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Cho Oyu

Cho Oyu is the sixth-highest mountain in the world at 8,188 metres above sea level. Cho Oyu means "Turquoise Goddess" in Tibetan; the mountain is the westernmost major peak of the Khumbu sub-section of the Mahalangur Himalaya 20 km west of Mount Everest. The mountain stands on the China–Nepal border. Just a few kilometres west of Cho Oyu is Nangpa La, a glaciated pass that serves as the main trading route between the Tibetans and the Khumbu's Sherpas; this pass separates the Rolwaling Himalayas. Due to its proximity to this pass and the moderate slopes of the standard northwest ridge route, Cho Oyu is considered the easiest 8,000 metre peak to climb, it is a popular objective for professionally guided parties. Cho Oyu's height was measured at 26,750 feet and at the time of the first ascent it was considered the seventh highest mountain on earth, after Dhaulagiri at 8,167 metres. A 1984 estimate of 8,201 metres made it move up to sixth place. New measurements made in 1996 by the Government of Nepal Survey Department and the Finnish Meteorological Institute in preparation for the Nepal Topographic Maps put the height at 8,188 m, one remarkably similar to the 26,867 feet used by Edmund Hillary in his 1955 book High Adventure.

Cho Oyu was first attempted in 1952 by an expedition organised and financed by the Joint Himalayan Committee of Great Britain as preparation for an attempt on Mount Everest the following year. The expedition included Edmund Hillary, Tom Bourdillon and George Lowe. A foray by Hillary and Lowe was stopped due to technical difficulties and avalanche danger at an ice cliff above 6,650 m and a report of Chinese troops a short distance across the border influenced Shipton to retreat from the mountain rather than continue to attempt to summit; the mountain was first climbed on October 19, 1954, via the north-west ridge by Herbert Tichy, Joseph Jöchler and Sherpa Pasang Dawa Lama of an Austrian expedition. Cho Oyu was the fifth 8000 metre peak to be climbed, after Annapurna in June 1950, Mount Everest in May 1953, Nanga Parbat in July 1953 and K2 in July 1954; until the ascent of Mount Everest by Reinhold Messner and Peter Habeler in 1978, this was the highest peak climbed without supplemental oxygen.

Cho Oyu is considered the easiest eight-thousander, with the lowest death-summit ratio. It is the second most climbed eight-thousander after Everest, has over four times the ascents of the third most popular eight-thousander, Gasherbrum II, it is marketed as a "trekking peak", achievable for climbers with high fitness, but low mountaineering experience. It has a broadly flat summit plateau with no cairn, which can be a source of confusion, debate, amongst climbers. 1952 First reconnaissance of north-west face by party. 1954 First ascent by Austrians Joseph Jöchler and Herbert Tichy, Pasang Dawa Lama 1958 Second ascent of the peak, by an Indian expedition. Sherpa Pasang Dawa Lama reached the peak for the second time. First death on Cho Oyu. 1959 Four members killed in an avalanche during a failed international women's expedition. 1964 Controversial third ascent by a German expedition as there is no proof of reaching the summit. Two mountaineers die of exhaustion in camp 4 at 7,600 m. 1978 Edi Koblmüller and Alois Furtner of Austria summit via the difficult southeast face.

1983 Reinhold Messner succeeds with Hans Kammerlander and Michael Dacher. 1984 Věra Komárková and Dina Štěrbová were the first women to climb Cho Oyu. Štěrbová was the first woman from Czechoslovakia to climb an 8000er. 1985 On February 12, Poles Maciej Berbeka and Maciej Pawlikowski make the first winter ascent. It is the only winter ascent on eight-thousander made on a new route. Repeated three days by Andrzej Heinrich and Jerzy Kukuczka. 1988 On November 2, a Slovenian expedition consisting of Iztok Tomazin, Roman Robas, Blaž Jereb, Rado Nadvešnik, Marko Prezelj, Jože Rozman, reach the summit via the never before climbed north face. 1994 On May 13 Carlos Carsolio sets a world record speed ascent from base camp to summit, ascending in 18 hours and 45 minutes. 1994 First solo ascent via the South West face by Yasushi Yamanoi. 2004 Second summit by a double amputee 2007 Second Indian ascent. Expedition led by Abhilekh Singh Virdi. 2009 Clifton Maloney, husband of US Representative Carolyn Maloney and at that time the oldest American to summit an eight-thousander, died at age 71 after summiting on 25 September.

His final words were. I’ve just summited a beautiful mountain." 2011 Dutch climber Ronald Naar dies after becoming unwell at 8,000 m. 1952 British Cho Oyu expedition Nangpa La shootings Cho Oyu 8201m – Field Recordings from Tibet Hillary, Edmund. High Adventure. Bloomsbury Publishing. ISBN 0-7475-6696-8. Retrieved 2014-01-15. Sources Herbert Tichy, Cho Oyu - Gnade der Götter, Media related to Cho Oyu at Wikimedia Commons Cho Oyu page on Summitpost.org Cho Oyu page on Himalaya-Info.org Cho Oyu on Peakware Ascents and fatalities statistics Cho Oyu from Kyrgyzstan Birdseye view video

La Cienega/Jefferson station

La Cienega/Jefferson is an elevated light rail station in the Los Angeles County Metro Rail system. It is located at the intersection of La Cienega Jefferson Boulevard in Los Angeles; this station is served by the E Line. E Line service hours are from 5 AM to 12:30 AM Sunday through Thursday and from 5 AM to 2:30 AM on Friday and Saturday; this station is within walking distance to the following attraction: Los Angeles architect Eric Owen Moss proposed a 17-storey glass ribbon office tower with underground parking with within steps of this station. The tower began preparation in late 2018. Condominiums and retail across from the station is under construction, it will be built by the Carmel Partners firm. A large parking structure located just south of the station provides "park-and-ride" access to the station. According to Public Art in Public Places, the station's public art was created by Daniel Gonzales and titled Engraved in Memory and consists of pole-mounted glazed ceramic bas relief panels depicting the history of the Ballona Creek and Culver City areas.

A stop on the 1875 Los Angeles and Independence Railroad, 1906 Los Angeles Pacific Railroad and 1911 Pacific Electric railroads, it closed on September 30, 1953 with closure of the Santa Monica Air Line and remained out of service until re-opening on Saturday, April 28, 2012. It was rebuilt into an elevated station for the opening of the Expo Line from little more than a station stop marker. Regular scheduled service resumed Monday, April 30, 2012. Media related to La Cienega / Jefferson at Wikimedia Commons Metro Expo Line Construction Authority Project Website, Metro Rail Expo Corridor, Phase 1 to Culver City

In-database processing

In-database processing, sometimes referred to as in-database analytics, refers to the integration of data analytics into data warehousing functionality. Today, many large databases, such as those used for credit card fraud detection and investment bank risk management, use this technology because it provides significant performance improvements over traditional methods. Traditional approaches to data analysis require data to be moved out of the database into a separate analytics environment for processing, back to the database.. Doing the analysis in the database, where the data resides, eliminates the costs and security issues associated with the old approach by doing the processing in the data warehouse itself. Though in-database capabilities were first commercially offered in the mid-1990s, as object-related database systems from vendors including IBM, Illustra/Informix and Oracle, the technology did not begin to catch on until the mid-2000s; the concept of migrating analytics from the analytical workstation and into the Enterprise Data Warehouse was first introduced by Thomas Tileston in his presentation entitled, “Have Your Cake & Eat It Too!

Accelerate Data Mining Combining SAS & Teradata” at the Teradata Partners 2005 "Experience the Possibilities" conference in Orlando, FL, September 18–22, 2005. Mr. Tileston presented this technique globally in 2006, 2007 and 2008. At that point, the need for in-database processing had become more pressing as the amount of data available to collect and analyze continues to grow exponentially, from megabytes to gigabytes and petabytes; this “big data” is one of the primary reasons it has become important to collect and analyze data efficiently and accurately. The speed of business has accelerated to the point where a performance gain of nanoseconds can make a difference in some industries. Additionally, as more people and industries use data to answer important questions, the questions they ask become more complex, demanding more sophisticated tools and more precise results. All of these factors in combination have created the need for in-database processing; the introduction of the column-oriented database designed for analytics, data warehousing and reporting, has helped make the technology possible.

There are three main types of in-database processing: translating a model into SQL code, loading C or C++ libraries into the database process space as a built-in user-defined function, out-of-process libraries written in C, C++ or Java and registering them in the database as a built-in UDFs in a SQL statement. In this type of in-database processing, a predictive model is converted from its source language into SQL that can run in the database in a stored procedure. Many analytic model-building tools have the ability to export their models in either SQL or PMML. Once the SQL is loaded into a stored procedure, values can be passed in through parameters and the model is executed natively in the database. Tools that can use this approach include SAS, SPSS, R and KXEN. With C or C++ UDF libraries that run in process, the functions are registered as built-in functions within the database server and called like any other built-in function in a SQL statement. Running in process allows the function to have full access to the database server’s memory and processing management capabilities.

Because of this, the functions must be well-behaved so as not to negatively impact the database or the engine. This type of UDF gives the highest performance out of any method for OLAP, statistical, univariate distributions and data mining algorithms. Out-of-process UDFs are written in C, C++ or Java. By running out of process, they do not run the same risk to the database or the engine as they run in their own process space with their own resources. Here, they wouldn’t be expected to have the same performance as an in-process UDF, they are still registered in the database engine and called through standard SQL in a stored procedure. Out-of-process UDFs are a safe way to extend the capabilities of a database server and are an ideal way to add custom data mining libraries. In-database processing makes data analysis more accessible and relevant for high-throughput, real-time applications including fraud detection, credit scoring, risk management, transaction processing and margin analysis, usage-based micro-segmenting, behavioral ad targeting and recommendation engines, such as those used by customer service organizations to determine next-best actions.

In-database processing is performed and promoted as a feature by many of the major data warehousing vendors, including Teradata, IBM, IEMC Greenplum, ParAccel, SAS, EXASOL. Some of the products offered by these vendors, such as CWI's MonetDB or IBM's Db2 Warehouse, offer users the means to write their own functions or extensions to enhance the products' capabilities. Fuzzy Logix offers libraries of in-database models used for mathematical, data mining and classification modelling, as well as financial models for equity, fixed income, interest rate, portfolio optimization. In-DataBase Pioneers collaborates with marketing and IT teams to institutionalize data mining and analytic processes inside the data warehouse for fast and customizable consumer-behavior and predictive analytics. In-database processing is one of several technologies focused on improving data warehousing performance. Others include parallel computing, shared everything archi