jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Е. В. Антипина | Antipina E.V. | А.Ф. Антипин | Antipin A.F. | С.А. Мустафина | Mustafina S.A.
Source: Международный журнал Программные продукты и системы (article, 2020-02-26)
Field: Materials Science — Materials Chemistry

Программное обеспечение для автоматизации процесса поиска кинетических параметров химических реакций The paper describes the software, which the authors developed. It is for solving the problem of finding the kinetic parameters of chemical reactions. In the conditions of modern industrial production, methods of mathematical modeling of chemical-technological processes are widely used, which allow solving the problems of forecasting and optimizing production at the stage of a computational experiment. To solve these problems, we need the mathematical description of the chemical process, which relies on the construction and observation of the kinetic model of the chemical reaction. Computer science Thermal and Kinetic Analysis ; Process Optimization and Integration ; Chemical and Environmental Engineering Research
Authors: Fidelina Flores | Joanne Foliente | Kevin F. Yaptenco | Paul Armstrong
Source: Philippine Journal of Agricultural and Biosystems Engineering (article, 2020-12-30)
Field: Chemistry — Analytical Chemistry

Non-Destructive Prediction of Paddy Seed Quality using Near Infrared Spectroscopy The need for a rapid and non-destructive method for measuring paddy seed quality is important since it could help save time and effort of the breeders and farmers. Near-infrared (NIR) spectroscopy which is a non-destructive analytical technique was used in this study. It was used to predict the germination rate and vigor of hybrid paddy seeds and classify the seeds according to the level of germination rate. A total of 71 seed lots with varying germination rate and vigor were used in the study. Paddy seeds were classified according to their germination rate (very high &gt;90%, high 80-90%, moderate 70-79% and low &lt;70%). Each seed lots were scanned at five random locations. Reflectance values of paddy seeds were scanned using NIR spectrometers. After scanning, the germination rate was determined using standard methods in the laboratory. Pre-processing techniques were done to the spectral data gathered. The preprocessed spectral data were subjected to principal component analysis and partial least square regression (PLSR) to predict the paddy seed quality parameters. Performance of PLSR using the PCA scores from the preprocessed spectral data of paddy seeds showed that the calibration model for predicting the germination rate had a computed R2 value of 0.626-0.804 and the RMSE was 11.716-8.489. The R2 and RMSE of the model for seed vigor was 0.670-0.787 and 14.095-11.328, respectively. The model for predicting the seed class had a computed R 2 value of 0.803 and the RMSE was 0.514 for the NIR spectrometer and the R2 and RMSE was 0.648 and 0.687, respectively, for the vis NIR spectrometer. Based on the RMSE values and using the guidelines by Williams and Norris (2001) the models for seed class can be used with caution in most applications like in research. Results showed the potential of NIR spectroscopy as a non-destructive method of predicting seed quality parameters and classifying paddy seeds according to the level of germination rate. The results of the study could be used to predict seed germination rate and vigor and classify sort seed lots quickly based on the values of germination rate and seed vigor. Germination ; Principal component analysis ; Partial least squares regression ; Mathematics ; Mean squared error ; Regression analysis ; Environmental science ; Agronomy ; Horticulture ; Statistics ; Biology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; GABA and Rice Research
Authors: Krzysztof Szafran | Ireneusz Kramarski
Source: Fatigue of Aircraft Structures (article, 2020-12-01)
Field: Materials Science — Polymers and Plastics

Service Life Extension of Parachutes with Use of Non-Desctructive and Partially Destructive Testing Methods of Textile Materials Abstract The specificity of personal rescue and reserve parachutes is the fact that they are practically never used for jumping during their service life as they are intended for use only in emergency situations. Therefore, these parachutes throughout the entire period of use are only periodically aired and repacked every 6-12 months. Airing and repacking is necessary even if the parachute is only stored. Rescue and reserve parachutes’ components wear unevenly because the canopy with the suspension lines is inside the container and the cover, while the external components of the harness and the container undergo typical operational wear. Therefore, the service life of rescue parachutes can even reach 20 years (this refers to the canopy with the suspension lines alone). During normal exploitation, parachutes are subjected to non-destructive visual and tactile inspection in preparation for packing. When a parachute reaches its maximum service life, extension of its service life can be calculated based on its technical condition. The procedure for extending parachute’s service life involves non-destructive tests at a fabric air permeability test stand and partially destructive tests at the strength test stand. In the paper, both methods are described and their advantages and disadvantages are discussed. Also, observations some regarding the packers’ work and the desired new properties of raw materials that could be introduced to the parachute industry are presented. Service life ; Service (business) ; Container (type theory) ; Engineering ; Textile ; Forensic engineering ; Suspension (topology) ; Structural engineering ; Mechanical engineering ; Materials science ; Composite material ; Business Textile materials and evaluations ; Additive Manufacturing and 3D Printing Technologies ; Mechanical Behavior of Composites
Authors: Guo‐Ming Wang | Han Hu | Min Tang | Jinlong Gong | Yifan Wang | Hong‐Keun Ji | Gyung-Suk Kil
Source: Journal of Electrical Engineering (article, 2020-08-01)
Field: Materials Science — Materials Chemistry

De-noising of partial discharge signal using wavelet transform for GIS under HVDC Abstract Detection and analysis of partial discharge (PD) have been regard as the most effective method for condition monitoring and asset management of gas-insulated structures (GIS) in the power system. However, PD detection sensitivity and accuracy are greatly influenced by on-site noise and interference, resulting in failures in PD severity assessment, defect identification or localization. Although de-noising of PD signal under AC was well studied, related investigations under DC have not been carried out. With the rapid development of HVDC technology, it is a new challenge to eliminate noise from PD signal under DC for diagnosis of related power facilities. Therefore, this paper dealt with the discrimination of PD signal based on wavelet transform (WT) techniques for HVDC GIS, aiming to improve the sensitivity and accuracy of insulation diagnosis. Experimental setup was configured to generate PD signal under DC and four types of artificial defects were fabricated to simulate typical insulation defects in GIS. The WT techniques were used to discriminate PD pulse sequences from background noise, amplitude modulation radio interference, non-sinusoidal noise, and switching impulse and the effectiveness was compared with a high-pass filter. Partial discharge ; Wavelet ; Sensitivity (control systems) ; Wavelet transform ; Noise (video) ; Interference (communication) ; SIGNAL (programming language) ; Filter (signal processing) ; Electronic engineering ; Computer science ; Impulse (physics) ; Acoustics ; Engineering ; Electrical engineering ; Artificial intelligence ; Telecommunications ; Physics ; Voltage ; Channel (broadcasting) ; Computer vision High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Lightning and Electromagnetic Phenomena
Authors: Tao Yan | Qian Ma | Tie Jun Cui
Source: Journal of Computer and Communications (article, 2020-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Circular Polarization Hologram Realized by Pancharatnam-Berry Phase in Microwave Frequency Metasurfaces have shown great potential in controlling the propagation of electromagnetic waves, making them suitable for holographic beam-shaping elements. Using the principle of array synthesis, holograms have been realized in microwave frequency to manipulate electromagnetic waves to generate specific field patterns. However, current research is almost based on linear polarization and has little analysis on the circular polarization microwave hologram. Herein, we propose a circular polarization hologram realized by sub-wavelength units with self-adaptively phase profiles of electromagnetic waves. The full, continuous control of the phase is achieved by using a single structure unit based on the Pancharatnam-Berry phase. The inhomogeneity of wave-front is considered through amplitude and phase compensation which are essential to improve the quality of microwave hologram. The model achieves circular polarization hologram in microwave frequency and the clear field pattern is generated. The circular polarization hologram enriched the research field of microwave imaging, thus providing more inspirations for the development of various related techniques. Holography ; Polarization (electrochemistry) ; Optics ; Microwave ; Circular polarization ; Physics ; Electromagnetic radiation ; Wavefront ; Amplitude ; Linear polarization ; Phase (matter) ; Near and far field ; Wavelength ; Electromagnetic field ; Microstrip Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Dongdong Zhang | Jin Liu | Fengbo Tao | Xiaoning Huang | Chengshun Yang | Zhijin Zhang
Source:  (article, 2020-09-06)
Field: Materials Science — Materials Chemistry

Research on Non-contact Pollution Monitoring Method of Composite Insulator Based on Space Electric Field Insulator contamination directly threatens the safe and stable operation of the overhead line. Through spatial electric field monitoring, it is expected to realize insulator pollution condition monitoring and contamination flashover warning in a non-contact way. So in this paper, the spatial electric field distribution characteristics of 110 kV composite insulators are simulated, where the effects of different surface states and their discharge levels on the spatial electric field of insulators are analyzed. On this basis, a non-contact monitoring method for composite insulator pollution based on the spatial electric field is proposed. The results show that there are significant differences in the spatial electric field of the composite insulator among three conditions of clean, pollution layer wetting, and dry band arcing. With the increase of pollution layer wetting and dry band arcing, it would lead to an increase of the amplitude of the spatial electric field of the insulator. It is feasible to identify the degree of pollution layer wetting as well as dry band arcing of the insulator string, by fixed-point monitoring the spatial electric field signal at the cross-strand of d = 0.5 m and directly opposite the last three positions. Research results can provide references for the online monitoring of overhead line pollution insulators and its flashover warning. Insulator (electricity) ; Electric field ; Arc flash ; Electric arc ; Pollution ; Overhead line ; Environmental science ; Materials science ; Remote sensing ; Electrical engineering ; Composite material ; Engineering ; Electrode ; Geology ; Physics High voltage insulation and dielectric phenomena ; Electrical Fault Detection and Protection ; Lightning and Electromagnetic Phenomena
Authors: Mohamad Izmir Farhan Mohamad Radzi | N. H. Nik Ali | Azrul Mohd Ariffin | M. S. Abd Rahman | N. Rameli | Mohamad Radzi Ahmad | Ali Syari’ati Mohd Salleh
Source: Indonesian Journal of Electrical Engineering and Computer Science (article, 2020-06-27)
Field: Materials Science — Materials Chemistry

Development process and testing of partial discharge detection device on medium voltage XLPE cable High voltage assets play a vital role in providing uninterrupted power to the consumers and any slight problems experienced by the assets may cause losses in millions of dollars to businesses. Therefore it is of utmost importance to monitor the health of high voltage assets. This research presents the development process of a Partial Discharge (PD) device that is able to detect PD acoustic waves for monitoring high voltage assets purposes. Medium voltage Cross-Linked Polyethylene (XLPE) cable was used which was introduced with spherical void defects at the joints of the cable that functioned to produce PD acoustic waves. Outcome of the development processes provides the finished design of the PD sensing device, known as Partial Discharge Detection (PDD) device. The functionality of the PDD device was also assessed through controlled experimentations, and they proved to be successful. Pure PD waveform captured by the ultrasonic sensor was similar when compared to a HFCT sensor’s pure PD waveform. The PDD device is a small and affordable, and is opened to various improvements such as integrating Artificial Intelligence (AI) unto the device, and one day may replace most existing bulky and expensive PD sensing devices that are readily available in the market. Partial discharge ; Voltage ; Waveform ; High voltage ; Process (computing) ; Ultrasonic sensor ; Electrical engineering ; Void (composites) ; Acoustic emission ; Materials science ; Computer science ; Engineering ; Acoustics ; Composite material High voltage insulation and dielectric phenomena ; Water Quality Monitoring Technologies ; Elevator Systems and Control
Authors: Robson Aparecido Gomes de Macedo | Peterson Adriano Belan | Sidnei Alves de Araújo
Source: International Journal of Computer Applications (article, 2020-10-15)
Field: Chemistry — Analytical Chemistry

An Embedded Computer Vision System for Beans Quality Inspection Despite the importance of agricultural grains appearance for their choice by the consumers as well as for determining their selling price, the visual inspection of the quality of these products is usually conducted in a manual way and, therefore, susceptible to high operational costs, human errors and inaccurate results. Recently, a computer vision system for quality inspection of beans composed by a set of hardware and software, named the SIVQUAF, was proposed in the literature. However, the software of the SIVQUAF was designed for a personal computer, which makes its operation more complex, decreases its performance and raises the cost of the equipment. Thus, in this work we explored the customization and optimization of SIVQUAF aiming its running on a Raspberry Pi 3, keeping similar performance, generating the SIVQUAFCompact. Besides redesigning and parallelizing algorithms, we proposed improvements in the classification and defect detection steps, and a new touchsensitive interface. The experiments conducted with SIVQUAFCompact embedded in a Raspberry Pi 3 demonstrated that in addition to reproducing high hit rates in the tasks of segmentation (97.50%), classification (97.06%) and detection of defects (74.78% ), there was a significant gain in terms of cost, operation and compaction of the equipment, increasing its operational, technical and economic viability. Computer science ; Quality (philosophy) ; Computer vision Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Ryo Murakami | Kazuki Nakamura | Hiromi Tanaka | Hiroshi Shinotsuka | Hideki Yoshikawa
Source: e-Journal of Surface Science and Nanotechnology (article, 2020-05-27)
Field: Materials Science — Surfaces, Coatings and Films

Efficient Removal of Noise-derived Components for Automatic XPS Spectral Decomposition Using Hierarchical Clustering In this paper, we aim to automatically provide a solution to peak separation in an X-ray photoelectron spectroscopy (XPS) spectrum with non-negligible statistical noise that is inevitably accepted in multi-dimensional (e.g., 2-dimensional/3-dimensional XPS profiles) XPS measurement. To achieve this, in our previous study [H. Shinotsuka et al., J. Electron Spectros. Relat. Phenomena 239, 146903 (2020)], we automatically selected optimal solutions using the Bayesian information criterion (BIC) for measured XPS spectra. This was successfully performed for many varieties of XPS spectra. However, the optimal solution rarely included a small and sharp peak that was likely to be caused by statistical noise. In this study, we investigate a practical method to eliminate the infrequent solution with a noise-derived peak. This method uses hierarchical clustering with peak parameters (i.e., width and area) as a preprocessing step before selecting the solutions using the BIC. X-ray photoelectron spectroscopy ; Noise (video) ; Principal component analysis ; Cluster analysis ; Hierarchical clustering ; Preprocessor ; Biological system ; Analytical Chemistry (journal) ; Spectral line ; Decomposition ; Computer science ; Pattern recognition (psychology) ; Materials science ; Chemistry ; Artificial intelligence ; Physics ; Nuclear magnetic resonance ; Chromatography Electron and X-Ray Spectroscopy Techniques ; Geochemistry and Geologic Mapping
Authors: Subrata Kumar Saha | Jamal Hossen | Masudur Rahman ANM
Source:  (article, 2020-01-01)
Field: Materials Science — Polymers and Plastics

Effect of Blend Ratio on Cotton-Modal Fibre Blended Ring- Spun Yarn Quality with Varying Modal Fibre Percentage Fibre blend ratio is an important factor that determines the properties of spun yarn. Modal is a regenerated man-made fibre and free from short fibres, neps, and impurities. In this paper, the influence of modal fibre in cotton-modal fibre blend ratio on the blended yarn properties has been studied. Cotton-modal blended yarn with blend ratio of 80:20, 70:30 and 50:50 and 100% cotton yarn of 30 Ne were produced in ring spinning frame. The properties of fibres, slivers, rovings and manufactured yarns were tested by using the Uster HVI, Wrap reel, Wrap block, Uster Evenness tester-5 and Lea strength tester. The experimental results show that the yarn quality parameters such as Um%, CVm%, thick places, thin places, neps, Imperfection Index and hairiness of 100% cotton are higher than cotton-modal blended yarns. With the increase of modal fibre percentage, the quality of blended yarns has been improved than 100% cotton yarn. In regards to the CSP value, the cotton-modal blended yarns show an increasing trend with increasing modal fibre percentage in the blend ratio. It can be attributed that the absence of short fibres in modal fibre which phenomena contributes to the yarn properties with increasing the modal fibre percentage. Modal ; Yarn ; Materials science ; Composite material ; Quality (philosophy) ; Ring (chemistry) ; Chemistry ; Physics Textile materials and evaluations ; Dyeing and Modifying Textile Fibers
Authors: Anirban Dutta | Biswapati Chatterjee
Source: Fashion and Textiles (article, 2020-12-15)
Field: Materials Science — Polymers and Plastics

Development of prediction model through linear multiple regression for the prediction of longitudinal stiffness of embroidered fabric Abstract Embroidery through computer aided semi-automatic machines is one of the most widely used option for the surface ornamentation of apparel fabrics at present. Since the embroidery process includes addition of certain amount of embroidery-threads depending upon the design motif, it is quite obvious that basic physical and functional properties of fabric are subject to change. It is therefore important to develop an algorithm or empirical equation for proper prediction of the properties of the embroidered fabric, relevant to its required end-use in apparel industry. In this context, an effort has been made to determine a prediction equation through linear multiple regressions for the prediction of longitudinal stiffness of embroidered fabric in terms of flexural rigidity in warp direction of the base fabric, considering the input parameters as warp-way flexural rigidity of the base fabric, breaking load and linear density of the embroidery thread, stitch density, average stitch length and average stitch angle of the embroidery design. The final Prediction model is statistically verified taking new embroidery samples of different varieties. It is found that the model can predict with a very satisfactory level of accuracy. Also, the influences of the embroidery parameters in this context have been analyzed through the corresponding regression coefficients and the three dimensional (3D) surface curves. Stitch density has been emerged as the most influential parameter, followed by the stitch length and the stitch angle. Flexural rigidity ; Stiffness ; Linear regression ; Linear density ; Rigidity (electromagnetism) ; Clothing ; Context (archaeology) ; Computer science ; Thread (computing) ; Regression ; Mathematics ; Structural engineering ; Engineering ; Materials science ; Statistics ; Geology ; Composite material Textile materials and evaluations ; Color perception and design ; Color Science and Applications
Authors: Ronaldo Hueb Baroni | Tufik Bauab | Leonardo Kayat Bittencourt | Giuseppe D’Ippolito | Suzan Menasce Goldman | Guilherme Hohgraefe Neto | Adonis Manzella | Antônio José da Rocha | Luis Augusto Sonoda | Fabio Seichi Takeda
Source: Radiologia Brasileira (article, 2020-07-15)
Field: Materials Science — Materials Chemistry

Practical recommendations for the safe use of gadolinium in magnetic resonance imaging: a Delphi expert panel study When choosing a GBCA, it is important to consider the characteristics of the gadolinium deposition in patient tissues and minimize potential risks. Furthermore, medical education programs are needed to increase the awareness of the potential risks of gadolinium deposition and thus avoid instances of overexposure to the contrast agent. Gadolinium ; Nephrogenic systemic fibrosis ; Medicine ; Delphi method ; Magnetic resonance imaging ; Radiology ; Medical physics ; Nuclear medicine ; Intensive care medicine ; Computer science ; Materials science ; Artificial intelligence Lanthanide and Transition Metal Complexes ; MRI in cancer diagnosis ; Medical Imaging and Pathology Studies
Authors: Seung Hyun Baek | Alberto Garcia‐Diaz | Yuanshun Dai
Source: Methodology (article, 2020-06-17)
Field: Chemistry — Analytical Chemistry

Multi-choice wavelet thresholding based binary classification method <p xmlns="http://www.ncbi.nlm.nih.gov/JATS1">Data mining is one of the most effective statistical methodologies to investigate a variety of problems in areas including pattern recognition, machine learning, bioinformatics, chemometrics, and statistics. In particular, statistically-sophisticated procedures that emphasize on reliability of results and computational efficiency are required for the analysis of high-dimensional data. Optimization principles can play a significant role in the rationalization and validation of specialized data mining procedures. This paper presents a novel methodology which is Multi-Choice Wavelet Thresholding (MCWT) based three-step methodology consists of three processes: perception (dimension reduction), decision (feature ranking), and cognition (model selection). In these steps three concepts known as wavelet thresholding, support vector machines for classification and information complexity are integrated to evaluate learning models. Three published data sets are used to illustrate the proposed methodology. Additionally, performance comparisons with recent and widely applied methods are shown. Thresholding ; Computer science ; Artificial intelligence ; Machine learning ; Feature selection ; Wavelet ; Data mining ; Pattern recognition (psychology) ; Dimensionality reduction ; Ranking (information retrieval) Spectroscopy and Chemometric Analyses ; Face and Expression Recognition ; Remote-Sensing Image Classification