Heritage Institute of Technology

About: Heritage Institute of Technology is a based out in . It is known for research contribution in the topics: Steganography & Support vector machine. The organization has 581 authors who have published 1045 publications receiving 8345 citations.

Scalable Hierarchical Recommendations Using Spatial Autocorrelation

Abstract: Collaborative Filtering (CF) is one of the most successful and widely used approaches behind Recommendation Algorithms. CF algorithms use the known preferences of a group of users to make recommendations or predictions of the unknown preferences for other users. In this paper, we deal with the Scalability issue which is one of the main challenges to the CF algorithms. In Collaborative Filtering, finding similarity amongst N users is an O(N2) process. If N is large then similarity computation becomes very expensive. In this work, we propose a Quadtree based user partitioning technique that partitions the entire users' space into regions based on the location. We develop a Spatially Aware Recommendation Algorithm, where the Recommendation Algorithm is applied separately to each region and therefore allows us to reduce the quadratic complexity associated with the CF process. The proposed work tries to measure the Spatial Autocorrelation indices, such as Geary's index in the regions or cells formed by the Quadtree decomposition. One of the main objectives of our work is to reduce the running time as well as maintain a good quality of recommendation. This approach of recommendation using the decomposition method makes our algorithm feasible to work with large datasets. We have tested our algorithms on the MovieLens and the Book-Crossing datasets.

Frequency Tunable Differentially Fed Inverted Microstrip Patch Antenna with Low Cross-Polarized Radiation

Abstract: In this article tunable characteristic of differentially fed inverted microstrip patch antenna is presented for C-band operation. Differential feeding is applied through a unilayer integrated coupler feed. Near the operating frequency of the designed antenna the fabricated coupler shows that the amplitude imbalance is 0.3 dB and phase imbalance corresponds to 3.2°. Tuning is achieved by changing the air gap height in the antenna structure from 1 to 4 mm. Proposed concept of tunablity is verified for two different patch geometries (circular and rectangular) and three different patch dimensions through analysis and experiments. Closed form expressions are proposed to predict the tuning frequency. This design offers low cross-polarized radiation in the H-plane and symmetric co-polarized radiation in both principal planes. Fabricated prototype is measured and compared with simulated and theoretical values. The comparison among the simulated values, theoretically computed values and the measured values for different air gap heights of 2, 3, and 4 mm, shows an error less than 1%.

A New Experiment on Bengali Character Recognition

Abstract: This paper presents a method to use View based approach in Bangla Optical Character Recognition (OCR) system providing reduced data set to the ANN classification engine rather than the traditional OCR methods. It describes how Bangla characters are processed, trained and then recognized with the use of a Backpropagation Artificial neural network. This is the first published account of using a segmentation-free optical character recognition system for Bangla using a view based approach. The methodology presented here assumes that the OCR pre-processor has presented the input images to the classification engine described here. The size and the font face used to render the characters are also significant in both training and classification. The images are first converted into greyscale and then to binary images; these images are then scaled to a fit a pre-determined area with a fixed but significant number of pixels. The feature vectors are then formed extracting the characteristics points, which in this case is simply a series of 0s and 1s of fixed length. Finally, an artificial neural network is chosen for the training and classification process.

Inseparability of Quantum Parameters

Abstract: In this work, we show that ‘splitting of quantum information’ (Zhou, D., et al. in quant-ph/0503168) is an impossible task from three different but consistent principles namely unitarity of Quantum Mechanics, no-signaling condition and non-increase of entanglement under Local Operation and Classical Communication.