jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Faridatul Ama Ismail | Nina Korlina Madzhi | Noor Ezan Abdullah | Hadzli Hashim
Source: IAES International Journal of Artificial Intelligence (article, 2020-05-19)
Field: Chemistry — Analytical Chemistry

Classification of RRIM clone series using artificial neural network This paper presents comparative investigation on the classification of rubber latex clone series using Artificial Neural Network (ANN) based on optical sensing technique. Rubber Research Institute of Malaysia (RRIM) introduced the rubber breeding program known as RRIM clone series in order to increase the yield of latex production and the rubber wood to meet the requirement for export and import in upstream sector. Due to the large numbers of clones launched with different characteristics and properties, this bring difficulty such as lack of information regarding to the identification on cloning. Therefore, this work developed an optical based sensing system for classification of the selected RRIM 2000 and 3000 clone series based. Near Infrared Sensors was used as sensing element in order to measure the latex from the top surface and photodiode which received the reflected light from the sensor via reflectance index in term of voltage. The raw obtained data was then used as input parameter for ANN tool which supervised by scaled gradient back propagation and the performance was optimized at 25 neurons with 74.4% accuracy. By using ANN the sensitivity, specificity and accuracy for each clones are measured. RRIM 3001 shows the highest sensitivity, 94.1% while RRIM 2002 shows the highest specificity of 99.1% accuracy, 93.1%. As a result, the system could differentiate RRIM 2002 more compare to other clones. Sensitivity (control systems) ; clone (Java method) ; Computer science ; Artificial neural network ; Remote sensing ; Artificial intelligence ; Biology ; Geology ; Engineering Spectroscopy and Chemometric Analyses ; Plant biochemistry and biosynthesis ; Analytical Chemistry and Sensors
Authors: Nicole Creange | Mathew Cabral | Stephen D. Funni | Zijin Yang | Zhu Xiao-li | Xiangming Chen | Elizabeth C. Dickey
Source: Microscopy and Microanalysis (article, 2020-07-30)
Field: Materials Science — Materials Chemistry

Local Structure Quantification in Tetragonal Tungsten Bronze Structures Utilizing Convolutional Neural Networks An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button. Tungsten ; Tetragonal crystal system ; Convolutional neural network ; Bronze ; Materials science ; Computer science ; Artificial intelligence ; Metallurgy ; Crystallography ; Crystal structure ; Chemistry Ferroelectric and Piezoelectric Materials ; Electronic and Structural Properties of Oxides ; Advanced materials and composites
Authors: Ronei J. Poppi
Source: Brazilian Journal of Analytical Chemistry (article, 2020-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Professor Ronei Jesus Poppi, a chemist with a clear vocation for research, recently gave an interview to BrJAC IQ-Unicamp) in 1986 with a degree in chemistry, and holds a master's degree (1989) and a doctoral (1993) degree from the same IQ-Unicamp and a postdoctoral degree from the Free University of Brussels, Belgium (1996). Chemist ; Psychoanalysis ; Psychology ; Philosophy ; Art ; Chemistry ; Organic chemistry Various Chemistry Research Topics
Authors: Oxana Ye. Rodionova | Sergey Kucheryavskiy | Alexey L. Pomerantsev
Source: ChemRxiv (preprint, 2020-12-10)
Field: Chemistry — Analytical Chemistry

Efficient PCA-Exploration of High-Dimensional Datasets Basic tools for exploration and interpretation of Principal Component Analysis (PCA) results are well- known and thoroughly described in many comprehensive tutorials. However, in the recent decade, several new tools have been developed. Some of them were originally created for solving authentication and classification tasks. In this paper we demonstrate that they can also be useful for the exploratory data analysis.We discuss several important aspects of the PCA exploration of high dimensional datasets, such as estimation of a proper complexity of PCA model, dependence on the data structure, presence of outliers, etc. We introduce new tools for the assessment of the PCA model complexity such as the plots of the degrees of freedom developed for the orthogonal and score distances, as well as the Extreme and Distance plots, which present a new look at the features of the training and test (new) data. These tools are simple and fast in computation. In some cases, they are more efficient than the conventional PCA tools. A simulated example provides an intuitive illustration of their application. Three real-world examples originated from various fields are employed to demonstrate capabilities of the new tools and ways they can be used. The first example considers the reproducibility of a handheld spectrometer using a dataset that is presented for the first time. The other two datasets, which describe the authentication of olives in brine and classification of wines by their geographical origin, are already known and are often used for the illustrative purposes.The paper does not touch upon the well-known things, such as the algorithms for the PCA decomposition, or interpretation of scores and loadings. Instead, we pay attention primarily to more advanced topics, such as exploration of data homogeneity, understanding and evaluation of an optimal model complexity. The examples are accompanied by links to free software that implements the tools. Computer science ; Principal component analysis ; Outlier ; Data mining ; Data exploration ; Artificial intelligence ; Classifier (UML) ; Computation ; Machine learning ; Pattern recognition (psychology) ; Algorithm ; Visualization Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Metabolomics and Mass Spectrometry Studies
Authors: Nur Haziqah Syazni Mohd Hatta
Source: International Journal of Emerging Trends in Engineering Research (article, 2020-09-15)
Field: Materials Science — Materials Chemistry

Review on Partial Discharge and Time Domain Reflectometry using Finite Element Analysis In this paper, the concept of Partial Discharge (PD) and Time Domain Reflectometry (TDR) are discussed as they are among the most commonly used technique by utility company to enhance the fault characterization during routine based maintenance or failure in the system. The aim of this paper to review a technique that is able to shorten the period of cable fault diagnosis so that the replacement of cable can take place more efficiently. Correspondingly, this paper will investigate the ability of combining both techniques (PD and TDR) to reduce the cable replacement cost and subsequently prolong the lifespan of the cable. The proposed technique combination of PD, water tree and TDR with finite element analysis has been discussed in this paper. It can be seen, for future development the technique combination could be improve to monitor the cable health efficiently. Reflectometry ; Finite element method ; Partial discharge ; Time domain ; Mathematics ; Materials science ; Mathematical analysis ; Computer science ; Structural engineering ; Electrical engineering ; Engineering ; Voltage ; Computer vision High voltage insulation and dielectric phenomena
Authors: Daniela Mesa Sanchez | Steve Creger | Veerupaksh Singla | Ruwan T. Kurulugama | John C. Fjeldsted | Julia Laskin
Source: ChemRxiv (preprint, 2020-06-03)
Field: Chemistry — Spectroscopy

An Ion Mobility-Mass Spectrometry Imaging Workflow &lt;p&gt;Mass spectrometry imaging (MSI) is a powerful technique for the label-free spatially-resolved analysis of biological tissues. Coupling ion mobility (IM) separation with MSI allows separation of isobars in the mobility dimension and increases confidence of peak assignments. Recently, imaging experiments have been implemented on the Agilent 6560 Ion Mobility Quadrupole Time of Flight Mass Spectrometer, making MSI experiments more broadly accessible to the MS community. However, the absence of data analysis software for this system presents a bottleneck. Herein, we present a vendor-specific imaging workflow to visualize IM-MSI data produced on the Agilent IM-MS system. Specifically, we have developed a Python script, the ion mobility-mass spectrometry image creation script (IM-MSIC), which interfaces Agilent’s Mass Hunter Mass Profiler software with the MacCoss lab’s Skyline software and generates drift time and mass-to-charge selected ion images. In the workflow, Mass Profiler is used for an untargeted feature detection. The IM-MSIC script mediates user input of data and extracts ion chronograms utilizing Skyline’s command-line interface, then proceeds towards ion image generation within a single user interface. Ion image post-processing is subsequently performed using different tools implemented in accompanying scripts.&lt;/p&gt; Ion-mobility spectrometry ; Mass spectrometry imaging ; Workflow ; Mass spectrometry ; Software ; Computer science ; Interface (matter) ; Chemistry ; Database ; Operating system ; Chromatography Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Ion-surface interactions and analysis
Authors: M. Salomi | R. Lakshmi Priya | G Manimannan | N. Manjula Devi
Source: International Journal of Recent Technology and Engineering (IJRTE) (article, 2020-11-26)
Field: Materials Science — Polymers and Plastics

Data mining Application of Data Reduction and Clustering Domain of Textile Database This research paper attempts to identify the textile data structure and hidden pattern of original database with certain important parameters. The main objectives of this study are to identify the first n number of factors that explained over the study period. Initially factor analysis is performed to extract factor scores. Principal extraction is performed through Data mining package with sixteen textile fabrics parameters. Factor extraction is aimed to uncover the intrinsic pattern among the textile parameters considered and an important point of factor analysis is to extract factor scores for further investigation. Thus, factor analysis consistently resulted in three factors for the whole datasets. The amount of total variation explained is over 75 percent in factor analysis with varimax rotation. The factor loadings or factor structure matrix with unassociated rotation methods are not always easy to interpret. The nonhierarchical k-mean clustering is also used to identify meaningful cluster based on their parameter means of original database. Varimax rotation ; Cluster analysis ; Principal component analysis ; Factor (programming language) ; Factor analysis ; Data mining ; Rotation (mathematics) ; Computer science ; Cluster (spacecraft) ; Domain (mathematical analysis) ; Statistics ; Database ; Pattern recognition (psychology) ; Artificial intelligence ; Mathematics Textile materials and evaluations ; Color perception and design ; Color Science and Applications
Authors: Luca Asproni | Davide Caputo | Blanca Silva | Giovanni Fazzi | Marco Magagnini
Source: Quantum Machine Intelligence (preprint, 2020-03-19)
Field: Materials Science — Materials Chemistry

Accuracy and minor embedding in subqubo decomposition with fully connected large problems: a case study about the number partitioning problem Abstract In this work, we investigate the capabilities of a hybrid quantum-classical procedure to explore the solution space using the D-Wave 2000 Q T M quantum annealer device. Here, we study the ability of the quantum hardware to solve the number partitioning problem, a well-known NP-hard optimization model that poses some challenges typical of those encountered in real-world applications. This represents one of the most complex scenario in terms of qubits connectivity and, by increasing the input problem size, we analyze the scaling properties of the quantum-classical workflow. We find remarkable results in most instances of the model; for the most complex ones, we investigate further the D-Wave Hybrid suite. Specifically, we were able to find the optimal solutions even in the worst cases by fine-tuning the parameters that schedule the annealing time and allowing a pause in the annealing cycle. Quantum annealing ; Embedding ; Qubit ; Computer science ; Quantum ; Scaling ; Schedule ; Workflow ; Suite ; Simulated annealing ; Quadratic unconstrained binary optimization ; Mathematical optimization ; Theoretical computer science ; Algorithm ; Parallel computing ; Quantum computer ; Mathematics ; Artificial intelligence ; Physics ; Quantum mechanics Chemical and Physical Properties of Materials ; Quantum Computing Algorithms and Architecture ; Advanced Physical and Chemical Molecular Interactions
Authors: Antonio R. Jiménez | Gabriel Beltrán
Source: International Journal of Computer Applications (article, 2020-06-18)
Field: Chemistry — Organic Chemistry

Applied Soft Computing on Virgin Olive Oil Elaboration Process Fuzzy Control of Grinding Stage A decisional system on fuzzy logic based (DFS) was built for automatization of the olives fruit grinding stage, on extra virgin olive oils elaboration process, for modulation of 'biophenols' content (BPH) in the oils obtained. This Fuzzy model was integrated in a `Simulink' laboratory simulator of this stage which consists on a PI feedback controller type. The input to controller was constituted by the fruits temperature, the pore size of sieve, the rotational speed of hammer mill and the error, which this is the difference between BPH levels predicted at simulator output versus the setpoint BPH level. The importance of these variable, on end level of BPH in oils, was established by 'data-mining' analysis which enabled defined the behavior rules and decisional tables for built the membership functions of Fuzzy system. The temperature, sieve and error were constituted the antecedent function for fuzzification and the hammer speed the consequent function for desfuzzification. A total of 27 rules "if..the..and..then.." were extracted. To work with this laboratory simulator and verify the performance of the fuzzy model an EVOO process model an Artificial Neural Networks based (ANN) was used which was built by employing the Near Infrared (NIR) spectral properties of olives fruit and technological variables of process for prediction of BPH level in oils (r=0.937, RMSE=354 mg kg -1 ) at horizontal decanter output. This laboratory simulator was checked by application of different BPH setpoint step and monitorization of adjust of the BPH prediction to setpoint for the different hammer speeds established by de Fuzzy system, showing a good response in short times and the ability to modulate the BPH content within a wide range of these ( 450 mg kg -1 ) with respect to the initial value. Computer science ; Elaboration ; Olive oil ; Soft computing ; Fuzzy logic ; Process (computing) ; Stage (stratigraphy) ; Grinding ; Process engineering ; Artificial intelligence ; Operating system ; Geology ; Metallurgy ; Materials science ; Food science ; Humanities ; Chemistry Edible Oils Quality and Analysis ; Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies
Authors: Jenna Hershberger | Nicolás Morales | Christiano C. Simoes | Bryan J. Ellerbrock | Guillaume Bauchet | Lukas A. Mueller | Michael A. Gore
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-09-20)
Field: Chemistry — Analytical Chemistry

Making WAVES in Breedbase: An Integrated Spectral Data Storage and Analysis Pipeline for Plant Breeding Programs ABSTRACT Visible and near-infrared (vis-NIRS) spectroscopy is a promising tool for increasing phenotyping throughput in plant breeding programs, but existing analysis software packages are not optimized for a breeding context. Additionally, commercial software options are often outside of budget constraints for some breeding and research programs. To that end, we developed an open-source R package, waves , for the streamlined analysis of spectral data with several cross-validation schemes to assess prediction accuracy. Waves is compatible with a wide range of spectrometer models and performs visualization, filtering, aggregation, cross-validation set formation, model training, and prediction functions for the association of vis-NIRS spectra with reference measurements. Furthermore, we have integrated this package into the Breedbase family of open-source databases, expanding the analysis capabilities of this growing digital ecosystem to a number of crop species. Taken together, the standalone and Breedbase versions of waves enhance the accessibility of tools for the analysis of spectral data during the plant breeding process. Core ideas waves is an open-source R package for spectral data analysis in plant breeding Breeding relevant cross-validation schemes to evaluate predictive accuracy of models Extension of Breedbase—an open-source database—to support spectral data storage Graphical user interface developed for implementation of waves in Breedbase Computer science ; Context (archaeology) ; Software ; Visualization ; Pipeline (software) ; Graphical user interface ; Process (computing) ; Data mining ; Geography Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Remote Sensing in Agriculture
Authors: И.В. Баранец | А.Д. Бобков | Л.В. Гайдукова | А.В. Краснов | Ф.Ф. Легуша | С.И. Пугачев | Е.Ю. Рытов
Source: МОРСКИЕ ИНТЕЛЛЕКТУАЛЬНЫЕ ТЕХНОЛОГИИ (article, 2020-11-23)
Field: Materials Science — General Materials Science

Influence of curing technology on morphology and physical characteristics of epoxy glue DM-5-65 Проведено комплексное исследование воздействия энергетических полей различной физической природы – электротермического (ЭТ), ультразвукового (УЗ), сверхвысокочастотного (СВЧ) и комбинации этих полей на морфологию, удельную плотность и свободную поверхностную энергию промышленного эпоксидного клея ДМ-5-65, содержащего в качестве одного из неорганических наполнителей титанат бария (BaTiO3). В соответствии с технологией изготовления составных электроакустических преобразователей гидроакустических систем клей наносился на поверхность пьезокерамики, металлизированную серебром высокотемпературным методом «вжигания». Экспериментально установлено существенное варьирование характера расположения наполнителя BaTiO3 в матрице связующего, плотности химических связей и адгезии образующегося соединения клей – металл при изменении технологии отверждения клея. Анализ полученных результатов свидетельствует о возможности регулирования в широких пределах плотности и однородности клея, а также смачиваемости клеем поверхности твердого тела. A comprehensive study of the effect of energy fields of various physical nature – electrothermal (ET), ultrasonic (US), microwave and a combination of these fields on the morphology, specific density and free surface energy of industrial epoxy glue DM-5-65, containing barium titanate (BaTiO3) as one of the non-organic fillers. In accordance with the technology of manufacturing composite electroacoustic transducers of hydroacoustic systems, glue was applied to the surface of piezoceramics, metallized with silver by the high-temperature "burning" method. Experimentally, a significant variation in the nature of the location of the BaTiO3 filler in the binder matrix, the density of chemical bonds, and the adhesion of the resulting glue-metal compound when the glue curing technology changes. The analysis of the obtained results shows that it is possible to control the density and uniformity of the glue, as well as the wettability of the solid surface by the glue, within a wide range. GLUE ; Materials science ; Composite material ; Barium titanate ; Epoxy ; Curing (chemistry) ; Wetting ; Ceramic ; Surface energy ; Adhesive ; Composite number ; Ultrasonic sensor ; Microwave ; Acoustics Material Properties and Applications ; Polymer Science and Applications ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry
Authors: Antoine Laborde
Source: SPIRE - Sciences Po Institutional REpository (preprint, 2020-12-03)
Field: Chemistry — Analytical Chemistry

Detection of minor compounds in food powder using near infrared hyperspectral imaging L’imagerie hyperspectrale proche infrarouge (PIR) permet d’obtenir une carte spectrale d’un échantillon organique. La mesure d’un spectre pour chaque pixel de la caméra permet notamment la recherche de composés minoritaires dans les poudres agroalimentaires. Cependant, l’analyse spectrale PIR est limitée à une couche de profondeur donnée. De plus, la taille des particules associée à une résolution insuffisante des caméras PIR actuelles induisent un mélange des signaux spectraux dans les pixels de l’image. Ces deux problèmes sont une limitation pour l’analyse des composés minoritaires dans les poudres agroalimentaires.Nous proposons une méthode permettant de déterminer la profondeur de détection d’une cible composite placée dans un produit pulvérulent tel que la farine de blé. Basée sur une régression par projection sur les structures latentes, cette méthode permet d’appréhender l’atténuation du signal PIR lorsque la couche de poudre augmente, et ce malgré les problèmes inhérents à la détection en profondeur.De plus, deux stratégies de démélange de spectres sont proposées dans le but de détecter les pixels contenant des signatures de particules minoritaires. Le manque de valeur de référence utilisées en tant que données de validation des algorithmes ainsi que l’ambiguïté des spectres des composés pures à démélanger sont deux difficultés majeures. Une première stratégie consiste à modélisation la variabilité des spectres étudiés via l’Analyse en Composantes Principales afin de construire un algorithme de détection performant. La deuxième stratégie, basée sur la Multivariate Curve Resolution Alternating Least-Squares permet le démélange des signaux par pixels dans un cas plus complexe. Hyperspectral imaging ; Pixel ; Partial least squares regression ; Spectral signature ; Near-infrared spectroscopy ; Principal component analysis ; Multispectral image ; Minor (academic) ; Remote sensing ; Artificial intelligence ; Pattern recognition (psychology) ; Mathematics ; Computer science ; Geography ; Optics ; Statistics ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Ioannis F. Gonos | I. Fofana
Source: Energies (article, 2020-09-22)
Field: Materials Science — Materials Chemistry

Special Issue “Selected Papers from the 2018 IEEE International Conference on High Voltage Engineering (ICHVE 2018)” The 2018 IEEE International Conference on High Voltage Engineering and Application (ICHVE 2018) was organized by the National Technical University of Athens, Greece and endorsed by the IEEE Dielectrics and Electrical Insulation Society [...] Engineering ; High voltage ; Electrical engineering ; Telecommunications ; Engineering physics ; Engineering management ; Voltage High voltage insulation and dielectric phenomena ; Lightning and Electromagnetic Phenomena ; Thermal Analysis in Power Transmission