Safeer Alam

38 papers receiving 265 citations

Peers

Safeer Alam
Comparison fields: 5 of 90
  • Marketing 78
  • Business and International Management 12
  • Strategy and Management 73
  • Animal Science and Zoology 31
  • Agronomy and Crop Science 26
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Citations per year

Countries citing papers authored by Safeer Alam

Since Specialization
Citations

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

Fields of papers citing papers by Safeer Alam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Safeer Alam, 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 Safeer Alam Line = papers co-authored together Safeer Alam links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202195
2 202428
3 201124
4 202216
5 202112
6
Corporate Social Responsibility (CSR) of MNCs in Bangladesh: A Case Study on GrameenPhone Ltd.
201011
7 20109
8
Reproductive performance of Beetal goats in its breeding tract
20078
9
EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed TarekShahriar Abstract—An EMD-chaos based approach is proposed todiscriminate EEG signals corresponding to healthy persons,and epileptic patients during seizure-free intervals and seizureattacks. An electroencephalogram (EEG) is first empiricallydecomposed to intrinsic mode functions (IMFs). The nonlineardynamics of these IMFs are quantified in terms of the largestLyapunov exponent (LLE) and correlation dimension (CD).This chaotic analysis in EMD domain is applied to a large groupof EEG signals corresponding to healthy persons as well asepileptic patients (both with and without seizure attacks). It isshown that the values of the obtained LLE and CD exhibitfeatures by which EEG for seizure attacks can be clearlydistinguished from other EEG signals in the EMD domain.Thus, the proposed approach may aid researchers in developingeffective techniques to predict seizure activities. Index Terms—Electroencephalogram (EEG), empiricalmode decomposition (EMD), largest Lyapunov exponent (LLE),correlation dimension (CD), epileptic seizures. The Authors are with the Electrical and Electronic EngineeringDepartment, Bangladesh University of Engineering and Technology,Dhaka-1000, Bangladesh (e-mail: imamul@eee.buet.ac.bd) [PDF] Cite: S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed Tarek Shahriar, "EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain," International Journal of Computer and Electrical Engineering vol. 4, no. 3, pp. 326-330, 2012. PREVIOUS PAPER Perception of Emotions Using Constructive Learningthrough Speech NEXT PAPER Physical Layer Impairments Aware OVPN Connection Selection Mechanisms Copyright © 2008-2013. International Association of Computer Science and Information Technology Press (IACSIT Press)
20128
10 20207
11 20217
12 20226
13 20215
14
Morphological studies and management of Beetal goats in its native tract
20083
15 20173
16 20202
17
Genetics of some reproduction traits in some sheep breeds from India: A review
20202
18
Exon IV prolactin (PRL) gene polymorphism and its association with milk production traits in dairy cattle of Kashmir, India
20212
19 20212
20 20232

About Safeer Alam

Safeer Alam is a scholar working on Genetics, Agronomy and Crop Science, General Agricultural and Biological Sciences, Animal Science and Zoology and Marketing, having authored 43 papers that have together received 272 indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (18 papers), Livestock Management and Performance Improvement (13 papers), Agricultural Economics and Practices (8 papers), Effects of Environmental Stressors on Livestock (4 papers), Environmental Sustainability in Business (4 papers), Technology Adoption and User Behaviour (3 papers), Reproductive Physiology in Livestock (3 papers) and Innovation and Socioeconomic Development (2 papers). The work is most often cited by research in Marketing (78 citations), Business and International Management (12 citations), Strategy and Management (73 citations), Animal Science and Zoology (31 citations) and Agronomy and Crop Science (26 citations). Safeer Alam has collaborated with scholars based in India, Bangladesh and Oman. Frequent co-authors include K.M. Zahidul Islam, Nazir Ahmad Ganai, Syed Shanaz, Abdullah Al Masud, Ambreen Hamadani, Md. Alamgir Hossain, Nusrat Nabi Khan, Syed Mudasir Ahmad, Agus Rizal Ardy Hariandy Hamid and Syed Sameer Aga. Their work appears in journals such as Small Ruminant Research, Tropical Animal Health and Production, Scientific Reports, Cleaner Logistics and Supply Chain and IEEE Engineering Management Review.

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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