Energy efficiency optimization of one-way and two-way DF relaying considering circuit power

In this paper, the energy efficiency (EE) of a decode and forward (DF) relay system is studied, where two sources communicate through a half-duplex relay node in one-way and two-way relaying strategies. Both the circuitry power and the transmission power of all nodes are taken into consideration. In addition, three different coding schemes for two-way DF relaying strategy with two phases and two-way DF relaying with three phases are considered. The aim is to maximize the EE of the system for a constant spectral efficiency (SE). For this purpose, the transmission time and the transmission power of each node are optimized. Simulations are used to compare the EE–SE curve of different DF strategies with one-way and two-way amplify and forward (AF) strategies and direct transmission (DT), to find the best energy efficient strategy in different SE conditions. Analytical and simulation results demonstrate that in low SE conditions, DF relaying strategies are more energy efficient compared to that of AF strategies and DT. However, in high SE conditions, the EE of two-way AF relaying and DT strategy outperform some of the DF relaying strategies. In simulations, the impact of different circuitry power and different channel conditions on the EE–SE curves are also investigated.     

Content‐Based Image Retrieval Based on Relevance Feedback and Reinforcement Learning for Medical Images

To enable a relevance feedback paradigm to evolve itself by users’ feedback, a reinforcement learning method is proposed. The feature space of the medical images is partitioned into positive and negative hypercubes by the system. Each hypercube constitutes an individual in a genetic algorithm infrastructure. The rules take recombination and mutation operators to make new rules for better exploring the feature space. The effectiveness of the rules is checked by a scoring method by which the ineffective rules will be omitted gradually and the effective ones survive. Our experiments on a set of 10,004 images from the IRMA database show that the proposed approach can better describe the semantic content of images for image retrieval with respect to other existing approaches in the literature.     

Fluid Flow and Mixing in Non-Isothermal Water Model of Continuous Casting Tundish

Fluid flow and mixing of molten steel in a twin-slab-strand continuous casting tundish were investigated using a mixing model under non-isothermal conditions.This model led to a set of ordinary differential equations that were solved with a Runge-Kutta algorithm.Steady state water modeling was carried out under non-isothermal conditions.Experimental data obtained from the water model were used to calibrate the mixing model.Owing to the presence of a mixed convection in the non-isothermal conditions,a channelizing flow would be created in the fluid inside the tundish.A mixing model was designed that was capable of predicting RTD（residence time distribution）curves for different cases in non-isothermal conditions.The relationship between RTD parameters and the Tu（tundish Richardson number）was obtained for various cases under non-isothermal conditions.The results show that the RTD parameters were completely different under isothermal and non-isothermal conditions.The comparison of the RTD curves between the isothermal and non-isothermal conditions presents that the extent of mixing in the tundish in non-isothermal conditions is lower than the mixing extent in isothermal conditions.     

A cross‐cultural comparison of colour emotion for two‐colour combinations

Psychophysical experiments were conducted in the UK, Taiwan, France, Germany, Spain, Sweden, Argentina, and Iran to assess colour emotion for two‐colour combinations using semantic scales warm/cool, heavy/light, active/passive, and like/dislike. A total of 223 observers participated, each presented with 190 colour pairs as the stimuli, shown individually on a cathode ray tube display. The results show consistent responses across cultures only for warm/cool, heavy/light, and active/passive. The like/dislike scale, however, showed some differences between the observer groups, in particular between the Argentinian responses and those obtained from the other observers. Factor analysis reveals that the Argentinian observers preferred passive colour pairs to active ones more than the other observers. In addition to the cultural difference in like/dislike, the experimental results show some effects of gender, professional background (design vs. nondesign), and age. Female observers were found to prefer colour pairs with high‐lightness or low‐chroma values more than their male counterparts. Observers with a design background liked low‐chroma colour pairs or those containing colours of similar hue more than nondesign observers. Older observers liked colour pairs with high‐lightness or high‐chroma values more than young observers did. Based on the findings, a two‐level theory of colour emotion is proposed, in which warm/cool, heavy/light, and active/passive are identified as the reactive‐level responses and like/dislike the reflective‐level response. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2012     

Fast evolving neuro-fuzzy model and its application in online classification and time series prediction

A strategy for improving speed of the previously proposed evolving neuro-fuzzy model (ENFM) is presented in this paper to make it more appropriate for online applications. By considering a recursive extension of Gath?CGeva clustering, the ENFM takes advantage of elliptical clusters for defining validity region of its neurons which leads to better modeling with less number of neurons. But this necessitates the computing of reverse and determinant of the covariance matrices which are time consuming in online applications with large number of input variables. In this paper a strategy for recursive estimation of singular value decomposition components of covariance matrices is proposed which converts the burdensome computations to calculating reverse and determinant of a diagonal matrix while keeping the advantages of elliptical clusters. The proposed method is applied to online detection of epileptic seizures in addition to prediction of Mackey?CGlass time series and modeling a time varying heat exchanger. Simulation results show that required time for training and test of fast ENFM is far less than its basic model. Moreover its modeling ability is similar to the ENFM which is superior to other online modeling approaches.     

A quantitative approach to study solid state phase coarsening in solder alloys using combined phase-field modeling and experimental observation

In the present work, a quantitative phase-field approach is introduced to study the phase-coarsening phenomena in solder alloys, Pb-Sn alloy here. The most important part of this work is to introduce a simple and versatile approach to quantify the experimental and simulation data, without putting into difficulties corresponding to the stochastic nature of phenomenon, in order to compute unknown physical data required to perform numerical simulation. For this purpose, at first, the evolution of microstructure vs. time is studied experimentally by the conventional optical microscopy. Then, unknown physical data, the interface mobility here, is computed by fitting the time evolution of the total interface perimeter of the simulation results to that of the experimental data. In fact, by this approach, the physical data is computed such that it will be applied to predict reality in the subsequent simulations, i.e., the presented method can be accounted as the calibration of the corresponding mathematical model and numerical method. The validity of the presented approach is supported by comparing simulation data to experimental ones.     

The use of simulation in discrete-event dynamic systems design

The use of simulation as a tool to design complex stochastic systems is often inhibited by cost. We present a procedure for estimating a value for the controllable input parameter which generates a desirable output. Since the output has to be matched by varying the input parameter, an iterative method of solution is applied. The proposed solution algorithm is based on Newton's method using a single-run simulation approach to estimate the needed derivative. The major contribution of this paper is to provide a framework for arriving at a target value for product, process and service attributes through Monte Carlo experiments. The effectiveness of the proposed procedure is demonstrated by determining a desirable service rate in a queueing system with known analytical solution.     

Evolutionary boundary constraint handling scheme

The performance of an optimization tool is largely determined by the efficiency of the search algorithms used in the process as well as the proper handling of complex constraints. From the implementation point of view, an important part of task ensuring an efficient algorithm to work to its best capability is to handle the boundary constraints properly and effectively. As most studies in the literature have focused on the development of algorithms and performance evaluation and comparison of optimization algorithms, this crucial step has not been explored very well, and consequently only limited studies have been carried out in this field. This paper intends to propose a simple and yet efficient evolutionary scheme for handling boundary constraints. The simplicity of this approach means that the proposed scheme is very easy to implement and thus can be suitable for many applications. We demonstrate this approach with an efficient algorithm, differential evolution, and we also compare it with other boundary constraint handling approaches for a wide set of benchmark problems. Based on statistical parameters and especially mean values, the results obtained by the evolutionary scheme are better than the best known solutions obtained by the existing methods.     

Voice controlled wheelchairs: Fine control by humming

People without disabilities seamlessly control devices with their hands. Interestingly, their hands can perform coarse and fine control. Implementing smooth control for computerized systems is not straightforward and most of the time it is not intuitive either. Here we offer a solution to that problem: smooth control through humming. Voice commands have become ubiquitous in modern technology. Speech-to-text applications abound. Smooth control, on the other hand, has not been tackled yet. Here we design and implement a humming control technique, and demonstrate a hardware implementation with a powered wheelchair. Once actuated, the speed with which the chair moves will depend on the subtle variation on the fundamental frequency of the user's humming, acquired through an accelerometer measuring vocal cord vibration. We also discuss two signal processing techniques that handle commonly encountered issues when trying to resolve frequencies in real time data. The hardware implementation shows performance of 80% and higher in speech recognition for signal-to-noise ratio (SNR) higher than 8 dB and 100% in smooth control and frequency detection for all tested SNRs. We also discuss potential applications of smooth humming control to other assistive technology.