Correlation between instrumental texture and colour quality attributes with sensory analysis of selected cheeses as affected by fat contents

This study evaluated several physical and sensory parameters of different types of cheese available in the Polish market. The measurements of textural properties were conducted in an Instron universal testing machine, while the colour properties of cheeses were measured using a Minolta chromameter. The chemical composition was determined by means of the near‐infrared spectroscopy (NIRs). Moreover, a trained sensory panel was invited to assess the cheese texture‐related properties. Generally, cheeses with reduced fat content were characterised by higher hardness, adhesiveness, cohesiveness and elasticity. Texture‐related parameters of cheese with canola oil were comparable to that of most of full‐fat cheeses. The correlation analysis between physical and sensory attributes related to cheese textural properties indicated the potential applications of TPA, shear and penetration tests (r = 0.766, r = 0.75 and r = 0.765, respectively) for the evaluation of sensory properties related to the hardness. Meanwhile, the elasticity of cheese obtained from sensory evaluation was strongly correlated with the elasticity determined from the shear test (r = 0.722) and moderately correlated with the elasticity from penetration test (r = 0.588), indicating a need to refine the method of penetration test. In addition, cheeses exhibited higher meltability during convection heating at 230 °C than microwave heating. The values of meltability for cheese with reduced fat content were lower than those of full‐fat cheese.     

Privacy-preserving iris authentication using fully homomorphic encryption

Multimedia Tools and Applications - Rapid advancement in technology has led to the use of biometric authentication in every field. In particular, from the past few years, iris recognition systems...     

A new deep convolutional neural network model for classifying breast cancer histopathological images and the hyperparameter optimisation of the proposed model

The Journal of Supercomputing - Deep learning algorithms have yielded remarkable results in medical diagnosis and image analysis, besides their contribution to improvements in a number of fields...     

Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.

Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.     

Benchmark simulation Model no 2 in Matlab-simulink: towards plant-wide WWTP control strategy evaluation.

In this paper, implementation of the Benchmark Simulation Model No 2 (BSM2) within Matlab-Simulink is presented. The BSM2 is developed for plant-wide WWTP control strategy evaluation on a long-term basis. It consists of a pre-treatment process, an activated sludge process and sludge treatment processes. Extended evaluation criteria are proposed for plant-wide control strategy assessment. Default open-loop and closed-loop strategies are also proposed to be used as references with which to compare other control strategies. Simulations indicate that the BM2 is an appropriate tool for plant-wide control strategy evaluation.     

WWTP dynamic disturbance modelling--an essential module for long-term benchmarking development.

Intensive use of the benchmark simulation model No. 1 (BSM1), a protocol for objective comparison of the effectiveness of control strategies in biological nitrogen removal activated sludge plants, has also revealed a number of limitations. Preliminary definitions of the long-term benchmark simulation model No. 1 (BSM1_LT) and the benchmark simulation model No. 2 (BSM2) have been made to extend BSM1 for evaluation of process monitoring methods and plant-wide control strategies, respectively. Influent-related disturbances for BSM1_LT/BSM2 are to be generated with a model, and this paper provides a general overview of the modelling methods used. Typical influent dynamic phenomena generated with the BSM1_LT/BSM2 influent disturbance model, including diurnal, weekend, seasonal and holiday effects, as well as rainfall, are illustrated with simulation results. As a result of the work described in this paper, a proposed influent model/file has been released to the benchmark developers for evaluation purposes. Pending this evaluation, a final BSM1_LT/BSM2 influent disturbance model definition is foreseen. Preliminary simulations with dynamic influent data generated by the influent disturbance model indicate that default BSM1 activated sludge plant control strategies will need extensions for BSM1_LT/BSM2 to efficiently handle 1 year of influent dynamics.