Distributed Simulation Model Research Articles

Natural resource rent's effect on Ethiopian inequality and manufacturing's moderating role: evidence from dynamic simulated ARDL model

Purpose The purpose of this study is to empirically examine the impact of natural resource rents on income inequality in Ethiopia from 1981 to 2022 and investigate whether investments in manufacturing moderate this relationship. Design/methodology/approach Dynamic autoregressive distributed lag simulation and Kernel-based regularized least squares (KRLS) models are used to analyses short- and long-run relationships, as well as the potential moderating role of manufacturing. Findings The bounds test indicates natural resource rents have a long-run positive effect on inequality but a short-run negative impact. The KRLS model finds manufacturing conditions for this linkage in the short run. In the long run, economic growth decreases inequality following an inverted Kuznets pattern, while government expenditures reduce disparities when directed at priority social services. Research limitations/implications The findings provide mixed support for theories while highlighting nuances not fully captured without local analyses. Strategic sectoral investments may help optimize outcomes from resource dependence. Practical implications The results imply Ethiopia should prudently govern resources, productively invest revenues and prioritize social spending to equitably manage industrialization and uphold stability. Social implications Reducing disparities through inclusive development aligned with empirical evidence could help Ethiopia sustain peace amid transformation and realize its goals of shared prosperity. Originality/value This study applies innovative econometrics to provide novel insights into Ethiopia's experience, resolving inconsistencies in the literature on relationships between key determinants and inequality.

Implementation of Distributed Simulation Modeling in MTSS System

Implementation of Distributed Simulation Modeling in MTSS System

Distributed ANN-bi level two-stage stochastic fuzzy possibilistic programming with Bayesian model for irrigation scheduling management

To optimize irrigation amount and date, and water allocation target across spatially distributed crops under uncertainties and risks, the framework of the distributed ANN-bi level two-stage stochastic fuzzy possibilistic programming with Bayesian (distributed ANN-BLTSFPPB) model was established by integrating bi-level programming, two stochastic programming (TSP), fuzzy possibilistic programming, Bayesian, downside risk with the distributed ANN model. Decisions making of distributed crops were conducted by building distributed model to optimize decisions at several spatially heterogeneous units. The risks of economic benefit and water productivity were considered and measured by the downside risk approach, and uncertainties of runoff were presented as fuzzy normal distribution numbers to reduce uncertainties and improve robustness of decisions. Besides, tradeoffs between economic benefit and risks in the upper layers, and contradictory relationships across objectives at the upper and lower layers were balanced by the BLTSFPPB model. Moreover, effects of water right trading on economic benefit with considerations of subjectivities of managers under different hydrological years were quantified by Bayesian approach. Calculation efficiencies of the distributed AquaCrop-optimization model were effectively improved by establishing the distributed ANN-BLTSFPPB, making it easy-to-use and expanding its applications. The developed model was applied to Yingke district to verify its application. The results disclosed that economic benefit and yield enlarged, and water productivity and risks lessened when the water right trading was considered. The results could offer insight into how to establish the distributed ANN model to replace distributed simulation model and further couple with optimization model to conduct spatially distributed decisions and improve calculation efficiencies for managers. They can reach key tradeoffs across economic benefit, yield and risks, and support in-depth analysis about how water right trading affects system outcomes.

Microscopic Simulation-based Pedestrian Distribution Service Network in Urban Rail Station

In the internal distribution structure of urban rail transit stations, multi-layered building space structure, functionally different facilities differentiated pedestrian decision-making, and complex interrelationships between pedestrians and facilities make the study of the distribution process complicated. According to the pedestrian library modeling principle of AnyLogic pedestrian simulation software to construct the pedestrian distribution simulation model of the rail transit station, and propose the evaluation method of distributed feature value. Due to the distribution model, divide the distribution system of rail transit stations into three levels. Calculate the decision value in the path selection considering the facility's working state and the decision-making method of the pedestrian. Taking the transfer station as an example, applying the decision value to the distributed simulation model, and the accuracy of the model and the station's distribution state is verified. We found that the model can better reflect the pedestrian decision-making model of the real scene and the station's distribution process and can judge the distribution status of the station from the multi-angle service level.

Graphical Analysis of Rollback Process in Ad Hoc Distributed Traffic Simulation

Recent advancements in sensor, mobile computing, and wireless communication technologies is creating new opportunities to effectively exploit real-time traffic data. Onboard vehicles collect, process, simulate traffic states in a distributed fashion and a local transportation management center coordinates the overall simulation with an optimistic execution technique. Such a distributed approach can provide more up-to-date and robust estimates with decreased communication bandwidth requirements and increased computing capacity. This paper proposes an online ad hoc distributed simulation. The physical operating platform for the model including operating system, communicational middleware, and traffic simulation model are described. Also, this paper investigates the analytical background of rollback process of the proposed ad hoc distributed simulation model. Flow rate diagram and cumulative number of vehicle diagram show that the overall system simulation speed and estimate accuracy may differ significantly as a function of the selected threshold.

Extension of Bayesian chemistry-assisted hydrograph separation to reveal water quality trends (BACH2)

A Bayesian chemistry-assisted hydrograph separation (BACH) approach was previously demonstrated using 15 years of monthly total phosphorus (TP) and total nitrogen (TN) data from eight mesoscale catchments in New Zealand’s North Island. Calibration was done separately for three 5-year data periods, and in each period, concentrations of the two tracers (TP and TN) discharged from each of the three separated flow paths—fast (event-response near-surface flow), medium (seasonal shallow local groundwater flow), and slow (persistent deeper regional groundwater flow)—were assumed to be constant. This approach has now been extended to reveal non-linear trends in the tracer concentrations in each flow path, each represented using a four-parameter curve (initial and final values of a linear trend plus two harmonics). The extended method (called BACH2) identified clear TP and TN concentration trends in the medium and slow flow paths in most of the eight catchments. TP and TN concentration trends in the fast flow path were generally uncertain, however, due to the infrequency and inherent variability of concentrations sampled during high flow conditions. Concentrations closely matched previously published results from the constant-concentration BACH model calibrated to shorter data series. The BACH2 approach is a powerful tool for revealing concentration trends in the different pathways that sustain stream flow using commonly available water quality and flow data. This type of analysis has not previously been available outside of complex distributed simulation models.

Design of Distributed Discrete-Event Simulation Systems Using Deep Belief Networks

In this research study, we investigate the ability of deep learning neural networks to provide a mapping between features of a parallel distributed discrete-event simulation (PDDES) system (software and hardware) to a time synchronization scheme to optimize speedup performance. We use deep belief networks (DBNs). DBNs, which due to their multiple layers with feature detectors at the lower layers and a supervised scheme at the higher layers, can provide nonlinear mappings. The mapping mechanism works by considering simulation constructs, hardware, and software intricacies such as simulation objects, concurrency, iterations, routines, and messaging rates with a particular importance level based on a cognitive approach. The result of the mapping is a synchronization scheme such as breathing time buckets, breathing time warp, and time warp to optimize speedup. The simulation-optimization technique outlined in this research study is unique. This new methodology could be realized within the current parallel and distributed simulation modeling systems to enhance performance.

Distributed MASON: A scalable distributed multi-agent simulation environment

Computational Social Science (CSS) involves interdisciplinary fields and exploits computational methods, such as social network analysis as well as computer simulation with the goal of better understanding social phenomena.Agent-Based Models (ABMs) represent an effective research tool for CSS and consist of a class of models, which, aim to emulate or predict complex phenomena through a set of simple rules (i.e., independent actions, interactions and adaptation), performed by multiple agents. The efficiency and scalability of ABMs systems are typically obtained distributing the overall computation on several machines, which interact with each other in order to simulate a specific model. Unfortunately, the design of a distributed simulation model is particularly challenging, especially for domain experts who sporadically are computer scientists and are not used to developing parallel code.D-MASON framework is a distributed version of the MASON library for designing and executing ABMs in a distributed environment ensuring scalability and easiness. D-MASON enable the developer to exploit the computing power of distributed environment in a transparent manner; the developer has to do simple incremental modifications to existing MASON models, without re-designing them.This paper presents several novel features and architectural improvements introduced in the D-MASON framework: an improved space partitioning strategy, a distributed 3D field, a distributed network field, a decentralized communication layer, a novel memory consistency mechanism and the integration to cloud environments.Full documentation, additional tutorials, and other material can be found at https://github.com/isislab-unisa/dmason where the framework can be downloaded.

Context Aware SmartHealth Cloud Platform for Medical Diagnostics

Healthcare has seen a great evolution in current era in terms of new computer technologies. Intensive medical data is generated that opens up research in healthcare analytics. Coping with this intensive data along with making it meaningful to deliver knowledge and be able to make decisions are the most important tasks. To deduce the authenticity of the data on basis of precision, correction, associations and true meaning is important to validate the understanding of correct semantics. In case of medical diagnosis to form accurate understanding of associations while removing ambiguity and forming a correct picture of the case is of utmost importance. To come up with the right metrics for the diagnostic solution we have explored the known criteria to validate healthcare analytics techniques involved in formation of diagnosis that results in betterment and safety of patients under observations and heading towards possible treatments. In this work, we have proposed a thematic taxonomy for the comparison of existing healthcare analytics techniques with emphasis on diabetes and its underlying diseases. This analysis lead us to propose a data model for hybrid distributed simulation model for future Context Aware SmartHealth cloud platform for diagnostics. This platform is designed to inherit smartness of unsupervised learning which in turn would keep updating itself under supervised learning by qualified experts. Finally, the accuracy would be determined using HUM approach with biomarkers or a better accuracy model than AUC. The recommended action plan is also presented.

Modelling the Potential of Integrated Vegetation Bands (IVB) to Retain Stormwater Runoff on Steep Hillslopes of Southeast Queensland, Australia

Rainfall intensity is predicted to increase under a changing climate, leading to increased risks of hillslope erosion, downstream sedimentation and flooding. For many catchments used for grazing and agricultural land uses, it will become increasingly important to maintain ecohydrological functioning despite climatic extremes. One means to achieve this is through strategic reforestation using locally endemic species, in spatial configurations that effectively intercept, retain or and redistribute overland flows. This paper adopts a modelling approach for investigating the potential of one such design termed “integrated vegetation bands” (IVB), to increase the retention of runoff across steep hillslopes, particularly in the sub-tropics where rainstorms are becoming increasingly intense. A spatially distributed simulation model (MIKE-SHE) was applied to a steep, grazed catchment (Maronghi Creek catchment, Southeast Queensland, Australia) to compare stormwater runoff characteristics between: (1) the existing pasture land cover; and (2) a series of hypothetical IVB added across this pasture land. The IVB were approximately 20 m wide, and configured at 5% gradient towards ridgelines. Results for estimates of overland flow depth and infiltration (spatial), and accumulative water balance (temporal), confirm that the area of hillslope retaining > 10 mm/day more runoff increased by 22% under IVB compared to the pasture land use. Excluding the IVB themselves, the area of hillslope where runoff retention increased was 11%. During the most intense rainfall, IVB held up to 25% greater water depth and had 10% greater infiltration at the hillslope scale. At the sub-catchment scale, discharge decreased by 7% and infiltration increased by 23%. The findings for sub-tropical landscapes presented here are consistent with studies conducted in temperate regions. Based on the results of this preliminary modelling work, the IVB concept has been established as a paired-catchment field trial in a high rainfall catchment in Southeast Queensland, Australia.

항공무기체계 LVC 시뮬레이션을 위한 통합연동시스템 V&V

This paper describes the verification and the validation about the development of the integrated interoperability system for live, virtual, and constructive simulations on the aircraft weapon system. The proposed integrated interoperability system provides the framework and application softwares for implementing a synthetic environment emulating real-world environment among distributed simulation models, which are a mission model and an air combat model of a constructive level, an tactical simulator of a virtual level, and simulated ACMI of a live level. In this paper, we verify requested functions through an developmental test and evaluation, and validate operability and usability through conducing integrated LVC scenarios on the integrated interoperability system.

Special Issue on Production Planning and Scheduling

This issue focuses on production planning and scheduling for production system and the related problems that have arisen in these areas in the last half century as digital computer systems developed. These problems relate to production management, production planning, shop floor control, product design and process planning. In the first stage of production planning and scheduling systems R&D, optimization is a key issue that has been widely discussed and many theories and optimization algorithms proposed. Rule-based methods are discussed as potential solutions to these problems. With rapid advances in computer and information processing technologies and performance, tremendous progress has been made in the areas of production systems such as production planning, production scheduling, advances production systems (APS), enterprise resource planning (ERP), just-in time (JIT) processes, the theory of constraint (TOC), product data management (PDM) and computer-aided design / manufacturing / engineering (CAD/CAM/CAE). This special issue addresses the latest research advances, applications, and case studies in production planning and scheduling covering such as decentralized and autonomous production systems, distributed simulation models, robust capacity planning models, wireless sensor networks for production systems and applications to automotive component and steel production. We hope that learning about these advances will enable readers to share their own experience and knowledge in technology, new developments and the potential applications of production planning and scheduling methods and solutions.

Runtime balancing effect in distributed simulation model

The paper deals with study of the load distribution effect between computing nodes for simulation run-time of a distributed computer network model. Two main types of balancing are considered: computational load balancing and reduction of transmitted amounts of data. Simulation was performed on one computer, and distribution was carried out between the cores of one processor. Simulation experiments showed that the lack of balance in the amounts of data, transferred between parts of a distributed model, leads to decrease of the simulation speed by several times due to overhead charges for data transmission between logical processes because of MPI usage. Model run-time changing at uneven distribution of computational load depends to a large extent on the load, which is created by the applications running on the simulated network nodes. It is shown that a balanced model is performed much faster than unbalanced version even when using applications that do not require significant computing resources. Simulation time reduction can be achieved by model separation in such manner as to reduce amounts of data transferred between its parts and reduce variability of loads generated by applications in different logical processes.

A holistic framework for engineering simulation platform development gluing open-source and home-made software resources

The budgetary pressure of engineering simulation platform development is continuing to increase in industry, especially for those scientific institutions, while simulation platform is becoming increasingly important for the researchers in their daily work. Plenty of basic components provided for free by open-source communities can be used to develop simulation platform; however, using open-source components is much more technically difficult than directly utilizing commercial simulation platform. We propose a novel gluing components to tackle the existing difficulties of engineering simulation platform development by using open-source components and home-made resources. In order to reduce the development cost, a holistic framework named TPL.Frame, whose core is the gluing component, is designed to develop engineering simulation platform that consists of SALOME simulation platform, OGRE engine and some other home-made numerical codes. Unlike general commercial simulation solutions, the framework provides not only the basic functionalities, including CAD (Computer-Aided Design) and CAE (Computer-Aided Engineering), but also advanced features, such as real-time 3D visualization, interoperability between FE (Finite Element) method and MB (Multi-Body) dynamics, distributed simulation modeling and other user-defined features. To compare with traditional development method, several cases studied in railway industry are given to demonstrate how to rapidly develop engineering simulation platform using TPL.Frame, thus to prove the effectiveness of the proposed framework.

Research on Software Algorithm Capture of Spread Spectrum TT&C Signals

Study a suitable algorithm for implementation of spread spectrum tt&c signals capture software.Analyzes in detail the serial capture pseudo-code algorithm based on FFT, according to the measurement and control conditions, in consideration of pseudo-code doppler and deal with the impact of bandwidth on the basis of, put forward the suitable for software implement methods of capture, primarily through the establishment of a distributed system simulation model and implements a spread spectrum tt&c signals of quasi real-time processing, prove the validity of the method.

Distributed supply chain network modelling and simulation: integration of agent-based distributed simulation and improved SCOR model

Agent-based distributed simulation is an efficient methodology for modelling and analysing such complex adaptive systems as dynamic supply chain networks. However, it lacks an acceptable generic standard. Supply chain operations reference (SCOR) model is a cross-functional framework widely accepted as an industry standard. It provides the standard processes, performance metrics, best practices and associated software functionalities for modelling, evaluating and improving supply chain networks. However, it is a static tool. Integration of agent-based distributed simulation and SCOR model can exploit their advantages to form a generic methodology for modelling and simulation of a wide range of supply chain networks. Therefore, this paper proposes a methodology for distributed supply chain network modelling and simulation by means of integration of agent-based distributed simulation and an improved SCOR model. The methodology contains two components: a hierarchical framework for modelling supply chain network based on the improved SCOR model and agent building blocks integrating the standard processes from the SCOR model. The hierarchical framework provides an approach for structure modelling in any level with different granularities based on the improved SCOR model, and allows rapidly mapping a supply chain network into the structure model of a multi-agent system; while agent building blocks are quite useful and convenient to fill the structure model to fulfil its function modelling. With the approach of structure modelling and function filling, not only can the process of agent-based supply chain network modelling be accelerated, but also the built models can be reused and expanded. Because the hierarchical framework is based on the conceptual framework of SCOR model and agent building blocks integrate the standard processes from SCOR model, the proposed methodology is more generic. In addition, the issues of sub-model synchronisation and data distribution management in the agent-based distributed simulation implementation are taken into consideration and the corresponding solutions for these issues are proposed. Finally, an example of a supply chain network is modelled and implemented to illustrate the proposed methodology and related solutions.

A robust simulation–optimization modeling system for effluent trading—a case study of nonpoint source pollution control

In this study, a robust simulation-optimization modeling system (RSOMS) is developed for supporting agricultural nonpoint source (NPS) effluent trading planning. The RSOMS can enhance effluent trading through incorporation of a distributed simulation model and an optimization model within its framework. The modeling system not only can handle uncertainties expressed as probability density functions and interval values but also deal with the variability of the second-stage costs that are above the expected level as well as capture the notion of risk under high-variability situations. A case study is conducted for mitigating agricultural NPS pollution with an effluent trading program in Xiangxi watershed. Compared with non-trading policy, trading scheme can successfully mitigate agricultural NPS pollution with an increased system benefit. Through trading scheme, [213.7, 288.8] × 10(3) kg of TN and [11.8, 30.2] × 10(3) kg of TP emissions from cropped area can be cut down during the planning horizon. The results can help identify desired effluent trading schemes for water quality management with the tradeoff between the system benefit and reliability being balanced and risk aversion being considered.

An ontology-driven framework for enhancing reusability of distributed simulation modeling of industrial construction processes

This paper describes an ontology-driven framework for developing distributed simulation modeling of construction processes. The research described in the paper is motivated by the necessity of knowledge sharing between distributed simulation modeling collaborators, and reuse and portability challenges in construction simulation models. Our approach addresses these challenges through ontological modeling and linking of construction simulation modeling components including (i) ontology of construction process, (ii) ontology of simulation world view, and (iii) ontology of distributed simulation modeling application tool. Within the paper, ontology driven approach and mapping of ontologies for information transference between simulation components has been described. Another discussed application of ontologies is structuring of simulation modeling development through use of reusable elements. A large-scale distributed simulation model of industrial construction processes has been outlined to illustrate the application of the approach.

Conceptual Framework to Optimize Building Energy Consumption by Coupling Distributed Energy Simulation and Occupancy Models

AbstractIn this paper, a conceptual framework that couples energy modeling with occupancy characteristics and energy use data is developed and tested to achieve two main objectives: (1) couple distinct and spatially distributed simulation models and synchronize their data exchange, and (2) illustrate the coupled model behavior through a hypothetical case study example of a building. This conceptual framework is developed using a distributed computing environment based on the principles defined in the high-level architecture (HLA). Thus, individual simulation models and control interfaces developed for their own purpose, called federates, are composed and coupled together in an HLA-compliant federation that allows federates to continuously communicate with one another and exchange relevant information at each time step to achieve the global objective of reducing the building’s energy use. A case study example of a typical commercial building illustrates how the model coordinates data synchronization and tr...

Алгоритмическая модель процесса распределенной имитации для технологии анализа распределенных имитационных моделей

В статье рассматривается алгоритмическая модель процесса распределенной имитации, основанная на программном представлении распределенных имитационных моделей. Модель учитывает потоки данных, возникающие как внутри частных моделей, так и при обмене информацией между моделями, а также временные характеристики процесса моделирования. Модель предназначена для использования в информационной технологии анализа распределенных имитационных моделей.