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 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.     

A particle swarm approach for multi-objective optimization of electrical discharge machining process

This paper proposes an experimental investigation and optimization of various machining parameters for the die-sinking electrical discharge machining (EDM) process using a multi-objective particle swarm (MOPSO) algorithm. A Box–Behnken design of response surface methodology has been adopted to estimate the effect of machining parameters on the responses. The responses used in the analysis are material removal rate, electrode wear ratio, surface roughness and radial overcut. The machining parameters considered in the study are open circuit voltage, discharge current, pulse-on-time, duty factor, flushing pressure and tool material. Fifty four experimental runs are conducted using Inconel 718 super alloy as work piece material and the influence of parameters on each response is analysed. It is observed that tool material, discharge current and pulse-on-time have significant effect on machinability characteristics of Inconel 718. Finally, a novel MOPSO algorithm has been proposed for simultaneous optimization of multiple responses. Mutation operator, predominantly used in genetic algorithm, has been introduced in the MOPSO algorithm to avoid premature convergence. The Pareto-optimal solutions obtained through MOPSO have been ranked by the composite scores obtained through maximum deviation theory to avoid subjectiveness and impreciseness in the decision making. The analysis offers useful information for controlling the machining parameters to improve the accuracy of the EDMed components.     

Fuzzy medial axis transformation (fmat): Image representation,skeleton extraction and uncertainty management in computer vision

The problem of extraction of medial axis transformation of a gray image with reference to skeletonization, image representation and uncertainty management in a vision system has been addressed. The Fuzzy Medial Axis Transformation (fmat) of a fuzzy setf is a set of fuzzy disks whose sup isf. Unfortunately, specifying thefmat sometimes requires more storage space than specifyingf itself. The present paper describes some techniques to improve the compact representation offmat; thereby making it practically useful to an image for its skeleton extraction and compact representation, for shape analysis and template matching, for representation and retrieval, for uncertainty management in recognition and for creating new images of various poses. The algorithms involve reduction of redundancy infmat, its approximation, and reduction of the searching spaces for its computation. Computational aspects for the convenience of writing an efficient program have been described. Some applications of thefmat have also been mentioned. This work was done while SKP held annrc-nasa Senior Research Associateship at the Lyndon B Johnson Space Center, Houston, Texas.     

Initial high beta operation of the HBT-EP Tokamak

HBT-EP is a new research tokamak designed and built to investigate passive and active feedback techniques to control MHD instabilities. In particular, HBT-EP will be able to test techniques to control fast MHD instabilities occurring at high Troyon-normalized beta, _N Ba/I_p [Tm/MA], since it is equipped with a thick, close-fitting, and adjustable conducting shell. The major goals of the initial operation of HBT-EP have been the achievement of high beta operation (_N 3) using only ohmic heating and the observation of MHD instabilities. By using a unique fast startup technique, we have successfully achieved these goals. A variety of MHD phenomena were observed during the high beta operation of HBT-EP. At modest beta (_N 2), discharges have been maintained for more than 10 msec, and these discharges exhibit saturated resistive instabilities. When _N approaches 3, major disruptions occur preceded by oscillating, growing precursors. During start-up, one or more minor disruptions are usually observed. A 1-D transport code has been used to simulate the evolution of the current profile, and these early minor instabilities are predicted to be double tearing modes. The simulation also reproduces the observed high beta operation when saturated neo-Alcator energy confinement scaling is assumed.     

Performance of Pile-Supported Bridge Approach Slabs

A large number of pile-supported bridge approach slabs in southeastern Louisiana were examined to identify the factors that affect their long-term performance. Design drawings and subsoil conditions at these sites as well as their traffic and maintenance records were compiled, and seven representative test sites were selected for thorough field investigation that included inspection of the approach slabs, bridge decks, bridge abutments, and roadway pavement. Field evaluation included walking profiler, falling-weight deflectometer (FWD), laser profiler, geodetic survey, soil borings, cone penetrometer, and nondestructive testing. Measurements made with the walking profiler agreed well with the geodetic survey. The FWD and nondestructive testing were effectively used to detect voids under the approach slab. Results of the study indicated that the current empirical methodology used by the Louisiana Department of Transportation and Development for design of pile-supported approach slabs yields inconsistent field performance. It was concluded that this inconsistent performance is primarily due to the differences in roadway embankment design and construction and in subsoil conditions, which in turn affect the negative skin friction (downdrag) loads imparted on the piles. Impact of other variables such as ramp type, speed limit, traffic volume, and so on was found to be insignificant. Results of the field study were used to develop a new rating system for approach slabs (IRIS) based on International Roughness Index (IRI) measurements obtained with the laser profiler.     

Incorporating Ancestors' Influence in Genetic Algorithms

A new criterion of fitness evaluation for Genetic Algorithms is introduced where the fitness value of an individual is determined by considering its own fitness as well as those of its ancestors. Some guidelines for selecting the weighting coefficients for quantifying the importance to be given to the fitness of the individual and its ancestors are provided. This is done both heuristically and automatically under fixed and adaptive frameworks. The Schema Theorem corresponding to the proposed concept is derived. The effectiveness of this new methodology is demonstrated extensively on the problems of optimizing complex functions including a noisy one and selecting optimal neural network parameters.     

Yield and Functional Properties of Taro Starch as Affected by Ultrasound

Effect of ultrasound pretreatment on yield and functional properties of taro starch was investigated. A three-factor two-level factorial design was employed with treatment time (5 and 10 min), treatment cycle (0.5 and 1), and amplitude of ultrasound (50 and 100 %). Starch yield from ultrasonic treatment varied from 17.45 to 18.97 % compared to 15.29 % in conventional method. The highest yield of 18.97 % was obtained with treatment time 10 min, treatment cycle 0.5, and amplitude 50 %. A significant increase in swelling, solubility, pasting, and texture properties of the ultrasonically extracted starch was observed. A slight decrease in clarity of the starch pastes was also observed after ultrasonic pretreatment, but the differences were not much significant. Freeze-thaw stability of the ultrasonically extracted starches was found to be better compared to starch extracted using conventional method, making them suitable for foods subjected to refrigeration. The whiteness of the ultrasonically extracted starch powders was lower compared to conventionally extracted starch, but the differences were not statistically significant.     

Synthesis,structural and optical properties of Er doped,Li doped and Er + Li co-doped ZnO nanocrystallites by solution-combustion method

Pure zinc oxide (ZnO) and 2 mol% of Er, 1 mol% of Li individually doped and Er + Li co-doped ZnO nanopowders were synthesized by auto-combustion method. Crystal structure and grain size were characterized by X-ray diffractometer and found that all synthesized samples have hexagonal wurtzite crystal structure. Scanning electron microscope (SEM) and Transmission electron microscope (TEM) studies were used to determine the morphology and size of the nanocrystallites. A UV–VIS measurement shows four absorbance peaks in the visible regions and the band gap is slowly blue shifted after annealing at 800 °C. The presence of Er, Li and the hexagonal wurtzite structure was confirmed by FT-IR studies. FT-Raman spectroscopy has been employed to study the crystalline quality and structural disorders.