Browsing by Author "Ajay Pratap"

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Assessing ethnoarchaeology’s contemporary relevance
(Routledge, 2016) Ajay Pratap
[No abstract available]
COVID-19 Spread Detection and Controlling with Fog-based Infection Probability Evaluation Model
(Association for Computing Machinery, 2023) Moirangthem Biken Singh; Suraj Mahawar; Himanshu Singh; Ajay Pratap
COVID-19 has created a pandemic worldwide, paused the path of building the future, and is still ongoing without any long-term solution. The time taken in vaccine distribution is too slow compared to the spread of COVID-19. Hence, it is important to be aware and take precautions on time without delaying and waiting for long-duration after getting infected with the virus. Technology nowadays is more advanced than ever before. Almost everyone has access to at least one mobile device with internet connection. Therefore, we propose a Fog Server (FS) based system that helps create awareness about the spread of COVID-19 within the surroundings of an individual, utilizing the concept of Hidden Markov Model (HMM) and Bluetooth contact tracing in polynomial computational time complexity. Moreover, we evaluate the effectiveness of the proposed model through real-world data analysis on different simulation settings. © 2023 ACM.
Criticality and Utility-Aware Fog Computing System for Remote Health Monitoring
(Institute of Electrical and Electronics Engineers Inc., 2023) Moirangthem Biken Singh; Navneet Taunk; Naveen Kumar Mall; Ajay Pratap
Growing remote health system allows continuous monitoring of patients' conditions outside medical facilities. However, the real-time smart-healthcare applications having latency limitations, must be solved efficiently. Fog computing is emerging as an efficient solution for such real-time applications. Therefore, Medical Centers (MCs) are becoming more interested in offering IoT-based remote health monitoring services to get profited by deploying fog resources. However, an efficient algorithmic model for allocating limited fog computing resources in a criticality-aware smart-healthcare system while considering the profit of MCs is needed. Thus, we formulate an optimization problem by maximizing system utility, calculate as a linear combination of MC's profit and patients' cost together. We propose a flat-pricing based scheme to measure the profit of MC in health monitoring system. Further, we propose a swapping-based heuristic to maximize the system utility. The proposed heuristic is evaluated on various parameters and shown to be closed to the optimal while considering the criticality of patients and the profit of MC, together. Through extensive simulations, analysis on real-world data and prototype implementation, we find that the proposed heuristic achieves an average utility of 94.5% of the optimal, in polynomial time complexity. © 2008-2012 IEEE.
Cyclic Stable Matching Inspired Resource Provisioning for IoT-Enabled 5G Networks
(Institute of Electrical and Electronics Engineers Inc., 2022) Ajay Pratap
The next-generation wireless network is expected to be highly dense with a large number of heterogeneous Internet of Things (IoT) devices, working in co-operation with various Small Cell Access Points (SAPs) and Fog Servers (FSs) underlying cellular 5G infrastructure, altogether. The densely deployed 5G architecture is expected to fulfill the IoT's growing data demand in a feasible computational complexity. In this work, the resource provisioning mechanism in a heterogeneous 5G network is formulated to maximize the overall benefit of SAPs by selecting the most appropriate FSs for offloading the set of IoT tasks, as an NP-hard problem. Moreover, a Restricted Three-sided Matching with Size and Cyclic (R-TMSC) preference model is implemented to obtain a stable solution among IoTs, SAPs, and FSs underlying cellular 5G networks. Furthermore, the effectiveness of the proposed heuristic is shown through theoretical, experimental, and real-world data analysis. © 1967-2012 IEEE.
Energy-Efficient and Privacy-Preserving Blockchain Based Federated Learning for Smart Healthcare System
(Institute of Electrical and Electronics Engineers Inc., 2024) Moirangthem Biken Singh; Himanshu Singh; Ajay Pratap
The privacy-focused concept of Federated Learning (FL) allows local data processing without disclosing patients' health details to a central server. However, its vulnerability to privacy breaches through shared model weights and susceptibility to a single point of failure remain concerns. Energy constraints of Wireless Body Area Networks (WBANs) necessitate considering computation and transmission energy in the FL process. Thus, this article introduces a smart healthcare system prioritizing energy efficiency and privacy through a blockchain-backed FL model. Yet, WBAN users might be unwilling to share data without adequate incentives, and miners might hesitate due to the high energy usage associated with maintaining the blockchain. Therefore, an optimization problem is formulated to maximize system utility while considering energy, WBAN incentives, miner revenue, and FL loss. A computationally efficient stable matching-based algorithm is proposed for optimizing utility via associating WBANs and miners. Associated WBANs use Quantized Neural Networks (QNNs) to minimize computation energy. Moreover, this work integrates Differential Privacy (DP) and Homomorphic Encryption (HE) mechanisms to prevent information leakage by adding noise to gradients before updating model weights and encrypting consequences before transmitting them to miners. Real-world experiments validate the framework, yielding an average of 15.1%, 9.03%, and 15.35% improvements over existing methods. © 2008-2012 IEEE.
Generative Adversarial Neural Machine Translation for Phonetic Languages via Reinforcement Learning
(Institute of Electrical and Electronics Engineers Inc., 2023) Amit Kumar; Ajay Pratap; Anil Kumar Singh
Neural Machine Translation (NMT) heavily depends on the context vectors generated via attention network for the target word prediction. Existing works primarily focus on generating context vectors from words or subwords of sentences, limiting NMT models' ability to learn sufficient information about the source sentence representations. These situations are even worse when languages belong to extremely low-resource categories due to rare word problem. To improve the learning of source sentence representations and handle the rare word problem of Low Resource Languages (LRLs), we propose a novel improvement in Generative Adversarial Networks (GAN)-NMT by incorporating deep reinforcement learning-based optimised attention in generator and convolutional neural network in discriminator. We also create the novel joint embedding of subwords and sub-phonetic representation of sentences as input to GAN that helps models to learn the better representations and generate suitable context vectors compared to existing traditional approaches for LRLs. To show the effectiveness of our method, we demonstrate experiments on LRLs pairs, e.g., Gujarati Hindi, Nepali Hindi, Punjabi Hindi, Maithili Hindi and Urdu Hindi. Our proposed novel approach suppress the existing state-of-the-art techniques with considerable improvement. © 2017 IEEE.
Ideas and images: A historical interpretation of Eastern Vindhyan rock art, India
(Archaeopress, 2024) Ajay Pratap
This book argues that the development of symbols and signs informing scripts, mainly the idea of coding thoughts through symbols and images, has always been uniquely 'historical.' Rock art abuts and occupies long periods of time in which the translation of indigenous thoughts was perfected through numerous mnemonic practices. Ideas and Images argues that the development of symbols and signs informing scripts, mainly the idea of coding thoughts through symbols and images, has always been uniquely 'historical.' Rock art abuts and occupies long periods of time, from the Mesolithic, Neolithic-Chalcolithic, and Iron Age, to the medieval and colonial, in which the translation of indigenous thoughts was perfected through numerous mnemonic practices, some of them evidently to record in a surprisingly sophisticated historical oeuvre. These are ordered and direct representations of the ontological, philosophical, thought-object world of prehistoric or pre- or non-scripted communities. Such representations are better understood as so many graphic archives, and their temporality is broadly sequential, authentic, unique and historically contextualized since they record exceptional and everyday events, but also sometimes emotionally or humorously charged stories. The genre called 'rock art' is a successful and reliable record of interpretations accorded to society and the natural worlds of the past. The development of symbols informing scripts, or the idea of coding thoughts through symbols, was already in the domain of rock art thousands of years ago. This work builds on the strength of recent historical and archaeological work arguing for the presence of a 'historical sense' in prehistory as the basis for including all prehistoric material as potentially of historical value. The rise of scripts in early parts of the historical era was therefore anticipated in earlier techniques of memorialization. Much of Vindhyan rock art came into existence during a period identified distinctly as historical, and it offers alternate perspectives and views of the 'historical'. The book presents verifiable imagery and events in rock art. It is also postulated that it might be worth considering whether rock art influenced later symbolic forms in terracotta, pottery, sculpture, and coinage. Human, animal, design, decorative forms and imagery feature in all these chronologically later media, although such comparisons and relationships posited with rock art on a one-to-one basis would be misleading. © Archaeopress and Ajay Pratap 2024. All rights reserved.
Loss Aware Federated Learning for Service Migration in Multimodal E-Health Services
(Institute of Electrical and Electronics Engineers Inc., 2024) Himanshu Singh; Ajay Pratap; Ram Narayan Yadav; Debasis Das
In an emergency healthcare situation, delay between injury and treatment is one of the most critical parameters with regard to survivability. Reduction in diagnosis/pre-treatment time by processing real-time ambulance data while en route to hospital can cut back the delay in treatment of the patient. However, several research challenges arise in accessing real-time patient data from ambulance to hospital while moving along different Road Side Units (RSUs). Due to the severity of medical data, there is a need to minimize computational losses along with costs due to migration and ambulance perceived latency. Considering the above scenarios, this paper formulates an average cost minimization problem keeping latency, energy, and loss function into deliberation as NP-hard. To solve the formulated problem, Minimum Cost Algorithm (MCA) using Federated Averaging (FedAvg) algorithm utilizing RSUs for effectively transferring real-time patient data to hospitals has been proposed considering above stated constraints altogether. Moreover, to handle imbalances in health data across different hospitals during processing, FedAvg algorithm combines augmentation techniques. Through experimental and prototype demonstration, the efficacy of proposed framework is shown by achieving 12.5 \%, 27 \%,12.5%,27%, and 38 \%38% reduction in an average total cost compared to other state-of-the-art techniques on real-world data sets, respectively. © 2008-2012 IEEE.
New Brahmi Inscriptions from Maukalan, Panchmukhi, Ahraura, and Lekhahia Pahar in Chandauli, Sonbhadra and Mirzapur Districts, Uttar Pradesh
(ARF India, 2024) Ajay Pratap; T.S. Ravishankar; J.T. Rapheal; Ajit Kumar Singh; Shyam Janam Dubey
Visual symbolic material has been reported from the Eastern Vindhyas for a long time (Cockburn 1883, Ghosh 1932, Kenoyer et al. 2015). Much of this is rock art (Pratap and Kumar 2009, Pratap 2016, 2024). This article discusses finds of unreported early Brahmi and early Nagari inscriptions of the early medieval period. These were discovered during rock art-related fieldwork from July 2021 onwards. This extends our earlier findings of unreported inscriptions in Southern Uttar Pradesh (Pratap and Singh, 2020). In this paper, we discuss a boulder inscription in Maukalan Village, in South Chandauli, and a stele inscription stored in the Maukalan Village Museum, established by the Directorate of Archaeology, Uttar Pradesh. We also discuss this little-known village as an early centre for sculpting, mentioning a Vaikuntha Vishnu statue and an early medieval temple. It is likely this ancient Gond village of Maukalan, existed as a centre for the manufacture of idols, the writing of inscriptions, and other types of stone craft, under the patronage of the nearby fort called Vijaigarh. We also discuss some graffiti at Ahraura (Mirzapur) next to Ashoka’s Minor Rock Edict-I (the Ahraura Version), and two painted inscriptions inside caves at Panchmukhi, in Sonbhadra District, and at Lekhahia Pahar, in Mirzapur. Decipherments and analyses are in a cultural-historical framework. The inscriptions are donative issued by lay people, or itinerant pilgrims and ascetics, while on religious pilgrimage. The spread of Buddhist culture was significant in our study area, due to its proximity to Rajagriha, Sarnath and Kaushambi, Kashi and Mathura. © 2024, ARF India. All rights reserved.
On the use of the term 'non-Anglo archaeologists'
(2008) Ajay Pratap
Many universities in India teach in both English and Hindi to separate classes-the students have an option to choose their language of instruction. Thus the claim of non-Anglo archaeologists as being co-opted raises the double question of being co-opted by whom and for what purpose? If it is the case that there are co-opted third and fourth world archaeologists, then who is to blame and how may this situation be rectified. I feel every-one has the answer to this question and nothing more needs be said about it. My sympathies rest with the co-opted. © 2008 World Archaeological Congress.
Optimized Doctor Recommendation System using Supervised Machine Learning
(Association for Computing Machinery, 2023) Himanshu Singh; Moirangthem Biken Singh; Ranju Sharma; Jayesh Gat; Ayush Kumar Agrawal; Ajay Pratap
In the past decade, we have seen many patients and healthcare problems. Due to this, patients find difficulty choosing doctors according to their disease. Several Machine Learning (ML) based techniques already exist to predict doctors based on patient's health conditions. However, it is essential to accurately recommend doctors to patients with low errors based on patients' health conditions. Therefore, we propose a method that assigns quantitative importance (weight) to each feature using an ML technique. Moreover, we offer a framework to recommend doctors based on the similarity score and doctor's skill score, which utilizes weight prediction to enhance operational efficiency. Additionally, on real-world datasets, the effectiveness of the proposed framework is demonstrated empirically by lowering the average loss by roughly 34% and 3% as compared to Convolutional Neural Network (CNN) and Support Vector Machine (SVM), respectively. The outcome demonstrates that the algorithm can efficiently recommend doctors to patients compared to state-of-the-art techniques. This analysis technique aid patients in opting for the right doctor. © 2023 ACM.
Optimizing Resource Utilization and QoS-Conscious Application Deployment Through AHP in Edge Computing
(Institute of Electrical and Electronics Engineers Inc., 2024) Yasasvitha Koganti; Ram Narayan Yadav; Ajay Pratap
Edge computing has emerged as a promising technology to satisfy the demand for data computational resources in Internet of Things (IoT) networks. With edge computing, processing of the massive data-intensive tasks can be in the proximity of IoT users. Thus, the required constraints related to tasks such as resource requirements, and the quality of service can be guaranteed. However, the question that how to determine the task offloading strategy under various constraints of resources, distance, and cost is still an open issue. In this paper, we study the task offloading problem from a matching perspective and propose an Edge-User Assignment Algorithm (EUAA) that aims to maximize the resource utilization of edge servers while satisfying the Quality of Service (QoS) requirement of IoT users. In any matching algorithm, the main concern is how to generate the preference order of either side. To generate preference orders for edge servers, we use the concept of the Analytical Hierarchy Process (AHP). We have considered the following criteria: distance from users to the server, latency, available resources, and pricing. This generates the priority of the users for matching to edge servers. From IoT users' perspective, we use cost, and QoS parameters to improve their satisfaction. We compare the performance using the number of assigned users, servers' profit, number of satisfied users, and edge server resources used. The simulation results confirm that significant profit and satisfied users can be achieved by the proposed algorithm. © 2024 IEEE.
QoS-Aware Application Assignment and Resource Utilization Maximization Using AHP in Edge Computing
(Institute of Electrical and Electronics Engineers Inc., 2025) Yasasvitha Koganti; Vidhyuth Sridhar; Ram Narayan Yadav; Ajay Pratap
Edge computing (EC) has emerged as a promising technology to meet the demand for computational resources in Internet of Things (IoT) networks. With EC, the processing of massive data-intensive tasks can occur in proximity to IoT users. Thus, required constraints related to tasks, such as latency and Quality of Service (QoS) can be guaranteed. However, determining the task offloading strategy under various constraints, including resources, distance, and cost, remains an open issue. In this article, we study the task offloading problem from a matching perspective and propose an edge-user assignment algorithm (EUAA) that aims to maximize the resource utilization of edge servers and the number of assigned IoT users. A key concern in any matching algorithm is how to generate the preference order for either side. To generate preference orders for edge servers, we apply the analytical hierarchy process (AHP), considering criteria, such as distance from users to the server, latency, resource requirements, and pricing. This approach establishes the priority of users for matching to edge servers. From the IoT users’ perspective, we use cost and QoS parameters to enhance their satisfaction. We evaluate the performance of the proposed model based on the number of assigned users, server profit, number of satisfied users, edge server resource utilization, and execution time, comparing it with state-of-the-art schemes. © 2014 IEEE.
Rock art of the vindhyas: An archaeological survey: Documentation and analysis of the rock art of Mirzapur District, Uttar Pradesh
(Archaeopress, 2016) Ajay Pratap
Rock paintings and petroglyphs are a record of human memories. No doubt, this function defines in essence all archaeological objects. Yet some objects such as tools, beyond their symbolic value, are clearly fashioned for their utility. How does rock art as an object fashioned by human hands then differ from tools? What utility does it have beyond its symbolic value? The Vindhyan corpus of rock paintings has provided us with a very valuable opportunity to be answering such questions. © Archaeopress and A Pratap 2016.
Splitfed-based Patient Severity Prediction and Utility Maximization in Industrial Healthcare 4.0
(Association for Computing Machinery, 2024) Himanshu Singh; Biken Moirangthem; Ajay Pratap; Shilpi Kumari; Abhishek Kumar; Sajal K. Das
The healthcare industry has transitioned from traditional healthcare 1.0 to AI-powered healthcare 4.0. However, overall cost for patient treatment remains high and challenging to manage due to the absence of a centralized cost evaluation mechanism before hospital visits. Therefore, in this paper, we devise a cloud-based mechanism to calculate hospitals' star rating based on questionnaire with the application of Z-score and K∗clustering algorithm. To evaluate disease severity at cloud, splitfed technique is utilized in coordination with Wireless Body Area Network (WBAN). Finally, the cloud calculates provisional treatment costs and finds a preferable hospital with a low payable treatment cost and satisfactorily high rating for the patient via utility maximization in a cloud-based environment. Moreover, the effectiveness of the proposed polynomial algorithmic model is shown theoretically, experimentally, and comparing with other state-of-the-art methods on real-world data. © 2024 ACM.
Stable Matching Based Resource Allocation for Service Provider's Revenue Maximization in 5G Networks
(Institute of Electrical and Electronics Engineers Inc., 2022) Ajay Pratap; Sajal K. Das
5G technology is foreseen to have a heterogeneous architecture with the various computational capability, and radio-enabled service providers (SPs) and service requesters (SRs), working altogether in a cellular model. However, the coexistence of heterogeneous network model spawns several research challenges such as diverse SRs with uneven service deadlines, interference management, and revenue maximization of non-uniform computational capacities enabled SPs. Thus, we propose a coexistence of heterogeneous SPs and SRs enabled cellular 5G network and formulate the SPs' revenue maximization via resource allocation, considering different kinds of interference, data rate, and latency altogether as an optimization problem and further propose a distributed many-to-many stable matching based solution. Moreover, we offer an adaptive stable matching based distributed algorithm to solve the formulated problem in a dynamic network model. Through extensive theoretical and simulation analysis, we have shown the effect of different parameters on the resource allocation objectives and achieves 94 percent of optimum network performance. © 2002-2012 IEEE.
The Depicted Past: “Historical” Panels in the Rock Art of the Eastern Vindhyas, Uttar Pradesh, India
(Routledge, 2025) Ajay Pratap
In this paper, we discuss continuities in rock art preserving long-term visual histories in the Eastern Vindhyan Hills of Mirzapur and Sonbhadra Districts of southern Uttar Pradesh. Following this argument, we also try to explicate the probable causes of symbolic historical narratives, from the Mesolithic until the nineteenth century, in the Vindhyan highlands. It is thought that “prehistoric” groups had memory but no sense of history, but the past was depicted, curated, and storied panels continued from prehistory to the present, on the mountainous peripheries of the Ganges Valley. Symbolic skills for depiction, in various media, were also passed down through several generations of escarpment dwelling. We treat rock drawings and paintings therefore as a social self-reflexive record of “the past within the past”, by connecting visual representation with cognition and memory. In the documentation presented, we refer to the local ethnography of traditional pastoral and agricultural groups with notable symbolic behaviour. Among these plateau groups, symbolic depiction was a cultural response to environmental change and, much later, early historic urbanization in adjoining valleys. Notable urban demands upon indigenous raw material resources and labour led to representations in which non-indigenous people were also drawn and painted. We conclude that rock paintings were adjunct to oral tradition and were a form of inclusive “cultural cognition”. © 2025 The British Association for South Asian Studies.