jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tejasv Bedi
Source: RIT Scholar Works (Rochester Institute of Technology) (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Simulation-Based Inference on Mixture Experiments Mixture Experiments provide a foundation to optimize the predicted response basedon blends of different components . Parody and Edwards (2006) gave a method of inference on the expected response of a 2nd-order rotatable design, utilizing a simulation-based critical point to give substantially sharper intervals when compared to the simultaneous confidence intervals provided by Sa and Edwards (1993). Here, we begin with discussing the theory of mixture experiments and pseudocomponents. Then we move on to review the literature of simulation-based methods forgenerating critical points and visualization techniques of general response surface designs. Next, we develop the simulation-based technique for a {q, 2} Simplex-Lattice Design and visualize the simulation-based confidence intervals for the expected improvement in response based on two examples. Finally, we compare theefficiency of the simulation-based critical points relative to Scheffé’s adaptation ofcritical points for the general response surface. We conclude by providing an efficiency table and demonstrate superiority of the simulation-based method over the Scheffé’s adaptation on the basis of sample size savings. Inference ; Computer science ; Artificial intelligence ; Econometrics ; Mathematics Crystallization and Solubility Studies
Authors: Luther Sonda | Abdul Salam
Source: Jurnal Teknik Mesin Sinergi (article, 2019-05-24)
Field: Materials Science — Materials Chemistry

Analisis Modifikasi Sudut Pahat Gurdi terhadap Keausan Pahat pada Penggurdian Material Komposit Karbon/Epoxy Penelitian ini bertujuan untuk menganalisis sejauhmana keausan pahat pada penggurdian material komposit karbon/epoxy dengan menggunakan pahat gurdi konvensional HSS yang dimodifikasi sudut 2Kr nya menjadi dua tingkat. Selain itu, untuk mendapatkan besarnya putaran mesin, gerak makan, dan bentuk sudut 2Kr yang dimodifikasi agar diperoleh keausan pahat.yang paling minimal. Hasil yang diperoleh menunjukkan bahwa pengaruh variabel putaran mesin, gerak makan, dan sudut pahat modifikasi terhadap respon keausan pahat adalah berturut-turut sebagai berikut 10,128%, 8,653%, dan 5,394%. Setting kondisi optimum respon keausan pahat yang memberikan nilai keausan pahat paling minimum sebesar 0,2284 mm adalah berturut-turut sebagai berikut S = 650 rpm, F = 55 mm/min, dan 2Kr = 740. Dibandingkan dengan penggunaan pahat gurdi HSS standar untuk range variabel permesinan yang sama, keausan pahat rata-rata adalah 0,3280 mm, dengan demikian penggunaan pahat gurdi HSS yang dimodifikasi dapat mereduksi keausan pahat sekitar 30,5%. Materials science Material Selection and Properties ; Heat Transfer and Numerical Methods ; Epoxy Resin Curing Processes
Authors: Aly Badran | Hrishikesh Bale | Stephen T. Kelly | David B. Marshall
Source: Microscopy and Microanalysis (article, 2019-08-01)
Field: Materials Science — Materials Chemistry

Multiscale 3D Investigation of Damage in Angle-Interlocked Ceramic Matrix Composite under <i>in situ</i> Loading Journal Article Multiscale 3D Investigation of Damage in Angle-Interlocked Ceramic Matrix Composite under in situ Loading Get access Aly Badran, Aly Badran Mechanical Engineering, University of Colorado, Boulder CO, United States Search for other works by this author on: Oxford Academic Google Scholar Hrishikesh Bale, Hrishikesh Bale Carl Zeiss X-ray Microscopy, Pleasanton, CA, United States Corresponding author: hrishikesh.bale@zeiss.com Search for other works by this author on: Oxford Academic Google Scholar Stephen Kelly, Stephen Kelly Carl Zeiss X-ray Microscopy, Pleasanton, CA, United States Search for other works by this author on: Oxford Academic Google Scholar David Marshall David Marshall Mechanical Engineering, University of Colorado, Boulder CO, United States Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 25, Issue S2, 1 August 2019, Pages 362–363, https://doi.org/10.1017/S143192761900254X Published: 01 August 2019 Matrix (chemical analysis) ; Library science ; Art history ; Art ; Materials science ; Engineering ; Composite material ; Computer science Microstructure and mechanical properties ; Aluminum Alloys Composites Properties ; Nanofabrication and Lithography Techniques
Authors: И.С. Зорин | Sergey A. Lisakov | A. I. Sidorenko | Е.В. Сыпин
Source: Южно-Сибирский научный вестник (article, 2019-12-20)
Field: Chemistry — Spectroscopy

Разработка и испытания экспериментального образца многокритериального оптико-электронного прибора контроля аварийных и предаварийных ситуаций в угольных шахтах Выполнена разработка экспериментального образца многокритериального оптико-электронного прибора (МКОЭП) контроля аварийных и предаварийных ситуаций в угольных шахтах. Разработана структурная схема и выбрана элементная база для изготовления экспериментального образца МКОЭП. Выполнено проектирование и изготовление экспериментального образца МКОЭП. Разработаны методики калибровки оптико-электронных датчиков концентрации контролируемых газов (CH4, CO2, CO) и угольной пыли, входящих в состав МКОЭП. Получены калибровочные коэффициенты поглощения для контролируемых газов и угольной пыли. Проведены испытания экспериментального образца МКОЭП подтверждающие возможность обнаружения аварийных ситуаций пламенного горения газовоздушной смеси и тления угольной пыли. The development of an experimental sample of a multicriteria optical-electronic device (MCEOD) for the control of emergency and pre-emergency situations in coal mines was carried out. The structural scheme of the experimental sample MCEOD was developed. Element base for MCEOD manufacture was chosen. The design and manufacture of the experimental model MCEOD was performed. Methods for calibrating electro-optical sensors for the concentration of monitored gases (CH4, CO2, CO) and coal dust that are part of MCEOD have been developed. Calibration absorption coefficients for controlled gases and coal dust were obtained. Tests of experimental sample MCEOD were conducted. The test results confirm the possibility of detecting emergency situations the flame combustion of the gas-air mixture and the smoldering of coal dust. Computer science Spectroscopy and Laser Applications ; Advanced Power Generation Technologies ; Industrial Engineering and Technologies
Authors: M.S. Roobini | M. Lakshmi | Ahmed Naeem | Velo Qureshi | Habibullah Suthar | Muhammad Magsi | Mubeena Sheikh | Barkatullah Pathan | Qureshi | A Dinu | Felix Ganesan | Balaji Joseph | Dr | Vidhyavathi | Dibyadeep Nandi | Amira Ashour | * | Sourav Samanta | Sayan Chakraborty | Mohammed Salem | Nilanjan Dey | Mohamed Dessouky | Mohamed Elrashidy | Taha Taha | M Hatem | Abdelkader | Srimanip | A Caprihan | G Pearlson | V Calhoun | A Association
Source: International Journal of Recent Technology and Engineering (IJRTE) (article, 2019-08-10)
Field: Chemistry — Analytical Chemistry

Advancement of Principal Component Judgment for the Classification and Prediction of Alzheimer’s Disease Alzheimer is a dynamic issue of dementia, which deals with mind issue that assaults synapses, cerebrum cells, and nerves, memory, and practices and afterward finally causing dementia on old individuals. In spite of its significance, there is at present no remedy for it. In any case, there are drugs accessible on remedy that can help defer the advancement of the condition. Principal Component Analysis is an incredible system to recognize the examples of vast informational indexes, offers an in vogue factual strategy to dissect multivariate information by building a brief information portrayal utilizing the predominant Eigen vectors of the information covariance lattice. Along these lines, early conclusion of AD is basic for patient consideration and pertinent examines. In this paper, we have assessed a calculation utilizing Principal Component Analysis for its application in information investigation. In the exploration field, it is exceptionally hard to comprehend the expansive measure of information and is very tedious as well. In this way, so as to maintain a strategic distance from wastage of time and for the simplicity in understanding we have examined a PCA calculation that can diminish the gigantic component of the information. Principal Component Analysis (PCA) has been utilized in this paper to locate the base number of credits to improve the classifiers for quicker execution, cost-adequacy and precision. The strategy for PCA is utilized to pack the greatest measure of data into initial two sections of the changed lattice known as the vital parts by ignoring alternate vectors that conveys the immaterial data or repetitive information. Utilizing PCA we expect to locate the important highlights of the informational indexes. This paper proposes a system for forecast of Alzheimer sickness by discovering the most critical highlights important to Alzheimer Disease and furthermore different therapeutic picture application-based PCA results are displayed to demonstrate its productivity Principal component analysis ; Expansive ; Computer science ; Dementia ; Artificial intelligence ; Component (thermodynamics) ; Principal (computer security) ; Machine learning ; Field (mathematics) ; Data mining ; Pattern recognition (psychology) ; Data science ; Disease ; Mathematics ; Medicine ; Computer security Spectroscopy and Chemometric Analyses
Authors: Adrien Dolimont | François Ducobu | Clément Dutoit
Source: ORBi UMONS (article, 2019-05-01)
Field: Materials Science — Polymers and Plastics

Les composites participent à l'allègement du véhicule pour le concours Shell Eco-Marathon Shell (structure) ; Deformation (meteorology) ; Compression (physics) ; Process (computing) Polymer Nanocomposites and Properties ; Fiber-reinforced polymer composites ; Microplastics and Plastic Pollution
Authors: Angus I. Lamond | Alejandro Brenes Murillo
Source: Faculty of 1000 Research Ltd (article, 2019-01-01)
Field: Chemistry — Spectroscopy

Referee report. For: A Bioconductor workflow for the Bayesian analysis of spatial proteomics [version 1; peer review: 1 approved, 2 approved with reservations] Workflow ; Bayesian probability ; Bioconductor ; Spatial analysis Advanced Proteomics Techniques and Applications ; Advanced Biosensing Techniques and Applications ; Cell Image Analysis Techniques
Authors: Pierre M. Jean Beltran
Source: Faculty of 1000 Research Ltd (article, 2019-01-01)
Field: Chemistry — Spectroscopy

Referee report. For: A Bioconductor workflow for the Bayesian analysis of spatial proteomics [version 1; peer review: 1 approved with reservations] Workflow ; Bayesian probability ; Bioconductor ; Spatial analysis Advanced Proteomics Techniques and Applications ; Advanced Biosensing Techniques and Applications ; Single-cell and spatial transcriptomics
Authors: Rayssa Renata Correa Pojo | JEDSON LOBATO DOS SANTOS
Source: Blucher Chemical Engineering Proceedings (article, 2019-08-01)
Field: Chemistry — Analytical Chemistry

MODELAGEM DA INTERFACE DE LICOR CLARIFICADO DOS DECANTADORES DE LAMA DO PROCESSO BAYER COM AJUSTE DE PARÂMETROS USANDO SOMA ACUMULADA (CUSUM) medem claridade do licor no overflow, pode-se gerar modelo de altura da zona de interface de licor clarificado em conjunto com tcnica estatstica de soma acumulada, obtendo um modelo ajustado que representa a resposta do processo de floculao. Humanities ; Art Dye analysis and toxicity
Authors: Qianqian Shan
Source: Iowa State University Digital Repository (Iowa State University) (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Topics in recurrent event prediction with generalized non-homogeneous Poisson process (NHPP) and electronic circuit troubleshooting with Bayesian inference This dissertation consists of three projects focused on seasonal recurrent event prediction, electronic circuit troubleshooting and the development of an open source software, RSpice, respectively. Big challenges when making recurrent event prediction include (1) the recurrent event rate may show a seasonal pattern and the pattern may also be affected by locations; (2) individual level variabilities can also affect the recurrent event rate. We present a general methodology to solve these challenges by using hierarchical clustering for the seasonal patterns and introducing random effects into our models. These help us in improving both the model fitting and prediction performance. This work is illustrated with two motivating product warranty applications in Chapter 2. Electronic circuits are widely used in industry, and the troubleshooting process of an electronic circuit based on previous experience may suggest a replacement of the whole circuit or some components, however, the failure of the circuit may just due to a less number of specific electronic components. The unnecessary removal of components can increase the costs significantly. Motivated by finding a more precise and faster troubleshooting procedure based on limited data, we propose the use of data simulation and Bayesian inference in circuit troubleshooting in Chapter 3. In the third project (Chapter 4), we address challenges that arise when doing data simulation and Bayesian inference in the second project (Chapter 3). In order to do exploratory analysis of an electronic circuit and make inference on which specific electronic components cause the failure of a circuit, we need to use a circuit simulator, ngspice, to generate the response (e.g., voltage values\nat specified nodes of a circuit) given the circuit setup. We also need to ensure that the component values generated by Bayesian inference algorithm can be passed to the circuit simulator and the output from the circuit simulator can be passed back to the algorithm for evaluation interactively. We present our work of writing an R package called RSpice to accomplish the above tasks. Troubleshooting ; Event (particle physics) ; Computer science ; Inference ; Bayesian probability ; Bayesian inference ; Homogeneous ; Poisson process ; Process (computing) ; Artificial intelligence ; Data mining ; Poisson distribution ; Machine learning ; Statistics ; Mathematics ; Combinatorics ; Programming language Machine Learning in Materials Science ; Software Engineering Research
Authors: Arzu YAVAŞCAOĞLU | Recep Eren | Gülcan Süle
Source: Gazi Üniversitesi Fen Bilimleri Dergisi Part C Tasarım ve Teknoloji (article, 2019-06-11)
Field: Materials Science — Polymers and Plastics

Atkı İplik Numarası, Atkı Sıklığı ve Örgü Tipinin %100 Akrilik Dokuma Kumaşların Hava ve Su Buharı Geçirgenliğine Etkisi Bu çalışmada %100 akrilik dokuma kumaşların hava ve su buharı geçirgenliği özelliklerine atkı iplik numarası, atkı sıklığı ve örgü tipi değişiminin etkisi incelenmiş ve istatistiksel olarak değerlendirilmiştir. Çalışmada iki farklı numara atkı ipliği ile üç farklı örgüde kumaş üretilerek iplik numarası ve örgü tipi değişiminin etkisi, bezayağı örgülü kumaş yapılarında ise 3 farklı atkı sıklığı kullanılarak atkı sıklığı değişiminin etkisi değerlendirilmiştir. Çalışma sonucuna göre, akrilik dokuma kumaşlarda atkı sıklığı arttıkça hava ve su buharı geçirgenliği azalmaktadır. Bezayağı örgünün hava geçirgenliği dimi ve saten örgülü kumaş yapılarına göre daha düşük bulunmuştur. Kalın atkı ipliği kullanılan kumaşlarda daha yüksek su buharı geçirgenliği elde edilmiştir. Physics ; Materials science Textile materials and evaluations ; Dyeing and Modifying Textile Fibers ; Natural Fiber Reinforced Composites
Authors: Mohammed Amine Benjira
Source: Le dépôt institutionnel (Université du Québec à Trois-Rivières) (article, 2019-01-01)
Field: Materials Science — Biomaterials

Classification automatique des diatomées une partie importante de ce mmoire ou de cette thse requiert son autorisation. Geology ; Diatom ; Computer science ; Oceanography Diatoms and Algae Research
Authors: Jiayue Xu
Source: cIRcle (University of British Columbia) (article, 2019-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Parameters estimation based on recursive extended least-squares method in dc distribution systems and interior permanent magnet synchronous motors Adaptive control is widely used in modern control systems to maintain optimal system performance when the plant parameters are unknown and/or varying with time. Various system identification methods have been developed to estimate the system parameters in real time, which allows a parameter-related adaptive controller to be accordingly calibrated under parameter variation conditions. In this thesis, two practical applications of online parameters estimation are introduced: one the online source impedance identification for self-stabilizing controller design in dc distribution systems; and the adaptive controller design in interior permanent magnet synchronous motor (IPMSM) drive systems. In dc distribution systems, the parameters of source impedances are crucial for load controller design to guarantee the stability of source-load interface. Since the source impedance may vary when the system configuration changes, the online impedance estimation is necessary for designing advanced self-stabilizing controllers with “plug-n-play” functionality. In this thesis, an innovative technique is proposed for parametric estimation of source impedance using the recursive extended least-squares (RELS) method in conjunction with impulse and pseudo-random binary sequence (PRBS) injections. Rigorous simulation studies demonstrate that the proposed technique yields direct results while providing advantages over traditional ac sweep and commonly used discrete Fourier transform (DFT) techniques. To further verify the feasibility of the proposed method in the real-time environment, the proposed online parameters estimator is implemented and validated on the Typhoon and Opal-RT hardware-in-the-loop (HIL) platform. Moreover, the proposed methodology is extended to parameter-estimation-based adaptive control to mitigate the impact of parameter variations on the maximum torque per ampere (MTPA) operation of IPMSM drive systems. Specifically, a parameter estimator that exploits the RELS algorithm is established to accurately estimate the main parameters of the machine in real time, which enables calibration of the optimal current vector angle that is critical in the MTPA operation of IPMSMs. Extensive simulation studies have been carried out to verify the effectiveness and robustness of the proposed strategy. Synchronous motor ; Control theory (sociology) ; Permanent magnet synchronous generator ; DC motor ; Permanent magnet synchronous motor ; Distribution (mathematics) ; Magnet ; Recursive least squares filter ; Least-squares function approximation ; Mathematics ; Computer science ; Engineering ; Algorithm ; Mathematical analysis ; Electrical engineering ; Statistics ; Artificial intelligence Magnetic Properties and Applications ; Electric Motor Design and Analysis ; Sensorless Control of Electric Motors
Authors: Akimitsu Ishii | Akinori Yamanaka | Yuki Okada | Akiyasu Yamamoto
Source: Keisan Rikigaku Koenkai koen ronbunshu/Keisan Rikigaku Kouenkai kouen rombunshuu (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Three-dimensional phase-field simulation of microstructure formation during solid-state sintering in polycrystalline superconducting materials In order to improve the electrical performances of polycrystalline bulk superconducting materials, which are attracting much attention for several applications, we need to control the polycrystalline microstructure formed by the solid-state sintering. Although some numerical simulation models based on the phase-field (PF) method have been proposed to reveal the microstructural evolution in the solid-state sintering, very few experimental verifications of the simulation results have been reported. The purpose of this study is to carry out the experimental verification of the PF simulation results of the solid-state sintering in polycrystalline bulk superconducting materials. For the quantitative comparison between the simulation and experimental results, we perform three-dimensional PF simulations of the solidstate sintering including many particles. In this article, we report the PF simulation with parallel computing using Message Passing Interface (MPI) library to reduce the computation time. The results of the simulation demonstrate that the simulation results comparable to the experimental results can be obtained by the PF model, since the PF model can analyze three-dimensional rigid motion and grain boundary formation in the solid-state sintering. Sintering ; Materials science ; Microstructure ; Crystallite ; Superconductivity ; Computation ; Grain boundary ; Phase (matter) ; Solid-state ; Computer simulation ; Field (mathematics) ; Mechanics ; Composite material ; Mechanical engineering ; Simulation ; Computer science ; Engineering physics ; Condensed matter physics ; Metallurgy ; Physics ; Engineering Solidification and crystal growth phenomena ; Metallurgy and Material Forming ; Powder Metallurgy Techniques and Materials
Authors: Alvin Noe Ladines | Thomas Hammerschmidt | Ralf Drautz
Source: Computational Materials Science (preprint, 2019-12-10)
Field: Materials Science — Materials Chemistry

BOPcat software package for the construction and testing of tight-binding models and bond-order potentials Tight binding ; Computer science ; Software ; Modular design ; Software package ; Computational science ; Set (abstract data type) ; Graphical user interface ; Programming language ; Chemistry ; Electronic structure ; Computational chemistry Microstructure and mechanical properties ; Machine Learning in Materials Science ; Microstructure and Mechanical Properties of Steels
Authors: Alvin Noe Ladines | Thomas Hammerschmidt | Ralf Drautz
Source: arXiv (Cornell University) (preprint, 2019-07-29)
Field: Materials Science — Materials Chemistry

BOPcat software package for the construction and testing of\n tight-binding models and bond-order potentials Atomistic models like tight-binding (TB), bond-order potentials (BOP) and\nclassical potentials describe the interatomic interaction in terms of\nmathematical functions with parameters that need to be adjusted for a\nparticular material. The procedures for constructing TB/BOP models differ from\nthe ones for classical potentials. We developed the BOPcat software package as\na modular python code for the construction and testing of TB/BOP\nparameterizations. It makes use of atomic energies, forces and stresses\nobtained by TB/BOP calculations with the BOPfox software package. It provides a\ngraphical user interface and flexible control of raw reference data, of derived\nreference data like defect energies, of automated construction and testing\nprotocols, and of parallel execution in queuing systems. We outline the\nconcepts and usage of the BOPcat software and illustrate its key capabilities\nby exemplary constructing and testing of an analytic BOP for Fe. The\nparameterization protocol with a successively increasing set of reference data\nleads to a magnetic BOP that is transferable to a variety of properties of the\nferromagnetic bcc groundstate and to crystal structures that were not part of\nthe training set.\n Tight binding ; Computer science ; Software ; Modular design ; Software package ; Computational science ; Set (abstract data type) ; Graphical user interface ; Python (programming language) ; Theoretical computer science ; Programming language ; Chemistry ; Electronic structure ; Computational chemistry Microstructure and mechanical properties ; Machine Learning in Materials Science ; Microstructure and Mechanical Properties of Steels