Three-dimensional (3D) modeling is a key requirement in computer vision, yet achieving high-speed and high-quality image acquisition remains challenging. Flat image sensors, commonly used in 3D scanners, suffer from edge blurring due to misalignment between the sensor plane and the curved focal surface of the lens. While complex lens designs can mitigate this issue, they increase manufacturing costs, weight, and optical distortions. This study investigates the advantages of curved sensors in improving imaging performance. Through software-based modeling and simulation, the study compares curved and flat sensors by analyzing key optical errors, including astigmatism, distortion, spherical aberration, and coma. The results indicate that curved sensors significantly enhance image quality and measurement accuracy. Notably, measurement errors are reduced by 44.68% compared to flat sensors. The findings highlight curved sensors as a promising alternative for high-precision 3D imaging, offering improved edge detection and dimensional measurement accuracy while reducing optical distortions.

Accurate knowledge of seawater optical properties is essential for underwater imaging, sensing, and optical communication, particularly in coastal and shallow-water environments where geometric light propagation effects can influence measurement accuracy. While empirical formulations describing the refractive index of seawater are well established and widely used in the visible spectral range, their applicability in the near-ultraviolet region has received limited experimental validation. In this work, the applicability of an established empirical seawater refractive-index formulation in the near-ultraviolet band is investigated through a combined numerical and experimental approach. First, the empirical model is evaluated numerically to examine its spectral behavior across the visible-near-ultraviolet transition. The results indicate smooth and physically consistent refractive-index variation near the ultraviolet boundary. Second, a controlled laboratory experiment is conducted in which near-ultraviolet beam refraction through stratified seawater is measured using a multi-compartment tank designed to emulate discrete ocean depth intervals. Beam displacement measurements at two near-ultraviolet wavelength bands are compared directly with predictions obtained from a multi-layer ray-tracing simulation based on the empirical formulation. The close agreement between simulated and experimentally measured beam displacement across multiple depth configurations provides physical validation of the empirical refractive-index model in the near-ultraviolet region under the investigated conditions. These findings support the use of established refractive-index formulations for near-ultraviolet underwater optical modeling and contribute to a more reliable foundation for near-UV marine optical sensing and measurement applications.

This study explores how classical painting techniques, particularly those rooted in the Renaissance tradition, can produce illusions of depth that vary with the viewer's position. Focusing on a work rich in soft shading and subtle tonal transitions, we investigate how movement across the frontal plane influences the perception of spatial structure. A sequence of high-resolution photographs was taken from slightly offset viewpoints, simulating natural viewer motion. Using image alignment and pixel-wise difference mapping, we reveal perceptual shifts that suggest the presence of latent three-dimensional cues embedded within the painted surface. The findings offer visual and empirical support for concepts such as and dynamic engagement, where depth is constructed not solely by the image, but by the interaction between the artwork and the observer. Our approach demonstrates how digital analysis can enrich art historical interpretation, offering new insight into how still images can evoke the illusion of spatial presence.

We study underwater optical communication under photon-counting (Poisson) detection with realistic attenuation, background radiance, directionality, and pointing uncertainty. Information is embedded in (i) a temporal dictionary of pseudo-random noise (PRN) intensity sequences and (ii) an optional spatio-temporal extension, denoted SIM-TS (spatial-index modulation with temporal signaling), that combines temporal coding with spatial indexing across multiple transmit/receive apertures. For a fixed optical energy-per-symbol (photon budget), these structured waveforms increase observation dimensionality and improve maximum-likelihood separability under Poisson statistics. We present a layered modeling framework, derive the corresponding Poisson detection metrics, and use Monte Carlo evaluation to extract maximum range at a target symbol error rate. The results show that dimensional signaling provides a modest but repeatable gain in clear-water photon-limited regimes: at 100 kbps, SIM-TS increases the clear-water range from 593.8 m to 617.2 m at 450 nm (3.95%) and from 457.8 m to 473.4 m at 420 nm (3.41%) under fixed total power. In coastal water the gain falls below 1%, while in the 1 Gbps benchmark SIM-TS under fixed total power remains within about 2% of on-off keying (OOK) and the larger improvement under power combining is attributable primarily to increased photon budget. These rate-range trade-offs clarify when dimensional signaling yields practical gains and when attenuation, background, and misalignment dominate the link budget.

This article builds on the argument that design for complex interactive systems should shift from creating transactional interactions to ‘organizing relational complexity’. Grounded in agential realism, we reframe computational agents from black-box predictors to material-discursive apparatuses. We utilize a standard reservoir computing architecture, conceptualized here as the Affective Reservoir, as a diffractive instrument to visualize the co-constitution of gameplay. In doing so, we replace the teleological concept of a fixed ‘goal’ with the agential realist concept of a ‘yearning’: the continuous negotiation of situated tension. By analyzing the reservoir’s dynamics, we show how coherent regimes of interaction emerge within the agent’s internal state space, not from error minimization but from Dynamical Friction; the intense interference pattern generated when the agent’s Re-membered Inertia (habitual momentum) resists the Affective Gradients (situational forcing) of its environment. Ultimately, we argue that by orchestrating an agent’s capacity to be affected via its resistance to and resonance with the environment, designers can move beyond transactional logic to sustain emergent relational phenomena.

This article builds on the argument that design for complex interactive systems should shift from creating linear transactional interactions toward organizing relational complexity. Grounded in Karen Barad’s agential realism, we argue that a designer’s role can benefit from not predefining interactions but from curating the material-discursive conditions under which meaningful relations can emerge. To explore the empirical and temporal dimensions of this practice, we conducted an exploratory workshop setting the conditions for emergent gameplay dynamics and discussions on agential realist anticipation. Participants utilized a custom-designed game and built their own physical controllers to anticipate and adapt to shifting gameplay conditions. Our results demonstrate how alterations in relational constraints, rather than explicit pre-programmed goals, drove the emergence of non-predefined gameplay rhythms. The findings provide empirical grounding for an agential realist understanding of anticipation, showing that an interactive system’s identity lies in its unfolding processual patterns rather than a static final state. Based on these findings, we propose three design principles for further exploration: Design for Relational Emergence, Design for Re-membering, and Design for Emergent Patterns. Consequently, we conclude by outlining a conceptual approach for non-linear computational architectures, drawing on principles from Enactive AI and reservoir computing.

This paper introduces a novel Physical Layer Security (PLS) framework tailored for LiFi-based sensor networks within industrial environments. The proposed system comprises multiple sensor nodes, each equipped with at least three radar sensors integrating both infrared (IR) and visible light communication (VLC) subsystems. The IR subsystem employs a handshake protocol, activating the IR transmitter when data is ready for transmission and ensuring the receiver is prepared to establish a secure link. Upon successful IR handshake, the VLC subsystem initiates data communication between sensors. Additionally, the IR subsystem monitors for mobile obstacles, pausing transmission if discontinuities are detected, thereby maintaining link integrity. Environmental factors, such as walls, significantly influence the secrecy rate performance; hence, the system utilizes parallel alignment of transmitters and receivers to optimize the signal-to-background ratio. The proposed system is examined by simulation and the feasibility results are presented. The results shows that this architecture enhances the robustness and security of inter-sensor communication in challenging industrial settings. 

Light Fidelity (LiFi) offers a high-speed, interference-resistant alternative to conventional wireless communication, making it well-suited for sensitive environments such as healthcare, defense, and industrial systems. While LiFi's confinement to line-of-sight communication provides a natural layer of physical security, it remains susceptible to local eavesdropping and insider interception within its coverage area. These limitations underscore the need for additional data-level protection strategies that align with LiFi's operational constraints. This paper introduces a novel steganographic method tailored for data structured in matrix form, a common representation in many digital systems. To demonstrate the effectiveness of the proposed technique, images-naturally represented as two-dimensional matrices-are used as test cases. The approach avoids traditional payload embedding, which can be statistically detectable, and instead applies recursive segmentation, matrix reshaping, and hierarchical tree-based indexing to transform the structure of the data itself. This process produces encrypted outputs that appear statistically random and visually unstructured (i.e., noise-like), concealing both the data content and the presence of hidden communication. Quantitative evaluations using metrics such as entropy, correlation coefficients, contrast, homogeneity, and Bhattacharya distance confirm that while the encrypted data is statistically obfuscated, the original matrix can be losslessly reconstructed through inverse recursion. The method's design ensures lightweight processing is suitable for resource-constrained LiFi-enabled sensor nodes while significantly enhancing communication confidentiality. By restructuring data at the matrix level rather than embedding within it, this approach provides an effective and generalizable framework for secure transmission in physically exposed but bandwidth-rich LiFi networks. 

With this paper we want to contribute to both anticipation studies and game studies by addressing how futures get made. By exploring the concept of anticipation in relation to game design, using Karen Barad's agential realism, we argue that anticipation should not be confused with prediction but rather seen as a fundamental force that shapes our experience of the world.

By using agential realism as a framework and games as context, we show how subject/object relations are continuously (re)configured through intra-actions, and how agency arises in specific situations. An experimental game, Lightning Dice illustrates how anticipation and measurements interact to create different future possibilities. By changing the game's rules and measurement methods, it demonstrates how different patterns and power dynamics can emerge.

The paper concludes by revisiting a design approach called re-verb, outlining a collaborative design workshop in which participants will explore anticipation and agency. The workshop aims to spark questions and further research on anticipation with respect to AI.

Blockchain technology is increasingly recognized as a promising solution for managing health-related data, particularly in promoting well-being through physical activity. This is becoming more significant as the Internet of Things (IoT) and sport monitoring sensors continue to expand and become more available, leading to a growing number of users in sports and prolonged usage of these devices, which continuously capture large volumes of physical activity data. The substantial volume of data generated in sports and physical activities, combined with distinct concerns compared to medical and health-related information, makes this domain a unique case for blockchain applications. This paper presents a systematic review of blockchain applications in physical activity, exercise-based rehabilitation, fitness, sport, and exercise-based therapeutics (PARFSET). It specifically focuses on examining their quality attributes, including privacy, security, accountability, personalization, adherence, and extensibility. Our objective is to establish a foundational understanding of the benefits of a blockchain in PARFSET domains, particularly following the decline in initial hype for blockchain technology. We aim to provide a clearer perspective on potential applications, future advancements, and research directions. To this end, we assess the maturity levels of blockchain adoption in these areas and highlight specific examples where a blockchain contributes to enhanced data protection, user-centered customization, trust through accountability, and system scalability. Additionally, we present a hypothetical illustrative case to demonstrate how blockchain applications and their quality outcomes can be effectively integrated. Finally, the paper explores the challenges associated with blockchain implementation and outlines potential directions for future research.