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Almost all research output includes tables, diagrams, photographs and even sketches, and papers within HCI typically take advantage of including these figures in their files. However the space given to non-diagrammatical or tabular figures is often small, even in papers that primarily concern themselves with visual output. The reason for this might be the publishing models employed in most proceedings and journals: Despite moving to a digital format which is unhindered by page count or physical cost, there remains a somewhat arbitrary limitation on page count. Recent moves by ACM SIGCHI and others to remove references from the maximum page count suggest that there is movement on this, however images remain firmly within the limits of the text. We propose that images should be celebrated – not penalised – and call for not only the adoption of the Pictorials format in CHI, but for images to be removed from page counts in order to encourage greater transparency of process in HCI research.

Climate change is expected to have marked impacts on forest ecosystems. In Ontario forests, this includes changes in tree growth, stand composition and disturbance regimes, with expected impacts on many forest-dependent communities, the bioeconomy, and other environmental considerations. In response to climate change, renewable energy systems, such as forest bioenergy, are emerging as critical tools for carbon emissions reductions and climate change mitigation. However, these systems may also need to adapt to changing forest conditions. Therefore, the aim of this research was to estimate changes in forest growth and forest cover in response to anticipated climatic changes in the year 2100 in Ontario forests, to ultimately explore the sustainability of bioenergy in the future. Using the Haliburton Forest and Wildlife Reserve in Ontario as a case study, this research used a spatial climate analog approach to match modeled Haliburton temperature and precipitation (via Fourth Canadian Regional Climate Model) to regions currently exhibiting similar climate (climate analogs). From there, current forest cover and growth rates of core species in Haliburton were compared to forests plots in analog regions from the US Forest Service Forest Inventory and Analysis (FIA). This comparison used two different emission scenarios, corresponding to a high and a mid-range emission future. This research then explored how these changes in forests may influence bioenergy feasibility in the future. It examined possible volume availability and composition of bioenergy feedstock under future conditions. This research points to a potential decline of softwoods in the Haliburton region with a simultaneous expansion of pre-established hardwoods such as northern red oak and red maple, as well as a potential loss in sugar maple cover. From a bioenergy perspective, hardwood residues may be the most feasible feedstock in the future with minimal change in biomass availability for energy production; under these possible conditions, small scale combined heat and power (CHP) and residential pellet use may be the most viable and ecologically sustainable options. Ultimately, understanding the way in which forests may change is important in informing meaningful policy and management, allowing for improved forest bioenergy systems, now and in the future.

The development of a cost structure for energy storage systems (ESS) has received limited attention. In this study, we developed data-intensive techno-economic models to assess the economic feasibility of ESS. The ESS here includes pump hydro storage (PHS) and compressed air energy storage (CAES). The costs were developed using data-intensive bottom-up models. Scale factors were developed for each component of the storage systems. The life cycle costs of energy storage were estimated for capacity ranges of 98-491 MW, 81-404 MW, and 60-298 MW for PHS, conventional CAES (C-CAES), and adiabatic CAES (A-CAES), respectively, to ensure a market-driven price can be achieved. For CAES systems, costs were developed for storage in salt caverns hard rock caverns, and porous formations. The results show that the annual life cycle storage cost is $220-400 for PHS, $215-265 for C-CAES, and $375-480 per kW-year for A-CAES. The levelised cost of electricity is $69-121 for PHS, $58-70 for C-CAES, and $96-121 per MWh for A-CAES. C-CAES is economically attractive at all capacities, PHS is economically attractive at higher capacities, and A-CAES is not attractive at all. The developed information is helpful in making investment decision related to large energy storage systems.

This study aims to design a new warehouse layout as a solution to the warehouse’s main problem: lack of space to store all the materials in stock. Besides the existing warehouse building, which currently presents an unsuitable layout for the storage of large volumes, there is a second area right next to the first to increase the storage area. The two buildings were re-dimensioned to accommodate a great quantity of stock, enabling one to transform the warehouse building into an industrial warehouse with appropriate storage methods. The final layout increased the storage area by 64%, from a total of 1.471,41 m2 to 2.414,22 m2 overall.

The Optical Spectrograph and Infra-Red Imager System (OSIRIS) and the Atmospheric Chemistry Experiment (ACE) have been taking measurements from space since 2001 and 2003, respectively. This paper presents intercomparisons between ozone and NO2 measured by the ACE and OSIRIS satellite instruments and by ground-based instruments at the Polar Environment Atmospheric Research Laboratory (PEARL), which is located at Eureka, Canada (80° N, 86° W) and is operated by the Canadian Network for the Detection of Atmospheric Change (CANDAC). The ground-based instruments included in this study are four zenith-sky differential optical absorption spectroscopy (DOAS) instruments, one Bruker Fourier transform infrared spectrometer (FTIR) and four Brewer spectrophotometers. Ozone total columns measured by the DOAS instruments were retrieved using new Network for the Detection of Atmospheric Composition Change (NDACC) guidelines and agree to within 3.2%. The DOAS ozone columns agree with the Brewer spectrophotometers with mean relative differences that are smaller than 1.5%. This suggests that for these instruments the new NDACC data guidelines were successful in producing a homogenous and accurate ozone dataset at 80° N. Satellite 14–52 km ozone and 17–40 km NO2 partial columns within 500 km of PEARL were calculated for ACE-FTS Version 2.2 (v2.2) plus updates, ACE-FTS v3.0, ACE-MAESTRO (Measurements of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation) v1.2 and OSIRIS SaskMART v5.0x ozone and Optimal Estimation v3.0 NO2 data products. The new ACE-FTS v3.0 and the validated ACE-FTS v2.2 partial columns are nearly identical, with mean relative differences of 0.0 ± 0.2% and −0.2 ± 0.1% for v2.2 minus v3.0 ozone and NO2, respectively. Ozone columns were constructed from 14–52 km satellite and 0–14 km ozonesonde partial columns and compared with the ground-based total column measurements. The satellite-plus-sonde measurements agree with the ground-based ozone total columns with mean relative differences of 0.1–7.3%. For NO2, partial columns from 17 km upward were scaled to noon using a photochemical model. Mean relative differences between OSIRIS, ACE-FTS and ground-based NO2 measurements do not exceed 20%. ACE-MAESTRO measures more NO2 than the other instruments, with mean relative differences of 25–52%. Seasonal variation in the differences between NO2 partial columns is observed, suggesting that there are systematic errors in the measurements and/or the photochemical model corrections. For ozone spring-time measurements, additional coincidence criteria based on stratospheric temperature and the location of the polar vortex were found to improve agreement between some of the instruments. For ACE-FTS v2.2 minus Bruker FTIR, the 2007–2009 spring-time mean relative difference improved from −5.0 ± 0.4% to −3.1 ± 0.8% with the dynamical selection criteria. This was the largest improvement, likely because both instruments measure direct sunlight and therefore have well-characterized lines-of-sight compared with scattered sunlight measurements. For NO2, the addition of a ±1° latitude coincidence criterion improved spring-time intercomparison results, likely due to the sharp latitudinal gradient of NO2 during polar sunrise. The differences between satellite and ground-based measurements do not show any obvious trends over the missions, indicating that both the ACE and OSIRIS instruments continue to perform well.

Smart grid is an advanced and sophisticated electrical network that uses a combination of information and communication technology to gather required data from different nodes on the network through a reliable, robust and cost effective communication solution, and acts on them to improve the efficiency and reliability of production and distribution of electricity. Volt/Var optimization (VVO) is one of the most important smart grid applications that gives this capability to utility companies to have an efficient electricity distribution network by maintaining an acceptable voltage level along the distribution section under different loading situations. This project focused on characterizing and evaluating the performance of narrow band power line communication (NB-PLC) as a prevalent communication technology for smart grid applications such as VVO in North American power grid. This work was done by establishing and setting up a real test bed in the lab. In this work we tried to implement S-parameter measurements due to its simplicity for channel characterization at high frequency ranges, when we have cascades of different components over the channel. It should be mentioned that the main focus of our work was on analyzing the behavior of an energized 5KVA MV/LV transformer over our channel. Then, we have shown the relationship between S-parameters and ABCD parameters to derive the channel transfer function based on ABCD matrix. Additionally, we did some simple noise measurements over our channel when it was non-energized and energized.

The dataset compiles pigment content, absorptance data, photosynthetic parameters and primary production data as proxies for summertime photoacclimation of the temperate intertidal eelgrass Zostera marina after a 25-day exposure to a natural light intensity gradient (6, 36, 74, 133, 355, 503 and 860 µmol photons/m²/s) under laboratory conditions at the Pointe-au-Père research station, East Rimouski, Quebec, Canada. The data bundle contains: 1) photosynthetic and total absorptance data at the end of the experiment, which respectively represent the fraction of incident visible light absorbed by the photosynthetic tissues corrected and not corrected for non-photosynthetic absorption; 2) pigment content at the end of the experiment, which includes chlorophyll a and b and total carotenoids contents; 3) photosynthetic parameters obtained by Rapid Light Curves (RLC) on days 5 and 25, including photosynthetic apparatus efficiency (alpha), capacity (ETRmax) and saturation (Ek); 4) whole shoot primary production at the end of the experiment, which was calculated from oxygen fluxes under light and dark conditions, and normalized by leaf surface.

A graph drawing is greedy if, for every ordered pair of vertices (x,y), there is a path from x to y such that the Euclidean distance to y decreases monotonically at every vertex of the path. Greedy drawings support a simple geometric routing scheme, in which any node that has to send a packet to a destination "greedily" forwards the packet to any neighbor that is closer to the destination than itself, according to the Euclidean distance in the drawing. In a greedy drawing such a neighbor always exists and hence this routing scheme is guaranteed to succeed. In 2004 Papadimitriou and Ratajczak stated two conjectures related to greedy drawings. The greedy embedding conjecture states that every 3-connected planar graph admits a greedy drawing. The convex greedy embedding conjecture asserts that every 3-connected planar graph admits a planar greedy drawing in which the faces are delimited by convex polygons. In 2008 the greedy embedding conjecture was settled in the positive by Leighton and Moitra. In this paper we prove that every 3-connected planar graph admits a planar greedy drawing. Apart from being a strengthening of Leighton and Moitra's result, this theorem constitutes a natural intermediate step towards a proof of the convex greedy embedding conjecture.

This data set contains temperature, salinity, oxygen, fluorescence, turbidity, currents, and lagrangian drift data collected in the bay of Sept-Îles, on the north shore of the Gulf of St. Lawrence, Canada. Five sampling campaigns were conducted from May to September of 2017, to assess seasonal variations in the oceanographic conditions. An additional campaign was conducted in May 2018, focusing on the measurement of currents. These surveys covered the inside of the bay and the nearby archipelago. The bay of Sept-Îles has recently been the subject of a multidisciplinary study by the Canadian Healthy Oceans Network (CHONe II) because it is a heavily industrialized and urban coastal area at Canadian midlatitudes. It is therefore a good site to study the impact of such human presence on adjacent marine ecosystems. The objective of this data set was to enable the development and calibration of hydrodynamic and biogeochemical models of the bay, which was hindered by scarce knowledge of the environmental conditions. Water properties were collected using a Seabird Electronics SBE19plus and a Sontek CastAway CTD probe. Currents were measured using a towed acoustic Doppler current profiler (ADCP) model Teledyne RDI Sentinel V, and passive surface drifters which used Spot GPS probes.

Recent advances in multi-atlas based algorithms address many of the previous limitations in model-based and probabilistic segmentation methods. However, at the label fusion stage, a majority of algorithms focus primarily on optimizing weight-maps associated with the atlas library based on a theoretical objective function that approximates the segmentation error. In contrast, we propose a novel method—Autocorrecting Walks over Localized Markov Random Fields (AWoL-MRF)—that aims at mimicking the sequential process of manual segmentation, which is the gold-standard for virtually all the segmentation methods. AWoL-MRF begins with a set of candidate labels generated by a multi-atlas segmentation pipeline as an initial label distribution and refines low confidence regions based on a localized Markov random field (L-MRF) model using a novel sequential inference process (walks). We show that AWoL-MRF produces state-of-the-art results with superior accuracy and robustness with a small atlas library compared to existing methods. We validate the proposed approach by performing hippocampal segmentations on three independent datasets: (1) Alzheimer's Disease Neuroimaging Database (ADNI); (2) First Episode Psychosis patient cohort; and (3) A cohort of preterm neonates scanned early in life and at term-equivalent age. We assess the improvement in the performance qualitatively as well as quantitatively by comparing AWoL-MRF with majority vote, STAPLE, and Joint Label Fusion methods. AWoL-MRF reaches a maximum accuracy of 0.881 (dataset 1), 0.897 (dataset 2), and 0.807 (dataset 3) based on Dice similarity coefficient metric, offering significant performance improvements with a smaller atlas library (< 10) over compared methods. We also evaluate the diagnostic utility of AWoL-MRF by analyzing the volume differences per disease category in the ADNI1: Complete Screening dataset. We have made the source code for AWoL-MRF public at: https://github.com/CobraLab/AWoL-MRF.