The mechatronic design of a biomimetic finger prosthesis driven by a new hybrid mechanism is presented. The finger joints are driven by a miniature direct current (DC) motor and a shape memory alloy (SMA) wire. By using a miniature DC motor, a high response rate as well as comparable torque and speed can be achieved at the metacarpophalangeal (MCP) joint. By using SMA to actuate the proximal interphalangeal (PIP) joint, the finger configuration has been miniaturized to anthropomorphic size and weight. Kinematic analysis shows that the finger design can achieve the range of movements of the human counterpart and hence closely resemble its functionality. In order to assess the performance characteristic of the SMA wire, the relationship between the generated displacement and the contraction time has been tested for varying energizing currents. Furthermore, a comparison has been made to ascertain the viability of the conductive rubber sheet for tactile sensing compared to the quantum tunneling composite (QTC) pills.
In this paper, we propose a system for Arabic online word extraction from handwritten text lines, a problem addressed for the first time for Arabic language as there is no public dataset of Arabic online handwritten texts available so far. We collected a dataset of unconstrained online handwritten sentences and used it to design and evaluate our system. First, our system classifies the white gaps between words connected components into either intra-word or interword gap according to some local and global online features extracted from each gap together with the groups of strokes encompassing the gap. The classifier is a polynomial kernel support vector machine (SVM) which decisions are used for initial word extraction. A post stage is added to the system to test the extracted words for under-segmentation and resolve this undersegmentation by reconsidering the gap type decisions for the stuck word. Classifiers decision fusion takes place by consulting five different classifiers (four SVM and a radial basis function neural network 'RBF NN') and feeding their decisions to a separate pre-trained SVM to make the final decision. Most stuck words are correctly detected and a lot of them have been correctly resolved. The post stage leads to remarkable error reduction compared to single classifiers performance. Promising results are achieved regarding the fact that the unconstrained Arabic handwriting nature adds more difficulties to the problem.
Texture defect detection became one of the problems which has been paid much attention on by image processing scientists since late 90s. Since now many different methods have been proposed to analysis and classification textures. An approach which provides good features to classification is local binary patterns. In this paper an approach is proposed to detection porosity in stones by using the improved form of local binary patterns features. The proposed approach includes two stages. First of all, in train stage, by applying local binary pattern operator on absolutely porosity less images, the basic feature vector is calculated. After that, by image windowing and computing the non-similarity amount between these and basic vector, the porosityless threshold is computed. Finally, in test stage, by using the porosity-less threshold the porosities is detected on test images. In the result part, the accuracy rate of proposed approach is computed by applying on some captured images and compared with some previous methods. High detection rate, low time complexity, rotate invariant and noise insensitive are advantages of proposed approach. Also, the proposed approach can use for every case of defect detections or visual classification.
This paper studies the design of a static output feedback controller of a Synchronous Machine. By employing a well-known Takagi-Sugeno approach, the continuous nonlinear system is first described by Takagi-Sugeno (T-S) models. Next, we develop a technique for designing a output feedback control law which stabilizes the Synchronous Machine. The controller is designed in terms of Linear Matrix Inequalitie (LMI) problem. Motivated by stability results developed for parallel distributed compensation (PDC) controller, the Output PDC (OPDC) controller was studied in this work. Simulation results for synchronous machine demonstrate the OPDC controller's effectiveness.
With the remarkable progress in the field of gene technology, proteins take an important place in the field of disease diagnosis and treatment. Adsorption of biomolecules on the surface of inorganic materials is an important technique for diagnostic assays and gene applications. Here, mesocage cubic Pm3n aluminosilica monoliths with well-defined mesostructures offer high adsorption and loading capacity of proteins from aqueous solution. The three-dimensional (3D) with spherical pore cavities of monoliths show promise for efficient adsorption of insulin (INS), cytochrome C (CytC), lysozyme (LYS), myoglobin (Mb), β-lactoglobin (β-LG) proteins. Our findings indicated that the formation of monolayer coverage of proteins onto bioadsorbent surfaces during the immobilization and uptake assays. The adsorption efficiency of proteins was attained after a number of reuse cycles, indicating the significant dead-end porosity of bioadsorbant monoliths. Such integration of bioadsorbent might lead to the feasibility of its application in various scientific fields, such as nanobioscience, material science, artificial implant, proteins-purification strategies, biosensors, drug delivery systems, and molecular biology/biotechnology.
We report the fabrication of hierarchical mesoporous NiO nanocrystals (NCs) with sheet-like morphology via a simple, and eco-friendly hydrothermal method. Mesoporous NiO particles were characterized by small- and wide-angle X-ray diffraction, nitrogen adsorption/desorption, Scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The results demonstrated that the as-prepared Ni(OH)2 sheet converted to disordered mesoporous NiO NCs with retention their hexagonal morphology during controlled thermal treatment. The physical characteristics of NiO NCs such as porosity, surface area, and pore volume enabled the phenolic pollutants such o-aminothiophenol (o-ATP) to access the active site of the nanosheets. The features of NiO NCs with sheet-like morphology induced high catalytic activity and excellent reusability even after extended recycle uses. Moreover, the mechanistic pathway of the phenolic pollutants transformation was demonstrated theoretically using density functional theory (DFT).
In adaptive control and system identification the self tuning regulator has wide range of applications. Neural network and artificial intelligence have big role in this area. This paper presents adaptive neural network control based on self tuning regulator (STR) scheme. The paper presents neural network block for on line system identification and discrete PID block controller. Analysis for the whole scheme is presented and simulated for different systems. Adequate desired performance is obtained by comparison with the nominal methods for using self tuning regulator.
The considerable contamination of the aqueous environment by organic pollutants still requires the development of effective adsorbents these compounds. The current work reports the applicability of mesoporous aluminosilica monoliths with three-dimensional structures and aluminum contents with 19 ≤ Si/Al ≥ 1 as effective adsorbents of aniline molecules from an aqueous solution. To better understanding the role of microscopic geometry and the nanoscale pore orientation of mesostructures, theoretical models have been developed. In addition, the atomic charge distribution in the interior structures was investigated to give insight about the effect of active site surfaces in the enhancement of the adsorption process. Our experimental results suggest that the acidity of the adsorbents significantly increased with increasing amounts of aluminum species in the pore framework walls. The natural surfaces of active acid sites of monoliths strongly induced the removal and adsorption of environmentally toxic aromatic amines from wastewater. The relative adsorption affinity of the mesocage adsorbent for organic pollutants was decreased in the order of p-nitroaniline
The problem of rigid bodies' systems dynamics and its practical engineering applications such as attitude motion and control of multi-rotor spacecrafts (gyrostats-satellites, dual-spin-spacecrafts, spacecrafts with systems of momentum wheels and control moment gyros) and robotics are very important for modern science and, especially for space flight mechanics. Despite classical analytical research results this problem is still far from complete due to the existence of complicated non-linear regular and chaotic phenomena. In the framework of the indicated problem we describe the following points: deriving exact and approximated analytical solutions, the analysis of the attitude motion under an influence of external and internal disturbances, research into chaotic behaviors of the SC, study of the attitude motion of the SC with variable parameters (timedependent mass-inertia parameters), investigation into attitude reorientations of the SC and multi-rotor roll-walking robots. Firstly, we consider the attitude motion of the dual-spin spacecraft with time-dependent moments of inertia (with an active solid-propellant rocket engine) on the base of special method of the phase trajectories' curvature analysis. Secondly, we conduct the dynamics simulation of the gyrostats in a resistant environment at presence of chaotic attractors (Lorenz, Rossler, Newton--Leipnik, and Sprott systems). In the third place we examine the heteroclinic dynamics of the dual-spin spacecraft on the base of analytical solutions for heteroclinic orbits in the space of the SC angular moment components. With the help on Melnikov's method we show the system motion chaotization and possibility of the SC chaotic tilting motion. Finally, we present a multi-rotor drive system, which can be used for the attitude control of the spacecraft and a roll-walking motion of the multi-rotor robot. This multi-rotor system contains a large number of rotor-equipped rays. It allows using spinups and captures of conjugate rotors to perform compound motion of the multi-rotor spacecraft and the walking robot attitude reorientation.
In this paper a roll-walking motion of a robot with a multi-rotor drive system is considered. The robot represents a rigid body with the multi-rotor drive system which consists of pairs of conjugate rotors located on the main axes. The multi-rotor drive system allows using conjugate spinups and captures of conjugate rotors to perform roll-walking motion of the robot. To perform a single step of the robot we need to perform conjugate spinup of the pair of conjugate rotors, and then make a capture (braking) one of them. After this capture the rotor's angular moment is transmitted to the main rigid body of the robot and it makes an angular motion relative to one of its axes. Capture of the second conjugate rotor compensates the angular moment and stops the rotation of the main robot body.
Understanding various interaction forces between building blocks is of great importance to their selfassembly. In this paper, the effects of size, crystal plane, shape and atomic discrete structure on interaction potentials between carbon nanoparticles have been studied by fully atomistic molecular dynamics simulation. The results show that Hamaker approach underestimates the interaction potentials between carbon nanospheres, indicating that it does not apply to nanoparticles; the interaction energies between identical crystal planes of diamond are of the order (111) (110) (001); The larger the particle is, the greater the equilibrium separation. For a given particle size, interaction potential between amorphous carbon nanosphers is higher than that between diamond nanospheres. The results may also provide insight into nanoparticle growth and packing behaviors.
Recent research on Ln2O3-type oxide nanomaterials provide challenges to both fundamental and breakthrough development of technologies in various areas such as electronics, photonics, display, lasing, detection, optical amplification, fluorescent sensing in biomedical engineering and environmental control. Gadolinium oxide (Gd2O3) is a Ln2O3-type oxide. Gd2O3 nanocrystalline phosphor was synthesized by solution combustion method by using citric acid and urea fuels. The final product was examined by well characterized techniques such as powder X-ray diffraction pattern (PXRD), UV-Visible, photoluminescence (PL) measurements etc. A broad PL emission band at ∼375 nm was observed in all samples excavated at 270 nm. This emission band may be attributed to recombination of a delocalized electron close to the conduction band with a single charged state of surface oxygen vacancy, according to Wang's proposal.
Our trans-disciplinary and trans-generational team is realizing home+, an intelligent physical environment featuring a suite of networked, robotic components distributed across any domestic interior. home+ is aimed at increasing the quality of life of both healthy individuals and persons with impaired mobility and cognitive functioning by intelligently supporting their interaction with their home environment. This paper is focused on a key discrete component of the larger home+ project: an Assistive, Robotic Table [ART]. Physically, ART is the hybrid of a typical nightstand found at home and the over-the-bed table universally found in hospital patient rooms, comprised of: a smart storage volume that physically manages and delivers personal effects; a table surface that gently folds, extends, and reconfigures to support work and leisure activities; and an accessorized headboard. These aspects of ART recognize, communicate with, and partly remember each other in interaction with human users and, as we envision, with other home+ components.
Environmental pollutions due to the toxic gases, elements and pathogenic species are a serious problem with harmful effects on plants, animals, and human health. Achieving proper designs of nanosensors for highly sensitive and selective detection and removal of extremely hazardous materials is one of the crucial issues in our laboratory. Our main interest is not only to make nanotechnological designs-based nanomaterials but also to reduce the production cost and to expand their potential on-site and real-time measurements. El-Safty and Coworkers designed of nanopackages-based mesocage mosaic, core/double-shell, nanosheets, hollow sphere and nanowires metal oxides for capturing and monitoring toxic agents to protect human health and improve the environmental quality. However, we developed rapid easy-handling and cheap nanosensors for visual detection and removal of toxic metals from water and wastewater treatment systems, which are major public health challenges in world wide. Our optical mesoporous sensors show ability to create simultaneous designs for complete removal of extremely toxic metals such as As(V), Hg (II), Cd(II), Pb(II), Cr(VI), Zn(II) ions and etc.., with indoor and outdoor responses, and with revisable, selective and sensitive recognition of these toxic metals. Toward the challenging subject of radiaoactive monitoring and separation after the recent disaster of the nuclear plants at Fukushima Diaichi, JAPAN (March, 11, 2011), El-Safty and co-workers developed simple processing and captors-based nanomaterials for separation of the radioactive of Iodine (131I2), strontium (85Sr), cesium (137Cs), cerium (144Ce) and cobalt (60Co) in aqueous and marine water. Our technology is not only enabled the ultra-trace concentrating collection of 137Cs, 85Sr and 131I2 radio-elements but also led to decreasing capacity, and managing of these radioactive elements. Moreover, the nanocapture material can be repeatedly recycled. Significantly, the color of the nano-capture material changes when the radio-element is adsorbed. Therefore, it is possible not only had to be captured the element effectively but also to be used to detect radioactive elements by visualization. Recently, we have successfully fabricated nanopackage gas sensors. The patterned design based on nanosized WO3, Co2O3, SnO2 and NiO oxides enabled the detection of extremely toxic nitrogen dioxide and volatile organic compounds VOCs. The principal design of the nanopackages relies on the enhancement of total-volume-exposure of sensing materials to the analytic gases. The key component of this design is that the gas nanosensors can offer ultra-sensitive and selective detection of nitrogen dioxide at a low level concentration among carbon monoxide, and VOCs, such as acetone, benzene, and ethanol. We expected this nanopackage sensors can revolutionize the consumer and industrial market in environmental pollution monitoring, transportation, security, defense, space missions, energy, agriculture, and medicine.
In this work, a novel structured silica-supported Preyssler nano particles /carbon nanotube composite is synthesized. Multiwalled carbon nanotubes (MWCNTs) were synthesized by catalytic chemical vapor deposition method (CVD). The characterization of the materials by the Fourier transform infrared spectroscopy (FTIR), and Transmition electron microscopy (TEM), showed that the functionalization of MWCNTs by silicasupported Preyssler nano particles was successfully achieved via impregnation method. It has been found that the synthesized composite with 30 wt% loading is highly active catalyst in synthesis of β-acetamido ketones/esters and shows high yields in this reaction. This catalyst can be easily recovered and reused for many times without a significant loss in its activity.
Clustering algorithms have many useful applications in signal processing and pattern recognition. In conventional clustering methods, we classify objects in terms of all features available and measure the similarity between two objects using a distance metric. In biclustering, we detect coherent patterns in both object and feature directions and we are interested in data consistency, such as simultaneous downward or upward changes of a subset of features for a subset of objects, rather than the distances among all objects for all features. Biclustering is naturally more difficult than clustering computationally and is often considered intractable mathematically. We have recently developed hyperplane based methods for the detection of a class of biclusters in a high-dimensional signal space. Our methods provide a unified model for several types of biclusters and can be implemented using efficient signal processing algorithms. We have also found an interesting link between biclustering and the spectral graph theory. We have applied our biclustering methods to disease diagnosis and drug therapeutic effect assessment using DNA microarray gene expression data. For example, we are able to identify biclusters of a subset of genes that co-express under a subset of conditions. These biclusters are useful for the identification of caner types and sub-types. We have also implemented biclustering algorithms on the field-programmable gate array (FPGA) for fast computation. In this seminar, the recent work of our research group on biclustering methods and their applications will be presented.
The industrial revolution of the 1800's was underpinned by iron, copper, and aluminum materials. The electronics revolution in the 1900's was based on silicon and semiconductor materials. Then the composite materials revolution began replacing metals later in the 1900's. While the materials developed in these revolutions have been effective, they are now hitting the wall in terms of meeting the performance requirements for current machines, structures, and electronic devices. Metals are too heavy and they corrode and fail by fatigue, silicon electronics is reaching its limit of miniaturization, and current composite materials are brittle and poor thermal and electrical conductors. In the 21st century, carbon materials are being synthesized at the nanoscale and are providing properties that greatly exceed those of traditional materials. Carbon nanoscale materials are also being scaled up to form macro-scale materials with properties that are becoming competitive with existing materials. But overall, producing consistent high quality nanoscale materials and scaling them up to produce macroscale materials with breakthrough properties has not been achieved. Nanotechnology has been going on for about fifteen years. This is a short time compared to the early industrial revolutions that took 50-100 years to develop. Still, progress toward industrializingnanotechnology is too slow.Unless this issue of scalability and consistency is addressed, the major benefits of carbon nanotechnology may never be realized. Now is the time for a large internationally coordinated effort directed toward improving material quality and scalability and to transition carbon nanotechnology from science to industrialization. This talk will discuss approaches for Industrializing Carbon Nanotechnology with the vision to collaborate and power an industrial revolution in carbon nanotechnology for the 21st century. The goal of the nanotechnology industrial revolution will develop scalable nanostructured carbon materials, transformative devices, and recyclable materials and systems with breakthrough performance to replace traditional materials. Four science thrust areas will be discussed where research efforts are particularly needed: ST-1 CNT Synthesis Chemistry, Post treatments; ST-2Superlong, High Quality CNT Arrays, andNanosphere Chains; ST-3 Graphene Synthesis; and ST-4 Substrate and Reactor Engineering.Synthesis of nanoscale materials is the most important science thrust andembodies all of the promise and challenges of nanotechnology. A critical priority in developing scalable nanotechnology is to develop technology that allows transitioning from nanotubes and graphene flakes to 3- D structures and systems. This talk will discusssynthesis of carbon nanotube arrays or forests, why carbon materials have defects, why nanotubes stop growing, why yarn does not achieve the strength of nanotubes, and how to scale up the properties of graphene. The importance of carbon nucleation and growth is fundamental in terms of engineering because it may enable manufacturing the strongest and most electrically conductive materials in the world. Similarly, four technology thrust areas will be discussed where research efforts are particularly needed: TT-1 Energy Systems; TT-2 Nanomedicine Devices; TT-3Space Industrialization; and TT-4 Composite Materials. Medicine is an area that can benefit tremendously from carbon nanotechnology.Implantable electronics, biomedical fiber that is electrically conductive, pliable, and stronger than steel, biosensors, and tissue scaffolding are near-term applications. Carbon will be the only material available to build non-metallic tiny electric motors and solenoids that will work inside the body. And close collaboration between the medical community and engineers will provide solutions doctors and biologists can't see alone. Putting these kinds of devices in the hands of physicians would produce mind-boggling advances, like science fiction come alive. Energy harvesting and generation using carbon nanostructured materials is expected to revolutionize the way electricity is produced including improved solar cells, fuel cells, and hydrogen production and storage. CNT arrays, ribbon, and yarn will replace copper and metals for power distribution, to build carbon electronics, superinductors, electrical fiber, and supercapacitors. Ultra-high magnetic field densities >5 T and forces that can tear materials apart theoretically can be produced using nanotube electromagnetics. An all carbon electric motor may be 60% lighter than conventional motors. The carbon industrial revolution should also include Space Industrialization with advisement from leaders like Stephen Hawking at Cambridge. There's plenty of carbon in the universe along with energy for growing CNTs, and vacuum is suitable for post processing and spinning yarn. Space nanotechnology may be the only way to manufacture large structures like a space elevator ribbon and large solar panels to provide enough clean energy for the world. The carbon industrial revolution has a high probability of success because samples of super-strong CNT yarn and highly conductive graphene have already been demonstrated.
Wireless sensor network plays a vital role in the determination as well as evaluation of the performance behaviour of different routing protocols available in this domain. Here in this paper we evaluated one of the commonly used networks routing protocol-Ad-hoc on demand distance vector routing. This paper proposes an improved assessment about the AODV protocol over temperature specific constraints in the wireless sensor network. In this paper the performance of AODV protocol is judged on the basis of different layer's performance of network model like Application, MAC, Transport and physical layer in its association. Also it is contributing towards the assessment parameters such as average jitter, end to end delay, broadcasting, signalling and errors associated with temperature in a more particular way. This paper is presented to aid the researchers for their assessment towards the behaviour of AODV routing protocol. The simulation results show the assessment of AODV routing protocol under proposed real time Scenario
In this paper, a frontier-based technique is used with team of cooperating mobile robots to explore unknown environment. The aim is to decrease the exploration time. The exploration algorithm explicitly coordinates the robots. It tries to maximize overall utility by minimizing the potential of overlap in information gain amongst the robots. The proposed frontier-based exploration algorithm is based on a new bidding function in which a special parameter was introduced to decrease the overlap between the robots in addition to the utility and cost parameters. The special parameter depends on the future positions of the robots. The proposed algorithm has been tested with different environments. The new technique led to promising results.
