Results 31 to 40 of about 35,060 (262)
Sensors, 2023 Traditional parallel computing for power management systems has prime challenges such as execution time, computational complexity, and efficiency like process time and delays in power system condition monitoring, particularly consumer power consumption ...
Ahmed Hadi Ali AL-Jumaili +4 more
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New Benchmarking Methodology and Programming Model for Big Data Processing
International Journal of Distributed Sensor Networks, 2015 Big data processing is becoming a reality in numerous real-world applications. With the emergence of new data intensive technologies and increasing amounts of data, new computing concepts are needed.
Anton Kos +5 more
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Applied SciencesThe increasing complexity of conventional energy distribution systems, combined with the growing demand for efficient data processing, has necessitated the implementation of smart grid technologies and the integration of advanced computing paradigms such
Fatma Yıldırım +3 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen +23 more
wiley +1 more source
instancespace: A Python package for insightful algorithm testing through Instance Space Analysis
SoftwareXInstance Space Analysis is a methodology to evaluate algorithm performance across diverse problem fields. Through visualisation and exploratory data analysis techniques, Instance Space Analysis offers objective, data-driven insights into the diversity of
Yusuf Berdan Güzel +7 more
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Smart Adaptive Big Data Analysis with Advanced Deep Learning
Open Engineering, 2018 Increasing volumes of data, referred as big data, require massive scale and complex computing. Artificial intelligence, deep learning, internet of things and cloud computing are proposed for heterogeneous datasets in hierarchical analytics to manage with
Juuso Esko K.
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Multi-Objective Application-Driven Approximate Design Method
IEEE Access, 2021 Approximate Computing (AxC) paradigm aims at designing computing systems that can satisfy the rising performance demands and improve the energy efficiency. AxC exploits the gap between the level of accuracy required by the users, and the actual precision
Salvatore Barone +3 more
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Performance forecasting: towards a methodology for characterizing large computational applications [PDF]
Proceedings. 1998 International Conference on Parallel Processing (Cat. No.98EX205), 2002 We present a methodology that can identify and formulate performance characteristics of a computational application and uncover program performance trends on very large, future computer architectures and problem sizes. Based on this methodology we present "performance forecast diagrams" that predict the scalability of a large seismology application ...
Brian Armstrong, Rudolf Eigenmann
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Central nervous system (CNS) involvement in childhood acute lymphoblastic leukemia (ALL) is assessed by cell counting and cytomorphology from cerebrospinal fluid (CSF) and is used for treatment stratification worldwide. The ratio of “CNS2” patients in clinical trials ranges from 3% to 40%, with unclear prognostic significance ...
Laura Almási +14 more
wiley +1 more source
IEEE AccessAffective computing, as its name implies, focuses on the recognition of human emotions, sentiments, and feelings. This interdisciplinary field encompasses diverse areas such as languages, sociology, psychology, computer science, and physiology.
Sitara Afzal +3 more
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