Lack of associative filters in lattice implication algebras

Jun et al. (Bull Korean Math Soc 35(1):53–61, 1998) introduced the notion of associative filters in lattice implication algebra and studied some of its properties. In this paper, we show that there is no associative filter in lattice implication algebra.     

A novel method for tracking and counting pedestrians in real-timeusing a single camera

This paper presents a real-time system for pedestrian tracking in sequences of grayscale images acquired by a stationary camera. The objective is to integrate this system with a traffic control application such as a pedestrian control scheme at intersections. The proposed approach can also be used to detect and track humans in front of vehicles. Furthermore, the proposed schemes can be employed for the detection of several diverse traffic objects of interest (vehicles, bicycles, etc.) The system outputs the spatio-temporal coordinates of each pedestrian during the period the pedestrian is in the scene. Processing is done at three levels: raw images, blobs, and pedestrians. Blob tracking is modeled as a graph optimization problem. Pedestrians are modeled as rectangular patches with a certain dynamic behavior. Kalman filtering is used to estimate pedestrian parameters. The system was implemented on a Datacube MaxVideo 20 equipped with a Datacube Max860 and was able to achieve a peak performance of over 30 frames per second. Experimental results based on indoor and outdoor scenes demonstrated the system s robustness under many difficult situations such as partial or full occlusions of pedestrians     

Rapid Separating and Enrichment of 4,4′-Dimethylsterols of Vegetable Oils by Solid-Phase Extraction

Phytosterols are separated into three classes: 4-desmethylsterols, 4-monomethylsterols and 4,4′-dimethylsterols. 4,4′-Dimethylsterols are used to detect vegetable oil adulteration and some compounds from this class can have anti-inflammatory and anticancer properties. There are methods such as thin layer chromatography (TLC) and solid phase extraction (SPE) used to separate phytosterol classes from each other. However, in some cases, separation of all three classes is not required. In addition, TLC has some drawbacks such as low recovery and it is time consuming. An SPE method has previously been used, but it was necessary to use high volume of solvents with this method to avoid coelution of phytosterol classes. In this study, an SPE (silica, 1 g) method was developed to separate and enrich only 4,4′-dimethylsterols from unsaponifiables of vegetable oil samples using 25 mL n-hexane and diethyl ether (95:5, v:v). This method was applied to hazelnut and olive oils and results were compared with those of TLC and the previously developed SPE method. Recovery of 4,4′-dimethylsterols was two times higher with the new SPE method compared with the TLC method. The newly developed SPE method generally gave a similar recovery compared with the previously developed SPE method. Moreover, the SPE method developed in this study has the advantage of using a 3.5 times lower volume of solvent than previously developed SPE methods. Because the newly developed SPE method has a single step requiring a low volume of solvents, it is rapid and simple, and can easily be used to detect olive oil adulteration with hazelnut oil and to analyze and quantify effective nutritional compounds in the 4,4′-dimethylsterols class.     

Mining and fusion of petroleum data with fuzzy logic and neural network agents

Analyzing data from well logs and seismic is often a complex and laborious process because a physical relationship cannot be established to show how the data are correlated. In this study, we will develop the next generation of “intelligent” software that will identify the nonlinear relationship and mapping between well logs/rock properties and seismic information and extract rock properties, relevant reservoir information and rules (knowledge) from these databases. The software will use fuzzy logic techniques because the data and our requirements are imperfect. In addition, it will use neural network techniques, since the functional structure of the data is unknown. In particular, the software will be used to group data into important data sets; extract and classify dominant and interesting patterns that exist between these data sets; discover secondary, tertiary and higher-order data patterns; and discover expected and unexpected structural relationships between data sets.     

Facile synthesis and characterization of CdTiO<Subscript>3</Subscript> nanoparticles by Pechini sol–gel method

In this work, CdTiO₃ nanoparticles were synthesized through reaction between Cd(CH₃COO)₂.2H₂O, Ti(OC₄H₉)₄, trimesic acid as a new chelating agent and ethanol as solvent by Pechini sol–gel method. X-ray diffraction (XRD) patterns showed that CdTiO₃ nanostructures have rhombohedral structure with diameter of about 35.61 nm. The structure, morphology and size of CdTiO₃ nanoparticles were characterized by FT-IR, XRD, SEM and EDAX. The optical properties of the products were studied by DRS. Based on the results of experiments, it was found that temperature and time of calcination, pH and the solvent of reaction are important parameters for formation of CdTiO₃ nanoparticles. Utilizing trimesic acid (benzene-1,3,5-tricarboxylic acid) as a new chelating agent for preparation of CdTiO₃ nanostructures was initiative of this work.     

Synthesis of Co<Subscript>2</Subscript>P/Co nanocomposites using single source precursor by thermal decomposition method

In this article, the synthesis and characterization of Co₂P/Co nanocomposites are reported. Three kinds of precursors are studied: bis(salicylidene)cobalt(II) [Co(sal)₂], bis(salicylate)cobalt(II) [Co(Hsal)₂] and cobalt oxalate [Co(O₄C₂)·4H₂O]. The cobalt(II) acetate tetrahydrate Co(CH₃COO)₂·4H₂O is used as reference. The nanocomposites are prepared by thermal decomposition method using triphenylphosphine as a surfactant solvent and phosphorus precursor. A possible mechanism of the formation of the nanocomposites is put forward to explain the experimental observations. This is the first time that Co₂P/Co nanocomposites are synthesized. To study the crystalline structure, composition, size, morphology and magnetic property of the products, characterization techniques including XRD, SEM, TEM, FT-IR and VSM are employed.     

Development of a disposable sensor for electrocatalytic detection of guanine and ss-DNA using a modified sol-gel screen-printed carbon electrode

The electrocatalytic oxidation of guanine and DNA is demonstrated on a sol-gel coated carbon screen printed electrode modified with {MeReO(edt)}₂ using cyclic and differential pulse voltammetric techniques. An oxidation peak at 370 mV was found, but no corresponding reduction peaks could be detected in the negative scan, which indicates that the oxidation of guanine is completely irreversible process. The oxidation peak potentials are shifted to more negative values with increasing pH. The utility of applying the sensor for determination of guanine and ss-DNA were investigated. The linear ranges were 0.19-10.8 and 0.45-7.8 μg ml⁻¹ for guanine and DNA, respectively. Detection limits of 0.1 and 0.32 μg ml⁻¹ were obtained for guanine and ss-DNA, respectively.     

Multiobjective shape optimization of speed humps

This paper presents a new approach to the shape optimization of road speed humps. The proposed approach is based on multiobjective genetic optimization of the hump profile while taking into account the separation phenomenon, which occurs when the front tires of the vehicle momentarily lose contact with the road surface. The optimization is carried out for speeds up to twice the authorized speed (throughout this article, the term authorized speed refers to speed limits enforced in speed reduction [bump] areas of the roads) rather than for illegally high speeds as adopted by many of the previous works. A 6-degree of freedom non-linear dynamic model is used to identify the speeds at which separation occurs, and hump profiles associated with these speeds are discarded as infeasible solutions. Three independent objective functions are selected for optimization. They include the maximum vertical acceleration experienced by the driver when crossing the hump below the authorized speed limit (to be minimized), the same vertical acceleration at speeds above the authorized speed (to be maximized), and the ascending ratio of the “speed—vertical acceleration” curve (to be maximized). These objective functions are evaluated for more than 10,000 humps of two popular profile types (sinusoidal and flat top with straight ramps) and optimum profiles for three speed limits of 20, 25, and 30km/h are determined using the multiobjective nondominated sorting genetic algorithm II. As a result, a Pareto front of at least ten optimal points is achieved for each of the two hump profile types. Furthermore, to incorporate the economical aspects of the real-world problem, Pareto optimal points for the two profile types were compared based on their lateral section areas (an indication of the manufacturing cost). The comparison shows that sinusoidal humps more often than not outdo their flat top rivals economically.     

A microprocessor-based adaptive power factor corrector fornonlinear loads

A microprocessor-based adaptive power factor corrector for poor power factor (linear or nonlinear) loads is introduced. The system power factor is measured by the microprocessor and compared with a predetermined reference value. Accordingly, the microprocessor adjusts the power factor to get the predetermined value. This is achieved by controlling the firing angle of a thyristorized static VAR (volt-ampere reactive) compensator through microcomputer software. The system power factor is measured by the microprocessor at every supply cycle, and the above sequence is repeated. The proposed scheme achieves both accurate measurement and adjustment of the system power factor