This paper suggests a systematic orderly process based approach to stating software quality objec tives and knowing if and when they have been achieved We suggest that quality in software is a complex multifaceted array of characteristics and that it is important to establish speci c objectives along various software quality dimensions as requirements for software quality assurance determinatio...

Many software developing companies use Quality Gates to mitigate quality problems and to steer projects in time. The necessary structures, activities, methods, roles and documents can be encapsulated in a Quality Gate reference process, which then can be tailored to fulfill the needs of different projects. Each company has to implement a Quality Gate reference process individually because quali...

Traditional color spaces have been widely used in a variety of applications including digital color imaging, color image quality, and color management. These spaces, however, were designed for the domain of color stimuli typically encountered with reflecting objects and image displays of such objects. This means the domain of stimuli with luminance levels from slightly above zero to that of a p...

A new technique for finding the root cause for problems in a manufacturing process is presented. The new technique is designated to continuously and automatically detect quality drifts on various manufacturing processes and then induce the common root cause. The proposed technique consists of a fast, incremental algorithm that can process extremely high dimensional data and handle more than one...

Organizations are facing the challenge of transferring knowledge from experienced to novice employees and are seeking for solutions that avoid the loss of knowledge with retiring experts. A possible way for overcoming this challenge is having employees develop learning materials for their novice colleagues. Based on insights from both, education and collaboration research, designing structured ...

Resources for data management, discovery and (re)use are numerous and diverse, and more specifically we need data resources that enable the FAIR principles1 of Findability, Accessibility, Interoperability and Reusability of data.