A Survey of Non-Linear Filtering Techniques For Image Noise Removal

Image is captured or noninheritable by any image capturing device like camera or scanner and then it is stored in the mass storage of the computer system. In many of these applications the existence of impulsive noise among the noninheritable pictures is one altogether common problems. This noise is characterized by spots on the image and is usually related to the innate image because of errors in image sensors and information transmission. Now-a-days there are numerous strategies that are offered to remove noise from digital images. Most of the novel methodology includes 2 stages: the primary stage is to find the noise within the image and the second stage is to eliminate the noise from the image. This paper explores the varied novel methods for the removal of noise from the digital images. The distinctive feature of the all the described filters is that offers well line, edge and detail preservation performance while, at the constant time, effectively removing noise from the input image. In later section, we present a short introduction for various strategies for noise reduction in digital images

Solving kk-means on High-dimensional Big Data

In recent years, there have been major efforts to develop data stream algorithms that process inputs in one pass over the data with little memory requirement. For the $k$-means problem, this has led to the development of several $(1+\varepsilon)$-approximations (under the assumption that $k$ is a constant), but also to the design of algorithms that are extremely fast in practice and compute solutions of high accuracy. However, when not only the length of the stream is high but also the dimensionality of the input points, then current methods reach their limits. We propose two algorithms, piecy and piecy-mr that are based on the recently developed data stream algorithm BICO that can process high dimensional data in one pass and output a solution of high quality. While piecy is suited for high dimensional data with a medium number of points, piecy-mr is meant for high dimensional data that comes in a very long stream. We provide an extensive experimental study to evaluate piecy and piecy-mr that shows the strength of the new algorithms.Comment: 23 pages, 9 figures, published at the 14th International Symposium on Experimental Algorithms - SEA 201

A Survey on Touch Based Data Transfer Using Cloud

Currently, computer technology is completely based on touch screen technology. Any digital device users want to use touch screen technology for easier and faster way to accomplish their work. Transfer of data and keeping it secure is common issue in digital world, so to achieve different and great method for transferring of data, there is need to focus on simpler way to transfer any type of files between two digital devices. Need to provide users functionality to sharing of file over wireless network by using simple touch gesture as well as to provide secure and effective way of data sharing over cloud. In this paper basic techniques which are utilized for data sharing have been studied well and main objective is to provide easy, secure as well as attractive way for sharing of data between digital devices over cloud. This paper focuses on methodologies and primitives which are being used till now for data transfer system

From Sit-Forward to Lean-Back: Using a Mobile Device to Vary Interactive Pace

Although online, handheld, mobile computers offer new possibilities in searching and retrieving information on the go, the fast-paced, “sit -forward” style of interaction may not be appropriate for all user search needs. In this paper, we explore how a handheld computer can be used to enable interactive search experiences that vary in pace from fast and immediate through to reflective and delayed. We describe a system that asynchronously combines an offline handheld computer and an online desktop Personal Computer, and discuss some results of an initial user evaluation

Ward's Hierarchical Clustering Method: Clustering Criterion and Agglomerative Algorithm

The Ward error sum of squares hierarchical clustering method has been very widely used since its first description by Ward in a 1963 publication. It has also been generalized in various ways. However there are different interpretations in the literature and there are different implementations of the Ward agglomerative algorithm in commonly used software systems, including differing expressions of the agglomerative criterion. Our survey work and case studies will be useful for all those involved in developing software for data analysis using Ward's hierarchical clustering method.Comment: 20 pages, 21 citations, 4 figure

Defining the role of cellular immune signatures in diagnostic evaluation of suspected tuberculosis

BACKGROUND: Diagnosis of paucibacillary tuberculosis (TB) including extrapulmonary TB is a significant challenge, particularly in high-income, low-incidence settings. Measurement of Mycobacterium tuberculosis (Mtb)-specific cellular immune signatures by flow cytometry discriminates active TB from latent TB infection (LTBI) in case-control studies; however, their diagnostic accuracy and clinical utility in routine clinical practice is unknown. METHODS: Using a nested case-control study design within a prospective multicenter cohort of patients presenting with suspected TB in England, we assessed diagnostic accuracy of signatures in 134 patients who tested interferon-gamma release assay (IGRA)-positive and had final diagnoses of TB or non-TB diseases with coincident LTBI. Cellular signatures were measured using flow cytometry. RESULTS: All signatures performed less well than previously reported. Only signatures incorporating measurement of phenotypic markers on functional Mtb-specific CD4 T cells discriminated active TB from non-TB diseases with LTBI. The signatures measuring HLA-DR+IFNγ + CD4 T cells and CD45RA-CCR7-CD127- IFNγ -IL-2-TNFα + CD4 T cells performed best with 95% positive predictive value (95% confidence interval, 90-97) in the clinically challenging subpopulation of IGRA-positive but acid-fast bacillus (AFB) smear-negative TB suspects. CONCLUSIONS: Two cellular immune signatures could improve and accelerate diagnosis in the challenging group of patients who are IGRA-positive, AFB smear-negative, and have paucibacillary TB

International Journal of Advances in Engineering Research NEW REGIME FOR THE SYNCHRONIZATION OF TIMINGS IN WIRELESS SENSOR NETWORK

ABSTRAC

A Survey on Unusual Event Detection in Videos

As the usage of CCTV cameras in outdoor and indoor locations has increased significantly, one needs to design a system to detect the unusual events, at the time of its occurrence. Computer vision is used for Human Action recognition, which has been widely implemented in the systems, but unusual event detection is lately entering into the limelight. In order to detect the unusual events, supervised techniques, semi-supervised techniques and unsupervised techniques have been adopted. Social force model (SFM) and Force field are used to model the interaction among crowds. Only normal events training samples is not sufficient for detection of unusual events. Double sparse representation has been used as a solution to this, which includes normal and abnormal training data. To develop an intelligent video surveillance system, behavioural representation and behavioural modelling techniques are used. Various machine learning techniques to identify unusual events include: Graph modelling and matching, object trajectory based, object silhouettes based and pixel based approaches. Kullback–Leibler (KL) divergence, Quaternion Discrete Cosine Transformation (QDCT) analysis, hidden Markov model (HMM) and histogram of oriented contextual gradient (HOCG) descriptor are some of the models used are used for detecting unusual events. This paper briefly discusses the above mentioned strategies and pay attention on their pros and cons

Nanoparticle Network Formation in Nanostructured and Disordered Block Copolymer Matrices

Incorporation of nanoparticles composed of surface-functionalized fumed silica (FS) or native colloidal silica (CS) into a nanostructured block copolymer yields hybrid nanocomposites whose mechanical properties can be tuned by nanoparticle concentration and surface chemistry. In this work, dynamic rheology is used to probe the frequency and thermal responses of nanocomposites composed of a symmetric poly(styrene-b-methyl methacrylate) (SM) diblock copolymer and varying in nanoparticle concentration and surface functionality. At sufficiently high loading levels, FS nanoparticle aggregates establish a load-bearing colloidal network within the copolymer matrix. Transmission electron microscopy images reveal the morphological characteristics of the nanocomposites under these conditions