jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mikhail Olkhovskiy | Eva Müllerová | Petr Martínek
Source: Journal of Electrical Engineering (article, 2020-12-01)
Field: Materials Science — Materials Chemistry

Impulse signals classification using one dimensional convolutional neural network Abstract The main purpose of this work is to propose a modern one-dimensional convolutional neural network (1 D CNN) configurations for distinguishing separate PD impulses from different types of PD sources while the parameters of these sources are changed. Three PD sources were built for signal generation: corona discharge, discharge in a void, and surface discharge. The reason for using separate PD impulses for classification is to develop a universal tool with the ability to recognize an insulation defects by analysing very few events in the insulation in a short range of time. Additionally, we found the optimal sample rates for the data acquisition for these network configurations. The necessity of signal filtering was also tested. The following configurations of a neural network were proposed: configuration for classification raw PD impulses; configuration for classification of PD impulses represented by power spectral density, for both filtered and unfiltered variants. Convolutional neural network ; Impulse (physics) ; Partial discharge ; Pattern recognition (psychology) ; Artificial neural network ; Computer science ; SIGNAL (programming language) ; Void (composites) ; Artificial intelligence ; Materials science ; Voltage ; Engineering ; Physics ; Electrical engineering High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Electrostatic Discharge in Electronics
Authors: Cihat Cagdas Uydur | Oktay Arıkan
Source: Energies (article, 2020-10-12)
Field: Materials Science — Materials Chemistry

Use of Tanδ and Partial Discharge for Evaluating the Cable Termination Assembly It is known that the failure of cable terminations causes power outages and impairs system quality and continuity. Besides, serious economic losses on both the distribution and consumer sides occur. In this study, the dielectric behavior of the cable and the faults caused by the defects in the cable termination under overvoltage has been examined. As test samples, 12 kV XLPE insulated cable is used and they were aged at three (3*U0) and five (5*U0) times the rated voltage. After each aging cycle, dielectric parameters of the cable were measured by an OMIRCRON CPC100/CPTD1 device, and the partial discharge (PD) was measured by an OMICRON MPD600 device. In the measurements, it was observed that the cable was broken down at different aging cycle numbers as a result of defects in the cable termination due to weak workmanship. As a result of the measurements, it is concluded that defects in the cable termination give information about the increase in the probability of failure and the decrease of the cable lifetime. Consequently, it is concluded that fine workmanship and timely maintenance of cable terminations prevent the system from unwanted power outages and economic losses. Workmanship ; Overvoltage ; Partial discharge ; Power cable ; Direct-buried cable ; All-dielectric self-supporting cable ; Electrical engineering ; Voltage ; Power (physics) ; Materials science ; Structural engineering ; Engineering ; Composite material ; Cable harness ; Cable gland ; Cable theory ; Physics High voltage insulation and dielectric phenomena ; Electrical Fault Detection and Protection ; Power Transformer Diagnostics and Insulation
Authors: Ruzhen Xu | Xu Zhou | Shaojin Wang
Source: International journal of agricultural and biological engineering (article, 2020-01-01)
Field: Chemistry — Analytical Chemistry

Comparative analyses of three pretreatments on color of kiwifruits during hot air drying Color is one of the most important quality attributes for agricultural products due to its great influence on consumers’ appetite. Effects of pretreatments, including blanching with hot water, osmosis with sucrose solution, and soaking with ascorbic acid solution on the color of kiwifruit slices were investigated during hot air drying, and three models (i.e. zero-order, first-order and Weibull models) were used to describe the color change kinetics of soaking samples. The results illustrated that color parameters (L*, a* and b*) of dried kiwifruit slices were improved significantly by immersing in sucrose solution or ascorbic acid solution before drying, whereas immersing in hot water for long time led to severe color deterioration. For un-pretreated samples, the Weibull model was the best to describe change kinetics of L* and a* values with R2 =0.974 and 0.996, respectively, while the zero-order model was best for the changes of ΔE value (R2 =0.996). For samples immersed in 1% ascorbic acid solution for 15 min, change kinetics of L* and ΔE values were best fitted to zero-order models with R2 =0.988 and 0.972, respectively. ΔE of dried samples without pretreatment was 12.55, but decreased by approximately 16.33% when samples soaked in 1% ascorbic acid solution for 15 min before drying. Keywords: color, computer vision system, kinetic model, ascorbic acid, sucrose DOI: 10.25165/j.ijabe.20201302.5489 Citation: Xu R Z, Zhou X, Wang S J. Comparative analyses of three pretreatments on color of kiwifruits during hot air drying. Int J Agric & Biol Eng, 2020; 13(2): 228–234. Ascorbic acid ; Blanching ; Chemistry ; Sucrose ; Food science ; Horticulture ; Mathematics Spectroscopy and Chemometric Analyses ; Food Drying and Modeling
Authors: Shailendra Rajput | Alon Kuperman | Asher Yahalom | Moshe Averbukh
Source: Energies (article, 2020-09-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Studies on Dynamic Properties of Ultracapacitors Using Infinite r–C Chain Equivalent Circuit and Reverse Fourier Transform The specific power storage capabilities of double-layer ultracapacitors are receiving significant attention from engineers and scientific researchers. Nevertheless, their dynamic behavior should be studied to improve the performance and for efficient applications in electrical devices. This article presents an infinite resistor–capacitor (r–C) chain-based mathematical model for the analysis of double layer ultracapacitors. The internal resistance and capacitance were measured for repetitive charging and discharging cycles. The magnitudes of internal resistance and capacitance showed approximately ±10% changes for charge-discharge processes. Electrochemical impedance spectroscopy investigations revealed that the impedance of a double-layer ultracapacitor does not change significantly in the temperature range of (−30 °C to +30 °C) and voltage range of (0.3376–2.736 V). The analysis of impedance data using the proposed mathematical model showed good agreement between the experimental and theoretical data. The dynamic behavior of the ultracapacitor was successfully represented by utilizing the proposed infinite r–C chains equivalent circuit, and the reverse Fourier transform analysis. The r–C electrical equivalent circuit was also analyzed using the PSIM simulation software to study the dynamic behavior of ultracapacitor parameters. The simulation study yields an excellent agreement between the experimental and calculated voltage characteristics for repetitive charging-discharging processes. Supercapacitor ; Capacitance ; Dielectric spectroscopy ; Equivalent circuit ; Capacitor ; Electrical impedance ; Materials science ; Resistor ; Voltage ; Internal resistance ; Electronic engineering ; Electrical engineering ; Power (physics) ; Electrochemistry ; Engineering ; Chemistry ; Physics ; Electrode ; Thermodynamics ; Battery (electricity) Supercapacitor Materials and Fabrication ; Electric and Hybrid Vehicle Technologies ; Advanced Sensor and Energy Harvesting Materials
Authors: Mahmoud M. Sebaiy
Source: Biomedical Journal of Scientific & Technical Research (article, 2020-02-04)
Field: Chemistry — Analytical Chemistry

Absorbance Subtraction Method fоr Simultaneous Determination оf Paracetamol and Orphenadrine Citrate in their Combined Pharmaceutical Dosage Forms A simple, specific, accurate and precise spectrophotometric method ws settled fr simultaneous determination f paracetamol and orphenadrine citrate in their pure form and in their pharmaceutical formulation. Absorbance Subtraction technique hs bn usd in simultaneous determination f both drugs without prior separation. Absorbance Subtraction method parameters wr validated according t ICH guidelines in which accuracy, precision, repeatability and robustness wr found in accepted limits. Advantages and disadvantages f Absorbance Subtraction wr discussed and statistical comparison betwn the proposed method and the reference one ws also performed. Pharmacy ; Medicine ; Dosage form ; Traditional medicine ; Chemistry ; Pharmacology ; Family medicine Analytical Methods in Pharmaceuticals ; Antibiotics Pharmacokinetics and Efficacy ; Pharmacological Effects and Assays
Authors: Zhong Zheng | Xin Zhang | Jingxin Yu | Rui Guo | Lili Zhangzhong
Source: Sensors (article, 2020-02-23)
Field: Chemistry — Analytical Chemistry

Deep Neural Networks for the Classification of Pure and Impure Strawberry Purees In this paper, a comparative study of the effectiveness of deep neural networks (DNNs) in the classification of pure and impure purees is conducted. Three different types of deep neural networks (DNNs)-the Gated Recurrent Unit (GRU), the Long Short Term Memory (LSTM), and the temporal convolutional network (TCN)-are employed for the detection of adulteration of strawberry purees. The Strawberry dataset, a time series spectroscopy dataset from the UCR time series classification repository, is utilized to evaluate the performance of different DNNs. Experimental results demonstrate that the TCN is able to obtain a higher classification accuracy than the GRU and LSTM. Moreover, the TCN achieves a new state-of-the-art classification accuracy on the Strawberry dataset. These results indicates the great potential of using the TCN for the detection of adulteration of fruit purees in the future. Convolutional neural network ; Artificial intelligence ; Computer science ; Artificial neural network ; Deep learning ; Pattern recognition (psychology) ; Long short term memory ; Deep neural networks ; Recurrent neural network ; Machine learning Spectroscopy and Chemometric Analyses ; Horticultural and Viticultural Research ; Fermentation and Sensory Analysis
Authors: Ahmed A. Farid
Source:  (article, 2020-03-27)
Field: Chemistry — Analytical Chemistry

A Composite Hybrid Feature Selection Learning-Based Optimization of Genetic Algorithm For Breast Cancer Detection Breast cancer is a significant health issue across the world. Breast cancer is the most widelydiagnosed cancer in women; early-stage diagnosis of disease and therapies increase patient safety. This paper proposes a synthetic model set of features focused on the optimization of the genetic algorithm (CHFS-BOGA) to forecast breast cancer. This hybrid feature selection approach combines the advantages of three filter feature selection approaches with an optimize Genetic Algorithm (OGA) to select the best features to improve the performance of the classification process and scalability. We propose OGA by improving the initial population generating and genetic operators using the results of filter approaches as some prior information with using the C4.5 decision tree classifier as a fitness function instead of probability and random selection. The authors collected available updated data from Wisconsin UCI machine learning with a total of 569 rows and 32 columns. The dataset evaluated using an explorer set of weka data mining open-source software for the analysis purpose. The results show that the proposed hybrid feature selection approach significantly outperforms the single filter approaches and principal component analysis (PCA) for optimum feature selection. These characteristics are good indicators for the return prediction. The highest accuracy achieved with the proposed system before (CHFS-BOGA) using the support vector machine (SVM) classifiers was 97.3%. The highest accuracy after (CHFS-BOGA-SVM) was 98.25% on split 70.0% train, remainder test, and 100% on the full training set. Moreover, the receiver operating characteristic (ROC) curve was equal to 1.0. The results showed that the proposed (CHFS-BOGA-SVM) system was able to accurately classify the type of breast tumor, whether malignant or benign. Feature selection ; Computer science ; Selection (genetic algorithm) ; Genetic algorithm ; Breast cancer ; Artificial intelligence ; Composite number ; Feature (linguistics) ; Machine learning ; Algorithm ; Pattern recognition (psychology) ; Cancer ; Optimization algorithm ; Mathematical optimization ; Mathematics ; Biology ; Genetics Spectroscopy and Chemometric Analyses ; AI in cancer detection ; Gene expression and cancer classification
Authors: M. Carmen Aguilera-Morillo | Ana M. Aguilera
Source: Statistical Modelling (article, 2020-10-14)
Field: Chemistry — Analytical Chemistry

Multi-class classification of biomechanical data: A functional LDA approach based on multi-class penalized functional PLS A functional linear discriminant analysis approach to classify a set of kinematic data (human movement curves of individuals performing different physical activities) is performed. Kinematic data, usually collected in linear acceleration or angular rotation format, can be identified with functions in a continuous domain (time, percentage of gait cycle, etc.). Since kinematic curves are measured in the same sample of individuals performing different activities, they are a clear example of functional data with repeated measures. On the other hand, the sample curves are observed with noise. Then, a roughness penalty might be necessary in order to provide a smooth estimation of the discriminant functions, which would make them more interpretable. Moreover, because of the infinite dimension of functional data, a reduction dimension technique should be considered. To solve these problems, we propose a multi-class approach for penalized functional partial least squares (FPLS) regression. Then linear discriminant analysis (LDA) will be performed on the estimated FPLS components. This methodology is motivated by two case studies. The first study considers the linear acceleration recorded every two seconds in 30 subjects, related to three different activities (walking, climbing stairs and down stairs). The second study works with the triaxial angular rotation, for each joint, in 51 children when they completed a cycle walking under three conditions (walking, carrying a backpack and pulling a trolley). A simulation study is also developed for comparing the performance of the proposed functional LDA with respect to the corresponding multivariate and non-penalized approaches. Linear discriminant analysis ; Kinematics ; Mathematics ; Functional data analysis ; Gait ; Rotation (mathematics) ; Artificial intelligence ; Data set ; Computer science ; Pattern recognition (psychology) ; Statistics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Advanced Statistical Methods and Models
Authors: Thanasan Intarakumthornchai | Ramil Kesvarakul
Source: PLoS ONE (article, 2020-11-05)
Field: Chemistry — Analytical Chemistry

Double yolk eggs detection using fuzzy logic Chicken egg products increased by 60% worldwide resulting in the farmers or traders egg industry. The double yolk (DY) eggs are priced higher than single yolk (SY) eggs around 35% at the same size. Although, separating DY from SY will increase more revenue but it has to be replaced at the higher cost from skilled labor for sorting. Normally, the separation of double yolk eggs required the expertise person by weigh and shape of egg but it is still high error. The purpose of this research is to detect double-yolked (DY) chicken eggs with weight and ratio of the egg's size using fuzzy logic and developing a low cost prototype to reduce the cost of separation. The K-means clustering is used for separating DY and SY, firstly. However, the error from this technique is still high as 15.05% because of its hard clustering. Therefore, the intersection zone scattering from using the weight and ratio of the egg's size to input of DY and SY is taken into consider with fuzzy logic algorithm, to improve the error. The results of errors from fuzzy logic are depended with input membership functions (MF). This research selects triangular MF of weight as low = 65 g, medium = 75 g and high = 85 g, while ratio of the egg is triangular MF as low = 1.30, medium = 1.40 and high = 1.50. This algorithm is not provide the minimum total error but it gives the low error to detect a double yolk while the real egg is SY as 1.43% of total eggs. This algorithm is applied to develop a double yolk egg detection prototype with Mbed platform by a load cell and OpenMV CAM, to measure the weight and ratio of the egg respectively. Yolk ; Fuzzy logic ; Sorting ; Cluster analysis ; Mathematics ; Algorithm ; Statistics ; Biology ; Computer science ; Artificial intelligence ; Fishery Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Antonio De Nicola | Gianmarco Munaò | Nino Grizzuti | Finizia Auriemma | Claudio De Rosa | Agur Sevink | Giuseppe Milano
Source: Soft Materials (article, 2020-01-25)
Field: Materials Science — Materials Chemistry

Generation of well relaxed all atom models of stereoregular polymers: a validation of hybrid particle-field molecular dynamics for polypropylene melts of different tacticities ABSTRACT The tacticity of vinyl polymer chains strongly affects the physical properties of polymeric materials, as example the chain conformations and stiffness. In the present work we tested how the hybrid Particle-Field Molecular Dynamics (PF-MD) technique is capable to describe conformational differences of polymer chains as function of the tacticity. In particular, we focus on tacticity effect of atactic, isotactic, and syndiotactic polypropylene (PP) homopolymer melts. We found that PF-MD simulations exhibit dependence of Flory’s Characteristic Ratio from the fraction of racemo diads along the PP chains in qualitative agreement with Small Angle Neutron Scattering (SANS) experiments and theoretical previsions. Finally, we calculated and compared the packing length parameter on very high stereoregular syndiotactic PP systems with rheological measurements. A qualitative agreement between the calculated and experimental packing length is found. Tacticity ; Materials science ; Polymer ; Molecular dynamics ; Polypropylene ; Polymer chemistry ; Rheology ; Neutron scattering ; Particle (ecology) ; Chemical physics ; Thermodynamics ; Scattering ; Composite material ; Computational chemistry ; Chemistry ; Physics ; Polymerization Material Dynamics and Properties ; Rheology and Fluid Dynamics Studies ; Polymer crystallization and properties
Authors: Patrick Krenn | Patrick Zimmermann | Michael Fischlschweiger | Tim Zeiner
Source: Journal of Chemical & Engineering Data (article, 2020-10-22)
Field: Materials Science — Materials Chemistry

SAFT-Based Maxwell–Stefan Approach to Model the Diffusion through Epoxy Resins Epoxy resins are often applied to prevent sensitive electronics to come into contact with solvents. Therefore, it is necessary to know the diffusion through the epoxy resins to determine the thickness of the epoxy resins layer for different applications. In this work a diffusion model is developed on the basis of the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) equation of state. To consider the polymer network, PC-SAFT is combined with an elastic term. The driving force for the diffusion is the gradient of the chemical potential, but additionally the viscoelastic polymer relaxation below the glass transition temperature is considered. The model is applied to calculate the diffusion of water, isopropyl alcohol, and heptane through the epoxy resin at different temperatures. The modeled diffusion processes are in good agreement with experimentally determined data. Even highly anomalous absorption kinetics, which were measured for isopropyl alcohol diffusion, could be explained and calculated on the basis of the developed diffusion model. Epoxy ; Diffusion ; Chemistry ; Viscoelasticity ; Isopropyl alcohol ; Thermodynamics ; Glass transition ; Polymer ; Relaxation (psychology) ; Composite material ; Polymer chemistry ; Materials science ; Organic chemistry Material Dynamics and Properties ; Epoxy Resin Curing Processes ; Composite Material Mechanics
Authors: Anna Baun | Zuyuan Wang | Svenja Morsbach | Zijie Qiu | Akimitsu Narita | George Fytas | Kläus Müllen
Source: Macromolecules (article, 2020-06-23)
Field: Chemistry — Organic Chemistry

Rigidification of Poly(<i>p</i>-phenylene)s through <i>ortho</i>-Phenyl Substitution A sterically π-congested ortho-phenylated poly(<i>p</i>-phenylene) (PPP) has been synthesized with unprecedentedly high molecular weights up to 29 kDa after fractionation, as confirmed by gel permeation chromatography coupled with a multiangle laser light scattering detector. The chain translation diffusion coefficient obtained from dynamic light scattering experiments displayed strong scaling (∼<i>L</i> <sub>w</sub> <sup>-0.8</sup>) to the chain contour length, indicating a rodlike shape with remarkably high rigidity of this novel PPP. These results provide an interesting insight into the relationship between the structure and the chain stiffness of PPP-based polymers and challenge the validity of the existing diffusion models in polymer physics. Gel permeation chromatography ; Polymer ; Chemistry ; Multiangle light scattering ; Steric effects ; Polymer chemistry ; Hydrodynamic radius ; Dynamic light scattering ; Phenylene ; Light scattering ; Rigidity (electromagnetism) ; Scattering ; Fractionation ; Analytical Chemistry (journal) ; Materials science ; Chromatography ; Stereochemistry ; Organic chemistry ; Copolymer ; Optics ; Nanotechnology ; Physics Synthesis and Properties of Aromatic Compounds ; Luminescence and Fluorescent Materials ; Organoboron and organosilicon chemistry
Authors: Víctor‐Alfonso Gracia‐Medrano‐Bravo | Jakob Gröne | S. Baesch | Philip Scharfer | Wilhelm Schabel
Source: Langmuir (article, 2020-05-21)
Field: Materials Science — Polymers and Plastics

Influence of Particle Shape on the Drying Regime Maps for Platelike Particle–Polymer Composites In previous works, the influence of drying conditions on the particle distribution in filled polymer films was investigated using spherical silica particles and polystyrene pellets. The results showed that changing drying conditions can influence the particle distribution in a dry film. These were summarized in drying regime maps to predict the distribution of the particles in the final film; the particles accumulate at the top of the coating (evaporation regime) or sink to the bottom (sedimentation regime) or remain homogeneously distributed (diffusion regime). In the present study, the particle geometry was oblate to determine the changes in the particle distribution in comparison to spherical particles. A simulation was developed by changing the sedimentation and diffusion models. Concentration-dependent sedimentation rates and the particle orientation in the dry film were experimentally determined. New drying regime maps were plotted and compared. The simulation results show an expansion of the diffusion regime for the platelike particles in comparison with spherical particles. The regime maps were validated using platelike glass particles dispersed in poly(vinyl alcohol) (PVA) with water. The particle concentration profiles in the dry film and the film morphology were obtained via three-dimensional (3-D) Raman spectroscopy. Materials science ; Particle (ecology) ; Polystyrene ; Diffusion ; Composite material ; Sedimentation ; Evaporation ; Polymer ; Particle-size distribution ; Particle size ; Chemical engineering ; Thermodynamics Polymer Foaming and Composites ; Nanomaterials and Printing Technologies ; Aerogels and thermal insulation