Advances in Computer Recognition, Image Processing and Communications, Selected Papers from CORES 2021 and IP&C 2021

As almost all human activities have been moved online due to the pandemic, novel robust and efficient approaches and further research have been in higher demand in the field of computer science and telecommunication. Therefore, this (reprint) book contains 13 high-quality papers presenting advancements in theoretical and practical aspects of computer recognition, pattern recognition, image processing and machine learning (shallow and deep), including, in particular, novel implementations of these techniques in the areas of modern telecommunications and cybersecurity

ULTRA CLOSE-RANGE DIGITAL PHOTOGRAMMETRY AS A TOOL TO PRESERVE, STUDY, AND SHARE SKELETAL REMAINS

Skeletal collections around the world hold valuable and intriguing knowledge about humanity. Their potential value could be fully exploited by overcoming current limitations in documenting and sharing them. Virtual anthropology provides effective ways to study and value skeletal collections using three-dimensional (3D) data, e.g. allowing powerful comparative and evolutionary studies, along with specimen preservation and dissemination. CT- and laser scanning are the most used techniques for three-dimensional reconstruction. However, they are resource-intensive and, therefore, difficult to be applied to large samples or skeletal collections. Ultra close-range digital photogrammetry (UCR-DP) enables photorealistic 3D reconstructions from simple photographs of the specimen. However, it is the least used method in skeletal anthropology and the lack of appropriate protocols often limit the quality of its outcomes. This Ph.D. thesis explored UCR-DP application in skeletal anthropology. The state-of-the-art of this technique was studied, and a new approach based on cloud computing was proposed and validated against current gold standards. This approach relies on the processing capabilities of remote servers and a free-for-academic use software environment; it proved to produce measurements equivalent to those of osteometry and, in many cases, they were more precise than those of CT-scanning. Cloud-based UCR-DP allowed the processing of multiple 3D models at once, leading to a low-cost, quick, and effective 3D production. The technique was successfully used to digitally preserve an initial sample of 534 crania from the skeletal collections of the Museo Sardo di Antropologia ed Etnografia (MuSAE, Università degli Studi di Cagliari). Best practices in using the technique for skeletal collection dissemination were studied and several applications were developed including MuSAE online virtual tours, virtual physical anthropology labs and distance learning, durable online dissemination, and values-led participatorily designed interactive and immersive exhibitions at the MuSAE. The sample will be used in a future population study of Sardinian skeletal characteristics from the Neolithic to modern times. In conclusion, cloud-based UCR-DP offers many significant advantages over other 3D scanning techniques: greater versatility in terms of application range and technical implementation, scalability, photorealistic restitution, reduced requirements relating to hardware, labour, time, and cost, and is, therefore, the best choice to document and value effectively large skeletal samples and collections

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse