Optimization of waste quail eggshells as biocomposites for polyaniline in ammonia gas detection

A simple, cost-effective, and novel chemical sensor for ammonia (NH₃) gas detection was developed from polyaniline (PANI)/quail eggshell (QES) composites. QES is a natural waste enriched in calcium carbonate. In this work, pure PANI was synthesized from chemical oxidation method and PANI/QES composites were prepared from physical mixing of QES with the synthesized PANI at different mass ratio. A series of complementary techniques including Fourier transform infrared and ultraviolet-visible spectrometers, scanning electron microscope with energy dispersive detection coupled with mapping, thermogravimetric analysis, and X-ray diffractometer were used to characterize the physicochemical and textural properties of the biocomposites. From the results, PANI/QES composite with a mass ratio of 1 exhibited the lowest NH₃ detection limit of 5.24 ppm with a linear correlation coefficient (R²) of close to unity (0.9932) between the signal and NH₃ gas concentration. As a whole, the PANI/QES biocomposites synthesized from this work exhibited excellent selectivity toward NH₃ gas even in the presence of other gas impurities, such as acetone, ethanol, and hexane. For the sensor reusability, the PANI/QES biocomposites can be reused in the application of NH₃ gas detection for at least 4 cycles.     

On-line emission and economic load dispatch using adaptive Hopfield neural network

This paper presents an adaptive Hopfield neural network (AHNN) based methodology, where the slope of the activation function is adjusted, for finding approximate Pareto solutions for the multi-objective optimization problem of emission and economic load dispatch (EELD). We have placed emphasis on finding solutions quickly, rather than the global Pareto solutions, so that our algorithm can be employed in large on-line power systems where variations in load are quite frequent. To enable faster convergence, adaptive learning rates have been developed by using energy function and applied to the slope adjustment method. The proposed algorithm has been tested on selected IEEE bus benchmark systems. The convergence of AHNN is found to be nearly 50% faster than the non-adaptive version.     

Multidimensional vector radix FHT algorithms

In this paper, efficient multidimensional (M-D) vector radix (VR) decimation-in-frequency and decimation-in-time fast Hartley transform (FHT) algorithms are derived for computing the discrete Hartley transform (DHT) of any dimension using an appropriate index mapping and the Kronecker product. The proposed algorithms are more effective and highly suitable for hardware and software implementations compared to all existing M-D FHT algorithms that are derived for the computation of the DHT of any dimension. The butterflies of the proposed algorithms are based on simple closed-form expressions that allow easy implementations of these algorithms for any dimension. In addition, the proposed algorithms possess properties such as high regularity, simplicity and in-place computation that are highly desirable for software and hardware implementations, especially for the M-D applications. A close relationship between the M-D VR complex-valued fast Fourier transform algorithms and the proposed M-D VR FHT algorithms is established. This type of relationship is of great significance for software and hardware implementations of the algorithms, since it is shown that because of this relationship and the fact that the DHT is an alternative to the discrete Fourier transform (DFT) for real data, a single module with a little or no modification can be used to carry out the forward and inverse M-D DFTs for real- or complex-valued data and M-D DHTs. Thus, the same module (with a little or no modification) can be used to cover all domains of applications that involve the DFTs or DHTs.     

Comments, with reply, on `Passive equalization of semiconductordiode laser frequency modulation' by S.B. Alexander et al

Some flaws in a recent article by S.B. Alexander et al. (ibid., vol.7, no.1, p.11-23, Jan. 1989) on the theory of equalization of FM response of a laser diode using passive filters are noted. An error has occurred as a result of assuming a constant C as a positive instead of negative. When C is negative and large, the equalization network cannot be realized with passive networks. Also the simulated time waveform shown in the article for the optical frequency of an equalized laser does not show some spikes which are expected theoretically. The spikes occur as a result of an imperfect equalization provided by the proposed passive filters that were realized assuming C as positive. In replying the original author feels that the comments and observations result simply from attempting to extend the simple FM transfer-function model far beyond its limits while trying to introduce unnecessary theoretical rigor     

Biodegradation and corrosion behavior of manganese oxidizer Bacillus cereus ACE4 in diesel transporting pipeline

The degradation problem of petroleum products arises since hydrocarbon acts as an excellent food source for a wide variety of microorganisms. Microbial activity leads to unacceptable level of turbidity, corrosion of pipeline and souring of stored product. The present study emphasizes the role of Bacillus cereus ACE4 on degradation of diesel and its influence on corrosion of API 5LX steel. A demonstrating bacterial strain ACE4 was isolated from corrosion products and 16S rRNA gene sequence analysis showed that it has more than 99% similarity with B. cereus. The biodegradation and corrosion studies revealed that B. cereus degraded the aliphatic protons and aromatic protons in diesel and is capable of oxidizing ferrous/manganese into oxides. This is the first report that discloses the involvement of manganese oxidizer B. cereus ACE4 on biodegradation of diesel and its influence on corrosion in a tropical country pipeline.     

On the VLSI implementation of real-time order statistic filters

Real-time implementation of an order-statistic filter (OSF) or ranked order filter requires the computation of the order statistic (ranked order) of the samples in a window which gets periodically updated with the arrival of a new sample(s). The authors give an algorithm for the computation of the running order statistic. A highly parallel architecture suitable for VLSI implementation is presented. The architecture is very versatile, with programmable window size and rank order. An expansion algorithm and its VLSI architecture, which permit the usage of two r-bit OSFs to implement an (r+1)-bit OSF, where r is the resolution of the input signal samples, are given. In a special case where one is satisfied with at most one LSB error, the hardware complexity of the proposed architecture can be reduced by almost one half. It is further shown how a VLSI chip incorporating the proposed architecture can be used as the basic building block in the real-time implementation of other forms of nonlinear filters