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1

A New Approach to Evaluate Fabric Hand Based on Three-Dimensional Drape Model

Hussain Azmat, Zhong Yueqi, Naveed Tayyab, Yu Zhicai, Xi Zhang, Ge Wu

Autex Research Journal

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2020

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Vol. 20, no. 2

155--167

EN

Fabric quality and performance is assessed subjectively by the customer using an important and complex phenomenon of fabric hand. Objectively, it is evaluated with complicated and expensive instruments, such as Kawabata Evaluation System for Fabrics (KES-F) and Fabric Assurance with Simple Testing (FAST). The present research explores a non-touch objective approach, i.e., three-dimensional (3D) drape model to estimate fabric hand. Fabric hand prediction was testified on different commercial fabrics spanning a wide range of areal weight, thickness, yarn count, and fabric density. Fabric objective ranks based on drape indicators using principal component analysis (PCA) were compared with subjective ranks of fabric hand. Additionally, fabric drape is evaluated three dimensionally and a new drape indicator drape height (DH) is proposed. The cosine similarity results have proved fabric drape as an objective alternate to fabric hand.

2

The evaluation of text string matching algorithms as an aid to image search

Ochelska-Mierzejewska J.

Journal of Applied Computer Science

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2018

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Vol. 26, nr 1

33--62

EN

The main goal of this paper is to analyse intelligent text string matching methods (like fuzzy sets and relations) and evaluate their usefulness for image search. The present study examines the ability of different algorithms to handle multi-word and multi-sentence queries. Eight different similarity measures (N-gram, Levenshtein distance, Jaro coefficient, Dice coefficient, Overlap coefficient, Euclidean distance, Cosine similarity and Jaccard similarity) are employed to analyse the algorithms in terms of time complexity and accuracy of results. The outcomes are used to develop a hierarchy of methods, illustrating their usefulness to image search. The search response time increases significantly in the case of data sets containing several thousand images. The findings indicate that the analysed algorithms do not fulfil the response-time requirements of professional applications. Due to its limitations, the proposed system should be considered only as an illustration of a novel solution with further development perspectives. The use of Polish as the language of experiments affects the accuracy of measures. This limitation seems to be easy to overcome in the case of languages with simpler grammar rules (e.g. English).

3

The versatile hardware accelerator framework for sparse vector calculations

Karwatowski R., Wiatr K.

Measurement Automation Monitoring

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2015

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Vol. 61, No. 7

327--329

EN

In this paper, we present the advantage of the ability of FPGAs to perform various computationally complex calculations using deep pipelining and parallelism. We propose an architecture that consists of many small stream processing blocks. The designed framework maintains proper data movement and synchronization. The architecture can be easily adapted to be implemented in FPGA devices of a various size and cost - from small SoC devices to high-end PCIe accelerator cards. It is capable to perform a selected operation on a sparse data that are loaded as the stream of vectors. As an example application, we have implemented the cosine similarity measure for the text similarity calculations that uses the TF-IDF weighting scheme. The presented example application calculates the similarity of texts from the set of input documents to documents from the large database. The scheme is used to find the most similar documents. The proposed design can decrease the service time of search queries in computer centers while reducing power consumption.

4

Using Non-Zero Dimensions for the Cosine and Tanimoto Similarity Search Among Real Valued Vectors

Kryszkiewicz M.

Fundamenta Informaticae

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2013

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Vol. 127, nr 1-4

307--323

EN

The cosine and Tanimoto similarity measures are typically applied in the area of chemical informatics, bio-informatics, information retrieval, text and web mining as well as in very large databases for searching sufficiently similar vectors. In the case of large sparse high dimensional data sets such as text or Web data sets, one typically applies inverted indices for identification of candidates for sufficiently similar vectors to a given vector. In this article, we offer new theoretical results on how the knowledge about non-zero dimensions of real valued vectors can be used to reduce the number of candidates for vectors sufficiently cosine and Tanimoto similar to a given one. We illustrate and discuss the usefulness of our findings on a sample collection of documents represented by a set of a few thousand real valued vectors with more than ten thousand dimensions.