Low Power Reversible Parallel Binary Adder/Subtractor

In recent years, Reversible Logic is becoming more and more prominent technology having its applications in Low Power CMOS, Quantum Computing, Nanotechnology, and Optical Computing. Reversibility plays an important role when energy efficient computations are considered. In this paper, Reversible eight-bit Parallel Binary Adder/Subtractor with Design I, Design II and Design III are proposed. In all the three design approaches, the full Adder and Subtractors are realized in a single unit as compared to only full Subtractor in the existing design. The performance analysis is verified using number reversible gates, Garbage input/outputs and Quantum Cost. It is observed that Reversible eight-bit Parallel Binary Adder/Subtractor with Design III is efficient compared to Design I, Design II and existing design.Comment: 12 pages,VLSICS Journa

Drag and inertia coefficients for horizontally submerged rectangular cylinders in waves and currents

The results of an experimental investigation carried out to measure combined wave and current loads on horizontally submerged square and rectangular cylinders are reported in this paper. The wave and current induced forces on a section of the cylinders with breadth-depth (aspect) ratios equal to 1, 0.5, and 0.75 are measured in a wave tank. The maximum value of Keulegan-Carpenter (KC) number obtained in waves alone is about 5 and Reynolds (Re) number ranged from 6.3976103 to 1.186105. The drag (CD) and inertia (CM) coefficients for each cylinder are evaluated using measured sectional wave forces and particle kinematics calculated from linear wave theory. The values of CD and CM obtained for waves alone have already been reported (Venugopal, V., Varyani, K. S., and Barltrop, N. D. P. Wave force coefficients for horizontally submerged rectangular cylinders. Ocean Engineering, 2006, 33, 11-12, 1669-1704) and the coefficients derived in combined waves and currents are presented here. The results indicate that both drag and inertia coefficients are strongly affected by the presenceof the current and show different trends for different cylinders. The values of the vertical component inertia coefficients (CMY) in waves and currents are generally smaller than the inertia coefficients obtained in waves alone, irrespective of the current's magnitude and direction. The results also illustrate the effect of a cylinder's aspect ratio on force coefficients. This study will be useful in the design of offshore structures whose columns and caissons are rectangular sections

DRSP : Dimension Reduction For Similarity Matching And Pruning Of Time Series Data Streams

Similarity matching and join of time series data streams has gained a lot of relevance in today's world that has large streaming data. This process finds wide scale application in the areas of location tracking, sensor networks, object positioning and monitoring to name a few. However, as the size of the data stream increases, the cost involved to retain all the data in order to aid the process of similarity matching also increases. We develop a novel framework to addresses the following objectives. Firstly, Dimension reduction is performed in the preprocessing stage, where large stream data is segmented and reduced into a compact representation such that it retains all the crucial information by a technique called Multi-level Segment Means (MSM). This reduces the space complexity associated with the storage of large time-series data streams. Secondly, it incorporates effective Similarity Matching technique to analyze if the new data objects are symmetric to the existing data stream. And finally, the Pruning Technique that filters out the pseudo data object pairs and join only the relevant pairs. The computational cost for MSM is O(l*ni) and the cost for pruning is O(DRF*wsize*d), where DRF is the Dimension Reduction Factor. We have performed exhaustive experimental trials to show that the proposed framework is both efficient and competent in comparison with earlier works.Comment: 20 pages,8 figures, 6 Table

Forecasting Stock Time-Series using Data Approximation and Pattern Sequence Similarity

Time series analysis is the process of building a model using statistical techniques to represent characteristics of time series data. Processing and forecasting huge time series data is a challenging task. This paper presents Approximation and Prediction of Stock Time-series data (APST), which is a two step approach to predict the direction of change of stock price indices. First, performs data approximation by using the technique called Multilevel Segment Mean (MSM). In second phase, prediction is performed for the approximated data using Euclidian distance and Nearest-Neighbour technique. The computational cost of data approximation is O(n ni) and computational cost of prediction task is O(m |NN|). Thus, the accuracy and the time required for prediction in the proposed method is comparatively efficient than the existing Label Based Forecasting (LBF) method [1].Comment: 11 page

What factors influence UK medical students' choice of foundation school?

Background: We aimed to identify the factors influencing UK medical student applicants’ choice of foundation school. We also explored the factors that doctors currently approaching the end of their 2-year program believe should be considered. Methods: A cross-sectional study was conducted during the 2013–2014 academic year. An online questionnaire was distributed to 2092 final-year medical students from nine UK medical schools and 84 foundation year-2 (FY2) doctors from eight foundation schools. Participants were asked to rank their top 3 from a list of 12 factors that could potentially influence choice of foundation school on a 5-point Likert scale. Collated categorical data from the two groups were compared using a chi-square test with Yates correction. Results: Geographic location was overwhelmingly the most important factor for medical students and FY2 doctors with 97.2% and 98.8% in agreement, respectively. Social relationships played a pivotal role for medical student applicants. Clinical specialties within the rotations were of less importance to medical students, in comparison to location and social relationships. In contrast, FY2 doctors placed a significantly greater importance on the specialties undertaken in their 2-year training program, when compared to medical students (chi-square; p=0.0001). Conclusion: UK medical schools should make their foundation program applicants aware of the importance of choosing rotations based on specialties that will be undertaken. Individual foundation schools could provide a more favorable linked application system and greater choice and flexibility of specialties within their 2-year program, potentially making their institution more attractive to future applicants

Framework for Cross Layer Energy Optimization in Wireless Sensor Networks

Cross-layer routing technique interacts among the various layers of the OSI model and exchanges information among them. It enhances the usage of network resources and achieves significant performance improvements in Quality of Service (QoS) parameters. The Low Energy Adaptive Clustering Hierarchy Protocol (LEACH) routing algorithm consumes higher energy due to communication overhead and thus, a hierarchical model-based routing protocol named Cross-Layer Energy Efficient Scalable-Low Energy Adaptive Clustering Hierarchy Protocol (CLEES-LEACH) is proposed. This increases scalability using the Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) protocol between the intermediary node and cluster head, with the overhead of latency. A Linear Programming model is used, which further makes use of scheduling to overcome latency. Energy efficiency and latency are addressed with the proposed cross-layer routing algorithm CLEESLEACH. The cross-layer design establishes Physical, Media Access Control (MAC), and Network layer interactions in the proposed algorithm. The present LEACH algorithm also increases the network overhead as there is no mechanism for communication among the network layer and consumes high energy. In the proposed algorithm CLEES-LEACH, latency is reduced to 25% and throughput is maximized to 20% compared to existing Energy-Efficient Distributed Schedule Based protocol (EEDS) and Integer Linear Programming (ILP) protocols. The energy consumption is also reduced to 20 % and the scalability is increased to 10 % compared to the existing LEACH and CL-LEACH

DRFSD: Directed Restricted Flooding For Secure Data-Aggregation In Wireless Sensor Networks

Secured Data Transmission is a major issue in Wireless Sensor Networks (WSNs). In this paper we have proposed Directed Restricted Flooding Protocol (DRFSD) in WSNs. This protocol is better than H-SPREAD (Hybrid Security Protocol for REliable dAta Delivery). In DRFSD, alternate multipaths are selected based on the sensor node, that are placed at 180? direction with the Base Station (BS). This scheme is ef?cient in sending the Data Packets to the Base Station in shorter duration than the H-SPREAD. Simulation Results show that our algorithm approach performs well with respect to latency in comparison with earlier algorithm