Optimal tradeoffs for addition on systolic arrays

The complexity of adding twon-bit numbers on a two-dimensional systolic array is investigated. We consider different constraints on the systolic array, including:

whether or not the input and output ports lie on the periphery of the array,

constraints placed on the arrival and departure times of inputs and outputs

. For all combinations of the above constraints, we obtain optimal tradeoffs among the resources of area, pipeline delay, and worst-case time. It turns out that there is a subtle interplay among the constraints and some of our results seem counterintuitive. For instance, we show that allowing more-significant bits to arrive earlier than less-significant bits can speed up addition by a factor of logn. We also show that multiplexing can often result in a smaller array. On the other hand, we show that some known results, such as Chazelle and Monier's bounds for arrays that have input/output ports on the perimeter, also hold in less constrained models.     

Dielectric properties of synthetic quartz crystals

The dielectric constant (K) and loss (tan), and hence the conductivity), of high-quality synthetic quartz crystals have been measured with the electric field parallel (or perpendicular) to the optical axis (c-axis). These measurements are carried out in the frequency region 102 to 10⁷ Hz and in the temperature range 30 to 400° C. Values ofK at 30° C areE c 4.58 andE c 4.36, and these are frequency independent; tan), values are quite low,E c having larger values at 10² Hz compared toE c. The temperature variation ofK at different frequencies exhibits two regions: (i) a slow increase up to about 280° C which is frequency independent, and (ii) a fast increase beyond 280° C which is frequency dependent,K having larger values at lower frequencies; similar behaviour is exhibited by tan. Log), against 1/T plots show the usual extrinsic and intrinsic regions. The values for activation energy for conduction in the intrinsic region are calculated to be 0.85 and 1.0 eV, respectively, forE c andE c. An attempt is made to understand these results.     

Functional modelling,validation and testing of analog to digital converters (ADC) from system design perspective

In this paper a methodology to develop PSpice (SPICE) model for flash type analog to digital converters and its validation is presented. With the onset of the Internet of Things and ongoing digitization of electronic devices around us, almost every device needs an interface or controlling unit as a digital computing device. As more and more products perform calculations in the digital or discrete time domain, more sophisticated data converters must translate the digital data to and from our inherent analog world. This varied nature of interfaces necessitates simulation of ADC along with a functional simulation of the system to optimize the performance of design and improve reliability. The paper focuses on the development of a functional model for ADC which can expedite system development. The design philosophy was at the block level and the development was conducted for commercially available ADC, AD7828. The complete model has been simulated using PSpice and results were compared with laboratory test measurements using AD7828.     

Identification of cancerous gene groups from microarray data by employing adaptive genetic and support vector machine technique

Nowadays, microarray gene expression data plays a vital role in tumor classification. However, due to the accessibility of a limited number of tissues compared to large number of genes in genomic data, various existing methods have failed to identify a small subset of discriminative genes. To overcome this limitation, in this paper, we developed a new hybrid technique for gene selection, called ensemble multipopulation adaptive genetic algorithm (EMPAGA) that can overlook the irrelevant genes and classify cancer accurately. The proposed hybrid gene selection algorithm comprises of two phase. In the first phase, an ensemble gene selection (EGS) method used to filter the noisy and redundant genes in high-dimensional datasets by combining multilayer and F-score approaches. Then, an adaptive genetic algorithm based on multipopulation strategy with support vector machine and naïve Bayes (NB) classifiers as a fitness function is applied for gene selection to select the extremely sensible genes from the reduced datasets. The performance of the proposed method is estimated on 10 microarray datasets of numerous tumor. The comprehensive results and various comparisons disclose that EGS has a remarkable impact on the efficacy of the adaptive genetic algorithm with multipopulation strategy and enhance the capability of the proposed approach in terms of convergence rate and solution quality. The experiments results demonstrate the superiority of the proposed method when compared to other standard wrappers regarding classification accuracy and optimal number of genes.     

Pattern identification of different human joints for different human walking styles using inertial measurement unit (IMU) sensor

Artificial Intelligence Review - A bipedal walking robot is a kind of humanoid robot. It is suppose to mimics human behavior and designed to perform human specific tasks. Currently, humanoid robots...     

A feature selection method using improved regularized linear discriminant analysis

Investigation of genes, using data analysis and computer-based methods, has gained widespread attention in solving human cancer classification problem. DNA microarray gene expression datasets are readily utilized for this purpose. In this paper, we propose a feature selection method using improved regularized linear discriminant analysis technique to select important genes, crucial for human cancer classification problem. The experiment is conducted on several DNA microarray gene expression datasets and promising results are obtained when compared with several other existing feature selection methods.     

Effect of ambient‐temperature and high‐temperature electron‐beam radiation on the structural,thermal, mechanical,and dynamic mechanical properties of injection‐molded polyamide‐6,6

Electron‐beam irradiation of injection‐molded specimens of polyiminohexamethyleneiminoadipoyl (better known as polyamide‐6,6) was carried out in air at ambient temperature (303 K) and a high temperature (393 K). Most of the irradiated specimens were tensile dumbbells, although a few were cylinders for compressive stress relaxation testing. A few representative samples were dipped in triallyl cyanurate (TAC) solution before ambient‐temperature irradiation. The gel content of the specimens increased with radiation dose and the temperature of irradiation. Moreover, the TAC‐treated specimens showed an increase in gel content over the neat specimens irradiated at the same dose levels. Wide‐angle X‐ray scattering and differential scanning calorimetry studies revealed that the crystallinity decreased with increasing radiation dose. Irradiation at the high temperature and treatment with TAC further decreased the crystallinity compared to irradiation at ambient temperature. As determined from compressive stress relaxation and mechanical and dynamic mechanical properties, the optimized radiation dose for ambient‐temperature radiation was 200 kGy. The gels had a stiffening effect, and the rate of relaxation decreased significantly. The water‐uptake characteristics of the tensile specimens were investigated; this revealed a decrease in the water absorption tendency with increasing gel content. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 99: 1633–1644, 2006     

Combining CNN streams of dynamic image and depth data for action recognition

RGB-D sensors have been in great demand due to its capability of producing large amount of multimodal data like RGB images and depth maps, useful for bette