Increasing Intelligence in Autonomous Wheelchairs

The ideas shown in this paper have been developed having in mind the main goal of designing a completely autonomous wheelchair prototype. The state of the art of mobile robotics is compared with the new trends in the field. The idea of autonomy made us focus our research in extracting the best from conventional Intelligent Mobile Robots techniques, looking towards the concept of Autonomous Mobile Systems (AMS). In order to clarify the body of the presentation, some practical examples, developed at our laboratory (DISAM-UPM), are included in parallel with the main discourse.     

Morphology,thermal and mechanical behavior of polypropylene nanocomposites toughened with poly(ethylene‐co‐octene)

Rubber‐toughened polypropylene (PP) nanocomposites containing organophilic layered silicates were prepared by means of melt extrusion at 230 °C using a co‐rotating twin‐screw extruder in order to examine the influence of the organoclay and the addition of PP grafted with maleic anhydride (PPgMAH) as a compatibilizer on the morphological, mechanical and thermal properties. The mechanical properties of rubber‐toughened polypropylene nanocomposites (RTPPNCs) were studied through tensile, flexural and impact tests. Scanning electron microscopy (SEM) was used for investigation of the phase morphology and rubber particles size. X‐ray diffraction (XRD) was employed to characterize the formation of nanocomposites. The thermal properties were investigated by using thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). The dynamic mechanical properties were examined by using dynamic mechanical analysis (DMA). From the tensile and flexural tests, the optimum loading of organoclay in RTPP was found to be 6 wt%. The optimum loading of PPgMAH, based on the tensile and flexural properties, was also 6 wt%. The increase in the organoclay and PPgMAH content resulted in a severe embrittlement, manifested by a drop in the impact strength and tensile elongation at break. XRD studies revealed that intercalated RTPPNCs had been successfully prepared where the macromolecular PP segments were intercalated into the interlayer space of the organoclay. In addition, the organoclay was dispersed more evenly in the RTPPNC as the PPgMAH content increased. TGA results revealed that the thermal stability of the RTPPNC improved significantly with the addition of a small amount of organoclay. Copyright © 2006 Society of Chemical Industry     

Separation of vitamin E (tocopherol,tocotrienol, and tocomonoenol) in palm oil

Previous reports showed that vitamin E in palm oil consists of various isomers of tocopherols and tocotrienols [α-tocopherol (α−T), α-tocotrienol, γ-tocopherol, γ-tocotrienol, and δ-tocotrienol), and this is normally analyzed using silica column HPLC with fluorescence detection. In this study, an HPLC-fluorescence method using a C₃₀ silica stationary phase was developed to separate and analyze the vitamin E isomers present in palm oil. In addition, an α-tocomonoenol (α−T₁) isomer was quantified and characterized by MS and NMR. α−T₁ constitutes about 3–4% (40±5 ppm) of vitamin E in crude palm oil (CPO) and is found in the phytonutrient concentrate (350±10 ppm) from palm oil, whereas its concentration in palm fiber oil (PFO) is about 11% (430±6 ppm). The relative content of each individual vitamin E isomer before and after interesterification/transesterification of CPO to CPO methyl esters, followed by vacuum distillation of CPO methyl esters to yield the residue, remained the same except for α−T and γ−T₃. Whereas α−T constitutes about 36% of the total vitamin E in CPO, it is present at a level of 10% in the phytonutrient concentrate. On the other hand, the composition of γ−T₃ increases from 31% in CPO to 60% in the phytonutrient concentrate. Vitamin is present at 1160±43 ppm, and its concentrations in PFO and the phytonutrient concentrate are 4,040±41 and 13,780±65 ppm, respectively. The separation and quantification of α−T₁ in palm oil will lead to more in-depth knowledge of the occurrence of vitamin E in palm oil.     

Adsorption and desorption characteristics of zinc on ash particles derived from oil palm waste

Solid waste such as palm fibre and shell produced by the palm oil industry is used by palm oil mills as boiler fuel to produce steam for electricity generation. The ash produced after combustion creates a disposal problem for the palm oil industry. This study explored the potential of oil palm ash as an adsorbent material for removal and recovery of zinc ions from aqueous solutions. The equilibrium uptake of zinc was found to increase with solution pH in the range 3–6, yielding a maximum adsorption capacity of 0.163 mmol g^?1 of ash at a pH of 6. The affinity constant of oil palm ash was found to greatly exceed that of a commercial ion exchange resin, suggesting that oil palm ash may find potential application in treating dilute zinc‐containing waste streams. Four isotherm models were used to fit the constant pH equilibrium isotherms obtained at four different pH values. The entire data set was successfully simulated using two of the isotherm models: a Langmuir model with pH‐dependent parameters and an extended Langmuir–Freundlich model with pH‐independent parameters. The rates of adsorption and desorption for zinc were measured using a stirred‐batch contactor. The contact time required to reach apparent adsorption equilibrium was found to decrease with increasing adsorbent dosage. Both the rate and the extent of zinc desorption were affected by the pH of the desorbing solution. The adsorption and desorption rates were consistent with simple first‐order rate models. © 2002 Society of Chemical Industry     

An antibacterial coating based on a polymer/sol-gel hybrid matrix loaded with silver nanoparticles

In this work a novel antibacterial surface composed of an organic-inorganic hybrid matrix of tetraorthosilicate and a polyelectrolyte is presented. A precursor solution of tetraethoxysilane (TEOS) and poly(acrylic acid sodium salt) (PAA) was prepared and subsequently thin films were fabricated by the dip-coating technique using glass slides as substrates. This hybrid matrix coating is further loaded with silver nanoparticles using an in situ synthesis route. The morphology and composition of the coatings have been studied using UV-VIS spectroscopy and atomic force microscopy (AFM). Energy dispersive X-ray (EDX) was also used to confirm the presence of the resulting silver nanoparticles within the thin films. Finally the coatings have been tested in bacterial cultures of genus Lactobacillus plantarum to observe their antibacterial properties. It has been experimentally demonstrated that these silver loaded organic-inorganic hybrid films have a very good antimicrobial behavior against this type of bacteria.     

Fourier transform infrared study of polypyrrole–poly(vinyl alcohol) conducting polymer composite films: Evidence of film formation and characterization

The electrochemical preparation of polypyrrole (PPY)–poly(vinyl alcohol) (PVA) conducting polymer composite films on an indium–tin oxide glass electrode from an aqueous solution containing a pyrrole monomer, a p‐toluene sulfonate electrolyte, and a PVA insulating polymer is reported. The prepared PPY–PVA composite films were characterized by Fourier Transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), and conductivity measurements. The FTIR study showed that the composite of PPY and PVA formed through bond formation between PVA and the p‐toluene sulfonate dopant anion. The conductivity data of PPY–PVA showed that with increasing PVA concentration in the pyrrole solution, the conductivity of the prepared PPY–PVA film increased up to a certain level due to an increase in conjugation length, and later, it decreased with further increases in the PVA concentration in the solution due to a decrease in conjugation length. This was supported by the FTIR band intensity I₁₅₆₀/I₁₄₈₀. The TGA results show that the PPY–PVA polymer composite film was thermally more stable than the PPY film. A shielding effectiveness of 45.6 dB was exhibited by the PPY–PVA composite film in the microwave frequency range. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 4107–4113, 2006     

Gamma radiation-induced synthesis of nanocurcumin: Characterization and cell viability test

Curcumin is a bioactive agent with wide ranging therapeutic efficacy in the treatment of inflammations, wounds, microbial infections, and cancers. Despite having potent anticancer properties, its potential in cancer treatment is hampered by reduced bioavailability that mainly due to its limited solubility in water. Several studies have been performed to improve its water solubility by way of encapsulation or entrapment in nanogels or nanoparticles. These are synthesized from classical chemistry methods that involve several toxic chemicals those are difficult to purify. This study explores a novel production method to prepare nanosized curcumin (nanocurcumins) in view of avoiding the use of chemical crosslinkers and accelerants. Micellar aggregates were first synthesized by random copolymerization of N-isopropylacrylamide (NIPAAM), vinyl pyrollidone (VP), and polyethylene glycol diacrylate (PEGDA) using gamma radiation-induced polymerization. The micellar aggregates were then used to entrap curcumin in water to form nanocurcumins—making it readily soluble in water. An MTT assay test shows that lowest cell viability for MCF-7 and HEP-G2 cells was observed at 1,000 and 5,000?µM nanocurcumin concentration, respectively, while free curcumin had higher cell viability in almost all concentrations. The tests revealed that a comparable final product could be obtained using the gamma radiation-induced polymerization method.     

Size-dependent adsorption and conformational changes induced in bovine serum albumin (BSA) on exposure to titanium dioxide (TiO2) nanoparticles

In this study, TiO₂ nanoparticles (NPs) of different sizes were synthesized using sol gel method and calcined at different temperatures ranging from 200 to 700°C. The specific surface area of TiO₂ was found to decrease with the increase in calcination temperature. It was observed that adsorption of bovine serum albumin (BSA) on TiO₂ NPs obeyed the Freundlich adsorption isotherm, and the isotherm parameters were calculated from equilibrium adsorption batch experiments. The kinetics of adsorption was best fitted by pseudo-first-order kinetic model. The effect of particle dosage on BSA adsorption was also studied and it was observed that the adsorption increased with the increase in particle dosage and decrease in particle size. The conformational changes of BSA on exposure to TiO₂ NPs of various sizes were investigated using circular dichroism spectropolarimetry. The results suggested that BSA underwent a distortion in the secondary structure which was quantified by the percent α-helicity. A size-dependent distortion was observed. The α-helix content changed from 32.3% for pure BSA to 21.9% when exposed to NPs calcined at 200°C (350 mg/L) and to 28.4% for NPs calcined at 700°C at the same concentration.     

A flexible method to estimate the software development effort based on the classification of projects and localization of comparisons

The estimation of software development effort has been centralized mostly on the accuracy of estimates through dealing with heterogeneous datasets regardless of the fact that the software projects are inherently complex and uncertain. In particular, Analogy Based Estimation (ABE), as a widely accepted estimation method, suffers a great deal from the problem of inconsistent and non-normal datasets because it is a comparison-based method and the quality of comparisons strongly depends on the consistency of projects. In order to overcome this problem, prior studies have suggested the use of weighting methods, outlier elimination techniques and various types of soft computing methods. However the proposed methods have reduced the complexity and uncertainty of projects, the results are not still convincing and the methods are limited to a special domain of software projects, which causes the generalization of methods to be impossible. Localization of comparison and weighting processes through clustering of projects is the main idea behind this paper. A hybrid model is proposed in which the software projects are divided into several clusters based on key attributes (development type, organization type and development platform). A combination of ABE and Particle Swarm Optimization (PSO) algorithm is used to design a weighting system in which the project attributes of different clusters are given different weights. Instead of comparing a new project with all the historical projects, it is only compared with the projects located in the related clusters based on the common attributes. The proposed method was evaluated through three real datasets that include a total of 505 software projects. The performance of the proposed model was compared with other well-known estimation methods and the promising results showed that the proposed localization can considerably improve the accuracy of estimates. Besides the increase in accuracy, the results also certified that the proposed method is flexible enough to be used in a wide range of software projects.     

An intelligent optimization–based prediction model for natural gas hydrate formation in a deepwater pipeline

Temperature, pressure, and composition of gas mixtures in deepwater pipelines promote rapid formation of gas hydrates. To avert this dilemma, it is more significant to find out the temperature and pressure limits in gas hydrates formation of the deepwater pipeline. The objective of this research is to develop an optimization method that finds the optimal temperature and pressure profile for natural gas hydrate formation conditions and an error calculation method to find the realistic approach of the hydrate formation prediction model. A newly developed correlation model is computing the hydrate formation pressure and temperature for a single component of methane (CH₄) gas. The proposed developed prediction model is based on the 2 and 15 constant coefficients and holds a wide range of temperature and pressure data about 2.64 to 46°C and 0.051 to 400 MPa for pure water and methane, respectively. The reducing error discrepancies are 1.2871, 0.35012, and 1.9052, which is assessed by GA, PSO, and GWO algorithms, respectively. The results show the newly developed optimization algorithms are in admirable compliance with the experimental data and standards of empirical models. These correlations are providing the capability to predict gas hydrate forming conditions for a wide range of hydrate formation data.