Innovative Architecture Research Articles

Physics-informed neural nets for control of dynamical systems

Physics-informed neural networks (PINNs) incorporate established physical principles into the training of deep neural networks, ensuring that they adhere to the underlying physics of the process while reducing the need for labeled data, since the desired output is not a prerequisite for physics-informed training. For modeling systems described by Ordinary Differential Equations (ODEs), traditional PINNs typically take continuous time as an input variable and produce the solution to the corresponding ODE. However, in their original form, PINNs neither accommodate control inputs nor do they effectively simulate variable long-range intervals without experiencing a significant decline in prediction accuracy. In this context, this work introduces a novel framework known as “Physics-Informed Neural Nets for Control” (PINC). PINC presents an innovative PINN-based architecture tailored to control problems, capable of simulating longer-range time horizons that are not predetermined during training. This increased flexibility sets it apart from traditional PINNs. The variable simulation time is achieved by adding inputs to the PINC network that convey the initial condition and the control signal for a particular time interval. Simulating variable long-range intervals involves running the PINC net across a sequence of shorter intervals. In this autoregressive process, the network predictions are linked in a self-feedback mode, with the initial state (input) of the next interval set to the last predicted state (network output) of the previous interval. We showcase the effectiveness of our proposal in identifying and controlling three nonlinear dynamic systems: the Van der Pol oscillator, the four-tank system, and an electric submersible pump. Crucially, these experiments demonstrate that learning the dynamics of these systems can be achieved without relying on any sample collected from the actual process, and it offers faster inference speed compared to numerical simulations.

Multi-depth branch network for efficient image super-resolution

A longstanding challenge in Super-Resolution (SR) is how to efficiently enhance high-frequency details in Low-Resolution (LR) images while maintaining semantic coherence. This is particularly crucial in practical applications where SR models are often deployed on low-power devices. To address this issue, we propose an innovative asymmetric SR architecture featuring Multi-Depth Branch Module (MDBM). These MDBMs contain branches of different depths, designed to capture high- and low-frequency information simultaneously and efficiently. The hierarchical structure of MDBM allows the deeper branch to gradually accumulate fine-grained local details under the contextual guidance of the shallower branch. We visualize this process using feature maps, and further demonstrate the rationality and effectiveness of this design using proposed novel Fourier spectral analysis methods. Moreover, our model exhibits more significant spectral differentiation between branches than existing branch networks. This suggests that MDBM reduces feature redundancy and offers a more effective method for integrating high- and low-frequency information. Extensive qualitative and quantitative evaluations on various datasets show that our model can generate structurally consistent and visually realistic HR images. It achieves state-of-the-art (SOTA) results at a very fast inference speed. Our code is available at https://github.com/thy960112/MDBN.

Hunting for pearls in the shallow water: designing and building spatial immateriality in the aquatic theatre La Perle

This essay discusses the working process behind Franco Dragone’s aquatic theatre La Perle (2017) in Dubai. The aim of the case study is to provide unique insight into the development and implementation of an innovative architecture typology of a theatre building conceived as a ‘living thing’, a spatial system able to adapt and change according to the demands of dramaturgy. Remembering imaginative, but never built, proposals for theatre buildings from the beginning of the twentieth century, and their objectives regarding more flexibility of a performance space, the study explains what it takes to actually realise a ‘fluid’ spatial system. At the same time, it is an attempt to broaden the understanding of scenography by discussing it in relation to its materiality, technical requirements, and the virtual content employed in the La Perle show. Using the lens of posthumanism, the analysis includes discussion on the culture/nature divide in the realm of contemporary spectacle, concentrating on Karen Barad’s notion of non-human matter and its role within an aquatic theatre, adaptable and ever-changing. It explains an approach to treating space as a scenographic body, and the contribution of architectural design proceedings to the conception and production of new kinds of theatres.

The use of containers as a constructive method in buildings: a viable and sustainable alternative

With the increase in environmental concern, alternatives for the use of resources that are less harmful to the environment have been explored, including materials and construction methods. In this context, there is a growing search for new construction processes, especially container buildings, which have gained popularity and acceptance in society, being applied in both commercial and residential contexts. The main attractions for those interested in acquiring a container construction are the reduction of costs and the shortening of the execution time of the work. This is due to the minimization of waste generated during construction and the recycling of metal boxes, which would otherwise remain useless in ports. This advantage goes beyond the economic benefits, contributing to adding sustainable value to the project. This paper aims to discuss the feasibility analysis of the use of containers as a sustainable and financially advantageous proposal compared to conventional methods of structural construction for housing. Through a literature review, evidence of the feasibility and reuse of shipping containers for housing purposes is presented, exploring viable alternatives for the use of waste. The comparative study is based on the parameters established by the National System of Research on Costs and Indices of Civil Construction – SINAPI. The steps include the initial survey of all the improvements and adaptations necessary to provide housing conditions, considering standards of acoustic comfort, lighting, and ventilation. The results indicate that the reuse of the container results in savings of approximately 10% compared to masonry construction. Therefore, this approach has numerous advantages, being a financially viable, fast, and flexible solution for new architectural arrangements, in addition to incorporating architectural innovations aligned with environmental awareness.

A Cyber-physical-social systems approach to the semantic segmentation of pulmonary embolism

Cyber-Physical-Social Systems (CPSS) epitomize the modern era’s intelligent connectivity. They integrate physical devices, computer networks, and social networks, forming an innovative paradigm for intelligent systems. Utilizing CPSS to enhance intelligence, automation, and remote services in healthcare represents a primary research focus. Pulmonary embolism, a prevalent condition resulting from the blockage of the pulmonary artery and its branches by emboli, leads to a spectrum of clinical syndromes marked by impaired pulmonary circulation and right heart dysfunction, contributing to sudden and unpredictable fatalities. Nevertheless, the diagnosis of pulmonary embolism remains challenging due to non-specific clinical presentations, constrained diagnostic capabilities, delayed diagnoses, insufficient physician knowledge, and suboptimal diagnostic techniques. Consequently, we introduce the innovative LSCU-Net architecture within the CPSS framework, designed to develop an automated segmentation and intelligent assessment system for pulmonary embolism, facilitating its automated and intelligent detection. The experimental findings demonstrate that the model accurately segments pulmonary embolism, evidenced by a Jaccard index of 0.6958, a Dice coefficient of 0.8193, a Mean Pixel Accuracy (mPA) of 0.8519, and an accuracy of 0.9993. Empirical studies reveal that our proposed model substantially surpasses existing models in performance. Consequently, this model can aid physicians in the diagnosis of pulmonary embolism during clinical practice. The established pulmonary embolism automatic segmentation and assessment system also showcases the application successes of CPSS in intelligent remote healthcare. The system’s development and deployment not only streamline physicians’ diagnostic processes but also elevate public health standards and advance CPSS research within the medical domain.

Multiple Branch Deep Neural Network and Feature Fusion Model for Underwater Image Enhancement

Underwater imaging faces formidable challenges due to light absorption, scattering, and restricted visibility, demanding sophisticated enhancement methods. This research presents a novel Multiple Branch Deep Neural Network and Feature Fusion (MB-DNN-FF) Model tailored specifically for Underwater Images Enhancement (UWIE), with a focus on its application to the UFO120 dataset. Driven by the limitations of existing techniques, our model harnesses the potential of Deep Learning (DL) and Feature Fusion (FF) to effectively address the intricate complexities present in underwater environments. The innovative architecture incorporates multiple branches, each strategically designed to tackle distinct challenges such as contrast degradation, limited visibility, and color distortion. Central to our model is feature fusion, a critical aspect that harmoniously integrates information from diverse branches, thereby enhancing overall image quality. The training and optimization processes are thoroughly detailed, encompassing unique strategies and loss functions fine-tuned for the nuances of UWIE, with emphasis on the characteristics of the UFO120 dataset. Experimental evaluations leverage the comprehensive UFO120 dataset, employing established performance metrics to quantitatively assess the efficacy of our model. Results exhibit substantial improvements over baseline models and state-of-the-art methods, showcasing the effectiveness and versatility of the proposed multiple branch model, particularly on the UFO120 dataset. The discussion interprets these findings in the context of underwater imaging challenges, highlighting the model's effectiveness and outlining potential applications. This research contributes a valuable asset to the area of UWIE, offering a nuanced and potent solution through the integration of multiple branches and feature fusion, validated on the UFO120 dataset. The conclusions underscore the significance of the MB-DNN-FF in advancing the state-of-the-art in UWIE, opening avenues for future research and practical applications in marine sciences, surveillance, and exploration.

Innovative Architecture for Phosphor‐in‐Glass Films Enabling Superior Luminance and Color Quality Laser‐Driven White Light

AbstractLaser‐driven white light exhibits exceptional brightness and directionality, making it particularly well‐suited for spotlight applications. Yet, attaining high‐quality white light remains challenging due to the sluggish heat dispersion and inconsistent light uniformity of color converters. In this study, an innovative phosphor‐in‐glass (PiG) film architecture is introduced, aiming to achieve superior quality laser‐driven light, where the traditional Y3(Ga,Al)5O12:Ce3+ (YAGG:Ce3+) PiG film is topped with a Al2O3‐in‐glass (AiG) film. The heightened thermal conductivity of the AiG film facilitates quicker dissipation of heat, consequently elevating the luminescence saturation threshold from 14 to 16 W mm−2 and luminous flux from 1243.8 to 1475.9 lm. The increased light scattering attributed to the AiG film also effectively disperses both laser and emitted light, significantly enhancing the angular consistency of color rendering index (Ra). This improvement is evident as the coefficient of variation (Cv) decreases dramatically from 16.69% to 0.25%. Moreover, by integrating CaAlSiN3:Eu2+ (CASN:Eu2+) into the PiG film and fine‐tuning the YAGG:Ce3+ and CASN:Eu2+ ratio, a high‐quality laser‐driven white light achieving an impressive color rendering index (Ra) of 88.7 and offering an adjustable correlated color temperature (CCT) has been developed. This innovation holds tremendous potential as a versatile spotlight solution for both indoor and outdoor settings.

A Link Status-Based Multipath Scheduling Scheme on Network Nodes

Traditional internet protocol (IP) networks, adhering to a “best-effort” service model, typically utilize shortest-path routing for data transmission. Nevertheless, this methodology encounters limitations, especially considering the increasing demands for both high reliability and high bandwidth. These demands reveal shortcomings in this routing strategy, notably its inefficient bandwidth utilization and fault recovery capabilities. The method of multipath transmission has been extensively researched as a solution to these challenges. With the emergence of innovative Internet architectures, notably information-centric networking (ICN), network nodes have gained enhanced capabilities, opening new avenues for multipath transmission design. This paper introduces a multipath scheduling approach for network nodes, capitalizing on the advanced features of these modern nodes. It reimagines the conventional next-hop node as a group of potential next-hop nodes based on both global and local routing strategies and assigns traffic shares to each node within this group for balanced traffic distribution. Network nodes are configured to periodically review and adjust traffic shares according to the link statuses. If scheduling cannot be completed within the set, feedback is sent to upstream nodes. Simulations demonstrate that this approach effectively leverages network path variety, improves bandwidth usage and throughput, and minimizes average data transmission time.

디지털 기술 역량이 아키텍처 혁신에 미치는 영향

This study verified the impact of digital technology capabilities on architectural innovation and the mediating role of digital leadership capabilities in order to promote competitive advantage and survival of companies through new product launches in the context of recently intensifying digital transformation. A total of 250 valid data were obtained by conducting a survey of small and medium-sized domestic ICT & telecommunications and manufacturing companies, and the Jamovi 2.3.26 application was used for hierarchical regression analysis. As a result of this study's analysis, digital technology capabilities had a positive impact on architectural innovation, and the partial mediating effect of digital leadership capabilities was confirmed in this process. This study contributes to the theoretical expansion of architectural innovation research due to the combined effect of technology and leadership in the context of digital transformation. In addition, in the digital age that brings about rapid and widespread change, a company's technical capabilities are important, but it also presented practical implications that digital transformation can be implemented more effectively by performing architectural innovation through leadership capabilities.

Stochastic performances estimate of a universal and flexible power management system for the future European electricity network

This paper presents the final results of the activities carried out by the authors to estimate the availability performances of an innovative modular power conversion architecture, developed within the UNIFLEX-PM (Universal and Flexible Power Management) EU project. The performed study also addresses the analysis of the effects on system stochastic performances deriving from basic components wear out phenomena, and the ones deriving from the adoption of different redundancy strategies and maintenance policies. The UNIFLEX-PM architecture represents an innovative solution for power management in the distribution networks, thus the reliability and availability studies have been focused on obtaining basic figures useful to define the effectiveness of the proposed solution through comparison with a power converter architecture already used for building commercial products and assumed as the reference case.

Principles of social housing development in Spain

The issue of social housing has always been a vital concern for most countries, given its crucial role in ensuring a dignified life for citizens. Each country has a unique history and approaches to the development of social housing, reflecting distinct social, economic, and cultural requirements. Spain's practice in this area, developed over a long period, is particularly appealing and can be beneficial for Ukraine, which seeks to improve its own standards of social housing construction. This article examines the architectural features of social housing formation in Spain, based on the analysis of both historical and contemporary projects. Successful examples such as the Caño Roto housing complex, a symbol of modernism and high social experience, and the contemporary housing quarter Vivazz in Asturias, emphasizing their contribution to the transformation of the urban environment and creation of comfortable spaces for different population segments, are highlighted. Special attention is given to architectural innovations, energy efficiency, and the use of public spaces as centers of social interaction. The conclusions emphasize the importance of adapting social housing to changes in requirements and the social environment, highlighting its impact on improving the quality of life and forming communities.

Innovations in architecture and the impact of architects´ mobility on their application: the case of the new building of the Slovak National Theatre in Bratislava

Innovations in architecture and the impact of architects´ mobility on their application: the case of the new building of the Slovak National Theatre in Bratislava

Tailoring Service Delivery Innovation Architecture: A Service-Dominant Logic Theory Perspective for Micro Small and Medium Enterprises

Tailoring Service Delivery Innovation Architecture: A Service-Dominant Logic Theory Perspective for Micro Small and Medium Enterprises

Bi-channel hybrid GAN attention based anomaly detection system for multi-domain SDN environment

Software-Defined Networking (SDN) is a strategy that leads the network via software by separating its control plane from the underlying forwarding plane. In support of a global digital network, multi-domain SDN architecture emerges as a viable solution. However, the complex and ever-evolving nature of network threats in a multi-domain environment presents a significant security challenge for controllers in detecting abnormalities. Moreover, multi-domain anomaly detection poses a daunting problem due to the need to process vast amounts of data from diverse domains. Deep learning models have gained popularity for extracting high-level feature representations from massive datasets. In this work, a novel deep neural network architecture, supervised learning based LD-BiHGA (Low Dimensional Bi-channel Hybrid GAN Attention) system is designed to learn class-specific features for accurate anomaly detection. Two asymmetric GANs are employed for learning the normal and abnormal network flows separately. Then, to extract more relevant features, a bi-channel attention mechanism is added. This is the first study to introduce an innovative hybrid architecture that merges bi-channel hybrid GANs with attention models for the purpose of anomaly detection in a multi-domain SDN environment that effectively handles real-time unbalanced data. The suggested architecture demonstrates its effectiveness on three benchmark datasets, achieving an average accuracy improvement of 7.225% on balanced datasets and 3.335% on imbalanced datasets compared to previous intrusion detection system (IDS) architectures in the literature.

ECRLoRa: LoRa Packet Recovery under Low SNR via Edge–Cloud Collaboration

Low-Power Wide-Area Networks (LPWANs), extensively utilized for connecting billions of IoT devices, encounter wireless interference challenges in unlicensed frequency bands. Cutting-edge research suggests employing Received Signal Strength Indication (RSSI) sequences for error detection to mitigate interference-related issues. Nevertheless, the effectiveness of this method significantly declines under low signal-to-noise ratios (SNRs). Additionally, long-range communication often results in low SNR received signals, sometimes even below the noise floor. Targeting this fundamental issue, this article proposes the LPWAN packet technique, broadly applicable across diverse scenarios through edge–cloud collaboration. On the edge side, we propose an innovative architecture that fully exploits spatial distribution and interference independence in the field. Rather than utilizing resource-intensive RSSI-based error detection, we leverage a lightweight coding scheme for error detection at the Long Range (LoRa) edge, forwarding correct frames to the cloud. On the cloud side, packet recovery is achieved utilizing group-weighted voting. We design and implement ECRLoRa with commercially available devices (SemTech’s SX1278 and SX1302 LoRa chipsets) and assess its performance in low SNR environments. Our thorough evaluation demonstrates that our approach attains a Packet Recovery Ratio of 96% with low SNR (i.e., below −10 dB), resulting in 1.8× throughput, 7.5× faster recovery time, and 4.92× average accuracy compared to state-of-the-art cloud-optimized application layer solutions.

Charge Carrier Dynamics at Carbon/Perovskite Interface: Implications on Carbon‐Based HTM‐Free Solar Cell Stability

Carbon‐based hole transport material (HTM)‐free perovskite solar cells (CPSCs) are an innovative device architecture that mitigates inherent challenges associated with record‐breaking perovskite solar cells (PSCs), which rely on metal/HTMs, including instability, manufacturing intricacy, and elevated costs. The photovoltaic efficiency and stability of CPSCs are profoundly influenced by the charge carrier dynamics at the interfaces. Herein, the charge carrier dynamics at the carbon(C)–perovskite interface in CPSCs and its implications on photovoltaic performances and stability, an aspect that has received limited exploration thus far are probed, are investigated using transient surface photovoltage (Tr‐SPV) and transient photoluminescence measurements. The study reveals that the C‐electrode effectively acts as a selective barrier, impeding electrons while facilitating the extraction of holes at the C–perovskite interface. This selective blocking mechanism holds significant implications for improving the performance and stability of CPSCs over HTM‐free PSCs with gold(Au) electrodes. The stability of CPSCs is evaluated by measuring shelf life, maximum power point tracking, Tr‐SPV, and X‐Ray diffraction measurements. By delving into these pivotal aspects, this work aims to contribute to the advancement and understanding of CPSCs for sustainable and efficient energy conversion.

Review of FABRIC[ated]: Fabric Innovation and Material Responsibility in Architecture

This review unravels FABRIC[ated]: Fabric Innovation and Material Responsibility in Architecture, edited by Tolya Stonorov. A timely survey of textile applications in architecture, the book positions fabric construction as a promising technology which the architectural profession can embrace in its charge to lower the environmental impacts of building. Synthesizing current discourse around low-carbon building materials and material optimization, the book crystallizes a distinct approach to sustainable design premised on lightness and flexibility.

Innovative Architectures and Management Strategies in 5G Communication Networks

The evolution of communication networks has witnessed a remarkable transformation with the advent of 5G technology. As the latest generation of cellular networks, 5G promises to revolutionize the way we connect, communicate, and interact with the digital world. This paper explores the architecture, management, and implications of 5G communication networks, shedding light on the key features, challenges, and opportunities presented by this transformative technology. At the core of 5G networks lies a sophisticated architecture designed to deliver unprecedented levels of speed, reliability, and connectivity. The 5G New Radio (NR) architecture encompasses three primary components: the User Equipment (UE), the Radio Access Network (RAN), and the Core Network (CN). These components work in tandem to facilitate seamless communication between user devices and the broader network infrastructure. One of the defining features of 5G networks is their ability to support significantly higher data speeds and lower latency compared to previous generations. With the potential to deliver data rates of several gigabits per second and latency as low as a few milliseconds, 5G opens the door to a plethora of innovative applications and services, ranging from immersive virtual reality experiences to real-time remote surgeries. Effective management of 5G networks is paramount to ensuring optimal performance, reliability, and security. Network management systems employ advanced algorithms for dynamic resource allocation, quality of service (QoS) optimization, and network slicing. Network slicing, in particular, enables operators to create virtual networks tailored to specific use cases, such as enhanced mobile broadband, massive IoT deployments, and mission-critical communications. However, the deployment and management of 5G networks pose several challenges and considerations. Infrastructure deployment requires substantial investment and coordination, while ensuring interoperability between different vendors' equipment and standards remains a pressing issue. Spectrum availability and allocation also play a critical role in determining the performance and capacity of 5G networks, necessitating careful regulatory oversight and spectrum management strategies. Despite these challenges, the implications of 5G technology are far-reaching and profound. From empowering smart cities and autonomous vehicles to enabling the widespread adoption of IoT devices and applications, 5G networks have the potential to reshape industries, drive innovation, and enhance the quality of life for billions of people around the world. 5G communication networks represent a paradigm shift in the way we connect and communicate. With their advanced architecture, dynamic management capabilities, and transformative potential, 5G networks are poised to unlock new opportunities, accelerate digital transformation, and usher in a new era of connectivity and innovation.

Innovative Architectures and Management Strategies in 5G Communication Networks

The evolution of communication networks has witnessed a remarkable transformation with the advent of 5G technology. As the latest generation of cellular networks, 5G promises to revolutionize the way we connect, communicate, and interact with the digital world. This paper explores the architecture, management, and implications of 5G communication networks, shedding light on the key features, challenges, and opportunities presented by this transformative technology. At the core of 5G networks lies a sophisticated architecture designed to deliver unprecedented levels of speed, reliability, and connectivity. The 5G New Radio (NR) architecture encompasses three primary components: the User Equipment (UE), the Radio Access Network (RAN), and the Core Network (CN). These components work in tandem to facilitate seamless communication between user devices and the broader network infrastructure. One of the defining features of 5G networks is their ability to support significantly higher data speeds and lower latency compared to previous generations. With the potential to deliver data rates of several gigabits per second and latency as low as a few milliseconds, 5G opens the door to a plethora of innovative applications and services, ranging from immersive virtual reality experiences to real-time remote surgeries. Effective management of 5G networks is paramount to ensuring optimal performance, reliability, and security. Network management systems employ advanced algorithms for dynamic resource allocation, quality of service (QoS) optimization, and network slicing. Network slicing, in particular, enables operators to create virtual networks tailored to specific use cases, such as enhanced mobile broadband, massive IoT deployments, and mission-critical communications. However, the deployment and management of 5G networks pose several challenges and considerations. Infrastructure deployment requires substantial investment and coordination, while ensuring interoperability between different vendors' equipment and standards remains a pressing issue. Spectrum availability and allocation also play a critical role in determining the performance and capacity of 5G networks, necessitating careful regulatory oversight and spectrum management strategies. Despite these challenges, the implications of 5G technology are far-reaching and profound. From empowering smart cities and autonomous vehicles to enabling the widespread adoption of IoT devices and applications, 5G networks have the potential to reshape industries, drive innovation, and enhance the quality of life for billions of people around the world. 5G communication networks represent a paradigm shift in the way we connect and communicate. With their advanced architecture, dynamic management capabilities, and transformative potential, 5G networks are poised to unlock new opportunities, accelerate digital transformation, and usher in a new era of connectivity and innovation.

Integrating nApps in 5G for Verticals: Architecture Innovation and Technology Enablers

Integrating nApps in 5G for Verticals: Architecture Innovation and Technology Enablers