by 75%, 71%, 63%, and 72%, when we replaced vowels /A, æ, I, E/, respectively. The confusion pattern in each case provides insight into how these changes affect the phone recognition in each HI ear. We propose to prescribe hearing aid amplification tailored to individual HI ears, based on the confusion pattern, the response from cue enhancement, and the response from frequency fine-tuning of the cue. Copyright © 2019, The Authors. All rights reserved.

关键词： Audition

来源：评论

学校读者我要写书评

暂无评论

Automated Assessment of Pain Intensity Based on EEG Signal Analysis

Automated Assessment of Pain Intensity Based on EEG Signal A...

引用

IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Panagiotis A. Bonotis Dimosthenis C. Tsouros Panagiotis N. Smyrlis Alexandros T. Tzallas Nikolaos Giannakeas Evripidis Glavas Markos G. Tsipouras Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Department of Informatics and Telecommunication University of Ioannina Arta Greece UNIVEYE IKE Science and Technology Park of Epirus Ioannina Greece Dept. of Electrical and Computer Engineering Univ. of Western Macedonia Kozani Greece

Objective characterization of pain intensity is necessary under certain clinical conditions. The portable electroencephalogram (EEG) is a cost-effective assessment tool and lately, new methods using efficient analysis of related dynamic changes in brain activity in the EEG recordings proved that these can reflect the dynamic changes of pain intensity. In this paper, a novel method for automated assessment of pain intensity using EEG data is presented. EEG recordings from twenty-two (22) healthy volunteers are recorded with the Emotiv EPOC+ using the Cold Pressor Test (CPT) protocol. The relative power of each brain band's energy for each channel is extracted and the stochastic forest algorithm is employed for discrimination across five classes, depicting the pain intensity. Obtained results in terms of classification accuracy reached high levels (72.7%), which renders the proposed method suitable for automated pain detection and quantification of its intensity.

关键词： Protocols Pain Forestry Tools Electroencephalography Mobile handsets Signal analysis

来源：评论

学校读者我要写书评

暂无评论

A Whole Slide Ki-67 Proliferation Analysis System for Breast Carcinoma

A Whole Slide Ki-67 Proliferation Analysis System for Breast...

引用

IEEE International Conference on Ubi-Media Computing

作者： Chien-Chuan Ko Chun-Hung Lin Chih-Hung Chuang Chuan-Yu Chang Shih-Hao Chang Ji-Han Jiang Dept. of Computer Science and Information Engineering National Chia Yi University ChaiYi City Taiwan R.O.C Inst. of General Surgery Dalin TsuChi Hospital ChiaYi County Taowan R.O.C Dept. of Computer Science and Information Engineering National YunLin University of Science and Technology YunLin County Taiwan R.O.C. Dept. of Computer Science and Information Engineering Tamkang University New Taipei City Taiwan R.O.C

ISBN: (数字)9781728128207

ISBN: (纸本)9781728128214

The expression of Ki-67 with IHC stain has been utilized to assess the prognosis of breast cancer, and the degree of cellular differentiation and proliferation rate. Recently, some researchers utilize the index to predict metastasis of breast carcinoma. In traditional pathological screening, manual assessment of Ki-67 proliferative index may be limited by manual evaluation from different pathologists. Especially, inconsistent biopsy staining would affect the quantitation of Ki-67 proliferation so that developing an automatic system to assess Ki-67 proliferation index poses a big challenge. The goal of this paper is to propose an automatic analysis system to evaluate the degrees of Ki-67 proliferation on IHC stained cells of breast tissue using image processing and machine intelligence techniques. The proposed system not only can assist physicians diagnose, but also provides important information of treatment and prognosis. In order to validate the evaluation performance, we compared with visual assessments by a pathologist and the ImmnuoRatio (i.e., a web-based evaluation system in Ki-67 expression) developed by Vilppu J Tuominen et al.[1] via a number of Ki-67 stained samples for patients with breast carcinoma. Experimental results also demonstrate that the proposed system can automatically, accurately and reliably assess the Ki-67 proliferation index on the breast tissue images with a precision of around 87.37%. However, the accuracy evaluating with ImmunoRatio only can reach 75.82% with the same samples. Moreover, our proposed system also provides various interaction functions including browsing, navigation, and quantitative analyses for pathologists who evaluate the expression of the Ki-67 proliferation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Roadmap on Deep Learning for Microscopy

arXiv

引用

arXiv 2023年

作者： Volpe, Giovanni Wählby, Carolina Tian, Lei Hecht, Michael Yakimovich, Artur Monakhova, Kristina Waller, Laura Sbalzarini, Ivo F. Metzler, Christopher A. Xie, Mingyang Zhang, Kevin Lenton, Isaac C.D. Rubinsztein-Dunlop, Halina Brunner, Daniel Bai, Bijie Ozcan, Aydogan Midtvedt, Daniel Wang, Hao Sladoje, Nataša Lindblad, Joakim Smith, Jason T. Ochoa, Marien Barroso, Margarida Intes, Xavier Qiu, Tong Yu, Li-Yu You, Sixian Liu, Yongtao Ziatdinov, Maxim A. Kalinin, Sergei V. Sheridan, Arlo Manor, Uri Nehme, Elias Goldenberg, Ofri Shechtman, Yoav Moberg, Henrik K. Langhammer, Christoph Špačková, Barbora Helgadottir, Saga Midtvedt, Benjamin Argun, Aykut Thalheim, Tobias Cichos, Frank Bo, Stefano Hubatsch, Lars Pineda, Jesus Manzo, Carlo Bachimanchi, Harshith Selander, Erik Homs-Corbera, Antoni Fränzl, Martin de Haan, Kevin Rivenson, Yair Korczak, Zofia Adiels, Caroline Beck Mijalkov, Mite Veréb, Dániel Chang, Yu-Wei Pereira, Joana B. Matuszewski, Damian Kylberg, Gustaf Sintorn, Ida-Maria Caicedo, Juan C. Cimini, Beth A. Bell, Muyinatu Lediju A. Saraiva, Bruno M. Jacquemet, Guillaume Henriques, Ricardo Ouyang, Wei Le, Trang Gómez-De-Mariscal, Estibaliz Sage, Daniel Muñoz-Barrutia, Arrate Lindqvist, Ebba Josefson Bergman, Johanna Department of Physics University of Gothenburg Gothenburg41296 Sweden Dept. IT and SciLifeLab Uppsala University Sweden Department of Electrical and Computer Engineering Boston University BostonMA02215 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Görlitz Germany Department of Renal Medicine Division of Medicine University College London Royal Free Hospital Campus London United Kingdom Artificial Intelligence for Life Sciences CIC Dorset United Kingdom Roche Pharma International Informatics Roche Diagnostics GmbH Mannheim Germany Department of Electrical Engineering and Computer Sciences UC Berkeley United States Technische Universität Dresden Faculty of Computer Science Dresden Germany Max Planck Institute of Molecular Cell Biology and Genetics Center for Systems Biology Dresden Dresden Germany University of Maryland College Park United States Klosterneuburg3400 Austria School of Mathematics and Physics The University of Queensland Brisbane4072 Australia Australian Research Council Centre of Excellence for Engineered Quantum Systems The University of Queensland Brisbane4072 Australia Département d’Optique P. M. Duffieux Institut FEMTO-ST Université Franche-Comté CNRS UMR 6174 Besançon France Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA United States Department of Information Technology Uppsala University Sweden Department of Biomedical Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Elephas 1 Erdman Pl. Madison53705 United States University of Wisconsin–Madison Department of Medical Physics MadisonWI53705 United States Department of Molecular and Cellular Physiology Albany Medical College AlbanyNY12208 United States Research Laboratory of Electronics Electrical Engineering and Computer Science Massachusetts Institute of Technology BostonMA United States Center for Nanophase Materials Sciences Oak R

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

DiamondGAN: Unified multi-modal generative adversarial networks for mri sequences synthesis

arXiv

引用

arXiv 2019年

作者： Li, Hongwei Paetzold, Johannes C. Sekuboyina, Anjany Koer, Florian Zhang, Jianguo Kirschke, Jan S. Wiestler, Benedikt Menze, Bjoern Dept. of Informatics Technical University of Munich Germany Dept. of Neuroradiology Klinikum rechts der Isar Germany Dept. of Computer Science and Engineering Southern University of Science and Technology China Shenzhen Institude of Artificial Intelligence and Robotics for Society China Institude for Advanced Study Technical University of Munich

Synthesizing MR imaging sequences is highly relevant in clin-ical practice, as single sequences are often missing or are of poor quality (e.g. due to motion). Naturally, the idea arises that a target modality would benefit from multi-modal input, as proprietary information of in-dividual modalities can be synergistic. However, existing methods fail to scale up to multiple non-aligned imaging modalities, facing common drawbacks of complex imaging sequences. We propose a novel, scalable and multi-modal approach called DiamondGAN. Our model is capable of performing exible non-aligned cross-modality synthesis and data in-fill, when given multiple modalities or any of their arbitrary subsets, learning structured information in an end-to-end fashion. We synthesize two MRI sequences with clinical relevance (i.e., double inversion recovery (DIR) and contrast-enhanced T1 (T1-c)), reconstructed from three com-mon sequences. In addition, we perform a multi-rater visual evaluation experiment and find that trained radiologists are unable to distinguish synthetic DIR images from real ones. Copyright © 2019, The Authors. All rights reserved.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Predicting Community Engagement on Twitter on Environmental Health Hazards

Predicting Community Engagement on Twitter on Environmental ...

引用

International Conference on Semantic Computing

作者： Adel Alshehri Wainella Isaacs Aseel Addawood Maya Trotz Sriram Chellappan King Abdulaziz City for Science and Technology Riyadh Saudi Arabia Dept. of Civil and Environmental Engineering University of South Florida Tampa Florida Illinois Informatics Institute University of Illinois at Urbana Champaign Champaign Illinois Dept. of Computer Science and Engineering University of South Florida Tampa Florida

In this empirical study, a framework was developed for binary and multi-class classification of Twitter data. We first introduce a manually built gold standard dataset of 4000 tweets related to the environmental health hazards in Barbados for the period 2014 - 2018. Then, the binary classification was used to categorize each tweet as relevant or irrelevant. Next, the multiclass classification was then used to further classify relevant tweets into four types of community engagement: reporting information, expressing negative engagement, expressing positive engagement, and asking for information. Results indicate that (combination of TF-IDF, psychometric, linguistic, sentiment and Twitter-specific features) using a Random Forest algorithm is the best feature for detecting and predicting binary classification with (87% F1 score). For multi-class classification, TF-IDF using Decision Tree algorithm was the best with (74% F1 score).

关键词： Twitter Feature extraction Diseases Hazards Support vector machines Data mining

来源：评论

学校读者我要写书评

暂无评论

Firefly Algorithm Approach For Rational Bézier Border Reconstruction of Skin Lesions from Macroscopic Medical Images

Firefly Algorithm Approach For Rational Bézier Border Recon...

引用

International Conference on Software, Knowledge Information, Industrial Management and Applications (SKIMA)

作者： Akemi Gálvez Andrés Iglesias Hassan Ugail Lihua You Habibollah Haron Zulfiqar Habib Dept. of Information Science Toho University Funabashi Japan Faculty of Engineering & Informatics Media Design and Technology University of Bradford Bradford UK National Center for Computer Animation Bournemouth University Poole UK Dept. of Computer Science Universiti Teknologi Malaysia Skudai Malaysia Center for Research in VIG-Robotics COMSATS University Islamabad Lahore Pakistan

Image segmentation is a fundamental step for image processing of medical images. One of the most important tasks in this step is border reconstruction, which consists of constructing a border curve separating the organ or tissue of interest from the image background. This problem can be formulated as an optimization problem, where the border curve is computed through data fitting procedures from a collection of data points assumed to lie on the boundary of the object under analysis. However, standard mathematical optimization techniques do not provide satisfactory solutions to this problem. Some recent papers have applied evolutionary computation techniques to tackle this issue. Such works are only focused on the polynomial case, ignoring the more powerful (but also more difficult) case of rational curves. In this paper, we address this problem with rational Bézier curves by applying the firefly algorithm, a popular bio-inspired swarm intelligence technique for optimization. Experimental results on medical images of melanomas show that this method performs well and can be successfully applied to this problem.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Assessing the performance of novel and sustainable electrochemical sensor based on cobalt sulfide/upcycled reduced graphene oxide from plastic waste

引用

Electrochemistry Communications 2025年

作者： Arafat Toghan N. Roushdy Sami A. Al-Hussain Mohamed S. Elnouby Samah M. Yousef A.A.M. Farag M. Elsayed Youssef Noha A. Elessawy Chemistry Department College of Science Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh 11623 Saudi Arabia Electronics Materials Department Advanced Technology and New Materials Research Institute City of Scientific Research and Technological Applications (SRTA-City) New Borg El-Arab City Alexandria 21934 Egypt Nanomaterials and Composites Research Department Advanced Technology and New Materials Research Institute City of Scientific Research and Technological Applications (SRTA-City) New Borg El-Arab City Alexandria 21934 Egypt Basic Science Department Higher Institute of Engineering and Technology New Borg El-Arab City Alexandria Egypt Thin Film Laboratory Physics Department Faculty of Education Ain Shams University Heliopolis Roxy Cairo 11757 Egypt Computer Based Engineering Applications Dept. Informatics Research Institute City of Scientific Research and Technological Applications (SRTA-City) New Borg El-Arab City Alexandria 21934 Egypt

Developing electrochemical sensors that are both highly sensitive and environmentally sustainable is a pressing need in modern healthcare and environmental analysis. In this study, a cobalt sulfide/reduced graphene oxide (CoS/rGO) nanocomposite was synthesized via a straightforward, low-cost method that integrates thiourea and cobalt acetate to form CoS, with rGO derived from recycled plastic waste. The structural and electrochemical properties of the composites were systematically investigated using cyclic voltammetry (CV) and linear sweep voltammetry (LSV). The addition of rGO, varied from 0 to 50 wt%, notably enhanced the electrical conductivity and surface activity of the sensing interface. Among the tested formulations, the composite containing 40 wt% rGO exhibited the highest performance, achieving a sensitivity of 12.4 μA mM −1  cm −2 and a detection limit of 0.2 μM, which is approximately 7.5 times lower than that of pristine CoS. Kinetic analysis confirmed that the sensing mechanism follows a pseudo-second-order model, indicative of a chemisorption-driven interaction between paracetamol molecules and the sensor surface. The sensor displayed excellent operational stability over 100 consecutive cycles and high repeatability with a relative standard deviation below 2.5 %. This work demonstrates a novel, green strategy for sensor fabrication that effectively combines electronic functionality with environmental sustainability, making the CoS/rGO nanocomposite a viable platform for next-generation sensing technologies.

关键词： CoS NPs Plastic waste recycling Reduced graphene oxide Paracetamol Sensitivity-kinetic assessments

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：