Miracle-dz/UniFAR-FTUs huggingface dataset:
PROCURE DATA CENTRE SHARING SCHEME IN VIRTUAL CLOUD ENVIRONMENT USING CLOUDSIM

-Procure Data Centre (PDC) is a coming forth patient data-centric framework of data interchange, large scale data centric applications. In which the data is been outsourced to be stored to general IT providers, such as cloud providers and how to assure their private data while being stored in the cloud servers. To secure the information govern over entree to their own file, it is a hopeful method to encrypt file and personal information before outwards. Yet, effects such as danger of privacy view, measurability in key management, compromising entree and efficient user revocation, have continued the most significant disputes accomplishing fine-grained, cryptographically imposed information entree assure. In this thesis, propose a new data centric role model and a suit of method for information access control to personal profiles put in half-believed servers. To reached close–grained and measurable information entree assure for PDC’s, and gained Distributed Multi Authority-Attribute Based Encryption (DMA-ABE) method to generation cipher text of data through for encrypt each data file. Different from past works in assure information outsourcing, focus on the more than one data proprietor security script, and split the users in the PDC scheme into multiple assured area that heavily shrinks the key management complexity for proprietors and consumers. A peak of data privacy is ensured at the same time by working distributed multi-authority ABE. In this scheme also enables dynamic alteration of access policies or file attribute, confirms efficient availability of data that can be needed by users/attribute revocation. Evaluating the performance of Cloud provisioning policies, application workload models, and resources performance models in a repeatable manner under varying system and user configurations and requirements is difficult to achieve. To overcome this challenge, propose CloudSim: an extensible simulation toolkit that enables modeling and simulation of Cloud computing systems and application provisioning environments. The CloudSim toolkit supports both system and behavior modeling of Cloud system components such as Data Centres, Virtual Machines (VMs). The implementation of proposed algorithm is performed by using CloudSim3.0. 1 simulator.
Exploring GAPIT Package Features with Simulated Genomic Data

: The agronomic information process in the genetics prospect currently presents voluminous data, which necessitates the continuous development of innovative and quality statistical methods that meet the Big Data era in which much is being reestablished in the form of generating, analyzing and absorbing data. The R language is an efficient tool for these types of analyzes and allows some structures and functionalities, such as the GAPIT package
Design of Chaos Based Turbo Systems in Fading Channel

: The increasing growth for widespread wireless communication system demands stronger coding scheme to reduce the signal deterioration during its transmission, generally without facilitating to the expensive hardware materials. Turbo code is a forward error correcting code. It mainly consists of RSC encoder, an interleaver in the encoder part and SISO module used in decoder part. The code performance is mainly based on design of an interleaver. The encoder uses multi tent map and inverse multi tent map structure for generating chaotic like samples. The chaotic sequence corresponds to the dynamics of tent map and they are used in engineering applications. For chaos based Turbo decoding, maximum a posteriori algorithm also known as BCJR algorithm, which is based on trellis coded estimation algorithm. It uses SISO module, is a soft decision decoder it performs the decoding operation in an iterative scheme.
A Comparative Analysis of Proactive and Reactive Routing Protocols over NS3 in VANET

-There is a massive use of vehicles now days. Due to this road safety is a major concern for the society. Vehicular Ad-Hoc Network (VANET) is a wireless ad hoc network formed by moving vehicles with each other or with the road side units (RSU). The network is formed to transfer safety and Infotainment messages between nodes (Vehicles and RSU). That means the nodes share different kind of information such as safety information for the prevention of road accidents, traffic related information such as traffic jams and entertainment service information. Message transfer is the responsibility of the routing protocol in the network. Routing of data in VANET is a challenging area due to fast speed of nodes and dynamic topology. VANET is a subset of MANET where some features are distinct. The protocols can be categorised in proactive and reactive protocols based on topology. The performance of these routing protocols can vary with the change in different parameters such as vehicle speed, traffic conditions and node density. In this paper we have analysed the performance of protocols such as OLSR, AODV and DSDV has been tested in terms of packet delivery and end to end delay under TCP connection using NS3 simulator.
Audit Quality and Earnings Management among Nigerian Listed Deposit Money Banks

In recent times, the call for reliable financial reporting has gained prominence in Nigeria and global economy at large. The capability or incapability of banks to effectively fulfill intermediate mandate has been the crux of many financial crises. Mediating between the surplus and deficit units within the economy expedites distribution of national savings, thereby improving investments and national output. In 2005, the Central Bank of Nigeria mandated every Nigerian bank to increase capital base from 2 billion naira to 25 Billion Naira in order to enhance competitiveness in the international market. Noteworthy capital market expectations were raised and banks were under pressure to achieve survival and generate higher returns to shareholders. This pressure from the Central Bank of Nigeria has occasioned banks falsifying accounts, inflating earnings and capital. The need for reliable reports has led to statutory audit that provides independent authentication of financial statements prepared by banks’ directors.
Performance Evaluation Of Topology Based Routing Protocols In VANET

Vehicular Ad Hoc Network (VANET) is a sub class of mobile ad hoc networks. VANET provides wireless communication among vehicles and vehicle to road side equipments. The communication between vehicles is used for safety, comfort and for entertainment as well. The performance of communication depends on how better the routing takes place in the network. Routing of data depends on the routing protocols being used in network. In this study we investigated about different ad hoc routing protocols for VANET. The main aim of our study is to identify which ad hoc routing method has better performance in highly mobile environment of VANET. To measure the performance of routing protocols in VANET, we considered three different scenarios i.e. low, medium and higher density vehicular ad hoc scenario. Routing protocols were selected carefully after carrying out literature review. The selected protocols are then evaluated through simulation in terms of performance metrics i.e. throughput and packet drop. After simulation results, we used excel to plot the graph to compare the results of selected routing protocols with each other. From results of performance metrics in different environments of VANET, we realized that topology based routing method of VANET shows significant results towards the considered performance metrics. However, it is hard to provide any universal routing protocol that can deal with all the various environments of VANET. The selection of a single routing protocol is hard in VANET because the protocol performance depends on vehicle speed, driving environment etc. That may vary from one environment of network to another.
Experimental Observations of Ideal Binary Mask for CASA based Systems

: Sound is a primary form of communication between human beings. By various ways the information is received from the outside world or to communicate with each other. Three most important sources of information are speech, images and written text. Speech not only conveys linguistic contents, but also communicates other useful information like the mood of the speaker, emotions attached with persons etc. the question is how to train the machines to understand the speaker, identifying the emotions attached with the persons etc. Human hearing system posses this property of suppressing the unwanted signal like voice or speech and concentrate on the wanted speech. To train the machines to understand the spoken speech it is necessary to train the machines to recognise the various sound sources and from them extracting sound of interest. In speech communication systems the quality and intelligibility of speech is most important for easy and accurate exchange of information. In realistic listening situations, speech is often contaminated by various types of background noise. The presence of background noise degrades the quality as well as intelligibility of speech. This degradation of speech by noise creates problems not only for just interpersonal communication but more serious problems in applications in which decision or control is made on the basis of speech signal. So, there is need to develop a new method for speech enhancement which will improve quality as well as intelligibility of the speech. This paper presents method of speech enhancement by using Ideal Binary Mask. This is a simple method for enhancing the speech with the objective to eliminate the additive noise present in speech signal and restore the speech signal to its original form with improved quality as well as intelligibility of speech. This paper will focus on Computational Auditory sense analysis to extract voice or speech of interest from interference
Cross Wavelet Transform Based Analysis of Electrocardiogram Signals

This paper presents a method for analysis of ECG patterns using Cross Wavelet Transform (XWT) and Wavelet Coherence (WCOH) techniques. The cross-correlation is the measure of similarity between two waveforms. The application of the Continuous Wavelet Transform to two time series and the cross examination of the two decomposition reveals localized similarities in time and scale. Morlet wavelet is used as the mother wavelet. A pathologically varying pattern in QT zone of inferior lead III shows the presence of Inferior Myocardial Infarction (IMI). The Cross Wavelet Transform and Wavelet Coherence is used for the cross examination of normal and abnormal (IMI) beats. A normal beat template is selected as the absolute normal pattern and the coherence between various other normal and abnormal is computed. The Wavelet cross spectrum and Wavelet coherence of various ECG patterns shows distinguishing characteristics over two specific regions R1 and R2, where R1 is the QRS complex area and R2 is the T wave region. These obtained results further opens scopes for extraction of appropriate parameter(s) for classification of normal and abnormal data.
FINGERPRINT MATCHING BASED ON STATISTICAL TEXTURE FEATURES

: Fingerprint is a reliable biometric which is used for personal verification. Three arithmetical features are extracted from fingerprint images and represented using a mathematical reproduction. These features are (1) an entropy coefficient, computed from the intensity histogram of the image, (2) a relationship coefficient, computed by correlation operation between the novel image and a filtered version of the image obtained using a 2D wiener filter, and (3) an energy coefficient, obtained by first subjecting the image to a 5-level wavelet decomposition and thereafter computing the proportion energy of the approximation coefficient obtained after the 5th level decomposition. Results show that fingerprint texture feature can be convincingly used for discrimination and for personal verification.
Image Fusion using Transformation & Edge Detection & Filtering

— Fusion of images is an important concept and can be used in a wide variety of applications, especially in the enhancement of images taken from satellites. Although there are various techniques through which images can be fused. Image Fusion is an integration of more than two images so that the invisible or blurred part of the images is visible in the resultant image. Guided filtering is a technique of filtering images so that the fused image is an enhanced image. But the technique implemented for the image fusion is not efficient in terms of fused ratio and the technique is not feasible for all type of images. Hence an efficient technique is implemented here which uses the concept of image enhancement using DWT and canny edge detection, after both the images gets enhanced the resultant images are fused to get the final fused image. The proposed technique implemented here is an efficient technique as compared to the existing technique of fusion using guided filtering. The proposed and the existing technique is applied on various datasets including Multiexposure dataset, Multimodal images dataset and Multifocus image datasets. The proposed technique gives efficient results as compared to the existing technique.
ACIR WITH IMAGE ANNOTATION BY LABEL CORRELATION AND VISUAL FEATURES TO IMPROVE THE RETRIEVAL ACCURACY

: Now a days the popularity of digital images increases due to the improving digital imaging technologies and convenient availability facilitated by the internet. So to find user intended images from large image dataset is very difficult. As a way to facilitate image categorization and retrieval, automatic image annotation has received much research attention. Considering that there are a great number of unlabelled images available, it is beneficial to develop an effective mechanism to leverage unlabelled images for large-scale image annotation. Meanwhile, a single image is usually associated with multiple labels, which are inherently correlated to each other improves the performance significantly. A straightforward method of image annotation is to decompose the problem into multiple independent single-label problems, but this ignores the underlying correlations among different labels. In this topic, to bridge the gap between high level semantic concept and low level image features well, we propose a new annotation & content based image retrieval (ACIR) system with image annotation by integrating label correlation and visual similarity mining into a joint framework to annotate the unlabelled images and interactive boosting algorithm to enhance the retrieval accuracy.
SECURE SHARING OF DATA AMONG GROUP OF USERS IN CLOUD

: According to the Standards, cloud computing is a new model to facilitate mobile and network access on on-demand requests from the pool of computing resources. When data sharing comes into picture, Data owner provides common key to the group members for accessing of data files. The problem with this technique is if data owner deny access rights of group member but that group members still has the data access key, the data owner need to re-encrypt the entire data with a new key, in order to make revoked member’s key useless. This makes computational over head for data owner to calculate key every time. So we propose a method proxy re-encryption which realizes authorization without on user’s private information.
Support Vector Machine Kernel Functions Performance Evaluation in Epileptic Seizure Detection from EEG

: Epilepsy is the fourth most common neurological disorder that affects almost 1% of the world population.Electroencephalogram contains significant amount of clinical information about epilepsy. Automatic epileptic seizure detection from electroencephalogram is one the most challenging task due to its unknown mechanism and patient specific epileptic pattern. Support vector machine based classifier have been used in several studies to classify epileptic activity from healthy brain activities. In this study, a relative performancesof Support Vector Machine Kernel Functionsare evaluated for epileptic seizure detection. Firstly, electroencephalogram segment is decomposed with empirical mode decomposition method to produce subband signals called intrinsic mode function. Later, two time-domain features Coefficient of Variation and Fluctuation Index are calculated for each subband which are combined to produce a feature vector to feed into the support vector machine classifier. To evaluate the performance of the classifier, the experiment is carried out with several kernel functions and assessing the performance with three statistical parameters called sensitivity, specificity and accuracy.
Comparative Study on Multi-Modal Topic Modeling with Dense block Detection

— There has been incredible growth of events over the internet in recent years. Google has become the giant source of knowledge for any event which has happened or happening over the internet. Some networking sites such as facebook, micro blogging sites such as twitter are evolved with time and became the highly used sites over the internet. Various E-commerce websites such as Amazon, Ebay, Flipkart etc are the widely used sites for online shopping. Above mentioned sites generates large amount of text data. In association with text data some images are also uploaded over the internet on these sites. The images associated with particular topic plays vital role for understanding the semantic relationship between the textual content and visual content which are related to images. To model this huge amount of data having both textual and visual contents multi-modal topic model is suggested in this paper. While dealing with multi-modality, study of semantic relationship between the images and text data is crucial part. This model also helps to study semantic relationship between them effectively. Topics which are trending, popular over the world can be seen on Social sites as well as micro blogging sites. In online shopping sites fake reviews, advertises, spam spreading information is posted. So to study this suspicious behavior dense suspicious block is also detected in this model. In this paper some and methods are presented and compared. The focus is to effectively model the textual and visual contents in multi-modal dataset having dense block for examining lockstep behaviors.
Design of Booth Multiplier using Double Gate MOSFET

Double gate MOSFET technology is used wherever low power delay product is desired. It uses to reduce leakage current drain induced barrier lowering effect (DIBL) and other short channel affects. In this work 8×8, Booth Multiplier is analysed in 90nm technology, with one single-gate MOSFET technology and then other using the proposed that is Double-Gate MOSFET technique. Depending on the input patterns, the proposed technique saves 24% in power consumption has observed in proposed circuit. Design and simulations are performed in cadence virtuoso and spectre tools using 90nm technology.
Randomly Amplified Polymorphic DNA Assay of Methicillin Resistant Staphylococcus aureus Isolated from Clinical Samples from Bengaluru, India

Staphylococcus aureus is an opportunistic pathogen that causes a nosocomial infections ranging from self-limiting to lifethreatening in both developing and developed countries (Deleo et al., 2010; Kennedy et al., 2009; Rehm, 2008; Franklin lowy, 2003). Due to its high clonal variability, S. aureus has the ability to develop a resistance towards common antibiotics by renovating their genomes through gene mutations or horizontal gene transfer (Kuroda et al., 2001). The incidence of Methicillin Resistant S. aureus (MRSA) varies from 25% to 50% in western and southern parts of India respectively (Patel et al., l2010; Joshi et al., 2013). The intrinsic resistance of S.aureus towards methicillin is due to expression of mecA gene, whose product is a 78-kDa protein called penicillin binding protein 2a (Shahkarami et al., 2014).
A HYBRID APPROACH FOR TEST CASE GENERATION

: Today, Software testing is an essential part of successful software development process. The input executes the program and produces the expected output. The outcome of the software product depends on software testing. Manual testing is difficult to produce expected output. The manual testing takes long time to test. The major problem in manual testing is code coverage is not done at regular interval. Many techniques are used to automatically produce inputs in recent years. The test suite generation method is used to produce test suites with high code coverage. We produce a hybrid approach which provides the methodology to improve coverage level of branches in code at regular intervals. The main objective of the proposed system is to increase the coverage level with minimum test suite in a short time. The hybrid approach combines two techniques for improving the accuracy of branch coverage. The test cases are generated by using EVOSUITE tool. Optimization technique is based on coverage level of branch statements.
Sentiment Analysis On Twitter Data

Now-a-days Millions of people are sharing their views daily on micro blogging sites, it contains short and simple expressions. In this paper, we will discuss about a perspective to extract the sentiment from a Twitter, where users post their opinions for everything. we are going to concentrate on twitter, which is a micro blogging site. Many people tweet their feeling on twitter. In this project , we are going to analyze the tweets made by people. And determine their happiness. We are going to do sentiment analysis on this twitter data. These messages or tweets are classified as positive, negative or neutral with respect to a expression. This is very useful for the companies who want to know the feedback about their product brands or the customers who want to search the recommendation from others about product before purchase. We will use natural language toolkit processing algorithms for classifying the sentiment of Twitter messages We are going to make a web based UI application. Which will show the data and crawl through live feeds.
INVESTIGATION OF ANTIBACTERIAL POTENTIAL OF ASCIDIAN, MICROCOSMUS EXASPERATUS (Heller, 1878) AGAINST HUMAN URINARY TRACT PATHOGENS

The current investigation is based on the discovery of novel antibacterial from new sources which have not been amply exploited. The main objectives of this work was to ascertain the antibacterial efficacy of a marine ascidian, Microcosmus exasperatus, collected from Palk Bay, Southeast coast of India, against selected urinary tract pathogens. The crude methanol extract was more active and exhibiting a broad spectrum antibacterial activity than the crude ethyl acetate extract against each of the bacterial strains tested. Maximum inhibition zone (10.0 ± 0.1 mm) was observed against the gram negative Pseudomonas aeruginosa in crude methanol extract. The consequent zone of 6.5 ± 0.1 mm was observed in ethyl acetate extract in P.aeruginosa.
TWO STEP TECHNIQUES FOR IMAGE COMPRESSION

The image compression is the technique which is applied to reduce size of the original image. The image compression can be classified into lossy and loss-less type of compressions. The WDR is the lossy type of compression in which unwanted pixels will be removed from the image. In this work, improvement in the WDR algorithm is been proposed using the algorithm of decision tree. The decision tree is constructed of according to the similarity between the pixels. The pixels which have least similarity with the other pixels will be removed from the image. The simulation is been performed in MATLAB and it is been analyzed that PSNR, MSE and compression ratio parameters are improved with the proposed technique.