Microstrip stepped impedance resonator bandpass filter with an extended optimal rejection bandwidth

Bandpass filters with an optimal rejection bandwidth are designed using parallel-coupled stepped impedance resonators (SIRs). The fundamental (f/sub o/) and higher order resonant harmonics of an SIR are analyzed against the length ratio of the high-Z and low-Z segments. It is found that an optimal length ratio can be obtained for each high-Z to low-Z impedance ratio to maximize the upper rejection bandwidth. A tapped-line input/output structure is exploited to create two extra transmission zeros in the stopband. The singly loaded Q(Q/sub si/) of a tapped SIR is derived. With the aid of Q/sub si/, the two zeros can be independently tuned over a wide frequency range. When the positions of the two zeros are purposely located at the two leading higher order harmonics, the upper rejection band can be greatly extended. Chebyshev bandpass filters with spurious resonances up to 4.4f/sub o/, 6.5f/sub o/, and 8.2f/sub o/ are fabricated and measured to demonstrate the idea.     

Classification of audio radar signals using radial basis function neural networks

Radial basis function (RBF) neural networks are used to classify real-life audio radar signals that are collected by a ground surveillance radar mounted on a tank. Currently, a human operator is required to operate the radar system to discern among signals bouncing off tanks, vehicles, planes, and so on. The objective of this project is to investigate the possibility of using a neural network to perform this target recognition task, with the aim of reducing the number of personnel required in a tank. Different signal classification methods in the neural net literature are considered. The first method employs a linear autoregressive (AR) model to extract linear features of the audio data, and then perform classification on these features, i.e, the AR coefficients. AR coefficient estimations based on least squares and higher order statistics are considered in this study. The second approach uses nonlinear predictors to model the audio data and then classifies the signals according to the prediction errors. The real-life audio radar data set used here was collected by an AN/PPS-15 ground surveillance radar and consists of 13 different target classes, which include men marching, a man walking, airplanes, a man crawling, and boats, etc. It is found that each classification method has some classes which are difficult to classify. Overall, the AR feature extraction approach is most effective and has a correct classification rate of 88% for the training data and 67% for data not used for training.     

Mechanical spectroscopy in commercial Fe–6 wt.% Si alloys between 400 and 1000 K

Mechanical spectroscopy, neutron diffraction and differential scanning calorimetry (DSC) were performed on commercial Fe–6 wt.% Si alloy after quenching from high temperature. The damping spectrum shows a peak at around 800 K and an associated modulus defect. The modulus shows an increase during the second and subsequent heating runs. In addition, an anomaly in the modulus behavior has been found at around 400 K. Different thermal treatments allows to obtain two different recovery degrees of the quenched-in defects. The influence of the recovery degree on the 800 K internal friction peak and on the anelastic modulus has been evaluated and confirm the validity of the grain boundary mechanism associated to this peak. Experimental results are discussed on the basis of recovery and ordering processes.     

Wavelength-tunable 40-GHz picosecond harmonically mode-locked fiber laser source

We demonstrate a novel 40-GHz mode-locked fiber laser that utilizes a single active device to provide both gain and mode-locking. The laser produces pulses as short as 2.2 ps, is tunable over a 27-nm band centered at 1553 nm, and exhibits long-term stability without cavity-length feedback control. The pulse train at 1556 nm was used in a 40-Gb/s transmission experiment over 45 km with a low 0.4-dB power penalty.     

Anthocyanin composition of the red wine Babić affected by maceration treatment

Identification of anthocyanins in the wine made of the Croatian autochthonous grape variety of Babić (Vitis vinifera L.) was carried out and their profile was determined by means of high-performance liquid chromatography with diode array and mass spectrometric detection. Dependence of anthocyanins content and profile on maceration treatment conditions was investigated. Statistically significant differences of anthocyanins concentration in wines Babić produced by various maceration treatments were confirmed by the use of multivariate analysis of variances. The investigation results indicated that the maceration temperature exerts higher influence on anthocyanins concentration than the duration of maceration. In addition, on the basis of anthocyanin composition and using different multivariate statistical analyses, differentiation of wines Babić according to maceration treatments was procured.     

Modification of ASM3 for the determination of biomass adsorption/storage capacity in bulking sludge control.

The selector activated sludge (SAS) systems are known to prevent excessive growth of filamentous microorganisms responsible for bulking sludge, but these systems were hardly ever modelled. This study aimed to develop a model capable of predicting rapid substrate removal in the SAS systems. For this purpose, the Activated Sludge Model No. 3 (ASM3) was extended with three processes (adsorption, direct growth on the adsorbed substrate under aerobic or anoxic conditions). The modified ASM3 was tested against the results of batch experiments with the biomass originating from two full-scale SAS systems in Germany. The endogenous biomass was mixed with various readily biodegradable substrates (acetate, peptone, glucose and wastewater) and the utilisation of substrate (expresses as COD) and oxygen uptake rates (OURs) were measured during the experiments. In general, model predictions fitted to the experimental data, but a considerable number of kinetic (5) and stoichiometric (2) parameters needed to be adjusted during model calibration. The simulation results revealed that storage was generally a dominating process compared to direct growth in terms of the adsorbed substrate utilisation. The contribution of storage ranged from 65-71% (Plant A) and 69-92% (Plant B).     

Robust decoding of variable-length encoded Markov sources using a three-dimensional trellis

In this letter, we present an improved index-based a-posteriori probability (APP) decoding approach for the error-resilient transmission of packetized variable-length encoded Markov sources. The proposed algorithm is based on a novel two-dimensional (2D) state representation which leads to a three-dimensional trellis with unique state transitions. APP decoding on this trellis is realized by employing a 2D version of the BCJR algorithm where all available source statistics can be fully exploited in the source decoder. For an additional use of channel codes the proposed approach leads to an increased error-correction performance compared to a one-dimensional state representation.