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expertise is what continues every thing working easily within the finance sector, and is used in relatively neatly each factor. Many IT jobs do not require a detailed capabilities of the present market, or of typical monetary items, however many employers will price a confirmed hobby in the monetary sector, or an capacity to display some diploma of monetary competencies relating to the sphere wherein the job lies.besides the fact that children assistance expertise jobs can be inside any sector of the finance trade, there is one enviornment in particular which has these days introduced further and further computerized programs - equities. The equities market is taking steps to circulation far from manual operations in a bid to enhance efficiency and reduce human error. there are many equities-related IT jobs in finance because of the manner the inner system are at the moment evolving.
IT in Equities
a method that it's being utilized within equities is to harness the circulate of monetary counsel to enable trading choices to be made greater instantly, regularly instantly. as soon as the buying and selling resolution is made, the exchange is entered into an order management equipment with straight via processing, so that there is not any want for guide intervention in any respect. an important part of this is the introduction and maintenance of execution administration methods (EMS) which connects merchants with probably the most economical broking service to get the deal performed as economically as possible. support builders for EMS systems are sometimes obligatory, as these techniques are used by means of millions of traders day-after-day - downtime isn't a chance. It can be a busy, on-the-go, round-the-clock job at times, however the rewards are high.
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As work itself is altering, one of the crucial fundamental tenets of management construction are being challenged. The very idea of leading individuals in jobs is changing with the democratization of labor and the persisted enhance of digital expertise. These twin forces are relocating work past the average structure of activities that are equipped into solid jobs inside a siloed firm. Work is being disaggregated into projects that can also be dispersed inside and outdoors of the corporation — the “uberization” of work.
And as AI and robotics increasingly supplement and substitute the work of people, the expectations of leaders — in fact figuring out the work, how it can be carried out now and in the future, and the can charge, means and risk implications of latest and future work alternatives — are increasing exponentially.
believe how IBM has tackled new approaches of labor distribution as described in Lead The Work: Navigating an international beyond Employment, a booklet which one of us, Ravin, co-authored. IBM has been constructing a talent system that each aligns with and hurries up this phenomenon of the exterior disaggregation of labor. here’s how the e-book describes it:
IBM’s tactics to work range from excessive deconstruction and dispersion of the job task (the place IBMers can choose to work on short-time period projects) to those who preserve projects in a job but create permeable inner and exterior boundaries, reminiscent of changing personnel with shoppers or companions for short term assignments … The enterprise sees tangible business and customer outcomes and better construction alternatives for personnel.
to meet these challenges, we see three priorities for constructing the next technology of leaders in the “work-disrupted” age:Mastery of Digital
Digital expertise is increasing the complexity and alternate options associated with this plurality of work. we are increasingly seeing organizations making an attempt to infuse a more desirable focal point and figuring out of “digital” among their leaders. And while it's a good starting aspect in helping leaders make new connections, see distinct patterns and identify opportunities and threats, it does not go well-nigh far sufficient in assisting groups boost the leadership muscle required to steer within the new world of labor.perception core
“Digital” isn't some thing it's going on to companies, it has and continues to be the potential through which work is accomplished. comparable to the advance of “standardized procedure” in the early 20th century, digital is not only the new product to present our customers (e.g., the one-click on mobile purchasing app), it is the means by which we get work done (e.g., robotics for kit loading on and off the truck, the disaggregation of an accounting job, the transition to free agents on a skill platform), the mechanism wherein we have interaction with all our stakeholders (e.g., employees, valued clientele, free agents, communities we function in) and so tons greater.
studying digital requires leaders to be agile amid disruption. To simply lead, skills of know-how actually concerns however there’s plenty greater to leaders getting to know and optimizing digital for his or her companies. Leaders have to have the imaginative and prescient and forward-focal point to assume how technology could disrupt the enterprise model and the skill to mobilize the company for exchange and power a culture of collaboration.
corresponding to what we’ve realized about developing cultures of innovation, it takes greater than a handful of leaders contributing inventive brilliance; it takes leaders riding the center of attention on and readiness for alternate that going digital requires. accordingly, organizations would do well to support leaders go digital via discovering content material founded round envisioning the future, taking dangers, main trade, driving collaboration and leveraging the abundance of information generated via going digital.
moreover leadership development courses being used to support leaders “go digital,” these programs should mirror the new realities of the digital and democratized place of work. construction classes have to evolve from a static, closed-device strategy. as an alternative, these classes ought to maintain tempo by way of delivering attractive, “open source” content material and experiential studying alternatives that are prosperous with high-fidelity simulations and real-existence technology applications.
it's crucial to recognize that setting up a digital focal point among leaders requires a multi-pronged strategy from seeding the organization with people who are “born digital’ whereas also weaving digital discovering content throughout the leadership development curriculum to support other leaders “go digital.” Focusing this category of approach shift and habits alternate have to circulate past a core neighborhood of leaders and in its place elevate the total leadership cadre across the prominence of digital and its relevance and which means for how leaders lead.beyond-the-school room Experiences
Relying totally on classroom-primarily based discovering has a acceptance for being inspiring within the moment but providing little to no transfer of coaching — nothing changes returned on the job. however relying fully on on-the-job learning poses its own obstacles together with lack of first rate feedback and limited opportunities to be trained new things. The energy comes from bringing formal studying and on-the-job studying collectively in a deliberate method. Use formal getting to know to set the context and content material for alternate in a typical and thorough approach. Then apply and practice new behavior again on the job while instituting routines for supervisor, peer and instruct comments.
trust 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 but not like many properly leaders within the company, he had a break in carrier at the precise of his career. Voser took a detour to be CFO for ABB from 2002 to 2004 after which returned to Shell to become CEO in 2009. Voser changed into impatient for a brand new event which attracted him to ABB and there he learned an entire new degree of turnaround management. In his own phrases, “it became a truly formative event.”
Let’s go returned to the IBM illustration. IBM runs an inside skill platform, the Open ability marketplace (OTM) that suits talent needs to talent supply on the ability, assignment and job level. OTM assignments are sourced and brief-time period talent matches made to speed up the completion work throughout the companies, un-bounded with the aid of geography or company line or trade section. This OTM method is furthered via exterior talent exchanges with purchasers and companions.
This equal approach is used for constructing leaders. using task management, ability brokering, and adventure mapping are recent examples of internal management construction practices to make improved skill-to-position matching that solves either side of the equation — organizational need and particular person construction.
Boundaryless or open-methods discovering is the subsequent step during this migration. trust, for instance, open enrollment on the John F. Welch leadership core at Crotonville the place leaders from other businesses (e.g., market partners to GE) can take knowledge of the entertaining GE studying experience.knowledgeable coaching
coaching is a different factor of the management construction agenda that has evolved. traditionally having a train was viewed as a terrible, an intermediary getting involved to repair an issue. Now many leaders are trying to find out not simply mentors but dedicated coaches — and many are reporting that they have got a couple of exterior coach who has adopted them from enterprise to business, providing viewpoint and a “protected” vicinity for talk.
What’s subsequent on the horizon for teaching as a management building practice? efficiency or existence coaches with true technical potential. efficiency coaches are inside substances that aren't in the chief’s hierarchy however have insight into the corporation and notice the leader in motion. existence coaches are typically external to the firm and are referred to as upon as a relied on confidant and marketing consultant when mandatory. both are there to hash via ambiguity, discuss issues, look at various assumptions and be reminded of his or her personal building pathway.
trust Marshall Goldsmith’s new 15 Coaches venture. because the #1 government teach on earth, Marshall Goldsmith has determined to pay it forward and present a lifetime of getting to know without charge to fifteen of what are bound to be thousands of candidates. through a sequence of premier getting to know classes with Marshall and a set of widespread international leaders, the 15 members will learn what it takes to excel in govt teaching. With this selfless act, a new cadre of professional coaches could be available to leaders world wide.
today and the next day’s leaders require an agility to thrive in times of turbulence and disruption, a mastery of all issues digital, and the ability to steer without formal vigor in a growing to be non-employment labor market. Leaders should learn how to reward people in the “foreign money” they covet; attracting, engaging and maintaining skill throughout the entire spectrum of labor relationships and recognizing the other ways of main. Upskilling leaders to navigate through this new world of work requires a reboot on how leaders benefit and use their experiences.
SAN FRANCISCO, Jan. 9, 2019 /PRNewswire/ -- currently, IEEE ICDM 2018 was hosted in Singapore. consultants, professors and scholars from in every single place the realm in the container of facts mining gathered collectively. As one of the crucial vital visitors to the convention, Squirrel AI researching's chief scientist Wei Cui delivered a speech with the business's self-developed Squirrel AI intelligent adaptive equipment. He introduced the purposeful application and development possibilities of big records, AI and other technologies in training to the public, which changed into unanimously preferred through the attendees.
As one of the crucial right three international conferences on global statistics mining, IEEE ICDM has been committed to in-depth information mining in statistics, machine discovering, sample recognition, database and statistics warehouse, facts visualization, skills-primarily based programs, high-performance 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 college of Computing and suggestions programs, Melbourne college of Engineering, the college of Melbourne; Graham William, Microsoft Asia Pacific R&D group's director of cloud computing, AI and data science; Steve Miller, SMU Vice Provost (research) of assistance systems; and different tech giants. They displayed their newest technologies and achievements in computer imaginative and prescient, blockchain, machine learning and other connected fields. in addition, the attendees additionally discussed a big range of commonplace considerations about the advertising and application of slicing-part applied sciences similar to database and computer studying, as well as their future challenges.
World-sought after facts mining and AI student Prof. Xindong Wu delivered a gap keynote speech titled "first-rate wisdom". He proposed combining human intelligence (hi), artificial intelligence (AI) and corporation/business intelligence (O/BI) with huge statistics evaluation for industrial intelligence in organizational actions. UBTECH's chief scientist Prof. Dacheng Tao introduced his group's achievements in computing device imaginative and prescient, together with breakthroughs in object detection, situation analysis, depth recuperation from single colour photographs, goal monitoring and other aspects. IBM Almaden fellow C. Mohan shared a sturdy, advantageous and accurate automatic 3D segmentation algorithm for OCT imaging of retinal tissue layer and choroid.
As one of the pioneers of the application of AI and massive statistics in training situations in China, Squirrel AI studying has opened more than 1,600 learning facilities in more than 300 cites in China, which have served more than 1 million college students. The contract renewal price is set 80%. Now it has become a crucial force in revolutionizing traditional training in China. Squirrel AI getting to know's chief scientist Dr. Wei Cui mentioned in his speech that these achievements count on Squirrel AI's self-built algorithm core. by using gathering and examining learning statistics, Squirrel AI uses a nanoscale potential graph to realize abilities features involving the goals in the least time and create personalised dynamic student pics, forming self-getting to know and comments on the prediction ability of AI and the impact of gaining knowledge of content.
at the technical level, Squirrel AI has built-in the most chopping-aspect AI, large records expertise, psychology, pedagogy and different important theories, forming a set of adaptive researching strategic algorithms working in the course of the entire teaching procedure.
First, Squirrel AI has rebuilt the talents graph, profiting from the development in AI and algorithm expertise. In education, knowledge graph and graph idea are usually used to describe and characterize every discipline's competencies equipment. youngsters, there were at all times two problems in past knowledge graphs. First, the outline of scholars' advantage points become very crude; 2d, simplest strong correlations between talents aspects have been marked, while susceptible correlations in the majority were not taken into account.
Squirrel AI adopts nanoscale separation to mark the 4 key points, i.e. difficulty level, importance, mastery and status with distinctive icons and colors. in addition, the formerly popular four-6 dimensions of student talents pictures in international intelligent adaptative discovering were upgraded to more than 30, so that each scholar's mastery of advantage aspects can be evidently displayed in one talents graph. Taking core faculty math as an example, in the adaptive equipment of Squirrel AI, the common 300 capabilities features have been subtle to 30,000 skills elements. during this technique, Squirrel AI uses the idea of affiliation chance of non-correlated talents aspects to construct a network constitution between abilities aspects, in order that advantage features can be deduced from each and every different. on the operational level, Squirrel AI can alter verify questions with the biggest amount of counsel in actual time based on diverse remarks on every query from every scholar, to be able to look at various essentially the most advantage facets with the least questions.
Squirrel AI learning’s chief scientist Wei Cui delivered a speechmore
2nd, Squirrel AI can song students' getting to know situations via facts analysis and grasp their researching curves in actual time. in line with the human forgetting curve in educational psychology, college students always accumulate some capabilities loopholes in their every day getting to know process. however, such potential loopholes will no longer disappear as a result of students increase to the subsequent stage, but will affect college students' capabilities researching within the next stage. the use of the Bayesian community and probabilistic graphical mannequin, Squirrel AI can obviously complete students' competencies photographs and take note students' standard mastery of talents extra comprehensively. moreover, Squirrel AI adopts Bayesian skills tracking idea, which can observe college students' previous abilities loopholes.
Third, based on the dynamic monitoring of students' advantage facets, Squirrel AI can help college students build personalized gaining knowledge of paths. With the genetic algorithm, neural community and machine researching technology, Squirrel AI can push appropriate discovering content material to college students, get feedback and preserve drawing multi-dimensional scholar images. in line with the diploma and state of students' talents mastery, the device automatically plans essentially the most relevant researching problem and order for students, helps them investigate their omissions and fill in the gaps, with a view to ensure that students can use the least time to hold close the advantage should still be grasped.
To sum up, Squirrel AI can go deep into the hyperlinks of educating, learning, testing and practicing via facts collection and evaluation, and in reality understand accurate manage of the complete chain of scholars' getting to know, turning education ideas comparable to "individualized teaching" and "educating students in keeping with their aptitude" into reality.
in addition, Squirrel AI discovering's chief scientist Wei Cui pointed out: "however Squirrel AI already has a very specific query pushing gadget, which may proceed to enhance throughout the improvement of Squirrel AI's knowledge detection equipment, we nevertheless hope to enrich interactivity. sooner or later, students' true-time heart fee, brain wave and facial expression consciousness all over researching may be delivered for finished evaluation. each pupil could be equipped with a digital personal assistant to supply superior discovering functions for them."
definitely, Squirrel AI studying has at all times attached tremendous importance to expertise research and construction. because its establishment, the business has gathered three of the world's main experts in clever adaptive researching, particularly Wei Cui, Richard Tong and Dan Bindman, as chief scientist, chief architect and chief records scientist of Squirrel AI studying. They respectively came from three world noted AI adaptive schooling organisations RealizeIT, Knewton and ALEKS. Integrating their very nearly ten years of first-hand adventure in the application and R&D of AI adaptive training expertise with China's training and educating habits, they efficiently developed Squirrel AI, China's first AI adaptive researching engine centered on advanced algorithms with proprietary highbrow property rights. at the AIAED on Nov. 16, Prof. Tom Mitchell, the godfather of global desktop researching, dean of CMU faculty of computer Science, a member of the American Academy of Arts and Sciences and the national Academy of Engineering, AAAS fellow and AAAI fellow, officially approved Squirrel AI studying's present of the place of Chief AI Officer. As Squirrel AI discovering's first grownup in cost in the container of AI, Mitchell will lead a crew of more than 10 AI scientists and hundreds of AI software engineers and technical teams to conduct basic AI analysis in the field of intelligent adaptative schooling, as well as the development and utility of linked products.
furthermore, Squirrel AI gaining knowledge of has centered a joint AI Lab with Stanford analysis Institute (SRI) and a joint AI adaptive schooling lab with chinese Academy of Sciences (CAS) to permit a customizable, measurable, and teachable personalized training mode. in the past two years, Squirrel AI researching has made great achievements in AI and large facts. Its scientific research papers have been taken by using EDM, CSEDU, AIED, AERA and other correct foreign academic conferences. The company has gained many overseas scientific research awards, corresponding to EdTechX innovation award, which has established its leading place within the container of AI+ education.
in the future, Squirrel AI learning will continue to enhance funding in AI, massive records, laptop getting to know, training idea and other related fields, and promote the practical utility of AI in schooling scenarios.
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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
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 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.
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.”
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.
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
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 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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LPI [24 Certification Exam(s) ]
LSI [3 Certification Exam(s) ]
Magento [3 Certification Exam(s) ]
Maintenance [2 Certification Exam(s) ]
McAfee [8 Certification Exam(s) ]
McData [3 Certification Exam(s) ]
Medical [69 Certification Exam(s) ]
Microsoft [374 Certification Exam(s) ]
Mile2 [3 Certification Exam(s) ]
Military [1 Certification Exam(s) ]
Misc [1 Certification Exam(s) ]
Motorola [7 Certification Exam(s) ]
mySQL [4 Certification Exam(s) ]
NBSTSA [1 Certification Exam(s) ]
NCEES [2 Certification Exam(s) ]
NCIDQ [1 Certification Exam(s) ]
NCLEX [2 Certification Exam(s) ]
Network-General [12 Certification Exam(s) ]
NetworkAppliance [39 Certification Exam(s) ]
NI [1 Certification Exam(s) ]
NIELIT [1 Certification Exam(s) ]
Nokia [6 Certification Exam(s) ]
Nortel [130 Certification Exam(s) ]
Novell [37 Certification Exam(s) ]
OMG [10 Certification Exam(s) ]
Oracle [279 Certification Exam(s) ]
P&C [2 Certification Exam(s) ]
Palo-Alto [4 Certification Exam(s) ]
PARCC [1 Certification Exam(s) ]
PayPal [1 Certification Exam(s) ]
Pegasystems [12 Certification Exam(s) ]
PEOPLECERT [4 Certification Exam(s) ]
PMI [15 Certification Exam(s) ]
Polycom [2 Certification Exam(s) ]
PostgreSQL-CE [1 Certification Exam(s) ]
Prince2 [6 Certification Exam(s) ]
PRMIA [1 Certification Exam(s) ]
PsychCorp [1 Certification Exam(s) ]
PTCB [2 Certification Exam(s) ]
QAI [1 Certification Exam(s) ]
QlikView [1 Certification Exam(s) ]
Quality-Assurance [7 Certification Exam(s) ]
RACC [1 Certification Exam(s) ]
Real-Estate [1 Certification Exam(s) ]
RedHat [8 Certification Exam(s) ]
RES [5 Certification Exam(s) ]
Riverbed [8 Certification Exam(s) ]
RSA [15 Certification Exam(s) ]
Sair [8 Certification Exam(s) ]
Salesforce [5 Certification Exam(s) ]
SANS [1 Certification Exam(s) ]
SAP [98 Certification Exam(s) ]
SASInstitute [15 Certification Exam(s) ]
SAT [1 Certification Exam(s) ]
SCO [10 Certification Exam(s) ]
SCP [6 Certification Exam(s) ]
SDI [3 Certification Exam(s) ]
See-Beyond [1 Certification Exam(s) ]
Siemens [1 Certification Exam(s) ]
Snia [7 Certification Exam(s) ]
SOA [15 Certification Exam(s) ]
Social-Work-Board [4 Certification Exam(s) ]
SpringSource [1 Certification Exam(s) ]
SUN [63 Certification Exam(s) ]
SUSE [1 Certification Exam(s) ]
Sybase [17 Certification Exam(s) ]
Symantec [134 Certification Exam(s) ]
Teacher-Certification [4 Certification Exam(s) ]
The-Open-Group [8 Certification Exam(s) ]
TIA [3 Certification Exam(s) ]
Tibco [18 Certification Exam(s) ]
Trainers [3 Certification Exam(s) ]
Trend [1 Certification Exam(s) ]
TruSecure [1 Certification Exam(s) ]
USMLE [1 Certification Exam(s) ]
VCE [6 Certification Exam(s) ]
Veeam [2 Certification Exam(s) ]
Veritas [33 Certification Exam(s) ]
Vmware [58 Certification Exam(s) ]
Wonderlic [2 Certification Exam(s) ]
Worldatwork [2 Certification Exam(s) ]
XML-Master [3 Certification Exam(s) ]
Zend [6 Certification Exam(s) ]
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