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P2080-034 Tealeaf Technical Mastery Test v1

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P2080-034 exam Dumps Source : Tealeaf Technical Mastery Test v1

Test Code : P2080-034
Test Name : Tealeaf Technical Mastery Test v1
Vendor Name : IBM
: 38 Real Questions

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IBM Tealeaf Technical Mastery Test

As Work adjustments, management building Has to keep up | killexams.com Real Questions and Pass4sure dumps

As work itself is changing, probably the most fundamental tenets of management construction are being challenged. The very thought of leading people in jobs is altering with the democratization of work and the continued boost of digital expertise. These twin forces are relocating work beyond the common constitution of actions which are geared up into good jobs within a siloed organization. Work is being disaggregated into projects that will also be dispersed internal and outdoors of the firm — the “uberization” of work.

And as AI and robotics more and more complement and exchange the work of people, the expectations of leaders — basically realizing the work, how it can also be executed now and sooner or later, and the cost, capacity and possibility implications of existing and future work options — are expanding exponentially.

consider how IBM has tackled new approaches of work distribution as described in Lead The Work: Navigating a global past Employment, a ebook which considered one of us, Ravin, co-authored. IBM has been constructing a ability gadget that both aligns with and quickens this phenomenon of the external disaggregation of labor. here’s how the booklet describes it:

IBM’s techniques to work range from extreme deconstruction and dispersion of the job assignment (where IBMers can choose to work on short-time period tasks) to folks that keep projects in a job but create permeable inner and exterior boundaries, corresponding to changing personnel with shoppers or companions for short term assignments … The company sees tangible company and customer results and better development opportunities for employees.

to meet these challenges, they see three priorities for constructing the subsequent technology of leaders in the “work-disrupted” age:

Mastery of Digital

Digital technology is expanding the complexity and alternate options associated with this plurality of work. they are increasingly seeing organizations attempting to infuse a more advantageous focus and figuring out of “digital” among their leaders. And while it truly is a very good starting factor in assisting leaders make new connections, see different patterns and determine opportunities and threats, it doesn't go essentially a long way adequate in helping businesses improve the leadership muscle required to steer within the new world of labor.

insight middle

“Digital” is not some thing it truly is occurring to corporations, it has and continues to be the capability through which work is completed. akin to the enhance of “standardized method” in the early twentieth century, digital isn't just the new product to present their valued clientele (e.g., the one-click on cellular purchasing app), it's the ability during which they get work done (e.g., robotics for kit loading on and off the truck, the disaggregation of an accounting job, the transition to free brokers on a skill platform), the mechanism by which they have interaction with all their stakeholders (e.g., personnel, customers, free agents, communities they operate in) and so an awful lot greater.

learning digital requires leaders to be agile amid disruption. To comfortably lead, expertise of know-how actually concerns however there’s plenty extra to leaders studying and optimizing digital for his or her corporations. Leaders need to have the vision and forward-center of attention to count on how technology may disrupt the enterprise mannequin and the skill to mobilize the corporation for change and power a subculture of collaboration.

akin to what we’ve realized about developing cultures of innovation, it takes more than a handful of leaders contributing creative brilliance; it takes leaders using the focal point on and readiness for change that going digital requires. hence, groups would do neatly to support leaders go digital through studying content situated round envisioning the longer term, taking dangers, main alternate, using collaboration and leveraging the abundance of records generated by means of going digital.

in addition to leadership development courses getting used to help leaders “go digital,” these courses need to mirror the brand new realities of the digital and democratized office. construction courses must evolve from a static, closed-gadget method. as a substitute, these classes need to maintain pace by way of providing enticing, “open source” content and experiential researching opportunities that are wealthy with excessive-constancy simulations and precise-existence know-how applications.

it's essential to respect that constructing a digital focus among leaders requires a multi-pronged method from seeding the corporation with people that are “born digital’ while additionally weaving digital gaining knowledge of content material across the management construction curriculum to help other leaders “go digital.” Focusing this classification of approach shift and habits change need to movement past a core neighborhood of leaders and instead elevate the entire leadership cadre around the prominence of digital and its relevance and that means for a way leaders lead.

past-the-classroom Experiences

Relying completely on lecture room-based mostly studying has a acceptance for being inspiring within the moment but offering little to no transfer of training — nothing adjustments lower back on the job. however relying totally on on-the-job gaining knowledge of poses its own barriers together with lack of decent remarks and restrained alternatives to learn new issues. The vigor comes from bringing formal gaining knowledge of and on-the-job discovering together in a deliberate method. Use formal gaining knowledge of to set the context and content material for exchange in a standard and thorough approach. Then follow and apply new conduct returned on the job while instituting routines for manager, peer and train remarks.

trust the case of Peter Voser, former CEO of Royal Dutch Shell. As described in Lead The Work, he had an expansive profession with Shell that spanned 25 years but unlike many precise leaders in the company, he had a damage in provider at the precise of his career. Voser took a detour to be CFO for ABB from 2002 to 2004 and then back to Shell to become CEO in 2009. Voser turned into impatient for a new experience which attracted him to ABB and there he learned a whole new level of turnaround leadership. In his personal words, “it changed into a truly formative journey.”

Let’s go returned to the IBM illustration. IBM runs an internal skill platform, the Open talent market (OTM) that suits skill should skill provide on the ability, assignment and job stage. OTM assignments are sourced and short-term talent matches made to accelerate the completion work across the corporations, un-bounded by geography or enterprise line or industry section. This OTM approach is furthered through exterior talent exchanges with clients and partners.

This same strategy is used for developing leaders. using task administration, talent brokering, and journey mapping are fresh examples of interior leadership building practices to make more suitable ability-to-role matching that solves both sides of the equation — organizational need and individual development.

Boundaryless or open-techniques discovering is the next step during this migration. believe, as an instance, open enrollment at the John F. Welch management center at Crotonville where leaders from other organizations (e.g., market companions to GE) can take abilities of the entertaining GE discovering journey.

skilled teaching

coaching is a further aspect of the management building agenda that has advanced. historically having a coach became seen as a terrible, an middleman getting concerned to repair an issue. Now many leaders searching for out not just mentors but committed coaches — and a lot of are reporting that they have more than one exterior train who has followed them from business to business, providing standpoint and a “protected” location for talk.

What’s subsequent on the horizon for coaching as a leadership building follow? performance or lifestyles coaches with actual technical abilities. efficiency coaches are inside components that are not in the chief’s hierarchy but have insight into the company and see the leader in motion. life coaches are typically exterior to the organization and are known as upon as a depended on confidant and consultant when needed. each are there to hash via ambiguity, talk about issues, check assumptions and be reminded of his or her personal development pathway.

believe Marshall Goldsmith’s new 15 Coaches mission. as the #1 government coach on the earth, Marshall Goldsmith has decided to pay it forward and present a lifetime of learning without charge to 15 of what are certain to be lots of candidates. through a sequence of premier getting to know sessions with Marshall and a group of in demand world leaders, the 15 contributors will be taught what it takes to excel in government coaching. With this selfless act, a new cadre of skilled coaches may be attainable to leaders all over the world.

nowadays and tomorrow’s leaders require an agility to thrive in instances of turbulence and disruption, a mastery of all issues digital, and the ability to steer with out formal vigour in a growing non-employment labor market. Leaders should learn how to reward americans in the “forex” they covet; attracting, enticing and keeping skill throughout the total spectrum of work relationships and recognizing the alternative ways of main. Upskilling leaders to navigate through this new world of work requires a reboot on how leaders profit and use their experiences.


Squirrel AI researching Attended IEEE ICDM 2018 to exhibit the allure of AI +schooling | killexams.com Real Questions and Pass4sure dumps

SAN FRANCISCO, Jan. 9, 2019 /PRNewswire/ -- currently, IEEE ICDM 2018 became hosted in Singapore. experts, professors and students from all over the place the area within the field of facts mining gathered together. As one of the most essential visitors to the conference, Squirrel AI researching's chief scientist Wei Cui delivered a speech with the company's self-developed Squirrel AI intelligent adaptive equipment. He delivered the purposeful utility and development prospects of huge records, AI and other technologies in schooling to the public, which was unanimously appreciated by means of the attendees.

As one of the most desirable three international conferences on world information mining, IEEE ICDM has been committed to in-depth statistics mining in facts, computer researching, sample recognition, database and facts warehouse, statistics visualization, advantage-primarily based programs, high-performance computing and different fields. The conference also invited UBTECH's chief scientist Prof. Dacheng Tao; IBM Almaden fellow C. Mohan; Ramamohanarao (Rao) Kotagiri, dean of the faculty of Computing and advice techniques, Melbourne school of Engineering, the university of Melbourne; Graham William, Microsoft Asia Pacific R&D community's director of cloud computing, AI and facts science; Steve Miller, SMU Vice Provost (analysis) of tips programs; and other tech giants. They displayed their newest applied sciences and achievements in laptop vision, blockchain, computer getting to know and different related fields. additionally, the attendees additionally discussed a wide array of general concerns in regards to the merchandising and application of cutting-aspect applied sciences comparable to database and computing device discovering, in addition to their future challenges.

World-widespread facts mining and AI scholar Prof. Xindong Wu delivered a gap keynote speech titled "excellent wisdom". He proposed combining human intelligence (hi), synthetic intelligence (AI) and company/enterprise intelligence (O/BI) with large data analysis for industrial intelligence in organizational actions. UBTECH's chief scientist Prof. Dacheng Tao delivered his team's achievements in computing device imaginative and prescient, together with breakthroughs in object detection, scenario evaluation, depth recovery from single color photographs, goal monitoring and different points. IBM Almaden fellow C. Mohan shared a strong, constructive and correct computerized 3D segmentation algorithm for OCT imaging of retinal tissue layer and choroid.

As one of the vital pioneers of the utility of AI and large information in training eventualities in China, Squirrel AI discovering has opened greater than 1,600 learning centers in more than 300 cites in China, which have served greater than 1 million college students. The contract renewal rate is ready 80%. Now it has turn into a crucial drive in revolutionizing traditional education in China. Squirrel AI studying's chief scientist Dr. Wei Cui mentioned in his speech that these achievements rely on Squirrel AI's self-developed algorithm core. by means of accumulating and examining discovering statistics, Squirrel AI makes use of a nanoscale skills graph to become aware of competencies elements regarding the pursuits the least bit time and create personalised dynamic scholar portraits, forming self-studying and remarks on the prediction capability of AI and the effect of discovering content material.

on the technical degree, Squirrel AI has integrated probably the most slicing-part AI, large information technology, psychology, pedagogy and different relevant theories, forming a collection of adaptive researching strategic algorithms working during the entire teaching manner.

First, Squirrel AI has rebuilt the knowledge graph, profiting from the development in AI and algorithm expertise. In schooling, skills graph and graph conception are usually used to describe and represent every discipline's knowledge device. however, there were at all times two complications in past potential graphs. First, the outline of students' capabilities points become very crude; second, only amazing correlations between knowledge points had been marked, whereas weak correlations within the majority were not taken under consideration.

Squirrel AI adopts nanoscale separation to mark the 4 key points, i.e. issue degree, value, mastery and status with distinctive icons and colours. in addition, the formerly customary 4-6 dimensions of student abilities images in world clever adaptative getting to know have been upgraded to greater than 30, so that each pupil's mastery of expertise elements may also be clearly displayed in a single abilities graph. Taking core school math as an example, in the adaptive system of Squirrel AI, the normal 300 knowledge aspects were refined to 30,000 skills features. in this system, Squirrel AI makes use of the idea of affiliation likelihood of non-correlated advantage elements to build a network structure between abilities features, so that capabilities features may also be deduced from each and every other. on the operational stage, Squirrel AI can regulate look at various questions with the biggest quantity of assistance in precise time in accordance with different feedback on each question from every scholar, with the intention to verify probably the most expertise aspects with the least questions.

Story continues

Squirrel AI studying’s chief scientist Wei Cui delivered a speech

more

second, Squirrel AI can track college students' studying conditions via records evaluation and hold close their studying curves in real time. according to the human forgetting curve in tutorial psychology, students all the time accumulate some skills loopholes of their each day gaining knowledge of manner. besides the fact that children, such knowledge loopholes will now not disappear as a result of students boost to the next stage, but will affect college students' knowledge studying in the subsequent stage. using the Bayesian community and probabilistic graphical model, Squirrel AI can naturally complete students' skills pix and take into account college students' usual mastery of capabilities greater comprehensively. additionally, Squirrel AI adopts Bayesian skills tracking conception, which may notice students' past skills loopholes.

Third, in keeping with the dynamic tracking of students' abilities points, Squirrel AI can support students build personalized discovering paths. With the genetic algorithm, neural community and computing device learning know-how, Squirrel AI can push appropriate researching content material to college students, get feedback and preserve drawing multi-dimensional student pictures. according to the diploma and state of students' potential mastery, the gadget automatically plans the most correct gaining knowledge of issue and order for college kids, helps them assess their omissions and fill within the gaps, so as to be sure that college students can use the least time to hold close the expertise should be grasped.

To sum up, Squirrel AI can go deep into the hyperlinks of training, getting to know, trying out and training via facts collection and analysis, and in fact realize correct control of the whole chain of students' getting to know, turning training ideas similar to "individualized teaching" and "teaching college students in accordance with their aptitude" into fact.

in addition, Squirrel AI researching's chief scientist Wei Cui said: "however Squirrel AI already has a extremely precise question pushing gadget, that may proceed to enhance during the development of Squirrel AI's potential detection equipment, they nonetheless hope to improve interactivity. in the future, students' actual-time heart fee, brain wave and facial expression attention all through discovering can be brought for complete analysis. every pupil may be geared up with a digital personal assistant to supply stronger learning features for them."

basically, Squirrel AI learning has at all times connected terrific importance to know-how research and building. for the reason that its institution, the company has gathered three of the realm's leading consultants in clever adaptive studying, particularly Wei Cui, Richard Tong and Dan Bindman, as chief scientist, chief architect and chief records scientist of Squirrel AI learning. They respectively came from three world noted AI adaptive schooling businesses RealizeIT, Knewton and ALEKS. Integrating their well-nigh ten years of first-hand event within the software and R&D of AI adaptive education know-how with China's training and educating habits, they correctly developed Squirrel AI, China's first AI adaptive gaining knowledge of engine established on advanced algorithms with proprietary highbrow property rights. at the AIAED on Nov. 16, Prof. Tom Mitchell, the godfather of global laptop learning, dean of CMU faculty of computing device Science, a member of the American Academy of Arts and Sciences and the country wide Academy of Engineering, AAAS fellow and AAAI fellow, formally accepted Squirrel AI studying's present of the position of Chief AI Officer. As Squirrel AI learning's first grownup in cost in the box of AI, Mitchell will lead a group of more than 10 AI scientists and lots of of AI utility engineers and technical groups to habits primary AI analysis in the container of intelligent adaptative training, as well as the construction and utility of related items.

in addition, Squirrel AI learning has established a joint AI Lab with Stanford analysis Institute (SRI) and a joint AI adaptive training lab with chinese language Academy of Sciences (CAS) to allow a customizable, measurable, and teachable personalized schooling mode. in the past two years, Squirrel AI researching has made superb achievements in AI and massive data. Its scientific research papers had been taken with the aid of EDM, CSEDU, AIED, AERA and other properly international academic conferences. The company has won many international scientific research awards, similar to EdTechX innovation award, which has established its main place within the field of AI+ training.

sooner or later, Squirrel AI researching will proceed to boost investment in AI, large statistics, computing device gaining knowledge of, schooling conception and different connected fields, and promote the functional application of AI in training eventualities.

View usual content to down load multimedia:http://www.prnewswire.com/news-releases/squirrel-ai-researching-attended-ieee-icdm-2018-to-exhibit-the-attraction-of-ai-schooling-300776050.html


AI wins as Google algorithm beats No. 1 Go participant (replace) | killexams.com Real Questions and Pass4sure dumps

China's 19-year-historic Go player Ke Jie (L) makes a movement during the first in shape against Google's synthetic intelligence programme AlphaGo

Google's laptop algorithm AlphaGo narrowly beat the world's correct-ranked participant within the historic chinese language board online game of Go on Tuesday, reaffirming the advent of what its builders tout as a ground-breaking new sort of artificial intelligence.

AlphaGo took the first of a scheduled three games towards brash 19-12 months-historical chinese world number one Ke Jie, who after the suit annointed the programme because the new "Go god".

AlphaGo stunned the Go group and futurists a year in the past when it trounced South Korean grandmaster Lee Se-Dol four video games to 1. That marked the primary time a pc programme had crushed a properly player in a full contest and changed into hailed as a landmark for synthetic intelligence (AI).

This week's match-up within the jap chinese metropolis of Wuzhen, between Ke and an updated edition of AlphaGo, has been highly predicted amid hypothesis about even if AI might beat the area's suitable participant.

however a visibly flummoxed Ke—who closing year had declared he would by no means lose to an AI opponent—referred to AlphaGo had become too mighty for people, regardless of the razor-skinny half-factor profitable margin.

"I believe like his video game is more and more just like the 'Go god'. basically, it's astonishing," he referred to.

Ke vowed under no circumstances again to area himself to the "horrible adventure" of matching wits with the machine following this week's contests.

AlphaGo's feats have fuelled visions of a courageous new world of AI that can not most effective force cars and operate "wise buildings", but potentially assist mankind work out one of the most most complicated scientific, technical and clinical problems.

laptop programmes have in the past beaten humans in cerebral contests, beginning with the victory via IBM's Deep Blue over chess grandmaster Garry Kasparov in 1997.

but AlphaGo's success is regarded probably the most big yet for AI because of the complexity of Go, which has an incomputable variety of stream options and places a top class on human-like "intuition", instinct and the ability to learn.

Go involves two players alternately laying black and white stones on a grid, in search of to seal off essentially the most territory.

'attractive' online game

earlier than AlphaGo, mechanical mastery of the video game had been perceived to be years away. Its victories were analysed and praised by students of the game as imaginitive and even "pleasing", opening up new methods of approaching approach.

AlphaGo makes use of two units of "deep neural networks" containing thousands and thousands of connections similar to neurons in the brain.

it is partly self-taught, having performed thousands and thousands of games in opposition t itself following preliminary programming.

After Lee lost to AlphaGo closing year, Ke boldly declared "bring it on!"

but the writing become on the wall in January when Ke and different accurate chinese gamers have been flattened via a mysterious competitor in on-line contests.

That opponent changed into published afterwards to be the latest edition of AlphaGo, which become being given an internet verify run by means of its developer, London-based AI business DeepMind technologies, which Google bought in 2014.

Ke, a phenom who went pro at age 11 and has described himself as "pretentious", has vacillated between awe and disdain for AlphaGo.

He known as it a "bloodless computer" missing passion for the video game in feedback Monday evening on China's Twitter-like Weibo platform.

Ke and AlphaGo will face off once more on Thursday and Saturday.

For some, swift advances in AI conjure sci-fi photographs of a "Terminator" future in which machines "wake up" and enslave humanity.

but DeepMind founder Demis Hassabis pushed aside such concerns.

"This isn't about man competing with machines, however reasonably the usage of them as tools to discover and find new expertise collectively," he talked about before Tuesday's match.

"sooner or later, it does not matter even if AlphaGo wins or loses... both manner, humanity wins."

explore additional: capable, Set, Go! Rematch of man vs laptop in ancient video game

© 2017 AFP


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Declassified documents offer a new perspective on Yuri Gagarin’s flight | killexams.com real questions and Pass4sure dumps

  Gagarin launch

The launch of Vostok on April 12, 1961. A declassified document offers new information on what happened during Gagarin’s flight.

by Asif SiddiqiMonday, October 12, 2015 Bookmark and Share

As anyone who has done research on the topic knows, there’s an abundance of bewildering information about the Soviet space program, both in print and especially online. During the Cold War, Westerners generally had little to go on, but enterprising amateur sleuths chipped away at the edifice of secrecy, thus bringing to light many of its darkest secrets. The end of the Cold War brought a deluge of information on the program, most of it filtered through Russian journalists who were good at tracking down veterans willing to talk. The result was a kind of revisionist history, a history concerned with “what really happened” rather than “what they thought happened.”

Despite all this quite impressive work, the principal challenge of doing Soviet space history has always been the problem of archival research. How do you go about digging into archives in Moscow to get at the documents, as one is able to do (for example) with the American space program?

With Russian openness, a huge market opened up in the US and Europe for writers (mostly amateur historians or journalists) to step in and produce an unending stream of books on arcane aspects of the program. This strand has been further enriched by academics—mostly professional historians of modern Russia—who have looked at the rich cultural detritus of the Soviet space program. There’s a lot of this stuff out there, and some of it is very good, shedding light on the cultural importance of the Soviet space program as well as mapping how Russian culture has cultivate an interest in space exploration for well over a hundred years. (For those interested, I moderated a very interesting discussion on Soviet space culture a couple of years ago on the Russian History Blog.)

Gagarin launch

Gagarin being led to his spaceship at the top of the gantry by Oleg Ivanovsky who was the “lead” (production) designer of the Vostok spaceship.

Despite all this quite impressive work, the principal challenge of doing Soviet space history has always been the problem of archival research. How do you go about digging into archives in Moscow to get at the documents, as one is able to do (for example) with the American space program? Since the early 1990s, it has actually been possible to visit archives in Moscow and get access to Party and government documents at various state archives. It’s not easy, but it can be done and there are many academics, both professors and graduate students, who routinely do research at Russian archives on a huge array of topics related to Soviet history. I myself have been in Moscow many times (including for months at a time) working at various archives for my book on the pre-Sputnik history of the Soviet space program.

Of course, as with any archival document, one has to have a critical eye and contextualize, evaluate, and weigh any document by drawing from other sources. Nevertheless, the availability of archival documents on the Soviet space program has been both a boon and source of confusion. Russian archival authorities, for example, published several collections of primary source documents in 2011 on the early days of the space program (all in Russian) which are now commercially available (I’ve written brief summaries of some of them in this NASA Newsletter, pp. 19–24) but at the same time, there is undoubtedly some selection bias in what has been included and what has been omitted. Selection bias is, of course, a problem with any published collection of archival documents but the Russian ones come with their own peculiar set of problems.

It was in this context that I was in Moscow this past summer and spent a month digging through archives on a non-space related book project (actually on the history of scientists and engineers who worked in the Stalinist Gulag). I had a few days left at the end and went digging for space-related documents. At the Russian State Archive of the Economy (RGAE), one can find thousands of fat binders containing records of the grim-sounding Military-Industrial Commission, the body that managed Soviet military R&D and production during much of the Cold War. These folders are heavy, dusty, and for the most part, no one has looked at them since they were originally put away by archivists. The richness of materials is quite astonishing. Over the past few years, I have found and collected an enormous amount of material on the space program and related fields. These include: plans and schedules for their interplanetary program; detailed lists of technical materials from the American aerospace industry coveted by Soviet industrial managers; documents complaining that secrecy at Baikonur (the site from where the Soviets launched their satellites and cosmonauts) was not strict enough; abandoned anti-satellite projects; and documents on their massive N-1 Moon program.

Gagarin launch

Ivanovsky helping Gagarin get settled in his ship.

In this catalog of riches, in June of this year, I ran across a document on the historic flight of famed cosmonaut Yuri Gagarin, who on April 12, 1961, became the first human being in space. The document sheds new light on that historical flight, revealing the enormous risks involved in that mission. Gagarin’s Vostok flight, of course, has been quite amply documented, in print and online (with quite a nice recent biography in English by Andrew Jenks). I myself published a lengthy account, based largely on official mission documents (released in 1991), in one my earlier books, Challenge to Apollo: The Soviet Union and the Space Race, 1945–1974. However, documents have continued to trickle out on the flight in the past decade, and while nothing that has been declassified fundamentally shifts their perception of the mission, the Russian declassifications from 2011 have clarified much about the flight. The document that I found also provides confirmation of certain aspects of the flight, which is all the more important given the proliferation of Gagarin conspiracy websites (especially in Russian) which are easy to find with a Google search. Many websites will tell you that Gagarin was not the first human in space, that there were earlier “lost cosmonauts,” and, most sensationally, that his untimely death in 1968 was part of some nefarious Communist Party plan.

The document underscores what has often been overlooked by casual historians—that the flight of Gagarin’s Vostok was fundamentally embedded in a military environment. His spaceship was actually an offshoot variant of a new spy satellite (“Zenit”), not, as many often claim, that the spy satellite was the offshoot of the human variant.

The text of my document was remarkably somber in tone, very much in line with Soviet bureaucratic norms. Its title a literal description of its contents: “On the Results of the Launch of the ‘Vostok’ Space Ship with a Human on Board and on Plans for Future Work on Launches of the ‘Vostok’ Space Ship.” What was this? It was the official summary report—classified “Top Secret”—on Gagarin’s mission prepared by designers for the highest levels of the Soviet government. This five-page summary report, produced on May 9, 1961, less than a month after Gagarin’s flight, briefly compiled all that engineers knew about the flight. How did Gagarin do? How well did his spaceship perform? What can they do next?

For a start, they can dismiss the notion that Gagarin was not well during the flight. The authors of the document note that “Cosmonaut Major Yu. A. Gagarin normally bore the effects of all the factors accompanying the insertion of [his] ship into orbit, the space flight, and the return to Earth, maintaining full working ability during the flight and fully completed the flight assignment and program of observation.”

The document underscores what has often been overlooked by casual historians—that the flight of Gagarin’s Vostok was fundamentally embedded in a military environment. His spaceship was actually an offshoot variant of a new spy satellite (“Zenit”), not, as many often claim, that the spy satellite was the offshoot of the human variant. Engineers basically took out the cameras from the spy satellite, added life support, an ejection seat, and redundancies, and rigged the spacecraft for a human being. Besides the document’s comment about a “program of observation,” they get an explicit confirmation of the military importance of Gagarin’s flight in the next sentence, when the authors note that the flight has “opened up new prospects in the mastery of cosmic space and the use of these objects for the interests of defense.”

Gagarin launch

The “USSR” insignia was not originally on Gagarin’s helmet but was painted on on the morning of his flight.

Despite the obvious note of self-congratulation about the flight (“all systems ensuring the insertion into orbit, flight in orbit, and return of the return module and the cosmonaut [back] to Earth, worked normally”) the document notes there were numerous “basic shortcomings” during the preparation and implementation of the mission. Going through these they get a rare and peculiar glimpse into the Cold War Soviet space program and its functioning in a climate of high stakes and incredibly high risk.

We find from the document that during the preparation of two precursor missions with dogs in March 1961, and then in manufacturing Gagarin’s actual vehicle, at least 70 anomalies were detected in instruments on the vehicle. Yet, still, the flight went ahead!

Second, the “air conditioning” (basically, the life support system on Vostok) “did not fully correspond to the [design] requirements,” meaning that life support was essentially operating at its limits for Gagarin.

We also know that there were a few other “anomalies” (in NASA parlance) that marred the mission, including one that potentially could have killed Gagarin.

Third, the “portable emergency reserve” (in Russian, known as NAZ for nosimyy avariynyy zapas), a package used by cosmonauts to survive (for about three extra days) in case of landing in an unexpected area, was insufficiently debugged, especially for emergency splashdowns, which was certainly a possibility. In fact, the document notes that after being ejected from his capsule after his single orbit, when Gagarin was parachuting down, “the cable connected to the [portable emergency reserve] snapped,” basically depriving him of these supplies. In other words, if he had actually landed way off target, he would have had to survive without any supplies.

Fourth, a key valve in an engine (known variously as the 8D719, RD-0109, or RO-7) on two upper stages was assembled incorrectly at the factory, which, the document notes, “could have led to a premature shutdown of the engine and [failure] of orbital insertion of the [spaceship].” One imagines the outcome for Gagarin if that had happened. The best case scenario was an unscheduled landing, perhaps in eastern Siberia, on the initial portion of the orbital ground track. The worst case, given all the unknowns, was a fatality. In fact, as I describe below, this particular valve and its operation during orbital insertion did put Gagarin’s life in serious jeopardy, but not in the way one might expect.

Fifth, the short-wave mode for the voice radio-communication system (known as “Zarya”) basically did not “provide for normal communications during flight of the cosmonaut with ground communication stations,” which explains the repeated complaints by both the ground and Gagarin of difficulty in hearing each other, not to mention the poor quality of the audio that has been released by Russian archivists.1 Yet, Gagarin recorded some vivid impressions of his time in orbit on a tape recorder in real time. (“The flight is proceeding marvelously. The feeling of weightlessness is no problem, I feel fine… At the edge of the Earth, at the edge of the horizon, there’s such a beautiful blue halo that becomes darker the farther it is from the Earth…”)

Sixth, one of the two onboard radar sensors (known as “Rubin”), which helped the ground track the coordinates of the spaceship, did not work during Gagarin’s flight. This meant that tracking data during the mission was spotty at best.

Finally, the spaceship’s main data recorder (a kind of “black box”) known as “Mir-V1” did not work during reentry and landing due to “unsound assembly” at the factory. This meant that much critical data on the final portion of Gagarin’s mission was simply never recorded, making troubleshooting after the mission that much harder.

document cover

Front page of the document found at an archive in Moscow reporting on the results of Gagarin's flight to government leaders.

We also know that there were a few other “anomalies” (in NASA parlance) that marred the mission, including one that potentially could have killed Gagarin. During launch into orbit, the upper stage engine worked longer (the faulty valve!) than it should have, putting Gagarin in a much higher orbit than planned—the apogee of the orbit was 327 kilometers instead of 230 kilometers. This meant that in case the retrorocket system failed, Gagarin’s ship would not naturally decay after a week or so, or even after ten days—the absolute limit of resources in the ship. It would instead reenter after 30 days, by which time Gagarin would certainly be dead, having exhausted all the air inside. In other words, either the retrorocket worked, or Gagarin was a dead man.

In his postflight report, he remembered, “I waited for separation. There was no separation.”

During the actual flight, as soon as orbital insertion occurred, a timer known as Granit-5V activated. Precisely 67 minutes later, this timer sent a signal to fire the retrorocket engine (known as the S5.4) which, basically, did its job and deorbited Gagarin. In retrospect, that the retrorocket engine fired as it was intended to do is not terribly surprising given that it was one of the most ground-tested elements of the entire spaceship—17 out of 18 ground firings before the launch were successful. An interesting aside to all this is that during the entire time he was in space, Gagarin had no idea he was in the wrong orbit.

A much bigger problem occurred when, having ignited, the retrorocket engine stopped firing after 44 seconds, one second before the planned shutdown time due to another faulty valve. That one second meant that Gagarin would land 300 kilometers short of the planned target point. The lack of a proper shutdown also meant that some remaining propellant from the retro-engine (as well as residual gas from the gas bottles of the attitude control system) put Gagarin’s ship in an uncontrolled spin (of about 30° per second). Gagarin, as affable as always, reported on this in his later postflight report as a “corps de ballet” as the spaceship madly spun around. He remembered that it was “head, then feet, head, then feet, rotating rapidly. Everything was spinning around. Now I see Africa… next the horizon, then the sky… I was wondering what was going on.”

The problem, however, was much more serious than anyone could have anticipated, for the unexpected spin disrupted the internal program that would have immediately (four to eight seconds after engine shutdown) led to separation of the two modules that made up the Vostok spaceship: the spherical descent module carrying Gagarin, and the conical instrument module, which lacked a heat shield but ideally would burn up separately far from Gagarin’s capsule. In his postflight report, he remembered, “I waited for separation. There was no separation.” Instead, shackled to each other, the two objects began to enter the atmosphere as one. This was highly dangerous, for parts of the module not designed to survive reentry could have easily impacted and blown through Gagarin’s capsule. Fortunately for Gagarin, about ten minutes later, the two parts of Vostok separated, at an altitude of about 150–170 kilometers above the Mediterranean. That was lower than usual, but still high enough that Gagarin’s capsule was unharmed. And even then all was not safe. For a few seconds, a wiring harness kept the two modules connected, in a wild dance, separating only when four steel strips attaching the harness came off.

After experiencing about 10–12 g’s during reentry, Gagarin, once in the atmosphere, ejected from his capsule at an altitude of approximately seven kilometers. However, he soon discovered that once his primary large parachute deployed, the reserve parachute, slightly smaller than the primary one, also partially deployed. Fortunately, descending with one fully deployed parachute and one partial one—a recipe for disaster in a worst case scenario—did not adversely affect his descent. Gagarin was, however, busy with other problems: for six minutes, as he descended, he struggled to open a respiration valve on his spacesuit to help him breathe atmospheric air. His life was not in danger but it must have been extremely uncomfortable for a few tense minutes. Luckily, none the worse for the wear, he parachuted down safely at 1053 Moscow Time (not at 1055, as thought for decades).

he many problems that Gagarin faced on his mission were not necessarily due to poor design or bad engineering, I would argue, but instead a combination of haste and poor workmanship on the factory floor. I would argue that the Vostok design was in fact excellent engineering if they define “excellent engineering” as also being incredibly robust.

What does this all mean? Gagarin was an incredibly lucky man to have come out of this unhurt and alive. In rushing to accomplish a human spaceflight in the race with the US, Soviet engineers pushed the boundary of acceptable risk to its limits. Fortunately for Soviet planners everything went well. Sure, some of this was due to luck. Things that could have gone wrong didn’t. But some of it was also the undeniably robust design of the Vostok spaceship itself. Its relatively simple and elegant design was intended first and foremost to get a person into orbit and back as quickly and reliably as possible. The Soviets, for example, bypassed a slightly more complex blunt, truncated cone design (such as used on NASA’s Mercury spacecraft) in favor of a simple sphere capable of ballistic reentry into the Earth’s atmosphere.

The many problems that Gagarin faced on his mission were not necessarily due to poor design or bad engineering, I would argue, but instead a combination of haste and poor workmanship on the factory floor. Consider that the Vostok spacecraft consisted of 241 vacuum tubes, more than 6,000 transistors, 56 electric motors, and about 800 relays and switches connected by about 15 kilometers of cable. In addition, there were 880 plug connectors, each (on average) having 850 contact points. A total of 123 organizations, including 36 factories, contributed parts to the entire Vostok system. Despite redundancy in a large number of systems, human-rating such a spacecraft with absolute confidence was practically impossible. Yet, the way that Soviet engineers designed the system, it was meant to operate even at the blurry edges where parameters were pushed to the max. It is because of this that I would argue that the Vostok design was in fact excellent engineering if they define “excellent engineering” as also being incredibly robust.

The problem with Vostok was not the design itself but that it was insufficiently tested. There were too many bugs in the system that could have been eliminated in a slower testing program. But the frantic pace of the “space race” ensured that you had to sacrifice thorough ground testing in favor of debugging the technology in space. This means that you automatically increase the risk to human subjects on board spaceships. Extended ground testing versus flight testing is a tough call for mission managers, and depending on the urgency (as in Apollo 8, for example), you sometimes do something on the mission that you haven’t really tested on the ground—or can’t test at all.

What all this tells us is that while “good engineering” has some objective measures for evaluation, they also need to introduce context into the equation. The question is not simply, “Will it get the job done?” The question is, “Will it get the job done, on time, and even if lots of things go wrong?” And in Gagarin’s case, the answer was obviously “yes.” Regardless of all the troubles on his mission, he will always be the first human being in space. You can’t take that away.

Endnote
  • Basically, UHF communications with Gagarin were maintained from the moment he entered the capsule to about 23 minutes after launch. After that, they switched to short-wave, from various ground stations. But Novosibirsk and Alma-Ata received no word from Gagarin, while Khabarovsk maintained two-way communication for only four minutes (from 09:53 to 09:57 Moscow Time), and Moscow for a minute or so (beginning 10:13 Moscow Time).
  • General References
  • “On the Results of the Launch of the ‘Vostok’ Space Ship with a Human on Board and on Plans for Future Work on Launches of the ‘Vostok’ Space Ship” (May 9, 1961) [in Russian], Russian State Archive of the Economy (RGAE), fond 298, opis’ 1, delo 2057, ll. 249-253.
  • Asif A. Siddiqi, Challenge to Apollo: The Soviet Union and the Space Race, 1945–1974 (Washington, DC: NASA History Office, 2000).
  • L. V. Uspenskaya, ed., Chelovek. Korabl’. Kosmos: sbornik dokumentov i materialov k 50-letiyu poleta v kosmos Yu. A. Gagarina (Moscow: Novyy khronograf, 2011).

  • Violinists can’t tell the difference between Stradivarius violins and new ones | killexams.com real questions and Pass4sure dumps

    Antique Italian violins, such as those crafted by Antonio Stradivari or Giuseppe Guarneri “del Gesu”, can fetch millions of dollars.  Many violinists truly believe that these instruments are better than newly made violins, and several scientists have tried to work out why. Some suspected at the unusually dense wood, harvested from Alpine spruces that grew during an Ice Age. Others pointed the finger at the varnish, or the chemicals that Stradivari used to treat the wood.

    But Claudia Fritz (a scientist who studies instrument acoustics) and Joseph Curtin (a violin-maker) may have discovered the real secret to a Stradivarius’s sound: nothing at all.

    The duo asked professional violinists to play new violins, and old ones by Stradivari and Guarneri. They couldn’t tell the difference between the two groups. One of the new violins even emerged as the most commonly preferred instrument.

    Ever since the early 19th century, many tests have questioned the alleged superiority of the old Italian violins. Time and again, listeners have failed to distinguish between the sound of the old and new instruments. But critics have been quick to pick holes in these studies. In most cases, the listeners weren’t experts, and the players and researchers knew which violin was which – a flaw that could have biased the results.

    What’s more, no one has tested whether violinists themselves can truly pick up the supposedly distinctive sound of a Strad. The common wisdom is that they can, but Fritz and Curtin showed that this isn’t true. “Many people were convinced that as soon as you play an old violin, you can feel that it’s old, it’s been played a lot, and it has a special sound quality,” says Fritz. “People who took part in the experiment said it was the experience of a lifetime when they told them the results. They were fully convinced they could tell the difference, and they couldn’t.”

    During the Eighth International Violin Competition of Indianapolis – one of the world’s most important competitions – Fritz and Curtin persuaded six violinists to part with their instruments. Three of the violins were new; one was made a few days before. The other three had illustrious, centuries-long histories. Two were made by Stradivari and the other by Guarneri. One of the Stradivari, denoted “O1”, currently belongs to an institution, and is loaned to only the most gifted players. All three have featured in concerts and recordings, bowed by famous violinists. Their combined value is around 10 million US dollars, a hundred times more than the three new ones.

    Curtin’s influence was essential in persuading people to give up such prized, fragile possessions, especially to be played by blindfolded strangers. “Joseph is a well-known person in the community and people trust him,” says Fritz. “That’s why they managed to do the study: the combination of me as the scientist and him as the violin-maker.”

    Back in the lab, Fritz and Curtin asked 21 professional volunteers to play the six violins. They had played for anywhere from 15 to 61 years, and some of them were even involved in the competition as contestants and judges. They played the instruments in a dimly lit hotel room chosen for relatively dry acoustics.

    The test was a true “double-blind” one, as neither the players nor the people who gave them the violins had any way of knowing which instrument was which. The room was dimly lit. The players were wearing goggles so they couldn’t see properly. The instruments had dabs of perfume on the chinrests that blocked out any distinctive smells. And even though Fritz and Curtin knew which the identities of the six violins, they only passed the instruments to the players via other researchers, who were hidden by screens, wearing their own goggles, and quite literally in the dark.

    First, the players were given random pairs of violins. They played each instrument for a minute, and said which they preferred. Unbeknownst to them, each pair contained an old violin and a new one. For the most part, there was nothing to separate the two, and the players preferred the new instrument as often as the old one. There was one exception: O1, the Stradivarius with the most illustrious history, was chosen far less often than any of the three new violins.

    Next, Fritz and Curtin gave the recruits a more natural task. They saw all six violins, laid out in random order on a bed. They had 20 minutes to play any violin against any other and to choose the one they’d most like to take home. They also picked the best and worst instruments in terms of four qualities: range of tone colours; projection; playability; and response.

    This time, a clear favourite emerged. The players chose one of the new violins (“N2”) as their take-home instrument most often, and it topped the rankings for all four qualities. As before, O1 received the most severe rejections. Overall, just 38 percent of the players (8 out of 21) chose to take an old violin home, and most couldn’t tell if their instrument was old or new. As Fritz and Curtin write, this “stands as a bracing counterexample to conventional wisdom.”

    There are some issues with the study. Curtin, being a maker of new violins, has an obvious bias, but the double-blind design should have prevented that from affecting the results. The sample size – six violins and 21 players – is fairly small, but as large as can be expected when dealing with rare and incredibly expensive objects. There might also other variables that could affect the players’ perceptions – perhaps, for example, they might feel differently in rooms with different acoustics.

    Fritz expects scepticism. She says, “It might help to change people’s mentality, but quite slowly. It’s a very conservative community. We’ll probably get critics saying they didn’t take this or that into account, but obviously, it was the same for the new violins too.” She adds, “Modern makers should be very happy, and they hope that it’ll help them to promote their violins. It shows that they’re doing a great job and their violins are on a par with the old ones.”

    Perhaps the esteem that’s placed on Stradivarius violins is less about the triumph to age-old craftsmanship, and more a testament to their ability to delude ourselves. This ability has come out in other areas. Take wine, another product where certain specimens fetch critical acclaim and exorbitant prices on the basis of superior quality. And yet, study after study has shown that expensive wines taste the same as cheap plonk when you test people under double-blind conditions. The imagined link between price and quality is a delusion but, as Jonah Lehrer skilfully argues, it can be a pleasant one.

    The same could be said of violins. The joy of owning and playing a Stradivarius comes not from any objective advantage in its sound, but simply from the knowledge that it is a Stradivarius. Never mind what it sounds like – it’s an elegant and beautifully made instrument that carries status in its name, gravitas in its price tag, and the weight of centuries in its wood.

    For this reason, studies like this are useful for busting some myths, and they may boost the credibility of new violins, but they are unlikely to diminish the lust for the old ones. Fritz and Curtin recognise as much. Writing about one of their volunteers, they say, “When asked the making-school of the new instrument he had just chosen to take home, he smiled and said only, “I hope it’s an [old] Italian.”

    UPDATE: John Soloninka, one of the 21 violinists who took part in the study, has commented about his experiences below: “It was fascinating. I too, expected to be able to tell the difference, but could not. Claudia sent me my comments about the instruments that I made while I was playing them, and it was hilarious how wrong my impressions were at the time!”

    Reference: Fritz, Curtin, Poitevineau, Morrel-Samuels & Tao. 2011. Player preferences among new and old violins. PNAS http://dx.doi.org/10.1073/pnas.1114999109

    Image: by Håkan Svensson


    The researcher’s journey: leveling up as a user researcher | killexams.com real questions and Pass4sure dumps

    The shift from medium to senior level started in late March of 2015 when my consulting team delivered a scientific disaster modeling system for a client. They had tried to redesign an on-premise solution for the cloud, spending millions of dollars and two years shipping a system their customers wouldn’t accept. It wasn’t usable, attempted to do everything but could do nothing well, and it ignored pages of feedback customers felt were essential. Given the messy context of the project, I ran a user-centered discovery and testing program designed to force focus on the project and help pave the way for successful delivery.

    During discovery with customer proxies and subject matter experts, they built a set of personas encapsulating the goals, needs, and workflow scenarios of the system’s main users. Within their client and with their top customers they socialized the persona “Daniel” as their primary target: they claimed that if V1 could solve for Daniel’s specific needs (without specifying how), all parties would see real and immediate value from the system. Slowly, with open lines of feedback and iteration, client and customers agreed that Daniel represented their core and most pressing needs. They aligned on a goal: if, by a specified date, their system could support Daniel’s target scenarios, the project’s first phase would be a success.

    We tested conceptual and functional prototypes with the client’s customers, learning and iterating until real users could achieve Daniel’s core tasks in the system. The customers, especially non-user buyers, invariably piled on feedback outside the bounds their V1 scope (much like before). With clear alignment on Daniel’s needs, they could address feedback honestly and openly, maintaining focus in development: “Given what you’ve seen so far, do you believe [this input] would help Daniel with [goal] in [target scenario]?” The client and their customers came to trust and respect their team’s ability to act–or not–on their feedback with a clear lens. Phase 1 ended as a success.



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