Using Producer and Consumer Manipulators to Extend Stream I/O Formatting in C++

The C++ iostream package makes use of the notion of stream manipulators, principally as a means of manipulating formatting state associated with a stream. This paper illustrates how parameterized manipulators which produce output and consume input can be defined to extend stream I/O formatting. Such manipulators can be especially useful for simple parsing of stream input. [Appeared in ACM SIGPLAN Notices 29(3), March 1994

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments

Technology 2002: The Third National Technology Transfer Conference and Exposition, volume 2

Proceedings from symposia of the Technology 2002 Conference and Exposition, December 1-3, 1992, Baltimore, MD. Volume 2 features 60 papers presented during 30 concurrent sessions

Advanced Automation for Space Missions

The feasibility of using machine intelligence, including automation and robotics, in future space missions was studied

Digital photos, social media sharing, and the Office of Prime Minister Justin Trudeau

Social media has given Canadians the opportunity to directly connect and share content with each other. Market trends show that users of new digital media prefer to consume and share visual content with celebrity or human interest themes. Finding such visual content is easier when it has been produced and distributed by others. In particular, both traditional news and social media sometimes reproduce digital photo handouts produced by the Prime Minister‘s Office (PMO). These handouts give the PMO an opportunity to feed a stream of positive visuals of Prime Minister Justin Trudeau into online Canadian media platforms. These campaign-style photos promote the prime minister but do little to educate Canadians on civic issues or government business. This creates a situation where the PMO might be diminishing the independence of social media spaces in the pursuit of political goals by reorienting these handouts towards social media-driven consumption. Where are PMO-produced digital photographs of Prime Minister Trudeau reproduced on social media and other non-social media web sites? By addressing this question, I attempt to demonstrate that by providing social media geared towards content sharing with affordable, in-demand digital photo handouts, political actors such as the Trudeau PMO use these platforms as distribution vehicles for their own positive leader-centric visuals. I hypothesize that almost all PMO digital photo handouts are reproduced by individual citizens on social media. However, significant numbers of reproductions on non-social media web sites were discovered under a specific set of circumstances. I highlight these trends that popular handouts follow and use them to construct a "shareability formula" that I suggest maximizes the spread of handouts online if followed. I then discuss the implications of these trends for public discourse on Canadian digital media and the changing dynamics between the PMO, mainstream news media, and a more responsive public

A Flexible, Low-Power, Programmable Unsupervised Neural Network Based on Microcontrollers for Medical Applications

We present an implementation and laboratory tests of a winner takes all (WTA) artificial neural network (NN) on two microcontrollers (μC) with the ARM Cortex M3 and the AVR cores. The prospective application of this device is in wireless body sensor network (WBSN) in an on-line analysis of electrocardiograph (ECG) and electromyograph (EMG) biomedical signals. The proposed device will be used as a base station in the WBSN, acquiring and analysing the signals from the sensors placed on the human body. The proposed system is equiped with an analog-todigital converter (ADC), and allows for multi-channel acquisition of analog signals, preprocessing (filtering) and further analysis

The disinformation pandemic : understanding, identification, and mitigation in COVID-19 era

In 2020 during COVID-19, in addition to the spread of coronavirus disease, we also observed a pandemic of disinformation about the disease. This pandemic of disinformation became known as Infodemic in the medical world. Just as coronavirus was infecting our bodies, Infodemic was infecting our information ecosystem and exasperating the fight against the COVID-19 pandemic. Disinformation can be produced by various sources including scientists, media personalities, and others and it can be disseminated by news media, webpages, and social media from one source to another. Additionally, disinformation can spread easily from web media to social media where it can spread even faster to a wider audience. Therefore, it is important that disinformation be detected before it has a chance to spread. However, the identification of disinformation is fraught with several challenges. This fact highlights the importance of studying and identifying disinformation both in the content of web pages and social media posts before it is allowed to spread. In this dissertation, I pursued a three-essay approach to understand, identify, and mitigate the disinformation pandemic. While manual fact-checking is difficult, time-consuming, and expensive, various automated detection solutions could speed up this process. Therefore, in my first essay, I explored whether Machine Learning (ML) techniques can be used to develop predictive models for automatic identification of disinformation. Computational linguistics methods are used to extract content-based, and sentiment-based features of selected webpage’ articles to construct our study dataset. This dataset is used to train various ML algorithms to develop predictive models to identify disinformation. The results showed that there are significant differences among features of true and false information that can be used to identify disinformation. Since the spread of disinformation happens both on media pages and on social media platforms, it is important to analyze disinformation at both levels. Moreover, the literature shows that disinformation spreads six times faster than true information on social media, demonstrating that users get more engaged with disinformation. Therefore, I extended my research to enhance the understanding of disinformation detection based on content-based features and its impact on users’ engagement in social media posts. The findings of the second essay highlighted the critical role of linguistic structure, emotional tone, and the psychological load of social media posts on users’ engagement that can be used to differentiate information from disinformation. The results of the first two essays confirmed that negative emotional tone was one of the most important factors in disinformation posts and was associated with a high engagement score. So, in the third essay, I explore the impact of negative emotional tones in developing users’ perceptions regarding the accuracy of the content. Three separate experiments were developed to explore this. The results of experiments in the third essay highlighted the significant role of negative emotional tones on the believability of the content and their potential influence on behavioral change. My research findings allow for a better understanding and identification of disinformation by highlighting and identifying content-based features that are meant to mislead users to falsely perceive disinformation as information

Using Producer and Consumer Manipulators to Extend Stream I/O Formatting in C++

This paper illustrates how parameterized manipulators which produce output and consume input can be defined to extend stream I/O formatting. Such manipulators can be especially useful for simple parsing of stream input

On flexibly integrating machine vision inspection systems in PCB manufacture

The objective of this research is to advance computer vision techniques and their applications in the electronics manufacturing industry. The research has been carried out with specific reference to the design of automatic optical inspection (AOI) systems and their role in the manufacture of printed circuit boards (PCBs). To achieve this objective, application areas of AOI systems in PCB manufacture have been examined. As a result, a requirement for enhanced performance characteristics has been identified and novel approaches and image processing algorithms have been evolved which can be used within next generation of AOI systems. The approaches are based on gaining an understanding of ways in which manufacturing information can be used to support AOI operations. Through providing information support, an AOI system has access to product models and associated information which can be used to enhance the execution of visual inspection tasks. Manufacturing systems integration, or more accurately controlled access to electronic information, is the key to the approaches. Also in the thesis methods are proposed to achieve the flexible integration of AOI systems (and computer vision systems in general) within their host PCB manufacturing environment. Furthermore, potential applications of information supported AOI systems at various stages of PCB manufacturing have been studied. It is envisaged that more efficient and cost-effective applications of AOI can be attained through adopting the flexible integration methods proposed, since AOI-generated information can now be accessed and utilized by other processes

Improvisational interaction : a framework for structural exploration of media

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2006.Includes bibliographical references (p. 106-108).Whenever we use computers to interact with media, our experience is that of direct control, and the goal of our interactions is either artifact-production (the editor paradigm) or passive exploration (the browser paradigm). This thesis proposes an alternative: a model of media interaction based on the ideas of non-idiomatic improvisation that encourages active exploration of media and its structures. We argue that in order to facilitate this kind of exploration, (1) computational tools must actively participate in the creative process and (2) the interaction framework must allow structural exploration of media. This leads to our main claim: improvisation should be considered a valid and appropriate paradigm for media interaction. To this extent, we present a Cognitive Model of Improvisational action (CMIA) that integrates element-centric and process-centric (structural) modes of control into a single framework for media exploration. This model allows participants to switch their attention between compositional elements and structural processes.(cont.) The model is argued to be particularly powerful in leading us to novel spaces for media creation and consumption. We follow by presenting the Emonic Environment (Implementation), an interactive system built on the principles of CMIA. We conclude by describing two studies (Scenarios a Experiments) that analyze the ways in which Emonic Environment affects how people interact and think about their interactions with digital media. These studies illustrate the potential of CMIA as a paradigm for interaction between humans and machines.by Paul Nemirovsky.Ph.D