| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 706 | 23 | 18 | 7 |
| Engineering and Technology | 1143 | 10 | 20 | 6 |
The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology primarily focuses on research topics in Computer security, Modeling and simulation, Systems engineering, Operations research and Simulation. In addition to Computer security research, the journal aims to explore topics under Situation awareness and Command and control. The DEVS studies presented in The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology fall under the field of Modeling and simulation, but it also has connections to other fields such as Simulation modeling.
While the journal focused on Systems engineering, it was also able to explore topics like Software engineering, Interoperability and Process (engineering).
The main points discussed in the published papers deal with Systems engineering, Software engineering, Process (engineering), Modeling and simulation and Computer security. The journal articles explore themes in Systems engineering like DEVS and link them with other fields of study like Completeness (order theory). The journal papers address concerns in Modeling and simulation which are intertwined with other disciplines, such as Distributed computing, Composability, Interoperation, Interoperability and Submarine.
The main research concerns discussed in The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology are Artificial intelligence, Constructive, Systems engineering, Machine learning and Optics. Topics in Artificial intelligence explored in The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology were investigated in conjunction with research in Signal and Pattern recognition. Attendees participated in lively discussions that mix various fields of study, including Constructive and Force protection, Aerial reconnaissance, SWORD, Discrete time and continuous time and Real-time computing.
Systems engineering research featured in The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology incorporates concerns from various other topics such as Air combat, Human machine interaction, Wargame, Situation awareness and Command and control. Many of the research works in Machine learning, specifically Curse of dimensionality and Reinforcement learning, closely connected to disciplines like Training (meteorology) and Environmental remediation. Most of the Optics studies addressed also intersect with Warhead.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 8.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 43.48% were posted by at least one author from the top 10 institutions publishing in the journal. Another 4.35% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 17.39% of all publications and 34.78% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
An essential aspect that is crucial to understand the diversity of a journal's authorship is the demographic data, such as their geographical location, academic background, and professional roles. For example, examining the academic background and professional roles can reveal valuable insights into the journal composition. Is it primarily comprised of researchers or practitioners? Do we see a fair representation of teachers or students who are shaping and contributing to the field, such as those aspiring to be a high school history teacher in South Dakota? Similarly, the geographical data can help in understanding the scope of the journal. Does it attract submissions globally, or is it regionally focused? What countries stand out for their contribution to the journal? The information can be gathered by carefully examining the affiliations and biographical information of the authors in the journal edition under review. Here, it is crucial to respect privacy and confidentiality, making sure not to disclose private information unless it is necessary and permitted. Collecting and analyzing this data can give us a broader perspective on the demographics of the contributing authors to The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology.
Dipankar Dasgupta;Zahid Akhtar;Sajib Sen
(2020)Krzysztof Fiok;Farzad V Farahani;Waldemar Karwowski;Tareq Ahram
(2021)Erim Yanik;Xavier Intes;Uwe Kruger;Pingkun Yan
(2021)Ravi Shankar
(2020)Bhanu Pratap Chaudhary;Ravi Shankar;Ritesh Kumar Mishra
(2021)Ksm Tozammel Hossain;Shuyang Gao;Brendan Kennedy;Aram Galstyan
(2020)Randall Spain;Jonathan Rowe;Andy Smith;Benjamin Goldberg
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