An approach for document retrieval using cluster-based inverted indexing

2021 ◽  
pp. 016555152110184
Author(s):  
Gunjan Chandwani ◽  
Anil Ahlawat ◽  
Gaurav Dubey
Keyword(s):  
High Performance ◽  
Clustering Algorithm ◽  
Pearson Correlation ◽  
Relevant Information ◽  
Document Retrieval ◽  
Bhattacharyya Distance ◽  
Data Set ◽  
Query Matching ◽  
Inverted Indexing ◽  
Query Optimisation

Document retrieval plays an important role in knowledge management as it facilitates us to discover the relevant information from the existing data. This article proposes a cluster-based inverted indexing algorithm for document retrieval. First, the pre-processing is done to remove the unnecessary and redundant words from the documents. Then, the indexing of documents is done by the cluster-based inverted indexing algorithm, which is developed by integrating the piecewise fuzzy C-means (piFCM) clustering algorithm and inverted indexing. After providing the index to the documents, the query matching is performed for the user queries using the Bhattacharyya distance. Finally, the query optimisation is done by the Pearson correlation coefficient, and the relevant documents are retrieved. The performance of the proposed algorithm is analysed by the WebKB data set and Twenty Newsgroups data set. The analysis exposes that the proposed algorithm offers high performance with a precision of 1, recall of 0.70 and F-measure of 0.8235. The proposed document retrieval system retrieves the most relevant documents and speeds up the storing and retrieval of information.

scholarly journals Application of PZT Technology and Clustering Algorithm for Debonding Detection of Steel-UHPC Composite Slabs

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2953 ◽  
Author(s):  
Banfu Yan ◽  
Qiqi Zou ◽  
You Dong ◽  
Xudong Shao
Keyword(s):  
Lead Zirconate Titanate ◽  
High Performance ◽  
Clustering Algorithm ◽  
High Performance Concrete ◽  
Fatigue Cracks ◽  
Experimental Tests ◽  
Interfacial Debonding ◽  
Data Set ◽  
Composite Slabs ◽  
Steel Deck

A lightweight composite bridge deck system composed of steel orthotropic deck stiffened with thin Ultra-High Performance Concrete (UHPC) layer has been proposed to eliminate fatigue cracks in orthotropic steel decks. The debonding between steel deck and UHPC layer may be introduced during construction and operation phases, which could cause adverse consequences, such as crack-induced water invasion and distinct reduction of the shear resistance. The piezoelectric lead zirconate titanate (PZT)-based technologies are used to detect interfacial debonding defects between the steel deck and the UHPC layer. Both impedance analysis and wave propagation method are employed to extract debonding features of the steel-UHPC composite slab with debonding defect in different sizes and thicknesses. Experimental tests are performed on two steel-UHPC composite slabs and a conventional steel-concrete composite deck. Additionally, an improved Particle Swarm Optimization (PSO)-k-means clustering algorithm is adopted to obtain debonding patterns based on the feature data set. The laboratory tests demonstrate that the proposed approach provides an effective way to detect interfacial debonding of steel-UHPC composite deck.

scholarly journals Impact of hospital volume on in-hospital mortality and 30-day cardiac readmission of hospitalized patients with heart faliure. A population based study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
J.L Bonilla Palomas ◽  
M.P Anguita-Sanchez ◽  
F.J Elola ◽  
J.L Bernal ◽  
C Fernandez-Perez ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Regression Models ◽  
Hospital Volume ◽  
Clustering Algorithm ◽  
Pearson Correlation ◽  
High Volume ◽  
Hospitalized Patients ◽  
Data Set ◽  
High Volume Hospital ◽  
Low Volume

Abstract Background Heart failure (HF) is a major health care problem. Epidemiological data from hospitalized patients are scarce and the association between hospital volume and patient outcomes is largely unknown. Purpose The aim of this study was to analyze the relationship between hospital volume and outcomes (in-hospital mortality and 30-day cardiac readmission). Methods We conducted an observational study of patients discharged with the principal diagnosis of HF from The National Health System' acute hospitals during 2015. The source of the data was the Minimum Basic Data Set of the Ministry of Health, Consumer and Social Welfare. We calculated risk-standardized mortality rates (RSMR) at the index episode and risk-standardized cardiac diseases readmissions rates (RSRR) within 30 days after discharge by using a risk adjustment multilevel logistic regression models developed by the Medicare and Medicaid Services. Information on the number of HF discharges at each hospital in 2015 was analysed to classify centres into 2 categories (high- and low-volume hospitals). To discriminate between high- and low-volume centers, a K-means clustering algorithm was used. The association between volume and RSMR or RSRR was tested with the Pearson correlation coefficient and linear regression models. Results A total of 117 233 episodes of HF were selected during 2015. The mean age was 80±10 years and 46% were women. The crude in-hospital mortality rate was 12.1% and 30-day cardiac readmission rate was 18%. The cut-off point was set at 517 HF discharges per hospital during 2015. High volume hospitals had a statistically lower RSMR (10.3±2.8 vs 11.3±3.6; p<0.001) and higher RSRR (10.7±1.9 vs 9.2±1.6; p<0.001) than low volume hospitals. Low-volume hospitals showed higher dispersion of outcomes than high-volume, both for RSMR and RSRR (Figure). Conclusions We found that patients hospitalized for HF in 2105 had lower in-hospital mortality if they were admitted to a high-volume hospital. We have also found that high-volume hospitals had higher 30-day cardiac readmission rates. Funding Acknowledgement Type of funding source: None

scholarly journals Debonding Detection of Steel-UHPC Composite Slab Using PZT Technology and Clustering Algorithm

2018 ◽  
Author(s):  
Banfu Yan ◽  
Qiqi Zou ◽  
You Dong ◽  
Xudong Shao
Keyword(s):  
Lead Zirconate Titanate ◽  
High Performance ◽  
Clustering Algorithm ◽  
High Performance Concrete ◽  
Fatigue Cracks ◽  
Clustering Algorithms ◽  
Interface Condition ◽  
Data Set ◽  
Composite Slab ◽  
Steel Deck

A lightweight composite bridge deck system composed of steel orthotropic deck stiffened with thin Ultra-High Performance Concrete (UHPC) layer is developed to eliminate fatigue cracks in orthotropic steel decks. During the construction and operation period of the bridge, the debonding between the steel deck and the UHPC layer may introduce the several issues, such as crack-induced water invasion and distinct reduction of the shear resistance. In the study, an effective and novel non-destructive interface condition monitoring approach using piezoelectric lead zirconate titanate (PZT)-based technologies is proposed to detect interfacial delamination between steel deck and UHPC layer. Experimental tests are performed on several steel-UHPC composite slabs and a conventional steel-concrete composite slab. The thin styrofoam sheets with different sizes and thicknesses are set on different locations of the steel deck as the artificial debondings. The PZT ceramic patches are bonded on the surfaces of the steel deck and UHPC layer as the actuators/sensors. An improved PSO (Particle Swarm Optimization)-K-means clustering algorithms is proposed to obtain the debonding patterns based on the feature data set. The laboratory tests demonstrate that the proposed approach provides an effective and accurate way to detect interfacial debonding of steel-UHPC composite slab.

A Study and Implementation of a Movie Recommendation System in a Cloud-based Environment

2017 ◽  
Vol 9 (1) ◽  
pp. 25-36 ◽  
Author(s):  
Jaime Raigoza ◽  
Vikrantsinh Karande
Keyword(s):  
High Performance ◽  
Recommendation System ◽  
Pearson Correlation ◽  
Software As A Service ◽  
Psychological Profile ◽  
Choice Overload ◽  
Data Set ◽  
Movie Recommendation ◽  
Movie Ratings ◽  
Content Based Filtering

The availability of huge amounts of data in recent years have led users to being faced with an overload of choices. The outcome is a growth on the importance of recommendation systems due to their ability to solve this choice overload problem, by providing users with the most relevant products from many possible choices. For producing recommendations, things like a user's psychological profile, their browsing history and movie ratings from other users can be considered. To determine how strongly two user's behavior are related to each other, a Pearson correlation coefficient value is often calculated. In this paper, we study the recommendation system on a proposed cloud based environment to produce a list of recommended movies based on a user's profile information. Based on the Software-as-a-Service (SaaS) model implemented, we discuss the concepts such as collaborative filtering and content-based filtering. Given a MovieLens data-set, our results indicate that the proposed approach can provide a high performance in terms of precision, and generate more reliable and personalized movie recommendations, when given a greater number of movies rated by a user. An evaluation was done under minimal known data, which commonly leads to the cold-start problem.

Sulphonamide: Distribution, Toxicology, Environmental Characteristics, and Analysis - A Review

2020 ◽  
Vol 16 ◽  
Author(s):  
Kirubanandam Grace Pavithra ◽  
Vasudevan Jaikumar ◽  
Ponnusamy Senthil Kumar ◽  
PanneerSelvam SundarRajan
Keyword(s):  
Aqueous Solution ◽  
High Performance Liquid Chromatography ◽  
Capillary Electrophoresis ◽  
Liquid Chromatography ◽  
High Performance ◽  
Uv Spectroscopy ◽  
Relevant Information ◽  
Fluorometric Determination ◽  
Distinctive Features ◽  
The World

Background: Many antibiotics were widely used as medication based on their distinctive features. Among them, sulphonamides were commonly used, however their recalcitrant nature makes them difficult to dispose. Hence, their interaction with environment and analytic technique requires considerable attention globally. Objective: Therefore, this review aimed to provide detailed discussion about environmental as well as human health behaviour and analytic techniques corresponding to sulphonamides. Methods: Various results and discussion were extracted from technical journals and books published by different researchers from all over the world. The cited bibliographic references were intentionally investigated in order to extract relevant information related to proposed work. Results: In this review, the determination techniques such as UV-spectroscopy, Enthalpimetry, Immunosensor, Chromatography, Chemiluminescence, Photoinduced fluorometric determination, Capillary electrophoresis for sulphonamide determination were discussed in detail. Among them, High performance liquid chromatography (HPLC) and UV-spectroscopy was effective and extensively used for screening sulphonamide. Conclusion: Knowing the quantification and behaviour of sulphonamide in aqueous solution is mandatory to opt the suitable wastewater treatment required. Hence, choosing appropriate high precision and feasible screening techniques is necessary, which can be attained with this review.

Recording Epigraphic Sources as Part of Artworks

2020 ◽  
pp. 128-144
Author(s):  
Gabriele Pieke
Keyword(s):  
Original Artwork ◽  
Art History ◽  
Historical Analysis ◽  
Relevant Information ◽  
Ancient Egypt ◽  
Historical Study ◽  
Data Set ◽  
Line Drawings ◽  
Color Data ◽  
Written Word

Art history has its own demands for recording visual representations. Objectivity and authenticity are the twin pillars of recording artistic data. As such, techniques relevant to epigraphic study, such as making line drawings, may not always be the best approach to an art historical study, which addresses, for example, questions about natural context and materiality of the artwork, the semantic, syntactic, and chronological relation between image and text, work procedures, work zones, and workshop traditions, and interactions with formal structures and beholders. Issues critical to collecting data for an art historical analysis include recording all relevant information without overcrowding the data set, creating neutral (i.e., not subjective) photographic images, collecting accurate color data, and, most critically, firsthand empirical study of the original artwork. A call for greater communication in Egyptology between epigraphy/palaeography and art history is reinforced by drawing attention to images as tools of communication and the close connection between the written word and figural art in ancient Egypt.

scholarly journals Hugoniot Data and Equation of State Parameters for an Ultra-High Performance Concrete

2021 ◽  
Author(s):  
C. Sauer ◽  
F. Bagusat ◽  
M.-L. Ruiz-Ripoll ◽  
C. Roller ◽  
M. Sauer ◽  
...  
Keyword(s):  
Equation Of State ◽  
High Performance ◽  
High Performance Concrete ◽  
Applied Pressure ◽  
High Strength ◽  
Parameter Study ◽  
Ultra High Performance Concrete ◽  
Data Set ◽  
Shock Response ◽  
Particle Velocities

AbstractThis work aims at the characterization of a modern concrete material. For this purpose, we perform two experimental series of inverse planar plate impact (PPI) tests with the ultra-high performance concrete B4Q, using two different witness plate materials. Hugoniot data in the range of particle velocities from 180 to 840 m/s and stresses from 1.1 to 7.5 GPa is derived from both series. Within the experimental accuracy, they can be seen as one consistent data set. Moreover, we conduct corresponding numerical simulations and find a reasonably good agreement between simulated and experimentally obtained curves. From the simulated curves, we derive numerical Hugoniot results that serve as a homogenized, mean shock response of B4Q and add further consistency to the data set. Additionally, the comparison of simulated and experimentally determined results allows us to identify experimental outliers. Furthermore, we perform a parameter study which shows that a significant influence of the applied pressure dependent strength model on the derived equation of state (EOS) parameters is unlikely. In order to compare the current results to our own partially reevaluated previous work and selected recent results from literature, we use simulations to numerically extrapolate the Hugoniot results. Considering their inhomogeneous nature, a consistent picture emerges for the shock response of the discussed concrete and high-strength mortar materials. Hugoniot results from this and earlier work are presented for further comparisons. In addition, a full parameter set for B4Q, including validated EOS parameters, is provided for the application in simulations of impact and blast scenarios.

scholarly journals ESR white paper: blockchain and medical imaging

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
◽  
Elmar Kotter ◽  
Luis Marti-Bonmati ◽  
Adrian P. Brady ◽  
Nandita M. Desouza
Keyword(s):  
Medical Imaging ◽  
Image Data ◽  
Distributed Database ◽  
Relevant Information ◽  
White Paper ◽  
Imaging Data ◽  
Data Set ◽  
Blockchain Technology ◽  
Potential Applications ◽  
Basic Technology

AbstractBlockchain can be thought of as a distributed database allowing tracing of the origin of data, and who has manipulated a given data set in the past. Medical applications of blockchain technology are emerging. Blockchain has many potential applications in medical imaging, typically making use of the tracking of radiological or clinical data. Clinical applications of blockchain technology include the documentation of the contribution of different “authors” including AI algorithms to multipart reports, the documentation of the use of AI algorithms towards the diagnosis, the possibility to enhance the accessibility of relevant information in electronic medical records, and a better control of users over their personal health records. Applications of blockchain in research include a better traceability of image data within clinical trials, a better traceability of the contributions of image and annotation data for the training of AI algorithms, thus enhancing privacy and fairness, and potentially make imaging data for AI available in larger quantities. Blockchain also allows for dynamic consenting and has the potential to empower patients and giving them a better control who has accessed their health data. There are also many potential applications of blockchain technology for administrative purposes, like keeping track of learning achievements or the surveillance of medical devices. This article gives a brief introduction in the basic technology and terminology of blockchain technology and concentrates on the potential applications of blockchain in medical imaging.

scholarly journals A Fast and Lightweight Method with Feature Fusion and Multi-Context for Face Detection

2018 ◽  
Vol 10 (8) ◽  
pp. 80
Author(s):  
Lei Zhang ◽  
Xiaoli Zhi
Keyword(s):  
Face Detection ◽  
Graphics Processing Units ◽  
High Performance ◽  
Feature Fusion ◽  
Local Context ◽  
Data Set ◽  
Global Context ◽  
Detection Algorithms ◽  
Multi Scale ◽  
Benchmark Datasets

Convolutional neural networks (CNN for short) have made great progress in face detection. They mostly take computation intensive networks as the backbone in order to obtain high precision, and they cannot get a good detection speed without the support of high-performance GPUs (Graphics Processing Units). This limits CNN-based face detection algorithms in real applications, especially in some speed dependent ones. To alleviate this problem, we propose a lightweight face detector in this paper, which takes a fast residual network as backbone. Our method can run fast even on cheap and ordinary GPUs. To guarantee its detection precision, multi-scale features and multi-context are fully exploited in efficient ways. Specifically, feature fusion is used to obtain semantic strongly multi-scale features firstly. Then multi-context including both local and global context is added to these multi-scale features without extra computational burden. The local context is added through a depthwise separable convolution based approach, and the global context by a simple global average pooling way. Experimental results show that our method can run at about 110 fps on VGA (Video Graphics Array)-resolution images, while still maintaining competitive precision on WIDER FACE and FDDB (Face Detection Data Set and Benchmark) datasets as compared with its state-of-the-art counterparts.

scholarly journals Metalearning approach for leukemia informative genes prioritization

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Vânia Rodrigues ◽  
Sérgio Deusdado
Keyword(s):  
High Performance ◽  
Information Gain ◽  
Pearson Correlation ◽  
Microarray Gene Expression Data ◽  
Microarray Gene Expression ◽  
The Public ◽  
Leukemia Diagnosis ◽  
Chi Squared ◽  
Logistic Regression Method ◽  
Single Attribute

AbstractThe discovery of diagnostic or prognostic biomarkers is fundamental to optimize therapeutics for patients. By enhancing the interpretability of the prediction model, this work is aimed to optimize Leukemia diagnosis while retaining a high-performance evaluation in the identification of informative genes. For this purpose, we used an optimal parameterization of Kernel Logistic Regression method on Leukemia microarray gene expression data classification, applying metalearners to select attributes, reducing the data dimensionality before passing it to the classifier. Pearson correlation and chi-squared statistic were the attribute evaluators applied on metalearners, having information gain as single-attribute evaluator. The implemented models relied on 10-fold cross-validation. The metalearners approach identified 12 common genes, with highest average merit of 0.999. The practical work was developed using the public datamining software WEKA.

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