Cutting tool tracking and recognition based on infrared and visual imaging systems using principal component analysis (PCA) and discrete wavelet transform (DWT) combined with neural networks

The implementation of computerised condition monitoring systems for the detection cutting tools’ correct installation and fault diagnosis is of a high importance in modern manufacturing industries. The primary function of a condition monitoring system is to check the existence of the tool before starting any machining process and ensure its health during operation. The aim of this study is to assess the detection of the existence of the tool in the spindle and its health (i.e. normal or broken) using infrared and vision systems as a non-contact methodology. The application of Principal Component Analysis (PCA) and Discrete Wavelet Transform (DWT) combined with neural networks are investigated using both types of data in order to establish an effective and reliable novel software program for tool tracking and health recognition. Infrared and visual cameras are used to locate and track the cutting tool during the machining process using a suitable analysis and image processing algorithms. The capabilities of PCA and Discrete Wavelet Transform (DWT) combined with neural networks are investigated in recognising the tool’s condition by comparing the characteristics of the tool to those of known conditions in the training set. The experimental results have shown high performance when using the infrared data in comparison to visual images for the selected image and signal processing algorithms

A review on the latest advances in extraction and analysis of artemisinin

Introduction: Artemisinin (1), a well-known natural antimalarial drug, is a sesquiterpene lactone that contains a unique peroxide bridge. Since its discovery, the amount of research into the analysis of artemisinin has increased considerably, and it has been further intensified since the Noble Prize win by Tu Youyou in the year 2015 for the discovery of artemisinin. Objective: To review published literature on the extraction and analysis of artemisinin, published during 2017-present, and to present an appraisal of those methods. Methodology: Extensive literature search was carried out which involved, but not limited to, the use of, various databases, like Web of Knowledge, PubMed and Google Scholar, and relevant published materials including published books. The keywords used, in various combinations, with artemisinin being present in all combinations, in the search were artemisinin, Artemisia annua, analysis, extraction, quantitative, qualitative and quality control. Results: During the period covered in this review, there are several methods of analysis of artemisinin have been reported, the most of which were LC-based methods. However, the use of new methods like near infrared analysis, fluorometirc analysis and molecular imprinting, and a significant increase in the use of computational tools have been observed. Mainly several methods involving supercritical fluid extraction and ultrasound-assisted extraction of artemisinin have dominated the extraction area. Conclusions: Newer analytical tools, as well as improved protocols for the known analytical tools, for qualitative and quantitative determination of artemisinin (1), have been made available by various researchers during the period covered by this review. Supercritical fluid extraction and ultrasound-assisted extraction are still the methods of choice for extraction of artemisinin

Stability Constraints on Classical de Sitter Vacua

We present further no-go theorems for classical de Sitter vacua in Type II string theory, i.e., de Sitter constructions that do not invoke non-perturbative effects or explicit supersymmetry breaking localized sources. By analyzing the stability of the 4D potential arising from compactification on manfiolds with curvature, fluxes, and orientifold planes, we found that additional ingredients, beyond the minimal ones presented so far, are necessary to avoid the presence of unstable modes. We enumerate the minimal setups for (meta)stable de Sitter vacua to arise in this context.Comment: 18 pages; v2: argument improved, references adde

Large Deviations for Stochastic Nematic Liquid Crystals driven by Multiplicative Gaussian Noise

We study a stochastic two-dimensional nematic liquid crystal model with multiplicative Gaussian noise. We prove the Wentzell-Freidlin type large deviations principle for the small noise asymptotic of solutions using weak convergence metho

Time-Course Analysis of Cyanobacterium Transcriptome: Detecting Oscillatory Genes

The microarray technique allows the simultaneous measurements of the expression levels of thousands of mRNAs. By mining these data one can identify the dynamics of the gene expression time series. The detection of genes that are periodically expressed is an important step that allows us to study the regulatory mechanisms associated with the circadian cycle. The problem of finding periodicity in biological time series poses many challenges. Such challenge occurs due to the fact that the observed time series usually exhibit non-idealities, such as noise, short length, outliers and unevenly sampled time points. Consequently, the method for finding periodicity should preferably be robust against such anomalies in the data. In this paper, we propose a general and robust procedure for identifying genes with a periodic signature at a given significance level. This identification method is based on autoregressive models and the information theory. By using simulated data we show that the suggested method is capable of identifying rhythmic profiles even in the presence of noise and when the number of data points is small. By recourse of our analysis, we uncover the circadian rhythmic patterns underlying the gene expression profiles from Cyanobacterium Synechocystis

Five-Year Follow-Up of Parapapillary Atrophy: The Beijing Eye Study

Purpose: To assess longitudinal changes in parapapillary atrophy in the adult population of Greater Beijing. Methods: The population-based Beijing Eye Study 2006 included 3251 subjects who had participated in the Beijing Eye Study 2001 and returned for re-examination. The mean age was 60.4610.1 years. Using optic disc photographs, we measured parapapillary atrophy which was divided into alpha zone and beta zone. Results: Overall progression rate of alpha zone was seen in 0.660.1 % (95 % confidence interval (CI):0.3,0.9) of the subjects and of beta zone in 8.260.5 % (95%CI:7.2,9.1) of the subjects. In binary regression analysis, rate of progression of alpha zone was significantly associated higher age (P = 0.04) and the co-progression of zone Beta (P,0.001). Rate of progression of beta zone was significantly associated with higher age (P,0.001; odds ratio (OR):1.11;95%CI:1.10,1.14), higher intraocular pressure (P,0.001;OR:1.10;95%CI:1.05,1.14), higher myopic refractive error (P,0.001;OR:0.71; 95%CI:0.67,0.75), rural region of habitation (P = 0.002;OR: 0.58; 95%CI:0.41,0.82), presence of glaucomatous optic nerve damage (P,0.001;OR:2.89; 95%CI:1.62,5.14), co-progression of alpha zone (P,0.001;OR:7.13;95%CI:2.43,20.9), absence of arterial hypertension (P = 0.03;OR: 0.70; 95%CI:0.51,0.96), and thicker central corneal thickness (P = 0.02;OR:1.01;95%CI:1.00,1.01). Subjects with a non-glaucomatous optic nerve damage (n = 22) as compared to the remaining subjects did not vary in the progression rate of alpha zone (0.0 % versus 0.660.1%; P = 1.0) and beta zone (8.260.5 % versus 6.360.6%;P = 1.0)