• A separable temporal convolutional networks based deep learning technique for discovering antiviral medicines 

  Singh, Vishakha; Singh, Sanjay Kumar (Nature Research, 2023-12)

  An alarming number of fatalities caused by the COVID-19 pandemic has forced the scientific community to accelerate the process of therapeutic drug discovery. In this regard, the collaboration between biomedical scientists ...
• Criticality and Utility-Aware Fog Computing System for Remote Health Monitoring 

  Singh, Moirangthem Biken; Taunk, Navneet; Mall, Naveen Kumar; Pratap, Ajay (Institute of Electrical and Electronics Engineers Inc., 2023-05-01)

  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 ...
• Performance measurement of safety-critical systems based on ordinary differential equations and Petri nets: A case study of nuclear power plant 

  Singh, Lalit Kumar (Korean Nuclear Society, 2022-11-29)

  This article proposes a novel approach to measure the performance of Safety-Critical Systems (SCS). Such systems contain multiple processing nodes that communicate with each other is modeled by a Petri nets (PN). The paper ...
• A Review of the Machine Learning Algorithms for Covid-19 Case Analysis 

  Tiwari, Shrikant; Chanak, Prasenjit; Singh, Sanjay Kumar (Institute of Electrical and Electronics Engineers Inc., 2023-02-01)

  The purpose of this article is to see how machine learning (ML) algorithms and applications are used in the COVID-19 inquiry and for other purposes. The available traditional methods for COVID-19 international epidemic ...
• Measurement of missing video frames in NPP control room monitoring system using Kalman filter 

  Chaubey, Mrityunjay; Singh, Lalit Kumar; Gupta, Manjari (Korean Nuclear Society, 2022-09-03)

  Using the Kalman filtering technique, we propose a novel method for estimating the missing video frames to monitor the activities inside the control room of a nuclear power plant (NPP). The purpose of this study is to ...
• Advanced Hierarchical Topic Labeling for Short Text 

  Tiwari, Paras; Tripathi, Ashutosh; Singh, Avaneesh; Rai, Sawan (Institute of Electrical and Electronics Engineers Inc., 2023-04-05)

  Hierarchical Topic Modeling is the probabilistic approach for discovering latent topics distributed hierarchically among the documents. The distributed topics are represented with the respective topic terms. An unambiguous ...
• Machine Learning-Based Interference Mitigation in Long-Range Networks for High-Ceiling Smart Buildings 

  Kumar, Ramakant; Gupta, Hari Prabhat; Mishra, Rahul; Pandey, Shubham (Institute of Electrical and Electronics Engineers Inc., 2023-08-29)

  Long-Range networks are increasingly used in smart spaces due to their ability to provide longer communication range while consuming low energy. To facilitate communication among different Long-Range nodes, a gateway is ...
• Security, Trust and Privacy Solutions for Intelligent Internet of Vehicular Things-Part II 

  Ghosh, Uttam; Maziku, Hellen; Gupta, Hari Prabhat; Sikdar, Biplab; Rodrigues, Joel J. P. C. (Institute of Electrical and Electronics Engineers Inc., 2022-12-06)
• Designing and Training of Lightweight Neural Networks on Edge Devices using Early Halting in Knowledge Distillation 

  Mishra, Rahul; Gupta, Hari Prabhat (Institute of Electrical and Electronics Engineers Inc., 2023-07-19)

  Automated feature extraction capability and significant performance of Deep Neural Networks (DNN) make them suitable for Internet of Things (IoT) applications. However, deploying DNN on edge devices becomes prohibitive due ...
• Dependency Prediction of Long-Time Resource Uses in HPC Environment 

  Upadhyay, Navin Mani; Singh, Ravi Shankar; Dwivedi, Shri Prakash (Institute of Electrical and Electronics Engineers Inc., 2023-12-08)

  High-Performance computing provides a new infrastructure for scientific calculation and its simulation. However, unbalanced load distribution among the processors causes a decreased performance in such computations, and ...
• Advanced Hierarchical Topic Labeling for Short Text 

  TIWARI, PARAS (Institute of Electrical and Electronics Engineers Inc., 2023-04-05)

  Hierarchical Topic Modeling is the probabilistic approach for discovering latent topics distributed hierarchically among the documents. The distributed topics are represented with the respective topic terms. An unambiguous ...
• A Game-Theoretic Approach for Increasing Resource Utilization in Edge Computing Enabled Internet of Things 

  Kumar, Sumit; Gupta, Ruchir; Lakshmanan K.; Maurya, Vipin (Institute of Electrical and Electronics Engineers Inc., 2022)

  Edge computing is a new paradigm that reduces latency and saves bandwidth by deploying edge servers in different geographic locations. This technology plays a crucial role in the rapidly growing app market for IoT devices ...
• Criticality and Utility-Aware Fog Computing System for Remote Health Monitoring 

  Singh, Moirangthem Biken; Taunk, Navneet; Mall, Naveen Kumar; Pratap, Ajay (Institute of Electrical and Electronics Engineers Inc., 2022)

  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 ...
• Stochastic Arrow-Hurwicz Algorithm for Path Selection and Rate Allocation in Self-Backhauled mmWave Networks 

  Sharma, Abhinav; Lakshmanan K; Gupta, Ruchir; Gupta, Atul (Institute of Electrical and Electronics Engineers Inc., 2022-03)

  ne of the key promoters of 5G deployment using millimetre waves is multi-hop self-backhauling. However, the rate allocation and path selection for these networks are challenging tasks. For this purpose, we consider a network ...
• Clus-DR: Cluster-based pre-trained model for diverse recommendation generation 

  Yadav, Naina; Pal, Sukomal; Singh, Anil Kumar; Singh, Kartikey (King Saud bin Abdulaziz University, 2022-09)

  Recommender Systems are a predictive model for personalized suggestions utilizing past interactions and experiences. Collaborative filtering is the most popular and successful approach. The core idea behind this approach ...
• An integrated approach of designing functionality with security for distributed cyber-physical systems 

  Tripathi, Dipty; Biswas, Amit; Tripathi, Anil Kumar; Singh, Lalit Kumar; Chaturvedi, Amrita (Springer, 2022-09)

  In this work, we propose a multi-tier architectural model to separate functionality and security concerns for distributed cyber-physical systems. On the line of distributed computing, such systems require the identification ...
• Integration of morphological features and contextual weightage using monotonic chunk attention for part of speech tagging 

  Mundotiya, Rajesh Kumar; Mehta, Arpit; Baruah, Rupjyoti; Singh, Anil Kumar (King Saud bin Abdulaziz University, 2022-10)

  Part-of-Speech (POS) tagging is a fundamental sequence labeling problem in Natural Language Processing. Recent deep learning sequential models combine the forward and backward word informatio for POS tagging. The information ...
• TLSPG: Transfer learning-based semi-supervised pseudo-corpus generation approach for zero-shot translation 

  Kumar, Amit; Mundotiya, Rajesh Kumar; Pratap, Ajay; Singh, Anil Kumar (King Saud bin Abdulaziz University, 2022-10)

  Machine Translation (MT) has come a long way in recent years, but it still suffers from data scarcity issue due to lack of parallel corpora for low (or sometimes zero) resource languages. However, Transfer Learning (TL) ...
• Hierarchical self attention based sequential labelling model for Bhojpuri, Maithili and Magahi languages 

  Mundotiya, Rajesh Kumar; Mishra, Swasti; Singh, Anil Kumar (King Saud bin Abdulaziz University, 2022-10)

  Sequential labelling plays a vital role in solving numerous Natural Language Processing (NLP) applications such as Machine Translation and Information Extraction etc. One of these is Part-of-Speech (POS) tagging, which ...
• A Fast, Multi-Camera, and Intelligent System for Exact Stampede Detection in Large Crowds 

  Nigam, Nitika; Dutta, Tanima (Association for Computing Machinery, Inc, 2022-11)

  With the increasing population, events with large crowds also increased. It often leads to uncontrolled stampede situations, causing several deaths. Deployment of intelligent systems with the quick alert feature may reduce ...

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