Mıshra, Deepti

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Profile URL
https://hdl.handle.net/20.500.14411/7868
Name Variants
Deepti, Mıshra
Deepti, Mishra
M.,Deepti
M., Deepti
Mishra,D.
D.,Mıshra
Mishra, Deepti
Mıshra, Deepti
Mıshra,D.
D.,Mishra
D., Mishra
Mıshra, Deeptı
Mishra, D
Job Title
Doktor Öğretim Üyesi
Email Address
Main Affiliation
Computer Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
Research Products
GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
8
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
4
Research Products
GENDER EQUALITY5
GENDER EQUALITY
1
Research Products
CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
Research Products
AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
2
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
3
Research Products
CLIMATE ACTION13
CLIMATE ACTION
4
Research Products
LIFE BELOW WATER14
LIFE BELOW WATER
4
Research Products
LIFE ON LAND15
LIFE ON LAND
0
Research Products
PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
3
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
1
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

102

Articles

41

Views / Downloads

55/63

Supervised MSc Theses

4

Supervised PhD Theses

1

WoS Citation Count

930

Scopus Citation Count

1312

Patents

0

Projects

0

WoS Citations per Publication

9.12

Scopus Citations per Publication

12.86

Open Access Source

13

Supervised Theses

5

JournalCount
Acta Polytechnica Hungarica4
Computer Standards & Interfaces3
Confederated International Workshops and Posters: EI2N plus NSF ICE, ICSP plus INBAST, ISDE, ORM, OTMA, SWWS plus MONET plus SeDeS, and VADER -- OCT 17-21, 2011 -- Hersonissos, GREECE3
Tehnicki Vjesnik3
Journal of Universal Computer Science3
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Start date: 2020Subject: [No Keyword Available]

Scholarly Output Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Book Part
    Citation - Scopus: 12
    Sustainable Software Engineering: Curriculum Development Based on Acm/Ieee Guidelines
    (Springer International Publishing, 2021) Mishra,A.; Mishra,D.
    Climate change risk and environmental degradation are the most critical issues of our society. Our technology-influenced daily lifestyle involves many types of software and apps which are used by society at large, and their use is increasing more than ever before. Sustainability is a significant topic for future professionals and more so for software engineers due to its impact on society. It is crucial to motivate and raise concern among students and faculty members regarding sustainability by including it in the Software Engineering (SE) curriculum. This chapter discusses how sustainability can be included in various courses of the SE curriculum by considering ACM/IEEE curriculum guidelines for the SE curriculum, literature review, and various viewpoints so that SE students can attain knowledge on sustainable software engineering. It also includes an assessment of key competences in sustainability for proposed units in the SE curriculum. © Springer Nature Switzerland AG 2021. All rights reserved.
  • Thumbnail Image
    Article
    Citation - WoS: 34
    Citation - Scopus: 41
    A Computationally Efficient Method for Hybrid Eeg-Fnirs Bci Based on the Pearson Correlation
    (Hindawi Ltd, 2020) Hasan, Mustafa A. H.; Khan, Muhammad U.; Mishra, Deepti
    A hybrid brain computer interface (BCI) system considered here is a combination of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). EEG-fNIRS signals are simultaneously recorded to achieve high motor imagery task classification. This integration helps to achieve better system performance, but at the cost of an increase in system complexity and computational time. In hybrid BCI studies, channel selection is recognized as the key element that directly affects the system's performance. In this paper, we propose a novel channel selection approach using the Pearson product-moment correlation coefficient, where only highly correlated channels are selected from each hemisphere. Then, four different statistical features are extracted, and their different combinations are used for the classification through KNN and Tree classifiers. As far as we know, there is no report available that explored the Pearson product-moment correlation coefficient for hybrid EEG-fNIRS BCI channel selection. The results demonstrate that our hybrid system significantly reduces computational burden while achieving a classification accuracy with high reliability comparable to the existing literature.