Satheesh Kumar received his B. Sc. degree in Mathematics from University of Kerala and M. Sc. degree in Mathematics from Annamalai University. He did his doctoral research at NIIST (formerly Regional Research Laboratory(CSIR)), Trivandrum on chaotic rheological parameters of periodically forced suspensions of weak Brownian slender bodies in simple shear flow and received his Ph. D. degree from Cochin Univ. of Science
In this paper, we compared the efficacy of observation based modeling approach using a genetic al... more In this paper, we compared the efficacy of observation based modeling approach using a genetic algorithm with the regular statistical analysis as an alternative methodology in plant research. Preliminary experimental data on in vitro rooting was taken for this study with an aim to understand the effect of charcoal and naphthalene acetic acid (NAA) on successful rooting and also to optimize the two variables for maximum result. Observation-based modelling, as well as traditional approach, could identify NAA as a critical factor in rooting of the plantlets under the experimental conditions employed. Symbolic regression analysis using the software deployed here optimised the treatments studied and was successful in identifying the complex non-linear interaction among the variables, with minimalistic preliminary data. The presence of charcoal in the culture medium has a significant impact on root generation by reducing basal callus mass formation. Such an approach is advantageous for es...
Wind speed forecasting has received a lot of attention in the recent past from researchers due to... more Wind speed forecasting has received a lot of attention in the recent past from researchers due to its enormous benefits in the generation of wind power and distribution. The biggest challenge still remains to be accurate prediction of wind speeds for efficient operation of a wind farm. Wind speed forecasts can be greatly improved by understanding its underlying dynamics. In this paper, we propose a method of time series partitioning where the original 10 minutes wind speed data is converted into a twodimensional array of order (N x 144) where N denotes the number of days with 144 the daily 10-min observations. Upon successful time series partitioning, a point forecast is computed for each of the 144 datasets extracted from the 10 minutes wind speed observations using an Auto-Regressive (AR) process which is then combined together to give the (N+1) day forecast. The results of the computations show significant improvement in the prediction accuracy when AR model is coupled with time ...
Maximisation of influence propagation is a key ingredient to any viral marketing or socio-politic... more Maximisation of influence propagation is a key ingredient to any viral marketing or socio-political campaigns. However, it is an NP-hard problem, and various approximate algorithms have been suggested to address the issue, though not largely successful. In this paper, we propose a bio-inspired approach to select the initial set of nodes which is significant in rapid convergence towards a sub-optimal solution in minimal runtime. The performance of the algorithm is evaluated using the re-tweet network of the hashtag #KissofLove on Twitter associated with the non-violent protest against the moral policing spread to many parts of India. Comparison with existing centrality based node ranking process the proposed method significant improvement on influence propagation. The proposed algorithm is one of the hardly few bio-inspired algorithms in network theory. We also report the results of the exploratory analysis of the network kiss of love campaign.
In this paper we use tools of social network analysis to study the road network of Kochi in the b... more In this paper we use tools of social network analysis to study the road network of Kochi in the backdrop of the Kochi Metro Rail project for designing optimal public transportation networks.This study shows how the road transport system can be restructured to act as an efficient feeder mechanism for the metro rail transport system. We visualized clusters and computed various network characteristics such as centrality, density etc. and also have verified the existence of small world behavior. This will help to eliminate the future bottlenecks in the existing road network by supporting traffic density reduction and enhancing connectivity to Kochi Metro rail stations.
We demonstrate for the first time that the rheological parameters like the apparent viscosities a... more We demonstrate for the first time that the rheological parameters like the apparent viscosities and the first and second normal stress differences of suspensions of orientable particles can show chaotic behavior when the orientation vector evolves chaotically. We also demonstrate that the range of the values of the rheological parameters is about 10 000 times greater when the parameters evolve chaotically. This suggests that a wide range of properties may be obtained by small variations in controllable parameters. When coupled with suitable control of chaos algorithms, a wide range of suspension behavior is thus possible since a chaotic solution can be considered as an unlimited reservoir of periodic solutions of arbitrary period.
In an earlier paper, we had outlined a procedure for calculating the rheological parameters for p... more In an earlier paper, we had outlined a procedure for calculating the rheological parameters for periodically forced suspensions of slender rods in simple shear flow in the chaotic regime. In this work, we examine the consequences of the above procedure on the dynamics and rheology of similar suspensions starting off with uniform initial orientation distributions as well as aligned initial distributions. We provide numerical evidence for existence of riddled and intermingled basins of attractions in the system. We discuss the limitations of the diffusion equation approach in the chaotic regime. We also demonstrate that small changes in the preparation of aligned suspensions can lead to dramatically different rheological behaviour in some parametric regimes. In other parametric regimes differences in the dynamical behaviour do not translate into differences in the rheological behaviour of aligned suspensions.
We review results obtained over a period of about a decade on a class of technologically and fund... more We review results obtained over a period of about a decade on a class of technologically and fundamentally important problems in suspension rheology viz., the dynamics and rheology of dipolar suspensions of orientable particles in simple shear flow. The areas explored in ...
In this paper, we compared the efficacy of observation based modeling approach using a genetic al... more In this paper, we compared the efficacy of observation based modeling approach using a genetic algorithm with the regular statistical analysis as an alternative methodology in plant research. Preliminary experimental data on in vitro rooting was taken for this study with an aim to understand the effect of charcoal and naphthalene acetic acid (NAA) on successful rooting and also to optimize the two variables for maximum result. Observation-based modelling, as well as traditional approach, could identify NAA as a critical factor in rooting of the plantlets under the experimental conditions employed. Symbolic regression analysis using the software deployed here optimised the treatments studied and was successful in identifying the complex non-linear interaction among the variables, with minimalistic preliminary data. The presence of charcoal in the culture medium has a significant impact on root generation by reducing basal callus mass formation. Such an approach is advantageous for establishing in vitro culture protocols as these models will have significant potential for saving time and expenditure in plant tissue culture laboratories, and it further reduces the need for specialised background. Trials to find out the best combination of factors that contribute to the desired response takes up the chunk of time and resources in any plant tissue culture laboratory. The output of such experiments is analysed statistically to come to a conclusion. However, without prior statistical modifications, the results could be misleading. Recent reports from several labs point out the use of artificial neural networks to circumvent this. We have chosen to use a computational process that can predict the best combination of factors for the desired response after randomly testing the higher and lower limit of the factors with experiments. The magnitude of the desired response can be presumed at any concentration within this range using the models generated by symbolic regression. The procedure provides both optimum model function as well as the optimum variable values in the model. The variable sensitivity and percentage response add depth to the information thus obtained. The study indicated that these models would have significant potential for
Wind speed oscillations are known to exhibit varying characteristics at different time scales. Ou... more Wind speed oscillations are known to exhibit varying characteristics at different time scales. Our recent analysis has shown that a collection of autoregressive models fitted separately on the frequency components of wind speed data can significantly increase the prediction accuracy. In this paper, we report the results of the investigation of dynamical behaviour across a broad frequency spectrum of wind speed measurements. The results show the existence of diverse characteristics such as stochastic, deterministic and chaotic behaviour apart from the variation of the dimensionality of underlying dynamics as well as the degree of fluctuations. It is also demonstrated that a cluster of deterministic models built upon separate frequency components of a wind speed time series can enhance the prediction accuracy by as much as 80%, on the average, consistently for predictions up to 12 h. The comparison shows the definite advantage of deterministic prediction models over autoregressive models. The f-index introduced in this paper to measure the fluctuations of wind speed over a period indicates that the observed seasonal variations of prediction errors can be correlated with changes in the f-index of the component series contributed mostly by the lower scales of decomposition.
Abstract
Maximisation of influence propagation is a key ingredient to any viral marketing or soc... more Abstract
Maximisation of influence propagation is a key ingredient to any viral marketing or socio-political campaigns. However, it is an NP-hard problem, and various approximate algorithms have been suggested to address the issue, though not largely successful. In this paper, we propose a bio-inspired approach to select the initial set of nodes which is significant in rapid convergence towards a sub-optimal solution in minimal runtime. The performance of the algorithm is evaluated using the re-tweet network of the hashtag #KissofLove on Twitter associated with the non-violent protest against the moral policing spread to many parts of India. Comparison with existing centrality based node ranking process the proposed method significant improvement on influence propagation. The proposed algorithm is one of the hardly few bio-inspired algorithms in network theory. We also report the results of the exploratory analysis of the network kiss of love campaign.
Interlocking directorates play a crucial role in the corporate governance system. In this paper w... more Interlocking directorates play a crucial role in the corporate governance system. In this paper we analyse the structural characteristics of the network of the interlocking directorate of National Stock Exchange (NSE) listed Indian companies using the tools of social network analysis to examine the effects of the underlying network on the performance of companies and directors. A component analysis of the network shows that 78.5% of the companies fall under one giant component with the largest island containing 6 companies. The giant component was further analysed for clusters and centrality measures. The results show that the highly boarded directors who constitute just 2.25% of the director population are associated with 42% of the total listed companies which account for 65.5% of the total market capitalisation. The top central actors in both director as well as company networks have been identified. The calculated values of mean path length and global clustering coefficient provide evidence for the existence of small world structure in the Indian corporate field.
In this paper, we consider the technologically important problem of periodically forced spheroids... more In this paper, we consider the technologically important problem of periodically forced spheroids in simple shear flow and demonstrate the existence of chaotic parametric regimes. The approach used by Strand (1989) (for the Strong Brownian limit) is inappropriate in the chaotic regimes corresponding to the weak Brownian limit. Our results also indicate a strong dependence of the solutions obtained on the aspect ratio of the spheroids. This strong dependence on the aspect ratio may be utilized to separate particles from a suspension of particles having different shapes but similar sizes.
In this paper, we compared the efficacy of observation based modeling approach using a genetic al... more In this paper, we compared the efficacy of observation based modeling approach using a genetic algorithm with the regular statistical analysis as an alternative methodology in plant research. Preliminary experimental data on in vitro rooting was taken for this study with an aim to understand the effect of charcoal and naphthalene acetic acid (NAA) on successful rooting and also to optimize the two variables for maximum result. Observation-based modelling, as well as traditional approach, could identify NAA as a critical factor in rooting of the plantlets under the experimental conditions employed. Symbolic regression analysis using the software deployed here optimised the treatments studied and was successful in identifying the complex non-linear interaction among the variables, with minimalistic preliminary data. The presence of charcoal in the culture medium has a significant impact on root generation by reducing basal callus mass formation. Such an approach is advantageous for es...
Wind speed forecasting has received a lot of attention in the recent past from researchers due to... more Wind speed forecasting has received a lot of attention in the recent past from researchers due to its enormous benefits in the generation of wind power and distribution. The biggest challenge still remains to be accurate prediction of wind speeds for efficient operation of a wind farm. Wind speed forecasts can be greatly improved by understanding its underlying dynamics. In this paper, we propose a method of time series partitioning where the original 10 minutes wind speed data is converted into a twodimensional array of order (N x 144) where N denotes the number of days with 144 the daily 10-min observations. Upon successful time series partitioning, a point forecast is computed for each of the 144 datasets extracted from the 10 minutes wind speed observations using an Auto-Regressive (AR) process which is then combined together to give the (N+1) day forecast. The results of the computations show significant improvement in the prediction accuracy when AR model is coupled with time ...
Maximisation of influence propagation is a key ingredient to any viral marketing or socio-politic... more Maximisation of influence propagation is a key ingredient to any viral marketing or socio-political campaigns. However, it is an NP-hard problem, and various approximate algorithms have been suggested to address the issue, though not largely successful. In this paper, we propose a bio-inspired approach to select the initial set of nodes which is significant in rapid convergence towards a sub-optimal solution in minimal runtime. The performance of the algorithm is evaluated using the re-tweet network of the hashtag #KissofLove on Twitter associated with the non-violent protest against the moral policing spread to many parts of India. Comparison with existing centrality based node ranking process the proposed method significant improvement on influence propagation. The proposed algorithm is one of the hardly few bio-inspired algorithms in network theory. We also report the results of the exploratory analysis of the network kiss of love campaign.
In this paper we use tools of social network analysis to study the road network of Kochi in the b... more In this paper we use tools of social network analysis to study the road network of Kochi in the backdrop of the Kochi Metro Rail project for designing optimal public transportation networks.This study shows how the road transport system can be restructured to act as an efficient feeder mechanism for the metro rail transport system. We visualized clusters and computed various network characteristics such as centrality, density etc. and also have verified the existence of small world behavior. This will help to eliminate the future bottlenecks in the existing road network by supporting traffic density reduction and enhancing connectivity to Kochi Metro rail stations.
We demonstrate for the first time that the rheological parameters like the apparent viscosities a... more We demonstrate for the first time that the rheological parameters like the apparent viscosities and the first and second normal stress differences of suspensions of orientable particles can show chaotic behavior when the orientation vector evolves chaotically. We also demonstrate that the range of the values of the rheological parameters is about 10 000 times greater when the parameters evolve chaotically. This suggests that a wide range of properties may be obtained by small variations in controllable parameters. When coupled with suitable control of chaos algorithms, a wide range of suspension behavior is thus possible since a chaotic solution can be considered as an unlimited reservoir of periodic solutions of arbitrary period.
In an earlier paper, we had outlined a procedure for calculating the rheological parameters for p... more In an earlier paper, we had outlined a procedure for calculating the rheological parameters for periodically forced suspensions of slender rods in simple shear flow in the chaotic regime. In this work, we examine the consequences of the above procedure on the dynamics and rheology of similar suspensions starting off with uniform initial orientation distributions as well as aligned initial distributions. We provide numerical evidence for existence of riddled and intermingled basins of attractions in the system. We discuss the limitations of the diffusion equation approach in the chaotic regime. We also demonstrate that small changes in the preparation of aligned suspensions can lead to dramatically different rheological behaviour in some parametric regimes. In other parametric regimes differences in the dynamical behaviour do not translate into differences in the rheological behaviour of aligned suspensions.
We review results obtained over a period of about a decade on a class of technologically and fund... more We review results obtained over a period of about a decade on a class of technologically and fundamentally important problems in suspension rheology viz., the dynamics and rheology of dipolar suspensions of orientable particles in simple shear flow. The areas explored in ...
In this paper, we compared the efficacy of observation based modeling approach using a genetic al... more In this paper, we compared the efficacy of observation based modeling approach using a genetic algorithm with the regular statistical analysis as an alternative methodology in plant research. Preliminary experimental data on in vitro rooting was taken for this study with an aim to understand the effect of charcoal and naphthalene acetic acid (NAA) on successful rooting and also to optimize the two variables for maximum result. Observation-based modelling, as well as traditional approach, could identify NAA as a critical factor in rooting of the plantlets under the experimental conditions employed. Symbolic regression analysis using the software deployed here optimised the treatments studied and was successful in identifying the complex non-linear interaction among the variables, with minimalistic preliminary data. The presence of charcoal in the culture medium has a significant impact on root generation by reducing basal callus mass formation. Such an approach is advantageous for establishing in vitro culture protocols as these models will have significant potential for saving time and expenditure in plant tissue culture laboratories, and it further reduces the need for specialised background. Trials to find out the best combination of factors that contribute to the desired response takes up the chunk of time and resources in any plant tissue culture laboratory. The output of such experiments is analysed statistically to come to a conclusion. However, without prior statistical modifications, the results could be misleading. Recent reports from several labs point out the use of artificial neural networks to circumvent this. We have chosen to use a computational process that can predict the best combination of factors for the desired response after randomly testing the higher and lower limit of the factors with experiments. The magnitude of the desired response can be presumed at any concentration within this range using the models generated by symbolic regression. The procedure provides both optimum model function as well as the optimum variable values in the model. The variable sensitivity and percentage response add depth to the information thus obtained. The study indicated that these models would have significant potential for
Wind speed oscillations are known to exhibit varying characteristics at different time scales. Ou... more Wind speed oscillations are known to exhibit varying characteristics at different time scales. Our recent analysis has shown that a collection of autoregressive models fitted separately on the frequency components of wind speed data can significantly increase the prediction accuracy. In this paper, we report the results of the investigation of dynamical behaviour across a broad frequency spectrum of wind speed measurements. The results show the existence of diverse characteristics such as stochastic, deterministic and chaotic behaviour apart from the variation of the dimensionality of underlying dynamics as well as the degree of fluctuations. It is also demonstrated that a cluster of deterministic models built upon separate frequency components of a wind speed time series can enhance the prediction accuracy by as much as 80%, on the average, consistently for predictions up to 12 h. The comparison shows the definite advantage of deterministic prediction models over autoregressive models. The f-index introduced in this paper to measure the fluctuations of wind speed over a period indicates that the observed seasonal variations of prediction errors can be correlated with changes in the f-index of the component series contributed mostly by the lower scales of decomposition.
Abstract
Maximisation of influence propagation is a key ingredient to any viral marketing or soc... more Abstract
Maximisation of influence propagation is a key ingredient to any viral marketing or socio-political campaigns. However, it is an NP-hard problem, and various approximate algorithms have been suggested to address the issue, though not largely successful. In this paper, we propose a bio-inspired approach to select the initial set of nodes which is significant in rapid convergence towards a sub-optimal solution in minimal runtime. The performance of the algorithm is evaluated using the re-tweet network of the hashtag #KissofLove on Twitter associated with the non-violent protest against the moral policing spread to many parts of India. Comparison with existing centrality based node ranking process the proposed method significant improvement on influence propagation. The proposed algorithm is one of the hardly few bio-inspired algorithms in network theory. We also report the results of the exploratory analysis of the network kiss of love campaign.
Interlocking directorates play a crucial role in the corporate governance system. In this paper w... more Interlocking directorates play a crucial role in the corporate governance system. In this paper we analyse the structural characteristics of the network of the interlocking directorate of National Stock Exchange (NSE) listed Indian companies using the tools of social network analysis to examine the effects of the underlying network on the performance of companies and directors. A component analysis of the network shows that 78.5% of the companies fall under one giant component with the largest island containing 6 companies. The giant component was further analysed for clusters and centrality measures. The results show that the highly boarded directors who constitute just 2.25% of the director population are associated with 42% of the total listed companies which account for 65.5% of the total market capitalisation. The top central actors in both director as well as company networks have been identified. The calculated values of mean path length and global clustering coefficient provide evidence for the existence of small world structure in the Indian corporate field.
In this paper, we consider the technologically important problem of periodically forced spheroids... more In this paper, we consider the technologically important problem of periodically forced spheroids in simple shear flow and demonstrate the existence of chaotic parametric regimes. The approach used by Strand (1989) (for the Strong Brownian limit) is inappropriate in the chaotic regimes corresponding to the weak Brownian limit. Our results also indicate a strong dependence of the solutions obtained on the aspect ratio of the spheroids. This strong dependence on the aspect ratio may be utilized to separate particles from a suspension of particles having different shapes but similar sizes.
Uploads
Papers by Satheesh Kumar
Maximisation of influence propagation is a key ingredient to any viral marketing or socio-political campaigns. However, it is an NP-hard problem, and various approximate algorithms have been suggested to address the issue, though not largely successful. In this paper, we propose a bio-inspired approach to select the initial set of nodes which is significant in rapid convergence towards a sub-optimal solution in minimal runtime. The performance of the algorithm is evaluated using the re-tweet network of the hashtag #KissofLove on Twitter associated with the non-violent protest against the moral policing spread to many parts of India. Comparison with existing centrality based node ranking process the proposed method significant improvement on influence propagation. The proposed algorithm is one of the hardly few bio-inspired algorithms in network theory. We also report the results of the exploratory analysis of the network kiss of love campaign.
Maximisation of influence propagation is a key ingredient to any viral marketing or socio-political campaigns. However, it is an NP-hard problem, and various approximate algorithms have been suggested to address the issue, though not largely successful. In this paper, we propose a bio-inspired approach to select the initial set of nodes which is significant in rapid convergence towards a sub-optimal solution in minimal runtime. The performance of the algorithm is evaluated using the re-tweet network of the hashtag #KissofLove on Twitter associated with the non-violent protest against the moral policing spread to many parts of India. Comparison with existing centrality based node ranking process the proposed method significant improvement on influence propagation. The proposed algorithm is one of the hardly few bio-inspired algorithms in network theory. We also report the results of the exploratory analysis of the network kiss of love campaign.