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.

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.

Selective Sampling and Orientation of Non-Homogeneous Tissues

1968 ◽  
Vol 26 ◽  
pp. 98-99
Author(s):  
C. C. Clawson ◽  
L. W. Anderson ◽  
R. A. Good
Keyword(s):  
Electron Microscopy ◽  
Electron Microscope ◽  
Light Microscopy ◽  
Random Sampling ◽  
New Method ◽  
Microscope Examination ◽  
Small Areas ◽  
Selective Sampling ◽  
Large Numbers ◽  
Specific Orientation

Investigations which require electron microscope examination of a few specific areas of non-homogeneous tissues make random sampling of small blocks an inefficient and unrewarding procedure. Therefore, several investigators have devised methods which allow obtaining sample blocks for electron microscopy from region of tissue previously identified by light microscopy of present here techniques which make possible: 1) sampling tissue for electron microscopy from selected areas previously identified by light microscopy of relatively large pieces of tissue; 2) dehydration and embedding large numbers of individually identified blocks while keeping each one separate; 3) a new method of maintaining specific orientation of blocks during embedding; 4) special light microscopic staining or fluorescent procedures and electron microscopy on immediately adjacent small areas of tissue.

Advanced Statistical Tools for Improving Yield and Reliability

1999 ◽  
Author(s):  
Richard C. Kittler
Keyword(s):  
Data Mining ◽  
Analysis Data ◽  
Neural Nets ◽  
Future Trends ◽  
Statistical Tools ◽  
Mining Technology ◽  
Explanatory Variables ◽  
Data Coverage ◽  
Statistical Approaches ◽  
Adequate Data

Abstract Analysis of manufacturing data as a tool for failure analysts often meets with roadblocks due to the complex non-linear behaviors of the relationships between failure rates and explanatory variables drawn from process history. The current work describes how the use of a comprehensive engineering database and data mining technology over-comes some of these difficulties and enables new classes of problems to be solved. The characteristics of the database design necessary for adequate data coverage and unit traceability are discussed. Data mining technology is explained and contrasted with traditional statistical approaches as well as those of expert systems, neural nets, and signature analysis. Data mining is applied to a number of common problem scenarios. Finally, future trends in data mining technology relevant to failure analysis are discussed.

Framework and performance analysis of college English testing system based on data mining technology

2021 ◽  
pp. 1-11
Author(s):  
Liu Narengerile ◽  
Li Di ◽  
Keyword(s):  
Data Mining ◽  
Test System ◽  
Test Time ◽  
Testing System ◽  
Test Results ◽  
System Software ◽  
Examination System ◽  
Mining Technology ◽  
College English ◽  
And Performance

At present, the college English testing system has become an indispensable system in many universities. However, the English test system is not highly humanized due to problems such as unreasonable framework structure. This paper combines data mining technology to build a college English test framework. The college English test system software based on data mining mainly realizes the computer program to automatically generate test papers, set the test time to automatically judge the test takers’ test results, and give out results on the spot. The test takers log in to complete the test through the test system software. The examination system software solves the functions of printing test papers, arranging invigilation classrooms, invigilating teachers, invigilating process, collecting test papers, scoring and analyzing test papers in traditional examinations. Finally, this paper analyzes the performance of this paper through experimental research. The research results show that the system constructed in this paper has certain practical effects.

scholarly journals Mechanical equipment fault detection applying data mining technology

2020 ◽  
Vol 1684 ◽  
pp. 012024
Author(s):  
Yiqun Liu ◽  
Xiaogang Wang ◽  
Xiaoyuan Gong ◽  
Hua Mu
Keyword(s):  
Data Mining ◽  
Fault Detection ◽  
Mechanical Equipment ◽  
Mining Technology
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