Alfred Daniel

942 citations
46 papers · 557 · h-index 12

Impact in

Papers in

Alfred Daniel

44 papers receiving 527 citations

Peers

Alfred Daniel
Comparison fields: 5 of 90
  • Computer Networks and Communications 145
  • Building and Construction 72
  • Automotive Engineering 57
  • Computer Vision and Pattern Recognition 94
  • Information Systems 88
Replace Young-Guk Ha with:
Young-Guk Ha South Korea
Hariprasath Manoharan Saudi Arabia
Hanan Abdullah Mengash Saudi Arabia
Huyin Zhang China
Susanna Pirttikangas Finland
José Javier Astráin Spain
Nouman Ashraf Pakistan
Revathi Sundarasekar India
Vijender Kumar Solanki India
Harun Jamil South Korea
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Citations per field
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Citations per year

Countries citing papers authored by Alfred Daniel

Since Specialization
Citations

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

Fields of papers citing papers by Alfred Daniel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Alfred Daniel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Alfred Daniel Line = papers co-authored together Alfred Daniel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015125
2 201553
3 202346
4 202034
5 201732
6
Intelligent Vehicular Networks and Communications: Fundamentals, Architectures and Solutions
201624
7 200822
8 202321
9 202317
10 202016
11 202216
12 201515
13 202311
14 201410
15 202110
16 201810
17 20239
18 20158
19 20238
20 20218

About Alfred Daniel

Alfred Daniel is a scholar working on Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems and Computer Vision and Pattern Recognition, having authored 46 papers that have together received 557 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (6 papers), Vehicular Ad Hoc Networks (VANETs) (5 papers), Cognitive Radio Networks and Spectrum Sensing (4 papers), Smart Grid Energy Management (3 papers), Air Quality Monitoring and Forecasting (3 papers), Traffic Prediction and Management Techniques (3 papers), Data Management and Algorithms (2 papers) and Sentiment Analysis and Opinion Mining (2 papers). The work is most often cited by research in Computer Networks and Communications (145 citations), Building and Construction (72 citations), Automotive Engineering (57 citations), Computer Vision and Pattern Recognition (94 citations) and Information Systems (88 citations). Alfred Daniel has collaborated with scholars based in India, South Korea and China. Frequent co-authors include Anand Paul, Seungmin Rho, Awais Ahmad, BalaAnand Muthu, C. B. Sivaparthipan, Carlos Montenegro, R. Santhosh, M. Mazhar Rathore, Naveen Chilamkurti and S. Iniyan. Their work appears in journals such as Electronics, Journal of Combinatorial Optimization, Multimedia Tools and Applications, Wireless Personal Communications and Vehicular Communications.

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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