Priti Dimri - Academia.edu (original) (raw)

Papers by Priti Dimri

The generation of fractals and study of the dynamics of polynomials is one of the emerging and in... more The generation of fractals and study of the dynamics of polynomials is one of the emerging and interesting fields of research nowadays. We introduce in this paper the dynamics of modified multibrot function z d - z + c = 0 for d

Mathematical Problems in Engineering, Jun 3, 2021

Cloud computing platforms have been extensively using scientific workflows to execute large-scale... more Cloud computing platforms have been extensively using scientific workflows to execute large-scale applications. However, multiobjective workflow scheduling with scientific standards to optimize QoS parameters is a challenging task. Various metaheuristic scheduling techniques have been proposed to satisfy the QoS parameters like makespan, cost, and resource utilization. Still, traditional metaheuristic approaches are incompetent to maintain agreeable equilibrium between exploration and exploitation of the search space because of their limitations like getting trapped in local optimum value at later evolution stages and higher-dimensional nonlinear optimization problem. is paper proposes an improved Fruit Fly Optimization (IFFO) algorithm to minimize makespan and cost for scheduling multiple workflows in the cloud computing environment. e proposed algorithm is evaluated using CloudSim for scheduling multiple workflows. e comparative results depict that the proposed algorithm IFFO outperforms FFO, PSO, and GA.

Much more information itself needs information about information. Since last twenty years, data s... more Much more information itself needs information about information. Since last twenty years, data scientists are working on Big Data and its analytics. We already covered a long distance in all verticals of Big Data but cloud based software testing. Big Data analytics is based on 5 V's and analytical results may sometime generate unwanted data for the financial forecasters. Cloud computing plays a crucial role in the analytical scenario. Cloud computing supports everything as service like IAAS, SAAS, PAAS, TAAS etc. and in this environment, we need testing as well as validation tool in the same environment. Testing as a Service (TaaS) is being offered by many players through cloud. Dearth literature availability and wide application of testing tools in financial market cloud computing Big Data prompted us to work on the area of cloud based automated validation and testing tool model. In this paper, we are trying to address the real challenges of online cloud based automated testing tools not as testing as a service (TaaS) but mandatory tool applicable in the financial market computing and introducing new model. This model will be applicable during testing and validation of the desired data for financial forecasting.

Lecture notes in networks and systems, 2020

Over the past few years, fingerprints have been considered the most sensitive and crucial identif... more Over the past few years, fingerprints have been considered the most sensitive and crucial identification basis for low enforcement agencies. In crime scene and forensics, recording of latent fingerprints from uneven and noisy surface is a difficult task and conventional algorithm fails in most of the times. A robust orientation field estimation algorithm is the need of the time to recognize the poor quality latent. To overcome the limitations of conventional algorithm, various techniques have been proposed in the last decade. In this paper, a comparative study has been done of state-of-the-art techniques with their advancements and limitations. Our proposal aims at effectively minimizing the difficulties faced to separate ridges and segmentation of latent images reducing search time and computational complexity while optimizing the system retrieval performance.

International journal of computer applications, Apr 30, 2012

In this paper we investigate the new Julia set and a new Tricorn and Multicorns of fractals. The ... more In this paper we investigate the new Julia set and a new Tricorn and Multicorns of fractals. The beautiful and useful fractal images are generated using Ishikawa iteration to study many of their properties. The paper mainly emphasizes on reviewing the detailed study and generation of Relative Superior Tricorn and Multicorns along with Relative Superior Julia Set.

Advances in intelligent systems and computing, 2020

Latent fingerprints are the fingerprints that are left by the criminals unintentionally on items ... more Latent fingerprints are the fingerprints that are left by the criminals unintentionally on items touched by the fingers. These types of fingerprints are not often directly visible by naked eyes. Segmentation is a very important part of the fingerprint identification system (AFIS). The fingerprint segmentation algorithms separate the foreground (friction ridge pattern) from background. In this paper different segmentation algorithms are presented that are DTV, ADTV, ATV, Ridge Template Correlation method, Segmentation based on statistical characteristics of gray and orientation field information theory, Adaptive Latent Fingerprint Segmentation using Feature Selection and Random Decision Forest Classification, Latent Fingerprint Image Segmentation using Fractal Dimension Features and WELME are discussed and compared their performance. This study evaluates the effectiveness, advantages, limitations and applications of various segmentation methods that are being used in latent fingerprinting segmentation techniques.

Kuwait Journal of Science

High-performance computing is changing the way we compute. In the past decade, the cloud computin... more High-performance computing is changing the way we compute. In the past decade, the cloud computing paradigm has changed the way we compute, communicate, and technology. Cover real-world problems. There are still many complex challenges in the cloud computing paradigm. Improving effective planning strategies is a complex problem in the service-oriented computing paradigm.In this article, our research focuses on improving task scheduler strategies to improve the performance of cloud applications. The proposed model is inspired by an artificial neural network-based system and astrology base scheduler Big-Bang Big-Crunch. The results show that the proposed strategy based on BBBC and neural network is superior to the method based on astrology (BigBang BigCrunch costaware), genetic cost and many other existing methods.The proposed BB-BC-ANN model is validated using standard workload file (San Diego Supercomputer Center (SDSC) Blue Horizon logs). The results show that the proposed BB-BC-AN...

Journal of Scientific & Industrial Research

Latent fingerprints have become most important evidence in law enforcement department and forensi... more Latent fingerprints have become most important evidence in law enforcement department and forensic agencies worldwide. It is also very important evidence in forensic applications to identify criminals as it is mostly encountered in crime scenes. Segmentation is one of the solutions to extract quality features. Fingerprint indexing reduces the search space without compromising accuracy. In this paper, minutiae based rotational and translational features and a global matching approach in combination with local matching is used in order to boost the indexing efficiency. Also, a machine learning (ML) based segmentation model is designed as a binary classification model to classify local blocks into foreground and background. Average indexed time as well as accuracy for full as well as partial fingerprints is tabulated by varying the template sminutiae.

Journal of Scientific & Industrial Research

Since decades fingerprints have been the prime source in identification of suspects latent finger... more Since decades fingerprints have been the prime source in identification of suspects latent fingerprints are compared and examined with rolled and plain fingerprints which are stored in the dataset. The common challenges which are faced while examining latent fingerprints are background noise, nonlinear distortions, poor ridge clarity and partial impression of the finger. As conventional methods of Segmentation doesn't perform well on latent fingerprints. The current advancement in machine learning based segmentation approach has been showing good results in terms of segmentation accuracy but lacks to provide accurate result in terms of matching accuracy. As one of the problem faced in matching latent fingerprint is low clarity of ridge-valley pattern which results in detection of false minutiae and poor matching accuracy. A multilayer processing of artificial neural network based segmentation is proposed to minimize the detection of false minutiae and increase the matching accuracy. This approach is designed on binary classification model where the simulation will be carried out on IIIT-D latent fingerprint dataset. Segmentation will be divided into full and partial impression fingerprints which are then compared with minutiae with the database using local and global matching algorithm. An improvised result is received which is more accurate as compared to the previous algorithms.

Mathematical Problems in Engineering

Cloud computing platforms have been extensively using scientific workflows to execute large-scale... more Cloud computing platforms have been extensively using scientific workflows to execute large-scale applications. However, multiobjective workflow scheduling with scientific standards to optimize QoS parameters is a challenging task. Various metaheuristic scheduling techniques have been proposed to satisfy the QoS parameters like makespan, cost, and resource utilization. Still, traditional metaheuristic approaches are incompetent to maintain agreeable equilibrium between exploration and exploitation of the search space because of their limitations like getting trapped in local optimum value at later evolution stages and higher-dimensional nonlinear optimization problem. This paper proposes an improved Fruit Fly Optimization (IFFO) algorithm to minimize makespan and cost for scheduling multiple workflows in the cloud computing environment. The proposed algorithm is evaluated using CloudSim for scheduling multiple workflows. The comparative results depict that the proposed algorithm IFF...

International Journal of Electrical and Electronics Research

Cloud computing relies on the collection and distribution of services from internet-based data ce... more Cloud computing relies on the collection and distribution of services from internet-based data centers. With the large resource pool available in internet wide range of users are accessing the cloud. Load balance is important feature involving resource allocation to prevent overloading of any system or optimal use of resources. Major load in cloud network are concerned with CPU, memory and network. This cloud computing aspect has not yet earned too much coverage. Although load balancing is an important feature for cloud computing, concurrent computing etc. In these areas, several algorithms were suggested to solve load balance problem. However, it does recommend very few cloud computing algorithms. Given that cloud storage differs considerably from all other environments, particular load balancing algorithm should will built in sort to serve its needs. This work proposes novel load-balancing algorithm based on artificial bee colony algorithm and load balancing min-min scheduling alg...

Resource provisioning and resource optimization are the key issues in cloud computing. To balance... more Resource provisioning and resource optimization are the key issues in cloud computing. To balance the load in across virtual machine load balancing algorithms are classified into two categories i.e. static, dynamic. For homogeneous and stable environment we prefer static load balancing algorithms. For heterogeneous, dynamic environment we prefer dynamic load balancing algorithms. Load balancing may take place in the public, private or hybrid cloud. In this paper, we focus on a load balancing policy i.e. Closest data Center with different no of virtual machines. The evaluation metrics is the response time and data center processing time. Cloud Environment is simulated for the scenario of “Internet banking ” of an international bank in simulation toolkit CloudAnalyst. Using these two evaluation metrics we identify that for real deployment of such customers application what should be a threshold value of key parameters which are supported by the Cluster of users across the Globe.

Advances in Intelligent Systems and Computing, 2020

Latent fingerprints are the fingerprints that are left by the criminals unintentionally on items ... more Latent fingerprints are the fingerprints that are left by the criminals unintentionally on items touched by the fingers. These types of fingerprints are not often directly visible by naked eyes. Segmentation is a very important part of the fingerprint identification system (AFIS). The fingerprint segmentation algorithms separate the foreground (friction ridge pattern) from background. In this paper different segmentation algorithms are presented that are DTV, ADTV, ATV, Ridge Template Correlation method, Segmentation based on statistical characteristics of gray and orientation field information theory, Adaptive Latent Fingerprint Segmentation using Feature Selection and Random Decision Forest Classification, Latent Fingerprint Image Segmentation using Fractal Dimension Features and WELME are discussed and compared their performance. This study evaluates the effectiveness, advantages, limitations and applications of various segmentation methods that are being used in latent fingerprinting segmentation techniques.

2016 International Conference System Modeling & Advancement in Research Trends (SMART), 2016

Much more information itself needs information about information. Since last twenty years, data s... more Much more information itself needs information about information. Since last twenty years, data scientists are working on Big Data and its analytics. We already covered a long distance in all verticals of Big Data but cloud based software testing. Big Data analytics is based on 5 V's and analytical results may sometime generate unwanted data for the financial forecasters. Cloud computing plays a crucial role in the analytical scenario. Cloud computing supports everything as service like IAAS, SAAS, PAAS, TAAS etc. and in this environment, we need testing as well as validation tool in the same environment. Testing as a Service (TaaS) is being offered by many players through cloud. Dearth literature availability and wide application of testing tools in financial market cloud computing Big Data prompted us to work on the area of cloud based automated validation and testing tool model. In this paper, we are trying to address the real challenges of online cloud based automated testin...

e-Governance is the application of Information and Communication Technology (ICT) for delivering ... more e-Governance is the application of Information and Communication Technology (ICT) for delivering government services, exchange of information communication transactions, integration of various stand-alone systems as well as back office processes and interactions within the entire government framework. The Cloud provides an exciting platform to develop new applications and new ways to deliver services and information to communities. It has the stamina to overcome the challenge in the ICT world. E-Governance is required to run the government in efficient way with the use of ICT. Cloud solutions can help improve transparency, accuracy and can stop the malpractices which are major goal for government enterprises. The key to successfully using the Cloud for e- governance is based on how to combine the new capabilities of computing with the heritage systems that will often be the most valuable link in the value chain, holding data vital to the end user's experience. We are here to pro...

At present Green Computing is under the consideration of businesses organizations and IT industri... more At present Green Computing is under the consideration of businesses organizations and IT industries. With the advancement in variety of applications and user demands the infrastructure and resources are increasing exponentially. In past few years, computer and IT industry have realized the importance of going green, both in terms of environmental issues and minimizing costs which has led to remarkable drift in strategies and policies of IT industry. The motivation behind this change comes from the ever increasing business computing demand, ever growing cost of energy, rising awareness of global warming issues. This paper presents several green initiatives under way in the IT industry and in brief covers the main research challenges which are still open in the race to meet green computing requirements.

2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), 2016

Computing paradigm plays an important role to study the scientific applications. Here we focus on... more Computing paradigm plays an important role to study the scientific applications. Here we focus on tool based simulation of Cloud computing Infrastructure for power aware analysis. We introduce the cloud computing paradigm for resource like data center which is enabled with DVFS (dynamic voltage frequency scaling) with power aware deployment across the Globe in different geographic region. In this paper we find out the best policy across data center with minimum power consumption. The management of resources, to schedule the task on cloud computing environment is difficult in real time mode across the Globe in different organizations with their own power consumption policies. If there is a case of non homogenous and data center without awareness about power consumption, hosts coming under this category consume maximum power which is not in favor of green computing. To deal with these limitations, we will use a discrete-event cloud simulation toolkit to identify that how to save power...

2016 6th International Conference - Cloud System and Big Data Engineering (Confluence), 2016

Nature and behavior of data required for the financial market forecasting specially in the stock ... more Nature and behavior of data required for the financial market forecasting specially in the stock market is not only restricted to the stock prices. Data scientists had studied market behavior by applying behavior study tools like Google-Profile of Mood States (GPOMS) and OpinionFinder on information available through news and social media platforms like twitter. But behavior finance is still at a novice state and growing with a substantial pace. Data required for the market is big, heterogeneous and mammoth. It consists of prices of stock exchanges as well as socio - political - economic data from all over the globe. Green database design will help to increase the efficiency of the database towards green drive but restricted to the prices of the stock. In continuation of our previous work on green computing in financial market, we are proposing a model as score based financial forecasting method by incorporating different sources of integrated information flow into integrative river...

2015 2nd International Conference on Computing for Sustainable Global Development (INDIACom), 2015

Quality of service(QoS) becomes a more challenging task due to bandwidth constraints and dynamic ... more Quality of service(QoS) becomes a more challenging task due to bandwidth constraints and dynamic topology of a wireless network. Because of dynamic topology reason nodes in a network moves freely and results in various routing problems. Therefore, to overcome these challenges a protocol with QoS is proposed in this paper named QAODV. In this paper two additional fields are to the message of Ad-hoc on demand distance vector (AODV) routing protocol added in order to improve performance in terms of packet delivery rate (PDR), packet loss ratio (PLR) and average end to end delay. The simulation results reveals the improved performances of QAODV with AODV and is achieved in packet delivery ratio and total no. of packets dropped in the network at the expense of forwarding more routing packets makes it more reliable in realtime traffic scenario.

The generation of fractals and study of the dynamics of polynomials is one of the emerging and in... more The generation of fractals and study of the dynamics of polynomials is one of the emerging and interesting fields of research nowadays. We introduce in this paper the dynamics of modified multibrot function z d - z + c = 0 for d

Mathematical Problems in Engineering, Jun 3, 2021

Cloud computing platforms have been extensively using scientific workflows to execute large-scale... more Cloud computing platforms have been extensively using scientific workflows to execute large-scale applications. However, multiobjective workflow scheduling with scientific standards to optimize QoS parameters is a challenging task. Various metaheuristic scheduling techniques have been proposed to satisfy the QoS parameters like makespan, cost, and resource utilization. Still, traditional metaheuristic approaches are incompetent to maintain agreeable equilibrium between exploration and exploitation of the search space because of their limitations like getting trapped in local optimum value at later evolution stages and higher-dimensional nonlinear optimization problem. is paper proposes an improved Fruit Fly Optimization (IFFO) algorithm to minimize makespan and cost for scheduling multiple workflows in the cloud computing environment. e proposed algorithm is evaluated using CloudSim for scheduling multiple workflows. e comparative results depict that the proposed algorithm IFFO outperforms FFO, PSO, and GA.

Much more information itself needs information about information. Since last twenty years, data s... more Much more information itself needs information about information. Since last twenty years, data scientists are working on Big Data and its analytics. We already covered a long distance in all verticals of Big Data but cloud based software testing. Big Data analytics is based on 5 V's and analytical results may sometime generate unwanted data for the financial forecasters. Cloud computing plays a crucial role in the analytical scenario. Cloud computing supports everything as service like IAAS, SAAS, PAAS, TAAS etc. and in this environment, we need testing as well as validation tool in the same environment. Testing as a Service (TaaS) is being offered by many players through cloud. Dearth literature availability and wide application of testing tools in financial market cloud computing Big Data prompted us to work on the area of cloud based automated validation and testing tool model. In this paper, we are trying to address the real challenges of online cloud based automated testing tools not as testing as a service (TaaS) but mandatory tool applicable in the financial market computing and introducing new model. This model will be applicable during testing and validation of the desired data for financial forecasting.

Lecture notes in networks and systems, 2020

Over the past few years, fingerprints have been considered the most sensitive and crucial identif... more Over the past few years, fingerprints have been considered the most sensitive and crucial identification basis for low enforcement agencies. In crime scene and forensics, recording of latent fingerprints from uneven and noisy surface is a difficult task and conventional algorithm fails in most of the times. A robust orientation field estimation algorithm is the need of the time to recognize the poor quality latent. To overcome the limitations of conventional algorithm, various techniques have been proposed in the last decade. In this paper, a comparative study has been done of state-of-the-art techniques with their advancements and limitations. Our proposal aims at effectively minimizing the difficulties faced to separate ridges and segmentation of latent images reducing search time and computational complexity while optimizing the system retrieval performance.

International journal of computer applications, Apr 30, 2012

In this paper we investigate the new Julia set and a new Tricorn and Multicorns of fractals. The ... more In this paper we investigate the new Julia set and a new Tricorn and Multicorns of fractals. The beautiful and useful fractal images are generated using Ishikawa iteration to study many of their properties. The paper mainly emphasizes on reviewing the detailed study and generation of Relative Superior Tricorn and Multicorns along with Relative Superior Julia Set.

Advances in intelligent systems and computing, 2020

Latent fingerprints are the fingerprints that are left by the criminals unintentionally on items ... more Latent fingerprints are the fingerprints that are left by the criminals unintentionally on items touched by the fingers. These types of fingerprints are not often directly visible by naked eyes. Segmentation is a very important part of the fingerprint identification system (AFIS). The fingerprint segmentation algorithms separate the foreground (friction ridge pattern) from background. In this paper different segmentation algorithms are presented that are DTV, ADTV, ATV, Ridge Template Correlation method, Segmentation based on statistical characteristics of gray and orientation field information theory, Adaptive Latent Fingerprint Segmentation using Feature Selection and Random Decision Forest Classification, Latent Fingerprint Image Segmentation using Fractal Dimension Features and WELME are discussed and compared their performance. This study evaluates the effectiveness, advantages, limitations and applications of various segmentation methods that are being used in latent fingerprinting segmentation techniques.

Kuwait Journal of Science

High-performance computing is changing the way we compute. In the past decade, the cloud computin... more High-performance computing is changing the way we compute. In the past decade, the cloud computing paradigm has changed the way we compute, communicate, and technology. Cover real-world problems. There are still many complex challenges in the cloud computing paradigm. Improving effective planning strategies is a complex problem in the service-oriented computing paradigm.In this article, our research focuses on improving task scheduler strategies to improve the performance of cloud applications. The proposed model is inspired by an artificial neural network-based system and astrology base scheduler Big-Bang Big-Crunch. The results show that the proposed strategy based on BBBC and neural network is superior to the method based on astrology (BigBang BigCrunch costaware), genetic cost and many other existing methods.The proposed BB-BC-ANN model is validated using standard workload file (San Diego Supercomputer Center (SDSC) Blue Horizon logs). The results show that the proposed BB-BC-AN...

Journal of Scientific & Industrial Research

Latent fingerprints have become most important evidence in law enforcement department and forensi... more Latent fingerprints have become most important evidence in law enforcement department and forensic agencies worldwide. It is also very important evidence in forensic applications to identify criminals as it is mostly encountered in crime scenes. Segmentation is one of the solutions to extract quality features. Fingerprint indexing reduces the search space without compromising accuracy. In this paper, minutiae based rotational and translational features and a global matching approach in combination with local matching is used in order to boost the indexing efficiency. Also, a machine learning (ML) based segmentation model is designed as a binary classification model to classify local blocks into foreground and background. Average indexed time as well as accuracy for full as well as partial fingerprints is tabulated by varying the template sminutiae.

Journal of Scientific & Industrial Research

Since decades fingerprints have been the prime source in identification of suspects latent finger... more Since decades fingerprints have been the prime source in identification of suspects latent fingerprints are compared and examined with rolled and plain fingerprints which are stored in the dataset. The common challenges which are faced while examining latent fingerprints are background noise, nonlinear distortions, poor ridge clarity and partial impression of the finger. As conventional methods of Segmentation doesn't perform well on latent fingerprints. The current advancement in machine learning based segmentation approach has been showing good results in terms of segmentation accuracy but lacks to provide accurate result in terms of matching accuracy. As one of the problem faced in matching latent fingerprint is low clarity of ridge-valley pattern which results in detection of false minutiae and poor matching accuracy. A multilayer processing of artificial neural network based segmentation is proposed to minimize the detection of false minutiae and increase the matching accuracy. This approach is designed on binary classification model where the simulation will be carried out on IIIT-D latent fingerprint dataset. Segmentation will be divided into full and partial impression fingerprints which are then compared with minutiae with the database using local and global matching algorithm. An improvised result is received which is more accurate as compared to the previous algorithms.

Mathematical Problems in Engineering

Cloud computing platforms have been extensively using scientific workflows to execute large-scale... more Cloud computing platforms have been extensively using scientific workflows to execute large-scale applications. However, multiobjective workflow scheduling with scientific standards to optimize QoS parameters is a challenging task. Various metaheuristic scheduling techniques have been proposed to satisfy the QoS parameters like makespan, cost, and resource utilization. Still, traditional metaheuristic approaches are incompetent to maintain agreeable equilibrium between exploration and exploitation of the search space because of their limitations like getting trapped in local optimum value at later evolution stages and higher-dimensional nonlinear optimization problem. This paper proposes an improved Fruit Fly Optimization (IFFO) algorithm to minimize makespan and cost for scheduling multiple workflows in the cloud computing environment. The proposed algorithm is evaluated using CloudSim for scheduling multiple workflows. The comparative results depict that the proposed algorithm IFF...

International Journal of Electrical and Electronics Research

Cloud computing relies on the collection and distribution of services from internet-based data ce... more Cloud computing relies on the collection and distribution of services from internet-based data centers. With the large resource pool available in internet wide range of users are accessing the cloud. Load balance is important feature involving resource allocation to prevent overloading of any system or optimal use of resources. Major load in cloud network are concerned with CPU, memory and network. This cloud computing aspect has not yet earned too much coverage. Although load balancing is an important feature for cloud computing, concurrent computing etc. In these areas, several algorithms were suggested to solve load balance problem. However, it does recommend very few cloud computing algorithms. Given that cloud storage differs considerably from all other environments, particular load balancing algorithm should will built in sort to serve its needs. This work proposes novel load-balancing algorithm based on artificial bee colony algorithm and load balancing min-min scheduling alg...

Resource provisioning and resource optimization are the key issues in cloud computing. To balance... more Resource provisioning and resource optimization are the key issues in cloud computing. To balance the load in across virtual machine load balancing algorithms are classified into two categories i.e. static, dynamic. For homogeneous and stable environment we prefer static load balancing algorithms. For heterogeneous, dynamic environment we prefer dynamic load balancing algorithms. Load balancing may take place in the public, private or hybrid cloud. In this paper, we focus on a load balancing policy i.e. Closest data Center with different no of virtual machines. The evaluation metrics is the response time and data center processing time. Cloud Environment is simulated for the scenario of “Internet banking ” of an international bank in simulation toolkit CloudAnalyst. Using these two evaluation metrics we identify that for real deployment of such customers application what should be a threshold value of key parameters which are supported by the Cluster of users across the Globe.

Advances in Intelligent Systems and Computing, 2020

Latent fingerprints are the fingerprints that are left by the criminals unintentionally on items ... more Latent fingerprints are the fingerprints that are left by the criminals unintentionally on items touched by the fingers. These types of fingerprints are not often directly visible by naked eyes. Segmentation is a very important part of the fingerprint identification system (AFIS). The fingerprint segmentation algorithms separate the foreground (friction ridge pattern) from background. In this paper different segmentation algorithms are presented that are DTV, ADTV, ATV, Ridge Template Correlation method, Segmentation based on statistical characteristics of gray and orientation field information theory, Adaptive Latent Fingerprint Segmentation using Feature Selection and Random Decision Forest Classification, Latent Fingerprint Image Segmentation using Fractal Dimension Features and WELME are discussed and compared their performance. This study evaluates the effectiveness, advantages, limitations and applications of various segmentation methods that are being used in latent fingerprinting segmentation techniques.

2016 International Conference System Modeling & Advancement in Research Trends (SMART), 2016

Much more information itself needs information about information. Since last twenty years, data s... more Much more information itself needs information about information. Since last twenty years, data scientists are working on Big Data and its analytics. We already covered a long distance in all verticals of Big Data but cloud based software testing. Big Data analytics is based on 5 V's and analytical results may sometime generate unwanted data for the financial forecasters. Cloud computing plays a crucial role in the analytical scenario. Cloud computing supports everything as service like IAAS, SAAS, PAAS, TAAS etc. and in this environment, we need testing as well as validation tool in the same environment. Testing as a Service (TaaS) is being offered by many players through cloud. Dearth literature availability and wide application of testing tools in financial market cloud computing Big Data prompted us to work on the area of cloud based automated validation and testing tool model. In this paper, we are trying to address the real challenges of online cloud based automated testin...

e-Governance is the application of Information and Communication Technology (ICT) for delivering ... more e-Governance is the application of Information and Communication Technology (ICT) for delivering government services, exchange of information communication transactions, integration of various stand-alone systems as well as back office processes and interactions within the entire government framework. The Cloud provides an exciting platform to develop new applications and new ways to deliver services and information to communities. It has the stamina to overcome the challenge in the ICT world. E-Governance is required to run the government in efficient way with the use of ICT. Cloud solutions can help improve transparency, accuracy and can stop the malpractices which are major goal for government enterprises. The key to successfully using the Cloud for e- governance is based on how to combine the new capabilities of computing with the heritage systems that will often be the most valuable link in the value chain, holding data vital to the end user's experience. We are here to pro...

At present Green Computing is under the consideration of businesses organizations and IT industri... more At present Green Computing is under the consideration of businesses organizations and IT industries. With the advancement in variety of applications and user demands the infrastructure and resources are increasing exponentially. In past few years, computer and IT industry have realized the importance of going green, both in terms of environmental issues and minimizing costs which has led to remarkable drift in strategies and policies of IT industry. The motivation behind this change comes from the ever increasing business computing demand, ever growing cost of energy, rising awareness of global warming issues. This paper presents several green initiatives under way in the IT industry and in brief covers the main research challenges which are still open in the race to meet green computing requirements.

2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), 2016

Computing paradigm plays an important role to study the scientific applications. Here we focus on... more Computing paradigm plays an important role to study the scientific applications. Here we focus on tool based simulation of Cloud computing Infrastructure for power aware analysis. We introduce the cloud computing paradigm for resource like data center which is enabled with DVFS (dynamic voltage frequency scaling) with power aware deployment across the Globe in different geographic region. In this paper we find out the best policy across data center with minimum power consumption. The management of resources, to schedule the task on cloud computing environment is difficult in real time mode across the Globe in different organizations with their own power consumption policies. If there is a case of non homogenous and data center without awareness about power consumption, hosts coming under this category consume maximum power which is not in favor of green computing. To deal with these limitations, we will use a discrete-event cloud simulation toolkit to identify that how to save power...

2016 6th International Conference - Cloud System and Big Data Engineering (Confluence), 2016

Nature and behavior of data required for the financial market forecasting specially in the stock ... more Nature and behavior of data required for the financial market forecasting specially in the stock market is not only restricted to the stock prices. Data scientists had studied market behavior by applying behavior study tools like Google-Profile of Mood States (GPOMS) and OpinionFinder on information available through news and social media platforms like twitter. But behavior finance is still at a novice state and growing with a substantial pace. Data required for the market is big, heterogeneous and mammoth. It consists of prices of stock exchanges as well as socio - political - economic data from all over the globe. Green database design will help to increase the efficiency of the database towards green drive but restricted to the prices of the stock. In continuation of our previous work on green computing in financial market, we are proposing a model as score based financial forecasting method by incorporating different sources of integrated information flow into integrative river...

2015 2nd International Conference on Computing for Sustainable Global Development (INDIACom), 2015

Quality of service(QoS) becomes a more challenging task due to bandwidth constraints and dynamic ... more Quality of service(QoS) becomes a more challenging task due to bandwidth constraints and dynamic topology of a wireless network. Because of dynamic topology reason nodes in a network moves freely and results in various routing problems. Therefore, to overcome these challenges a protocol with QoS is proposed in this paper named QAODV. In this paper two additional fields are to the message of Ad-hoc on demand distance vector (AODV) routing protocol added in order to improve performance in terms of packet delivery rate (PDR), packet loss ratio (PLR) and average end to end delay. The simulation results reveals the improved performances of QAODV with AODV and is achieved in packet delivery ratio and total no. of packets dropped in the network at the expense of forwarding more routing packets makes it more reliable in realtime traffic scenario.