Ontario Tech University

Recent years have seen a rapid proliferation of mass-market consumer software that takes inspiration from video games. Usually summarized as "gamification", this trend connects to a sizeable body of existing concepts and research in human-computer interaction and game studies, such as serious games, pervasive games, alternate reality games, or playful design. However, it is not clear how "gamification" relates to these, whether it denotes a novel phenomenon, and how to define it. Thus, in this paper we investigate "gamification" and the historical origins of the term in relation to precursors and similar concepts. It is suggested that "gamified" applications provide insight into novel, gameful phenomena complementary to playful phenomena. Based on our research, we propose a definition of "gamification" as the use of game design elements in non-game contexts.

Previous work has identified 6 important areas to consider when evaluating validity and bias in studies of prognostic factors: participation, attrition, prognostic factor measurement, confounding measurement and account, outcome measurement, and analysis and reporting. This article describes the Quality In Prognosis Studies tool, which includes questions related to these areas that can inform judgments of risk of bias in prognostic research.A working group comprising epidemiologists, statisticians, and clinicians developed the tool as they considered prognosis studies of low back pain. Forty-three groups reviewing studies addressing prognosis in other topic areas used the tool and provided feedback. Most reviewers (74%) reported that reaching consensus on judgments was easy. Median completion time per study was 20 minutes; interrater agreement (κ statistic) reported by 9 review teams varied from 0.56 to 0.82 (median, 0.75). Some reviewers reported challenges making judgments across prompting items, which were addressed by providing comprehensive guidance and examples. The refined Quality In Prognosis Studies tool may be useful to assess the risk of bias in studies of prognostic factors.

ABA Receptor Rumbled? The plant hormone abscisic acid (ABA) is critical for normal development and for mediating plant responses to stressful environmental conditions. Now, two papers present analyses of candidate ABA receptors (see the news story by Pennisi ). Ma et al. (p. 1064; published online 30 April) and Park et al. (p. 1068, published online 30 April) used independent strategies to search for proteins that physically interact with ABI family phosphatase components of the ABA response signaling pathway. Both groups identified different members of the same family of proteins, which appear to interact with ABI proteins to form a heterocomplex that can act as the ABA receptor. The variety of both families suggests that the ABA receptor may not be one entity, but rather a class of closely related complexes, which may explain previous difficulties in establishing its identity.

Purpose The purpose of this paper is to investigate the mechanisms controlling the bond formation among extruded polymer filaments in the fused deposition modeling (FDM) process. The bonding phenomenon is thermally driven and ultimately determines the integrity and mechanical properties of the resultant prototypes. Design/methodology/approach The bond quality was assessed through measuring and analyzing changes in the mesostructure and the degree of healing achieved at the interfaces between the adjoining polymer filaments. Experimental measurements of the temperature profiles were carried out for specimens produced under different processing conditions, and the effects on mesostructures and mechanical properties were observed. Parallel to the experimental work, predictions of the degree of bonding achieved during the filament deposition process were made based on the thermal analysis of extruded polymer filaments. Findings Experimental results showed that the fabrication strategy, the envelope temperature and variations in the convection coefficient had strong effects on the cooling temperature profile, as well as on the mesostructure and overall quality of the bond strength between filaments. The sintering phenomenon was found to have a significant effect on bond formation, but only for the very short duration when the filament's temperature was above the critical sintering temperature. Otherwise, creep deformation was found to dominate changes in the mesostructure. Originality/value This study provides valuable information about the effect of deposition strategies and processing conditions on the mesostructure and local mechanical properties within FDM prototypes. It also brings a better understanding of phenomena controlling the integrity of FDM products. Such knowledge is essential for manufacturing functional parts and diversifying the range of application of this process. The findings are particularly relevant to work conducted on modeling of the process and for the formulation of materials new to the FDM process.

We examine empirically the role of high-frequency traders (HFTs) in price discovery and price efficiency. Based on our methodology, we find overall that HFTs facilitate price efficiency by trading in the direction of permanent price changes and in the opposite direction of transitory pricing errors, both on average and on the highest volatility days. This is done through their liquidity demanding orders. In contrast, HFTs’ liquidity supplying orders are adversely selected. The direction of buying and selling by HFTs predicts price changes over short horizons measured in seconds. The direction of HFTs’ trading is correlated with public information, such as macro news announcements, market-wide price movements, and limit order book imbalances.

Since blockchain was introduced through Bitcoin, research has been ongoing to extend its applications to non-financial use cases. Healthcare is one industry in which blockchain is expected to have significant impacts. Research in this area is relatively new but growing rapidly; so, health informatics researchers and practitioners are always struggling to keep pace with research progress in this area. This paper reports on a systematic review of the ongoing research in the application of blockchain technology in healthcare. The research methodology is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and a systematic mapping study process, in which a well-designed search protocol is used to search four scientific databases, to identify, extract and analyze all relevant publications. The review shows that a number of studies have proposed different use cases for the application of blockchain in healthcare; however, there is a lack of adequate prototype implementations and studies to characterize the effectiveness of these proposed use cases. The review further highlights the state-of-the-art in the development of blockchain applications for healthcare, their limitations and the areas for future research. To this end, therefore, there is still the need for more research to better understand, characterize and evaluate the utility of blockchain in healthcare.

CONTEXT: Although many studies suggest that physical activity may reduce risk of type 2 diabetes, the role of moderate-intensity activity such as walking is not well understood. OBJECTIVES: To examine the relationship of total physical activity and incidence of type 2 diabetes in women and to compare the benefits of walking vs vigorous activity as predictors of subsequent risk of type 2 diabetes. DESIGN AND SETTING: The Nurses' Health Study, a prospective cohort study that included detailed data for physical activity from women surveyed in 11 US states in 1986, with updates in 1988 and 1992. PARTICIPANTS: A total of 70,102 female nurses aged 40 to 65 years who did not have diabetes, cardiovascular disease, or cancer at baseline (1986). MAIN OUTCOME MEASURE: Risk of type 2 diabetes by quintile of metabolic equivalent task (MET) score, based on time spent per week on each of 8 common physical activities, including walking. RESULTS: During 8 years of follow-up (534, 928 person-years), we documented 1419 incident cases of type 2 diabetes. After adjusting for age, smoking, alcohol use, history of hypertension, history of high cholesterol level, and other covariates, the relative risks (RRs) of developing type 2 diabetes across quintiles of physical activity (least to most) were 1.0, 0.77, 0.75, 0.62, and 0.54 (P for trend <.001); after adjusting for body mass index (BMI), RRs were 1.0, 0.84, 0.87, 0.77, and 0.74 (P for trend = .002). Among women who did not perform vigorous activity, multivariate RRs of type 2 diabetes across quintiles of MET score for walking were 1.0, 0.91,0.73, 0.69, and 0.58 (P for trend <.001). After adjusting for BMI, the trend remained statistically significant (RRs were 1.0, 0.95, 0.80, 0.81, 0.74; P for trend = .01). Faster usual walking pace was independently associated with decreased risk. Equivalent energy expenditures from walking and vigorous activity resulted in comparable magnitudes of risk reduction. CONCLUSIONS: Our data suggest that greater physical activity level is associated with substantial reduction in risk of type 2 diabetes, including physical activity of moderate intensity and duration.

The concept of smart grid has emerged as a convergence of traditional power system engineering and information and communication technology. It is vital to the success of next generation of power grid, which is expected to be featuring reliable, efficient, flexible, clean, friendly, and secure characteristics. In this paper, we propose an efficient and privacy-preserving aggregation scheme, named EPPA, for smart grid communications. EPPA uses a superincreasing sequence to structure multidimensional data and encrypt the structured data by the homomorphic Paillier cryptosystem technique. For data communications from user to smart grid operation center, data aggregation is performed directly on ciphertext at local gateways without decryption, and the aggregation result of the original data can be obtained at the operation center. EPPA also adopts the batch verification technique to reduce authentication cost. Through extensive analysis, we demonstrate that EPPA resists various security threats and preserve user privacy, and has significantly less computation and communication overhead than existing competing approaches.

Electrochemical impedance spectroscopy (EIS) is a highly applicable electrochemical, analytical, and non-invasive technique for materials characterization, which allows the user to evaluate the impact, efficiency, and magnitude of different components within an electrical circuit at a higher resolution than other common electrochemical techniques such as cyclic voltammetry (CV) or chronoamperometry. EIS can be used to study mechanisms of surface reactions, evaluate kinetics and mass transport, and study the level of corrosion on conductive materials, just to name a few. Therefore, this review demonstrates the scope of physical properties of the materials that can be studied using EIS, such as for characterization of supercapacitors, dye-sensitized solar cells (DSSCs), conductive coatings, sensors, self-assembled monolayers (SAMs), and other materials. This guide was created to support beginner and intermediate level researchers in EIS studies to inspire a wider application of this technique for materials characterization. In this work, we provide a summary of the essential background theory of EIS, including experimental design, signal responses, and instrumentation. Then, we discuss the main graphical representations for EIS data, including a scope of the foundation principles of Nyquist, Bode phase angle, Bode magnitude, capacitance and Randles plots, followed by detailed step-by-step explanations of the corresponding calculations that evolve from these graphs and direct examples from the literature highlighting practical applications of EIS for characterization of different types of materials. In addition, we discuss various applications of EIS technique for materials research.

This paper focuses on clean energy solutions in order to achieve better sustainability, and hence discusses opportunities and challenges from various dimensions, including social, economic, energetic and environmental aspects. It also evaluates the current and potential states and applications of possible clean-energy systems. In the first part of this study, renewable and nuclear energy sources are comparatively assessed and ranked based on their outputs. By ranking energy sources based on technical, economic, and environmental performance criteria, it is aimed to identify the improvement potential for each option considered. The results show that in power generation, nuclear has the highest (7.06/10) and solar photovoltaic (PV) has the lowest (2.30/10). When nonair pollution criteria, such as land use, water contamination, and waste issues are considered, the power generation ranking changes, and geothermal has the best (7.23/10) and biomass has the lowest performance (3.72/10). When heating and cooling modes are considered as useful outputs, geothermal and biomass have approximately the same technical, environmental, and cost performances (as 4.9/10), and solar has the lowest ranking (2/10). Among hydrogen production energy sources, nuclear gives the highest (6.5/10) and biomass provides the lowest (3.6/10) in ranking. In the second part of the present study, multigeneration systems are introduced, and their potential benefits are discussed along with the recent studies in the literature. It is shown that numerous advantages are offered by renewable energy-based integrated systems with multiple outputs, especially in reducing overall energy demand, system cost and emissions while significantly improving overall efficiencies and hence output generation rates. Copyright © 2015 John Wiley & Sons, Ltd.

Fifty-nine 3-year-olds were tested 3 times over a period of 7 months in order to assess the contribution of theory of mind to language development and of language to theory-of-mind development (including the independent contributions of syntax and semantics). Language competence was assessed with a standardized measure of reception and production of syntax and semantics (the Test of Early Language Development). Theory of mind was assessed with false-belief tasks and appearance-reality tasks. Earlier language abilities predicted later theory-of-mind test performance (controlling for earlier theory of mind), but earlier theory of mind did not predict later language test performance (controlling for earlier language). These findings are consistent with the argument that language is fundamental to theory-of-mind development.

: We describe a set of best practices for scientific software development, based on research and experience, that will improve scientists' productivity and the reliability of their software.

This paper examines photocatalytic hydrogen production as a clean energy solution to address challenges of climate change and environmental sustainability. Advantages and disadvantages of various hydrogen production methods, with a particular emphasis on photocatalytic hydrogen production, are discussed in this paper. Social, environmental and economic aspects are taken into account while assessing selected production methods and types of photocatalysts. In the first part of this paper, various hydrogen production options are introduced and comparatively assessed. Then, solar-based hydrogen production options are examined in a more detailed manner along with a comparative performance assessment. Next, photocatalytic hydrogen production options are introduced, photocatalysis mechanisms and principles are discussed and the main groups of photocatalysts, namely titanium oxide, cadmium sulfide, zinc oxide/sulfide and other metal oxide-based photocatalyst groups, are introduced. After discussing recycling issues of photocatalysts, a comparative performance assessment is conducted based on hydrogen production processes (both per mass and surface area of photocatalysts), band gaps and quantum yields. The results show that among individual photocatalysts, on average, Au–CdS has the best performance when band gap, quantum yield and hydrogen production rates are considered. From this perspective, TiO2–ZnO has the poorest performance. Among the photocatalyst groups, cadmium sulfides have the best average performance, while other metal oxides show the poorest rankings, on average. Copyright © 2016 John Wiley & Sons, Ltd.

Over the last few years, deep learning techniques have yielded significant improvements in image inpainting. However, many of these techniques fail to reconstruct reasonable structures as they are commonly over-smoothed and/or blurry. This paper develops a new approach for image inpainting that does a better job of reproducing filled regions exhibiting fine details. We propose a two-stage adversarial model EdgeConnect that comprises of an edge generator followed by an image completion network. The edge generator hallucinates edges of the missing region (both regular and irregular) of the image, and the image completion network fills in the missing regions using hallucinated edges as a priori. We evaluate our model end-to-end over the publicly available datasets CelebA, Places2, and Paris StreetView, and show that it outperforms current state-of-the-art techniques quantitatively and qualitatively. Code and models available at: https://github.com/knazeri/edge-connect

There is a consensus that serious games have a significant potential as a tool for instruction. However, their effectiveness in terms of learning outcomes is still understudied mainly due to the complexity involved in assessing intangible measures. A systematic approach—based on established principles and guidelines—is necessary to enhance the design of serious games, and many studies lack a rigorous assessment. An important aspect in the evaluation of serious games, like other educational tools, is user performance assessment. This is an important area of exploration because serious games are intended to evaluate the learning progress as well as the outcomes. This also emphasizes the importance of providing appropriate feedback to the player. Moreover, performance assessment enables adaptivity and personalization to meet individual needs in various aspects, such as learning styles, information provision rates, feedback, and so forth. This paper first reviews related literature regarding the educational effectiveness of serious games. It then discusses how to assess the learning impact of serious games and methods for competence and skill assessment. Finally, it suggests two major directions for future research: characterization of the player’s activity and better integration of assessment in games.

In this article, we introduce an Internet of Things application, smart community, which refers to a paradigmatic class of cyber-physical systems with cooperating objects (i.e., networked smart homes). We then define the smart community architecture, and describe how to realize secure and robust networking among individual homes. We present two smart community applications, Neighborhood Watch and Pervasive Healthcare, with supporting techniques and associated challenges, and envision a few valueadded smart community services.

In recent years, many deep learning techniques have been applied to the image inpainting problem: the task of filling incomplete regions of an image. However, these models struggle to recover and/or preserve image structure especially when significant portions of the image are missing. We propose a two-stage model that separates the inpainting problem into structure prediction and image completion. Similar to sketch art, our model first predicts the image structure of the missing region in the form of edge maps. Predicted edge maps are passed to the second stage to guide the inpainting process. We evaluate our model end-to-end over publicly available datasets CelebA, CelebHQ, Places2, and Paris StreetView on images up to a resolution of 512 × 512. We demonstrate that this approach outperforms current state-of-the-art techniques quantitatively and qualitatively.

Lithium (Li)-ion batteries have become the mainstream energy storage solution for many applications, such as electric vehicles (EVs) and smart grids. However, various faults in a Li-ion battery system (LIBS) can potentially cause performance degradation and severe safety issues. Developing advanced fault diagnosis technologies is becoming increasingly critical for the safe operation of LIBS. This article provides a comprehensive review of the mechanisms, features, and diagnosis of various faults in LIBSs, including internal battery faults, sensor faults, and actuator faults. Future trends in the development of fault diagnosis technologies for a safer battery system are presented and discussed.

This research examines the potential for new Health Level 7 (HL7) standard Fast Healthcare Interoperability Resources (FHIR, pronounced “fire”) standard to help achieve healthcare systems interoperability. HL7 messaging standards are widely implemented by the healthcare industry and have been deployed internationally for decades. HL7 Version 2 (“v2”) health information exchange standards are a popular choice of local hospital communities for the exchange of healthcare information, including electronic medical record information. In development for 15 years, HL7 Version 3 (“v3”) was designed to be the successor to Version 2, addressing Version 2's shortcomings. HL7 v3 has been heavily criticized by the industry for being internally inconsistent even in it's own documentation, too complex and expensive to implement in real world systems and has been accused of contributing towards many failed and stalled systems implementations. HL7 is now experimenting with a new approach to the development of standards with FHIR. This research provides a chronicle of the evolution of the HL7 messaging standards, an introduction to HL7 FHIR and a comparative analysis between HL7 FHIR and previous HL7 messaging standards.

The following paper is based on a review of 68 refereed journal articles that focused on introducing technology to preservice teachers. Ten key strategies emerged from this review, including delivering a single technology course; offering mini-workshops; integrating technology in all courses; modeling how to use technology; using multimedia; collaboration among preservice teachers, mentor teachers and faculty; practicing technology in the field; focusing on education faculty; focusing on mentor teachers; and improving access to software, hardware, and/or support. These strategies were evaluated based on their effect on computer attitude, ability, and use. The following patterns emerged: First, most studies looked at programs that incorporated only one to three strategies. Second, when four or more strategies were used, the effect on preservice teacher’s use of computers appeared to be more pervasive. Third, most research examined attitudes, ability, or use, but rarely all three. Fourth, and perhaps most important, the vast majority of studies had severe limitations in method: poor data collection instruments, vague sample and program descriptions, small samples, an absence of statistical analysis, or weak anecdotal descriptions of success. It is concluded that more rigorous and comprehensive research is needed to fully understand and evaluate the effect of key technology strategies in preservice teacher education.