Showing papers by "Ryerson University published in 2017"
01 Jul 2017
TL;DR: In this paper, a fine discretization of the 3D space around the subject and train a ConvNet to predict per voxel likelihoods for each joint is proposed.
Abstract: This paper addresses the challenge of 3D human pose estimation from a single color image. Despite the general success of the end-to-end learning paradigm, top performing approaches employ a two-step solution consisting of a Convolutional Network (ConvNet) for 2D joint localization and a subsequent optimization step to recover 3D pose. In this paper, we identify the representation of 3D pose as a critical issue with current ConvNet approaches and make two important contributions towards validating the value of end-to-end learning for this task. First, we propose a fine discretization of the 3D space around the subject and train a ConvNet to predict per voxel likelihoods for each joint. This creates a natural representation for 3D pose and greatly improves performance over the direct regression of joint coordinates. Second, to further improve upon initial estimates, we employ a coarse-to-fine prediction scheme. This step addresses the large dimensionality increase and enables iterative refinement and repeated processing of the image features. The proposed approach outperforms all state-of-the-art methods on standard benchmarks achieving a relative error reduction greater than 30% on average. Additionally, we investigate using our volumetric representation in a related architecture which is suboptimal compared to our end-to-end approach, but is of practical interest, since it enables training when no image with corresponding 3D groundtruth is available, and allows us to present compelling results for in-the-wild images.
593 citations
TL;DR: The current study proposes the potential of the pharmaceuticals carbamazepine, naproxen, diclofenac and ibuprofen to be regarded as priority ECs for environmental monitoring due to their regular detection and persistence in environmental waters and their possible contribution towards adverse health effects in humans and wildlife.
505 citations
TL;DR: In this paper, a comprehensive review of the artificial neural network (ANN) based model predictive control (MPC) system design is carried out followed by a case study in which ANN models of a residential house located in Ontario, Canada are developed and calibrated with the data measured from site.
427 citations
TL;DR: The reality of BIM, its widespread benefits and current level of uptake are discussed, as well as recommendations regarding how future BIM adoption could be developed are also highlighted.
Abstract: Rapid advancement of technology continues to leverage change and innovation in the construction industry. Continued digitization of the industry offers the opportunity to totally reinvent contemporary construction design and delivery practice for future development. Building Information Modelling (BIM) within the context of Architecture, Engineering & Construction (AEC) has been developing since the early 2000s and is considered to be a key technology. Despite major technical advancements in BIM, it has not been fully adopted and its definitive benefits have not been fully capitalized upon by industry stakeholders. The lack of widespread uptake of BIM appears to be linked to the risks and challenges that are potentially impeding its effectiveness. This paper aims to discuss the reality of BIM, its widespread benefits and current level of uptake. The risks and challenges associated with the adoption of BIM, as well as recommendations regarding how future BIM adoption could be developed are also highlighted.
417 citations
TL;DR: The development of MMC circuit topologies and their mathematical models over the years are presented and the evolution and technical challenges of the classical and model predictive control methods are discussed.
Abstract: Modular multilevel converter (MMC) is one of the most promising topologies for medium to high-voltage high-power applications. The main features of MMC are modularity, voltage and power scalability, fault tolerant and transformer-less operation, and high-quality output waveforms. Over the past few years, several research studies are conducted to address the technical challenges associated with the operation and control of the MMC. This paper presents the development of MMC circuit topologies and their mathematical models over the years. Also, the evolution and technical challenges of the classical and model predictive control methods are discussed. Finally, the MMC applications and their future trends are presented.
404 citations
TL;DR: In this article, the authors present and discuss data taken from several studies about the building energy consumptions in US, EU, and BRIC (Brazil, Russia, India, and China) countries and provide an updated inventory of useful figures.
Abstract: Although it is often stated that the energy consumption in buildings accounts for more than 30% of total global final energy use, only a few studies analyze updated data about the current building energy consumptions or focus on comparing different countries. Similarly, models that predict future trends in building energy demand often use contrasting algorithms which result in diverse forecasts. Scope of this paper is to present and discuss data taken from several studies about the building energy consumptions in US, EU, and BRIC (Brazil, Russia, India, and China) countries and to provide an updated inventory of useful figures. Comparisons among countries are used to show historical, actual, and future energy consumption trends. Data presented by the World Bank, the United Nations Environment Program, the Intergovernmental Panel on Climate Change, and the International Energy Agency are compared with national reports as well as with research studies. The variety of the approaches used in each of the previous sources was considered fundamental to allow a complete review. The paper shows that the total building energy consumptions in BRIC countries have already overcome those in developed countries, and the continuous increase in the building stock of the BRIC countries creates an urgency for promoting building energy efficiency policies in these countries. At the same time, the policies actually adopted in developed countries are insufficient to guarantee a significant reduction in their building energy consumption in the years to come. In the current scenario, at least a doubling of the global energy demand in buildings compared to today’s levels will occur by 2050. To avoid this forecast, cost-effective best practices and technologies as well as behavioral and lifestyle changes need to be diffused and accepted globally.
383 citations
TL;DR: A unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities and the energy harvesting in smart cities is provided, which is a promising solution for extending the lifetime of low-power devices and its related challenges.
Abstract: The drastic increase in urbanization over the past few years requires sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, and so on. The Internet of Things offers many sophisticated and ubiquitous applications for smart cities. The energy demand of IoT applications is increased, while IoT devices continue to grow in both numbers and requirements. Therefore, smart city solutions must have the ability to efficiently utilize energy and handle the associated challenges. Energy management is considered as a key paradigm for the realization of complex energy systems in smart cities. In this article, we present a brief overview of energy management and challenges in smart cities. We then provide a unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities. We also discuss the energy harvesting in smart cities, which is a promising solution for extending the lifetime of low-power devices and its related challenges. We detail two case studies. The first one targets energy-efficient scheduling in smart homes, and the second covers wireless power transfer for IoT devices in smart cities. Simulation results for the case studies demonstrate the tremendous impact of energy- efficient scheduling optimization and wireless power transfer on the performance of IoT in smart cities.
371 citations
TL;DR: In this paper, the authors investigate the extent to which Airbnb is used as a hotel substitute and examine how Airbnb guests expect their accommodations to perform relative to hotels, and find that nearly two-thirds of the tourists who use Airbnb use it as their hotel substitute.
365 citations
TL;DR: A systematic review of the development of green rating systems is presented in this article, where the authors identify the similarity, difference, strength and weakness of green ratings, and examine whether they fully assess the projects in all aspects of sustainability.
353 citations
14 Mar 2017
TL;DR: In this paper, the authors combine semantic keypoints predicted by a convolutional network (convnet) with a deformable shape model to estimate the continuous 6-DoF pose of an object from a single RGB image.
Abstract: This paper presents a novel approach to estimating the continuous six degree of freedom (6-DoF) pose (3D translation and rotation) of an object from a single RGB image. The approach combines semantic keypoints predicted by a convolutional network (convnet) with a deformable shape model. Unlike prior work, we are agnostic to whether the object is textured or textureless, as the convnet learns the optimal representation from the available training image data. Furthermore, the approach can be applied to instance- and class-based pose recovery. Empirically, we show that the proposed approach can accurately recover the 6-DoF object pose for both instance- and class-based scenarios with a cluttered background. For class-based object pose estimation, state-of-the-art accuracy is shown on the large-scale PASCAL3D+ dataset.
351 citations
TL;DR: This empirical study uses a panel data set consisting of 142 economies, split into 116 developing and 26 developed countries, over the period 19952010 to confirm that the relationship between ICT and CO2 emissions is an inverted U-shaped relationship.
TL;DR: This article reviewed a representative sample of articles published in the Journal of Personality and Social Psychology for construct validity evidence and found that validity evidence of existing and author-developed scales was lacking, with coefficient α often being the only psychometric evidence reported.
Abstract: The verity of results about a psychological construct hinges on the validity of its measurement, making construct validation a fundamental methodology to the scientific process. We reviewed a representative sample of articles published in the Journal of Personality and Social Psychology for construct validity evidence. We report that latent variable measurement, in which responses to items are used to represent a construct, is pervasive in social and personality research. However, the field does not appear to be engaged in best practices for ongoing construct validation. We found that validity evidence of existing and author-developed scales was lacking, with coefficient α often being the only psychometric evidence reported. We provide a discussion of why the construct validation framework is important for social and personality researchers and recommendations for improving practice.
TL;DR: A review paper introduces potential inhibitory compounds, inhibition mechanisms, and engineering perspectives on the control of inhibition in dark fermentation of organic wastes for hydrogen gas production.
Abstract: Dark fermentation of organic wastes for hydrogen gas (H2) production is an attractive strategy of being renewable and carbon neutral However, various toxic or inhibitory compounds can significantly limit sustainable operation and widespread adoption of this biotechnology The metabolism of fermentative microbes in dark fermentation system can be inhibited by excess substrate, micronutrients, macronutrients, metal ions, high temperature, acidic pH, un-dissociated organic acids, competitive microbes, and substrate-derived toxic substances This review paper introduces these potential inhibitory compounds, inhibition mechanisms, and provides engineering perspectives on the control of inhibition
TL;DR: In this paper, the authors present a comparative analysis to provide a state-of-the-art review of the recent attempts towards mitigating the urban heat island (UHI) effect in Kuala Lumpur, Singapore, and Hong Kong.
01 Jul 2017
TL;DR: A geometry-driven approach to automatically collect annotations for human pose prediction tasks and achieves state-of-the-art results on standard benchmarks, demonstrating the effectiveness of the method in exploiting the available multi-view information.
Abstract: Recent advances with Convolutional Networks (ConvNets) have shifted the bottleneck for many computer vision tasks to annotated data collection. In this paper, we present a geometry-driven approach to automatically collect annotations for human pose prediction tasks. Starting from a generic ConvNet for 2D human pose, and assuming a multi-view setup, we describe an automatic way to collect accurate 3D human pose annotations. We capitalize on constraints offered by the 3D geometry of the camera setup and the 3D structure of the human body to probabilistically combine per view 2D ConvNet predictions into a globally optimal 3D pose. This 3D pose is used as the basis for harvesting annotations. The benefit of the annotations produced automatically with our approach is demonstrated in two challenging settings: (i) fine-tuning a generic ConvNet-based 2D pose predictor to capture the discriminative aspects of a subjects appearance (i.e.,personalization), and (ii) training a ConvNet from scratch for single view 3D human pose prediction without leveraging 3D pose groundtruth. The proposed multi-view pose estimator achieves state-of-the-art results on standard benchmarks, demonstrating the effectiveness of our method in exploiting the available multi-view information.
TL;DR: The results of the analysis indicate that management-oriented efficiency criteria dominated prior research on OP, and that there is a clear lack of attention to HF in the design and management of OP systems.
Abstract: Order picking (OP) is one of the most labour- and time-intensive processes in internal logistics Over the last decades, researchers have developed various mathematical planning models that help to increase the efficiency of OP systems, for example, by optimising storage assignments or by specifying routes for the order pickers that minimise travel distance in the warehouse Human characteristics that are often a major determinant of OP system performance have, however, widely been ignored in this stream of research This paper systematically evaluates the literature on manual OP systems and conducts a content analysis to gain insights into how human factors (HF) have been considered and discussed in the scientific literature The results of the analysis indicate that management-oriented efficiency criteria dominated prior research on OP, and that there is a clear lack of attention to HF in the design and management of OP systems This poses an opportunity for research and design of manual OP systems
TL;DR: In this paper, the authors presented two models (classical and VMI-CS coordination) for a two-level closed-loop supply chain with a manufacturer and a retailer with a facility to remanufacture used items.
TL;DR: In this article, the authors examine the dynamic nature of the resilience process as an interaction between individuals and their larger socio-ecological context, and introduce a novel, multi-systems model of resilience that addresses limitations within existing models, clarifies ambiguity brought on by heterogeneous definitions of resilience, and recognizes resilience as a process across the lifespan.
TL;DR: There are observed sex differences at various time points of the reactive cortisol following the TSST, and current results suggest that these sex differences can be, at least in part, attributed to variations in methodological considerations across studies.
TL;DR: In this article, an inverse method to predict the acoustical properties of nine natural fibers (kenaf, wood, hemp, coconut, straw, and granular cork) is presented.
TL;DR: A new shift operator based GSP framework enables the signal analysis along a correlation structure defined by a graph shift manifold as opposed to classical signal processing operating on the assumption of the correlation structure with a linear time shift manifold.
Abstract: Defining a sound shift operator for graph signals, similar to the shift operator in classical signal processing, is a crucial problem in graph signal processing (GSP), since almost all operations, such as filtering, transformation, prediction, are directly related to the graph shift operator. We define a set of energy-preserving shift operators that satisfy many properties similar to their counterparts in classical signal processing, but are different from the shift operators defined in the literature, such as the graph adjacency matrix and Laplacian matrix based shift operators, which modify the energy of a graph signal. We decouple the graph structure represented by eigengraphs and the eigenvalues of the adjacency matrix or the Laplacian matrix. We show that the adjacency matrix of a graph is indeed a linear shift invariant (LSI) graph filter with respect to the defined shift operator. We further define autocorrelation and cross-correlation functions of signals on the graph, enabling us to obtain the solution to the optimal filtering on graphs, i.e., the corresponding Wiener filtering on graphs and the efficient spectra analysis and frequency domain filtering in parallel with those in classical signal processing. This new shift operator based GSP framework enables the signal analysis along a correlation structure defined by a graph shift manifold as opposed to classical signal processing operating on the assumption of the correlation structure with a linear time shift manifold. Several illustrative simulations are presented to validate the performance of the designed optimal LSI filters.
TL;DR: In this article, it was shown that uoconvergence is stable under passing to and from regular sublattices, which leads to many applications in functional-analytic aspects of uo-convergence.
Abstract: A net (x
α
) in a vector lattice X is said to uo-converge to x if $$\left| {{x_\alpha } - x} \right| \wedge u\xrightarrow{o}0$$
for every u ≥ 0. In the first part of this paper, we study some functional-analytic aspects of uo-convergence. We prove that uoconvergence is stable under passing to and from regular sublattices. This fact leads to numerous applications presented throughout the paper. In particular, it allows us to improve several results in [27, 26]. In the second part, we use uo-convergence to study convergence of Cesaro means in Banach lattices. In particular, we establish an intrinsic version of Komlos’ Theorem, which extends the main results of [35, 16, 31] in a uniform way. We also develop a new and unified approach to Banach–Saks properties and Banach–Saks operators based on uo-convergence. This approach yields, in particular, short direct proofs of several results in [20, 24, 25].
TL;DR: In this article, the authors examine the international literature to show how urban sanctuary policies and practices differ between national contexts and assess whether there are common features of sanctuary cities, uncover legal, discursive, identity-formative, and scalar aspects of urban sanctuary policy and practices.
Abstract: Sanctuary cities in the USA, UK, and Canada aim to accommodate illegalized migrants and refugees in their communities. The concept of the “sanctuary city,” however, is highly ambiguous: it refers to a variety of different policies and practices, and focuses on variable populations in different national contexts. In this article, I examine the international literature to show how urban sanctuary policies and practices differ between national contexts and assess whether there are common features of sanctuary cities. I uncover legal, discursive, identity-formative, and scalar aspects of urban sanctuary policies and practices. These aspects assemble in ways that differ between countries. The article concludes by raising important practical and theoretical questions about urban sanctuary.
TL;DR: In this paper, the authors discuss issues that have affected and that will continue to affect tourism in Russia, including destination image, infrastructure development, workforce training and education, quality management, and sustainable management.
TL;DR: It is demonstrated that food structure design may be used as a tool to modulate fat and oil digestion potentially resulting in a number of targeted physiological outcomes.
TL;DR: In this paper, the authors investigated the potential of adding two different mineral producing bacteria into two types of cementitious mortar matrix to enhance self-healing ability for autonomous crack repair.
Abstract: There is a compelling economic incentive to develop concrete materials that can repair its own damage, increase durability and prevent structural failure This research investigated the potential of adding two different mineral producing bacteria into two types of cementitious mortar matrix to enhance self-healing ability for autonomous crack repair In this study, zeolite was used as a carrier material to protect bacteria in high pH environment normally exists in concrete The spore forming ability and ureolytic activity of zeolite-immobilized bacteria were investigated in order to examine potential for producing healing compounds The self-healing ability of bacteria incorporated normal and fiber reinforced mortars was judged based on the development of compressive strength and permeation properties of cracked specimens with age as well as micro-structural characterization of crack healing compounds using scanning electron microscopy (SEM), energy dispersive spectrometer (EDS) and X-ray diffraction
TL;DR: In this article, the impact of the temperature dependency of the thermal conductivity in exterior walls and flat roofs was quantified for different insulating materials, such as fiberglass, rock wool, polyisocyanurate, and extruded polystyrene.
TL;DR: The evidence on factors that predict duration of sick leave in workers after 6 weeks low back pain (LBP) related sick leave is systematically reviewed and cannot conclude that prognostic factors change over time.
Abstract: Purpose We systematically reviewed the evidence on factors that predict duration of sick leave in workers after 6 weeks low back pain (LBP) related sick leave. We hypothesized that different factors affect the duration of the leave depending on the time away from work. Methods The review occurred in seven phases: (1) developing the central question, (2) conducting the literature search, (3) identifying relevant publications, (4) quality appraisal, (5) data extraction, (6) evidence synthesis, and (7) knowledge translation. We searched for studies that reported episodes of LBP and sick leave that lasted more than 6 weeks. All included studies reported at least one prognostic factor where return to work was the outcome. Results We identified twenty-two relevant publications. The impact of pain, functional status and radiating pain seems to change with duration of work disability. Workers’ recovery expectations remain important after 6 weeks. Modified duties are rarely studied in later phases of work disability. Depression/mental health did not appear to be an important factor in later phases. Workplace physical factors remain important. There is insufficient evidence that pain catastrophising and fear avoidance are predictive factors in later phases. There was moderate evidence for age in the later phases. Functional capacity and claim related factors were supported by some evidence. Discusion Physical demands in the workplace are preventing workers from getting back to work in a timely fashion across phases. The psychosocial work environment is understudied in later phases. Overall, we cannot conclude that prognostic factors change over time.
TL;DR: In this paper, the authors introduce Markov regime switching models to the Heterogeneous Autoregressive model of the Realized Volatility (HAR-RV) models to forecast the realized volatility of the crude oil futures market.
TL;DR: In this article, a flying-capacitor modular multilevel converter (FC-MMC) based on series-connected submodules is proposed for improving the performance of a medium-voltage motor drive system in the entire speed range.
Abstract: This paper presents a flying-capacitor modular multilevel converter (FC-MMC) based on series-connected submodules. It is intended for completely improving the performance of a medium-voltage motor drive system in the entire speed range especially at zero/low speed under rated torque condition. The proposed FC-MMC circuit is characterized by the cross connection of upper and lower arm middle taps through a flying capacitor in per phase leg. By properly controlling the ac current flowing through the flying capacitor, the power balance between upper and lower arms is achieved, leading to very small voltage ripples on submodule dc capacitors in the entire speed range from standstill to rated speed even under the rated torque condition. Meanwhile, no common-mode voltage is injected. Simulation results obtained from a 4160-V 1-MW model show that the proposed FC-MMC along with the proposed control method performances satisfactorily in dynamic and static state even when operated at zero/low speed. Experiments on a downscaled prototype also prove the effectiveness of the proposal.