Defence Research and Development Canada

Forming connections between human performance and design Engineering Psychology and Human Performance, 4e examines human-machine interaction. The book is organized directly from the psychological perspective of human information processing. The chapters generally correspond to the flow of information as it is processed by a human being--from the senses, through the brain, to action--rather than from the perspective of system components or engineering design concepts. This book is ideal for a psychology student, engineering student, or actual practitioner in engineering psychology, human performance, and human factors Learning Goals Upon completing this book, readers should be able to: * Identify how human ability contributes to the design of technology. * Understand the connections within human information processing and human performance. * Challenge the way they think about technology's influence on human performance.  * show how theoretical advances have been, or might be, applied to improving human-machine interaction

An annotated reference sequence representing the hexaploid bread wheat genome in 21 pseudomolecules has been analyzed to identify the distribution and genomic context of coding and noncoding elements across the A, B, and D subgenomes. With an estimated coverage of 94% of the genome and containing 107,891 high-confidence gene models, this assembly enabled the discovery of tissue- and developmental stage-related coexpression networks by providing a transcriptome atlas representing major stages of wheat development. Dynamics of complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. This community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding.

Abstract We present a psychometric scale that assesses risk taking in five content domains: financial decisions (separately for investing versus gambling), health/safety, recreational, ethical, and social decisions. Respondents rate the likelihood that they would engage in domain‐specific risky activities (Part I). An optional Part II assesses respondents' perceptions of the magnitude of the risks and expected benefits of the activities judged in Part I. The scale's construct validity and consistency is evaluated for a sample of American undergraduate students. As expected, respondents' degree of risk taking was highly domain‐specific, i.e. not consistently risk‐averse or consistently risk‐seeking across all content domains. Women appeared to be more risk‐averse in all domains except social risk. A regression of risk taking (likelihood of engaging in the risky activity) on expected benefits and perceived risks suggests that gender and content domain differences in apparent risk taking are associated with differences in the perception of the activities' benefits and risk, rather than with differences in attitude towards perceived risk. Copyright © 2002 John Wiley & Sons, Ltd.

Autonomous underwater vehicle (AUV) navigation and localization in underwater environments is particularly challenging due to the rapid attenuation of Global Positioning System (GPS) and radio-frequency signals. Underwater communications are low bandwidth and unreliable, and there is no access to a global positioning system. Past approaches to solve the AUV localization problem have employed expensive inertial sensors, used installed beacons in the region of interest, or required periodic surfacing of the AUV. While these methods are useful, their performance is fundamentally limited. Advances in underwater communications and the application of simultaneous localization and mapping (SLAM) technology to the underwater realm have yielded new possibilities in the field. This paper presents a review of the state of the art of AUV navigation and localization, as well as a description of some of the more commonly used methods. In addition, we highlight areas of future research potential.

We combine high-redshift Type Ia supernovae from the first three years of the Supernova Legacy Survey (SNLS) with other supernova (SN) samples, primarily at lower redshifts, to form a high-quality joint sample of 472 SNe (123 low-z, 93 SDSS, 242 SNLS, and 14 Hubble Space Telescope). SN data alone require cosmic acceleration at >99.999% confidence, including systematic effects. For the dark energy equation of state parameter (assumed constant out to at least z = 1.4) in a flat universe, we find w = –0.91^(+0.16)_(–0.20)(stat)^(+0.07)_(–0.14)(sys) from SNe only, consistent with a cosmological constant. Our fits include a correction for the recently discovered relationship between host-galaxy mass and SN absolute brightness. We pay particular attention to systematic uncertainties, characterizing them using a systematic covariance matrix that incorporates the redshift dependence of these effects, as well as the shape-luminosity and color-luminosity relationships. Unlike previous work, we include the effects of systematic terms on the empirical light-curve models. The total systematic uncertainty is dominated by calibration terms. We describe how the systematic uncertainties can be reduced with soon to be available improved nearby and intermediate-redshift samples, particularly those calibrated onto USNO/SDSS-like systems.

In recent years, the rapid urbanization of world's population causes many economic, social, and environmental problems, which affect people's living conditions and quality of life significantly. The concept of “smart city” brings opportunities to solve these urban problems. The objectives of smart cities are to make the best use of public resources, provide high-quality services to the citizens, and improve the people's quality of life. Information and communication technology plays an important role in the implementation of smart cities. Blockchain as an emerging technology has many good features, such as trust-free, transparency, pseudonymity, democracy, automation, decentralization, and security. These features of blockchain are helpful to improve smart city services and promote the development of smart cities. In this paper, we provide a comprehensive survey on the literature involving blockchain technology applied to smart cities. First, the related works and background knowledge are introduced. Then, we review how blockchain technology is applied in the realm of smart cities, from the perspectives of smart citizen, smart healthcare, smart grid, smart transportation, supply chain management, and others. Finally, some challenges and broader perspectives are discussed.

Forming connections between human performance and design, this new edition of Engineering Psychology and Human Performance examines human–machine interaction. The book is organized directly from a psychological perspective of human information processing, and chapters correspond to the flow of information as it is processed by a human being—from the senses, through the brain, to action—rather than from the perspective of system components or engineering design concepts. Upon completing this book, readers will be able to identify how human ability contributes to the design of technology; understand the connections within human information processing and human performance; challenge the way they think about technology’s influence on human performance; and show how theoretical advances have been, or might be, applied to improving human–machine interactions. This new edition includes the following key features: A new chapter on research methods Sections on interruption management and distracted driving as cogent examples of applications of engineering psychology theory to societal problems A greatly increased number of references to pandemics, technostress, and misinformation New applications Amplified emphasis on readability and commonsense examples Updated and new references throughout the text This book is ideal for psychology and engineering students, as well as practitioners in engineering psychology, human performance, and human factors. The text is also supplemented by online resources for students and instructors.

Aims. We present photometric properties and distance measurements of 252 high redshift Type Ia supernovae (0.15 < z < 1.1) discovered during the first three years of the Supernova Legacy Survey (SNLS). These events were detected and their multi-colour light curves measured using the MegaPrime/MegaCam instrument at the Canada-France-Hawaii Telescope (CFHT), by repeatedly imaging four one-square degree fields in four bands. Follow-up spectroscopy was performed at the VLT, Gemini and Keck telescopes to confirm the nature of the supernovae and to measure their redshifts. Methods. Systematic uncertainties arising from light curve modeling are studied, making use of two techniques to derive the peak magnitude, shape and colour of the supernovae, and taking advantage of a precise calibration of the SNLS fields. Results. A flat CDM cosmological fit to 231 SNLS high redshift type Ia supernovae alone gives M = 0.211 0.034(stat) 0.069(sys). The dominant systematic uncertainty comes from uncertainties in the photometric calibration. Systematic uncertainties from light curve fitters come next with a total contribution of 0.026 on M . No clear evidence is found for a possible evolution of the slope () of the colour-luminosity relation with redshift.

We present observational constraints on the nature of dark energy using the Supernova Legacy Survey three-year sample (SNLS3) of Guy et al. and Conley et al. We use the 472 Type Ia supernovae (SNe Ia) in this sample, accounting for recently discovered correlations between SN Ia luminosity and host galaxy properties, and include the effects of all identified systematic uncertainties directly in the cosmological fits. Combining the SNLS3 data with the full WMAP7 power spectrum, the Sloan Digital Sky Survey luminous red galaxy power spectrum, and a prior on the Hubble constant H_0 from SHOES, in a flat universe we find Ω_m = 0.269 ± 0.015 and w = –1.061^(+0.069)_(–0.068) (where the uncertainties include all statistical and SN Ia systematic errors)—a 6.5% measure of the dark energy equation-of-state parameter w. The statistical and systematic uncertainties are approximately equal, with the systematic uncertainties dominated by the photometric calibration of the SN Ia fluxes—without these calibration effects, systematics contribute only a ~2% error in w. When relaxing the assumption of flatness, we find Ω_m = 0.271 ± 0.015, Ω_k = –0.002 ± 0.006, and w = –1.069^(+0.091)_(–0.092). Parameterizing the time evolution of w as w(a) = w_0 + w_a (1–a) gives w_0 = –0.905 ± 0.196, w_a = –0.984^(+1.094)_(– 1.097) in a flat universe. All of our results are consistent with a flat, w = –1 universe. The size of the SNLS3 sample allows various tests to be performed with the SNe segregated according to their light curve and host galaxy properties. We find that the cosmological constraints derived from these different subsamples are consistent. There is evidence that the coefficient, β, relating SN Ia luminosity and color, varies with host parameters at &gt;4σ significance (in addition to the known SN luminosity-host relation); however, this has only a small effect on the cosmological results and is currently a subdominant systematic.

Severe acute respiratory syndrome (SARS) is characterized by a risk of nosocomial transmission; however, the risk of airborne transmission of SARS is unknown. During the Toronto outbreaks of SARS, we investigated environmental contamination in SARS units, by employing novel air sampling and conventional surface swabbing. Two polymerase chain reaction (PCR)-positive air samples were obtained from a room occupied by a patient with SARS, indicating the presence of the virus in the air of the room. In addition, several PCR-positive swab samples were recovered from frequently touched surfaces in rooms occupied by patients with SARS (a bed table and a television remote control) and in a nurses' station used by staff (a medication refrigerator door). These data provide the first experimental confirmation of viral aerosol generation by a patient with SARS, indicating the possibility of airborne droplet transmission, which emphasizes the need for adequate respiratory protection, as well as for strict surface hygiene practices.

Precision cosmology with Type Ia supernovae (SNe Ia) makes use of the fact that SN Ia luminosities depend on their light-curve shapes and colours. Using Supernova Legacy Survey (SNLS) and other data, we show that there is an additional dependence on the global characteristics of their host galaxies: events of the same light-curve shape and colour are, on average, 0.08 mag (&amp;sime;4.0σ) brighter in massive host galaxies (presumably metal-rich) and galaxies with low specific star formation rates (sSFR). These trends do not depend on any assumed cosmological model, and are independent of the SN light-curve width: both fast and slow-declining events show the same trends. SNe Ia in galaxies with a low sSFR also have a smaller slope (‘β’) between their luminosities and colours with ∼2.7σ significance, and a smaller scatter on SN Ia Hubble diagrams (at 95 per cent confidence), though the significance of these effects is dependent on the reddest SNe. SN Ia colours are similar between low-mass and high-mass hosts, leading us to interpret their luminosity differences as an intrinsic property of the SNe and not of some external factor such as dust. If the host stellar mass is interpreted as a metallicity indicator using galaxy mass–metallicity relations, the luminosity trends are in qualitative agreement with theoretical predictions. We show that the average stellar mass, and therefore the average metallicity, of our SN Ia host galaxies decreases with redshift. The SN Ia luminosity differences consequently introduce a systematic error in cosmological analyses, comparable to the current statistical uncertainties on parameters such as &lt;it&gt;w&lt;/it&gt;, the equation of state of dark energy. We show that the use of two SN Ia absolute magnitudes, one for events in high-mass (metal-rich) galaxies and the other for events in low-mass (metal-poor) galaxies, adequately corrects for the differences. Cosmological fits incorporating these terms give a significant reduction in χ2 (3.8σ–4.5σ); linear corrections based on host parameters do not perform as well. We conclude that all future SN Ia cosmological analyses should use a correction of this (or similar) form to control demographic shifts in the underlying galaxy population.

Reverse engineering is a manually intensive but necessary technique for understanding the inner workings of new malware, finding vulnerabilities in existing systems, and detecting patent infringements in released software. An assembly clone search engine facilitates the work of reverse engineers by identifying those duplicated or known parts. However, it is challenging to design a robust clone search engine, since there exist various compiler optimization options and code obfuscation techniques that make logically similar assembly functions appear to be very different. A practical clone search engine relies on a robust vector representation of assembly code. However, the existing clone search approaches, which rely on a manual feature engineering process to form a feature vector for an assembly function, fail to consider the relationships between features and identify those unique patterns that can statistically distinguish assembly functions. To address this problem, we propose to jointly learn the lexical semantic relationships and the vector representation of assembly functions based on assembly code. We have developed an assembly code representation learning model \emph{Asm2Vec}. It only needs assembly code as input and does not require any prior knowledge such as the correct mapping between assembly functions. It can find and incorporate rich semantic relationships among tokens appearing in assembly code. We conduct extensive experiments and benchmark the learning model with state-of-the-art static and dynamic clone search approaches. We show that the learned representation is more robust and significantly outperforms existing methods against changes introduced by obfuscation and optimizations.

The human body constantly exchanges heat with the environment. Temperature regulation is a homeostatic feedback control system that ensures deep body temperature is maintained within narrow limits despite wide variations in environmental conditions and activity-related elevations in metabolic heat production. Extensive research has been performed to study the physiological regulation of deep body temperature. This review focuses on healthy and disordered human temperature regulation during heat stress. Central to this discussion is the notion that various morphological features, intrinsic factors, diseases, and injuries independently and interactively influence deep body temperature during exercise and/or exposure to hot ambient temperatures. The first sections review fundamental aspects of the human heat stress response, including the biophysical principles governing heat balance and the autonomic control of heat loss thermoeffectors. Next, we discuss the effects of different intrinsic factors (morphology, heat adaptation, biological sex, and age), diseases (neurological, cardiovascular, metabolic, and genetic), and injuries (spinal cord injury, deep burns, and heat stroke), with emphasis on the mechanisms by which these factors enhance or disturb the regulation of deep body temperature during heat stress. We conclude with key unanswered questions in this field of research.

The proteomics analysis reported here shows that a major cellular response to oxidative stress is the modification of several peroxiredoxins. An acidic form of the peroxiredoxins appeared to be systematically increased under oxidative stress conditions. Peroxiredoxins are enzymes catalyzing the destruction of peroxides. In doing so, a reactive cysteine in the peroxiredoxin active site is weakly oxidized (disulfide or sulfenic acid) by the destroyed peroxides. Cellular thiols (e.g. thioredoxin) are used to regenerate the peroxiredoxins to their active state. Tandem mass spectrometry was carried out to characterize the modified form of the protein produced in vivo by oxidative stress. The cysteine present in the active site was shown to be oxidized into cysteic acid, leading to an inactivated form of peroxiredoxin. This strongly suggested that peroxiredoxins behave as a dam upon oxidative stress, being both important peroxide-destroying enzymes and peroxide targets. Results obtained in a primary culture of Leydig cells challenged with tumor necrosis factor alpha suggested that this oxidized/native balance of peroxiredoxin 2 may play an active role in resistance or susceptibility to tumor necrosis factor alpha-induced apoptosis.

Modern automobiles have been proven vulnerable to hacking by security researchers. By exploiting vulnerabilities in the car's external interfaces, such as wifi, bluetooth, and physical connections, they can access a car's controller area network (CAN) bus. On the CAN bus, commands can be sent to control the car, for example cutting the brakes or stopping the engine. While securing the car's interfaces to the outside world is an important part of mitigating this threat, the last line of defence is detecting malicious behaviour on the CAN bus. We propose an anomaly detector based on a Long Short-Term Memory neural network to detect CAN bus attacks. The detector works by learning to predict the next data word originating from each sender on the bus. Highly surprising bits in the actual next word are flagged as anomalies. We evaluate the detector by synthesizing anomalies with modified CAN bus data. The synthesized anomalies are designed to mimic attacks reported in the literature. We show that the detector can detect anomalies we synthesized with low false alarm rates. Additionally, the granularity of the bit predictions can provide forensic investigators clues as to the nature of flagged anomalies.

We report on the achievement of wafer-level photocatalytic overall water splitting on GaN nanowires grown by molecular beam epitaxy with the incorporation of Rh/Cr(2)O(3) core-shell nanostructures acting as cocatalysts, through which H(2) evolution is promoted by the noble metal core (Rh) while the water forming back reaction over Rh is effectively prevented by the Cr(2)O(3) shell O(2) diffusion barrier. The decomposition of pure water into H(2) and O(2) by GaN nanowires is confirmed to be a highly stable photocatalytic process, with the turnover number per unit time well exceeding the value of any previously reported GaN powder samples.

CLOSURE IS the perception of an object or event which is not completely or immediately represented. Previous studies (1, 2, 3, 4, 5, 6, 7, 8, 9) have revealed marked individual differences in this perceptual ability, but have thrown little light on its development. Street's use of a Gestalt Completion Test with school children revealed no consistent or significant differences in scores attributable to age—which later prompted Thurstone (7, p. 9) to remark that the finding was of interest an indication that the test involves some factors which mature at an early age, and it may be taken as indicative of some fundamental and primitive function. The study by Verville and Cameron (9) of age and sex differences in the perception of incomplete pictures by adults revealed slight differences in reaction times and perceptual set attributable to age, but did not reveal a relationship between age and perceptual ability. Street's test comprised only thirteen items in its final form; the items were not of a single class; nor could the particular percepts be presumed to be universally familiar. Verville and Cameron used only ten items, and they were checking age differences between two groups of adults—those aged 16 to 23 and those aged 35 to 56. Both studies are open to the presumption that the tests, subjects, and procedures were not adequate to reveal an association between perceptual ability and age. The present study was undertaken to reveal, through an early age range, the likely association between closure ability and age. The procedure was designed to minimize the differential effects of prior perceptual experience through the use, on the one hand, of subjects of common social and educational background, and, on the other hand, of closure test-items representative of a single class of percepts that might be presumed to be universally familiar. In short, the aim was to correlate closure ability and age in a uni-dimensional perceptual domain.

Modern aerospace industry is migrating from reactive to proactive and predictive maintenance to increase platform operational availability and efficiency, extend its useful life cycle and reduce its life cycle cost. Multiphysics modeling together with data-driven analytics generate a new paradigm called “Digital Twin.” The digital twin is actually a living model of the physical asset or system, which continually adapts to operational changes based on the collected online data and information, and can forecast the future of the corresponding physical counterpart. This paper reviews the overall framework to develop a digital twin coupled with the industrial Internet of Things technology to advance aerospace platforms autonomy. Data fusion techniques particularly play a significant role in the digital twin framework. The flow of information from raw data to high-level decision making is propelled by sensor-to-sensor, sensor-to-model, and model-to-model fusion. This paper further discusses and identifies the role of data fusion in the digital twin framework for aircraft predictive maintenance.

BACKGROUND: Although triptans are widely used in the acute management of migraine, there is uncertainty around the comparative efficacy of triptans among each other and vs non-triptan migraine treatments. We conducted systematic reviews and network meta-analyses to compare the relative efficacy of triptans (alone or in combination with other drugs) for acute treatment of migraines compared with other triptan agents, non-steroidal anti-inflammatory drugs (NSAIDs), acetylsalicylic acid (ASA), acetaminophen, ergots, opioids, or anti-emetics. METHODS: The Cochrane Library, MEDLINE, and EMBASE were searched for randomized controlled trials that compared triptans (alone or in combination with other drugs) with placebo-controlled or active migraine treatments. Study selection, data extraction, and quality assessment were completed independently by multiple reviewers. Outcome data were combined and analyzed using a Bayesian network meta-analysis. For each outcome, odds ratios, relative risks, and absolute probability of response were calculated. RESULTS: A total of 133 randomized controlled trials met the inclusion criteria. Standard dose triptans relieved headaches within 2 hours in 42 to 76% of patients, and 2-hour sustained freedom from pain was achieved for 18 to 50% of patients. Standard dose triptans provided sustained headache relief at 24 hours in 29 to 50% of patients, and sustained freedom from pain in 18 to 33% of patients. Use of rescue medications ranged from 20 to 34%. For 2-hour headache relief, standard dose triptan achieved better outcomes (42 to 76% response) than ergots (38%); equal or better outcomes than NSAIDs, ASA, and acetaminophen (46 to 52%); and equal or slightly worse outcomes than combination therapy (62 to 80%). Among individual triptans, sumatriptan subcutaneous injection, rizatriptan ODT, zolmitriptan ODT, and eletriptan tablets were associated with the most favorable outcomes. INTERPRETATION/CONCLUSIONS: Triptans are effective for migraine relief. Standard dose triptans are associated with better outcomes than ergots, and most triptans are associated with equal or better outcomes compared with NSAIDs, ASA, and acetaminophen. Use of triptans in combination with ASA or acetaminophen, or using alternative modes of administration such as injectables, may be associated with slightly better outcomes than standard dose triptan tablets.

Simultaneous localization and mapping (SLAM) in unknown GPS-denied environments is a major challenge for researchers in the field of mobile robotics. Many solutions for single-robot SLAM exist; however, moving to a platform of multiple robots adds many challenges to the existing problems. This paper reviews state-of-the-art multiple-robot systems, with a major focus on multiple-robot SLAM. Various issues and problems in multiple-robot SLAM are introduced, current solutions for these problems are reviewed, and their advantages and disadvantages are discussed.