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  • Open Access


    Application of Wavelength Selection Combined with DS Algorithm for Model Transfer between NIR Instruments

    Honghong Wang1, Zhixin Xiong1,*, Yunchao Hu1, Zhijian Liu1, Long Liang2

    Journal of Renewable Materials, Vol.11, No.6, pp. 2713-2727, 2023, DOI:10.32604/jrm.2023.025817

    Abstract This study aims to realize the sharing of near-infrared analysis models of lignin and holocellulose content in pulp wood on two different batches of spectrometers and proposes a combined algorithm of SPA-DS, MCUVE-DS and SiPLS-DS. The Successive Projection Algorithm (SPA), the Monte-Carlo of Uninformative Variable Elimination (MCUVE) and the Synergy Interval Partial Least Squares (SiPLS) algorithms are respectively used to reduce the adverse effects of redundant information in the transmission process of the full spectrum DS algorithm model. These three algorithms can improve model transfer accuracy and efficiency and reduce the manpower and material consumption required for modeling. These results… More >

  • Open Access


    Infrared Spectroscopy-Based Chemometric Analysis for Lard Differentiation in Meat Samples

    Muhammad Aadil Siddiqui1,*, M. H. Md Khir1, Zaka Ullah2, Muath Al Hasan2, Abdul Saboor3, Saeed Ahmed Magsi1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2859-2871, 2023, DOI:10.32604/cmc.2023.034164

    Abstract One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness. The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary, for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis. Fourier Transform Infrared Spectroscopy (FTIR) is used in this work to identify lard adulteration in cow, lamb, and chicken samples. A simplified extraction method was implied to obtain the lipids from pure and adulterated meat. Adulterated samples were obtained by mixing lard with chicken, lamb, and… More >

  • Open Access


    Functional Nonparametric Predictions in Food Industry Using Near-Infrared Spectroscopy Measurement

    Ibrahim M. Almanjahie1,2,*, Omar Fetitah3, Mohammed Kadi Attouch3, Tawfik Benchikh3,4

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6307-6319, 2023, DOI:10.32604/cmc.2023.033441

    Abstract Functional statistics is a new technique for dealing with data that can be viewed as curves or images. Parallel to this approach, the Near-Infrared Reflectance (NIR) spectroscopy methodology has been used in modern chemistry as a rapid, low-cost, and exact means of assessing an object’s chemical properties. In this research, we investigate the quality of corn and cookie dough by analyzing the spectroscopic technique using certain cutting-edge statistical models. By analyzing spectral data and applying functional models to it, we could predict the chemical components of corn and cookie dough. Kernel Functional Classical Estimation (KFCE), Kernel Functional Quantile Estimation (KFQE),… More >

  • Open Access


    Process Characterization of the Transesterification of Rapeseed Oil to Biodiesel Using Design of Experiments and Infrared Spectroscopy

    Tobias Drieschner1,2,*, Andreas Kandelbauer1, Bernd Hitzmann2, Karsten Rebner1

    Journal of Renewable Materials, Vol.11, No.4, pp. 1643-1660, 2023, DOI:10.32604/jrm.2023.024429

    Abstract For optimization of production processes and product quality, often knowledge of the factors influencing the process outcome is compulsory. Thus, process analytical technology (PAT) that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality. The present study aims at characterizing a well-known industrial process, the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters (FAME) for usage as biodiesel in a continuous micro reactor set-up. To this end, a… More >

  • Open Access


    Physical and Mechanical Properties of Catalpa bungei Clones and Estimation of the Properties by Near-Infrared Spectroscopy

    Rui Wang, Lanlan Shi, Yurong Wang*

    Journal of Renewable Materials, Vol.10, No.12, pp. 3285-3302, 2022, DOI:10.32604/jrm.2022.020546

    Abstract Air-dry density, modulus of rupture (MOR), modulus of elasticity (MOE), compressive strength parallel to grain, and hardness of Catalpa bungei clones were investigated in this study with feasibility of predicting these properties by near-infrared (NIR) spectroscopy. The best candidate ‘Luoqiu 3’ has been selected from three clones based on wood physical and mechanical property indices. Lower values of wood physical and mechanical properties have been found in the corewood compared to the outerwood. There were significant positive correlations between the air-dry density and mechanical properties. Information from cross section for air-dry density, compressive strength parallel to grain, and hardness yielded… More >

  • Open Access


    Soil Urea Analysis Using Mid-Infrared Spectroscopy and Machine Learning

    J. Haritha1,*, R. S. Valarmathi2, M. Kalamani3

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1867-1880, 2022, DOI:10.32604/iasc.2022.022547

    Abstract Urea is the most common fertilizer used by the farmers. In this study, the variation of mid-infrared transmittance spectra with addition of urea in soil was studied for five different concentrations of urea. 150 gm of soil is taken and dried in a hot air oven for 5 h at 80°C and then samples are prepared by adding urea and water to it. The spectral signature of soil with urea is obtained by using an Infrared Spectrometer that reads the spectra in the mid infra-red region. The analysis is done using Partial Least Square Regression and Support Vector Machine algorithms… More >

  • Open Access


    Cluster Analysis for IR and NIR Spectroscopy: Current Practices to Future Perspectives

    Simon Crase1,2, Benjamin Hall2, Suresh N. Thennadil3,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1945-1965, 2021, DOI:10.32604/cmc.2021.018517

    Abstract Supervised machine learning techniques have become well established in the study of spectroscopy data. However, the unsupervised learning technique of cluster analysis hasn’t reached the same level maturity in chemometric analysis. This paper surveys recent studies which apply cluster analysis to NIR and IR spectroscopy data. In addition, we summarize the current practices in cluster analysis of spectroscopy and contrast these with cluster analysis literature from the machine learning and pattern recognition domain. This includes practices in data pre-processing, feature extraction, clustering distance metrics, clustering algorithms and validation techniques. Special consideration is given to the specific characteristics of IR and… More >

  • Open Access


    Industrial Food Quality Analysis Using New k-Nearest-Neighbour methods

    Omar Fetitah1, Ibrahim M. Almanjahie2,3, Mohammed Kadi Attouch1,*, Salah Khardani4

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2681-2694, 2021, DOI:10.32604/cmc.2021.015469

    Abstract The problem of predicting continuous scalar outcomes from functional predictors has received high levels of interest in recent years in many fields, especially in the food industry. The k-nearest neighbor (k-NN) method of Near-Infrared Reflectance (NIR) analysis is practical, relatively easy to implement, and becoming one of the most popular methods for conducting food quality based on NIR data. The k-NN is often named k nearest neighbor classifier when it is used for classifying categorical variables, while it is called k-nearest neighbor regression when it is applied for predicting noncategorical variables. The objective of this paper is to use the… More >

  • Open Access


    Cerebral tissue oxygenation index and lactate at 24 hours postoperative predict survival and neurodevelopmental outcome after neonatal cardiac surgery

    Safwat A. Aly1, David Zurakowski2, Penny Glass3, Kami Skurow-Todd4, Richard A. Jonas5, Mary T. Donofrio4

    Congenital Heart Disease, Vol.12, No.2, pp. 188-195, 2017, DOI:10.1111/chd.12426

    Abstract Importance: There are no well-established noninvasive biomarkers for identifying patients at risk for poor outcome after surgery for congenital heart disease. Few studies have assessed prognostic accuracy of cerebral tissue oxygenation index (cTOI) measured by near infrared spectroscopy (NIRS).
    Objective: To assess the utility of noninvasive NIRS monitoring as a predictor of outcomes after neonatal cardiac surgery through measurement of cTOI. To examine the utility of noninvasive NIRS monitoring in combination with lactate concentration and inotropic score in prediction of outcomes after neonatal cardiac surgery.
    Design: Prospective longitudinal cohort study.
    Setting: Operating room and cardiac intensive care unit, Children’s National… More >

  • Open Access


    S100B and its relation to cerebral oxygenation in neonates and infants undergoing surgery for congenital heart disease

    Jan Hinnerk Hansen1, Lydia Kissner1, Jana Logoteta1, Olaf Jung1, Peter Dütschke2, Tim Attmann3, Jens Scheewe3, Hans‐Heiner Kramer1,4

    Congenital Heart Disease, Vol.14, No.3, pp. 427-437, 2019, DOI:10.1111/chd.12741

    Abstract Objectives: Neonates and infants undergoing surgery for congenital heart disease are at risk for developmental impairment. Hypoxic‐ischemic brain injury might be one contributing factor. We aimed to investigate the perioperative release of the astro‐ cyte protein S100B and its relation to cerebral oxygenation.
    Methods: Serum S100B was measured before and 0, 12, 24, and 48 hours after sur‐ gery. Cerebral oxygen saturation was derived by near‐infrared spectroscopy. S100B reference values based on preoperative samples; concentrations above the 75th per‐ centile were defined as elevated. Patients with elevated S100B at 24 or 48 hours were compared to cases with S100B in… More >

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