Prashanta Kumar Patra

College of Engineering and Technology | CET · Department of Computer Science and Engineering

Cardiovascular Diseases (CVDs), or heart diseases, are one of the top-ranking causes of death worldwide. About 1 in every 4 deaths is related to heart diseases, which are broadly classified as various types of abnormal heart conditions. However, diagnosis of CVDs is a time-consuming process in which data obtained from various clinical tests are man...

Medical specialists are primarily interested in researching health care as a potential replacement for conventional healthcare methods nowadays. COVID-19 creates chaos in society regardless of the modern technological evaluation involved in this sector. Due to inadequate medical care and timely, accurate prognoses, many unexpected fatalities occur....

Digital forensic methods for cybercrime investigation in a cloud computing environment (i.e., cloud forensic) is a broad term that encompasses a number of different fields, including digital forensics and cloud computing. The authors hope to gain a better understanding of cloud computing and identify challenges and opportunities in forensic science...

The measurement of solar radiation and its forecasting at any particular location is a difficult task as it depends on various input parameters. So, intelligent modeling approaches with advanced techniques are always necessary for this challenging activity. Adaptive neuro-fuzzy inference system ( A N F I S ) based on modeling plays a vital role in...

In the past few decades, the offline recognition of handwritten Indic scripts has received much attention of researchers. Although an intensive research has been reported for various Indic languages, limited research work is carried out for handwritten Odia, Bangla character recognition owing to their complex shapes and the unavailability of the st...

Malware is a term used to represent malicious software which comprises of viruses, spyware, and many such. With the advent of Web-based technologies, the attacker strategies are also transforming. Thus, detection of malware becomes a key task. Traditional approaches like signature-based approach, behavior-based approach, and many such need certain...

Nowadays, healthcare is the most important domain to be analyzed by the technology experts for replacing the traditional techniques. Unexpected death is happening due to lack of medical treatment and diagnosis at right time. As healthcare applications have become technology-oriented, therefore, the upcoming technologies can be integrated for provid...

Automatic Character Recognition for the handwritten Indic script has listed up as most the challenging area for research in the field of pattern recognition. Although a great amount of research work has been reported, but all the state-of-art methods are limited with optimal features. This article aims to suggest a well-defined recognition model wh...

Handwritten Character Recognition (HCR) of Indic scripts is one of the most challenging as compared other scripts. Recognition of handwritten character is more difficult one as compares with the printed one due to their similar structure and orientation. To have a proper recognition system for handwritten characters various researchers have adapted...

Cloud computing is the recent trend in computing paradigms. It is widely being used by different communities due to its abundant opportunities as resources or services. The cloud hosts a variety of web applications and provides services on a pay-per-use basis. It has many computing issues related to server management, response time, content deliver...

Cloud computing is gaining more popularity due to its advantages over conventional computing. It offers utility based services to subscribers on demand basis. Cloud hosts a variety of web applications and provides services on the pay-per-use basis. As the users are increasing in the cloud system, the load balancing has become a critical issue in cl...

Handwritten Character Recognition is most challenging area of research, in which for various aspects a little enhancement can be always achieved. It is due to the irregularity of writing and shapes of different class user's orientation affects the recognition rate. In this paper we have taken the complexity of Odia handwritten character recognition...

In this current digital age of world, character recognition (CR) has been done through various machine learning algorithms. And it considered to be one the most challenging segment of pattern recognition. In addition to the above context, offline handwritten character is the most challenging one as compared with the printed one. Despite various alg...

Offline handwritten recognition system for Odia characters has received attention in the last few years. Although the recent research showed that there has been lots of work reported in different language, there is limited research carried out in Odia character recognition. Most of Odia characters are round in nature, similar in orientation and siz...

Cloud computing is a jargon in the era of information technology. It acts as a metaphor for the internet. Still, it possesses several challenges related to automated resource provisioning, security, event content dissemination, server consolidation, virtual machine migration. Load balancing is one of the critical challenges in the cloud that are fa...

The main idea of Optical Character Recognition system is to have a good level of recognition rate and that must be in robust in nature. OCR has created a great impact in terms of huge application in this era of digitalization world. To obtain a well-defined recognition system one must have to adopt a robust feature extraction procedure along with g...

Background In the past decades, handwritten character recognition has received considerable attention from researchers across the globe because of its wide range of applications in daily life. From the literature, it has been observed that there is limited study on various handwritten Indian scripts and Odia is one of them. We revised some of the p...

Optical Character Recognition is one of the most interesting and highly motivated areas of research, which has been very much ap-preciated in different aspect to the area of digitations world. Here in this paper we have suggested a probabilistic approach for develop-ing recognition system for handwritten Odia numerals. To report a good level of rec...

Cloud computing is gaining more popularity due to its advantages over conventional computing. It offers utility based services to subscribers on demand basis. Cloud hosts a variety of web applications and provides services on the pay-per-use basis. As the users are increasing in the cloud system, the load balancing has become a critical issue in cl...

Optical character recognition (OCR) is one of the most popular and challenging topic of pattern recognition with a wide range of applications in various fields. This paper proposes an OCR system for Odia scripts which comprises of three stages, namely preprocessing, feature extraction, and classification. In the preprocessing stage, we have employe...

Recognition system to various scripts was very much challenging and fascinating in this digital world. This character recognition has vast number of application in the current scenario of the digital world. Character Recognition with respect printed, handwritten and degrades characters of different zonal languages comes under Indian regional script...

Solar energy is going to play a measure role in the future global energy supply. Its acceptance has already been on rise in developing countries like India, where there is acute shortage of energy due to economic and other climatic reasons. Forecasting or predicting the future output of solar energy is a much needed step to integrate high insolatio...

Automation of handwritten character recognition is one of the challenging tasks in the problem domain of document analysis. However various writing style in orientation, shape and size are the key factor which affects the offline recognition system of Indian scripts. Here we have used a set of symmetry axes which are perceptually uniquely represent...

Prediction of solar radiation data using different soft computing approaches like Multi layer Perceptron (MLP), Artificial Neuro Fuzzy Inference System (ANFIS), and Radial Basis Function (RBF) for East coast region of India has been presented in this paper. Based on the input data like sunshine duration, temperature and humidity for the period of 1...

Cloud computing is gaining more popularity due to its advantages over conventional computing. It offers utility based services to subscribers on demand basis. Cloud hosts a variety of web applications and provides services on the pay-per-use basis. As the users are increasing in the cloud system, the load balancing has become a critical issue. Sche...

The paper presents prediction of solar radiation data of Bhubaneswar by using least square support vector machine. We used the least squares support vector machine (LS-SVM) based algorithm to predict the monthly average solar radiation of Bhubaneswar based upon the input parameters sunshine duration and temperature. A Gaussian Radial Basis F...

This article provide maximum preventive control, high performance and fault tolerance at an optimal resources, cost, time with high availability and quality of services to be invested into dynamic security mechanisms deciding on the measure component of real time operating system resources (Shell, File, Memory, Processor, Kernel, Encryption key, I/...

Solar radiation data plays a crucial role in solar energy research and application. It provides the vital information about the energy that strikes the earth and is highly useful for modeling and design of solar thermal technologies and solar photovoltaic applications. As Conventional energy sources are depleting day by day, it becomes necessary to...

Character recognition is one of the most interesting and challenging research areas in the field of image processing. The recognition rate of handwritten character is still limited due to the presence of large variety of shape, scale and format in hand written characters. A sophisticated handwritten character recognition system demands a better fea...

Load balancing is one of the major issue in cloud computing. Load balancing helps in achieving maximum resource utilization and user satisfaction. This mechanism transparently transfer load from heavily loaded process to under loaded process. In this paper we have proposed a hybrid technique for solving task assignment problem in cloud platform. PS...

Clustering is the unsupervised classification of patterns which has been addressed in many contexts and by researchers in many disciplines. Fuzzy clustering is recommended than crisp clustering when the boundaries among the clusters are vague and uncertain. Popular clustering algorithms are K-means, K-medoids, Hierarchical Clustering, fuzzy-c-means...

Solar energy is regarded as the most vital non conventional energy sources among all fossil fuels. For the purpose of modeling of solar energy conversion device solar radiation data is most essential. Hence, accurate measurement or prediction of solar radiation data is important for a particular location. The proposed system uses a Nonlinear Autore...

The access control is a mechanism that a system grants, revoke the right to access the object. The subject and object can able to integrate, synchronize, communicate and optimize through read, write and execute over a UFS. The access control mechanism is the process of mediating each and every request to system resources, application and data maint...

Control and risk are the two parts of the coin. Risk assessment is the process of identifying uncertainties, vulnerabilities and threats to the operating system resources in order to achieve business objectives. Risk evaluation involved deciding what counter measures to take in reducing uncertainty to the lowest level of risk. Control is probably t...

The automated access control mechanism afforded to an automated system control in order to attain the maximum objectives of preserving the confidentiality, integrity, authentication & high availability of information system resources. The risk optimization is the process of identifying vulnerabilities, risk, uncertainties and threats to operating s...

In this paper, a Neural Network (NN) based approach for classification of images represented by translation, scale and rotation-invariant features is presented. The utilized network is a multi-layer perception (MLP) classifier with one hidden layer. The back-propagation learning is used for its training. The translation and scale invariant feautres...

The access control is a mechanism that a system grants, revoke the right to access the object. The subject and object can able to integrate, synchronize, communicate and optimize through read, write and execute over a UFS. The access control mechanism is the process of mediating each and every request to system resources, application and data maint...

Control and risk are the two parts of the coin. Risk assessment is the process of identifying uncertainties, vulnerabilities and threats to the operating system resources in order to achieve business objectives. Risk evaluation involved deciding what counter measures to take in reducing uncertainty to the lowest level of risk. Control is probably t...

Parallel algorithms for solving any image processing task is a highly demanded approach in the modern world. Cellular Automata (CA) are the most common and simple models of parallel computation. So, CA has been successfully used in the domain of image processing for the last couple of years. This paper provides a survey of available literatures of...

The reliability engineering is the high utilization of system Product (i.e. Processor, Memory, File, Sh, K & Encryption key) Services, Business and Resources at minimal cost. The Real Time Operating System providing highest services at optimal cost and time. The reliability engineering provides the maximum performance, accountability, reliability,...

The access control mechanism is one of the well advance controls for all the time on every time on recent pervasive computing for protection of data and services from the hacker, thefts and unauthorized users. This paper contributes to the development of an optimization model that aims to determine the optimal cost to be implementing into DOOS secu...

This virtual programming language is a primary method of improving the performance and protecting system resources in around the clock on anywhere and anytime platform. This proposed article is contributes to the development of an optimal method that aims to determine the minimal cost and time to be invested into secure and robust computing in righ...

The value engineering is the umbrella of the many more sub-system like quality assurance, quality control, quality function design and development for manufacturability. The system engineering & value engineering is two part of the coin. The value engineering is the high level of technology management for every aspect of engineering fields. The val...

The preventive control is the one of the best and well advanced control in all aspects of day to day life. The prevention afforded to an automated system control system in order to attain the highest applicable objectives of preserving the confidentiality, integrity and high availability of information system resources (including hardware, system s...

There are a number of approaches, which have been developed and are still in process of development, to regulate and frame the data transfer to/from the servers or storage base. The developers are still facing number of difficulties in terms of time required in fetching or storing the data in remotely located servers during the development (coding...

This paper presents application of yet one more optimization technique based on evolutionary computation approach to locate the optimal values of the coefficients of terms of polynomial equations which is developed to classify the unknown dataset. A recent optimization technique known as Teaching Learning Based Optimization (TLBO) is used here for...

Mining frequent pattern from spatial databases systems has always remained a challenge for researchers. However, the performance of SQL based spatial data mining is known to fall behind specialized implementation since the prohibitive nature of the cost associated with extracting knowledge, and the lack of suitable declarative query language suppor...

This paper studies the applicability of hybridization of Differential Evolution (DE) and PSO techniques to data clustering problem. A new way of integrating DE and PSO is explored in the paper. In one approach, a parallel DE and PSO developed and in other, a transitional approach of alternate DE and PSO technique followed. Simulations for number of...

A low pass filter using defected ground with multiple numbers of scaled down complementary split ring resonators (CSSR) structures of a micro strip line is designed.The introduction of CSSR unit results in interesting filtering characteristics, like very high attenuation rate, couple of the dimension dependent finite attenuation poles and a very lo...

Cluster detection in Spatial Databases is an important task for discovery of knowledge in spatial databases and in this domain density based clustering algorithms are very effective. Density Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm effectively manages to detect clusters of arbitrary shape with noise, but it fails in de...

Recently, a concept of wireless sensor networks has attracted much attention due to its wide-range of potential applications. Wireless sensor networks also pose a number of challenging optimization problems. One of the fundamental problems in sensor networks is the coverage problem, which reflects the quality of service that can be provided by a pa...

Detection of clusters in Spatial Databases is a major task for knowledge discovery. Density based clustering algorithms plays a major role in this domain. DBSCAN algorithm effectively manages to detect clusters of any arbitrary shape with noise, but it fails to detect local clusters. DDSC and LDBSCAN does manages to detect local clusters effectivel...

Spatial Data Mining is based on correlation of spatial objects in space. Mining frequent pattern fromspatial databases systems has always remained a challenge for researchers. In the light of the first law ofgeography “everything is related to everything else but nearby things is more related than distant things”suggests that values taken from samp...

In this paper, Optical Back Propagation and Levenberg Marquardt (LM) algorithms are used for Pattern Recognition. These two algorithms are compared with Classical Back Propagation algorithm with varying Learning rate and Momentum .The simulation results are obtained and are shown in different graphs. The corresponding simulation results show the ef...

Wireless sensor networks illustrate enormous potential for increasing the information availability to people in numerous applications like military application, agriculture, smart buildings, health care, and environmental studies. Sensor network nodes are spreaded over specific area with limited battery energy, low computational capacity and restri...

This paper presents a design for map reading based on Corner Stitching for handling the spatial data. Corner Stitching is a technique for representing the rectangular two dimensional objects. It is a technique initially used in VLSI layout editing systems. GIS systems store spatial data using rectangular objects. The concept of corner stitching has...

Sensor network nodes are spreaded over specific area with limited battery energy, low computational capacity and restricted communication bandwidth. In Sensor networks, the cluster-based routing algorithms are used to reduce the energy consumption of nodes and prolong the network lifetime. In most cluster-based algorithms, a predefined number of cl...

Present data sharing and integration among collaborating organizations requires a central and trusted authority to check the users' requests before allowing the request to pass to the centralized repository to collect data from all data sources and integrate the collected data. Heterogeneity and dynamic nature of ubiquitous computing environments m...

This paper proposes a novel control scheme for channel equalization for wireless communication system. The proposed scheme considers channel equalization as a classification problem. For efficient solution of the problem, this paper makes use of a neural network working on Algebraic Perceptron (AP) algorithm as a classifier. Also, this paper introd...

Spatial Data Warehouses (SDWs) combine spatial databases (SDBs) and data warehouses (DWs) allowing analysis of historical data. This data can be queried using Spatial On-Line Analytical Processing (SOLAP). SDW and SOLAP systems are emerging areas that raise several research issues. In this paper, we refer to a different problem existing in SDWs tha...

Spatial databases (SDBs) are naturally distributed due to the data collection process, the distances between the geographical entities of interest, and the physical geographical boundaries. This calls for ways of interoperation among the distributed spatial databases. In order for the interoperability among distributed spatial databases to be possi...

Association Rule Mining (ARM) is an important problem in spatial database system. Much effort has been devoted for developing algorithms for efficiently discovering relationship between objects in space. In this paper, we propose an enhancement of existing mining algorithm for efficiently mining frequent patterns for positive and negative spatial o...

Spatial Data Mining is based on correlation of spatial objects in space. Mining frequent pattern from spatial databases systems has always remained a challenge for researchers. In the light of the first law of geography " everything is related to everything else but nearby things is more related than distant things " suggests that values taken from...

One of the most vexing issues in design of a high-speed computer is the wide gap of access times between the memory and the disk. To solve this problem, static file access predictors have been used. In this paper, we propose dynamic file access predictors using neural networks to significantly improve upon the accuracy, success-per-reference, and e...

Recently Negative Association Rule Mining (NARM) has become a focus in the field of spatial data mining. Negative association rules are useful in data analysis to identify objects that conflict with each other or that complement each other. Much effort has been devoted for developing algorithms for efficiently discovering relation between objects i...

Data warehouses (DWs) and on-line analytical processing (OLAP) systems rely on a multidimensional model that includes dimensions and measures. Such model allows expressing users' requirements for supporting the decision-making process. Spatial related data has been used for a long time; however, spatial dimensions have not been fully exploited. To...

Neural Network is an effective tool in the field of pattern recognition. The neural network classifies the pattern from the training data and recognizes if the testing data holds that pattern. The classical Back propagation (BP) algorithm is generally used to train the neural network for its simplicity. The basic drawback of this algorithm is its u...

In this paper we propose an intelligent data processing engine for spatial data management. The spatial data management scheme is being applied to vehicular telematics system. In this paper we also propose the data model for database management of spatiotemporal resource information in centralized telematics system. The platform includes spatiotemp...

In this paper the Modified Probabilistic Neural Network (MPNN) is used for dealing with the problem of channel equalization. Some improvements are suggested for the MPNN so that it is more suitable for the current problem. Firstly, the MPNN is extended to process complex signals. Secondly, a stochastic gradient adaptation technique is proposed, suc...

In this paper we propose an algorithm for taxi telematics system. The paper shows how the central call server, call customer, and an empty taxi co-ordinate with one another. With this algorithm, the central call server works efficiently in response to the customer call as well as for an empty taxi. Location history data is required for the central...

Estimating geographic information from an image is an excellent, difficult high-level computer vision problem whose time has come. The emergence of vast amounts of geographically calibrated image data is a great reason for computer vision to start looking globally on the scale of the entire planet. In this paper, we propose a correlated association...

As the World Wide Web is growing rapidly and data in the present day scenario is stored in a distributed manner. The need to develop a search engine based architectural model for people to search through the Web. Broad Web search engines as well as many more specialized search tools rely on Web crawlers to acquire large collections of pages for ind...

This paper presents a design for map reading based on Corner Stitching for handling the spatial data. Corner Stitching is a technique for representing the rectangular two dimensional objects. It is a technique initially used in VLSI layout editing systems. GIS systems store spatial data using rectangular objects. The concept of corner stitching has...

In existing speech coding systems, all Quantizer Code Books are designed to suit the statistical and perceptual characteristics of speech signals of a population of speakers. However, an individual's speech signal does not exhibit, even over a long time, the entire range of characteristics of the population. With the advent of the personal communic...

A neural network (NN) based approach for classification of images which are invariant to translation, scale and rotation is presented. The utilized network is a probabilistic neural network (PNN) classifier. The translation and scale invariant features are obtained by Fourier-modified direct Mellin transform (F-MDMT) method. The rotation invariance...

Emergence of data mining methods in data representation has resulted in discovering knowledge from large database systems. Efficient algorithms to mine frequent patterns are crucial to many tasks in spatial association rule mining. A promising approach for mining such spatial frequent pattern is mining frequent sub-patterns which are closed and max...

Emergence of vast amounts of geographically calibrated image data is an estimation of geographic information of an image. Extracting information from images has always been considered to be complex as it depends upon the type and nature of the image and data existing in it. In this paper we apply traditional Colour Filter Array (CFA) approach to ca...