53 resultados para algorithm design and analysis

em Deakin Research Online - Australia


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The objective of this research is to model and analyze candidate hull configurations for a low-cost, modular, autonomous underwater robot. As the computational power and speed of microprocessors continue to progress, we are seeing a growth in the research, development, and the utilization of underwater robots. The number of applications is broadening in the R&D and science communities, especially in the area of multiple, collaborative robots. These underwater collaborative robots represent an instantiation of a System of Systems (SoS). While each new researcher explores a unique application, control method, etc. a new underwater robot vehicle is designed, developed, and deployed. This sometimes leads to one-off designs that are costly. One limit to the wide-scale utilization of underwater robotics is the cost of development. Another limit is the ability to modify the configuration for new applications and evolving requirements. Consequently, we are exploring autonomous underwater vehicle (AUV) hull designs towards the goal of modularity, vehicle dexterity, and minimizing the cost. In our analysis, we have employed 3D solid modeling tools and finite element methods. In this paper we present our initial results and discuss ongoing work.

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In this paper, we introduce a single-walled boron nitride nanotube (SWBNNT)-based cantilever biosensor, and investigate its bending deformation. The BNNT-based cantilever is modelled by accounting that the surface of the cantilever beam is coated with the antibody molecule. We have considered two main approaches for the mechanical deformation of the BNNT beam. The first one is differential surface stress produced by the binding of biomolecules onto its surface, and the second one is the charge released from the biomolecular interaction. In addition, other parameters including length of beam, variation of beam’s location and chiralities of the BNNT have been taken into consideration to design the cantilever biosensor. The computed results are in good agreement with the well known electrostatic equations that govern the deformation of the cantilever.

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This paper presents design and simulation investigation of a fuzzy controller and a conventional PID controller for a servo system. First, a servo system is considered and its stability is discussed. Then, a PID controller that is tuned by the Ziegler-Nichols method is formulated for controlling the servo system. To improve the servo system's dynamic response parameters, a fuzzy controller is then proposed for controlling the system. A performance comparison between the fuzzy and the PID controllers are carried out. The results are presented and discussed.

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This paper describes a multilayer localized surface plasmon resonance (LSPR) graphene biosensor that includes a layer of graphene sheet on top of the gold layer, and the use of different coupled configuration of a laser beam. The study also investigates the enhancement of the sensitivity and detection accuracy of the biosensor through monitoring biomolecular interactions of biotin-streptavidin with the graphene layer on the gold thin film. Additionally, the role of thin films of gold, silver, copper and aluminum in the performance of the biosensor is separately investigated for monitoring the binding of streptavidin to the biotin groups. The performance of the LSPR graphene biosensor is theoretically and numerically assessed in terms of sensitivity, adsorption efficiency, and detection accuracy under varying conditions, including the thickness of biomolecule layer, number of graphene layers and operating wavelength. Enhanced sensitivity and improved adsorption efficiency are obtained for the LSPR graphene biosensor in comparison with its conventional counterpart; however, detection accuracy under the same resonance condition is reduced by 5.2% with a single graphene sheet. This reduction in detection accuracy (signal to noise ratio) can be compensated for by introducing an additional layer of silica doped B2O3 (sdB2O3) placed under the graphene layer. The role of prism configuration, prism angle and the interface medium (air and water) is also analyzed and it is found that the LSPR graphene biosensor has better sensitivity with triangular prism, higher prism angle, lower operating wavelength and larger number of graphene layers. The approach involves a plot of a reflectivity curve as a function of the incidence angle. The outcomes of this investigation highlight the ideal functioning condition corresponding to the best design parameters.

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Designed a multilayer SPR biosensor to improve the detection sensitivity and accuracy simultaneously. Developed a design procedure to identify optimum design parameters for SPR biosensing. Devised a new detection measurement technique based on S-parameters for SPR biosensing.

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This paper presents design and simulation of a circular meander dipole antenna at the industrial, scientific, and medical band of 915 MHz for energy scavenging in a passive head-mountable deep brain stimulation device. The interaction of the proposed antenna with a rat body is modeled and discussed. In the antenna, the radiating layer is meandered, and a FR-4 substrate is used to limit the radius and height of the antenna to 14 mm and 1.60 mm, respectively. The resonance frequency of the designed antenna is 915 MHz and the bandwidth of 15 MHz at a return loss of -10 dB in free space. To model the interaction of the antenna with a rat body, two aspects including functional and biological are considered. The functional aspect includes input impedance, resonance frequency, gain pattern, radiation efficiency of the antenna, and the biological aspect involves electric field distribution, and SAR value. A complete rat model is used in the finite difference time domain based EM simulation software XFdtd. The simulated results demonstrate that the specific absorption rate distributions occur within the skull in the rat model, and their values are higher than the standard regulated values for the antenna receiving power of 1W.

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This paper presents an analysis of optimum rectifier circuits for wireless energy harvesting in deep brain stimulation (DBS) devices. Since DBS demands compact and low power consumption devices, small, high conversion efficient, and high output voltage rectifiers need to be developed. The investigation that is presented in this paper is analytical and simulated based. Analysis on a variety of circuit configurations brings more evidence to improve the performance of rectifiers. Analytical parameters influencing the output DC voltage and the efficiency of the rectifiers are described. The operating frequency of the 915 MHz industrial, scientific and medical (ISM) radio band is used in this study. The maximum conversion efficiency of the LC matched half wave rectifier, the Greinacher voltage doubler, the Delon doubler, and the 2-stage voltage multiplier is obtained as 56.34%, 74.45%, 71.48%, and 31.44%, respectively, at the 30 dBm input power level. The corresponding maximum output DC voltages are 6.27 V, 16.83 V, 13.36 V, and 9.20 V. Thus the Greinacher voltage doubler is deemed as the best configuration according to the conversion efficiency and the output voltage measurements.

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This paper presents an Electrowetting-on-Dielectric (EWOD) device with optimized insulating layers operated by low actuation voltage. The device consists of an electrode array on a silicon substrate, covered by a dielectric layer and a hydrophobic layer. To characterize the performance of the device, simulations are performed for the dielectric layer of Sio2 and the hydrophobic layer of Sio2, Su-8 and Parylene C at different voltages. The volume finite difference approach of the Coventorware software was used to carry out the simulations. Two different molar of di-ionized water droplet were considered in the simulations. It was observed that the device having the Sio2 dielectric layer and the Parylene C hydrophobic layer moved the 1M KCL (potassium chloride) droplet at the actuation voltage of 25V.

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The purpose of this study is to design a low-cost planar Archimedean dipole antenna for batteryless transcranial direct current stimulation devices. The antenna parameters including resonance frequency, radiation efficiency, radiation pattern, and gain are simulated using finite difference time domain based electromagnetic simulation software XFdtd. The proposed antenna is simulated with low-cost FR4 PCB substrate of thickness of 1.6 mm. The antenna is designed with half wavelength of resonant frequency and fed with a matching line. The target frequency band is the industrial, scientific and medical (ISM) band of 915 MHz which is in the simulated band width of 31 MHz (903-934MHz). Moreover, since the bio-effect of specific absorption rate by radio frequency electromagnetic wave for power harvesting is an important concern, we try to find out the safety limit. Thus a quantitative analysis of distributions of electric field and power absorption in anatomical human head model by the far field radio frequency energy received by our designed antenna has been presented.

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Today’s power system network has become more complex and it has more responsibilities and challenges to provide secure, reliable and quality energysupply to the communities. A small entity of electrical network known as Microgrid (MG) is more popular nowadays to enhance reliablity and secure level of energy supply, in case of any energy crisis in the utility network. The MG can also provide clean energy supply by integrating renewable energy sources effectively. TheMG with small scale solar photovoltaic (PV) power system is more suitable to provide reliable and clean energy supply for remote or urban communities in residential level. This paper presents the basic analysis study of stand-alone solar photovoltaic (PV) MG power system which has been developed with the aid of Matlab - Simulink software, on the basis of residential load profile and solar exposure level in a particular area of Geelong, Victoria State. The simulation result depicts the control behavior of MG power system with optimum sizing of PV (4.385 kW)and battery storage (480Ah/48V) facility, fulfills daily energy needs in residential load level. This study provides a good platform to develop an effective and reliable stand-alone MG power system for the remote communities in the near future.

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Mesoporous silica nanoparticles (MSNs) are exceptionally promising drug carriers for controlled drug delivery systems because their morphology, pore structure, pore volume and pore size can be well tailored to obtain certain drug release profiles. Moreover, they possess the ability to specifically transport and deliver anti-cancer drugs when targeting molecules are properly grafted onto their surface. MSNs based drug delivery systems have the potential to revolutionize cancer therapy. This review provides a comprehensive overview of the fabrication, modification of MSNs and their applications in tumour-targeted delivery. In addition, the characterization and analysis of MSNs with computer aided strategies were described. The existing issues and future prospective concerning the applications of MSNs as drug carriers for controlled drug delivery systems were discussed.

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In this paper, an interactive genetic algorithm (IGA) approach is developed to optimize design variables for a monolithic microwave integrated circuit (MMIC) low noise amplifier. A layered encoding structure is employed to the problem representation in genetic algorithm to allow human intervention in the circuit design variable tuning process. The MMIC amplifier design is synthesized using the Agilent Advance Design System (ADS), and the IGA is proposed to tune the design variables in order to meet multiple constraints and objectives such as noise figure, current and simulated power gain. The developed IGA is compared with other optimization techniques from ADS. The results showed that the IGA performs better in achieving most of the involved objectives.

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The challenge of comparing two or more genomes that have undergone recombination and substantial amounts of segmental loss and gain has recently been addressed for small numbers of genomes. However, datasets of hundreds of genomes are now common and their sizes will only increase in the future. Multiple sequence alignment of hundreds of genomes remains an intractable problem due to quadratic increases in compute time and memory footprint. To date, most alignment algorithms are designed for commodity clusters without parallelism. Hence, we propose the design of a multiple sequence alignment algorithm on massively parallel, distributed memory supercomputers to enable research into comparative genomics on large data sets. Following the methodology of the sequential progressiveMauve algorithm, we design data structures including sequences and sorted k-mer lists on the IBM Blue Gene/P supercomputer (BG/P). Preliminary results show that we can reduce the memory footprint so that we can potentially align over 250 bacterial genomes on a single BG/P compute node. We verify our results on a dataset of E.coli, Shigella and S.pneumoniae genomes. Our implementation returns results matching those of the original algorithm but in 1/2 the time and with 1/4 the memory footprint for scaffold building. In this study, we have laid the basis for multiple sequence alignment of large-scale datasets on a massively parallel, distributed memory supercomputer, thus enabling comparison of hundreds instead of a few genome sequences within reasonable time.

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We present improved algorithms for automatic fade and dissolve detection in digital video analysis. We devise new two-step algorithms for fade and dissolve detection and introduce a method for eliminating false positives from a list of detected candidate transitions. In our detailed study of these gradual shot transitions, our objective has been to accurately classify the type of transitions (fade-in, fade-out, and dissolve) and to precisely locate the boundary of the transitions. This distinguishes our work from early work in scene change detection which focuses on identifying the existence of a transition rather than its precise temporal extent. We evaluate our algorithms against two other commonly used methods on a comprehensive data set, and demonstrate the improved performance due to our enhancements.