Abstract: Recent innovations in the field of technology led to the use of wireless sensor networks in various applications, which consists of a number of small, very tiny, low-cost, non-tamper proof and resource constrained sensor nodes. These nodes are often distributed and deployed in an unattended environment, so as to collaborate with each other to share data or information. Amidst various applications, wireless sensor network finds a major role in monitoring battle field in military applications. As these non-tamperproof nodes are deployed in an unattended location, they are vulnerable to many security attacks. Amongst many security attacks, the node replication attack seems to be more threatening to the network users. Node Replication attack is caused by an attacker, who catches one true node, duplicates the first certification and cryptographic materials, makes at least one or more copies of the caught node and spots them at certain key positions in the system to screen or disturb the network operations. Preventing the occurrence of such node replication attacks in network is a challenging task. In this survey article, we provide the classification of detection schemes and also explore the various schemes proposed in each category. Also, we compare the various detection schemes against certain evaluation parameters and also its limitations. Finally, we provide some suggestions for carrying out future research work against such attacks.
Abstract: Cancer affects people globally with breast cancer being a leading killer. Breast cancer is due to the uncontrollable multiplication of cells resulting in a tumour or neoplasm. Tumours are called ‘benign’ when cancerous cells do not ravage other body tissues and ‘malignant’ if they do so. As mammography is an effective breast cancer detection tool at an early stage which is the most treatable stage it is the primary imaging modality for screening and diagnosis of this cancer type. This paper presents an automatic mammogram classification technique using wavelet and Gabor filter. Correlation feature selection is used to reduce the feature set and selected features are classified using different decision trees.
Abstract: For scores of years now, several microfinance
organizations, non governmental organizations and other welfare
organizations have, with a view to aiding the progress of
communities rooted in poverty have been focusing on creating
microentrepreneurs, besides taking several other measures. In recent
times, business corporations have joined forces to combat poverty by
taking up microenterprise development. Hindustan Unilever Limited
(HUL), the Indian subsidiary of Unilever Limited exemplifies this
through its Project Shakti. The company through the Project creates
rural women entrepreneurs by making them direct to home sales
distributors of its products in villages that have thus far been ignored
by multinational corporations. The members participating in Project
Shakti are largely self help group members. The paper focuses on
assessing the impact made by the company on the members engaged
in Project Shakti. The analysis involves use of quantitative methods
to study the effect of Project Shakti on those self help group
members engaged in Project Shakti and those not engaged with
Project Shakti. Path analysis has been used to study the impact made
on those members engaged in Project Shakti. Significant differences
were observed on fronts of entrepreneurial development, economic
empowerment and social empowerment between members associated
with Project Shakti and those not associated with Project Shakti.
Path analysis demonstrated that involvement in Project Shakti led to
entrepreneurial development resulting in economic empowerment
that in turn led to social empowerment and that these three elements
independently induced a feeling of privilege in the women for being
associated with the Project.