Scale | GEOG 030: Geographic Perspectives on Sustainability and Human-Environment Systems, 2011 - Iceweasel Printer-friendly version One of the central concepts in geography is scale. In rough terms, scale refers to how big or small something is. That "something" could be an event, a process, or some other phenomenon. In geography, we often focus on spatial scale, which is the spatial extent of something. Some examples can help us understand scale. A nice depiction of scale can be found in the 1977 video "Powers of Ten": The video shows the same point in space on a broad range of scales, from the subatomic to the astronomical. It is important to appreciate that phenomena can be considered or observed at multiple scales. Another example important to Geog 30 is deforestation. * Economic integration: Global freight shipping permits Brazilian trees to be sold to European consumers. * Political integration: American environmental policies may limit the types or quantities of trees that can be imported from Brazil. Figure 1: Energy commodity chain Consider this...
Araucaria (software) The user interface is composed of a main window (diagramming), a schemes editor and the AraucariaDB online interface. While Araucaria helps identify the structure of an argument, it provides freedom of analysis resources. The scheme editor allows the user to create argumentation schemes, group them together and save them into a scheme set file. The scheme set is then applied to the diagram, entirely or in part. As an illustration, an argument scheme relying on symptoms could be applied to the following assertion: "The light has gone off. The AraucariaDB Online Repository can be browsed to retrieve specific arguments to fit a diagram. Because it is based on XML, a standard widely used by developers, AML content can be accessed through other software that support XML.
A Brief History of Decision Support Systems by D. J. Power Editor, DSSResources.COM version 4.1 or see version 2.8 see version 4.1 in Spanish translated by Maria Ramos Summary Information Systems researchers and technologists have built and investigated computerized Decision Support Systems (DSS) for approximately 40 years. I. Computerized decision support systems became practical with the development of minicomputers, timeshare operating systems and distributed computing. This hypertext document is a starting point in explaining the origins of the various technology threads that are converging to provide integrated support for managers working alone, in teams and in organization hierarchies to manage organizations and make more rational decisions. The study of decision support systems is an applied discipline that uses knowledge and especially theory from other disciplines. The next section describes the origins of the field of decision support systems. II. In 1960, J.C.R. T.P. John D.C. III. IV. IV.1 Model-driven DSS
Penn State Institutes of Energy and the Environment: Resources for Students homepage - Iceweasel you are here: home » resources for students home Energy and environmental courses Database contains more than 500 courses. Programs of Study Penn State offers an extensive array of energy and environmental and enregy/environmentally—related majors and minors spanning a wealth of disciplines at both the undergraduate and graduate level. Undergraduate: Majors | Minors Graduate: Programs and Minors Find an Advisor Use this tool to find faculty that match your interests. Career Planning Resources Browse list of job board maintained by various Penn State departments and majors or browse career planning resources including career guides; volunteer, government, and internship opportunities; professional organization's employment resources; and other job bulletin boards. Student Funding Resources Links to open undergraduate and graduate funding opportunities from rfp database. Current Student Spotlight The student spotlight highlights the research of various students supported by the PSIEE.
Artificial intelligence in video games AI used for video games, usually non-player characters In general, game AI does not, as might be thought and sometimes is depicted to be the case, mean a realization of an artificial person corresponding to an NPC in the manner of the Turing test or an artificial general intelligence. The term game AI is used to refer to a broad set of algorithms that also include techniques from control theory, robotics, computer graphics and computer science in general, and so video game AI may often not constitute "true AI" in that such techniques do not necessarily facilitate computer learning or other standard criteria, only constituting "automated computation" or a predetermined and limited set of responses to a predetermined and limited set of inputs.[4][5][6] Many industries and corporate voices[who?] People[who?] The emergence of new game genres in the 1990s prompted the use of formal AI tools like finite state machines. In computer simulations of board games [edit] In modern video games Lists
How to Disagree March 2008 The web is turning writing into a conversation. Twenty years ago, writers wrote and readers read. The web lets readers respond, and increasingly they do—in comment threads, on forums, and in their own blog posts. Many who respond to something disagree with it. That's to be expected. The result is there's a lot more disagreeing going on, especially measured by the word. If we're all going to be disagreeing more, we should be careful to do it well. DH0. This is the lowest form of disagreement, and probably also the most common. u r a fag!!!!!!!!!! But it's important to realize that more articulate name-calling has just as little weight. The author is a self-important dilettante. is really nothing more than a pretentious version of "u r a fag." DH1. An ad hominem attack is not quite as weak as mere name-calling. Of course he would say that. This wouldn't refute the author's argument, but it may at least be relevant to the case. DH2. DH3. DH4. DH5. DH6. What It Means Related:
Home — Penn State Meteorology and Atmospheric Science - Iceweasel Applications of artificial intelligence Artificial intelligence has been used in a wide range of fields including medical diagnosis, stock trading, robot control, law, remote sensing, scientific discovery and toys. However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore," Nick Bostrom reports.[1] "Many thousands of AI applications are deeply embedded in the infrastructure of every industry." In the late 90s and early 21st century, AI technology became widely used as elements of larger systems, but the field is rarely credited for these successes. Computer science[edit] AI researchers have created many tools to solve the most difficult problems in computer science. Finance[edit] Banks use artificial intelligence systems to organize operations, invest in stocks, and manage properties. Hospitals and medicine[edit] Heavy industry[edit] Music[edit]
Lateral thinking Lateral thinking is solving problems through an indirect and creative approach, using reasoning that is not immediately obvious and involving ideas that may not be obtainable by using only traditional step-by-step logic. The term was coined in 1967 by Edward de Bono. [1] According to de Bono, lateral thinking deliberately distances itself from standard perceptions of creativity as either "vertical" logic (the classic method for problem solving: working out the solution step-by-step from the given data) or "horizontal" imagination (having many ideas but being unconcerned with the detailed implementation of them). Methods[edit] Critical thinking is primarily concerned with judging the true value of statements and seeking errors. Lateral thinking is more concerned with the "movement value" of statements and ideas. Random Entry Idea Generating Tool: The thinker chooses an object at random, or a noun from a dictionary, and associates it with the area they are thinking about. See also[edit]
GIScience | Penn State Department of Geography - Iceweasel Research in Geographic Information Sciences at Penn State includes topics concerning: • cartography, • geovisual analytics, • representation, • ontologies and GeoSemantics, • (geographic) information retrieval, • qualitative and quantitative methods, • spatial cognition, • human factors, • remote sensing, and • education. Research Centers in GIScience The GeoVISTA Center (the Geographic Visualization Science, Technology, and Applications Center) is devoted to fundamental and applied scientific research on the visualization of geo-referenced information, development of geographic visualization (GVis) technologies, and the application of both in science, industry, decision-making, and education. The Peter R. Online Geospatial Education In collaboration with the Dutton e-Education Institute and the World Campus , The Department of Geography has offered instructor-led online education for current and aspiring geographic information systems professionals since 1999.
As a service Service model[edit] See cloud computing service models for more information. Examples[edit] Examples include: References[edit] ^ Robin Hastings, Making the Most of the Cloud: How to Choose and Implement the Best Services (2013), p. 3.^ I. A Model of The Creative Process Created in collaboration with Jack Chung, Shelley Evenson, and Paul Pangaro. The creative process is not just iterative; it’s also recursive. It plays out “in the large” and “in the small”—in defining the broadest goals and concepts and refining the smallest details. It branches like a tree, and each choice has ramifications, which may not be known in advance. The creative process involves many conversations—about goals and actions to achieve them—conversations with co-creators and colleagues, conversations with oneself. See also our How do you design? Download PDF
Nature /Society | Penn State Department of Geography - Iceweasel The study of Nature/Society (human-environment interactions) is central to the discipline of Geography. Geographers working in this tradition examine complex linkages and multi-scalar processes between the biophysical environment and human societies. In an era of profound economic and environmental change, scholarship and teaching in this field are of high relevance to scientific debates and political decision-making in environmental governance, conflicts over increasingly scarce resources, human dimensions of global change, including climate change, livelihood and ecological sustainability, and ecosystem service provision. In the Department of Geography at Penn State, scholarship on human-environment interactions focuses on justice and the environment, global change processes, climate change impacts and adaptation, hazards, risks, and vulnerability, water governance, and changes in agro-biodiversity.
Browser extension A browser extension is a small software module for customizing a web browser. Browsers typically allow a variety of extensions, including user interface modifications, ad blocking, and cookie management. History[edit] API conformity[edit] In 2015, a community working group formed under the W3C to create a single standard application programming interface (API) for browser extensions.[3] While that goal is unlikely to be achieved,[4] the majority of browsers already use the same or very similar APIs due to the popularity of Google Chrome. Chrome was the first browser with an extension API based solely on HTML, CSS, and JavaScript. With its own market share in decline, Mozilla also decided to conform. Unwanted behavior[edit] There have also been cases of applications installing browser extensions in a sneaky manner, while making it hard for the user to uninstall the unwanted extension.[25] References[edit] External links[edit] Official extension stores for Chrome, Safari, Firefox, Edge, Opera