System Architecture Research Articles

Mechanisms of Monetary Cooperation in BRICS: First Results and New Challenges

The issues of creating a more equitable global monetary and financial system have been constantly in the focus of the BRIC countries since 2006. Gradual introduction of unprecedented restrictive measures against one of the participants – Russia – forced member states to intensify the work on diminishing their dependence on actions of the United States, searching for alternative ways of payment for goods and services and reducing transactions in US dollars. The article analyses prerequisites for development of monetary cooperation within BRICS and implications of the measures already taken in this direction. The extent to which introduction of a common currency can contribute or, on the contrary, create barriers to deepening economic integration within BRICS is explored. The experience of introducing euro in the EU shows that the decision on joining a common currency is not just an economic, but also a political one. Ignoring the risks associated with a radical change in payment systems can lead to serious disruptions in the world economy and push exporters and importers away from implementation of agreements reached at the highest level. The authors come to the conclusion that speeding up currency cooperation without relying on comprehensive consideration of the interests of BRICS countries and assessment of potential costs and benefits can lead to deterioration of the terms of mutual trade against the backdrop of the US attempts to maintain the existing architecture of global monetary system with absolute domination of the US dollar.

Modeling for underground logistics system in the Korean metropolitan area

This study evaluated the development and validation of an integrated operational model for the Underground Logistics System (ULS) in South Korea’s metropolitan area, aiming to address challenges in urban logistics and freight transportation by highlighting the potential of innovative logistics systems that utilize underground spaces. This study used conceptual modeling to define the core concepts of ULS and explored the system architecture, including cargo handling, transportation, operations and control systems, as well as the roles of cargo crews and train drivers. The ULS operational scenarios were verified through model simulation, incorporating both logical and temporal analyses. The simulation outcomes affirm the model’s logical coherence and precision, emphasizing ULS’s pivotal role in boosting logistics efficiency. Thus, ULS systems in Korea offer prospects for elevating national competitiveness and spurring urban growth, underscoring the merits of ULS in navigating contemporary urban challenges and championing sustainability.

ClearDepth: a simple, robust, and low-cost method to assess root depth in soil.

Root depth is a major determinant of plant performance during drought and a key trait for strategies to improve soil carbon sequestration to mitigate climate change. While the model Arabidopsis thaliana offers numerous advantages for studies of root system architecture and root depth, its small and fragile roots severely limit the use of the methods and techniques currently available for such studies in soils. To overcome this, we have developed ClearDepth, a conceptually simple, non-destructive, sensitive, and low-cost method to estimate the root depth of Arabidopsis in relatively small pots that are amenable to mid- and large-scale studies. In our method, the root system develops naturally inside of the soil, without considerable space constraints. The ClearDepth parameter wall root shallowness (WRS) quantifies the shallowness of the root system by measuring the depth of roots that reach the transparent walls of clear pots. We show that WRS is a robust and sensitive parameter that distinguishes deep root systems from shallower ones while also capturing relatively smaller differences in root depth caused by the influence of an environmental factor. In addition, we leveraged ClearDepth to study the relation between lateral root angles measured in non-soil systems and root depth in soil. We found that Arabidopsis genotypes characterized by steep lateral roots in transparent growth media produce deeper root systems in the ClearDepth pots. Finally, we show that ClearDepth can also be used to study root depth in crop species like rice.

Rapidly developing NLP applications for content curation

AbstractTime and again we are faced, in a number of collaborative research projects, with the challenge of interconnecting various language processing tools to implement certain industry-driven use cases focusing, for the most part, upon digital content curation processes. In this paper we first describe several of the relevant projects and their technology platforms, followed by a description of the corresponding use cases and their requirements. The content curation platform we focus upon in this article and which has been implemented as a prototype makes use of a large number of NLP services, which we also build upon for other use cases and prototypes. In addition to the implemented NLP services, the article presents a workflow manager for the flexible creation and customisation of processing workflows that make use of the above mentioned NLP services. Based on the four key principles of generality, flexibility, scalability and efficiency, we present the first version of the workflow manager by providing details on its custom definition language, explaining the communication components and the general system architecture and setup. The paper also addresses challenges in interoperability across different NLP tasks and hardware-based resource use.

Radii, masses, and transit-timing variations of the three-planet system orbiting the naked-eye star TOI-396

TOI-396 is an F6\,V bright naked-eye star ($V$\,approx \,6.4) orbited by three small ($R_p$\,approx \,2 $R_ transiting planets discovered thanks to space-based photometry from two sectors. The orbital periods of the two innermost planets, namely TOI-396\,b and c, are close to the 5:3 commensurability ($P_b$\,sim \,3.6\,d and $P_c$\,sim \,6.0\,d), suggesting that the planets might be trapped in a mean motion resonance (MMR). To measure the masses of the three planets, refine their radii, and investigate whether planets b and c are in MMR, we carried out radial velocity (RV) observations of TOI-396 and retrieved archival high-precision transit photometry from four sectors. We extracted the RVs via a skew-normal fit onto the cross-correlation functions and performed a Markov chain Monte Carlo joint analysis of the Doppler measurements and transit photometry, while employing the breakpoint method to remove stellar activity from the RV time series. We also performed a transit timing variation (TTV) dynamical analysis of the system and simulated the temporal evolution of the TTV amplitudes of the three planets following an N-body numerical integration. Our analysis confirms that the three planets have similar sizes ($R_b=2.004_ oplus $; $R_c=1.979_ oplus $; $R_d=2.001_ oplus $) and is thus in agreement with previous findings. However, our measurements are sim \,1.4 times more precise thanks to the use of two additional sectors. For the first time, we have determined the RV masses for TOI-396\,b and d, finding them to be oplus $ and $M_d=7.1 oplus $, which implies bulk densities of $ $ and $ $, respectively. Our results suggest a quite unusual system architecture, with the outermost planet being the densest. Based on a frequency analysis of the activity indicators and light curves, we find the rotation period of the star to be $ d, in agreement with the value predicted from $ R'_ HK $-based empirical relations. The Doppler reflex motion induced by TOI-396\,c remains undetected in our RV time series, likely due to the proximity of the planet's orbital period to the star's rotation period. We also discovered that TOI-396 b and c display significant TTVs. While the TTV dynamical analysis returns a formally precise mass for TOI-396\,c of c dyn oplus $, the result might not be accurate, owing to the poor sampling of the TTV phase. We also conclude that TOI-396\,b and c are close to but out of the 5:3 MMR. A TTV dynamical analysis of additional transit photometry evenly covering the TTV phase and super-period is likely the most effective approach for precisely and accurately determining the mass of TOI-396\,c. Our numerical simulation suggests TTV semi-amplitudes of up to five hours over a temporal baseline of sim \,5.2 years, which should be duly taken into account when scheduling future observations of TOI-396.

An Optimization Method for Manned/Unmanned Aerial Vehicle Collaborative Operation System Architecture Based on PGQNSGA-II

The architecture of the Manned/Unmanned Aerial Vehicle Collaborative Operation System (MAV/UAV COS) is crucial for improving combat effectiveness and resource utilization efficiency. Optimizing this architecture involves managing complex, interdependent components, which presents a constrained multi-objective optimization challenge. Initially, the elements of the MAV/UAV COS architecture were analyzed and formally expressed, transforming the architecture optimization problem into a multi-objective optimization problem, with the objectives of maximizing total system effectiveness, command-and-control performance, and system execution performance. Constraints were formulated based on mission and payload information. Subsequently, a Quantum Non-Dominated Sorting Genetic Algorithm based on Preference Guidance (PGQNSGA-II) was developed, incorporating an adaptive quantum gate mechanism based on preference information to enhance chromosome updating, ensuring that the probability amplitude of quantum bits aligns more closely with the optimal chromosome. The simulation results demonstrate that the proposed PGQNSGA-II algorithm significantly enhances the global search capability and efficiency compared to traditional quantum genetic algorithms, making it well-suited for optimizing MAV/UAV COS architectures.

Infrastructure and Tools for Testing the Vulnerability of Control Systems to Cyberattacks: A Coal Mine Industrial Facility Case

Testing the vulnerability of information systems to cyberattacks is essential to ensure the operational security of organizations and industrial processes. In particular, it is essential to ensure the resilience of industrial processes, as a possible cyberattack can lead to process malfunctions and even process shutdowns, which can lead to substantial economic losses. The possibility of various attacks, e.g., ransomware, phishing, or advanced persistent threats (APTs), requires the evaluation of the effectiveness of cyberattack detection and incident response mechanisms. In industry, it is often impossible to carry out this type of test without risking system disruption, making it difficult to assess the true effectiveness of security features. This article discusses the issues concerned with testing the cyber resilience of a system operating in a real coal mine. First, this work briefly presents the hardware and software architecture used in the coal mine. Secondly, it describes the problem of replicating a real system in the laboratory and the necessary tools and methods used to implement a resilient system architecture. Finally, the scenarios of cyberattacks are detailed, and the obtained results are discussed.

Magmatic evolution and architecture of an oceanic intraplate volcano: Vesteris Seamount, Atlantic Ocean

Vesteris is a large (33 × 27 km) and young (summit age: 0.65–0.010 Ma) intraplate seamount in the Greenland Sea, formed from ocean island basalt (OIB) magmatism. The volcano is composed of alkali basalt, basanite/tephrite, phonotephrite, mugearite, and benmoreite. Its phenocryst assemblage includes clinopyroxene, plagioclase, olivine, amphibole, rare haüyne, and oxides (Ti–magnetite and Cr–spinel), with phenocrysts hosting inclusions of apatite, sulfides (pyrrhotite), and melt. Despite its geological significance, the processes governing magma storage, ascent, and eruption dynamics remain poorly understood. To address this, we conducted detailed micro–chemical analyses of phenocrysts, groundmass microcrysts, melt inclusions, and groundmass glass. Using mineral–melt thermobarometry, we characterized the pre– to syn–eruptive crystallization conditions and reconstructed the architecture of the volcanic plumbing system. Our findings indicate that basanite liquids were primarily stored in the upper mantle (∼6.4 kbar; ∼22 km depth) with evidence of multi-level storage extending to ∼9 kbar (∼30 km depth). Textural and compositional zoning in clinopyroxenes suggests rapid magma ascent, while mafic recharge emerged as a key mechanism for remobilizing evolved clinopyroxene mush. Mafic recharge magmas also introduced early olivine crystals, which were later overgrown by high-Mg clinopyroxene upon mixing with more evolved melts. These results demonstrate that major crystal fractionation occurs in the upper mantle beneath Vesteris, resembling processes observed in low-flux ocean island basalt volcanoes. The evidence for rapid magma ascent highlights the dynamic nature of magma movement within the plumbing system, driven by mafic recharge and crystal-melt interactions.

Innovative Approaches to System Architecture in Modern Engineering Applications

Innovative Approaches to System Architecture in Modern Engineering Applications

Enhancing efficiency and sustainability in construction: a product configurator for customizable off-site building solutions

ABSTRACT Research on expert systems and configurators has gained momentum in manufacturing. Although comparable approaches in construction date back to early 70s, literature on the application of configurators in the construction industry remains few and far between, and existing configurators do not benefit from knowledge transfer/integration from manufacturing. This study utilizes design science research method with case study as an exploratory research instrument to develop a configurator to enable co-design and automate sales and production of a modular annex building typology. The technical development of the garage configurator along with an algorithm to customize the garage structure, realize and personalize the 3D model, detail the connections, and generate off-site production documents and assembly details have been explored. The configurator is based on a three-tier distributed system architecture that demonstrates the potential of a fully automated tool to engineer the value chain. Preliminary results indicate that the configurator facilitates more effective data handling, reduces delivery time and resources, and enables more effective management of materials for the company with potentially measurable contributions to waste reduction and circular economy.

Planet Mass Function around M Stars at 1–10 au: A Plethora of Sub-Earth Mass Objects

Small planets (≲1 M ⊕) at intermediate orbital distances (∼1 au) represent an uncharted territory in exoplanetary science. The upcoming microlensing survey by the Nancy Grace Roman Space Telescope will be sensitive to objects as light as Ganymede and unveil the small planet population at 1–10 au. Instrumental sensitivity to such planets is low, and the number of objects we will discover is strongly dependent on the underlying planet mass function. In this work, we provide a physically motivated planet mass function by combining the efficiency of planet formation by pebble accretion with the observed disk mass function. Because the disk mass function for M dwarfs (0.4–0.6 M ⊙) is bottom heavy, the initial planet mass function is also expected to be bottom heavy, skewing toward Ganymede and Mars mass objects, more so for heavier initial planetary seeds. We follow the subsequent dynamical evolution of planetary systems over ∼100 Myr varying the initial eccentricity and orbital spacing. For initial planet separations of ≥3 local disk scale heights, we find that Ganymede and Mars mass planets do not grow significantly by mergers. However, Earth-like planets undergo vigorous merging and turn into super-Earths, potentially creating a gap in the planet mass function at ∼1 M ⊕. Our results demonstrate that the slope of the mass function and the location of the potential gap in the mass function can probe the initial architecture of multiplanet systems. We close by discussing implications on the expected difference between bound and free-floating planet mass functions.

A novel reverse and forward directional relaying scheme in six phase overhead transmission lines using adaptive neuro-fuzzy inference system

Recent power system is structurally difficult and is vulnerable to undesirable conditions like transmission faults. In this event of transmission line faults, exact fault zone detection enhances the restoration process, thus improving reliability of the complete power system. In order to solve the above problem, this paper presents an adaptive neuro-fuzzy inference system (ANFIS) based fault zone detector, which combines artificial neural network (ANN) and fuzzy logic technique (FLT) in six phase overhead transmission lines (SPOTL). To overcome the limitation of ANN and fuzzy expert system (FES) architectures and, the selection work has been formulated as an optimization method and solved using ANFIS. The inputs are the zero sequence component currents at the middle bus of the transmission line. The training data are extracted using discrete Fourier transform and collected, and then ANFIS is trained to identify the fault zone. The ANFIS based scheme reach setting has been checked for various types of faults, with a wide range of faults and transmission line parameters. Simulation study ensure that this method has a high reach setting, does not require the design of communication channel. Further, the ANFIS study shows that ANFIS is suitable for all type of faults. The ANFIS significantly outperforms other techniques proposed in the literature in terms of various evaluation metrics.

Soil Organic Matter Influences Citrus Growth, Nutrient Uptake, and Root System Architecture

Florida citrus production faces multiple challenges, including low nutrient retention, low soil organic matter (SOM) and, more importantly, the devastating impacts of citrus greening, which is a bacterial disease that impacts root growth and nutrient uptake. Growers are exploring management practices to improve SOM and hoping to enhance tree health, nutrient uptake, and yield. Despite these efforts, research of the effects of SOM on citrus root systems and nutrient absorption remains limited, particularly that defining a target SOM range for optimal production. This study investigated the influence of varying SOM levels on citrus tree root system architecture, biomass, and nutrient uptake. This experiment was conducted in a greenhouse where 1-year-old ‘US-942’ rootstocks were assigned to a completely randomized experimental design and exposed to one of six experimental treatments with differing levels of SOM as the growing media [0% (control), 1%, 2%, 3%, 5%, or >10% (100% compost)]. Each pot was considered an experimental unit and replicated six times (n = 6), for a total of 36 seedlings. The results indicated that although root biomass did not change significantly, lower SOM levels resulted in longer roots with greater surface area and volume, likely because of increased soil exploration for nitrogen. Higher SOM treatments, however, showed improved leaf nutrient content, with increased nitrogen, phosphorus, and potassium uptake. In conclusion, the results of this study indicate that 3% SOM may be ideal for citrus because it positively impacted both root system architecture and nutrient uptake, which are both of primary concern because of citrus greening. Further research is necessary to establish critical SOM thresholds and evaluate the effects under field conditions and in combination with different irrigation and fertilizer regimes.

Information system architecture for healthcare company based on TOGAF

Information system architecture for healthcare company based on TOGAF

Hybrid manufacturing thermal environment cycle and industrial economic transformation based on artificial intelligence

With the continuous development of global manufacturing, hybrid manufacturing has become an important way to improve production efficiency and respond to market demand. However, traditional manufacturing enterprises face many challenges in thermal environment management and energy consumption, and urgently need to achieve transformation and upgrading through artificial intelligence technology. This article aims to explore the thermal environment cycle of hybrid manufacturing based on artificial intelligence and its impact on industrial economic transformation, in order to provide theoretical support and practical guidance for manufacturing enterprises in intelligent manufacturing and energy management. We have researched and designed an intelligent manufacturing system, clarified the design principles and requirements of the system, constructed the system architecture, and designed the functional modules in detail. By collecting and processing data, using intelligent scheduling prediction technology to simulate the thermal environment of the manufacturing workshop, and then simulate the energy consumption situation. Finally, a manufacturing workshop scheduling model was constructed, process optimization strategies were proposed, and the transformation path of industrial economy was explored. Research has shown that through the implementation of intelligent manufacturing systems, the energy consumption of manufacturing workshops is significantly reduced, the thermal environment is effectively improved, and the application of process optimization and scheduling models greatly improves production efficiency. The exploration of the path of industrial economic transformation provides new ideas for the sustainable development of enterprises in the new situation.

Navify: Smart Shopping Application

The Smart Shopping Application project aims to enhance the shopping experience in large retail stores by integrating indoor navigation and personalized assistance. It employs an Indoor Positioning System (IPS) using Bluetooth Low Energy (BLE) beacons/RFID for real-time shopper tracking and optimized pathfinding. This project bridges the gap between the convenience of e-commerce and traditional shopping, offering a seamless, efficient, and satisfying shopping experience for customers. The paper outlines the system's Architecture, implementation, and future scope.

Empowering Access to Justice through Automated Legal Case Management

This article presents an analytical framework for understanding automated legal case management systems, specifically focusing on Pega's implementation across public defense organizations. A comprehensive examination of system architecture and empirical evidence gathered from multiple jurisdictions demonstrates how workflow automation and intelligent case routing can substantially enhance case processing efficiency while reducing operational costs. This article examines implementation patterns across immigration, family law, and public defense sectors, revealing significant improvements in case management efficiency. This article indicates that automated case management systems markedly improve access to legal services for underserved communities, demonstrated through substantial reductions in case backlogs and increased case handling capacity. A novel framework is used to evaluate legal automation systems that consider technical performance and societal impact metrics. This article extends the current understanding of legal technology implementation by providing detailed insights into system architecture, data flow optimization, and social impact assessment. This article reveals that properly implemented automation systems can transform public legal services, creating more equitable access to justice while maintaining high standards of legal service delivery

JET CODAS - the final status

The JET Control and Data Acquisition System (CODAS) has stood the test of time and seen us through to the end of JET plasma operations in 2023. The system architecture has remained largely un-changed over the last decade or so although many new diagnostics and control systems have been added and the volume of data collected has grown massively. CAMAC remains at the heart of the system, particularly for continuous acquisition and control for much of the traditional, stable parts of the system. However, most of the newer diagnostics and control systems are network attached. The CAMAC interface was changed, about a decade ago, to remove the serial highway driver from the subsystem host so that the subsystem hosts could be virtualised and run on more powerful Oracle/Sun hosts, with the Serial Highway driver running on legacy sub-system host network attached. Other significant changes have been the development of a standard, web-based interface for control and data acquisition for diagnostics, the adoption of EPICS for several diagnostics and plant control along with integration into CODAS and the adoption of the ITER SDN protocols over ethernet to supplement the original ATM based real time control infrastructure.These developments were driven by the increased monitoring and machine protection requirements for the ITER Like Wall and the enhanced requirements for the high power Tritium Campaigns (DTE2 and DTE3). The latter, including significant expansion of the neutron and gamma diagnostics, along with expansion of the Tritium introduction systems and enhanced control systems. Towards the end of plasma operations, the requirement for the Laser Induced Desorption with Quadrupole Mass Spectroscopy (LIDS-QMS) involved significant development work to incorporate the associated control and data acquisition systems together with pushing the mode of operation for JET Pulses. At the very end of plasma operations, the requirements for long pulse operation also pushed the pulse operating mode. We now progress to Decommissioning and Repurposing JET and CODAS continues to be adapted to support the diminishing number of systems required to support the plant that is still operational and support diagnostic calibration later this year.

Development of the architecture of a computer aided diagnosis system in medicine

With the development of information technology, automation of various production processes is an urgent task, and medical diagnostics is no exception. In recent decades, artificial intelligence and information technology have been widely used in computer diagnostic systems. However, as technology advances, so do the challenges. Not every system is optimized and fast, and traditional methods are fading into the background. Often, systems do not use cloud technologies and have unoptimized architectures. This all affects their performance and, accordingly, is an urgent problem. The study analyzes the methods used in computer diagnostic systems and compares them in terms of advantages and disadvantages. The scientific works related to computer diagnostic systems in medicine for specific tasks are analyzed. The existing architectures of computer diagnostic systems are analyzed, which made it possible to identify the use of consistent approaches to diagnosis. Based on the analyzed data, the purpose, objectives, object and subject of the study are determined. A new architecture has been developed that uses the capabilities of U-Net for image segmentation and convolutional neural networks for medical image classification. The developed architecture is designed to increase the speed and automation of diagnostic processes through the use of neural networks and, accordingly, reduce human intervention. The scientific novelty of the developed architecture lies in the parallel execution of medical image segmentation and classification tasks, which gives a potential increase in data processing speed, and in the availability of an image generator, which solves the problem of lack of test data for model training.

Fault-tolerant hierarchical energy management system for an electrical power system on more-electric aircraft

The concept of More-Electric Aircraft (MEA) has the potential to improve the environmental, economic, and reliability performance in the energy and transportation sectors. To achieve this potential, it has become a tendency to develop complex architectures of Electrical Power Systems (EPSs) for MEA to supply increasing electrical power demands. Moreover, a reliable and intelligent Energy Management System (EMS) is critical to coordinate the various EPS subsystems to ensure safe and efficient flight, following the real-time EPS operating requirements and safety criteria, while reducing the operating costs for all flight stages. This paper presents a fault-tolerant hierarchical EMS, for an innovative multi-converter-based aircraft EPS, to configure the system, ensure power distribution, and manage energy storage in multiple faulty scenarios over different time scales. There are two levels in this EMS: The High Level (HL) is based on Model Predictive Control (MPC), formulated by Mixed-Integer-Linear-Programming (MILP), to optimise the long-term EPS performance while considering future predictions; The Low Level (LL) adopts deterministic rules to cope with load changes and fault occurrences over the short term, during the HL sample intervals, with a faster clock. In particular, the LL controller contains four modes: to either cooperate with the HL online MPC or to operate independently, in either EPS normal or faulty conditions. The proposed EMS is evaluated in two cases, firstly considering load deviations in a normal operating scenario, and then considering behaviour in fault scenarios. The results indicate that the proposed EMS successfully reduces the EPS operational costs while ensuring quick responses to dynamic changes with either EPS component faults or EMS internal faults.