Motor Oil Classification Using Color Histograms and Pattern Recognition Techniques.

Motor oil classification is important for quality control and the identification of oil adulteration. In this work, we propose a simple, rapid, inexpensive and nondestructive approach based on image analysis and pattern recognition techniques for the classification of nine different types of motor oils according to their corresponding color histograms. For this, we applied color histogram in different color spaces such as red green blue (RGB), grayscale, and hue saturation intensity (HSI) in order to extract features that can help with the classification procedure. These color histograms and their combinations were used as input for model development and then were statistically evaluated by using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and support vector machine (SVM) techniques. Here, two common solutions for solving a multiclass classification problem were applied: (1) transformation to binary classification problem using a one-against-all (OAA) approach and (2) extension from binary classifiers to a single globally optimized multilabel classification model. In the OAA strategy, LDA, QDA, and SVM reached up to 97% in terms of accuracy, sensitivity, and specificity for both the training and test sets. In extension from binary case, despite good performances by the SVM classification model, QDA and LDA provided better results up to 92% for RGB-grayscale-HSI color histograms and up to 93% for the HSI color map, respectively. In order to reduce the numbers of independent variables for modeling, a principle component analysis algorithm was used. Our results suggest that the proposed method is promising for the identification and classification of different types of motor oils.

Motor oil classification based on time-resolved fluorescence.

A time-resolved fluorescence (TRF) technique is presented for classifying motor oils. The system is constructed with a third harmonic Nd:YAG laser, a spectrometer, and an intensified charge coupled device (ICCD) camera. Steady-state and time-resolved fluorescence (TRF) measurements are reported for several motor oils. It is found that steady-state fluorescence is insufficient to distinguish the motor oil samples. Then contour diagrams of TRF intensities (CDTRFIs) are acquired to serve as unique fingerprints to identify motor oils by using the distinct TRF of motor oils. CDTRFIs are preferable to steady-state fluorescence spectra for classifying different motor oils, making CDTRFIs a particularly choice for the development of fluorescence-based methods for the discrimination and characterization of motor oils. The two-dimensional fluorescence contour diagrams contain more information, not only the changing shapes of the LIF spectra but also the relative intensity. The results indicate that motor oils can be differentiated based on the new proposed method, which provides reliable methods for analyzing and classifying motor oils.

Prevalence of hypertension and pre-hypertension in rural women: a report from the villages of West Bengal, a state in the eastern part of India.

OBJECTIVE: To find out the prevalence of hypertension, pre-hypertension and tachycardia among the women in rural areas of West Bengal, identify co-factors associated with the prevalence and contribute to the body of evidence for future health programs to identify at-risk groups. DESIGN: A population-based cross-sectional study was conducted. SETTING: The study was conducted in remote villages. PARTICIPANTS: 1186 women participants, aged 18 years or more were included. MAIN OUTCOME MEASURES: They were interviewed using standard structured questionnaire. Blood pressure and tachycardia was monitored using digital sphygmomanometer. For each participant, we made two blood pressure measurements with an interval of 48 hours. Data was analysed statistically using SPSS software. RESULTS: Overall prevalence of hypertension in the study subjects was 24.7% and that of pre-hypertension and tachycardia was 40.8% and 6.4%, respectively. Both hypertension and pre-hypertension were seen to increase with age. Other identified significant factors were use of biomass fuel for cooking, absence of separate kitchen, higher body mass index (BMI), education and average family income. CONCLUSION: This study suggests quite high prevalence of hypertension as well as pre-hypertension among the women of rural areas. The findings are significant from the women health perspectives. Early detection of pre-hypertensive and hypertensive subjects will help to formulate intervention strategies to allay the spread of cardiovascular diseases.

Prediction of source rock origin by chemometric analysis of fourier transform infrared-attenuated total reflectance spectra of oil petroleum: evaluation of aliphatic and aromatic fractions by self-modeling mixture analysis.

This study describes a new methodology for the interpretation of Fourier transform infrared (FT-IR) attenuated total reflectance (ATR) spectra of Algerian, Brazilian, and Venezuelan crude oils. It is based on a comparative study between a chemometric treatment and the classical one, which refers to indices calculation. In fact, the combined use of FT-IR indices and principal component analysis (PCA) has led to the classification of the studied samples in terms of geographic distribution. Quantitative analysis has been successfully realized by the supervised method partial least squares (PLS), which has permitted the prediction of the locations of oils. We have also applied another mathematical processing method, simple-to-use interactive self-modeling mixture analysis (SIMPLISMA), to evaluate the aromatic and aliphatic composition of the oils by extracting pure spectra representative of the different fractions.