What's wrong with science journalism? How did it become so dull and predictable? And how do we fix it?My point was really about predictability and stagnation. The formula I outlined – using a few randomly picked BBC science articles as a guide – isn't necessarily an example of bad journalism; butscience reporting is predictable enough that you can write a formula for it that everyone recognises, and once the formula has been seen it's very hard to un-see, like a faint watermark at the edge of your vision.
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Smart contact lenses for health and head-up displays - tech - 10 January 2011 - New Sci... - 0 views
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Lenses that monitor eye health are on the way, and in-eye 3D image displays are being developed too - welcome to the world of augmented vision
EPFL spinoff turns thousands of 2D photos into 3D images | KurzweilAI - 0 views
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Researchers in EPFL's Computer Vision Laboratory developed a computer-based modeling service that generates a 3D image from up to thousands of 2D shots, with all the processing done in the cloud. Since April, the EPFL startup Pix4D has been offering the modeling service with a fourth dimension: time. Now, individuals and small businesses looking for fast, cheap, large-scale 3D models can get them without investing in heavy processing, the company states. With Pix4D, users upload a series of photos of an object, and within 30 minutes they have a 3D image. The software defines "points of interest" from among the photos, or common points of high-contrast pixels. Next, the program pastes the images together seamlessly by matching up the points of interest. Much in the same way our two eyes work together to calculate depth, the software computes the distance and angle between two or more photos and lays the image over the model appropriately, creating a highly accurate 3D model that avoids the time intensive, "point by point" wireframe method. With Pix4D's 3D models, you can navigate in all directions as well as change the date on a timeline to see what a place looked like at different times of the year. The company is collaborating with several drone makers (including another EPFL startup,senseFly) to market their software as a package with senseFly's micro aerial vehicles, or autonomous drones. Pix4D's time element avoids waiting for Google to update its satellite data or for an expensive plane to fly by and take high-resolution photos. Farmers, for example, can now send relatively inexpensive flying drones into the air to take pictures as often as they like, allowing them to survey the evolution of their crops over large distances and long periods of time. And since the calculations are done on a cloud server, the client doesn't need a powerful computer of his or her own.
Why I spoofed science journalism | Martin Robbins | Science | guardian.co.uk - 0 views
Human Computer Interaction (HCI) by John M. Carroll - Interaction-Design.org: HCI, Usab... - 0 views
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The challenge of personal computing became manifest at an opportune time. The broad project of cognitive science, which incorporated cognitive psychology, artificial intelligence, linguistics, cognitive anthropology, and the philosophy of mind, had formed at the end of the 1970s. Part of the programme of cognitive science was to articulate systematic and scientifically-informed applications to be known as "cognitive engineering". Thus, at just the point when personal computing presented the practical need for HCI, cognitive science presented people, concepts, skills, and a vision for addressing such needs. HCI was one of the first examples of cognitive engineering. Other historically fortuitous developments contributed to establishment of HCI. Software engineering, mired in unmanageable software complexity in the 1970s, was starting to focus on nonfunctional requirements, including usability and maintainability, and on non-linear software development processes that relied heavily on testing. Computer graphics and information retrieval had emerged in the 1970s, and rapidly came to recognize that interactive systems were the key to progressing beyond early achievements. All these threads of development in computer science pointed to the same conclusion: The way forward for computing entailed understanding and better empowering users.
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One of the most significant achievements of HCI is its evolving model of the integration of science and practice. Initially this model was articulated as a reciprocal relation between cognitive science and cognitive engineering. Later, it ambitiously incorporated a diverse science foundation, notably Activity Theory, distributed cognition, and ethnomethodology, and a culturally embedded conception of human activity, including the activities of design and technology development. Currently, the model is incorporating design practices and research across a broad spectrum. In these developments, HCI provides a blueprint for a mutual relation between science and practice that is unprecedented.
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In the latter 1980s and early 1990s, HCI assimilated ideas from Activity Theory, distributed cognition, and ethnomethodology. This comprised a fundamental epistemological realignment. For example, the representational theory of mind, a cornerstone of cognitive science, is no longer axiomatic for HCI science. Information processing psychology and laboratory user studies, once the kernel of HCI research, became important, but niche areas. The most canonical theory-base in HCI now is socio-cultural, Activity Theory. Field studies became typical, and eventually dominant as an empirical paradigm. Collaborative interactions, that is, groups of people working together through and around computer systems (in contrast to the early 1980s user-at-PC situation) have become the default unit of analysis. It is remarkable that such fundamental realignments were so easily assimilated by the HCI community.
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