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Significance of exponential space- and thermal-dependent heat source effects on nanofluid flow due to radially elongated disk with Coriolis and Lorentz forces /
Journal of Thermal Analysis And Calorimetry, Vol.141, Issue 3, pp.37-44, ISSN No: 1588-2926. -
Time-dependent flow due to noncoaxial rotation of an infinite vertical surface subjected to an exponential space-dependent heat source: An exact analysis /
Heat Transfer Asian Research, Vol.48, Issue 7, pp.3162-3185 -
IEEHR: Improved Energy Efficient Honeycomb Based Routing in MANET for Improving Network Performance and Longevity
In present scenario, efficient energy conservation has been the greatest focus in Mobile Adhoc Networks (MANETs). Typically, the energy consumption rate of dense networks is to be reduced by proper topological management. Honeycomb based model is an efficient parallel computing technique, which can manage the topological structures in a promising manner. Moreover, discovering optimal routes in MANET is the most significant task, to be considered with energy efficiency. With that motive, this paper presents a model called Improved Energy Efficient Honeycomb based Routing (IEEHR) in MANET. The model combines the Honeycomb based area coverage with Location-Aided Routing (LAR), thereby reducing the broadcasting range during the process of path finding. In addition to optimal routing, energy has to be effectively utilized in MANET, since the mobile nodes have energy constraints. When the energy is effectively consumed in a network, the network performance and the network longevity will be increased in respective manner. Here, more amount of energy is preserved during the sleeping state of the mobile nodes, which are further consumed during the process of optimal routing. The designed model has been implemented and analyzed with NS-2 Network Simulator based on the performance factors such as Energy Efficiency, Transmission Delay, Packet Delivery Ratio and Network Lifetime. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Classification of countries based on development indices by using K-means and grey relational analysis
Clustering countries based on their development profile is important, as it helps in the efficient allocation and use of resources for institutions like the World Bank, IMF and many others. However, measuring the status of development in each country is challenging, as development encompasses several facets such as economic, social, environmental and institutional aspects. These dimensions should be captured and aggregated appropriately before attempting to classify countries based on development. In this context, this paper attempts to measure various dimensions of development through four indices namely, Economic Index (EI), Social Index (SI), Sustainability Index (SUI) and Institutional Index (II) for the period between 1996 through 2015 for 102 countries. And then we categorize the countries based on these development indices using the grey relational analysis and K-means clustering method. Our study classifies countries into four clusters with twelve countries in the first cluster, fifty in second, twenty-seven and thirteen countries in third and fourth clusters respectively. Having taken each of the dimensions of development independently, our results show that no cluster has performed poorly in all four aspects. 2021, The Author(s), under exclusive licence to Springer Nature B.V. -
Analysis of club convergence for economies: identification and testing using development indices
This paper attempts to identify club convergence using the procedure suggested by Phillips and Sul (Phillips and Sul, Econometrica 75:17711855, 2007, Phillips and Sul, J Appl Economet 24:11531185, 2009) based on GDP per capita for 102 countries across the globe for the time period 1996 through 2015. The results indicate the presence of five clubs with four countries belonging to the non- convergent group. After identifying the clubs, the study analyzed the transitional behaviors among the clubs. Finally, to understand the determinant of the club membership, we used the ordered logit model by considering the initial level of GDP, gross capital formation, growth rate of population, and four indices, namely social, governance, sustainability, and globalization as the explanatory variables. The results suggest that the initial level of GDP per capita, gross capital formation, social, governance, sustainability, and globalization are the major factors for determining the club. 2021, The Japan Section of the Regional Science Association International. -
Synthesis and characterization of alkali-activated binders with slag and waste printed circuit board
The global production of printed circuit board (PCB) is expected to rise substantially in the next decade due to the advancement in technology. The production of PCB results in generation of hazardous waste of various kinds, and one such waste is the very fine particles of the board material that is generated due to drilling and other preparatory operations. The disposal of such waste in the environment can result in serious consequences which needs attention. Therefore, recycling of waste printed circuit board (WPCB) can mitigate its harmful effects on the environment and also reduce the remediation costs. In this study, the WPCB is used as a substitute to ground granulated blast furnace slag (GGBFS) in development of alkali-activated binder. Alkali-activated binder was synthesized with GGBFS, WPCB, sodium hydroxide sol. (NaOH), and sodium silicate sol. (Na2SiO3). GGBFS was replaced with WPCB at replacement rates of 0%, 10%, 20%, and 30% by volume. Additionally, the effect of varying concentration of NaOH and Na2SiO3 on the physical and mechanical performance of the binder was studied. The developed binders were evaluated for workability, strength, water absorption, and efflorescence properties. Further, to ascertain its safety on the environment, the toxicity characteristic leaching procedure (TCLP) test was also performed. The results indicate that WPCB characteristics are compatible with GGBFS in terms of its particle size distribution. Moreover, the replacement of GGBFS with up to 20% WPCB provides desirable properties for the alkali-activated binder. However, higher replacements are not recommended, since it had detrimental effect on the mechanical performance of the binder. The study revealed that desirable performance can be achieved for binders with 8 M NaOH and with Na2SiO3 to NaOH ratio of 2, and up to 20% GGBFS replaced with WPCB. The results of TCLP test disclose that the contaminant in the leachate from alkali-activated binders with WPCB are within regulatory limits, and do not pose any threat to the environment. Finally, the outcome of this study provides an innovative approach towards formulation of eco-friendly binder for various construction applications such as foundations, buildings, bridges, pavements, etc. 2024 The Author(s) -
Segmentation and identification of MRI Brain segment in digital image
Brain image segmentation is important in the area of clinical diagnosis. MRI Brain image segmentation is time consuming and there is always a chance of occurrence of error when the segmentation is done manually. It is always possible to detect the infected tissues easily in the current medical field. However, the accuracy and the characteristics of abnormalities of the tissues are not precise. In the past, many researchers have identified the drawbacks of manual segmentation and hence proposed the semiautomatic and fully automatic segmentation methods in the field of medical imaging. The amount of precision about the detection of defective tissues leads to acceptance of a particular image segmentation method. In this article three segmentation methods are hybridized to get the optimum extraction of the region of interest (ROI) in brain MRI image. Further, the region properties of segment is extracted and stored as knowledgebase. The proposed algorithm integrates multiple segmentation methods and identifies the Brain Outer layer in MRI image. This identification AIDS medical experts for optimum diagnosis of defective tissues in the brain. IAEME Publication. -
Numerical and sensitivity analysis of MHD bioconvective slip flow of nanomaterial with binary chemical reaction and Newtonian heating
The impact of Stefan blowing on the MHD bioconvective slip flow of a nanofluid towards a sheet is explored using numerical and statistical tools. The governing partial differential equations are nondimensionalized and converted to similarity equations using apposite transformations. These transformed equations are solved using the RungeKuttaFehlberg method with the shooting technique. Graphical visualizations are used to scrutinize the effect of the controlling parameters on the flow profiles, skin friction coefficient, local Nusselt, and Sherwood number. Moreover, the sensitivities of the reduced Sherwood and Nusselt number to the input variables of interest are explored by adopting the response surface methodology. The outcomes of the limiting cases are emphatically in corroboration with the outcomes from preceding research. It is found that the heat transfer rate has a positive sensitivity towardsthe haphazard motion of the nanoparticles and a negative sensitivity towardsthe thermomigration. The thermal field is enhanced by the Stefan blowing aspect. Moreover, the fluid velocity can be controlled by the applied magnetic field. 2021 Wiley Periodicals LLC -
Eccentricity splitting graph of a graph
Let G = (V, E) be any connected graph with (Figure presented.) for all uj, uk ? Si if e(uj) = e(uk)(1 ? i ? t) with each | Si |? 2 and (Figure presented.). The eccentricity splitting graph of a graph denoted by ES(G) is obtained by taking a copy of G and adding vertices w 1, w 2, , wt such that wi is adjacent only to the vertices of Si for 1 ? i ? t. We initiate the study on eccentricity splitting graph ES(G) and examine its structural properties. We also analyze diameter, girth and chromatic number of eccentricity splitting graphs of certain classes of graphs. 2021 Taru Publications. -
ON BLOCK-RELATED DERIVED GRAPHS
This paper introduces and analyses the block-degree of a vertex and the cut-degree of a block. The block-degree of a vertex v is the number of blocks containing v. The cut-degree of a block b is the number of cut vertices of G contained in b. The block-degree sequence of cut vertices of the graph and the cut-degree sequence of the graph are defined. A few characterizations of the block-degree and cut-degree sequence of the graph are established. Given a graph, its block graph (B(G)) is a graph where each vertex represents a block, and two vertices are connected if their blocks intersect. The number of cut vertices of B(G) is determined. Further, an investigation is carried out on the traversability of B(G). A block cutpoint graph (BC(G)) of a graph represents a graph where each vertex corresponds to either a block or a cut vertex, and two vertices are connected if one represents a block and the other represents a cut vertex contained within that block. The properties of BC(G) and its iterations are studied. The graph G for which BC(G) is a perfect m-ary tree is characterized. 2024, Canadian University of Dubai. All rights reserved. -
A Compartmental Mathematical Model of Novel Coronavirus-19 Transmission Dynamics
The COVID-19 pandemic has spread quickly throughout the world, posing a serious threat to human-to-human transmission. The novel coronavirus pandemic is described quantitatively in this paper using a mathematical model of COVID-19 driven by a system of ordinary differential equations. The suggested model is used to provide predictions regarding the behavior of a COVID-19 outbreak over a shorter time frame. It is demonstrated that the system of model equations has a unique and existing solution. Furthermore, the answer is positive and bounded. Thus, it is argued that the model created and discussed in this work is both mathematically and biologically sound. A threshold parameter that controls the disease transmission is used in a qualitative analysis of the model to confirm the existence and stability of disease-free and endemic equilibrium points. Additionally, the key parameters undergo sensitivity analysis to ascertain their relative significance and potential influence on the COVID-19 virus dynamics. 2024 NSP Natural Sciences Publishing Cor. -
Enhancing mobility management in 5G networks using deep residual LSTM model
Mobility management is an essential component of 5G networks to provide mobile users with seamless connectivity and efficient cell transition. However, increasing user mobility, device density, and the diversity of service requirements all pose significant challenges to achieving optimal mobility management. This article describes a novel method for improving mobility management in 5G networks that employs a deep residual Long Short-Term Memory model. Deep learning and LSTM, a type of recurrent neural network, are used in the proposed model to identify temporal dependencies and patterns in user mobility data. The model learns to predict future user locations and mobility patterns by training on historical mobility data, allowing for proactive resource allocation and handover decisions. We incorporate residual connections into the LSTM architecture, inspired by the residual learning framework, to address the inability of traditional LSTM models to capture complex temporal dynamics. This allows the model to effectively incorporate long-term dependencies and improves prediction accuracy. Furthermore, we incorporate the mLSTM model into the mobility management framework of 5G networks. The model continuously obtains real-time user location updates and predicts future user positions, allowing for proactive handover decisions. The network can optimize resource allocation, reduce handover latency, and improve user experience by leveraging anticipated mobility patterns. We test the proposed method by simulating it extensively with real-world mobility traces. The results show that the mLSTM model accurately predicts user mobility and outperforms conventional methods in transition performance. The model is not affected by changing network conditions, user mobility patterns, or service specifications. 2024 Elsevier B.V. -
Blind separation of speech from aortic regurgitation signals using Dhoulaths method
Conducting auscultation of traumatically distressed patients has always been demanding for medical professionals. The challenge calls for an innovative solution enabling doctors to conduct precise diagnoses despite other sound interference. This suggested study presents an entirely non-invasive and convenient method designed to aid doctors in routine diagnostic procedures. This study is centred on the segregation of aortic regurgitation heart sounds from speech. The mixture utilised for the study is a combination of speech and aortic regurgitation signals. The method applied for the study is a revised procedure of Blind Source component separation utilising a solo sensor method. With this technique, doctors are not compelled to prevent patients from articulating their pain or discomfort while diagnosing heart sounds. Doctors can offer a consoling word to patients while the auscultation is in progress without worrying about how the speech sounds affect the diagnosis. For babies, timely detection of heart-related issues can be life-saving. With Dhoulaths method, the distressing sounds of a babys cries can be effectively separated, thereby offering doctors clear audio of heartbeats. The study was conducted to ascertain if heartbeats can be segregated from the signals of speech or cries. This segregation procedure has succeeded in arriving at an enhanced level of clarity. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Industrial Applications of Hybrid Nanocatalysts and Their Green Synthesis
Abstract: The era of industrial revolution has been hugely dependent on a myriad of catalysts. The present era has contributed another dimension to this by the advent of nanocatalysts. The last decades saw even more fine tuning with the use of hybrid nanocatalysts by the integration of a plethora of functionalities into a single nanoparticle. The extremely high surface area, low toxicity, easy recovery and reusability, high product output and possibilities of green synthesis makes hybrid nanocatalysts significant in various fields like bioremediation, fuel cell production, cleaner energy production, dye degradation etc. Metal based hybrid nanocatalysts are highly appealing due to their extremely high surface over volume ratio, entailing unique electronic properties and access to more reaction sites. The recent years have seen more thrust being given to greener modes of synthesis of nanocatalysts, rather than the classical modes (which uses hazardous chemicals), aligning with sustainability goals.The current review is an attempt to explore the myriad uses of magnetic, metal and metal oxide hybrid nanocatalysts and their green synthesis methods. Optimizing the use of hybrid nanocatalysts in various domains would definitely help us achieve the SDGs of the United Nations for a more sustainable life on this planet. Graphical Abstract: [Figure not available: see fulltext.] Highlights: Types of hybrid nanocatalysts have been described. Industrial applications of hybrid nanocatalysis has been summarized. Ways of greener synthesis of hybrid nanocatalysts for environmental sustainability depicted. Advantages and limitations of hybrid nanocatalysts have been evaluated. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
The mediating influence of leadership behaviour on the relationship between organizational health and work engagement
Efficient leadership and a healthy teaching environment are the two factors that determine how school teachers conduct themselves professionally. Work engagement not only reflects the teachers' performance but also implies the performance of the pupils and the school and it depends on how congenial their working conditions are. The present study intended to assess the extent to which the leadership behaviour of principals mediated the effect of organizational health on the work engagement of 516 secondary school teachers working in Bengaluru, India. The organizational health inventory was employed to quantify the organizational health of schools at institutional, managerial and technical levels, the Utrecht tool was used to measure teachers' work engagement through their vigor, dedication and absorption, and the leadership behaviour of principals was measured in terms of consideration and initiating behaviour. The findings implied a positive relationship between organizational health and teachers' work engagement. Further, while leadership behaviour indeed mediated the impact of organizational health on work engagement, the mediating effect was only partial. The results imply that the teachers' work engagement cannot be entirely attributed to the school management and working conditions, which implies scope for further research on the factors affecting work engagement among the teachers. 2020 by authors. -
Enhanced AIS Based Intrusion Detection System Using Natural Killer Cells
Intrusion detection system is used to monitor the system and network activities to identify anomalies and attacks so that integrity, availability, and confidentiality can be preserved. Here an intrusion detection system based on Artificial Immune System is proposed based on Natural Killer (NK) cells with immunological memory. NK cells are created and each NK cells detection radius is determined using the negative selection algorithm and is trained to detect various attacks. Effective cells with high fairness values are proliferated and distributed to the network using clonal selection algorithm. In this paper, two types of NK cell are used-a Heavyweight NK cell (HWNK) and a number of Lightweight NK cells (LWNK). The incoming data is vectorized and Major Histocompatibility Complex Class I (MHC1) is created. Then based on this MHC1, any of the receptors i.e. Activating Receptor or Inhibiting Receptor is activated. If it is the signature of an attack, Activating Receptor is activated. Activating receptor activation results in either cytokine release or apoptosis. Here cytokine release means an alarm is generated informing the administrator and apoptosis stands for dropping of the packet. If Inhibiting Receptor is activated, it's a normal packet there is no action taken. The technique proposed yields high accuracy, better detection rate and quick response time. 2020 River Publishers. All Rights Reserved. -
A generic cyber immune framework for anomaly detection using artificial immune systems
Intrusion detection systems play a significant role in computer security. Artificial immune systems are the prime contender in developing an anomaly-based intrusion detection system due to their simplicity. The fundamental goal of this paper is to create a generic framework for an artificial immune system which is fast and accurate in detecting anomalies using artificial immune system concepts. Natural killer cells in the immune system and their quick response to foreign pathogens inspired the adaptation of those cells into an artificial immune system based framework. A natural killer cell-based framework is proposed to improve the accuracy and speed of anomaly detection. The structure of the proposed framework includes major histocompatibility complex class 1 representation, affinity calculation, cell generation, and cell proliferation. This framework addresses the overlapping and hole problem while creating natural killer cells to increase the system's performance. The negative selection algorithm and the positive selection algorithm generate the cells that enhance the anomaly detection technique and give high precision. The parameter response time introduced in this paper is crucial for an intrusion system to be used in real-time. 2022 Elsevier B.V. -
Representation of Cancer in the Digital Space
[No abstract available] -
Platt number of total graphs
The degree of an edge uv is defined as the number of edges incident on vertices u and v other than itself. The Platt number of a graph is the sum of degrees of all its edges. In this paper, the concept of degree of an edge is analysed in social networks. The Platt number is investigated in certain classes of graphs and their total graphs. Also related bounds are proposed on connected graphs. An algorithm developed to determine the Platt number of any connected graph is presented. 2018 Academic Publications.