Journal of Advanced Simulation in Science and Engineering

Scope & Guideline

Exploring Innovative Frontiers in Simulation Technology

Introduction

Delve into the academic richness of Journal of Advanced Simulation in Science and Engineering with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN2188-5303
PublisherJAPAN SOC SIMULATION TECHNOLOGY-JSST
Support Open AccessNo
Country-
Type-
Converge-
AbbreviationJ ADV SIMUL SCI ENG / J. Adv. Simul. Sci. Eng.
Frequency-
Time To First Decision-
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Acceptance Rate-
Home Page-
AddressTENJINCHO 78, SHINJUKU-KU, TOKYO 162-0808, JAPAN

Aims and Scopes

The Journal of Advanced Simulation in Science and Engineering focuses on advancing the field of simulation across various scientific and engineering domains. It aims to publish high-quality research that contributes to theoretical and practical advancements in simulation methodologies, applications, and technological innovations.
  1. Simulation Methodologies:
    The journal emphasizes the development and refinement of simulation techniques, including numerical methods, machine learning approaches, and advanced computational algorithms.
  2. Interdisciplinary Applications:
    It covers a broad range of applications in fields such as material science, biomedical engineering, environmental science, and aerospace, showcasing how simulation can solve complex real-world problems.
  3. Emerging Technologies:
    The journal pays special attention to the integration of emerging technologies like artificial intelligence, additive manufacturing, and virtual reality in simulation practices.
  4. Data Analysis and Modeling:
    Research focusing on data analysis techniques, including big data and machine learning applications, is a core area, highlighting the importance of data-driven simulation.
  5. Theoretical Foundations:
    The journal also delves into the theoretical underpinnings of simulation methods, exploring mathematical models and their implications in scientific research.
Recent publications in the Journal of Advanced Simulation in Science and Engineering reveal several emerging themes that signify the journal's responsiveness to current scientific and technological advancements. These trends reflect a growing interest in innovative simulation techniques and their applications.
  1. Machine Learning Integration:
    There is a significant increase in the application of machine learning techniques to enhance simulation accuracy and efficiency, indicating a trend towards data-driven methodologies.
  2. Advanced Material Simulations:
    Research focusing on the simulation of advanced materials, including additive manufacturing and molecular dynamics, is gaining traction, reflecting its relevance in modern engineering.
  3. Healthcare and Biomedical Applications:
    Emerging themes in healthcare simulation, particularly in medical training and nuclear medicine, underscore the journal's commitment to addressing pressing societal challenges.
  4. Environmental and Disaster Management Simulations:
    Papers addressing disaster response systems and environmental simulations indicate a growing emphasis on using simulation for societal benefits and crisis management.
  5. Virtual and Augmented Reality in Simulation:
    The incorporation of virtual and augmented reality into simulation methodologies is increasingly prevalent, showcasing the journal's focus on cutting-edge technologies that enhance user experience and interaction.

Declining or Waning

While the Journal of Advanced Simulation in Science and Engineering has a diverse range of topics, some areas have shown a declining interest in recent publications. This reflects the evolving nature of research priorities and the journal's adaptation to emerging trends.
  1. Traditional Numerical Techniques:
    There appears to be a waning focus on classical numerical methods without integration of modern approaches, as newer techniques gain prominence.
  2. Generalized Applications:
    Papers that address broad or generalized applications without specific case studies seem to be less frequent, signaling a shift towards more specialized and detailed research.
  3. Basic Theoretical Research:
    There is a noticeable decline in publications focused solely on basic theoretical research, as practical applications and interdisciplinary studies become more favored.
  4. Static Simulations:
    Static or less dynamic simulation studies are less represented, with a growing demand for simulations that incorporate real-time data and dynamic modeling.
  5. Non-Interdisciplinary Approaches:
    Research that does not integrate insights from multiple disciplines is becoming less common, highlighting a trend towards interdisciplinary collaboration.

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