1,059 research outputs found
3E: Energy-Efficient Elastic Scheduling for Independent Tasks in Heterogeneous Computing Systems
Reducing energy consumption is a major design constraint for modern heterogeneous computing systems to minimize electricity cost, improve system reliability and protect environment. Conventional energy-efficient scheduling strategies developed on these systems do not sufficiently exploit the system elasticity and adaptability for maximum energy savings, and do not simultaneously take account of user expected finish time. In this paper, we develop a novel scheduling strategy named energy-efficient elastic (3E) scheduling for aperiodic, independent and non-real-time tasks with user expected finish times on DVFS-enabled heterogeneous computing systems. The 3E strategy adjusts processors’ supply voltages and frequencies according to the system workload, and makes trade-offs between energy consumption and user expected finish times. Compared with other energy-efficient strategies, 3E significantly improves the scheduling quality and effectively enhances the system elasticity
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series
Decomposing complex time series into trend, seasonality, and remainder
components is an important task to facilitate time series anomaly detection and
forecasting. Although numerous methods have been proposed, there are still many
time series characteristics exhibiting in real-world data which are not
addressed properly, including 1) ability to handle seasonality fluctuation and
shift, and abrupt change in trend and reminder; 2) robustness on data with
anomalies; 3) applicability on time series with long seasonality period. In the
paper, we propose a novel and generic time series decomposition algorithm to
address these challenges. Specifically, we extract the trend component robustly
by solving a regression problem using the least absolute deviations loss with
sparse regularization. Based on the extracted trend, we apply the the non-local
seasonal filtering to extract the seasonality component. This process is
repeated until accurate decomposition is obtained. Experiments on different
synthetic and real-world time series datasets demonstrate that our method
outperforms existing solutions.Comment: Accepted to the thirty-third AAAI Conference on Artificial
Intelligence (AAAI 2019), 9 pages, 5 figure
Deformational Mechanism and Tectonic Evolution of Mesozoic-Cenozoic Nonmarine Basins from Bohai Bay Basin - China
Bohai Bay Basin,China, is a rift basin developed in Mesozoic-Cenozoic time span.
It was compressionally deformed during Caledonian Orogeny and situated on a Paleozoic platform
“old craton” basement and later subjected to extensional stress and induced major strike-slip
(wrench) fault. The basin opening transpired on a series of half-grabens trending NNE-SSW in
Bohai Bay Basin zone. Models for deformational mechanism and evolution of the Bohai Bay Basin,
China, and its tectonic and stratigraphic history were proposed. Two separate scenarios were set for
the evolution of Bohai Bay Basin: the first is based on the changes in plate convergence rates along
the eastern plate boundary of Eurasia/ Pacific plates which have additional role in the extensional
skin of Bohai Bay Basin in certain stage of extension or rifting and the second is a model of three
major incidents of extensional tectonism: basement pre-rifting, a syn-rift stage, and a post-rift sag
stage were documented for Bohai Bay Basin. The major factor controlling the lacustrine basins is
global eustasy; however, the role of global tectonic played a significant control mechanism in the
evolution and development of Bohai Bay Basin
A novel optimization method on logistics operation for warehouse & port enterprises based on game theory
Purpose: The following investigation aims to deal with the competitive relationship among different warehouses & ports in the same company.
Design/methodology/approach: In this paper, Game Theory is used in carrying out the optimization model. Genetic Algorithm is used to solve the model.
Findings: Unnecessary competition will rise up if there is little internal communication among different warehouses & ports in one company. This paper carries out a novel optimization method on warehouse & port logistics operation model.
Originality/value: Warehouse logistics business is a combination of warehousing services and terminal services which is provided by port logistics through the existing port infrastructure on the basis of a port. The newly proposed method can help to optimize logistics operation model for warehouse & port enterprises effectively. We set Sinotrans Guangdong Company as an example to illustrate the newly proposed method. Finally, according to the case study, this paper gives some responses and suggestions on logistics operation in Sinotrans Guangdong warehouse & port for its future development.Peer Reviewe
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