Search

Due to diverse reasons, energy production will move from centralized facilities to distributed networks of community-scale or smaller, independent producers. If such on-site energy producers are guided by sound engineering principles and safe practices, there is nothing to fear about Distributed Generation (DG) of power, energy or fuel. However, moving the production facilities closer to residences—whenever such facilities are operated with substandard equipment by poorly trained people- could be quite dangerous. The worst case is an improvised facility operated by non-professional staff that uses toxic chemicals. Home-based biodiesel production fits this model. Thus this paper documents the biodiesel production process. The chemicals of concern are described. A “what if” exercise follows to understand the various risk exposures. A Preliminary Hazard List is developed. Finally, the risks of each potential challenge are quantified and assessed to determine severity and policy implications. Recomme...

Peer review goes back to at least 1665 with the founding of Philosophical Transactions of the Royal Society. However peer review did not become well established until the middle of the last century. For example, Einstein's 1905 papers in Annalen der Physik were not subjected to a peer review process. The purpose for which peer review was established is not clear. The probable motives include a combination of rationing of (then) very expensive journal pages, catching obvious errors, and at least some degree of quality control on what is published. The question now is "Do past models make sense in the world of the Internet?", as today, on-line published pages are essentially free and continuous on-line review and rebuttal is practical.

Since the abstract can be found at the beginning of most scientific articles and is an essential part of the article, several attempts have been made to explore the rhetorical moves of abstracts in various research fields. These studies dealt only with accepted articles since they can be easily accessed. Although the findings of such works have some pedagogical implications for academic writing courses for young researchers who are relatively new to their fields, they do not contribute enough to the transparency of the peer review processes conducted in research fields. Increasing transparency requires considering rejected articles since they help to clarify the decision criteria in the peer review. Based on 591 abstracts of accepted or rejected articles submitted to Journal of Visualization (JOV), the present study aimed at exploring the differences between the accepted and rejected abstracts. The results show that there are significant differences in the structures of the abstracts. Since we also successfully develop a classification model for the decision using a machine-learning technique, the findings of this study have some implications for developing a semi-automatic reviewing system that can reduce the reviewer’s burden and increase the review quality. Graphical abstract

Each year it is the privilege and responsibility of the Editor-in-Chief to acknowledge the reviewers whose largely anonymous efforts lie at the heart of any scientific publication, and the communities of scholars and practitioners whom it serves. As such, it is worth taking a few minutes to reflect on the purpose of the peer review process, and the contributions our reviewers make. To my mind the principal purposes of peer review are to determine whether the paper merits publication, and to help authors write better papers.

I wish to extend my deep appreciation to all those who have so generously volunteered their time and talents during 2015 to the peer review and publication of the IEEE Transactions on Broadcasting . Special thanks go to our BTS Publications Chair and Associate Editors who have shared their valuable time and broadcast engineering expertise in managing a steadily increasing flow of papers and evaluating manuscripts through the peer review process.

This pioneering Special Issue aims at providing the state-of-the-art on open energy data analytics; its availability in the different contexts, i.e., country peculiarities; and at different scales, i.e., building, district, and regional for data-aware planning and policy-making. Ten high-quality papers were published after a demanding peer review process and are commented on in this Editorial.

Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly develop behavioral risk factors in humans. Behavioral risk factors such as unhealthy habits, improper diet, and physical inactivity lead to physiological risks, and &ldquo, obesity/overweight&rdquo, is one of the consequences. &ldquo, Obesity and overweight&rdquo, are one of the major lifestyle diseases that leads to other health conditions, such as cardiovascular diseases (CVDs), chronic obstructive pulmonary disease (COPD), cancer, diabetes type II, hypertension, and depression. It is not restricted within the age and socio-economic background of human beings. The &ldquo, World Health Organization&rdquo, (WHO) has anticipated that 30% of global death will be caused by lifestyle diseases by 2030 and it can be prevented with the appropriate identification of associated risk factors and behavioral intervention plans. Health behavior change should be given priority to avoid life-threatening damages. The primary purpose of this study is not to present a risk prediction model but to provide a review of various machine learning (ML) methods and their execution using available sample health data in a public repository related to lifestyle diseases, such as obesity, CVDs, and diabetes type II. In this study, we targeted people, both male and female, in the age group of &gt, 20 and &lt, 60, excluding pregnancy and genetic factors. This paper qualifies as a tutorial article on how to use different ML methods to identify potential risk factors of obesity/overweight. Although institutions such as &ldquo, Center for Disease Control and Prevention (CDC)&rdquo, and &ldquo, National Institute for Clinical Excellence (NICE)&rdquo, guidelines work to understand the cause and consequences of overweight/obesity, we aimed to utilize the potential of data science to assess the correlated risk factors of obesity/overweight after analyzing the existing datasets available in &ldquo, Kaggle&rdquo, University of California, Irvine (UCI) database&rdquo, and to check how the potential risk factors are changing with the change in body-energy imbalance with data-visualization techniques and regression analysis. Analyzing existing obesity/overweight related data using machine learning algorithms did not produce any brand-new risk factors, but it helped us to understand: (a) how are identified risk factors related to weight change and how do we visualize it? (b) what will be the nature of the data (potential monitorable risk factors) to be collected over time to develop our intended eCoach system for the promotion of a healthy lifestyle targeting &ldquo, obesity and overweight&rdquo, as a study case in the future? (c) why have we used the existing &ldquo, UCI&rdquo, datasets for our preliminary study? (d) which classification and regression models are performing better with a corresponding limited volume of the dataset following performance metrics?

The subject of this study was the product development project creating a new innovative proof-of-concept (POC) prototype device that could control a connected industrial overhead crane in order to perform automatic or semi-automatic high precision lifts within a limited time frame. The development work focused on innovating a new measuring concept, which was parallel to finding suitable sensors for the application. Furthermore, the project resulted in a closed loop control system with Industrial Internet connected sensors and a user interface for factory workers. The prototyping journey is depicted to illustrate the decisions made during the product development project to contribute to both the pragmatic and the process discussion in the field of Industrial Internet. The purpose of this research was to explore and generate hypotheses for how new applications should be developed for heavy industry connected devices. The research question is: what are the implications of applying agile product development methods, such as Wayfaring, to heavy industrial machinery and Industrial Internet -based problems? The methodologies used in this paper, in addition to developing the device, are case study research and hypotheses generated from case studies. The hypotheses generated include that it is also possible to prototype large size connected machinery with low-cost and in a short time, and investment decisions for heavy Industrial Internet products become easier with concrete data from proof-of-concept prototypes by creating knowledge about the investment risk and the value proposition.

Over the last 15 years, the Internet has enabled new modes of authorship, new forms of open licensing and distribution, and new forms of collaboration and peer production to flourish. But in turn, new anxieties have arisen, especially concerning quality assurance, peer review, reuse, and modification. New innovations are appearing in peer review, endorsement, the measurement of trust, and the understanding of reputation, but without any systematic analysis of the general principles of quality assurance and peer review in this new era. In this paper, we propose a general set of principles for understanding what peer review was in the past and how it should be applied today to different kinds of content and in new platforms for managing quality. The principles stress an analysis not only on the content in materials but also on their context of use. Our focus is on open educational resources, and we present a case study of the open education project Connexions' lens system for quality assurance and review. However, the principles can be applied across multiple levels of knowledge production, including scholarship in engineering and science and reference materials in addition to educational publishing.

This study describes an effective web-based learning strategy, peer review, used by 143 computer science undergraduate students in an operating systems class at a Taiwanese university. Peer review, based on social constructivism, can be easily implemented via the authors' well-developed web-based peer review (WPR) system. Through peer review, the authors hope to form an authentic learning environment similar to an academic society in which a researcher submits a paper to a journal and receives reviews from society members before publication. Students using this learning strategy are expected to develop higher level thinking skills. The WPR system functioned in the following roles in this study: (1) an information distribution channel and management center for assignment submissions and peer review; (2) a forum for peer interaction and knowledge construction; and (3) storage for knowledge construction procedures. An evaluation of learning effects and students' perceptions about peer review during the spring of 1998 revealed that students not only performed better under peer review, but also displayed higher level thinking skills, i.e., critical thinking, planning, monitoring, and regulation. Students perceived peer review as an effective strategy that promoted their learning motivation. However, merely being an effective reviewer or an effective author may not excel in a peer review environment. The most effective individual appears to be the strategic adapter who effectively constructs a project, adjusts to peers' comments, and serves as a critical reviewer as well.