Starch urea formaldehyde matrix encapsulation of solid agrochemicals. I. Matrix synthesis and characterizations

A starch urea formaldehyde (starch-UF) matrix has been studied for application to the encapsulation of a solid insecticide. The pertinent parameters relating to the matrix synthesis have been identified and the influences of these parameters on release of the insecticide from the starch UF matrix have been investigated. The key parameter controlling the rate of release is the urea to starch ratio. It is shown that the release process can be described in terms of the generalized equation M_t/M_∞ = ktⁿ where k and n vary with system variables.     

Diagnosis of Wireless Sensor Networks in Presence of Permanent and Intermittent Faults

In this paper we consider the problem of distributed fault diagnosis in Wireless Sensor Networks (WSNs). The proposed Fault Diagnosis Algorithm (FDA) aims to handle both permanent and intermittent faults. The sensor nodes with permanent communication faults can be diagnosed by using the conventional time-out mechanism. In contrast, it is difficult to detect intermittent faults due to their inherent unpredictable behavior. The FDA is based on the comparison of sensor measurements and residual energy values of neighboring sensor nodes, exploiting their spatial correlations. To handle intermittent faults, the comparisons are made for \(r\) rounds. Two special cases of intermittent faults are considered: one, when an intermittently faulty node sends similar sensor measurement and similar residual energy value to some of its neighbors in all \(r\) rounds; another, when it sends these values, either or both of which deviates significantly from that of some neighbors in all \(r\) rounds. Through extensive simulation and analysis, the proposed scheme is proved to be correct, complete, and efficient to handle intermittent faults and hence, well suited for WSNs.     

Starch urea formaldehyde matrix encapsulation of solid agrochemicals. II. Release mechanism and release modeling

Based on experimental observation, a mechanism is proposed to describe the release of carbofuran from a starch-UF matrix. A simple mathematical model is developed to describe the diffusion-controlled release of a solid insecticide from a porous starch-UF matrix undergoing both volume and surface erosions. The model is tested with the release data collected for different matrices and with different pH values of the environmental liquid. The comparison between the model predictions and data is found to be reasonably good. The model describes the release process at different pH values by accounting for the influence of pH on the erosion rates.     

A Mean Phi Model for Pressure Filtration of Fine and Colloidal Suspensions

A working model for engineering analysis of pressure filtration is presented. Based on the filtration characteristics of fine and colloidal suspensions, the process was divided into two stages. A time‐invariant spatially uniform volume fraction of solids approximation is invoked in the growing filter cake stage (stage 1). A time‐dependent spatially uniform volume fraction of solids assumption is made in the cake consolidation stage (stage 2). The two models, named collectively as Mean Phi (M‐P) model, have a common physical basis, seamless continuity between the stages and internal consistency. The M‐P model has only three parameters: terminal or equilibrium volume fraction of solids in the filter cake that is related to its compressive yield stress, critical volume fraction of solids, which joins stage 1 and stage 2, and a permeability factor, which is common to stages 1 and 2. The model is validated with a large number of colloidal suspensions filtered under highly diverse physical‐chemical process conditions. A Pareto profile is identified that relates the timescale of filtration and the extent of dewatering achieved, the two most important performance indices of the process.     

A model for microencapsulation in polyurea shell by means of interfacial polycondensation

A quasi-steady state model, based on two parallel modes of diffusion and a polycondensation reaction at the inside surface of a microcapsule, is formulated to compute the time of this microencapsulation process. The predicted times of encapsulation are in agreement with observed values reported in patents. It is also shown that, for small shell thickness, the process is reaction-controlled.     

Fault diagnosis in wireless sensor network using clonal selection principle and probabilistic neural network approach

The fault diagnosis in wireless sensor networks is one of the most important topics in the recent years of research work. The problem of fault diagnosis in wireless sensor network can be resembled with artificial immune system in many different ways. In this paper, a detection algorithm has been proposed to identify faulty sensor nodes using clonal selection principle of artificial immune system, and then the faults are classified into permanent, intermittent, and transient fault using the probabilistic neural network approach. After the actual fault status is detected, the faulty nodes are isolated in the isolation phase. The performance metrics such as detection accuracy, false alarm rate, false‐positive rate, fault classification accuracy, false classification rate, diagnosis latency, and energy consumption are used to evaluate the performance of the proposed algorithm. The simulation results show that the proposed algorithm gives superior results as compared with existing algorithms in terms of the performance metrics. The fault classification performance is measured by fault classification accuracy and false classification rate. It has also seen that the proposed algorithm provides less diagnosis latency and consumes less energy than that of the existing algorithms proposed by Mohapatra et al, Panda et al, and Elhadef et al for wireless sensor network.     

Fault diagnosis in wireless sensor network using negative selection algorithm and support vector machine

In this article, an improved negative selection algorithm (INSA) has been proposed to identify faulty sensor nodes in wireless sensor network (WSN) and then the faults are classified into soft permanent, soft intermittent, and soft transient fault using the support vector machine technique. The performance metrics such as fault detection accuracy, false alarm rate, false positive rate, diagnosis latency (DL), energy consumption, fault classification accuracy (FCA), and false classification rate (FCR) are used to evaluate the performance of the proposed INSA. The simulation result shows that the INSA gives better result as compared to the existing algorithms in terms of performance metrics. The fault classification performance is measured by FCA and FCR. It has also seen that the proposed algorithm gives less DL and consumes less energy than that of existing algorithms proposed by Mohapatra et al, Zhang et al, and Panda et al for WSN.     

Fire Controlling Under Uncertainty in Urban Region Using Smart Vehicular Ad hoc Network

Every year thousands of urban and industrial fires occur, which leads to the destruction of infrastructure, buildings, and loss of lives. One of the reasons behind this is the delayed transmission of information to the fire station and the nearer hospitals for ambulance service as the transmission of information is dependent on observer at the location where the fire is caught and cellular network. This paper proposed an automated routing protocol for the urban vehicular ad-hoc network to send the information from the location where the fire is caught to the nearest fire stations and hospitals with optimum service time. This transmission of information involves Road Side Unit (RSU) at the junction and the vehicles present in the transmission path. Selection of route to transmit faulty vehicle information from the RSU to the required faulty vehicle is based on a parameter called path value. The computation of path value is done by the attributes such as expected End To End (E2E) delay, the shortest distance to destination, the density of vehicle between the junctions, and attenuation. From the current junction, the selection of the next junction is based on minimum path value. The proposed routing protocol considers the performance parameters such as E2E delay, total service time (TST), number of network fragments or network gaps, number of hops, and attenuation for the propagation path for the evaluation of the proposed methodology. The proposed routing algorithm is implemented through OmNet++ and SUMO. Results obtained for the proposed routing protocol is compared with three existing VANET protocols (GSR, A-STAR, and ARP) in terms of End To End delay, number of hops, number of vehicular gaps, and Total Service Time (TST).

     

An analytical geometric range free localization scheme based on mobile beacon points in wireless sensor network

In many applications of wireless sensor network, the position of the sensor node is useful to identify the actuating response of the environment. The main idea of the proposed localization scheme is similar with most of the existing localization schemes, where a mobile beacon with global positioning system broadcast its current location coordinate periodically. The received information of the coordinates help other unknown nodes to localize themselves. In this paper, we proposed a localization scheme using mobile beacon points based on analytical geometry. Sensor node initially choose two distant beacon points, in-order to minimize its residence area. Later using the residence area, sensor node approximate the radius and half length of the chord with reference to one of the distant beacon point. Then the radius and half length of the chord are used to estimate the sagitta of an arc. Later, sensor node estimate its position using radius, half length of the chord, and sagitta of an arc. Simulation result shows the performance evaluation of our proposed scheme on various trajectories of mobile beacon such as CIRCLE, SPIRAL, S-CURVE, and HILBERT.     

Online Distributed Fault Diagnosis in Wireless Sensor Networks

This paper presents an online fault diagnosis algorithm for wireless sensor networks. This work explicitly takes into account the possibility of faults in different sections of sensor networks and communication channel. The diagnostic local view is obtained by exploiting the spatially correlated sensor measurements. These local views are then disseminated using a spanning tree of cluster heads. Our algorithm is shown to be energy efficient as it works in conjunction with the normal network activities and requires minimum additional diagnostic messages to be exchanged. Simulation results show that the performance of our algorithm is less sensitive to the average node degree for a wide range of fault rates.