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.     

Iodine-loaded poly(silicic acid) gellan nanocomposite mucoadhesive film for antibacterial application

Iodine-loaded poly(silicic acid) gellan nanocomposite film was fabricated and evaluated for antibacterial properties. Poly(silicic acid) nanoparticles were synthesized by condensation of silicic acid under alkaline conditions in the presence of polyvinyl pyrrolidone, phosphate ions, and molecular iodine. The nanoparticles were incorporated into gellan dispersion to prepare gellan nanocomposite film using the solvent casting method. The nanocomposite films were characterized by Fourier transformed infrared spectroscopy, thermogravimetric analysis, and X-ray diffraction studies. The results of characterization studies indicated improved thermal stability and an increase in the degree of crystallinity. The scanning electron micrographs and energy dispersive X-ray spectrum confirmed the uniform dispersion of silica and iodine in the nanocomposite films. The analysis of physical and mechanical properties revealed the enhanced tensile strength, moisture resistance, and higher folding endurance of poly(silicic acid) gellan nanocomposite films as compared to gellan film. Further, the iodine-loaded poly(silicic acid) gellan nanocomposite films showed good antibacterial activity against Staphylococcus aureus and Escherichia coli and effective mucoadhesive strength. The results indicate that iodine-loaded poly(silicic acid) gellan nanocomposite mucoadhesive film can be used for potential antibacterial applications in pharmaceuticals.     

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.     

A case study comparing defect profiles of a reused framework and of applications reusing it

The benefits of software reuse have been studied for many years. Several previous studies have observed that reused software has a lower defect density than newly built software. However, few studies have investigated empirically the reasons for this phenomenon. To date, we have only the common sense observation that as software is reused over time, the fixed defects will accumulate and will result in high-quality software. This paper reports on an industrial case study in a large Norwegian Oil and Gas company, involving a reused Java class framework and two applications that use that framework. We analyzed all trouble reports from the use of the framework and the applications according to the Orthogonal Defect Classification (ODC), followed by a qualitative Root Cause Analysis (RCA). The results reveal that the framework has a much lower defect density in total than one application and a slightly higher defect density than the other. In addition, the defect densities of the most severe defects of the reused framework are similar to those of the applications that are reusing it. The results of the ODC and RCA analyses reveal that systematic reuse (i.e. clearly defined and stable requirements, better design, hesitance to change, and solid testing) lead to lower defect densities of the functional-type defects in the reused framework than in applications that are reusing it. However, the different “nature” of the framework and the applications (e.g. interaction with other software, number and complexity of business logic, and functionality of the software) may confound the causal relationship between systematic reuse and the lower defect density of the reused software. Using the results of the study as a basis, we present an improved overall cause–effect model between systematic reuse and lower defect density that will facilitate further studies and implementations of software reuse.

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.