Marjorie Darrah

721 total citations
42 papers, 488 citations indexed

About

Marjorie Darrah is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Aerospace Engineering. According to data from OpenAlex, Marjorie Darrah has authored 42 papers receiving a total of 488 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 8 papers in Aerospace Engineering. Recurrent topics in Marjorie Darrah's work include Robotic Path Planning Algorithms (8 papers), Neural Networks and Applications (6 papers) and Fault Detection and Control Systems (5 papers). Marjorie Darrah is often cited by papers focused on Robotic Path Planning Algorithms (8 papers), Neural Networks and Applications (6 papers) and Fault Detection and Control Systems (5 papers). Marjorie Darrah collaborates with scholars based in United States, Iraq and China. Marjorie Darrah's co-authors include Brian J. Taylor, Kristen L. Murphy, Edgar Fuller, James J. Nolan, Lei Wang, Laura Pullum, Jay Wilhelm, James G. Hougland, Mridul Gautam and Mark J. Webb and has published in prestigious journals such as Sensors, Information Sciences and The Scientific World JOURNAL.

In The Last Decade

Marjorie Darrah

39 papers receiving 459 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Marjorie Darrah United States 13 132 113 110 97 88 42 488
David Bull United Kingdom 14 251 1.9× 69 0.6× 94 0.9× 121 1.2× 138 1.6× 50 1.2k
Pramod Abichandani United States 14 132 1.0× 20 0.2× 106 1.0× 53 0.5× 108 1.2× 34 497
Qi Cao China 14 143 1.1× 22 0.2× 49 0.4× 121 1.2× 33 0.4× 113 584
Bo Jiang China 13 287 2.2× 58 0.5× 45 0.4× 148 1.5× 62 0.7× 68 646
Seongsoo Lee South Korea 16 266 2.0× 42 0.4× 163 1.5× 47 0.5× 194 2.2× 100 1.1k
Moustafa M. Nasralla Saudi Arabia 19 148 1.1× 42 0.4× 205 1.9× 160 1.6× 424 4.8× 92 1.1k
Yang Jiang China 15 130 1.0× 75 0.7× 18 0.2× 160 1.6× 43 0.5× 55 629
F. Jakab Slovakia 10 104 0.8× 41 0.4× 19 0.2× 63 0.6× 100 1.1× 100 419
Mau‐Tsuen Yang Taiwan 14 322 2.4× 50 0.4× 91 0.8× 64 0.7× 44 0.5× 28 564
Dino Schweitzer United States 12 177 1.3× 57 0.5× 13 0.1× 71 0.7× 38 0.4× 45 639

Countries citing papers authored by Marjorie Darrah

Since Specialization
Citations

This map shows the geographic impact of Marjorie Darrah's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marjorie Darrah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marjorie Darrah more than expected).

Fields of papers citing papers by Marjorie Darrah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marjorie Darrah. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marjorie Darrah. The network helps show where Marjorie Darrah may publish in the future.

Co-authorship network of co-authors of Marjorie Darrah

This figure shows the co-authorship network connecting the top 25 collaborators of Marjorie Darrah. A scholar is included among the top collaborators of Marjorie Darrah based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marjorie Darrah. Marjorie Darrah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Darrah, Marjorie, et al.. (2022). Self-efficacy, mindfulness, and self-compassion as predictors of math anxiety in undergraduate students. International Journal of Mathematical Education in Science and Technology. 55(4). 883–898. 9 indexed citations
2.
Darrah, Marjorie, et al.. (2022). Analyzing the Growth of a Statewide Network to Increase Recruitment to and Persistence in STEM. 28(2). 188–212. 1 indexed citations
3.
Darrah, Marjorie, et al.. (2022). Optimal LiDAR Data Resolution Analysis for Object Classification. Sensors. 22(14). 5152–5152. 1 indexed citations
4.
Darrah, Marjorie, et al.. (2020). Rule Insertion Technique for Dynamic Cell Structure Neural Network. 7. 1 indexed citations
5.
Fuller, Edgar, et al.. (2019). Affective States of University Developmental Mathematics Students and their Impact on Self-Efficacy, Belonging, Career Identity, Success and Persistence. International Journal of Research in Undergraduate Mathematics Education. 5(3). 337–358. 10 indexed citations
6.
Fuller, Edgar, et al.. (2019). Supporting Students through Peer Mentoring in Developmental Mathematics.. 24(1). 87–112. 3 indexed citations
7.
Darrah, Marjorie, et al.. (2019). Analysis of Forest Fire Data Using Neural Network Rule Extraction with Human Understandable Rules. 1917–19176. 3 indexed citations
8.
Murphy, Kristen L. & Marjorie Darrah. (2015). Haptics-Based Apps for Middle School Students with Visual Impairments. IEEE Transactions on Haptics. 8(3). 318–326. 18 indexed citations
9.
Darrah, Marjorie, et al.. (2014). Salary, Space, and Satisfaction: An Examination of Gender Differences in the Sciences.. Research in higher education journal. 23. 7 indexed citations
10.
Darrah, Marjorie, et al.. (2014). Are Virtual Labs as Effective as Hands-on Labs for Undergraduate Physics? A Comparative Study at Two Major Universities. Journal of Science Education and Technology. 23(6). 803–814. 102 indexed citations
11.
Darrah, Marjorie, et al.. (2014). Analyses of Crime Patterns in NIBRS Data Based on a Novel Graph Theory Clustering Method: Virginia as a Case Study. The Scientific World JOURNAL. 2014. 1–8. 1 indexed citations
12.
Stylinski, Cathlyn, et al.. (2010). Innovative uses of IT applications in STEM classrooms: A preliminary review of ITEST teacher professional development. The Journal of Technology and Teacher Education. 18(2). 203–230. 1 indexed citations
13.
Darrah, Marjorie, Edgar Fuller, & David Miller. (2010). A Comparative Study of Partial Credit Assessment and Computer-Based Testing. EdMedia: World Conference on Educational Media and Technology. 2010(1). 2335–2340. 1 indexed citations
14.
Darrah, Marjorie, Edgar Fuller, & David Miller. (2010). A Comparative Study of Partial Credit Assessment and Computer-Based Testing for Mathematics. Journal of Computers in Mathematics and Science Teaching. 29(4). 373–398. 1 indexed citations
15.
Darrah, Marjorie & Amy Blake. (2009). Providing Real World Experience for High School Teachers and Students. Society for Information Technology & Teacher Education International Conference. 2009(1). 3390–3394. 2 indexed citations
16.
Pullum, Laura, Brian J. Taylor, & Marjorie Darrah. (2007). Guidance for the Verification and Validation of Neural Networks (Emerging Technologies). 2 indexed citations
17.
Darrah, Marjorie, et al.. (2006). Multiple UAV Task Allocation for an Electronic Warfare Mission Comparing Genetic Algorithms and Simulated Annealing (Preprint). Defense Technical Information Center (DTIC). 1 indexed citations
18.
Darrah, Marjorie, Brian J. Taylor, & Mark J. Webb. (2005). A GEOMETRIC RULE EXTRACTION APPROACH USED FOR VERIFICATION AND VALIDATION OF A SAFETY CRITICAL APPLICATION. The Florida AI Research Society. 3(18). 624–627. 4 indexed citations
19.
Darrah, Marjorie, et al.. (2004). Rule Extraction From Dynamic Cell Structure Neural Network Used in a Safety Critical Application.. The Florida AI Research Society. 629–634. 14 indexed citations
20.
Darrah, Marjorie, et al.. (2002). Improvement Of Hubble Space Telescope Subsystems Through Data Mining. WIT transactions on information and communication technologies. 28.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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