We theoretically propose a method to achieve an optimum absorbing material through a modulus-near-zero (MNZ) metamaterial immersed in air or water with a change in slit width part. The destructive interference has paved the way to achieve perfect absorption (PA). Depending upon theoretical analysis, an acoustic metamaterial (AMMs) that supports resonance with a monopole (140 Hz) is developed to construct a low-frequency sound-absorbing technology. The dissipative loss effect can be by attentively controlling onto slit width to achieve perfect absorption. When there are thin slit width and visco-thermal losses in the structure, it is observed that they lead to high absorption. We use finite element simulations via COMSOL Multiphysics software to theoretical measurement in impedance tube and show the influence of structural parameters in both mediums. The results are of extraordinary correspondence at low frequency to achieve optimum perfect absorption (99%). That might support AMMs to actual engineering-related applications in the process of mitigating noise, slow sound trapping, notch filtering, energy conversion, and time reversal technology.

In order to keep the WWTP performance under control and to make decisions of minimizing the potential influence of wastewater components on the stable and proper WWTP operation, the devices for on-line control of oxygen uptake rate were designed and manufactured. The devices were used for three aims: controlling the presence of harmful substances for microorganisms in raw wastewater (Toximctcr), assessment of the real physiological condition of activated sludge in the aeration chamber (Activmcter), determining of the effects of activated sludge settling properties deterioration and its influence on the secondary clarificrs operation as well as microorganisms presence in treated wastewater (Sedimctcr). The results confirmed that the devices arc helpful for the WWTP operators as an early warning system and enable optimal decisions making.

The impact ionization in semiconductor materials is a process that produces multiple charge carrier pairs from a single excitation. This mechanism constitutes a possible road to increase the efficiency of the p-n and p-i-n solar cells junctions. Our study considers the structure of InN/InGaN quantum dot solar cell in the calculation. In this work, we study the effect of indium concentration and temperature on the coefficient of the material type parameter of the impact ionization process for a p(InGaN)-n(InGaN) and p(InGaN)- i(QDs-InN)-n(InGaN) solar cell. Next, we investigate the effect of perturbation such as temperature and indium composition on conventional solar cell’s (p(InGaN)-n(InGaN)) and solar cells of the third generation with quantum dot intermediate band IBSC (p(InGaN-i(QD-InN)-n(InGaN)) by analyzing their behaviour in terms of efficiency of energy conversion at the presence of the impact ionization process. Our numerical results show that the efficiency is strongly influenced by all of these parameters. It is also demonstrated that decreased with the increase of indium concentration and temperature which contributes to an overall improvement of the conversion efficiency.

In this paper, a new feature-extraction method is proposed to achieve robustness of speech recognition systems. This method combines the benefits of phase autocorrelation (PAC) with bark wavelet transform. PAC uses the angle to measure correlation instead of the traditional autocorrelation measure, whereas the bark wavelet transform is a special type of wavelet transform that is particularly designed for speech signals. The extracted features from this combined method are called phase autocorrelation bark wavelet transform (PACWT) features. The speech recognition performance of the PACWT features is evaluated and compared to the conventional feature extraction method mel frequency cepstrum coefficients (MFCC) using TI-Digits database under different types of noise and noise levels. This database has been divided into male and female data. The result shows that the word recognition rate using the PACWT features for noisy male data (white noise at 0 dB SNR) is 60%, whereas it is 41.35% for the MFCC features under identical conditions

We address one of the weaknesses of the RSA ciphering systems i.e. the existence of the private keys that are relatively easy to compromise by the attacker. The problem can be mitigated by the Internet services providers, but it requires some computational effort. We propose the proof of concept of the GPGPU-accelerated system that can help detect and eliminate users’ weak keys. We have proposed the algorithms and developed the GPU-optimised program code that is now publicly available and substantially outperforms the tested CPU processor. The source code of the OpenSSL library was adapted for GPGPU, and the resulting code can perform both on the GPU and CPU processors. Additionally, we present the solution how to map a triangular grid into the GPU rectangular grid – the basic dilemma in many problems that concern pair-wise analysis for the set of elements. Also, the comparison of two data caching methods on GPGPU leads to the interesting general conclusions. We present the results of the experiments of the performance analysis of the selected algorithms for the various RSA key length, configurations of GPU grid, and size of the tested key set.