Virtual Reality Technology in Visual Design of Artistic Images: Analysis and Applications

Within a few decades of development, Internet is been refreshing the world’s awareness of its development and potentials at an unexpected speed. In recent years, virtual reality technology has begun to be applied to more and more fields. Especially in instant transmission of information, the applications of VR are incomparable. Akin to the wide-ranged advantages of the technology in education and health, the applications of VR in the art of artistic image designing need to be addressed. With this research work, a comprehensive study is presented about the applications of virtual reality in the art of image visualization. The research intends to analyze the possibility of intermingling modern image visualization with the emerging VR technology. Following a systematic approach, the history and development of display design are reviewed besides studying the artistry techniques used in the technology of art image visualization design. The interdisciplinary association of the two fields is explored with the help of relevant algorithms. The model proposed in the paper for the design of art image is based on the visual interactive process, rigorous assembly sequence, and appropriate equipment mode. As a result, the whole design process is more controllable and feasible. The suggested design concept is verified dynamically. Through the collection and comparison of feedback information, the hypothesis algorithm of the model is updated to accommodate the dynamic information so that to reflect the complete image design process. To assess performance of the model, evaluation was conducted from various perspectives. The three basic image operations such as illumination change, occlusion change, and color change were performed by using the two technologies such as the traditional image design and VR-based image design. From the comparison of experimental data, it was revealed that the effects of traditional art image visualization products produced by the art image visualization and that of VR technology are quite different. For instance, the visualization score achieved for the lighting change operation using the VR technology was 95.48%, whereas 85.57% was obtained for the same operation using the traditional image design technology. Similarly, while adding visual effects using the VR technology, an average of 9% higher score was obtained for the said image operations. The promising results attained for the VR-based design testify that the technology is feasible and suitable to be intermingled with the visual design of art image. As a whole, the findings justify that the proposed approach is quite applicable in visual design of art image systems. In view of the significance of the research, the study can be extended to related domains of computer-based designing and visualization as well.

A Decision Support System for Power Components Based on Improved YOLOv4-Tiny

The traditional image object detection algorithm applied in power inspection cannot effectively position power components, and the accuracy of recognition is low in scenes with some interference. In this research, we proposed a data-driven power detection method based on the improved YOLOv4-tiny model, which combined the ResNet-D module and the adjusted Res-CBAM to the backbone network of the existing YOLOv4-tiny module. We replaced the CSPOSANet module in the YOLOv4-tiny backbone network with the ResNet-D module to reduce the FLOPS required by the model. At the same time, the adjusted Res-CBAM whose feature fusion ways were replaced with stacking in the channels was combined as an auxiliary classifier. Finally, the features of five different receptive scales were used for prediction, and the display of the results was optimized by merging the prediction boxes. In the experiment, 57134 images collected on the power inspection line were processed and labeled, and the default anchor boxes were re-clustered, and the speed and accuracy of the model were evaluated by video and validation set of 3459 images. Processing multiple pictures and videos collected from the power inspection projects, we re-clustered the default anchor box and tested the speed and accuracy of the model. The results show that compared with the original YOLOv4-tiny model, the accuracy of our method that can position objects under occlusion and complex lighting conditions is guaranteed while the detection speed is about 13% faster.

Diagnosis of interior damage with a convolutional neural network using simulation and measurement data

Current deep learning applications in structural health monitoring (SHM) are mostly related to surface damage such as cracks and rust. Methods using traditional image processing techniques (such as filtering and edge detection) usually face difficulties in diagnosing internal damage in thicker specimens of heterogeneous materials. In this paper, we propose a damage diagnosis framework using a deep convolutional neural network (CNN) and transfer learning, focusing on internal damage such as voids and cracks. We use thermography to study the heat transfer characteristics and infer the presence of damage in the structure. It is challenging to obtain sufficient data samples for training deep neural networks, especially in the field of SHM. Therefore we use finite element (FE) computer simulations to generate a large volume of training data for the deep neural network, considering multiple damage shapes and locations. These computer-simulated data are used along with pre-trained convolutional cores of a sophisticated computer vision-based deep convolutional network to facilitate effective transfer learning. The CNN automatically generates features for damage diagnosis as opposed to manual feature generation in traditional image processing. Systematic parameter selection study is carried out to investigate accuracy versus computational expense in generating the training data. The methodology is demonstrated with an example of damage diagnosis in concrete, a heterogeneous material, using both computer simulations and laboratory experiments. The combination of FE simulation, transfer learning and experimental data is found to achieve high accuracy in damage localization with affordable effort.

Unusual Sculptures of Buddhist Deities in Japan in the Halo of Legends and Historical Facts

Diverse, unusual images of Buddhist deities are ubiquitous in Japan. In a number of ways, they differ from traditional temple images, demonstrating a deviation from the canon, which dictates certain, centuries-old norms and rules regarding postures, position of feet, fingers, gestures, symbols. Simplification of expressive means, a stylized image become the predominant features in the image of extraordinary images. The appearance of unusual Buddhist sculptures in the plastic field of the country is often associated with the existence of legends, traditions, and also facts that took place throughout the history of Japan among the population. The iconography of unusual Buddhas is very diverse and encompasses both the Buddhas themselves and the bodhisattvas, Kings of Light, Heavenly Kings, and so on. Six-armed Jizō, Rope-tied Jizō, Yata Jizō, Child-giving Jizō are added to the familiar images of the Bodhisattva Jizō. Amida Buddha, who is habitually portrayed as sitting frontally, appears in a new form – standing and in profile or with his head bowed. A very colourful group is represented by deities sitting on zoomorphic thrones – lions, elephants, riding birds – knocked out of the canonical image. The traditional images of the Eleven-headed, Thousand-armed Bodhisattva Kannon always seemed unusual, although they became familiar. However, placing the bodhisattva on a mount bird – a four-legged, eight-headed raven gives reason to consider this sculpture unusual. In unusual sculptures, there is a deviation from the norm, an abstraction from the traditional image. Aesthetic ideals are not realized through a complex of canons, rather through a new figurative language, not yet fixed by tradition.

Joseph’s Food Politics as Life-Keeper of Many People: A Close Rereading of Genesis 47:13–26

The Septuagint reading predominantly influences the interpretation of Genesis 47:13-26 (primarily v. 21). Despite a positive portrayal of Joseph, he is also seen as Pharaoh’s accomplice to enslave the Egyptian people. This connection with slavery activities contradicts the traditional image of Joseph as the life-keeper of many people. Solution for the negative portrait of Joseph usually refers to the Masoretic Text, although it is not a reference to many modern Bible translations and commentaries. The Septuagint as a reference, in this case, is indeed difficult to reject. However, that does not mean that Joseph promotes the slavery of the Egyptian people throughout the land, but rather an ancient form of state capitalism. This article draws on textual criticism, word studies, form criticism, and agricultural knowledge background in the ancient Middle East. The contribution of this research is to show that, instead of enslaving, Joseph formulated an Egyptian food politics in the larger context of Joseph’s narrative reality as the life-keeper of many people.

Truck-Lifting Prevention System Based on Vision Tracking for Container-Lifting Operation

Truck-lifting accidents are common in container-lifting operations. Previously, the operation sites are needed to arrange workers for observation and guidance. However, with the development of automated equipment in container terminals, an automated accident detection method is required to replace manual workers. Considering the development of vision detection and tracking algorithms, this study designed a vision-based truck-lifting prevention system. This system uses a camera to detect and track the movement of the truck wheel hub during the operation to determine whether the truck chassis is being lifted. The hardware device of this system is easy to install and has good versatility for most container-lifting equipment. The accident detection algorithm combines convolutional neural network detection, traditional image processing, and a multitarget tracking algorithm to calculate the displacement and posture information of the truck during the operation. The experiments show that the measurement accuracy of this system reaches 52 mm, and it can effectively distinguish the trajectories of different wheel hubs, meeting the requirements for detecting lifting accidents.

V. M. Essipov. A. S. Pushkin’s correspondence with A. K. Benckendorff

V. Essipov’s monograph is alandmark product of Pushkin studies. It follows the relationship between Pushkin and Benckendorff over a ten-year period (1826– 1836). Benckendorff’s character is shown in an entirely new light. Unlike the one-sided depiction promoted by Soviet literary criticism, the author creates a controversial portrait, greatly aided by substantial details found in documents. Essipov treats this historical figure not only as a functionary, but also a human being. He demonstrates that Benckendorff was not nearly as narrow-minded and primitive as his traditional image in literature. The reviewer finds that the book will be of interest not only to Pushkin scholars, but also historians and anyone who would like to learn about the unconventional approach to Pushkin’s relationship with Benckendorff. The monograph can also be useful for playwrights and directors who are fascinated with that particular period in Russian history and literature.

CULTURAL, ARCHITECTURAL, ‘SENSE OF PLACE’ AND SUFISTIC BELIEFS IN MOSQUE TOURISM CASE STUDY: MASJID AR-RAHMAN, PULAU GAJAH, KELANTAN

The mosque is a sacred important religious symbol for bringing Muslims together as demonstrated during the time of Prophet Muhammad (PBUH). This paper investigates the potential of Masjid Ar-Rahman of Pulau Gajah, Kelantan as a spot for mosque tourism. Although this mosque was constructed in 2016, it has demonstrated a simplicity in its scale and traditional image. It has value as a hybrid assimilation of HinduBuddhist syncretism and tolerance, and has coined the term Nusantara to denote its hybridised Malay and Javanese architectural styles. The typology of this humble Malay Mosque architecture is of medium-scale and reflects the Sufistic contextual value beliefs of encouraging religious and architectural tourism alike. The conceptual framework capitalises on the research gap found in mosque cultural, architectural and Sufistic beliefs. Research by further delving into constructing the “Sense of Place” in relation to the “Sacred Places”. This research employs qualitative methods of interviewing visitors, applying phenomenological and case study approaches supported by architectural documentation in emphasising the symbolic and semiotic aesthetics aspects in constructing the “Sense of Place” bonded by Sufistic symbolic aesthetics. The theory is constructed in the deeply rooted Islamic Mosque architecture via Sufistic beliefs that provides a platform for mosque tourism activities.

Generalized multi-channel scheme for secure image encryption

The ability of metamaterials to manipulate optical waves in both the spatial and spectral domains has provided new opportunities for image encoding. Combined with the recent advances in hyperspectral imaging, this suggests exciting new possibilities for the development of secure communication systems. While traditional image encryption approaches perform a 1-to-1 transformation on a plain image to form a cipher image, we propose a 1-to-n transformation scheme. Plain image data is dispersed across n seemingly random cipher images, each transmitted on a separate spectral channel. We show that the size of our key space increases as a double exponential with the number of channels used, ensuring security against both brute-force attacks and more sophisticated attacks based on statistical sampling. Moreover, our multichannel scheme can be cascaded with a traditional 1-to-1 transformation scheme, effectively squaring the size of the key space. Our results suggest exciting new possibilities for secure transmission in multi-wavelength imaging channels.