156 research outputs found
Comparative Analysis on Offshore Water Quality Status: A Case Study of Haizhou Bay, China
No full textThe offshore region of Haizhou Bay is characterized by intense anthropogenic activities. And the study on comparative analysis of water quality status in this offshore region has attracted more and more attention of the researchers and decision-makers. In this paper, comparative analysis on water quality status of different samples in Haizhou Bay during May 10-21, 2007 was studied by principal component analysis method (PCAM). The water quality status in Haizhou Bay was compared and analyzed by using 13 samples, with DO, SS, Active Phosphate and Petroleum impact factors. Based on the PCAM analysis procedures, the comparative analysis results of water quality state in Haizhou Bay show that the spatial order from good to bad is determined as follows: JS03> JS01> JS04> JS07> JS02> JS09> JS05> JS06> JS13> JS10> JS12> JS08> JS11.</jats:p
Industrial Transformation and Sustainable Urban Planning in the Pearl River Delta: A Landscape-based Approach
No full textIndustrialization in the PRD has brought about great economic growth and contributed to the rise and consolidation of this deltaic region as a key global player. However, it also generated severe environmental imbalances and pollution of vital and non-renewable resources, such as soil, water and air. Nowadays, the increasing shift towards service-oriented and innovation-driven sectors makes abandoned and decommissioned industrial areas available for transformation. However, to make the most of the potential of these areas to achieve sustainable urban development, novel approaches in planning and design practise are needed to tackle the complexity arising from the challenges posed by climate change and urbanization. This contribution provides a landscape-based approach to adaptive industrial transformation that looks at the spatio-temporal dimension, leveraging the intrinsic and relational qualities of these sites. The approach is tested through two applications in the Chancheng district (Foshan) and Haizhou (Guangzhou).Urban Data Scienc
The R Journal (December 2011) 3(2): Complete Issue
No full textContributed Research Articles
Creating and Deploying an Application with (R)Excel and R, Thomas Baier, Erich Neuwirth, and Michele De Meo
glm2: Fitting Generalized Linear Models with Convergence Problems, Ian C. Marschner
Implementing the Compendium Concept with Sweave and DOCSTRIP, Michael Lundholm
Watch Your Spelling! Kurt Hornik and Duncan Murdoch
Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic Programming, Haizhou Wang and Mingzhou Song
Nonparametric Goodness-of-Fit Tests for Discrete Null Distributions, Taylor B. Arnold and John W. Emerson
Using the Google Visualisation API with R, Markus Gesmann and Diego de Castillo
GrapheR: a Multiplatform GUI for Drawing Customizable Graphs in R, Maxime Hervé
rainbow: An R Package for Visualizing Functional Time Series, Han Lin Shang
Portable C++ for R Packages, Martyn Plummer
News and Notes
R\u27s Participation in the Google Summer of Code 2011
Conference Report: useR! 2011
Forthcoming Events: useR! 2012
Changes in R
Changes on CRAN
News from the Bioconductor Project
R Foundation New
ESAA: an EEG-Speech auditory attention detection database
No full textWe build a database for AAD research, which consists of competing speech stimuli and associated human neural responses, i.e, electroencephalography (EEG) recordings, namely EEG-Speech AAD (ESAA) database. This is the first AAD database with speech stimuli in a tonal language (Mandarin). Moreover, we develop an AAD baseline as a reference model for decoding which speech stream a listening subject is attending to (speaker attention detection), and a baseline for decoding which spatial locus a listening subject is attending to (speaker locus attention detection) on the ESAA database.
We release the source code and the database for use in research purpose.
This database consists of response data for 17 normal-hearing subjects (S1-S17). It includes:
- 64-channel EEG data: responses to two-speaker speech stimuli
- Auditory stimuli data (clean): Chinese short stories narrated by a female and a male professional story teller.
- Auditory stimuli data (hrtf): Auditory stimuli after head-related transfer function (HRTF) filtering (simulating sound coming from ± 90 deg).
- Preprocessing code
- AAD baseline (CNN model)The work is funded by the National Natural Science Foundation of China (Grant No. 52075177).
This research project is supported by IAF, A*STAR, SOITEC, NXP and National University of Singapore under FD-fAbrICS: Joint Lab for FD-SOI Always-on Intelligent Connected Systems (Award I2001E0053). Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of the institutions and companies supporting the joint lab.
The work by Haizhou Li is also supported by the Guangdong Provincial Key Laboratory of Big Data Computing, The Chinese University of Hong Kong, Shenzhen (Grant No. B10120210117-KP02)
Effect of ICU Quality Control and Secondary Analysis: A 12-Year Multicenter Quality Improvement Project
No full textYu Qiu,1 Mengya Zhao,1 Haizhou Zhuang,1 Zhuang Liu,1 Pei Liu,1 Deyuan Zhi,1 Jing Bai,1 Xiuming Xi,2 Jin Lin,1 Meili Duan1 1Department of Critical Care Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, People’s Republic of China; 2Department of Critical Care Medicine, Fuxing Hospital, Capital Medical University, Beijing, 100038, People’s Republic of ChinaCorrespondence: Meili Duan, Department of Critical Care Medicine, Beijing Friendship Hospital, Capital Medical University, No. 95 Yong’an Road, Xicheng District, Beijing, 100050, People’s Republic of China, Email [email protected] Jin Lin, Department of Critical Care Medicine, Beijing Friendship Hospital, Capital Medical University, No. 95 Yong’an Road, Xicheng District, Beijing, 100050, People’s Republic of China, Email [email protected]: China’s aging population and increasing demand for critical care pose significant challenges to ICU quality improvement (QI). This study evaluates the impact of a 12-year multicenter QI initiative on ICU performance and patient outcomes in the context of resource constraints.Methods: A pre-post intervention study was conducted across 75 ICUs in Beijing from January 2011 to December 2022. Key interventions included the establishment of QI teams, infection prevention protocols, pain and sedation management, nutritional support, and early mobilization strategies based on the PDCA cycle, as well as regular training and feedback. Primary outcomes included ICU mortality, standardized mortality ratio (SMR) (ratio of observed to expected deaths, adjusted for risk), and healthcare-associated infections (HAIs), such as VAP, CLABSI, and CAUTI rates. Secondary outcomes included unplanned extubation rates, reintubation within 48 hours, and ICU readmission rates within 48 hours.Results: Analysis of 425,534 patient records from 5396 reports revealed significant improvements. The proportion of ICU admissions among total inpatients increased from 4.1% in 2011 to 7.3% in 2022 (P 0.05).Conclusion: The study highlights the importance of addressing structural, process, and outcome indicators for effective ICU management. Continued monitoring and targeted interventions for high-risk ICUs are essential to sustaining quality improvements.Keywords: intensive care unit, quality improvement, data analysis, patient prognosis, mortality rat
Spiking Neural Network Learning, Benchmarking, Programming and Executing
No full textThis eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contac
Leaning to train: Linking financial news articles to company short names
No full textAs a special type of named entity, company name is frequently mentioned in financial news articles, leading to significant necessity on company-oriented information retrieval and management. However, company names are usually mentioned with short names, which are sometimes ambiguous. For example, apple refers in some cases to Apple Incorporation while in other cases to a kind of sweet fruit. This motivates our research on linking financial news articles to company short name, which aims to determine whether a mention in an article is short name of a company. The supervised approach requires labor on annotation of news article that mention the specific company short name. It is rather unpractical as new company short names appear constantly. In this work, we propose a self-contained unsupervised learning framework, which relies on probabilistic topic model to collect training data automatically. Experimental results show that the performance is close to the state-of-the-art supervised approach which relies on human-judged gold standard. ? 2014 IEEE.EI
Automatic rank-ordering of singing vocals with twin-neural network
No full textWhen making judgements, humans are known to be better at choosing a preferred option amongst a small number of options, rather than giving an absolute ranking of all the options. This preference-based judgment rank-ordering method is called Best-Worst Scaling (BWS). Inspired by this concept, we propose a preference-based framework to generate a relative rank-ordering of singing vocals, and therefore, singers. We adopt a twin-neural network (Siamese) that learns to choose a preferred candidate in terms of singing quality between two inputs. With a few such pairwise comparisons, this method generates a relative rank-order of a complete list of singers. Additionally, we incorporate a knowledge-based musically-relevant pitch histogram representation, as a conditioning vector, to provide explicit musical information to the network. The experiments show that this method is able to reliably evaluate singing quality and rank-order singing vocals, independent of the song or the singer. The results suggest that the twin-neural network learns the underlying discerning properties relevant to singing quality, instead of being specific to the content of a song or singer
Enhancement of furfural formation from C5 carbohydrates by NaCl in a green reaction system of CO<sub>2</sub> -water-isopropanol
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