Design of nearly perfect reconstructed non-uniform filter bank by constrained equiripple FIR technique

In this paper, an efficient iterative algorithm is proposed for the design of multi-channel nearly perfect reconstructed non-uniform filter bank. The method employs the constrained equiripple FIR technique to design the prototype filter for filter banks with novelty of exploiting a new perfect reconstruction condition of the non-uniform filter banks instead of using complex objective functions. In the proposed algorithm, passband edge frequency (ω_p) is optimized using linear optimization technique such that the filter coefficients values at quadrature frequency are approximately equal to 0.707. Several design examples are included to illustrate the efficacy of this methodology for designing non-uniform filter bank (NUFB). It was found that the proposed methodology performs better as compared to earlier reported results in terms of reconstruction error (RE), number of iteration (NOI) and computation time (CPU time). The proposed algorithm is very simple, linear in nature, and easy to implement.     

KUMBH MELA: a case study for dense crowd counting and modeling

Dense crowd counting and modeling at different gatherings has ignited a new flame in the visual surveillance research community. There is a high possibility of mishappenings in the form of stampede, mob fighting at these gatherings and the administration is helpless in these scenarios. There is a requirement of analyzing the crowd to prevent these dangerous situations. The proposed work is a case study of Kumbh Mela which models the crowd counting in densely populated images. In the proposed work, the orthographic projection of the crowd is captured using a camera attached to a drone, to reduce the effect of occlusion and scaling which, otherwise, may get introduce during image acquisition process. The captured data is fed to a Convolutional Neural Network for training the model to count head of persons present in the frame. The results obtained from the trained model are validated using geometry and imaging techniques. The proposed model has achieved a mean-absolute-error of 94.3 and a mean-squared-error of 104.6 which seems to outperform the existing state-of-the-art models with respect to the reported performance parameters. The proposed model can be used as a viable solution in applications related to modeling the crowd behavior.

     

Evaluation of Seasonal Variability of First-Order Ionospheric Delay Correction at L5 and S1 Frequencies Using Dual-Frequency NavIC System

Wireless Personal Communications - For the precise positioning applications it is important to determine and eliminate the positioning error introduced by various sources such as the ionosphere. To...     

A tutorial survey of topics in wireless networking: Part I

In this two part paper, we provide a survey of recent and emerging topics in wireless networking. We view the area of wireless networking as dealing with problems of resource allocation so that the various connections that utilise the network achieve their desired performance objectives. In the first part of the paper, we first survey the area by providing a taxonomy of wireless networks as they have been deployed. Then, we provide a quick tutorial on the main issues in the wireless ‘physical’ layer, which is concerned with transporting bits over the radio frequency spectrum. Then, we proceed to discuss some resource allocation formulations in CDMA(code division multiple access) cellular networks and OFDMA(orthogonal frequency division multiple access) networks. In the second part of the paper, we first analyse random access wireless networks and pay special attention to 802·11 (Wi-Fi) networks.We then survey some topics in ad hoc multihop wireless networks, where we discuss arbitrary networks, as well as some theory of dense random networks. Finally, we provide an overview of the technical issues in the emerging area of wireless sensor networks.     

Remarkably Selective Propylene–Propane Separation Using a Copper Scorpionate

Propylene is a crucial building block to produce many industrial-scale chemicals including polypropylene. The separation of propylene from propane to reach the high-purity levels needed for downstream applications is a difficult task due to the close similarities in their physical properties. The olefin/paraffin separation including that involving propylene mainly relies on highly energy-intensive distillation processes and accounts for nearly 0.3% of the global energy consumption. The utility of a copper complex supported by a fluorinated bis(pyrazolyl)borate is demonstrated to accomplish the separation of propylene from propane repeatedly, under mild conditions with high selectivity. Complete characterization of a rare, copper(I) propylene complex is also reported including the molecular structure.     

A new grouping genetic algorithm approach to the multiple traveling salesperson problem

The multiple traveling salesperson problem (MTSP) is an extension of the well known traveling salesperson problem (TSP). Given m > 1 salespersons and n > m cities to visit, the MTSP seeks a partition of cities into m groups as well as an ordering among cities in each group so that each group of cities is visited by exactly one salesperson in their specified order in such a way that each city is visited exactly once and sum of total distance traveled by all the salespersons is minimized. Apart from the objective of minimizing the total distance traveled by all the salespersons, we have also considered an alternate objective of minimizing the maximum distance traveled by any one salesperson, which is related with balancing the workload among salespersons. In this paper, we have proposed a new grouping genetic algorithm based approach for the MTSP and compared our results with other approaches available in the literature. Our approach outperformed the other approaches on both the objectives.