179,346 research outputs found
Will Preece
No full textWilliam R. (Will) Preece is the baby son of William Roland and Laura Preece of Myton, Utah
Doris Preece
No full textDoris Preece is pictured her freshman year at Uintah High School. She was born to Alma R. and Mary "Mamie" Preece on May 29, 1926. She married Dellis Ivan Morrill in 1948. She died August 29, 1998
Doris Preece
No full textDoris Preece is pictured her freshman year at Uintah High School. She was born to Alma R. and Mary "Mamie" Preece on May 29, 1926. She married Dellis Ivan Morrill in 1948. She died August 29, 1998
William and Edith Preece
No full textWilliam R. and Edith Preece are the children of William Roland and Laura Preece of Myton, Utah
Doris Preece
No full textDoris Preece is pictured her freshman year at Uintah High School. She was born to Alma R. and Mary "Mamie" Preece on May 29, 1926. She married Dellis Ivan Morrill in 1948. She died August 29, 1998
Integrative Use of Information Extraction, Semantic Matchmaking and Adaptive Coupling Techniques in Support of Distributed Information Processing and Decision-Making
No full textIn order to press maximal cognitive benefit from their social, technological and informational environments, military coalitions need to understand how best to exploit available information assets as well as how best to organize their socially-distributed information processing activities. The International Technology Alliance (ITA) program is beginning to address the challenges associated with enhanced cognition in military coalition environments by integrating a variety of research and development efforts. In particular, research in one component of the ITA ('Project 4: Shared Understanding and Information Exploitation') is seeking to develop capabilities that enable military coalitions to better exploit and distribute networked information assets in the service of collective cognitive outcomes (e.g. improved decision-making). In this paper, we provide an overview of the various research activities in Project 4. We also show how these research activities complement one another in terms of supporting coalition-based collective cognition
Phymatodes nigrescens Hardy and Preece, NEW STATUS
No full textPhymatodes nigrescens Hardy and Preece, NEW STATUS (Figs 23, 24) Phymatodes vulneratus var. nigrescens Hardy and Preece, 1927: 190. Type locality: Sydney, British Columbia, Canada. CNC Phymatodes oregonensis Chemsak, 1963: 39. Type locality: Grave Creek, Josephine County, Oregon, USA. CASC NEW SYNONYMY Chemsak (1963) diagnosed his P. oregonensis from the Pacific Northwest with P. a t e r from eastern North America, noting that the two species were most similar. However, among North American Phymatodes, P. oregonensis appears most similar to P. vulneratus. In fact, the name P. vulneratus var. nigrescens Hardy and Preece was already available for populations in the Pacific Northwest and has priority over Chemsak’s P. oregonensis. The type of P. v. var. nigrescens matches P. oregonensis, and the type series of this taxon extends the range of this species into Washington and British Columbia. Linsley (1964) noted that P. oregonensis “resembles the dark forms of P. vulneratus LeConte, but the elytral punctation differs greatly in the two species”, without further elaboration. Phymatodes nigrescens is in fact distinct from these dark forms of P. vulneratus as well. It can be separated from both bicolored and unicolored forms of P. vulneratus by the coarsely punctate apical one-half of the elytra; the overall more coarsely, sparsely punctate elytra; and the narrower, sinuate antemedian fasciae. Phymatodes vulneratus has impunctate, rugose elytral apices; more finely and densely punctate elytra at the basal one-half; and thinner, more linear, parallel-sided antemedial fasciae. Under ICZN (1999) article 45.6.4, the infrasubspecific variety named by Hardy and Preece is considered subspecific, and therefore an available name. Specimens examined: 123, including the type of P. v. var. nigrescens, P. oregonensis, and P. vulneratusPublished as part of Swift, Ian P. & Ray, Ann M., 2010, Nomenclatural changes in North American Phymatodes Mulsant (Coleoptera: Cerambycidae), pp. 35-52 in Zootaxa 2448 on pages 45-46, DOI: 10.5281/zenodo.29419
When data lie: Fairness and robustness in contested environments
No full textMany important decisions historically made by humans are now being made by algorithms - often learnt from data - whose accountability measures and legal standards are far from satisfactory. While model transparency is important, it is neither necessary nor sufficient. Accountability is arguably more important. However, accountability needs to carefully take into consideration the weaknesses of the original data, as well as the weaknesses of the model itself: Indeed, robust datasets enable model robustness, and vice versa. In this paper we will focus on unfair datasets, as an example of the weaknesses in datasets. Fairness directly involves privacy problems, since learning without fairness can emphasize certain features or directions that generate private information leakage. For instance, a model may inadvertently reveal a persons age if age is a discriminating feature in a models decision making. Moreover, we will investigate the robustness of model in presence of adversarial activities. Indeed, we should strengthen our models by estimating what an adversary will do based on continuous dynamic learning, mindful of concealment and deception, and with a clear, explainable, insightful summary for the final decision makers. In this paper we will discuss how models based on unfair datasets can hardly be robust; and datasets used by weak models can hardly be fair
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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