Adaptive Processing of Spatial-Keyword Data Over a Distributed Streaming Cluster

The widespread use of GPS-enabled smartphones along with the popularity of micro-blogging and social networking applications, e.g., Twitter and Facebook, has resulted in the generation of huge streams of geo-tagged textual data. Many applications require real-time processing of these streams. For example, location-based e-coupon and ad-targeting systems enable advertisers to register millions of ads to millions of users. The number of users is typically very high and they are continuously moving, and the ads change frequently as well. Hence sending the right ad to the matching users is very challenging. Existing streaming systems are either centralized or are not spatial-keyword aware, and cannot efficiently support the processing of rapidly arriving spatial-keyword data streams. This paper presents Tornado, a distributed spatial-keyword stream processing system. Tornado features routing units to fairly distribute the workload, and furthermore, co-locate the data objects and the corresponding queries at the same processing units. The routing units use the Augmented-Grid, a novel structure that is equipped with an efficient search algorithm for distributing the data objects and queries. Tornado uses evaluators to process the data objects against the queries. The routing units minimize the redundant communication by not sending data updates for processing when these updates do not match any query. By applying dynamically evaluated cost formulae that continuously represent the processing overhead at each evaluator, Tornado is adaptive to changes in the workload. Extensive experimental evaluation using spatio-textual range queries over real Twitter data indicates that Tornado outperforms the non-spatio-textually aware approaches by up to two orders of magnitude in terms of the overall system throughput

Evaluation of routing protocol with multi-mobile sinks in WSNs using QoS and energy consumption parameters

An efficient networks’ energy consumption and Quality of Services (QoS) are considered the most important issues, to evaluate the route quality of the designed routing protocol in Wireless Sensor Networks (WSNs). This study is presented an evaluation performance technique to evaluate two routing protocols: Secure for Mobile Sink Node location using Dynamic Routing Protocol (SMSNDRP) and routing protocol that used K-means algorithm to form Data Gathered Path (KM-DGP), on small and large network with Group of Mobile Sinks (GMSs). The propose technique is based on QoS and sensor nodes’ energy consumption parameters to assess route quality and networks’ energy usage. The evaluation technique is conducted on two routing protocols in two phases: The first phase is used to evaluate the route quality and networks’ energy consumption on small WSN with one mobile Sink Node (SN) and GMSs. The second phase, is used to evaluate the route quality and networks’ energy consumption on large network (four WSNs) with GMSs. The two phases are implementated by creating five sceneries via using NS2.3 simulator software. The implementation results of the proposed performance evaluation technique have demonstrated that SMSNDRP gives better networks’ energy consumption on small single network in comparison with KM-DGP. Also, it gives high quality route in large network that used four mobile SN, in contrast to KM-DGP that used sixteen mobile SNs. While in large network, it found that KM-DGP with sixteen mobile SNs gives better networks’ energy consumption in comparison with SMSNDRP with four mobile SNs

Amelioration of a saline sodic soil through cultivation of a salt-tolerant grass Leptochloa fusca

Reclamation of saline lands seems difficult for climatic and economic reasons, but cultivation of salt-tolerant plants is an approach to increasing productivity and improvement of salt-affected wastelands. A five-year field study was conducted to evaluate the effects of growing a salt-tolerant species Leptochloa fusca (L.) Kunth (kallar grass) on chemical properties of a saline sodic soil irrigated with poor quality groundwater. Soil salinity, sodicity and pH decreased exponentially by growing kallar grass as a result of leaching of salts from surface (0–20 cm) to lower depths (>100 cm). Concentrations of soluble cations (Na+, K+, Ca2+ and Mg2+) and anions (Cl−, SO42− and HCO3−) were reduced through to greater soil depths. A significant decline in soil pH was attributed to release of CO2 by grass roots and solublization of CaCO3. Both soil salinity and soil pH were significantly correlated with Na+, Ca2+, Mg2+, K+, Cl−, HCO3− and sodium adsorption ratio (SAR). Significant correlations were found between soluble cations (Na+, Ca2+ and K+), soluble anions (Cl−, SO42− and HCO3−) and the SAR. In contrast, there were negative correlations between soil organic matter content and all chemical properties. The ameliorative effects on the soil chemical environment were pronounced after three years of growing kallar grass. Cultivation of kallar grass enhanced leaching and interactions among soil chemical properties and thus restored soil fertility. The soil maintained the improved characteristics with further growth of the grass up to five years suggesting that growing salt-tolerant plants is a sustainable approach to biological amelioration of saline wastelands.J. Akhter, K. Mahmood, K.A. Malik, S. Ahmed and R. Murra

Evaluation, Antioxidant, Antimitotic and Anticancer Activity of Iron Nanoparticles Prepared by Using Water Extract of Vitis Vinifera L. Leaves

The water extract of Vitis vinifera was used for the rapid synthesis of the iron nanoparticle, which is very simple and eco-friendly in nature. The UV-visible spectroscopy technique was employed to establish the formation of which inhibition onion root growth in a dose-dependent manner. A decrease in the mitotic index may indicate its genotoxic effect on Allium cepa root assay. Nanoparticle was studied for its in vitro anti-inflammatory and antioxidant activity using different models, all the testing, gave significant correlation existed between concentrations of the nanoparticle and percentage inhibition of protein denaturation and scavenging free radicals.  These results clearly indicate that iron nanoparticle is effective against inflammation and free radical-mediated disease

A Multidimensional Approach to Measure Poverty in Rural Bangladesh

Poverty is increasingly being understood as a multidimensional phenomenon. Other than income-consumption, which has been extensively studied in the past, health, education, shelter, and social involvement are among the most important dimensions of poverty. The present study attempts to develop a simple tool to measure poverty in its multidimensionality where it views poverty as an inadequate fulfillment of basic needs, such as food, clothing, shelter, health, education, and social involvement. The scale score ranges between 72 and 24 and is constructed in such a way that the score increases with increasing level of poverty. Using various techniques, the study evaluates the poverty-measurement tool and provides evidence for its reliability and validity by administering it in various areas of rural Bangladesh. The reliability coefficients, such as test-retest coefficient (0.85) and Cronbach's alpha (0.80) of the tool, were satisfactorily high. Based on the socioeconomic status defined by the participatory rural appraisal (PRA) exercise, the level of poverty identified by the scale was 33% in Chakaria, 26% in Matlab, and 32% in other rural areas of the country. The validity of these results was tested against some traditional methods of identifying the poor, and the association of the scores with that of the traditional indicators, such as ownership of land and occupation, asset index (r=0.72), and the wealth ranking obtained from the PRA exercise, was consistent. A statistically significant inverse relationship of the poverty scores with the socioeconomic status was observed in all cases. The scale also allowed the absolute level of poverty to be measured, and in the present study, the highest percentage of absolute poor was found in terms of health (44.2% in Chakaria, 36.4% in Matlab, and 39.1% in other rural areas), followed by social exclusion (35.7% in Chakaria, 28.5% in Matlab, and 22.3% in other rural areas), clothing (6.2% in Chakaria, 8.3% in Matlab, and 20% in other rural areas), education (14.7% in Chakaria, 8% in Matlab, and 16.8% in other rural areas), food (7.8% in Chakaria, 2.9% in Matlab and 3% in other rural areas), and shelter (0.8% in Chakaria, 1.4% in Matlab, and 3.7% in other rural areas). This instrument will also prove itself invaluable in assessing the individual effects of poverty-alleviation programmes or policies on all these different dimensions