Reduce API Debugging Overhead via Knowledge Prepositioning

OpenAPI indicates a behavior where producers offer Application Programming Interfaces (APIs) to help end-users access their data, resources, and services. Generally, API has many parameters that need to be entered. However, it is challenging for users to understand and document these parameters correctly. This paper develops an API workbench to help users learn and debug APIs. Based on this workbench, much exploratory work has been proposed to reduce the overhead of learning and debugging APIs. We explore the knowledge, such as parameter characteristics (e.g., enumerability) and constraints (e.g., maximum/minimum value), from the massive API call logs to narrow the range of parameter values. Then, we propose a fine-grained approach to enrich the API documentation by extracting dependency knowledge between APIs. Finally, we present a learning-based prediction method to predict API execution results before the API is called, significantly reducing user debugging cycles. The experiments evaluated on the online system show that this work's approach substantially improves the user experience of debugging OpenAPIs.Comment: arXiv admin note: text overlap with arXiv:1509.01626, arXiv:1502.01710 by other author

HyperCI: A higher order collective influence measure for hypernetwork dismantling

Network dismantling aims to scratch the network into unconnected fragments by removing an optimal set of nodes and has been widely adopted in many real-world applications such as epidemic control and rumor containment. However, conventional methods often disassemble the system from the perspective of classic networks, which have only pairwise interactions, and often ignored the more ubiquitous and nature group-wise interactions modeled by hypernetwork. Moreover, a simple network can't describe the collective behavior of multiple objects, it is necessary to solve related problems through hypernetwork dismantling. In this work, we designed a higher order collective influence measure to identify key node sets in hypernetwork. It comprehensively consider the environment in which the target node is located and its own characteristics to determine the importance of the node, so as to dismantle the hypernetwork by removing these selected nodes. Finally, we used the method to carry out a series of real-world hypernetwork dismantling tasks. Experimental results on five real-world hypernetworks demonstrate the effectiveness of our proposed measure

Visualizing inorganics in wood and wood composites using X-ray micro-CT

Inorganic materials are a natural component of wood and can also be added to lumber and wood composites to improve their durability. Traditional methods of visualizing the distribution of inorganics in wood are limited to a two-dimensional space and thus are not ideal for studying the 3D distribution of inorganics. I hypothesize that X-ray micro-CT will be able to visualize and reveal novel information about spatial distribution of inorganics in wood. I first test this hypothesis by visualizing the distribution of silica particles in four siliceous Australian hardwood species. A number of novel findings arose from this research. I found that silica particles were associated with rays in the four hardwoods, but their distribution within rays varied. Silica particles were evenly distributed in rays in most species except in Endiandra palmerstonii where they were mainly found in the upright and square cells of rays. Silica particles were associated with growth rings in Lophostemon confertus. Dense materials other than silica particles were found in the vessels of Syncarpia glomulifera and Syncarpia hilli. X-ray fluorescence microscopy confirmed that these materials were inorganic silica and metal elements. Secondly, I tested my hypothesis by visualizing the distribution of zinc borate (ZB) in a wood-plastic-composite (WPC) and examined if a sodium iodide label could improve the contrast between wood and plastic in CT images of WPC. I found that ZB occurred mainly as discrete particles between wood flakes. Interfacial voids formed a network of cracks within the WPC. Impregnation with NaI improved visualization of wood and plastic and made it possible to quantify the levels of wood, plastic, void and zinc borate in the WPC and the geometry of wood particles. However, NaI impregnation swelled wood, closed interfacial voids, and partially dissolved ZB particles. In conclusion, X-ray micro-CT is an effective method for visualizing the spatial distribution of inorganics in solid wood and wood composites, but the intimate association of inorganics with the cell wall in solid wood, and the poor X-ray contrast between wood and polymers complicates the visualization of inorganics in wood and wood composites. Further research is required to address these issues.Forestry, Faculty ofGraduat

Sodium Iodide as a Contrast Agent for X-ray Micro-CT of a Wood Plastic Composite

The properties of wood plastic composites (WPCs) depend on their microstructure, particularly the level and geometry of wood reinforcement in the composite. We hypothesize that impregnating a WPC with a radiocontrast agent will increase the contrast between wood and plastic, allowing better visualization of its microstructure and numerical analysis of the geometry of its wood reinforcement. A commercial WPC was scanned using X-ray micro-CT, impregnated with aqueous sodium iodide, and then rescanned. CT data from both scans were visualized, and we analyzed the geometry of wood reinforcement and levels of wood, plastic, zinc borate (ZB), and voids in the WPC. ZB occurred mainly as discrete particles between wood flakes, and interfacial voids formed a network of cracks within the WPC. Sodium iodide labeling made it possible to clearly visualize wood and plastic in the WPC and quantify levels of different phases and the geometry of wood particles. However, sodium iodide was not an ideal contrast agent because it swelled wood particles, closed interfacial voids, and partially dissolved ZB particles. We suggest methods of overcoming these limitations and conclude that advances in labeling are necessary to improve our understanding of the relationship between the microstructure of WPCs and their properties.Forestry, Faculty ofNon UBCWood Science, Department ofReviewedFacultyResearche

Stack shut-down strategy optimisation of proton exchange membrane fuel cell with the segment stack technology

International audienceIn the previous researches, researchers mainly focus on the single cell which is far away from the practical application. In this paper, shut-down process is studied in a 5-cell stack with segment technology. In the unprotected group, the hydrogen/air boundary is observed, and the output voltage performance degrades greatly after 300 start-stop cycles. A 2-phase auxiliary load strategy is proposed to avoid the hydrogen/air boundary. The lifetime is extended. But a serious local starvation is observed during the shut-down process. And corrosion happened in the inlet region. To avoid the starvation, the second strategy is designed, which combines 2-phase auxiliary and air purge (2-phase loadand air purge strategy). With the new strategy, the degradation of the stack after 1500 cycles is acceptable, and the carbon corrosion in the inlet is effectively reduced. It could conclude that the hydrogen/air boundary is the main cause of the degradation of fuel cell during an unprotected shut-down process. And a strategy only with auxiliary load may suffer from the local starvation. The purge process can avoid the vacuum effect in the fuel cell caused by the auxiliary load. Therefore, adding an air purge during the shut-down process is promising in vehicle fuel cell

Analysis of the Relationship between Vegetation and Radar Interferometric Coherence

To effectively reduce the impact of vegetation cover on surface settlement monitoring, the relationship between normalized difference vegetation index (NDVI) and coherence coefficient was established. It provides a way to estimate coherence coefficient by NDVI. In the research, a new method is tried to make the time range coincident between NDVI results and coherence coefficient results. Using the coherence coefficient results and the NDVI results of each interference image pair in the study area, the mathematical relationship between NDVI and the coherent coefficient was established based on statistical analysis of the fitting results of the exponential model, logarithmic model, and linear model. Four indicators were selected to evaluate the fitting results, including root mean square error, determinant coefficient, prediction interval coverage probability, and prediction interval normalized average width. The fitting effect of the exponential model was better than that of the logarithmic model and linear model. The mean of error was −0.041 in study area ROI1 and −0.126 in study area ROI2.The standard deviation of error was 0.165 in study area ROI1 and 0.140 in study area ROI2. The fitting results are consistent with the coherence coefficient results. The research method used the NDVI results to estimate the InSAR coherence coefficient. This provides an easy and efficient way to indirectly evaluate the interferometric coherence and a basis in InSAR data processing. The results can provide pre-estimation of coherence information in Ningxia by optical images