Browsing by Author "Chakraborty, S."

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A Comparative Study of Optimizers on Non-pretrained CNN Models for Stray Animal Surveillance System
(Springer Science and Business Media Deutschland GmbH, 2025) Chakraborty, S.
The stray animals sighted on the Indian vehicular roads cause traffic congestions and lead to major road accidents. Due to the menace, many people and animals get serious injuries and even lose their life. The attacks on the humans, damaging of properties and spreading of dangerous diseases such as rabies are the other major concerns due to the increase in stray animals. The present study performs detection and classification of the stray animals on the vehicular streets. The dataset comprises of 500 images of vehicular roads with and without stray animals. The classification accuracy of the surveillance system is compared between Stochastic Gradient Descent (SGD) and Adam optimizer for a 3-layer and 4-layer CNN having different batches. The study aims to act as a surveillance system on the roads for detecting the presence of stray animals. Timely detection and relocation of stray animals can help in preventing the fatalities and spread of diseases. Â© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
A Single Source Quadruple Boost Nine-Level Switched-Capacitor Inverter with Reduced Components and Continuous Input Current
(Institute of Electrical and Electronics Engineers Inc., 2024) Kumar, D.; Raushan, R.; Chakraborty, S.
The multilevel inverter (MLI) serves as a pivotal class of power electronic converters, well-suited for high-power applications at medium voltage levels, ensuring superior power quality. While designing an MLI, there is a motif among the number of components, voltage stress on the semiconductor devices, and its voltage-boosting ability. A single source nine-level switched-capacitor based novel inverter with reduced components has been proposed in this paper. The proposed H-bridge based switched capacitor inverter topology employs nine switches, two capacitors, two diodes, and one DC source. The inverter has a quadruple voltage boost and the ability to draw continuous input current from the DC supply and self-voltage balance with a voltage ripple of less than 5%. A comprehensive study of performance parameters, design consideration, and loss analysis of the proposed inverter is also incorporated. A level-shifted pulse width modulation technique is implemented to operate the inverter for unity to 0.5 lagging load power factors and 1-0.2 modulation indices. The dynamic responses of the proposed switched capacitor inverter topology are obtained through MATLAB simulation for analysis and further validated by hardware prototype. © 2013 IEEE.
An Approach for Predicting Election Results with Trending Twitter Hashtag Information Using Graph Techniques and Sentiment Analysis
(Springer Science and Business Media Deutschland GmbH, 2023) Patra, C.; Shetty D, D.; Chakraborty, S.
India is one of the largest democracies in the world where the Lok Sabha and the Rajya Sabha elections are held every five years. Nowadays, social media acts as an important and inexpensive platform for propagating messages of the political parties. In the present study, a methodology is proposed by combining sentiment analysis and graph techniques to look into the trending hashtag networks propagated by the political parties using Twitter. The demonstration of the proposed methodology is done on the trending hashtagâ€™s information collected from Twitter on the Uttar Pradesh (U.P) state elections, 2022. Â© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
An Approach forÂ Efficient Graph Mining fromÂ Big Data Using Spark
(Springer Science and Business Media Deutschland GmbH, 2023) Gupta, R.K.; Shetty D, D.; Chakraborty, S.
Huge amount of data is generated and accumulated over the last decade, and therefore, the use of data mining techniques is required to extract usable information from these massive data sets. Gaining important connections between data helps in getting useful insights. Depiction of relationships between the data using graphical approach is observed to be a helpful method. It provides an effective technique for demonstrating the working in a variety of situations, including biological networks, social networks, Web networks, and so on. Clustering techniques used in graph mining can be helpful for accumulating significant information. In this paper, an approach for graph mining from big data in Spark (AGMBS) is proposed on the basis of label propagation. The suggested technique enhances the efficiency of the conventional label propagation algorithm by making it more resilient. In addition to this, AGMBS employs a sparse matrix as its primary data structure, resulting in quicker performance. Thereafter, GraphX is used for managing the processing of the graphical data. The experiments were conducted on two graph data sets from the real world, and it is observed that the suggested AGMBS gives faster results as compared to the best available clustering algorithms. Â© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Analyzing Information Flow of Hashtag Networks during Elections using Sentiment Analysis and Graph Algorithms
(Institute of Electrical and Electronics Engineers Inc., 2022) Patra, C.; Shetty D, P.D.; Chakraborty, S.
An exponential increase in the usage of social media across the world creates a lot of unstructured data and cross-communication between individuals. These platforms provides opportunity to the political parties to spread their word out. The information is spread using several hashtags in the form of user-generated tagging that facilitates cross-referencing of content. These hashtag-generated networks serve as a huge reservoir of data and if analyzed systematically can help in understanding the agenda-setting of each party and how successful or unsuccessful they are. This in turn helps in predicting the outcome of the election looking from the prism of social media. In the present study, a model is proposed by combining sentiment analysis and graph techniques to look into the trending hashtag networks propagated by political parties using Twitter. The sentiment analysis gives us a sense of inclination of each tweet and thereafter it's extrapolated onto the hashtag's user network to get insights as to how the information is diffusing and how one party propagates its favorable hashtag and how the others try to counter it. The major aim of the present work is to find out the intricacies that go on in the social media space before a major election. Â© 2022 IEEE.
Castelnuovo–Mumford regularity of the closed neighborhood ideal of a graph
(Springer, 2025) Chakraborty, S.; Joseph, A.P.; Roy, A.; Singh, A.
Let G be a finite simple graph, and let NI(G) denote the closed neighborhood ideal of G in a polynomial ring R. We show that if G is a forest, then the Castelnuovo–Mumford regularity of R/NI(G) is the same as the matching number of G, thus proving a conjecture of Sharifan and Moradi in the affirmative. We also show that the matching number of G provides a lower bound for the Castelnuovo–Mumford regularity of R/NI(G) for any G. Furthermore, we prove that if G contains a simplicial vertex, then NI(G) admits a Betti splitting, and consequently, we show that the projective dimension of R/NI(G) is also bounded below by the matching number of G, if G is a forest or a unicyclic graph. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
CoMCLOUD: Virtual Machine Coalition for Multi-Tier Applications over Multi-Cloud Environments
(Institute of Electrical and Electronics Engineers Inc., 2023) Addya, S.K.; Satpathy, A.; Ghosh, B.C.; Chakraborty, S.; Ghosh, S.K.; Das, S.K.
Applications hosted in commercial clouds are typically multi-tier and comprise multiple tightly coupled virtual machines (VMs). Service providers (SPs) cater to the users using VM instances with different configurations and pricing depending on the location of the data center (DC) hosting the VMs. However, selecting VMs to host multi-tier applications is challenging due to the trade-off between cost and quality of service (QoS) depending on the placement of VMs. This paper proposes a multi-cloud broker model called CoMCLOUD to select a sub-optimal VM coalition for multi-tier applications from an SP with minimum coalition pricing and maximum QoS. To strike a trade-off between the cost and QoS, we use an ant-colony-based optimization technique. The overall service selection game is modeled as a first-price sealed-bid auction aimed at maximizing the overall revenue of SPs. Further, as the hosted VMs often face demand spikes, we present a parallel migration strategy to migrate VMs with minimum disruption time. Detailed experiments show that our approach can improve the federation profit up to 23% at the expense of increased latency of approximately 15%, compared to the baselines. © 2013 IEEE.
Container-based Service State Management in Cloud Computing
(Institute of Electrical and Electronics Engineers Inc., 2021) Nath, S.B.; Addya, S.K.; Chakraborty, S.; Ghosh, S.K.
In a cloud data center, the client requests are catered by placing the services in its servers. Such services are deployed through a sandboxing platform to ensure proper isolation among services from different users. Due to the lightweight nature, containers have become increasingly popular to support such sandboxing. However, for supporting effective and efficient data center resource usage with minimum resource footprints, improving the containers' consolidation ratio is significant for the cloud service providers. Towards this end, in this paper, we propose an exciting direction to significantly boost up the consolidation ratio of a data-center environment by effectively managing the containers' states. We observe that many cloud-based application services are event-triggered, so they remain inactive unless some external service request comes. We exploit the fact that the containers remain in an idle state when the underlying service is not active, and thus such idle containers can be checkpointed unless an external service request comes. However, the challenge here is to design an efficient mechanism such that an idle container can be resumed quickly to prevent the loss of the application's quality of service (QoS). We have implemented the system, and the evaluation is performed in Amazon Elastic Compute Cloud. The experimental results have shown that the proposed algorithm can manage the containers' states, ensuring the increase of consolidation ratio. Â© 2021 IFIP.
Containerized deployment of micro-services in fog devices: a reinforcement learning-based approach
(Springer, 2022) Nath, S.B.; Chattopadhyay, S.; Karmakar, R.; Addya, S.K.; Chakraborty, S.; Ghosh, S.K.
The real power of fog computing comes when deployed under a smart environment, where the raw data sensed by the Internet of Things (IoT) devices should not cross the data boundary to preserve the privacy of the environment, yet a fast computation and the processing of the data is required. Devices like home network gateway, WiFi access points or core network switches can work as a fog device in such scenarios as its computing resources can be leveraged by the applications for data processing. However, these devices have their primary workload (like packet forwarding in a router/switch) that is time-varying and often generates spikes in the resource demand when bandwidth-hungry end-user applications, are started. In this paper, we propose pick–test–choose, a dynamic micro-service deployment and execution model that considers such time-varying primary workloads and workload spikes in the fog nodes. The proposed mechanism uses a reinforcement learning mechanism, Bayesian optimization, to decide the target fog node for an application micro-service based on its prior observation of the system’s states. We implement PTC in a testbed setup and evaluate its performance. We observe that PTC performs better than four other baseline models for micro-service offloading in a fog computing framework. In the experiment with an optical character recognition service, the proposed PTC gives average response time in the range of 9.71 sec–50 sec, which is better than Foglets (24.21 sec–80.35 sec), first-fit (16.74 sec–88 sec), best-fit (11.48 sec–57.39 sec) and mobility-based method (12 sec–53 sec). A further scalability study with an emulated setup over Amazon EC2 further confirms the superiority of PTC over other baselines. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
CSMD: Container state management for deployment in cloud data centers
(Elsevier B.V., 2025) Nath, S.B.; Addya, S.K.; Chakraborty, S.; Ghosh, S.K.
As the containers are lightweight in resource usage, they are preferred for cloud and edge computing service deployment. Containers serve the requests whenever a user sends a query; however, they remain idle when no user request comes. Again, improving the consolidation ratio of container deployments is essential to ensure fewer servers are used in a cloud data center with an optimal resource balance. To increase the consolidation ratio of a cloud data center, in this paper, we propose a system called Container State Management for Deployment (CSMD) to manage the container states. CSMD uses an algorithm to checkpoint the idle containers so that their resources can be released. The new containers are deployed using the released resources in a server. In addition, CSMD uses an algorithm to check the container status periodically, and the containers are resumed from the checkpoint state when the user requests them. We evaluate CSMD in Amazon Elastic Compute Cloud (Amazon EC2) by performing efficient state management of the containers. The experiments in the Amazon cloud show that the proposed CSMD system is superior to the existing algorithms as the proposed system increases the consolidation ratio of data centers. © 2024 Elsevier B.V.
Geo-Distributed Multi-Tier Workload Migration Over Multi-Timescale Electricity Markets
(Institute of Electrical and Electronics Engineers Inc., 2023) Addya, S.K.; Satpathy, A.; Ghosh, B.C.; Chakraborty, S.; Ghosh, S.K.; Das, S.K.
Virtual machine (VM) migration enables cloud service providers (CSPs) to balance workload, perform zero-downtime maintenance, and reduce applications' power consumption and response time. Migrating a VM consumes energy at the source, destination, and backbone networks, i.e., intermediate routers and switches, especially in a Geo-distributed setting. In this context, we propose a VM migration model called Low Energy Application Workload Migration (LEAWM) aimed at reducing the per-bit migration cost in migrating VMs over Geo-distributed clouds. With a Geo-distributed cloud connected through multiple Internet Service Providers (ISPs), we develop an approach to find out the migration path across ISPs leading to the most feasible destination. For this, we use the variation in the electricity price at the ISPs to decide the migration paths. However, reduced power consumption at the expense of higher migration time is intolerable for real-time applications. As finding an optimal relocation is $\mathcal {NP}$NP-Hard, we propose an Ant Colony Optimization (ACO) based bi-objective optimization technique to strike a balance between migration delay and migration power. A thorough simulation analysis of the proposed approach shows that the proposed model can reduce the migration time by 25%-30% and electricity cost by approximately 25% compared to the baseline. © 2008-2012 IEEE.
Influence of disjoining pressure on the dynamics of steadily moving long bubbles inside narrow cylindrical capillaries
(2014) Chaudhury, K.; Acharya, P.V.; Chakraborty, S.
We study the influence of disjoining pressure for moving long bubbles inside cylindrical capillaries. Towards that end, consistent thin-film equations, for the annular region separating the bubble from the channel surface, are presented with specific emphasis on three different attributes: (a) the van der Waals interaction, formalized by the classical Lifshitz form of disjoining pressure; (b) the nonuniformity in film thickness, accommodated by the necessary corrections in the disjoining pressure; and (c) the electrostatic component of disjoining pressure, reminiscent of the electrostatic interactions in the presence of surface charges. The present thin-film analysis appositely uncovers the existence and the breakdown of the two-thirds power law for minimum film thickness behavior. This is attributed to the alteration in the characteristic length scales governing the underlying physics, as quantitatively established by our consistent scaling analysis. In the breakdown regimes, the characteristic length scales are found to be composed of the suitable combinations of the capillary number and the physics driven intrinsic length scales. The characteristics of the breakdown regime reported by us appear to match excellently with reported experimental data in the low capillary number regime. Towards unveiling the possible implications of slope and curvature dependence of disjoining pressure, our analysis reveals that the consequent correction term endorses an order two-thirds power of the capillary number contribution without alerting the governing length scales. The subsequent asymptotic analysis reveals that this correction may be neglected to the leading order approximation. Finally, we consider the electrostatic component of the disjoining pressure which may be realized in the presence of surface charges. Our analysis reveals that the significance of the electrostatic interaction is realized over a very small capillary number regime, leading towards the departure from the two-thirds power law type behavior. Reasonably good agreement is obtained with reported experimental data over this regime. 2014 American Physical Society.
Influence of disjoining pressure on the dynamics of steadily moving long bubbles inside narrow cylindrical capillaries
(American Physical Society, 2014) Chaudhury, K.; Acharya, P.V.; Chakraborty, S.
We study the influence of disjoining pressure for moving long bubbles inside cylindrical capillaries. Towards that end, consistent thin-film equations, for the annular region separating the bubble from the channel surface, are presented with specific emphasis on three different attributes: (a) the van der Waals interaction, formalized by the classical Lifshitz form of disjoining pressure; (b) the nonuniformity in film thickness, accommodated by the necessary corrections in the disjoining pressure; and (c) the electrostatic component of disjoining pressure, reminiscent of the electrostatic interactions in the presence of surface charges. The present thin-film analysis appositely uncovers the existence and the breakdown of the two-thirds power law for minimum film thickness behavior. This is attributed to the alteration in the characteristic length scales governing the underlying physics, as quantitatively established by our consistent scaling analysis. In the breakdown regimes, the characteristic length scales are found to be composed of the suitable combinations of the capillary number and the physics driven intrinsic length scales. The characteristics of the breakdown regime reported by us appear to match excellently with reported experimental data in the low capillary number regime. Towards unveiling the possible implications of slope and curvature dependence of disjoining pressure, our analysis reveals that the consequent correction term endorses an order two-thirds power of the capillary number contribution without alerting the governing length scales. The subsequent asymptotic analysis reveals that this correction may be neglected to the leading order approximation. Finally, we consider the electrostatic component of the disjoining pressure which may be realized in the presence of surface charges. Our analysis reveals that the significance of the electrostatic interaction is realized over a very small capillary number regime, leading towards the departure from the two-thirds power law type behavior. Reasonably good agreement is obtained with reported experimental data over this regime. © 2014 American Physical Society.
Monitoring COVID-19 Cases and Vaccination in Indian States and Union Territories Using Unsupervised Machine Learning Algorithm
(Springer Science and Business Media Deutschland GmbH, 2023) Chakraborty, S.
The worldwide spread of the novel coronavirus originating from Wuhan, China led to an ongoing pandemic as COVID-19. The disease being a contagion transmitted rapidly in India through the people having travel histories to the affected countries, and their contacts that tested positive. Millions of people across all states and union territories (UT) were affected leading to serious respiratory illness and deaths. In the present study, two unsupervised clustering algorithms namely k-means clustering and hierarchical agglomerative clustering are applied on the COVID-19 dataset in order to group the Indian states/UTs based on the pandemic effect and the vaccination program from the period of March, 2020 to early June, 2021. The aim of the study is to observe the plight of each state and UT of India combating the novel coronavirus infection and to monitor their vaccination status. The research study will be helpful to the government and to the frontline workers coping to restrict the transmission of the virus in India. Also, the results of the study will provide a source of information for future research regarding the COVID-19 pandemic in India. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Multi-response optimisation of surface texturing using artificial bee colony algorithm
(2016) Chakraborty, S.; Chakraborty, R.; Nagendrababu, K.; Talla, G.; Gangopadhyay, S.
Determination of the optimal combination of process parameters plays a pivotal role in reducing manufacturing costs while enhancing rate of productivity and standard of quality of the product. This paper deals with fabrication of arrayed structures consisting of cylindrical pillars using reverse electro discharge machining (R-EDM) process, followed by optimisation of the process using artificial bee colony (ABC) algorithm. The influence of various machining parameters such as peak current (Ip), pulse-on time (Ton) and flushing pressure (Fp) on multiple performance measures in R-EDM like material removal rate (MRR), surface roughness (SR), taper and cylindricity error (CE) has been investigated using response surface methodology (RSM) based approach. In the course of this paper, the optimal parameters have been found to be Ip = 10 A; Ton = 179.091 ?s; Fp = 0.2 kg/cm2. The fast convergence and the high degree of closeness with the experimental data under optimal condition establishes the efficiency and robustness of the algorithm. Copyright 2016 Inderscience Enterprises Ltd.
Multi-response optimisation of surface texturing using artificial bee colony algorithm
(Inderscience Publishers, 2016) Chakraborty, S.; Chakraborty, R.; Nagendrababu, K.; Talla, G.; Gangopadhyay, S.
Determination of the optimal combination of process parameters plays a pivotal role in reducing manufacturing costs while enhancing rate of productivity and standard of quality of the product. This paper deals with fabrication of arrayed structures consisting of cylindrical pillars using reverse electro discharge machining (R-EDM) process, followed by optimisation of the process using artificial bee colony (ABC) algorithm. The influence of various machining parameters such as peak current (Ip), pulse-on time (Ton) and flushing pressure (Fp) on multiple performance measures in R-EDM like material removal rate (MRR), surface roughness (SR), taper and cylindricity error (CE) has been investigated using response surface methodology (RSM) based approach. In the course of this paper, the optimal parameters have been found to be Ip = 10 A; Ton = 179.091 ?s; Fp = 0.2 kg/cm2. The fast convergence and the high degree of closeness with the experimental data under optimal condition establishes the efficiency and robustness of the algorithm. © © 2016 Inderscience Enterprises Ltd.
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.
Performance Analysis of Disruptive Instances in Cloud Environment
(Institute of Electrical and Electronics Engineers Inc., 2024) Nandy, P.; Saha, R.; Satpathy, A.; Chakraborty, S.; Addya, S.K.
Virtualization enables the service providers (SPs) to logically partition the resources into virtual machines (VM) instances. Real-world SPs such as Amazon, Google, Microsoft Azure, IBM, and Oracle provide different flavors of VM instances, such as on-demand, reserved, and low-cost or spot, depending on the type of application hosted. The on-demand instances are short-term and typically incur a higher cost than reserved instances that are provisioned for a longer duration at a discounted rate. Low-cost or spot instances are cost-effective compared to on-demand but are reclaimable by the SPs. The SPs often claim that the on-demand and spot instances achieve similar performance, but it is far from that. This paper studies the performance of spot instances via rigorous experimentation over commercial SPs such as Amazon AWS and Microsoft Azure. Real-world evaluations affirm that spot instances perform poorly compared to their on-demand counterpart concerning memory, CPU, disk read, and write operations. We identify such instances as disruptive and name them so because it does not fulfill the performance, durability, and flexibility expectations like an on-demand instance having the same configuration. We also perform hypothesis testing over the experimental data obtained to corroborate our claim further. Â© 2024 IEEE.
Tunable adhesion and slip on a bio-mimetic sticky soft surface
(2019) Bandyopadhyay, S.; Sriram, S.M.; Parihar, V.; Das, Gupta, S.; Mukherjee, R.; Chakraborty, S.
Simultaneous tuning of wettability and adhesion of a surface requires intricate procedures for altering the interfacial structures. Here, we present a simple method for preparing a stable slippery surface, with an intrinsic capability of varying its adhesion characteristics. Cross-linked PDMS, an inherent hydrophobic material commonly used for microfluidic applications, is used to replicate the structures on the surface of a rose petal which acts as a high adhesion solid base and is subsequently oleoplaned with silicone oil. Our results demonstrate that the complex hierarchical rose petal structures can arrest dewetting of the silicone oil on the cross linked PDMS base by anchoring the oil film strongly even under flow. Further, by tuning the extent of submergence of the rose petal structures with silicone oil, we could alter the adhesion characteristics of the surface on demand, while retaining its slippery characteristics for a wide range of the pertinent parameters. We have also demonstrated the possible fabrication of gradient adhesion surfaces. This, in turn, may find a wide variety of applications in water harvesting, droplet maneuverability and no-loss transportation in resource-limited settings. � 2019 The Royal Society of Chemistry.
Tunable adhesion and slip on a bio-mimetic sticky soft surface
(Royal Society of Chemistry, 2019) Bandyopadhyay, S.; Sriram, S.M.; Parihar, V.; das Gupta, S.; Mukherjee, R.; Chakraborty, S.
Simultaneous tuning of wettability and adhesion of a surface requires intricate procedures for altering the interfacial structures. Here, we present a simple method for preparing a stable slippery surface, with an intrinsic capability of varying its adhesion characteristics. Cross-linked PDMS, an inherent hydrophobic material commonly used for microfluidic applications, is used to replicate the structures on the surface of a rose petal which acts as a high adhesion solid base and is subsequently oleoplaned with silicone oil. Our results demonstrate that the complex hierarchical rose petal structures can arrest dewetting of the silicone oil on the cross linked PDMS base by anchoring the oil film strongly even under flow. Further, by tuning the extent of submergence of the rose petal structures with silicone oil, we could alter the adhesion characteristics of the surface on demand, while retaining its slippery characteristics for a wide range of the pertinent parameters. We have also demonstrated the possible fabrication of gradient adhesion surfaces. This, in turn, may find a wide variety of applications in water harvesting, droplet maneuverability and no-loss transportation in resource-limited settings. © 2019 The Royal Society of Chemistry.