5,592 research outputs found
Do dolphins benefit from nonlinear mathematics when processing their sonar returns?
No full textAn interview with author Tim Leighton about the paper
Evaluating Citebase, an open access Web-based citation-ranked search and impact discovery service
No full textCitebase is a new citation-ranked search and impact discovery service that measures citations of scholarly research papers which are openly accessible on the Web, i.e. papers that are assessable continuously online. Other services, such as ResearchIndex, have emerged in recent years to offer citation indexing of Web research papers. In the first detailed user evaluation of an open access Web citation indexing service, Citebase has been evaluated by nearly 200 users from different backgrounds. The paper details the procedures used in the evaluation, and analyses the results of this study, which took place between June and October 2002. It was found that within the scope of its primary components, the search interface and services available from its rich bibliographic records, Citebase can be used simply and reliably for the purpose intended, and that it compares favourably with other bibliographic services. It is shown tasks can be accomplished efficiently with Citebase regardless of the background of the user. More data need to be collected and the process refined before it is as reliable for measuring citation impact of indexed papers. Better explanations and guidance are required for first-time users. Coverage is seen as a limiting factor, even though Citebase indexes over 200,000 papers from arXiv. Non-physicists were frustrated at the lack of papers from other sciences. The principle of citation searching of open access archives has thus been demonstrated and need not be restricted to current users. Since the evaluation, Citebase has become a featured service of the ArXiv physics eprint archives
Correspondence from Tim McCoy to Virgil E. Barnes, October 16, 1994
No full textLetter from Tim McCoy to Virgil E. Barnes inquiring about the state of the Bluff meteorite sample and Native Americans' relationship with tektites.NATIONAL RESEARCH COUNCIL National Aeronautics and Space Administration Johnson Space Center Houston, TX 77058 Dr. V.E. Barnes Bureau of Economic Geology Univ. of Texas at Austin Box X Univ. Station Austin, TX 78713-7508 Oct. 16, 1994 Dear Dr. Barnes, My name is Tim McCoy and I am currently working as a postdoctoral fellow at Johnson Space Center. I recently earned my Ph.D. with Klaus Keil at the Univ. of Hawaii. Since moving to Texas, I have been working on meteorites from Fayette County, Texas, with Dr. Art Ehlmann of Texas Christian University. I have also become interested in bediasites. I am writing to ask you a few questions which I thought you might be able to answer. 1. I have examined the Bluff meteorite specimen at the Texas Memorial Museum and noted that it has had two large pieces sawn off of it. The curator at the Museum has no knowledge of the removal of these pieces. However, a sample of Cedar from the Smithsonian is present in the collection with a note that it was received on 2/5/57 on exchange from the Smithsonian. Do you have any knowledge about the removal of these pieces or their final destination. 2. I have examined Oscar Monnig's tektite collection at Texas Christian University. I find it very interesting that none of the tektites show any evidence of having been worked by the Indians which inhabited the region. Yet, these large tektites would have made excellent arrowheads and the Indians must have been aware of them. Alternatively, tektite collections may contain only unaltered tektites, while worked tektites might be contained within arrowhead collections. Do you know of any evidence for the working of tektites by the Native Americans? I realize you are probably quite busy, but I would very much appreciate any insights you might provide about these questions. Thank you in advance for your time and effort. Sincerely, Tim McCoy Code SN4 NASA/Johnson Space Center Houston, TX 7705
Dan Leatham, Robert E. Steele, Tim Slocum, Harold W. Johnson, and W. Fred Hurst v. Utah Department of Corrections and the Career Service Review Board of the State of Utah : Brief of Appellant
No full textBRIEF OF APPELLANTS/PETITIONERS DAN LEATHAM, ROBERT E. STEELE, TIM SLOCUM, HAROLD W. JOHNSON AND W. FRED HURS
What to bid and when to stop
No full textNegotiation is an important activity in human society, and is studied by various disciplines, ranging from economics and game theory, to electronic commerce, social psychology, and artificial intelligence. Traditionally, negotiation is a necessary, but also time-consuming and expensive activity. Therefore, in the last decades there has been a large interest in the automation of negotiation, for example in the setting of e-commerce. This interest is fueled by the promise of automated agents eventually being able to negotiate on behalf of human negotiators.Every year, automated negotiation agents are improving in various ways, and there is now a large body of negotiation strategies available, all with their unique strengths and weaknesses. For example, some agents are able to predict the opponent's preferences very well, while others focus more on having a sophisticated bidding strategy. The problem however, is that there is little incremental improvement in agent design, as the agents are tested in varying negotiation settings, using a diverse set of performance measures. This makes it very difficult to meaningfully compare the agents, let alone their underlying techniques. As a result, we lack a reliable way to pinpoint the most effective components in a negotiating agent.There are two major advantages of distinguishing between the different components of a negotiating agent's strategy: first, it allows the study of the behavior and performance of the components in isolation. For example, it becomes possible to compare the preference learning component of all agents, and to identify the best among them. Second, we can proceed to mix and match different components to create new negotiation strategies., e.g.: replacing the preference learning technique of an agent and then examining whether this makes a difference. Such a procedure enables us to combine the individual components to systematically explore the space of possible negotiation strategies.To develop a compositional approach to evaluate and combine the components, we identify structure in most agent designs by introducing the BOA architecture, in which we can develop and integrate the different components of a negotiating agent. We identify three main components of a general negotiation strategy; namely a bidding strategy (B), possibly an opponent model (O), and an acceptance strategy (A). The bidding strategy considers what concessions it deems appropriate given its own preferences, and takes the opponent into account by using an opponent model. The acceptance strategy decides whether offers proposed by the opponent should be accepted.The BOA architecture is integrated into a generic negotiation environment called Genius, which is a software environment for designing and evaluating negotiation strategies. To explore the negotiation strategy space of the negotiation research community, we amend the Genius repository with various existing agents and scenarios from literature. Additionally, we organize a yearly international negotiation competition (ANAC) to harvest even more strategies and scenarios. ANAC also acts as an evaluation tool for negotiation strategies, and encourages the design of negotiation strategies and scenarios.We re-implement agents from literature and ANAC and decouple them to fit into the BOA architecture without introducing any changes in their behavior. For each of the three components, we manage to find and analyze the best ones for specific cases, as described below. We show that the BOA framework leads to significant improvements in agent design by wining ANAC 2013, which had 19 participating teams from 8 international institutions, with an agent that is designed using the BOA framework and is informed by a preliminary analysis of the different components.In every negotiation, one of the negotiating parties must accept an offer to reach an agreement. Therefore, it is important that a negotiator employs a proficient mechanism to decide under which conditions to accept. When contemplating whether to accept an offer, the agent is faced with the acceptance dilemma: accepting the offer may be suboptimal, as better offers may still be presented before time runs out. On the other hand, accepting too late may prevent an agreement from being reached, resulting in a break off with no gain for either party. We classify and compare state-of-the-art generic acceptance conditions. We propose new acceptance strategies and we demonstrate that they outperform the other conditions. We also provide insight into why some conditions work better than others and investigate correlations between the properties of the negotiation scenario and the efficacy of acceptance conditions.Later, we adopt a more principled approach by applying optimal stopping theory to calculate the optimal decision on the acceptance of an offer. We approach the decision of whether to accept as a sequential decision problem, by modeling the bids received as a stochastic process. We determine the optimal acceptance policies for particular opponent classes and we present an approach to estimate the expected range of offers when the type of opponent is unknown. We show that the proposed approach is able to find the optimal time to accept, and improves upon all existing acceptance strategies.Another principal component of a negotiating agent's strategy is its ability to take the opponent's preferences into account. The quality of an opponent model can be measured in two different ways. One is to use the agent's performance as a benchmark for the model's quality. We evaluate and compare the performance of a selection of state-of-the-art opponent modeling techniques in negotiation. We provide an overview of the factors influencing the quality of a model and we analyze how the performance of opponent models depends on the negotiation setting. We identify a class of simple and surprisingly effective opponent modeling techniques that did not receive much previous attention in literature.The other way to measure the quality of an opponent model is to directly evaluate its accuracy by using similarity measures. We review all methods to measure the accuracy of an opponent model and we then analyze how changes in accuracy translate into performance differences. Moreover, we pinpoint the best predictors for good performance. This leads to new insights concerning how to construct an opponent model, and what we need to measure when optimizing performance.Finally, we take two different approaches to gain more insight into effective bidding strategies. We present a new classification method for negotiation strategies, based on their pattern of concession making against different kinds of opponents. We apply this technique to classify some well-known negotiating strategies, and we formulate guidelines on how agents should bid in order to be successful, which gives insight into the bidding strategy space of negotiating agents. Furthermore, we apply optimal stopping theory again, this time to find the concessions that maximize utility for the bidder against particular opponents. We show there is an interesting connection between optimal bidding and optimal acceptance strategies, in the sense that they are mirrored versions of each other.Lastly, after analyzing all components separately, we put the pieces back together again. We take all BOA components accumulated so far, including the best ones, and combine them all together to explore the space of negotiation strategies.We compute the contribution of each component to the overall negotiation result, and we study the interaction between components. We find that combining the best agent components indeed makes the strongest agents. This shows that the component-based view of the BOA architecture not only provides a useful basis for developing negotiating agents but also provides a useful analytical tool. By varying the BOA components we are able to demonstrate the contribution of each component to the negotiation result, and thus analyze the significance of each. The bidding strategy is by far the most important to consider, followed by the acceptance conditions and finally followed by the opponent model.Our results validate the analytical approach of the BOA framework to first optimize the individual components, and then to recombine them into a negotiating agent
Dan Leatham, Robert E. Steele, Tim Slocum, Harold W. Johnson, and W. Fred Hurst v. Utah Department of Corrections, and The Career Service Review Board of the State of Utah : Reply Brief
No full textREPLY BRIEF OF APPELLANTS/PETITIONERS DAN LEATHAM, ROBERT E. STEELE, TIM SLOCUM, HAROLD W. JOHNSON AND W. FRED HURS
Efficient stochastic wake modeling for wind farm control
No full textIncludes bibliographical references
Nostalgia: content, triggers, functions
No full textSeven methodologically diverse studies addressed 3 fundamental questions about nostalgia. Studies 1 and 2 examined the content of nostalgic experiences. Descriptions of nostalgic experiences typically featured the self as a protagonist in interactions with close others (e.g., friends) or in momentous events (e.g., weddings). Also, the descriptions contained more expressions of positive than negative affect and often depicted the redemption of negative life scenes by subsequent triumphs. Studies 3 and 4 examined triggers of nostalgia and revealed that nostalgia occurs in response to negative mood and the discrete affective state of loneliness. Studies 5, 6, and 7 investigated the functional utility of nostalgia and established that nostalgia bolsters social bonds, increases positive self-regard, and generates positive affect. These findings demarcate key landmarks in the hitherto uncharted research domain of nostalgi
Bibliographics for the 983 eprints in the live archives of E-LIS : trends and status report up to 7th July 2004, based on author-self-archiving metadata
No full textThe priority for ideas and philosophy related to "Network Theory" have been traced back and documented by Braun(2004),and credit goes to Karinthy(1929).The IT has empowered to realise it, as the most practical phenomena and it is no more a humour. The OAI (Open Archives Initiatives)and ACIS (Academic Contributor Information System)are progressive in the direction ,which may lead to realise the "Collective Genius" at global level. Focus of present study is on Author-Self-Archiving (A-S-A)Metadata of the 983 Eprints in the Live Archives of the E-LIS (EPrints of Library and Information Science),which were approved till 7th July 2004.The A-S-A Metadata was used for librametric analysis. Self-explanatory bibliographics are illustrated.The highlights include: Conference papers (34%); highest approval, June 2004 (28%); published archives (76%);not refereed (52%); not in public domain (60%); highest self-archiving-author (De Robbio, Antonella).The Nos. of EPrints having single JITA domain specifications were: Theoretical and general aspects of libraries and information(27); Information use and sociology of information(80);Users,literacy and reading(13);Libraries as physical collections(30);Publishing and legal issues(57);Management(13);Industry, profession and education(36);Information sources, supports, channels(113) ; Information treatment for information services, Information functions and techniques (101); Technical services libraries, archives and museums(25); Housing technologies(1); Information technology and library technology(92); and Inter-domainery (395) i.e. having specifications of two or more than two JITA classes
- …
