Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing
نویسندگان
چکیده
Accelerating Materials Development via Automation, Machine Learning, and HighPerformance Computing Juan Pablo Correa-Baena1, Kedar Hippalgaonkar2, Jeroen van Duren3, Shaffiq Jaffer4, Vijay R. Chandrasekhar5, Vladan Stevanovic6, Cyrus Wadia7, Supratik Guha8, Tonio Buonassisi1* 1Massachusetts Institute of Technology, Cambridge, MA 02139, USA 2Institute of Materials Research and Engineering (IMRE), A*STAR (Agency for Science, Technology and Research), Innovis, Singapore 3Intermolecular Inc., San Jose, CA 95134, USA 4TOTAL American Services, Inc., 82 South Street, Hopkington, MA 01748, USA 5Institute for Infocomm Research (I2R), A*STAR (Agency for Science, Technology and Research), #2101 Connexis (South Tower), Singapore 6Colorado School of Mines, Golden, CO 80401, USA 7Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA 8Center for Nanoscale Materials, Argonne National Laboratory, Argonne, IL 60439, USA *Corresponding author: Tonio Buonassisi, [email protected]
منابع مشابه
IoT based Agro Automation System using Machine Learning Algorithms
The needs and necessities of an agro automation system in large scale applications for monitoring various parameters are on a rise. The overview of all core challenges faced by the farmers can highly be overcome with the proposed 'IoT based Agro Automation System using Machine Learning Algorithms' which is established through multiple sensor fusion with the affirmation of results in a hybrid ap...
متن کاملCloud Computing; A New Approach to Learning and Learning
Introduction: The cloud computing and services, as a technological solution for developing educational services, can accelerate the provision and expansion of these highly useful services. This study intended to provide an overall picture of practical areas of learning services based on cloud computing teaching and learning equipment. Methods: This was a theoretical hybrid research study in whi...
متن کاملAssessment Methodology for Anomaly-Based Intrusion Detection in Cloud Computing
Cloud computing has become an attractive target for attackers as the mainstream technologies in the cloud, such as the virtualization and multitenancy, permit multiple users to utilize the same physical resource, thereby posing the so-called problem of internal facing security. Moreover, the traditional network-based intrusion detection systems (IDSs) are ineffective to be deployed in the cloud...
متن کاملImage Classification via Sparse Representation and Subspace Alignment
Image representation is a crucial problem in image processing where there exist many low-level representations of image, i.e., SIFT, HOG and so on. But there is a missing link across low-level and high-level semantic representations. In fact, traditional machine learning approaches, e.g., non-negative matrix factorization, sparse representation and principle component analysis are employed to d...
متن کاملAutomatic Face Recognition via Local Directional Patterns
Automatic facial recognition has many potential applications in different areas of humancomputer interaction. However, they are not yet fully realized due to the lack of an effectivefacial feature descriptor. In this paper, we present a new appearance based feature descriptor,the local directional pattern (LDP), to represent facial geometry and analyze its performance inrecognition. An LDP feat...
متن کامل