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News Article | May 23, 2017

TechCrunch is pleased to bring you Alchemist Accelerator‘s demo day. Alchemist is one of those rare programs that focuses on enterprise startups. These aren’t your parents’ enterprise companies. Pitches today will span products that help businesses with crowdfunding, wearables, sustainable farming and managing meetings with the power of AI. Investors and press will hear pitches from 15 enterprise companies. The demos start at 3:00pm PT and are expected to last two hours. You can watch it live here. Nobal Technologies The Imirror is the world’s most advanced interactive mirror, helping retail connect with consumers in the fitting room — where buying decisions are made. Team: Pieter Boekhoff (2016 Startup Canada Entrepreneur of the Year, CIS MRU), Thomas Battle (MBA), Alain Kassangana (Masters Eng). Everykey The revolution of access control, Everykey can unlock your phone, laptop, car, house or any other device when you’re close by, and also log you into your website accounts! Team: John McAfee (founder of McAfee Antivirus), Simon Boag (former president of Chrysler and GM), Chris Wentz (who made more than $100,000 in college selling iPads), Max Simon (started a haunted house in middle school and grew it to millions in annual revenue). Flowzo The fastest internet service powered by locals that helps property owners generate cash flow. Team: Thu Nguyen (5G/Wireless at TELUS/Marvell, Waterloo Engineering), Andrew Ta (managed technology strategy teams at both of the largest Canadian telecoms: TELUS/Bell, Ivey MBA), Chris Yap (shipped fiber chips at Marvell, previous startup focused on 60GHz Hardware, Stanford Engineering). Visage Smart crowdsourcing platform allowing companies to find and engage instantly with diverse talent. Team: Joss Leufrancois (co-founded Aldelia, a $50 million recruitment business established in nine countries), Emmanuel Marboeuf (former technical expert and international speaker in cyberdefense innovation). Amper Helps plant managers in factories increase machine and labor productivity by having real-time access to key metrics of machines. Data is captured using a simple, non-invasive retrofit sensor that monitors across machine types. Team: Akshat Thirani (CS Northwestern University, won the Thiel Summit pitch prize), Phil House (CS Northwestern University), Sachin Lal (CS Northwestern University, won the 2016 MIT Clean Energy prize). Uptime (previously EyePiece) Building a smarter industrial communication system using wearables. Team: Will Schumaker (PhD in optics from Stanford/UMich), Michael Leung (PhD student in EE from Stanford/Waterloo). ContextSmith Enterprise sales and expansion platform that uses AI to maximize revenue for sales and account management teams. Team: Will Cheung (head of customer success at Sequoia-backed startup, CS from CMU), Jochen Bedersdorfer (Intel AI Group, VP Eng of text analytics startup). Edyza High-density Internet of Things for industrial IoT, smart agriculture and other use cases that involve scaling sensors and actuators to thousands in close proximity. Team: Rana Basheer (PhD, principal scientist Broadcom, Garmin), Atul Patel (OneScreen, Jornaya and OptimalSocial). HydroVirga High-sensitivity NMR detection for elemental analysis in water. Our unique IP allows for detection of trace contaminants in real time, using micro NMR technology. Team: George Farquar, PhD (former LLNL), Julie Bowen, PhD (former LLNL), Mark Stephenson (20+ years water industry experience). Privacera Data security platform for enterprises to manage and mitigate risks with sensitive data in one place. Team: Balaji Ganesan (former XA Secure, acquired by Hortonworks), Don Bosco Durai (former XA Secure, acquired by Hortonworks, former Bharosa, acquired by Oracle). Stellic (previously Metis Labs) Student success platform designed to help students organize their college journey and graduate on time. Built by students, for students, this solves growing student retention problem faced by higher education. Team: Sabih (CMU CS ’15), Rukhsar (CMU CS ’15), Jiyda (CMU IS ’15). MeetingSift AI-driven meeting collaboration platform that delivers deep actionable insights from meetings across the enterprise. Team: Alex Bergo, PhD (Expert Collab., NLP, ML), Viil Lid, PhD (Collab. tech., HCI, Analytics). Fuse Next-generation inventory software. In the U.S., $1 trillion, or 20 percent of retail sales, are Lost every year because of stockouts and overstocks. We prevent this loss by algorithmically generating a demand forecast and centralizing it with real-time sales, inventory and procurement data. Team: Anna Tolmach (Wharton, Stanford MBA), Rachel Liaw (Stanford, UCLA, JD Candidate, 2018), Bridget Vuong (Stanford University, MS CS). Moesif Platform that makes sense of the world’s API data to change how APIs are created, debugged and used. Team: Derric Gilling (Intel Xeon Phi CPU Architect, Computer Eng @University of Michigan), Xing Wang (Executive Producer @Zynga, previously Microsoft, Computer Science @MIT). Text IQ Protecting enterprises from high-stakes legal disasters by using AI to identify sensitive, reputationally damaging and privileged documents that frequently get missed by human analysts and attorneys. Team: Apoorv Agarwal (PhD in Computer Science, Columbia, original contributor of IBM Watson), Omar Haroun (JD/MBA, Columbia, 3x founder with recent exit). Deep Relevance Internal fraud monitoring platform that uses behavioral AI to help finance and audit teams prevent employee and vendor fraud. Team: Kiran Ratnapu (VP Risk Technology, Merrill Lynch, MIT, IIT Bombay), Prasanna Kumar (healthcare and machine learning at Epic and startups, IIT Bombay CS). Strypes 3D visualizations powering new digital experiences for consumers across all devices and browsers. Team: Alexa Fleischman (EMC, Box, Boston College), Zack Fleischman (Microsoft Xbox, Zynga, Carnegie Mellon University), Matt Schiller (The Advisory Board, Cornell University). The History Project Empowering organizations to document, share and present institutional knowledge through a visual collaboration tool. Team: Niles Lichtenstein (Harvard, Monitor, Ansible — acquired by IPG, Velti — acquired by Blackstone), Michael Devin (principal tech architect at Frog, DARPA Director’s Medal, GE), Ben Yee (ITP, UX at Gilt Group).

Thorne J.H.,University of California at Davis | Santos M.J.,The History Project | Bjorkman J.H.,University of California at Davis
PLoS ONE | Year: 2013

Assessment of landscape change is critical for attainment of regional sustainability goals. Urban growth assessments are needed because over half the global population now lives in cities, which impact biodiversity, ecosystem structure and ecological processes. Open space protection is needed to preserve these attributes, and provide the resources humans need. The San Francisco Bay Area, California, is challenged to accommodate a population increase of 3.07 million while maintaining the region's ecosystems and biodiversity. Our analysis of 9275 km2 in the Bay Area links historic trends for three measures: urban growth, protected open space, and landcover types over the last 70 years to future 2050 projections of urban growth and open space. Protected open space totaled 348 km2 (3.7% of the area) in 1940, and expanded to 2221 km2 (20.2%) currently. An additional 1038 km2 of protected open space is targeted (35.1%). Urban area historically increased from 396.5 km2 to 2239 km2 (24.1% of the area). Urban growth during this time mostly occurred at the expense of agricultural landscapes (62.9%) rather than natural vegetation. Smart Growth development has been advanced as a preferred alternative in many planning circles, but we found that it conserved only marginally more open space than Business-as-usual when using an urban growth model to portray policies for future urban growth. Scenarios to 2050 suggest urban development on non-urban lands of 1091, 956, or 179 km2, under Business-as-usual, Smart Growth and Infill policy growth scenarios, respectively. The Smart Growth policy converts 88% of natural lands and agriculture used by Business-as-usual, while Infill used only 40% of those lands. Given the historic rate of urban growth, 0.25%/year, and limited space available, the Infill scenario is recommended. While the data may differ, the use of an historic and future framework to track these three variables can be easily applied to other metropolitan areas. © 2013 Thorne et al.

Smith T.D.,The History Project | Reeves R.R.,Okapi Wildlife Associates
Marine Fisheries Review | Year: 2010

Whaling for humpback whales, Megaptera novaeangliae, in the North Atlantic Ocean has occurred in various forms (e.g. for local subsistence, for oil to be sold commercially, using hand harpoons and deck-mounted cannons, using oar-driven open boats and modern powered catcher boats) from the early 1600's to the present. Several previous attempts to estimate the total numbers of humpback whales removed were considered close to comprehensive, but some uncertainties remained. Moreover, the statistical uncertainty was not consistently presented with the previous estimates. Therefore, we have pursued several avenues of additional data collection and conducted further analyses to close outstanding data gaps and address remaining issues. Our new estimates of landings and total removals of humpback whales from the North Atlantic are 21,476 (SE=214) and 30,842 (SE=655), respectively. These results include statistical uncertainty, reflect new data and improved analysis methods, and take account of some fisheries for which estimates had not been made previously. The new estimates are not sufficiently different from previous ones to resolve the major inconsistencies and discrepancies encountered in efforts to determine the conservation status of humpback whale populations in the North Atlantic.

Shore whaling along North America's California and Baja California coasts during 1854-99 was ancillary to the offshore and alongshore American whale fishery, which had begun in the North Pacific in the early 1800's and was flourishing by the 1840's. From its inception at Monterey, Calif, in the mid 1850's, the shore fishery, involving open boats deployed from land to catch and tow whales for processing, eventually spread from Monterey south to San Diego and Baja California and north to Crescent City near the California-Oregon border. It had declined to a relict industry by the 1880's, although sporadic efforts continued into the early 20th century. The main target species were gray whales, Eschrichtius robustus, and humpback whales, Megaptera novaeangliae, with the valuable North Pacific right whale, Eubalaena japonica, also pursued opportunistically. Catch data are grossly incomplete for most stations; no logbooks were kept for these operations as they were for high-seas whaling voyages. Even when good information is available on catch levels, usually as number of whales landed or quantity of oil produced, it is rarely broken down by species. Therefore, we devised methods for extrapolation, interpolation, pro rationing, correction, and informed judgment to produce time series of catches. The resulting estimates of landings from 1854 to 1899 are 3,150 (SE = 112) gray whales and 1,637 (SE = 62) humpback whales. The numbers landed should be multiplied by 1.2 to account for hunting loss (i.e. whales harpooned or shot but not recovered and processed).

Smith A.B.,University of California at Berkeley | Smith A.B.,Missouri Botanical Garden | Santos M.J.,The History Project | Koo M.S.,University of California at Berkeley | And 6 more authors.
Ecography | Year: 2013

Species distribution models (SDMs) are commonly applied to predict species' responses to anticipated global change, but lack of data from future time periods precludes assessment of their reliability. Instead, performance against test data in the same era is assumed to correlate with accuracy in the future. Moreover, high-confidence absence data is required for testing model accuracy but is often unavailable since a species may be present when undetected. Here we evaluate the performance of eight SDMs trained with historic (1900-1939) or modern (1970-2009) climate data and occurrence records for 18 mammalian species. Models were projected to the same or the opposing time period and evaluated with data obtained from surveys conducted by Joseph Grinnell and his colleagues in the Sierra Nevada of California from 1900 to 1939 and modern resurveys from 2003 to 2011. Occupancy modeling was used to confidently assign absences at test sites where species were undetected. SDMs were evaluated using species' presences combined with this high-confidence absence (HCA) set, a low-confidence set in which non-detections were assumed to indicate absence (LCA), and randomly located 'pseudoabsences' (PSA). Model performance increased significantly with the quality of absences (mean AUC ± SE: 0.76 ± 0.01 for PSA, 0.79 ± 0.01 for LCA, and 0.81 ± 0.01 for HCA), and apparent differences between SDMs declined as the quality of test absences increased. Models projecting across time performed as well as when projecting within the same time period when assessed with threshold-independent metrics. However, accuracy of presence and absence predictions sometimes declined in cross-era projections. Although most variation in performance occurred among species, autecological traits were only weakly correlated with model accuracy. Our study indicates that a) the quality of evaluation data affects assessments of model performance; b) within-era performance correlates positively but unreliably with cross-era performance; and c) SDMs can be reliably but cautiously projected across time. © 2013 The Author. Ecography © 2013 Nordic Society Oikos.

Tinjod N.,The History Project
European Space Agency Bulletin | Year: 2015

The 40th anniversary of the signing of the Convention for the creation of a single European Space Agency (ESA) in May 1975 was celebrated in May 2015. The idea of building an independent space capability in Europe dated back to the early 1960s when six European countries, such as Belgium, France, Germany, Italy, the Netherlands and the United Kingdom, formed the European Launcher Development Organization (ELDO) to develop a heavy launcher, called 'Europa'. The ESA Convention, which broadened the scope of the new agency's remit to include operational space applications systems, was opened for signature until December 31, 1975. The ESA Convention entered into force on 30 October 1980, with the deposit of the last instrument of ratification by France, after being signed at the European Space Conference in Paris on 30 May 1975 by the representatives of the European Space Research Organization (ESRO) and ELDO member States.

Wright D.,The History Project
Space Policy | Year: 2012

The UK government appears to be taking space more seriously, even if funding for the sector remains limited. Speeches and attendees at the conference confirm this trend, with a particular emphasis on innovation and a general sense that prospects for the UK space industry are good. The various themes and highlights of the conference are discussed. © 2012 .

The History Project | Date: 2013-09-03

printed educational materials, namely, workbooks and handouts in the fields of history and science.

The History Project | Date: 2011-03-25

Printed educational materials, namely, books, magazines, workbooks and handouts in the fields of history and science.

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