Global Journal of Computer Science and Technology (GJCST)
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Modified Multi-Wavelet Noise Filtering Algorithm for Mammographic Image Denoising Using Recurrent Neural Network
Get PDFThe digital mammographic images are affected by several types of noises which require filters to denoise the noise level. This will help the medical practitioner to enhance the image quality of the mammograms and helps them in giving accurate diagnosis. There are so many works on image denoising technique but there are not much which gives emphasis on the mammographic images. . In application point of view medical images are classified as Multispectral Image (used for satellite surveillance), RGB standard colour scheme Image or other digital versions of the film image i.e., in our case its mammographic image. For every image type it requires different approach for denoising because in each type of image, it contains different factors in it. In denoising the mammographic image , the filtering technique that is to be applied depend on its noises at each resolution level of the microns to make the micro-classification of the cancerous tissues to that of the bright water dense patches caused by the calcium salts in the mammary glands. Thus, any single algorithm cannot provide similar performance range for different types of noise because not every method is effective for the scenario of mammographic image denoising. In the given study we have shown a method for the mammographic image denoising which is having higher accuracy and the performance range is suited for denoising applications.raphic image denoisin
Improving the Performance of the Distributed File System through Anticipated Parallel Processing
Get PDFIn the emerging Big Data scenario, distributed File systems (DFSs) are used for storing and accessing information in a scalable manner. Many cloud computing systems use DFS as the main storage component. The Big Data applications de-ployed in cloud computing systems more frequently perform read operations and less frequently the write operations. So, improving the performance of read access has become an im-portant research issue in DFS. In the literature, many client side caching with appropriate pre fetching techniques are proposed for improving the performance read access in the DFS. A speculation-based approach which uses client side caching is also proposed in the literature for improving the performance of read access in the DFS. In this paper, we have proposed a new read algorithm for the DFS based on anticipated parallel processing. We have evaluated the per- formance of the proposed algorithm using mathematical and simulation methods and the results indicate that the pro-posed algorithm performs better than the speculation-based algorithm proposed in the literature
Public AOriented Personalized Health Care Platform based on web service
Get PDFIn this paper, we are using web service technologies in order to store data and also giving guideline line to people ,and that information is very confidentiality of patient data. Web service is playing a vital role in present scenario. Now days we are seeing web service have a more importance and so many technologies are existing .But in this paper we are using SOA and WSC. SO A means service oriented architecture which makes a communication between the two service and simple pass the data. WSC which means web service coordination which distributed the application actions. The main aim health care application development but health care industry is lagging behind other sectors
A Nobel Approach to Retrieveactual Image from a Compressedoneby using Dequantisation Technique
Get PDFImage Compression addresses the problem of reducing the amount of data required to represent the digital image. Image compression and decompression are very popular processes in image processing. Image compression is a way in which the data to be transmitted are compressed into a smaller version and then transmitted. Compression is achieved by the removal of one or more of three basic data redundancies: (1) Coding redundancy, which is present when less than optimal (i.e. the smallest length) code words are used; (2) Interpixel redundancy, which results from correlations between the pixels of an imag
Secure On-Line Transaction through Augmented Biometrics System
Get PDFInternet and its facilities facilitate on-line shopping by allowing shoppers to browse the online stores and obtain their needs with minimum effort. This is not possible with familiar traditional system of buying and selling. This advantage offered by the internet is restricted by issue arising from on-line security and payment systems. Although research has been conducted and several approaches have been devised to reduce this restriction but there is need for further improvement. As a result, this research work proposes a new solution that combines biometrics technology (Finger Print) together with (password) to provide secure on line transaction through multiple factors security solution. It makes, verifying process and verification for shopper2019;s identity more secured by recognize individual based on measurable biological characteristics (Fingerprint) and provision of a link to identify the authorized user, this minimizes frauds. This addresses and reduced the security problems that are associated with existing on line transaction and e-payments. The design was implemented using Visual Basic.Net and SQL because of their supports for implementing web-based security systems. Samples of (130) on line shoppers were used for this research work to capture fingerprints from index and thumb fingers of left and right hands, also the attitudes of the customers in terms of password selection and management
QFSRD: Orthogenesis Evolution based Genetic Algorithm for QoS Fitness Scope aware Route Discovery in Ad hoc Networks
Get PDFHere in this paper we devised a novel orthogenesis evolution based GA technique for QoS fitness scope aware routing in Mobile Ad hoc Networks. The past decade research towards route discovery strategies for mobile ad hoc networks is continuing with magnitude speed. However, the majority of the routing solutions devised in past are dealing only with the optimality of the data transmission. QoS aware hop level connections in a given rute are not supported with the desired frequency. Hence the QoS aware routing in mobile ad hoc networks is grabbing the attention of many researchers as this domain is on the hot edge of the current research
A Modified Version of the K-means Clustering Algorithm
Get PDFClustering is a technique in data mining which divides given data set into small clusters based on their similarity. K-means clustering algorithm is a popular, unsupervised and iterative clustering algorithm which divides given dataset into k clusters. But there are some drawbacks of traditional k-means clustering algorithm such as it takes more time to run as it has to calculate distance between each data object and all centroids in each iteration. Accuracy of final clustering result is mainly depends on correctness of the initial centroids, which are selected randomly. This paper proposes a methodology which finds better initial centroids further this method is combined with existing improved method for assigning data objects to clusters which requires two simple data structures to store information about each iteration, which is to be used in the next iteration. Proposed algorithm is compared in terms of time and accuracy with traditional k-means clustering algorithm as well as with a popular improved k-means clustering algorithm
A New Approach to Adaptive Neuro-fuzzy Modeling using Kernel based Clustering
Get PDFData clustering is a well known technique for fuzzy model identification or fuzzy modelling for apprehending the system behavior in the form of fuzzy if-then rules based on experimental data Fuzzy c- Means FCM clustering and subtractive clustering SC are efficient techniques for fuzzy rule extraction in fuzzy modeling of Adaptive Neuro-fuzzy Inference System ANFIS In this paper we have employed a novel technique to build the rule base of ANFIS based on the kernel based variants of these two clustering techniques which have shown better clustering accuracy In kernel based clustering approach the kernel functions are used to calculate the distance measure between the data points during clustering which enables to map the data to a higher dimensional space This generalization makes data set more distinctly separable which results in more accurate cluster centers and therefore a more precise rule base for the ANFIS can be constructed which increases the prediction performance of the system The performance analysis of ANFIS models built using kernel based FCM and kernel based SC has been done on three business prediction problems viz sales forecasting stock price prediction and qualitative bankruptcy prediction A performance comparison with the ANFIS models based on conventional SC and FCM clustering for each of these forecasting problems has been provided and discusse
Fuel Your Growth with Integration: Hybrid Cloud Computing
Get PDFCurrent IT services were built to serve a static and functionally concrete operating replica In future prospects IT needs to become much more dynamically adaptable to maintain pace with the speed of business today However when cloud is considered in the context of a hybrid model of combining both the on-premise with Internet-services then the value of the cloud in its broadest definition becomes incredibly empowering 1 2 Hybrid solutions combine the benefits of public cloud infrastructure speed and agility of development with private cloud resources security and control In this paper we have given the power of Hybrid Cloud Computin
Character Education Development Model-based E-Learning and Multiple Intelegency in Childhood in Central Java
Get PDFKusumandari et al 2015 Character Education Development Model-Based E-Learning and Multiple Intelegency In Childhood In Central Java Competitive Research Grant Faculty of Education Semarang State Universit