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EN
This paper presents practical capabilities of a system for ceramic mould quality forecasting implemented in an industrial plant (foundry). The main assumption of the developed solution is the possibility of eliminating a faulty mould from a production line just before the casting operation. It allows relative savings to be achieved, and faulty moulds, and thus faulty castings occurrence in the production cycle to be minimized. The numerical computing module (the DEFFEM 3D package), based on the smoothed particle hydrodynamics (SPH) is one of key solutions of the system implemented. Due to very long computing times, the developed numerical module cannot be effectively used to carry out multi-variant simulations of mould filling and solidification of castings. To utilize the benefits from application of the CUDA architecture to improve the computing effectiveness, the most time consuming procedure of looking for neighbours was parallelized (cell-linked list method). The study is complemented by examples of results of performance tests and their analysis.
2
Content available Image classification for jpeg compression
EN
We analyse storage problems of digital images in accordance with image quality and image compression efficiency. Storage problems are relevant for Cloud storage and file hosting services, online file storage providers, social networks, etc. In this paper, an approach is proposed to process a group of images with a JPEG algorithm that all the processed images satisfy the minimum threshold of quality with the automatic selection of the quality factor (QF). The experimental investigation reveals advantages of the compression efficiency of the proposed approach over the traditional JPEG algorithm. The proposed approach enables saving storage spaces while maintaining the desirable image quality.
PL
Celem pracy była ocena możliwości przewidywania barwy mięsa wołowego po obróbce cieplnej w oparciu o komputerową analizę obrazu mięsa surowego. Jako model wykorzystano łopatkę wołową, którą poddano obróbce cieplnej w piecu konwekcyjno-parowym. Dokonano pomiaru składowych barwy w systemie RGB, przy wykorzystaniu systemu komputerowej analizy obrazu. Stwierdzono, że składowe barwy R, G oraz B łopatki wołowej nie korelują z barwą mięsa po obróbce cieplnej, ale korelują z barwą jego zbrązowionej powierzchni. Możliwe jest zatem przewidywanie barwy zbrą-zowionej powierzchni mięsa łopatki wołowej po obróbce cieplnej w piecu konwekcyjno-parowym.
EN
The aim of the presented research was to assess the possibilities of colour of beef after thermal treatment prediction, on the basis of computer image analysis of beef before thermal treatment. The applied model was beef blade and thermal treatment was conducted in steam-convection oven. The measure-ment of RGB compon ents of colour was conducted, using the computer image analysis system. It was observed, that R, G and B components of colour of beef blade were not correlated with components of colour of meat after thermal treatment, but were correlated with components of colour of browned surface of meat. It was concluded, that prediction of colour of browned surface of meat after thermal treatment conducted in steam-convection oven is possible.
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