Survey of denoising,segmentation and classification of magnetic resonance imaging for prostate cancer

Multimedia Tools and Applications - Prostate cancer (PCa) has become the second most dreadful cancer in men after lung cancer. Traditional approaches used for treatment of PCa were manual, time...     

A method for automatic classification of gender based on text- independent handwriting

Handwriting recognition is used for the prediction of various demographic traits such as age, gender, nationality, etc. Out of all the applications gender prediction is mainly admired topic among researchers. The relation between gender and handwriting can be seen from the physical appearance of the handwriting. This research work predicts gender from handwriting using the landmarks of differences between the two genders. We use the shape or visual appearance of the handwriting for extracting features of the handwriting such as slanteness (direction), area (no of pixels occupied by text), perimeter (length of edges), etc. Classification is carried out using the Support Vector Machine (SVM) as a classifier which transforms the nonlinear problem into linear using its kernel trick, logistic regression, KNN and at the end to enhance the classification rates we use Majority Voting. The experimental results obtained on a dataset of 282 writers with 2 samples per writer shows that the proposed method attains appealing performance on writer detection and text-independent environment.

     

Evaluating the role of composition and local structure on alkali out-diffusion in glasses for thin-film solar cells

The presence of alkali ions has reportedly improved the performance of CIGS/CZTS–based thin-film solar cells. The out-diffusion of the alkali ion, in particular, Na, from the glass substrate offers a facile scalable route of supplying the alkali ions during the growth of the absorber layer. In this work, we demonstrate the diffusion of different alkali ions (Li/Na/K) from composition tuned glasses with intentionally incorporated excess alkali ions into a thin Mo film, typically used as a bottom electrode in solar cells. We also evaluate the physical, mechanical, and thermal properties of the glasses for suitability as a substrate in thin-film deposition. The out-diffusion of alkali ions to the overlayer is found to be critically influenced by the composition and the local structure of the glasses. The Na ions exhibit the highest extent of diffusion among the alkali ions present in glass substrates, while that for the K-ions is the lowest. For the glasses with mixed alkali ions, the presence of Li facilitated the out-diffusion of Na, whereas K ions appear to inhibit the same. Differently with the existing reports, we show that the activation energy and the presence of Ca ions as additional modifiers play a crucial role in the transport mechanism of the ions. In addition, the synthesized glasses exhibit hardness of the order 5-7 GPa, density ~2.55 g cm^-3. The glass transition temperature lies between 535 and 580°C and the coefficient of thermal expansion 8.5-10 ppm/K, which is highly suitable for use as substrates in thin-film solar cells.     

Reputation based probabilistic resource allocation for avoiding free riding and formation of common interest groups in unstructured P2P networks

Free riding is a major problem in peer-to-peer networks. Reputation management systems are generally employed to overcome this problem. In this paper, a new reputation based scheme called probabilistic resource allocation is proposed. This strategy probabilistically decide whether to provide the resource to requesting peer or not. Aforesaid method gives selection preference to higher reputation peers and at the same time provides some finite probability of interaction between those peers who don’t have good reputation about each other. This avoids disconnection between the aforesaid peers. The proposed scheme also introduces a new mechanism for resource distribution which not only allocates resources based on peers’ reputation but simultaneously maximizes network utility also. Algorithm for formation of interest groups based upon both similarity of interests and reputation between peers is also presented.     

The dark side of information technology use

A large body of research has considered the positive aspects of information technology (IT) use. However, emerging research and practice commentary is beginning to focus on complex and often alarming ways in which use of IT affects organisational and social life. This Special Issue focuses on these ‘dark’ effects of IT use.     

AVCOL: Availability-aware information aggregation in large distributed systems under uncollaborative behavior

Aggregation of system-wide information in large-scale distributed systems, such as p2p systems and Grids, can be unfairly influenced by nodes that are selfish, colluding with each other, or are offline most of the time. We present AVCOL, which uses probabilistic and gossip-style techniques to provide availability-aware aggregation. Concretely, AVCOL is the first aggregation system that: (1) implements any (arbitrary) global predicate that explicitly specifies any node’s probability of inclusion in the global aggregate, as a mathematical function of that node’s availability (i.e., percentage time online); (2) probabilistically tolerates large numbers of selfish nodes and large groups of colluders; and (3) scales well with hundreds to thousands of nodes. AVCOL uses several unique design decisions: per-aggregation tree construction where nodes are allowed a limited but flexible probabilistic choice of parents or children, probabilistic aggregation along trees, and auditing of nodes both during aggregation as well as in gossip-style (i.e., periodically). We have implemented AVCOL, and we experimentally evaluated it using real-life churn traces. Our evaluation and our mathematical analysis show that AVCOL satisfies arbitrary predicates, scales well, and withstands a variety of selfish and colluding attacks.     

A closed-loop cross-correlation method for detecting model mismatch in MIMO model-based controllers

Correlation between a dithering signal and the prediction error has been used for detecting model mismatch in univariate model based control systems. This paper extends that approach to MIMO control systems. A closed-loop cross-correlation method is presented to detect which specific input-output pairings of a model-based controller are mismatched. This method may be used in screening the complete set of models and in selecting candidate models for re-identification. The method first finds the rows and columns of the transfer function matrix that contain mismatch, and then the candidates are found by the intersection of the said rows and columns. Placing the system under partial control, whereby one or more of the manipulated variables are held constant, can be used to further reduce the set of candidate models.     

Entrance effects for power-law fluid

Entrance pressure losses for the creeping flow of a power-law fluid are calculated for an abrupt contraction of ratio 2, 4, 8 and ∞ for both the axisymmetric and planar cases using P₂P₁ and PP₁ finite elements. Contrary to some earlier findings in the literature, the entrance pressure loss obtained by using the two different types of finite elements, both of which satisfy the Babus?ka-Brezzi condition, are found to converge to the same results. The present results also confirm that the variational method of Duda and Vrentas gives excellent upper bounds for both the axisymmetric and planar cases with infinite contraction ratio.