A generalized geo-hazard warning system

An automated geo-hazard warning system is the need of the hour. It is integration of automation in hazard evaluation and warning communication. The primary objective of this paper is to explain a geo-hazard warning system based on Internet-resident concept and available cellular mobile infrastructure that makes use of geo-spatial data. The functionality of the system is modular in architecture having input, understanding, expert, output and warning modules. Thus, the system provides flexibility in integration between different types of hazard evaluation and communication systems leading to a generalized hazard warning system. The developed system has been validated for landslide hazard in Indian conditions. It has been realized through utilization of landslide causative factors, rainfall forecast from NASA's TRMM (Tropical Rainfall Measuring Mission) and knowledge base of landslide hazard intensity map and invokes the warning as warranted. The system evaluated hazard commensurate with expert evaluation within 5-6 % variability, and the warning message permeability has been found to be virtually instantaneous, with a maximum time lag recorded as 50 s, minimum of 10 s. So it could be concluded that a novel and stand-alone system for dynamic hazard warning has been developed and implemented. Such a handy system could be very useful in a densely populated country where people are unaware of the impending hazard.

Generalizing the Amplify-and-Forward Relay Gain Model: An Optimal SEP Perspective

Two models for AF relaying, namely, fixed gain and fixed power relaying, have been extensively studied in the literature given their ability to harness spatial diversity. In fixed gain relaying, the relay gain is fixed but its transmit power varies as a function of the source-relay channel gain. In fixed power relaying, the relay transmit power is fixed, but its gain varies. We revisit and generalize the fundamental two-hop AF relaying model. We present an optimal scheme in which an average power constrained AF relay adapts its gain and transmit power to minimize the symbol error probability (SEP) at the destination. Also derived are insightful and practically amenable closed-form bounds for the optimal relay gain. We then analyze the SEP of MPSK, derive tight bounds for it, and characterize the diversity order for Rayleigh fading. Also derived is an SEP approximation that is accurate to within 0.1 dB. Extensive results show that the scheme yields significant energy savings of 2.0-7.7 dB at the source and relay. Optimal relay placement for the proposed scheme is also characterized, and is different from fixed gain or power relaying. Generalizations to MQAM and other fading distributions are also discussed.

Review of Geohazard Warning Systems toward Development of a Popular Usage Geohazard Warning Communication System

The advent and evolution of geohazard warning systems is a very interesting study. The two broad fields that are immediately visible are that of geohazard evaluation and subsequent warning dissemination. Evidently, the latter field lacks any systematic study or standards. Arbitrarily organized and vague data and information on warning techniques create confusion and indecision. The purpose of this review is to try and systematize the available bulk of information on warning systems so that meaningful insights can be derived through decidable flowcharts, and a developmental process can be undertaken. Hence, the methods and technologies for numerous geohazard warning systems have been assessed by putting them into suitable categories for better understanding of possible ways to analyze their efficacy as well as shortcomings. By establishing a classification scheme based on extent, control, time period, and advancements in technology, the geohazard warning systems available in any literature could be comprehensively analyzed and evaluated. Although major advancements have taken place in geohazard warning systems in recent times, they have been lacking a complete purpose. Some systems just assess the hazard and wait for other means to communicate, and some are designed only for communication and wait for the hazard information to be provided, which usually is after the mishap. Primarily, systems are left at the mercy of administrators and service providers and are not in real time. An integrated hazard evaluation and warning dissemination system could solve this problem. Warning systems have also suffered from complexity of nature, requirement of expert-level monitoring, extensive and dedicated infrastructural setups, and so on. The user community, which would greatly appreciate having a convenient, fast, and generalized warning methodology, is surveyed in this review. The review concludes with the future scope of research in the field of hazard warning systems and some suggestions for developing an efficient mechanism toward the development of an automated integrated geohazard warning system. DOI: 10.1061/(ASCE)NH.1527-6996.0000078. (C) 2012 American Society of Civil Engineers.

Generalized bidirectional multi-pair multi-antennawireless network coding

In this paper, we focus on increasing the throughput and diversity of network coded MIMO transmissions in bidirectional multi-pair wireless relay networks. All nodes have multi-antenna capability. Pairs of nodes want to exchange messages via a relay having multi-antenna and encoding/decoding capability. Nodes transmit their messages to the relay in the first (MAC) phase. The relay decodes all the messages and XORs them and broadcasts the XORed message in the second (BC) phase. We develop a generalized framework for bidirectional multi-pair multi-antenna wireless network coding, which models different MIMO transmission schemes including spatial multiplexing (V-BLAST), orthogonal STBC (OSTBC), and non-orthogonal STBC (NO-STBC) in a unified way. Enhanced throughputs are achieved by allowing all nodes to simultaneously transmit at their full rate. High diversity orders are achieved through the use of NO-STBCs, characterized by full rate and full transmit diversity. We evaluate and compare the performance of VBLAST, OSTBC, and NO-STBC schemes in one-dimensional 1-pair linear network (one pair of nodes and a relay) and two-dimensional 2-pair `cross' network (two pairs of nodes and a relay).

Asymptotics of the invariant measure in mean field models with jumps

We consider the asymptotics of the invariant measure for the process of spatial distribution of N coupled Markov chains in the limit of a large number of chains. Each chain reflects the stochastic evolution of one particle. The chains are coupled through the dependence of transition rates on the spatial distribution of particles in the various states. Our model is a caricature for medium access interactions in wireless local area networks. Our model is also applicable in the study of spread of epidemics in a network. The limiting process satisfies a deterministic ordinary differential equation called the McKean-Vlasov equation. When this differential equation has a unique globally asymptotically stable equilibrium, the spatial distribution converges weakly to this equilibrium. Using a control-theoretic approach, we examine the question of a large deviation from this equilibrium.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Antenna Selection in Interference-Constrained Underlay Cognitive Radios: SEP-Optimal Rule and Performance Benchmarking

In the underlay mode of cognitive radio, secondary users are allowed to transmit when the primary is transmitting, but under tight interference constraints that protect the primary. However, these constraints limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which exploit spatial diversity with less hardware, help improve secondary system performance. We develop a novel and optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained multiple-input-single-output secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gain of the channel from the secondary transmit antenna to the primary receiver and from the secondary transmit antenna to the secondary receive antenna. We also propose a simpler, tractable variant of the optimal rule that performs as well as the optimal rule. We then analyze its SEP with L transmit antennas, and extensively benchmark it with several heuristic selection rules proposed in the literature. We also enhance these rules in order to provide a fair comparison, and derive new expressions for their SEPs. The results bring out new inter-relationships between the various rules, and show that the optimal rule can significantly reduce the SEP.

A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

Multispecies coexistence of trees in tropical forests: spatial signals of topographic niche differentiation increase with environmental heterogeneity

Neutral and niche theories give contrasting explanations for the maintenance of tropical tree species diversity. Both have some empirical support, but methods to disentangle their effects have not yet been developed. We applied a statistical measure of spatial structure to data from 14 large tropical forest plots to test a prediction of niche theory that is incompatible with neutral theory: that species in heterogeneous environments should separate out in space according to their niche preferences. We chose plots across a range of topographic heterogeneity, and tested whether pairwise spatial associations among species were more variable in more heterogeneous sites. We found strong support for this prediction, based on a strong positive relationship between variance in the spatial structure of species pairs and topographic heterogeneity across sites. We interpret this pattern as evidence of pervasive niche differentiation, which increases in importance with increasing environmental heterogeneity.

Large scale features and assessment of spatial scale correspondence between TMPA and IMD rainfall datasets over Indian landmass

Daily rainfall datasets of 10 years (1998-2007) of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) version 6 and India Meteorological Department (IMD) gridded rain gauge have been compared over the Indian landmass, both in large and small spatial scales. On the larger spatial scale, the pattern correlation between the two datasets on daily scales during individual years of the study period is ranging from 0.4 to 0.7. The correlation improved significantly (similar to 0.9) when the study was confined to specific wet and dry spells each of about 5-8 days. Wavelet analysis of intraseasonal oscillations (ISO) of the southwest monsoon rainfall show the percentage contribution of the major two modes (30-50 days and 10-20 days), to be ranging respectively between similar to 30-40% and 5-10% for the various years. Analysis of inter-annual variability shows the satellite data to be underestimating seasonal rainfall by similar to 110 mm during southwest monsoon and overestimating by similar to 150 mm during northeast monsoon season. At high spatio-temporal scales, viz., 1 degrees x1 degrees grid, TMPA data do not correspond to ground truth. We have proposed here a new analysis procedure to assess the minimum spatial scale at which the two datasets are compatible with each other. This has been done by studying the contribution to total seasonal rainfall from different rainfall rate windows (at 1 mm intervals) on different spatial scales (at daily time scale). The compatibility spatial scale is seen to be beyond 5 degrees x5 degrees average spatial scale over the Indian landmass. This will help to decide the usability of TMPA products, if averaged at appropriate spatial scales, for specific process studies, e.g., cloud scale, meso scale or synoptic scale.

Nonparametric distributed sequential detection via universal source coding

We consider nonparametric or universal sequential hypothesis testing when the distribution under the null hypothesis is fully known but the alternate hypothesis corresponds to some other unknown distribution. These algorithms are primarily motivated from spectrum sensing in Cognitive Radios and intruder detection in wireless sensor networks. We use easily implementable universal lossless source codes to propose simple algorithms for such a setup. The algorithms are first proposed for discrete alphabet. Their performance and asymptotic properties are studied theoretically. Later these are extended to continuous alphabets. Their performance with two well known universal source codes, Lempel-Ziv code and KT-estimator with Arithmetic Encoder are compared. These algorithms are also compared with the tests using various other nonparametric estimators. Finally a decentralized version utilizing spatial diversity is also proposed and analysed.

Modified current space vector based powerline communication method for distributed inverters interfaced smart grids

The following paper presents a Powerline Communication (PLC) Method for grid interfaced inverters, for smart grid application. The PLC method is based on the concept of the composite vector which involves multiple components rotating at different harmonic frequencies. The pulsed information is modulated on the fundamental component of the grid current as a specific repeating sequence of a particular harmonic. The principle of communication is same as that of power flow, thus reducing the complexity. The power flow and information exchange are simultaneously accomplished by the interfacing inverters based on current programmed vector control, thus eliminating the need for dedicated hardware. Simulation results have been shown for inter-inverter communication, both under ideal and distorted conditions, using various harmonic modulating signals.

Spatial memory deficits in maternal iron deficiency paradigms are associated with altered glucocorticoid levels

``The goal of this study was to examine the effect of maternal iron deficiency on the developing hippocampus in order to define a developmental window for this effect, and to see whether iron deficiency causes changes in glucocorticoid levels. The study was carried out using pre-natal, post-natal, and pre + post-natal iron deficiency paradigm. Iron deficient pregnant dams and their pups displayed elevated corticosterone which, in turn, differentially affected glucocorticoid receptor (GR) expression in the CA1 and the dentate gyrus. Brain Derived Neurotrophic Factor (BDNF) was reduced in the hippocampi of pups following elevated corticosterone levels. Reduced neurogenesis at P7 was seen in pups born to iron deficient mothers, and these pups had reduced numbers of hippocampal pyramidal and granule cells as adults. Hippocampal subdivision volumes also were altered. The structural and molecular defects in the pups were correlated with radial arm maze performance; reference memory function was especially affected. Pups from dams that were iron deficient throughout pregnancy and lactation displayed the complete spectrum of defects, while pups from dams that were iron deficient only during pregnancy or during lactation displayed subsets of defects. These findings show that maternal iron deficiency is associated with altered levels of corticosterone and GR expression, and with spatial memory deficits in their pups.'' (C) 2013 Elsevier Inc. All rights reserved.

Data Fusion of Dual Foot-Mounted INS to Reduce the Systematic Heading Drift

In this report, we investigate the problem of applying a range constraint in order to reduce the systematic heading drift in a foot-mounted inertial navigation system (INS) (motion-tracking). We make use of two foot-mounted INS, one on each foot, which are aided with zero-velocity detectors. A novel algorithm is proposed in order to reduce the systematic heading drift. The proposed algorithm is based on the idea that the separation between the two feet at any given instance must always lie within a sphere of radius equal to the maximum possible spatial separation between the two feet. A Kalman filter, getting one measurement update and two observation updates is used in this algorithm.