Joint cost and secured node disjoint energy efficient multipath routing in mobile ad hoc network

Wireless Networks - The severe resource constraints and deployment environments of mobile ad hoc networks (MANETs) pose challenges for the security and energy consumption during data transmission...     

A method for embedding a computer vision application into a wearable device

Pattern classification applications can be found everywhere, especially the ones that use computer vision. What makes them difficult to embed is the fact that they often require a lot of computational resources. Embedded computer vision has been applied in many contexts, such as industrial or home automation, robotics, and assistive technologies. This work performs a design space exploration in an image classification system and embeds a computer vision application into a minimum resource platform, targeting wearable devices. The feature extractor and the classifier are evaluated for memory usage and computation time. A method is proposed to optimize such characteristics, leading to a reduction of over 99% in computation time and 92% in memory usage, with respect to a standard implementation. Experimental results in an ARM Cortex-M platform showed a total classification time of 0.3 s, maintaining the same accuracy as in the simulation performed. Furthermore, less than 20 KB of data memory was required, which is the most limited resource available in low-cost and low-power microcontrollers. The target application, used for the experimental evaluation, is a crosswalk detector used to help visually impaired persons.     

Analytical Performance Evaluation of a STBC Coded OFDM FSO Communication System over Turbulent Atmospheric Channel

Journal of Communications Technology and Electronics - An analytical approach is presented for an optical IM/DD system with STBC coded OFDM RF subcarrier modulation over a free space optical...     

Stabilization of 2D nonsymmetric half-plane digital filters using the concept of reciprocity

In this paper, the concept of reciprocity for two-dimensional (2D) quarter plane (QP) filters are extended to stabilize 2D nonsymmetric half-plane (NSHP) filters. In general the stabilization of NSHP filters is done by transforming NSHP arrays into QP arrays using mapping theorems. The concept of reciprocity is applied directly without any mapping to stabilize a class of 2D NSHP filters which are otherwise unstable when all singularities lie within the unit bicircle. It is shown that the magnitude spectrum of the stabilized 2D NSHP filter is identical to the magnitude spectrum of the original unstable filter. The proposed stabilization method is simple as compared to two other popular stabilization techniques in the literature, the double planar least squares inverse (DPLSI) and 2D discrete Hilbert transform (2D DHT).     

A tradeoff between unit capacity and average production cost in spinning reserve optimization

In power systems the spinning reserve (SR) amount can be determined by deterministic or probabilistic techniques. Probabilistic techniques draw more attention since they can consider the economics and the stochastic nature of system behavior and component failures. In probabilistic techniques, the tradeoff between cost and reliability directly affects the SR deployment and it has been extensively analyzed. However, there is another tradeoff which reflects the compromise between the unit capacity and average production cost in the SR optimization problem. This tradeoff impacts the solution accuracy to a certain extent and influences the complexity of the model, and it has not been explicitly analyzed before. In this paper, a new SR optimization method is proposed in which the tradeoff between unit capacity and average production cost is well respected. The proposed method strikes a good balance between solution accuracy and computation efficiency and can obtain better results within a desirable run time compared with those of the previous methods. Besides, the proposed method can also be used to improve the solution of the reserve constrained unit commitment problem. It can lower the total cost by just redistributing the MW dispatch even when the SSR is fixed. The efficiency and validity of the proposed method are verified using the IEEE reliability test system.     

FPGA-based genetic algorithm implementation for AC chopper fed induction motor

Genetic algorithm (GA)-based harmonic elimination technique is proposed for designing AC chopper. GA is used to calculate optimal firing angles to eliminate lower order harmonics in output voltage. Total harmonic distortion of output voltage is taken for the fitness function used in the GA. Thus, the ratings of the load are not mandatory to be known for calculating the switching angles using proposed technique. For the performance assessment of GA, Newton–Raphson (NR) method is applied in this present work. Simulation results show that the proposed technique is better in terms of less computational complexity and quick convergence. Simulation results were verified by field programmable gate array controller-based prototype. Simulation study and experimental investigations show that the proposed GA method is superior to the conventional methods.     

Simultaneous optimization of phase balancing and reconfiguration in distribution networks using BF–NM algorithm

Rephasing strategy is one of the main methods used for phase balancing and neutral current reduction in electrical distribution networks and the reconfiguration technique is an effective method for network loss reduction. In this paper, a new method for the simultaneous implementation of reconfiguration and phase balancing strategies is presented as a combinational strategy. In order to solve the proposed optimization problem, Nelder Mead algorithm combined with a bacterial foraging algorithm (BF–NM) is used based on a fuzzy multi-objective function. The proposed method allows for the simultaneous execution of reconfiguration and phase balancing while minimizing the interruption cost of rephasing in addition to eliminating network unbalancing and reducing neutral current and network losses. To demonstrate the efficiency of the BF–NM algorithm, its performance is compared with bacterial foraging (BF), particle swarm optimization (PSO), genetic and immune algorithms (GA and IA). The proposed method is applied to the IEEE 123-bus test network for evaluation. The simulation results confirm the efficiency of the method in reducing the system costs and network phase balancing.     

Minimization of digital logic gates and ultra-low power AES encryption core in 180CMOS technology

This work concentrate on the design of low power substitution box architecture with enhanced galois field based transform towards multiplier in advanced cryptographic encryption core. Basic components such as AND, XOR, XNOR are being used for the designing process. Initially tree based XNOR gates are picked up and then the AND gates are replaced by NAND gated with less number of transistor in it. Here, logical method is carried out, which is actually considered as better method for re-sizing of transistor. This will further decrease the overall delay and power consumption. The less delay can be obtained by 4-input XOR gate architecture. The implementation results with an 180 nm CMOS standard library show that the proposed AES core can reduce the area and power consumption significantly.     

Efficient fuzzy feature matching and optimal feature points for multiple objects tracking in fixed and active camera models

Multimedia Tools and Applications - In computer vision, the multiple objects tracking play a vital challenging role. To solve the issues in this research field, various traditional techniques had...