Embedded intelligence for electrical network operation and control

Integrating multiple types of intelligent, mulitagent data analysis within a smart grid can pave the way for flexible, extensible, and robust solutions to power network management

Endovascular Embolization by Transcatheter Delivery of Particles: Past, Present, and Future.

Minimally invasive techniques to occlude flow within blood vessels, initially pioneered in the 1970s with autologous materials and subsequently advanced with increasingly sophisticated engineered biomaterials, are routinely performed for a variety of medical conditions. Contemporary interventional radiologists have at their disposal a wide armamentarium of occlusive agents to treat a range of disease processes through a small incision in the skin. In this review, we provide a historical perspective on endovascular embolization tools, summarize the current state-of-the-art, and highlight burgeoning technologies that promise to advance the field in the near future

A Machine Learning Based Analytical Framework for Semantic Annotation Requirements

The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable form. Therefore, semantic level information is one of the cornerstones of the Semantic Web. The process of adding semantic metadata to web resources is called Semantic Annotation. There are many obstacles against the Semantic Annotation, such as multilinguality, scalability, and issues which are related to diversity and inconsistency in content of different web pages. Due to the wide range of domains and the dynamic environments that the Semantic Annotation systems must be performed on, the problem of automating annotation process is one of the significant challenges in this domain. To overcome this problem, different machine learning approaches such as supervised learning, unsupervised learning and more recent ones like, semi-supervised learning and active learning have been utilized. In this paper we present an inclusive layered classification of Semantic Annotation challenges and discuss the most important issues in this field. Also, we review and analyze machine learning applications for solving semantic annotation problems. For this goal, the article tries to closely study and categorize related researches for better understanding and to reach a framework that can map machine learning techniques into the Semantic Annotation challenges and requirements

Network of Tinkerers: A Model of Open-Source Technology Innovation

Airplanes were invented by hobbyists and experimenters, and some personal computers were as well. Similarly, many open-source software developers are interested in the software they make, and not focused on profit. Based on these cases, this paper has a model of agents called tinkerers who want to improve a technology for their own reasons, by their own criteria, and who see no way to profit from it. Under these conditions, they would rather share their technology than work alone. The members of the agreement form an information network. The network's members optimally specialize based on their opportunities in particular aspects of the technology or in expanding or managing the network. Endogenously there are incentives to standardize on designs and descriptions of the technology. A tinkerer in the network who sees an opportunity to produce a profitable product may exit the network to create a startup firm and conduct focused research and development. Thus a new industry can arise.Technological Change, Open Source Software, Uncertainty, Innovation, Invention, Collective Invention, Hackers, Hobbyists, Experimenters, Airplane

Development of rapid, automated diagnostics for infectious disease: advances and challenges

The last 2 years has seen an exponential rise in the amount of research funding made available for the development of rapid diagnostic devices for infectious agents of medical importance. This review reports on several such projects. These highlight the development of fully automated devices for rapid diagnostics, ranging from fully automated real-time PCR-based detection methods to fully automated PCR- and array-based machines for the detection and typing of influenza. This review will also highlight the importance of refocusing work on classical immunoassay techniques, showing how biosensor-based immunoassays can greatly enhance existing assays and at a much reduced cost to molecular-based methods

Consideration of building a common platform of collaborative learning environment

This paper reports on considerations about a common and basic functions/components for building a collaborative learning environment. We make efforts to specify the technological issues towards the future standardization of this environment through our research experiences. The problem of standardization includes many embarrassed aspects, however it will extend and widen the field of applications possible within the collaborative learning paradigm, and will make possible the usage of the fruits of years of research and individual implementations of the concept of collaborative learning, from many researches, developments and experiences. So we would like to locate this problem as building a common platform