A Modified Particle Filter for Simultaneous Localization and Mapping

The implementation of a particle filter (PF) for vision-based bearing-only simultaneous localization and mapping (SLAM) of a mobile robot in an unstructured indoor environment is presented in this paper. Variations, using techniques from the genetic algorithm (GA), to standard PF procedures are proposed to alleviate the sample impoverishment problem. A monochrome CCD camera mounted on the robot is used as the measuring device and a measure on the image quality is incorporated into data association and PF update. Since the bearing-only measurement does not contain range information, we add a pseudo range to the measurement during landmark initialization as a hypothesised pair and the non-promising landmark is removed by a map management strategy. Simulation and experimental results from an implementation using real-life data acquired from a Pioneer robot are included to demonstrate the effectiveness of our approach.     

Design and implementation of a new tuned hybrid intelligent model to predict the uniaxial compressive strength of the rock using SFS-ANFIS

This study proposes a novel design to systematically optimize the parameters for the adaptive neuro-fuzzy inference system (ANFIS) model using stochastic fractal search (SFS) algorithm. To affirm the efficiency of the proposed SFS-ANFIS model, the predicting results were compared with ANFIS and three hybrid methodologies based on ANFIS combined with genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO). Accurate prediction of uniaxial compressive strength (UCS) is of great significance for all geotechnical projects such as tunnels and dams. Hence, this study proposes the use of SFS-ANFIS, GA-ANFIS, DE-ANFIS, PSO-ANFIS, and ANFIS models to predict UCS. In this regard, the fresh water tunnel of Pahang–Selangor located in Malaysia was considered and the requirement data samples were collected. Different statistical metrics such as coefficient of determination (R²) and mean absolute error were used to evaluate the models. Referring to the efficiency results of SFS-ANFIS, it can be found that the SFS-ANFIS (with the R² of 0.981) has higher ability than PSO-ANFIS, DE-ANFIS, GA-ANFIS, and ANFIS models in predicting the UCS.

     

Polyester composite water uptake and organic contaminant release affected by carbon nanofiber reinforcements

The incorporation of carbon nanofiber (CNF) into glass fiber (GF) composites is a potential route to extend polymer composite service‐life and enhance mechanical properties. Under nonstatic conditions, only limited information concerning water uptake and contaminant release properties of nanocomposite materials is currently available. Polyester composites containing GF and oxidized CNF were immersed in water for 30 days under nominal pressure at 23 °C, below the polymer's glass‐transition temperature. Water was analyzed and changed every three days to simulate water chemistry regeneration similar to exposures in flowing systems. Composites with oxidized CNF had greater water sorption capacity and leaching rates than CNF‐free composites. The total mass of organic contaminant released correlated with the amount of water sorbed by each composite (r² = 0.91), although CNF dispersion was found to vary greatly within composites. The greatest and least contaminant release rates were found for the polyester‐CNF and the polyester‐GF composites, respectively. While volatile aromatic resin solvents and stabilizer compounds were detected, their concentrations declined over the 30 day exposure period. We hypothesize that the hydrophilic nature of the oxidized CNF increased the water sorption capacity of the polyester composites. Additional studies are warranted that examine the impact of this phenomenon on composite mechanical and long‐term durability properties. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43724.     

Hierarchy-Debug: a scalable statistical technique for fault localization

Considering the fact that faults may be revealed as undesired mutual effect of program predicates on each other, a new approach for localizing latent bugs, namely Hierarchy-Debug, is presented in this paper. To analyze the vertical effect of predicates on each other and on program termination status, the predicates are fitted into a logistic lasso model. To support scalability, a hierarchical clustering algorithm is applied to cluster the predicates according to their presence in different executions. Considering each cluster as a pseudo-predicate, a distinct lasso model is built for intermediate levels of the hierarchy. Then, we apply a majority voting technique to score the predicates according to their lasso coefficients at different levels of the hierarchy. The predicates with relatively higher scores are ranked as fault relevant predicates. To provide the context of failure, faulty sub-paths are identified as sequences of fault relevant predicates. The grouping effect of Hierarchy-Debug helps programmers to detect multiple bugs. Four case studies have been designed to evaluate the proposed approach on three well-known test suites, Space, Siemens, and Bash. The evaluations show that Hierarchy-Debug produces more precise results compared with prior fault localization techniques on the subject programs.     

High temperature latent heat thermal energy storage using heat pipes

A thermal network model is developed and used to analyze heat transfer in a high temperature latent heat thermal energy storage unit for solar thermal electricity generation. Specifically, the benefits of inserting multiple heat pipes between a heat transfer fluid and a phase change material (PCM) are of interest. Two storage configurations are considered; one with PCM surrounding a tube that conveys the heat transfer fluid, and the second with the PCM contained within a tube over which the heat transfer fluid flows. Both melting and solidification are simulated. It is demonstrated that adding heat pipes enhances thermal performance, which is quantified in terms of dimensionless heat pipe effectiveness.     

Investigation of the Binding Behavior between the S-heterocyclic Aromatic Palladium(II) Complex and Human Serum Albumin: Spectroscopic Approach

The interaction of 1, 10-phenanthroline octhyldithiocarbamato palladium(II) nitrate ([Pd(Oct-dtc)(phen)]NO₃) with human serum albumin (HSA) has been investigated by various spectroscopic techniques under physiological conditions. Here, HSA was titrated with the Pd(II) complex, followed by UV–Vis absorption spectroscopy to estimate a binding constant (K_b) and other thermodynamic parameters. The results indicate that the Pd (II) complex has a high affinity for bind HSA. Thermodynamic analysis showed that the enthalpy (ΔH°) and entropy changes (ΔS°) are positive and Gibbs free energy change (ΔG°) is negative which indicated that hydrophobic interactions played the predominant role in the binding process. Fluorescence spectroscopy were used to show the mechanism and binding parameters of this interaction. Utilizing the Stern–Volmer equation, the Pd(II) complex quenched the intrinsic fluorescence of HSA via a static quenching procedure. The specific binding distances between the tryptophan (donor) proteins and Pd(II) complex (acceptor) were estimated by Forster resonance energy transfer. The CD results also showed the conformational changes on serum albumin upon binding with the Pd(II) complex.     

Theoretical and practical investigations of copper ion selective electrode with polymeric membrane based on N,N′-(2,2-dimethylpropane-1,3-diyl)-bis(dihydroxyacetophenone)

A novel ion-selective poly(vinyl chloride) (PVC) membrane sensor for Cu²⁺ ions based on N,N′-(2,2-dimethylpropane-1,3-diyl)-bis(dihydroxyacetophenone) (NDHA) as a new ionophore was prepared and studied. The best performance was observed for the membrane composition, including 30:65:1:4 (wt%) = PVC:DBP:KTpClPB:NDHA. The electrode showed a good Nernstian slope of 30.0 ± 0.5 mV/decade in a wide linear range activity of 3.0 × 10⁻⁷ to 1.0 × 10⁻² mol dm⁻³ Cu(NO₃)₂ with limit of detection 2.5 × 10⁻⁷. Sensor exhibited a fast response time (t_95% < 10 s) and could be used for about 4 months in the pH range of 3.0–7.4. The proposed potentiometric sensor was found to work satisfactorily in partially non-aqueous media up to 30 (vol%) content of methanol, ethanol and acetone. Applications of this electrode for the determination of copper in real samples, and as an indicator electrode for potentiometric titration of Cu²⁺ ion using EDTA, were reported. In order to predict the extraction ability of NDHA for different metallic ions, the complexes [M(NDHA)] and [M(H₂O)₆] (where M = Cu²⁺, Co²⁺, Hg²⁺, Pb²⁺, Ag⁺, Mg²⁺, Ca²⁺, Mn²⁺, Zn²⁺, Cd²⁺, K⁺ and Al³⁺) were investigated using ab initio theoretical calculations. The metal binding capability was evaluated using the binding energy. Results of our study could be useful for prediction of the extraction power of this Schiff base and could play a guiding role in planning experiments.     

Electrical Resistance Tomography (ERT) applications to Chemical Engineering

Electrical Resistance Tomography (ERT) has the capability of offering time-evolving multidimensional comprehensive process knowledge, enrichment of fundamental process understanding and enhancement of the design and operation of process equipment by measuring the conductivity distribution within a process-plant of interest. This paper reviews the wide variety of previous work on ERT applications to Chemical Engineering. The applications are categorized based on the unit operations ERT has been applied to, the media under investigation, the purpose of ERT measurements and also other technologies used in conjunction with ERT. The aim of this taxonomy is to provide the reader with a general understanding of the current situation of ERT related research and proven applications in the Chemical Engineering field and to facilitate the recognition of research gaps for future investigation. Based on this detailed taxonomy and review the potential application of ERT to the milk powder processing industry was identified. Some results of the application of ERT to milk mixing/holding tanks and milk flow pipelines for the purpose of concentration and composition measurements, detection of abnormalities and faults, and multidimensional flow and velocity profile measurements have also been presented as a case study of using this taxonomy.