Integrated System Model Research Articles

Amplification of Northern Hemisphere winter stationary waves in a warming world

This study leverages the Global/Regional Integrated Model system (GRIMs) version 4.0 climate model to examine the mechanisms behind the recent intensification of winter stationary waves over western North America. Prescribed sea surface temperature warming forces a strengthening of westerly winds, amplifying the ridge that characterizes the stationary waves in western North America. The streamfunction budget analysis reveals relative vorticity advection is mainly associated with this process. We further show that ocean warming is the primary driver of changes in westerly winds and stationary waves in the Northern Hemisphere. Sea ice losses exert a considerable effect through a different mechanism, complementing the dominant influence of ocean warming on these atmospheric changes. Our results thus reveal the crucial role tropical oceans play in modulating global warming’s effect on the stationary waves in the Northern Hemisphere and add a more quantitative perspective to the previously reported influence of Arctic amplification.

Simulation of a Reverse Electrodialysis-Absorption Refrigeration Integration System for the Efficient Recovery of Low-Grade Waste Heat.

The absorption refrigeration system (ARS) stands as a remarkable device that is capable of efficiently harnessing low-grade thermal energy and converting it into cooling capacity. The reverse electrodialysis (RED) system harvests the salinity gradient energy embedded in two solutions of different concentrations into electricity. An innovative RED-ARS integration system is proposed that outputs cooling capacity and electric energy, driven by waste heat. In this study, a comprehensive mathematical simulation model of a RED-ARS integration system was established, and an aqueous lithium bromide solution was selected as the working solution. Based on this model, the authors simulated and analyzed the impact of various factors on system performance, including the heat source temperature (90 °C to 130 °C), concentrated solution concentration (3 mol∙L⁻1 to 9 mol∙L⁻1), dilute solution concentration (0.002 mol∙L⁻1 to 0.5 mol∙L⁻1), condensing temperature of the dilute solution (50 °C to 70 °C), solution temperature (30 °C to 60 °C) and flow rate (0.4 cm∙s⁻1 to 1.3 cm∙s⁻1) in the RED stacks, as well as the number of RED stacks. The findings revealed the maximum output power of 934 W, a coefficient of performance (COP) of 0.75, and overall energy efficiency of 33%.

CONCEPTUAL FOUNDATIONS OF ORGANIZATIONAL CULTURE OF MANUFACTURING ENTERPRISES IN THE WARTIME PERIOD

The article is devoted to the study of the conceptual foundations of organizational culture of manufacturing enterprises in wartime. The author generalizes approaches to the concept of “organizational culture” and presents the author’s own definition, which is understood as an integrated system of values, norms and behavioral models, which in wartime acts as an adaptive and protective mechanism, providing the enterprise with the ability to quickly restructure and strengthening corporate solidarity by enhancing the socio-psychological stability of the team; as a strategic tool, it ensures cohesion and motivation of employees, activating their ability to dedication and support each other, which is a once-in-a-lifetime opportunity. The article highlights the peculiarities of organizational culture in wartime, in particular: strategic direction; values that form a unique socio-psychological environment at an enterprise, thereby shaping its competitive advantages; specific components - implicit (socio-psychological) and explicit (regulatory and image elements). The characteristics of modern models of organizational culture are identified: spiritual, socio-psychological, and material. It is proved that the organizational culture of an enterprise is formed under the influence of external and internal factors, and the factors from each group are specified. The functions of the organizational culture of enterprises are studied and the functions of internal integration and functions of external adaptation are allocated. The functions of internal integration include organizational, integrating, regulatory, substitution, adaptive, educational and cognitive, motivating, communicative, quality management, and recreational. External adaptation is ensured by the following functions: innovation, formation of a positive image, customer orientation, management of partnership relations, and adaptation of the enterprise to the needs of society. The key aspects of the conceptual foundations of building the organizational culture of production enterprises are defined: process orientation; hierarchical organizational structure; physical work; safety and risks; innovation and adaptation; relationship with suppliers and consumers. New requirements for the formation of the organizational culture of enterprises during the war period were considered. The experience of foreign countries regarding the formation of organizational culture in conditions of war and constant armed conflicts, in particular Germany, South Korea, and Israel, is studied. It is proposed to introduce as elements of organizational culture specific for production enterprises under conditions of war, including: adaptability to risks and crises, support for safety and protection of personnel, patriotic aspect and values of sustainability, as well as humanitarian and social responsibility.

Benchmarking a Novel Particle Swarm Optimization Dynamic Model Versus HOMER in Optimally Sizing Grid-Integrated Hybrid PV–Hydrogen Energy Systems

This paper presents the development of an Artificial Intelligence (AI)-based integrated dynamic hybrid PV-H2 energy system model together with a reflective comparative analysis of its performance versus that of the commercially available HOMER software. In this paper, a novel Particle Swarm Optimization (PSO) dynamic system model is developed by integrating a PSO algorithm with a precise dynamic hybrid PV-H2 energy system model that is developed to accurately simulate the hybrid system by considering the dynamic behaviour of its individual system components. The developed novel model allows consideration of the dynamic behaviour of the hybrid PV-H2 energy system while optimizing its sizing within grid-connected buildings to minimize the levelized cost of energy and maintain energy management across the hybrid system components and the grid in feeding the building load demands. The developed model was applied on a case-study grid-connected building to allow benchmarking of its results versus those from HOMER. Benchmarking showed that the developed model’s optimal sizing results as well as the corresponding levelized cost of energy closely match those from HOMER. In terms of energy management, the benchmarking results showed that the strategy implemented within the developed model allows maximization of the green energy supply to the building, thus aligning with the net-zero energy transition target, while the one implemented in HOMER is based on minimizing the levelized cost of energy regardless of the green energy supply to the building. Another privilege revealed by benchmarking is that the developed model allows a more realistic quantification of the hydrogen output from the electrolyser because it considers the dynamic behaviour of the electrolyser in response to the varying PV input, and also allows a more realistic quantification of the electricity output from the fuel cell because it considers the dynamic behaviour of the fuel cell in response to the varying hydrogen levels stored in the tank.

Dispatch model of park-level integrated energy system with photovoltaic/thermal hydrogen generation equipment: A scenario analysis method based on improved K-means clustering

As the carbon emission problem brought by the traditional energy consumption pattern is becoming more and more prominent, it has become a common strategic choice for all countries to realize the carbon-neutral goal and to drive energy conversion to clean and renewable energy. Meanwhile, the significant uncertainty of renewable energy sources and their large-scale access to the grid poses new challenges to power system operation and dispatch. Therefore, this paper proposes a dispatch model for the park-level integrated energy system (PIES) with photovoltaic/thermal (PV/T) hydrogen generation equipments based on improved stepped carbon trading and adopts a scenario analysis method based on improved K-means clustering to cope with the uncertainties of the multi-energy loads and PV/T output. First, the PV/T model is constructed through five energy balance equations of the glass protection screen, solar panel, heat pipe, water inside the heat pipe, and heat storage tank, which is further combined with the hydrogen ion exchange membrane electrolyzer (HIEME) to analyze the energy flow conversion in the process of hydrogen production by the coupled equipment. Second, an improved stepped carbon trading price model is proposed by constructing a continuously monotonically increasing trading price function. Finally, based on the improved stepped carbon trading mechanism, the day-ahead dispatching model aims to optimize the sum of PIES operation cost and carbon trading cost, and the example simulation is carried out by the scenario analysis method based on improved K-means clustering. The simulation results show that the proposed model has certain significance in hydrogen production efficiency and carbon emission reduction.

Integrated analysis of air quality-vegetation-health effects of near-future air pollution control strategies

To explore the effects of air pollution control strategies on air quality, vegetation, and health, we conducted an integrated modeling analysis for a representative industrial city, Zibo in the North China Plain, China. Two air pollution control scenarios for the near future (year 2026) are developed, including basic and strict control scenarios. The integrated modeling system based on Weather Research and Forecasting-Community Multiscale Air Quality Modeling (WRF-CMAQ) is utilized to analyze the effects of different scenarios on air quality improvement, vegetation, and health effects. Results indicate that under the basic (strict) control scenarios, the emissions of sulfur dioxide (SO2), nitrogen oxides (NOx), particulate matter (PM2.5), volatile organic compounds (VOCs), ammonia (NH3) will be reduced by 16% (53%), 14% (24%), 16% (38%), 9% (28%), and 12% (12%) respectively, together with a 15% reduction in emissions of NOx, SO2, VOCs, PM2.5, along with a 5% reduction in NH3 emissions in the vicinity of Zibo in the year 2026, could meet the air quality target for 2026 (with PM2.5 and MDA8 O3_90% at 38 and 185 μg/m³, respectively). In terms of crop yield, under the basic (strict) control scenarios, the ozone-induced yield loss for wheat and corn is expected to increase by 30,000 tonnes (decrease by 80,000 tonnes) and 6000 tonnes (decrease by 4000 tonnes), respectively. In the basic control scenario, the number of deaths due to changes in PM2.5 is 1210 (95% Cl: 950, 1472) and the number of deaths due to O3-related changes is 1042 (95% Cl: 780, 1304). In the strict control scenario, the number of deaths due to PM2.5 changes was 1180 (95% Cl: 992, 1366) and the number of deaths due to O3-related changes was 768 (95% Cl: 581, 955). Our results provide a scientific basis for governments to formulate future air pollution prevention strategies.

(Invited) Integrated Model System of the Biological Membrane on Solid Surface

The biological membrane comprising lipid bilayer membrane and membrane-associated proteins performs a wide range of cellular functions, including signal transduction and energy conversion. Diseases such as cancer and COVID-19 are mechanistically linked with the biological membrane. An important structural feature of the biological membrane is the combination of two-dimensional (2D) and three-dimensional (3D) architectures that form organized 2D fluid and create compartments in the cell and cell-cell junctions. The dynamic self-assembly of the 2D/ 3D membrane structures and their cooperative functions are important in understanding the biological membranes.Synthetic model membranes such as lipid vesicles and black lipid membrane (BLM) have played important roles in extending our understanding of the biological membrane. They also provide platforms for biosensors and biomedical applications. Substrate supported lipid bilayers (SLBs) are a model membrane supported on a planar solid substrate such as silicon and glass (1). They have some unique features compared with other formats of model membranes. First, they are mechanical stable owing to the solid support. Second, they are accessibility to highly sensitive analytical techniques at the liquid-solid interface. Third, they are amenable to application of micro-fabrication techniques. These features render SLBs highly attractive for the development of devices that utilize artificially mimicked cellular functions.We have been developing an integrated model system of the biological membrane on the solid substrate utilizing a micro-patterned membrane of polymeric and natural lipid bilayers (2). The polymeric bilayer is formed from polymerizable diacetylene-containing phospholipid (DiynePC) and acts as a framework to support embedded lipid membranes. The embedded natural lipid membranes retain important characteristics of the biological membrane such as fluidity, and are used as a model system that reproduces the functions of the biological membrane. Various types of natural lipid membranes and proteins have been incorporated. We incorporated rhodopsin photoreceptor (Rh), a G-protein coupled receptor (GPCR), and its cognate G-protein transducin (Gt) into the patterned model membrane. The 2D diffusion and distribution of Rh and Gt were studied for elucidating the functional roles of lipid membrane environments (3). We also reconstituted natural membranes directly from their sources such as mammalian cell membranes and plant thylakoid membranes (4). Reconstituted thylakoid membrane provides a platform for investigating the functional roles of 2D membrane organizations in the photosynthesis.The 3D compartments formed by the biological membrane are also important for cellular functions. For mimicking the 3D compartments, we have developed a nanometric gap structure on the patterned membrane by attaching the polymeric bilayer with a silicone elastomer (PDMS) using an adhesion layer having a defined thickness (nanogap-junction) (5). Nanogap-junction provides a unique possibility to analyze biological molecules with a vastly heightened signal-noise ratio. Nanogap-junction can be used as a platform to study molecular properties and functions of membrane proteins. It should also provide opportunities to detect biomarker molecules using sandwich immuno-assay on the fluid membrane. The combination of 2D mobility and 3D compartmentalization of the membrane will be exploited to open new possibilities in the biomedical applications.The integrated model membrane reproduces some essential structural, physicochemical, and functional features of the biological membrane. These solid supported model membranes have been mainly studied by the optical methods. However, they should be integrated with electrodes, enabling electrochemical detection of the membrane functions. In combination with advanced fabrication technologies and analytical methods, it should provide novel opportunities in fundamental biological sciences as well as biomedical/ analytical applications such as "single molecule diagnostics". E. Sackmann, Science (Washington), 271, 43 (1996). K. Morigaki, Jpn. J. Appl. Phys., 63, 040801 (2024). Y. Tanimoto, K. Okada, F. Hayashi and K. Morigaki, Biophys. J., 109, 2307 (2015). T. Yoneda, Y. Tanimoto, D. Takagi and K. Morigaki, Langmuir, 36, 5863 (2020). M. Tanabe, K. Ando, R. Komatsu and K. Morigaki, Small, 14, 1802804 (2018).

Energy and exergy analysis of a new solar hybrid system for hydrogen, power and superheated steam production

This study investigates the amalgamation of solar tower technology and thermal energy storage (TES) within the framework of a supercritical carbon dioxide (S-CO2) Brayton cycle, a copper-chlorine (Cu-Cl) hydrogen production cycle, and a heat recovery steam generator (HRSG) to generate superheated steam. The various subsystems have been merged to enhance overall energy efficiency significantly, ensure uninterrupted operation, and minimize exergy loss. Energy and exergy analyses have been carried out to assess the prerequisites and effectiveness of each subsystem, highlighting the thermodynamic benefits of integration. Engineering Equation Solving Software (EES) was employed to solve the integrated system model and assess the thermodynamic properties provided by the EES library. Results showed that in the basic design mode, exergy destruction in the solar tower, S-CO2 Brayton cycle, and Cu-Cl cycle are 9930 kW, 7111 kW, and 9735 kW, respectively. The system produces 4226 kW of power, 2697 kW of heat, and 0.04971 kg/s of hydrogen. The overall energy and exergy efficiency of the power plant are 17.48 % and 18.72 %, respectively. These findings demonstrate that this integrated system can address key gaps in the literature by presenting a novel combination of solar power-driven Cu-Cl hydrogen production and superheated steam generation. The proposed system contributes to advancing renewable, efficient, and uninterrupted energy production.

Application of coupled MIKE SHE/MIKE HYDRO on streamflow dynamics under climate change in Lake Tana sub basin, Abay Basin, Ethiopia

AbstractWater availability and quality are fluctuating due to climate change, which has disastrous effects on life. Modeling climate change impact on streamflow in the Lake Tana sub‐basin (LTSB) in selected watersheds was the main goal of the research. This research is unique in that it applies the coupled MIKE SHE/MIKE HYDRO model technique, which has not been applied before to investigate changes in streamflow due to climate change in LTSB. Streamflow in the LTSB was forecasted using the MIKE SHE/MIKE HYDRO model from seven ensembles of GCMs under two emission scenarios (SSP2–4.5 and SSP5–8.5) between 2041 and 2,100. According to the calibration and validation results in the period of 1985–2007, MIKE SHE performs well while simulating streamflow in LTSB. During calibration and validation, the Nash‐Sutcliffe efficiency (NSE) values in all watersheds were greater than 0.8, except for the Ribb watershed calibration, where it was 0.75. The mean monthly changes in temperatures indicate an incremental tendency in the next decades. According to the simulation result, the monthly mean rainfall for SSP2–4.5 and SSP5–8.5 will increase from 0.05 to 61.9% and 2.02 to 46.26% in the 2050s and 8.7 to 44.38% to 6.44 to 66.24% in the 2080s, respectively. Gilgle Abay, Gumara, and Ribb watersheds will lose 56.2, 56.65, 57.01% of their mean monthly streamflow in the 2050s, according to SSP2–4.5. For the Gilgle Abay, Gumara, and Ribb watersheds, streamflow will increase by 6.7% to 21.94%, 6.08% to 23.26%, and 6.51% to 22.88%, accordingly, in the 2050s under SSP5–8.5. Increased rainfall in the watershed could result in floods in the already‐flooded Gumara and Ribb flood plains. The government and community should implement coping mechanisms to lessen the impact of climate change like early warring and planting more trees. Overall, the study showed that it is expected that conditions related to streamflow may change in the future due to climate alteration. By offering a better understanding of current and future climates, the integrated modeling system developed can assist environmentalists, hydrologists, and policymakers in water management and policy intervention.

Development of a total variation diminishing (TVD) sea ice transport scheme and its application in an ocean (SCHISM v5.11) and sea ice (Icepack v1.3.4) coupled model on unstructured grids

Abstract. As the demand for increased resolution and complexity in unstructured sea ice models is growing, higher demands are also placed on the sea ice transport scheme. In this study, we couple the Semi-implicit Cross-scale Hydro-science Integrated System Model (SCHISM, v5.11) with Icepack (v1.3.4), the column physics package of the Los Alamos sea ice model (CICE); a key step is to implement a total variation diminishing (TVD) transport scheme for the multi-class sea ice module in the coupled model. Compared with the second-order upwind scheme and the finite-element flux-corrected transport (FEM-FCT) scheme, the TVD transport scheme is overall superior when evaluated based on conservation, accuracy, efficiency (even with very high resolution), and strict monotonicity. Although it is slightly weaker than FEM-FCT in terms of accuracy alone, the TVD scheme still outperforms the other two schemes in comprehensive performance. The new coupled model outperforms the existing single-class ice model of SCHISM in the case of Lake Superior. For the Arctic Ocean case, it successfully reproduces the long-term changes in the sea ice extent, sea ice boundary, concentration observations from satellites, and thickness from in situ measurement.

Two-Way Coupling of the National Water Model (NWM) and Semi-Implicit Cross-Scale Hydroscience Integrated System Model (SCHISM) for Enhanced Coastal Discharge Predictions

This study addresses the limitations of and the common challenges faced by one-dimensional river-routing methods in hydrological models, including the National Water Model (NWM), in accurately representing coastal regions. We developed a two-way coupling between the NWM and the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM). The approach demonstrated improvements in modeling coastal river dynamics, particularly during extreme events like Hurricane Matthew. The coupled model successfully captured tidal influences, storm surge effects, and complex river–river interactions that the standalone NWM missed. The approach revealed more accurate representations of peak discharge timing and magnitude as well as water storage and release in coastal floodplains. However, we also identified challenges in reconciling variable representations between hydrological and hydraulic models. This work not only enhances the understanding of coastal–riverine interactions but also provides valuable insights for the development of next-generation hydrological models. The improved modeling capabilities have implications for flood forecasting, coastal management, and climate change adaptation in vulnerable coastal areas.

A review of integrated modeling and simulation of control and communication systems in Smart Grid

In order to provide effective, safe, and dependable grid operation, the use of information and communication technologies (ICT) for real-time monitoring and control of the Smart Grid (SG) has grown in recent years. With such technologies, our system evolved into a complex cyber-physical system (CPS) in which communications networks play an important role in the dynamic performance of SG. Therefore, it is imperative to perform integrated modeling and simulation (IMS) of control and communication systems to evaluate the SG CPS for new control strategies or select appropriate communication technologies for specific applications before implementing them on a larger scale. This paper provides a state-of-the-art literature review about co-simulation, one of the key methods to perform an IMS. The paper starts with a brief review of the SG communication infrastructure, communication, and SG simulators used for co-simulations to give the readers an understanding of the requirements and issues for modeling and simulating SG communication systems. Then, detailed literature about the co-simulation platform covers the individual simulators used, the key features, test case advantages, and the limitations of different co-simulation platforms. In the discussion section, comparative analyses of co-simulation platforms are provided. The review summarizes critical challenges and opportunities in co-simulation, emphasizing the potential of IMS for advancing SG design and operation.

An Integrated Systems Model of Ethical Messaging in Organizations

An Integrated Systems Model of Ethical Messaging in Organizations

Early warning systems for desertification hazard: a review of integrated system models and risk management

Early warning systems for desertification hazard: a review of integrated system models and risk management

Coastal CUBEnet: an integrated observation and modeling system for sustainable Northern Gulf of Mexico coastal areas

The University of Southern Mississippi has developed the coastal CUBEnet environment. Coastal CUBEnet is a high-resolution, coastal ocean sensor, modeling, and data sharing web-based network that provides the environmental intelligence needed to support the complex modeling of the interlinked processes in the northern Gulf of Mexico. With near-real time data delivery via a common infrastructure, CUBEnet uses state of the art sensors to provide a set of networked measurements systems, visualization tools, and model developments to gain an understanding of the Gulf of Mexico’s marine environments. CUBEnet is also a mechanism for improved human engagement with Gulf of Mexico resources and provides stake holders with the data needed to make informed coastal, environmental, and economic decisions. The Coastal CUBEnet’s data environment utilizes both stationary and uncrewed mobile systems and high-resolution distributed sensors to create a networked platform across the northern coastal Gulf of Mexico. CUBEnet’s modeling environment has developed an implementation of The Coupled Ocean Atmosphere Wave Sediment Transport (COAWST) Model for the Mississippi Bight region that has been applied to investigate shore to shelf advective exchange processes, and their influence on coastal water quality conditions that support the region’s prolific marine ecosystem. CUBEnet’s modeling environment provides prototype modeling applications that are supported by real-time observations of key coastal environmental variables. CUBEnet’s Web accessible visualization tools provide parameter fields and vertical profiles from hydrodynamic models and field observations. Nowcasts and forecast results are available for the Eastern LA coastline, MS coastline, Mobile Bay, and the West coast of Florida.

Semi-automated creation of reciprocal frame structures using deep learning

Systems that can transform two-dimensional (2D) sketches into 3D models while performing structural analyses are necessary for architectural sketches. To address this challenge, this paper focuses on how deep-learning algorithms can aid in this transformation process. It presents a model that uses the instance-segmentation technique with Mask RCNN to detect and distinguish two types of short beams of reciprocal frame structures (RFs) in 2D sketches and uses this information in the systematic creation of a 3D model of RFs to conduct their structural analysis. The results indicate that the model is capable of clustering beam types in 2D sketches via masking and classifying, eliminating irrelevant background objects, creating parametric RFs using masking information, and performing structural analysis. The model, which helps optimise and ease the design process, can be used by architects or engineers. This paper will inspire future work on the creation of integrated modelling systems.

Optimization method for capacity configuration and power allocation of electrolyzer array in off-grid integrated energy system

Hydrogen production using renewable energy is in line with China's the goal of carbon peak and carbon neutrality. The construction of off-grid hydrogen energy industrial park can effectively achieve local utilization of renewable energy and develop the green hydrogen industry. However, off-grid hydrogen energy industrial park has not the compensation and sustentation from large power grid, the stable operation and economic production of electrolyzer are affected by significant factors, such as power fluctuation and frequent start stop. Therefore, this paper proposed the optimization method for capacity configuration and power allocation of electrolyzer array in off-grid integrated energy system. Firstly, based on units of energy supply, energy conversion, and energy storage, a structural model of off-grid integrated energy system was established. Then, by analyzing the operational characteristics of single electrolyzer and electrolyzer array, flexible mode of multiple electrolyzers operating in combination was proposed. Furthermore, considering the hydrogen production cost, the mean of hydrogen production volatility and penalty cost, the capacity configuration and power allocation methods for electrolyzer array were proposed, and the optimization problem is solved with multi-objective particle swarm optimization algorithm. Finally, the hydrogen energy industrial park in Zhangye is taken as example to verify the effectiveness of above research content. Compared to a single type of alkaline electrolyzer, the mean of hydrogen production volatility of multiple electrolyzers operating in combination has decreased by 43.2 %, the hydrogen production quantity has increased by 9.74 %. Compared to a single type of proton exchange membrane electrolyzer, the hydrogen production cost has been reduced by 14.16 %. Compared with the balanced running mode, the flexible operation mode can improve the cost-effective and quantity of hydrogen production.

From test case to trusted tool: Lithuania’s evolving SWAT system for water and agricultural management

Lithuania’s development of the river modelling system (RMS) exemplifies an institutional development and application of integrated modelling for water and agricultural management. What started as a test case, continued to develop focusing on environmental compliance with the EU regulations. Currently, the RMS is a part of decision-making. By incorporating the soil and water assessment tool (SWAT) model and comprehensive data sources, the system facilitates in-depth analysis and policy formulation. Applications in water management plans, pollution assessments, and climate change studies demonstrate the reliability of RMS. Despite data quality and skill retention challenges, institutional commitment and collaboration ensure the RMS’s persistence. This experience emphasizes the value of sustained investment in integrated modelling systems for achieving sustainable environmental governance and signifies Lithuania’s shift towards data driven green transition practices.

Development of a dynamic traffic microsimulator for on-demand transit operations within an integrated modelling system

ABSTRACT This study develops an intelligent dynamic agent-based microsimulation (iDAMS) module for on-demand transit (ODT) operations within an integrated transport, land-use and energy (iTLE) model. A real-time optimization component within the iDAMS is formulated by the utilization of travelling salesman problem and simulated annealing metaheuristics that perform dynamic passenger-vehicle assignment. It simulates ODT operations for meeting the 24-hour auto-trip demand of Halifax, Canada, to compare the performance of the proposed system with personal cars (PCs). The optimization objectives are to determine the optimal fleet size and seat capacity that satisfies maximum trip requests while minimizing waiting time, travel time and vehicle kilometres travelled (VKT). Simulation results indicate that the ODT system can deliver service similar to PCs in Halifax while decreasing cost and emissions (13% reduction in VKT). The tools developed in this research will provide transit planners ability to conduct ODT scenario simulation and test system performance in real time.

An Intelligent Model and Methodology for Predicting Length of Stay and Survival in a Critical Care Hospital Unit

This paper describes the design and methodology for the development and validation of an intelligent model in the healthcare domain. The generated model relies on artificial intelligence techniques, aiming to predict the length of stay and survival rate of patients admitted to a critical care hospitalization unit with better results than predictive systems using scoring. The proposed methodology is based on the following stages: preliminary data analysis, analysis of the architecture and systems integration model, the big data model approach, information structure and process development, and the application of machine learning techniques. This investigation substantiates that automated machine learning models significantly surpass traditional prediction techniques for patient outcomes within critical care settings. Specifically, the machine learning-based model attained an F1 score of 0.351 for mortality forecast and 0.615 for length of stay, in contrast to the traditional scoring model’s F1 scores of 0.112 for mortality and 0.412 for length of stay. These results strongly support the advantages of integrating advanced computational techniques in critical healthcare environments. It is also shown that the use of integration architectures allows for improving the quality of the information by providing a data repository large enough to generate intelligent models. From a clinical point of view, obtaining more accurate results in the estimation of the ICU stay and survival offers the possibility of expanding the uses of the model to the identification and prioritization of patients who are candidates for admission to the ICU, as well as the management of patients with specific conditions.