Distributed Opportunistic Scheduling for MIMO Ad-Hoc Networks

Distributed opportunistic scheduling (DOS) protocols are proposed for multiple-input multiple-output (MIMO) ad-hoc networks with contention-based medium access. The proposed scheduling protocols distinguish themselves from other existing works by their explicit design for system throughput improvement through exploiting spatial multiplexing and diversity in a {\em distributed} manner. As a result, multiple links can be scheduled to simultaneously transmit over the spatial channels formed by transmit/receiver antennas. Taking into account the tradeoff between feedback requirements and system throughput, we propose and compare protocols with different levels of feedback information. Furthermore, in contrast to the conventional random access protocols that ignore the physical channel conditions of contending links, the proposed protocols implement a pure threshold policy derived from optimal stopping theory, i.e. only links with threshold-exceeding channel conditions are allowed for data transmission. Simulation results confirm that the proposed protocols can achieve impressive throughput performance by exploiting spatial multiplexing and diversity.Comment: Proceedings of the 2008 IEEE International Conference on Communications, Beijing, May 19-23, 200

Distributed Opportunistic Scheduling For Ad-Hoc Communications Under Noisy Channel Estimation

Distributed opportunistic scheduling is studied for wireless ad-hoc networks, where many links contend for one channel using random access. In such networks, distributed opportunistic scheduling (DOS) involves a process of joint channel probing and distributed scheduling. It has been shown that under perfect channel estimation, the optimal DOS for maximizing the network throughput is a pure threshold policy. In this paper, this formalism is generalized to explore DOS under noisy channel estimation, where the transmission rate needs to be backed off from the estimated rate to reduce the outage. It is shown that the optimal scheduling policy remains to be threshold-based, and that the rate threshold turns out to be a function of the variance of the estimation error and be a functional of the backoff rate function. Since the optimal backoff rate is intractable, a suboptimal linear backoff scheme that backs off the estimated signal-to-noise ratio (SNR) and hence the rate is proposed. The corresponding optimal backoff ratio and rate threshold can be obtained via an iterative algorithm. Finally, simulation results are provided to illustrate the tradeoff caused by increasing training time to improve channel estimation at the cost of probing efficiency.Comment: Proceedings of the 2008 IEEE International Conference on Communications, Beijing, May 19-23, 200

VConv-DAE: Deep Volumetric Shape Learning Without Object Labels

With the advent of affordable depth sensors, 3D capture becomes more and more ubiquitous and already has made its way into commercial products. Yet, capturing the geometry or complete shapes of everyday objects using scanning devices (e.g. Kinect) still comes with several challenges that result in noise or even incomplete shapes. Recent success in deep learning has shown how to learn complex shape distributions in a data-driven way from large scale 3D CAD Model collections and to utilize them for 3D processing on volumetric representations and thereby circumventing problems of topology and tessellation. Prior work has shown encouraging results on problems ranging from shape completion to recognition. We provide an analysis of such approaches and discover that training as well as the resulting representation are strongly and unnecessarily tied to the notion of object labels. Thus, we propose a full convolutional volumetric auto encoder that learns volumetric representation from noisy data by estimating the voxel occupancy grids. The proposed method outperforms prior work on challenging tasks like denoising and shape completion. We also show that the obtained deep embedding gives competitive performance when used for classification and promising results for shape interpolation

Cache-Aided Non-Orthogonal Multiple Access

In this paper, we propose a novel joint caching and non-orthogonal multiple access (NOMA) scheme to facilitate advanced downlink transmission for next generation cellular networks. In addition to reaping the conventional advantages of caching and NOMA transmission, the proposed cache-aided NOMA scheme also exploits cached data for interference cancellation which is not possible with separate caching and NOMA transmission designs. Furthermore, as caching can help to reduce the residual interference power, several decoding orders are feasible at the receivers, and these decoding orders can be flexibly selected for performance optimization. We characterize the achievable rate region of cache-aided NOMA and investigate its benefits for minimizing the time required to complete video file delivery. Our simulation results reveal that, compared to several baseline schemes, the proposed cache-aided NOMA scheme significantly expands the achievable rate region for downlink transmission, which translates into substantially reduced file delivery times.Comment: Accepted for presentation at IEEE ICC 201

Measurements of Wind-driven Rain on Mid- and High-rise Buildings in three Canadian Regions

AbstractWind-driven rain (WDR) is an important boundary condition for the study of the hygrothermal behaviour and durability of building envelopes. Understanding the WDR characteristics is important for establishing designs that minimize moisture related issues. Three buildings located in three Canadian cities (Fredericton, Montreal and Vancouver) have been instrumented with equipment to quantify the WDR loads on building façades. This paper presents the experimental setup, spatial distribution of WDR on façades in terms of wall factors, and the comparison between measurements and calculated WDR using the standard ISO 15927. The preliminary results show that the ISO model overestimates the WDR amount most of the time

The cost of inadequate sleep among on-call workers in Australia: A workplace perspective

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. On-call or stand-by is becoming an increasingly prevalent form of work scheduling. However, on-call arrangements are typically utilised when workloads are low, for example at night, which can result in inadequate sleep. It is a matter of concern that on-call work is associated with an increased risk of workplace injury. This study sought to determine the economic cost of injury due to inadequate sleep in Australian on-call workers. The prevalence of inadequate sleep among on-call workers was determined using an online survey, and economic costs were estimated using a previously validated costing methodology. Two-thirds of the sample (66%) reported obtaining inadequate sleep on weekdays (work days) and over 80% reported inadequate sleep while on-call. The resulting cost of injury is estimated at $2.25 billion per year ($1.71–2.73 billion). This equates to $1222 per person per incident involving a short-term absence from work;$2.53 million per incident classified as full incapacity, and $1.78 million for each fatality. To the best of our knowledge this is the first study to quantify the economic cost of workplace injury due to inadequate sleep in on-call workers. Well-rested employees are critical to safe and productive workplace operations. Therefore, it is in the interest of both employers and governments to prioritise and invest far more into the management of inadequate sleep in industries which utilise on-call work arrangements

Barriers to Institutional Investment in Rental Housing: A Systematic Review of Market Risks

Housing practitioners and policy experts are advocating for an expansion in rental housing supply in contemporary cities around the world. The objective is to convince institutional investors to include rental housing investment in their investment portfolio to contribute to boosting housing supply. Unfortunately, the rental sector is characterized by numerous uncertainties and challenges, making it unattractive to institutional investors. With the growing attention to institutional investors in various housing market contexts, an understanding of the market risks (also known as barriers), is useful to inform future research and policymaking. Using a systematic literature review methodology, this paper synthesizes the extant literature on the market risks inhibiting institutional investment in rental housing. Findings reveal the following barriers: low profitability, non-progressive rent control policies, unclear target group for rented projects, poor landlord-tenant relations, inadequate property management and unreliable property market information. Among all the barriers identified, low profitability and inadequate property management had great influence on their investment decision. Firstly, institutional investors perceive rental housing investment as less profitable and unattractive in terms of project performance. Secondly, the lack of supporting structures for the property management sector contributes to derailing rental yields. The review also finds that the target group for rental projects are often vague especially for projects under government assistance. The rental sectors in many countries are confronted with numerous problems, some of which greatly inhibit institutional investors from investing in the rental asset. This paper concludes that, although the idea of expanding rental housing supply seems laudable, ignoring these problems may be detrimental to housing markets in the long run. Rental markets in many countries are volatile, and thus not ready to receive institutional investors fully into the sector. An expanded rental sector could be advanced if policy makers take the appropriate steps to resolve the identified challenges. Adequate structural preparations must also be made for large scale rental housing supply

Source of lead pollution, its influence on public health and the countermeasures

Lead is a well-known toxic heavy metal, which can have serious public health hazards at very low levels, especially for young children. This report summarized the background information on lead as well as its applications, pollution sources, poisoning pathways, biomarkers of exposure and effect, toxicities, poisoning mechanisms, preventive actions, decontamination strategies, and detoxification methods.

Temporal dynamics of maize plant growth, water use, and leaf water content using automated high throughput RGB and hyperspectral imaging

Automated collection of large scale plant phenotype datasets using high throughput imaging systems has the potential to alleviate current bottlenecks in data-driven plant breeding and crop improvement. In this study, we demonstrate the characterization of temporal dynamics of plant growth and water use, and leaf water content of two maize genotypes under two different water treatments. RGB (Red Green Blue) images are processed to estimate projected plant area, which are correlated with destructively measured plant shoot fresh weight (FW), dry weight (DW) and leaf area. Estimated plant FW and DW, along with pot weights, are used to derive daily plant water consumption and water use efficiency (WUE) of the individual plants. Hyperspectral images of plants are processed to extract plant leaf reflectance and correlate with leaf water content (LWC). Strong correlations are found between projected plant area and all three destructively measured plant parameters (R2 \u3e 0.95) at early growth stages. The correlations become weaker at later growth stages due to the large difference in plant structure between the two maize genotypes. Daily water consumption (or evapotranspiration) is largely determined by water treatment, whereas WUE (or biomass accumulation per unit of water used) is clearly determined by genotype, indicating a strong genetic control of WUE. LWC is successfully predicted with the hyperspectral images for both genotypes (R2 = 0.81 and 0.92). Hyperspectral imaging can be a very powerful tool to phenotype biochemical traits of the whole maize plants, complementing RGB for plant morphological trait analysis