Various techniques have been developed for the identification of different types of requirements like interview, questionnaire, group elicitation techniques, attributed goal-oriented requirements analysis, fuzzy based...
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Solution counting and solution space integration over linear constraints are important problems with many applications. Previous works addressed either only counting integer points in polytopes (integer counting) with...
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This paper introduces the Yet Another Kernel Launcher (YAKL) C++ portability library, which strives to enable user-level code with the look and feel of Fortran code. The intended audience includes both C++ developers ...
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Deep learning (DL) techniques hold immense promise for revolutionizing medical diagnostics, including brain tumor detection. Detecting malignancies in the brain is fraught with challenges that carry critical implicati...
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Continuity and steadiness are vital for services with massive users, which requires the anomalies of services should be detected and resolved in a timely manner. Our previous work proposed a tool, namely ImpAPTr (Impa...
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Continuity and steadiness are vital for services with massive users, which requires the anomalies of services should be detected and resolved in a timely manner. Our previous work proposed a tool, namely ImpAPTr (Impact Analysis based on Pruning Tree), to identify the combination of multiple dimensional attributes as the clues leading to the root cause of service anomalies. However, ImpAPTr applies a threshold driven strategy, i.e., it needs to be triggered by a = 0:05% drop of the success rate of the service calls (abbr. SRSC), which may face problems in an atypical yet pervasive situation in field application. For example, the combination of trivial anomalies (i.e., each causes a drop less than 0.05% to SRSC) can lead to a far more than 0.05% drop on SRSC. Besides, a suitable threshold is usually hard to be determined, etc. To address these problems, we propose a new method, namely ImpAPTr+ in this paper to free the constraint of the 0.05% threshold. The basic idea is to involve time dimension and identify clues across multiple time intervals of data. We performed evaluation on three typical methods (i.e., ImpAPTr+, RAdtributor and Squeeze) with both production environment dataset and simulation dataset. The former dataset is directly retrieved from the service monitoring data in Meituan, one of the largest on-line service providers worldwide. The latter dataset is fabricated also using the monitoring data from the same company. The results indicate: (1) ImpAPTr+ outperforms previous approaches to a large degree in terms of accuracy. (2) Both ImpAPTr+ and R-Adtributor are able to find proper clues within seconds. (3) ImpAPTr+ tends to find proper clues with shorter time intervals (i.e., less data), which implies that the method is more suitable for near realtime monitoring scenarios.
Automated Teller Machines (ATM) are critical to banking operations due to their convenient and widespread use. Apart from queues reduced in banking halls, bank clients can still access services outside the regular ope...
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Intelligent traffic signal control plays a crucial role in reducing the escalating problem of traffic congestion. However, traditional methods of traffic signal control struggle to effectively adapt to the ever-changi...
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Cooperative multi-agent reinforcement learning (Co-MARL) commonly employs different parameter sharing mechanisms, such as full and partial sharing. However, imprudent application of these mechanisms can potentially co...
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The integration of machine learning (ML) algorithms in healthcare is transforming diagnostics, treatment planning, and patient management. However, the complexity and diversity of these algorithms, coupled with hetero...
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Microservices architecture is a promising approach for developing reusable scientific workflow capabilities for integrating diverse resources, such as experimental and observational instruments and advanced computatio...
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ISBN:
(纸本)9798350355543
Microservices architecture is a promising approach for developing reusable scientific workflow capabilities for integrating diverse resources, such as experimental and observational instruments and advanced computational and data management systems, across many distributed organizations and facilities. In this paper, we describe how the INTERSECT Open Architecture leverages federated systems of microservices to construct interconnected science ecosystems, review how the INTERSECT software development kit eases microservice capability development, and demonstrate the use of such capabilities for deploying an example multi-facility INTERSECT ecosystem.
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