Faculty Publications

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Author: search.filters.author.Joshi, S.

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    A new probabilistic rekeying method for secure dynamic groups
    (2008) Joshi, S.; Pais, A.R.
    Logical Key Hierarchy (LKH) is a basic method in secure multicast group rekeying. LKH maintains a balanced tree which provide uniform cost of O(log N) for compromise recovery, where N is group size. However, it does not distinguish the behavior of group members even though they have different probabilities of join or leave. When members have diverse changing probability the gap between LKH and the optimal rekeying algorithm will become bigger. The Probabilistic optimization of LKH (PLKH) scheme, optimized rekey cost by organizing LKH tree with user rekey characteristic. In this paper, we concentrate on further reducing the rekey cost by organizing LKH tree with respect to compromise probabilities of members using new join and leave operations. Simulation results show that our scheme performs 18% to 29% better than PLKH and 32% to 41% better than LKH.
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    Multipath fading characteristics of millimeter wave radio propagation in urban microcellular environment
    (2008) Joshi, S.; Sancheti, S.
    The frequency region 28-38 GHz has potential applications in fixed-wireless broadband services on account of availability of large spectrum and adequate device support to ease spectrum congestion problems, particularly in urban centers. This paper envisages development of a multiray propagation model to investigate multipath fading prevailing in millimeter wave radio propagation in a micro cellular environment. The model is simulated and measurements are carried out to estimate fast fading, propagation loss, and delay spread along micro cellular streets of variable width. The results depicted in the paper yields quantitative trends, with specific use in planning radio cells for fixed- wireless broadband services in urban microcellular environment. © 2008 IEEE.
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    Foliage loss measurements of tropical trees at 35 GHz
    (2008) Joshi, S.; Sancheti, S.
    The presence of foliage in the propagation channel can lead to severe signal attenuation, and thus the effects of vegetation in the propagation environment need to be considered in any prediction model. In the present work, a measurement study is undertaken to quantify the attenuation caused due to tree canopies, at 35 GHz. The trees prevailing in typical Indian deserts, having variation in the leaf size and leaf density along the tree canopy are included in the study and in each case, attenuation characteristics are reported. The results presented in the paper may be of vital importance for radio cell planning operating at millimeter wave frequency. © 2008 IEEE.
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    Investigating the "wisdom of crowds" at scale
    (Association for Computing Machinery, Inc acmhelp@acm.org, 2015) Mysore, A.S.; Yaligar, V.S.; Ibarra, I.A.; Simoiu, C.; Goel, S.; Arvind, R.; Sumanth, C.; Srikantan, A.; Bhargav, H.S.; Pahadia, M.; Dobhal, T.; Ahmed, A.; Shankar, M.; Agarwal, H.; Agarwal, R.; Anirudh-Kondaveeti, S.; Arun-Gokhale, S.; Attri, A.; Chandra, A.; Chilukuri, Y.; Dharmaji, S.; Garg, D.; Gupta, N.; Gupta, P.; Jacob, G.M.; Jain, S.; Joshi, S.; Khajuria, T.; Khillan, S.; Konam, S.; Kumar-Kolla, P.; Loomba, S.; Madan, R.; Maharaja, A.; Mathur, V.; Munshi, B.; Nawazish, M.; Neehar-Kurukunda, V.; Nirmal-Gavarraju, V.; Parashar, S.; Parikh, H.; Paritala, A.; Patil, A.; Phatak, R.; Pradhan, M.; Ravichander, A.; Sangeeth, K.; Sankaranarayanan, S.; Sehgal, V.; Sheshan, A.; Shibiraj, S.; Singh, A.; Singh, A.; Sinha, P.; Soni, P.; Thomas, B.; Tuteja, L.; Varma-Dattada, K.; Venkataraman, S.; Verma, P.; Yelurwar, I.
    In a variety of problem domains, it has been observed that the aggregate opinions of groups are often more accurate than those of the constituent individuals, a phenomenon that has been termed the "wisdom of the crowd." Yet, perhaps surprisingly, there is still little consensus on how generally the phenomenon holds, how best to aggregate crowd judgements, and how social influence affects estimates. We investigate these questions by taking a meta wisdom of crowds approach. With a distributed team of over 100 student researchers across 17 institutions in the United States and India, we develop a large-scale online experiment to systematically study the wisdom of crowds effect for 1,000 different tasks in 50 subject domains. These tasks involve various types of knowledge (e.g., explicit knowledge, tacit knowledge, and prediction), question formats (e.g., multiple choice and point estimation), and inputs (e.g., text, audio, and video). To examine the effect of social influence, participants are randomly assigned to one of three different experiment conditions in which they see varying degrees of information on the responses of others. In this ongoing project, we are now preparing to recruit participants via Amazon's Mechanical Turk.
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    Network Science based Predictive Analysis on Social Media Data
    (Institute of Electrical and Electronics Engineers Inc., 2023) Joshi, S.; Kamath S․, S.
    Traditional approaches utilizing machine learning algorithms have limitations in capturing the full depth and semantic nuances of text, hindering comprehensive analysis for tasks like opinion mining, sentiment analysis, population health analytics etc. To overcome these limitations, we propose the integration of graph analysis and Social Network Analysis (SNA) techniques to enhance the informative value of tweet analysis and facilitate the extraction of structured knowledge from textual and visual content. This work focuses on modeling user-generated content on Twitter to enable intelligent population analytics applications in the healthcare domain. Standard datasets comprising user details and their tweets are considered for the experiments, which are transformed into graph representations suitable for both structural and behavioral analytics. Additionally, a comparative study to assess the impact of varying network sizes by manipulating the number of nodes within the network is conducted. To evaluate the network properties, different centrality measures were employed and compared. © 2023 IEEE.
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    Social Network Science Approaches for Disease Named Entity Recognition and Extraction
    (IEEE Computer Society, 2024) Joshi, S.; Kamath S․, S.
    Conventional machine learning approaches adopted for large-scale social media analysis have encountered significant limitations in capturing the underlying dynamics, evolution, and semantic nuances of user posts, hindering comprehensive analysis for tasks related to population health analytics. In this article, the integration of network science-based techniques for node importance/influence analysis, and, Transformer models for Named Entity Recognition are proposed, to facilitate the extraction of structured knowledge from social network posts for population health analytics applications. Standard datasets comprising user account details and postsare considered for the experiments, which are first transformed into graph representations suitable for both structural and behavioral analytics. To evaluate the node importance/influence, different centrality measures were employed and compared. Additionally, a comparative study to assess the impact of varying network sizes by manipulating the number of nodes within the network is conducted. Large-scale mining of disease mentions as a named entity recognition task is also attempted, using neural language models. The proposed approach achieved promising results, outperforming state-of-the- art works by 14.7% in terms of f1-score. © 2024 IEEE.
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    Valorization of Incinerated Biomedical Waste Ash in Cementitious System: A Comprehensive Review
    (Springer Science and Business Media Deutschland GmbH, 2025) Joshi, S.; Snehal, K.; Das, B.B.; Barbhuiya, S.
    Disposing of incinerated biomedical waste ash (IBWA) contaminated with heavy metals (e.g., Cr, Zn, Pb) poses significant environmental and public health concerns, necessitating innovative and sustainable management strategies. Cement-based solidification emerges as a promising approach to repurpose IBWA by effectively immobilizing heavy metals and mitigating their ecological footprint. However, broader industrial and societal acceptance of IBWA as a substitute for cement and sand remains constrained owing to limited quantification of IBWA availability and safety concerns. In this perspective, the current paper presents a global database on IBWA availability and maps the geographic distribution of biomedical waste incinerators in India. It also comprehensively reviews IBWA’s potential in mortar/concrete, focusing on its physico-chemical, leachability, hydration, mechanical, durability, and microstructural properties. The study further highlights the importance of a cradle-to-gate and gate-to-gate Life Cycle Assessment (LCA) to holistically assess the environmental performance of IBWA-incorporated mortar systems, promoting circular economy principles and resource efficiency in the construction sector. IBWA, with its high SiO₂ and CaO content (> 50%), exhibits latent hydraulic properties suitable for construction applications. The porous cellular structure of IBWA can lead to increased porosity and water absorption in concrete. Leachate analysis demonstrated the effective stabilization of heavy elements within the cement hydration matrix (C-S-H, C-A-S-H, etc.), meeting US EPA regulatory standards. LCA interprets that IBWA utilization of up to 10% cement replacement material and 30% sand replacement material could curtail the carbon footprint and energy demand by ~ 25–35% and 15–25%, respectively, compared to conventional cement-based mortar systems. These findings highlight IBWA’s potential to transform the construction sector, aligning it with global sustainability goals and reducing its dependence on non-renewable resources. © The Author(s), under exclusive licence to Shiraz University 2025.
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    A new probabilistic rekeying method for secure multicast groups
    (2010) Pais, A.R.; Joshi, S.
    The Logical Key Hierarchy (LKH) is the most widely used protocol in multicast group rekeying. LKH maintains a balanced tree that provide uniform cost of O(log N) for compromise recovery, where N is group size. However, it does not distinguish the behavior of group members even though they may have different probabilities of join or leave. When members have diverse changing probabilities, the gap between LKH and the optimal rekeying algorithm will become bigger. The Probabilistic optimization of LKH (PLKH) scheme, optimized rekey cost by organizing LKH tree with user rekey characteristic. In this paper, we concentrate on further reducing the rekey cost by organizing LKH tree with respect to rekey probabilities of members using new join and leave operations. Simulation results show that our scheme performs 18 to 29% better than PLKH and 32 to 41% better than LKH. © 2010 Springer-Verlag.
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    Exploring grinding and burnishing as surface post-treatment options for electron beam additive manufactured Alloy 718
    (Elsevier B.V., 2020) Karthick Raaj, R.; Vijay Anirudh, P.; Karunakaran, C.; Kannan, C.; Jahagirdar, A.; Joshi, S.; Balan, A.S.S.
    Numerous additive manufacturing (AM) techniques have been developed over the past decade. Features like immense freedom of intricate part design and shorter lead time make AM routes promising for a wide range of applications spanning aerospace, marine and automobile sectors. Among the various metal AM processes, Electron Beam Additive Manufacturing (EBAM) is being widely explored to realise the potential of Ni-based superalloys and Ti alloys for varied high-performance applications. A novel attempt has been made in this paper to assess the surface integrity of as-built EBAM nickel-based superalloy 718 (AB) subjected to grinding (G), Low Plasticity Burnishing (LPB) and their sequential combination. Apart from their influence on sub-surface microstructures, the effect of process variables during the above post-treatments on the residual stress profiles was also investigated. Results revealed that G + LPB results in about 0.6 ?m lower surface roughness, 17% improved microhardness compared to AB + LPB, and higher compressive surface residual stress as compared to LPB processed EBAM samples. The sequential grinding and LPB - improved microhardness, was also found to extend about 500 ?m more when compared to the LPB process. The G + LPB, which is greatly influenced by the prior grinding, smoothens the surface and thus results in a better surface finish. Highest hardness, superior surface finish, reduced porosity and improved compressive residual stress were observed in samples that adopted the AB + G + LPB sequence over other samples, with the LPB step at 40 MPa yielding the best results. © 2020 Elsevier B.V.
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    Numerical modelling and analytical comparison of delamination during cryogenic drilling of cfrp
    (MDPI, 2021) Balan, A.S.S.; Kannan, C.; Jain, K.; Chakraborty, S.; Joshi, S.; Rawat, K.; F Alsanie, W.F.; Thakur, V.K.
    Carbon-Fibre-Reinforced Polymers (CFRPs) have seen a steady rise in modern industrial applications due to their high strength-to-weight ratio and corrosion resistance. However, their potential is being hindered by delamination which is induced on them during machining operations. This has led to the adoption of new and innovative techniques like cryogenic-assisted machining which could potentially help reduce delamination. This study is aimed at investigating the effect of cryogenic conditions on achieving better hole quality with reduced delamination. In this paper, the numerical analysis of the drilling of CFRP composites is presented. Drilling tests were performed experimentally for validation purposes. The effects of cooling conditions and their subsequent effect on the thrust force and delamination were evaluated using ABAQUS/CAE. The numerical models and experimental results both demonstrated a significant reduction in the delamination factor in CFRP under cryogenic drilling conditions. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.