Journal of Print and Media Technology Research

A neural network to predict the spectral reflectance of prints

2024-11-12T09:43:47+00:00

The reconstruction of spectral reflectance from RGB triplets created by digital cameras is a topic of great interest. Different approaches dealing with this topic have been published. In the recent years, most approaches utilize neural networks. These approaches mainly differ in the chosen network architecture, the way of obtaining the dataset and the used hardware. While the most approaches aim for generalized applicability on a wide range of spectra, this paper aims for applicability on a limited set of spectra given by a typical use case of the printing industry. In this paper a neural network was trained to predict the spectral reflectance of prints. Therefore, 10 800 color patches were printed, measured by a spectrophotometer and captured by an RGB camera under different light sources generated with a DLP projector. The performance of the trained network was tested by determining the CIEDE2000 color difference as well as the mean squared error between the predicted and the measured spectral reflectance. The dataset was systematically reduced to examine how the number of color patches and light sources used for training influences the performance of a network. This paper shows that a network performed best when confronted with prints printed on the same substrate using the same color management settings as the dataset used for training. Training a network with multiple datasets on different substrates increased the generalization of a network, but decreased the performance compared to a network trained with a single combination of substrate and color management settings. Reducing the number of color patches as well as reducing the number of light sources influenced the performance of a network negatively, but still leads to decent results.

Fostering organisational resilience in print and media industry in Sri Lanka: The role of dynamic capability and strategic orientation

2024-11-13T09:49:00+00:00

Organisational resilience has gained significant prominence as a result of unprecedented shocks in the corporate marketplace,where print and media enterprises are particularly vulnerable. Therefore, print and media enterprises are required to develop organisational resilience strategically, focusing on fostering business resilience. In this context,the theory of dynamic capability offers a framework for print and media enterprise leaders to navigate capabilities toward potential opportunities. This research provides an extensive framework to examine the relationship between organisational resilience and dynamic capability. Primary data were gathered from 300 print and media Enterprise leaders in Sri Lanka using a structured questionnaire. The data was analysed using SPSS and AMOS. The findings indicate that a well-combined set of dynamic capabilities, centered around seizing new opportunities, has a significant effect on improving company resilience in the PME sector. Moreover, strategic orientation plays a significant role as a mediator between dynamic capability and organisational resilience. A key finding of this study further reveals that company characteristics and market conditions also have a considerable effect on fostering organisational resilience.The study suggests that older print and media enterprises must adopt a more strategic orientation and reforms must be implemented to enhance company resilience in the print and media industry in Sri Lanka.

Modeling the process of ink transfer from the gravure printing plate to the printing substrate

2024-11-13T09:52:28+00:00

The article presents a mathematical model of imprint formation in gravure printing on cardboard substrates. The focus is on ensuring imprint quality by balancing interactions between the structural subsystems of the printing press, specifically the plate cylinder, ink, printing system, and substrate. Using mathematical models, the behavior of the printing substrate and printing plate elements system is investigated by determining the stress–strain state of the contacting elements during imprint formation. The study describes the ink transfer process from the gravure printing plate to the substrate, considering factors such as substrate weight and structure, technical characteristics of the printing press, and its structural subsystems. The method for calculating printing pressure is also examined. At higher printing speeds and pressures, cylinder coatings can be damaged, leading to overheating and cracking,which necessitates cylinder cooling. Increased press width requires greater pressure to achieve the desired contact area, causing cylinder deflection and uneven pressure distribution, affecting image quality and color matching.Morphological analysis confirmed the significant influence of the printing and inking systems of web-fed gravure presses on pressure distribution in the printing zone. The stress–strain state of objects in direct contact is a key factor in imprint quality. Therefore, studying the micromechanics of contacting surfaces during printing is crucial for high-quality images. Mathematical modeling allows calculation and control of the load in the contact zone between the substrate and ink-filled printing elements, ensuring the quality of gravure imprints on various materials.