A Radar Sensing Algorithm by Gabor Theory

In this paper, an alternative Target Density Function( TDF) is proposed for narrowband radar model. This is achieved by estimating a new target density function by Gabor theory. It is shown how Gabor transform can be used to obtaining wideband target density function by transmitting a waveform which is a kernel for this transform. The windowing characteristics of this theory is plausible to reaching an accurate result. The presented wideband target density function is developed in a various manner different from the conventional methods

An Approach to Active Sensor Imaging

In this paper, an alternative Target Density Function (TDF) is proposed to image the radar targets in a dense target environment. It is obtained by considering a novel range and scanning angle plane different from the conventional methods. An alternative method is briefly proposed for smoothing the target density function by taking advantage of Walsh functions. Although the imaging is obtained via the phased array radars, the problem associated with beamforming in linear phased array radar system is bypassed in this new algorithm

Thrombosis with Behçet’s disease should be evaluated different conditions

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An Alternative Target Density Function for Radar Imaging

In this paper, an alternative Target Density Function (TDF) is proposed to image the radar targets in a dense target environment. It is produced by wavelet theory considering a new range and angle plane different from the conventional methods. It is shown that Wavelet theory can be used as approach to imaging by active sensors by transmitting a waveform which is a kernel for this transform such as a window function. Although the imaging is obtained via the phased array radars, the problem associated with beamforming in linear phased array radar system is bypassed in this new algorithm

On Local Activity and Edge of Chaos in a NaMLab Memristor

Local activity is the capability of a system to amplify infinitesimal fluctuations in energy. Complex phenomena, including the generation of action potentials in neuronal axon membranes, may never emerge in an open system unless some of its constitutive elements operate in a locally active regime. As a result, the recent discovery of solid-state volatile memory devices, which, biased through appropriate DC sources, may enter a local activity domain, and, most importantly, the associated stable yet excitable subdomain, referred to as edge of chaos, which is where the seed of complexity is actually planted, is of great appeal to the neuromorphic engineering community. This paper applies fundamentals from the theory of local activity to an accurate model of a niobium oxide volatile resistance switching memory to derive the conditions necessary to bias the device in the local activity regime. This allows to partition the entire design parameter space into three domains, where the threshold switch is locally passive (LP), locally active but unstable, and both locally active and stable, respectively. The final part of the article is devoted to point out the extent by which the response of the volatile memristor to quasistatic excitations may differ from its dynamics under DC stress. Reporting experimental measurements, which validate the theoretical predictions, this work clearly demonstrates how invaluable is non-linear system theory for the acquirement of a comprehensive picture of the dynamics of highly non-linear devices, which is an essential prerequisite for a conscious and systematic approach to the design of robust neuromorphic electronics. Given that, as recently proved, the potassium and sodium ion channels in biological axon membranes are locally active memristors, the physical realization of novel artificial neural networks, capable to reproduce the functionalities of the human brainmore closely than state-of-the-art purely CMOS hardware architectures, should not leave aside the adoption of resistance switching memories, which, under the appropriate provision of energy, are capable to amplify the small signal, such as the niobium dioxide micro-scale device fromNaMLab, chosen as object of theoretical and experimental study in this work

A linear programming-based method for job shop scheduling

We present a decomposition heuristic for a large class of job shop scheduling problems. This heuristic utilizes information from the linear programming formulation of the associated optimal timing problem to solve subproblems, can be used for any objective function whose associated optimal timing problem can be expressed as a linear program (LP), and is particularly effective for objectives that include a component that is a function of individual operation completion times. Using the proposed heuristic framework, we address job shop scheduling problems with a variety of objectives where intermediate holding costs need to be explicitly considered. In computational testing, we demonstrate the performance of our proposed solution approach

Characterisation and mechanical modelling of polyacrylonitrile-based nanocomposite membranes reinforced with silica nanoparticles

In this study, neat polyacrylonitrile (PAN) and fumed silica (FS)-doped PAN membranes (0.1, 0.5 and 1 wt% doped PAN/FS) are prepared using the phase inversion method and are characterised extensively. According to the Fourier Transform Infrared (FTIR) spectroscopy analysis, the addition of FS to the neat PAN membrane and the added amount changed the stresses in the membrane structure. The Scanning Electron Microscope (SEM) results show that the addition of FS increased the porosity of the membrane. The water content of all fabricated membranes varied between 50% and 88.8%, their porosity ranged between 62.1% and 90%, and the average pore size ranged between 20.1 and 21.8 nm. While the neat PAN membrane’s pure water flux is 299.8 L/m2 h, it increased by 26% with the addition of 0.5 wt% FS. Furthermore, thermal gravimetric analysis (TGA) and differential thermal analysis (DTA) techniques are used to investigate the membranes’ thermal properties. Finally, the mechanical characterisation of manufactured membranes is performed experimentally with tensile testing under dry and wet conditions. To be able to provide further explanation to the explored mechanics of the membranes, numerical methods, namely the finite element method and Mori–Tanaka mean-field homogenisation are performed. The mechanical characterisation results show that FS reinforcement increases the membrane rigidity and wet membranes exhibit more compliant behaviour compared to dry membranes

Opposing roles of the aldo-keto reductases AKR1B1 and AKR1B10 in colorectal cancer

Purpose: Aldo-keto reductases (including AKR1B1 and AKR1B10) constitute a family of oxidoreductases that have been implicated in the pathophysiology of diabetes and cancer, including colorectal cancer (CRC). Available data indicate that, despite their similarities in structure and enzymatic functions, their roles in CRC may be divergent. Here, we aimed to determine the expression and functional implications of AKR1B1 and AKR1B10 in CRC. Methods: AKR1B1 and AKR1B10 gene expression levels were analyzed using publicly available microarray data and ex vivo CRC-derived cDNA samples. Gene Set Enrichment Analysis (GSEA), The Cancer Genome Atlas (TCGA) RNA-seq data and The Cancer Proteome Atlas (TCPA) proteome data were analyzed to determine the effect of high and low AKR1B1 and AKR1B10 expression levels in CRC patients. Proliferation, cell cycle progression, cellular motility, adhesion and inflammation were determined in CRC-derived cell lines in which these genes were either exogenously overexpressed or silenced. Results: We found that the expression of AKR1B1 was unaltered, whereas that of AKR1B10 was decreased in primary CRCs. GSEA revealed that, while high AKR1B1 expression was associated with increased cell cycle progression, cellular motility and inflammation, high AKR1B10 expression was associated with a weak inflammatory phenotype. Functional studies carried out in CRC-derived cell lines confirmed these data. Microarray data analysis indicated that high expression levels of AKR1B1 and AKR1B10 were significantly associated with shorter and longer disease-free survival rates, respectively. A combined gene expression signature of AKR1B10 (low) and AKR1B1 (high) showed a better prognostic stratification of CRC patients independent of confounding factors. Conclusions: Despite their similarities, the expression levels and functions of AKR1B1 and AKR1B10 are highly divergent in CRC, and they may have prognostic implications. © 2017, International Society for Cellular Oncology