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P8010-034 | Tealeaf Technical Mastery Test v1

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P8010-034 - Tealeaf Technical Mastery Test v1 - braindump

Vendor IBM
Exam Number P8010-034
Exam Name Tealeaf Technical Mastery Test v1
Questions 38 Q & A
Recent Update February 15, 2019
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P8010-034 exam Dumps Source : Tealeaf Technical Mastery Test v1

Test Code : P8010-034
Test Name : Tealeaf Technical Mastery Test v1
Vendor Name : IBM
Q&A : 38 Real Questions

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IBM Tealeaf Technical Mastery Test

As Work alterations, leadership construction Has to keep up | killexams.com Real Questions and Pass4sure dumps

As work itself is changing, one of the most fundamental tenets of management construction are being challenged. The very theory of main americans in jobs is altering with the democratization of labor and the endured strengthen of digital expertise. These twin forces are moving work past the average structure of activities which are organized into good jobs inside a siloed organization. Work is being disaggregated into projects that can also be dispersed internal and outside of the firm — the “uberization” of labor.

And as AI and robotics more and more supplement and replace the work of people, the expectations of leaders — in reality realizing the work, the way it may also be achieved now and sooner or later, and the can charge, potential and possibility implications of latest and future work options — are increasing exponentially.

believe how IBM has tackled new approaches of labor distribution as described in Lead The Work: Navigating a global past Employment, a book which one in every of us, Ravin, co-authored. IBM has been building a talent equipment that each aligns with and hastens this phenomenon of the external disaggregation of labor. here’s how the booklet describes it:

IBM’s procedures to work range from severe deconstruction and dispersion of the job assignment (where IBMers can decide to work on brief-time period tasks) to those that keep projects in a job however create permeable inner and external boundaries, reminiscent of changing personnel with customers or companions for short term assignments … The business sees tangible company and client effects and more suitable development opportunities for personnel.

to satisfy these challenges, we see three priorities for setting up the next technology of leaders in the “work-disrupted” age:

Mastery of Digital

Digital know-how is increasing the complexity and options associated with this plurality of work. we're increasingly seeing businesses trying to infuse a improved focus and figuring out of “digital” among their leaders. And while it's an outstanding beginning point in assisting leaders make new connections, see diverse patterns and establish opportunities and threats, it doesn't go just about far ample in assisting companies improve the leadership muscle required to steer in the new world of labor.

perception core

“Digital” is not whatever it's happening to companies, it has and remains the potential in which work is completed. comparable to the boost of “standardized system” in the early 20th century, digital is not only the brand new product to present our customers (e.g., the one-click on mobile deciding to buy app), it is the capability during which we get work executed (e.g., robotics for equipment loading on and off the truck, the disaggregation of an accounting job, the transition to free brokers on a talent platform), the mechanism wherein we interact with all our stakeholders (e.g., personnel, clients, free agents, communities we function in) and so lots greater.

getting to know digital requires leaders to be agile amid disruption. To comfortably lead, knowledge of technology definitely matters however there’s much extra to leaders gaining knowledge of and optimizing digital for his or her agencies. Leaders should have the imaginative and prescient and ahead-focal point to count on how technology might disrupt the business model and the ability to mobilize the firm for alternate and power a lifestyle of collaboration.

akin to what we’ve discovered about growing cultures of innovation, it takes greater than a handful of leaders contributing creative brilliance; it takes leaders driving the center of attention on and readiness for alternate that going digital requires. for that reason, corporations would do neatly to aid leaders go digital through researching content material centered round envisioning the longer term, taking dangers, leading change, using collaboration and leveraging the abundance of records generated by way of going digital.

apart from management construction programs getting used to aid leaders “go digital,” these classes need to replicate the new realities of the digital and democratized workplace. construction classes need to evolve from a static, closed-system approach. instead, these courses ought to maintain tempo with the aid of providing engaging, “open source” content and experiential gaining knowledge of opportunities that are wealthy with excessive-fidelity simulations and true-existence expertise functions.

it is critical to recognize that developing a digital focal point amongst leaders requires a multi-pronged method from seeding the firm with people that are “born digital’ whereas additionally weaving digital researching content across the management building curriculum to support other leaders “go digital.” Focusing this type of attitude shift and habits trade ought to circulate past a core group of leaders and in its place bring up the full management cadre around the prominence of digital and its relevance and which means for a way leaders lead.

beyond-the-school room Experiences

Relying totally on school room-based studying has a popularity for being inspiring within the moment however offering little to no switch of coaching — nothing alterations back on the job. however relying completely on on-the-job getting to know poses its own obstacles together with lack of first rate feedback and restrained opportunities to study new issues. The vigor comes from bringing formal learning and on-the-job getting to know collectively in a deliberate method. Use formal researching to set the context and content for change in a typical and thorough method. Then apply and practice new conduct lower back on the job while instituting routines for supervisor, peer and instruct comments.

believe the case of Peter Voser, former CEO of Royal Dutch Shell. As described in Lead The Work, he had an expansive career with Shell that spanned 25 years however unlike many correct leaders within the company, he had a destroy in service on the top of his career. Voser took a detour to be CFO for ABB from 2002 to 2004 after which lower back to Shell to become CEO in 2009. Voser was impatient for a new experience which attracted him to ABB and there he realized an entire new level of turnaround management. In his personal words, “it turned into a really formative journey.”

Let’s go again to the IBM illustration. IBM runs an interior skill platform, the Open ability marketplace (OTM) that matches talent should ability deliver on the skill, assignment and job level. OTM assignments are sourced and short-term skill fits made to accelerate the completion work across the agencies, un-bounded through geography or company line or industry segment. This OTM method is furthered through external skill exchanges with purchasers and companions.

This identical method is used for establishing leaders. the use of assignment management, talent brokering, and adventure mapping are contemporary examples of internal management development practices to make more advantageous ability-to-position matching that solves both sides of the equation — organizational need and individual construction.

Boundaryless or open-techniques researching is the next step during this migration. accept as true with, as an example, open enrollment at the John F. Welch leadership middle at Crotonville the place leaders from other companies (e.g., market partners to GE) can take potential of the enjoyable GE researching journey.

knowledgeable teaching

coaching is another factor of the management construction agenda that has developed. historically having a educate turned into viewed as a poor, an middleman getting involved to repair a problem. Now many leaders are looking for out not simply mentors but committed coaches — and a lot of are reporting that they have multiple exterior instruct who has adopted them from enterprise to company, presenting viewpoint and a “secure” location for dialogue.

What’s next on the horizon for teaching as a leadership building follow? performance or lifestyles coaches with real technical abilities. efficiency coaches are interior components that aren't in the chief’s hierarchy however have insight into the company and notice the chief in motion. lifestyles coaches are usually exterior to the corporation and are referred to as upon as a depended on confidant and consultant when vital. each are there to hash through ambiguity, discuss issues, look at various assumptions and be reminded of his or her personal development pathway.

consider Marshall Goldsmith’s new 15 Coaches task. because the #1 govt train on earth, Marshall Goldsmith has determined to pay it forward and present a lifetime of getting to know for gratis to 15 of what are certain to be heaps of candidates. through a series of premier gaining knowledge of classes with Marshall and a collection of popular international leaders, the 15 participants will be taught what it takes to excel in government teaching. With this selfless act, a brand new cadre of knowledgeable coaches may be accessible to leaders all over the world.

today and the next day’s leaders require an agility to thrive in instances of turbulence and disruption, a mastery of all issues digital, and the ability to lead devoid of formal energy in a growing to be non-employment labor market. Leaders should learn how to reward individuals within the “foreign money” they covet; attracting, engaging and retaining ability throughout the complete spectrum of labor relationships and recognizing the different ways of main. Upskilling leaders to navigate via this new world of labor requires a reboot on how leaders gain and use their experiences.


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

SAN FRANCISCO, Jan. 9, 2019 /PRNewswire/ -- recently, IEEE ICDM 2018 was hosted in Singapore. experts, professors and students from in all places the realm within the container of records mining gathered together. As one of the critical guests to the conference, Squirrel AI gaining knowledge of's chief scientist Wei Cui delivered a speech with the business's self-developed Squirrel AI clever adaptive gadget. He added the purposeful software and construction prospects of massive facts, AI and other technologies in education to the public, which turned into unanimously liked by the attendees.

As some of the true three overseas conferences on world data mining, IEEE ICDM has been dedicated to in-depth information mining in information, desktop learning, sample consciousness, database and records warehouse, records visualization, advantage-based methods, high-efficiency computing and different fields. The conference additionally invited UBTECH's chief scientist Prof. Dacheng Tao; IBM Almaden fellow C. Mohan; Ramamohanarao (Rao) Kotagiri, dean of the faculty of Computing and advice methods, Melbourne college of Engineering, the university of Melbourne; Graham William, Microsoft Asia Pacific R&D community's director of cloud computing, AI and statistics science; Steve Miller, SMU Vice Provost (research) of suggestions programs; and different tech giants. They displayed their latest applied sciences and achievements in desktop vision, blockchain, desktop discovering and different linked fields. furthermore, the attendees also mentioned a wide range of regular considerations in regards to the promoting and software of cutting-facet applied sciences reminiscent of database and laptop discovering, as well as their future challenges.

World-trendy facts mining and AI student Prof. Xindong Wu delivered a gap keynote speech titled "brilliant wisdom". He proposed combining human intelligence (hello), artificial intelligence (AI) and company/company intelligence (O/BI) with huge data analysis for industrial intelligence in organizational actions. UBTECH's chief scientist Prof. Dacheng Tao brought his group's achievements in computer vision, including breakthroughs in object detection, situation evaluation, depth restoration from single colour images, goal monitoring and other points. IBM Almaden fellow C. Mohan shared a strong, useful and accurate automated 3D segmentation algorithm for OCT imaging of retinal tissue layer and choroid.

As some of the pioneers of the application of AI and massive information in education scenarios in China, Squirrel AI gaining knowledge of has opened more than 1,600 studying facilities in more than 300 cites in China, which have served greater than 1 million college students. The contract renewal fee is about eighty%. Now it has develop into a crucial force in revolutionizing common education in China. Squirrel AI discovering's chief scientist Dr. Wei Cui pointed out in his speech that these achievements rely on Squirrel AI's self-constructed algorithm core. by means of amassing and examining gaining knowledge of facts, Squirrel AI uses a nanoscale competencies graph to realize potential elements related to the objectives the least bit time and create personalised dynamic scholar photographs, forming self-discovering and feedback on the prediction capability of AI and the effect of getting to know content.

at the technical level, Squirrel AI has integrated essentially the most cutting-edge AI, massive facts technology, psychology, pedagogy and other important theories, forming a collection of adaptive getting to know strategic algorithms running through the whole instructing method.

First, Squirrel AI has rebuilt the potential graph, profiting from the development in AI and algorithm expertise. In training, potential graph and graph theory are always used to describe and symbolize every area's capabilities device. youngsters, there were all the time two complications in past talents graphs. First, the description of students' expertise aspects turned into very crude; 2nd, only amazing correlations between competencies aspects had been marked, whereas vulnerable correlations in the majority have been not taken under consideration.

Squirrel AI adopts nanoscale separation to mark the four key aspects, i.e. issue level, significance, mastery and standing with distinctive icons and colours. furthermore, the previously conventional 4-6 dimensions of pupil knowledge photos in world intelligent adaptative getting to know were upgraded to greater than 30, in order that every student's mastery of potential features can also be naturally displayed in a single talents graph. Taking middle faculty math for instance, within the adaptive system of Squirrel AI, the usual 300 talents features have been refined to 30,000 competencies elements. during this procedure, Squirrel AI uses the idea of association likelihood of non-correlated potential points to build a network structure between competencies aspects, so that talents aspects can also be deduced from every other. at the operational stage, Squirrel AI can modify check questions with the greatest quantity of guidance in true time according to distinctive remarks on each and every query from every student, so as to verify probably the most competencies aspects with the least questions.

Story continues

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

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second, Squirrel AI can song students' getting to know situations via statistics analysis and draw close their getting to know curves in real time. based on the human forgetting curve in educational psychology, students all the time accumulate some knowledge loopholes in their day by day getting to know procedure. although, such expertise loopholes will no longer disappear as a result of college students improve to the next stage, but will affect students' competencies learning in the next stage. the usage of the Bayesian network and probabilistic graphical mannequin, Squirrel AI can evidently comprehensive students' capabilities images and be aware students' overall mastery of skills more comprehensively. moreover, Squirrel AI adopts Bayesian potential monitoring idea, that can realize college students' previous advantage loopholes.

Third, in accordance with the dynamic monitoring of students' talents facets, Squirrel AI can support college students build customized getting to know paths. With the genetic algorithm, neural network and computing device learning expertise, Squirrel AI can push appropriate gaining knowledge of content to college students, get comments and retain drawing multi-dimensional student images. in accordance with the diploma and state of students' expertise mastery, the device automatically plans probably the most correct discovering problem and order for college students, helps them examine their omissions and fill in the gaps, with the intention to ensure that students can use the least time to draw close the abilities should still be grasped.

To sum up, Squirrel AI can go deep into the links of training, getting to know, checking out and training through information assortment and evaluation, and really know accurate control of the whole chain of students' learning, turning schooling concepts reminiscent of "individualized teaching" and "instructing students in accordance with their aptitude" into reality.

furthermore, Squirrel AI discovering's chief scientist Wei Cui noted: "despite the fact Squirrel AI already has a extremely genuine query pushing device, that can proceed to enrich throughout the improvement of Squirrel AI's expertise detection system, we still hope to increase interactivity. in the future, students' true-time coronary heart cost, mind wave and facial expression focus right through gaining knowledge of will be introduced for complete analysis. every pupil can be equipped with a digital personal assistant to give stronger researching services for them."

basically, Squirrel AI discovering has all the time connected first-rate significance to expertise analysis and building. when you consider that its establishment, the company has gathered three of the realm's main consultants in intelligent adaptive gaining knowledge of, specifically Wei Cui, Richard Tong and Dan Bindman, as chief scientist, chief architect and chief statistics scientist of Squirrel AI researching. They respectively got here from three world noted AI adaptive schooling corporations RealizeIT, Knewton and ALEKS. Integrating their just about ten years of first-hand experience in the utility and R&D of AI adaptive education know-how with China's training and teaching habits, they efficiently developed Squirrel AI, China's first AI adaptive gaining knowledge of engine based on superior algorithms with proprietary highbrow property rights. at the AIAED on Nov. sixteen, Prof. Tom Mitchell, the godfather of world laptop learning, dean of CMU faculty of computing device Science, a member of the American Academy of Arts and Sciences and the countrywide Academy of Engineering, AAAS fellow and AAAI fellow, formally authorized Squirrel AI studying's offer of the place of Chief AI Officer. As Squirrel AI researching's first grownup in can charge in the container of AI, Mitchell will lead a group of greater than 10 AI scientists and lots of of AI utility engineers and technical teams to habits simple AI analysis within the field of clever adaptative education, as well because the development and application of related items.

additionally, Squirrel AI discovering has centered a joint AI Lab with Stanford analysis Institute (SRI) and a joint AI adaptive schooling lab with chinese language Academy of Sciences (CAS) to enable a customizable, measurable, and teachable customized education mode. in the past two years, Squirrel AI getting to know has made awesome achievements in AI and big facts. Its scientific analysis papers had been taken with the aid of EDM, CSEDU, AIED, AERA and other right international educational conferences. The enterprise has won many international scientific research awards, akin to EdTechX innovation award, which has established its leading place in the field of AI+ education.

in the future, Squirrel AI gaining knowledge of will continue to raise funding in AI, huge statistics, computer gaining knowledge of, schooling idea and other related fields, and promote the functional application of AI in schooling situations.

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

China's 19-12 months-historical Go player Ke Jie (L) makes a circulation all over the first suit against Google's artificial intelligence programme AlphaGo

Google's desktop algorithm AlphaGo narrowly beat the realm's exact-ranked player in the historic chinese language board online game of Go on Tuesday, reaffirming the arrival of what its developers tout as a floor-breaking new type of artificial intelligence.

AlphaGo took the first of a scheduled three video games towards brash 19-year-ancient chinese language world no 1 Ke Jie, who after the in shape annointed the programme as the new "Go god".

AlphaGo shocked the Go neighborhood and futurists a yr in the past when it trounced South Korean grandmaster Lee Se-Dol 4 games to at least one. That marked the first time a pc programme had crushed a desirable participant in a full contest and changed into hailed as a landmark for synthetic intelligence (AI).

This week's in shape-up in the japanese chinese metropolis of Wuzhen, between Ke and an up to date 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 ultimate yr had declared he would on no account lose to an AI opponent—said AlphaGo had develop into too powerful for people, despite the razor-thin half-aspect profitable margin.

"I think like his video game is more and more just like the 'Go god'. truly, it's impressive," he talked about.

Ke vowed on no account once again to field 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't only power automobiles and function "sensible buildings", however probably aid mankind determine one of the crucial most complicated scientific, technical and clinical issues.

computer programmes have up to now beaten people in cerebral contests, starting with the victory through IBM's Deep Blue over chess grandmaster Garry Kasparov in 1997.

but AlphaGo's success is considered the most significant yet for AI due to the complexity of Go, which has an incomputable variety of move alternate options and places a top rate on human-like "instinct", instinct and the skill to study.

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

'alluring' video game

before AlphaGo, mechanical mastery of the game had been perceived to be years away. Its victories had been analysed and praised via students of the video game as creative and even "attractive", opening up new ways of drawing near approach.

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

it's partly self-taught, having played hundreds of thousands of games towards itself following preliminary programming.

After Lee lost to AlphaGo last yr, Ke boldly declared "bring it on!"

but the writing became on the wall in January when Ke and other precise chinese players had been flattened via a mysterious competitor in online contests.

That opponent became revealed afterwards to be the newest version of AlphaGo, which was being given a web check run with the aid of its developer, London-primarily based AI company DeepMind applied sciences, which Google received in 2014.

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

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

Ke and AlphaGo will face off again on Thursday and Saturday.

For some, quick advances in AI conjure sci-fi images of a "Terminator" future during which machines "awaken" and enslave humanity.

but DeepMind founder Demis Hassabis disregarded such concerns.

"This is rarely about man competing with machines, but fairly using them as equipment to explore and find new potential collectively," he mentioned earlier than Tuesday's in shape.

"ultimately, it would not remember whether AlphaGo wins or loses... both means, humanity wins."

explore extra: ready, Set, Go! Rematch of man vs desktop in historic 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 we 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 our 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 we do next?

For a start, we 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,” we 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 we 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 we 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 we 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, we 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 we 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 we 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 we 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 we 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 our 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, we built a set of personas encapsulating the goals, needs, and workflow scenarios of the system’s main users. Within our client and with their top customers we socialized the persona “Daniel” as our primary target: we 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. We aligned on a goal: if, by a specified date, our 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 our V1 scope (much like before). With clear alignment on Daniel’s needs, we 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 our team’s ability to act–or not–on their feedback with a clear lens. Phase 1 ended as a success.



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