Organizational Control for Data Mining with Large Numbers of Agents

2013 ◽  
pp. 3-3
Author(s):  
Victor Lesser
Keyword(s):  
Data Mining ◽  
Organizational Control ◽  
Large Numbers

The Garment Fashionable Shape Prognosticating Based on Manufacture Database

2011 ◽  
Vol 55-57 ◽  
pp. 1091-1096
Author(s):  
Xiao Gang Wang ◽  
Xin Zhan Li ◽  
Yue Li
Keyword(s):  
Data Mining ◽  
Body Size ◽  
Female Body ◽  
Science Research ◽  
New Method ◽  
Mining Technology ◽  
Cad System ◽  
Large Numbers ◽  
Error Bar ◽  
Historical Database

Based on the research about outside shape of woman warm jacket more than twenty years, fashion variables that were representative and can describe the fashionable shape were discussed. Experiment was designed to achieve data of large numbers of female body. Body size variables were statistically analyzed to decide the module that was the basement for achieving data from historical photos. Fashionable characteristic diagrams of garment length, front chest width, shoulder length, collar height and their error bar charts were drawn for discussing the change of fashionable shape. The fashion trends in the future were also prognosticated scientifically. At the same time, a historical database was developed for manufacture and designing, which it is the basement for automatic pattern designing. This new method for fashion trend research was introduced by data mining technology, which it opens our minds for garment science research and offers a new database for improving garment CAD system.

scholarly journals WAVELET ANALYSIS OF PROTEIN MOTION

2012 ◽  
Vol 10 (04) ◽  
pp. 1250040 ◽  
Author(s):  
NOAH C. BENSON ◽  
VALERIE DAGGETT
Keyword(s):  
Data Mining ◽  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Wavelet Transforms ◽  
Time Course ◽  
Relevant Information ◽  
Structural Rearrangements ◽  
Large Numbers ◽  
Time Course Data ◽  
Dynamics Simulations

As high-throughput molecular dynamics simulations of proteins become more common and the databases housing the results become larger and more prevalent, more sophisticated methods to quickly and accurately mine large numbers of trajectories for relevant information will have to be developed. One such method, which is only recently gaining popularity in molecular biology, is the continuous wavelet transform, which is especially well-suited for time course data such as molecular dynamics simulations. We describe techniques for the calculation and analysis of wavelet transforms of molecular dynamics trajectories in detail and present examples of how these techniques can be useful in data mining. We demonstrate that wavelets are sensitive to structural rearrangements in proteins and that they can be used to quickly detect physically relevant events. Finally, as an example of the use of this approach, we show how wavelet data mining has led to a novel hypothesis related to the mechanism of the protein γδ resolvase.

Data-Driven Sizing Specification Utilizing Consumer Text Reviews

2017 ◽  
Vol 139 (11) ◽  
Author(s):  
Rushtin Chaklader ◽  
Matthew B. Parkinson
Keyword(s):  
Data Mining ◽  
Observational Studies ◽  
New Method ◽  
Preliminary Design ◽  
Specific Product ◽  
Consumer Reviews ◽  
Design Specifications ◽  
Product Features ◽  
Large Numbers ◽  
Automated Tool

The objective of this work is to introduce a new method for determining preliminary design specifications related to human-artifact interaction. This new method uses data mining of large numbers of consumer reviews. User opinion on specific product features can be time-consuming or expensive to obtain through traditional methods including surveys, experiments, and observational studies. Data mining review text of already released products may be a potentially less time consuming and costly method. Previously established methods of determining design for human variability information from consumer reviews, such as the frequency and accuracy summation (FAS) number and subsequent manual analysis, are explored. The weighted phrase rating (WPR), a new metric which can be an automated tool to quickly analyze consumer reviews, is also introduced. It does not require manual parsing of the reviews, which extends its applicability to larger review pools. This new method is shown to quickly and economically provide information useful to the establishment of design specifications.

scholarly journals Review of medical diagnostics via data mining techniques

2021 ◽  
pp. 2401-2424
Author(s):  
Suhad Faisal ◽  
Sarah Sameer ◽  
Iyden Kamil Mohammed ◽  
Mustafa S Abd
Keyword(s):  
Public Health ◽  
Data Mining ◽  
Decision Support ◽  
Safety Monitoring ◽  
Clinical Decision ◽  
Medical Diagnostics ◽  
Electronic Information ◽  
Large Numbers ◽  
Health Studies ◽  
Classification And Regression

Data mining is one of the most popular analysis methods in medical research. It involves finding patterns and correlations in previously unknown datasets. Data mining encompasses various areas of biomedical research, including data collection, clinical decision support, illness or safety monitoring, public health and inquiry research. Health analytics frequently uses computational methods for data mining, such as clustering, classification, and regression. Studies of large numbers of diverse heterogeneous documents, including biological and electronic information, provided medical and health studies.

Patterns Relevant to the Temporal Data-Context of an Alarm of Interest

2010 ◽  
pp. 18-39 ◽  
Author(s):  
Savo Kordic ◽  
Chiou Peng Lam ◽  
Jitian Xiao ◽  
Huaizhong Li
Keyword(s):  
Data Mining ◽  
Main Idea ◽  
High Volume ◽  
Chemical Plants ◽  
Data Mining Technique ◽  
Time Intervals ◽  
Alarm Systems ◽  
Large Numbers ◽  
Petroleum Refineries ◽  
Active Exploration

The productivity of chemical plants and petroleum refineries depends on the performance of alarm systems. Alarm history collected from distributed control systems (DCS) provides useful information about past plant alarm system performance. However, the discovery of patterns and relationships from such data can be very difficult and costly. Due to various factors such as a high volume of alarm data (especially during plant upsets), huge amounts of nuisance alarms, and very large numbers of individual alarm tags, manual identification and analysis of alarm logs is usually a labor-intensive and time-consuming task. This chapter describes a data mining approach for analyzing alarm logs in a chemical plant. The main idea of the approach is to investigate dependencies between alarms effectively by considering the temporal context and time intervals between different alarm types, and then employing a data mining technique capable of discovering patterns associated with these time intervals. A prototype has been implemented to allow an active exploration of the alarm grouping data space relevant to the tags of interest.

scholarly journals IMPLEMENTASI MODEL CRISP-DM UNTUK MENENTUKAN SALES PIPELINE PADA PT X

2017 ◽  
Vol 6 (1) ◽  
Author(s):  
Dina Feblian ◽  
Dadan Umar Daihani
Keyword(s):  
Data Mining ◽  
Joint Venture ◽  
Customer Segmentation ◽  
Data Preparation ◽  
Sources Of Information ◽  
Industry Standard ◽  
General Insurance ◽  
Large Numbers ◽  
Business Data ◽  
A Company

<p>PT X is a joint venture subsidiary of a bank in Indonesia, which is a company, engaged in<br />general insurance business. PT X is required to increase its share of the parent company by the<br />shareholders in developing its business potential. In developing the potential of the business, companies<br />need enough information to be analyzed further. Sources of information that can be used is the business<br />data of the company, both of PT X as a subsidiary and its holding company. By utilizing business data<br />in large numbers, the company will find a variety of information needed. For the business data<br />processing required a technique of data mining. In a study conducted, the implementation of the model<br />refers to the six stages of Cross-Industry Standard Process for Data Mining or commonly known by the<br />acronym CRISP-DM. In doing data mining, the six phases of the CRISP-DM is business understanding,<br />understanding the data, the data preparation, modeling, evaluation, and deployment. At this stage of<br />deployment, the report will be made by the customer segmentation by region. The expected result is the<br />information required in the form of a new customer pipeline.</p>

scholarly journals Application of medical equipment procurement data mining using the Apriori method

SinkrOn ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 213-220
Author(s):  
Phindika Phindika ◽  
Yopi Handrianto ◽  
Sulaeman Hadi Sukmana
Keyword(s):  
Data Mining ◽  
Medical Devices ◽  
Policy Process ◽  
Medical Equipment ◽  
A Algorithm ◽  
Hospital Policy ◽  
Large Numbers ◽  
Quality Of Health Services ◽  
Processing Algorithms

The procurement of an item in an agency is an activity that is commonly carried out, including in a hospital, particularly the procurement of medical equipment. The procurement of medical equipment at Pengayoman Cipinang Hospital, Jakarta currently still uses the conventional method where the process is still using the manual method, namely by relying on disposable physical items as the main resource and seems to use many procedures that require a long working time. The influx of medical equipment in very large numbers can cause many risks, such as the amount of money it costs to store medical devices and also being vulnerable to the risk of theft. The conditions mentioned above can affect the quality of health services provided by the hospital to patients who should be well preserved. One of the data processing algorithms that is often used in the data mining process is the A algorithm. The benefit is to find trends between one item and another, where more and more medical equipment appears to be used as a reference in the hospital policy process in ensuring the availability of this medical equipment when needed so that the procurement process can always be fulfilled. Based on the results of the research conducted, it was found that the medical equipment that had the most demand was Surgical Ear Loop Masks 3 (58.33%), Non-Sterile Gloves Size M (58.33%), and Surgical Tie-On 3 PLY Masks (100%)

scholarly journals Data Mining the Internet Archive Collection

2014 ◽  
Author(s):  
Caleb McDaniel
Keyword(s):  
Data Mining ◽  
The Internet ◽  
Specific Information ◽  
Historical Sources ◽  
Internet Archive ◽  
Large Numbers ◽  
Bibliographic Data

The collections of the Internet Archive include many digitized historical sources. Many contain rich bibliographic data in a format called MARC. In this lesson, you'll learn how to use Python to automate the downloading of large numbers of MARC files from the Internet Archive and the parsing of MARC records for specific information such as authors, places of publication, and dates. The lesson can be applied more generally to other Internet Archive files and to MARC records found elsewhere.

Cytoplasmic Granules in Lymphocytes from Rats Dosed with SK&F 14336-D

1971 ◽  
Vol 29 ◽  
pp. 556-557
Author(s):  
T. G. Merrill ◽  
B. J. Payne ◽  
A. J. Tousimis
Keyword(s):  
Lipid Storage ◽  
Pokeweed Mitogen ◽  
Electron Microscopic ◽  
Cytoplasmic Granules ◽  
Storage Diseases ◽  
Tay Sachs Disease ◽  
Large Numbers ◽  
Microscopic Studies ◽  
Neurovisceral Lipidosis

Rats given SK&F 14336-D (9-[3-Dimethylamino propyl]-2-chloroacridane), a tranquilizing drug, developed an increased number of vacuolated lymphocytes as observed by light microscopy. Vacuoles in peripheral blood of rats and humans apparently are rare and are not usually reported in differential counts. Transforming agents such as phytohemagglutinin and pokeweed mitogen induce similar vacuoles in in vitro cultures of lymphocytes. These vacuoles have also been reported in some of the lipid-storage diseases of humans such as amaurotic familial idiocy, familial neurovisceral lipidosis, lipomucopolysaccharidosis and sphingomyelinosis. Electron microscopic studies of Tay-Sachs' disease and of chloroquine treated swine have demonstrated large numbers of “membranous cytoplasmic granules” in the cytoplasm of neurons, in addition to lymphocytes. The present study was undertaken with the purpose of characterizing the membranous inclusions and developing an experimental animal model which may be used for the study of lipid storage diseases.

Prolonged Fixation Studies For Spaceflight

1973 ◽  
Vol 31 ◽  
pp. 332-333
Author(s):  
Robert Corbett ◽  
Delbert E. Philpott ◽  
Sam Black
Keyword(s):  
High Pressure ◽  
Living Systems ◽  
Prolonged Storage ◽  
Time Intervals ◽  
Early Signs ◽  
Large Numbers

Observation of subtle or early signs of change in spaceflight induced alterations on living systems require precise methods of sampling. In-flight analysis would be preferable but constraints of time, equipment, personnel and cost dictate the necessity for prolonged storage before retrieval. Because of this, various tissues have been stored in fixatives and combinations of fixatives and observed at various time intervals. High pressure and the effect of buffer alone have also been tried.Of the various tissues embedded, muscle, cartilage and liver, liver has been the most extensively studied because it contains large numbers of organelles common to all tissues (Fig. 1).

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