System Model Research Articles

Hippocampal storage and recall of neocortical "What"-"Where" representations.

A key question for understanding the function of the hippocampus in memory is how information is recalled from the hippocampus to the neocortex. This was investigated in a neuronal network model of the hippocampal system in which "What" and "Where" neuronal firing rate vectors were applied to separate neocortical modules, which then activated entorhinal cortex "What" and "Where" modules, then the dentate gyrus, then CA3, then CA1, then the entorhinal cortex, and then the backprojections to the neocortex. A rate model showed that the whole system could be trained to recall "Where" in the neocortex from "What" applied as a retrieval cue to the neocortex, and could in principle be trained up towards the theoretical capacity determined largely by the number of synapses onto any one neuron divided by the sparseness of the representation. The trained synaptic weights were then imported into an integrate-and-fire simulation of the same architecture, which showed that the time from presenting a retrieval cue to a neocortex module to recall the whole memory in the neocortex is approximately 100 ms. This is sufficiently fast for the backprojection synapses to be trained onto the still active neocortical neurons during storage of the episodic memory, and this is needed for recall to operate correctly to the neocortex. These simulations also showed that the long loop neocortex-hippocampus-neocortex that operates continuously in time may contribute to complete recall in the neocortex; but that this positive feedback long loop makes the whole dynamical system inherently liable to a pathological increase in neuronal activity. Important factors that contributed to stability included increased inhibition in CA3 and CA1 to keep the firing rates low; and temporal adaptation of the neuronal firing and of active synapses, which are proposed to make an important contribution to stabilizing runaway excitation in cortical circuits in the brain.

Air‐Ice‐Ocean Coupling During a Strong Mid‐Winter Cyclone: Observing Coupled Dynamic Interactions Across Scales

AbstractArctic cyclones are key drivers of sea ice and ocean variability. During the 2019–2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, joint observations of the coupled air‐ice‐ocean system were collected at multiple spatial scales. Here, we present observations of a strong mid‐winter cyclone that impacted the MOSAiC site as it drifted in the central Arctic pack ice. The sea ice dynamical response showed spatial structure at the scale of the evolving and translating cyclonic wind field. Internal ice stress and ocean stress play significant roles, resulting in timing offsets between the atmospheric forcing and the ice response and post‐cyclone inertial ringing in the ice and ocean. Ice motion in response to the wind field then forces the upper ocean currents through frictional drag. The strongest impacts to the sea ice and ocean from the passing cyclone occur as a result of the surface impacts of a strong atmospheric low‐level jet (LLJ) behind the trailing cold front and changing wind directions between the warm‐sector LLJ and post cold‐frontal LLJ. Impacts of the cyclone are prolonged through the coupled ice‐ocean inertial response. Local impacts of the approximately 120 km wide LLJ occur over a 12 hr period or less and at scales of a kilometer to a few tens of kilometers, meaning that these impacts occur at combined smaller spatial scales and faster time scales than most satellite observations and coupled Earth system models can resolve.

DESIGN OF UD BRICK RAW MATERIAL PREDICTION APPLICATION. INARA

Raw material data processing system is a very important thing in trading business. A computerized system is needed that can make predictions that are more effective, efficient and balanced with adequate human resources. UD.INARA does not yet have a system that can predict the need for brick raw materials. Because in the process of processing raw brick material data still uses manual predictions which are of course inaccurate, so that the process of ordering customers to calculating raw materials is not effective and efficient. The system design uses the SDLC (System Development Life Cycle) waterfall method which consists of five stages, namely 1) planning, 2) analysis, 3) design, 4) implementation, 5) maintenance. System modeling uses UML (Unified Modeling Language) to describe visually, which is then implemented using the Hypertext Preprocessor (PHP) programming language with MySQL database as the database used. This design produces a data processing application for ud.inara brick raw materials that is effective and efficient in the process of predicting raw materials. This system can also generate accurate raw material reports. The design of a data processing application for brick raw materials is expected to improve UD.INARA's performance, to be more productive and efficient in providing services to customers.

DESIGN OF TOURISM BUS RENTAL SYSTEM AT PT. BAGINDO WEB-BASED TRANSWISATA

For businesses engaged in transportation services, a rental system is very important. A computerized system is needed to improve the efficiency and productivity of the rental system and ensure the availability of adequate human resources. PT. Bagindo Transwisata does not have a system that can handle all rental activities. The design of an effective and efficient tourist bus rental information system is needed because the process of recording and processing tourist bus rental data is still carried out using records in books and of course there is still the possibility of human error. System modeling is depicted visually through the use of UML (Unified Modeling Language), which is then implemented with the Hypertext Preprocessor (PHP) programming language, with MySQL as the database used. This tourist bus rental information system is expected to help customers make transactions and help the administration and management departments create accurate rental reports. This will encourage effective and efficient performance and help make decision-making plans..

A Corpus-Based Text-Centric Approach to the Scientific Discourse Actualization in the Process of Forming the Professional Language Personality of Linguistic Specialties Students

The article analyses the effect of the corpus text-centered approach on the development of the personality of a linguistics student in the changing socio-pedagogical and professional context of modern society. The ways of scientific discourse actualization in the digital linguodidactic space are investigated, a systematic and in-depth justification of its forms is given, practical and didactic measures affecting the formation and harmonious development of the professional language personality of students are considered. The key characteristics of scientific communication necessary for future specialists for successful professional development in the field of linguistic knowledge are being clarified. The specifics of teaching students a foreign language based on a text-centric approach based on the online corpus dictionaries and digital word cloud technology use are being clarified. The purpose of the article is to investigate and demonstrate the conceptual model and principles of the modern didactic system, which is based on the corpus text-centered approach in the teaching of scientific discourse to language students and the development of their professional language personality. Methodology. In addition to quantitative methods, the pedagogical experiment aimed to find out the characteristics of the formation and development of the scientific discussion skills of students in the field of education “Professional education (according to industry)” a text-centric approach was used. In conclusion, it can be stated that the effectiveness of the corpus text-centered approach in the development of the professional personality of language students has been demonstrated. Recognizing the specifics of scientific communication, this approach helps students improve their reading, writing, speaking skills and understanding of foreign scientific discourse, as well as expand their vocabulary and develop logical thinking and communication skills.

Modeling a solar shading system that controls heat gain by using solar energy to change louver slat angles

In this study, we propose a model for a passive louver system that adjusts slat angles using solar heat energy. The model is structured in two stages: predicting the surface temperature of a solar collector plate and using this temperature to determine the slat angles. The system was installed and monitored in a building in Okinawa, Japan, to validate the model’s accuracy with field measurements. The validation showed that while the model accurately predicted the daily opening and closing times of the louvers, it faced limitations in minute-by-minute variations, making it less suitable for scenarios requiring instantaneous state evaluations, such as lighting environment assessments. Additionally, predicting the temperature for the double-skin façade was challenging and could affect overall model accuracy. Despite these issues, the model effectively achieved its primary goal of predicting annual energy consumption by accurately forecasting the daily opening and closing times of the louvers. The model’s fast computation speed and simplicity make it particularly suitable for annual energy simulations and easy to integrate with existing energy simulation programs. Further research is needed to enhance minute-by-minute reproducibility and integrate temperature predictions for double-skin façades, ensuring a comprehensive evaluation of both thermal and lighting environments.

Mathematical Modelling of a Single Magneto-Rheological for Car Suspension System Using Modified Bouc-Wen Model

Magneto-Rheological (MR) automotive suspension represents the most advanced technology currently available for enhancing passenger comfort through intelligent fluid behaviour. This work employed a Modified Bouc-Wen model to create a mathematical representation of a single MR vehicle suspension and compared its ride performance to that of passive suspension systems. The model was formulated and solved using second-order linear differential equations, with MATLAB software utilized to visualize the results. The maximum vertical displacement for the single MR mathematical model in this work was 0.031 m, while the minimum was -0.0124 m. At the minimum position, the vertical displacements for the passive model were 0.0532 m and -0.0133 m. The results demonstrated that the vertical displacement variation was similar for both the mathematical model and the passive system. All displacements obtained from the mathematical modeling of the single MR system were close to its mean of 0.000875 m (nearly zero). There was reduced vibration when zero displacement was achieved. It was concluded that MR damper significantly improved car suspension performance compared to passive solutions. This paper developed a single MR vehicle suspension system using the Modified Bouc-Wen model in a Proton Preve.

Does cognitive control mediate the relationship between peer presence and adolescent risk-taking? An ERP study.

Peer presence influences risk-taking behavior, particularly in adolescence. Based on the dual system model, this event-related potential study examined whether and how the presence of a peer displayed a preference for risky behavior would increase adolescents' risk-taking by disrupting their cognitive control processes in either emotional or non-emotional contexts. A sample of 106 adolescents (17-19 years of age) completed two Stoop tasks and a Balloon Analog Risk Task under three peer presence conditions. Results revealed that compared to other conditions, the presence of a risk-averse peer caused adolescents to make safer decisions through improving their conflict monitoring (more negative N200-diff), whereas a risk-preference peer's presence led adolescents to more risky decisions through disrupting their conflict resolution (more positive N450-diff) but they were only observed on the Emotional Stroop task. These findings suggest that different peer presence contexts could increase or decrease adolescents' risk-taking behaviors by influencing their cognitive control under an emotional context rather than in a non-emotional context.

Active Control for Construction Stability of Suspension Arch Rib Segments Based on ARID System

In response to the issues of vibrations affecting the construction safety, speed, and accuracy of suspended structures due to dynamic disturbances during lifting, environmental disturbances, and improper operator actions, this paper investigates the application of the Active Rotary Inertia Driver (ARID) system for double-rope suspended structures, namely analyzes, and applies control to the vibration response of double-rope suspended structures under external excitations. Taking the double-rope suspended structure as an example, a dynamic analytical model of the double-rope suspended structure is established based on D’Alembert’s principle. Through shake table tests, the dynamic response characteristics and vibration control effects of the double-rope suspended structure under various external excitations are studied, and the influence of the twisting radius of the suspended structure on the control effect is analyzed. The experimental results show that the ARID control system achieves significant control effects on the swing and torsional vibrations of the suspended structure, which validates the accuracy of the theoretical model for the ARID control system and demonstrates its feasibility for practical applications.

Grading and Sorting of Capsicum Using Convolutional Neural Networks (CNN): A Review

Abstract: Grading and sorting of capsicum, or bell peppers, is a critical task in the agricultural industry to ensure consistent quality control and efficient distribution. In recent years, Grading & Sorting of Capsicum using Convolutional Neural Networks (CNNs), have shown promise in automating this process. The objective is to automate the Grading and Sorting process, which currently done manually and time-consuming. The proposed approach involves the collection of capturing dataset of capsicum images, extracting relevant features, and training a CNN model to classify the capsicum based on their quality criteria such as size, shape, color, and quality levels. These images are pre-processed to enhance their quality and standardize the inputs. A CNN architecture of 85 trained datasets and 33 tested datasets images using for accurate grading and sorting. After the training phase, the model's accuracy is evaluated using appropriate metrics such as precision, recall, or F1-score. The performance of the CNN model of grading and sorting system is determined based on the accuracy values, providing an objective measure of its effectiveness. Experimental results of testing datasets obtained an accuracy value of above 90% indicates that the system correctly classified, the capsicum into their respective grades or sorted categories 97.43% accuracy achieved

Dynamic and Static Workout of In Vitro Skeletal Muscle Tissue through a Weight Training Device.

Enhancing muscle strength through workouts is a key factor inimproving physical activity and maintaining metabolic profiles. The controversial results concerning the impacts of weight training often arise from clinical experiments that require controlled experimental conditions. In this study, a weight training system for a muscle development model is presented, which is capable of performing weight training motions with adjustable weight loads. Through the implementation of cultured skeletal muscle tissue with floating structures and a flexible ribbon, both isotonic (dynamic change in muscle length) and isometric (static in muscle length) exercises can be performed without the deflection of the tissue. Quantitative analysis of contraction force, changes in metabolic processes, and muscle morphology under different weight training conditions demonstrates the effectiveness of the proposed system. Our proposed system holds potential for establishing effective muscle development and for further applications in rehabilitation training methods.

Development of a patient-specific model of the human coronary system for percutaneous transluminal coronary angioplasty balloon catheter training and testing.

To treat stenosed coronary arteries, percutaneous transluminal coronary angioplasty (PTCA) balloon catheters must combine pushability, trackability, crossability, and rewrap behavior. The existing anatomic track model (ASTM F2394) for catheter testing lacks 3D morphology, vessel tortuosity, and compliance, making evaluating performance characteristics difficult. This study aimed to develop a three-dimensional patient-specific phantom (3DPSP) for device testing and safe training for interventional cardiologists. A range of silicone materials with different shore hardnesses (00-30-45A) and wall thicknesses (0.5mm, 1mm, 2mm) were tested to determine compliance for creating coronary vessel phantoms. Compliance was assessed using optical coherence tomography (OCT) and compared to values in the literature. Stenosis was induced using multilayer casting and brushing methods, with gypsum added for calcification. The radial tensile properties of the samples were investigated, and the relationship between Young's modulus and compliance was determined. Various methods have been introduced to approximate the friction between silicone and real coronary vessel walls. Computerized tomography (CT) scans were used to obtain patient-specific anatomy from the femoral artery to the coronary arteries. Artery lumens were segmented from the CT scans to create dissolvable 3D-printed core models. A 15A shore hardness silicone yielded an experimental compliance of 12.3-22.4 for stenosed tubes and 14.7-57.9 for uniform tubes, aligning closely with the literature data (6.28-40.88 ). The Young's modulus ranged from 43.2 to 75.5kPa and 56.6-67.9kPa for the uniform and calcified materials, respectively. The dependency of the compliance on the wall thickness, Young's modulus, and inner diameter could be shown. Introducing a lubricant reduced the silicone friction coefficient from 0.52 to 0.13. The 3DPSP was successfully fabricated, and comparative analyses were conducted among eight commercially available catheters. This study presents a novel method for crafting 3DPSPs with realistic mechanical and frictional properties. The proposed approach enables the creation of comprehensive and anatomically precise setups spanning the right femoral artery to the coronary arteries, highlighting the importance of such realistic environments for advancing medical device development and fostering safe training conditions.

Mobile Learning and Resource Sharing Mode of College English Translation Based on 5G Mobile Communication Technology

The application of 5G and other mobile communication technologies to education and teaching, and the construction of College English Translation mobile learning and resource sharing model and related models have important scientific value and significance for the effective organization and management of learning resources and the improvement of the speed and efficiency of college english translation resource retrieval. This research mainly combines the characteristics of complementarity and expansion of mobile learning technology for traditional online learning technology. Based on Moodle online teaching platform, this research develops a mobile learning and resource sharing mode for college english translation based on 5G mobile communication technology, designs and implements a mobile learning model based on Moodle platform, and designs the system architecture, functional modules, learning mode and learning process, Finally, the main functional modules of the system model are implemented and tested. To promote mobile learning in the teaching field to play a helping role in a wide range. The experimental results show that the AKAZE algorithm is used to optimize the model, and the overall accuracy rate reaches 74.7%, and the test probability value P (siq)=0.00, which is significantly less than the significant level of 0.05. Therefore, we believe that the application of mobile learning instructional design mode will help students improve their academic performance.

Analysis of Underground Distribution System Models for Secondary Substations

Analysis of Underground Distribution System Models for Secondary Substations

Identification of nonlinear system model and inverse model based on conditional invertible neural network

In applications such as adaptive inverse control, internal model control, and active noise control, the identification accuracy of the system model and the inverse model directly affects the performance. However, it is not easy to identify inverse models for nonlinear systems. Moreover, existing methods require two identification calculations to obtain the system model and the inverse model. Therefore, an identification method of nonlinear system model and inverse model based on conditional invertible neural network (cINN) is proposed. The invertible structure of cINN enables simultaneous approximation of complex nonlinear functions and simultaneous acquisition of the corresponding inverse functions. Consequently, both the nonlinear system model and the inverse model can be identified concurrently through cINN. Moreover, the identification performance of the cINN-based method is validated and applied to disturbance cancellation in a classical nonlinear simulation system. Finally, the inverse model of the actuator is identified by cINN, and the inverse model is applied to the nonlinear compensation of the actuator.

Inequality in the Distribution of Wealth and Income as a Natural Consequence of the Equal Opportunity of All Members in the Economic System Represented by a Scale-Free Network

The purpose of this work is to examine the nature of the historically observed and empirically described by the Pareto law inequality in the distribution of wealth and income in an economic system. This inequality is presumed to be the result of unequal opportunity by its members. An analytical model of the economic system consisting of a large number of actors, all having equal access to its total wealth (or income) has been developed that is formally represented by a scale-free network comprised of nodes (actors) and links (states of wealth or income). The dynamic evolution of the complex network can be mapped in turn, as is known, into a system of quantum particles (links) distributed among various energy levels (nodes) in thermodynamic equilibrium. The distribution of quantum particles (photons) at different energy levels in the physical system is then derived based on statistical thermodynamics with the attainment of maximal entropy for the system to be in a dynamic equilibrium. The resulting Planck-type distribution of the physical system mapped into a scale-free network leads naturally into the Pareto law distribution of the economic system. The conclusions of the scale-free complex network model leading to the analytical derivation of the empirical Pareto law are multifold. First, any complex economic system behaves akin to a scale-free complex network. Second, equal access or opportunity leads to unequal outcomes. Third, the optimal value for the Pareto index is obtained that ensures the optimal, albeit unequal, outcome of wealth and income distribution. Fourth, the optimal value for the Gini coefficient can then be calculated and be compared to the empirical values of that coefficient for wealth and income to ascertain how close an economic system is to its optimal distribution of income and wealth among its members. Fifth, in an economic system with equal opportunity for all its members there should be no difference between the resulting income and wealth distributions. Examination of the wealth and income distributions described by the Gini coefficient of national economies suggests that income and particularly wealth are far off from their optimal value. We conclude that the equality of opportunity should be the fundamental guiding principle of any economic system for the optimal distribution of wealth and income. The practical application of this conclusion is that societies ought to shift focus from policies such as taxation and payment transfers purporting to produce equal outcomes for all, a goal which is unattainable and wasteful, to policies advancing among others education, health care, and affordable housing for all as well as the re-evaluation of rules and institutions such that all members in the economic system have equal opportunity for the optimal utilization of resources and the distribution of wealth and income. Future research efforts should develop the scale-free complex network model of the economy as a complement to the current standard models.

Modular, Physically Motivated Simulation Model of an Ultrasonic Testing System

Modular, Physically Motivated Simulation Model of an Ultrasonic Testing System

Coupling Relationship between Basin Evolution and Hydrocarbon Reservoirs in the Northern Central Myanmar Basin: Insights from Basin and Petroleum System Modeling

Coupling Relationship between Basin Evolution and Hydrocarbon Reservoirs in the Northern Central Myanmar Basin: Insights from Basin and Petroleum System Modeling

A Modified ADRC Scheme Based on Model Information for Maglev Train

During the operation of maglev trains, they are subjected to various disturbances. The presence of these disturbances presents a significant challenge for attaining high-performance control and even poses the risk of system instability. To further enhance the anti-disturbance capability of maglev trains, this paper proposes a model information-assisted modified active disturbance rejection control (MADRC) approach. A mathematical model of the single-point suspension system of maglev trains is constructed for the design of the extended state observer (ESO), which is a modified extended state observer (MESO), and a nonlinear mechanism is incorporated to boost the performance of the ESO. Owing to the introduction of model information, the estimated quantity of disturbances by MESO no longer considers the system model deviation as a disturbance. Hence, the linear feedback control law is modified accordingly. The MESO is regarded as an ESO with time-varying gain using the equivalent gain method, and its stability is proven using the Lyapunov method. The tracking and anti-disturbance performances of different controllers are compared via simulation experiments. Suspension and anti-disturbance experiments are conducted on the single-point suspension experimental platform, verifying that the proposed MADRC has a more potent suppression ability for load disturbances in the suspension system.

Research on Intelligent Ventilation System of Metal Mine Based on Real-Time Sensing Airflow Parameters with a Global Scheme

In ventilation systems of metal mines, the real-time measurement of the airflow field and a reduction in pollutants are necessary for clean environmental management and human health. However, the limited quantitative data and expensive detection technology hinder the accurate assessment of mine ventilation effectiveness and safety status. Therefore, we propose a new method for constructing a mine intelligent ventilation system with a global scheme, which can realize the intelligent prediction of unknown points in the mine ventilation system by measuring the airflow parameters of multiple known points. Firstly, the nodal wind pressure method combined with the Hardy–Cross iterative algorithm is used to solve the mine ventilation network, and the airflow parameters under normal operation and extreme working conditions are simulated, based on which an intelligent ventilation training database is established. Secondly, we compared the airflow parameter prediction ability of three different machine learning models with different neural network models based on the collected small-sample airflow field dataset of a mine roadway. Finally, the depth learning method is optimized to build the intelligent algorithm model of the mine ventilation system, and a large number of three-dimensional simulation data and field measurement data of the mine ventilation system are used to train the model repeatedly to realize the intelligent perception of air flow parameters of a metal mine ventilation network and the construction of an intelligent ventilation system. The results show that the maximum error of a single airflow measurement point is 1.24%, the maximum overall error is 3.25%, and the overall average error is 0.51%. The intelligent algorithm has a good model training effect and high precision and can meet the requirements of the research and application of this project. Through case analysis, this method can predict the airflow parameters of any position underground and realize the real-time control of mine safety.