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The ways our cultural heritage reserve is preserved and disseminated to the public have changed significantly, with the use of immersive technologies, such as virtual reality environments, and serious games. Nowadays, these technologies are also exploited for developing interactive informative applications, to support historical education and enhance museum visits, physical or virtual, especially to younger generations. The field of edutainment, educational entertainment, has been rapidly developing during the last 10 or 15 years. The main goal of this research is to develop an educational 3D puzzle-like serious game which can operate within a virtual reality environment while aiming towards the dissemination of cultural heritage content to the younger public, i.e., students, children etc., through a pleasant gamification process. The cultural heritage objects used are an ancient Greek temple and a statue of the Roman era, whose high-resolution fully textured 3D models were available from previous projects. The game application was developed in Unity game engine with suitable coding to enable the smooth execution of the 3D puzzle solution. The application verified that it is more interesting to learn about cultural assets through a game than in the conventional ways, and even more when it is implemented within a Virtual Reality environment, where the contact with the assets appears to be more direct and realistic. The same application can also be utilized in different educational areas and can be expanded by the inclusion of other digital assets.

The on-demand content enrichment of an exhibition center visit is an active applied research domain. This work focuses on the exploitation of mobile devices as an efficient medium to deliver information related to an exhibit or an area within the exhibition center by utilizing machine learning approaches. We present YPOPSEI, an integrated system that formulates the information retrieval task as an image recognition mechanism, enabling visitors to simply capture an entity of interest in order to acquire information similar to a tour-guidance experience via their personal mobile devices. This scheme not only minimizes the additional infrastructure requirements, but additionally enhances the versatility in cases of exhibits topology alterations while still providing high accuracy in terms of image content recognition. Two hybrid approaches are developed that set Convolutional Neural Networks (CNNs) and Bags of VisualWords (BOVWs) to operate in a synergistic and cooperative manner. They are evaluated under real-world conditions on a client-server Web architecture system that experimentally operates within the premises of the Folklore Museum of Xanthi, Greece.

The 3D digitisation of small artefacts is a very complicated procedure because of their complex morphological feature structures, concavities, rich decorations, high frequency of colour changes in texture, increased accuracy requirements etc. Image-based methods present a low cost, fast and effective alternative because laser scanning does not meet the accuracy requirements in general. A shallow Depth of Field (DoF) affects the image-based 3D reconstruction and especially the point matching procedure. This is visible not only in the total number of corresponding points but also in the resolution of the produced 3D model. The extension of the DoF is a very important task that should be incorporated in the data collection to attain a better quality of the image set and a better 3D model. An extension of the DoF can be achieved with many methods and especially with the use of the focus stacking technique. In this paper, the focus stacking technique was tested in a real-world experiment to digitise a museum artefact in 3D. The experiment conditions include the use of a full frame camera equipped with a normal lens (50mm), with the camera being placed close to the object. The artefact has already been digitised with a structured light system and that model served as the reference model in which 3D models were compared and the results were presented.

The Depth of Field (DoF) is a vital factor in photogrammetric applications. Its effect is in most cases pretty obvious especially when capturing small artefacts. It is very important to observe its behaviour as it affects the ability to capture all the details of an object. Focus stacking is a technique in computational photography, in which a set of images focused on different planes with limited DoF are combined in order to considerably extend the DoF. Today, there is a number of focus stacking methods that can be applied in order to produce a full-focus image. In this paper, we investigate the application and effects of focus stacking on SfM-MVS 3D reconstruction. Specifically, our experiment involves the 3D reconstruction of a selected artefact using both traditional all-focus photography and focus stacking. The artefact has already been digitised with a high accuracy and resolution structured light 3D scanner, and that 3D model served as the reference model, with which SfM models were compared. We discuss on these fist results and present some preliminary assessment on the application of focus stacking for the SfM-MVS-based 3D reconstruction.

3D digitisation has been applied in different application domains. Due to the continuous growing interest, commercial and experimental 3D acquisition systems have evolved. Nevertheless, there isn't an all-in-one solution, thus there is a need for combining different technologies in order to exploit the advantages of each approach. In this paper, we present a solution to a specific problem related to the combination of 3D data resulted from a non-colour laser triangulation scanner and a shape-fromsilhouette system. Our approach combines the data of these two 3D acquisition systems in order to produce a hybrid 3D mesh model with the geometric accuracy and detail captured by the laser scanner and the high resolution textural information of the shape-fromsilhouette system. We propose an algorithm that is based on virtual photo shooting and an inverse texture map projection phase. We present an example of our algorithm’s operation on exchanging the texture maps of a replica artefact which has been digitised by both systems.

The phytopathogenic bacterium Pantoea stewartii subsp. stewartii synthesizes stewartan exo/capsular polysaccharide (EPS) in a cell density-dependent manner governed by the EsaI/EsaR quorum-sensing (QS) system. This study analyzes biofilm development and host colonization of the WT and QS regulatory mutant strains of P. stewartii. First, we show that the cell density-dependent synthesis of stewartan EPS, governed by the EsaI/EsaR QS system, is required for proper bacterial adhesion and development of spatially defined, 3D biofilms. Second, a nonvirulent mutant lacking the esaI gene adheres strongly to surfaces and develops densely packed, less structurally defined biofilms in vitro. This strain appears to be arrested in a low cell density developmental mode. Exposure of this strain to exogenous N-acyl-homoserine lactone counteracts this adhesion phenotype. Third, QS mutants lacking the EsaR repressor attach poorly to surfaces and form amorphous biofilms heavily enmeshed in excess EPS. Fourth, the WT strain disseminates efficiently within the xylem, primarily in a basipetal direction. In contrast, the two QS mutant strains remain largely localized at the site of infection. Fifth, and most significantly, epifluorescence microscopic imaging of infected leaf tissue and excised xylem vessels reveals that the bacteria colonize the xylem with unexpected specificity, particularly toward the annular rings and spiral secondary wall thickenings of protoxylem, as opposed to indiscriminate growth to fill the xylem lumen. These observations are significant to bacterial plant pathogenesis in general and may reveal targets for disease control.

This paper introduces the concept of evolving actor–network ontologies (EANO) as a new paradigm for cultural digital twins. Building on actor–network theory, EANO reframes ontologies from static representations into reflexive, dynamic structures in which semantic interpretations are continuously negotiated among heterogeneous actors. We propose a five-layer architecture that operationalizes this principle, embedding reflexivity, actor salience, and systemic parameters such as resistance and volatility directly into the ontological model. To illustrate this approach, we present minimal simulations that demonstrate how different actor constellations and systemic conditions lead to distinct patterns of semantic evolution, ranging from expert erosion to contested equilibria and balanced coexistence. Rather than serving as predictive models, these simulations exemplify how EANO captures semantic plurality and contestation within a transparent and interpretable framework. The contribution of this work is thus twofold: it provides a conceptual foundation for evolving ontologies in digital heritage and a lightweight demonstration of how such models can be instantiated and explored computationally.

In this paper, we present a method for partial matching and retrieval of 3D objects based on range image queries. The proposed methodology addresses the retrieval of complete 3D objects using range image queries that represent partial views. The core methodology relies upon Bag-of-Visual-Words modelling and enhanced Dense SIFT descriptor computed on panoramic views and range image queries. Performance evaluation builds upon standard measures and a challenging 3D pottery dataset originating from the Hampson Archaeological Museum collection.

Digital media and learning initiatives for virtual collaborative environments are contributing to the definition of new (sub-)disciplines in archaeological and heritage sciences. New nomenclature and terminology is emerging such as cyber archaeology, cyber archaeometry, virtual worlds and augmented and immersive realities; and all of them are related to museums and cultural heritage—tangible, intangible or natural (Forte 2010; Liritzis et al. 2015).

Some archetypal critics and literary scholars have realized the necessity to treat the hero's and the heroine's quest pattern in a very distinct and specialized manner. In this thesis I show the effect that western literature has had on revealing the female quest pattern and I reevaluate the role of the heroine and the significance of her journey largely by using Alice Hoffman's novel, The Ice Queen, and some related literature. To aid in this task I have employed the five phase pattern of the heroine developed by Annis Pratt. Moreover, five goddesses (Artemis, Athena, Aphrodite, Persephone and Hera) are used as archetypes to reveal how the goddess qualities can be applied to these phases in the heroine's struggle for identity. Re-examining the goddesses and separating the hero's journey from the heroine's enable a more profound understanding of the female quest for identity.