Combustion analysis of a CI engine performance using waste cooking biodiesel fuel with an artificial neural network aid

[Abstract]: A comprehensive combustion analysis has been conducted to evaluate the performance of a commercial DI engine, water cooled two cylinders, in-line, naturally aspirated, RD270 Ruggerini diesel engine using waste vegetable cooking oil as an alternative fuel. In order to compare the brake power and the torques values of the engine, it has been tested under same operating conditions with diesel fuel and waste cooking biodiesel fuel blends. The results were found to be very comparable. The properties of biodiesel produced from waste vegetable oil was measured based on ASTM standards. The total sulfur content of the produced biodiesel fuel was 18 ppm which is 28 times lesser than the existing diesel fuel sulfur content used in the diesel vehicles operating in Tehran city (500 ppm). The maximum power and torque produced using diesel fuel was 18.2 kW and 64.2 Nm at 3200 and 2400 rpm respectively. By adding 20% of waste vegetable oil methyl ester, it was noticed that the maximum power and torque increased by 2.7 and 2.9% respectively, also the concentration of the CO and HC emissions have significantly decreased when biodiesel was used. An artificial neural network (ANN) was developed based on the collected data of this work. Multi layer perceptron network (MLP) was used for nonlinear mapping between the input and the output parameters. Different activation functions and several rules were used to assess the percentage error between the desired and the predicted values. The results showed that the training algorithm of Back Propagation was sufficient enough in predicting the engine torque, specific fuel consumption and exhaust gas components for different engine speeds and different fuel blends ratios. It was found that the R2 (R: the coefficient of determination) values are 0.99994, 1, 1 and 0.99998 for the engine torque, specific fuel consumption,CO and HC emissions, respectively

Psychological elements explaining the consumer's adoption and use of a website recommendation system: A theoretical framework proposal

The purpose of this paper is to understand, with an emphasis on the psychological perspective of the research problem, the consumer's adoption and use of a certain web site recommendation system as well as the main psychological outcomes involved. The approach takes the form of theoretical modelling. Findings: A conceptual model is proposed and discussed. A total of 20 research propositions are theoretically analyzed and justified. Research limitations/implications: The theoretical discussion developed here is not empirically validated. This represents an opportunity for future research. Practical implications: The ideas extracted from the discussion of the conceptual model should be a help for recommendation systems designers and web site managers, so that they may be more aware, when working with such systems, of the psychological process consumers undergo when interacting with them. In this regard, numerous practical reflections and suggestions are presented

Online Popularity and Topical Interests through the Lens of Instagram

Online socio-technical systems can be studied as proxy of the real world to investigate human behavior and social interactions at scale. Here we focus on Instagram, a media-sharing online platform whose popularity has been rising up to gathering hundred millions users. Instagram exhibits a mixture of features including social structure, social tagging and media sharing. The network of social interactions among users models various dynamics including follower/followee relations and users' communication by means of posts/comments. Users can upload and tag media such as photos and pictures, and they can "like" and comment each piece of information on the platform. In this work we investigate three major aspects on our Instagram dataset: (i) the structural characteristics of its network of heterogeneous interactions, to unveil the emergence of self organization and topically-induced community structure; (ii) the dynamics of content production and consumption, to understand how global trends and popular users emerge; (iii) the behavior of users labeling media with tags, to determine how they devote their attention and to explore the variety of their topical interests. Our analysis provides clues to understand human behavior dynamics on socio-technical systems, specifically users and content popularity, the mechanisms of users' interactions in online environments and how collective trends emerge from individuals' topical interests.Comment: 11 pages, 11 figures, Proceedings of ACM Hypertext 201

The Size Conundrum: Why Online Knowledge Markets Can Fail at Scale

In this paper, we interpret the community question answering websites on the StackExchange platform as knowledge markets, and analyze how and why these markets can fail at scale. A knowledge market framing allows site operators to reason about market failures, and to design policies to prevent them. Our goal is to provide insights on large-scale knowledge market failures through an interpretable model. We explore a set of interpretable economic production models on a large empirical dataset to analyze the dynamics of content generation in knowledge markets. Amongst these, the Cobb-Douglas model best explains empirical data and provides an intuitive explanation for content generation through concepts of elasticity and diminishing returns. Content generation depends on user participation and also on how specific types of content (e.g. answers) depends on other types (e.g. questions). We show that these factors of content generation have constant elasticity---a percentage increase in any of the inputs leads to a constant percentage increase in the output. Furthermore, markets exhibit diminishing returns---the marginal output decreases as the input is incrementally increased. Knowledge markets also vary on their returns to scale---the increase in output resulting from a proportionate increase in all inputs. Importantly, many knowledge markets exhibit diseconomies of scale---measures of market health (e.g., the percentage of questions with an accepted answer) decrease as a function of number of participants. The implications of our work are two-fold: site operators ought to design incentives as a function of system size (number of participants); the market lens should shed insight into complex dependencies amongst different content types and participant actions in general social networks.Comment: The 27th International Conference on World Wide Web (WWW), 201

Taste and the algorithm

Today, a consistent part of our everyday interaction with art and aesthetic artefacts occurs through digital media, and our preferences and choices are systematically tracked and analyzed by algorithms in ways that are far from transparent. Our consumption is constantly documented, and then, we are fed back through tailored information. We are therefore witnessing the emergence of a complex interrelation between our aesthetic choices, their digital elaboration, and also the production of content and the dynamics of creative processes. All are involved in a process of mutual influences, and are partially determined by the invisible guiding hand of algorithms. With regard to this topic, this paper will introduce some key issues concerning the role of algorithms in aesthetic domains, such as taste detection and formation, cultural consumption and production, and showing how aesthetics can contribute to the ongoing debate about the impact of today’s “algorithmic culture”

Internet Information and Communication Behavior during a Political Moment: The Iraq War, March 2003

This article explores the Internet as a resource for political information and communication in March 2003, when American troops were first sent to Iraq, offering us a unique setting of political context, information use, and technology. Employing a national survey conducted by the Pew Internet & American Life project. We examine the political information behavior of the Internet respondents through an exploratory factor analysis; analyze the effects of personal demographic attributes and political attitudes, traditional and new media use, and technology on online behavior through multiple regression analysis; and assess the online political information and communication behavior of supporters and dissenters of the Iraq War. The factor analysis suggests four factors: activism, support, information seeking, and communication. The regression analysis indicates that gender, political attitudes and beliefs, motivation, traditional media consumption, perceptions of bias in the media, and computer experience and use predict online political information behavior, although the effects of these variables differ for the four factors. The information and communication behavior of supporters and dissenters of the Iraq War differed significantly. We conclude with a brief discussion of the value of "interdisciplinary poaching" for advancing the study of Internet information practices

Whole egg consumption and cortical bone in healthy children

Eggs contain bioactive compounds thought to benefit pediatric bone. This cross-sectional study shows a positive link between childhood egg intake and radius cortical bone. If randomized trials confirm our findings, incorporating eggs into children's diets could have a significant impact in preventing childhood fractures and reducing the risk of osteoporosis. INTRODUCTION: This study examined the relationships between egg consumption and cortical bone in children. METHODS: The cross-sectional study design included 294 9-13-year-old black and white males and females. Three-day diet records determined daily egg consumption. Peripheral quantitative computed tomography measured radius and tibia cortical bone. Body composition and biomarkers of bone turnover were assessed using dual-energy X-ray absorptiometry and ELISA, respectively. RESULTS: Egg intake was positively correlated with radius and tibia cortical bone mineral content (Ct.BMC), total bone area, cortical area, cortical thickness, periosteal circumference, and polar strength strain index in unadjusted models (r = 0.144-0.224, all P < 0.050). After adjusting for differences in race, sex, maturation, fat-free soft tissue mass (FFST), and protein intakes, tibia relationships were nullified; however, egg intake remained positively correlated with radius Ct.BMC (r = 0.138, P = 0.031). Egg intake positively correlated with total body bone mineral density, BMC, and bone area in the unadjusted models only (r = 0.119-0.224; all P < 0.050). After adjusting for covariates, egg intake was a positive predictor of radius FFST (β = 0.113, P < 0.050) and FFST was a positive predictor of Ct.BMC (β = 0.556, P < 0.050) in path analyses. There was a direct influence of egg on radius Ct.BMC (β = 0.099, P = 0.035), even after adjusting for the mediator, FFST (β = 0.137, P = 0.020). Egg intake was positively correlated with osteocalcin in both the unadjusted (P = 0.005) and adjusted (P = 0.049) models. CONCLUSION: If the positive influence of eggs on Ct.BMC observed in this study is confirmed through future randomized controlled trials, whole eggs may represent a viable strategy to promote pediatric bone development and prevent fractures