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Partial domination in prisms of graphs
For any graph G = (V,E) and proportion p ? (0,1], a set S ? V is a p-dominating set if |N|V[S|]| ? p. The p-domination number ?p(G) equals the minimum cardinality of a p-dominating set in G. For a permutation ? of the vertex set of G, the graph ?G is obtained from two disjoint copies G1 and G2 of G by joining each v in G1 to ?(v) in G2. i.e., V (?G) = V (G1) ? V (G2) and E(G) = E(G1) ? E(G2) ? {(v, ?(v)): v ? V (G1), ?(v) ? V (G2)}. The graph ?G is called the prism of G with respect to ?. In this paper, we find some relations between the domination and the p-domination numbers in the context of graph and its prism graph for particular values of p. 2022 Forum-Editrice Universitaria Udinese SRL. All rights reserved. -
On some properties of partial dominating sets
A subset of the vertex set of a graph is a dominating set of the graph if that subset and all the adjacent vertices of that subset form the whole of the vertex set. In case, if a subset and all the adjacent vertices of that subset form part of the whole set, say, for 0 < p < 1, ptimes of the whole vertex set, we say it is a partial domination. In this paper, we explore some of the properties of partial dominating sets with respect to particular values of p. 2020 Author(s). -
Balancing cerebrovascular disease data with integrated ensemble learning and SVM-SMOTE
The paper addresses the challenge of imbalanced classification in the context of cerebrovascular diseases, including stroke, transient ischemic attack (TIA), and vascular dementia. The imbalanced nature of cerebrovascular disease datasets poses significant challenges to conventional machine learning algorithms, making precise diagnosis and effective management difficult. The aim of the paper is to propose a novel approach, the INTEL_SS algorithm, which combines ensemble learning techniques with Support Vector Machine-Synthetic Minority Over-sampling Technique (SVM-SMOTE) to effectively handle the imbalanced nature of cerebrovascular disease datasets. The goal is to improve the accuracy of diagnosis and management of cerebrovascular diseases through advanced machine learning techniques. The proposed methodology involves several key steps, including preprocessing, SVM-SMOTE, and ensemble learning. Preprocessing techniques are used to improve the quality of the dataset, SVM-SMOTE is employed to address class imbalance, and ensemble learning methods such as bagging, boosting, and stacking are utilized to improve overall classification performance. The experimental results demonstrate that the INTEL_SS algorithm outperforms existing methods in terms of accuracy, precision, recall, F1-score, and AUC-ROC. Performance metrics are used to assess the effectiveness of the proposed approach, and the results consistently show the superiority of INTEL_SS compared to state-of-the-art imbalanced classification algorithms. The paper concludes that the INTEL_SS algorithm has the potential to enhance the diagnosis and management of cerebrovascular diseases, offering new opportunities to apply machine learning techniques to improve healthcare outcomes. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024. -
Cerebral Stroke Classification Using Over Sampling Technique and Machine Learning Models
In recent years, cerebral stroke has ascended as a paramount concern in global public health. Proactive strategies emphasizing metabolic control over salient risk factors present a superior approach compared to relying solely on physiological indicators, which may not delineate clear preventive directives. In this research, we present the SPX-CerebroPredict modela novel machine learning framework designed to classify imbalanced cerebral stroke data for clinical diagnostics. The study delves into feature selection methodologies, employing both information gain and principal component analysis (PCA). To address the class imbalance dilemma, the Synthetic Minority Over-sampling Technique (SMOTE) was harnessed. The empirical evaluation, conducted on the cerebral stroke prediction dataset from Kagglecomprising 43,400 medical records with 783 stroke instancespitted well-established algorithms such as support vector machine, logistic regression, decision tree, random forest, XGBoost, and K-nearest neighbor against one another. The results evince that our SPX-CerebroPredict model, integrating SMOTE, PCA, and XGBoost, surpasses its contemporaries, achieving an impressive accuracy rate of 95%. This discovery underscores the models potential for clinical applicability in cerebral stroke diagnostics. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Microwave-assisted extraction of phytochemicals
Microwave-assisted extraction (MAE) has emerged as a promising technique for the extraction of phytochemicals and has received substantial scientific attention in recent years. MAE involves the utilization of microwaves to heat the sample, which facilitates the release of bioactive compounds from the plant matrix. MAE offers several advantages over traditional extraction methods, including faster extraction times, higher extraction yields, and reduced solvent consumption. To improve the efficiency of the extraction process, research has concentrated on optimizing various parameters, including the extraction temperature, extraction time, and solvent type. Additional studies have investigated the effect of MAE on the chemistry and bioactivity of the extracted phytochemicals. Several classes of phytochemicals, including phenolic compounds, flavonoids, and alkaloids, have been successfully extracted using MAE. These compounds possess various biological activities, such as antioxidant, antimicrobial, and anticancer properties. Essential oils from aromatic plants have also been extracted using MAE, which is widely employed in the food, cosmetic, and pharmaceutical industries. Despite its many advantages, the major challenge in the application of MAE is the potential degradation of the extracted compounds due to the high-temperature and high-pressure conditions during extraction. Additionally, the cost of microwave equipment and the need for specialized expertise may stunt its widespread adoption. In diverse omics disciplines, MAE shows promise, notably for the development of analytical platforms for research in genomics, proteomics, metabolomics, and related subdisciplines. Nonetheless, more investigation is required to optimize the extraction conditions and guarantee that the chemical makeup and biological activity of the isolated phytochemicals are preserved. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023, Corrected Publication 2023. All rights reserved. -
A Study on Partial Domination in Graphs
The theory of domination is one of the most studied fields in graph theory. Many new domination parameters have been defined and studied so far. One such parame- ter that was introduced in 2017 is partial domination number. For a graph G = (V, E) and for a p and#8712; (0, 1], a subset S of V (G) is said to partially dominate or p-dominate G if |N[S]| and#8805; p|V (G)|. The cardinality of a smallest p-dominating set is called the p-domination number and it is denoted by and#947;p(G). In scenarios wherein domination con-cepts are applied, partial domination concepts can also be applied with the added ad-vantage of being able to dominate the underlying graph partially, when the need arises. This advantage makes this parameter appear unique amongst most other domination parameters. We present some basic properties of partial dominating sets, some prop- erties related to particular values of p, some properties related to the eccentricity of a p-dominating set, some results in the line of classical domination and characterization of minimal and minimum p-dominating sets. Then we study partial domination in the con-text of prisms of graphs. We give some bounds for partial domination numbers of prisms of graphs G in terms of partial domination numbers of G for particular values of p. We define universal and#947;p-fixers and universal and#947;p-doublers and we characterize paths, cycles and complete bipartite graphs which are universal and#947;1 2 - fixers and universal and#947;1 2 - dou- blers. Then we concentrate on establishing a domination chain in the context of partial domination, which we call as partial domination chain . For this, we defined indepen-dent partial domination number (IPD-number), found exact values of IPD-numbers for some classes of graphs, found bounds for IPD-numbers in terms of independent domi-nation number and some relations between the independent partial dominating sets and the independent dominating sets. -
A study on partial domination in graphs
The theory of domination is one of the most studied fields in graph theory. Many new domination parameters have been defined and studied so far. One such parameter that was introduced in 2017 is partial domination number. For a graph G = (V,E) and for a p ∈ (0,1], a subset S of V(G) is said to partially dominate or p-dominate G if |N[S]| ≥ p|V(G)|. The cardinality of a smallest p-dominating set is called the p-domination number and it is denoted by γp(G). In scenarios wherein domination concepts are applied, partial domination concepts can also be applied with the added advantage of being able to dominate the underlying graph partially, when the need arises. This advantage makes this parameter appear unique amongst most other domination parameters. We present some basic properties of partial dominating sets, some properties related to particular values of p, some properties related to the eccentricity of a p-dominating set, some results in the line of classical domination and characterization of minimal and minimum p-dominating sets. Then we study partial domination in the context of prisms of graphs. We give some bounds for partial domination numbers of prisms of graphs G in terms of partial domination numbers of G for particular values of p. We define universal γp-fixers and universal γp-doublers and we characterize paths, cycles and complete bipartite graphs which are universal γ 1 2 - fixers and universal γ 1 2 - doublers. Then we concentrate on establishing a domination chain in the context of partial
domination, which we call as ‘partial domination chain’. -
Purchase intention of deconstructed end-of-lifecycle fashion products in an online and offline retail environment
Obsolete or slow-moving inventory is one of the major influencers for the bottom line of any business today. Surplus stock- be it from overbuys, returns, defects or simply merchandise hitting the end of their lifecycle- need to be accounted, accommodated and dealt with in a manner that can least affect the planned margins. For the fashion newlinebusiness, such merchandise poses greater challenges. The business is ground by seasonal preferences, fast-changing trends, short lead-times and shorter shelf-lives. With rising costs of traditional retail businesses, the associated costs of carrying such inventory are something that the newlineretailer can easily do without. At the retailers end, such merchandise is newlineoften subjected to traditional liquidation methods such as Markdowns, carry forwards, or selling at lowered prices to discount stores or factory outlets. From a manufacturer s perspective, overruns from production newlineare either sold at discounted costs to the retailer or are diverted to other sources of sales. In either case, such decisions do affect the margins of the business, and retailers often account for these necessary evils while planning their pricing strategy. Liquidation methods for such obsolete merchandise also need to meet the additional challenge of maintaining the perceived value of the products, and to not adversely newlineaffect planned margins due to lowered price points. This study seeks to explore fashion consumers acceptance of Deconstructed or up-cycled fashion for such obsolete or EOLC (End-of-lifecycle) merchandise that newlineremain unsold. It also maps the Perceived value of such merchandise and explores the other factors that may affect the Purchase Intention of the merchandise, like the Internal reference price, Perceived monetary newlinesacrifice and Perceived quality. Through an experimental study, a comparative analysis is built across consumers in an E-commerce vs newlineOffline store purchase scenario, to derive if the method of presentation of such products affects the Purchase intention. -
IOT based prediction of rainfall forecast in coastal regions using deep reinforcement model
This research proposes an IoT based technique for predicting rainfall forecast in coastal regions using a deep reinforcement learning model. The proposed technique utilizes Long Short-Term Memory (LSTM) networks to capture the temporal dependencies between the rainfall data collected from the coastal regions and the prediction model parameters. The proposed technique is evaluated on a dataset of rainfall data collected from the coastal regions of India and compared to traditional methods of rainfall forecasting. The accuracy and reliability of these models are evaluated by comparing them to prior models. Precipitation in coastal locations may be predicted with an average accuracy of 89% using the suggested model, as shown by the results. The suggested framework is computationally efficient and can be trained with little input. The results of this research give strong evidence that the proposed model is an effective tool for coastal precipitation forecasting. 2023 The Authors -
Secure Data Processing System Using Decision Tree Architecture
[No abstract available] -
Magnetic iron oxide nanoparticles immobilized on microporous molecular sieves as efficient porous catalyst for photodegradation, transesterification and esterification reactions
Magnetic iron oxide nanoparticles were immobilized on microporous molecular sieves (13X) via a plant extract mediated green synthesis method. The prepared material was then characterized using XRD, FTIR, TGA, FESEM, and TEM techniques. The synthesized iron oxide nanoparticles-molecular sieves (Fe2O3/MS) composite showed excellent photodegradation of methylene blue (MB) at 99% efficiency. Enhanced photocatalytic properties were observed in comparison with the pure iron oxide (Fe2O3) nanoparticles synthesized. Catalytic conversion of triglycerides to fatty-acid ethyl esters (FAEE) was carried out using sunflower oil, and the reaction showed very good catalytic activity in the transesterification of sunflower oil, converting 84% of the sunflower oil to FAEE. The catalyst was also used in the esterification reaction and found to have excellent applicability. The catalyst showed excellent reusability, and easy separation from the reaction mixture using an external magnet. This enables the synthesized material to act as a promising photocatalyst in degradation and organic synthesis. Very few reports are available on the synthesis of magnetic iron oxide coated on molecular sieves and used for photodegradation, transesterification, and esterification catalysis. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Novel synthesis and dft calculations of 3-PHENYL-2-(1H-TETRAZOL-5-YL)acrylamdes under catalyst-free, one-pot cascade reaction /
Patent Number: 202141023459, Applicant: Jyothis Devasia.
The present invention offers a novel method for the synthesis of 3-phenyl-2-(1H-tetrazol-5-yl)acrylamides 4(a-g) under catalyst-free conditions. All the reactions were carried out in an one-pot cascade process starting with various aromatic/heteroaryl aldehydes, 2-cyanoacetamide and sodium azide at 110 oC using dimethylformamide (DMF) as a solvent. In addition, the reaction conditions were screened for optimization conditions towards solvent, catalyst, temperature and equivalence of sodium azide. -
Single activity recognition system: A review
Human Activity Recognition (HAR) plays an important role in smart home assisted living system which is one among the growing research area in smart computing. In this modern era, Smart home assisted living is highly recommended for elderly people to monitor and assist in taking care of themselves. HAR is applied in various ambiences to recognize single activity and group activity as well. This chapter focuses on single activity recognition system with respect to variety of sensors used in smart homes, activity recognition methods and wide range of communication systems that helps to ease the living style of elderly people in healthy environment which can be linked to the advancement of IoT technology in smart building. This chapter reviews many applications with variety of sensors, real time smart home projects, and smart home assisted living systems including activity recognition methods and communication systems. Springer Nature Switzerland AG 2020. -
Effect of Coriolis force on Rayleigh-Bard convection with internal heat generation
The objective of this paper is to analyze the influence of the Coriolis force and internal heat source on Rayleigh-Bard convection in a Boussinesquian fluid of depth d. A linear theory which is oriented towards the normal mode analysis technique is used for this mono-diffusive convection in order to find the criteria for the onset of Rayleigh-Bard convection. The eigenvalue of the said problem was obtained by the use of the Galerkin method in the cases of rigid-rigid, rigid-free, and free-free velocity boundary combinations considering the isothermal and adiabatic temperature boundaries that determine the stability of the system. The effects of various parameters, Taylor number and the internal Rayleigh number are put under consideration only for stationary convection. Treating Taylor number as a critical parameter, shown that it plays a major role in stabilization of the system in case of any particular infinitesimal disturbance. The destabilization of the system has been possible with rotation by treating internal Rayleigh numbers as a critical parameter since the increase in values of the internal Rayleigh number advances the onset of convection. Oscillatory convection seems highly improbable as the scaled frequency of oscillation remains less than 0 for all combinations of Prandtl number, internal Rayleigh number, and Taylor number. 2019, Accent Social and Welfare Society. All rights reserved. -
Heat and mass transfer of triple diffusive convection in viscoelastic liquids under internal heat source modulations
The influence of sinusoidal (trigonometric cosine [TC]) and nonsinusoidal waveforms (square, sawtooth, and triangular) of internal heat source modulation on triple diffusive convection in viscoelastic liquids is investigated. An Oldroyd-B type model is taken into account for viscoelastic liquids. Nonlinear analysis is carried out using a truncated representation of the Fourier series. To analyze the heat and mass transfer over a triply diffusive liquid layer, expressions for average Nusselt and average Sherwood numbers are derived using 8-mode generalized Lorenz equations. The transient behavior of Nusselt and Sherwood numbers is analyzed on different parameters of the problem. From the results, it is found that the internal heat source enhances the heat transfer and diminishes the mass transfer while the heat sink diminishes the heat transfer and enhances the mass transfer. The results for respective waveforms are obtained for each parameter and it is found that the maximum heat and mass transfer occurs due to TC waveform. The limiting cases of viscoelastic liquids (Newtonian, Oldroyd-B, Maxwell, and RivlinEricksen) have been tabulated and corresponding results for each of the waveforms onheat and mass transfer have been shown. 2021 Wiley Periodicals LLC -
Effect of internal heat source modulations on the onset of triple diffusive convection in viscoelastic liquids
The paper aims to study the dynamic behavior of a triple diffusive system subjected to sinusoidal (trigonometric cosine) and non-sinusoidal wave forms (square, sawtooth and triangular) of internal heat source modulation. The configuration of the system is such that a layer of viscoelastic liquid is heated and salted with two solutes from below. An Oldroyd-B type model is made use for viscoelastic liquids. In order to regulate the convection onset, internal heat source modulation is applied. This investigation is modelled using a linear stability analysis where a stationary convection is preferred. Venezian approach facilitates a solution by finding the eigen values of the problem. The influence of pertinent parameters which are varied for a wide range of values have been reported. It is captured via graphs that for small values of frequency of modulation, square wave form is more stable while sawtooth wave form is more stable for an increment in the values of frequency of modulation. Further, liquids such as Newtonian, Maxwell and Rivlin-Ericksen are analysed as the limiting cases of the problem. It seems worthwhile to discuss the results of the present study as it is the first work on linear theory of different wave forms of internal heat source modulation and thus paves a way for new theoretical and experimental endeavors. 2021, National Institute of Science Communication and Information Resources. All rights reserved. -
Study of Rayleigh-Benard Dynamical System Involving Newtonian and Nanofluids in Rectangular and Cylindrical Enclosures
Analyzing and#64258;uid and#64258;ow behavior in the presence of temperature gradients subjected to internal and external forces in diand#64256;erent geometries is essential for optimization newlineprocesses for various engineering applications, guiding the design of more efcient thermal systems. This thesis focuses on investigating the Rayleigh-Bard convection problems occupying rectangular and cylindrical enclosures. The linear and newlineweakly nonlinear analyses are carried out that reveal the results on regular convection, heat transport and chaotic motion for each of the problems. Steady and newlineunsteady states of the Rayleigh-Bard system are studied using the Lorenz model. The dynamical system is investigated to look for possible chaotic motion. Fluid systems can exhibit chaotic behavior, and understanding the chaotic nature of these and#64258;ows is essential for accurate predictions of their evolution over time. In view of this, the regular, chaotic, and periodic natures of the dynamical system is thoroughly analyzed. Further, the inand#64258;uence of various parameters on the indicators of chaos is explored. Additionally, the thermal performance of the system is looked into by introducing nanoparticles/nanotubes into the base and#64258;uid. newlineWith the aformentioned motivation, we now present the abstract of each of the problems considered in this thesis one-by-one. 1. Impact of boundary conditions on Rayleigh-Bard convection: stability, heat transfer and chaos In the frst problem of the thesis, discussed in Chapter 3, a comparison is made newlinebetween the results of Rayleigh-Bard convection problem for diand#64256;erent boundary combinations, namely, rigid-rigid-isothermal, rigid-free-isothermal and free-free isothermal boundaries for a Newtonian and#64258;uid. The linear and weakly-nonlinear analyses reveal that the onset of regular and chaotic motions in the case of rigid-freeisothermal boundaries happens later than that of free-free isothermal boundaries but earlier than rigid-rigid-isothermal boundaries.+ -
Elastic circuit de-constructor: a pattern to enhance resiliency in microservices
Cloud-based workloads have proliferated with the deep penetration of the internet. Microservices based handling of high volume transactions and data have become extremely popular owing to their scalability and elasticity. The major challenge that cloud-based microservice patterns face is predicting dynamic load and failure patterns, which affect resiliency and uptime. Existing Circuit breaker patterns are biased toward denying incoming requests to maintain acceptable latency values, at the cost of availability. This paper proposes the Elastic Circuit De-Constructor (ECD) pattern to address these gaps. The proposed ECD pattern addresses this challenge by dynamically adapting to changing workloads and adjusting circuit-breaking thresholds based on real-time performance metrics. The proposed ECD pattern introduces a novel De-constructed state, that allows the ECD to identify alternate paths pre-defined by the application, ensuring user requests continue to be routed to the microservice. By leveraging Availability, Latency and Error rate as performance metrics, the ECD pattern is able to balance the fault tolerance and resiliency imperatives in the cloud-based microservices environment. The performance of the proposed ECD pattern has been verified against both no Circuit Breaker and a default Circuit Breaker setting. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Circuit Breaker: A Resilience Mechanism for Cloud Native Architecture
Over the past decade, the utilization of cloud native applications has gained significant prominence, leading many organizations to swiftly transition towards developing software applications that leverage the powerful, accessible, and efficient cloud infrastructure. As these applications are deployed in distributed environments, there arises a need for reliable mechanisms to ensure their availability and dependability. Among these mechanisms, the circuit breaker pattern has emerged as a crucial element in constructing resilient and trustworthy cloud native applications in recent times. This research article presents a comprehensive review and analysis of circuit breaker patterns and their role within cloud-native applications. The study delves into various aspects of circuit breakers, encompassing their design, implementation, and recommended practices for their utilization in cloud native applications. Additionally, the article examines and compares different circuit breaker libraries available for employment in modern software development. The paper also presents a concept for improving the circuit breaker pattern, which will be pursued in our upcoming research. 2023 IEEE.