Graceful Object-Based Performance Evolution

Object-based design and development are thought to facilitate graceful evolution of functionality, and thus enhance the reusability of software components. They can also facilitate graceful performance evolution. The performance of a layered object-based component can be made tunable to meet changing needs by permitting clients to ‘plug in’ appropriate implementations for its constituent components through generic parameters. If the components and their constituents are carefully designed, then performance tuning is possible without direct modification to the internal details of the participating components, thus significantly lowering the cost for performance evolution. The contribution of this paper is to software practice. It explains how software engineers can build performance-tunable components using C++ templates. It includes empirical results confirming that tuning produces expected performance improvements with minimal code change. The results are especially significant because they are scalable to arbitrarily large and heavily layered software components and subsystems. © 1997 by John Wiley & Sons, Ltd.     

DEVELOPMENTAL GENETIC ANALYSIS FOR CRUDE FIBER CONTENT AND CRUDE ASH CONTENT OF RAPESEED MEAL IN TWO DIFFERENT GROWING YEARS

ABSTRACT

Developmental genetic analyses method for diploid seed quantitative traits was used to determine the unconditional and conditional genetic main effects and genotype × environment interaction effects from embryo, cytoplasm and maternal genetic systems on crude fiber content (CFC) and crude ash content (CAC) of rapeseed meal in two growing years. The results suggested that the performance at most developmental times/stages for CFC and CAC was mainly affected by the genetic main effects. By using the conditional analysis method, for the different genetic systems, CFC and CAC were simultaneously controlled by the genetic effects from three genetic systems, especially for the maternal main effects. Also, the additive effects were more prominent at most developmental times/stages, and the improvement of both traits could be expected in earlier generation(s) in rapeseed breeding programs. The heritability analysis revealed that the maternal heritability was more prominent during seed development times, especially at maturity. Thus, it suggested that maternal plant selection could be utilized to reduce CFC and increase CAC in rapeseed meal breeding programs. The study further suggested Youcai 601 could be used for reducing CFC, while Huashuang 3 and Zhongyou 821 were suitable for increasing CAC in rapeseed, as evidenced from their predicted parent effects.

PRACTICAL APPLICATIONS

Rapeseed is an industrially and commercially important oilseed crop. For the oilseed industry, the meal remaining after oil extraction represents a product of a value equal to that of the oil itself. It represents a very valuable protein component of feed mixes that are, in turn, indispensable in modern monogastric animals raising for intensive production of meat, eggs and milk. In certain cases, the oilmeal is further processed to produce concentrates (with 50–60% of crude protein) or isolates (nearly pure protein) for use in human food. Rapeseed flours, protein concentrates and isolates are lower in protein but higher in crude fiber and ash contents than corresponding soybean products. Also, rapeseed or canola meal has been used as fermentation substrate, as an additive in compost for commercial button mushroom (Agaricus bisporus) production and also as substrate for xylanase production by Trichoderma reesei. Oilmeals are mainly valued for low fiber content, high protein content of good quality and absence or low presence of toxic and antinutritional compounds. One drawback of rapeseed meal is its higher crude fiber content, which results in lower digestible energy, especially for non‐ruminants. Decreasing the crude fiber and improving the crude ash (an indicator of the mineral content) could increase the demand for rapeseed meal as a feed source for livestock.

     

A new design for digital adaptive filters

The design and operation of a digital adaptive filter based on a modified Widrow-Hoff algorithm is described. It uses LSI components as main elements. This filter realization converges faster than other realizations reported hitherto because its weight vector is updated at every sampling instant.     

Effect of different carbon fillers and dopant acids on electrical properties of polyaniline nanocomposites

Electrically conducting nanocomposites of polyaniline (PANI) with carbon-based fillers have evinced considerable interest for various applications such as rechargeable batteries, microelectronics, sensors, electrochromic displays and light-emitting and photovoltaic devices. The nature of both the carbon filler and the dopant acid can significantly influence the conductivity of these nanocomposites. This paper describes the effects of carbon fillers like carbon black (CB), graphite (GR) and muti-walled carbon nanotubes (MWCNT) and of dopant acids like methane sulfonic acid (MSA), camphor sulfonic acid (CSA), hydrochloric acid (HCl) and sulfuric acid (H₂SO₄) on the electrical conductivity of PANI. The morphological, structural and electrical properties of neat PANI and carbon–PANI nanocomposites were studied using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT–IR), UV–Vis spectroscopy and the four-point probe technique, respectively. Thermogravimetric analysis (TGA) and X-ray diffraction (XRD) studies were also conducted for different PANI composites. The results show that PANI and carbon–PANI composites with organic acid dopants show good thermal stability and higher electrical conductivity than those with inorganic acid dopants. Also, carbon–PANI composites generally show higher electrical conductivity than neat PANI, with highest conductivities for PANI–CNT composites. Thus, in essence, PANI–CNT composites prepared using organic acid dopants are most suitable for conducting applications.     

A modified LMS algorithm for fast processing — analysis and realization

Fast convergence and simplicity of the real-time implementation of the adaptive filter algorithm are desirable in several applications. In this paper, a fast modified least mean square (LMS) algorithm is presented and analysed. The performance of the LMS and the modified LMS algorithm is compared with the help of both simulation and experimental results. Once the algorithms reach the track period (i.e. steady-state conditions), their performance is found to be essentially the same. The tracking performance of the modified algorithm is better as it operates twice as fast as the LMS algorithm.     

A class of modified adaptive recursive filter algorithms

A new class or adaptive infinite impulse response ( IIR) or recursive filter algorithms is obtained by incorporating a simple modification in the correction vectors of some existing algorithms. The resulting class of algorithms explores the inherent parallelism present in their coefficient update equations, and hence the possibility of faster initial convergence. Two IIR filter algorithms are considered for discussion and simulation.     

Performance investigation of artificial intelligence based controller for three phase four leg shunt active filter

In this paper, the choice of power quality compensator is a DSTATCOM which constitutes a three phase four leg voltage source converter (VSC) with a DC capacitor. The control strategy proposed for the DSTATCOM is a neural network based one cycle control (OCC). This control strategy involves neural network block, digital circuits and linear elements, which eliminates the sensors required for sensing the load current and coupling inductor current in addition to the multiplier employed in the conventional method. The calculation of harmonic and reactive currents for the reference current generation is also eliminated, thus minimizing the complexity in the control strategy. The control strategy mitigates harmonic/reactive currents, ensures balanced and sinusoidal source current from the supply mains that are nearly in phase with the supply voltage, compensates neutral current, and maintains voltage across the capacitor under unbalanced source and load conditions. The performance of the DSTATCOM with the proposed artificial neural network (ANN) controllers is validated and investigated through simulations using Matlab software. The simulation results prove the efficacy of the proposed neural network based control strategy under varying source and load conditions.