Papers by Valarmathi Krishnasamy
Selection of browsers for smartphones: a fuzzy hybrid approach and machine learning technique
Knowledge and Information Systems, Jan 4, 2023
Information Technology and Control, Sep 23, 2022
Data division using Fuzzy Logic and Blockchain for data security in cyber space
Procedia Computer Science, 2022
International Journal of Chemical Engineering, 2014
The main objective of the paper is to design a model reference adaptive controller (MRAC) with im... more The main objective of the paper is to design a model reference adaptive controller (MRAC) with improved transient performance. A modification to the standard direct MRAC called fuzzy modified MRAC (FMRAC) is used in the paper. The FMRAC uses a proportional control based Mamdani-type fuzzy logic controller (MFLC) to improve the transient performance of a direct MRAC. The paper proposes the application of real-coded genetic algorithm (RGA) to tune the membership function parameters of the proposed FMRAC offline so that the transient performance of the FMRAC is improved further. In this study, a GA based modified MRAC (GAMMRAC), an FMRAC, and a GA based FMRAC (GAFMRAC) are designed for a coupled tank setup in a hybrid tank process and their transient performances are compared. The results show that the proposed GAFMRAC gives a better transient performance than the GAMMRAC or the FMRAC. It is concluded that the proposed controller can be used to obtain very good transient performance for the control of nonlinear processes.
Hybrid Optimal Ensemble SVM Forest Classifier for Task Offloading in Mobile Cloud Computing
The Computer Journal
Mobile devices (MDs) are becoming more prevalent and their battery life is optimised by offloadin... more Mobile devices (MDs) are becoming more prevalent and their battery life is optimised by offloading tasks to cloud servers. However, communication costs must be considered when offloading tasks. To make task offloading worthwhile, it is important to measure the energy consumed during communication activities. Thus, a heterogeneous framework is developed to enhance the energy efficiency of smartphones by analysing parameters such as task and non-task offloading, local cloudlets, radio access networks and remote cloud servers. This paper proposes a task offloading framework that uses a novel algorithm, the Hybrid Red Fox Flow Direction-based Ensemble SVM Forest Classifier, to enhance the system parameters and schedule tasks in offloading cloud computing conditions. The multi-objective function aims to improve user satisfaction by maximising resource utilisation and minimising function. The framework was tested in the Cloudsim simulation tool and compared with different techniques, with...
Data division using Fuzzy Logic and Blockchain for data security in cyber space
Procedia Computer Science
Selection of browsers for smartphones: a fuzzy hybrid approach and machine learning technique
Knowledge and Information Systems
Information Technology and Control
IT and Telecommunication sector has grown massively over the past few decades. Mobile phones that... more IT and Telecommunication sector has grown massively over the past few decades. Mobile phones that were initially developed for making calls and now become an essential item and are just not restricted to calling. They have dominated most of the gadgets like computers, cameras etc. Regularly people come across an extensive number of enhanced and better-quality features being inbuilt with them. A variety of mobile phones with different shapes and sizes are manufactured within a wide range of budgets. This is the key motivation behind an exponential growth in the number of users and the arrival of new manufacturers in the field. Along with this growth, there is a fast growth of mobile application software providers also. Apart from calling, many consumers use smartphones for browsing the internet. This puts users into a dilemma to select a better browser for their smartphone to fulfill their requirements. With this aim, an attempt is made in this paper for the evaluation and selection ...
Intelligent Automation & Soft Computing
Social Networking Sites (SNSs) are nowadays utilized by the whole world to share ideas, images, a... more Social Networking Sites (SNSs) are nowadays utilized by the whole world to share ideas, images, and valuable contents by means of a post to reach a group of users. The use of SNS often inflicts the physical and the mental health of the people. Nowadays, researchers often focus on identifying the illegal behaviors in the SNS to reduce its negative influence. The state-of-art Natural Language processing techniques for anomaly detection have utilized a wide annotated corpus to identify the anomalies and they are often time-consuming as well as certainly do not guarantee maximum accuracy. To overcome these issues, the proposed methodology utilizes a Modified Convolutional Neural Network (MCNN) using stochastic pooling and a Leaky Rectified Linear Unit (LReLU). Here, each word in the social media text is analyzed based on its meaning. The stochastic pooling accurately detects the anomalous social media posts and reduces the chance of overfitting. The LReLU overcomes the high computational cost and gradient vanishing problem associated with other activation functions. It also doesn't stop the learning process when the values are negative. The MCNN computes a specified score value using a novel integrated anomaly detection technique. Based on the score value, the anomalies are identified. A Teaching Learning based Optimization (TLBO) algorithm has been used to optimize the feature extraction phase of the modified CNN and fast convergence is offered. In this way, the performance of the model is enhanced in terms of classification accuracy. The efficiency of the proposed technique is compared with the state-of-art techniques in terms of accuracy, sensitivity, specificity, recall, and precision. The proposed MCNN-TLBO technique has provided an overall architecture of 97.85%, 95.45%, and 97.55% for the three social media datasets namely Facebook, Twitter, and Reddit respectively.
Energy aware smartphone tasks offloading to the cloud using gray wolf optimization
Journal of Ambient Intelligence and Humanized Computing, 2020
Hybrid PSO - Bacterial Foraging Based Intelligent PI Controller Tuning for pH Process
The control of pH process is a difficult problem due to its inherent nonlinearity and time-varyin... more The control of pH process is a difficult problem due to its inherent nonlinearity and time-varying characteristics. For the pH process, Proportional Integral (PI) control has been successfully used for many years. Tuning of the PI controller is necessary for the satisfactory operation of the system. This paper proposes a hybrid approach involving Bacterial Foraging Optimization (BFO) Algorithm and Particle Swarm Optimization (PSO) algorithm for determining the optimal proportional-Integral (PI) controller parameters for control of a pH ...
International Journal of Chemical Engineering, 2014
The main objective of the paper is to design a model reference adaptive controller (MRAC) with im... more The main objective of the paper is to design a model reference adaptive controller (MRAC) with improved transient performance. A modification to the standard direct MRAC called fuzzy modified MRAC (FMRAC) is used in the paper. The FMRAC uses a proportional control based Mamdani-type fuzzy logic controller (MFLC) to improve the transient performance of a direct MRAC. The paper proposes the application of real-coded genetic algorithm (RGA) to tune the membership function parameters of the proposed FMRAC offline so that the transient performance of the FMRAC is improved further. In this study, a GA based modified MRAC (GAMMRAC), an FMRAC, and a GA based FMRAC (GAFMRAC) are designed for a coupled tank setup in a hybrid tank process and their transient performances are compared. The results show that the proposed GAFMRAC gives a better transient performance than the GAMMRAC or the FMRAC. It is concluded that the proposed controller can be used to obtain very good transient performance fo...
Journal of Ambient Intelligence and Humanized Computing, 2020
The utility of mobile applications has been increased enormously due to the advancements in scien... more The utility of mobile applications has been increased enormously due to the advancements in science and technology to assist the users for various purposes. The main intention of integrating cloud services and resources with the mobile application is to reduce battery usage and to improve the efficiency of mobile devices. Thus the process of shifting a task that can be run on the cloud resources for assistance is referred to as task offloading. The process of task offloading is critical in the field of Mobile Cloud Computing. The major issue that pairs with task offloading are the communication cost estimation of the devices. To overcome the above-mentioned issues and to create an effective task offloading model, A Novel Mobile Cloud Computing framework called Rule Generation based Energy Estimation Model (RG-EEM) is designed. The energy required for executing the task in the local mobile device and cloud is estimated by implementing an energy estimation algorithm. Then a novel constraints specific rule generation algorithm is used to estimate the task execution time and memory utilization of the task, from which the decision has to be taken for offloading or local execution by considering all the possible affecting characteristics. Further, a novel task clustering and scheduling algorithm are implemented to execute the task in the cloud server effectively which will help in allocating similar tasks to a particular virtual machine in the cloud. The RG-EEM algorithm will also help in partitioning the task and parallel execution. The effectiveness of the RG-EEM technique is evaluated using the parametric measures and compared with the existing techniques.
International Journal of Power Electronics and Drive Systems (IJPEDS), 2015
The reliability, efficiency, and controllability of Photo Voltaic power systems can be increased ... more The reliability, efficiency, and controllability of Photo Voltaic power systems can be increased by embedding the components of a Boost Converter. Currently, the converter technology overcomes the main problems of manufacturing cost, efficiency and mass production. Issue to limit the life span of a Photo Voltaic inverter is the huge electrolytic capacitor across the Direct Current bus for energy decoupling. This paper presents a two-phase interleaved boost converter which ensures 180 angle phase shift between the two interleaved converters. The Proportional Integral controller is used to reshape that the controller attempts to minimize the error by adjusting the control inputs and also real coded genetic algorithm is proposed for tuning of controlling parameters of Proportional Integral controller. The real coded genetic algorithm is applied in the Interleaved Boost Converter with Advanced Pulse Width Modulation Techniques for improving the results of efficiency and reduction of ripple current. Simulation results illustrate the improvement of efficiency and the diminution of ripple current.
Ripple current reduction in interleaved boost converter by using advanced PWM techniques
2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies, 2014
The reliability, efficiency, and controllability of Photo Voltaic (PV) power systems can be incre... more The reliability, efficiency, and controllability of Photo Voltaic (PV) power systems can be increased by embedding the components of a Boost Converter. Technology of boost converter should overcome the main problems of manufacturing cost, efficiency and production. The key factor to limit the life span of a PV inverter is the huge electrolytic capacitor across the Direct Current (DC) bus for energy decoupling. A boost converter is a DC-DC power converter with higher output voltage, but it produces some ripple current. In order to improve the efficiency of the boost converter and reduce the ripple current, an interleaved boost converter is used. This paper presents a two-phase interleaved boost converter which ensures 180° phase shift between the two interleaved converters. This paper presents a two phase Interleaved Boost Converter with Proportional Integral (PI) controller. PI is designed for output voltage regulation and this boost converter is simulated for various Pulse Width Modulation (PWM) scheme. This simulation results shows output voltage is well tracked and it improves the efficiency and reduces the ripple current.
2008 4th International IEEE Conference Intelligent Systems, 2008
Brazilian Journal of Chemical Engineering, 2014
This paper describes the modelling and control of a pH neutralization process using a Local Linea... more This paper describes the modelling and control of a pH neutralization process using a Local Linear Model Tree (LOLIMOT) and an adaptive neuro-fuzzy inference system (ANFIS). The Direct and Inverse model building using LOLIMOT and ANFIS structures is described and compared. The direct and inverse models of the pH system are identified based on experimental data for the LOLIMOT and ANFIS structures. The identified models are implemented in the experimental pH system with IMC structure using a GUI developed in the MATLAB -SIMULINK platform. The main aim is to illustrate the online modelling and control of the experimental setup. The results of real-time control of an experimental pH process using the Internal Model Control (IMC) strategy are also presented.
Intelligent Identification of Moisture Control of Drying Process in Paper Machine
ABSTRACT 1 Abstract—This paper is focuses modeling of the last part of the paper machine – the dr... more ABSTRACT 1 Abstract—This paper is focuses modeling of the last part of the paper machine – the drying section. Paper is dried by letting it pass through a series of steam heated group of cylinders and the evaporation is thus performed by the latent heat of vaporization of the steam. The moisture in the paper is controlled by adjusting the set point of the steam pressure controllers to the cylinders. There exist several incentives to focus on the performance of the moisture control. The time to perform a grade change is often limited by the moisture and shorter grade change time is directly correlated to economic profit. The plant model is identified periodically and the changes in its dynamic characteristics are observed. Periodic identification gives a great advantage over the conventional controller tuning methods, which uses the plant model at the nominal operating conditions. A variety of model structures are available to assist in modelling a system. Model for the drying process of Paper industry is established based on gathering 1000 groups of 2500 real-time sample data. Based on the collection of data, that was adapted to both the conventional and intelligent modelling process. Finally the suitable model is tuned with the suitable controller for optimal control of the drying process.
Model-Based Control for Moisture in Paper Making Process
Advances in Intelligent Systems and Computing, 2014
This project deals with the performance evaluation on the comparison of model-based control for d... more This project deals with the performance evaluation on the comparison of model-based control for drying process of paper industry. The dryer section is the last part of the paper machine and consists of a large number of rotating steam-heated cast iron cylinders by adjusting the set point of the stream pressure controller to the cylinders. In the design of model reference adaptive control, schema is used, in which the adaptive law has been developed by MIT rule. Similarly, design of PID and MRAC controller is used. This paper presents a nonlinear dynamic control, based on heat and mass balance for steam, cylinder, and paper. The control was performed to the combined drying process system using both the adaptive control algorithm and MPC controller method and its results were analyzed. A simulation is carried out using MATLAB. Simulation results reveal clear benefits of the model reference adaptive control over traditional controller and MPC controller methods. Thus, by controlling, this process proves real incentives for industrial implementation.
Particle Swarm Optimization Based Pi Controller Tuning for Fermentation Process
Innovative Applications of Information Technology for the Developing World, 2007
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Papers by Valarmathi Krishnasamy