This paper presents a novel methodology for applying process mining techniques to an unstructured call log dataset, CallcenterExample. csv. The dataset, which has been simplified and anonymized to preserve confidentia...
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In June 2022, the Ministry of Public Health of Thailand announced that cannabis can be used in healthcare, medical, research, and commerce. This announcement led to a wide discussion in social media, TV broadcasts, an...
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This paper presents the development and validation of a Unified Modeling Language (UML) Activity Diagram for diagnosing Central Line-Associated Bloodstream Infections (CLABSIs) based on guidelines from the Centers for...
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With the increasing popularity of energy big data platforms, their security problems of insider threats have attracted a lot of attentions. Abnormal behavior detection based on user digital profiles is an effective wa...
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knowledge graph (KG) reasoning is becoming increasingly popular in both academia and industry. Conventional KG reasoning based on symbolic logic is deterministic, with reasoning results being explainable, while modern...
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The growing demand for efficient code generation has driven research into improving Large Language Models (LLMs). This project presents a novel system designed to enhance code generation by leveraging Retrieval-Augmen...
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Measuring heart rate is essential for evaluating a patient's health status. Non-contact heart rate measurement offers numerous advantages across various sectors, including medicine, hospital care, and sports, and ...
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The proceedings contain 185 papers. The topics discussed include: the evolution of original ERP customization: a systematic literature review of technical possibilities;data-driven process analysis of logistics system...
ISBN:
(纸本)9789897586927
The proceedings contain 185 papers. The topics discussed include: the evolution of original ERP customization: a systematic literature review of technical possibilities;data-driven process analysis of logistics systems: implementation process of a knowledge-based approach;a performance analysis for efficient schema design in cloud-based distributed data warehouses;quantitative analysis of the relationship between master data quality and process quality;analyzing sepsis treatment variations in subpopulations with process mining;balancing autonomy and control: an adaptive approach for security governance in large-scale agile development;project management in large-scale with international settings: challenges faced with multiculturalism;on the integration of privacy-enhancing technologies in the process of softwareengineering;and software engineers engagement and job satisfaction: a survey with practitioners working remotely in a public organization.
There has been a growing number of software supply chain vulnerabilities disclosed annually, posing increasingly formidable challenges to vulnerability validation. Timely validation plays a critical role in mitigating...
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In the realm of online portfolio selection, aggregating multiple experts is crucial for improving investment decisions in complex market conditions. However, existing methods often overlook two essential factors: expe...
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ISBN:
(数字)9789819754892
ISBN:
(纸本)9789819754885;9789819754892
In the realm of online portfolio selection, aggregating multiple experts is crucial for improving investment decisions in complex market conditions. However, existing methods often overlook two essential factors: expert diversity and adaptive expert selection, both of which significantly impact portfolio returns. To address these issues, this paper proposes a novel multiple experts portfolio selection method based on genetic algorithm (GA-MEPS). This method (i) introduces a portfolio trend tracking problem with closed-form sparse solutions, enabling optimal selection among assets within a unified framework;(ii) constructs a pool of 24 experts, each characterized by distinct trading behaviors;and (iii) designs a fitness function to enable efficient adaptive expert selection based on genetic algorithm. Extensive experiments on six datasets demonstrate GA-MEPS's superior performance over six competitive algorithms, achieving average cumulative wealth and Calmar ratio that are 4.17E+09 and 5.55 times higher, respectively, compared to the benchmark buy-and-hold strategy.
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