System Architecture Research Articles

A Novel Rational Medicine Use System Based on Domain Knowledge Graph

Medication errors, which could often be detected in advance, are a significant cause of patient deaths each year, highlighting the critical importance of medication safety. The rapid advancement of data analysis technologies has made intelligent medication assistance applications possible, and these applications rely heavily on medical knowledge graphs. However, current knowledge graph construction techniques are predominantly focused on general domains, leaving a gap in specialized fields, particularly in the medical domain for medication assistance. The specialized nature of medical knowledge and the distinct distribution of vocabulary between general and biomedical texts pose challenges. Applying general natural language processing techniques directly to the medical domain often results in lower accuracy due to the inadequate utilization of contextual semantics and entity information. To address these issues and enhance knowledge graph production, this paper proposes an optimized model for named entity recognition and relationship extraction in the Chinese medical domain. Key innovations include utilizing Medical Bidirectional Encoder Representations from Transformers (MCBERT) for character-level embeddings pre-trained on Chinese biomedical corpora, employing Bi-directional Gated Recurrent Unit (BiGRU) networks for extracting enriched contextual features, integrating a Conditional Random Field (CRF) layer for optimal label sequence output, using the Piecewise Convolutional Neural Network (PCNN) to capture comprehensive semantic information and fusing it with entity features for better classification accuracy, and implementing a microservices architecture for the medication assistance review system. These enhancements significantly improve the accuracy of entity relationship classification in Chinese medical texts. The model achieved good performance in recognizing most entity types, with an accuracy of 88.3%, a recall rate of 85.8%, and an F1 score of 87.0%. In the relationship extraction stage, the accuracy reached 85.7%, the recall rate 82.5%, and the F1 score 84.0%.

Ameliorating Ion-Transport Resistances in Membrane Capacitive Deionization Using Patterned Ion-Exchange Membranes and Ionomer Infiltrated Electrodes

Currently, 2 billion people live in water scarce regions and 4 billion people experience water scarcity for at least 1 month per year [1]. Besides implications to the broad masses, the U.S. Marine Corps also face enormous challenges of generating potable water during squad level field missions. Reverse osmosis is the most reliable and economical process for desalinating water, but it requires piping that can tolerate large pressures and is not conducive for portable missions. Membrane capacitive deionization (MCDI) is a modular and electrified water desalination platform that does not generate significant acoustic, thermal, or electromagnetic signatures nor does it require high pressure piping. Flow-by MCDI, which is commercialized, uses electrical energy to remove ions from water. The system architecture feature two porous electrodes covered by ion-exchange membranes – the latter material is used to prevent co-ion adsorption and greater Coulombic efficiency than the variant that does not utilize ion-exchange membranes.Our previous research improved the energy efficiency of MCDI by using IEMs with lower area-specific resistance (ASR) values and porous ionic conductors in the spacer channel that augmented solution conductivity and curtailed ohmic losses. Reducing these resistances enabled the MCDI to operate at 700 mV lower cell voltage at 2 mA cm-2 current density. This is important for shrinking the size of the MCDI unit and lowering the overall capital costs.This talk presents our recent work examining ionic charge transport resistance at patterned and non-patterned ion-exchange membrane interfaces in MCDI. Membrane surface patterning increased the interfacial area between the membrane and aqueous stream promoting greater salt removal fluxes. Soft-lithography methods were used to micropattern poly(phenylene alkylene) cation exchange membranes and anion exchange membranes with systematically varied topographies (e.g., cylindrical well and line structures that vary from 9 to 20 mm). We can reduce the MCDI cell voltage by 1 V when utilizing micropatterned ion-exchange membranes and ionomer infiltrated electrodes (operating at 2 mA cm-2 with a 2000 ppm NaCl feed). This translated to a 2.4x greater energy normalized adsorbed salt (ENAS) value - a metric used to assess the energy consumption for MCDI. Our future work examines electrode materials deposited at pattern membrane interfaces to reduce interfacial transport resistances from the membrane to the electrode. This strategy has been shown to be effective in reducing charge-transfer resistances in both proton exchange membrane (PEM) and AEM fuel cells and reducing the water dissociation kinetics resistance in bipolar membranes [2-5]. References Somini Sengupta, Weiyi Cai, A Quarter of Humanity Faces Looming Water Crises, in The New York Times. 2019: United States of America.Kole, S., et al., Bipolar membrane polarization behavior with systematically varied interfacial areas in the junction region. Journal of Materials Chemistry A, 2021. 9(4): p. 2223-2238.Breitwieser, M., et al., Tailoring the Membrane-Electrode Interface in PEM Fuel Cells: A Review and Perspective on Novel Engineering Approaches. Advanced Energy Materials, 2018. 8(4).Hee-Tak Kim, T.V.R., Ho-Jin Kweon, Microstructured Membrane Electrode Assembly for direct methanol fuel cell. Journal of The Electrochemical Society, 2007. 154(10).Tomizawa, M., et al., Heterogeneous pore-scale model analysis of micro-patterned PEMFC cathodes. Journal of Power Sources, 2023. 556. Figure 1

Neural algorithm for optimization of multidimensional object controller parameters

Optimal control of multivariable systems is a complex dynamic process that minimizes the cost function to obtain the optimal control strategy. Unfortunately, for nonlinear systems, it is not possible to use the traditional linear quadratic regulator (LQR), which would be optimal over the entire range of parameter variation. The problem of nonlinear multivariable systems and their optimal control is very momentous. The solution presented in this paper is based on the application of Reinforcement Learning (RL) networks in controlling a five-degree-of-freedom overhead crane system. Additionally, unlike the classical approach, the algorithm is adapted to directly analyze tabular data of inputs and outputs of the controlled model instead of analyzing its state as feedback (model-free). Implementing the new control structure for the multivariable system improved control quality compared to the classical LQR controller with linearization at the operating point. In addition to quality, the resource indicators, which in the LQR controller are represented by the matrix R, have been significantly improved. The architecture of the neural control system is presented, ensuring that over the entire range of nonlinearity, the quality of control is preserved while reducing the cost of its resource intensity. Obtaining optimal control with reduced resources for its implementation induces a wide range of applications of such neural control in engineering systems. The effectiveness of the proposed control system has been demonstrated in simulation studies. The simulation results present the system’s excellent control performance and adaptability over the entire range of object nonlinearity. The neural algorithm resulted in significantly shorter adjustment time and better control quality with significantly less system resource consumption and increased system dynamics.

Architecture and activation mechanism of the bacterial PARIS defence system.

Bacteria and their viruses (bacteriophages or phages) are engaged in an intense evolutionary arms race1-5. While the mechanisms of many bacterial antiphage defence systems are known1, how these systems avoid toxicity outside infection yet activate quickly after infection is less well understood. Here we show that the bacterial phage anti-restriction-induced system (PARIS) operates as a toxin-antitoxin system, in which the antitoxin AriA sequesters and inactivates the toxin AriB until triggered by the T7 phage counterdefence protein Ocr. Using cryo-electron microscopy, we show that AriA is related to SMC-family ATPases but assembles into a distinctive homohexameric complex through two oligomerization interfaces. In uninfected cells, the AriA hexamer binds to up to three monomers of AriB, maintaining them in an inactive state. After Ocr binding, the AriA hexamer undergoes a structural rearrangement, releasing AriB and allowing it to dimerize and activate. AriB is a toprim/OLD-family nuclease, the activation of which arrests cell growth and inhibits phage propagation by globally inhibiting protein translation through specific cleavage of a lysine tRNA. Collectively, our findings reveal the intricate molecular mechanisms of a bacterial defence system triggered by a phage counterdefence protein, and highlight how an SMC-family ATPase has been adapted as a bacterial infection sensor.

A mobile application and system architecture for online speech training in Portuguese: design, development, and evaluation of SofiaFala

A mobile application and system architecture for online speech training in Portuguese: design, development, and evaluation of SofiaFala

The effect of dynamical interactions in stellar birth environments on the orbits of young close-in planetary systems

Abstract Stars do not form in isolation but together with other stars, and often in a clustered environment. Depending on the initial conditions in these environments, such as initial density and substructure, the distances of encounters between stars will differ. These encounters can also affect just-formed exoplanetary systems. Using N-body simulations, we show the effect of a single fly-by on a common type of exoplanetary system: close-in Super-Earths/sub-Neptunes with or without a distant Giant planet. Even a single encounter can significantly modify the architecture of these exoplanetary systems over their long lifetimes. We test fly-bys with different characteristics, such as distance and mass, and show how they perturb the inner planets long after the encounter, leading to collisions and mutual inclination excitation, which can significantly modify the observed architecture of these systems in transit. We find that our initially four-planet inner systems reduce to three or two inner planets depending on their initial separation and that the mutual inclinations of these remaining planets can be high enough to reduce the number of observable, transiting planets. In our 500 Myr simulations, we show that this reduction in the number of transiting planets due to stellar fly-bys can contribute to the observed excess of single-transit systems.

Design and optimization strategy of electricity marketing information system supported by cloud computing platform

This paper provides an in-depth discussion on the comprehensive requirements analysis, design implementation, algorithm optimization, and experimental evaluation of an electric power marketing information system, aiming to build a modern information system that is efficient, secure, and user-friendly. In the requirements analysis phase, the importance of business process optimization, data management analysis, security compliance, system integration and scalability is emphasized, while the diversified needs of end customers are considered. For the design and implementation part, the system architecture is based on microservices and cloud-native technologies to ensure high performance and security; and modularized development is achieved through Spring Boot, Vue.js and other technology stacks. For algorithm optimization, LSTM is used for power demand prediction and anomaly detection by combining integrated learning and self-encoder, which improves the prediction accuracy and anomaly identification capability. Experimental evaluation shows that the system demonstrates good performance, security and scalability in cloud computing environment, and the cost-effectiveness is significantly better than traditional deployment.

Cutting-Edge Microwave Sensors for Vital Signs Detection and Precise Human Lung Water Level Measurement

In this article, a comprehensive review is presented of recent technological advancements utilizing electromagnetic sensors in the microwave range for detecting human vital signs and lung water levels. With the main objective of improving detection accuracy and system robustness, numerous advancements in front-end architecture, detection techniques, and system-level integration have been reported. The benefits of non-contact vital sign detection have garnered significant interest across a range of applications, including healthcare monitoring and search and rescue operations. Moreover, some integrated circuits and portable systems have lately been shown off. A comparative examination of various system architectures, baseband signal processing methods, system-level integration strategies, and possible applications are included in this article. Going forward, researchers will continue to focus on integrating radar chips to achieve compact form factors and employ advanced signal processing methods to further enhance detection accuracy.

Output feedback distributed economic model predictive control for parallel system in process networks

Abstract This paper proposes a distributed economic model predictive control algorithm for parallel systems which uses only output feedback. Such parallel systems are a fundamental system architecture frequently encountered in process networks where, in many cases, the state of the plant is not measurable. Economic performance is a key consideration in the operation of such industrial plants and it is of interest to develop theoretically rigorous approaches to tackle what is a practically very relevant scenario. The competitive couplings and competitive constraints inherent in parallel systems are explicitly addressed in the proposed controller design framework. Three measures are considered for optimization of such parallel systems including an economic stage cost function, energy efficiency and tracking accuracy. An economic cost function is optimized by the resulting distributed controller which can realize global control performance while also reducing the computational time for large-scale parallel systems. Stability of the system is formally proved using the principles of dissipativity. Finally, the effectiveness of the proposed theoretical approach is verified by both numerical simulation and experimentation to demonstrate practical relevance.

Mint: Integrating scientific visualizations into virtual reality

We present an image-based approach to integrate state-of-the-art scientific visualization into virtual reality (VR) environments: the mint visualization/VR inter-operation system. We enable the integration of visualization algorithms from within their software frameworks directly into VR without the need to explicitly port visualization implementations to the underlying VR framework—thus retaining their capabilities, specializations, and optimizations. Consequently, our approach also facilitates enriching VR-based scientific data exploration with established or novel VR immersion and interaction techniques available in VR authoring tools. The separation of concerns enables researchers and users in different domains, like virtual immersive environments, immersive analytics, and scientific visualization, to independently work with existing software suitable for their domain while being able to interface with one another easily. We present our system architecture and inter-operation protocol (mint), an example of a collaborative VR environment implemented in the Unity engine (VRAUKE), as well as the integration of the protocol for the visualization frameworks Inviwo, MegaMol, and ParaView. Our implementation is publicly available as open-source software.Graphical abstract

Review of Compensation Topologies Power Converters Coil Structure and Architectures for Dynamic Wireless Charging System for Electric Vehicle

The increasing demand for wireless power transfer (WPT) systems for electric vehicles (EVs) has necessitated advancements in charging solutions, with a particular focus on speed and efficiency. However, power transfer efficiency is the major concern in static and dynamic wireless charging (DWC) design. Design consideration and improvements in all functional units are necessary for an increase in overall efficiency of the system. Recently, different research works have been presented regarding DWC at the power converter, coil structure and compensators. This paper provides a comprehensive review of power converters incorporating high-order compensation topologies, demonstrating their benefits in enhancing the DWC of EVs. The review also delves into the coupling coil structure and magnetic material architecture, pivotal in enhancing power transfer efficiency and capability. Moreover, the high-order compensation topologies used to effectively mitigate low-frequency ripple, improve voltage regulation, and facilitate a more compact and portable design are discussed. Furthermore, optimal coupling and different techniques to achieve maximum power transfer efficiency are discussed to boost magnetic interactions, thereby reducing power loss. Finally, this paper highlights the essential role of these components in developing efficient and reliable DWC systems for EVs, emphasizing their contribution to achieving high-power transfer efficiency and stability.

Developing a custom communication protocol for UAVs: Ground control station and architecture design

Robots have become a prominent research topic across various application domains in recent decades. Additionally, unmanned aerial vehicles (UAVs) are extensively used in both the military and commercial sectors, substantially reducing transaction costs and enhancing safety. Researchers have addressed secure control and communication protocols between software, firmware, and hardware components. This study focuses on the design of three critical elements: the hardware architecture, the software ground control station (GCS), and the firmware tasks within the UAV embedded system. These components are interconnected via an enhanced MAVLink protocol (EMP). Furthermore, various sensors are integrated into the UAV's peripheral devices. We discuss flight control (FC) approaches, such as proportional-integral-derivative (PID) control and the Kalman filter (KF), detailing the process of the hovering algorithm. Additionally, we explain how access is messaged and how message commands are implemented at the protocol layer. We propose a large-scale UAV system architecture suitable for commercial and military applications, supported by a real-life scenario. Experimental results demonstrate the effectiveness and efficiency of the UAV in outdoor activities. Our findings confirm that the proposed UAV architecture is a robust and efficient system in practical applications.

An efficient blockchain-based framework for file sharing

File sharing, being the foundation of the Internet, has traditionally relied on a centralized service architecture resulting in significant maintenance costs. Moreover, due to the lack of an effective file management system, instances of sensitive information going out of control and loss of confidentiality in file sharing have occurred frequently. In order to address the difficulty of tamper detection and the lack of supervision in the entire process of file transfer in the current Internet environment, this paper designs a blockchain-based system architecture for secure sharing of electronic documents. An efficient blockchain model is used in our framework, and with the help of distributed storage system and asymmetric encryption technology, file sharing can be controlled, reliable and traceable in the transfer process. Referring to existing consensus mechanisms, e.g., Delegated Proof of Stake (DPoS) and Practical Byzantine Fault Tolerance (PBFT), we propose a new consensus for efficient and secure file sharing. Our experimental results show that our framework can maintain a higher throughput than existing schemes

Earth-like planets hosting systems: Architecture and properties

The discovery of Earth-like planets is a major focus of current planetology research and faces a significant technological challenge. Indeed, when it comes to detecting planets as small and cold as the Earth, the cost of observation time is massive. Understanding in what type of systems Earth-like planets (ELPs) form and how to identify them is crucial for preparing future missions such as PLATO, LIFE, or others. Theoretical models suggest that ELPs predominantly form within a certain type of system architecture. Therefore, the presence or absence of ELPs could be inferred from the arrangement of other planets within the same system. This study aims to identify the profile of a typical system that harbours an ELP by investigating the architecture of systems and the properties of their innermost detectable planets. Here, we introduce a novel method for determining the architecture of planetary systems and categorising them into four distinct classes. We then conduct a statistical study to identify the most favourable arrangements for the presence of an ELP. Using three populations of synthetic planetary systems generated using the Bern model around three different types of stars, we studied the `theoretical' architecture (the architecture of a complete planetary system) and the `biased' architecture (the architecture of a system in which only detectable planets are taken into account after applying an observation bias) of the synthetic systems. To describe a typical system hosting an ELP, we initially examined the distribution of ELPs across different categories of architectures, highlighting the strong link between planetary system architecture and the presence of an ELP. A more detailed analysis was then conducted, linking the biased architecture of a system with the physical properties of its innermost observable planet to establish the most favourable conditions for the presence or absence of an ELP in a system. First, using synthetic systems, we successfully reproduce the distribution of observed multi-planet systems within the five different architectural classes. This demonstrates the relevance, at the system level, of populations of the synthetic systems derived from the Bern model and the observational bias applied. Secondly, the biased architectures (with observation bias) correspond for the most part to the theoretical architectures (without bias) of the same system. Finally, the biased architecture of a system, studied in conjunction with the mass, radius, and period of the innermost detectable planet, appears to correlate with the presence or absence of an ELP in the same system. We conclude that the detections of ELPs can be predicted thanks to the already known properties of their systems, and we present a list of the properties of the systems most likely to host such a planet.

A Champernowne Adaptive Filter-Based Control of Grid Interactive Solar PV with Power Quality Enrichment

This work presents a variable step Champernowne Adaptive Filter (VS-CAF) based control architecture for a grid-integrated solar photovoltaic system. The control structure is implemented to successfully synchronize the two-stage solar photovoltaic at the point of common coupling where the source and domestic loads are connected. The control architecture ensures solar power injection and improvised power quality at the unity power factor. Moreover, the control structure provides only the balanced positive sequence fundamental sinusoidal source currents at solar irradiation alteration and load disturbances. The VS-CAF is exploited to estimate the peak of the fundamental component out of the harmonics-rich domestic load currents. To examine the efficacy of the suggested control technique, a 40 kW solar photovoltaic is simulated using MATLAB/Simulink. The performance assessment of the grid-tied solar generation system is carried out at solar irradiation alteration, zero solar irradiation, and detachment of one phase of the three-phase load. Various simulation results are carried out to verify the successful integration of solar photovoltaics into the three-phase grid following the IEEE-519 standard and satisfactory performance during various working conditions. Moreover, the simulation results are also verified with real-time results taken from the Opal-RT simulator.

Cyber-Physical Distributed Intelligent Motor Fault Detection.

This research paper explores the realm of fault detection in distributed motors through the vision of the Internet of electrical drives. This paper aims at employing artificial neural networks supported by the data collected by the Internet of distributed devices. Cross-verification of results offers reliable diagnosis of industrial motor faults. The proposed methodology involves the development of a cyber-physical system architecture and mathematical modeling framework for efficient fault detection. The mathematical model is designed to capture the intricate relationships within the cyber-physical system, incorporating the dynamic interactions between distributed motors and their edge controllers. Fast Fourier transform is employed for signal processing, enabling the extraction of meaningful frequency features that serve as indicators of potential faults. The artificial neural network based fault detection system is integrated with the solution, utilizing its ability to learn complex patterns and adapt to varying motor conditions. The effectiveness of the proposed framework and model is demonstrated through experimental results. The experimental setup involves diverse fault scenarios, and the system's performance is evaluated in terms of accuracy, sensitivity, and false positive rates.

Design of control system for seawater total alkalinity in-situ analyzer

Abstract To address the inadequacies of traditional seawater total alkalinity detection methods, which fail to meet the demands for continuous on-site monitoring at sea, a seawater total alkalinity analyzer based on single-point titration and spectrophotometry has been developed. This paper focuses on the design of the analyzer’s system architecture, hardware, and control systems. The instrument adopts a modular design concept and utilizes microfluidic technology for detection, with the STM32 serving as the control core. Through the design of the control system for the detection instrument, accurate in-situ automatic measurement of seawater total alkalinity is achieved. Laboratory testing and analysis demonstrate that the instrument’s measurement relative error is less than 1%, satisfying the accuracy requirements for seawater total alkalinity measurement. This research provides critical monitoring data support for a timely understanding of marine ecological environments and the marine carbon cycle.

Enhancing 5G network performance through effective resource management with network slicing

The immense growth of mobile networks leads to versatile applications and new demands. The improved concert, transferability, flexibility, and performance of innovative network services are applied in diversified fields. More unique networking concepts are incorporated into state-of-the-art mobile technologies to expand these dynamic features further. This paper presents a novel system architecture of slicing and pairing networks with intra-layer and inter-layer functionalities in 5th generation (5G) mobile networks. The radio access network layer slices and the core network layer slices are paired up using the network slicing pairing functionalities. The physical network elements of such network slices will be logically assigned entities called softwarization of the network. Such a novel system architecture called network sliced softwarization of 5G mobile networks (NSS-5G) has shown better performances in terms of end-to-end delay, total throughput, and resource utilization when compared to traditional mobile networks. Thus, effective resource management is achieved using NSS-5G. This study will pave the way for future softwarization of heterogeneous mobile applications.

Photo-dynamical characterisation of the TOI-178 resonant chain

Context. The TOI-178 system consists of a nearby, late-K-dwarf with six transiting planets in the super-Earth to mini-Neptune regime, with radii ranging from to 2.9 R⊕ and orbital periods between 1.9 and 20.7 days. All the planets, but the innermost one, form a chain of Laplace resonances. The fine-tuning and fragility of such orbital configurations ensure that no significant scattering or collision event has taken place since the formation and migration of the planets in the protoplanetary disc, thereby providing important anchors for planet formation models. Aims. We aim to improve the characterisation of the architecture of this key system and, in particular, the masses and radii of its planets. In addition, since this system is one of the few resonant chains that can be characterised by both photometry and radial velocities, we propose to use it as a test bench for the robustness of the planetary mass determination with each technique. Methods. We performed a global analysis of all the available photometry from CHEOPS, TESS and NGTS, and radial velocity from ESPRESSO, using a photo-dynamical modelling of the light curve. We also tried different sets of priors on the masses and eccentricity, as well as different stellar activity models, to study their effects on the masses estimated by transit-timing variations (TTVs) and radial velocities (RVs). Results. We demonstrate how stellar activity prevents a robust mass estimation for the three outer planets using radial velocity data alone. We also show that our joint photo-dynamical and radial velocity analysis has resulted in a robust mass determination for planets c to 𝑔, with precision of ~ 12% for the mass of planet c, and better than 10% for planets d to 𝑔. The new precisions on the radii range from 2 to 3%. The understanding of this synergy between photometric and radial velocity measurements will be valuable for the PLATO mission. We also show that TOI-178 is indeed currently locked in the resonant configuration, librating around an equilibrium of the chain.

Quality attributes of software architecture in IoT-based agricultural systems

Software architecture forms the cornerstone for achieving and ensuring various software quality attributes. It encompasses the collected requirements of the product, serving as a blueprint that delineates quality features for all project stakeholders, along with methods for measurement and control. Despite the significant increase in IoT-based agricultural systems, there is a dearth of studies on the quality elements of their software architecture. To address this need, this study offers an overview of components and services tailored to address specific quality attributes pertinent to agriculture systems. It identifies, investigates, and presents quality attributes influencing the design of software architecture for IoT-based agriculture systems. This paper identified and discussed several quality attributes, including performance, scalability, flexibility, interoperability, productivity, extensibility, and security, and mapped them to corresponding components of the IoT-based agriculture software architecture. Also, several issues were identified and discussed for the software architecture quality of IoT-based agriculture systems, such as real-time processing and interoperability due to the various devices and protocols utilized in these systems. The findings of this study offer valuable insights for developing, executing, and refining IoT-based agricultural systems to fulfill the changing requirements of the agriculture industry.