R. S. D. Wahida Banu

Bio: R. S. D. Wahida Banu is an academic researcher from Anna University. The author has contributed to research in topics: Scheduling (computing) & Load balancing (computing). The author has an hindex of 10, co-authored 47 publications receiving 252 citations. Previous affiliations of R. S. D. Wahida Banu include Government College of Engineering, Salem & Government Engineering College, Sreekrishnapuram.

A non-invasive study of alterations of the carotid artery with age using ultrasound images.

Abstract: A region-based method for measurement of arterial diameter to find out the elasticity of the vessel is proposed in this paper Arterial segments are studied by using images obtained through ultrasound scanning in B-mode Pulsatile changes of the common carotid artery during diastole and systole are computed To achieve this, thinned segmentation is done by suitably adjusting the contrast of the image The diameter changes of the artery wall from the centre of artery are calculated Fifty-three normal subjects with age group 20-40 years are taken for measurement Measured diameter is plotted as a graph and pulsatile changes of the artery are obtained Since no atherosclerotic lesions are detected in the studied subjects, it is suggested that the common carotid artery is a highly compliant artery with a strong alteration of viscoelastic properties with age

Occlusion invariant face recognition using mean based weight matrix and support vector machine

Abstract: In this paper, a novel occlusion invariant face recognition algorithm based on Mean based weight matrix (MBWM) technique is proposed. The proposed algorithm is composed of two phases—the occlusion detection phase and the MBWM based face recognition phase. A feature based approach is used to effectively detect partial occlusions for a given input face image. The input face image is first divided into a finite number of disjointed local patches, and features are extracted for each patch, and the occlusion present is detected. Features obtained from the corresponding occlusion-free patches of training images are used for face image recognition. The SVM classifier is used for occlusion detection for each patch. In the recognition phase, the MBWM bases of occlusion-free image patches are used for face recognition. Euclidean nearest neighbour rule is applied for the matching. GTAV face database that includes many occluded face images by sunglasses and hand are used for the experiment. The experimental results demonstrate that the proposed local patch-based occlusion detection technique works well and the MBWM based method shows superior performance to other conventional approaches.

Analysis of tacit knowledge sharing and codification in higher education

Abstract: An institution represents the ultimate knowledge organization. The rapid growth of data and technologies trigger the transformation of data to useful information known as ‘Knowledge’. To leverage knowledge, institutions need a knowledge sharing network that can meet the demands of changing knowledge. The knowledge sharing network is accomplished by sharing and capturing knowledge among faculty members and students. Info-Ca-Sh is a dynamic web content knowledge portal. The architecture serves as an information exchange of knowledge by using various open source tools. The tacit and explicit knowledge of the registered users are made codified and accumulated as knowledge repository. The various documents uploaded on the portal by the registered users are made share and capture. The implementation creates interests among faculty members to share and to capture information by exploring a social network. The result of social network analysis shows the information flow and degree of knowledge sharing in the network.

RE-AODV: An enhanced routing algorithm for QoS support in wireless ad-hoc sensor networks

Abstract: Low control overhead and power cost are two key issues in wireless sensor networks to improve protocol efficiency. They decide the quality of service provided by the protocol. Ad-hoc On Demand Distance Vector protocol (AODV) is a preferred routing protocol in wireless sensor networks. The routing overhead of AODV is a drawback in power-constrained environment. This paper presents an enhanced routing algorithm RE-AODV with a local route enhancement model for AODV which reduces the routing overhead and improves the efficiency. The Hello packet broadcast mechanism of the standard AODV is enhanced to save time-and-again discarding and rediscovering the routes. The theoretical substantiation and the performance evaluation using the TOSSIM simulator are presented. The results show that the new algorithm is efficient with reduced control overhead and end-to-end delay.

Efficient masked face recognition method during the COVID-19 pandemic

Abstract: The coronavirus disease (COVID-19) is an unparalleled crisis leading to a huge number of casualties and security problems. In order to reduce the spread of coronavirus, people often wear masks to protect themselves. This makes face recognition a very difficult task since certain parts of the face are hidden. A primary focus of researchers during the ongoing coronavirus pandemic is to come up with suggestions to handle this problem through rapid and efficient solutions. In this paper, we propose a reliable method based on occlusion removal and deep learning-based features in order to address the problem of the masked face recognition process. The first step is to remove the masked face region. Next, we apply three pre-trained deep Convolutional Neural Networks (CNN), namely VGG-16, AlexNet, and ResNet-50, and use them to extract deep features from the obtained regions (mostly eyes and forehead regions). The Bag-of-features paradigm is then applied to the feature maps of the last convolutional layer in order to quantize them and to get a slight representation comparing to the fully connected layer of classical CNN. Finally, Multilayer Perceptron (MLP) is applied for the classification process. Experimental results on Real-World-Masked-Face-Dataset show high recognition performance compared to other state-of-the-art methods.