Reiji Tomiku

454 total citations
36 papers, 342 citations indexed

About

Reiji Tomiku is a scholar working on Biomedical Engineering, Cognitive Neuroscience and Civil and Structural Engineering. According to data from OpenAlex, Reiji Tomiku has authored 36 papers receiving a total of 342 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Biomedical Engineering, 11 papers in Cognitive Neuroscience and 7 papers in Civil and Structural Engineering. Recurrent topics in Reiji Tomiku's work include Acoustic Wave Phenomena Research (27 papers), Hearing Loss and Rehabilitation (11 papers) and Noise Effects and Management (7 papers). Reiji Tomiku is often cited by papers focused on Acoustic Wave Phenomena Research (27 papers), Hearing Loss and Rehabilitation (11 papers) and Noise Effects and Management (7 papers). Reiji Tomiku collaborates with scholars based in Japan, Malaysia and Thailand. Reiji Tomiku's co-authors include Toru Otsuru, Takeshi Okuzono, Yasuo Takahashi, Nazli Bin Che Din, Hiroyasu Nishiguchi, Yosuke Yasuda, Noriaki Sakamoto, Makoto Yamaguchi and Kensuke Harada and has published in prestigious journals such as Construction and Building Materials, The Journal of the Acoustical Society of America and Applied Acoustics.

In The Last Decade

Reiji Tomiku

35 papers receiving 327 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Reiji Tomiku Japan 10 254 102 77 63 63 36 342
Toru Otsuru Japan 11 298 1.2× 116 1.1× 87 1.1× 66 1.0× 80 1.3× 46 396
Mirosław Meissner Poland 11 261 1.0× 113 1.1× 77 1.0× 39 0.6× 25 0.4× 42 330
Eckard Mommertz Germany 7 194 0.8× 128 1.3× 22 0.3× 36 0.6× 21 0.3× 12 296
Raffaele Dragonetti Italy 11 170 0.7× 26 0.3× 95 1.2× 64 1.0× 25 0.4× 34 314
Duncan Templeton United Kingdom 5 193 0.8× 22 0.2× 64 0.8× 90 1.4× 165 2.6× 7 499
Bryan H. Song United States 6 364 1.4× 32 0.3× 123 1.6× 94 1.5× 21 0.3× 14 465
Shaowu Ning China 8 305 1.2× 49 0.5× 45 0.6× 115 1.8× 17 0.3× 11 446
Yasushi Miki Japan 4 546 2.1× 44 0.4× 169 2.2× 75 1.2× 38 0.6× 9 592
Karsten Bo Rasmussen Denmark 12 269 1.1× 26 0.3× 152 2.0× 24 0.4× 36 0.6× 34 435
Teresa Pàmies Spain 9 188 0.7× 76 0.7× 58 0.8× 74 1.2× 14 0.2× 33 339

Countries citing papers authored by Reiji Tomiku

Since Specialization
Citations

This map shows the geographic impact of Reiji Tomiku'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 Reiji Tomiku with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reiji Tomiku more than expected).

Fields of papers citing papers by Reiji Tomiku

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Reiji Tomiku. 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 Reiji Tomiku. The network helps show where Reiji Tomiku may publish in the future.

Co-authorship network of co-authors of Reiji Tomiku

This figure shows the co-authorship network connecting the top 25 collaborators of Reiji Tomiku. A scholar is included among the top collaborators of Reiji Tomiku 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 Reiji Tomiku. Reiji Tomiku 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.
Otsuru, Toru, et al.. (2020). Applying the ensemble averaging method with a pressure–velocity sensor to measure sound absorption characteristics of porous clay bricks. Applied Acoustics. 164. 107250–107250. 4 indexed citations
2.
Otsuru, Toru, et al.. (2019). Investigating the practicability of an ensemble averaging method for measuring sound absorption and surface normal impedance. Applied Acoustics. 156. 166–175. 5 indexed citations
3.
4.
Tomiku, Reiji, et al.. (2018). Flanking floor impact sound insulation in cross laminated timber model building for experiment. Journal of Physics Conference Series. 1075. 12023–12023. 1 indexed citations
5.
6.
Otsuru, Toru, et al.. (2017). DEVELOPMENT OF CONSTRUCTION CONDITION MANAGEMENT SYSTEM BY ABSORPTION CHARACTERISTICS MEASUREMENT OF BUILDING MATERIALS. AIJ Journal of Technology and Design. 23(54). 517–520.
7.
Tomiku, Reiji, et al.. (2015). APPLICATION OF AN IN-SITU MEASUREMENT METHOD USING ENSEMBLE AVERAGING TECHNIQUE TO MATERIAL DEVELOPMENT. AIJ Journal of Technology and Design. 21(47). 167–170. 1 indexed citations
8.
Okuzono, Takeshi, et al.. (2014). A finite-element method using dispersion reduced spline elements for room acoustics simulation. Applied Acoustics. 79. 1–8. 39 indexed citations
9.
Otsuru, Toru, et al.. (2013). A Practical System to Predict the Absorption Coefficient, Dimension and Reverberation Time of Room using GLCM, DVP and Neural Network. International Journal of Automotive and Mechanical Engineering. 8. 1256–1266. 2 indexed citations
10.
Din, Nazli Bin Che, et al.. (2012). Measurement method with a pressure-velocity sensor for measuring surface normal impedance of materials using ensemble averaging: Comparison with other methods and its geometrical configuration. Nippon Onkyo Gakkaishi/Acoustical science and technology/Nihon Onkyo Gakkaishi. 33(2). 86–95. 12 indexed citations
11.
Otsuru, Toru, et al.. (2010). Investigation the capability of neural network in predicting reverberation time on classroom. International Journal of Sustainable Construction Engineering Technology. 1(1). 19–32. 5 indexed citations
12.
Otsuru, Toru, et al.. (2009). Ensemble averaged surface normal impedance of material using an in-situ technique: Preliminary study using boundary element method. The Journal of the Acoustical Society of America. 125(6). 3784–3791. 25 indexed citations
13.
Okuzono, Takeshi, et al.. (2008). SOUND FIELD ANALYSIS OF ROOMS BY TIME DOMAIN FINITE ELEMENT METHOD WITH AN ITERATIVE METHOD. Journal of Environmental Engineering (Transactions of AIJ). 73(628). 701–706. 2 indexed citations
14.
Otsuru, Toru, et al.. (2008). 429 Time Domain Sound Field Analysis of Rooms by Finite element Method. : A investigation of setting of acoustic impedance.. 113–116. 1 indexed citations
15.
Takahashi, Yasuo, Toru Otsuru, & Reiji Tomiku. (2005). In situ measurements of surface impedance and absorption coefficients of porous materials using two microphones and ambient noise. Applied Acoustics. 66(7). 845–865. 61 indexed citations
16.
Otsuru, Toru, et al.. (2004). A STUDY ON ACOUSTIC ENVIRONMENT AT WAITING AREAS IN HOSPITALS. Journal of Environmental Engineering (Transactions of AIJ). 69(584). 9–16. 1 indexed citations
17.
Otsuru, Toru, et al.. (2004). 431 Accuracy of sound field analysis used a round robin test on Computational method for Environmental Acoustics : Sound Field Analysis by Finite Element Method. 121–124. 1 indexed citations
18.
Tomiku, Reiji & Toru Otsuru. (2002). SOUND FIELDS ANALYSIS IN AN IRREGULAR-SHAPED REVERBERATION ROOM BY FINITE ELEMENT METHOD. Journal of Architecture and Planning (Transactions of AIJ). 67(551). 9–15. 8 indexed citations
19.
Tomiku, Reiji, Toru Otsuru, & Yasuo Takahashi. (2002). Finite Element Sound Field Analysis of Diffuseness in Reverberation Rooms. Journal of Asian Architecture and Building Engineering. 1(2). 33–39. 10 indexed citations
20.
Otsuru, Toru & Reiji Tomiku. (2000). Basic characteristics and accuracy of acoustic element using spline function in finite element sound field analysis.. Journal of the Acoustical Society of Japan (E). 21(2). 87–95. 25 indexed citations

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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