Statistical relational learning (SRL) and graph neural networks (GNNs) are two powerful approaches for learning and inference over graphs. Typically, they are evaluated in terms of simple metrics such as accuracy over individual node labels. Complex aggregate graph queries (AGQ) involving multiple nodes, edges, and labels are common in the graph mining community and are used to estimate important network properties such as social cohesion and influence. While graph mining algorithms support AGQs, they typically do not take into account uncertainty, or when they do, make simplifying assumptions and do not build full probabilistic models. In this paper, we examine the performance of SRL and GNNs on AGQs over graphs with partially observed node labels. We show that, not surprisingly, inferring the unobserved node labels as a first step and then evaluating the queries on the fully observed graph can lead to sub-optimal estimates, and that a better approach is to compute these queries as an expectation under the joint distribution. We propose a sampling framework to tractably compute the expected values of AGQs. Motivated by the analysis of subgroup cohesion in social networks, we propose a suite of AGQs that estimate the community structure in graphs. In our empirical evaluation, we show that by estimating these queries as an expectation, SRL-based approaches yield up to a 50-fold reduction in average error when compared to existing GNN-based approaches.
Dimensional scaling approaches are widely used to develop multi-body human models in injury biomechanics research. Given the limited experimental data for any particular anthropometry, a validated model can be scaled to different sizes to reflect the biological variance of population and used to characterize the human response. This paper compares two scaling approaches at the whole-body level: one is the conventional mass-based scaling approach which assumes geometric similarity; the other is the structure-based approach which assumes additional structural similarity by using idealized mechanical models to account for the specific anatomy and expected loading conditions. Given the use of exterior body dimensions and a uniform Young’s modulus, the two approaches showed close values of the scaling factors for most body regions, with 1.5 % difference on force scaling factors and 13.5 % difference on moment scaling factors, on average. One exception was on the thoracic modeling, with 19.3 % difference on the scaling factor of the deflection. Two 6-year-old child models were generated from a baseline adult model as application example and were evaluated using recent biomechanical data from cadaveric pediatric experiments. The scaled models predicted similar impact responses of the thorax and lower extremity, which were within the experimental corridors; and suggested further consideration of age-specific structural change of the pelvis. Towards improved scaling methods to develop biofidelic human models, this comparative analysis suggests further investigation on interior anatomical geometry and detailed biological material properties associated with the demographic range of the population. 相似文献
This article provides a review of trade-offs and synergies of bioenergy within the water–energy–food security nexus, with emphasis on developing countries. It explores the links of bioenergy with food security, poverty reduction, environmental sustainability, health, and gender equity. It concludes that applying the nexus perspective to analyses of bioenergy widens the scope for achieving multiple-win outcomes along the above aspects. 相似文献
The continuous improvement strategies necessary in today's climate of random change mandate that IT organizations transform the way they relate to other business units, deploy new technology, and organize and develop their people. Crafting an individualized transformation program that balances efforts in each of these areas will help IT managers add value to the bottom line while achieving real gains in customer service and productivity. 相似文献
Speed control of a DC motor has always been a challenge because of its variable torque. But it becomes more challenging when noise enters the system at its input. Therefore, there is a need of more advanced controllers. In this paper, a multi-resolution proportional integral derivative (MRPID) controller has been proposed to be utilized to control the speed of a DC motor. It works well even in the presence of noise as compared to the conventional PID controller. Also, performance of a PID controller deteriorates when nonlinearity or uncertainty arises in the system. This degraded performance can be improved by utilizing the multi-resolution property of wavelets, which decomposes the error signal into various frequency components. Further, wavelet coefficients of these decompositions are used to generate the control signal for controlling speed of a DC motor. In this paper, performances of a MRPID, a fractional order PID (FOPID) and a conventional PID controllers are compared in the presence of noise for speed control of a DC motor. The results obtained using a MRPID controller are observed to be better in terms of improved transient characteristics and disturbance rejection for a DC motor as compared to those obtained with PID and FOPID controllers.
Cardiac catheterization is one of the critical procedures in patient care. It is pertinent for all process related issues in this department to be handled with due priority. This research is a cross-functional effort with a leading hospital that was in its planning stage to implement an overall process improvement at its cardiac catheterization lab department. It has been determined that significant process delays exist in this department. One of the identified key factors to process improvement was to reduce patient turnaround time. Process mapping was used to study the system and identify potential sources of delays in the system. A set of qualitative recommendations were put forward. These recommendations, include the reduction of wait time of outpatients and inpatients and the reduction of non-value-added times such as transfer time of patients, were evaluated using a discrete event simulation approach. The simulation study shows that the daily operating hours at the catheterization lab could be reduced, aiding to reallocate staff for discharging other duties, as the hospital may require. 相似文献
In a rapidly changing IT environment, IT professionals need to keep abreast of technological knowledge. We examined how well this is achieved by developing a motivational model of “technological knowledge renewal effectiveness.” We hypothesized that (1) renewal effectiveness was influenced by the IT professional's career orientation, perceived IT dynamism, tolerance of ambiguity, delegation; and (2) that this positively affected both intrinsic and extrinsic job satisfaction. Survey data from 126 IT professionals was used to test the hypotheses. The results generally supported the research model. We discussed the implications of these results in both research and practice. 相似文献
Epilepsy is one of the most common neurological disorders characterized by transient and unexpected electrical disturbance of the brain. The electroencephalogram (EEG) is an invaluable measurement for the purpose of assessing brain activities, containing information relating to the different physiological states of the brain. It is a very effective tool for understanding the complex dynamical behavior of the brain. This paper presents the application of empirical mode decomposition (EMD) for analysis of EEG signals. The EMD decomposes a EEG signal into a finite set of bandlimited signals termed intrinsic mode functions (IMFs). The Hilbert transformation of IMFs provides analytic signal representation of IMFs. The area measured from the trace of the analytic IMFs, which have circular form in the complex plane, has been used as a feature in order to discriminate normal EEG signals from the epileptic seizure EEG signals. It has been shown that the area measure of the IMFs has given good discrimination performance. Simulation results illustrate the effectiveness of the proposed method. 相似文献
Computational workflows are a powerful paradigm to represent and manage complex applications, particularly in large-scale distributed scientific data analysis. Workflows represent application components that result in individual computations as well as their interdependences in terms of dataflow. Workflow systems use these representations to manage various aspects of workflow creation and execution for users, such as the automatic assignment of execution resources. This article describes an approach to automating a new aspect of the process: the selection of application components and data sources. We present a novel approach that enables users to specify varying degrees of detail and amount of constraints in a workflow request, including the specification of constraints on input, intermediate or output data in the workflow, abstract workflow component classes rather than specific component implementations, and generic reusable workflow templates that express a pre-defined combination of components. The algorithm elaborates the user request into a set of fully ground workflows with specific choices of data sources and codes to be used so that they can be submitted for mapping and execution. The algorithm searches through the space of possible candidate workflows by creating increasingly more specialized versions of the original template and eliminating candidates that violate constraints cumulated in the candidate workflow as components and data sources are selected. A novel feature of our approach is that it assumes a distributed architecture where data and component catalogues are separate from the workflow system. The algorithm explicitly poses queries to external catalogues, and therefore any reasoning regarding data or component properties is not assumed to occur within the workflow system. We describe our implementation of this approach in the Wings workflow system. This implementation uses the W3C Web Ontology Language and associated reasoners to implement the workflow system as well as the data and component catalogues. This research demonstrates the use of artificial intelligence techniques to support the kinds of automation envisioned by the scientific community for large-scale distributed scientific data analysis. 相似文献