Enhanced backstepping sliding mode controller for motion tracking of a nonlinear 2-DOF piezo-actuated micromanipulation system

Microsystem Technologies - In this paper a robust backstepping sliding mode controller is developed for tracking control of 2-DOF piezo-actuated micromanipulation system. The control approach is...     

Recognition Using Region Correspondences

Recognition systems attempt to recover information about the identity of observed objects and their location in the environment. A fundamental problem in recognition is pose estimation. This is the problem of using a correspondence between some portions of an object model and some portions of an image to determine whether the image contains an instance of the object, and, in case it does, to determine the transformation that relates the model to the image. The current approaches to this problem are divided into methods that use global properties of the object (e.g., centroid and moments of inertia) and methods that use local properties of the object (e.g., corners and line segments). Global properties are sensitive to occlusion and, specifically, to self occlusion. Local properties are difficult to locate reliably, and their matching involves intensive computation.We present a novel method for recognition that uses region information. In our approach the model and the image are divided into regions. Given a match between subsets of regions (without any explicit correspondence between different pieces of the regions) the alignment transformation is computed. The method applies to planar objects under similarity, affine, and projective transformations and to projections of 3-D objects undergoing affine and projective transformations. The new approach combines many of the advantages of the previous two approaches, while avoiding some of their pitfalls. Like the global methods, our approach makes use of region information that reflects the true shape of the object. But like local methods, our approach can handle occlusion.     

Alcoholysis of palm oil mid-fraction by lipase from Rhizopus rhizopodiformis

A mycelial lipase from Rhizopus rhizopodiformis was prepared in fragment form. The lipase was examined to catalyze the alcoholysis of palm oil mid-fraction (PMF) in organic solvents. High percentage conversions of PMF to alkyl esters were achieved when methanol or propanol was used as acyl acceptor. Of the two most prevalent fatty acids in PMF, palmitic acid seemed to be preferred over oleic acid in the formation of methyl and propyl esters. The optimal ratio of oil to methanol in the alcoholysis reaction is 1 to 2 moles. The lipase exhibited high alcoholysis activities in nonpolar solvents (log P>2), such as hexane, benzene, toluene, and heptane. The enzyme showed exceptionally high thermostability.     

Enhanced mechanical flexibility and performance of sodium alginate polymer electrolyte bio‐membrane for application in direct methanol fuel cell

A new membrane was synthesized containing pure alginate, crosslinking agent (CaCl₂), and plasticizer (glycerol). Characterization studies of the membrane were applied to determine the characteristics and morphology using field emission scanning electron microscope, EDX, FTIR, XRD, and atomic force microscopy analysis. The half‐cell performance test of the membrane was verified by several tests, including proton conductivity and methanol permeability. The best membrane had high proton conductivity (10.1 × 10^?3 S cm^?1) and very low methanol permeability (1.984 × 10^?7 cm² s^?1), which consequently resulted in very high selectivity (5.0907 × 10⁴ Ss cm^?3). Glycerol had a positive modification and good influence on the alginate characteristics. Furthermore, the poor mechanical properties of the alginate biopolymer were enhanced by calcium chloride and glycerol inside the polymer. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46666.     

Improved catalytic activity by catalase immobilization using γ‐cyclodextrin and electrospun PCL nanofibers

Nanofibrous structures are promising for biocatalyst immobilization due to their large surface area which facilitates the enzyme attachment, stability, ease of separation, and fine porous structure. There is limited research available on the change in enzyme activity following interaction with cyclodextrin. In this study, catalase enzyme was immobilized into nanofibrous structures by various techniques, with and without γ‐CD addition, and the enzymatic activity of catalase was evaluated. In addition, catalase‐γ‐CD complex containing PEO polymer solution was electrospun in between PCL nanofibrous layers as a newly developed technique. The enzyme immobilized nanofibrous structures were characterized by SEM, XRD, and FT‐IR analysis methods. Among all the activity tests, best enzyme activity was recorded with catalase‐γ‐CD physical mixture encapsulated PCL nanofibrous layers. Moreover, the test results indicated that the use of cyclodextrin in immobilization process considerably improves the catalytic activity of the enzyme. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44404.     

Solid-phase extraction of Mn(II), Co(II), Ni(II), Cu(II), Cd(II) and Pb(II) ions from environmental samples by flame atomic absorption spectrometry (FAAS)

A new method using a column packed with Amberlite XAD-2010 resin as a solid-phase extractant has been developed for the multi-element preconcentration of Mn(II), Co(II), Ni(II), Cu(II), Cd(II), and Pb(II) ions based on their complex formation with the sodium diethyldithiocarbamate (Na-DDTC) prior to flame atomic absorption spectrometric (FAAS) determinations. Metal complexes sorbed on the resin were eluted by 1 mol L(-1) HNO3 in acetone. Effects of the analytical conditions over the preconcentration yields of the metal ions, such as pH, quantity of Na-DDTC, eluent type, sample volume and flow rate, foreign ions etc. have been investigated. The limits of detection (LOD) of the analytes were found in the range 0.08-0.26 microg L(-1). The method was validated by analyzing three certified reference materials. The method has been applied for the determination of trace elements in some environmental samples.     

Visual Homing: Surfing on the Epipoles

We introduce a novel method for visual homing. Using this method a robot can be sent to desired positions and orientations in 3D space specified by single images taken from these positions. Our method is based on recovering the epipolar geometry relating the current image taken by the robot and the target image. Using the epipolar geometry, most of the parameters which specify the differences in position and orientation of the camera between the two images are recovered. However, since not all of the parameters can be recovered from two images, we have developed specific methods to bypass these missing parameters and resolve the ambiguities that exist. We present two homing algorithms for two standard projection models, weak and full perspective.Our method determines the path of the robot on-line, the starting position of the robot is relatively not constrained, and a 3D model of the environment is not required. The method is almost entirely memoryless, in the sense that at every step the path to the target position is determined independently of the previous path taken by the robot. Because of this property the robot may be able, while moving toward the target, to perform auxiliary tasks or to avoid obstacles, without this impairing its ability to eventually reach the target position. We have performed simulations and real experiments which demonstrate the robustness of the method and that the algorithms always converge to the target pose.     

When is it Possible to Identify 3D Objects From Single Images Using Class Constraints?

One approach to recognizing objects seen from arbitrary viewpoint is by extracting invariant properties of the objects from single images. Such properties are found in images of 3D objects only when the objects are constrained to belong to certain classes (e.g., bilaterally symmetric objects). Existing studies that follow this approach propose how to compute invariant representations for a handful of classes of objects. A fundamental question regarding the invariance approach is whether it can be applied to a wide range of classes. To answer this question it is essential to study the set of classes for which invariance exists. This paper introduces a new method for determining the existence of invariant functions for classes of objects together with the set of images from which these invariants can be computed. We develop algebraic tests that determine whether the objects in a given class can be identified from single images. These tests apply to classes of objects undergoing affine projection. In addition, these tests allow us to determine the set of views of the objects which are degenerate. We apply these tests to several classes of objects and determine which of them is identifiable and which of their views are degenerate.     

A geometric interpretation of weak-perspective motion

We present a geometric interpretation of the problem of motion recovery from three weak-perspective images. Our interpretation is based on reducing the problem of estimating the motion to a problem of finding triangles on a sphere whose angles are known. Using this geometric interpretation, a simple method to completely recover the motion parameters using three images is developed. The results of running the algorithm on real images are presented. In addition, we describe which of the various motion parameters can be recovered already from two images     

Statistical analysis of accurate prediction of local atmospheric optical attenuation with a new model according to weather together with beam wandering compensation system: a season-wise experimental investigation

Abstract

Atmospheric parameters strongly affect the performance of Free Space Optical Communication (FSOC) system when the optical wave is propagating through the inhomogeneous turbulent medium. Developing a model to get an accurate prediction of optical attenuation according to meteorological parameters becomes significant to understand the behaviour of FSOC channel during different seasons. A dedicated free space optical link experimental set-up is developed for the range of 0.5 km at an altitude of 15.25 m. The diurnal profile of received power and corresponding meteorological parameters are continuously measured using the developed optoelectronic assembly and weather station, respectively, and stored in a data logging computer. Measured meteorological parameters (as input factors) and optical attenuation (as response factor) of size [177147 × 4] are used for linear regression analysis and to design the mathematical model that is more suitable to predict the atmospheric optical attenuation at our test field. A model that exhibits the R² value of 98.76% and average percentage deviation of 1.59% is considered for practical implementation. The prediction accuracy of the proposed model is investigated along with the comparative results obtained from some of the existing models in terms of Root Mean Square Error (RMSE) during different local seasons in one-year period. The average RMSE value of 0.043-dB/km is obtained in the longer range dynamic of meteorological parameters variations.