A hierarchical fuzzy system for modeling driver’s behavior

The study of human behavior during driving is of primary importance for improving the driver??s security. In this study, we propose a hierarchical driver_vehicle_environment fuzzy system to analyze driver??s behavior under stress conditions on a road. We include climate, road and car conditions in fuzzy modeling. For obtaining fuzzy rules, experts?? opinions are benefited by means of questionnaires on effects of parameters such as climate, road and car conditions on driving capabilities. The number of fuzzy rules is optimized by Particle Swarm Optimization (PSO) algorithm. Also the frequency of pressing on brake and gas pedals and the number of car??s direction changes are used to determine the driver??s behavior under different conditions. Three different positions are considered for driving and decision making; one position in driving lane and two positions in opposite lane. A fuzzy model called Model 1 is presented for modeling the change of steering angle and speed control by considering time distances with existing cars in these three positions, the information about the speed and direction of car, and the steering angle of car. The behaviors of different drivers under two stress conditions are investigated. Also we obtained two other models based on fuzzy rules called Model 2 and Model 3 by using Sugeno fuzzy inference. Model 2 has two linguistic terms and Model 3 has four linguistic terms for estimating the time distances with other cars. The results of three models are compared. The comparative studies have shown that simulation results are in good agreement with the real world situations.     

A comparative study of two approaches for supporting optimal network location queries

Given a set S of sites and a set O of weighted objects, an optimal location query finds the location(s) where introducing a new site maximizes the total weight of the objects that are closer to the new site than to any other site. With such a query, for instance, a franchise corporation (e.g., McDonald’s) can find a location to open a new store such that the number of potential store customers (i.e., people living close to the store) is maximized. Optimal location queries are computationally complex to compute and require efficient solutions that scale with large datasets. Previously, two specific approaches have been proposed for efficient computation of optimal location queries. However, they both assume p-norm distance (namely, L₁ and L₂/Euclidean); hence, they are not applicable where sites and objects are located on spatial networks. In this article, we focus on optimal network location (ONL) queries, i.e., optimal location queries in which objects and sites reside on a spatial network. We introduce two complementary approaches, namely EONL (short for Expansion-based ONL) and BONL (short for Bound-based ONL), which enable efficient computation of ONL queries with datasets of uniform and skewed distributions, respectively. Moreover, with an extensive experimental study we verify and compare the efficiency of our proposed approaches with real world datasets, and we demonstrate the importance of considering network distance (rather than p-norm distance) with ONL queries.     

A benzoate coprecipitation route for synthesizing nanocrystalline GDC powder with lowered sintering temperature

Electrolyte powders with low sintering temperature and high-ionic conductivity can considerably facilitate the fabrication and performance of solid oxide fuel cells (SOFCs). Gadolinia-doped ceria (GDC) is a promising electrolyte for developing intermediate- and low-temperature (IT and LT) SOFCs. However, the conventional sintering temperature for GDC is usually above 1200 °C unless additives are used. In this work, a nanocrystalline powder of GDC, (10 mol% Gd dopant, Gd_0.1Ce_0.9O_1.95) with low-sintering temperature has been synthesized using ammonium benzoate as a novel, environmentally friendly and cost-effective precursor/precipitant. The synthesized benzoate powders (termed washed- and non-washed samples) were calcined at a relatively low temperature of 500 °C for 6 h. Physicochemical characteristics were determined using thermal analysis (TG/DTA), Raman spectroscopy, FT-IR, SEM/EDX, XRD, nitrogen absorptiometry, and dilatometry. Dilatometry showed that the newly synthesized GDC samples (washed and non-washed routes) start to shrink at temperatures of 500 and 600 °C (respectively), reaching their maximum sintering rate at 650 and 750 °C. Sintering of pelletized electrolyte substrates at the sintering onset temperature for commercial GDC powder (950 °C) for 6 h, showed densification of washed- and non-washed samples, obtaining 97.48 and 98.43% respectively, relative to theoretical density. The electrochemical impedance spectroscopy (EIS) analysis for the electrolyte pellets sintered at 950 °C showed a total electrical conductivity of 3.83 × 10^?2 and 5.90 × 10^?2 S cm^?1 (under air atmosphere at 750 °C) for washed- and non-washed samples, respectively. This is the first report of a GDC synthesis, where a considerable improvement in sinterability and electrical conductivity of the product GDC is observed at 950 °C without additives addition.     

PiSHi: click the images and I tell if you are a human

This paper introduces pictorial intelligent system for human identification (PiSHi), an image-based captcha which uses three human cognitive abilities to distinguish humans from machines. The first is the human ability to easily recognise the image’s upright orientation. The second is the human brain’s ability in recognising a picture’s content when it is only partially visible. And the third is the human ability in unconscious decision making when encountering pictorial challenges. This work models such complicated human patterns in problem solving for the first time. In order to extract these behavioural patterns and save them in a pattern database, we have implemented our own captcha and performed a series of experiments. PiSHi’s interface presents the user with a set of distorted pictures and asks her to click on the upright orientation of all the pictures in any preferred order. Next, it captures the user’s interaction patterns, compares them with the ones saved in the pattern database, and grants her a corresponding credit. Based on this credit, the user either passes or fails the test, and participates in updating the picture database. Our experiments indicate that human users can solve our proposed captcha effectively—with an accuracy of 99.44 %. Besides, our proposed system is secure against several types of attacks including random guessing and reverse image search engines. The results offer the possibility of utilising the identified human behavioural models in practical captchas.     

Optimization of peroxidase-catalyzed oxidative coupling process for phenol removal from wastewater using response surface methodology

Hydroxylated aromatic compounds (HACs) are considered to be primary pollutants in a wide variety of industrial wastewaters. Horseradish peroxidase (HRP) is suitable for the removal of these toxic substances. However, development of a mathematical model and optimization of the HRP-based treatment considering the economical issues by novel methods is a necessity. In the present study, optimization of phenol removal from wastewater by horseradish peroxidase (HRP) was carried out using response surface methodology (RSM) and central composite design (CCD). As the initial experimental design, 2(4-1) half-fraction factorial design (H-FFD) is accomplished in triplicate at two levels to select the most significant factors and interactions in the phenol removal procedure. Temperature (degrees C), pH, concentration of enzyme (unit mL(-1)), and H202 (mM) were determined as the most effective independent variables. Finally, a fourfactor-five coded level CCD, 30 runs, was performed in order to fit a second-order polynomial function to the results and calculate the economically optimum conditions of the reaction. The goodness of the model was checked by different criteria including the coefficient of determination (R2 = 0.93), the corresponding analysis of variance ((Pmodel > F) < 0.0001) and parity plot (r = 0.96). These analyses indicated that the fitted model is appropriate for this enzymatic system. With the assumption that the minimum enzyme concentration was 0.26 unit mL(-1), the analysis of the response surface contour and surface plots defined the optimum conditions as follows: pH = 7.12, hydrogen peroxide concentration 1.72 mM, and 10 degrees C. This work improves phenol removal operation economically by applying minimum enzyme concentration and highest removal in comparison with previous studies.     

Synthesis, characterization, and electrochemical properties of ultrafine β-Ni(OH)2 nanoparticles

Nickel hydroxide was deposited via cathodic electrodeposition from low-temperature 0.005 M NiCl₂ bath without using any surfactant or template. The cathodic current density was 1 mA cm⁻² and stainless steel was used as the cathode. The XRD pattern confirmed that the prepared sample has a pure brucite crystal phase of β-Ni(OH)₂ and the broadening of diffraction peaks showed that the particles size of the prepared β-Ni(OH)₂ is extremely small. Thermal behavior and composition of the prepared β-Ni(OH)₂ were investigated by DSC-TG and FT-IR analyses. Morphological characterization by SEM and TEM revealed that β-Ni(OH)₂ is composed of well dispersed ultrafine particles with size of about 5 nm. The electrochemical properties of the prepared nanoparticles were studied by means of cyclic voltammetry (CV) and galvanostatic charge-discharge tests in 1 M KOH. The prepared β-Ni(OH)₂ nanoparticles showed excellent capacitance behavior of 740 F g⁻¹ in the potential window of 0-0.55 V vs. Ag/AgCl. These results make the β-Ni(OH)₂ nanoparticles as a promising candidate for the supercapacitor electrodes.     

Gabapentin treatment of mood disorders: a preliminary study

OBJECTIVE: To determine if gabapentin is effective either as adjunctive treatment or as monotherapy for major affective disorders in a naturalistic setting. METHOD: All charts of patients meeting DSM-IV criteria for bipolar disorder or unipolar major depressive disorder treated with gabapentin in a private psychiatric practice were reviewed and clinical response was assessed retrospectively using the Clinical Global Impressions scale for Improvement (CGI-I). RESULTS: Gabapentin was moderately to markedly effective in 30% (15/50) of patients, with statistically nonsignificant differences between patients with bipolar disorder type I, bipolar disorder type II and NOS, and unipolar major depressive disorder. 70% reported side effects, mainly sedation, with 16% of the total sample discontinuing treatment due to adverse events. CONCLUSION: Gabapentin appears to be somewhat effective as add-on treatment in a subgroup of patients with mood disorders in a naturalistic setting. Prospective, controlled studies are required to clarify these pilot data.     

Stochastic economic analysis of FACTS devices on contingent transmission networks using hybrid biogeography-based optimization

Electrical Engineering - Flexible AC transmission systems (FACTS) devices have advantages of enhancing AC system controllability and stability, increasing power transfer capability and relieving...     

Investigation of Size and Shape Dependencies of Phase Diagrams of the Ising Nanofilms and Nanotubes on the Honeycomb Lattice Using Cellular Automata Simulation Approach

Size and shape dependencies of phase diagrams of the Ising nanofilms and nanotubes on the honeycomb lattice are investigated by means of probabilistic cellular automata simulation based on Glauber algorithm. The values of reduced critical temperature, K _c = k _B T _c/J (where k _B and J are the Boltzmann constant and nearest-neighbor coupling, respectively), for both nanofilms and nanotubes, are obtained at the different sizes of the lattices and the dependency of K _c to the number of layers is studied. By increasing the number of layers K _c increases but for number of layer more than 8, the critical temperature increases very slowly. We have shown that between two isotropic nanotubes with the same number of spins, the ones with greater diameter (more spins on the edge) have larger critical temperature. For equal size of lattices, the obtained values of K _c for nanotube are greater than the nanofilm, but for large sizes, this difference disappears.