Mıshra, Alok

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14411/6902
Name Variants
Mishra, A.
Mishra, A
Mishra A.
Alok, Mishra
Mıshra, Alok
A., Mishra
Alok M.
M., Alok
M.,Alok
Mishra, Alok
Mishra,A.
A.,Mıshra
A.,Mishra
Alok, Mıshra
A., Mıshra
Mıshra,A.
Job Title
Profesor Doktor
Email Address
alok.mishra@atilim.edu.tr
Main Affiliation
Software Engineering
Status
Website
ORCID ID
0000-0003-1275-2050
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
AAE-2673-2019

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
1
Research Products
GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
9
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
6
Research Products
GENDER EQUALITY5
GENDER EQUALITY
1
Research Products
CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
1
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
8
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
4
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
4
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
10
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
2
Research Products
This researcher does not have a Scopus ID.
Documents

170

Citations

2551

Go to WoS profile
Scholarly Output

197

Articles

103

Views / Downloads

726/2439

Supervised MSc Theses

13

Supervised PhD Theses

8

WoS Citation Count

2074

Scopus Citation Count

3043

Patents

0

Projects

0

WoS Citations per Publication

10.53

Scopus Citations per Publication

15.45

Open Access Source

42

Supervised Theses

21

JournalCount
Sensors7
TEM Journal7
Computers in Human Behavior4
Applied Sciences4
Electronics Information and Planning4
Current Page: 1 / 22

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud
Start date: 2002Has files: false

Scholarly Output Search Results

Now showing 1 - 10 of 175
  • Thumbnail Image
    Article
    Citation - WoS: 8
    Citation - Scopus: 12
    Srcmimm: the Software Requirements Change Management and Implementation Maturity Model in the Domain of Global Software Development Industry
    (Springer, 2023) Akbar, Muhammad Azeem; Khan, Arif Ali; Mahmood, Sajjad; Mishra, Alok
    The software industry has widely adopted global software development (GSD) to gain economic benefits. Organizations that engage in GSD face various challenges, the majority being associated with requirements change management (RCM). The key motive of this study is to develop a requirement change management and implementation maturity model (SRCMIMM) for the GSD industry that could help the practitioners to assess and manage their RCM activities. A systematic literature review and questionnaire survey approach are used to identify and validate the critical success factors (CSFs), critical challenges (CCHs), and the related best practices of the RCM process. The investigated CSFs and CCHs are classified into five maturity levels based on the concepts of the existing maturity models in other domains, practitioners' feedback, and academic research. Every maturity level comprises different CSFs and CCHs that can help assess and manage a firm's RCM capability. To evaluate the effectiveness of the proposed model, four case studies are conducted in different GSD firms. The SRCMIMM has been developed to assist GSD organizations in improving their RCM process in efficiency and effectiveness.
  • Thumbnail Image
    Article
    Citation - WoS: 11
    Citation - Scopus: 14
    Sustainability Inclusion in Informatics Curriculum Development
    (Mdpi, 2020) Mishra, Deepti; Mishra, Alok
    (1) Background: Presently, sustainability is a crucial issue for human beings due to many disasters owing to climate change. Information Technology (IT) is now part of everyday life in society due to the proliferation of gadgets such as mobile phones, apps, computers, information systems, web-based systems, etc. (2) Methods: The analysis is based on recent ACM/IEEE curriculum guidelines for IT, a rigorous literature review as well as various viewpoints and their relevance for sustainability-oriented curriculum development; it also includes an assessment of key competencies in sustainability for proposed units in the IT curriculum. (3) Results: Sustainability is a critical subject for prospective IT professionals. Therefore, it is imperative to motivate and raise awareness among students and the faculty community regarding sustainability through its inclusion in the Informatics curriculum. This paper focuses on how sustainability can be included in various courses of the Informatics curriculum. It also considers recent ACM/IEEE curriculum guidelines for IT professionals, which assert that IT students should explore IT strategies required for developing a culture of green and sustainable IT. (4) Conclusions: This paper provides guidelines for IT curriculum development by incorporating sustainable elements in courses, so that future IT professionals can learn and practice sustainability in order to develop a sustainable society.
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    Article
    Citation - WoS: 19
    Citation - Scopus: 24
    A Novel Hybrid Machine Learning Based System To Classify Shoulder Implant Manufacturers
    (Mdpi, 2022) Sivari, Esra; Guzel, Mehmet Serdar; Bostanci, Erkan; Mishra, Alok
    It is necessary to know the manufacturer and model of a previously implanted shoulder prosthesis before performing Total Shoulder Arthroplasty operations, which may need to be performed repeatedly in accordance with the need for repair or replacement. In cases where the patient's previous records cannot be found, where the records are not clear, or the surgery was conducted abroad, the specialist should identify the implant manufacturer and model during preoperative X-ray controls. In this study, an auxiliary expert system is proposed for classifying manufacturers of shoulder implants on the basis of X-ray images that is automated, objective, and based on hybrid machine learning models. In the proposed system, ten different hybrid models consisting of a combination of deep learning and machine learning algorithms were created and statistically tested. According to the experimental results, an accuracy of 95.07% was achieved using the DenseNet201 + Logistic Regression model, one of the proposed hybrid machine learning models (p < 0.05). The proposed hybrid machine learning algorithms achieve the goal of low cost and high performance compared to other studies in the literature. The results lead the authors to believe that the proposed system could be used in hospitals as an automatic and objective system for assisting orthopedists in the rapid and effective determination of shoulder implant types before performing revision surgery.
  • Thumbnail Image
    Conference Object
    Citation - WoS: 7
    Citation - Scopus: 57
    Successful Requirement Elicitation by Combining Requirement Engineering Techniques
    (IEEE, 2008) Mishra,D.; Mishra,A.; Yazici,A.
    The role of customers and other stakeholders is becoming increasingly significant during requirement engineering activities. Methods of eliciting requirements are now more co-operative. There are many techniques to obtain requirements from customers. Selecting the right techniques according to the characteristics of the project is very important. In some complex problems, combination of requirement engineering techniques should be applied for efficient and successful requirement engineering process. In this paper, we have presented the application of combination of requirement engineering techniques for a real life complex project (Supply Chain Management) with higher requirements volatility developed in a small scale software development organization.This will help in understanding requirements elicitation for such kind of complex software and facilitate in selecting the appropriate techniques towards getting the consistent and complete requirements. ©2008 IEEE.
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    Article
    Citation - WoS: 18
    Citation - Scopus: 21
    Research Trends in Management Issues of Global Software Development: Evaluating the Past To Envision the Future
    (Taylor & Francis inc, 2011) Mishra, Deepti; Mishra, Alok
    This paper presents research trends in management issues (project management, process management, knowledge management, requirements management, configuration management, risk management, quality management) of distributed/global information system development. The main objective is to highlight the current research and practice direction in these areas. The results are based on peer-reviewed conference papers/journal articles, published between 2000 and early 2011. The analysis revealed that most research has been done in project management, process management, knowledge management and requirements management areas while configuration, risk, and quality management issues could get only limited attention in global/distributed information system development. This indicates the need for future research (quantitative and qualitative) in these areas.
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    Book Part
    Citation - Scopus: 2
    Novel Covid-19 Recognition Framework Based on Conic Functions Classifier
    (Springer Science and Business Media Deutschland GmbH, 2022) Karim,A.M.; Mishra,A.
    The new coronavirus has been declared as a global emergency. The first case was officially declared in Wuhan, China, during the end of 2019. Since then, the virus has spread to nearly every continent, and case numbers continue to rise. The scientists and engineers immediately responded to the virus and presented techniques, devices and treatment approaches to fight back and eliminate the virus. Machine learning is a popular scientific tool and is applied to several medical image recognition problems, involving tumour recognition, cancer detection, organ transplantation and COVID-19 diagnosis. It is proved that machine learning presents robust, fast and accurate results in various medical image recognition problems. Generally, machine learning-based frameworks consist of two stages: feature extraction and classification. In the feature extraction, overwhelmingly unsupervised learning techniques are applied to reduce the input data’s size. This step extracts appropriate features by reducing the computational time and increasing the performance of the classifiers. A classifier is the second step that aims to categorise the input. Within the proposed step, the unsupervised part relies on the feature extraction by using local binary patterns (LBP), followed by feature selection relying on factor analysis technique. The LBP is a kind of visual descriptor, mainly applied for image recognition problem. The aim of using LBP is to analyse the input COVID-19 image and extract salient features. Furthermore, factor analysis is a statistical technique applied to define variability among observed variables in less unnoticed variables named factors. The factor analysis applied to the LBP wavelet aims to select sensitive features from input data (LBP output) and reduce the size input. In the last stage, conic functions classifier is applied to classify two sets of data, categorising the extracted features by using LBP and factor analysis as positive or negative COVID-19 cases. The proposed solution aims to diagnose COVID-19 by using LBP and factor analysis, based on conic functions classifier. The conic functions classifier presents remarkable results compared with these popular classifiers and state-of-the-art studies presented in the literature. © 2022, Springer Nature Switzerland AG.
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    Article
    Citation - WoS: 5
    Citation - Scopus: 8
    A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
    (Mdpi, 2024) Kadhim, Yezi Ali; Guzel, Mehmet Serdar; Mishra, Alok
    Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep learning techniques, which were based on a convolutional neural network (CNN) or autoencoder, to extract features and combine them with the next step of the meta-heuristic algorithm in order to select optimal features using the particle swarm optimization (PSO) algorithm. This combination sought to reduce the dimensionality of the datasets while maintaining the original performance of the data. This is considered an innovative method and ensures highly accurate classification results across various medical datasets. Several classifiers were employed to predict the diseases. The COVID-19 dataset found that the highest accuracy was 99.76% using the combination of CNN-PSO-SVM. In comparison, the brain tumor dataset obtained 99.51% accuracy, the highest accuracy derived using the combination method of autoencoder-PSO-KNN.
  • Thumbnail Image
    Conference Object
    Citation - WoS: 2
    Object-Oriented Inheritance Metrics: Cognitive Complexity Perspective
    (Springer-verlag Berlin, 2009) Mishra, Deepti; Mishra, Alok
    Identifying high cognitive complexity modules can lead to a better quality software system and can help during maintenance also. It has been found that inheritance has an impact on cognitive complexity of a software system. In this paper, two inheritance metrics based on cognitive complexity, one at class level CCI (Class Complexity due to Inheritance) and another at program level ACI (Average Complexity of a program due to Inheritance), have been proposed for object-oriented software systems. These metrics are also compared with other well known object-oriented inheritance metrics.
  • Thumbnail Image
    Conference Object
    Citation - WoS: 6
    Software Architecture in Distributed Software Development: a Review
    (Springer-verlag Berlin, 2013) Mishra, Alok; Mishra, Deepti
    This paper presents a literature review of distributed software development (DSD) or global software development (GSD) and software architecture. The main focus is to highlight the current researches, observations, as well as practice directions in these areas. The results have been limited to peer-reviewed conference papers and journal articles, and analysis reports that major studies have been performed in software architecture and global software development, while the empirical studies of interfacing distributed/global software development and software architecture has only received very little attention among researchers up to now. This indicates the need for future research in these areas.
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    Article
    Citation - WoS: 4
    Citation - Scopus: 6
    A Conceptual Design of Smart Management System for Flooding Disaster
    (Mdpi, 2021) Ibrahim, Thaer; Mishra, Alok
    Disasters pose a real threat to the lives and property of citizens; therefore, it is necessary to reduce their impact to the minimum possible. In order to achieve this goal, a framework for enhancing the current disaster management system was proposed, called the smart disaster management system. The smart aspect of this system is due to the application of the principles of information and communication technology, especially the Internet of Things. All participants and activities of the proposed system were clarified by preparing a conceptual design by using The Unified Modeling Language diagrams. This effort was made to overcome the lack of citizens' readiness towards the use of information and communication technology as well as increase their readiness towards disasters. This study aims to develop conceptual design that can facilitate in development of smart management system for flooding disaster. This will assist in the design process of the Internet of Things systems in this regard.