System Architecture Research Articles

Low carbon scheduling method of mine integrated energy system based on two-stage P2G technology

Coal mines derive a large amount of various associated resources that can be used for production and living needs during the mining process. In order to realize the recycling of coal associated resources, a typical architecture of coal mine comprehensive energy system including the recycling of coal derived resources is proposed. Firstly, according to the coal mine resource endowment and its geological characteristics, the corresponding mine integrated energy system is constructed. Then, the refined two-stage P2G technology is combined with the mine integrated energy system to realize the complete consumption of wind and light and the efficient utilization of energy. Finally, the stepped carbon trading mechanism is used to further constrain the carbon emissions and realize the further reduction of carbon emissions in the mining area. The simulation model of the integrated mine energy system is established in MATLAB and the GUROBI solver is called to solve the results. The simulation results show that the method can effectively reduce carbon emissions, realize the complete consumption of wind and light and the efficient use of energy.

Sex-specific expression of circadian rhythms enables allochronic speciation

Abstract Noctuid moths provide prime examples of species in various stages of allochronic speciation, where reproductive barriers are mediated by genetic divergence in daily or seasonal timing. Theory indicates that allochronic divergence might be one of the most plausible mechanisms of adaptive speciation, especially when timing is subject to divergent ecological selection. Here, we show that the validity of this theoretical expectation is entirely contingent on species characteristics of the mating system. Our analysis focuses on the moth Spodoptera frugiperda (Lepidoptera, Noctuidae), which occurs as two strains that differ in circadian reproductive activity. Unlike in generic models of assortative mating, where chronotypes diverge under mild assumptions, individual-based evolutionary simulations of the mating system and life cycle of S. frugiperda fail to recover allochronic diversification, even under conditions highly conducive to speciation. Instead, we observe that both chronotypes advance their activity schedule toward the early night, resulting in a rapid loss of allochronic variation. This outcome is caused by the fact that mating in S. frugiperda takes considerable time and potential mates are encountered sequentially, so that early males enjoy a systematic advantage. The undermining effect of male mate competition can be overcome when circadian genes evolve sex-specific expression, enabling early and late chronotypes to be maintained or even to diversify in sympatry. These results give new significance to sex differences in biological rhythms and suggest that species characteristics of the mating system and genetic architecture are key to understanding the scope for allochronic speciation across diverse species exhibiting variation in timing.

Effectiveness Evaluation Method Using System of Systems Architecture Description of Aircraft Health Management in Aircraft Maintenance Program

This study proposes a system modeling method for aircraft maintenance program development that adopts condition-based maintenance using aircraft health management (AHM) based on a systems engineering approach, which considers AHM as a system of systems. The metamodel is tailored on the basis of the Unified Architecture Framework (UAF) and the NASA Systems Modeling Handbook for Systems Engineering. It is described using the modeling tool "Balus 2.0" (Levii, Inc). The applicability and effectiveness of a maintenance program adopting AHM is analyzed on the basis of the Maintenance Steering Group-3 (MSG-3), and its effectiveness is evaluated using the proposed system modeling method. The proposed method considers the uncertainty of the aircraft maintenance environment related to airline operations in addition to the uncertainty of the aircraft system. The effectiveness of the proposed system is investigated through a sample problem that considers a tire system using a pressure monitoring system as AHM based on the MSG-3 approach. Finally, the limitations of the proposed method are discussed.

An Order Statistics Perspective for System Reliability

ABSTRACTStructural reliability integrates the design variables over the safety region characterized by a positive limit state function when the reliability of the entire system is of concern. Calculating the structure function can be challenging for high‐dimensional systems or intricate system architectures. In order to enhance the efficiency of time‐dependent system reliability assessment, we emulate the integral formulation in structural reliability. To elaborate further, we treat each individual unit's lifetime variable as a design variable and subsequently perform calculations involving multiple integrals. Given the ordered nature of unit failure times, we leverage the order statistics distribution to simplify the multiple integrals into a double integral, and then multiply this result by the survival signature to obtain reliability. A two‐terminal nine‐unit network system configuration is illustrated to assess the performance and effectiveness of the proposed method.

Dynamical Viability Assessment for Habitable Worlds Observatory Targets

Exoplanetary science is increasingly prioritizing efforts toward direct imaging of planetary systems, with emphasis on those that may enable the detection and characterization of potentially habitable exoplanets. The recent 2020 Astronomy and Astrophysics decadal survey recommended the development of a space-based direct imaging mission that has subsequently been referred to as the Habitable Worlds Observatory (HWO). A fundamental challenge in the preparatory work for the HWO search for exo-Earths is the selection of suitable stellar targets. Much of the prior efforts regarding the HWO targets has occurred within the context of exoplanet surveys that have characterized the stellar properties for the nearest stars. The preliminary input catalog for HWO consists of 164 stars, of which 30 are known exoplanet hosts to 70 planets. Here, we provide a dynamical analysis for these 30 systems, injecting a terrestrial planet mass into the habitable zone (HZ) and determining the constraints on stable orbit locations due to the influence of the known planets. For each system, we calculate the percentage of the HZ that is dynamically viable for the potential presence of a terrestrial planet, providing an additional metric for inclusion of the stars within the HWO target list. Our analysis shows that, for 11 of the systems, less than 50% of the HZ is dynamically viable, primarily due to the presence of giant planets whose orbits pass near or through the HZ. These results demonstrate the impact that known system architectures can have on direct imaging target selection and overall system habitability.

Decentralized Integrity: Blockchain-Based Frameworks for Enhancing Software Update Security

This article examines the application of blockchain technology as a solution for secure and transparent software update distribution. As cyber threats evolve, traditional centralized update mechanisms face increasing vulnerabilities to tampering and unauthorized modifications. We propose a blockchain-based framework that leverages distributed ledger technology to create an immutable, decentralized environment for software updates. Our article demonstrates how this approach can eliminate single points of failure, ensure update integrity through cryptographic signing and network-wide verification, and enhance transparency in the update process. We discuss the system architecture, including update creation, distribution, and verification mechanisms, and evaluate its integration with existing software ecosystems. While acknowledging challenges such as scalability and implementation costs, we argue that blockchain-based solutions significantly advance securing software distribution. Our findings suggest that this approach has the potential to become a standard practice in the industry, substantially improving trust and reliability in software update systems. This article contributes to the growing body of research on blockchain applications in cybersecurity and provides insights for future developments in secure software distribution methods.

Blockchain‐IoT: A revolutionary model for secure data storage and fine‐grained access control in internet of things

AbstractWith the rapid expansion of the Internet of Things (IoT), cloud storage has emerged as one of the cornerstones of data management, facilitating ubiquitous access and seamless sharing of information. However, with the involvement of a third party, traditional cloud‐based storage systems are plagued by security and availability concerns, stemming from centralized control and management architectures. A novel blockchain‐IoT model that leverages blockchain technology and decentralized storage mechanisms to address these challenges is presented. The model combines the Ethereum blockchain, interplanetary file system, and attribute‐based encryption to ensure secure and resilient storage and sharing of IoT data. Through an in‐depth exploration of the system architecture and underlying mechanisms, it is demonstrated how the framework decouples storage functionality from resource‐constrained IoT devices, mitigating security risks associated with on‐device storage. In addition, data owners and users can easily exchange data with one another through the use of Ethereum smart contracts, fostering a collaborative environment and providing incentives for data sharing. Moreover, an incentive mechanism powered by the FileCoin cryptocurrency is introduced, which motivates and ensures data sharing transparency and integrity between stakeholders. Furthermore, in the proposed blockchain‐IoT model, the proof‐of‐authority system consensus algorithm has been replaced by a delegated proof‐of‐capacity system, which reduces transaction costs and energy consumption. Using the Rinkby Ethereum official testing network, the proposed model has been demonstrated to be feasible and economical, emphasizing its potential to redefine IoT data management.

Rice homolog of Arabidopsis Xylem NAC domain 1 (OsXND1), a NAC transcription factor regulates drought stress responsive root system architecture in indica rice.

Rice yield is greatly constrained by drought stress. In Arabidopsis, XYLEM NAC DOMAIN 1 (XND1) gene regulates the xylem formation, efficiency of water transport, and the delicate equilibrium between drought tolerance and resistance to pathogens. However, diversity and the role of rice homologs of OsXND1 is not reported so far. This study hypothesized that the rice homolog of OsXND1 also regulates drought stress tolerance through modulation of root architecture. Initially, phylogenetic analysis identified two OsXND1 homologs (Os02g0555300 and Os04g0437000) in rice. Further, 14 haplotypes were identified in the OsXND1 of which Hap1 and Hap3 were major haplotypes. The association analysis of OsXND1 with 16 different traits, including 10 root traits, showed three SNPs (Chr02:20972728-Promoter variant; Chr02:20972791-5' UTR variant, and Chr02:20973745-3' UTR variant) were significantly associated with root area, root surface area, total root length, and convex hull area only under drought stress in indica rice. Besides, the superior haplotype of OsXND1 increased the root area, root surface area, total root length, and convex hull area by 46%, 40%, 38%, and 42%, respectively, under drought stress conditions. Therefore, the identified superior haplotype of OsXND1 can be utilized in haplotype breeding programs for the improvement of drought tolerance in rice.

Election Voting Trend Prediction System

This paper presents the use of Bayesian networks and K-Nearest Neighbor algorithms for predicting election results. Our motivation stemmed from the complexities of the election data available, which spans over 120,000 voting locations across 36 states in Nigeria, and the requirement to develop a procedure that takes into consideration voter trends that are influenced by political parties seeking to win. The system architecture's translation was utilised, and the prototyping methodology was adopted. In order to realize the requirements, the system was designed and implemented using Java and MySQL in accordance with specifications. Since the outcome is positive, it can serve as a benchmark for further study in this field, particularly when it comes to using data mining tools to analyze election results.

NFTs for accessing, monetizing, and teleporting digital twins and digital artifacts in the metaverse

Digital twins and digital artifacts have become integral components of metaverse platforms, providing users with a rich, immersive, and interactive digital experience through the deployment of diverse digital twins and digital artifacts such as 3D avatars, images, and objects. To date, a significant challenge persists in the lack of practical mechanisms to enable seamless teleportation and cross-metaverse interoperability for these digital twins and digital artifacts. There is also a lack of trusted monetization methods that facilitate trading and leasing of digital twins and digital artifacts. To address these important challenges, this paper proposes a blockchain and Non-Fungible Token (NFT)-based solution that facilitates the integration and teleportation of these digital twins and digital artifacts by providing trusted metadata, verifying ownership, and ensuring the authenticity of digital creations in the virtual world. Key to our solution is the introduction of a bridging mechanism that enables cross-metaverse interoperability, allowing for the portable transfer of NFTs across decentralized metaverse platforms. In addition, our solution focuses on empowering original digital creators by enabling the monetization of their creations through the ownership management capabilities offered by NFTs. To reliably and securely store the metadata and content of tokenized digital twins and digital artifacts, we integrate into our solution the Interplanetary File System (IPFS), a decentralized storage system. To demonstrate the feasibility of our solution, we have developed and deployed all necessary smart contracts that govern the main functionalities and interactions of the proposed system on the Ethereum Goerli Testnet. We present our proposed system architecture, accompanied by informative sequence diagrams, algorithms, and testing details. We discuss how our proposed solution attains the main objectives outlined in the paper. We evaluate our proposed solution in terms of cost and security. We have made the complete source code of our smart contracts publicly available on GitHub.

TaNAR2.1 and TaNAR2.2 differ in influencing nitrogen uptake and growth of wheat (Triticum aestivum L.)

NAR2 (Nitrate assimilation related protein) is a protein chaperone involved in transporting nitrate across membranes. However, the expression pattern and function of NAR2 genes in wheat are still largely unknown. Here, we cloned two TaNAR2 genes (TaNAR2.1 and TaNAR2.2). To assess and compare the functional differences of TaNAR2.1 and TaNAR2.2, we analyzed the subcellular localization and expression pattern of the two genes in wheat under low nitrogen (LN) and high nitrogen (HN) conditions, as well as the nitrate influx and root system architecture of TaNAR2.1 and TaNAR2.2 overexpression wheat under LN and HN. Additionally, we investigated the effects of TaNAR2.1 and TaNAR2.2 overexpression on the growth phenotype, nitrogen uptake and yield of wheat throughout the growth period. There are significant differences in the expression patterns and functions of TaNAR2.1 and TaNAR2.2. TaNAR2.1 is located in the cytoplasm, nucleus and the plasma membrane, whereas TaNAR2.2 is a cytoplasm-specific protein. TaNAR2.1 appears to exhibit larger changes in expression levels and a higher capacity for nitrate influx than TaNAR2.2 under external nitrate supply. Overexpression of TaNAR2.1 significantly improves grain nitrogen use efficiency and increases grain yield, whereas overexpression of TaNAR2.2 enhances vegetative and reproductive growth of wheat roots. These findings indicate that TaNAR2.1 plays a crucial role in wheat nitrogen accumulation and yield, while TaNAR2.2 is pivotal for wheat root growth.

An enhanced algorithm for detection of HIAF in active distribution networks and real-time analysis

Identifying a downed conductor in distribution is challenging due to the insignificant variations in the current signal. Most of the distribution system faults are identified using overcurrent and earth fault protection. Fault path resistance decides the current magnitude while high resistance path may create timely issues in identifying a fault. Downed conductor and high resistance faults create arc in between the ground and conductor. Due to this the fault at the location is highly nonlinear with reduced magnitude. These faults are known as high impedance arcing fault (HIAF). Such faults can be identified effectively by conducting harmonic analysis of the signals. But in a modern distribution system apart from other renewable sources, the integration of electric vehicle (EV) may create HIAF detection challenges due to the inclusion of inverters and switching harmonics associated with EV. Considering the available advanced architecture of modern microgrid system, an effective solution is proposed in this work to securely detect HIAFs. The method is robust and highly reliable for HIAFs. The system stability and continuity can be unaffected with the help of the proposed method in case of various non-fault or transient/switching conditions. Comparison with other profound techniques is done to show the superiority of the proposed method.

Expanding road noise cancellation to higher frequencies

Active vehicle Road Noise Cancellation (RNC) systems effectively reduce persistent vehicle rumble and booming noise which is very difficult to control with traditional NVH measures, particularly at low frequencies. Therefore, more and more vehicles are adapting RNC systems in their production applications. Most current RNC systems cancel low frequency structure-born noise, which is typically below 400 Hz. Although it provides appreciable noise attenuation, remaining high frequency noise contents still requires mitigation for a premium cabin experience. This study targets a next generation RNC system development which extends noise cancellation frequency range up to 1 kHz. High frequency RNC system (HF-RNC) development begins with analyzing limiting factors of the current RNC systems. Theoretical and practical limitations of the current system are discussed. Then, new technology and enablers to overcome those limitations are introduced. New enablers investigated herein in includes feedforward microphones, low latency system, headrest speakers and microphones, and head tracking system. HF-RNC system architecture is defined to comprise extended features and enablers. Low latency software is ported into a development platform which is based on a commercial DSP. The new HF-RNC system demonstrates noise cancellation up to 1 kHz when applied to an electric vehicle.

Phosphate promotes Arabidopsis root skewing and circumnutation through reorganisation of the microtubule cytoskeleton.

Phosphate (Pi) plays a key role in plant growth and development. Hence, plants display a range of adaptations to acquire it, including changes in root system architecture (RSA). Whether Pi triggers directional root growth is unknown. We investigated whether Arabidopsis roots sense Pi and grow towards it, that is whether they exhibit phosphotropism. While roots did exhibit a clear Pi-specific directional growth response, it was, however, always to the left, independent of the direction of the Pi gradient. We discovered that increasing concentrations of KH2PO4, trigger a dose-dependent skewing response, in both primary and lateral roots. This phenomenon is Pi-specific - other nutrients do not trigger this - and involves the reorganisation of the microtubule cytoskeleton in epidermal cells of the root elongation zone. Higher Pi levels promote left-handed cell file rotation that results in right-handed, clockwise, root growth and leftward skewing as a result of the helical movement of roots (circumnutation). Our results shed new light on the role of Pi in root growth, and may provide novel insights for crop breeding to optimise RSA and P-use efficiency.

Model-based assembly process planning for flexible aircraft cabin architectures

AbstractThe configuration and equipment of an aircraft cabin has a significant impact on the passenger’s flight experience. To meet the needs of passengers and improve the flight experience, airlines repeatedly demand customised adaptations to the cabin design. The implementation of these changes requires a high degree of flexibility in production and can lead to difficulties in setting up a fixed final assembly line. In addition, unforeseen events and changes in the OEMs’ supply chain require a rapid response in aircraft production to be able to deliver on time. Digitalisation in product development and production planning makes it possible to overcome these challenges and makes an important contribution to flexibility, time and cost efficiency. This paper presents a digital approach to modelling and flexible planning of assembly processes of the cabin. To this end, aircraft design data is automatically linked to the assembly system to react quickly to design changes in the assembly planning process. The integration is realised in a system architecture model depicted with the systems modelling language (SysML). The architecture model follows the formal process description defined in VDI3682. A planning algorithm then uses the production architecture parameters to optimise the assembly processes, e.g. in terms of time. The approach presented is demonstrated using the example of scheduling the pre-assembly processes of the "crown module". The latter includes all structural and functional components above the window panels, such as overhead bins, electrics and air conditioning. The results show how changes in aircraft and cabin design or in the production plant and resources can be flexibly evaluated. This allows conceptual changes to be evaluated and traded before the cabin design is frozen and transferred to real production. These advantages contribute to the time and cost optimisation of aircraft production. This work thus makes a valuable contribution to the further development of digital solutions in aircraft production.

Transitioning trends into action: A simulation-based Digital Twin architecture for enhanced strategic and operational decision-making

In the dynamic realm of nowadays manufacturing, integrating digital technologies has become paramount for enhancing operational efficiency and decision-making processes. This article presents a novel system architecture that integrates a Simulation-based Digital Twin (DT) with emerging trends in manufacturing to enhance decision-making, accompanied by a detailed technical approach encompassing protocols and technologies for each component. The DT leverages advanced simulation techniques to model, monitor, and optimize production processes in real time, facilitating both strategic and operational decision-making. Complementing the DT, trending technologies such as artificial intelligence, additive manufacturing, collaborative robots, autonomous vehicles, and connectivity advancements are strategically integrated to enhance operational efficiency and facilitate the adoption of the Manufacturing as a Service (MaaS) paradigm. A case study within a MaaS supplier context, deployed in an industrial laboratory with advanced robotic systems, demonstrates the practical application of optimizing dynamic job-shop configurations using Simulation-based DT, showcasing strategies to improve operational efficiency and resource utilization. The results of the industrial experiment were highly encouraging, underscoring the potential for extension to more intricate industrial systems, with particular emphasis on incorporating sustainability and remanufacturing principles.

A Multi-Channel Urine Sensing Detection System Based on Creatinine, Uric Acid, and pH.

Urine analysis represents a crucial diagnostic technique employed in clinical laboratories. Creatinine and uric acid in urine are essential biomarkers in the human body and are widely utilized in clinical analysis. Research has demonstrated a correlation between the normal physiological concentrations of creatinine and uric acid in urine and an increased risk of hypertension, cardiovascular diseases, and kidney disease. Furthermore, the pH of urine indicates the body's metabolic processes and homeostatic balance. In this study, an integrated multi-channel electrochemical sensing system was developed, combining electrochemical analysis techniques, microelectronic design, and nanomaterials. The architecture of an intelligent medical detection system and the production of an interactive interface for smartphones were accomplished. Initially, multi-channel selective electrodes were designed for creatinine, uric acid, and pH detection. The detection range was 10 nM to 100 μM for creatinine, 100 μM to 500 μM for uric acid, and 4 to 9 for pH. Furthermore, interference experiments were also conducted to verify the specificity of the sensors. Subsequently, multi-channel double-sided sensing electrodes and function-integrated hardware were designed, with the standard equations of target analytes stored in the system's read-only memory. Moreover, a WeChat mini-program platform was developed for smartphone interaction, enabling off-body detection and real-time display of target analytes through smartphones. Finally, the aforementioned electrochemical detection electrodes were integrated with the smart sensing system and wirelessly interfaced with smartphones, allowing for intelligent real-time detection in primary healthcare and individual household settings.

Fuzzy Logic Control with Long Short-Term Memory Neural Network for Hydrogen Production Thermal Control System

In the development of decarbonization technologies and renewable energy, water electrolysis has emerged as a key technology. The efficiency of hydrogen production and its applications are significantly affected by power stability. Enhancing power stability not only improves hydrogen production efficiency and reduces maintenance costs but also ensures long-term reliable system operation. This study proposes a thermal control method that stabilizes hydrogen output by precisely adjusting the temperature of the electrolysis stack, thereby improving hydrogen production efficiency. Fluctuations in the electrolysis stack temperature can lead to instability in the hydrogen output and energy utilization, negatively affecting overall hydrogen production. To address this issue, this study introduces an innovative system architecture and a novel thermal control strategy combining fuzzy logic control with a long short-term memory neural network. This method predicts and adjusts the flow rate of chilled water to maintain the electrolysis stack temperature within a range of ±1 °C while sustaining a constant power output of 10 kW. This approach is crucial for ensuring system stability and maximizing hydrogen production efficiency. Long-term experiments have validated the effectiveness and reliability of this method, demonstrating that this thermal control strategy not only stabilizes the hydrogen production process but also increases the volume of hydrogen generated.

Optimization of solid oxide electrolysis cells using concentrated solar-thermal energy storage: A hybrid deep learning approach

The Solid Oxide Electrolysis Cell (SOEC) represents a cutting-edge solution for the conversion of CO2 and H2O into syngas, offering significant economic and environmental benefits. However, the process requires substantial high-temperature heat inputs, traditionally supplied by electricity. This study introduces a novel approach leveraging concentrated solar radiation as a renewable heat source for SOEC, addressing the challenge of its inherent fluctuations through the integration of Thermal Energy Storage (TES) systems. We propose a hybrid model that combines multi-physics simulation with a deep learning algorithm, enabling rapid optimization of the electrolysis process under real-time direct normal irradiance conditions. Our findings demonstrate that the inclusion of TES within the system architecture results in a remarkable 53 % reduction in temperature variation rate at the SOEC inlet, ensuring operational stability and efficiency. Furthermore, by fine-tuning capacity parameters, we have developed a control strategy that harmonizes efficiency with safety performance. The robustness of our system is underscored by its resilience to step changes, achieving a 75 % reduction in temperature fluctuations. This research contributes a pioneering method for the real-time optimization and control of SOEC systems, harnessing the power of TES to drive sustainable energy conversion with enhanced reliability and economic viability, facilitating precise and swift predictive capabilities even under dynamic operating conditions.

Research and Design of Intelligent Parking Management System based on the YOLO Algorithm

Given the difficulty in managing parking lots and inefficient utilization of parking spaces at university and college campuses, this paper designs an intelligent campus parking management system with functions such as license plate recognition (LPR), online parking space reservations, campus parking navigation, and mobile app payment through the parking space detection technology based on You Only Look Once (YOLO) algorithm, Internet of Things (IoT) technology, and cloud platform technology. This system obtains information relating to license plates, parking spaces, etc. from sensing nodes with the IoT technology and transmits the collected information through NB-IoT technology to a cloud platform for storage and management to facilitate information exchange between hardware and software. This paper describes the architecture of the intelligent parking management system, parking space detection technology based on the YOLOv4 algorithm, and hardware and software design of the system. The paper proposes an effective solution to parking problems facing colleges and universities. The paper concludes that the intelligent campus parking management system based on the YOLOv4 algorithm can prevent the haphazard parking of vehicles and traffic congestion at open campuses and therefore has important value for application and popularization.