jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Baina He | Shuo Wu | Lemiao Wang | Jingru Zhang | Xin Lin | Fantao Meng | Yang Liu
Source: Research Square (preprint, 2022-10-13)
Field: Materials Science — Materials Chemistry

Location prediction model of zero value insulator based on PNN Abstract Zero insulators directly reduce the electrical performance of insulator strings, affecting the safe and reliable operation of transmission lines. The grounding current of the insulator string contains the characteristic information of insulator electrical performance. Extracting the characteristic information of grounding current can realize the detection of zero value insulator, which is of great significance to ensure the safe operation of transmission lines. In this paper, the composite insulator used on ultra high voltage (UHV) lines is studied to analyze the influence of zero insulators on the electric field distribution. Furthermore, the corresponding characteristics of the zero insulators at different locations are extracted. The fitting relationship between the characteristic quantity and the zero-insulator position is analyzed. The effective characteristics of grounding current are selected as training sample to establish the zero-insulator position prediction model based on probabilistic neural network (PNN). The research result is meaningful for the detection of zero insulators. Insulator (electricity) ; Electric power transmission ; Ground ; Artificial neural network ; Voltage ; Zero crossing ; Electrical engineering ; Computer science ; Physics ; Engineering ; Artificial intelligence High voltage insulation and dielectric phenomena ; Power Line Inspection Robots ; Thermal Analysis in Power Transmission
Authors: J. Otto | K.-L. Krieger
Source:  (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

7.1 - Fusion Strategies of Spectral Data Generated by MEMS-FPI NIR Spectral Detectors Detector ; Sensor fusion ; Microelectromechanical systems ; Fusion ; Computer science ; Materials science ; Artificial intelligence ; Optoelectronics ; Telecommunications Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Charles-Élie Fillion | Johanna Fischer | Raj Kumar | Aymen Fassatoui | S. Pizzini | L. Ranno | Djoudi Ourdani | M. Belmeguenai | Y. Roussigné | Salim-Mourad Chérif | Stéphane Auret | Isabelle Joumard | Olivier Boulle | Gilles Gaudin | L. D. Buda-Prejbeanu | C. Baraduc | H. Béa
Source: arXiv (Cornell University) (preprint, 2022-04-08)
Field: Materials Science — Materials Chemistry

Gate-controlled skyrmion and domain wall chirality Magnetic skyrmions are localized chiral spin textures, which offer great promise to store and process information at the nanoscale. In the presence of asymmetric exchange interactions, their chirality, which governs their dynamics, is generally considered as an intrinsic parameter set during the sample deposition. In this work, we experimentally demonstrate that a gate voltage can control this key parameter. We probe the chirality of skyrmions and chiral domain walls by observing the direction of their current-induced motion and show that a gate voltage can reverse it. This local and dynamical reversal of the chirality is due to a sign inversion of the interfacial Dzyaloshinskii-Moriya interaction that we attribute to ionic migration of oxygen under gate voltage. Micromagnetic simulations show that the chirality reversal is a continuous transformation, in which the skyrmion is conserved. This control of chirality with 2 - 3 V gate voltage can be used for skyrmion-based logic devices, yielding new functionalities. Skyrmion ; Chirality (physics) ; Physics ; Nanotechnology ; Materials science ; Condensed matter physics ; Quantum mechanics ; Chiral symmetry Nanocluster Synthesis and Applications ; Molecular Junctions and Nanostructures ; Photoreceptor and optogenetics research
Authors: Ali Ben Abbes | Pedro Luiz Pizzigatti Corrêa | Jeaneth Machicao | Alison Specht | Michael Rigby | Guzmán Eduardo Gonzalez | E. Jamie Trammell | Jefrrey Evans | Yasuhisa Kondo
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2022-10-04)
Field: Materials Science — Materials Chemistry

PARSEC Scientific Results: methodology and use cases PARSEC Scientific results: Methodology and Case Studies. This session at the University of Sao Paulo's 6th Data Science Symposium was a presentation of PARSEC results to date. The organisers are grateful for funding from IUGS and UNESCO to support the attendance of early career researchers. • PARSEC execution. Introduction to the application of the PARSEC synthesis model with case studies from East Africa. Ali Ben Abbes (Foundation for Research on Biodiversity-CESAB) Research foci • Estimation of wealth index in Brazil: Pedro Luiz Pizzigatti Corrêa (Escola Politécnica da USP), Jeaneth Machicao and team • Socio-economic assessment and PAs in Australia: Alison Specht (University of Queensland, TERN), Germàn Gonzalez (AURIN), Michael Rigby (AURIN) • Mapping the socio-economic consequences of PAs in west coast USA: Jamie Trammell (Southern Oregon University) and Jeffrey Evans (The Nature Conservancy) • Pandemic effects on tourism: Yasuhisa Kondo (Research Institute for Humanity and Nature, RIHN) Parsec ; Computer science ; Astrophysics ; Physics ; Galaxy Graphite, nuclear technology, radiation studies ; Nuclear Physics and Applications ; Machine Learning in Materials Science
Authors: Daniel S. Karls | Steven M. Clark | Brendon Waters | Ryan S. Elliott | Ellad B. Tadmor
Source: arXiv (Cornell University) (preprint, 2022-05-28)
Field: Materials Science — Materials Chemistry

HPC Extensions to the OpenKIM Processing Pipeline Presentation for eScience conference Pipeline (software) ; Computer science ; Computation ; Computational science ; Implementation ; Cloud computing ; Supercomputer ; Parallel computing ; Distributed computing ; Computer engineering ; Software engineering ; Algorithm ; Programming language ; Operating system Machine Learning in Materials Science ; Advanced Materials Characterization Techniques ; Electronic and Structural Properties of Oxides
Authors: А.М. Серікбай | И. Молдахан | А.Ж. Аликулов | Grigoriy A. Mun
Source: INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES (article, 2022-02-15)
Field: Materials Science — Biomaterials

Problems of macroscopic recording of information in nanoscale structures В работе показан подход с использованием нейронов, обладающим двумя входами, которые отвечают двум различным термодинамическим переменным. Отработаны макромолекулярные системы, которые действительно представляют собой аналог нейронной сети и которые позволяют записывать информацию на молекулярном уровне. Nanoscopic scale ; Nanotechnology ; Materials science ; Computer science ; Data science Diatoms and Algae Research ; Advanced Electron Microscopy Techniques and Applications
Source: European Scientific e-Journal (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Rationalization of Reinforced Concrete Structural-Anisotropic Shells Design Parameters In the article, the formulation and implementation of the task to rationalize the structural parameters of reinforced concrete structurally anisotropic shells is presented.The criterion for such an objective is the energy principle, according to which it is considered that out of the entire set of possible system parameter values with a constant volume of material, the number of external and internal ties, the potential deformation energy after the reconstruction reaches the lower limit at a rational combination of the geometric parameter values.The coatings of buildings and structures perceive significant loads, which cause a high level of the stress-strain state of the system.That is why it is advisable to consider such types of coatings that could perceive, evenly distribute and transfer the load to the supports.Structurally anisotropic reinforced concrete shells of different Gaussian curvature are proved to be the most suitable for this purpose.The search for rational shell designs that perceive the specified types of loads is a rather urgent, but logically unfinished problem. Rationalization (economics) ; Reinforced concrete ; Deflection (physics) Structural mechanics and materials ; Heat Transfer and Mathematical Modeling ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry
Authors: K.M.Ø. Jensen
Source: Acta Crystallographica Section A Foundations and Advances (article, 2022-08-23)
Field: Materials Science — Materials Chemistry

Nanostructure characterization with pair distribution function analysis: tools for automated analysis Characterization (materials science) ; Nanostructure ; Materials science ; Function (biology) ; Nanotechnology ; Biology X-ray Diffraction in Crystallography
Authors: Alejandro Rubio | Carlos Avendaño | Fredy Hernán Martínez Sarmiento
Source: International Journal of Advanced Computer Science and Applications (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

A Deep Neural Network based Detection System for the Visual Diagnosis of the Blackberry Thanks to its geographical and climatic advantages, Colombia has a historically strong fruit-growing tradition. To date, the basis of its food and economic development in a significant part of its territory is based on a wide range of fruits. One of the most important in the central and western regions of the country is the blackberry, which is rooted not only from the economic and food point of view but also culturally. For the departments of Casanare, Santander, and Cundinamarca, this fruit is one of the primary sources of income, rural employment, and food supply and income. However, small and medium farmers cultivate without access to technological production tools and with limited economic capacity. This process suffers from several problems that affect the whole plant, especially the fruit, which is strongly influenced by fungi, extreme ripening processes, or low temperatures. One of the main problems to be dealt with in its cultivation is the spread of pests, which are one of the causes of fruit rot. As a support strategy in producing this fruit, the development of an embedded system for visually diagnosing the fruit using a deep neural network is proposed. The article presents the training, tuning, and performance evaluation of this convolutional network to detect three possible fruit states, ripe, immature, and rotten, to facilitate the harvesting and marketing processes and reduce the impact on the healthy fruit and the quality of the final product. The model is built with a ResNet type network, which is trained with its dataset, which seeks to use images captured in their natural environment with as little manipulation as possible to reduce image analysis. This model achieves an accuracy of 70%, which indicates its high performance and validates its use in a stand-alone embedded system. Computer science ; Product (mathematics) ; Process (computing) ; Production (economics) ; Quality (philosophy) ; Convolutional neural network ; Agricultural engineering ; Artificial intelligence ; Economics Spectroscopy and Chemometric Analyses ; Postharvest Quality and Shelf Life Management ; Smart Agriculture and AI
Authors: H. Oborskyi | Alexandr Orgiyan | V. Тikhenko | Anna Balaniuk | V. Kolesnik
Source: Odes’kyi Politechnichnyi Universytet Pratsi (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

DYNAMIC VIBRATION DAMPERS FOR CONSOLE INSTRUMENTS The maximum efficiency of dynamic vibration dampers (DD) is achieved at optimal values of their parameters. Inertial DD are tuned according to their own frequency and damping, and the optimal values of the absorber parameters depend on the spectral composition of the suppressed oscillations. For nonlinear DD, the optimal values of parameters (for example, gap or precompression) also depend on the intensity of external influences on the object. For multi-element DDs, the number of damper inertial elements should also be optimized. The conditions for optimal tuning of the inertial DD are the conditions of antiresonance. In this work, the tuning of an impact DD with viscous friction has been studied. To determine the optimal value of the gap between the mass of the absorber and its body, a nonlinear problem was solved by the method of point transformations. The influence of deviations from the optimal setting of the shock DD on the amplitude of oscillations is determined. It has been established that small deviations from the optimum cause significant increments in the oscillation range (by 2...5 times), which leads to the need to tune the shock DD with high accuracy. The sensitivity of the vibration damper to the optimization error of its parameters is estimated in the work. In addition, the tuning features of multi-element DDs built into the boring bar for eight types of absorbers were studied with varying their design features. When studying the frequency characteristics, the ratio of the maximum values A0 max/AD max was taken as a measure of efficiency, where A0 max is the oscillation amplitude in the system without a damper. The influence of the diametral clearance and the axial compression force on the efficiency of various types of DDs has been established. Damper ; Vibration ; Oscillation (cell signaling) ; Control theory (sociology) ; Shock absorber ; Inertial frame of reference ; Damping ratio ; Work (physics) ; Nonlinear system ; Fictitious force ; Shock (circulatory) ; Optimal design ; Range (aeronautics) ; Amplitude ; Sensitivity (control systems) ; Vibration control ; Structural engineering ; Physics ; Mechanics ; Acoustics ; Mathematics ; Materials science ; Engineering ; Computer science ; Optics ; Classical mechanics Structural mechanics and materials ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry ; Material Properties and Applications
Authors: Yoshihiro Nambu
Source:  (preprint, 2022-07-05)
Field: Materials Science — Materials Chemistry

Rejection-free Monte Carlo simulation of QUBO and Lechner--Hauke--Zoller optimization problems &lt;p&gt; In this study, we implemented a rejection-free Monte Carlo (RFMC) algorithm, which is a kernel of rejection-free SA (RFSA). We showed its validity and advantage in obtaining globally optimal solution for quadratic unconstrained binary optimization (QUBO) and spin-glass problem embedded in the Lechner–Hauke–Zoller (LHZ) architecture. Landscapes of success probabilities of finding the globally optimal solution as well as feasible solutions were evaluated as a function of a set of hyper-parameters used to characterize the weights of cost and penalty functions. We demonstrated that the efficiency of RFMC was greatly enhanced compared to that of standard MC. Furthermore, we found that the landscapes for QUBO and those for LHZ problem show considerably different views. When we focus on a specific class of problems, the smaller the problem size, the more scattered is the success probability. We also show that the success probabilities can be further improved by avoiding inefficiencies due to cycling of state transitions using short-term memory mechanisms. We suggest a reasonable strategy to tune hyper-parameters and find the correct global solution using RFSA. &lt;/p&gt; Computer science ; Monte Carlo method ; Mathematical optimization ; Quadratic unconstrained binary optimization ; Quadratic equation ; Algorithm ; Mathematics ; Physics ; Statistics Machine Learning in Materials Science ; Theoretical and Computational Physics
Authors: Nirma Ceisa Santi | Hastie Audytra
Source: Ultimatics Jurnal Teknik Informatika (article, 2022-07-25)
Field: Chemistry — Organic Chemistry

Teakwood Grade Identification with GLCM and K-NN with Adaboost Optimization Teak is one type of tree that has many functions and uses. Teak wood has a very high quality to be used as raw material for the manufacture of home furniture such as tables, chairs, cabinets, and others. But middle testers (Perhutani staff) who test the quality of wood grade have limitations if the classification uses the five senses of sight and also there are still many furniture entrepreneurs who are often mistaken about teak wood quality assessment. This resulted in a lack of quality grade teak wood used as raw material for making home appliances or for furniture and trade needs under the Perhutani Corporation, especially the Cepu Kph. The teak wood image data is then acquired through preprocessing data ready to be processed. By using GLCM as an image feature extraction both training data and testing data. After the image characteristics are obtained, the image is classified by the K-Nearest Neighbor method with adaboost optimization. The final result is obtained in the form of wood grade quality classification namely grade A, B, C and D according to the class Artificial intelligence ; Preprocessor ; Pattern recognition (psychology) ; Identification (biology) ; AdaBoost ; Computer science ; Quality (philosophy) ; Pulp and paper industry ; Engineering ; Mathematics ; Support vector machine ; Botany Wood and Agarwood Research ; Agricultural and Environmental Management ; Remote Sensing and LiDAR Applications
Authors: Borislava Toleva
Source: Croatian Review of Economic Business and Social Statistics (article, 2022-06-01)
Field: Chemistry — Analytical Chemistry

ANOVA bootstrapped principal components analysis for logistic regression Abstract Principal components analysis (PCA) is often used as a dimensionality reduction technique. A small number of principal components is selected to be used in a classification or a regression model to boost accuracy. A central issue in the PCA is how to select the number of principal components. Existing algorithms often result in contradictions and the researcher needs to manually select the final number of principal components to be used. In this research the author proposes a novel algorithm that automatically selects the number of principal components. This is achieved based on a combination of ANOVA ranking of principal components, the bootstrap and classification models. Unlike the classical approach, the algorithm we propose improves the accuracy of the logistic regression and selects the best combination of principal components that may not necessarily be ordered. The ANOVA bootstrapped PCA classification we propose is novel as it automatically selects the number of principal components that would maximise the accuracy of the classification model. Principal component analysis ; Dimensionality reduction ; Logistic regression ; Ranking (information retrieval) ; Curse of dimensionality ; Artificial intelligence ; Computer science ; Pattern recognition (psychology) ; Principal (computer security) ; Statistics ; Regression ; Mathematics ; Data mining Spectroscopy and Chemometric Analyses ; Advanced Statistical Methods and Models ; Fault Detection and Control Systems
Authors: Barbara Sturm | Oliver Hensel
Source: Proceedings of the 22nd International Drying Symposium on Drying Technology - IDS '22 (article, 2022-08-09)
Field: Chemistry — Analytical Chemistry

NIR-monochrome monitoring systems to predict moisture content of apple slices during drying process In smart drying process, a digital replica of the process operation is created via sensors (so-called Digital Twin) to optimize the drying conditions. To create a digital twin of the drying process, there are various measurements to take into consideration among which moisture content. In what follows, LED and LLBI imaging were studied at 1450 nm. GPR models trained using the LEDs data estimated the moisture content changes of apple slices by high Rsquared of 0.995 and low RMSE of 1.85%. The findings of this study can be considered as a stepping-stone towards the appearance of smart dryers. Monochrome ; Water content ; Process (computing) ; Moisture ; Content (measure theory) ; Environmental science ; Process engineering ; Computer science ; Materials science ; Artificial intelligence ; Composite material ; Engineering ; Mathematics ; Geotechnical engineering Spectroscopy and Chemometric Analyses
Authors: Fuhai Zhao | Zhiqiang Liu | Rifan Chen | Yi Hao | Zhihao Ma
Source: Research Square (preprint, 2022-05-02)
Field: Materials Science — General Materials Science

The effect of temperature field on the characteristics of carbon fiber reinforced thermoplastic composites in the laying and shaping process Composite material ; Materials science ; Thermoplastic composites ; Laying ; Thermoplastic ; Fiber ; Field (mathematics) ; Structural engineering ; Engineering ; Mathematics Material Properties and Applications ; Engineering Technology and Methodologies ; Additive Manufacturing and 3D Printing Technologies
Authors: Jingwen Liang | Xiner Huang | Huibing Wu
Source: Highlights in Science Engineering and Technology (article, 2022-12-07)
Field: Materials Science — Polymers and Plastics

Research and analysis of intercalated meltblown nonwovens based on machine learning This paper explores the relationship and change law between process parameters, structural variables and product performance, and through seeking the optimal combination of process parameters, the filtration efficiency of the product is as high as possible and the filtration resistance is as small as possible. Firstly, the correlation between structural variables and product performance is analyzed by Spearman correlation coefficient method after the relevant data are processed by factor analysis method. Secondly, linear regression, random forest regression and lightGMB regression models are used to judge the relationship between process parameters and structural variables. Finally, the relationship between structural variables and product performance can be obtained by using multidimensional scaling transform (MDS). The results showed that the product filtration efficiency was the highest when the acceptance efficiency distance was 20m and the hot air velocity was 800km/h. Filtration (mathematics) ; Regression analysis ; Linear regression ; Product (mathematics) ; Correlation coefficient ; Statistics ; Mathematics ; Regression ; Process (computing) ; Biological system ; Econometrics ; Computer science Textile materials and evaluations
Authors: Noer Aden Bahry Aden | Anis Siti Nurrohkayati
Source: TEKNOSAINS Jurnal Sains Teknologi dan Informatika (article, 2022-06-03)
Field: Materials Science — Materials Chemistry

Analisis Perubahan Temperatur Mata Pahat Karbida Pada Proses Pembubutan Baja Aisi 1045 Dengan FEM-Simulation di PT. X Proses pemesinan bubut adalah salah satu proses operasi permesinan yang paling umum dan banyak digunakan dalam bidang industri. Telah banyak dilakukan penelitian yang dikembangkan untuk menambah kemampuan permesinan untuk menentukan parameter proses pembubutan menggunakan pemodelan dan metode optimasi untuk mendapatkan karakteristik hasil permesinan yang baik. Optimasi dari parameter diperlukan untuk mengurangi gaya potong dalam proses permesinan. Gaya potong yang terlalu tinggi dapat menyebabkan perubahan temperatur antara benda kerja dengan pahat bubut, yang diakibatkan oleh perubahan energi pemotongan menjadi energi panas akibat gesekan antara benda kerja dengan pahat bubut, sehingga pada prosesnya terjadi penyerpihan yang cepat pada pahat bubut, dan pada akhirnya dapat menyebabkan keausan dan patahnya pahat bubut. Pada penelitian ini dilakukan simulasi proses pembubutan menggunakan perangkat lunak FEA dengan variasi parameter untuk mengetahui pengaruh variasi parameter terhadap temperatur permukaan pada proses pembubutan baja AISI 1045 dan pahat karbida. Pada penelitian ini menggunakan metode Taguchi dengan karakteristik kualistas hasil The Smaller is Better. Maka hasil terbaik dari penelitian ini adalah simulasi proses pembubutan dengan variasi parameter yang menghasilkan temperatur permukaan terkecil. Hasil penelitian menunjukkan bahwa semakin kecil nilai dari parameter yang digunakan maka semakin kecil temperature permukaan yang dihasilkan selama proses pembubutan. Physics Material Selection and Properties ; Manufacturing Process and Optimization ; Advanced machining processes and optimization