An Improved PSOGSA for Clustering and Routing in WSNs

Wireless Personal Communications - Wireless sensor network (WSN) is an integration of sensing, communicating, computing in a board range environment. Efficient energy consumption becomes the most...     

A case-based and practical approach for multivariate modeling of grinding process

Grinding process is claimed to be the only possible cost-effective means of shaping engineering part(s) or component(s) into finished products with required surface topology. However, because of the complicated relationship(s) between several phenomena and entities involved in a grinding process, determining functional relationship between relevant input(s), in-process variable(s), and output quality characteristic [or response] remains a critical and difficult task for researchers and practitioners. The complexity of the problem further increases as number of responses considered for modeling is more than one, and the situation is so-called multivariate or multiresponse surface modeling. Although various mechanistic and empirical modeling approaches have been proposed in literature, they are found to be of limited validity, with applied functional approximation and simplistic assumption(s). In addition, empirical models are sometimes based on off-line designed experimental data, which are expensive or uneconomical in many line layout type mass-manufacturing situations. This paper attempts to provide a case-based practical approach for practitioners, with detailed steps involved in multivariate modeling, based on conventional regression technique, and unconventional artificial neural network-based technique, using real-time production data. The two case examples selected to verify the approaches are from an automobile engine manufacturing unit located in eastern India.     

New machine-learning algorithms for prediction of Parkinson's disease

This article presents an enhanced prediction accuracy of diagnosis of Parkinson's disease (PD) to prevent the delay and misdiagnosis of patients using the proposed robust inference system. New machine-learning methods are proposed and performance comparisons are based on specificity, sensitivity, accuracy and other measurable parameters. The robust methods of treating Parkinson's disease (PD) includes sparse multinomial logistic regression, rotation forest ensemble with support vector machines and principal components analysis, artificial neural networks, boosting methods. A new ensemble method comprising of the Bayesian network optimised by Tabu search algorithm as classifier and Haar wavelets as projection filter is used for relevant feature selection and ranking. The highest accuracy obtained by linear logistic regression and sparse multinomial logistic regression is 100% and sensitivity, specificity of 0.983 and 0.996, respectively. All the experiments are conducted over 95% and 99% confidence levels and establish the results with corrected t-tests. This work shows a high degree of advancement in software reliability and quality of the computer-aided diagnosis system and experimentally shows best results with supportive statistical inference.     

An interoperable context sensitive model of trust

Although the notion of trust is widely used in secure information systems, very few works attempt to formally define it or reason about it. Moreover, in most works, trust is defined as a binary concept—either an entity is completely trusted or not at all. Absolute trust on an entity requires one to have complete knowledge about the entity. This is rarely the case in real-world applications. Not trusting an entity, on the other hand, prohibits all communications with the entity rendering it useless. In short, treating trust as a binary concept is not acceptable in practice. Consequently, a model is needed that incorporates the notion of different degrees of trust. We propose a model that allows us to formalize trust relationships. The trust relationship between a truster and a trustee is associated with a context and depends on the experience, knowledge, and recommendation that the truster has with respect to the trustee in the given context. We show how our model can measure trust and compare two trust relationships in a given context. Sometimes enough information is not available about a given context to evaluate trust. Towards this end we show how the relationships between different contexts can be captured using a context graph. Formalizing the relationships between contexts allows us to extrapolate values from related contexts to approximate the trust of an entity even when all the information needed to calculate the trust is not available. Finally, we show how the semantic mismatch that arises because of different sources using different context graphs can be resolved and the trust of information obtained from these different sources compared.

Thermal stability of additively manufactured austenitic 304L ODS alloy

Thermal stability and high-temperature mechanical properties of a 304L austenitic oxide dispersion strengthened(ODS)alloy manufactured via laser powder bed fusion(LPBF)are examined in this work.Additively manufactured 304LODS alloy samples were aged at temperatures of 1000,1100,and 1200℃for 100h in an argon atmosphere.Microstructure characterization of LPBF 304L ODS alloy before and after the thermal stability experiments revealed that despite the annihilation of dislocations,induced cellular substructure by the LPBF process was partially retained in the ODS alloy even after aging at 1200℃.The size of Y-Si-O nanoparticles after aging at 1200℃increased from 25 to 50 nm.EBSD analysis revealed that nanoparticles retained the microstructure of LPBF 304L ODS and hindered recrystallization and further grain growth.At 600℃and 800℃,the yield stress of the 290 and 145 MPa were measured,respectively,which are substantially higher than 113 MPa,and 68 MPa for 304L at the same temperatures.Furthermore,the creep properties of LPBF 304L ODS alloy were evaluated at a temperature of 700℃under three applied stresses of 70,85,and 100 MPa yielding a stress exponent(n)of～7.7;the minimum creep rate at 100 MPa was found to be about two orders of magnitude lower than found in the literature for wrought 304L stainless steel.     

Aqueous‐Phase Synthesis of Highly Luminescent CdTe/ZnTe Core/Shell Quantum Dots Optimized for Targeted Bioimaging

Semiconductor quantum dots (QDs) have traditionally been synthesized in organic phase and transferred to aqueous solution by functionalizing their surface with silica, polymers, short‐chain thiol ligand, or phospholipid micelles. However, these complex steps result in i) a reduction of the quantum yield (QY) of QDs, ii) partial degrdation of the QDs, and iii) a drastic increase in the hydrodynamic size of QDs, which may hinder their biomedical applications. In this work, the fabrication and applications of cysteine‐capped CdTe/ZnTe QDs, which are directly synthesized in aqueous media, as optical probes for specific targeting of pancreatic and esophageal cancer cells in vitro are reported, as well as their capability for in vivo imaging. The CdTe/ZnTe QDs are synthesized in a one‐pot method and capped with amino acid cysteine, which contains both carboxyl and amine functional groups on their surfaces for bioconjugation. The fabricated QDs have an ultrasmall hydrodynamic diameter (3–5 nm), possess high QY (52%), and are non‐toxic to cells at experimental dosages. Confocal imaging is used to demonstrate a receptor‐mediated uptake of antibody‐conjugated QDs into pancreatic cancer cells in vitro. In vitro cytotoxicity studies (MTS‐assay) show that the IC₅₀ value of these QDs is ≈160 µg mL^?1, demonstrating low toxicity. In addition, the QDs are used for small‐animal imaging where the in vivo biocompatiblity of these QDs and their clearance following systemic injection is studied.     

Microanalysis and optimization-based estimation of C-S-H contents of cementitious systems containing fly ash and silica fume

In this study, a new approach to characterize hardened pastes of pure portland cement as well as those containing cement with supplementary cementitious materials (SCM) was adopted using scanning electron microscopy (SEM) and energy dispersive X-ray spectra (EDS) microanalyses. The volume stoichiometry of the hydration reactions was used to estimate the quantities of the primary and secondary calcium silicate hydrate (C-S-H) and the calcium hydroxide produced by these reactions. The 3D plots of Si/Ca, Al/Ca and S/Ca atom ratios given by the microanalyses were compared with the estimated quantities of C-S-H to successfully determine the Ca/Si ratio of eleven different cementitious systems at four different ages using a constrained nonlinear least squares optimization formulation by General Algebraic Modeling System (GAMS). The estimated mass fraction of calcium hydroxide from the above method agreed well with the calcium hydroxide content determined from the thermogravimetric analyses (TGA).     

Non-invasive tumor detection in small animals using novel functional Pluronic nanomicelles conjugated with anti-mesothelin antibody

In this study QDs were encapsulated in carboxylated PluronicF127 (F127COOH) triblock polymeric micelles and conjugated with anti-mesothelin antibody for the purpose of alleviating potential toxicity, enhancing the stability and improving targeting efficiency of CdTe/ZnS quantum dots (QDs) in tumors. The amphiphilic triblock polymer of F127COOH contains hydrophilic carboxylated poly(ethylene oxide) (PEO) and hydrophobic poly(propylene oxide) (PPO) units. After encapsulating QDs into carboxylated F127 (F127COOH-QD) micelles, the particles were conjugated with anti-mesothelin antibodies to allow targeting of cancerous areas. The size of the monodispersed spherical QD-containing micelles was determined to be ～120 nm by dynamic light scattering (DLS). The critical micelle concentration (CMC) was estimated to be 4.7 × 10(-7) M. In an in vitro study, the anti-methoselin antibody conjugated F127COOH (Me-F127COOH-QD) nanomicelles showed negligible cytotoxicity to pancreatic cancer cells (Panc-1). Confocal microscopy demonstrated that the Me-F127COOH-QD nanomicelles were taken up more efficiently by Panc-1 cells, due to antibody mediated targeting. An in vivo imaging study showed that Me-F127COOH-QD nanomicelles accumulated at the pancreatic tumor site 15 min after intravenous injection. In addition, the low in vivo toxicity of the nanomicellar formulation was evaluated by pathological assays. These results suggest that anti-mesothein antibody conjugated carboxylated F127 nanomicelles may serve as a promising nanoscale platform for early human pancreatic cancer detection and targeted drug delivery.     

Levers for Thermoelectric Properties in Titania-Based Ceramics

While the beneficial impact of nanostructural engineering on thermoelectric performance has been demonstrated for many semiconducting materials (SiGe, skutterudites, PbTe₂, etc.), no significant advantages have been reported for oxide nanomaterials. In this study, titania is used as a model material to compare the impact of grain size, doping and substitution, second-phase nanodispersion, and crystallographic defects on the electronic and thermal properties. It is shown that the lattice thermal conductivity can be most efficiently reduced by high densities of crystallographic planar defects in the Magnéli phases, while modification of grain size or introduction of second phases on length scales of 20?nm to 100?nm introduces only minor improvement. For the electronic properties, donor dopants such as niobium provide improvement of the power factor, but are not able to compete with the enhanced carrier concentration that is reached through oxygen vacancy introduction.