Leveraging Big Data for Enhanced Business Values

In today’s age of globalization and internalization, precise and meaningful data plays a fundamental role in making crucial decisions across every strata of business, whether it is associated with human resource or sales or production or marketing or for any other field. For example, Apple, Facebook, Twitters and others know the next emerging trend in the market and transmute its strategies to adapt to the recent trends. All these multi-billionaire giants have the power of analysing the myriad of data flowing in from sundry of sources like social media, market trends, past annals and lot more. They are all accoutred with the most-indispensable tool in current globalized economy, “The BIG DATA." It refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyse. With the advent of Big Data, the business houses now can capture various trends in the market with minimal cost incurred. It had helped individuals as well as the organization to make proper decisions and increase the base of their operations by targeting the apt customers for the business. Big Data is playing a pivotal role in transfiguring the business decisions. On the other side, there are numerous challenges presented by the ‘Big Data," like security and privacy issues, infrastructure failure, and others. Thus, this paper presents the concept of Big Data, opportunities derived by companies using cases, and challenges related to Big Data. Since, Big Data is in its embryological phase; this paper will provide a snapshot to the scholar for future research in this field.

Design of Multicarrier Broadband Power Line Communication System for Tanzania Homes

Broadband Power Line Communication (BPLC) is a method of providing broadband internet access to consumers using High Frequency (HF) radio signals coupled into the mains power wiring. In the BPLC system, data signals are modulated at HF and injected into the power lines using broadband modulation techniques. Design of a BPLC system requires a complete understanding of the Power line network (PLN) topologies involved. PLN can be classified as Indoor or In-home, Low voltage, Medium voltage and High voltage respectively. In this study four maps representing typical Tanzania houses were selected randomly, and then four indoor power-line networks were derived from their circuit diagrams. The Impulse response was estimated at the switch sockets using the recent power-line channel model by Anatory et al. The delay spread estimated from the impulse response was used to design the OFDM system and the OFDM system performance was evaluated. General Terms Indoor Power Line Communications, Anatory et. al.

Robust and Secured Image Watermarking using DWT and Encryption with QR Codes

Phylogenetic Tree Generation using Different Scoring Methods

Data Mining is a branch of knowledge discovery in the field of research and development. The biological data is available in different formats and is comparatively more complex. Knowledge discovery from these large and complex databases is the key problem of this era. Data mining and machine learning techniques are needed which can scale to the size of the problems and can be customized to the application of biology. Hierarchical Clustering is the one of the main techniques for data mining. Phylogeny is the evolutionary history for a set of evolutionary related species. One approach on determining the evolutionary histories of a dataset are scoring based methods. There are number of different distance based methods of which two are details with here: the UPGMA (Unweighted Pair Group Method using Arithmetic average) and Neighbor Joining. A method for construction of distance based phylogenetic tree using hierarchical clustering is proposed and implemented on different rice varieties. The sequences are downloaded from NCBI databank. Evolutionary distances are calculated using jukes cantor distance method. Multiple sequence alignment is applied on different datasets. Trees are constructed for different datasets from available data using both the distance based methods and pruning technique. SNAP calculates synonymous and nonsynonymous substitution rates based on a set of codon aligned nucleotide sequences. The DNA Multiple sequences to calculate the GC content of eukaryotes, molecular weight, melting temperature and tree information. Extractions of closely related varieties are performed by applying threshold condition. Then, final tree is constructed using these closely related rice varieties.

A Hybrid Clustering Approach using Artificial Bee Colony (ABC) and Particle Swarm Optimization

Performance Evaluation of Improved Skew Detection and Correction using FFT and Median Filtering

Design of 0. 13um CMOS Two Stage Low Noise Amplifier

A Low Noise amplifier is one of the most commonly used components in analog and digital circuit designs. Low voltage and low power Low Noise amplifier design has become an increasingly interesting subject as many applications switch to portable battery powered operations. An electronic amplifier is an electronic device that increases the power of a signal. This design techniques is needed to allow amplifiers to maintain an acceptable level of performance when the supply voltages are decreased is immense for maintain low noise with high gain. The low-noise amplifier is a special type of electronic amplifier used to amplify very weak signals captured by an antenna. This paper presents a technique for substantially reducing the noise of a CMOS low noise amplifier implemented in the cascade inductive source degeneration topology. This 2.4 GHz Two Stage CMOS 130nm RF Low Noise Amplifier is optimize for low noise at low current with very low power consumption. In this proposed design work the two stage cascade low noise amplifier is used to achieve noise 28 dB, input return loss of >10 and output return loss of > -10 at 1.3 supply voltage.

Genetic Algorithm based Approach to Solve Non Fractional (0/1) Knapsack Optimization Problem

this paper we solve the non fractional knapsack problem also known as 0-1 knapsack using genetic algorithm. The usual approaches are greedy method and dynamic programming. Its an optimization problem where we try to maximize the values that can be put into a knapsack under the constraint of its weight. We solve the problem using genetic algorithm in matlab using gatool. In this research work different selection schemes have been used like roulette wheel, tournament selection, Stochastic selection etc. Following the introduction of genetic algorithm and knapsack problem, formulation of 0-1 knapsack problem in genetic algorithm is presented. Experimental results using various selection schemes have been analyzed and comparison of genetic algorithm technique is done with greedy method and dynamic programming optimizing techniques.

Strategical Comparison: Recognizing and Evicting Sybil Attack in Vehicular Ad Hoc Networks

A Comparative Analysis of Clustering Algorithms

Clustering is a process of grouping a set of similar data objects within the same group based on similarity criteria (i.e. based on a set of attributes). There are many clustering algorithms. The objective of this paper is to perform a comparative analysis of four clustering algorithms namely Kmeans algorithm, Hierarchical algorithm, Expectation and maximization algorithm and Density based algorithm. These algorithms are compared in terms of efficiency and accuracy, using WEKA tool. The data for clustering is used in normalized and as well as unnormalized format. In terms of efficiency and accuracy K-means produces better results as compared to other algorithms.