Constructing artificial images of facial expressions

This paper presents a method for construction of artificial images of facial expressions. The proposed fractal-based synthesis procedure called pixel-based correspondence works on 2D images and does not require any depth information. This method can generate artificial images of an object when only a single image is given. Using the proposed method, effective example-based facial analysis systems can be trained and utilised in various applications.<br /

Power-cycle-library-based control strategy for plug-in hybrid electric vehicles

It has been demonstrated that considering the knowledge of drive cycle as a priori in the PHEV control strategy can improve its performance. The concept of power cycle instead of drive cycle is introduced to consider the effect of noise factors in the prediction of future drivetrain power demand. To minimize the effect of noise factors, a practical solution for developing a power-cycle library is introduced. A control strategy is developed using the predicted power cycle which inherently improves the optimal operation of engine and consequently improves the vehicle performance. Since the control strategy is formed exclusively for each PHEV rather than a preset strategy which is designed by OEM, the effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered for each PHEV. Simulation results show that the control strategy based on the driver library of power cycle would improve both vehicle performance and battery health.<br /

Automatic extraction of abnormal regions from lung images

A system that could automatically extract abnormal lung regions may assist expert radiologists in verifying lung tissue abnormalities. This paper presents an automated lung nodule detection system consisting of five components: acquisition, pre-processing, background removal, detection, and false positives reduction. The system employs a combination of an ensemble classification and clustering methods. The performance of the developed system is compared against some existing counterparts. Based 011 the experimental results, the proposed system achieved a sensitivity of 100% and a false-positives/slice of 0.67 for 30 tested CT images.<br /

Identification of nonlinear systems using hybrid functions

Most real systems have nonlinear behavior and thus model linearization may not produce an accurate representation of them. This paper presents a method based on hybrid functions to identify the parameters of nonlinear real systems. A hybrid function is a combination of two groups of orthogonal functions: piecewise orthogonal functions (e.g. Block-Pulse) and continuous orthogonal functions (e.g. Legendre polynomials). These functions are completed with an operational matrix of integration and a product matrix. Therefore, it is possible to convert nonlinear differential and integration equations into algebraic equations. After mathematical manipulation, the unknown linear and nonlinear parameters are identified. As an example, a mechanical system with single degree of freedom is simulated using the proposed method and the results are compared against those of an existing approach.<br /

A resonance tunable and durable LSPR nano-particle sensor : AL2O3 capped silver nano-disks

Localized surface plasmon resonance (LSPR) biosensors are employed to detect target biomolecules which have particular resonance wavelengths. Accordingly, tunability of the LSPR wavelength is essential in designing LSPR devices. LSPR devices employing silver nano-particles present better efficiencies than those using other noble metals such as gold; however, silver nano-particles are easily oxidized when they come in contact with liquids, which is inevitable in biosensing applications. To attain both durability and tunabilty in a LSPR biosensor, this paper proposes alumina (AL2O3) capped silver nano-disks. It is shown that through controlling the thickness of the cap, the LSPR resonance frequency can be finely tuned over a wide range; and moreover, the cap protects silver nano-particles from oxidation and high temperature.<br /

Optical microsensor for counting food substance particles in lab-on-a-chips

Integrated optical detection is considered to be an important operation in lab-on-a-chips. This paper presents an optical fiber-based micro-sensor that is capable of detecting food substance particles in a lab-on-a-chip. The system consists of a microcontroller and associated circuitry, a laser emitter, a laser receiver, fiber optic cables, a microfluidics chip, and the food substance samples to be tested. When the particles flow through the microfluidic channel in the chip, the receiver&rsquo;s output voltage varies due to the particles blocking the passage of the laser ray. The changes in the collected signals are analyzed to count the number of particles. Experiments are conducted on several food substance samples including talcum powder, ground ginger, and soy sauce. The experimental results are presented and discussed

Developing lspr design guidelines

Applications of localized surface plasmon resonance (LSPR) such as surface enhanced Raman scattering (SERS) devices, biosensors, and nano-optics are growing. Investigating and understanding of the parameters that affect the LSPR spectrum is important for the design and fabrication of LSPR devices. This paper studies different parameters, including geometrical structures and light attributes, which affect the LSPR spectrum properties such as plasmon wavelength and enhancement factor. The paper also proposes a number of rules that should be considered in the design and fabrication of LSPR device

Modeling and control of flatness in cold rolling mill using fuzzy petri nets

Today, having a good flatness control in steel industry is essential to ensure an overall product quality, productivity and successful processing. Flatness error, given as difference between measured strip flatness and target curve, can be minimized by modifying roll gap with various control functions. In most practical systems, knowing the definition of the model in order to have an acceptable control is essential. In this paper, a fuzzy Petri net method for modeling and control of flatness in cold rolling mill is developed. The method combines the concepts of Petri net and fuzzy control theories. It focuses on the fuzzy decision making problems of the fuzzy rule tree structures. The method is able to detect and recover possible errors that can occur in the fuzzy rule of the knowledge-based system. The method is implemented and simulated. The results show that its error is less than that of a PI conventional controller.<br /

A random forest for lung nodule identification

A method is presented for identification of lung nodules. It includes three stages: image acquisition, background removal, and nodule detection. The first stage improves image quality. The second stage extracts long lobe regions. The third stage detects lung nodules. The method is based on the random forest learner. Training set contains nodule, non-nodule, and false-positive patterns. Test set contains randomly selected images. The developed method is compared against the support vector machine. True-positives of 100% and 85.9%, and false-positives of 1.27 and 1.33 per image were achieved by the developed method and the support vector machine, respectively.<br /

Design and simulation of a RF MEMS shunt switch for Ka and V bands and the impact of varying its geometrical parameters

RF MEMS plays an important role in microwave switching. The high performance of RF MEMS shunt such as high bandwidth, low insertion loss, and high isolation have made these switches well suitable for high performing microwave and millimeter wave circuits. This paper presents a RF MEMS shunt capacitive switch for Ka and V band application. This paper investigates the effect of various geometrical parameters on RF characteristics of the switch. The simulation results are presented and discussed.<br /