Modified covariance intersection for data fusion in distributed nonhomogeneous monitoring systems network

Monitoring networks contain monitoring nodes that observe an area of interest to detect any possible existing object and estimate its states. Each node has characteristics such as probability of detection and clutter density that may have different values for distinct nodes in nonhomogeneous monitoring networks. This paper proposes a modified covariance intersection method for data fusion in such networks. It is derived by formulating a mixed game model between neighbor monitoring nodes as players and considering the inverse of the trace of fused covariance matrix as players' utility function. Monitoring nodes estimate the states of any possible existing object by applying joint target detection and tracking filter on their own observations. Processing nodes fuse the estimated states received from neighbor monitoring nodes by the proposed modified covariance intersection. It is validated by simulating target detection and tracking problem in 2 situations: 1 target and unknown number of targets.     

Salicylic acid nanoparticles (SANPs) improve growth and phytoremediation efficiency of Isatis cappadocica Desv., under As stress

Arsenic (As) is a toxic metalloid dispersed in the environment and it cause serious toxicity to plants. Salicylic acid (SA) plays an important role in many plant growth processes involved in plant defence against heavy metal or metalloid stress. In the present study, for the first time, chitosan nanoparticles was synthesised, loaded by SA and the positive role of SA on growth and phytoremediation efficiency of Isatis cappadocica against As toxicity were evaluated. The highest arsenate treatment (1200 µM) caused a decrease in plant biomass that, however, its combined application with salicylic acid nanoparticles (SANPs) substantially increase in shoot height, root length and their biomass production compared with As stressed plants. The pretreatment of SANPs by increasing arsenate supply, simultaneously increased the As concentration in roots and shoots of I. cappadocica which reached a maximum of 705 and 1188 mg/kg, respectively. This results suggest that high levels of As stress induce stress status in I. cappadocica which SANPs pretreatment application limit these toxic effects of As. Therefore, SANPs has a significant beneficial effect on the growth and phytoremediation efficiency of I. cappadocica subjected to As stress.Inspec keywords: nanoparticles, nanobiotechnology, botany, toxicology, arsenic, biological techniques, polymersOther keywords: salicylic acid nanoparticles, SANP, plant growth efficiency, phytoremediation efficiency, Isatis cappadocica Desv, arsenic stress, toxic metalloid, plant toxicity, plant defence, metalloid stress, chitosan nanoparticles, plant biomass, shoot height, root length, biomass production, I. cappadocica, As     

FT-PDC: an enhanced hybrid congestion-aware fault-tolerant routing technique based on path diversity for 3D NoC

In recent years, using three-dimensional Network-on-Chip (3D-NoC) has increased due to its high performance and integration of processing elements. However, as technology evolves, dimension of processing elements and the number of connections are decreasing and this increases their sensitivity to external factors. Therefore, fault detection is one of the most important challenges of designing 3D-NoC because even a transistor not working well may cause the whole system not to work. Many methods have been provided so far to make three-dimensional NoC tolerant against fault, but most of these methods suffer from some disadvantages. For example, their fault detection models are not strong enough or they do not consider the network traffic. Regarding these problems, in this article, a routing technique called fault-tolerant routing algorithm based on path diversity and congestion (FT-PDC) for three-dimensional mesh connectivity based on NoC is provided that has some features like finding the shortest current path, considering fault in vertical and horizontal links, and considering path diversity and congestion. In addition to these features, FT-PDC could solve the problems of other methods to a great extent considering network traffic conditions and sending the packet from a path in which traffic conditions are two hops better than the other paths. These features have led to the superiority of the proposed method over other methods. The simulation results in the Noxim simulator show that latency and throughput of FT-PDC compared to similar recent methods have significantly improved.

     

Query optimization mechanisms in the cloud environments: A systematic study

The goal of a query optimizer is to provide an optimal Query Execution Plan (QEP) by comparing alternative query plans. In a distributed database system over cloud environment, the relations required by a query plan may be stored at multiple sites. This leads to an exponential increase in the number of possible equivalent plan alternatives to find an optimal QEP. Although it is not computationally reasonable to explore exhaustively all possible plans in such large search space. Although query optimization mechanisms are important in the cloud environments, to the best of our knowledge, there exists no complete and systematic review on investigating these issues. Therefore, in this paper, four categories to study these mechanisms are considered which are search‐based, machine learning‐based, schema‐based, and security‐based mechanisms. Also, this paper represents the advantages and disadvantages of the selected query optimization techniques and investigates the metrics of their techniques. Finally, the important challenges of these techniques are reviewed to develop more efficient query optimization techniques in the future.     

Synthesis and characterization of maleylated cellulose-<Emphasis Type="Italic">g</Emphasis>-polyacrylamide hydrogel using TiO<Subscript>2</Subscript> nanoparticles under sunlight

Graft polymerization onto the cellulose is one way to produce semisynthetic copolymers and semiconductors were hardly used as initiators. Maleylated cellulose (MC) with different degree of carboxyl groups was synthesized and degree of carboxyl groups was determined using titration method. Then the graft copolymers of acrylamide (AM) on MC were synthesized by titanium dioxide semiconductor photoinitiator in aqueous suspension under sunlight. The effect of different parameters, such as the degree of carboxyl groups, degassing of atmosphere, reactor type, light source, MC/AM ratio, and initiator concentration, was evaluated in the synthesis of graft copolymers. MC with a high degree of carboxyl groups about 2.8 mmol g^?1 was selected for graft photopolymerization. Maximum monomer conversion (55%) for Maleylated cellulose-g-polyacrylamide (MC-g-PAM) was achieved with 0.5 mg TiO₂, MC/AM = 0.056, argon atmosphere, sunlight source, and double quartz tube reactor. The maximum amount of equilibrium swelling (41 g g^?1) was achieved for MC-g-PAM with 34% monomer conversion. The resulting graft copolymers were characterized by FT-IR, SEM, and TGA. Synthesis of MC-g-PAM using TiO₂ nanoparticles (NPs) as the initiator was done successfully that shows the TiO₂ NPs are useable in graft polymerization of acrylamide monomers onto the MC under sunlight.     

Rapid and highly efficient synthesis of thioureas in biocompatible basic choline hydroxide

A straightforward and convenient synthesis of symmetrical thiourea derivatives by the reaction of primary amines and carbon disulfide in biocompatible basic choline hydroxide is presented. A variety of biologically important thiourea derivatives can be obtained in good to excellent yields without a tedious work-up under mild reaction conditions. A series of primary aliphatic and aromatic amines with different substituted functional groups have been converted to thiourea derivatives under milder reaction conditions and short reaction times.     

Automatic fire detection based on soft computing techniques: review from 2000 to 2010

Automatic fire detection system is a system that is capable of assessing environmental factors and their effects on the environment as well as predicting the occurrence of fire in the early stages and even before the outbreak. There are two perspectives in fire detection: fire detection in forests or jungles and fire detection in occupied or residential areas. Automatic fire detection has attracted increased attention due to its importance in decreasing fire damage. There are many studies that have considered appropriate techniques for early fire detection. In recent years researches have been studying technical developments in this field aimed at exploiting wireless communications networks, detection systems and fire prediction systems design. In this paper the automatic fire detection researches using intelligent techniques from 2000 to 2010 is reviewed. We could classify researches to four categories: fire detectors, reduce false alarms systems, fire data analysis and fire predictors. We also classify the intelligent techniques outlined in the researches for each category.     

A PSO-based model to increase the accuracy of software development effort estimation

Development effort is one of the most important metrics that must be estimated in order to design the plan of a project. The uncertainty and complexity of software projects make the process of effort estimation difficult and ambiguous. Analogy-based estimation (ABE) is the most common method in this area because it is quite straightforward and practical, relying on comparison between new projects and completed projects to estimate the development effort. Despite many advantages, ABE is unable to produce accurate estimates when the importance level of project features is not the same or the relationship among features is difficult to determine. In such situations, efficient feature weighting can be a solution to improve the performance of ABE. This paper proposes a hybrid estimation model based on a combination of a particle swarm optimization (PSO) algorithm and ABE to increase the accuracy of software development effort estimation. This combination leads to accurate identification of projects that are similar, based on optimizing the performance of the similarity function in ABE. A framework is presented in which the appropriate weights are allocated to project features so that the most accurate estimates are achieved. The suggested model is flexible enough to be used in different datasets including categorical and non-categorical project features. Three real data sets are employed to evaluate the proposed model, and the results are compared with other estimation models. The promising results show that a combination of PSO and ABE could significantly improve the performance of existing estimation models.     

Removal of Acid Orange 7 and Remazol Black 5 reactive dyes from aqueous solutions using a novel biosorbent

This study utilizes canola stalks (CS), an agro-residue, as a biosorbent to remove two different dyes, namely Acid Orange 7 (AO7) and Remozol Black 5 (RB5) from aqueous solutions. The effects of operational parameters on the efficiency of dye removal including pH, adsorbent mass, initial dye concentration and contact time have been investigated. For both tested dyes, the maximum absorption capacity was reached at initial pH 2.5 and 120 min contact time. The results showed that the absorption of both dyes depended on the pH of milieu, temperature, dye and CS concentrations. Freundlich and Langmuir models were used to analyze the obtained experimental data. The isotherms are found to be linear over the entire concentration range for both dyes. The highest value of linear correlation coefficients for AO7 (0.9926) and RB5 (0.9882) showed that the Langmuir is the best model to fit the experimental data. Kinetic study of absorption was done applying the pseudo first-order and the pseudo second-order equations. Absorption of both dyes could be well predicted by the pseudo second-order equation. The obtained results are very promising since: (i) high levels of dye removal (> 90%) were achieved with low contact times biosorbent/dye (less than 20 min contact); and (ii) the whole CS can be successfully used as biosorbent of AO7 and RB5 dyes in aqueous solution without needing any chemical modifications.     

Analysis and Assessment of Hydrochemical Characteristics of Maragheh-Bonab Plain Aquifer,Northwest of Iran

The present study aims at assessing the hydrochemistry of the groundwater system of the Maragheh-Bonab Plain located in the East Azarbaijan Province, northwest of Iran. The groundwater is used mainly for drinking, agriculture and industry. The study also discusses the issue of the industrial untreated wastewater discharge to the Plain aquifer that is a high Ca-Cl water type with TDS value of about 150 g/L. The hydrogeochemical study is conducted by collecting and analyzing the groundwater samples from July and September of 2013. The studied system contains three major groundwater types, namely Ca–Mg–HCO₃, Na–Cl, and non-dominant water, based on the analysis of the major ions. The main processes contributing to chemical compositions in the groundwater are the dissolution along the flow path, dedolomitisation, ion exchange reactions, and the mixing with wastewater. According to the computed water quality index (WQI) ranging from 25.45 to 194.35, the groundwater in the plain can be categorized into “excellent water”, “good water”, and “poor water”. There is a resemblance between the spatial distribution of the WQI and hydrochemical water types in the Piper diagram. The “excellent” quality water broadly coincides with the Ca-Mg-HCO₃ water type. The “poor” water matches with the Na–Cl water type, and the “good” quality water coincides with blended water. The results indicate that this aquifer suffers from intense human activities which are forcing the aquifer into a critical condition.