Evolutionary design of dynamic neural networks for evaporator control

This paper presents a novel neural network (NN) to control an ammonia refrigerant evaporator. Inspired by the latest findings on the biological neuron, a dynamic synaptic unit (DSU) is proposed to enhance the information processing capacity of artificial neurons. Treating the dynamic synaptic activity after the nonlinear somatic activity helps to capture the dynamics demarcated by the Gaussian activation pertaining to the input space. This practice leads to a remarkable reduction in curse of dimensionality. The proposed NN architecture has been compared with two other conventional architectures; one with dynamic neural units (DNUs) and the other with nonlinear static functions as perceptrons. The objective is to control evaporator heat flow rate and secondary fluid outlet temperature while keeping the degree of refrigerant superheat in the range 4–7 K at the evaporator outlet by manipulating refrigerant and evaporator secondary fluid flow rates. The drawbacks of conventional approaches to this problem are discussed, and how the novel method can overcome them are presented. An evolutionary approach is adopted to optimize the parameters of the NN controllers. Then evaporator process model is accomplished as a combination of governing equations and a sub NN resulting in a simple and sufficiently accurate model. The effectiveness of the proposed dynamic NN controller for the evaporator system model is validated using experimental data from the ammonia refrigeration plant.     

Pixel design of pulsed CMOS image sensor for retinal prosthesis with digital photosensitivity control

A newly designed pulse frequency modulation photosensor for use in retinal prosthesis is proposed and demonstrated. The pixel converts the intensity of incident light into biphasic current pulses at frequencies suitable for the electrical stimulation of retinal neurons. Experimental results showed that the device was sensitive over a dynamic range of input light of about 120 dB, and that photosensitivity could be varied from 0 dB to around -40 dB.     

Excessive closure of the right eye: a new sign of infarction in the territory of the ipsilateral right middle cerebral artery

In right middle cerebral territory infarction a new sign, excessive closure of the right eye ipsilateral to the lesion and mild closure of the left eye on command, was noted. The excessive ipsilateral eye closure was not observed on spontaneous eye closure.     

Hybrid negative example selection using visual and conceptual features

An application of Query-By-Example (QBE) is presented where shots that are visually similar to provided example shots are retrieved. To implement QBE, counter-example shots are required to accurately distinguish shots that are relevant to the query from those that are not (Li and Snoek (2009), Yu et al. (2004)). However, there are usually a huge number of shots, not relevant to a particular query, which can serve as counter-example shots. It is difficult for a user to provide counter-example shots that would aid retrieval. Thus, we developed a QBE method based on partially supervised learning where a retrieval model is constructed by selecting counter-example shots from shots without user supervision. To ensure the speed and accuracy of the QBE method, we select a small number of counter-example shots that are visually similar to given example shots but irrelevant to the query. Such shots are useful for characterizing the boundary between relevant and irrelevant shots. For our method, we first filter shots that are visually dissimilar to example shots based on SVMs on a visual feature. Then we filter shots relevant to the query based on concept detection results from pre-constructed classifiers. Shots that pass the above two tests are considered as counter-example shots. Experimental results obtained using TRECVID 2009 video data validate the effectiveness of our method.     

LC GRIN lens mode with wide viewing angle for rotatable 2D/3D tablet

To widen the vertical and horizontal angular ranges where the lens performs well, the off‐axis performance of a liquid crystal gradient index (LC GRIN) lens is analyzed by the combined simulation system of an LC director simulator and a ray‐tracing simulator. We found that the angular difference between an LC alignment direction and an electrode array direction of the LC GRIN lens is one of significant parameters, and detailed conditions of structure are established. The measurement result shows that the developed structure reduces the degradation ratio in a luminance profile from 61% to 3.2%. We have applied a user tracking system for the rotatable 3D display, equipped with a detection of a panel orientation and a face position. As a result, we have developed a rotatable 2D/3D tablet whose 3D viewing azimuth angle is over 30° in both landscape and portrait orientations.     

Sintering Kinetics at Isothermal Shrinkage: II, Effect of Y2O3 Concentration on the Initial Sintering Stage of Fine Zirconia Powder

The shrinkage behavior of fine zirconia powders containing 2.9 and 7.8 mol% Y₂O₃ was investigated to clarify the effect of Y₂O₃ concentration on the initial sintering stage. The shrinkage of powder compact was measured under both conditions of constant rates of heating (CRH) and constant temperatures. CRH measurements revealed that when the Y₂O₃ concentration of fine zirconia powder increased, the starting temperature of shrinkage shifted to a high temperature. Isothermal shrinkage measurements revealed that the increase in Y₂O₃ concentration causes the shrinkage rate to decrease. The values of activation energy ( Q ) and frequency-factor term (β₀) of diffusion at initial sintering were estimated by applying the sintering-rate equation to the isothermal shrinkage data. When the Y₂O₃ concentration increases, both Q and β₀ of diffusion increase. It is, therefore, concluded that the increase in Y₂O₃ concentration of fine zirconia powder decreases the shrinkage rate because of increasing Q of diffusion at the initial stage of sintering.     

Scale free interval graphs

Scale free graphs have attracted attention by their non-uniform structure that can be used as a model for various social and physical networks. In this paper, we propose a natural and simple random model for generating scale free interval graphs. The model generates a set of intervals randomly under a certain distribution, which defines a random interval graph. The main advantage of the model is its simpleness. The structure/properties of generated graphs are analyzable by relatively simple probabilistic and/or combinatorial arguments, which is different from many other models. Based on such arguments, we show for our random interval graph that its degree distribution follows a power law, and that it has a large average clustering coefficient.