The operation of multi robots has been a much-debated topic due to its potential to be applied in many different business sectors. Incheon International Airport is not an exception and we have been introducing a varie...
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ISBN:
(数字)9788993215380
ISBN:
(纸本)9798331517939
The operation of multi robots has been a much-debated topic due to its potential to be applied in many different business sectors. Incheon International Airport is not an exception and we have been introducing a variety of robots to assist in airport operations and passenger experience. However, every new robot we bring to the airport leads us to implement a whole new system that monitors and manages the robot. To solve this issue, we have constructed a functional model for a multi-robot control system. Based on the model, the entire process in which multi robots collaboratively synchronize their maps, analyze the context data, and finally generate and allocate collaborative tasks is specified. Incheon Airport aims to further build upon the proposed model and eventually develop a centralized multi-robot control system that can essentially unify the data format, functions and task specifications for robots from multi-vendors.
The proceedings contain 281 papers. The topics discussed include: a semantic data framework to support data-driven demand forecasting;identification of influential factors for combined energy consumption and indoor en...
The proceedings contain 281 papers. The topics discussed include: a semantic data framework to support data-driven demand forecasting;identification of influential factors for combined energy consumption and indoor environmental quality in residential buildings;thermochemical storage networks for integration of renewable energy sources through seasonal load shifting;value stacking flexibility services in neighborhoods participating in fast frequency reserve markets;next generation of heat pumps for buildings based on thermoelectricity integrated with smart grids;performance analysis and optimization of a solar assisted heat pump concept;the more the better? archetype segmentation in urban building energy modeling;towards sustainable energy consumption for occupants of buildings with collective heating systems;estimating perceived indoor air quality and environmental satisfaction using a camera;the potential of switchable glazing in cooling dominated climates;and influence of building geometry on the environmental impact of building structures.
The proceedings contain 34 papers. The topics discussed include: power insulator defect detection based on multi-scale dense adaptive sensing;abnormal line loss identification of distributed PV low-voltage distributio...
The proceedings contain 34 papers. The topics discussed include: power insulator defect detection based on multi-scale dense adaptive sensing;abnormal line loss identification of distributed PV low-voltage distribution area based on data driven;an improved optimal tracking rotor algorithm of wind turbine based on dynamic adjustment of compensation coefficient;flexible adaptive integrated compensation strategy for voltage sag;control strategy of three-level active neutral point clamped grid connected inverters in unbalanced power grid;analysis of minimum rotational inertia requirements for power system frequency stability;a fault diagnosis approach for wind turbine gearbox based on ensemble learning model and dung beetle optimization algorithm;power-impact-harmonic characteristics analysis and modeling of diversified power loads in urban power grid;and transmission section search method based on variable scale nearest neighbor propagation clustering.
Last December 2019, health officials in Wuhan, a province from China, identified a novel coronavirus called SARS-CoV-2 causing pneumonia. In March 2020, World Health Organization (WHO) declared COVID-19 disease being ...
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The oil stored in oil depot storage tanks is flammable, explosive and easy to diffuse, once a fire and explosion accident occurs, it will cause heavy losses. In this paper, the fire and explosion accidents in oil stor...
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The 18O Oxygen Isotope Separation process is critical for various scientific, industrial, and medical applications, including climate research and biomedical studies. Given the high value and sensitivity of isotopic m...
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With the rapid development of the social economy, various industries' water consumption is growing rapidly, and the sewage discharge is also increasing. This paper studies the modeling of the water quality of the ...
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This paper conducts fundamental research to apply several widely used data-driven models to automate the quality inspection of Tempcore-processed steel rebar and design a prediction model for rebar mechanical properti...
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Real world control systems are often of a highly nonlinear nature. Thus, modeling and controlling such systems comes with many challenges. One of them is that analytical descriptions of effects like friction and hyste...
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With the widespread application of single-cell RNA sequencing technology, integrating different batches of data has become a crucial step. Batch effects arise from non-biological variations such as different sequencin...
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ISBN:
(纸本)9789819756919;9789819756926
With the widespread application of single-cell RNA sequencing technology, integrating different batches of data has become a crucial step. Batch effects arise from non-biological variations such as different sequencing batches, sequencing protocols, sequencing depths, and so on. Batch effects introduce systematic biases and confound biological variations of interest, which have a detrimental impact on the validity of study findings. Eliminating batch effects can increase comparability and repeatability, prevent bias and confusion, and improve data quality and consistency. Currently, a great deal of batch effect removal techniques for single-cell transcriptome data has been developed based on finding mutual nearest neighbors (MNNs) across batches, the accuracy of which influences greatly the effect of data correction and the subsequent integrative analysis. To enhance the identification of MNNs, we propose an iterative integration method, called iEMNN, for single-cell transcriptome data by utilizing network similarity enhancement. iEMNN facilitates the detection of similar cells while separating distinct cells. iEMNN applies multiple iterations to improve the effectiveness of the integration process and can perform data correction in both high-dimensional and low-dimensional spaces. Through systematic experiments and comparisons with the existing methods, we demonstrate that iEMNN outperforms other approaches in improving batch correction removal and enhancing clustering performance across different scenarios. This study provides a new perspective and an effective solution for the field of single-cell transcriptomic data integration, with potential significance for a deeper understanding of cellular heterogeneity and dynamic changes.
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