Dr.A.Pankajam

@avinuty.ac.in

Associate Professor
Avinashilingam University for Women, Coimbatore

Dr.A.Pankajam


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https://researchid.co/apankajam

RESEARCH INTERESTS

Behavioural Finance, Finance,
18

Scopus Publications

100

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • DEEP REINFORCEMENT LEARNING FOR PROACTIVE CYBERSECURITY THREAT DETECTION
    DR. NAIM SHAIKH, DR. VIVEK VEERAIAH, DR. A.PANKAJAM, DR. TARUN DALAL, DR. MAMATHA G, DR. G. NAGESWARA RAO, DR. VINOD MOTIRAM RATHOD, DR. TRIPTI SHARMA
    Journal of Theoretical and Applied Information Technology, 2026
    The proliferation of interconnected ecosystems, encompassing cloud infrastructures, IoT networks, and 5G platforms, has facilitated the execution of cyberattacks. Consequently, systems are increasingly susceptible to intricate, adaptive attacks. Reactive security measures, such as signature-based IDS and conventional machine learning models, are ineffective until an attack has already occurred. This deficiency stems from their inability to predict and mitigate threats characterised by aggressive evasion, cognitive wander, and evolving assault methodologies. Furthermore, the expansion of digitally linked systems has exacerbated vulnerabilities to sophisticated cyberattacks. Traditional cybersecurity protocols typically identify threats only post-incident. In the field of cybersecurity, a shift towards proactive and adaptive approaches is necessary due to AI's limitations, even if AI enhances pattern recognition. In contrast to conventional reactive methods, this research demonstrates the potential of DRL to build a proactive system for danger identification that can adapt in real-time to new threats. To tackle these issues, we provide DRL-PRoTECT, a new proactive cybersecurity approach that combines deep reinforcement learning with existing methods. The system is able to autonomously detect and mitigate threats in real-time thanks to its hierarchical DRL decision engine, predictive anomaly scoring, and self-supervised representation learning. Results on enterprise-scale systems, NSL-KDD, and UNSW-NB15 show that DRL-PRoTECT outperforms traditional IDS, ML/DL benchmarks, and virtual testbeds. With an F1 score of 94.5%, a false positive rate of 2.8%, and a recall rate of 93.7%, the framework accomplished its goals. The technology also reduced the time needed to identify threats by half. Its ability to adapt allowed it to keep working well despite changing priorities, new types of attacks, and attempts to bypass it. Analysts found that including a human-in-the-loop orchestrator made it easier and less demanding to stay alert. This led to better understanding, compliance, and trust. The results suggest that DRL-PRoTECT could help move cybersecurity defences from a detection-focused approach to a more proactive, self-sufficient, and resilient one. In response to changing threats, this article presents a proactive and scalable cybersecurity model that automatically shifts from detection to defense.
  • A BLOCKCHAIN-DRIVEN MULTI-AGENT FRAMEWORK FOR ENHANCING TRANSPARENCY, EFFICIENCY, AND RESILIENCE IN SMART SUPPLY CHAIN MANAGEMENT
    DR. P. SANTHOSH KUMAR, DR. A.PANKAJAM, DR. VIVEK VEERAIAH, DR. ADVETA GHARAT, DR. MAMATHA G, DR. DEVIKA RANI ROY, ANKUR GUPTA, N RAJITHA
    Journal of Theoretical and Applied Information Technology, 2026
    As global supply chains have evolved quickly, challenges including transparency, collaboration, security, and the capacity to make choices in real time have become increasingly important. The present research fails to offer a unified, extensible framework that integrates decentralised trust, intelligent optimisation, and resilience across diverse supply chain contexts, even though blockchain and multi-agent systems have been examined independently to enhance autonomy and traceability. Most of the research done before this one is either too small in scope or hasn't been able to prove that integrated blockchain-MAS systems work in real life. Also, most of the studies have only looked at single services, like traceability or finance. The present study addresses this informational gap by proposing a novel Blockchain-Driven Multi-Agent Framework for the optimisation of supply chain activities from inception to completion. This system combines decentralised ledger technology, autonomous agents, reinforcement learning, and smart contract automation. The framework brings new information to the table by adding a scalable on-chain/off-chain data strategy, smart techniques to optimise for cost, resilience, and sustainability, and formalising hybrid agent-based coordination on blockchain. In the agricultural, industrial, and logistical sectors, simulation-based evaluations show big improvements over traditional methods in the following areas: transparency (+65%), speed of decision-making (+48%), time to recover from an interruption (-60%), energy efficiency (+32%), and reduction of product spoilage (-66%). The research contributes to the current knowledge on intelligent, decentralised supply chains by offering a generalisable architecture, empirical performance data, and practical insights.
  • FEDERATED LEARNING WITH BLOCKCHAIN FOR SECURE AND SCALABLE FINANCIAL SERVICES
    DR. NAIM SHAIKH, DR. A.PANKAJAM, DR. VIVEK VEERAIAH, SHEETAL PRADIP PATIL, DR. MAMATHA G, DR. SRIDEVI.R, ANKUR GUPTA, DR. M.YELLAIAH NAYUDU
    Journal of Theoretical and Applied Information Technology, 2026
    People are justifiably apprehensive about the safety, privacy, and scalability of their data in collaborative machine learning contexts now that digital financial services are available. But it is hard to get to, and different groups don't trust it. Blockchain is a kind of distributed ledger technology that stores and checks data in a way that doesn't need a trusted third party. However, when used alone, it has problems with its size and battery use. This research puts out a hybrid architecture that combines blockchain with FL to solve these problems and develop financial services that can grow. This approach, which uses blockchain technology, protects the data sovereignty of organisations. It also makes it easier for financial organisations to work together to build global models. It does this by being able to keep an eye on changes, build trust, and provide people the chance to get personal incentives. The suggested strategy is better than FL-only and blockchain-only solutions when it comes to accuracy, scalability, and safety. The amount of energy used and the time it takes to respond to queries are also maintained at a reasonable level. Research can perform a lot of important things with the system, including look into claims of fraud, assess credit risk, and stop money laundering. The outcomes help make the financial industry's digital infrastructure safer, more open, and more in line with the law.
  • A Blockchain-Enabled Adaptive Learning Model for Secure and Scalable Data Sharing
    Sudhir Anakal, Mohammad Arif, S. Artheeswari, K. Balaji, A. Pankajam, P. John Augustine, Maddula Ratna Mohitha, Anita Patil, H. Mickle Aancy, R. G. Vidhya
    International Journal of Basic and Applied Sciences, 2025
    The blockchain skillset is one of the most emerging skill sets that brings the world into the hands ‎of the self. The number of industrial applications depends on this new technology just because of its ‎decentralized, transparent, and secure nature. This enables a new way for the next generation ‎of computing environments like cloud computing and edge computing. By keeping this in mind, ‎this work develops a new disruptive method using adaptive learning model to address the ‎security issues in a data sharing environment with decentralized access control. The developed ‎framework has been executed and tested utilizing Python, and the results have been ‎presented. A performance study comparison between the existing RSA algorithm, AES ‎algorithm, and the proposed algorithm (ALM) has been done, and the various parameters ‎taken for the study and their values are presented in this paper. Results obtained show that the ‎algorithm presented is proven to be efficient in terms of security, scalability and time‎.
  • Feature fusion based deep learning model for Alzheimer's neurological disorder classification
    Arhath Kumar, S. Pradeep, Kumud Arora, G. Sreeram, A. Pankajam, Trupti Patil, Aradhana Sahu
    Neuroscience Informatics, 2025
    Alzheimer's disease (AD) is a severe brain disorder that can cause degradation of brain tissue and memory loss. Owing to Alzheimer's disease's high cost, a number of deep learning-based models have been put out to accurately identify the illness. This study introduces a new way to classify Alzheimer's disease using deep learning and combining different types of features. The 3D lightweight MBANet developed in this research has less parameters and can concentrate on more discriminative deep structures than conventional artificial neural networks like CNN, according to experimental data. We first create a Multi-Branch Attention Network (MBANet) to gather detailed features of the hippocampus from large sets of data. A new method is created to capture texture features in the hippocampus. It uses two techniques: multi-Tree Wavelet Transform (MTWT) and Gray Length Matrix (GLM). This method works in three dimensions and at different scales. Also, standard methods are used to measure the size and shape of the hippocampus. A mixed feature fusion network is created to simplify and combine data from the hippocampus, helping to classify Alzheimer's disease more effectively. Tests on the EADC-ADNI dataset show that the proposed method for classifying Alzheimer's disease achieves an accuracy of 93.39%, a F 1 -score of 93.10%, and an AUC of 93.21%. The test results show that the proposed method for classifying Alzheimer's disease is effective and better than traditional methods.
  • Human-AI Collaboration for Upskilling Workforce in the Industry 5.0 Era
    Geetha Manoharan, A. Shameem, Pravin D Sawant, Naresh Goke, A. Pankajam, Aneesya Panicker
    2025 World Conference on Cutting Edge Science and Technology Wccest 2025, 2025
    The interaction of human and artificial intelligence (AI) changes the labor force by modifying the work of employees and creating efficiency. Staff is the most valuable resource of the firm and their health has a direct reflection on their efficiency. Employees will be able to focus on problem-solving, strategic planning, and social interaction when AI handles specific and data-based work. This paper, in the context of Industry 5.0, researches the aspects of the worker wellness in firms as a way to upskill the workforce to allow industry to respond to changes via sentiment assessment of inbound inquiries and qualification of health. The general aim is to develop a Wellness Index (NI) that will quantify the wellness of workers based on a set of physical and mental criteria. The present-day study constructs Azure Textual Analysis (ATA) to carry out sentiment analysis to deal with negative messages reported to workers through the L-BFGS Optimum-Entropy ML denotes categorizing technology. The results show a relationship between physical measures and self-reported wellness, underscoring the usefulness of the WNI in pinpointing problematic aspects of worker conduct. This study suggests that the discontent score element (DSE) and the WNI be used for determining the worker worldwide index (WWI), which measures workers' general mental health. The analysis of 385 setups revealed that the WNP has a Macro-Accuracy of 91.82% and a Micro-Accuracy of 95.96%. When 2000 texts were analyzed by ATA, the accuracy and precision were 99.8% and 99.60%, respectively. Here, the F1-value was 99.74% and the recall was 99.90%. An innovative method called the Worker KPI Method (WKM) has been implemented for avoiding and detecting worker stress in the Industry 5.0 setting, which is human-centered. Equitably, the study shows that, though human-AI collaboration boosts efficiency and changes work-related roles, it also implies proactive actions to address ethical issues and changes in employees.
  • Harnessing AI Technologies to Simplify Human Resource Communication
    Gulshan Anjum Dudekula, H S. Abzal Basha, A. Pankajam, Ankur Gupta, Rati Shukla, Smrita Jain
    Ietacs 2025 2025 International Conference on Innovations and Emerging Technologies in AI and Communication Systems Unifying AI and Communication for A Smarter Tomorrow, 2025
    This research implies that the rise of AI might change how human resources (HR) works. When you try to reach human resources in more conventional means, you could not receive a response, have problems with language, or have individuals who aren't interested. This research shows that an AI-based model for HR communication that combines sentiment analysis, real-time chatbots, and support for several languages might help tackle this issue. The method will let everyone on the team talk to each other and keep track of what staff members are saying, so everyone will feel included, no matter what language they speak. To guarantee that data is handled in a way that is ethically acceptable, regulations concerning data privacy and compliance are strictly enforced. Through the use of performance evaluations, it has been shown that the levels of satisfaction, accuracy, and responsiveness of workers have all increased. The significance of AI in the implementation of HR solutions that are intelligent, empathetic, and broadly accessible is brought to light in this study.
  • Cross-Functional Impacts of Machine Learning in HR, Finance, and Strategic Management
    Manju Chopra, A. Pankajam, Sridhar N Koka, Priyanka Salgotra, Melanie Lourens, Seema Sharma
    2025 5th International Conference on Advancement in Electronics and Communication Engineering Aece 2025, 2025
    The introduction of machine learning (ML) in the organizational workflow is undermining strategy, operations and decision-making. Human resources (HR) machine learning (ML) algorithms are used to enhance employee engagement, retention and hiring, and assist in supporting more evidence-based and tailored work force management programs. ML also offers real-time information, which can be applied to offer more accurate and efficient financial management in the following ways: fraud detection and risk assessment, and financial development. ML helps strategic management to make better decisions on long-term actions and competitive standpoint through the processing of large data sets, discovering new tendencies, and supporting planning of scenarios. Most importantly, the crossfunctionality of ML, i.e. its implementation in the teams, can promote collaboration, i.e. the interdepartmental problems, e.g. the performance alignment or resource allocation can be resolved jointly. There are, however, downsides to its enactment; besides data privacy issues and ethical dilemmas, there is also the necessity of staff training. This paper discusses the cross-over, disruptive nature of ML systems on strategic management, finance and human resource with the highlight of the issues of pros and cons. The paper reiterates the significance of comprehensive ML approach that aligns technology potentials with business objectives because it does so by identifying case studies and new best practices. Finally, the adoption of ML cannot be successful without more than technological investment, and it must be a collective ecosystem of business functions, leadership buy-in, and a culture change.
  • ENHANCING HEALTHCARE SECURITY WITH BLOCKCHAIN-POWERED SMART CONTRACTS
    Journal of Theoretical and Applied Information Technology, 2025
  • The central bank of India as an example of the green revolution in the banking sector
    Shubhendu Shekher Shukla, Saurabh Bajpai, A. Pankajam, Ankur Gupta, Vivek Veeraiah, Sabyasachi Pramanik, Soma Bag
    Recent Developments in Financial Management and Economics, 2024
    The purpose of this chapter is to illustrate the State Bank of India's (the nation's central bank) involvement in advancing green banking practices in day-to-day operations. India has been dealing with severe environmental problems despite having lower per capita CO2 emissions than the rest of the world. The State Bank of India (SBP) released the green banking guidelines (GBG) in 2017 in response to the worsening environmental conditions. The guidelines aim to change the economy of the nation and recognize the financial sector's contribution to the transition to a low-carbon and climate-resilient economy. It aids in raising awareness among investors and the banking sector about the need to create sustainable green development investments, operations, infrastructure, and goods. The State Bank of India's comprehensive evaluation of the GBG is to examine and evaluate the GBG and pinpoint the main obstacles facing its stakeholders, including commercial banks and other financial organizations. The central bank's activities suggest that the GBG policy is a paradigm change for the banking sector and will likely have a significant effect on the economy. Furthermore, the rules delineate the roles, oversight, and structure for implementing the GBG and provide three primary topics for consideration. These include personal impact minimization, green business assistance, and environmental risk management. The central bank's involvement in putting the GBG into practice for all commercial banks is also covered in this chapter. Through GBG, the central bank of India mandates commercial banks, requiring the board of the banks to approve environmental exposure limits for various industries and sectors. This is projected to result in varying levels of green practices across various projects. The GBG may need the hiring of a sizable workforce, which would raise banks' estimated service costs. All projects and the sectors/industries they belong to need to have clear requirements and hazards related to the environment. In order to efficiently oversee and carry out the GBG, the SBP has taken a number of actions. For example, it plans to engage with international organizations to create a standard framework for consistent environmental risk management in the banking sector. Comparably, the banks have made certain moves, such as setting up green banking offices, hiring the necessary personnel, creating a checklist for identifying environmental risks, offering advice services for the development of green businesses, etc. A few of them are also the ones that started the social and environmental management system.
  • Lung Cancer Detection and Recognition using Deep Learning Mechanisms for Healthcare in IoT Environment
    International Journal of Intelligent Systems and Applications in Engineering, 2024
  • Customer Personality Analysis using Segmentation and Exploratory Data Analysis
    International Journal of Intelligent Systems and Applications in Engineering, 2024
  • A Study on Effects of GST on Farmers and Agricultural Sector: An Empirical Analysis in India
    Arun Gautam, Gitanjali Shrivastava, A. Pankajam, Rohit Bansal, Ankur Gupta, Malik Bader Alazzam
    Aip Conference Proceedings, 2023
  • Blockchain Based Cross Chain Trusted Clinical Records Sharing System
    International Journal of Intelligent Systems and Applications in Engineering, 2023
  • SERVICE QUALITY PERCEPTION IN PRIVATE BANKS: A STUDY WITH SPECIAL REFERENCE TO KARUR VYSYA BANK LTD
    Rani S, Nitu Maurya, Salauddeen Shaika, Pankajam A
    Ecs Transactions, 2022
  • Efficient COVID-19 Identification Using Deep Learning for IoT
    Vivek Veeraiah, A. Pankajam, Ela Vashishtha, Dharmesh Dhabliya, P. Karthikeyan, Radha Raman Chandan
    Proceedings of 5th International Conference on Contemporary Computing and Informatics Ic3i 2022, 2022
  • Empirical Analysis for Improving Food Quality Using Artificial Intelligence Technology for Enhancing Healthcare Sector
    S. K. UmaMaheswaran, Gaganpreet Kaur, A. Pankajam, A. Firos, Piyush Vashistha, Vikas Tripathi, Hussien Sobahi Mohammed
    Journal of Food Quality, 2022
  • Retraction:Secure Big Data Processing in Multihoming Networks with AI-Enabled IoT
    Sivakumar Venu, Jayasri Kotti, A. Pankajam, Dharmesh Dhabliya, G. Nageswara Rao, Rohit Bansal, Ankur Gupta, F. Sammy
    Wireless Communications and Mobile Computing, 2022

RECENT SCHOLAR PUBLICATIONS

  • Harnessing AI Technologies to Simplify Human Resource Communication
    GA Dudekula, HSA Basha, A Pankajam, A Gupta, R Shukla, S Jain
    2025 International Conference on Innovations and Emerging Technologies In AI … , 2025
    2025
  • Feature fusion based deep learning model for Alzheimer's neurological disorder classification
    A Kumar, S Pradeep, K Arora, G Sreeram, A Pankajam, T Patil, A Sahu
    Neuroscience Informatics 5 (2), 100196 , 2025
    2025
    Citations: 2
  • Neuroscience Informatics
    S Kumari, B Rana, S Chaudhary, R Rajan, SS Kumaran, AK Srivastava, ...
    2025
  • A Cross Country Analysis of the Opportunities and Challenges in the Banking Sector
    AS Kiruba, PM Safeer, A Pankajam, G Lakhera
    Advancements in Business for Integrating Diversity, and Sustainability, 17-22 , 2024
    2024
  • Empirical Analysis for Improving Food Quality Using Artificial Intelligence Technology for Enhancing Healthcare Sector (Retraction of Vol 2022, art no 1447326, 2022)
    SK UmaMaheswaran, G Kaur, A Pankajam
    JOURNAL OF FOOD QUALITY 2024 , 2024
    2024
  • Lung cancer detection and recognition using deep learning mechanisms for healthcare in ioT environment
    A Shalini, A Pankajam, V Talukdar, S Farhad, G Talele, E Muniyandy, ...
    Int J Intelligent Syst Appl Eng 12, 208-16 , 2024
    2024
    Citations: 5
  • The central bank of India as an example of the green revolution in the banking sector
    SS Shukla, S Bajpai, A Pankajam, A Gupta, V Veeraiah, S Pramanik, ...
    Recent Developments in Financial Management and Economics, 166-184 , 2024
    2024
    Citations: 3
  • A study on effects of GST on farmers and agricultural sector: An empirical analysis in India
    A Gautam, G Shrivastava, A Pankajam, R Bansal, A Gupta, MB Alazzam
    AIP Conference Proceedings 2587 (1), 140007 , 2023
    2023
    Citations: 2
  • Efficient COVID-19 identification using deep learning for IoT
    V Veeraiah, A Pankajam, E Vashishtha, D Dhabliya, P Karthikeyan, ...
    2022 5th International Conference on Contemporary Computing and Informatics … , 2022
    2022
    Citations: 15
  • FACTORS INFLUENCING THE ENGLISH LANGUAGE SKILLS OF THE HIGHER SECONDARY SCHOOL STUDENTS ON THEIR COMMUNICATION BEHAVIOUR.
    SK Nathan, S SreeLekha, A Pankajam, C Mandal, S Sekar, D Nimavat
    International Journal of Early Childhood Special Education 14 (3) , 2022
    2022
  • Service Quality Perception in Private Banks: A Study with Special Reference to Karur Vysya Bank Ltd
    S Rani, N Maurya, S Shaika, A Pankajam
    ECS Transactions 107 (1), 16803 , 2022
    2022
    Citations: 5
  • Research Article Secure Big Data Processing in Multihoming Networks with AI-Enabled IoT
    S Venu, J Kotti, A Pankajam, D Dhabliya, GN Rao, R Bansal, A Gupta, ...
    2022
  • Research Article Empirical Analysis for Improving Food Quality Using Artificial Intelligence Technology for Enhancing Healthcare Sector
    SK UmaMaheswaran, G Kaur, A Pankajam, A Firos, P Vashistha, ...
    2022
  • [Retracted] Secure Big Data Processing in Multihoming Networks with AI‐Enabled IoT
    S Venu, J Kotti, A Pankajam, D Dhabliya, GN Rao, R Bansal, A Gupta, ...
    Wireless Communications and Mobile Computing 2022 (1), 3893875 , 2022
    2022
    Citations: 24
  • [Retracted] Empirical Analysis for Improving Food Quality Using Artificial Intelligence Technology for Enhancing Healthcare Sector
    SK UmaMaheswaran, G Kaur, A Pankajam, A Firos, P Vashistha, ...
    Journal of Food Quality 2022 (1), 1447326 , 2022
    2022
    Citations: 36
  • Study On Impact Of Virtual Employee Performance Management On Employee Productivity During Covid-19 Pandemic With Reference To Higher Education Sector In Kerala
    NI Mumthas, AP Pankajam
    Design Engineering, 9745-9759 , 2021
    2021
  • A Study on Impact of HR Analytics on the Human Resource Management System in a Competitive Context: A Literature Review
    DAP Mumthaz
    International Journal of Multidisciplinary Educational Research 8 (12(7 … , 2019
    2019
  • Impact of Mobile Phone on Society - A Study on the Pattern of Mobile Phone Usage by the Young Generation in India
    International Journal of Multidisciplinary Educational Research 8 (12(7)), 55-62 , 2019
    2019
  • A Study on Job Satisfacion of Employees at Meriiboy Ice Creams (Supreme Food Industries)
    International Journal for Research in Applied Science & Engineering … , 2019
    2019
  • Make in India Initiate Progress and Road Map For Future
    An International Multidisciplinary Quarterly Research Journal AJANTA 7 (1 … , 2019
    2019

MOST CITED SCHOLAR PUBLICATIONS

  • [Retracted] Empirical Analysis for Improving Food Quality Using Artificial Intelligence Technology for Enhancing Healthcare Sector
    SK UmaMaheswaran, G Kaur, A Pankajam, A Firos, P Vashistha, ...
    Journal of Food Quality 2022 (1), 1447326 , 2022
    2022
    Citations: 36
  • [Retracted] Secure Big Data Processing in Multihoming Networks with AI‐Enabled IoT
    S Venu, J Kotti, A Pankajam, D Dhabliya, GN Rao, R Bansal, A Gupta, ...
    Wireless Communications and Mobile Computing 2022 (1), 3893875 , 2022
    2022
    Citations: 24
  • Efficient COVID-19 identification using deep learning for IoT
    V Veeraiah, A Pankajam, E Vashishtha, D Dhabliya, P Karthikeyan, ...
    2022 5th International Conference on Contemporary Computing and Informatics … , 2022
    2022
    Citations: 15
  • Lung cancer detection and recognition using deep learning mechanisms for healthcare in ioT environment
    A Shalini, A Pankajam, V Talukdar, S Farhad, G Talele, E Muniyandy, ...
    Int J Intelligent Syst Appl Eng 12, 208-16 , 2024
    2024
    Citations: 5
  • Service Quality Perception in Private Banks: A Study with Special Reference to Karur Vysya Bank Ltd
    S Rani, N Maurya, S Shaika, A Pankajam
    ECS Transactions 107 (1), 16803 , 2022
    2022
    Citations: 5
  • The central bank of India as an example of the green revolution in the banking sector
    SS Shukla, S Bajpai, A Pankajam, A Gupta, V Veeraiah, S Pramanik, ...
    Recent Developments in Financial Management and Economics, 166-184 , 2024
    2024
    Citations: 3
  • Digital India-A Transformative Technology in Everyday Life
    PJ Sai, A Pankajam
    Management and Social Sciences (IJMSS), 141 , 2019
    2019
    Citations: 3
  • Influence of behavioural factors on investment decision making behaviour of individual investors
    A Pankajam
    Department of Management Studies, Pondicherry University , 2017
    2017
    Citations: 3
  • Feature fusion based deep learning model for Alzheimer's neurological disorder classification
    A Kumar, S Pradeep, K Arora, G Sreeram, A Pankajam, T Patil, A Sahu
    Neuroscience Informatics 5 (2), 100196 , 2025
    2025
    Citations: 2
  • A study on effects of GST on farmers and agricultural sector: An empirical analysis in India
    A Gautam, G Shrivastava, A Pankajam, R Bansal, A Gupta, MB Alazzam
    AIP Conference Proceedings 2587 (1), 140007 , 2023
    2023
    Citations: 2
  • Digitalisation for sustainable development
    A Pankajam
    Asian Journal of Multidimensional Research (AJMR) 7 (1), 201-207 , 2018
    2018
    Citations: 2
  • Harnessing AI Technologies to Simplify Human Resource Communication
    GA Dudekula, HSA Basha, A Pankajam, A Gupta, R Shukla, S Jain
    2025 International Conference on Innovations and Emerging Technologies In AI … , 2025
    2025
  • Neuroscience Informatics
    S Kumari, B Rana, S Chaudhary, R Rajan, SS Kumaran, AK Srivastava, ...
    2025
  • A Cross Country Analysis of the Opportunities and Challenges in the Banking Sector
    AS Kiruba, PM Safeer, A Pankajam, G Lakhera
    Advancements in Business for Integrating Diversity, and Sustainability, 17-22 , 2024
    2024
  • Empirical Analysis for Improving Food Quality Using Artificial Intelligence Technology for Enhancing Healthcare Sector (Retraction of Vol 2022, art no 1447326, 2022)
    SK UmaMaheswaran, G Kaur, A Pankajam
    JOURNAL OF FOOD QUALITY 2024 , 2024
    2024
  • FACTORS INFLUENCING THE ENGLISH LANGUAGE SKILLS OF THE HIGHER SECONDARY SCHOOL STUDENTS ON THEIR COMMUNICATION BEHAVIOUR.
    SK Nathan, S SreeLekha, A Pankajam, C Mandal, S Sekar, D Nimavat
    International Journal of Early Childhood Special Education 14 (3) , 2022
    2022
  • Research Article Secure Big Data Processing in Multihoming Networks with AI-Enabled IoT
    S Venu, J Kotti, A Pankajam, D Dhabliya, GN Rao, R Bansal, A Gupta, ...
    2022
  • Research Article Empirical Analysis for Improving Food Quality Using Artificial Intelligence Technology for Enhancing Healthcare Sector
    SK UmaMaheswaran, G Kaur, A Pankajam, A Firos, P Vashistha, ...
    2022
  • Study On Impact Of Virtual Employee Performance Management On Employee Productivity During Covid-19 Pandemic With Reference To Higher Education Sector In Kerala
    NI Mumthas, AP Pankajam
    Design Engineering, 9745-9759 , 2021
    2021
  • A Study on Impact of HR Analytics on the Human Resource Management System in a Competitive Context: A Literature Review
    DAP Mumthaz
    International Journal of Multidisciplinary Educational Research 8 (12(7 … , 2019
    2019