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18 articles for “agent-based simulation”
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Evaluation of Emergency Response Plans in Industrial Environments Using Simulation Techniques
Abstract: Industrial facilities, particularly those in the chemical, manufacturing, and energy sectors, face significant hazards due to their complex operations and the handling of hazardous materials. Ensuring the safety of workers and minimizing the impact of incidents require robust and effective emergency response plans (ERPs). Traditional evaluation methods, such as drills and tabletop exercises, often fall short in replicating the complexities of real-world emergencies. These methods may lack the realism needed …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 3, 2024 · pp. 6–10 Read article
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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
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Enhancing Production Line Efficiency: Simulating and Optimizing Single and Parallel Line Processes
Abstract: During a time of fast-paced industrial growth, increasing production line effectiveness is a core issue for manufacturers looking to maximize output, reduce waste, and stay competitive. This study explores the use of simulation-based optimization methods to enhance single and parallel production line designs. Stepping beyond traditional trial-and-error methods, the research utilizes Siemens Tecnomatix Plant Simulation to simulate actual manufacturing scenarios, considering intricacies like buffer capacities, machine sequencing, and event-driven scheduling. …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 22–32 Read article
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Improving Node Efficiency in Wireless Sensor Networks Using Advanced Clustering and Routing Techniques
Abstract: Many Internet of Things (IoT) applications, such as disaster relief, smart buildings, smart farming, and healthcare monitoring, have made use of wireless sensor networks (WSN). It is one of the alternatives to address different IoT difficulties in different contexts. One of the main problems with sensor networks is power efficiency. WSN operated on the Client-Server (CS) architecture in the past, however researchers suggested Mobile Agent (MA) based WSN to increase …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 2, 2024 · pp. 35–64 Read article
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Biodegradable and Natural Fiber-Reinforced Polymer Composites for Co-Delivery of Multiple Therapeutic Agents
Abstract: The co-delivery of multiple drugs using advanced nanocarriers has revolutionized targeted therapy in various diseases, particularly in cancer, infectious diseases, and neurological disorders. Multi-layered polymeric nanocarriers (MLPNs) offer a sophisticated platform to encapsulate multiple therapeutic agents with precise control over drug release, bioavailability, and synergistic effects. These nanocarriers are designed with distinct polymer layers that enable sequential or simultaneous drug release based on stimuli-responsive mechanisms such as pH, temperature, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 406–419 Read article
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Role of Artificial Intelligence in Simulation and Therapeutics in Neurodegenerative Diseases
Abstract: Neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, etc., are a cause of significant mortality rates due to a lack of curative treatments and their complex nature. Traditional therapeutic methodologies have several disadvantages such as slow diagnosis and a lack of effective treatments. They mainly focused on the management of the disease rather than curing it. The integration of artificial intelligence in the simulation and therapeutics of neurodegenerative …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 19–29 Read article
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Feasibility of 3D Printed Temporal Bone for surgical simulation and practice
Abstract: Temporal bone (Ear Bone) has the most complex anatomical structure in body. ENT Surgeons need lot of practice before doing any surgery. Dissecting cadaver temporal bone is best teaching aid available with ENT surgeons, but have several constrains like legal, ethical, religious ground etc., restricts the hands-on dissection training. Availability of cadaver temporal bone is also very limited; it also houses many infectious agents and viruses. With recent advancement in …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 147–154 Read article
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DC Motor Control using Deep Reinforcement Learning for Enhanced Robustness and Precision
Abstract: DC motors remain the workhorse of industrial automation and mobile robotics, but achieving simultaneous high-speed transient response and negligible steady-state error under variable load conditions continues to challenge classical Proportional-Integral-Derivative (PID) controllers. These model-dependent systems often require extensive tuning and struggle to maintain optimal performance when confronted with parametric uncertainties, non-linear friction, or sudden voltage fluctuations. This study presents a novel, model-free control paradigm utilizing Deep Reinforcement Learning (DRL)—specifically, a …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 22–29 Read article
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Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
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Routing Protocols in FANETs with Future Enhancements
Abstract: Flying Ad Hoc Networks (FANETs), which are swarms of Unmanned Aerial Vehicles (UAVs), are an emerging solution which revolutionized the area of mission-critical and infrastructure-less communication systems. These networks provide real-time data transfer for use cases such as disaster relief, battlefield observation, environmental monitoring, and 6G-based smart cities. However, the dynamic profile of FANETs, which is defined by high 3D mobility, limited energy resources, unstable wireless links, and constant topology …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 8–13 Read article
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Computer-aided Drug Design Method for Anti-hepatitis C Drug Design
Abstract: Hepatitis C is a disease caused by the hepatitis C virus and can cause serious liver damage. There is currently no vaccine for this disease and the number of infections continues to increase worldwide. Currently used antiviral drugs are interferon alfa-2a and ribavirin, but about half of patients do not respond to therapy. Therefore, new drugs that protect against hepatitis C need to be investigated. Computational drug methods have been …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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An Approach Towards Chatbot Using Speech Recognition
Abstract: Chatbot is software that, rather than facilitating direct interaction with a live human agent, conducts online conversations using text or text-to-speech. It is designed to accurately mimic human behavior during conversation. This paper presents a proposed chat system that dynamically responds to web-based customer queries. Speech recognition is the basis of the artificial intelligence used in the proposed system. The web-based platform provides a large intelligence base to help simulate …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 1, 2024 · pp. 1–5 Read article
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ML-Enhanced Self-Healing Fiber-Reinforced Polymer Composites with Embedded IoT Sensors for Damage Prediction
Abstract: Fiber-reinforced polymer (FRP) composites are widely used in aerospace and structural systems; nevertheless, the potential for microcracking and fatigue-induced performance degradation remains an obstacle with respect to improved service life. Traditional self-healing methods, while performing well on a chemical level, often lack real-time diagnostic awareness and adaptive control. To circumvent this, we developed a machine-learning augmented self-healing FRP composite, in which a DCPD–Grubbs catalytic matrix was combined with IoT sensor …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 188–208 Read article
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Exploration of Diverse Epoxy-Based Surface Coating Methods for Enhancing Anticorrosion Characteristics
Abstract: Epoxy-based polymers, commonly referred to as polyepoxides, constitute one of the most versatile and widely adopted categories of polymeric materials due to their exceptional structural, mechanical, and chemical characteristics. Their unique macromolecular framework enables strong interfacial bonding, high mechanical stability, and superior resistance to environmental and chemical degradation, positioning them as advanced alternatives to many traditional organic corrosion inhibitors that often fail under prolonged exposure to aggressive conditions When polyepoxides …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 167–177 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Green Synthesis of Copper Nanoparticle for the Treatment of Neurodegenerative Disease
Abstract: The study of ecologically friendly CuNP synthesis is a growing area with potential applications in biomedical research and environmental remediation, as well as sustainable nanotechnology. Generally, reducing, and stabilizing agents such as microbes, plant extracts, or other natural sources are used. The green synthesis methodology guarantees the production of nanoparticles with desired characteristics for biomedical applications while simultaneously mitigating the environmental effect that comes with conventional chemical processes. CuNPs possess …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 14, Issue 1, 2024 · pp. 13–24 Read article
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A Strategy of Nano-Calcite Fillers for Enhancing the Mechanical and Thermal Properties of Polypropylene Polymers
Abstract: Particulate polymer composites have gained popularity because of their many uses. For some, using high loadings to achieve desired attributes without compromising the material's mechanical properties or restricting its processability is desirable. It is possible to use surface active agents to improve characteristics and increase solid loading. Interface characteristics in highly packed particulate composites based on nano-calcite (nano-calcium carbonate) and polypropylene as a binder are the focus of the current …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 1, 2025 · pp. 20–29 Read article
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Gold Nanoparticle Size, Biodistribution, and Toxicity: Insights from DualEnergy CT
Abstract: Dual-energy and spectral computed tomography (CT) have emerged as powerful platforms for noninvasive, quantitative mapping of nanoparticle biodistribution in vivo. By exploiting the energy-dependent attenuation profiles of high-atomic-number (high-Z) materials, these systems enable material decomposition and element-specific imaging, thereby distinguishing nanoparticle signals from those of soft tissues and conventional iodinated contrast agents. Photon-counting spectral CT further enhances this capability by binning individual photons into multiple energy channels, improving spatial resolution, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article