The extensive research in the field of multimodal biometrics by the research community and the advent of modern technology has compelled the use of multimodal biometrics in real life applications. Biometric systems that are based on a single modality have many constraints like noise, less universality, intra class variations and spoof attacks. On the other hand, multimodal biometric systems are gaining greater attention because of their high accuracy, increased reliability and enhanced security. This research paper proposes and develops a Convolutional Neural Network (CNN) based model for the feature level fusion of fingerprint and online signature. Two types of feature level fusion schemes for the fingerprint and online signature have been implemented in this paper. The first scheme named early fusion combines the features of fingerprints and online signatures before the fully connected layers, while the second fusion scheme named late fusion combines the features after fully connected layers. To train and test the proposed model, a new multimodal dataset consisting of 1400 samples of fingerprints and 1400 samples of online signatures from 280 subjects was collected. To train the proposed model more effectively, the size of the training data was further increased using augmentation techniques. The experimental results show an accuracy of 99.10% achieved with early feature fusion scheme, while 98.35% was achieved with late feature fusion scheme.

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A smart home is a context-aware system that adapts itself autonomously in response to context to satisfy user needs and to improve safety, security, resource use, etc. On the one hand, software autonomy serves the basic purpose of pervasive computing by reducing interaction with the users, easing the use of the system, and reducing the user distraction. On the other hand, it takes control away from the users of the applications, making users feel loss of control over their contextaware applications. The situations including applications may not behave as expected, user preferences may change over time or users may want to add new behaviors, etc, may arise and require smart home users to interact with the applications to control their behavior. This research addresses this issue and proposes an approach, which would provide a wider support of user control by exposing and manipulating (1) application parameters, (2) adaptation logic(s) thus allowing users to add new behaviors. Using this approach a complete system is developed in order to see its effectiveness; furthermore the system is tested on three different context aware applications and a preliminary usability study is done to evaluate the system effectiveness.

Conventional solar cells are not economical and are recently too expensive to the manufacturers for extensive-scale electricity generation. Cost and efficiency is most vital factor in the accomplishment of any solar technology. In order to improve the conversion efficiency, the major research in third generation photovoltaic (PV) cells is directed toward retaining more sunlight using nanotechnology. Advancement in nanotechnology solar cell via quantum dots (QDs) could reduce the cost of PV cell and additionally enhance cell conversion efficiency. Silicon quantum dots (Si-QDs) are semiconductor nano crystals of nanometers dimension whose electron-holes are confined in all three spatial dimensions. Quantum dots have discrete electronic states. Quantum dots have capacity to change band gap with the adjustment in size of quantum dot. As the quantum dots size fluctuates over a wide range that demonstrates the variety of band gap so it will assimilate or discharge light. In this paper, the generic mathematical models of PV cell are adopted and then I-V and P-V characteristic curves are obtained from selected parameters using MATLAB software. The essential parameters are taken from datasheets. I-V and P-V characteristics curves are obtained for selected model. Silicon quantum dots have the tunable band gap that is added to conventional PV cell and obtain the I-V and P-V curves. After simulation, efficiency and power of Conventional PV cell to quantum dots based PV cell is compared. The property of quantum dots is used in extending the band gap of solar cells and increasing the maximum proportion of incident sunlight absorbed, hence improving efficiency.