Hybrid Authentication Using Node Trustworthy to Detect Vulnerable Nodes

An ad-hoc sensor network (ASN) is a group of sensing nodes that transmit data over a wireless link to a target node, direct or indirect, through a series of nodes. ASN becomes a high-risk group for several security exploits due to the sensor node’s limited resources. Internal threats are more challenging to protect against than external attacks. The nodes are grouped, and calculate each node’s trust level. The trust level is the result of combining internal and external trust degrees. Cluster heads (CH) are chosen based on the anticipated trust levels. The communications are then digitally signed by the source, encoded using a key pair given by a trustworthy CH, decoded by the recipient, and supervised by verifications. It authenticates the technique by identifying the presence of both the transmitter and the recipient. Our approach looks for a trustworthy neighboring node that meets the trust threshold condition to authenticate the key produced. The companion node reaffirms the node’s reliability by getting the public-key certification. The seeking sensor node and the certification issuer node must have a close and trusting relationship. The results of the proposed hybrid authentication using a node trustworthy (HANT) system are modeled and tested, and the suggested approach outperforms conventional trust-based approaches in throughput, latency, lifetime, and vulnerability methods.     

Multi-Objective Modified Particle Swarm Optimization for Test Suite Reduction (MOMPSO)

Software testing plays a pivotal role in entire software development lifecycle. It provides researchers with extensive opportunities to develop novel methods for the optimized and cost-effective test suite Although implementation of such a cost-effective test suite with regression testing is being under exploration still it contains lot of challenges and flaws while incorporating with any of the new regression testing algorithm due to irrelevant test cases in the test suite which are not required. These kinds of irrelevant test cases might create certain challenges such as code-coverage in the test suite, fault-tolerance, defects due to uncovered-statements and overall-performance at the time of execution. With this objective, the proposed a new Modified Particle Swarm optimization used for multi-objective test suite optimization. The experiment results involving six subject programs show that MOMPSO method can outer perform with respect to both reduction rate (90.78% to 100%) and failure detection rate (44.56% to 55.01%). Results proved MOMPSO outperformed the other stated algorithms.     

An overview on microwave processing of material: A special emphasis on glass melting

Material processing adopting microwave heating has emerged as an alternative tool owing to faster processing, a cleaner environment, and several other advantages. This review provides a summary of recent reports of microwave synthesis of materials. This study reviews the use of microwave energy for application in several material processing technologies apart from food processing. A special emphasis has been made in the processing of glass adopting microwave energy. Melting of glass comprising SiO₂, P₂O₅, B₂O₃ as the main building block has been discussed. It has been revealed that silica, a microwave transparent material as reported earlier, can be heated under microwave heating directly. Microwave absorption of raw materials and different glass system has been discussed. Dielectric properties, particularly loss tangent or loss factor, are presented for some glass composition. Less evaporation of ingredient and low contamination from the crucible wall are noticed during glass melting using microwave heating. Enhanced iron redox ratio (Fe⁺²/∑Fe) in microwave processing may be considered an advantage in the preparation of heat absorbing filter glass. Small-scale glass melting using the microwave heating has a significant impact on energy and time saving. However, the challenges associated with the upscaling glass melting with microwave heating and future scope have been talked about.     

Improved bioavailability and pharmacokinetics of tea polyphenols by encapsulation into gelatin nanoparticles

The authors prepared surface modified (with polyelectrolyte layers), tea polyphenols (TPP) encapsulated, gelatin nanoparticles (TPP‐GNP) and characterised them. The size of the spherical nanoparticles was ∼50 nm. Number of polyelectrolyte layers and incubation time influenced the encapsulation efficiency (EE); highest EE was noted in nanoparticles with six polyelectrolyte layers (TPP‐GNP‐6L) incubated for 4 h. TPP released from TPP‐GNP‐6L in simulated biological fluids indicated protection and controlled release of TPP due to encapsulation. Mathematical modelling indicated anomalous type as a predominant mode of TPP release. TPP‐GNP‐6L exhibited enhanced pharmacokinetics in rabbit model compared with free TPP. The area under the concentration‐time curve and mean residence time were significantly higher in TPP‐GNP‐6L compared with free TPP which provide an evidence of higher bioavailability of TPP due to encapsulation. The authors demonstrated that encapsulation of TPP into GNPs favoured slow and sustained release of TPP with improved pharmacokinetics and bioavailability thereby can prolong the action of TPP.Inspec keywords: gelatin, nanoparticles, encapsulation, biomedical materials, nanomedicine, particle size, polymer electrolytes, polymer films, nanofabricationOther keywords: bioavailability, pharmacokinetics, gelatin nanoparticles, surface modified tea polyphenols, polyelectrolyte layers, spherical nanoparticle size, incubation time, encapsulation efficiency, TPP‐GNP‐6L, simulated biological fluids, mathematical modelling, TPP release, rabbit model, concentration‐time curve, mean residence time, time 4 h     

Fairness of Transitions in Diagnosability of Discrete Event Systems

Failure diagnosability has been widely studied for discrete event system (DES) models because of modeling simplicity and computational efficiency due to abstraction. In the literature it is often held that for diagnosability, such models can be used not only for systems that fall naturally in the class of DES but also for the ones traditionally treated as continuous variable dynamic systems. A class of algorithms for failure diagnosability of DES models has been successfully developed for systems where fairness is not a part of the model. These algorithms are based on detecting cycles in the normal and the failure model that look identical. However, there exist systems with all transitions fair where the diagnosability condition that hinges upon this feature renders many failures non-diagnosable although they may actually be diagnosable by transitions out of a cycle. Hence, the diagnosability conditions based on cycle detection need to be modified to hold for many real-world systems where all transitions are fair. In this work, however, it is shown by means of an example that a system may have some transitions fair and some unfair. A new failure diagnosability mechanism is proposed for DES models with both fair and unfair transitions. Time complexity for deciding diagnosability of DES models with fair and unfair transitions is analyzed and compared with the time complexities of other DES diagnosability analysis methods reported in the literature.     

Application of evolutionary optimization techniques for finding the optimal set of concentric circular antenna array

In this paper the maximum sidelobe level (SLL) reductions, optimal beam patterns and optimal beam widths of various designs of three-ring planar concentric circular antenna arrays (PCCAA) are examined using three different classes of evolutionary optimization techniques to finally determine the global optimal three-ring PCCAA design and then establish some sort of ranking among the techniques. Apart from physical construction of a PCCAA, one may broadly classify its design into two major categories: uniformly excited arrays and non-uniformly excited arrays. The present paper assumes non-uniform excitations and uniform spacing of excitation elements in each three-ring PCCAA design and a design goal of maximizing SLL reduction associated with optimal beam patterns and beam widths. The design problem is modeled as an optimization problem for each PCCAA design and solved using different evolutionary optimization techniques to determine an optimum set of normalized excitation weights for PCCAA elements, which, when incorporated, results in a radiation pattern with optimal (maximum) SLL reduction. Among the various PCCAA designs, one which yields the global minimum SLL with global minimum first null beamwidth is the global optimal design. In this work the three-ring PCCAA containing (N₁ = 4, N₂ = 6, N₃ = 8) elements proves to be such global optimal design. The optimization techniques employed are real coded GA (RGA), canonical PSO (CPSO), craziness based PSO (CRPSO), evolutionary programming (BEP), hybrid evolutionary programming (HEP). While ranking the techniques after 30 total runs for each design, HEP, CRPSO, RGA, CPSO, BGA hold the first five ranks in order of optimization capability. HEP yields global minimum SLL (?32.86 dB) and global minimum BWFN (77.0°) for the optimal design. BEP often changes the rank from second to fifth depending on the design set. Further, when compared to a uniformly excited PCCAA having equal number of elements and same radii a reduction of major lobe beamwidth is also observed in the optimal non-uniformly excited case.     

An imperfect production process for time varying demand with inflation and time value of money – An EMQ model

The paper deals with an economic manufacturing quantity (EMQ) model for time-dependent (quadratic) demand pattern. Every manufacturing sector wants to produce perfect quality items. But in long run process, there may arise different types of difficulties like labor problem, machinery capabilities problems, etc., due to that the machinery systems shift from in-control state to out-of-control state as a result the manufacturing systems produce imperfect quality items. The imperfect items are reworked at a cost to become the perfect one. The rework cost may be reduced by improvements in product reliability i.e., the production process depend on time and also the reliability parameter. We want to determine the optimal product reliability and production rate that achieves the biggest total integrated profit for an imperfect manufacturing process using Euler–Lagrange theory to build up the necessary and sufficient conditions for optimality of the dynamic variables. Finally, a numerical example is discussed to test the model which is illustrated graphically also.     

Complete discriminant evaluation and feature extraction in kernel space for face recognition

This work proposes a method to decompose the kernel within-class eigenspace into two subspaces: a reliable subspace spanned mainly by the facial variation and an unreliable subspace due to limited number of training samples. A weighting function is proposed to circumvent undue scaling of eigenvectors corresponding to the unreliable small and zero eigenvalues. Eigenfeatures are then extracted by the discriminant evaluation in the whole kernel space. These efforts facilitate a discriminative and stable low-dimensional feature representation of the face image. Experimental results on FERET, ORL and GT databases show that our approach consistently outperforms other kernel based face recognition methods.

Sensitivity improvement using optimized heater design for dual axis thermal accelerometers

This paper investigates the sensitivity improvement of an air filled cavity based thermal accelerometer. The accelerometer does not contain any solid proof mass and it is realizable in CMOS technology. The sensitivity has been improved by a new square ring shaped heater structure. The sensitivity of accelerometer performance is compared with other different heater shapes. It is found that, heater design having higher heat dissipation in the suspended beam gives higher sensitivity. The simulation is carried out using commercial FEM simulator COMSOL Multiphysics. For the peak heater temperature of 609 K, the proposed square ring shaped heater provides a sensitivity of 0.335 K/g. Under same conditions, sensitivity of an accelerometer with a meander shaped heater structure is only 0.098 K/g and diamond shaped structure is 0.229 K/g.