OCSO-CA: opposition based competitive swarm optimizer in energy efficient IoT clustering

With the advent of modern technologies,IoT has become an alluring field of research.Since IoT connects everything to the network and transmits big data frequently,it can face issues regarding a large amount of energy loss.In this respect,this paper mainly focuses on reducing the energy loss problem and designing an energy-efficient data transfer scenario between IoT devices and clouds.Consequently,a layered architectural framework for IoT-cloud transmission has been proposed that endorses the improvement in energy efficiency,network lifetime and latency.Furthermore,an Opposition based Competitive Swarm Optimizer oriented clustering approach named OCSO-CA has been proposed to get the optimal set of clusters in the IoT device network.The proposed strategy will help in managing intra-cluster and inter-cluster data communications in an energy-efficient way.Also,a comparative analysis of the proposed approach with the state-of-the-art optimization algorithms for clustering has been performed.     

Assessing growth and yield of wheat using remotely-sensed canopy temperature and spectral indices

Abstract

Prediction models were developed for wheat to assess crop growth in terms of leaf area index, dry matter production and grain yield from remotely-sensed temperature and spectral indices. The cumulative stress degree days (SDD) for the period of flowering to grain formation stage showed significantly higher correlation with dry matter (r= — 0940) and grain yield (r= —0-939) whereas that, for the period grain formation to harvest stage, showed significantly higher correlation lpar;r= —0-967) for crop water use. Significant and positive correlations between dry matter, leaf area and grain yield with infrared/red, normalised difference (ND), transformed vegetation index and greenness index were attained with the latter providing the highest degree of predictability. Spectral indices measured between flowering to milking stages gave the best prediction indicating the suitability of this period for crop growth assessment by this technique. Inter-stage sensitivity analysis by using multiple regression approach also revealed that greenness and transformed vegetation indices could provide better prediction of dry matter and grain yield. From the values of regression coefficients the jointing to beginning of milk formation period of the crop was found to be the most sensitive stage influencing the yield of crop.     

Simplification of Switching Functions Involving a very Large Number of ‘Don't Care’ States†

A method of simplification of switching functions involving a very large number of ‘ don't care’ states is suggested in the present paper. First a tabular technique is suggested which generates all the prime implicants starting from the maxterm type expressions of switching functions, avoiding generation of the prime implicants formed of ‘don't care’ states only. The technique presented is simple and iterative. Next it is suggested how the knowledge of the sets of prime implicants thus obtained can be utilized for finding minimal or other irredundant sums of switching functions.     

On a Method of Obtaining all the Irredundant Covers of Switching Functions by Utilizing their Connected Cover Term Matrices†

A simple, iterative technique for finding till the irredundant covers of switching functions by utilizing their connected cover term matrices has been suggested in the present paper, it has been shown that whenever the columns of the cover table of a function have to be arranged in a number of matrices having mutually common prime implicants between them, the generation of the redundant product terms can be greatly minimized while that of the duplicate product terms can be completely avoided by suitably dividing the cover table into a number of sub-tables.     

Prioritization of kanbans in the case of a single station serving multiple downstream stations

When implementing the kanban method in non-serial production lines, an interesting prioritization problem arises. Often a single server station will be linked with M different downstream stations via M separate kanban loops. Then the K-priority problem may be described as determining which kanban card should be processed next, given that empty cards are waiting in more than one loop. The objective in prioritizing the kanbans is to reduce back order or shortage costs and inventory costs at the downstream stations. Utilizing the theory of Markovian decision process and dynamic programming concepts, a solution to the K-priority problem is developed. This solution is labelled the K-rule, and was found to outperform the first-come-first-served and longest queue rules, plus a cost inclusive heuristic rule, in experimental tests,     

Modelling of post-rain attenuation of microwaves at 22·235 GHz in relation to vertical transport of water vapour

Abstract

Attenuation of microwaves (up to 30 GHz) around the water vapour absorption line on 22·235 GHz tends to persist even after the stoppage of rain during the monsoon season. A theoretical model has been developed for the post-rain residual absorption of radio waves at 22·235 GHz (λ = 1·349 cm) by considering the vertical transport of water vapour in the region of the rain event. The theoretical estimate agrees fairly well with that obtained experimentally during different post-rain events, recorded by a radiometer, operating at the Institute of Radio Physics and Electronics, Calcutta University on a round-the-clock basis.     

On fine structure of dot echoes as observed by acoustic sounder

Sometimes in the lower atmospheric boundary layer, depending upon the prevailing micro-/meso-scale meteorological condition, ‘dot’ (also known as ‘lump’) type echo structures appear generally during night-time with light wind and stable stratifications. They are associated often with disturbed atmospheric boundary layer conditions like the occurrence of thunderstorms and/or of precipitation. Digitization and scanning of individual dot/lump echo structure can indicate a cluster of points with varying echo intensity levels. In the coastal region of Calcutta they are found to be spreading vertically and the size of the cluster depends on the vertical height of occurrence. Using image processing technique fine structures of these echoes have been processed, their statisticalnature has been analysed and reported in this paper.