Hasil untuk "Art"

D. L. Sexton, R. Smilor

R. Plamondon, G. Lorette

D. Whitney

F. W. Taylor

A. Wildavsky

M. D. Pree

E. Rechtin

The design of complex systems is viewed as a blend of the art of architecture with the science of engineering. The principles of systems are discussed, with examples to illustrate each point. The artistic elements of architecture are then considered, and four methods in common use, depending on the nature and phase of the project, the particular problem to be solved, and the style of the architect, are described. The role of architecting throughout the system development cycle is examined. Architecting and concurrent engineering are compared and seem to be complementary strategies. >

Y. Konan, R. Gurny, E. Allémann

P. T. Vasudevan, Michael Briggs

A. Hastings

L. Andreotti

J. C. Roberts

Martin Arthur Kuppers

Andrea Lucarelli, P. Berg

Jomar Delos Reyes, Sealtiel Dy, Rica Mae Sales. Orrin Landon Uy et al.

Digital and interactive spaces are becoming increasingly prevalent as platforms for cultural engagement, offering new ways to make art more accessible, engaging, and inclusive. In the Philippine context, where visual art is deeply rooted in precolonial, colonial, and postcolonial histories, there is a growing need to explore how digital systems can support art appreciation without replacing or compromising traditional and physical artworks. Rather than treating digital experiences as substitutes, we argue for the value of creating interactive digital twins that allow audiences to explore, touch, and engage with artworks while preserving the integrity of the originals. In this paper, we present SoulWall, an extended reality (XR) interactive mural system designed to augment Filipino artworks through embodied interaction. SoulWall enables viewers to experience paintings and animations at scale, supporting exploratory and playful engagement while respecting artist intent. We describe the design and implementation of the system, including its mural layout, interaction techniques, and interaction logging infrastructure. We report findings from a user study focused on user experience complemented by analyses of interaction logs and spatial engagement patterns. Our results highlight the potential of XR murals as a cultural computing artifact for art appreciation and for showcasing Filipino artists in interactive public and exhibition spaces.

Haida Liang

Elena Emilia ȘTEFAN

The activity of public authorities is subject to the control of legality performed by the administrative courts, according to the law. On the basis of art. 52 of the Constitution, persons aggrieved in their legitimate rights and interests often complain before the courts that the administration fails to give reasoning on the administrative acts. At EU level, the Charter of Fundamental Rights of the European Union stipulates that giving reasons for administrative acts is a component of the right to good administration. In this context, the aim of this paper is to analyze the relevant case-law in order to be able to observe the national administrative contentious judge's opinion on the reasoning of administrative acts, in the sense of whether this formality is mandatory or not for the issuing public authority. In terms of the research methodology, the structure of the paper has two main components, a theoretical one, namely it will describe the state of the legislation applicable to the reasoning of administrative acts, then it will focus on the practical component, in order to understand what problems arise in the work of public administration in this aspect. The proposed subject is topical, practical and of general interest. Using specific legal methods, the conclusion of the paper will be emphasized, namely that the reasoning is a condition for the legality of the administrative act, without which the proper functioning of public administration would be questioned.

Shiqi Feng, Xuquan Wang, Xiong Dun et al.

Encoded computational hyperspectral cameras, propelled by advances in compressed sensing theory, making both miniaturization and real-time hyperspectral imaging feasible. Spectral-encoded or spatial-encoded hyperspectral imaging strategy have limited numbers of design parameters in optical components, leading to severe ill-posedness in hyperspectral images reconstruction, which constrain overall imaging quality. However, spatial-spectral-encoded hyperspectral imaging strategy which simultaneously performs spatial and spectral encoding entailing more powerful modulation, alleviating ill-posed problems and improving the quality of hyperspectral images. In this paper, we present a co-modulation framework based on diffractive optical element (DOE) and Superposition Fabry&#x2013;Perot (SFP) filter array for computational hyperspectral camera that integrates these two components with a transformer-based reconstruction network through end-to-end learning. The learned DOE and SFP filter encode the hyperspectral datacube on the sensor via phase and amplitude modulation, and the transformer-based network accurately reconstructs the images from sensor measurements. We conduct extensive simulations to analyze and validate the relatively contributions of the DOE, SFP filter, and transformer-based reconstruction algorithm to the significantly improved performance of hyperspectral image reconstruction across various ablation study models. We further investigate and identify the <inline-formula><tex-math notation="LaTeX">$\mathbf {4\times 4}$</tex-math></inline-formula> SFP filter unit configuration as the most effective design for achieving a balance between spectral fidelity and spatial resolution. Our results show that the proposed system outperforms state-of-the-art methods in hyperspectral images reconstruction quality, excelling in both spatial and spectral detail recovery, and maintaining good performance against realistic noise levels.

Annalisa Belli , Erica Gobbi , Stefano Amatori et al.

Introduction The use of Social Networking Sites (SNS) has been continuously increasing in recent years [1], contributing to the rise of significant behavioral and psychological issues, especially when SNS are used as a coping mechanism for stress and loneliness among young people. One of the most widely used SNS today is Instagram, and several studies indicate that excessive use of this platform may be associated with decreased cognitive functioning in young adults, as well as behavioral and sleep disorders [2]. In addiction, the Instagram platform's focus on food imagery, fitness content, and body aesthetics often perpetuates unattainable beauty standards, potentially triggering disordered eating patterns or body dissatisfaction [3,4]. Moreover, the study by Romero-Rodríguez et al. [5], found that while problematic smartphone use negatively influences self-esteem, the intensity of Instagram use itself was not a direct predictor of self-esteem among university students. This suggests a nuanced relationship between SNS engagement and self-perception, warranting further exploration.   Aims This study aimed to explore the relationships between problematic social media use (PSMU), self-esteem, physical activity (PA), and eating behaviors, using a moderated-mediation model. In this study, we tested a moderated-mediation model of how explained variables may be interrelated. The model’s starting point is the well-established link between PSMU and self-esteem, and PSMU and eating behaviour, with the hypothesis that higher PSMU is associated with higher levels of problematic affects and behaviors. We then hypothesized that participants who have higher self-esteem will show better eating habits despite higher levels of PSMU (mediation analysis). Finally, we supposed that physical activity and sedentary levels could moderate the relationship between PSMU and self-esteem (moderation analysis), with a protective role of PA.   Methods A cross-sectional study was conducted with 1237 university students (74.4% females, mean age = 22.7 ± 5.5 years). Participants completed an online survey assessing Instagram use, enrolled in 13 different academic programs (e.g., languages, art, biology, pharmacy, sport science). The students completed an online questionnaire composed of four sections about: physical activity (International Physical Activity Questionnaire, IPAQ) [6]; Instagram usage (Social Media Use Questionnaire, SMUQ) [7]; self-esteem (Rosenberg Self-Esteem Scale) [8]; eating behaviors (Dutch Eating Behavior Questionnaire, DEBQ) [9]. A chi-square test was used to test the gender differences in the distribution of participants in the three PA categories (low, moderate, high). Non-parametric Spearman’s correlations were then computed between Instagram use (minutes per day, reasons for use), SMUQ subscales (Withdrawal and Compulsion), PA (MET/min/week), sitting time (hours/day), self-esteem and eating behaviors (emotional eating, restrained eating, external eating). A multiple linear regression was then performed to test the effect of Instagram time (minutes per day) and motives of use on the two SMUQ subscales (Withdrawal and Compulsion). Finally, a moderated-mediation analysis [10] was conducted to examine the relationships between PSMU and Eating behaviors, considering PA and sitting time, and self-esteem, as potential moderators and mediator, respectively.   Results In our sample, females reported higher levels of PSMU and more problematic eating behaviors than males, who in turn exhibited significantly higher levels of physical activity (p < 0.001). Regarding Instagram use, females reported significantly higher daily usage (p < 0.001), number of followers (p < 0.01), following (p < 0.01), and higher scores for all reasons for Instagram use, except for self-promotion, where responses were similar to males. Two multiple linear regression analyses (one for each subscale of SMUQ) were used to investigate which of the motives for use or usage time were more influential on the problematic use. Considering Withdrawal as the dependent variable, the overall regression was statistically significant (R2adj = 0.222, F(6,1165) = 56.71, p < 0.001). All the independent variables were significant predictors of Withdrawal, with the exception of the use for Documenting. The correlation analysis showed that the PSMU (both Withdrawal and Compulsion) was significantly positively correlated to the daily usage time, and to all the three typologies of eating behaviors (restrained, emotional, and external eating). PSMU was positively correlated with restrained, emotional, and external eating behaviors and negatively correlated with PA and self-esteem. Self-esteem mediated the relationship between PSMU and eating behaviors, with higher self-esteem associated with healthier eating patterns. Sitting time moderated the relationship between PSMU and self-esteem, reinforcing the negative effects of excessive Instagram use. Gender differences were observed, with females reporting higher levels of PSMU, problematic eating behaviors and lower PA levels compared to males. This study highlights the complex interplay between PSMU, self-esteem, PA, and eating behaviors in university students.   Conclusion These findings highlight the importance of addressing PSMU’s impact on self-esteem and eating behaviors in young adults. PA emerged as a beneficial factor for self-esteem, but its inability to moderate the PSMU–self-esteem relationship suggests that targeted interventions should consider psychological components alongside lifestyle modifications mainly directed at reducing sedentary and sitting time. Promoting regular PA could serve as an effective strategy to enhance self-esteem and counteract the harmful effects of excessive Instagram use. Health education programs emphasizing digital literacy, self-esteem enhancement, and balanced SNS engagement may help mitigate PSMU’s adverse effects. Future research should explore longitudinal relationships and intervention strategies to promote healthier social media habits and psychological well-being among university students.

A. Sarala, C. Vinoth kumar

Abstract Underwater image enhancement poses unique challenges due to poor visibility, color distortion, and haze caused by light absorption and scattering in water. In this paper, we propose an ensemble model, Ensemble Pyramid-based Convolutional Neural Network and Deep Channel Prior Dehazing Network (EPCNN-DCPDN), which combines Pyramid-based Convolutional Neural Networks (CNNs) and the Deep Channel Prior Dehazing Network (DCPDN) to address these challenges. The model operates in two ways: sequentially, by first applying DCPDN for haze removal followed by Pyramid-based CNNs for multi-scale feature refinement, or in parallel, with outputs from both models fused using a weighted average or learned fusion mechanism. We evaluated the proposed model on multiple underwater datasets and compared its performance against nine state-of-the-art models, including CLAHE, FUnIE-GAN, WaterGAN, and Haze-Line Prior Model. The EPCNN-DCPDN model achieved superior results with a PSNR of 28.34 dB, SSIM of 0.902, and UIQM of 3.56. It also demonstrated outstanding accuracy in challenging underwater conditions, with an accuracy of 97.92% on shallow, deep, and low-light underwater datasets, outperforming existing models such as WaterGAN and Haze-Line Prior Model. The results highlight the effectiveness of the proposed model in restoring color, contrast, and fine details in underwater images. The model’s ability to handle a wide range of underwater conditions makes it an ideal solution for applications in underwater exploration, marine research, and object detection.