5th Iranian Biennial Chemometrics Seminar, 25-26 Nov 2015 Department of Chemistry, Faculty of Science , University of Tehran, Tehran, Iran
Development of New Interfaces for Performing Chemometric Methods in Portable Instruments and Smartphones Hamidreza Shaye, Hadi Parastar* Chemometrics Research Lab., Department of Chemistry, Sharif University of Technology, Tehran, Iran E-mail address:
[email protected] Abstract In the present contribution, a novel Java library entitled “MVC” is developed to perform different multivariate calibration methods. The developed library can implement in any Java-supported device as an environment for running. Different multivariate calibration methods, such as multiple linear regression (MLR), principal component regression (PCR) and partial least squares (PLS) are included in this library. Special versions of application were developed for Android and Linux operating systems (OS) based on MVC library. Android version named “MVC App” is capable to run in any smartphone and tablet based on Android OS (Version 4.0 and higher). Also, Linux versions specially designed to execute in Linux based portable platforms, such as Raspberry Pi and other ARM architecture based devices supported Java included in most of the portable analytical instruments (UV-Vis, NIR and Raman). These interfaces are designed for chemists who are not expert in programming or in advanced statistics.
Key words: Multivariate calibration; MLR; PCR; PLS; Android; Linux
Introduction Owing to the fact that analytical chemistry can involve samples that are far from simple and often contain many components, therefore, multivariate calibration (MVC) methods have been proposed in recent decades to overcome fundamental mathematical challenges occurred during analysis of these complex mixtures [1]. Among different MVC algorithms, multiple linear regression (MLR) [2], principal component regression (PCR) [2] and partial least squares regression (PLSR) [3] has attracted great attention in chemistry in recent years. However, one the most important features of chemometric methods is development of user-friendly software in order to develop the range of users of these methods. In this regard, development of software for chemists who are not expert in programming or in advanced statistics will be an important mission for chemometricians. The aim of this work was development of new interfaces (app) to perform different types of chemometric methods including multivariate calibration ones. These interfaces are based on Java language programming and it can be run on any hardware supported Java, such as Android, Linux and other ARM architecture based devices supported Java. On the other side, these types of apps can be coupled to portable instruments which are highly useful for in situ and field studies. In these cases, data can be collected with instruments and then, data can be transmitted to a smartphone or any supported device through a Wi-Fi or USB connection and finally, they can be easily manipulated and processed with no extra effort. Developed apps in this study include different MVC methods, such as MLR, PCR and PLSR. Also, several important tools for data preprocessing (e.g., mean-centring and auto-scaling), rank 5th Iranian Biennial Chemometrics Seminar,University of Tehran
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5th Iranian Biennial Chemometrics Seminar, 25-26 Nov 2015 Department of Chemistry, Faculty of Science , University of Tehran, Tehran, Iran
determination and model evaluation (e.g., Cross-Validation (CV) [4]) and also for android version plotting and sharing facilities are included. Running MVC app does not require a serious experience; however, a basic knowledge of the underlying methods is helpful to successfully interpret the results.
Results and Discussion As an instance, for performing PLS modelling on Android based smartphones, first calibration and validation data sets are imported (via USB or Wi-Fi). Then, the number of latent variables (LVs) is chosen using leave-one-out crossvalidation (LOO-CV). Afterwards, PLS model is built and the user can review the modelling results. In this regard, figures of merit (FOMs) of models, such as root-mean square error of prediction (RMSEP), standard error of prediction (SEP), bias and relative error (RE) and other parameters can be viewed for each analyte. Furthermore, various plotting options are included for each model. In this manner, there are two options: (1) showing data as a table which it is possible to scroll display horizontally and/or vertically to scan all matrix data and (2) showing data as a plot. In this way, horizontal scrolling in bottom-one-third of screen will change across the rows of data matrix and tapping the screen by three fingers will share current plot as JPEG-picture. Also, there is an option to share logs’ file by smartphone via Bluetooth, message, Email and other supported methods depends on user’s device. All of these options are available just by touching the screen, with no complexity that almost every chemist can use. Figure 1 shows some of the pages of the developed interface for smartphones.
References [1] Beebe K.R. and Kowalski B.R., An introduction to multivariate calibration and analysis. Anal. Chem., 1987: 59:1007A-1017A. [2] Brereton R.G., Chemometrics: data analysis for the laboratory and chemical plant. 2003: John Wiley & Sons, NY, USA. [3] Wold S., Sjöström M., and Eriksson L., PLS-regression: a basic tool of chemometrics. Chemom. Intell. Lab. Syst., 2001: 58:109-130. [4] Kohavi R., A study of cross-validation and bootstrap for accuracy estimation and model selection. Int. Joint Conf. Artif. Intell., 1995, 14, 1137– 1145.
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