Video Interpolation using Optical Flow and Laplacian Smoothness

Non-rigid video interpolation is a common computer vision task. In this paper we present an optical flow approach which adopts a Laplacian Cotangent Mesh constraint to enhance the local smoothness. Similar to Li et al., our approach adopts a mesh to the image with a resolution up to one vertex per pixel and uses angle constraints to ensure sensible local deformations between image pairs. The Laplacian Mesh constraints are expressed wholly inside the optical flow optimization, and can be applied in a straightforward manner to a wide range of image tracking and registration problems. We evaluate our approach by testing on several benchmark datasets, including the Middlebury and Garg et al. datasets. In addition, we show application of our method for constructing 3D Morphable Facial Models from dynamic 3D data

Learning Multi-Scale Representations for Material Classification

The recent progress in sparse coding and deep learning has made unsupervised feature learning methods a strong competitor to hand-crafted descriptors. In computer vision, success stories of learned features have been predominantly reported for object recognition tasks. In this paper, we investigate if and how feature learning can be used for material recognition. We propose two strategies to incorporate scale information into the learning procedure resulting in a novel multi-scale coding procedure. Our results show that our learned features for material recognition outperform hand-crafted descriptors on the FMD and the KTH-TIPS2 material classification benchmarks

Flexible operation of supercritical power plant via integration of thermal energy storage

© 2018 The Author(s).This chapter presents the recent research on various strategies for power plant flexible operations to meet the requirements of load balance. The aim of this study is to investigate whether it is feasible to integrate the thermal energy storage (TES) with the thermal power plant steam-water cycle. Optional thermal charge and discharge locations in the cycle have been proposed and compared. Dynamic modeling and simulations have been carried out to demonstrate the capability of TES integration in supporting the flexible operation of the power plant. The simulation software named SimuEngine is adopted, and a 600 MW supercritical coal-fired power plant model is implemented onto the software platform. Three TES charging strategies and two TES discharging strategies are proposed and verified via the simulation platform. The simulation results show that it is feasible to extract steam from steam turbines to charge the TES and to discharge the stored thermal energy back to the power generation processes. The improved capability of the plant flexible operation is further studied in supporting the responses to the grid load demand changes. The results demonstrated that the TES integration has led to much faster and more flexible responses to the load demand changes.Peer reviewe

Consistency Checking of Natural Language Temporal Requirements using Answer-Set Programming

Successful software engineering practice requires high quality requirements. Inconsistency is one of the main requirement issues that may prevent software projects from being success. This is particularly onerous when the requirements concern temporal constraints. Manual checking whether temporal requirements are consistent is tedious and error prone when the number of requirements is large. This dissertation addresses the problem of identifying inconsistencies in temporal requirements expressed as natural language text. The goal of this research is to create an efficient, partially automated, approach for checking temporal consistency of natural language requirements and to minimize analysts\u27 workload. The key contributions of this dissertation are as follows: (1) Development of a partially automated approach for checking temporal consistency of natural language requirements. (2) Creation of a formal language Temporal Action Language (TeAL), which provide a means to represent natural language requirements precisely and unambiguously. (3) Development of a front end to semi-automatically translate natural language requirements into TeAL. (4) Development of a translator from TeAL to the ASP language. Validation results to date show that the front end tool makes the task of translating natural language requirements into TeAL more accurate and efficient, and the translator generates ASP programs that correctly detect the inconsistencies in the requirements

Freeform extrusion fabrication of advanced ceramics and ceramic-based composites

Ceramic On-Demand Extrusion (CODE) is a recently developed freeform extrusion fabrication process for producing dense ceramic components from single and multiple constituents. In this process, aqueous paste of ceramic particles with a very low binder content ( \u3c 1 vol%) is extruded through a moving nozzle to print each layer sequentially. Once one layer is printed, it is surrounded by oil to prevent undesirable water evaporation from the perimeters of the part. The oil level is regulated just below the topmost layer of the part being fabricated. Infrared radiation is then applied to uniformly and partially dry the top layer so that the yield stress of the paste increases to avoid part deformation. By repeating the above steps, the part is printed in a layer-wise fashion, followed by post-processing. Paste extrusion precision of different extrusion mechanisms was compared and analyzed, with an auger extruder determined to be the most suitable paste extruder for the CODE system. A novel fabrication system was developed based on a motion gantry, auger extruders, and peripheral devices. Sample specimens were then produced from 3 mol% yttria stabilized zirconia using this fabrication system, and their properties, including density, flexural strength, Young\u27s modulus, Weibull modulus, fracture toughness, and hardness were measured. The results indicated that superior mechanical properties were achieved by the CODE process among all the additive manufacturing processes. Further development was made on the CODE process to fabricate ceramic components that have external/internal features such as overhangs by using fugitive support material. Finally, ceramic composites with functionally graded materials (FGMs) were fabricated by the CODE process using a dynamic mixing device --Abstract, page iv

To Fall Or Not To Fall: A Visual Approach to Physical Stability Prediction

Understanding physical phenomena is a key competence that enables humans and animals to act and interact under uncertain perception in previously unseen environments containing novel object and their configurations. Developmental psychology has shown that such skills are acquired by infants from observations at a very early stage. In this paper, we contrast a more traditional approach of taking a model-based route with explicit 3D representations and physical simulation by an end-to-end approach that directly predicts stability and related quantities from appearance. We ask the question if and to what extent and quality such a skill can directly be acquired in a data-driven way bypassing the need for an explicit simulation. We present a learning-based approach based on simulated data that predicts stability of towers comprised of wooden blocks under different conditions and quantities related to the potential fall of the towers. The evaluation is carried out on synthetic data and compared to human judgments on the same stimuli