Energy-efficient clustering in mobile ad-hoc networks using multi-objective particle swarm optimization

A mobile ad hoc network (MANET) is dynamic in nature and is composed of wirelessly connected nodes that perform hop-by-hop routing without the help of any fixed infrastructure. One of the important requirements of a MANET is the efficiency of energy, which increases the lifetime of the network. Several techniques have been proposed by researchers to achieve this goal and one of them is clustering in MANETs that can help in providing an energy-efficient solution. Clustering involves the selection of cluster-heads (CHs) for each cluster and fewer CHs result in greater energy efficiency as these nodes drain more power than noncluster-heads. In the literature, several techniques are available for clustering by using optimization and evolutionary techniques that provide a single solution at a time. In this paper, we propose a multi-objective solution by using multi-objective particle swarm optimization (MOPSO) algorithm to optimize the number of clusters in an ad hoc network as well as energy dissipation in nodes in order to provide an energy-efficient solution and reduce the network traffic. In the proposed solution, inter-cluster and intra-cluster traffic is managed by the cluster-heads. The proposed algorithm takes into consideration the degree of nodes, transmission power, and battery power consumption of the mobile nodes. The main advantage of this method is that it provides a set of solutions at a time. These solutions are achieved through optimal Pareto front. We compare the results of the proposed approach with two other well-known clustering techniques; WCA and CLPSO-based clustering by using different performance metrics. We perform extensive simulations to show that the proposed approach is an effective approach for clustering in mobile ad hoc networks environment and performs better than the other two approaches.     

Cumin Prevents 17β-Estradiol-Associated Breast Cancer in ACI Rats

Breast cancer (BC) is a leading cause of cancer deaths in women in less developed countries and the second leading cause of cancer death in women in the U.S. In this study, we report the inhibition of E2-mediated mammary tumorigenesis by Cuminum cyminum (cumin) administered via the diet as cumin powder, as well as dried ethanolic extract. Groups of female ACI rats were given either an AIN-93M diet or a diet supplemented with cumin powder (5% and 7.5%, w/w) or dried ethanolic cumin extract (1%, w/w), and then challenged with subcutaneous E2 silastic implants (1.2 cm; 9 mg). The first appearance of a palpable mammary tumor was significantly delayed by both the cumin powder and extract. At the end of the study, the tumor incidence was 96% in the control group, whereas only 55% and 45% animals had palpable tumors in the cumin powder and extract groups, respectively. Significant reductions in tumor volume (660 ± 122 vs. 138 ± 49 and 75 ± 46 mm³) and tumor multiplicity (4.21 ± 0.43 vs. 1.16 ± 0.26 and 0.9 ± 0.29 tumors/animal) were also observed by the cumin powder and cumin extract groups, respectively. The cumin powder diet intervention dose- and time-dependently offset E2-related pituitary growth, and reduced the levels of circulating prolactin and the levels of PCNA in the mammary tissues. Mechanistically, the cumin powder diet resulted in a significant reversal of E2-associated modulation in ERα, CYP1A1 and CYP1B1. Further, the cumin powder diet reversed the expression levels of miRNAs (miR-182, miR-375, miR-127 and miR-206) that were highly modulated by E2 treatment. We analyzed the composition of the extract by GC/MS and established cymene and cuminaldehyde as major components, and further detected no signs of gross or systemic toxicity. Thus, cumin bioactives can significantly delay and prevent E2-mediated mammary tumorigenesis in a safe and effective manner, and warrant continued efforts to develop these clinically translatable spice bioactives as chemopreventives and therapeutics against BC.     

Self and static interference mitigation scheme for coexisting wireless networks

High density of coexisting networks in the Industrial, Scientific and Medical (ISM) band leads to static and self interferences among different communication entities. The inevitability of these interferences demands for interference avoidance schemes to ensure reliability of network operations. This paper proposes a novel Diversified Adaptive Frequency Rolling (DAFR) technique for frequency hopping in Bluetooth piconets. DAFR employs intelligent hopping procedures in order to mitigate self interferences, weeds out the static interferer efficiently and ensures sufficient frequency diversity. We compare the performance of our proposed technique with the widely used existing frequency hopping techniques, namely, Adaptive Frequency Hopping (AFH) and Adaptive Frequency Rolling (AFR). Simulation studies validate the significant improvement in goodput and hopping diversity of our scheme compared to other schemes and demonstrate its potential benefit in real world deployment.     

ELF-Miner: using structural knowledge and data mining methods to detect new (Linux) malicious executables

Linux malware can pose a significant threat—its (Linux) penetration is exponentially increasing—because little is known or understood about Linux OS vulnerabilities. We believe that now is the right time to devise non-signature based zero-day (previously unknown) malware detection strategies before Linux intruders take us by surprise. Therefore, in this paper, we first do a forensic analysis of Linux executable and linkable format (ELF) files. Our forensic analysis provides insight into different features that have the potential to discriminate malicious executables from benign ones. As a result, we can select a features’ set of 383 features that are extracted from an ELF headers. We quantify the classification potential of features using information gain and then remove redundant features by employing preprocessing filters. Finally, we do an extensive evaluation among classical rule-based machine learning classifiers—RIPPER, PART, C4.5 Rules, and decision tree J48—and bio-inspired classifiers—cAnt Miner, UCS, XCS, and GAssist—to select the best classifier for our system. We have evaluated our approach on an available collection of 709 Linux malware samples from vx heavens and offensive computing. Our experiments show that ELF-Miner provides more than 99% detection accuracy with less than 0.1% false alarm rate.     

Solvent‐stable UV‐cured acrylic polysulfone membranes

A systematic investigation of the effect of the presence of acrylate resin on polysulfone‐based membranes was performed with the aim of obtaining chemically stable crosslinked membranes without affecting their flux performances. The membranes were prepared via UV curing of the polymer dope followed by a non‐solvent‐induced phase separation process. Two different acrylic monomers were investigated and their amount was varied in the polymer dope, to study the influence of concentration on final results. High crosslinking degrees were achieved by irradiating the solution for one minute. Morphological investigations of the active surface and of the cross‐sections of the fabricated membranes showed that the typical porosity of ultrafiltration membranes was obtained starting from solutions containing a low amount of crosslinker (10 wt%), which is consistent with the water flux values which were comparable to that of the pristine polysulfone membrane. High concentrations of crosslinker resin in the initial polymer dope produced denser membranes with lower permeability. High rejection of 27 nm particles (>90%) was measured for all samples having measurable flux. The addition of the crosslinker allowed one to obtain stability in various solvents without affecting the flux and rejection performance of the porous membranes. © 2016 Society of Chemical Industry     

Reactivity of partially reduced arylhydroxylamine and nitrosoarene metabolites of 2,4,6-trinitrotoluene (TNT) toward biomass and humic acids

Sequential anaerobic/aerobic treatment of 2,4,6-trinitrotoluene (TNT) generally results in the incorporation of residues into biomass and natural organic matter fractions of a system. To better understand the potential contribution of hydroxylamine and nitroso moieties in these reactions, studies were conducted using model systems taking advantage of the biocatalytic-activity of Clostridium acetobutylicum that does not produce aminated TNT derivatives. To evaluate binding to biomass only, systems containing cell-free extracts of C. acetobutylicum and molecular hydrogen as a reductant were employed. At the end of treatment, mass balance studies showed that 10% of the total 14C was associated with an insoluble protein-containing precipitate that could not be extracted with organic solvents. Model reactions were conducted between a mixture of 2,4-dihydroxylamino-6-nitrotoluene (DHA6NT) and 4-hydroxylamino-2,6-dinitrotoluene (4HADNT) and 1-thioglycerol to test the involvement of the nitroso-thiol reaction in binding to biomass. It was demonstrated that DHA6NT formed a new and relatively polar product with 1-thioglycerol only in the presence of oxygen. The oxygen requirement confirmed that the nitroso functionality was responsible for the binding reaction. The reactivity of arylhydroxylamino and nitrosoarene functionalities toward International Humic Substance Society (IHSS) peat humic acid was evaluated under anaerobic and aerobic conditions, respectively. 4HADNT showed no appreciable reactivity toward peat humic acid. Conversely, the nitrosoarene compound, nitrosobenzene, showed rapid reactivity with peat humic acid (50% removal in 48 h). When tested with two other humic acids (selected on the basis of their protein content), it became apparent that the proteinaceous fraction was responsible at least in part for the nitrosoarene's removal from solution. Furthermore, the pretreatment of the humic acids with a selective thiol derivatizing agent had a considerable effect on their ability to react with nitrosobenzene. Finally, molecular modeling tools were used to compare the electrophilic characteristics of potential nitroso intermediates forming from the oxidation of arylhydroxylamino metabolites of TNT. Molecular modeling analysis demonstrated that the more reduced TNT derivative containing nitroso groups were more likely to react with nucleophiles in humic substances than the less reduced nitroso intermediates.