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Automatic Three Dimensional Design for Tube-Shell Heat Exchanger and Software Development

王坤, 于庆波, 李玖重, 秦勤
Dynamical Systems and Control (DSC) , 2012, DOI: 10.12677/dsc.2012.11001
利用Visual BasicSolid Edge进行二次开发,实现了管壳式换热器三维自动化设计,并编写了相应的设计软件。软件采用模块化设计思想,主要分为工艺计算和三维图形输出两部分。工艺计算可实现管壳式换热器的热力计算和压降计算;三维图形是基于ActiveX Automation技术先采用参数化建模生成独立零件再由自底向上装配的方法生成。软件界面友好,人机交互能力强,能快速生成三维模型,有效提高了设计速度和设计质量。
Using Visual Basic to redevelop the Solid Edge, a software is developed to implement automatic three di- mensional drawing of tube-shell heat exchangers. According to the concept of modularization the software is divided into two parts: technical calculation and three dimensional drawing. The thermal calculations and the pressure drop calculations can be finished by the software; Based on the ActiveX Automation technology, using parametric modeling to generate the independent parts and then to generate three-dimensional drawing is output with bottom-up assembly method. At the same time, this software has friendly interfaces and a human-computer interaction environment. It will be benefit to the development of the three dimensional modeling, which can improve the design speed and design qual- ity.
An Introduction to Using Software Tools for Automatic Differentiation  [PDF]
Uwe Naumann,Andrea Walther
Computer Science , 2003,
Abstract: We give a gentle introduction to using various software tools for automatic differentiation (AD). Ready-to-use examples are discussed, and links to further information are presented. Our target audience includes all those who are looking for a straightforward way to get started using the available AD technology. The document is dynamic in the sense that its content will be updated as the AD software evolves.
Document Search Enginee Based on Automatic Clustering
Entin Martiana,Nur Rosyid,Usmaida Agusetia
Abstract: Web mining in searching based on keywords by automatic clustering is a document searching method by classifying documents based on its keyword. Following is the clustering by centroid linkage hierarchical method (CLHM) to the number of keywords from each document. In clustering, initialization is commonly required for the number of cluster to be formed first, however, in some clustering cases, the user cannot determine how many clusters can be built. Therefore, on this paper, the Valley tracing method is applied as a constraint which identifies variants movement from each cluster formation step and also analyzes its pattern to form automatic clustering. Document data used are from text mining process on documents. Based on 424 documents, this research shows that clustering method using CLHM algorithm can be generally used to classifying documents with exact number automatically.
Automatic Shell Detection in CGPS Data  [PDF]
Sergey Mashchenko,Nicole St-Louis
Physics , 2000,
Abstract: A numerical code aiming at the automatic detection of spherical expanding HI shells in radio data-cubes is presented. The following five shell parameters are allowed to vary within a specified range: angular radius, expansion velocity and three center coordinates (galactic coordinates l and b, and systemic radial velocity V). We discuss several factors which can reduce the sensitivity of the shell detection: the presence of noise (both instrumental and "structural"), the fragmentation and asphericity of the shell and the inhomogeneity of the background and/or foreground emission. The code is tested on four objects: two HII regions and two early B stars. We use HI data from the Canadian Galactic Plane Survey. In all four cases the evidence for an expanding HI shell is found.
Study for Document Interpretation and Automatic Abstracting Based on Analogic Sorting

TAN Wen-Rong,YANG Xian-Ze,TAN jin,

计算机科学 , 2006,
Abstract: Document interpretation and its relative processing technology are hotspots in the research domain of natural language understanding. In this paper, after analyzing the ideas and diffieults of natural language, we propose an analogie sorting alogrithem for document interpretation. We discuss the ways of chinese word segmentaion and its application ,which is the most difficult problem in chinese document interprtaion. Finally we develop a method of automatic abstracting,the elementary tests show that it has a high efficiency.
Induction of Word and Phrase Alignments for Automatic Document Summarization  [PDF]
Hal Daumé III,Daniel Marcu
Computer Science , 2009,
Abstract: Current research in automatic single document summarization is dominated by two effective, yet naive approaches: summarization by sentence extraction, and headline generation via bag-of-words models. While successful in some tasks, neither of these models is able to adequately capture the large set of linguistic devices utilized by humans when they produce summaries. One possible explanation for the widespread use of these models is that good techniques have been developed to extract appropriate training data for them from existing document/abstract and document/headline corpora. We believe that future progress in automatic summarization will be driven both by the development of more sophisticated, linguistically informed models, as well as a more effective leveraging of document/abstract corpora. In order to open the doors to simultaneously achieving both of these goals, we have developed techniques for automatically producing word-to-word and phrase-to-phrase alignments between documents and their human-written abstracts. These alignments make explicit the correspondences that exist in such document/abstract pairs, and create a potentially rich data source from which complex summarization algorithms may learn. This paper describes experiments we have carried out to analyze the ability of humans to perform such alignments, and based on these analyses, we describe experiments for creating them automatically. Our model for the alignment task is based on an extension of the standard hidden Markov model, and learns to create alignments in a completely unsupervised fashion. We describe our model in detail and present experimental results that show that our model is able to learn to reliably identify word- and phrase-level alignments in a corpus of pairs.
On Automatic Indexing of Document

Su Xinning Zou Xiaoming,

现代图书情报技术 , 2000,
Abstract: The center of automatic indexing of document ought to change from cutting Chinese keyword to analysis indexing in our country. For this reason, the authors introduce their results of automatic indexing, including the indexing source, defining and using words weights, designing dictionary database, the algorithm of automatic indexing and retrieval techniques.
Classification of automatic software build methods  [PDF]
Marcin Kawalerowicz
Computer Science , 2013,
Abstract: The process of creating working software from source code and other components (like libraries, database files, etc.) is called "software build". Apart from linking and compiling, it can include other steps like automated testing, static code analysis, documentation generation, deployment and other. All that steps can be automated using a build description of some sort (e.g. script). This article classifies the automatic software build processes beginning at build script and reaching the various types of continuous integration.
Finding skewness and deskewing scanned document  [PDF]
Sunita Parashar,Sharuti Sogi
International Journal of Computer Technology and Applications , 2012,
Abstract: Document image processing has become anincreasingly important technology in theautomation of office documentation tasks.Automatic document scanners such as text readersand OCR systems are an essential component ofsystems capable of those tasks. One of theproblems in this field is that the document to beread is not always placed correctly on a flatbedscanner. This means that the document may beskewed on the scanner bed, resulting in a skewedimage. Consequently, detecting the skew of adocument image and correcting it are importantissues in realizing a practical document reader
Automatic Arabic Document Classification Based on the HRWiTD Algorithm  [PDF]
Ehsan Othman, Ayoub Al-Hamadi
Journal of Software Engineering and Applications (JSEA) , 2018, DOI: 10.4236/jsea.2018.114011
Abstract: The documents contain a large amount of valuable knowledge on various subjects and, more recently, documents on the Internet are available from various sources. Therefore, automatic, rapid and accurate classification of these documents with less human interaction has become necessary. In this paper, we introduce a new algorithm called the highest repetition of words in a text document (HRWiTD) to classify the automatic Arabic text. The corpus is divided into a train set and a test set to be applied to proposed classification technique. The train set is analyzed for learning and the learning data is stored in the Learning Dataset file. The category that contains the highest repetition for each word is assigned as a category for the word in Learning Dataset file. This file includes non-duplicate words with the value of higher repetition and categories and they get from all texts in the train set. For each text in the test set, the category of words is assigned to a specific category by using Learning Dataset file. The category that contains the largest number of words is assigned as the predicted category of the text. To evaluate the classification accuracy of the HRWiTD algorithm, the confusion matrix method is used. The HRWiTD algorithm has been applied to convergent samples from six categories of Arabic news at SPA (Saudi Press Agency). As a result, the accuracy of the HRWiTD algorithm is 86.84%. In addition, we used the same corpus with the most popular machine learning algorithms which are C5.0, KNN, SVM, NB and C4.5, and their results of classification accuracy are 52.86%, 52.38%, 51.90%, 51.90% and 30%, respectively. Thus, the HRWiTD algorithm gives better classification accuracy compared to the most popular machine learning algorithms on the selected domain.
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