Prof.(Dr.) Jagathy Raj V. P.

EDUCATION

Ph. D Industrial Engineering and Management - Logistics and Supply Chain Management, Computer Simulation and Modeling Dept. of Industrial Engg. & Mgmt.
I I T, Kharagpur MAY, 2001
Diploma System Analysis and Data Processing Annamalai University 1992 First Class
M. B. A Operations and Systems Management Cochin University, Kerala 1990 First Class
M. Tech Electronics Cochin University, Kerala 1988 First Class
B. Tech Electrical Engineering Kerala University 1986 First Class with Distinction

RESEARCH INTERESTS

Both Engineering and Management

Scopus Publications

Development of a handheld GPU-assisted DSC-TransNet model for the real-time classification of plant leaf disease using deep learning approach
Midhun P. Mathew, Sudheep Elayidom, V. P. Jagathy Raj, and K. M. Abubeker
Springer Science and Business Media LLC



DNN-STACK: a stacking technique based on deep neural network for detecting copy-move forgery
G. Krishnalal, V. P. Jagathy Raj, G. Madhu, and K. S. Arun
Springer Science and Business Media LLC



A Deep Learning Framework for the Characterization of Thyroid Nodules from Ultrasound Images Using Improved Inception Network and Multi-Level Transfer Learning
O. A. Ajilisa, V. P. Jagathy Raj, and M. K. Sabu
MDPI AG
In the past few years, deep learning has gained increasingly widespread attention and has been applied to diagnosing benign and malignant thyroid nodules. It is difficult to acquire sufficient medical images, resulting in insufficient data, which hinders the development of an efficient deep-learning model. In this paper, we developed a deep-learning-based characterization framework to differentiate malignant and benign nodules from the thyroid ultrasound images. This approach improves the recognition accuracy of the inception network by combining squeeze and excitation networks with the inception modules. We have also integrated the concept of multi-level transfer learning using breast ultrasound images as a bridge dataset. This transfer learning approach addresses the issues regarding domain differences between natural images and ultrasound images during transfer learning. This paper aimed to investigate how the entire framework could help radiologists improve diagnostic performance and avoid unnecessary fine-needle aspiration. The proposed approach based on multi-level transfer learning and improved inception blocks achieved higher precision (0.9057 for the benign class and 0.9667 for the malignant class), recall (0.9796 for the benign class and 0.8529 for malignant), and F1-score (0.9412 for benign class and 0.9062 for malignant class). It also obtained an AUC value of 0.9537, which is higher than that of the single-level transfer learning method. The experimental results show that this model can achieve satisfactory classification accuracy comparable to experienced radiologists. Using this model, we can save time and effort as well as deliver potential clinical application value.


Cultural heritage preservation through dance digitization: A review
M.R. Reshma, B. Kannan, V.P. Jagathy Raj, and S. Shailesh
Elsevier BV



A Comparison of Optimization Techniques DeepLearning Models Based on Bell Pepper Leaves Diseases Classification
Midhun P Mathew, Sudheep Elayidom.M, Jagathy Raj VP, and Therese Yamuna Mahesh
IEEE
Deep learning has become a powerful tool for classifying and detecting images. In agriculture, deep learning can help organize and predict various issues, such as disease in leaves and stems, providing accurate information to farmers about various plant diseases, etc. This paper explains different optimization techniques used in deep learning, such as Rms prop, SGM, and Adam, specifically in the context of bell pepperdisease classification using Vgg 19. The study aims to analyze and improve the convergence capability of the Vgg 19 deep-learning CNN model. The study aims to determine the optimal configuration that achieves high accuracy in training, validation, and testing for disease classification in bell peppers. The work includes studying different optimizers and learning rates to find the most suitable optimizer and learning rate for the Vgg 19 CNN model in bell pepper leaf disease classification.Based on this study, the paper concludes that the Adam optimizer performs better with a small learning rate.


Advances in Copy Move Forgery Detection in Digital Images: A Comparative Examination of Conventional Approaches and Deep Learning Based Models
Krishnalal G, Jagathy Raj V P, Madhu G, and Arun K S
IEEE
In recent years, the ease of digital image alteration has significantly increased, primarily driven by the advancements in computing technology and the availability of user-friendly professional image editing software. Consequently, the process of authenticating digital images has become increasingly complex, especially when attempting to distinguish between altered and genuine images with the naked eye. This paper aims to explore various techniques used to detect Copy-Move Forgery in digital images. It provides a comparative analysis of conventional approaches, such as Binary Discriminative Features with Mean Colour Similarity, Color Histogram, DCT and SIFT against the deep learning models AlexNet and GoogleNet. Benchmark datasets such as MICC-F2000 and CoMoFoD are used to evaluate the performance of the comparing models. While conventional techniques exhibit respectable precision, recall, and F1 scores, contemporary deep learning methods outperform them marginally.


Strategic receptivity of maintenance quality function deployment across heterogeneous organisational cultures
V.R. Pramod, S.R. Devadasan, and V.P. Jagathy Raj
Inderscience Publishers



Segmentation of thyroid nodules from ultrasound images using convolutional neural network architectures
O.A. Ajilisa, V.P. Jagathy Raj, and M.K. Sabu
IOS Press
Thyroid nodule segmentation is an indispensable part of the computer-aided diagnosis of thyroid nodules from ultrasound images. However, it remains challenging to segment the nodules from ultrasound images due to low contrast, high noise, diverse appearance, and complex thyroid nodules structure. So, it requires high clinical experience and expertise for proper detection of nodules. To alleviate the doctor’s tremendous effort in the diagnosis stage, we utilized several convolutional neural network architectures based on Encoder-Decoder architecture, U-Net architecture, Res-UNet architecture. To handle the complexity of the residual blocks, we also proposed three hybrid Res-UNet architectures by reducing the number of residual connections. The experimental analysis of the segmentation models proves the viability of residual learning in the U-Net architecture. Hybrid models which use minimum residual connections provide efficient segmentation frameworks similar to Res-UNet architecture with a minimum computational requirement. The experimental results indicate that all the segmentation models based on residual learning and U-Net can accurately delineate nodules without human intervention. This model helps to reduce dependencies on operators and acts as a decision tool for the radiologist.


Ontology-based information extraction framework for academic knowledge repository
Veena Jose, V. P. Jagathy Raj, and Shine K. George
Springer Singapore



Significance of network properties of function words in author attribution
Sariga Raj, B. Kannan, and V. P. Jagathy Raj
Springer Singapore



Personalized News Media Extraction and Archival Framework with News Ordering and Localization
Shine K. George, V. P. Jagathy Raj, and Santhosh Kumar Gopalan
Springer Singapore



Application of Systems Engineering Principles for Concept Design of New Products
Karunakaran Nair Ajith Kumar and Vettuvila Purushothaman Jagathy Raj
Springer Science and Business Media LLC



Quadratic filter for the enhancement of edges in retinal images for the efficient detection and localization of diabetic retinopathy
V. S. Hari, V. P. Jagathy Raj, and R. Gopikakumari
Springer Science and Business Media LLC



A statistical analysis of soil fertility of Thrissur district, Kerala
R. Ajith Kumar, M. K. Muhammed Aslam, V. P Jagathy Raj, T. Radhakrishnan, K. Satheesh Kumar, and T K. Manojkumar
IEEE
A statistical analysis was performed on three thousand and eight hundred soil sample data from Thrissur district. Soil pH, Electrical conductivity, Organic Carbon, Phosphorus, Potassium, Calcium, Magnesium, Sulfur, Zinc, Boron, Iron, Copper and Manganese data were analyzed. Correlation analysis, ANOVA and Principal Component analysis were performed on the data set. Analysis indicate that different soil components are significantly correlated with soil properties.


Fraudulent image recognition using stable inherent feature
Deny Williams, G. Krishnalal, and V. P. Jagathy Raj
Springer International Publishing



Practical implementation of a secure email system using certificateless cryptography and domain name system




Interpretive structural modeling (ISM) and its application in analyzing factors inhibiting implementation of total productive maintenance (TPM)
Prasanth S. Poduval, V. R. Pramod, and Jagathy Raj V. P.
Emerald
Purpose – The purpose of this paper is to highlight the application of Interpretive Structural Modeling (ISM) to analyze the barriers in implementation of Total Productive Maintenance (TPM). TPM is explained in brief with emphasis on maintenance programs to improve quality of products, reliability of processes and reduction in cost. Barriers in implementation of TPM are also discussed. Concept of ISM and steps in developing ISM are described in detail. The authors then illustrate the research methodology which involves applying ISM to analyze barriers in TPM. Design/methodology/approach – The paper starts off by describing the concepts of TPM and ISM. Barriers in implementation of TPM are discussed. It explains ISM as a methodology to understand the underlying interrelationship among the inhibiting factors. The authors draw up an action plan to carry out research on the usage of ISM to study the TPM inhibitors, to develop an integrated model to establish the relationship among the different TPM inhibiting factors and to suggest action plan to mitigate these factors. Findings – Interpretive Structural Modeling (ISM) can be used to analyze the driving and dependence power of the variables inhibiting implementation of TPM. The barriers to implement TPM are described with detailed explanation. The complexity of the problem and the degree of interconnection among the variables can be found out. This will help Managers take action on mitigating the barriers. Practical implications – By analyzing the interrelationships among the barriers and their strengths, management can chalk out the strategy to implement TPM in an organization. Management will become aware of the barriers which have the maximum influence and then can act accordingly to mitigate these barriers. This will help in implementing TPM faster and in an organized manner. Originality/value – Many authors have used ISM to study various issues. A couple of authors have used ISM to determine barriers in implementation of TPM. The authors feel that most of the papers describe ISM in brief making it slightly difficult for readers to understand. This paper aims to explain elaborately step-by-step on how to develop an ISM making it easier for researchers to understand the ISM concept. Even though there are papers on TPM and difficulties in implementation of TPM, this paper explains the barriers in implementing TPM based on the experience of the corresponding author having worked in the refinery industry.


An evaluation of alternative approaches to reliability centered maintenance




Credit based scheduling algorithm in cloud computing environment
Antony Thomas, G. Krishnalal, and V.P. Jagathy Raj
Elsevier BV



Re-engineering towed arrays for quality enhancement - Network based towed array




Unsharp masking using quadratic filter for the enhancement of fingerprints in noisy background
V.S. Hari, V.P. Jagathy Raj, and R. Gopikakumari
Elsevier BV



Confirmatory factor modeling on emerging consumer purchase behaviour of passenger cars
Balakrishnan Menon and Jagathy Raj V. P.
Associated Management Consultants, PVT., Ltd.
With globalization and liberalization, many world leaders in automobile manufacturing such as Ford, General Motors, Honda, Toyota, Suzuki, Hyundai, Renault, Mitsubishi, Benz, BMW, Volkswagen and Nissan set up their manufacturing units in India in joint venture with their Indian counterpart companies, by making use of the Foreign Direct Investment policy of the Government of India. With a multiplicity of choices available to the Indian car buyers, it drastically changed the car purchase scenario in India, and particularly in the State of Kerala. This transformed the automobile scene from a sellers' market to a buyers' market. The main purpose of this paper was to develop a model with major variables that influenced the consumer purchase behaviour of passenger car owners in the State of Kerala. The results of the research contribute to the practical knowledge base of the automobile industry, specifically to the passenger car segment. It would also lend a great contributory value addition to the manufacturers and dealers for customizing their marketing plans in the State.


Ontology based framework for news extraction in visual media
Shine K George, V P Jagathy Raj, and G Santhosh Kumar
IEEE
Anticipating the increase in video information in future, archiving of news is an important activity in the visual media industry. When the volume of archives increases, it will be difficult for journalists to find the appropriate content using current search tools. This paper provides the details of the study we conducted about the news extraction systems used in different news channels in Kerala. Semantic web technologies can be used effectively since news archiving share many of the characteristics and problems of WWW. Since visual news archives of different media resources follow different metadata standards, interoperability between the resources is also an issue. World Wide Web Consortium has proposed a draft for an ontology framework for media resource which addresses the intercompatiblity issues. In this paper, the w3c proposed framework and its drawbacks is also discussed.


Short-term load forecast of a low load factor power system for optimization of merit order dispatch using adaptive learning algorithm
K. Pramelakumari, S. R. Anand, V. P. Jagathy Raj, and E. A. Jasmin
IEEE
Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year.


Spatial filtering of MRI images for the removal of impulsive noise using quadratic Volterra filter

RECENT SCHOLAR PUBLICATIONS

DNN-STACK: a stacking technique based on deep neural network for detecting copy-move forgery
G Krishnalal, VP Jagathy Raj, G Madhu, KS Arun
Neural Computing and Applications, 1-16 2024



Causes of Reworks in Projects: A Systematic Review of Literature
MV Akhil, J VP
Available at SSRN 5123908 2024



A Method for Simultaneously Comparing Multiple Mental Models
MV Akhil, MV Arya, BG Menon, J VP
Available at SSRN 4899821 2024



Mental Models Elicitation in Organizational and Field Settings: Development of a Methodological Framework
MV Akhil, BG Menon, J VP
Available at SSRN 4891697 2024



Advances in Copy Move Forgery Detection in Digital Images: A Comparative Examination of Conventional Approaches and Deep Learning Based Models
G Krishnalal, JR VP, G Madhu, KS Arun
2023 Annual International Conference on Emerging Research Areas 2023



Cultural heritage preservation through dance digitization: A review
MR Reshma, B Kannan, VPJ Raj, S Shailesh
Digital Applications in Archaeology and Cultural Heritage 28, e00257 2023



Strategic receptivity of maintenance quality function deployment across heterogeneous organisational cultures
VR Pramod, SR Devadasan, VPJ Raj
International Journal of Management Practice 16 (5), 585-614 2023



Impact of AI technologies on organisational learning: proposing an organisation cognition schema
PM Nimmi, G Vilone, VP Jagathyraj
Development and Learning in Organizations: An International Journal 36 (5), 7-9 2022



Error Reduction Based Demand Forecasting: An Appraisal of Kerala Power System
K Pramelakumari, VP Jagathy Raj, PS Sreejith
Retrieved May 12 2022



A novel clustering based undersampling algorithm for imbalanced data sets using artificial bee colony algorithm
OA Ajilisa, VP Jagathyraj, MK Sabu
Innovations in Bio-Inspired Computing and Applications: Proceedings of the 2021



Ontology-based information extraction framework for academic knowledge repository
V Jose, VP Jagathy Raj, SK George
Proceedings of Fifth International Congress on Information and Communication 2021



Significance of Network Properties of Function Words in Author Attribution
S Raj, B Kannan, VP Jagathy Raj
Intelligent Data Engineering and Analytics: Frontiers in Intelligent 2021



Employer brand and innovative work behaviour: Exploring the mediating role of employee engagement
A John, VPJ Raj
Colombo Business Journal 11 (2) 2020



Significance of Network Properties
S Raj, B Kannan, VPJ Raj
Intelligent Data Engineering and Analytics: Frontiers in Intelligent 2020



Computer-aided diagnosis of thyroid nodule from ultrasound images using transfer learning from deep convolutional neural network models
OA Ajilisa, VP Jagathyraj, MK Sabu
2020 Advanced Computing and Communication Technologies for High Performance 2020



Control area wise optimisation of power purchase and hydro scheduling a pragmatic approach
SR Anand, VP Jagathy Raj, CA Babu
Cochin University of Science and Technology 2020



Swarm intelligence based economic operation of hydro thermal power system with forecasted demand a case study
K Pramelakumari, VP Jagathy Raj, PS Sreejith
Cochin University of Science and Technology 2020



A Review on Environmental Performance Indicators Classification and its Challenges
S Varghese
Purakala with ISSN 0971-2143 is an UGC CARE Journal 31 (4), 2436-2446 2020



ROLE OF ORGANISATION LEARNING ON THE ADOPTION OF GREEN INNOVATION PRACTICES AND ITS IMPACTS ON FIRM PERFORMANCE
S Varghese
Studies in Indian Place Names 40 (29), 7-14 2020



Personalized news media extraction and archival framework with news ordering and localization
SK George, VP Jagathy Raj, SK Gopalan
Information and Communication Technology for Sustainable Development 2020

MOST CITED SCHOLAR PUBLICATIONS

Interpretive structural modeling (ISM) and its application in analyzing factors inhibiting implementation of total productive maintenance (TPM)
PS Poduval, VR Pramod, JR VP
International Journal of Quality & Reliability Management 32 (3), 308-331 2015
Citations: 214



Credit based scheduling algorithm in cloud computing environment
A Thomas, G Krishnalal, VPJ Raj
Procedia Computer Science 46, 913-920 2015
Citations: 145



A novel slotless Halbach-array permanent-magnet brushless DC motor for spacecraft applications
RP Praveen, MH Ravichandran, VTS Achari, VPJ Raj, G Madhu, ...
IEEE Transactions on Industrial Electronics 59 (9), 3553-3560 2011
Citations: 124



Integrating TPM and QFD for improving quality in maintenance engineering
VR Pramod, SR Devadasan, S Muthu, VP Jagathyraj, ...
Journal of Quality in Maintenance Engineering 12 (2), 150-171 2006
Citations: 112



Reinforcement Learning approaches to Economic Dispatch problem
EA Jasmin, TP Imthias Ahamed, VP Jagathy Raj
International Journal of Electrical Power & Energy Systems 33 (4), 836-845 2011
Citations: 77



Multicriteria decision making in maintenance quality function deployment through the analytical hierarchy process
VR Pramod, K Sampath, SR Devadasan, VP Jagathy Raj, GD Moorthy
International Journal of Industrial and Systems Engineering 2 (4), 454-478 2007
Citations: 47



Cultural heritage preservation through dance digitization: A review
MR Reshma, B Kannan, VPJ Raj, S Shailesh
Digital Applications in Archaeology and Cultural Heritage 28, e00257 2023
Citations: 42



Barriers in TPM implementation in industries
PS Poduval, VR Pramod, JVP Raj
International journal of scientific & technology research 2 (5), 28-33 2013
Citations: 42



CBM, TPM, RCM and A-RCM-a qualitative comparison of maintenance management strategies
D Prabhakar, VJ Raj
Int. J. Manag. Bus. Stud 4 (3), 49-56 2014
Citations: 39



Receptivity analysis of TPM among internal customers
VR Pramod, SR Devadasan, VP Jagathy Raj
International Journal of Technology, Policy and Management 7 (1), 75-88 2007
Citations: 33



A new model for reliability centered maintenance in petroleum refineries
P Deepak Prabhakar, DJR VP
International Journal of Scientific & Technology Research 2 (5) 2013
Citations: 32



Design and finite element analysis of hybrid stepper motor for spacecraft applications
RP Praveen, MH Ravichandran, VTS Achari, VPJ Raj, G Madhu, ...
2009 IEEE International Electric Machines and Drives Conference, 1051-1057 2009
Citations: 32



Design and analysis of zero cogging Brushless DC motor for spacecraft applications
RP Praveen, MH Ravichandran, VT Sadasivan Achari, VP Jagathy Raj, ...
Electrical Engineering/Electronics Computer Telecommunications and 2010
Citations: 30



Unsharp masking using quadratic filter for the enhancement of fingerprints in noisy background
VS Hari, VPJ Raj, R Gopikakumari
Pattern Recognition 46 (12), 3198-3207 2013
Citations: 29



A Reinforcement Learning algorithm to Economic Dispatch considering transmission losses
EA Jasmin, TPI Ahamed, VP Jagathiraj
TENCON 2008-2008 IEEE region 10 conference, 1-6 2008
Citations: 29



Reinforcement learning solution for unit commitment problem through pursuit method
EA Jasmin, IA TP, JR VP
2009 International conference on advances in computing, control, and 2009
Citations: 26



Model development and validation for studying consumer preferences of car owners
B Menon, JR VP
International Journals of Marketing and Technology 2 (5), 148-173 2012
Citations: 25



Enhancement of calcifications in mammograms using Volterra series based quadratic filter
VS Hari, RVP Jagathy, R Gopikakumari
2012 International Conference on Data Science & Engineering (ICDSE), 85-89 2012
Citations: 21



CBM, TPM, RCM and A-RCM-A Qualitative Comparison of Maintenance Management
P Deepak Prabhakar, VP Jagathy Raj
Revista IJMBS 4 (3), 5-8 2014
Citations: 20



Design and analysis of Enclosed Rotor Halbach array Brushless DC Motor for spacecraft applications
RP Praveen, MH Ravichandran, VTS Achari, VPJ Raj, G Madhu, ...
The XIX International Conference on Electrical Machines-ICEM 2010, 1-6 2010
Citations: 20