Application of convolutional error correcting codes in ultrawideband M-ary PPM signaling

The interference issues related to ultrawideband (UWB) radio pose tight restrictions on the maximum data rate of UWB radio telecommunication systems. A possible solution is to reduce the required signal to interference ratio (SIR) that gives satisfactory performance to the UWB system. In this letter, we propose coded M-ary UWB radio communication systems. Two classes of convolutional codes, namely, low-rate superorthogonal codes and high-rate punctured codes are considered for this purpose. Simulation results on the bit error rate of the proposed system indicates that the system is capable to work in lower SIR's and therefore supports higher data transmission rates in a real interference environment compared to the previously proposed UWB communication systems.     

Convenient spatial profiling of pulsed laser beams

This paper describes a convenient method for spatial profiling of pulsed laser beams using the scanning knife-edge technique. This method is applied to a Nd:YAG laser and a chopped CO2 laser.     

Spread-space holographic CDMA technique: basic analysis andapplications

We analyze the basic principles of the spread-space holographic code division multiple access (CDMA) technique. We describe the structure of the encoder and decoder and present a basic mathematical analysis based on spatial harmonic decomposition for the receiver's processing module, which is comprised of a Fourier transform lens and a holographic matched filter. Subsequently, we study two applications of optical holographic CDMA, namely, free-space holographic CDMA photonic switch and free-space (wireless) multiaccess optical (infrared) indoor communications. For both techniques, we describe the two-dimensional imaging techniques, namely user's code transmission, and highlight the basic parameters and components that need to be optimized. To obtain the bit-error rate (BER) of the proposed application, we first evaluate the probability density function of multiuser interference and then evaluate the BER as a function of the processing gain, number of users, the received power, and the optimum threshold. For BER ≈ 10^-9, the result shows an extraordinary number of users that can be supported via holographic CDMA, for both applications     

Some computational considerations in eddy-current NDE

Theoretical calculations of eddy-current phenomena often involve the numerical evaluation of various integral expressions. A discussion of some of the possible evaluation methods and of the factors to be considered in choosing a method is presented.     

Chaotic dynamics of the vertical model in vehicles and chaos control of active suspension system via the fuzzy fast terminal sliding mode control

Journal of Mechanical Science and Technology - In this paper, the control of chaotic vibrations in vehicle suspension system is studied via a fuzzy fast terminal sliding mode method. Therefore, the...     

Shear behavior of soft-matrix composites reinforced with polyethylene loop-formed fibers

A soft material is defined as a substance that its mechanical properties depend on ambient conditions, e.g. external stresses, temperature, etc. Since composite structures with soft-material matrix do not have adequate pullout resistance with flat-type reinforcements such as fibers, there are a large number of cases where reinforcements with passive resistance are used in conjunction with ordinary fibers. Randomly distributed loop-formed fiber (RDLFF) is a novel idea to reinforce these types of composite materials. Therefore, the main aim of this paper is to use polyethylene RDLFF elements in soft-matrix composites. First, shear behavior of polyethylene RDLFF-reinforced composite was modeled with the use of force-equilibrium method, and then it was compared with that of flat-polyethylene fiber. In the next step, a set of laboratory direct shear tests was conducted on different samples including the neat treatment, polyethylene RDLFF and polyethylene fiber-reinforced composites. Thus, it was shown that through the shearing, a loop-formed fiber has two reinforcing effects including the “fiber effect” and the “loop effect”. The “loop effect” is the main advantage of using RDLFF to ordinary fibers at the same orientation and it is also the major difference in using the two kinds of fibers. The proposed model also indicated that the number of looped-form fibers, fiber diameter, coefficient of friction between fiber and matrix, loop dimension, tensile modulus of fiber, shearing zone and vertical compressive stress determine the shear resistance of RDLFF-reinforced composite. Therefore, the proposed model adequately predicts the shear behavior of soft-matrix composites reinforced with fibers and/or loop-formed fibers.     

A recursive framework for expression recognition: from web images to deep models to game dataset

In this paper, we propose a recursive framework to recognize facial expressions from images in real scenes. Unlike traditional approaches that typically focus on developing and refining algorithms for improving recognition performance on an existing dataset, we integrate three important components in a recursive manner: facial dataset generation, facial expression recognition model building, and interactive interfaces for testing and new data collection. To start with, we first create candid images for facial expression (CIFE) dataset. We then apply a convolutional neural network (CNN) to CIFE and build a CNN model for web image expression classification. In order to increase the expression recognition accuracy, we also fine-tune the CNN model and thus obtain a better CNN facial expression recognition model. Based on the fine-tuned CNN model, we design a facial expression game engine and collect a new and more balanced dataset, GaMo. The images of this dataset are collected from the different expressions our game users make when playing the game. Finally, we run yet another recursive step—a self-evaluation of the quality of the data labeling and propose a self-cleansing mechanism for improve the quality of the data. We evaluate the GaMo and CIFE datasets and show that our recursive framework can help build a better facial expression model for dealing with real scene facial expression tasks.     

Nonlinear Analysis and Attitude Control of a Gyrostat Satellite with Chaotic Dynamics Using Discrete‐Time LQR‐OGY

Quasi‐periodic and chaotic behavior, along with the control of chaos for a Gyrostat satellite (GS), is investigated in this work. The quaternion‐based dynamical model of the GS is first derived, and then the influences of the reaction wheels in the GS structure, under the gravity gradient perturbation that causes a route to chaos through quasi‐periodicity mechanism, is investigated. For the suppression of chaos in the system, a chaos control system with the quaternion feedback is designed for the GS based on the extension of the Ott‐Grebogi‐Yorke (OGY) method using the linearization of the Poincaré map. In the extended OGY controller, the Poincaré map is estimated using the Least Square Support Vector Machine (LSSVM) technique. After linearization of the Poincaré map, the Discrete‐time Linear Quadratic Regulator (DLQR) is applied on the linearized Poincaré map, making the DLQR‐OGY controller for chaos. The DLQR‐OGY control system stabilizes the orbits to the fixed points providing a small control input signal, which leads to a decrease in the control effort and energy consumption in the GS system.     

A hybrid fuzzy group decision support framework for advanced-technology prioritization at NASA

The prioritization of advanced-technology projects at the National Aeronautic and Space Administration (NASA) is a difficult task. This difficulty is due to the multiple and often conflicting objectives in addition to the inherent technical complexities and valuation uncertainties involved in the assessment process. As such, a systematic and transparent decision support framework is needed to guide the assessment process, shape the decision outcomes and enable confident choices to be made. Methods for solving Multi-Criteria Decision Making (MCDM) problems have been widely used to select a finite number of alternatives generally characterized by multiple conflicting criteria. However, applying these methods is becoming increasingly difficult for technology assessment in the space industry because there are many emerging risks for which information is not available and decisions are made under significant uncertainty. In this paper, we propose a hybrid fuzzy group decision support framework for technology assessment at NASA. The proposed objective framework is comprised of two modules. In the first module, the complicated structure of the assessment criteria and alternatives are represented and evaluated with the Analytic Network Process (ANP). In the second module, the alternative advanced-technology projects are ranked using a customized fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). We demonstrate the applicability of the proposed framework through a case study at the Kennedy Space Center.