Hideyuki Kawashima

65 papers receiving 271 citations

Peers

Hideyuki Kawashima
Comparison fields: 5 of 37
  • Computer Networks and Communications 236
  • Information Systems 82
  • Artificial Intelligence 72
  • Signal Processing 68
  • Hardware and Architecture 60
Replace Hameed Hussain with:
Hameed Hussain Pakistan
Qingchao Cai Singapore
Shengfei Shi China
Juncheng Yang United States
Philipp M. Grulich Germany
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Prashanth Menon United States
Meiyuan Zhao United States
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Citations per field
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Citations per year

Countries citing papers authored by Hideyuki Kawashima

Since Specialization
Citations

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

Fields of papers citing papers by Hideyuki Kawashima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hideyuki Kawashima

This figure shows the co-authorship network connecting the top 25 collaborators of Hideyuki Kawashima. A scholar is included among the top collaborators of Hideyuki Kawashima 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 Hideyuki Kawashima. Hideyuki Kawashima 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
#WorkIndexed citations
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11 20
12
FPGA-based Implementation of Sliding-Window Aggregates over Disordered Data Streams
3
13
A software implementation and evaluation for searching and extracting information of application layer from network traffic
5
14
A Consideration of Window Join Operator over Data Streams by using FPGA
1
15
Hardware Architecture for Supporting High-speed Database Insertion on Service-oriented Router for Future Internet.
3
16
RSV: sensor data viewer for human-robot interaction
1
17 1
18 4
19
Contents Selection Method Based on a User Interest on the Interactive News Announcer Robot
2
20
Lagos: Context management system for a sensor-robot network
2

About Hideyuki Kawashima

Hideyuki Kawashima is a scholar working on Computer Networks and Communications, Hardware and Architecture and Signal Processing, having authored 75 papers that have together received 287 indexed citations. Recurring topics across this work include Distributed systems and fault tolerance (29 papers), Advanced Data Storage Technologies (28 papers) and Advanced Database Systems and Queries (17 papers). The work is most often cited by research in Computer Networks and Communications (236 citations), Hardware and Architecture (60 citations) and Signal Processing (68 citations). Hideyuki Kawashima has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Hiroyuki Kitagawa, Osamu Tatebe, Takashi Hoshino, Tsutomu Yoshinaga, Xin Li, Michita Imai, Satoru Satake, Zhitao Shen, Masato Edahiro and Anh‐Tu Nguyen. Their work appears in journals such as IEEE Transactions on Parallel and Distributed Systems, Proceedings of the VLDB Endowment and Concurrency and Computation Practice and Experience.

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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