Two-Hop Routing with Traffic-Differentiation for QoS Guarantee in Wireless Sensor Networks

This paper proposes a Traffic-Differentiated Two-Hop Routing protocol for Quality of Service (QoS) in Wireless Sensor Networks (WSNs). It targets WSN applications having different types of data traffic with several priorities. The protocol achieves to increase Packet Reception Ratio (PRR) and reduce end-to-end delay while considering multi-queue priority policy, two-hop neighborhood information, link reliability and power efficiency. The protocol is modular and utilizes effective methods for estimating the link metrics. Numerical results show that the proposed protocol is a feasible solution to addresses QoS service differenti- ation for traffic with different priorities.Comment: 13 page

On a problem relating to a tetrahedron

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Far-infrared observations of Circinus and NGC 4945 galaxies

Circinus and NGC 4945 are two galaxies luminous in the infrared and are characterized by compact non thermal radio nuclei, deep silicate absorption features and unusually strong water vapor maser luminosities. Moorwood and Glass (1984) have observed these galaxies extensively in the 1 to 20 micron range. In the far-infrared, observations up to 100 microns are available from the Infrared Astronomy Satellite (IRAS). In order to study the cool dust component of these galaxies, researchers observed them at 150 microns using the Tata Institute of Fundamental Research (TIFR) 100 cm balloon-borne telescope. Here, they report observations along with deconvolved maps at 50 and 100 microns obtained from the Chopped Photometric Channel (CPC) on board IRAS

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

A method of staining Neurospora nuclei

Staining Neurospora nucle